Measurement of cyclic dinucleotide in body fluid as biomarker for sting-related disease and involvement of dysbiosis therein

Abstract

The present disclosure provides a novel technique for diagnosing STING-related diseases. Specifically, the present disclosure provides: a method comprising Step (A) for measuring a cyclic dinucleotide (CDN) present in a subject or obtaining information on the presence or level of the CDN, Step (B) for determining whether the CDN is derived from the subject and / or derived from a microorganism (parasite) expected to be contained in the subject, and Step (C) for diagnosing a STING-related disease or condition on the basis of the result of the determination; a therapeutic method related thereto; and the like.

Description

Measurement of cyclic dinucleotides in body fluids as biomarkers for STING-related diseases and involvement of dysbiosis

[0001] The present disclosure relates to diagnostic techniques using cyclic dinucleotides.

[0002] Interferon gene stimulator (STING) is an ER-resident adapter important for transmitting immune signals from nucleic acid sensors such as cyclic GMP-AMP synthase (cGAS). STING plays an important role in antibacterial, antitumor immunity, and inflammatory diseases (especially aseptic inflammatory diseases). Abnormal STING activity is associated with diseases such as STING-associated vasculopathy with onset in infancy (SAVI), which causes systemic inflammation and conditions affecting blood vessels, skin, and lungs. Current therapeutic agents such as JAK-STAT inhibitors have side effect and resistance problems, and the need for alternative drugs has been emphasized. Environmental factors such as toxins and rough diets disrupt the gut microbiota and exacerbate autoimmune and autoinflammatory diseases.

[0003] The present disclosure was completed by the inventors based on the suggestion that changes in the gut microbiota may contribute to SAVI. By searching for microbial-derived metabolites as biomarkers, it was found that it may lead to new therapies for normalizing the microbiota and benefit patients with STING-related diseases such as SAVI, AGS, and SLE.

[0004] This disclosure provides: (Item 1) A method for detecting or determining the physical condition of a subject, comprising: A) measuring cyclic dinucleotides (CDNs) present in the subject or obtaining information on their presence or level; B) determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be present in the subject; and C) diagnosing or providing diagnostic support for a STING-related disease or condition based on the result of the determination. (Item 2) The method according to any one of the above items, wherein the STING-related disease or condition is an allergic or inflammatory disease (aseptic inflammatory disease), an autoimmune disease, cancer, or a condition related thereto. (Item 3) The method according to any one of the above items, wherein the STING-related disease or condition is an allergic or inflammatory disease (aseptic inflammatory disease), and the allergic or inflammatory disease (aseptic inflammatory disease) is asthma, hay fever, or chronic obstructive pulmonary disease (COPD). (Item 4) The method according to any one of the above items, wherein the STING-related disease or condition is (A) an allergic or inflammatory disease (aseptic inflammatory disease), and the allergic or inflammatory disease (aseptic inflammatory disease) is asthma, hay fever, or chronic obstructive pulmonary disease (COPD), or (B) an autoimmune disease, and the autoimmune disease is STING-associated vasculopathy with onset in infancy (SAVI), Ecardi-Goutieres syndrome (AGS), or systemic lupus erythematosus (SLE). (Item 5) The method according to any one of the above items, wherein the STING-related disease or condition is cancer. (Item 5A) The method according to any one of the above items, wherein the STING-related disease or condition is asthma and / or COPD. (Item 5B) The method according to any one of the above items, wherein the method enables differential diagnosis between asthma and chronic obstructive pulmonary disease (COPD), differential diagnosis between an asthmatic patient and a healthy control, or differential diagnosis between an asthmatic subject and a non-asthmatic subject.(Item 5C) The method according to any one of the above items, further comprising the step of performing the diagnosis or diagnostic support by using the level of the cyclic dinucleotide as an input feature to a classification model using a machine learning algorithm (e.g., a support vector machine (SVM)). (Item 5D) The method according to any one of the above items, wherein the input feature includes a serum CDN measurement. (Item 6) The method according to any one of the above items, wherein the CDN comprises at least one of 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP. (Item 7) The method according to any one of the above items, wherein if the CDN contains 2'3'-cGAMP, the CDN is determined to be of the origin of the subject. (Item 8) The method according to any one of the above items, wherein the presence or decrease of 2'3'-cGAMP indicates the presence or decrease of host cGAS activity. (Item 9) The method according to any one of the above items, wherein the CDN is determined to be of the origin of the microorganism if it contains at least one of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP. (Item 10) The method according to any one of the above items, wherein the 3'3'-cGAMP indicates the presence of either or both Gram-positive and Gram-negative bacteria. (Item 11) The method according to any one of the above items, wherein the c-di-AMP indicates the presence of mainly Gram-positive bacteria, such as Listeria monocytogenes, tuberculosis bacteria, or serious human pathogens or environmentally related microorganisms. (Item 12) The method according to any one of the above items, wherein the c-di-GMP indicates the presence of Gram-negative and / or Gram-positive bacteria (e.g., Bacillus subtilis and Listeria monocytogenes), and indicates the presence of numerous functions, including biofilm formation and motility. (Item 13) The method according to any one of the above items, wherein if any of the three microbial CDNs (3'3'-cGAMP, c-di-AMP, and c-di-GMP) are detected in abnormal amounts compared to a healthy control, it suggests a microbial imbalance.(Item 14) The method according to any one of the above items, wherein the microbial imbalance shown by these three types of microbial CDNs (3'3'-cGAMP, c-di-AMP, and c-di-GMP) contributes to further activation of the STING pathway, which may result in exacerbation of STING-mediated conditions. (Item 15) The method according to any one of the above items, wherein the 3'2'-cGAMP indicates the presence of bacteria or indicates a state related to antiviral immunity. (Item 16) The method according to any one of the above items, wherein the determination is made based on an individual comparison of (A) the amount or level of 2'3'-cGAMP with (B) one or more of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP. (Item 17) The method according to any one of the above items, wherein the determination is made by (A) the amount or level of 2'3'-cGAMP and (B) the total amount of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP. (Item 18) A method for adjusting a therapeutic strategy for a patient with an allergic disease (e.g., asthma) or a chronic inflammatory lung disease (e.g., COPD), comprising the steps of: 1) measuring serum levels of circular double-stranded DNA (CDN) containing 3'3'-cGAMP, 2'3'-cGAMP, and c-di-AMP in a patient sample; 2) identifying a disruption of the microbiome or hyperactivity of the cGAS-STING pathway based on elevated levels of bacterial or host-derived CDN, respectively; 3) implementing an appropriate therapeutic intervention (e.g., probiotics or antibiotics to normalize the gut microbiota and reduce bacterial-derived CDN levels, or cGAS-STING pathway inhibitors to reduce host-derived CDN levels); and 4) improving clinical outcomes by mitigating Th2-mediated allergic inflammation by redirecting the immune response to Th1-type immunity, if necessary, by concomitant use of a TLR9 agonist. (Item 19) The method according to any one of the above items, which utilizes the CDN level as a biomarker to stratify patients and adjust intervention strategies accordingly, thereby providing personalized diagnostic and therapeutic strategies for the management of allergic asthma and COPD.(Item 20) The method according to any one of the above items, wherein the CDN is measured or information obtained in the body fluid of the subject. (Item 21) The method according to any one of the above items, wherein the body fluid comprises at least one selected from the group consisting of serum, plasma, sweat, urine, intestinal extract and feces. (Item 22) The method according to any one of the above items, wherein the diagnosis comprises identifying a significant deviation indicating at least one selected from the group consisting of dysbiosis, leaky gut and increased cGAS-STING pathway activity. (Item 23) If the level of the host-derived CDN is higher than that of a healthy control, it indicates elevated cGAS activity, and a specific inhibitor may be included in the treatment protocol. The method according to any one of the above items, wherein if the level of the microbial-derived CDN is higher than that of a healthy control, it indicates a disruption of the microbiome, and such patients may be administered drugs that modify the microbiome, such as antibiotics or probiotics. (Item 24) The method according to any one of the above items, wherein the method is performed in vitro, and preferably the measurement is performed by an ELISA assay. (Item 25) The method according to any one of the above items, wherein the determination is made by comparing with a healthy control or by comparing with an already established threshold for a healthy control. (Item 26) The method according to any one of the above items, wherein the determination is made if, when compared with the healthy control, the level of host-derived CDN is higher than that of the healthy control, it indicates an increase in cGAS activity and whether a specific inhibitor targeting cGAS or its downstream pathway should be included in the treatment protocol; if the level of microbial-derived CDN is higher than that of the healthy control, it indicates a disruption of the microbiome and suggests that the patient may benefit from microbiome-modifying treatment such as antibiotics or probiotics; preferably, to determine the threshold for comparison, a statistical analysis is performed that takes into account a healthy control group matched for age, sex, and race, so that a significant deviation can be reliably and accurately determined, or in such cases, it is determined that a significant upregulation or downregulation has occurred.(Item 27) The method according to any one of the above items, indicating that if the level of the microbial CDN is high, the patient's microbiome needs to be normalized by at least one intervention selected from the group consisting of antibiotics and probiotics. (Item 28) The method according to any one of the above items, indicating that if the 2'3'-cGAMP level is elevated, cGAS activity is enhanced. (Item 29) The method according to any one of the above items, indicating that if the 2'3'-cGAMP level is elevated, a cGAS inhibitor with a targeted agent should be administered as necessary. (Item 30) A method for treating or preventing a physical condition of a subject, comprising: 1) determining the physical condition of the subject by the method according to any one of the above items; and 2) achieving treatment or prevention by taking appropriate measures for the subject in accordance with the determination result. (Item 31) An agent for detecting or determining the physical condition of a subject, comprising a detection agent for measuring cyclic dinucleotides (CDNs), wherein it is determined whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject, and a STING-related disease or condition is diagnosed based on the result of the determination. (Item 32) The agent according to Item 31, further comprising one or more features described in any one or more of Items 1 to 30. (Item 33) A device for detecting or determining the physical condition of a subject, comprising an element for measuring cyclic dinucleotides (CDNs), and a determination element for determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject, and a STING-related disease or condition is diagnosed based on the result of the determination. (Item 34) The device according to Item 33, further comprising one or more features described in any one or more of Items 1 to 30.(Item 35) A kit for detecting or determining the physical condition of a subject, comprising a detection agent or element for measuring cyclic dinucleotides (CDNs), and instructions, wherein the instructions describe determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject, and diagnosing a STING-related disease or condition based on the result of the determination. (Item 36) The kit according to Item 35, further comprising one or more features described in any one of Items 1 to 30. (Item 37) A pharmaceutical composition for treating or preventing a physical condition of a subject, comprising measuring cyclic dinucleotides (CDNs), determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject, diagnosing a STING-related disease or condition based on the result of the determination, and comprising a therapeutic or preventive agent determined to be suitable for the subject in accordance with the result of the diagnosis. (Item 38) The pharmaceutical composition according to Item 37, further comprising one or more features described in any one of Items 1 to 30. (Item 39) A device for treating or preventing a physical condition of a subject, comprising: an element for measuring cyclic dinucleotides (CDNs); and a determination element for determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject, wherein a STING-related disease or condition is diagnosed based on the result of the determination, and an appropriate therapeutic or preventive agent is set for the subject according to the result of the diagnosis. (Item 40) The device according to Item 39, further comprising one or more features described in any one or more of Items 1 to 30.(Item 41) A kit for treating or preventing a physical condition of a subject, comprising a detection agent or element for measuring cyclic dinucleotides (CDNs), and instructions, wherein the instructions explain that the CDNs are determined to be of origin to the subject and / or to microorganisms (parasites) expected to be present in the subject, a STING-related disease or condition is diagnosed based on the result of the determination, and an appropriate therapeutic or preventive agent is set for the subject according to the result of the diagnosis. (Item 42) The kit according to Item 41, further comprising one or more features described in any one of Items 1 to 30. (Item 43) Use of the level of cyclic dinucleotides (CDNs) measured in a sample taken from a subject as a marker for diagnosing the physical condition of a subject. (Item 44) A system for evaluating the physical condition of a subject, comprising means for measuring the level of cyclic dinucleotides (CDNs) in a sample taken from a subject, and configured to evaluate asthma based on the level. (Item 45) The system according to any one of the above items, comprising a physical condition assessment unit that assesses the physical condition of the subject using the level of cyclic dinucleotides as input features to a classification model using a machine learning algorithm. (Item 46) Use of cyclic dinucleotides (CDNs) measured in a sample taken from a subject as a diagnostic marker for STING-related diseases or conditions. (Item 46A) The use according to Item 46, further comprising the features described in any one or more of the above items. (Item 47) The use described in any one of the above items, wherein the CDN is at least one selected from the group consisting of 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP, and the STING-related disease or condition is selected from the group consisting of asthma, chronic obstructive pulmonary disease (COPD), hay fever, STING-associated vasculopathy with onset in infancy (SAVI), Ecardi-Goutier syndrome (AGS), systemic lupus erythematosus (SLE), and cancer.(Item 48) Use of a detection agent for cyclic dinucleotides (CDNs) for manufacturing a diagnostic reagent for diagnosing STING-related diseases or conditions. (Item 49) A system for evaluating the physical condition of a subject, comprising: an acquisition unit for acquiring the level of cyclic dinucleotides (CDNs) in a sample taken from a subject; a determination unit for determining whether the CDNs originate from the subject and / or from microorganisms expected to be contained in the subject; and a diagnostic unit for diagnosing or assisting in the diagnosis of STING-related diseases or conditions based on the determination result of the determination unit. (Item 49A) The system according to Item 49, further comprising the features described in any one or more of the above items. (Item 50) The system according to any one of the above items, wherein the diagnostic unit is configured to use the level of cyclic dinucleotides as an input feature to a classification model using a machine learning algorithm to calculate the difference between asthma and chronic obstructive pulmonary disease (COPD), the distinction between asthmatic subjects and non-asthmatic subjects, or the need for normalization of the microbiome. (Item 51) The system according to any one of the above items, wherein the determination unit is configured to determine the contribution from the subject based on the level of 2'3'-cGAMP and to determine the contribution from the microorganism based on the level of at least one of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP. (Item 52) A program for diagnosing or assisting in the diagnosis of a subject's physical condition, which causes a computer to perform the steps of: receiving data as input regarding the level of cyclic dinucleotides (CDNs) measured in a sample taken from a subject; determining, based on the data, whether the CDNs are of subject origin or microorganism origin; and outputting a diagnostic result regarding STING-related diseases or conditions using a classification model based on the result of the determination. (Item 52A) The program according to item 52, further comprising the features described in any one or more of the above items.(Item 53) The program according to any one of the above items, wherein the classification model is constructed by a machine learning algorithm including a support vector machine (SVM), and the output step includes outputting the identification result of asthma patients and healthy controls, or the differentiation result of asthma and chronic obstructive pulmonary disease (COPD), to a display device. (Item 54) The program according to any one of the above items, wherein in the determination step, the computer is instructed to perform a process to identify increased cGAS activity when the level of 2'3'-cGAMP exceeds a threshold, and to identify the presence of dysbiosis or leaky gut when the level of microbial-derived CDN exceeds a threshold.

[0005] Abnormal activity of STING is involved in autoinflammatory diseases such as STING-associated vascular disease (SAVI), which develops in infancy and is characterized by systemic inflammation affecting blood vessels, skin, and lungs. Although the exact mechanism is still unknown, SAVI mice carrying the N153S STING mutation mimic human disease and develop dysbiosis and colitis. In this disclosure, we observed that only some of these SAVI mice developed diarrhea and colitis, accompanied by more severe systemic inflammation compared to mice without diarrhea. Diarrhea-predominant SAVI mice showed a gut microbiota imbalance (dysbiosis) characterized by a decrease in short-chain fatty acid-producing bacteria and an increase in segmented bacteria, along with elevated levels of cyclic dinucleotides (CDNs) from microorganisms and the host that directly activate the STING pathway. Administration of antibiotics improved inflammation in these gut microbiota-abnormal mice, demonstrating a link between gut microbiota abnormalities and STING-mediated inflammation. Furthermore, SAVI patients had elevated plasma concentrations of microbial and host-derived CDNs compared to healthy controls, suggesting dysbiosis and enhanced cyclic GMP-AMP synthase (cGAS) activity. Systemic CDN levels in patients with STING-related inflammatory diseases, including systemic lupus erythematosus (SLE), correlated with the degree of systemic inflammation. Therefore, we found that microbial CDNs may be a potential biomarker and therapeutic target for STING-related autoinflammation.

[0006] STING-dependent diseases or conditions, such as STING-associated vasculopathy (SAVI) [hereinafter also referred to as STING-associated diseases or conditions], are caused by excessive immune activation.

[0007] This disclosure reveals that dysbiosis exacerbates inflammation by increasing both bacterial and host-derived CDNs, which are STING agonists.

[0008] In SAVI mice with colitis, these CDNs excessively stimulate the STING pathway, exacerbating systemic inflammation. Treatment of these mice with antibiotics reduced inflammation, suggesting the involvement of gut bacteria in STING-mediated exacerbation of inflammation. Elevated CDN levels in SAVI and lupus patients correlated with disease severity, suggesting that microbial CDNs may be biomarkers and potential therapeutic targets for STING-related diseases.

[0009] To date, there have been no reports of using CDN as a biomarker to tailor treatment strategies for STING-related diseases, and this disclosure is the first in this field to provide a tool that can lead to treatment strategies for STING-related diseases. In this disclosure, we found that SAVI model mice with gut microbiota disruption, diarrhea, colitis, and elevated fecal microorganisms and fecal CDN levels exhibited enhanced systemic inflammation and more severe symptoms compared to SAVI mice without gut microbiota disruption or colitis. Furthermore, a significant positive correlation was observed between disease severity markers and systemic CDN levels in patients with both SAVI and SLE, in which STING plays a crucial role. These findings highlight the industrial applicability of this disclosure, which offers applications in the diagnosis, personalized medicine, and targeted therapy strategies for STING-related diseases.

[0010] The use of CDNs proposed in this disclosure as biomarkers for STING-related diseases holds significant practical and industrial potential. These biomarkers can enable accurate disease identification as diagnostic tools, facilitate early detection and personalized treatment strategies, and improve the prognosis of SAVI, SLE, and other inflammatory diseases. This technology can also be applied to other STING-related diseases such as asthma and COPD, where STING pathway activity is important. Industrially, it has the potential to lead to new diagnostic kits and treatment monitoring systems, creating opportunities in diagnostics and personalized medicine. Healthcare companies, such as pharmaceutical companies, can leverage this for patient stratification and targeted therapy development, addressing important unmet needs in precision medicine.

[0011] The concentrations of five naturally occurring CDNs—2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP—are measured in biological fluids such as serum, plasma, urine, and feces using commercially available detection systems, including but not limited to CDN-specific ELISA kits. CDN levels are quantified in both patient and healthy control samples to identify significant upregulation or downregulation based on thresholds established from the healthy control cohort. Significant changes in CDN levels may indicate dysbiosis, leaky gut, or increased cGAS-STING pathway activity.

[0012] This disclosure aims to establish a diagnostic method for STING-related autoinflammatory diseases or conditions. These CDNs (including 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP) are measured in biological fluids such as serum, plasma, urine, and feces. This method can identify significant deviations indicating dysbiosis, leaky gut, and increased cGAS-STING pathway activity by quantifying CDN levels in patients and healthy controls. This approach can enable personalized treatment strategies by tailoring interventions based on specific CDN profiles, thereby improving the diagnosis and management of STING-dependent and dysbiosis-related diseases.

[0013] This disclosure utilizes mammalian and microbial CDNs such as 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP as biomarkers for STING-related diseases.

[0014] The CDNs used in this disclosure act as STING agonists and play a crucial role in inflammatory diseases. This disclosure utilizes these CDNs as diagnostic markers to achieve the effect of individualizing treatment strategies based on specific CDN profiles detected in patient samples. For example, high levels of microbial CDNs may indicate the need to normalize the patient's microbiome through interventions such as antibiotics or probiotics. Conversely, elevated levels of 2'3'-cGAMP, a mammalian CDN produced by cGAS, suggest enhanced cGAS activity, suggesting cGAS inhibition with targeted agents as a treatment strategy. This biomarker-based approach enables precise and individualized treatment, addressing the limitations of conventional therapies and improving outcomes for patients with STING-related diseases.

[0015] Figure 1 shows the results of phenotypic observations of STING N153S mice. (A) Sequence comparison of WT and STING N153S mutant alleles. (B) Survival curves of STING N153S mice (n=113) and littermates of wild-type (WT) mice (n=157). (C) Images showing perianal lesions (yellow arrows), anal prolapse (yellow arrows), and shortened colon in 6-month-old diarrhea-type STING N153S mice. Data are shown as mean ± SEM. Survival curves were tested using the Log-rank (Mantel-Cox) test, and colon length was tested using the Student's t-test. ****P < 0.0001. (D) Representative hematoxylin-eosin stained sections of paraffin-embedded colon, ileum, and stomach from 6-month-old diarrhea-predominant STING N153S and WT mice. Scale bar: 100 μm. Figure 2 shows the results of diarrhea-predominant STING N153S mice exhibiting hypercytokinemia. (A-G) Serum cytokine and chemokine levels were measured by Bio-Plex assay and ELISA in diarrhea-predominant STING N153S mice, non-diarrhea-predominant STING N153S mice, and littermates of WT mice. Individual data points for each mouse are plotted, with horizontal lines representing the mean values ​​(n=6-20 mice per group). *P<0.05, **P<0.01, ****P<0.0001 (according to Student's t-test). Figure 3 shows the results of abnormal gut microbiota formation and elevated levels of both host-derived and microbial-derived CDNs in feces in diarrhea-type STING N153S mice. (A) Principal coordinate analysis (PCoA) of the gut microbiota of 4-month-old diarrhea-type STING N153S mice, non-diarrhea-type STING N153S mice, and littermates (WT mice). (B) Comparative analysis of the gut microbiota of diarrhea-type STING N153S mice and non-diarrhea-type STING N153S mice using the effect size (LEfSe) of linear discriminant analysis (LDA). Bars with negative LDA scores (Log10) indicate bacteria increased in diarrhea-type STING N153S mice, and bars with positive LDA scores indicate bacteria increased in non-diarrhea-type STING N153S mice. (C) Concentrations of 2'3'-cGAMP, 3'3'-cGAMP, and c-di-GMP in stool samples from diarrhea-type STING N153S mice, non-diarrhea-type STING N153S mice, and WT mice from the same litter.The data points represent individual mice, and the horizontal lines indicate the mean values ​​(n=5-10 mice in each group). (D) Concentrations of 2'3'-cGAMP, 3'3'-cGAMP, and c-di-GMP in serum samples from mice of the same group. The data points represent individual mice, and the horizontal lines indicate the mean values ​​(n=5-10 mice in each group). The results were analyzed using Student's t-test. *p<0.05, **p<0.01. Figure 4 shows the results of an example in which antibiotic administration prevented inflammation in diarrheal STING N153S mice. WT mice aged 4-6 months with diarrheal STING N153S mice, non-diarrheal STING N153S mice, and littermates were given drinking water containing a mixture of vancomycin, ampicillin, neomycin, and metronidazole, or drinking water without antibiotics, for 14 days. (A) Changes in body weight during antibiotic administration in diarrhea-type STING N153S, non-diarrhea-type STING N153S, and littermates in WT mice. The diarrhea-type STING N153S, non-diarrhea-type STING N153S, and WT groups each contained n=8, 9, and 5 mice, respectively. Each point represents the mean percentage calculated based on body weight on day 0, and the error bars indicate SD. Data were analyzed using Student's t-test. *p < 0.05, ****p < 0.0001. (B) Serum IL-6 levels before and after antibiotic administration. *P < 0.05 (Mann-Whitney test). Figure 5 shows the results in SAVI patients who exhibited systemic elevations of both microbial and host-derived CDN. (A) Plasma concentrations of 2'3'-cGAMP, c-di-AMP, and c-di-GMP from three SAVI patients and seven healthy adults. One patient was treated with a JAK inhibitor, and another was treated with steroids. Data points represent individual samples, and bar graphs represent the mean values. Data were analyzed using the Mann-Whitney test. *p < 0.05, **p < 0.01. (B) Plasma CDN concentrations from one SAVI patient and four healthy donors. Samples were taken from the SAVI patient before and after steroid treatment. Bar graphs represent the average of multiple measurements of the same sample. Double values ​​of change between the mean values ​​of the SAVI patient and healthy controls, and double values ​​of change between the mean values ​​of the SAVI patient before and after steroid treatment are shown.(C) CDN concentrations in urine samples from one SAVI patient and three healthy donors. The SAVI patient was receiving steroid treatment. The bar graph represents the average of multiple measurements of the same sample. The double change between the mean values ​​of the SAVI patient and healthy controls is shown. Figure 6 shows results suggesting that systemic CDN is a potential biomarker for STING-related autoinflammation. (A) Correlation analysis between serum 2'3'-cGAMP, c-di-AMP, c-di-GMP levels and IFN-β in patients with various autoinflammatory and autoimmune diseases, including RA, SLE, SSc, PM / DM, Sjögren's syndrome, GCA, MPA, GPA, EGPA, Behçet's disease, and AOSD (n=4-8 for each disease). (B) Correlation analysis between serum 2'3'-cGAMP, c-di-AMP, c-di-GMP levels and serum anti-dsDNA antibody levels in seven SLE patients. (C) Correlation analysis between serum 2'3'-cGAMP, c-di-AMP, c-di-GMP levels and type I IFN scores in 32 SLE patients from a Dutch cohort, including 16 childhood-onset SLE patients and 16 adult-onset SLE patients. (D) Correlation analysis between serum 2'3'-cGAMP, c-di-AMP, c-di-GMP levels and serum IP-10 levels in 17 RA patients. (D) Correlation analysis between serum 2'3'-cGAMP, c-di-AMP, c-di-GMP levels and serum IP-10 levels in 17 RA patients. Data were analyzed using Spearman correlation analysis. * indicates p < 0.05, ** indicates p < 0.01. SLE, systemic lupus erythematosus, MPA, microscopic polyangiitis, EGPA, eosinophilic granulomatosis with polyangiitis, RA, rheumatoid arthritis, SSc, systemic sclerosis, PM / DM, polymyositis / dermatomyositis, GCA, giant cell arteritis, AOSD, adult-onset Still's disease, dsDNA, double-stranded DNA, CRP, C-reactive protein. Figure 7 shows findings in STING N153S mice consistent with previous reports. (A) Macroscopic lesions (arrows) and pleural effusion (triangle symbols) were observed in the lungs of WT and STING N153S mice. (B) Ulcerative skin lesions on the head and fibrotic tail of STING N153S mice. (C) Hematoxylin and eosin staining of paraffin-embedded lung sections and skin sections of 4-5 month old STING N153S mice and their littermates (WT mice). Scale bar, 100 μm. (D) Splenomegaly in STING N153S mice.(E) Quantitative results of anti-dsDNA immunoglobulin in serum of STING N153S and littermate WT mice. The horizontal bar represents the mean of samples obtained from two or more independent experiments. *p < 0.05, **p < 0.01, ****p < 0.0001 (by Mann-Whitney test). Figure 8 shows the results of reduced naive CD4-positive and CD8-positive T cells in STING N153S mice. (A) Gating for flow cytometry analysis. (B) Total number of CD45+, CD19+, CD3+, CD4+, CD8+, and Ly6G+ cells in WT splenocytes of 4-month-old STING N153S and littermate mice. (C, D) Percentages of naive, central memory, and effector memory CD4+ (C) and CD8+ (D) T cells in 4-month-old STING N153S and littermate WT splenocytes. *p < 0.05, ***p < 0.001 (Mann-Whitney test). Figure 9 shows the results of hypercytokinemia in diarrhea-type STING N153S mice. Serum cytokine and chemokine levels were measured by Bio-Plex assay in diarrhea-type STING N153S, non-diarrhea-type STING N153S, and WT littermates not shown in Figure 2. Horizontal bars represent mean values. One-way ANOVA: *p < 0.05, **p < 0.01, ***p < 0.001. Figure 10 shows the results of diarrhea-type STING N153S mice, which showed elevated spleen weight and anti-dsDNA IgM levels. (A, B) Spleen weight (A) and serum anti-dsDNA IgM titer (B) of diarrhea-type STING N153S mice, non-diarrhea-type STING N153S mice, and littermates of WT mice. The horizontal bars represent the mean values. *p < 0.05, **p < 0.01, ****p < 0.0001 by Student's t-test. Figure 11 shows the results of changes in disease phenotype due to differences in gut microbiota between mice raised at different facilities (University of Tokyo and Osaka University). (A) Survival curve of STING N153S heterozygous mice raised at Osaka University when raised at the University of Tokyo animal facility. (B-E) Gut microbiota of 12-week-old mice from Osaka University and the University of Tokyo. Principal coordinate analysis (B, D) and LEfSe (C, E) of WT and STING N153S mice.(F) Concentrations of 2'3'-cGAMP, 3'3'-cGAMP, and c-di-GMP in fecal samples of STING N153S heterozygous mice and WT mice from the same litter raised at the University of Tokyo. Data for individual mice are represented as points, and the mean for each group is shown (n=4 for each group). Statistical analysis was performed using Student's t-test. Figure 12 shows the changes in body weight during the growth process of WT and STING N153S mice. Data for littermates housed in two different cages are shown. Around 3 months of age, one STING N153S mouse in each cage began to show diarrhea and weight loss, but the WT mice and other STING N153S mice did not show weight loss or diarrhea. Figure 13 shows STING mutations in SAVI patients. (A) STING sequences of a Turkish SAVI patient and its parents. (B) Family tree and STING sequence of Japanese SAVI patients. Figure 14 shows the correlation between serum CDN levels and representative inflammatory cytokine levels in autoinflammatory and autoimmune patients. (A-D) Scatter plots showing the correlation between serum CDN levels and serum (A), IFN-α (B), IP-10 (C), and IL-6 (D) levels in patients with all autoinflammatory and autoimmune diseases, including RA, SLE, SSc, PM / DM, Sjögren's syndrome, GCA, MPA, GPA, EGPA, Behçet's disease, and AOSD (n=4-8 for each disease). Data were analyzed by Speerman correlation analysis. SLE is systemic lupus erythematosus, MPA is microscopic polyangiitis, EGPA is eosinophilic granulomatosis with polyangiitis, RA is rheumatoid arthritis, SSc is systemic sclerosis, PM / DM is polymyositis and dermatomyositis, GCA is giant cell arteritis, and AOSD is adult-onset Still's disease. Figure 15 shows the correlation between serum CDN levels and representative inflammatory cytokine levels in patients of the Dutch cohort. (A) Correlation between type I IFN score, IFN-α2 level, and type I IFN score and IFN-α2 level. (B) Scatter plot showing the correlation between serum CDN levels and type I IFN score in patients of the Dutch cohort, including SSc (n=10), Sjögren's syndrome (n=20), and childhood-onset and adult-onset SLE (n=16 per SLE group, 32 SLE patients in total). The data was analyzed using Spearman correlation analysis.SLE stands for systemic lupus erythematosus, and SSc stands for systemic sclerosis. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Correlations were analyzed using Spearman correlation analysis, and pairwise comparisons were performed using Student's test. Figure 16 shows a schematic diagram of the diagnostic technique using the CDN of this disclosure. The explanation for Figure 17 is as follows: Six-week-old female C57BL / 6J mice were given 0.5 × 10 B16 BL6 tumor cells on day 0. ６Individual doses were administered. Fecal samples for pretreatment were collected 6 days before tumor inoculation. On days 9, 11, and 13, mice were administered 10 μg each of control, TLR9 agonist (K3 CpG or D35 CpG), STING agonist (five types of CDN), or a combination of TLR9 agonist and STING agonist as intratumoral injections. Tumor growth was monitored for 15 days, and post-treatment samples including feces, serum, and tumors were collected from mice on day 15. Tumor weight was recorded, and fecal CDN levels were measured by ELISA for the five types of CDN. Correlation analysis was performed between pre-treatment (circles) and post-treatment (squares) fecal CDN levels and tumor weight (n=5 in each group). Data were analyzed by Speerman correlation analysis. **p < 0.01. Figure 18 shows serum 3'3'-cGAMP levels in patients with asthma and chronic obstructive pulmonary disease (COPD) compared to healthy controls. Serum 3'3'-cGAMP levels were significantly elevated in patients with asthma and COPD compared to healthy controls. Serum levels of 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP were measured in asthma patients (n=198), COPD patients (n=38), and healthy controls (n=29). The data are shown as a scatter plot, with the mean indicated by the horizontal line. Statistical significance was determined by the Mann-Whitney U test (**p<0.01, ****p<0.0001). Figure 19 shows the correlation analysis between serum cytokine levels and 3'3'-cGAMP in patients with chronic obstructive pulmonary disease (COPD). 3'3'-cGAMP showed a significant positive correlation with 2, eotaxin, rantes, MIP-1β, and IL-9 in COPD. Serum 3'3'-cGAMP levels in COPD patients were measured by ELISA. Serum levels of eotaxin, rantes, MIP-1β, and IL-9 were measured using the 27-plex Bio-Plex assay. Correlation analysis was performed between 3'3'-cGAMP and these cytokines / chemokines (n=38). Statistical significance was determined at **p < 0.001 and ***p < 0.0001. Figure 20 shows the correlation analysis between serum cytokine levels and 2'3'-cGAMP in patients with chronic obstructive pulmonary disease (COPD).2'3'-cGAMP showed a significant positive correlation with RANTES, MIP-1β, and IL-9 in COPD. Serum 2'3'-cGAMP levels in COPD patients were measured by ELISA. Serum levels of RANTES, MIP-1β, and IL-9 were measured using the 27-plex Bio-Plex assay. Correlation analysis was performed between 2'3'-cGAMP and these cytokines / chemokines (n=38). Statistical significance was determined at ***p < 0.0001. Figure 21 shows the correlation analysis between serum PDGF-BB levels and 3'2'-cGAMP in patients with chronic obstructive pulmonary disease (COPD). 3'2'-cGAMP showed a significant negative correlation with PDGF-BB and IgE in COPD. Serum 3'2'-cGAMP levels in COPD patients were measured by ELISA. Serum IgE levels in COPD patients were measured by ELISA. Serum PDGF-BB levels were measured using the 27-plex Bio-Plex assay. Correlation analysis between 3'2'-cGAMP and IgE was performed (n=38). Statistical significance was determined by *p < 0.05 and **p < 0.01. Figure 22 shows serum 3'3'-cGAMP levels, serum IL-1RA levels, and blood neutrophil percentage in asthma patients. Significant positive correlations were observed between serum 3'3'-cGAMP levels, serum IL-1RA levels, and blood neutrophil percentage in asthma patients. Serum 3'3'-cGAMP levels in asthma patients (n=198) were measured by ELISA. Serum IL-1RA levels were assessed using the Bio-Plex assay, and serum neutrophil percentage data were provided by Biobank Japan. Correlation analysis was performed between 3'3'-cGAMP and these parameters. Statistical significance was shown as follows: **p < 0.01, ***p < 0.001. Figure 23 shows the predictive performance of support vector machines (SVMs) for asthma and COPD using serum cyclic dinucleotide (CDN) profiles. The diagnostic performance of the SVM classifier using serum CDN profiles was evaluated by receiver operating characteristic (ROC) curve analysis.(A) ROC curves comparing healthy control group vs. asthma patient group, asthma group vs. non-asthma group, and COPD group vs. non-COPD group, using the same SVM model and serum CDN measurements as training data. (B) Classification performance in each comparison is summarized as the area under the ROC curve (AUC) value. SVM analysis showed that healthy control group vs. asthma patient group could be well distinguished based on serum CDN levels, while classification accuracy for COPD was relatively low. Figure 24 shows a comparison of the predictive performance of the SVM model with different input features. The predictive performance was compared when the features used as input parameters were changed using the same support vector machine (SVM) model. (A) AUC values ​​when only five types of serum CDN measurements were used as input parameters are shown. (B) AUC values ​​when only Bio-Plex data for 27 types of cytokines / chemokines were used as input parameters are shown. (C) The AUC values ​​are shown when a feature set combining serum CDN measurements (5 types) and Bio-Plex cytokine / chemokine data (27 types) is used as input parameters. By changing the input features while keeping the classification model constant, it was shown that the highest predictive performance was obtained when only serum CDN measurements were used. On the other hand, adding cytokine / chemokine data to the CDN data did not necessarily improve the asthma discrimination performance, indicating that classification using CDN alone is the most effective.

[0016] The present disclosure is described below in best form. Throughout this specification, singular expressions should be understood to include the concept of their plural form unless otherwise specified. Accordingly, singular articles (e.g., "a," "an," "the" in English) should be understood to include the concept of their plural form unless otherwise specified. Furthermore, terms used herein should be understood to have the meaning commonly used in the art unless otherwise specified. Accordingly, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure pertains. In case of any conflict, this specification (including definitions) shall prevail.

[0017] The following provides definitions of terms used specifically in this specification and / or basic technical concepts as appropriate.

[0018] In this specification, "approximately" refers to significant figures unless otherwise specified, but is understood to mean an equivalent amount permitted by the pharmacopoeia.

[0019] In this specification, "STING" refers to the following: STING (an IFN gene (adapter molecule) stimulator of interferon genes), identified as a membrane protein localized in the endoplasmic reticulum, plays a crucial role in the body's defense mechanisms against infection by various RNA and DNA viruses. Furthermore, STING has been reported to play an important role in inducing innate immune responses to DNA components derived from viruses and bacteria, although its molecular mechanism remained unclear. STING can form complexes not only with viral genomic DNA, but also with synthetic double-stranded DNA of 45-90 base pairs called ISD, and even with self-DNA components derived from apoptotic cells. Analysis of DNA interaction regions in vitro has shown that the C-terminal region of STING is important. It is known that recognition of various DNA components by STING induces dynamic changes in its localization to the peripheral region of the nuclear membrane, leading to the induction of interferon production via TBK1 activation. Furthermore, it has been suggested that STING may be involved in the regulation of chronic inflammatory responses through the recognition of not only non-self DNA components derived from microorganisms, but also self-DNA components.

[0020] In this specification, “STING-related diseases” refer to a group of diseases caused by abnormal activation or dysregulation of the STING (Stimulator of Interferon Genes) pathway. STING-related diseases include allergies, autoinflammatory diseases, autoimmune diseases, or cancer. Furthermore, STING-related diseases or conditions may include allergic or symptomatic diseases (e.g., sterile inflammatory diseases), autoimmune diseases, cancer, or conditions related thereto.

[0021] STING plays a central role in the innate immune response, inducing the production of type I interferons and inflammatory cytokines after detecting abnormal DNA. However, excessive activation of this pathway is known to lead to chronic inflammation and autoimmune diseases. A representative STING-related disease is STING-associated vasculopathy with onset in infancy (SAVI). This disease is caused by mutations in the STING gene and is a progressive vasculitis that develops in infancy. The main symptoms include interstitial lung disease, skin ulcers, and peripheral vascular disorders, which can lead to fatal complications in severe cases. Furthermore, excessive activation of STING can also cause autoinflammatory diseases and autoimmune diseases such as lupus-like syndrome. In these diseases, a persistent inflammatory response causes tissue damage. Furthermore, abnormalities in the STING pathway have been suggested to be involved in the onset and progression of cancer, and it has been pointed out that in some tumors, activation of the STING pathway may induce inflammatory responses in the tumor microenvironment, thereby promoting immunosuppression. As for treatment, the development of drugs that suppress the excessive activation of the STING pathway is underway. In particular, STING inhibitors are expected to be used in the treatment of SAVI and autoinflammatory diseases. Conversely, STING activators may be used in cancer immunotherapy and as vaccine adjuvants. Thus, because STING-related diseases encompass a wide range of pathologies, a detailed understanding of the STING pathway is essential for their diagnosis and treatment. Further research is expected to lead to the development of more effective treatments.

[0022] More specifically, the CDNs used in this disclosure act as STING agonists and are known to play a significant role in inflammatory diseases (e.g., sterile inflammatory diseases). Using the CDNs of this disclosure as diagnostic markers allows for the individualization of treatment strategies based on specific CDN profiles detected in patient samples. For example, high levels of microbial CDNs may indicate the need to normalize the patient's microbiome through interventions such as antibiotics or probiotics. Conversely, elevated levels of 2'3'-cGAMP, a mammalian-derived CDN produced by cGAS, suggest enhanced cGAS activity, allowing for targeted cGAS inhibition as a treatment strategy. This biomarker-based approach enables precise and individualized treatment, addressing the limitations of conventional therapies and improving outcomes for patients with STING-related diseases.

[0023] STING-related diseases are a group of diseases caused by abnormal activation of the STING pathway, and their relationship with the microbiome and personalized medicine is attracting attention. Representative diseases include STING-associated childhood vasculopathy with onset in infancy (SAVI) and autoinflammatory diseases (Aicardi-Goutieres syndrome). SAVI is caused by activating mutations in the STING gene and develops in infancy as vasculitis accompanied by skin ulcers, interstitial lung disease, and peripheral vascular disease. In Aicardi-Goutieres syndrome, chronic overproduction of interferon causes neurological disorders and developmental delays.

[0024] In this specification, "aseptic inflammatory disease" refers to inflammatory diseases that occur without infection by exogenous pathogens such as bacteria, viruses, and fungi. These diseases are caused by abnormal activation of the immune system, cell damage, metabolic abnormalities, etc. Examples include autoimmune diseases such as rheumatoid arthritis and systemic lupus erythematosus, gout, and age-related inflammatory responses. Chronic obstructive pulmonary disease (COPD) is also an example of an aseptic inflammatory disease, in which chronic inflammation is caused by factors other than infection, such as smoking and air pollution. Abnormal secretion of inflammatory cytokines and abnormal immune responses are observed in these diseases. This disclosure aims to provide novel diagnostic and therapeutic methods for aseptic inflammatory diseases.

[0025] A link between these diseases and the microbiome has been suggested. The gut microbiome is deeply involved in regulating the immune system, and imbalances in it (dysbiosis) may exacerbate chronic inflammation via the STING pathway. For example, the mechanism by which metabolites and DNA fragments produced by gut bacteria activate STING, leading to colitis and systemic inflammation, is being studied.

[0026] In the field of personalized medicine, approaches that consider genetic mutations and microbiome conditions are advancing in the treatment of STING-related diseases. For example, STING inhibitors may alleviate symptoms in SAVI patients, and analyzing each patient's genetic background and gut environment is crucial to enhancing treatment effectiveness. Furthermore, regulating gut bacteria using probiotics and prebiotics may contribute to reducing inflammation and improving symptoms.

[0027] Furthermore, the STING pathway is also associated with the development of lupus-like syndrome, asthma, COPD, and certain cancers (e.g., skin cancer, lung adenocarcinoma). Other conditions associated with STING include: • Autoinflammatory diseases (e.g., sarcoidosis, cryopyrin-associated periodic fever syndromes) • Neurodegenerative diseases (e.g., Alzheimer's disease, Parkinson's disease) • Infectious diseases (e.g., HIV infection, herpesvirus infection, tuberculosis) • Inflammatory bowel diseases (e.g., Crohn's disease, ulcerative colitis) • Vasculitis syndromes (e.g., Takayasu's arteritis, giant cell arteritis) • Obesity and metabolic diseases (e.g., type 2 diabetes, non-alcoholic fatty liver disease) In these diseases, new methods are being sought to control the STING pathway by regulating the microbiome and improve therapeutic outcomes. Elucidating the interaction between the microbiome and STING is expected to open new avenues for prevention and treatment of these diseases.

[0028] In this specification, "STING ligand" and "STING agonist" are interchangeable and are ligands (agonists) of IFN gene (adapter molecule) stimulants (STING = stimulator of interferon genes) that induce type I IFN production and NF-κB mediated cytokine production. Examples of STING ligands (agonists) include cGAMP, as well as bacterial cyclic dinucleotides (CDN = cyclic dinuclide) such as c-di-AMP and c-di-GMP, which are upstream molecules of TBK1-IRF3 and ligands of STING, an adapter molecule of the IFN gene that induces type I IFN production and NF-κB mediated cytokine production. [Burdette et al., Nature.] [(2011) 478:515-8; McWhitter et al., J. Exp. Med. (2009) 206:1899-1911]. Recent studies have shown that these CDNs function as potent vaccine adjuvants due to their ability to enhance antigen-specific T cells and humoral immune responses. Nevertheless, our group previously found that the STING agonist DMXAA induces STING-IRF3-mediated type I IFN production, while unexpectedly inducing a type II immune response [Tang et al., PLOS One. (2013) 8:1-6]. The clinical utility of STING agonists has been debatable because type II immune responses may not induce type I immune responses. For example, aluminum salts (aluminum), the most common adjuvants, are known to be excellent adjuvants for inducing type II immune responses, but they lack the ability to induce cellular immunity, which is thought to be effective in suppressing diseases originating from intracellular pathogens or cancer [Hogenesch et al., Front. Immunol. (2013) 3:1-13].To overcome this challenge, Aram has been combined with many different types of adjuvants, including monophosphoryl lipid A [Macleod et al., Proc. Natl. Acad. Sci. U.S.A. (2011) 108:7914-7919] and CpG ODN [Weeratna et al., Vaccine. (2000) 18:1755-1762]. Regarding techniques related to STING, host DNA, as well as microbial DNA, can also be a danger signal, leading to the production of interferons and inflammatory cytokines, especially if host DNA is improperly present in the cytoplasm [Desmet et al., Nat. Rev. Immunol. (2012) 12:479-491; Barber et al.]. [Immunol. Rev. (2011) 243:99-108]. One recently identified cytosolic DNA sensor is a cyclic GMP-AMP synthase (cGAS) that catalyzes the production of non-standard cGAMP (2'3'-cGAMP) containing atypical 2',5' and 3',5' links between guanosine and adenosine [Sun et al., Science. (2013) 339:786-91]. Standard cGAMP (3'3'-cGAMP) is synthesized in bacteria, with GMP and AMP nucleosides linked by bis-(3',5') bonds, and has lower binding affinity to STING than mammalian 2'3'-cGAMP [Wu et al., Science. (2013) 339:826-30; Zhang et al. , Mol. Cell. (2013) 51:226-35].

[0029] Therefore, examples of markers that may be used in this disclosure include CDNs such as 2'3'-cGAMP, c-di-AMP, c-di-GMP, 3'3'-cGAMP, and 3'2'-cGAMP, and xanthene derivatives such as DMXAA. CDNs are described in WO2010 / 017248, and the contents of that document are incorporated herein by reference.

[0030] In this specification, "cyclic dinucleotide (CDN)" refers to a dimer of a nucleotide that has been formed into a ring. Examples of CDNs include, but are not limited to, 2'3'-cGAMP, c-di-AMP, c-di-GMP, 3'3'-cGAMP, and 3'2'-cGAMP. (Japanese Patent Publication No. 2016-506408 (WO2014 / 099824) "Pharmacological Targeting of Mammalian Cyclic Dinucleotide Signaling Pathways") 2'3'-cGAMP is involved in the immune response in mammals, while the other c-di-AMP, c-di-GMP, 3'3'-cGAMP, and 3'2'-cGAMP are derived from microorganisms. In this specification, CDNs derived from mammals may be referred to as "mammalian CDNs," and CDNs derived from microorganisms may be referred to as "microbial CDNs." Microbial CDNs typically include c-di-AMP, c-di-GMP, 3'3'-cGAMP, and 3'2'-cGAMP.

[0031] 2'3'-cGAMP is considered an important molecule involved in the mammalian immune response. It is formed from guanosine triphosphate (GTP) and adenosine triphosphate (ATP), and its name "2',3'-" comes from the presence of phosphate ester bonds at the 2' and 3' positions. It is primarily synthesized by the enzyme cGAS (cycloGMP-AMP synthase). cGAS recognizes DNA as a sensor and produces 2'3'-cGAMP. 2'3'-cGAMP is synthesized when cGAS detects abnormal DNA within cells, and it binds to STING proteins, inducing the production of type I interferons and inflammatory cytokines. It is mainly involved in antiviral and antitumor responses, and its production within infected cells affects neighboring cells. In recent years, 2'3'-cGAMP has attracted attention for its application in cancer immunotherapy and as a vaccine adjuvant, and research into treatment methods is progressing. On the other hand, hyperactivation of the STING pathway can cause autoimmune diseases, and the development of inhibitors for this pathway is also underway. As described above, 2'3'-cGAMP is an extremely important molecule in both immune response and treatment. 2'3'-cGAMP plays an essential role in the mammalian immune response by generating 2'3'-cGAMP that binds to the adapter molecule STING, which initiates an antimicrobial and / or antitumor immune response, upon detection of viral or tumor DNA by the DNA sensor cGAS.

[0032] c-di-AMP (cyclic dinucleotide) is a cyclic dinucleotide produced by bacteria and archaea, and is an important second messenger involved in osmoregulation, potassium ion transport, and cell wall metabolism regulation within microorganisms. In particular, it is known to play a central role in adaptation under osmotic stress. On the other hand, in host immunity, the release of c-di-AMP from bacteria activates the STING pathway in mammalian cells, inducing the production of type I interferon. This action triggers an innate immune response to bacterial infection. Furthermore, if the amount of c-di-AMP produced is not properly regulated within bacteria, excessive production can cause bacterial growth impairment, so c-di-AMP signaling should be carefully regulated in bacteria. In recent years, there has been interest in developing antimicrobial agents targeting c-di-AMP and in using it as a vaccine adjuvant. Thus, while c-di-AMP is an important molecule in both microbial life activities and host immune responses, its function differs from that of 2'3'-cGAMP in that it is primarily specialized in regulatory mechanisms within microorganisms.

[0033] 3'3'-cGAMP (cyclic GMP-AMP) is a cyclic dinucleotide produced by bacteria and primarily functions as a signaling molecule within bacteria. It is formed from guanosine triphosphate (GTP) and adenosine triphosphate (ATP) and is characterized by a structure with phosphate bonds at the 3' and 3' positions. 3'3'-cGAMP is an important second messenger used by bacteria to adapt to external stress and environmental changes. Specifically, it is involved in intracellular stress responses and metabolic regulation, contributing to bacterial survival and adaptation. Furthermore, 3'3'-cGAMP has been reported to be involved in the innate immune response of mammals and has the ability to activate the STING pathway. However, in this respect, it is clearly different from 2'3'-cGAMP. 3'3'-cGAMP is mainly of bacterial origin, and its response in the host immune system is considered secondary. On the other hand, 2'3'-cGAMP is a natural ligand produced by host cells and is involved in the direct activation of innate immunity. In recent years, research has been progressing on the development of vaccine adjuvants utilizing the properties of 3'3'-cGAMP and on novel therapies for bacterial infections. 3'3'-cGAMP is attracting attention as a key to understanding the physiological functions of bacteria and as a potential target molecule in the immune response. The differences in its function and applications compared to 2'3'-cGAMP and c-di-AMP are the focus of research.

[0034] 3'2'-cGAMP (cyclic GMP-AMP) is a naturally occurring cyclic dinucleotide produced by certain bacteria (e.g., Drosophila melanogaster). This molecule is formed from guanosine triphosphate (GTP) and adenosine triphosphate (ATP) and is characterized by a phosphate ester bond at the 3' and 2' positions. Within bacteria, it primarily functions as a signaling molecule involved in stress response and metabolic regulation, playing a crucial role in cell adaptation and survival. Furthermore, 3'2'-cGAMP has been reported to be involved in the mammalian innate immune response. This molecule binds to STING and activates the immune system by inducing the production of type I interferon. This triggers an immune response against bacterial infections and tumors. 3'2'-cGAMP is produced by bacteria. 3'2'-cGAMP is a cyclic dinucleotide identified in Drosophila melanogaster (fruit fly). It is synthesized by cGAS-like receptors (cGLRs) in response to RNA recognition and plays a role in antiviral immunity. Regarding bacterial production of 3'2'-cGAMP, our research has shown that certain bacterial cGAS / DncV-like nucleotide transferases (CD-NTases) can produce various cyclic oligonucleotides, including 3'2'-cGAMP, as part of an anti-phage defense mechanism. In recent years, new therapeutic methods utilizing the immune-activating ability of 3'2'-cGAMP have been studied, with particular attention being paid to its potential as a vaccine adjuvant and immunotherapy drug. This molecule has different structural characteristics compared to 2'3'-cGAMP and 3'3'-cGAMP, which are also cyclic nucleotides, and therefore, differences in their physiological functions and application ranges are being studied.

[0035] c-di-GMP (cyclic dinucleotide) is a cyclic dinucleotide produced by bacteria and is an important second messenger that regulates the life cycle and behavior of bacteria. This molecule is synthesized from guanosine triphosphate (GTP) and controls various physiological functions within bacteria. In particular, c-di-GMP is known as a factor that promotes biofilm formation and plays an important role in strengthening the defense against antibiotics and host immunity when bacteria colonize. It also suppresses bacterial motility and controls the transition to a state of colonization where migration ceases. Furthermore, c-di-GMP is involved in the regulation of cell division and gene expression, enabling bacteria to adapt to environmental conditions. On the other hand, c-di-GMP also plays an important role in the immune response of mammals. It activates the STING pathway in host cells and induces the production of type I interferons and inflammatory cytokines, thereby triggering an infection defense response. In recent years, medical applications utilizing the functions of c-di-GMP have attracted attention. Research is being conducted on the development of antimicrobial drugs that target enzymes that regulate c-di-GMP concentration within bacteria, as well as on their use as vaccine adjuvants to enhance the immune response. Thus, c-di-GMP is a molecule of interest in both bacterial physiological function and host immune response.

[0036] In this specification, "allergic and inflammatory diseases" refer to conditions in which an immune response occurs excessively in response to a substance (in the case of allergies, a specific antigen). In this specification, "allergic and sterile inflammatory diseases," which are distinguished from infectious diseases, may be considered representative subjects. Environmental antigens that cause allergies are specifically called allergens. "Allergic and inflammatory diseases" refer to diseases in which an immune response occurs in response to external antigens. However, these antigens are often harmless in the amounts typically encountered in daily life (for example, spring pollen itself is not toxic), and it can be said that an immune response is occurring that unnecessarily leads to unpleasant results. These are also called allergic diseases. Representative diseases include atopic dermatitis, allergic rhinitis (hay fever), allergic conjunctivitis, allergic gastroenteritis, bronchial asthma, childhood asthma, food allergies, drug allergies, and urticaria. Recently, conditions in which type 1 allergic symptoms such as asthma and facial flushing appear in response to the scent of citrus fruits or fragrances in gum have attracted attention. Inflammatory diseases are chronic inflammatory conditions caused by the immune system attacking its own cells and tissues, and are sometimes called sterile inflammatory diseases to distinguish them from infectious diseases. This is due to dysregulation of the immune system, environmental factors, or genetic factors. Chronic obstructive pulmonary disease (COPD) is an example of both an inflammatory disease and a sterile inflammatory disease, mainly caused by smoking and air pollution, but its central pathology is chronic inflammation of the airways. COPD is characterized by shortness of breath, cough, and increased sputum, and as it progresses, it leads to a decline in lung function, seriously impacting the patient's quality of life.

[0037] Allergies and inflammatory diseases (especially sterile inflammatory diseases) have distinct pathologies, but they share the commonality of involving abnormal immune system responses as a central factor. Therefore, in this disclosure, they are classified as "allergic and inflammatory diseases (especially sterile inflammatory diseases)." Treatment for these diseases requires anti-allergic and anti-inflammatory drugs, improvements to the living environment, and the development of novel therapies based on disease mechanisms. Consequently, COPD is also included within the category of allergic and inflammatory diseases (especially sterile inflammatory diseases).

[0038] On the other hand, "autoimmune diseases" are diseases in which an immune response occurs in response to substances that make up the body's own tissues as antigens. These can manifest as damage to specific organs or parts of the body, inflammation, or systemic symptoms. Representative examples include collagen diseases such as rheumatoid arthritis and alopecia areata.

[0039] In this specification, “cancer” means any cancer that can be diagnosed in this disclosure, including, but is not limited to, hepatocellular carcinoma, esophageal squamous cell carcinoma, breast cancer, pancreatic cancer, squamous cell carcinoma or adenocarcinoma of the head and neck, colorectal cancer, kidney cancer, brain cancer (tumor), prostate cancer, small cell carcinoma (SCLC) and non-small cell lung cancer (NSCLC), bladder cancer, bone or joint cancer, uterine cancer, cervical cancer, multiple myeloma, hematopoietic malignancies, lymphoma, Hodgkin's disease, non-Hodgkin lymphoma, skin cancer, melanoma, squamous cell carcinoma, leukemia, lung cancer, ovarian cancer, gastric cancer, Kaposi's sarcoma, laryngeal cancer, endocrine cancer, thyroid cancer, parathyroid cancer, pituitary cancer, adrenal cancer, cholangiocarcinoma, endometriosis, esophageal cancer, liver cancer, osteosarcoma, pancreatic cancer, soft tissue tumors, acute myeloid leukemia (AML), and chronic myeloid leukemia (CML).

[0040] In this specification, "interferon (IFN)" refers to a protein (cytokine) secreted by cells in an animal body in response to the invasion of foreign substances such as pathogens (especially viruses) and tumor cells. Of these, IFN-α and IFN-β are type I IFNs, and IFN-γ is type II IFN.

[0041] In this specification, "physical condition" refers to any state of the body in question. This "condition" comprehensively describes the structural, functional, or pathological characteristics and conditions of the body, representing the state of the body at a specific time and in a specific environment. For example, a normal state of health, a state of illness or disability, or a temporary physiological change (such as fever or fatigue) are all included in physical conditions.

[0042] In this specification, "presence" refers to the state where an object is actually located or arranged in a specific place, space, or environment. The term "presence" is interpreted to also include the fact that an object can be detected based on physical, chemical, or abstract conditions, or that its effects can be confirmed. For example, this applies when a specific substance is contained in a sample or when a specific signal is observed in space. The specific meaning of the term "presence" in this specification is interpreted according to the context.

[0043] In this specification, the "presence" of a cyclic dinucleotide as a target can be specified by various methods. For example, after collecting a sample considered to contain the measurement target, the sample is prepared before detecting the biomarker. Sample preparation includes nucleic acid isolation. These isolation procedures include separation of nucleic acids from insoluble components (e.g., the cytoskeleton) and cell membranes. Generally, tissues or cells in the body may be treated with a lysis buffer before nucleic acid isolation. The lysis buffer is designed to lyse tissues, cells, lipids, and other biomolecules potentially present in biological samples. Nucleic acids can be conveniently extracted from biological samples obtained from, for example, endometrium (i.e., endometrial tissue) or ovarian tissue using standard extraction methods known to those skilled in the art. Standard extraction methods include the use of chemical agents such as guanidinium thiocyanate, phenol-chloroform extraction, guanidine-based extraction, etc. Commercially available nucleic acid extraction kits may also be used.

[0044] As used herein, "level" refers to the quantitative or qualitative state of a specific measurement target (e.g., the amount, concentration, ratio, etc. of CDN), and means an index serving as a criterion for determining treatment guidelines or evaluations based on the results. The level is used as an important factor in the treatment or prevention effect on STING-related syndrome, the patient's response, or the optimization of the treatment plan. Such a CDN level is applied as a reference value and is also used as a reference value in the selection of prevention / treatment targets and the adjustment of prevention / treatment plans. As used herein, "level information" refers to quantitative or qualitative data regarding a specific measurement target (e.g., immune response, amount, concentration, and ratio of CDN, gene expression, etc.), and means information serving as a basis for evaluating the patient's condition and determining the adaptability and guidelines of treatment based on this information.

[0045] As used herein, "subject" or "subject (person)" is used interchangeably and refers to an entity (e.g., an organism such as a human or cells, blood, serum, intestinal extract, feces, etc. taken from an organism) that is the target of the diagnosis, detection, treatment, etc. of the present disclosure.

[0046] As used herein, "treatment" refers to preventing the exacerbation of a certain disease or disorder (e.g., cancer, allergy), preferably maintaining the current state, more preferably reducing, and even more preferably eliminating the disease or disorder when in such a state, and includes the ability to exert a symptom improvement effect or a preventive effect on the patient's disease or one or more symptoms associated with the disease. Performing a diagnosis in advance and then performing appropriate treatment is called "companion treatment", and the diagnostic agent therefor may be called a "companion diagnostic agent".

[0047] In this specification, "therapeutic agent" broadly refers to any agent capable of treating a target condition (e.g., diseases such as cancer and allergies). In one embodiment of this disclosure, "therapeutic agent" may be a pharmaceutical composition comprising an active ingredient and one or more pharmacologically acceptable carriers. The pharmaceutical composition can be manufactured, for example, by mixing the active ingredient with the carriers and any method known in the art of pharmaceutical formulation. Furthermore, the therapeutic agent is not limited in its form of use as long as it is used for treatment, and may be an active ingredient alone or a mixture of the active ingredient with any other ingredient. Furthermore, the shape of the carrier is not particularly limited, and may be, for example, a solid or a liquid (e.g., a buffer solution). Note that therapeutic agents for cancer, allergies, etc. include drugs used for the prevention of cancer, allergies, etc. (preventive drugs), or inhibitors of cancer, allergies, etc.

[0048] In this specification, “prevention” means preventing a disease or disorder (e.g., allergy) from occurring before it occurs. Diagnosis can be made using the agents disclosed herein, and if necessary, the agents disclosed herein can be used to prevent, for example, allergies, or to take preventive measures.

[0049] In this specification, "preventive medicine" broadly refers to any medicine that can prevent a target condition (for example, diseases such as allergies).

[0050] In this specification, “kit” means a unit that provides components that would normally be provided in two or more separate compartments (e.g., test reagents, diagnostic reagents, therapeutic agents, antibodies, labels, instructions, etc.). This kit form is preferable when the aim is to provide a composition that, for stability or other reasons, should not be provided mixed, but is preferable to mix immediately before use. Such a kit is preferably advantageous to include the components to be provided (e.g., instructions or instructions describing how to use the test reagents, diagnostic reagents, therapeutic agents, or how to handle the reagents). When a kit is used as a reagent kit in this specification, the kit usually includes instructions describing how to use the test reagents, diagnostic reagents, therapeutic agents, antibodies, etc.

[0051] In this specification, “Instructions” are instructions for a physician or other user on how to use the Disclosure. These instructions contain language instructing the administration of the detection method, diagnostic agent, or drug of the Disclosure. The instructions may also contain language instructing the administration site to be oral or esophageal (e.g., by injection). These instructions shall be prepared in accordance with the format prescribed by the supervisory authority of the country in which the Disclosure is implemented (e.g., the Ministry of Health, Labour and Welfare in Japan, or the Food and Drug Administration (FDA) in the United States) and shall be clearly stated to have been approved by that supervisory authority. The instructions are a so-called package insert and are usually provided in paper format, but are not limited to that and may also be provided in electronic format (e.g., a homepage provided on the Internet, email).

[0052] In this specification, "agent," "agent," or "factor" (all equivalent to "agent" in English) may broadly refer to any substance or other element (e.g., energy such as light, radioactivity, heat, or electricity) that can be used interchangeably and achieve the intended purpose. Such substances include, but are not limited to, proteins, polypeptides, oligopeptides, peptides, polynucleotides, oligonucleotides, nucleotides, nucleic acids (e.g., DNA such as cDNA and genomic DNA, RNA such as mRNA), polysaccharides, oligosaccharides, lipids, small organic molecules (e.g., hormones, ligands, signaling molecules, small organic molecules, molecules synthesized by combinatorial chemistry, small molecules that can be used as pharmaceuticals (e.g., small molecule ligands), etc.), and complex molecules thereof. Typical examples of factors specific to polynucleotides include, but are not limited to, polynucleotides that complement the sequence of the polynucleotide with a certain degree of sequence homology (e.g., 70% or more sequence identity), polypeptides such as transcription factors that bind to promoter regions, etc. Typical examples of factors specific to a polypeptide include, but are not limited to, antibodies or derivatives or analogues specifically targeted to that polypeptide (e.g., single-chain antibodies), specific ligands or receptors when the polypeptide is a receptor or ligand, and substrates when the polypeptide is an enzyme. Typically, in this specification, "agent" refers to an agent containing factors such as antibodies, antibody-binding fragments, and mimetics, used for any purpose. Those used for diagnostic purposes are called diagnostic agents, and those used for therapeutic purposes are called therapeutic agents. Agents can be specified by their intended use.

[0053] In this specification, "entity" means any substance or other element (e.g., energy such as light, radioactivity, heat, or electricity) as long as it is a means to achieve the intended purpose and is sufficient to achieve that purpose. Such substances include, but are not limited to, proteins, polypeptides, oligopeptides, peptides, polynucleotides, oligonucleotides, nucleotides, nucleic acids (e.g., DNA such as cDNA and genomic DNA, RNA such as mRNA), polysaccharides, oligosaccharides, lipids, small organic molecules (e.g., hormones, ligands, signaling molecules, small organic molecules, molecules synthesized by combinatorial chemistry, small molecules that can be used as pharmaceuticals (e.g., small molecule ligands), etc.), and complex molecules thereof. Factors also include molecules that perform functions similar to antibodies, such as antibodies in the narrow sense, antigen-binding molecules, antibody-like molecules, and antibody mimetics.

[0054] In this specification, "device" refers to a part of a machine or apparatus (such as medical supplies, dental materials, or sanitary products) used for the diagnosis, treatment, or prevention of a physical condition such as a disease in a human or animal, or intended to affect the structure or function of a human or animal body. Where a mass spectrometer is intended for the purposes of this disclosure, the part necessary for mass analysis (e.g., a sample separation unit that separates ionized samples) is intended. For example, for the purposes of this disclosure, if the concentration of a control in the blood is known, disease state can be predicted by other methods, such as immunoassays based on antibody detection (not only ELISA, but also Western blotting and Luminex assay, etc.) or protein quantification that does not rely on antibodies (mass spectrometry, etc.).

[0055] In this specification, "disease" is interpreted in a broad sense and refers to a condition in which normal mental or physical functions are disrupted. This also includes conditions such as disabilities.

[0056] In this specification, “treatment” (or any grammatically equivalent term) means any action that directly or indirectly affects a condition (including disease) or a pre-condition (including health conditions or pre-disease in traditional Chinese medicine), and includes treatment and prevention. Treatment for cancer includes, but is not limited to, surgery, radiotherapy, proton therapy, chemotherapy, molecular targeted drugs, immunotherapy (also known as cancer immunotherapy, including, but not limited to, immune checkpoint inhibitors, CART cell therapy, etc.), and any combination thereof (including any combination of two or three or more homogeneous or heterogeneous drugs). In the case of T-cell related diseases, it includes, but is not limited to, immunomodulatory drugs (anti-inflammatory drugs (including biologics), immunosuppressants (such as steroids), immunostimulants (including immune checkpoint inhibitors)), and any combination thereof (including any combination of two or three or more homogeneous or heterogeneous drugs).

[0057] In this specification, "therapy" (or its grammatically equivalent term) means, with respect to a disease or disorder, preventing the worsening of such a condition, preferably maintaining the current state, more preferably reducing it, and even more preferably eliminating it. If such effects are achieved, it includes the possibility of improving the symptoms of the patient's disease or one or more symptoms associated with the disease, or additionally providing a preventive effect. Providing appropriate treatment based on prior diagnosis is called "companion therapy," and the diagnostic agent used for this purpose is sometimes called a "companion diagnostic agent."

[0058] In this specification, “prevention” (and its grammatically equivalent terms) means preventing a disease or disorder from occurring before it occurs. The drugs, devices, or compositions of this disclosure can be used to make a diagnosis and, if necessary, to prevent, or to take preventive measures against, for example, cancer.

[0059] In this specification, “diagnosis” (or its grammatically equivalent term) means identifying various parameters (e.g., the amount and properties of proteins in the body, or the copy number and presence or absence of substitutions of genes) related to the condition of a subject (e.g., disease, disability), and determining the current or future state of such a condition. By using the methods, compositions, and systems of this disclosure, the condition of the body can be examined, and such information can be used to select various parameters such as the condition of the subject, the treatment to be administered, or prescriptions or methods for prevention. In this specification, “diagnosis” in a narrow sense means diagnosing the current state, but in a broad sense it includes “early diagnosis,” “predictive diagnosis,” “preliminary diagnosis,” etc. In this disclosure, “diagnosis” may be used synonymously with “judgment.” The diagnostic methods of this disclosure are industrially useful because, in principle, they can be performed using materials obtained from the body and can be carried out without the intervention of medical professionals such as physicians. In this specification, in order to clarify that they can be carried out without the intervention of medical professionals such as physicians, “predictive diagnosis, preliminary diagnosis, or diagnosis” may be referred to as “supporting.” The technology disclosed herein can be applied to such diagnostic technologies.

[0060] In this specification, "prognosis" (or its grammatically equivalent term) refers to the condition of a patient after a procedure, or the future state of a disease or wound, particularly the prospects regarding those states. For example, in the case of cancer, it refers to the reduction of tumor volume, suppression of tumor growth, the course or outcome of the disease (e.g., whether or not there is a recurrence, survival, etc.) after a procedure for cancer (e.g., ICI, chemotherapy, etc.), and more specifically (but not limited to) the length of survival and the level of risk of recurrence. Determining prognosis may also involve predicting the survival period or the survival rate after a certain period following a procedure, and may include making predictions about the future state and the appropriateness of the procedure during treatment based on measurements taken during treatment.

[0061] In this specification, “effect” in treatment, therapy, prevention, etc., is interpreted in its broadest sense to mean the condition of a patient after a treatment, the future condition of a disease or wound, and especially the elimination or improvement of the underlying disorder to which the treatment is expected to be performed. Furthermore, the effect is interpreted as being achieved by the elimination or improvement of one or more physiological symptoms associated with the underlying disorder, so that improvement is observed in the patient, even if the patient may still be suffering from the underlying disorder.

[0062] In this specification, “prediction” is interpreted in its broadest sense and means, for example, calculating or making a preliminary determination of the effect or prognosis of a treatment or preventive measure for cancer, as represented in this disclosure. Examples of predictions include the state of the disease (disease staging), the speed and extent of recovery (prognosis prediction), and the effect of a drug.

[0063] In this specification, the terms “subject” or “subject” are equivalent to the term “individual,” and both terms may be used interchangeably herein. “Subject” means any individual, as well as any animal belonging to any species. Examples of subjects include, but are not limited to, animals of commercial interest, such as birds (hens, ostriches, chicks, geese, partridges, etc.), rabbits, hares, pets (dogs, cats, etc.), sheep, animals of the genus Capricornus (goat cattle, goats, etc.), animals of the genus Suo (boars, pigs, etc.), domesticated animals of the family Equidae (horses, ponies, etc.), animals of the genus Bosus (bulls, cows, castrated bulls, etc.); animals of hunting interest, such as male deer, stags, reindeer, etc.; and humans. However, in certain embodiments, the subject is a mammal, and in particular, a mammal is a human of any race, sex, or age.

[0064] In this specification, "sample" and "specimen" are interchangeable and typically refer to a certain amount of material from a biological source, environmental source, medical source, patient source, or subject, which is considered to contain the subject of measurement or detection (even if not detected as a result of measurement). A sample may preferably be a biological sample (also called a biologically derived sample). There is no particular need to limit biologically derived samples as long as they are derived from a living organism, and various biologically derived samples can be used. Examples of such biologically derived samples include samples taken directly from a living organism, samples that have been washed or crushed, and examples include blood, tissue lavage fluid such as alveolar lavage fluid, urine, cerebrospinal fluid, feces, and tissue sections. These biologically derived samples can be used in their original form in the evaluation system, or they may be used as test samples after certain pretreatment. It is preferable to use blood, tissue lavage fluid such as alveolar lavage fluid, urine, cerebrospinal fluid, and feces as biologically derived samples. This makes it possible to measure by ELISA or the like instead of immunohistochemical testing, and eliminates the influence of biopsy sites and variability between testing laboratories.

[0065] In this specification, "detection" means determining whether or not an object is present, and includes not only determining whether or not an object is present by zero or one, but also determining whether or not an object is present by measuring or calculating values ​​related to the presence of the object to calculate quantitative or semi-quantitative values ​​of presence (such as quantity, activity value (U (unit), etc.), or ratio), etc., and determining whether or not it is present.

[0066] In this specification, "quantification" means determining the amount of a substance in question. In a narrow sense, quantification refers to determining the amount using a standard substance, while determining the amount without using a standard substance is called semi-quantification. However, in a broader sense, treatment is understood to encompass both, and in this specification, when "quantification" is used, it is understood to encompass both quantification in the narrow sense and semi-quantification. Quantification may be calculated using absolute values, but it may also be expressed using relative or indirect values ​​such as activity values ​​(U (units), etc.) or ratios.

[0067] In this specification, "carrier" means a material used to immobilize the factors, agents, etc. of this disclosure and to facilitate their detection. For example, in the case of an agent containing a certain protein, if that protein is provided as a carrier on which it is immobilized, the carrier can be used as a means for reacting the sample with the carrier and as a means for interacting with, detecting, or quantifying the protein bound to the carrier. For example, a carrier on which a certain antibody is immobilized can be prepared, and the carrier can be used as a means for reacting the sample with the test sample and as a means for interacting with, detecting, or quantifying the protein bound to the carrier. The carrier serves as a carrier for immobilizing the agents of this disclosure. The carrier is not particularly limited as long as it fulfills this role, and can be made of various materials or in various shapes. Typically, hydrophobic plastic microplates, beads (magnetic beads, fluorescent particles, etc.), tubes, etc., can be used as carriers, and most preferably, multi-well microplates can be used.

[0068] In this specification, “Instructions” (including package inserts and labels used by the U.S. Food and Drug Administration (FDA)) are instructions for a physician or other user on how to use the Disclosure. Instructions may often be included in a kit. These instructions contain language instructing the administration of the diagnosis or the medicine based thereon of the Disclosure. They may also contain language instructing judgments regarding the prediction of treatment (e.g., cure or prevention). These instructions are prepared in accordance with the format prescribed by the supervisory authority of the country where the Disclosure is implemented (e.g., the Ministry of Health, Labour and Welfare in Japan, or the FDA in the United States) and are clearly marked as having been approved by that supervisory authority. Instructions are so-called package inserts and labels and may, but are not limited to, be provided in paper format, and may also be provided in electronic format (e.g., a homepage provided on the Internet, PDF, email). The kit may also include, or in place of, an instruction manual, a standard solution (calibrator), positive and negative control reagents, a washing solution, a stop solution, a supplement antibody and a detection antibody, the detection antibody may be labeled, and one or more of these may be included.

[0069] In this specification, "interaction" (or "interacting factors") refers to a state in which two or more substances interact with each other in a non-covalent manner, and is used synonymously with "binding" and "association" in the context of this specification. Detection can be performed based on interactions, and intracellular signal transduction can also be realized through interactions. Interactions are expressed as binding interactions, which are their strength, and are generally characterized by, but not limited to, a dissociation constant (Kd) of less than 10⁻⁶ M to less than 10⁻¹⁵ M. "Affinity" refers to the strength of the binding, with higher binding affinity occurring when the mutual relationship is associated at a lower Kd.

[0070] In this specification, the term "interacting factor" is used synonymously with "binding factor," "associating factor," etc., and when the purpose is detection, it is also called a "detecting factor," and includes, for example, antibodies or their antigen-binding fragments.

[0071] In this specification, "antibody" includes molecules or groups of molecules that can specifically bind to a particular epitope on an antigen. Antibodies may also be polyclonal or monoclonal antibodies. Antibodies can exist in various forms, for example, full-length antibodies (antibodies having a Fab region and an Fc region), Fv antibodies, Fab antibodies, F(ab') antibodies. ２The antibody may be one or more forms selected from the group consisting of antibodies, Fab' antibodies, diabodies, single-chain antibodies (e.g., scFv), dsFv, multivalent specific antibodies (e.g., bivalent specific antibodies), antigen-binding peptides or polypeptides, chimeric antibodies (e.g., mouse-human chimeric antibodies, chicken-human chimeric antibodies, etc.), mouse antibodies, chicken antibodies, humanized antibodies, human antibodies, or equivalents thereof. The antibody may also include modified or unmodified antibodies. Modified antibodies may have various molecules, such as polyethylene glycol, bound to the antibody. Modified antibodies can be obtained by chemically modifying the antibody using known methods. Furthermore, such antibodies may be covalently bonded to or recombinatively fused to enzymes, such as alkaline phosphatase, horseradish peroxidase, or α-galactosidase. The antibodies used in the present invention only need to bind to their target, and their origin, type, shape, etc., are not relevant. Specifically, known antibodies such as antibodies from non-human animals (e.g., mouse antibodies, rat antibodies, camel antibodies), human antibodies, chimeric antibodies, and humanized antibodies can be used. In the present invention, monoclonal or polyclonal antibodies can be used, but monoclonal antibodies are preferred. Specific binding of the antibody to the target is preferred. The antibody also includes modified or unmodified antibodies. Modified antibodies may have various molecules, such as polyethylene glycol, bound to the antibody. Modified antibodies can be obtained by chemically modifying the antibody using known methods. The term "antibody" also includes genetically modified forms such as chimeric antibodies (e.g., humanized mouse antibodies) and heteroconjugate antibodies (bispecific antibodies, etc.). (Pierce Catalogue Handbook, 1994-1995 (Pierce Chemical Co., Rockford, III.); Kuby, J.) See also Immunology, 3rd Ed., W. H. Freeman & Co., New York, 1997. An antibody "antigen-binding fragment" is a part of the antibody that retains the ability to specifically bind to the antibody's target antigen.As used herein, the term “antigen” refers to a compound, composition, or substance that can be specifically bound by an antibody molecule or a specific humoral or cellular immune product, such as a T cell receptor. Antigen-binding fragments of antibodies include Fv, dsFv, scFv, Fab, Fab', and F(ab')2. The Fv fragment consists of the VL and VH domains of the antibody, associated with each other by hydrophobic interactions; in the dsFv fragment, the VH:VL heterodimer is stabilized by a disulfide bond; and in the scFv fragment, the VL and VH domains are linked to each other via a flexible peptide linker, thus forming a single-chain protein. The Fab fragment is a monomeric fragment obtained by papain digestion of the antibody, and includes the entire L chain and the VH-CH1 fragment of the H chain, linked to each other by a disulfide bond. The F(ab')2 fragment can be produced by pepsin digestion of an antibody below a hinged disulfide and contains two Fab' fragments and, additionally, a portion of the hinge region of an immunoglobulin molecule. The Fab' fragment is obtained from F(ab')2 by cleavage of the disulfide bond at the hinge region. The F(ab')2 fragment is bivalent, i.e., contains two antigen-binding sites, like innate immunoglobulin molecules; on the other hand, the Fv (VH:VL dimer constituting the variable region of Fab), dsFv, scFv, Fab, and Fab' fragments are monovalent, i.e., contain a single antigen-binding site. These basic antigen-binding fragments of the present invention can be combined with each other to obtain polyvalent antigen-binding fragments, such as diabodies, triabodies, or tetrabodies. Polyvalent antigen-binding fragments are also part of the present invention. The “mimetics” of the antibody refers to the antigen-binding antibody mimetics. Antigen-binding antibody mimetics are organic compounds that specifically bind to an antigen but are not antibody-related. They are typically artificial peptides or small proteins with a molar mass of approximately 3–20 kDa. Nucleic acids and small molecules can also be considered antibody mimetics, but they are not considered artificial antibodies, antibody fragments, or fusion proteins composed of them. Common advantages over antibodies include superior solubility, tissue penetration, thermal and enzyme stability, and relatively low manufacturing costs. Antigen mimetics are being developed as therapeutic and diagnostic agents.Antigen-binding antibody mimetics can also be selected from a group that includes afibody, affin, affimer, afitin, DARPin, and monobody.

[0072] (Preferred Embodiments) Preferred embodiments of the present invention are described below. The embodiments provided below are provided for a better understanding of the present invention, and it is understood that the scope of the present invention should not be limited to the following description. Accordingly, it is clear to those skilled in the art that they can make appropriate modifications within the scope of the present invention by referring to the description herein. It is also understood that the following embodiments of the present invention can be used individually or in combination.

[0073] (Diagnostic Technique) This disclosure establishes a diagnostic method for STING-related autoinflammatory diseases using microbially derived cyclic dinucleotides (CDNs) as biomarkers. Naturally derived CDNs (including 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP) are measured in biological fluids such as serum, plasma, urine, intestinal extracts, and feces. We have found that quantifying CDN levels in patients and healthy controls can identify significant deviations indicating dysbiosis, leaky gut, and increased cGAS-STING pathway activity. This approach enables personalized treatment strategies by tailoring interventions based on specific CDN profiles, thereby improving the diagnosis and management of STING-dependent and dysbiosis-related diseases.

[0074] In one specific embodiment, this disclosure provides that the concentrations of five naturally occurring cyclic dinucleotides (CDNs)—2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP—are measured in biological fluids such as serum, plasma, urine, and feces using commercially available detection systems, including but not limited to CDN-specific ELISA kits. CDN levels are quantified in both patient and healthy control samples to identify significant upregulation or downregulation based on thresholds established from a healthy control cohort. Significant changes in CDN levels may indicate dysbiosis, leaky gut, or increased cGAS-STING pathway activity. This disclosure utilizes microbial and mammalian-derived CDNs—such as 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP—as biomarkers for STING-related diseases. These CDNs act as STING agonists and play a crucial role in autoinflammatory processes. By using these CDNs as diagnostic markers, treatment strategies can be individualized based on specific CDN profiles detected in patient samples. For example, high levels of microbial CDNs may indicate the need to normalize the patient's microbiome through interventions such as antibiotics or probiotics. Conversely, elevated levels of 2'3'-cGAMP, a mammalian CDN produced by cGAS, suggest enhanced cGAS activity, potentially leading to the proposal of targeted drug-mediated cGAS inhibition as a treatment strategy. This biomarker-based approach enables precise and individualized treatment, addressing the limitations of conventional therapies and improving outcomes for patients with STING-related diseases. To date, there have been no reports of using CDN as a biomarker to adjust treatment strategies for STING-related diseases, which is surprising. The data in this disclosure show that SAVI model mice with gut microbiota disruption, diarrhea, colitis, and elevated fecal microorganisms and fecal CDN levels exhibit enhanced systemic inflammation and develop more severe disease compared to SAVI mice without gut microbiota disruption or colitis.Furthermore, a significant positive correlation was observed between disease severity markers and systemic CDN levels in patients with both SAVI and SLE, in which STING plays a crucial role. These findings highlight the usefulness of this disclosure, offering applications in the diagnosis, personalized medicine, and targeted therapy strategies for STING-related diseases.

[0075] This disclosure also provides the use of CDNs, proposed as biomarkers for STING-related diseases, with various potential applications. For example, as a diagnostic tool, these biomarkers can enable accurate disease identification, facilitate early detection and personalized treatment strategies, and improve the prognosis of SAVI, SLE, and other autoinflammatory diseases. This technology can also be applied to other STING-related diseases, such as asthma and infections, where STING pathway activity is important. Industrially, it has the potential to lead to new diagnostic kits and treatment monitoring systems, creating opportunities in diagnostics and personalized medicine. It can be used to address important unmet needs in precision medicine, such as by utilizing it for patient stratification and the development of targeted therapies.

[0076] The STING pathway is known to play a crucial role in the onset and progression of asthma. While this pathway functions as a factor that promotes asthma, it has also been reported to play a protective role under certain conditions.

[0077] This section explains the role of promoting asthma. Host DNA released by NETossis, a type of specialized cell death performed by neutrophils and a process that functions as part of the immune response, has been reported to promote exacerbations of type 2 allergic asthma caused by rhinovirus infection (Toussaint et al., Nat Med. 2017). This mechanism may function as a major factor in worsening the inflammatory response in the airways. Regarding IL-33-dependent asthma induction by cyclic GMP-AMP (cGAMP), it has been confirmed that cGAMP induces IL-33-mediated asthma inhibited by the TBK1 inhibitor Amlexanox (Ozasa, Temizoz et al., Front. Immunol., 2019). This pathway plays an important role in regulating the expression of asthma pathology via STING signaling. Regarding the induction of allergic inflammation by cyclic GMP-AMP synthase (cGAS) in airway epithelium, it has been shown that cGAS in airway epithelium is important for inducing experimental allergic airway inflammation (Han et al., J Immunol., 2020). This study revealed that the cGAS-STING pathway is directly involved in the onset and progression of airway allergies.

[0078] Regarding the protective role of STING activation, one notable aspect is the suppression of IL-33-induced immunopathology. Activation of STING in alveolar macrophages and group 2 innate lymphoid cells (ILC2s) has been reported to suppress IL-33-dependent type 2 immunopathology. This effect has been confirmed by intra-airway administration of 2'3'-cGAMP in mice using an eosinophilic asthma model and IL-33 or a fungal allergen (Aspergillus flavus) (She et al., JCI Insight, 2021). These results suggest the STING pathway has potential as a therapeutic target for suppressing the progression of asthma.

[0079] The relationship between the STING pathway and chronic obstructive pulmonary disease (COPD) suggests that the STING pathway plays a crucial role in the progression and control of COPD. While this pathway is a factor that promotes the progression of COPD, it has also been confirmed to play a protective role under certain conditions.

[0080] DNA Damage and Increased Cell-Free DNA: DNA damage in peripheral blood is significantly increased in COPD patients. This phenomenon has been revealed in a study by Maluf et al., suggesting that DNA damage is an important factor in the pathogenesis of COPD (Maluf et al., Mutat Res., 2007). Furthermore, Avriel et al. reported that the level of cell-free DNA (cfDNA) can be used as an indicator to identify the risk of poor prognosis in COPD patients (Avriel et al., Int J Chrome Object Pulmon Dis., 2016). These studies indicate that DNA damage and cfDNA accumulation are associated with the progression of COPD.

[0081] Promotes inflammation through exposure to tobacco smoke (CS). CS is one of the major causes of COPD, and research by Nascimento et al. has confirmed that CS exposure increases the content of autologous DNA in the alveolar lumen. Furthermore, it has been revealed that this increased DNA causes neutrophil infiltration via the cGAS-STING pathway, promoting the inflammatory response. In a CS-induced pneumonia model, DNase I treatment suppressed the harmful effects of neutrophil extracellular traps (NETs) and reduced pneumonia (Nascimento et al., Sci Rep., 2019). These results suggest that NETs and the cGAS-STING pathway play important roles in the inflammatory pathogenesis of COPD.

[0082] Bleomycin-induced pulmonary fibrosis: Bleomycin induces pulmonary fibrosis, a process involving STING signaling. A study by Sun et al. reported that bleomycin treatment increased STING expression in the lungs (Sun et al., Biomedicine and Pharmacotherapy, 2020). However, this study did not include STING gene knockout (KO) experiments, and the direct impact of STING activation on the pathogenesis of COPD and pulmonary fibrosis remains unclear.

[0083] Protective Role of the STING Pathway in COPD: In a bleomycin-induced pulmonary fibrosis model (mouse COPD / idiopathic pulmonary fibrosis model), Savigny et al. demonstrated that STING activation plays a protective role in mitigating lung damage. This protective effect was confirmed to be independent of IFN-type signaling, IL-17A, and TGF-β, and to be related to dysregulated neutrophils. Furthermore, a significant reduction in the development of lung damage and pulmonary fibrosis was observed in STING KO mice, indicating that STING plays an important role in the protective mechanism (Savigny et al. Frontiers in Immunology, 2021).

[0084] STING is an important adapter molecule residing in the endoplasmic reticulum (ER) that transmits innate immune signals triggered by sensing pathogenic nucleic acids, tumor nucleic acids, or host-derived nucleic acids via nucleic acid sensors including cyclic GMP-AMP synthase (cGAS) (References 1-4). Detection of cytoplasmic DNA by cGAS is mediated by the STING agonist 2'3'-cyclic GMP-AMP (cGAMP) (Reference 5). Along with 2'3'-cGAMP, microbial cyclic dinucleotides (CDNs) such as cyclic di-AMP (c-di-AMP), cyclic di-GMP (c-di-GMP), 3'3'-cGAMP, and 3'2'-cGAMP can induce dimerization of STING. These agonists of STING, including TBK1, IRF3, and IκB, induce dimerization, rearrangement, and phosphorylation of downstream molecules, leading to IRF3-mediated type I interferon (IFN) and NF-κB-mediated inflammatory cytokine production (References 3, 4, 6-10). Furthermore, type I IFN produced downstream of STING transmits signals via the IFN receptor (interferon α / β receptor, IFNAR), inducing STAT1 phosphorylation and inducing interferon-inducing genes (ISGs) such as ISG15 (Reference 11).

[0085] Previous studies by us and other researchers have reported that STING activation by STING agonists, when used as a vaccine adjuvant, induces a potent CTL and Th1 / 2 immune response, and when used as an immunotherapy agent, provides strong protection against several tumors (References 4, 12-18). On the other hand, the detection of autologous nucleic acids via STING may cause systemic autoinflammatory conditions such as Aicardi-Goutieres syndrome and systemic lupus erythematosus (SLE) (References 19-21). Furthermore, four different gain-of-function mutations in STING (V147L, N154S, V155M, F269S) are responsible for a condition known as STING-associated vascular injury (SAVI), in which constitutive activation of STING leads to overproduction of inflammatory cytokines, ultimately resulting in systemic inflammation and conditions affecting mainly the blood vessels, skin, and lungs (References 22-26). JAK-STAT inhibitors appear to improve the pathology of SAVI, but currently there are no available treatments for SAVI patients (References 27, 28).

[0086] Several groups have developed SAVI mouse models in which N153S or V154M mutations are introduced into STING to elucidate the mechanisms that control immunopathology caused by STING hyperactivation (References 23-25, 29, 30). Both N153S and V154M knock-in (KI) mice develop severe systemic inflammation characterized by vascular disorders, growth disorders, interstitial lung disease, and severe immunodeficiency mainly due to T-cell lymphopenia and type I IFN-independent myeloid expansion (References 21, 23, 27-29). In particular, the V154M mutation induces a higher autoinflammatory response compared to the immunopathology observed in N153S KI mice (Reference 25). Furthermore, lung pathology caused by the N153S mutation is T-cell dependent but independent of type I IFN and cGAS (References 23, 28, 29). Meanwhile, Gary et al. used humanized N154S (human correspondence to the N153S mutation in mice) transgenic mice and showed that, unlike other mouse models, the development of vascular damage is dependent on IFNAR (Reference 24). More recently, Platt et al. also reported that Bacteroides-rich gut microbiota play a protective role in SAVI-induced lung lesions in mice with the N153S mutation, emphasizing the importance of the gut-lung connection (Reference 32) and the importance of commensal flora abnormalities in SAVI development (Reference 31).

[0087] (Detection or Determination of Physical Condition) In one aspect, the Disclosure provides a method for detecting or determining the physical condition of a subject, comprising the steps of: A) measuring cyclic dinucleotides (CDNs) present in the subject or obtaining information on their presence or level; B) determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be present in the subject; and C) diagnosing or providing diagnostic support for STING-related diseases or conditions based on the results of the determination, as well as drugs, devices, kits, systems, programs, recording media, etc., used therein.

[0088] In another aspect, the Disclosure provides a detection or determination agent for a subject's physical condition, comprising a detection agent for measuring cyclic dinucleotides (CDNs), wherein it is determined whether the CDNs originate from and / or from microorganisms (parasites) expected to be present in the subject, and based on the result of the determination, a STING-related disease or condition is diagnosed.

[0089] In another aspect, the Disclosure provides a device for detecting or determining the physical condition of a subject, comprising an element for measuring cyclic dinucleotides (CDNs) and a determination element for determining whether the CDNs originate from and / or from microorganisms (parasites) expected to be present in the subject, wherein a STING-related disease or condition is diagnosed based on the result of the determination. In another aspect, the Disclosure provides a kit for detecting or determining the physical condition of a subject, comprising a detection agent or element for measuring cyclic dinucleotides (CDNs) and instructions, wherein the instructions explain that it is determined whether the CDNs originate from and / or from microorganisms (parasites) expected to be present in the subject, and that a STING-related disease or condition is diagnosed based on the result of the determination.

[0090] In one embodiment, the STING-related disease or condition is an allergic or inflammatory disease (aseptic inflammatory disease), an autoimmune disease, or cancer, or a condition related thereto.

[0091] In one embodiment, the STING-related disease or condition covered by this disclosure is an allergic or inflammatory disease (aseptic inflammatory disease), which may be asthma, hay fever, chronic obstructive pulmonary disease (COPD), etc. In a preferred embodiment, the STING-related disease or condition is asthma and / or COPD. This preferred embodiment enables differential diagnosis between asthma and chronic obstructive pulmonary disease (COPD), differentiation between asthma patients and healthy controls, or differentiation between asthma subjects and non-asthma subjects.

[0092] In one embodiment, the STING-related disease or condition covered by this disclosure is an autoimmune disease, which may be STING-associated vasculopathy with onset in infancy (SAVI), Ecardi-Goutieres syndrome (AGS), or systemic lupus erythematosus (SLE).

[0093] In one embodiment, the STING-related disease or condition covered by this disclosure is cancer, which may include hepatocellular carcinoma, esophageal squamous cell carcinoma, breast cancer, pancreatic cancer, squamous cell carcinoma or adenocarcinoma of the head and neck, colorectal cancer, kidney cancer, brain cancer (tumor), prostate cancer, small cell carcinoma (SCLC) and non-small cell lung cancer (NSCLC), bladder cancer, bone or joint cancer, uterine cancer, cervical cancer, multiple myeloma, hematopoietic malignancies, lymphoma, Hodgkin's disease, non-Hodgkin lymphoma, skin cancer, melanoma, squamous cell carcinoma, leukemia, lung cancer, ovarian cancer, gastric cancer, Kaposi's sarcoma, laryngeal cancer, endocrine cancer, thyroid cancer, parathyroid cancer, pituitary cancer, adrenal cancer, cholangiocarcinoma, endometriosis, esophageal cancer, liver cancer, osteosarcoma, pancreatic cancer, soft tissue tumors, acute myeloid leukemia (AML), and chronic myeloid leukemia (CML).

[0094] In one embodiment, the CDN covered by this disclosure includes at least one of 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP.

[0095] In one embodiment, if the CDN covered by this disclosure includes 2'3'-cGAMP, the CDN is determined to be of the same origin.

[0096] In one embodiment, if the CDN covered by this disclosure contains at least one of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP, the CDN is determined to be of microorganism origin.

[0097] In one embodiment, the determination in this disclosure is performed based on individual comparisons of (A) the quantity or level of 2'3'-cGAMP and (B) any or a combination of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP. These determinations can be performed by assigning a CDN score based on data standardization, and the score can be used in a calculation formula.

[0098] In one embodiment, the determination in this disclosure is made by (A) the amount or level of 2'3'-cGAMP and (B) the total amount of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP. These determinations can be made by assigning a CDN score based on data standardization and using that score in a calculation formula.

[0099] In one embodiment, the present disclosure provides a method for tailoring a therapeutic strategy for a patient with an allergic disease (e.g., asthma) or a chronic inflammatory lung disease (e.g., COPD), comprising the steps of: 1) measuring CDN levels including 3'3'-cGAMP, 2'3'-cGAMP, and c-di-AMP in a patient sample; 2) identifying a disruption of the microbiome or hyperactivity of the cGAS-STING pathway based on elevated bacterial or host-derived CDN levels, respectively; 3) implementing an appropriate therapeutic intervention (e.g., probiotics or antibiotics to normalize the gut microbiota and reduce bacterial-derived CDN levels, or cGAS-STING pathway inhibitors to reduce host-derived CDN levels); and 4) optionally using a TLR9 agonist to redirect the immune response to Th1-type immunity, thereby mitigating Th2-type allergic inflammation and improving clinical outcomes.

[0100] In one embodiment, the approach of the present disclosure utilizes CDN levels as a biomarker to stratify patients and tailor intervention strategies accordingly, thereby providing personalized diagnostic and therapeutic strategies for the management of allergic asthma and COPD.

[0101] In one embodiment, the CDN covered by this disclosure is measured or information obtained from a sample such as the bodily fluids covered by this disclosure.

[0102] In one embodiment, the bodily fluids covered by this disclosure may be serum, plasma, sweat, urine, intestinal extract, or feces.

[0103] In one embodiment, the diagnosis covered by this disclosure includes identifying significant deviations indicating dysbiosis, leaky gut, or increased cGAS-STING pathway activity.

[0104] In one embodiment, if the level of host-derived CDN is higher than that of a healthy control, it indicates elevated cGAS activity, and a specific inhibitor may be included in the treatment protocol. If the level of microbial-derived CDN is higher than that of a healthy control, it indicates a disruption of the microbiome, and such patients may be given drugs that modify the microbiome, such as antibiotics or probiotics. Alternatively, if the level of host-derived CDN is higher than that of a healthy control, it indicates elevated cGAS activity. In such cases, a specific inhibitor targeting cGAS or its downstream pathways may be included in the treatment protocol. Conversely, if the level of microbial-derived CDN exceeds that of a healthy control, it suggests a disruption of the microbiome, and the patient may benefit from microbiome-modifying treatments such as antibiotics or probiotics.

[0105] In one embodiment, the measurement used in this disclosure is performed by an ELISA assay.

[0106] In one embodiment, the determination in this disclosure is made by comparing with a healthy control or by comparing with a previously established threshold for a healthy control.

[0107] In one embodiment, if the level of host-derived CDN is higher than that of a healthy control, it indicates an increase in cGAS activity and suggests that a specific inhibitor targeting cGAS or its downstream pathways should be included in the treatment protocol; if the level of microbial-derived CDN exceeds that of a healthy control, it indicates a disruption of the microbiome and suggests that the patient may benefit from microbiome-modifying treatments such as antibiotics or probiotics; preferably, to determine the threshold for comparison, a statistical analysis should be performed that considers a healthy control group matched for age, sex, and race as a baseline, so that significant deviations can be reliably and accurately determined, or in such cases, it can be determined that significant upregulation or downregulation has occurred.

[0108] In one embodiment, it is shown that when the level of the microbial CDN covered by this disclosure is high, it is necessary to normalize the patient's microbiome through interventions such as antibiotics or probiotics.

[0109] In one embodiment, an increase in the 2'3'-cGAMP level covered by this disclosure indicates enhanced cGAS activity (and, if necessary, that a cGAS inhibitor with a targeted agent should be administered).

[0110] (Companion Techniques) In another context, the Disclosure provides companion therapeutic techniques using the diagnostic techniques of the Disclosure. The Disclosure provides a method for treating or preventing a physical condition of a subject, which comprises: 1) determining the physical condition of the subject by the method of the Disclosure; and 2) achieving treatment or prevention by taking appropriate measures for the subject in accordance with the determination. It is understood that any of the methods described in (Diagnostic Techniques) may be used for determining the physical condition of the method of the Disclosure.

[0111] For example, the present disclosure provides a method comprising: A) measuring cyclic dinucleotides (CDNs) present in a subject or obtaining information on their presence or level; B) determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be present in the subject; C) diagnosing (or assisting in the diagnosis) a STING-related disease or condition based on the result of the determination; and D) taking appropriate measures for the subject to achieve treatment or prevention according to the determination or diagnosis result.

[0112] In another context, the Disclosure relates to a pharmaceutical or medical device for treating or preventing a physical condition of a subject, wherein the pharmaceutical or medical device is a drug or device used for treatment or prevention in which a treatment regimen is determined by 1) determining the physical condition of the subject by the method of the Disclosure, and 2) identifying an appropriate treatment for the subject in accordance with the determination result. The determination by the method of the Disclosure is understood to be any of the methods described in (Diagnostic Techniques).

[0113] (Embodiment of Diagnostic Technology Using a CDN) This disclosure discloses diagnostic technology using a CDN. The technology of this disclosure can be illustrated by referring to the schematic diagram shown in Figure 16.

[0114] In other words, in STING-related diseases such as SAVI, dysbiosis occurs when segmented bacteria (SFBs) such as Candidalus and Arthromitus become dominant over short-chain fatty acid-producing bacteria (probiotics) such as Ruminococcaceae and Lachnospiraceae. These differences in condition can be observed in the gut microbiota, and the condition (e.g., SAVI or SLE) can be predicted or diagnosed by examining host-derived CDNs and microbial-derived CDNs contained in body fluids including serum and plasma, as well as feces.

[0115] The present invention provides a method for detecting or determining the physical condition of a subject in a single situation, comprising: A) measuring cyclic dinucleotides (CDNs) present in the subject or obtaining information on their presence or level; B) determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject; and C) diagnosing or providing diagnostic support for STING-related diseases or conditions based on the results of the determination.

[0116] In certain embodiments, this invention relates to a method for detecting or determining a subject's physical condition using cyclic dinucleotides (CDNs). According to this disclosure, by measuring the presence, quantity, or level of CDNs, it is possible to obtain information about the subject's physiological or pathological condition. CDNs play an important role in immune responses and cellular signaling, and their levels are known to fluctuate in relation to a variety of physical conditions, such as infections, inflammation, tumorigenesis, or metabolic disorders. This invention enables high-precision detection or evaluation of these conditions by using an analytical method that includes a step of measuring CDNs. Measurement methods include, for example, highly sensitive analytical methods using liquid chromatography-mass spectrometry (LC-MS), quantitative methods using enzyme-linked immunosorbent assay (ELISA), or methods using molecular probes to detect specific CDNs. In particular, this disclosure is applicable when using patient serum, plasma, urine, intestinal samples, or cell samples as specimens, and by rapidly and accurately measuring the presence or level of CDNs in these specimens, the pathophysiological state of the subject can be revealed. This method is useful not only as a diagnostic tool but also for monitoring disease progression and evaluating treatment effectiveness. A specific example is its application for the early diagnosis of inflammatory diseases. For example, when CDN levels were measured in plasma samples taken from patients with chronic inflammatory bowel disease (IBD), they were significantly higher than those of healthy individuals. This result suggests the potential use of CDN as a diagnostic marker for IBD. Furthermore, tracking changes in CDN levels after the start of treatment makes it possible to evaluate the effectiveness of the treatment. Thus, the method of the present invention provides a new option in the diagnosis and management of diseases.

[0117] In one embodiment, when measuring cyclic dinucleotides (CDNs) present in a subject or obtaining information about their presence or level, a sample obtained from the subject can be used to measure or obtain information about CDNs. For example, as a specific method for measurement or information acquisition, it is preferable to use highly sensitive and accurate analytical techniques such as liquid chromatography-mass spectrometry (LC-MS) or enzyme-linked immunosorbent assay (ELISA). It is also possible to detect the presence of CDNs by using specific molecular probes or antibodies. These techniques enable rapid and accurate evaluation of the presence or level of CDNs contained in biological samples such as blood, urine, saliva, and tissue extracts.

[0118] In some embodiments of this disclosure, this information can be used as foundational data to evaluate the subject's physical condition, such as infection, inflammation, tumor formation, or immune response. This process is a critical step in diagnosis, monitoring, or evaluation of treatment effectiveness.

[0119] In one embodiment, determining whether a CDN originates from and / or from microorganisms (parasites) expected to be contained within the target includes identifying the type of CDN.

[0120] In detail, 2'3'-cGAMP is derived from the host mammal, and its simple presence suggests a host-derived CDN due to cGAS activation; however, the levels of such CDNs should be compared between healthy controls and diseased patients. In STING-related diseases, elevated 2'3'-cGAMP levels may indicate enhanced host cGAS activity.

[0121] On the other hand, microbial CDNs include 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP.

[0122] 3'3'-cGAMP typically originates from both Gram-positive and Gram-negative bacteria (it was initially identified in Vibrio cholerae).

[0123] c-di-AMP is primarily produced by Gram-positive bacteria such as Listeria monocytogenes. Many organisms that synthesize c-di-AMP are important human pathogens and environmental microorganisms that depend on c-di-AMP for growth and survival. Mycobacterium tuberculosis is also known to be a c-di-AMP-producing bacterium.

[0124] c-di-GMP is widely present in Gram-negative bacteria and controls many functions, including biofilm formation and motility. However, c-di-GMP is not only found in Gram-negative bacteria; some Gram-positive bacteria, such as Bacillus subtilis and Listeria monocytogenes, also produce this molecule.

[0125] If any of these microbial CDNs are detected in abnormal amounts compared to a healthy control, it may indicate dysbiosis (microbial imbalance). Such dysbiosis can contribute to further activation of the STING pathway, potentially exacerbating STING-mediated pathologies.

[0126] 3'2'-cGAMP is produced by bacteria. 3'2'-cGAMP is a cyclic dinucleotide identified in Drosophila melanogaster (fruit fly), synthesized by cGAS-like receptors (cGLRs) in response to RNA recognition, and plays a role in antiviral immunity. Regarding bacterial production of 3'2'-cGAMP, it has been shown that certain bacterial cGAS / DncV-like nucleotide transferases (CD-NTases) can produce a variety of cyclic oligonucleotides, including 3'2'-cGAMP, as part of an anti-phage defense mechanism.

[0127] In one embodiment, STING-related diseases or conditions include allergies and autoinflammatory diseases. In this case, treatment requires personalized medicine tailored to each patient's condition, and the development of new diagnostic technologies and therapeutic drugs is expected. This will make it possible to reduce the burden on patients caused by these diseases and improve their quality of life. Allergies and autoinflammatory diseases include a wide range of conditions. Allergic diseases include hay fever, atopic dermatitis, bronchial asthma, food allergies, drug allergies, urticaria, and anaphylaxis. On the other hand, autoinflammatory diseases include chronic obstructive pulmonary disease (COPD), rheumatoid arthritis, systemic lupus erythematosus (SLE), ulcerative colitis, Crohn's disease, and autoinflammatory syndromes. Furthermore, these diseases are based on abnormal reactions of the immune system, and chronic inflammation is recognized as a common characteristic. When dealing with these diseases, diagnosis and treatment must be carried out appropriately according to the specificity of the disease. In diagnosis, the patient's symptoms, medical history, and identification of allergens and inflammatory factors are important. In cases of allergies, skin prick tests and measurement of specific IgE antibodies are commonly used as diagnostic methods. For autoinflammatory conditions, blood tests measuring inflammatory markers (CRP and ESR) and imaging studies to evaluate lesions are effective. Furthermore, if a genetic factor is suspected, genetic analysis may be performed.

[0128] For allergy treatment, antihistamines, leukotriene receptor antagonists, or steroids are used. For example, in hay fever, symptoms can be effectively managed by appropriately combining these medications with allergen avoidance. Allergen immunotherapy is also promising as a fundamental treatment for allergies and has been shown to be effective in certain patients. In the case of autoinflammatory diseases, immunosuppressants and biological agents are central to treatment. For example, in chronic obstructive pulmonary disease (COPD), inhaled steroids and long-acting β2-agonists are used to suppress airway inflammation, and in severe cases, biological agents with anti-inflammatory effects may be applied. Lifestyle modifications and rehabilitation are also important factors in enhancing treatment effectiveness. Treatment of allergies and autoinflammatory diseases requires individualized medicine tailored to each patient's condition, and the development of new diagnostic technologies and therapeutic drugs is expected. This will reduce the burden on patients suffering from these diseases and improve their quality of life.

[0129] In one embodiment, STING-associated disease or condition is an autoimmune disease. Autoimmune diseases are caused by the immune system mistakenly attacking its own tissues and cells, which it should normally protect. This abnormal immune response may be limited to specific organs or may affect the entire body. There are many types of autoimmune diseases, including rheumatoid arthritis, systemic lupus erythematosus (SLE), type 1 diabetes, Hashimoto's disease (chronic thyroiditis), Graves' disease, multiple sclerosis, ulcerative colitis, Crohn's disease, and psoriasis. Furthermore, STING-associated vasculitis (SAVI) and Aicardi-Goutieres syndrome (AGS) are also noteworthy diseases as they are associated with interferon-mediated disorders.

[0130] In these diseases, the immune system mistakenly identifies self-antigens as foreign substances, triggering an attack by antibodies and immune cells. For example, in rheumatoid arthritis, the immune system attacks the synovial membrane of the joints, leading to inflammation and joint destruction. Systemic lupus erythematosus (SLE), on the other hand, affects tissues throughout the body, causing a variety of symptoms in the skin, kidneys, nervous system, and other areas. SAVI is a rare disease caused by abnormalities in the STING gene, resulting in systemic vasculitis and lung disease, while AGS causes abnormalities in the nervous system and skin due to excessive activation of interferon.

[0131] Diagnosis of autoimmune diseases involves detailed evaluation of the patient's symptoms and medical history, measurement of autoantibodies and inflammatory markers through blood tests, and furthermore, genetic testing and imaging studies. For example, measurement of antinuclear antibodies (ANA), rheumatoid factor (RF), antibodies against specific autoantigens, and interferon signatures is important. These diagnostic methods enable the identification of the disease and the understanding of its progression. Treatment of these diseases aims to suppress inflammation and control the immune response. Generally, steroids and immunosuppressants are used, and in recent years, biological agents have become the mainstay of treatment. For example, tumor necrosis factor (TNF) inhibitors and interleukin inhibitors are highly effective in suppressing inflammation. In addition, for rare diseases such as SAVI and AGS, janus kinase (JAK) inhibitors and other molecularly targeted therapies are considered promising. While autoimmune diseases are often difficult to cure completely, appropriate diagnosis based on this disclosure makes it possible to effectively manage symptoms and suppress disease progression through appropriate treatment.

[0132] In one embodiment, the STING-related disease or condition is cancer. Cancer is a disease in which cells proliferate abnormally, destroying surrounding tissues or metastasizing within the body. The types of cancer that may be covered by this disclosure are very diverse and are classified according to the site and tissue in which they occur. The main types include lung cancer, breast cancer, colorectal cancer, stomach cancer, liver cancer, pancreatic cancer, prostate cancer, cervical cancer, ovarian cancer, uterine cancer, esophageal cancer, bladder cancer, kidney cancer, thyroid cancer, small intestine cancer, bile duct cancer, gallbladder cancer, tonsil cancer, pharyngeal cancer, laryngeal cancer, nasal cavity cancer, penile cancer, testicular cancer, skin cancer (malignant melanoma, basal cell carcinoma, squamous cell carcinoma), etc.; thymoma, thymic carcinoma, peritoneal cancer, mesothelioma, neuroblastoma, Wilms' tumor (nephroblastoma), hepatoblastoma, eye cancer (retinoblastoma), leiomyosarcoma, liposarcoma, osteosarcoma, Cancers include rare cancers such as chondrosarcoma and Ewing's sarcoma; cancers of the central nervous system such as brain tumors (glioma, meningioma, glioblastoma, oligodendroglioma, cerebellar hemangioblastoma) and spinal cord tumors; and other unusual cancers such as Merkel cell carcinoma, Kaposi's sarcoma, angiosarcoma, anal cancer, and salivary gland cancer. In addition, cancers of the blood and lymphatic system include leukemia (acute lymphoblastic leukemia, acute myeloid leukemia, chronic lymphocytic leukemia, chronic myeloid leukemia), malignant lymphoma (Hodgkin lymphoma, non-Hodgkin lymphoma), and multiple myeloma. Genetic and environmental factors are involved in the development of cancer. Major risk factors for cancer include smoking, alcohol consumption, obesity, poor diet, UV exposure, air pollution, radiation exposure, and viral infections (e.g., cervical cancer caused by human papillomavirus (HPV), liver cancer caused by hepatitis B and C viruses, and nasopharyngeal cancer caused by Epstein-Barr virus (EBV)). While conventional cancer diagnosis has relied on imaging (CT, MRI, PET), endoscopy, tissue biopsy, and tumor marker tests, this disclosure enables early detection and detailed analysis, potentially expanding treatment options and improving survival rates. Treatment primarily involves surgery, radiotherapy, and chemotherapy, but recent advances in molecular targeted therapy and immunotherapy have led to the use of PD-1 inhibitors, CTLA-4 inhibitors, and tumor-specific vaccines for many cancers. Because cancer treatment varies depending on the type, stage, and the patient's overall health, personalized medicine is crucial. This disclosure enables such personalized medicine.Furthermore, improving lifestyle habits and promoting early screening are key to cancer prevention and early detection. Moving forward, research to deepen our understanding of cancer and develop new treatments will be crucial.

[0133] In one embodiment, the CDN contains at least one of 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP. Here, if the CDN contains 2'3'-cGAMP, the CDN is determined to be of the subject origin. If the CDN contains at least one of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP, the CDN is determined to be of the microorganism origin.

[0134] Given the complexity and scale of CDN concentrations, the assessment requires comparing the levels of host-derived CDNs (2'3'-cGAMP) and microbial-derived CDNs (3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, c-di-GMP) with data from healthy controls. An elevated trend in host-derived 2'3'-cGAMP suggests excessive cGAS activity, while the abnormal presence of specific microbial CDNs may indicate involvement in dysbiosis.

[0135] In this disclosure, the determination is made based on a comparison of (A) the amount or level of 2'3'-cGAMP with (B) the total amount of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP. More specifically, the determination is made by individually comparing (A) the amount or level of 2'3'-cGAMP with (B) one or a combination thereof of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP. Given the complexity and scale differences of CDN concentrations, the determination may need to compare the levels of host-derived CDN (2'3'-cGAMP) with those of microbial CDN (3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, c-di-GMP) with data from healthy controls. The elevated trend in host-derived 2'3'-cGAMP suggests excessive activity of cGAS, while the abnormal presence of specific microbial CDNs may be involved in dysbiosis.

[0136] The following are non-exclusive and illustrative criteria for determining the outcome. Those skilled in the art will understand that these criteria are merely examples and can be modified and updated as appropriate on an individual basis.

[0137] Calculation of Biomarkers Based on Common CDNs 1. Host-derived CDN (2'3'-cGAMP): Elevated levels suggest increased cGAS activity and indicate host immune abnormalities. 2. Microbial-derived CDN (3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, c-di-GMP): Elevated levels suggest microbial imbalance and contribute to systemic inflammation or disease-specific immune responses.

[0138] Exemplary Determination of Disease-Specific CDNs 1. SLE (Systemic Lupus Erythematosus) Key Biomarkers: Significant and Strong Correlation: c-di-AMP and hPBMC Type I IFN Score c-di-GMP and hPBMC Type I IFN Score - Calculation Formula: SLE Activity Index = ([c-di-AMP] + [c-di-GMP]) × PBMC Type I IFN Score - Interpretation: Elevated c-di-AMP and c-di-GMP levels are strongly correlated with Type I IFN activity in PBMCs, indicating overactivation of the STING pathway due to disruption of the microbiome in SLE and exacerbation of the disease.

[0139] 2. COPD (Chronic Obstructive Pulmonary Disease) • Key biomarkers: • Host-derived 2'3'-cGAMP: Correlated with RANTES, MIP-1β, and IL-9. • Bacterial-derived 3'3'-cGAMP: Correlated with eotaxin, RANTES, MIP-1β, and IL-9. • Formula: • COPD biomarker index = ([2'3'-cGAMP] + [3'3'-cGAMP]) × (RANTES + MIP-1β + IL-9) • Interpretation: The combination of host-derived and bacterial-derived CDN levels and inflammatory cytokines suggests activation of the STING pathway in COPD.

[0140] 3. Asthma - Key Biomarkers: • Weak but significant correlations: • 3'3'-cGAMP and serum neutrophil percentage • 3'3'-cGAMP and serum IL-1RA • Formula: • Asthma biomarker index = [3'3'-cGAMP] × (neutrophil percentage + IL-1RA) • Interpretation: Elevated 3'3'-cGAMP levels, which are weakly correlated with neutrophil percentage and IL-1RA, suggest the role of bacterial-derived CDNs in asthma pathology according to STING.

[0141] 4. SAVI (STING-associated vascular disease, childhood onset) - Main biomarkers: Elevated serum levels of 2'3'-cGAMP, c-di-AMP, and c-di-GMP. In one SAVI patient, 2'3'-cGAMP decreased with steroid treatment. Calculation formula: SAVI activity index = [2'3'-cGAMP] + [c-di-AMP] + [c-di-GMP] Interpretation: Elevated levels indicate hyperactivation of STING, and a decrease after steroid treatment suggests a response to treatment. General formula for measuring CDN biomarkers CDN biomarker index = Σ (host-derived CDN) + Σ (microbial-derived CDN) × disease-specific cytokine or severity score. Alternatively, an exemplary formula is a general formula based on applicable CDNs to integrate the diagnosis of various symptoms: General CDN Diagnostic Index = (((Σ(host-derived CDNs) + Σ(microbial-derived CDNs))) / median of healthy control group) × (disease-specific cytokines + severity biomarkers) This formula allows for normalization to a healthy control group and can be adapted to disease-specific cytokines and biomarkers to broadly address a variety of symptoms.

[0142] In one embodiment, CDN is measured or obtained in the subject's body fluid. In this invention, body fluid includes, but is not limited to, blood, serum, plasma, urine, saliva, cerebrospinal fluid, tears, sweat, amniotic fluid, or tissue extracts. These body fluids can be collected by non-invasive or minimally invasive methods and are important sources of information for assessing the subject's physical condition. Accurate measurement of the presence and level of CDN provides important clues for identifying the subject's pathological or physiological state. Several highly sensitive analytical techniques are used to measure or obtain information on CDN. For example, liquid chromatography-mass spectrometry (LC-MS) is a suitable method for precisely identifying the type and concentration of CDN. Furthermore, by using antibodies with high specificity for specific CDNs, rapid and efficient measurement is possible by enzyme-linked immunosorbent assay (ELISA). In addition, molecular diagnostic methods using nucleic acid probes and highly sensitive sensor technologies utilizing fluorescent labeling or chemiluminescence are also applicable to CDN detection. These technologies allow for the direct detection and quantification of CDN in the target body fluid. The method of the present invention evaluates pathological conditions such as immune responses, infections, inflammation, tumorigenesis, or metabolic disorders by determining the extent of CDN present in body fluid. For example, abnormally high CDN concentrations suggest the possibility of progressing inflammatory diseases or infections. On the other hand, decreased CDN levels may reflect specific immunodeficiencies or metabolic disorders. Thus, measuring or obtaining information on CDN in body fluids is useful for early disease detection, monitoring progression, and evaluating treatment effectiveness, and is expected to have widespread application as a non-invasive diagnostic method.

[0143] In one embodiment, body fluids may be serum, plasma, sweat, urine, intestinal extracts, or feces. Body fluids refer to various biological samples obtained from the body of a subject, and include, but are not limited to, serum, plasma, sweat, urine, intestinal extracts, or feces. These body fluids are important analytes that provide different physiological and pathological information and are used to assess the physical condition of a subject. Serum and plasma are samples obtained from blood and contain information reflecting metabolites and signaling molecules throughout the body via the circulatory system. Serum is the liquid component of blood from which blood cells and clotting factors have been removed and contains enzymes, hormones, antibodies, nutrients, and metabolites. Plasma is the liquid component of blood and, compared to serum, contains clotting factors, making it useful for analyzing a variety of physical conditions, including clotting and inflammatory responses. Sweat and urine are body fluids that can be collected non-invasively or minimally invasively and each contains different metabolites. Sweat is a liquid secreted mainly from the skin surface and is involved in thermoregulation and electrolyte excretion. Furthermore, sweat contains specific small molecule metabolites and hormones, allowing for the assessment of a subject's metabolic state and stress level by measuring these components. Urine, on the other hand, is produced in the kidneys and plays a role in eliminating waste products and unnecessary metabolites from the body. Components in urine are important indicators of kidney function, metabolic abnormalities, and the presence or absence of infections. Intestinal extracts and feces are samples obtained from the digestive system and reflect the state of the intestinal environment and microbiota (gut flora). Intestinal extracts refer to the liquid components present in the intestinal tract and include digestive enzymes, mucus, and intestinal metabolites. Feces, on the other hand, are important samples that show the metabolic activity of intestinal microorganisms and the state of digestive function, and are useful for evaluating specific pathological conditions (e.g., enteritis, dyspepsia, abnormalities in the gut microbiota). By targeting these bodily fluids, it is possible to diagnose systemic or local pathological conditions, monitor their progression, and even evaluate the effectiveness of treatment. This disclosure demonstrates that by analyzing specific molecules and metabolites in these bodily fluids, it is possible to obtain information on a wide range of diseases and physical conditions quickly and accurately.

[0144] In one embodiment of this disclosure, diagnosis involves identifying significant deviations indicating dysbiosis, leaky gut, and increased cGAS-STING pathway activity. These biological conditions are important indicators associated with the onset and progression of various chronic, inflammatory, and autoimmune diseases. Dysbiosis refers to an abnormality in the composition and balance of the gut microbiota (gut flora). This abnormality can manifest as a decrease in certain beneficial bacteria or an overgrowth of harmful bacteria. Dysbiosis is closely associated with diseases such as dyspepsia, inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), and metabolic syndrome. Diagnosis involves fecal examination to assess the composition and diversity of gut bacteria, as well as molecular biological techniques such as 16S rRNA sequencing. Leaky gut refers to a condition in which the intestinal barrier function is impaired and the intestinal wall is excessively permeable. In this condition, undigested food components, harmful substances, and toxins from gut bacteria (such as lipopolysaccharide (LPS)) leak into the bloodstream, potentially triggering systemic inflammation and immune responses. Leaky gut is associated with autoimmune diseases, allergies, chronic inflammation, and even neurological disorders. Diagnosis is aided by measuring blood levels of intestinal permeability markers (e.g., zonulin and LPS-binding protein). Increased GAS-STING pathway activity is a key molecular mechanism indicating abnormal activation of innate immunity. This pathway recognizes abnormal DNA within cells (e.g., damaged DNA, bacterial and viral DNA) and plays a role in inducing interferons and other inflammatory cytokines. Abnormal activation of the cGAS-STING pathway is involved in autoimmune diseases (e.g., systemic lupus erythematosus (SLE), STING-associated vasculitis (SAVI)), inflammatory diseases, and even cancer immune responses. Diagnosis involves measuring levels of interferon and inflammatory cytokines in the blood and bodily fluids, as well as analyzing gene mutations in cGAS and STING. The diagnostic method of the present invention identifies these conditions and contributes to the early detection and monitoring of progression of various diseases, as well as the evaluation of treatment effectiveness. This makes it possible to provide useful information for formulating treatment strategies appropriate for each patient.

[0145] The measurements described herein may be any measurement method known in the art. The measurements are performed by an enzyme-linked immunosorbent assay (ELISA) assay. ELISA is a method for detecting specific molecules with high sensitivity and specificity, utilizing antigen-antibody reactions. For example, in the measurement of CDN (cyclic dinucleotide), an antibody that specifically binds to CDN can be used to rapidly assess the presence or concentration of CDN in body fluids. ELISA is widely used in many fields and is characterized by its simplicity and high reproducibility. In addition to ELISA, other methods for measuring CDN and other molecules are also available. For example, liquid chromatography-mass spectrometry (LC-MS) is an analytical method with very high sensitivity and specificity, and can accurately identify the structure and concentration of small molecules such as CDN. This method is widely used for the quantitative analysis of target molecules in complex body fluid samples. Furthermore, probe techniques using fluorescence resonance energy transfer (FRET) and real-time intermolecular interaction analysis utilizing surface plasmon resonance (SPR) can also be applied to CDN detection. FRET is a technique that visualizes molecular binding and changes using fluorescent dyes and is suitable for evaluating dynamic molecular behavior. On the other hand, SPR can analyze molecular interactions without labeling, enabling direct detection of biomolecules. By combining these techniques, it becomes possible to measure molecules with high accuracy and reliability even in cases where ELISA alone is difficult. The aim of this invention is to accurately evaluate the physiological or pathological state of a target by selectively applying measurement methods.

[0146] The determination in this disclosure is made by comparing the measured values ​​obtained from the subject with control data from healthy individuals or with a pre-defined control threshold for healthy individuals. This method makes it possible to determine whether the levels of specific molecules or biomarkers in the subject's body fluids or tissues are within the normal range or indicate an abnormal state. The control data for healthy individuals is constructed based on measurement results obtained from a statistically sufficient number of healthy individuals. This data includes the mean and standard deviation of the molecule or biomarker being measured, and defines the normal range. For example, when determining the level of cyclic dinucleotides (CDNs), a reference value for CDNs in healthy individuals is set in advance, and it is evaluated whether the subject's measured value falls within that range. On the other hand, the pre-defined threshold is determined based on healthy data, but may be adjusted based on clinical experience or diagnostic criteria for specific diseases. This threshold is set to optimize the sensitivity and specificity for detecting specific diseases or abnormalities. For example, if CDN levels exceed the control threshold for healthy individuals, it may be determined to suggest inflammation or hyperactivation of the immune response. This comparison makes it possible to determine whether the subject is in a healthy state or in a diseased or abnormal physiological state. This invention provides useful information for early disease detection, monitoring of disease progression, or evaluation of treatment effectiveness through such comparisons. Furthermore, this method contributes to the development of treatment plans in personalized medicine.

[0147] In one embodiment, as described herein, a subject is determined to have a significantly altered level of a specific molecule or biomarker compared to a healthy control, as calculated by a determination formula described elsewhere in this specification. This significant alteration is classified as upregulation or downregulation and serves as an important indicator for evaluating the pathological or physiological state of the subject. Upregulation refers to a significantly higher level in the subject than the baseline or threshold in a healthy individual, which may suggest an abnormal condition such as inflammation, hyperactivation of the immune response, infection, or tumorigenesis. For example, upregulation of cyclic dinucleotide (CDN) levels may be due to activation of the innate immune pathway (cGAS-STING pathway), suggesting the presence of an inflammatory or autoimmune disease. Downregulation, on the other hand, refers to a significantly lower level in the subject than the baseline or threshold in a healthy individual, which may indicate immunosuppression, metabolic disorder, or decreased biological activity due to a specific pathological process. For example, if CDN levels are downregulated, it may be associated with suppression of cellular signaling or a weakened immune system. This invention enables highly accurate assessment of disease risk, progression, and treatment effectiveness by detecting such significant upregulation or downregulation. This assessment is extremely useful in early disease detection, personalized treatment planning, and disease monitoring.

[0148] In one embodiment, a high level of a particular CDN or its diagnostic formula may reflect an abnormality in the patient's body, particularly the gut microbiome. Such a condition suggests an imbalance in the gut microbiota, i.e., dysbiosis, and may require interventions such as antibiotics or probiotics to normalize the microbiome. Antibiotics are used to suppress pathogenic bacteria or certain bacteria that have overgrowthed. Such interventions can suppress excessive pro-inflammatory effects and toxin production in the gut microbiota, allowing for the reconstruction of a healthy microbiome environment. However, the use of antibiotics requires caution, as beneficial bacteria may also be affected, necessitating appropriate selection and administration planning. Probiotics, on the other hand, are used as a means of supplementing beneficial bacteria to restore balance to the gut environment. This can increase gut diversity and promote a healthy state. In particular, probiotics including Bifidobacteria and Lactobacillus are known to strengthen the gut barrier function and contribute to improved intestinal permeability and reduced inflammation. Furthermore, in some cases, the intake of prebiotics (nutrients that promote the growth of beneficial bacteria) and dietary therapy may be recommended in parallel with these interventions. This can more efficiently promote the normalization of the gut environment. In this disclosure, when high levels of biomarkers are confirmed, the aim is to normalize the patient's gut environment by appropriately selecting and implementing these interventions. This approach improves the balance of the gut microbiome and contributes to improved systemic health.

[0149] In one embodiment of the present invention, an increase in the level of 2'3'-cGAMP (cyclo GMP-AMP) indicates enhanced activity of the cGAS (cyclo GMP-AMP synthase) enzyme. cGAS is activated when abnormal DNA is present in cells and produces 2'3'-cGAMP. This molecule activates the STING (stimulator of interferon genes) pathway, inducing the production of interferons and inflammatory cytokines. Therefore, an increase in 2'3'-cGAMP levels is an important indicator of abnormal activation of the cGAS-STING pathway and is deeply involved in the pathogenesis of innate immune responses, inflammatory diseases, and autoimmune diseases. When enhanced cGAS activity is confirmed, it is highly likely that an abnormal inflammatory response is contributing to disease progression. In such cases, administration of targeted drugs that directly inhibit cGAS is an effective treatment method. cGAS inhibitors suppress the production of cGAMP and play a role in controlling excessive inflammatory responses via the STING pathway. This suppresses the production of inflammatory cytokines, which is expected to inhibit disease progression and alleviate symptoms. Specifically, diseases in which the use of cGAS inhibitors may be considered include systemic lupus erythematosus (SLE), STING-associated vasculitis (SAVI), autoinflammatory diseases, and cancer-immune conditions. In these diseases, abnormal activation of the cGAS-STING pathway is known to be underlying the pathogenesis, and there is a high possibility that therapeutic effects can be obtained by appropriately administering cGAS inhibitors. In the diagnostic and treatment protocols disclosed herein, measuring 2'3'-cGAMP levels is an important step in evaluating the state of cGAS activation and formulating appropriate treatment strategies. This approach enables personalized treatment tailored to each patient's condition, allowing for effective management of inflammatory and autoimmune diseases.

[0150] In one aspect, the present disclosure provides a companion diagnostic technology. The present disclosure provides a method for treating or preventing a physical condition of a subject, comprising: 1) determining the physical condition of the subject by the method of claim 1; and 2) achieving treatment or prevention by taking appropriate measures for the subject in accordance with the determination result.

[0151] In this disclosure, treatment or prevention can be achieved by implementing appropriate measures for the subject based on the assessment results. This approach aims to suppress or prevent disease progression by constructing an individualized treatment strategy based on diagnostic data and measurement results obtained from the subject. For example, if the CDN or assessment levels are abnormal, an appropriate treatment method will be selected based on the type and degree of the abnormality. If inflammatory or autoimmune diseases are suspected, immunosuppressants, anti-inflammatory drugs, or biological agents may be used. Furthermore, if the subject's goal is prevention, vaccination, lifestyle modifications, and the use of nutritional supplements may be applied. In particular, if molecules such as 2'3'-cGAMP show abnormally high levels, cGAS inhibitors and targeted drugs that regulate the STING pathway play an important role in treatment. Also, if an abnormality in the gut microbiota is identified, the administration of probiotics or prebiotics, or dietary therapy, may be selected as measures to promote the normalization of the gut environment. These measures are individually adjusted based on the patient's condition and diagnostic results. For example, for chronic diseases, it is necessary to develop a long-term management plan while monitoring disease progression. On the other hand, prompt and appropriate intervention is crucial for acute inflammation and infection. The process described in this disclosure provides effective medical care by directly linking diagnostic results with appropriate treatments or preventive measures. This reduces the burden on patients and improves the prognosis of the disease. Furthermore, preventive measures can reduce the risk of developing the disease and aim to maintain and improve health status.

[0152] In another aspect, the Disclosure provides a detection or determination agent for a subject's physical condition, comprising a detection agent for measuring cyclic dinucleotides (CDNs), wherein it is determined whether the CDNs originate from and / or from microorganisms (parasites) expected to be present in the subject, and based on the result of the determination, a STING-related disease or condition is diagnosed.

[0153] Any detection agent in the art may be used for measuring cyclic dinucleotides (CDNs) in this disclosure. Detectors for measuring CDNs are important tools that enable the specific detection and quantification of CDNs. Detectors are designed to accurately and efficiently assess the presence or level of CDNs and are advantageous in elucidating physiological or pathological processes in which CDNs are involved.

[0154] Detection agents can be composed of various forms, including, but are not limited to, the following examples: 1. Antibody-based detection agents: Detection agents utilizing antibodies that specifically bind to CDN can be applied to enzyme-linked immunosorbent assay (ELISA) and fluorescence immunoassay. Monoclonal and polyclonal antibodies have high specificity and sensitivity, enabling precise quantification of CDN. Furthermore, antibodies can be labeled with enzymes, fluorescent dyes, chemiluminescent substances, or nanoparticles to amplify the measurement signal. 2. Nucleic acid-based detection agents: Nucleic acid aptamers are short-chain nucleic acid molecules designed to specifically bind to CDN and have high binding affinity. These are used for CDN detection by being incorporated into fluorescent probes or electrochemical sensors. Fluorescently labeled nucleic acid probes, such as molecular beacons, have a mechanism to undergo structural changes in the presence of CDN and emit a fluorescent signal. 3. Chemical probes: Chemical probes utilizing small molecule compounds that specifically interact with CDN are also useful as detection agents. These probes can detect CDN through changes in fluorescence, chemiluminescence, or absorption spectra. Chemical probes are also used as tools to observe intracellular CDN dynamics in real time. 4. Enzyme-based detectors Detection systems using enzymes (e.g., cGAS and related enzymes) that recognize CDN as a substrate and perform chemical transformations are also conceivable. By detecting the products produced by the enzymatic reaction, the presence and concentration of CDN can be indirectly evaluated. 5. Nanomaterial-based detectors Detectors using nanomaterials such as gold nanoparticles, quantum dots, or nanotubes have signal amplification effects and specific detection capabilities, making them suitable for highly sensitive CDN detection. These materials use their physical and chemical properties to visually or electrochemically indicate the presence of CDN. 6. Electrochemical detectors Sensors that utilize the electrochemical response property of CDN are also used as detectors. These sensors work by immobilizing CDN-specific binding molecules on the electrode surface to measure changes in current or voltage. These detectors have the potential for a wide range of applications in CDN research and diagnosis. For example, measuring CDN levels can enable the diagnosis and monitoring of inflammatory diseases, autoimmune diseases, infectious diseases, and even cancer.Furthermore, it contributes to drug discovery research targeting CDNs. This disclosure describes how to achieve highly accurate and efficient CDN measurement by selecting the appropriate detection agent from among these diverse agents according to the purpose.

[0155] In one embodiment, CDN is measured to determine whether it originates from the subject or from microorganisms (parasites) expected to be present in the subject. This determination uses a detection agent that enables the specific detection of CDN. The detection agent has the ability to distinguish between different types of CDN and their origins, and contains specific molecules for distinguishing between CDN from the subject and CDN from microorganisms (parasites). Specifically, the following detection agents and techniques are used. By combining the above-described detection agents and techniques, it is possible to determine with high accuracy whether CDN originates from the subject or from microorganisms. This determination is important in the diagnosis and treatment of infectious diseases, autoimmune diseases, inflammatory diseases, etc., and provides valuable information for clarifying the pathogenesis and etiology of the subject. This approach is also useful in the early detection of microbial diseases and the selection of appropriate treatments.

[0156] In one aspect, the present disclosure provides a device for detecting or determining the physical condition of a subject, comprising an element for measuring cyclic dinucleotides (CDNs) and a determination element for determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject, wherein a STING-related disease or condition is diagnosed based on the result of the determination.

[0157] The disclosure also provides a kit for detecting or determining a physical condition of a subject, comprising a detection agent or element for measuring cyclic dinucleotides (CDNs), and instructions, wherein the instructions explain that it is determined whether the CDNs originate from and / or from microorganisms (parasites) expected to be present in the subject, and that a STING-related disease or condition is diagnosed based on the result of the determination.

[0158] In one embodiment, a device for measuring CDN refers to a device or component designed to detect the presence or concentration of CDN with high sensitivity and accuracy. This device is an important tool for elucidating biological processes and disease mechanisms involving CDN and has a wide range of applications in diagnosis, monitoring of therapeutic effects, and drug discovery research. Devices for measuring CDN can be composed of various forms, including the following examples: 1. Biosensor-type devices Biosensor-type devices immobilize specific molecular recognition elements for detecting CDN on electrodes or surfaces and convert the detection result into a signal. The following types are examples: ・Electrochemical sensors: Specific molecules that interact with CDN are immobilized on electrodes and changes in current or voltage are detected. This makes it possible to rapidly measure the presence or concentration of CDN. ・Optical sensors: These are devices whose fluorescence or absorbance changes in response to the binding of CDN, and real-time measurement is possible. 2. Immunosensor-type devices This device has a structure that utilizes antibodies or aptamers that specifically recognize CDN. This includes: • ELISA (Enzyme-Linked Immunoadsorption) plates: Uses antibody-immobilized wells to detect the presence of CDN by enzymatic reaction. • Lateral flow devices: Portable detection elements that specifically recognize CDN as the sample flows, allowing for visual or mechanical reading. 3. Mass spectrometry-based elements: Sample preparation elements for use with mass spectrometry (LC-MS) facilitate the concentration, separation, and detection of CDN. These elements are highly sensitive and can identify and accurately quantify different types of CDN (e.g., 2'3'-cGAMP, c-di-GMP, etc.). 4. Microfluidics-based elements: Elements with microfluidic channels are designed to measure CDN using small sample volumes. This enables real-time measurement and rapid diagnosis. This type of element incorporates a detection probe (antibody, aptamer, etc.) that generates a signal when CDN is present. 5. Nanotechnology-based elements: Elements utilizing nanoparticles (e.g., gold nanoparticles, quantum dots) exhibit changes in color or fluorescence when CDN is present. Such elements enable simple and highly sensitive measurements, and are also easy to visually confirm.6. Versatile Portable Devices: Portable measurement devices for use at the patient's bedside or in the field have also been devised. These utilize lab-on-a-chip technology that enables CDN detection with simple operation. Using these devices, accurate measurement of CDN becomes possible, enabling diagnosis and monitoring related to diseases such as inflammatory diseases, infections, autoimmune diseases, and cancer. Furthermore, these devices are widely used in research as important tools for analyzing the function and role of CDN.

[0159] In one embodiment, the determination element is a device or component designed to accurately identify and determine the origin of molecules or substances originating from or expected to be contained within a target by microorganisms (parasites). This determination element is critical in disease diagnosis, formulation of treatment strategies, and evaluation of the physiological or pathological state of the target. In one embodiment, the determination element includes, but is not limited to, a variety of components, including: 1. Specific Recognition Molecules: The determination element includes antibodies, aptamers, or chemical probes that specifically recognize molecules originating from the target or microorganisms (e.g., cyclic dinucleotides (CDNs)). These recognition molecules have the ability to distinguish subtle structural differences in CDNs and other biomarkers, providing a basis for clearly determining their origin. 2. Molecular Recognition Sensors: By incorporating electrochemical sensors, optical sensors (e.g., fluorescence sensors, surface plasmon resonance (SPR) sensors), molecular recognition events are converted into visible or electronic signals to distinguish between target and microorganism-derived molecules. 3. The mass spectrometry-based determination element includes a sample preparation module for using mass spectrometry (LC-MS / MS) to analyze the chemical structure and mass properties of specific molecules in the sample. This makes it possible to accurately distinguish between molecules originating from the target (e.g., 2'3'-cGAMP) and molecules originating from microorganisms (e.g., c-di-GMP, c-di-AMP). 4. Gene analysis module: By incorporating PCR or next-generation sequencing (NGS) technology to detect genes originating from the target or microorganisms, the source of microbial molecules can be clearly identified. This makes it possible to determine if a specific pathogen is involved. 5. Multi-purpose chip technology: Elements utilizing lab-on-a-chip or microfluidics technology enable rapid determination with small sample sizes. These elements are equipped with microfluidic channels with immobilized antibodies or probes, allowing for real-time determination of substances originating from the target or microorganisms. 6. Data processing and determination algorithm: The determination element may include a software module for processing and analyzing measurement results. This provides an automated process for rapidly determining whether a substance originates from the target organism or from microorganisms.This detection element can be used in a variety of fields, including: • Diagnosis of infectious diseases: Clarifying the presence or absence of infection and its etiology by identifying molecules derived from pathogenic microorganisms. • Evaluation of autoimmune diseases: Evaluating the mechanisms of autoimmunity by distinguishing between the subject's own molecules and exogenous molecules. • Treatment monitoring: Tracking molecular-level changes in the subject after treatment to determine the effectiveness of treatment. The detection element of this disclosure combines high sensitivity, high specificity, and speed, enabling non-invasive or minimally invasive identification of molecules derived from the subject and microorganisms. This is expected to enable early detection of diseases, monitoring of disease progression, optimization of treatment strategies, and improvement of the quality of patient care.

[0160] In one embodiment, instructions that may be included in the kit of this disclosure may allow for the determination of whether the CDN originates from the subject or from microorganisms (parasites) expected to be present in the subject. This determination is an important step in evaluating the physiological or pathological state of the subject based on the presence and concentration of the CDN. CDN originating from the subject reflects the subject's own biological processes, such as innate immune responses, inflammatory responses, or metabolic functions. On the other hand, CDN originating from microorganisms (parasites) suggests infections or pathological conditions involving pathogenic microorganisms or parasites present in the subject. Determining these origins allows for a more detailed analysis of the subject's condition.

[0161] Specifically, the determination is made using the following methods: Specific molecular identification: Highly sensitive analytical techniques (e.g., mass spectrometry (LC-MS), nucleic acid aptamers, antibody probes) are used to distinguish between molecules derived from the target organism (e.g., 2'3'-cGAMP) and molecules derived from microorganisms (e.g., c-di-GMP and c-di-AMP). Genetic analysis: PCR or next-generation sequencing (NGS) is used to identify the origin of the marker based on the genetic characteristics of the target organism or microorganism. Analysis of biological function: The function and expression pattern of the marker are evaluated to estimate its origin. Based on the results of this determination, STING-related diseases or conditions are diagnosed. For example, if the marker derived from the target organism is abnormally high, an inflammatory disease, autoimmune disease, or tumorigenesis is suspected. On the other hand, if a marker derived from a microorganism is detected, a bacterial infection, viral infection, or parasitic infection may be diagnosed. In this invention, the linked determination and diagnosis are expected to have the following applications: Early detection of STING-related diseases or conditions: Based on the detection of abnormal markers in the subject, it becomes possible to diagnose STING-related diseases or conditions at an early stage. Optimization of treatment strategies: It becomes easier to select treatment methods (e.g., antibiotics, anti-inflammatory drugs, immunomodulators) according to the cause of the subject's STING-related disease or condition. Preventive intervention: If the subject is at risk of disease, preventive measures for STING-related diseases or conditions (e.g., vaccination, lifestyle modifications) can be proposed. Thus, the method described in this disclosure comprehensively describes the process of determining the origin of markers in a subject and diagnosing related diseases or conditions based on that, and is expected to have a wide range of applications in the medical and research fields.

[0162] (Systems and Programs) This disclosure relates to methods, systems, programs, associated recording media, etc., for detecting, determining, or assisting in the diagnosis of a subject's physical condition using the technology described herein, and to markers used therein. More specifically, it relates to a technology for diagnosing STING-related diseases and identifying their causes (autologous or microbial) by analyzing the types and levels of cyclic dinucleotides (CDNs). In this disclosure, we have found that by individually measuring multiple CDN levels in a sample (such as serum) taken from a subject and analyzing the resulting profile, it is possible to accurately determine the type and state of the disease, as well as its pathological background (aseptic inflammation or microbial infection / leakage). Furthermore, we have found that by applying these multiple CDN measurements as input features to a machine learning algorithm (such as SVM), it becomes possible to differentiate between asthma and COPD, which was difficult with conventional single markers.

[0163] Examples of diagnostic and judgment logic are provided below, but are not limited to these. Determination of origin: If a high proportion of "2'3'-cGAMP" is detected in the sample, it is determined that the main cause of the pathology is abnormal activation of the host cGAS pathway (aseptic inflammation). On the other hand, if microbial-derived CDN (e.g., c-di-AMP) is predominantly detected, involvement of microbial factors (e.g., leaky gut) is suspected. Decision on intervention: If microbial-derived CDN is high, decision support is provided to recommend microbiome normalization treatment with antibiotics or probiotics in addition to conventional anti-inflammatory drugs. Differential diagnosis: Asthma and COPD have similar symptoms, but the method disclosed herein can be used to identify differences in the CDN profiles of the two conditions (e.g., combinations of ratios and absolute values ​​of 2'3'-cGAMP and c-di-AMP) and differentiate between them.

[0164] System and Machine Learning Application: The system of this disclosure comprises an input unit, a determination unit (processor), and an output unit. Machine Learning Model: A classification model is constructed using algorithms such as a support vector machine (SVM) with multiple CDN measurement values ​​obtained in advance from patients with each disease (asthma, COPD, healthy individuals, etc.) as training data. Features: As input features, a combination of serum concentration of each CDN, total value, ratio between specific CDNs, and clinical parameters such as the patient's age and sex can be used. The CDN measurement method (ELISA or LC-MS / MS) is a known technique and can be implemented by those skilled in the art according to the above description.

[0165] In one embodiment, serum samples are collected from target patients (e.g., asthma patients) and healthy controls, and the concentrations of 2'3'-cGAMP and c-di-AMP are measured using ELISA with specific antibodies. If the 2'3'-cGAMP levels are significantly higher in the asthma patient group compared to the healthy control group, this suggests activation of the cGAS-STING pathway. As an example, using serum CDN datasets from asthma patients and COPD patients, a classifier using SVM was created, and 2'3'-cGAMP, 3'3'-cGAMP, and c-di-AMP were used as input features. This allowed for higher accuracy (e.g., AUC 0.90 or higher) in distinguishing between the two groups than using a single marker. As another non-limiting example, in subjects suspected of having certain inflammatory bowel diseases, if serum c-di-GMP and c-di-AMP are detected above a threshold, it can be determined that the intestinal wall barrier function is impaired and that CDN derived from intestinal bacteria is leaking into the systemic circulation (leaky gut), and the need for probiotic administration can be suggested.

[0166] (Target Physical Condition Assessment System) In one embodiment, the system of this disclosure is physically implemented by a computer configuration having a CPU (Central Processing Unit), memory, storage, input interface, and output interface, or by a server configuration on the cloud. The system has the following configuration as a functional block.

[0167] (1) Acquisition Unit (Data Acquisition Interface) The acquisition unit acquires concentration data of cyclic dinucleotides (CDNs) measured in samples (serum, urine, fecal extract, etc.) collected from a subject, or information associated with said measurement values, from an external device (e.g., ELISA reader, mass spectrometer) or user input.

[0168] Types of data to be acquired: At least the level of "2'3'-cGAMP" is included, preferably the level of one or more microbial-derived CDNs selected from "3'3'-cGAMP", "3'2'-cGAMP", "c-di-AMP", and "c-di-GMP". Supplementary data: If necessary, metadata such as the age, sex, BMI, smoking history, and clinical symptoms (cough, wheezing, etc.) of the subject is also acquired.

[0169] (2) Determination Unit (Calculation Processing Engine) The determination unit is the core part of this system and performs the following calculations according to the program loaded into memory.

[0170] (2-1) Origin determination logic: The acquired CDN profile is analyzed to calculate the contribution rates of host-derived components (2'3'-cGAMP) and microbial-derived components (e.g., c-di-AMP). For example, if the concentration of 2'3'-cGAMP exceeds a predetermined threshold, it is determined to be "activation of the cGAS-STING pathway (aseptic inflammation)," and if the microbial-derived CDN exceeds the threshold, it is determined to be "dysbiosis or leaky gut."

[0171] (2-2) Identification / Discrimination Logic (Machine Learning Model): Multiple CDN concentrations obtained in the acquisition unit are used as "input feature vectors" and input into a pre-built, trained classification model (e.g., Support Vector Machine (SVM), Random Forest, etc.).

[0172] Example of features: $[x_1: 2'3'-cGAMP, x_2: c-di-AMP, x_3: (x_1 / x_2 \text{ ratio})]$ Output: Calculates the probability of having asthma, the probability of having COPD, or the result of differentiating between the two as a numerical value (score).

[0173] (2-3) Therapeutic intervention suggestion logic: Based on the determined disease background, identify the necessary intervention measures. For example, if microbial CDN is high, flag "microbiome normalization (probiotic administration, etc.)" and if only 2'3'-cGAMP is high, flag "STING inhibitor or anti-inflammatory drug" to recommend.

[0174] (3) Output Unit (Diagnostic Support Information Provision Interface) The output unit displays the calculation results from the judgment unit on a display device (display) in a format that can be viewed by doctors and medical technologists, or transmits them to an external electronic medical record system, etc.

[0175] Display contents: Includes graphs of measured values ​​for each CDN, disease identification results (e.g., "Possible asthma: 92%"), origin determination results (e.g., "Suspected inflammation due to microbial factors"), and advice on recommended treatment strategies.

[0176] (Diagnostic Support Program) The program of this disclosure is a set of instructions for causing a computer to function as the above-mentioned parts. Its main processing flow (algorithm) consists of the following steps: Step S1 (Data Input): Reads multiple types of CDN concentration data in serum via a network or local bus. Step S2 (Preprocessing): Normalizes (scales) the input concentration data into a format suitable for the classification model and calculates the ratio between specific components (e.g., 2'3'-cGAMP / c-di-AMP) as needed. Step S3 (Origin / State Determination): Condition A: 2'3'-cGAMP > Threshold T1 ⇒ Defined as "Increased Host cGAS Activity". Condition B: Microbial-derived CDN > Threshold T2 ⇒ Defined as "Barrier Dysfunction or Microbial Abnormality". Step S4 (Classification Execution): Inputs the results of S2 and S3 into the trained SVM model and calculates which class the subject belongs to: "Healthy", "Asthma", "COPD", or "Autoimmune Disease". Step S5 (Result Output): The calculated class and disease background information are visualized and output on the user interface.

[0177] (Building and Validating Machine Learning Models) The classification models used in this program are trained using, for example, the following procedure: 1. Serum samples are collected from a group of confirmed asthma patients, a group of COPD patients, and a group of healthy controls. 2. Multiple types of CDNs (2'3'-cGAMP, c-di-AMP, etc.) are measured for each sample. 3. Using the obtained multidimensional data as training data, the hyperplane (decision boundary) that most efficiently separates each group is determined using SVM or similar methods with kernel techniques. 4. Cross-validation is performed to confirm that the discrimination accuracy (sensitivity, specificity) for unknown data is sufficient. In this way, by combining multiple types of CDNs and analyzing them multidimensionally, "differentiation between asthma and COPD" and "separation of sterile inflammation and microbial-derived inflammation," which were difficult to achieve with a single marker due to significant overlap, can be realized with statistically significant accuracy.

[0178] In this specification, "or" is used when "at least one" of the items listed in the text can be adopted. The same applies to "or else". In this specification, when it is specified that "within the range" of "two values", that range includes the two values ​​themselves.

[0179] References such as scientific literature, patents, and patent applications cited herein are incorporated herein by reference to the same extent as they are specifically described herein.

[0180] The present disclosure has been described above with reference to preferred embodiments for ease of understanding. The present disclosure will now be described based on examples, but the above description and the following examples are provided for illustrative purposes only and not to limit the present disclosure. Accordingly, the scope of the present disclosure is not limited to the embodiments or examples specifically described herein, but is limited only by the claims.

[0181] This embodiment demonstrates that various CDNs can be used as markers for STING-related diseases or conditions, and that treatment based on them is possible. The animal protocol used in this embodiment has been approved by the Infectious Disease Animal Resource Center of Osaka University, the Faculty of Medicine of Osaka University, and the Animal Experiment Facility of the Institute of Medical Science, University of Tokyo. The procedure mainly followed the steps outlined below.

[0182] (Materials and Methods)

[0183] (Patient Samples) Two SAVI patients with the STING N154S mutation were included in the study, along with one SAVI patient with the STING V155M mutation. All SAVI patients were children, and after obtaining informed consent from their parents, samples were collected at Hacettepe University in Turkey (two patients with the N154S mutation) and Hiroshima University Hospital in Japan (one patient with the V155M mutation). One SAVI patient in Turkey was receiving treatment with a Jak1 / 2 inhibitor (baricitinib), and the patient in Japan was receiving treatment with steroids. The protocol for this study was approved by the Institutional Review Board of Hacettepe University and Hiroshima University Hospital.

[0184] Serum and plasma samples from healthy donors were obtained after obtaining informed consent at Hacettepe University Hospital. Additional healthy control plasma samples were purchased from Cellular Technology Limited (CTL, USA). Healthy control urine samples (from non-drug users, HIV, HBV, HCV, HTLV, and syphilis-negative donors aged 29–33) were purchased from BioIVT, Inc. (USA).

[0185] Serum samples from patients with connective tissue disease were obtained from a blood bank stock after obtaining comprehensive informed consent for the research from the Department of Respiratory Medicine and Clinical Immunology, Graduate School of Medicine, Osaka University. Additional serum samples from 10 SLE patients were obtained from Biobank Japan (BBJ). Serum samples from patients with systemic sclerosis, primary Sjögren's syndrome, and SLE were also obtained and analyzed at the Erasmus Medical Center. These were approved by the Rotterdam Medical Ethics Review Board, and all participants provided written informed consent.

[0186] (Mice) C57BL / 6 mice were reared at the Infectious Disease Animal Resource Center and the pathogen-free mouse facility of the Osaka University School of Medicine and given standard feed and water. STING N153S KI mice were created by Professor Yamamoto (Reference 25). Heterozygous mice were created by mating wild-caught (WT) male and female mice with heterozygous mice. Wild-caught (WT) littermates housed with heterozygous mice were used as control mice.

[0187] In the antibiotic administration experiment, mice were given free access to an antibiotic mixture. The antibiotic mixture consisted of 0.5 g / L vancomycin, 1.0 g / L ampicillin, neomycin, and metronidazole (Nacalai Tesque) dissolved in autoclaved distilled water.

[0188] (Genotyping) The tail was digested with proteinase K, and the DNA was isolated and purified using the Wizard SV Genomic DNA Purification System (Promega) according to the manufacturer's protocol. Two separate PCR reactions were performed to determine the genotype: WT allele PCR and STING N153S mutant allele PCR. A forward primer (5'-GCCTGCACGAACTTTGGACTACTGT-3' (SEQ ID NO: 1)) that recognizes the sequence of exon 5 of Tmem173 (STING) and a WT reverse primer (5'-CAGCCCGTGGCAACATT-3' (SEQ ID NO: 2)) or a STING N153S reverse primer (5'-CAGCCCGTGGCAACAGA-3' (SEQ ID NO: 3)) were added to KOD-Plus-Neo (Toyobo) PCR buffer at a final concentration of 0.3 μM. STING N153S mutant-positive mice were identified by the appearance of a 700 bp band on agarose gel electrophoresis.

[0189] (Cytokine Assay) Before measuring cytokine and chemokine levels on the Luminex platform using the Bio-Plex Pro Mouse Cytokine Group 1 Panel 23-Plex Assay Kit (Bio-Rad) and mouse CXCL10 / IP-10 / CRG-2 DuoSet ELISA (R&D SYSTEMS), mouse serum was collected by blood loss from euthanized mice and stored at -20°C. Both assays were performed according to the manufacturer's instructions. Cytokines and chemokines tested using the Bio-Plex Pro assay include IL-1α, IL-1β, IL-2, IL-3, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12p40, IL-12p70, IL-13, IL-17A, eotaxin, G-CSF, GM-CSF, IFN-γ, KC, MCP-1, MIP-1α, MIP-1β, RANTES, and TNF-α.

[0190] Ultra-high sensitivity IFN-α2 measurements were performed using the Simoa IFN-α Advantage Kit (No. 100860, Quanterix, Billerica, MA, USA) according to the manufacturer's instructions. Sample processing and analysis were performed using the HD-X Immunoassay Analyzer (Quanterix, software version 1.6.1905.300) with a detection limit of 5 fg / ml.

[0191] (Tissue staining) Organs were removed from euthanized STING N153S and WT mice, fixed with 4% PFA at room temperature for 24 hours, and embedded in paraffin blocks. Tissue sections were stained with hematoxylin and eosin. Samples were imaged using a KEYENCE BZ-X800 microscope.

[0192] (Flow Cytometry) Spleen tissue was isolated from euthanized WT mice and STING N153S mice, crushed and filtered through a 70 μm nylon cell strainer, washed twice with culture medium, and then treated with erythrocyte lysis buffer. Flow cytometry of spleen cells was performed using FACS LSR II (BD Biosciences), and the data were analyzed using FlowJo software.

[0193] (Microbiome research) Feces from STING N153S mice and WT mice were collected directly from the anus into autoclaved tubes and stored at -80°C. DNA extraction and 16S rRNA gene amplicon sequencing were performed using the previously described method with some modifications (Hosomi K, Ohno H, Murakami H, Natsume-Kitatani Y, Tanisawa K, Hirata S, Suzuki H, Nagatake T, Nishino T, Mizuguchi K, Miyachi M, Kunisawa J. Method for preparing DNA from feces in guanidine thiocyanate solution affects 16S rRNA-based profiling of human microbiota diversity. Sci Rep. 2017 Jun 28;7(1):4339. doi: 10.1038 / s41598-017-04511-0. PMID: 28659635; PMCID: PMC5489508.). In short, a mouse fecal sample was mixed with 0.5 ml of lysis buffer (No. 10; Kurabo) and 0.5 g of 0.1 mm glass beads. This mixture was mechanically disrupted by bead beating using a Cell destroyer PS1000 (Bio Medical Science, Tokyo, Japan). DNA was extracted from 0.2 ml of the centrifuged supernatant using a Gene Prep Star PI-80X instrument (Kurabo). The V3-V4 region of the 16S rRNA gene (Klindworth, 2013) was amplified, and the base sequence was determined using an Illumina MiSeq (Illumina) according to the manufacturer's instructions.

[0194] Taxonomic classification was performed according to the previously reported procedure (Mohsen A, Park J, Chen YA, Kawashima H, Mizuguchi K. Impact of quality trimming on the efficiency of reads joining and diversity analysis of Illumina paired-end reads in the context of QIIME1 and QIIME2 microbiome analysis frameworks. BMC Bioinformatics. 2019 Nov 15;20(1):581. doi: 10.1186 / s12859-019-3187-5. PMID: 31730472; PMCID: PMC6858638.). In short, the sequencing results were obtained using the SILVA v128 reference sequence (Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glockner FO. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013 Jan;41(Database issue):D590-6. doi: 10.1093 / nar / gks1219. Epub 2012 Nov 28. PMID: 23193283; PMCID: PMC3531112.) and UCLUST software (Edgar, 2010) based on sequence similarity (>97%) using QIIME (Quantitative Insights Into Microbial). The analysis was performed using the Ecology software package (Caporaso 2010).

[0195] The vegdist function of the R package "vegan" (version 3.5.1) was used to calculate the Bray-Curtis distance using genus-level data. Principal coordinate analysis (PCoA) was performed based on the Bray-Curtis distance using the dudi.pco function of the R package "ade4," and a PCoA plot was created using the R package "ggplot2." Different bacterial taxa were ranked based on the effect size (LEfSe) of linear discriminant analysis (LDA) (Segata, 2011).

[0196] (CDN Measurement) Stool samples were collected from mice and suspended in PBS at a final concentration of 100 mg / ml. This stool suspension was centrifuged at 5000 x g for 10 minutes at room temperature. The supernatant was used as a sample along with urine or serum samples from mice and patients or healthy controls. The levels of 2'3'-cGAMP, c-di-AMP, c-di-GMP, and 3'3'-cGAMP were measured on a Luminex platform using the 2'3'-cGAMP ELISA Kit, c-di-AMP ELISA Kit, c-di-GMP ELISA Kit (Cayman Chemical), and 3',3'-Cyclic GAMP ELISA Kit (Arbor Assays). Each assay was performed according to the manufacturer's instructions. Furthermore, the c-di-AMP ELISA kit has an ELISA plate coated with goat anti-mouse IgG, which would normally interfere with the measurement of mouse samples containing mouse antibodies. Therefore, it could be used to measure samples other than those derived from mice.

[0197] (Calculation of Type I IFN score) As mentioned above, the Type I IFN score was calculated based on RT-PCR analysis of ISG MxA, IFI44, IFI44L, IFIT1, and IFIT3 obtained from whole blood of Dutch cohort patients (Reference 43).

[0198] (Statistical Analysis) All data were analyzed using Graph-Pad Prism software with Mann-Whitney, Student's t-test, or Spearman correlation analysis. Flow cytometry data were analyzed using FlowJo software.

[0199] (Example 1) This example demonstrates that various CDNs can be used as markers for STING-related diseases or symptoms.

[0200] (Summary) Based on current evidence linking STING-related pathology and the microbiome, SAVI mice carrying the STING N153S mutation were generated, and the variability in symptom manifestation was observed. Notably, only a subset of these mice developed severe systemic inflammation characterized by diarrhea and colitis-like intestinal pathology, and abnormalities in the gut microbiota and elevated fecal CDN concentrations were observed. Importantly, antibiotic administration significantly improved the intestinal pathology and systemic immunopathology of these mice. To apply these findings to humans, microbial and host-derived CDN concentrations were measured in the serum of SAVI patients. As a result, elevated concentrations of commensal and host-derived CDN were observed in the serum and urine of SAVI patients compared to healthy controls, suggesting a correlation with elevated cGAS activity, dysbiosis, and disease severity. Further analysis in cohorts of various autoinflammatory and autoimmune diseases revealed a strong correlation between systemic microbial CDN levels and disease severity, particularly in SLE, supporting our hypothesis that CDN plays a crucial role in the pathogenesis of STING.

[0201] (Results) (Some STING N153S mice developed diarrhea and colitis.) Recent evidence from studies using STING N153S knock-in (KI) mice suggests a possible link between gut microbiota and SAVI development (References 30, 31). To further investigate this link and explore the underlying mechanisms of SAVI development, the inventors utilized a mouse model for the disease. Specifically, heterozygous STING N153S KI mice were generated using the CRISPR-Cas9 system (Figure 1A), and their clinical symptoms were monitored. As previously reported, STING N153S KI mice exhibited characteristic signs including pulmonary lesions with pleural effusion (Figure 7A), ulcerative skin lesions on the head, and a fibrotic tail (Figure 7B) (References 23, 31). Histopathological analysis of the lungs revealed perivascular mononuclear cell infiltration, localized granulomatous inflammation of the alveoli, thickened alveolar epithelium, and alveolar macrophage infiltration (Figure 7C). Histopathological examination of the skin showed infiltration of inflammatory cells in the dermis (Figure 7C). STING N153S KI mice showed higher mortality (Figure 1B), splenomegaly (Figure 7D), and elevated anti-double-stranded DNA antibody titers compared to wild-type (WT) littermates (Figure 7E). T-cell lymphopenia and an increase in myeloid cells were also observed in the spleen, consistent with previous reports on SAVI model mice (Figures 8A and 8B). However, T-cell subtype analysis using CD44 and CD62L expression revealed that STING N153S KI mice, unlike WT mice, had a lower proportion of naive T cells and central memory T cells (both CD4 and CD8) and a higher proportion of effector memory T cells. This finding is in contrast to the report by Luksch et al., which showed an increase in central memory T cells and a decrease in effector memory T cells (Figure 8C and D) (Reference 31).

[0202] The prominent phenotype observed in a subset of STING N153S KI mice was the development of perianal erosion, anal prolapse (Figure 1C), and diarrhea with bloody stools, typically occurring between 8 and 16 weeks of age or later, along with significant weight loss. These symptoms are consistent with those recently described by Liraz et al. (Reference 33). STING N153S KI mice that developed diarrhea showed colon enlargement and shortening (Figure 1C). Histopathological examination of diarrheal mice revealed significant inflammatory cell infiltration in the epithelium, lamina propria, and muscularis propria of the colon, the lamina propria of the ileum, and the glandular stomach. In contrast, no inflammatory cell infiltration was observed in the tissues of mice without diarrhea, and the mucosal structure remained intact (Figure 1D). These findings suggest that some STING N153S KI mice develop colitis after birth, due to external stimuli or host-derived internal factors, similar to pulmonary and cutaneous vascular disorders.

[0203] (Diarrhea-type STING N153S mice showed worse systemic inflammation compared to non-diarrhea-type STING N153S mice.) To evaluate the correlation between systemic inflammation and colitis, multiple cytokine assays were performed using serum samples from diarrhea-type mice, non-diarrhea-type STING N153S KI mice, and WT littermates. As a result, diarrhea-type mice showed elevated levels of multiple cytokines and chemokines, including IL-1b, IL-6, IFNγ, IL-10, IL-17A, IP-10, MIP-1β, RANTES, and G-CSF, compared to WT mice, and elevated levels of IP-10, IL-6, IFNγ, and IL-10 compared to non-diarrhea-type STING N153S KI mice (Figures 2 and 9). Furthermore, STING N153S KI mice that developed diarrhea showed significantly higher levels of splenomegaly and anti-dsDNA IgM titers (Figures 10A and B). These results suggest that STING N153S KI mice with diarrhea developed more severe systemic inflammation than STING N153S KI mice without diarrhea. Considering these findings in conjunction with the pathological findings of widespread gastroenteritis, diarrheal SAVI mice appeared to exhibit a human inflammatory bowel disease (IBD)-like phenotype.

[0204] (Diarrhea-type STING N153S mice exhibit dysbiosis, with elevated fecal CDN levels from both host and microbiome sources.) It is well known that abnormalities in the gut microbiota are frequently observed in IBD patients, and part of the pathogenesis of IBD is attributed to the improper regulation of the immune response caused by these abnormalities in the gut microbiota (References 34, 35). These findings and recent reports suggest a link between dysbiosis and the pathogenesis of SAVI (References 32, 33). The inventors investigated whether diarrheal STING N153S KI mice exhibit dysbiosis caused by or potentially contributing to diarrhea. Fecal samples were collected from WT mice, non-diarrheal STING N153S KI mice, and diarrheal STING N153S KI mice, and their nucleotide sequences were determined. Analysis revealed that the gut microbiota of diarrhea-type STING N153S KI mice was significantly different from that of both WT mice and non-diarrhea-type STING N153S KI mice, although the gut microbiota of non-diarrhea-type STING N153S KI mice was very similar to that of WT mice (Figure 3A). Refce analysis comparing the gut microbiota of diarrhea-type and non-diarrhea-type STING N153S KI mice showed a decrease in the relative amounts of 16 bacterial genera and an increase in the relative amount of 1 genus in diarrhea-type N153S KI mice (Figure 3B and Table 1).

[0205]

[0206] In particular, bacteria of the Ruminococcaceae and Lachnospiraceae families, known for producing butyric acid, a type of short-chain fatty acid, were reduced (References 36, 37). This suggests that bacteria generally considered to be probiotics are reduced in diarrheal STING N153S KI mice. Conversely, the segment bacterium Candidatus Arthromitus was a bacterial species whose abundance increased in these mice (Figure 3B and Table 1). It is well known that environmental factors such as rearing conditions can affect the microbiome composition of mice housed in different animal facilities, and in turn, can affect the disease phenotype in rodent models of inflammatory bowel disease, various autoinflammatory diseases, and autoimmune diseases (References 38, 39). In fact, when we attempted to establish STING N153S KI mice at the University of Tokyo using a sperm stock of SAVI mice obtained from Osaka University, no pathological signs of SAVI, including colitis, were observed (Figure 11A). When we compared the gut microbiota of mice raised in Tokyo and Osaka, we found significant differences between the two cohorts (Figures 11B-E). For example, probiotic bacteria such as Senegalimassilia and Acetatifactor were less abundant in Osaka mice than in Tokyo mice (Tables 2 and 3).

[0207]

[0208]

[0209] However, bacteria associated with prearthritis, such as Coprococcus, Ruminococcus, Odoribacter, Parabacteroides, and Prevotellaceae, were detected in greater numbers in mice from Osaka (Tables 2 and 3) (Reference 40). These results highlight the important role of the microbiome in the development of SAVI.

[0210] When CDN levels were measured in stool samples, STING N153S KI mice that developed diarrhea had significantly higher levels of both commensal bacteria-derived and host-derived cGAMP compared to WT mice and STING N153S KI mice that did not develop diarrhea, and these levels correlated with dysbiosis. On the other hand, there were no significant differences in c-di-GMP levels between the groups (Figure 3C). However, serum CDN levels were similar across all groups (Figure 3D). Furthermore, serum and fecal CDN levels were similar between WT mice and STING N153S KI mice from the University of Tokyo, and the expected development of SAVI was not observed (Figures 11F and 11G). These findings suggest that microbial and host-derived CDN may be involved in the development of colitis in the SAVI mouse model.

[0211] (In diarrheal STING N153S KI mice, inflammation was suppressed by antibiotic administration.) After the onset of diarrhea, STING N153S KI mice, unlike their littermate WT mice, began to lose weight and died due to severe systemic inflammation (Figure 12). To investigate whether the abnormal gut microbiota in diarrheal STING N153S KI mice was the cause or consequence of colitis, the mice were treated with a mixture of four antibiotics to reduce both Gram-positive and Gram-negative bacteria. Administration of the antibiotic cocktail in drinking water reduced the weight of WT and non-diarrheal STING N153S KI mice without inducing diarrhea, but the weight loss and diarrhea were reversed in diarrheal STING N153S KI mice (Figure 4A). Importantly, in diarrheal STING N153S KI mice, systemic IL-6 levels also decreased after antibiotic administration, suggesting that dysbiosis contributes to the SAVI pathology, particularly colitis and diarrhea (Figure 4B).

[0212] (Systemic CDNs as a Potential Biomarker for STING-Related Autoinflammation) To validate findings from the SAVI mouse model in humans, we measured microbial and host-derived cyclic dinucleotide (CDN) concentrations in serum, plasma, and urine samples from three SAVI patients. Surprisingly, these patients had significantly elevated concentrations of c-di-GMP, c-di-AMP, and host-derived 2'3'-cGAMP in their plasma (Figure 5A). Furthermore, analysis of a serum sample from one SAVI patient revealed significantly higher 2'3'-cGAMP levels compared to the healthy control group. Interestingly, although not statistically significant, serum levels of c-di-GMP, 3'3'-cGAMP, and 2'3'-cGAMP appeared to decrease during steroid treatment in SAVI patients (Figure 5B). Furthermore, analysis of urine samples from the same SAVI patients revealed significantly elevated levels of c-di-AMP, c-di-GMP, and 2'3'-cGAMP compared to healthy controls (Figure 5C). Correlation analysis could not be performed due to the small sample size and the limited possibility of obtaining these parameters from all patients.

[0213] The inventors aimed to investigate whether cyclic dinucleotides (CDNs) could serve as common biomarkers or therapeutic targets using a large cohort of serum samples collected from patients with various autoinflammatory and autoimmune diseases. Given the established association between dysbiosis and exacerbations of autoimmune and autoinflammatory diseases (References 19-21, 32, 41), the inventors focused on the relationship between systemic CDNs and disease severity in several STING-dependent and non-STING-dependent diseases, similar to the role of gut microbiota in the production of STING agonists such as c-di-AMP, c-di-GMP, and 3'3'-cGAMP. Of the four naturally occurring CDNs, -2'3'-cGAMP, 3'3'-cGAMP, c-di-AMP, and c-di-GMP-2'3'-cGAMP are mammalian-derived and produced by cGAS, while the others are microbial-derived, including those produced by gut bacteria (References 41, 42). To assess whether systemic CDN levels correlate with disease severity in patients with various autoinflammatory and autoimmune connective tissue diseases, serum CDN and inflammatory markers such as IFN-β, IP-10, and IL-6 were measured. A significant positive correlation was observed between serum IFN-β and 2'3'-cGAMP levels in all disease types (Figure 6A), and weak positive correlations were also observed between serum IFN-β and c-di-AMP, and between serum IP-10 and c-di-GMP, but these were not statistically significant (Figures 14A-C). No other strong correlations were observed between CDN and cytokine levels (Figures 14A-C).

[0214] However, disease-specific analyses revealed a strong and significant correlation, particularly in systemic lupus erythematosus (SLE), a STING-dependent disease (Figure 6B-D, Table 4). Table 4 lists the following for RA, rheumatoid arthritis, SLE, systemic lupus erythematosus, SSc, systemic sclerosis, PM, polymyositis, DM, dermatomyositis, Sjögren's syndrome, GCA, giant cell arteritis, MPA, microscopic polyangiitis, GPA, granulomatosis with polyangiitis, EGPA, eosinophilic granulomatosis with polyangiitis, Behçet's disease, AOSD, and adult-onset Still's disease: CRP, C-reactive protein, DAS28, disease activity score 28 joints, SDAI, simplified disease activity index, CDAI, clinical disease activity index, dsDNA, double-stranded DNA, TSS, modified Rodnan total skin thickness. This study summarizes the correlation between serum CDN levels and clinical parameters related to disease activity or inflammatory cytokines in patients with autoinflammatory / autoimmune diseases, focusing on clinical parameters such as score, CK, creatine kinase, ESSDAI, EULAR Sjögren's Syndrome Disease Activity Index, MPO, myeloperoxidase, ANCA, anti-neutrophil cytoplasmic antibodies, PR3, and proteinase 3.

[0215]

[0216] On the other hand, no significant correlation was found in STING-independent diseases such as rheumatoid arthritis (RA) (Figure 6D, Table 4). In particular, in SLE patients, a strong positive correlation was observed between serum anti-double-stranded DNA (dsDNA) antibody titers and c-di-AMP and c-di-GMP levels, but no correlation was found with 2'3'-cGAMP (Figure 6F). Because the number of SLE patients in this disclosure was small (n=7), we attempted to verify these findings in a larger cohort. In collaboration with Erasmus Medical Center, we measured CDN levels and type I IFN scores using the highly sensitive assay method reported by Huijser et al. (Reference 43). This was done in a cohort of 32 SLE patients (16 adult-onset, 16 childhood-onset), 10 systemic sclerosis patients, and 20 Sjögren's syndrome patients. In all disease groups, IFN scores and IFNα2 levels were significantly higher compared to the healthy control group, and there was a strong and significant correlation between the scores and IFNα2 levels (Figure 15A). As a result, while 2'3'-cGAMP did not show a significant correlation between serum c-di-AMP, c-di-GMP levels and IFN scores, a significant positive correlation was observed only in the SLE group, but not in the combined disease group (Figures 6B, C and 15B). Overall, our findings suggest that there is a significant association between disease severity markers and serum CDN levels not only in SAVI patients but also in SLE patients.

[0217] In conclusion, our data not only confirm the association between commensal microbial abnormalities and autoinflammation, but also suggest that systemic microbial or host-derived CDN levels correlate with disease severity, suggesting that they could serve as biomarkers for STING-related autoinflammation.

[0218] (Discussion) This disclosure reveals that the gut microbiota plays a crucial role in shaping the pathological outcomes of SAVI, an autoinflammatory disease. Specifically, SAVI mice that developed colitis (STING N153S KI) showed gut microbiota abnormalities characterized by a decrease in short-chain fatty acid-producing bacteria and an increase in segmented bacteria. These mice also showed elevated fecal CDN levels derived from both the host and the gut microbiota. Importantly, this is the first demonstration that SAVI patients have significantly higher plasma host-derived and microbiome-derived CDN concentrations compared to healthy controls, supporting the association between STING-mediated autoinflammation and dysbiosis in humans. Furthermore, a strong positive correlation was observed between systemic microbial CDN levels and disease severity in SLE, a STING-dependent autoimmune disease. Our findings highlight the potential of systemic CDN as a biomarker for STING-related autoinflammation, with dysbiosis and increased cGAS activity playing a central role.

[0219] Martin et al. reported that administering a STING agonist to mice with dextran sulfate sodium (DSS)-induced colitis worsened the disease, and that DSS administration increased STING expression in mouse macrophages, suggesting that STING is involved in the host response to experimental colitis (Reference 24). In humans, no reports were found of SAVI patients developing colitis, but one study reported that SAVI patients showed infiltration of inflammatory cells from the liver to the stomach, leading to fatal gastrointestinal bleeding (Reference 44). Furthermore, the inventors have for the first time shown that plasma samples from SAVI patients had significantly higher concentrations of microbial-derived c-di-GMP, c-di-AMP, and host-derived 2'3'-cGAMP compared to healthy control groups. These findings suggest that high cGAS activity and the presence of gut microbiota abnormalities contribute to the development of SAVI through enhanced activation of the STING pathway by both host-derived and microbiota-derived CDNs (Figure 5). In fact, our data are supported by findings reported by Platt et al., who found that STING mice with the N153S mutation responded more to c-di-GMP than WT STING mice, but microbial cGAMP did not further induce activation of STING with the N153S mutation (References 29, 39). Taken together, these findings suggest that colitis and enteritis in SAVI patients are caused by further activation of the STING pathway by microbial CDNs, and that its secretion is regulated by changes in the gut microbiota.

[0220] Both cGAS and STING, which produce 2'3'-cGAMP, are IFN-inducible genes, and their expression is regulated by IFN-inducing factors such as infection, cancer, and aging (Reference 46). Furthermore, the severity of inflammation can lead to leaky gut and abnormalities in the gut microbiota, potentially affecting microbial CDN production. Diseases such as Sjögren's syndrome, SLE, Behçet's disease, and granulomatosis with polyangiitis (GPA) have previously been linked to abnormalities in gut microbiota formation (References 47-51). Leaky gut can allow gut-derived CDN to enter the bloodstream, potentially triggering autoimmune diseases (References 52, 53). Therefore, regulating the gut microbiota could be a therapeutic strategy to regulate intestinal permeability, as demonstrated in SAVI mice that developed colitis (Reference 33). In fact, antibiotic administration has been shown to alleviate lupus-like symptoms in SLE model mice (Reference 54). Our data showing a positive correlation between serum microbial CDN levels and inflammatory markers in SLE patients further supports this hypothesis (Figures 6B and C). Importantly, our findings in a small SLE cohort were reproducible in another institution with a larger SLE patient population, highlighting the robustness and reliability of our data. Furthermore, elevated CDN levels observed in plasma, serum, and urine samples from SAVI patients, along with a decrease in CDN after steroid treatment in one SAVI patient, suggest that host and microbial CDN may cause systemic inflammation through STING activation not only in SAVI but also in other autoinflammatory diseases associated with dysbiosis and leaky gut (Figure 5).

[0221] SAVI patients had elevated plasma c-di-AMP levels compared to healthy controls (Figure 5). The source of this c-di-AMP is thought to be the reduced intestinal commensal bacteria in SAVI mice that developed colitis and diarrhea. However, due to limitations of the c-di-AMP ELISA system, it was not possible to measure c-di-AMP levels in mouse serum or fecal samples (Figures 3B and 3D). Deadenylyl cyclase, the c-di-AMP synthase, is mainly found in Gram-negative bacteria belonging to the Bacteroidetes phylum and Gram-positive bacteria belonging to the Firmicutes and Actinobacteria phyla. In both cases, levels were reduced in SAVI mice with diarrhea compared to SAVI mice without diarrhea and WT controls (Table 1) (Reference 55). One of the main limitations of this disclosure is the lack of data on the dysbiotic status of patients with SAVI or other autoinflammatory diseases due to the unavailability of fecal samples. However, the higher concentrations of microbial CDN in the plasma, serum, and urine of SAVI patients compared to healthy controls strongly suggest that SAVI patients may have dysbiosis and leaky gut. Nevertheless, no gut bacteria producing c-di-GMP and c-di-AMP, which showed a significant positive correlation with CDN, particularly systemic inflammation in SLE patients, were identified. Further research is needed to address these issues.

[0222] The first report on a mouse model of SAVI was published in 2017 (Reference 23). STING N153S+ / - mice exhibited pulmonary inflammation and skin pathology, along with T cell cytopenia and myeloid cell enlargement, which is consistent with our findings in STING N153S+ / - mice. In this disclosure, we reproduced the phenotype of STING N153S+ / - mice, including low survival rate, splenomegaly, skin lesions, and pulmonary vasculitis. We also showed high titers of anti-dsDNA IgM and IgG, hypercytokinemia, T cell cytopenia, and myeloid cell enlargement in the spleen. Furthermore, unlike the first report on SAVI model mice with the N153S mutation, B cell cytopenia was observed in the spleen of our STING N153S+ / - mice. Subsequently, Motwani et al. showed that the number of B cells in the spleen of 6-week-old N153S + / - mice was similar to that of wild-caught (WT) mice, but that of N153S + / - mice aged 16 to 20 weeks was significantly lower than that of WT mice (Reference 25). These results suggest that the B cell population in the spleen differs with age and decreases in adulthood. In fact, Luksch et al. reported that the number of B cells in the peripheral blood of N153S + / - mice was increased compared to WT mice (Reference 31). On the other hand, Martin et al. reported that the number of B cells in the peripheral blood was decreased in human STING N154S transgenic mice (Reference 24). This suggests that the cell populations in the spleen and peripheral blood may be different. STING activation in T cells has been shown to induce T cell apoptosis (Reference 56) and inhibit T cell proliferation (Reference 57). The T cell reduction observed in SAVI is thought to reflect these findings. Apoptosis of B cells induced by STING agonist treatment has also been reported (Reference 58). STING signaling suggests that it affects both B cells and T cells in terms of STING-mediated cell death.

[0223] According to a report by Jonathan J. Miner's group, STING N153S + / - mice lacking IRF3, IFNAR1, IRF3 / IRF7, or cGAS developed lung disease and T-cell depletion, suggesting that this pathology is independent of type I IFN signaling and cGAS (Reference 31). On the other hand, since STING also responds to bacterial cyclic dinucleotides, the inventors hypothesized that microbiome-related differences between SAVI mice developed at different research institutions might explain the phenotypic differences observed between SAVI mouse models. Nevertheless, heterogeneity of the gut microbiota, which can dramatically alter experimental results, was observed between mice housed at different research institutions as a result of differences in diet, cage, or stressors to which the mice were exposed (Reference 59). In fact, SAVI mice with diarrhea were observed at the animal research facility of Osaka University, but not at the animal research facility of the University of Tokyo. This is because the gut microbiota of mice raised in animal research facilities at Osaka University and the University of Tokyo differs (Figure 11). Compared to mice raised at the University of Tokyo, mice raised at Osaka University showed an increase in gut bacteria that can cause arthritis, such as Coprococcus, Ruminococcus, Odoribacter, Parabacteroides, and Prevotellaceae (Reference 40), while the relative amounts of probiotic bacteria such as Senegalli macilia and acetatefactor were decreased (Tables 2 and 3).

[0224] In line with our hypothesis, Bouis et al. reported that the survival rate of STING V154M + / - mice, another SAVI model mouse, after antibiotic administration was improved compared to STING V154M + / - mice without antibiotic administration (Reference 30). They suggested that the gut microbiota of mice may influence the disease phenotype. More recently, Platt et al. demonstrated that a Bacteriodarez-rich gut microbiota directly protects against SAVI-mediated pulmonary pathology (Reference 32). Unlike Platt et al.'s study, our antibiotic cocktail contains metronidazole, which has been shown to deplete the Bacteroides thetaiotaomicron species, and their study reported a protective effect. Therefore, the mechanism mediating the therapeutic effect of antibiotic intervention in our study is likely dependent on the depletion of segment bacteria, which were increased in SAVI mice that developed diarrhea.

[0225] This is the second report demonstrating that SAVI mice carrying the heterozygous STING N153S mutation develop colitis and dysbiosis. The first report, published recently, suggested that constitutive STING activity leads to STING accumulation in intestinal myeloid cells, followed by the release of commensal CDN, resulting in chronic colitis (Reference 33). However, these authors did not address or investigate why only some STING N153S + / - mice develop colitis. According to our data, only some STING N153S + / - mice developed diarrhea and severe weight loss 2-4 months after birth. Wild littermates housed in the same cage as the diarrheal mice did not develop diarrhea, nor did many other STING N153S + / - littermates housed in the same cage. The inventors hypothesized that changes in the microbiome of diarrheal mice might cause or worsen colitis. Therefore, they analyzed the microbiomes of three types of mice: WT mice and STING N153S + / - mice with or without diarrhea. As expected, diarrheal STING N153S + / - mice had a different gut microbiota compared to WT mice and non-diarrheal STING N153S + / - mice, with decreased levels of Ruminococcaceae and Lachnospiraceae and increased levels of Candidatus arthromitus. Lachnospiraceae are known to produce butyrate among gut microbiota (Reference 36). Short-chain fatty acids, including butyrate, suppress intestinal inflammation, maintain the intestinal barrier, and regulate intestinal motility. Furthermore, Candidatus arthromitus is classified as a segmented bacterium and assists in the development of innate and adaptive immune responses in the gut through mechanisms that depend on the induction of antigen-specific T cells and IgA-producing B cells. Based on the above, we concluded that the changes observed in the gut microbiota composition of diarrhea-type STING N153S+ / - mice are the cause of the specific colitis phenotype observed only in our SAVI model mice.

[0226] STING appears to be associated with intestinal homeostasis, and STING-deficient mice showed defects in the defense mechanisms of the intestinal mucosa compared to wild-caught (WT) mice, including a decrease in goblet cell count, reduced mucus production, and low levels of secretory IgA (Reference 56). One reason for the regulation of the STING pathway mediated by the gut microbiota is that CDN produced by the gut microbiota further activates the STING signal in the intestines, thereby exacerbating intestinal pathology. Diarrhea-type STING N153S + / - mice had high concentrations of 2'3'-cGAMP and 3'3'-cGAMP in their feces, and both microbial and host-derived cGAMP levels in their feces were higher compared to diarrhea-type STING N153S + / - mice and WT mice. Two possible explanations for this result are: 1) the gut microbiota of diarrheal mice produces CDN, which induces inflammation in the gut, particularly the large intestine, leading to colitis; and 2) the damaged gut, releasing host-derived CDN, alters gut homeostasis to allow specific CDN-producing bacteria to proliferate. Furthermore, considering that STING modulates intestinal barrier dysfunction and contributes to sepsis, and that STING and TLR agonists show a synergistic effect on IFN induction (References 12, 15, 57), it is thought that SAVI mice with diarrhea developed leaky gut due to excessive STING function, and that the synergistic effect of released microbial CDN and PAMPs such as LPS and CpG ODN maximized systemic inflammation, ultimately leading to the death of the mice. In relation to STING-mediated disease-associated dysbiosis, Mu et al. reported that vancomycin, rather than neomycin, eliminates Lachnospiraceae and increases the relative abundance of Lactobacillus species (Reference 54). They also showed that vancomycin administration enhances the barrier function of the intestinal epithelium and prevents the circulating transfer of lipopolysaccharide, a cell wall component of Gram-negative proteobacteria known to induce lupus in mice. This supports our findings that the balance between defensive and pathogenic bacteria influences the host's intestinal homeostasis.

[0227] In conclusion, the results of this disclosure confirm, for the first time, a potential link between gut microbiota abnormalities and STING-mediated autoinflammatory pathology, not only in mice but also in SAVI patients. Furthermore, this disclosure identifies a strong correlation between systemic CDN levels and systemic inflammation in SLE, a STING-dependent autoimmune disease. These findings suggest that antibiotic treatment may help eliminate pathogenic or disease-exacerbating bacteria and maintain gut homeostasis in patients with inflammatory / autoimmune diseases, including SAVI and SLE. Notably, the pathophysiology of SAVI and severe COVID-19 are similar, with delayed hyperactivation of the STING pathway and pathological conditions affecting blood vessels, lungs, and the intestines (Reference 59). Measuring systemic CDN levels may provide further insights into the development of novel therapeutic strategies for STING-related dysbiosis.

[0228] (List of references) In this specification, when a reference is referred to as "reference X" (where X is an integer), it refers to the following references. References 1. Barber GN. Cytoplasmic DNA innate immune pathways. Immunol. Rev. 2011;243(1):99-108. 2. Desmet CJ, Ishii KJ. Nucleic acid sensing at the interface between innate and adaptive immunity in vaccination. Nat. Rev. Immunol. 2012;12:479-91. 3. Zhang X et al. Cyclic GMP-AMP containing mixed Phosphodiester linkages is an endogenous high-affinity ligand for STING. Mol. Cell 2013;51:226-35. 4. Li XD et al. Pivotal roles of cGAS-cGAMP signaling in antiviral defense and immune adjuvant effects. Science.2013;341(6152):1390-4. 5. Sun L, Wu J, Du F, Chen X, Chen ZJ. Cyclic GMP-AMP Synthase Is a cytosolic DNA sensor that activates tye type I IFN pathway. Science. 2013;339:786-791. 6. Burdette DL et al. STING is a direct innate immune sensor of cyclic di-GMP. Nature2011;478:515-518. 7. Barker JR et al.STING-Dependent Recognition of Cyclic di- AMP Mediates Type I Interferon Responses during Chlamydia trachomatis Infection STING-Dependent Recognition of Interferon Responses during Chlamydia trachomatis Infection. MBio2013;4(3):1-11. 8. McWhirter SM et al. A host type I interferon response is induced by cytosolic sensing of the bacterial second messenger cyclic-di-GMP. J Exp Med2009;206:1899-1911. 9. Fatma S、Chakravarti A、Zeng X、Huang RH. Molecular mechanisms of the CdnG-Cap5 antiphage defense system employing 3′,2′-cGAMP as the second messenger. Nat. Commun. 2021;12(1):1-9. 10. Holleufer A et al. Two cGAS-like receptors induce antiviral immunity in Drosophila. Nature 2021;597(7874):114-118. 11. Platanias LC. Mechanisms of type-I- and type-II-interferon-mediated signalling. Nat. Rev. Immunol. 2005;5(5):375-386. 12. Temizoz B et al. TLR9 and STING agonists synergistically induce innate and adaptive type-II IFN. Eur. J. Immunol. 2015;45:1159-1169. 13. Temizoz B、Kuroda E、Ishii KJ.Vaccine adjuvants as potential cancer immunotherapeutics. Int. Immunol. 2016;28(7):329-338. 14. Temizoz B、Kuroda E、Ishii KJ. Combination and inducible adjuvants targeting nucleic acid sensors. Curr. Opin. Pharmacol.2018;41:104-113. 15. Temizoz B et al. Anti-tumor immunity by transcriptional synergy between TLR9 and STING activation. Int. Immunol. 2022; 34(7):353-364. 16. Schadt L et al. Cancer-Cell-Intrinsic cGAS Expression Mediates Tumor Immunogenicity. Cell Rep. 2019;29(5):1236-1248.e7. 17. Tang CK et al. The Chemotherapeutic Agent DMXAA as a Unique IRF3-Dependent Type-2 Vaccine Adjuvant. PLoS One 2013;8:6-11. 18. Woo SR et al. STING-Dependent Cytosolic DNA Sensing Mediates Innate Immune Recognition of Immunogenic Tumors. Immunity 2014;41:830-42. 19. Ahn J、Gutman D、Saijo S、Barber GN. STING manifests self DNA-dependent inflammatory disease. Proc. Natl. Acad. Sci. U. S. A.2012;109(47):19386-19391. 20. Ahn J、Ruiz P、Barber GN.Intrinsic Self-DNA Triggers Inflammatory Disease Dependent on STING. J. Immunol. 2014;193:4634-42. 21. Gao D et al. Activation of cyclic GMP-AMP synthase by self-DNA causes autoimmune diseases. PNAS 2015;5699-705. 22. Liu Y et al. Activated STING in a Vascular and Pulmonary Syndrome. N. Engl. J. Med. 2014;371:507-18. 23. Warner JD et al. STI NG-associated vasculopathy develops independently of IRF3 in mice. J. Exp. Med. 2017;214(11):3279-3292. 24. Martin GR et al. Expression of a constitutively active human STING mutant in hematopoietic cells produces an Ifnar1-dependent vasculopathy in mice. Life Sci. Alliance 2019;2(3):1-15. 25. Motwani M et al. Hierarchy of clinical manifestations in SAVI N153S and V154M mouse models. Proc. Natl. Acad. Sci. U. S. A. 2019;116(16):7941-7950. 26. Valeri E et al. A novel STING variant triggers endothelial toxicity and SAVI disease. J. Exp. Med.2024;221(9):e20232167. 27. Montealegre Sanchez GA et al.JAK1 / 2 inhibition with baricitinib in the treatment of autoinflammatory interferonopathies. J. Clin. Invest.2018;128(7):3041-3052. 28. Saldanha RG et al. A mutation outside the dimerization domain causing atypical STING-associated vasculopathy with onset in infancy. Front. Immunol.2018;9:1535. 29. Bennion BG et al. A Human Gain-of-Function STING Mutation Causes Immunodeficiency and Gammaherpesvirus-Induced Pulmonary Fibrosis in Mice. J. Virol. 2019;93(4):1-18. 30. Bouis D et al. Severe combined immunodeficiency in stimulator of interferon genes (STING) V154M / wild-type mice. J. Allergy Clin. Immunol.2019;143(2):712-725.e5. 31. Luksch H et al. STING-associated lung disease in mice relies on T cells but not type I interferon. J. Allergy Clin. Immunol. 2019;144(1):254-266.e8. 32. Platt DJ et al. Transferrable protection by gut microbes against STING-associated lung disease ll ll Transferrable protection by gut microbes against STING-associated lung disease . Cell Reports 2021;35(6):109113.33. Liraz SGet al. Dysbiosis exacerbates colitis by promoting ubiquitination and accumulation of the innate immune adaptor STING in myeloid cells. Rev. Immun. 2021;1-17. 34. Morgan XC et al. Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment. Genome Biol. 2012;13(9):R79. 35. Gevers D et al. The treatment-naive microbiome in new-onset Crohn’s disease. Cell Host Microbe 2014; 15(3):382-392. 36. Darnaud M et al. Enteric Delivery of Regenerating Family Member 3 alpha Alters the Intestinal Microbiota and Controls Inflammation in Mice With Colitis. Gastroenterology2018; 154(4):1009-1023. 37. Zhang J et al. Beneficial effect of butyrate-producing Lachnospiraceae on stress-induced visceral hypersensitivity in rats. J. Gastroenterol. Hepatol.2019; 34(8):1368-1376. 38. Forster SC et al. Identification of gut microbial species linked with disease variability in a widely used mouse model of colitis. Nat. Microbiol.2022;7(4):590-599. 39. Hansen AK、Hansen CHF.The microbiome and rodent models of immune mediated diseases . Mamm. Genome 2021;32(4):251-262. 40. Liu X et al. Role of the Gut Microbiome in Modulating Arthritis Progression in Mice . Sci. Rep. 2016;6:30594. 41. Danilchanka O et al. An outer membrane channel protein of Mycobacterium tuberculosis with exotoxin activity. Proc. Natl. Acad. Sci. U. S. A.2014; 111(18):6750-5. 42. Krasteva PV et al. Insights into the structure and assembly of a bacterial cellulose secretion system. Nat. Commun. 2017; 8(1):2065.43. Huijser E et al. Serum interferon-α2 measured by single-molecule array associates with systemic disease manifestations in Sjogren’s syndrome. Rheumatology2022;61(5):2156-2166. 44. Ishikawa T、Tamura E、Kasahara M、Uchida H、Higuchi M. Severe Liver Disorder Following Liver Transplantation in STING-Associated Vasculopathy with Onset in Infancy2021; 45. Liu Y et al. Activated STING in a Vascular and Pulmonary Syndrome. N. Engl. J. Med. 2014;371:507-518. 46. Li T、Chen ZJ.The cGAS - cGAMP - STING pathway connects DNA damage to inflammation 、senescence 、and cancer. J. Exp. Med. 2018;215(5):1287-1299. 47. Mandl T、Marsal J、Olsson P、Ohlsson B、Andreasson K. Severe intestinal dysbiosis is prevalent in primary Sjogren’s syndrome and is associated with systemic disease activity. Arthritis Res. Ther. 2017;19(1):237. 48. Hevia A et al. Intestinal dysbiosis associated with systemic lupus erythematosus. MBio 2014;5(5):1-10. 49. Andreasson K、Alrawi Z、Persson A、Jonsson G、Marsal J. Intestinal dysbiosis is common in systemic sclerosis and associated with gastrointestinal and extraintestinal features of disease . Arthritis Res. Ther. 2016;18(1):1-8. 50. Consolandi C et al. Behcet’s syndrome patients exhibit specific microbiome signature . Autoimmun. Rev. 2015;14(4):269-276. 51. Fasano A. Leaky gut and autoimmune diseases. Clin. Rev. Allergy Immunol.2012;42(1):71-78. 52. Mu Q、Kirby J、Reilly CM、Luo XM. Leaky gut as a danger signal for autoimmune diseases. Front. Immunol.2017;8(MAY):1-10. 53. Corrigan RM、Grundling A. Cyclic di-AMP: Another second messenger enters the fray. Nat. Rev. Microbiol. 2013;11(8):513-524. 54. Gulen MF et al. Signalling strength determines proapoptotic functions of STING. Nat. Commun. 2017; 8(1):427. 55. Cerboni S et al. Intrinsic antiproliferative activity of the innate sensor STI NG in T lymphocytes. J. Exp. Med. 2017; 214(6):1769-1785. 56. Canesso MCC et al. The cytosolic sensor STING is required for intestinal homeostasis and control of inflammation. Mucosal Immunol. 2018;11(3):820-834. 57. Hu Q et al. STING-mediated intestinal barrier dysfunction contributes to lethal sepsis . EBioMedicine. 2019;41:497-508. 58. Tang CHA et al. Agonist-mediated activation of STING induces apoptosis in malignant B cells. Cancer Res. 2016; 76(8):2137-52. 59. Berthelot J、Liote F. COVID-19 as a STING disorder with delayed over-secretion of IFN-β. EBioMedicine. 2020;56: 102801.

[0229] (Example 2: Cancer Example) This example demonstrates that the technology of the present disclosure can also be applied to cancer. (Methods and Materials) The effects of STING agonists, TLR9 agonists, and combinations thereof were evaluated in experiments using mice. Specifically, STING agonists (CDNs), TLR9 agonists, and combinations of STING agonists and TLR9 agonists were tested, with fecal / serum CDN levels measured before and after treatment to see if there was a correlation with the outcome of cancer immunotherapy using TLR9 and / or STING agonists.

[0230] Specifically, it is as follows:

[0231] Six-week-old female C57BL / 6J mice were given 0.5 × 10⁶ B16 BL6 tumor cells on day 0. ６ The mice were inoculated with 10 μg of the following: control, TLR9 agonist (K3 CpG or D35 CpG), STING agonist (five types of CDNs: 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, c-di-GMP), or a combination of TLR9 and STING agonist. Tumor growth was monitored for 15 days, and post-treatment samples including feces, serum, and tumors were collected from the mice on day 15. Tumor weight was recorded using a digital caliper, and fecal CDN levels were measured using ELISA for the five types of CDNs. Correlation analysis was performed between fecal CDN levels and tumor weight (n=5 for each group) before (circles) and after (squares) treatment. **p < 0.01.

[0232] Correlation analysis was performed between the fecal concentrations of five types of CDNs (2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP) and tumor weight in 90 mice treated with various adjuvant therapies. Fecal samples were prepared by dissolving 50 mg / ml of feces in PBS, vortexing, and boiling the solution at 95°C for 30 minutes. After centrifugation at 10,000 rpm for 10 minutes, the supernatant was collected and analyzed using CDN-specific ELISA.

[0233] As a result, the group administered antibiotics showed a significant change in the antitumor effect of specific STING agonists. Specifically, regarding changes in fecal CDN levels, as shown in Figure 17, the levels of 3'3'-cGAMP and 3'2'-cGAMP were higher after adjuvant administration compared to before administration. On the other hand, the levels of 2'3'-cGAMP, c-di-AMP, and c-di-GMP were higher before adjuvant administration compared to after administration.

[0234] To further investigate these observations, we are currently measuring CDN levels in the feces of these mice at multiple time points: • After tumor inoculation, and • After STING agonist administration for cancer immunotherapy.

[0235] (Discussion) Previous studies have demonstrated that the combined use of STING and TLR9 agonists synergistically induces a potent antitumor immune response in several mouse tumor models. Based on this, we formulated the following hypothesis.

[0236] In mice exhibiting both gut microbiota dysfunction and cancer, elevated CDNs may indicate that endogenous STING agonists are already contributing to the activation of the STING pathway. In such cases, using only TLR9 agonists as immunotherapy may sufficiently induce a potent antitumor response through synergistic interactions with elevated STING agonists.

[0237] This approach highlights the potential to personalize cancer immunotherapy strategies based on individual CDN levels. By monitoring CDN profiles, it may be possible to optimize treatments for patients with gut microbiota imbalances, ensuring more effective and personalized treatment outcomes.

[0238] As shown in Figure 17, in the experiment described in this embodiment, a significant negative correlation was found between the 3'3'-cGAMP level in the feces before treatment and the tumor volume.

[0239] Data Discussion: The significant negative correlation observed between pre-treatment fecal 3'3'-cGAMP levels and tumor burden suggests that microbiome-derived 3'3'-cGAMP enhances the antitumor response to immunotherapy. Elevated pre-treatment 3'3'-cGAMP levels may serve as a useful biomarker predicting improved treatment outcomes, particularly in cancer immunotherapy based on STING, TLR9, or agonist combinations. The antitumor effect may be attributable to 3'3'-cGAMP's ability to prepare the immune system by activating the STING pathway, thereby creating a favorable immune microenvironment before treatment initiation. This microbiome-derived CDN is likely to enhance the subsequent activation of innate and adaptive immunity mediated by STING and TLR9 agonists, resulting in a synergistic antitumor response. Therefore, pre-treatment fecal 3'3'-cGAMP levels can be a valuable tool for patient stratification and adjustment of immunotherapy strategies to maximize efficacy.

[0240] (Example 3: Example of allergic and inflammatory diseases) In this example, as an example of allergic and inflammatory diseases, we conducted an example to evaluate the relationship between asthma and COPD.

[0241] (Materials and Methods) The following is an experimental protocol to evaluate the association between the CDN-STING pathway and asthma / COPD.

[0242] In this example, experiments were conducted using BBJ serum samples from 198 asthma patients and 38 COPD patients, as well as serum samples from 29 healthy individuals. ELISA and bioplex assays were performed using these samples.

[0243] (Measurement of cytokines / chemokines / CDN) A 27-plex bioplex (-Bio-Plex Pro Human Cytokine GI 27-plex panel #M500KCAF0Y) was used. CDN (2'3'-cGAMP, 3'3'-cGAMP, c-di-AMP, c-di-GMP) was measured using an ELISA kit (ELISA Pro: Human IgE, Mabtech, #: 3810-1HP-2). IL-33 and total IgE were measured using an ELISA kit (Human IL-33 ELISA Kit-Quantikine, Catalogue #: D3300B).

[0244] (Results) (In the case of COPD) As shown in Figure 18, serum c-di-AMP, c-di-GMP, 3'3'-cGAMP, 3'2'-cGAMP, and 2'3'-cGAMP levels were significantly elevated in asthma patients compared to healthy controls. Serum levels of c-di-AMP, c-di-GMP, 3'3'-cGAMP, 3'2'-cGAMP, and 2'3'-cGAMP were measured in asthma patients (n=198), patients with chronic obstructive pulmonary disease (n=38), and healthy controls (n=29). The data are shown as a scatter plot, with the mean value indicated by the gray line. Statistical significance was determined by the Mann-Whitney U test (*p<0.05, **p<0.01, ****p<0.0001). As shown in Figure 19, serum 3'3'-cGAMP showed a significant positive correlation with eotaxin, rantes, mip-1β, and IL-9 levels in patients with chronic obstructive pulmonary disease (COPD). Serum 3'3'-cGAMP levels in COPD patients (n=38) were measured by ELISA. Serum levels of eotaxin, rantes, mip-1β, and IL-9 were measured using the 27-plex Bio-Plex assay. Correlation analysis was performed between 3'3'-cGAMP and these cytokines / chemokines. Statistical significance was determined at **p < 0.001 and ***p < 0.0001.

[0245] As shown in Figure 20, a significant positive correlation was observed between serum 2'3'-cGAMP levels and serum RANTES, MIP-1β, and IL-9 levels in patients with chronic obstructive pulmonary disease (COPD). Serum 2'3'-cGAMP levels in COPD patients (n=38) were measured by ELISA. Serum RANTES, MIP-1β, and IL-9 levels were evaluated using a 27-parameter simultaneous Bio-Plex assay. Correlation analysis was performed between 2'3'-cGAMP and these parameters. Statistical significance was shown as follows: ***p < 0.0001.

[0246] As shown in Figure 21, a significant negative correlation was observed between serum 3'2'-cGAMP levels and serum PDGF-BB and IgE levels in patients with chronic obstructive pulmonary disease (COPD). Serum 3'2'-cGAMP and IgE levels in COPD patients (n=38) were measured by ELISA. Serum PDGF-BB levels were evaluated using a 27-parameter simultaneous Bio-Plex assay. Correlation analysis was performed between 2'3'-cGAMP and these parameters. Statistical significance was shown as follows: *p < 0.05, **p < 0.01.

[0247] As shown in Figure 22, a significant positive correlation was observed between serum 3'3'-cGAMP levels, serum IL-1RA levels, and serum neutrophil percentage in asthma patients. Serum 3'3'-cGAMP levels in asthma patients (n=198) were measured by ELISA. Serum IL-1RA levels were evaluated using a 27-parameter simultaneous Bio-Plex assay, and serum neutrophil percentages were provided by BBJ. Correlation analysis was performed between 3'3'-cGAMP and these parameters. Statistical significance was shown as follows: **p < 0.01, ***p < 0.001.

[0248] Discussion on COPD / Asthma Data: The observed correlation between serum 3'3'-cGAMP levels and clear inflammatory markers in asthma and COPD patients provides insight into their potential role in disease progression. In asthma, a significant positive correlation was found between 3'3'-cGAMP and IL-1RA levels and neutrophil percentage, suggesting that microbial-derived CDNs may promote the activation of innate immunity and contribute to neutrophil-mediated airway inflammation. Elevated IL-1RA may be a compensatory mechanism to suppress inflammation caused by excess IL-1, suggesting a role in regulating asthma severity. In COPD patients, significant correlations were found between 3'3'-cGAMP and eotaxin, rantes, mip-1β, and IL-9, highlighting their association with eosinophil and chemokine-mediated inflammation. These markers are key factors in airway remodeling and chronic inflammation in COPD, and 3'3'-cGAMP has been suggested to amplify chemotactic signaling and Th2 cytokine responses. The distinctive inflammatory profiles associated with 3'3'-cGAMP in asthma and COPD highlight its dual role in regulating disease-specific immune responses. Therefore, elevated 3'3'-cGAMP levels may serve as a biomarker of disease activity and progression, potentially aiding in patient stratification for targeted therapeutic interventions.

[0249] (Proposed Methods) Based on the results of the above examples, the proposed methods for the treatment and companions for autoimmune diseases are as follows: 1. <Asthma> (Biomarkers) ・3'3'-cGAMP correlates with serum neutrophil percentage and IL-1RA level. (Calculation Method) ・Asthma biomarker index = [3'3'-cGAMP] × (neutrophil % + IL-1RA). (Therapeutic Implications) ・Elevated bacterial CDN levels indicate the need for microbiome-targeted therapy to reduce airway inflammation. ・Host-derived CDN elevation may benefit from STING pathway inhibitors. 2. <Chronic Obstructive Pulmonary Disease (COPD)> (Biomarkers) ・Host-derived 2'3'-cGAMP correlates with RANTES, MIP-1β, and IL-9.・Microbial 3'3'-cGAMP correlates with eotaxin, rantes, mip-1β, and IL-9. (Calculation method) ・COPD biomarker index = ([2'3'-cGAMP] + [3'3'-cGAMP]) × (rantes + mip-1β + mip-9). (Therapeutic implications) ・Therapies targeting microbiome abnormalities for increased microbial CDN (e.g., antibiotics, probiotics). ・Anti-inflammatory interventions targeting hyperactivation of the STING pathway against host-derived CDN. 3 <Allergy (Hypothesis)> (Biomarkers) ・Similar CDN and cytokine profiles are helpful in managing allergic diseases. (Therapeutic implications) ・In Th2-dominant inflammation (e.g., allergic asthma), TLR9 agonists may redirect the immune response towards Th1 immunity.

[0250] <Proposed Method> (Measurement) Quantify CDNs (e.g., 2'3'-cGAMP, 3'3'-cGAMP) and related cytokines (e.g., RANTES, IL-9) using an ELISA assay. (Diagnosis) Measure CDN levels compared to thresholds obtained from healthy individuals to identify microbiome disruption or hyperactivation of the cGAS-STING pathway. (Adjustment of Treatment) If bacterial CDN levels are high: Normalize the microbiome with antibiotics or probiotics. If host CDN levels are elevated: Suppress hyperactivation of cGAS-STING using STING inhibitors. If allergic symptoms are present: Shift the immune balance towards Th1 by using a TLR9 agonist in combination.

[0251] (Summary) This example outlines a companion therapy strategy for autoimmune diseases that utilizes CDN biomarkers and microbiome-targeted interventions to improve treatment outcomes.

[0252] In other words, the combination therapy strategy described herein employs CDN profiling to guide individualized treatment plans for asthma, allergies, and chronic obstructive pulmonary disease (COPD). This approach ensures: • Modulation and restoration of microbiome disturbances. • Precise immunomodulation targeting the STING or TLR9 pathway. • Improved clinical outcomes through individualized interventions.

[0253] 2'3'-cGAMP is produced by host cGAS. Furthermore, 3'3'-cGAMP is typically derived from both Gram-positive and Gram-negative bacteria (initially identified in Vibrio cholerae), while c-di-AMP is primarily produced by Gram-positive bacteria such as Listeria monocytogenes. Many organisms that synthesize c-di-AMP are important human pathogens and environmental microorganisms, and their growth and survival depend on c-di-AMP. Mycobacterium tuberculosis is also known to produce c-di-AMP, but c-di-GMP is widely present in Gram-negative bacteria and controls many functions, including biofilm formation and motility. However, c-di-GMP is not exclusive to Gram-negative bacteria; several Gram-positive bacteria, such as Bacillus subtilis and Listeria monocytogenes, also produce this molecule.

[0254] (Discussion) The main points of this embodiment are summarized below. Significant but weak correlations were observed between serum CDN levels and disease parameters in asthma (e.g., 3'3'-cGAMP vs. neutrophil% and IL-1RA, 2'3'-cGAMP vs. neutrophil and lymphocyte%, c-di-AMP vs. neutrophil% and ALT levels). COPD patients were found to have significantly higher serum c-di-AMP levels compared to healthy controls. 3'3'-cGAMP (bacterial origin) showed a significant positive correlation with eotaxin, rantes, MIP-1β, and IL-9 in COPD. 2'3'-cGAMP (host origin) also showed a significant positive correlation with rantes, MIP-1β, and IL-9 in COPD.

[0255] (Example 4: Companion therapy for autoimmune diseases) This example demonstrates companion therapy for autoimmune diseases. This example shows the effect of antibiotic treatment using a SAVI mouse model.

[0256] Specifically, in SAVI mice exhibiting disruption of the gut microbiota and increased systemic inflammation, antibiotic treatment alleviated systemic inflammation and significantly improved SAVI-related pathology. These findings, demonstrated in Example 1, provide clear evidence of the therapeutic potential of microbiome regulation in STING-related autoinflammatory diseases.

[0257] Furthermore, the potential of antibiotics as a therapeutic intervention for other inflammatory diseases such as SLE is supported by existing literature. For example, Mu et al. demonstrated that antibiotic treatment alleviates lupus-like symptoms in an SLE mouse model (Mu Q et al., Antibiotics ameliorate lupus-like symptoms in mice (Scientific Reports, 2017)). As demonstrated here, the role of antibiotic therapy in regulating the microbiome has been investigated in SLE and related diseases. As shown in Figure 4, in SAVI, administering antibiotics to a diarrheal mouse model resulted in symptom improvement, and verification in other diseases and in humans is also possible. Combining the inventions of this disclosure allows for the selection of appropriate antibiotics based on companion diagnostic results, leading to more effective treatment. Since high doses of four antibiotics were administered to deplete the intestinal microorganisms, it is unlikely that this would cause disruption of the gut microbiota. However, in humans, prolonged antibiotic use can deplete specific bacteria, potentially disrupting the gut microbiota. This differs from the experiment in this embodiment, where four antibiotics were administered for a long period to deplete all types of bacteria. In humans, it is necessary to select an appropriate combination of antibiotics, which may be possible by observing the actual state of the gut microbiota beforehand.

[0258] This embodiment demonstrates that CDN measurement and microbiome-targeted therapies (e.g., antibiotics) are useful as companion therapies for autoimmune diseases such as SAVI and SLE. This addresses both systemic inflammation and disease pathology.

[0259] (Example 5: Companion therapy in cancer immunotherapy) In this example, we demonstrate that companion therapy in cancer immunotherapy is possible using the results diagnosed by the diagnostic method of this disclosure. (Combination therapy of STING and TLR9 agonist) The inventors previously reported that the combination of STING agonists (CDNs) and TLR9 agonists synergistically enhances the antitumor immune response in various mouse tumor models. This combination therapy can significantly promote Th1 immune activity and improve tumor regression. (Effects of gut microbiota disruption on cancer treatment) The inventors induced disruption of the gut microbiota in tumor-transplanted mice by administering antibiotics and verified the following effects: STING agonist monotherapy, TLR9 agonist monotherapy, and combination therapy of STING and TLR9 agonist. (Tailor-made therapy using CDN biomarkers) Here, we demonstrate the possibility of tailor-made therapy, or companion therapy, using CDN biomarkers. (1) Measure fecal and systemic CDN levels before and after antibiotic treatment, tumor inoculation, and therapeutic intervention. (2) Elevated 3'3'-cGAMP (bacterial origin) levels may be a useful biomarker for individualizing cancer treatment. (3) In patients with elevated bacterial CDN levels, TLR9 agonists alone may be sufficient, as endogenous STING agonists may already be activating the STING pathway. (4) In patients with low CDN levels, combination therapy using both STING agonists and TLR9 agonists may be necessary to induce an optimal antitumor response. (Discussion) These findings suggest that CDN profiling can guide personalized cancer treatment and potentially identify patients who would benefit from it, as described below. • Modification of the microbiome to optimize treatment (e.g., probiotics or antibiotics) • Personalized immunotherapy approaches (e.g., STING or TLR9 agonists, alone or in combination)

[0260] (Example 6: Companion therapy for allergic and inflammatory diseases (asthma, COPD, etc.)) The main points regarding asthma, an allergic disease, and chronic obstructive pulmonary disease (COPD), a chronic inflammatory lung disease, are summarized below.

[0261] A significant but weak correlation was observed between serum CDN levels and asthma disease parameters (e.g., 3'3'-cGAMP vs. neutrophil % and IL-1RA levels).

[0262] Asthma patients have significantly higher serum c-di-AMP, c-di-GMP, 3'3'-cGAMP, 3'2'-cGAMP, and 2'3'-cGAMP levels compared to healthy controls.

[0263] 3'3'-cGAMP (bacterial origin) showed a significant positive correlation with eotaxin, rantes, MIP-1β, and IL-9 in COPD. 2'3'-cGAMP (host origin) also showed a significant positive correlation with rantes, MIP-1β, and IL-9 in COPD.

[0264] Based on these results, administering appropriate medications for asthma and COPD can enable early initiation or prevention of treatment in the host.

[0265] (Discussion) Companion therapy for asthma and chronic obstructive pulmonary disease using CDN biomarkers

[0266] (Summary) This approach leverages CDN biomarkers to personalize the treatment of asthma, allergies, and chronic obstructive pulmonary disease, optimizing treatment based on individual immune and microbial profiles. Key biomarkers and their significance: Host-derived CDN (e.g., 2'3'-cGAMP) Elevated levels of this CDN indicate increased activation of the cGAS-STING pathway, reflecting potential immune dysfunction and exacerbation of inflammatory diseases. Targeted therapy: Use cGAS-STING inhibitors to mitigate hyperactivation. Microbial-derived CDN (e.g., 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, c-di-GMP): (1) Elevated levels suggest a microbial imbalance contributing to systemic inflammation or disease-specific immune responses. (2) Targeted therapy: Microbiota modulating interventions to restore microbial balance (e.g., antibiotics, probiotics).

[0267] (Disease) A. Asthma: A-1) Biomarker: 3'3'-cGAMP correlates with serum neutrophil percentage and IL-1RA level. A-2) Calculation method: Asthma biomarker index = [3'3'-cGAMP] × (neutrophil % + IL-1RA). A-3) Implications for treatment: Elevated bacterial CDN levels indicate the need for microbiome-targeted therapy to reduce airway inflammation. Host-derived CDN elevation may benefit from STING pathway inhibitors.

[0268] B. Chronic Obstructive Pulmonary Disease (COPD): Biomarkers: B-1) Host-derived 2'3'-cGAMP correlates with RANTES, MIP-1β, and IL-9. B-2) Microbial-derived 3'3'-cGAMP correlates with eotaxin, RANTES, MIP-1β, and IL-9. B-3) Calculation method: B-3-1) COPD biomarker index = ([2'3'-cGAMP] + [3'3'-cGAMP]) × (RANTES + MIP-1β + IL-9). B-4) Therapeutic implications: B-4-1) Treatment targeting microbiome abnormalities for increased microbial-derived CDN (e.g., antibiotics, probiotics). B-4-2) Anti-inflammatory intervention targeting hyperactivation of the STING pathway for host-derived CDN.

[0269] C. Allergies: C-1) Biomarkers: Similar CDN and cytokine profiles are helpful in managing allergic diseases. C-2) Therapeutic implications: C-2-1) In Th2-dominant inflammation (e.g., allergic asthma), TLR9 agonists may redirect the immune response towards Th1 immunity. Proposed methods: C-3) Measurement: C-3-1) Quantify CDNs (e.g., 2'3'-cGAMP, 3'3'-cGAMP) and related cytokines (e.g., RANTES, IL-9) using the ELISA assay. C-4) Diagnosis: C-4-1) Measure CDN levels compared to thresholds obtained from healthy controls to identify microbiome disruption or overactivation of the cGAS-STING pathway. C-5) Therapeutic adjustments: (1) If bacterial CDN levels are high: Normalize the microbiome with antibiotics or probiotics. (2) If host CDN levels are high: Use a STING inhibitor to suppress the overactivation of cGAS-STING. (3) In the case of allergic symptoms: Use a TLR9 agonist in combination to shift the immune balance toward Th1.

[0270] (Summary) This combination therapy strategy uses CDN profiling to derive individualized treatment plans for asthma and COPD. This approach ensures: • Modulation and restoration of microbiome disturbances. • Precise immunomodulation targeting the STING or TLR9 pathway. • Improved clinical outcomes through individualized interventions.

[0271] (Example 6) Predictive models for asthma and COPD In this example, predictive models for asthma and COPD were developed.

[0272] (Materials and Methods) Measurement of serum CDNs, cytokines, and clinical parameters Serum cyclic dinucleotides (CDNs) including 3'3'cGAMP, 2'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP were quantified using ELISA. Serum cytokine and chemokine levels were measured using a multiplex Bio-Plex assay panel consisting of 27 cytokines and chemokines. Clinical parameters, including blood neutrophil ratios, were obtained from Biobank Japan (BBJ).

[0273] In the analyses shown in correlation analysis figures 21 and 22, the correlation between serum CDN levels and inflammatory or immunological parameters was evaluated using appropriate correlation analysis methods according to the methods described in the brief descriptions of the figures. Statistical significance was determined according to the criteria described in the descriptions of the figures.

[0274] To evaluate the diagnostic and predictive potential of serum CDN profiles using machine learning-based classification analysis, we performed machine learning-based classification analysis using the Support Vector Machine (SVM) algorithm. The same SVM model architecture was applied to all analyses. Model performance was evaluated using receiver operating characteristic (ROC) curve analysis, and classification accuracy was quantified by calculating the area under the ROC curve (AUC).

[0275] Regarding the feature set used for SVM analysis (Figure 23), the SVM model was trained using serum CDN measurements as input features for the following classifications: • Healthy controls vs. asthma patients • Asthma vs. non-asthma subjects • COPD vs. non-COPD subjects

[0276] Regarding Figure 24, the prediction performance was compared by keeping the SVM model constant and changing the input feature set as follows: 1. Serum CDN measurement values ​​only (5 types of CDNs) 2. Bio-Plex cytokine / chemokine data only (27 types of analytes) 3. Combined feature set consisting of serum CDN and Bio-Plex cytokine / chemokine data (5 types of CDNs + 27 types of analytes)

[0277] Figure 23 shows the results: Receiver operating characteristic (ROC) curve analysis was performed to show the diagnostic performance of a support vector machine (SVM)-based classifier using serum CDN profiles to predict asthma and COPD. (A) ROC curves comparing healthy controls vs. asthma patients, asthma vs. non-asthma subjects, and COPD vs. non-COPD subjects, generated using the same SVM model trained on serum CDN measurements. (B) A summary of classification performance expressed as the area under the ROC curve (AUC) for each comparison. The SVM-based analysis showed robust differentiation between healthy controls and asthma patients based on serum CDN levels, while the classification accuracy for COPD was relatively low.

[0278] Figure 24: Feature-dependent performance of SVM models in CDN-based asthma prediction. The prediction performance of SVM models using different input feature sets was compared. (A) AUC value obtained when only serum CDN measurements of five types of CDNs were used as input parameters. (B) AUC value obtained when only Bioplex cytokine data of 27 types of cytokines / chemokines were used as input parameters. (C) AUC value obtained when a combined feature set (5 types of CDNs + 27 types of cytokines / chemokines) including both serum CDN measurements and Bioplex cytokine data was used as input parameters.

[0279] These results demonstrate that changing input parameters while keeping the classification model constant affects predictive performance in a disease-dependent manner. For asthma, the best predictive performance was obtained when using only serum CDN measurements as input features, while for COPD, superior discriminative ability was achieved when using only cytokine and chemokine data obtained from Bio-Plex analysis.

[0280] Discussion: In the results presented earlier (Figures 21 and 22), simple correlation analysis showed that serum levels of the cyclic dinucleotide 3'3'cGAMP were significantly associated with inflammatory markers and immune cell parameters in asthma patients. While these findings indicate that serum CDNs reflect disease-related immune and inflammatory states, they do not in themselves establish diagnostic capabilities. Therefore, to further evaluate the diagnostic usefulness of serum CDN profiles, multivariate machine learning analysis using a support vector machine (SVM) model was performed (Figures 23 and 24). In this regard, it is suggested that the linear correlation between a single cyclic dinucleotide and immunological or inflammatory parameters exhibits different patterns depending on the disease. Specifically, in COPD, a relatively strong linear correlation is observed between specific CDNs and immunological indicators, while in asthma, multivariate feature patterns based on combinations of multiple CDN measurements may have higher informational value in disease identification than single CDN levels.

[0281] As shown in Figure 23, SVM-based classification using serum CDN measurements enabled robust differentiation between healthy controls and asthma patients, as indicated by high AUC values. In contrast, the classification performance for COPD was relatively low, suggesting that serum CDN profiles may be more strongly associated with immunological features related to asthma than to COPD.

[0282] Importantly, the SVM model architecture remained constant across all analyses, indicating that differences in predictive performance were due to input data rather than changes in the classification algorithm. Figure 24 further demonstrates that predictive performance depends on the type of biological features used as input parameters, and that the optimal feature set differs depending on the disease context. When the same support vector machine (SVM) model was applied to different input feature sets, only serum CDN measurements yielded the best ROC-AUC values ​​in predicting asthma. In contrast, for COPD, classification performance was higher when cytokine and chemokine data obtained by Bio-Plex analysis were used as input features compared to serum CDN data alone.

[0283] These findings suggest that while serum CDN profiles capture particularly valuable disease-related information in asthma, inflammatory cytokine and chemokine profiles may better reflect pathological features associated with COPD. Importantly, these differences were observed while keeping the classification model constant, indicating that disease-specific predictive performance stems from the biological properties of the input features, rather than differences in machine learning algorithms.

[0284] Based on the above, the results in Figures 23 and 24 suggest that serum CDN is a distinct class of biomarkers with strong diagnostic or predictive value for asthma, while alternative or complementary sets of biomarkers may be more suitable for COPD. This feature-dependent performance supports the use of a combination of biomarkers tailored for disease-specific prediction rather than a uniform diagnostic approach.

[0285] (Note) As described above, the present disclosure has been illustrated using preferred embodiments thereof, but it is understood that the scope of the present disclosure should be interpreted solely by the claims. Patents, patent applications and other documents cited herein should be incorporated into this specification as if their contents were specifically described herein. This application claims priority to Japanese Patent Application No. 2025-011753, filed with the Japan Patent Office on January 27, 2025, and the entirety of its specification and other documents should be incorporated into this specification as if their contents were specifically described herein.

[0286] This disclosure provides a novel therapeutic or preventive agent.

[0287] Sequence ID 1: Forward primer that recognizes the sequence of exon 5 of Tmem173 (STING) Sequence ID 2: WT reverse primer Sequence ID 3: STING N153S reverse primer

Claims

1. A method for detecting or determining the physical condition of a subject, comprising: A) measuring cyclic dinucleotides (CDNs) present in the subject or obtaining information on their presence or level; B) determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be present in the subject; and C) diagnosing or providing diagnostic support for STING-related diseases or conditions based on the results of the determination.

2. The method according to claim 1, wherein the STING-related disease or condition is an allergic or inflammatory disease (aseptic inflammatory disease), an autoimmune disease, or cancer, or a condition related thereto.

3. The method according to claim 1 or 2, wherein the STING-related disease or condition is an allergic or inflammatory disease (aseptic inflammatory disease), and the allergic or inflammatory disease (aseptic inflammatory disease) is asthma, hay fever, or chronic obstructive pulmonary disease (COPD).

4. The method according to any one of claims 1 to 3, wherein the STING-related disease or condition is (A) an allergic or inflammatory disease (aseptic inflammatory disease), and the allergic or inflammatory disease (aseptic inflammatory disease) is asthma, hay fever, or chronic obstructive pulmonary disease (COPD), or (B) an autoimmune disease, and the autoimmune disease is STING-associated vasculopathy with onset in infancy (SAVI), Ecardi-Goutieres syndrome (AGS), or systemic lupus erythematosus (SLE).

5. The method according to any one of claims 1 to 4, wherein the STING-related disease or condition is cancer.

6. The method according to any one of claims 1 to 4, wherein the STING-related disease or condition is asthma and / or COPD.

7. The method according to any one of claims 1 to 4, which enables differential diagnosis between asthma and chronic obstructive pulmonary disease (COPD), differential diagnosis between asthma patients and healthy controls, or differential diagnosis between asthma subjects and non-asthma subjects.

8. The method according to any one of claims 1 to 7, further comprising the step of performing the diagnosis or diagnostic support by using the level of the cyclic dinucleotide as an input feature to a classification model using a machine learning algorithm.

9. The method according to claim 8, wherein the input feature includes serum CDN measurement values.

10. The method according to any one of claims 1 to 9, wherein the CDN comprises at least one of 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP.

11. The method according to any one of claims 1 to 10, wherein if the CDN includes 2'3'-cGAMP, the CDN is determined to originate from the subject.

12. The method according to any one of claims 1 to 11, wherein if the CDN contains at least one of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP, the CDN is determined to be derived from the microorganism.

13. The method according to any one of claims 1 to 12, wherein the determination is made based on an individual comparison of (A) the amount or level of 2'3'-cGAMP with (B) one or more of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP.

14. The method according to any one of claims 1 to 13, wherein the CDN is measured or information obtained in the body fluid of the subject.

15. The method according to claim 14, wherein the body fluid comprises at least one selected from the group consisting of serum, plasma, sweat, urine, intestinal extracts, and feces.

16. The method according to any one of claims 1 to 15, wherein the diagnosis comprises identifying a significant deviation indicating at least one selected from the group consisting of dysbiosis, leaky gut, and increased cGAS-STING pathway activity.

17. The method according to any one of claims 1 to 16, wherein the measurement is performed by an ELISA assay.

18. The method according to any one of claims 1 to 17, wherein the determination is made by comparing with a healthy control or by comparing with a previously established threshold for a healthy control.

19. The method according to any one of claims 1 to 18, wherein, in cases where the level of the microbial CDN is high, it is necessary to normalize the patient's microbiome by at least one intervention selected from the group consisting of antibiotics and probiotics.

20. The method according to any one of claims 1 to 19, wherein when the 2'3'-cGAMP level increases, cGAS activity is enhanced.

21. A method for treating or preventing a physical condition of a subject, comprising: 1) determining the physical condition of the subject by the method described in any one of claims 1 to 20; and 2) achieving treatment or prevention by taking appropriate measures for the subject according to the determination result.

22. A detection or determination agent for the physical condition of a subject, comprising a detection agent for measuring cyclic dinucleotides (CDNs), wherein it is determined whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject, and a STING-related disease or condition is diagnosed based on the result of the determination.

23. The agent according to claim 22, further comprising one or more features described in any one or more of claims 1 to 20.

24. A device for detecting or determining the physical condition of a subject, comprising: an element for measuring cyclic dinucleotides (CDNs); and a determination element for determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject, wherein a STING-related disease or condition is diagnosed based on the result of the determination.

25. The device according to claim 24, further comprising one or more features described in any one or more of claims 1 to 20.

26. A kit for detecting or determining the physical condition of a subject, comprising a detection agent or element for measuring cyclic dinucleotides (CDNs), and instructions, wherein the instructions explain that it is determined whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject, and that STING-related diseases or conditions are diagnosed based on the results of the determination.

27. The kit according to claim 26, further comprising one or more features described in any one or more of claims 1 to 20.

28. A pharmaceutical composition for treating or preventing a physical condition of a subject, wherein a cyclic dinucleotide (CDN) is measured, it is determined whether the CDN originates from the subject and / or from microorganisms (parasites) expected to be contained in the subject, a STING-related disease or condition is diagnosed based on the result of the determination, and the pharmaceutical composition comprises a therapeutic or preventive agent determined to be suitable for the subject according to the result of the diagnosis.

29. The pharmaceutical composition according to claim 28, further comprising one or more features described in any one or more of claims 1 to 20.

30. A device for treating or preventing a physical condition of a subject, comprising: an element for measuring cyclic dinucleotides (CDNs); and a determination element for determining whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject, wherein a STING-related disease or condition is diagnosed based on the result of the determination, and an appropriate therapeutic or preventive agent is set for the subject according to the result of the diagnosis.

31. The device according to claim 30, further comprising one or more features described in any one or more of claims 1 to 20.

32. A kit for treating or preventing a physical condition of a subject, comprising a detection agent or element for measuring cyclic dinucleotides (CDNs), and instructions, wherein the instructions explain that it is determined whether the CDNs originate from the subject and / or from microorganisms (parasites) expected to be contained in the subject, that a STING-related disease or condition is diagnosed based on the result of the determination, and that an appropriate therapeutic or preventive agent is set for the subject according to the result of the diagnosis.

33. The kit according to claim 32, further comprising one or more features described in any one or more of claims 1 to 20.

34. Use of cyclic dinucleotide (CDN) levels measured in samples taken from subjects as markers for diagnosing the physical condition of subjects.

35. A system for assessing the physical condition of a subject, comprising means for measuring the level of cyclic dinucleotides (CDNs) in a sample taken from a subject, and configured to assess asthma based on the level.

36. The system according to claim 35, further comprising a physical condition evaluation unit that evaluates the physical condition of the subject by using the level of a cyclic dinucleotide as an input feature to a classification model using a machine learning algorithm.

37. Use of cyclic dinucleotides (CDNs) measured in samples taken from subjects as diagnostic markers for STING-related diseases or conditions.

38. The use according to claim 37, wherein the CDN is at least one selected from the group consisting of 2'3'-cGAMP, 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP, and the STING-related disease or condition is selected from the group consisting of asthma, chronic obstructive pulmonary disease (COPD), hay fever, STING-associated vasculopathy with onset in infancy (SAVI), Ecardi-Goutier syndrome (AGS), systemic lupus erythematosus (SLE), and cancer.

39. Use of a detection agent for cyclic dinucleotides (CDNs) for the manufacture of diagnostic reagents for diagnosing STING-related diseases or conditions.

40. A system for evaluating the physical condition of a subject, comprising: an acquisition unit for acquiring the level of cyclic dinucleotides (CDNs) in a sample taken from a subject; a determination unit for determining whether the CDNs originate from the subject and / or from microorganisms expected to be contained in the subject; and a diagnosis unit for diagnosing or supporting the diagnosis of STING-related diseases or conditions based on the determination result of the determination unit.

41. The system according to claim 40, wherein the diagnostic unit is configured to use the level of the cyclic dinucleotide as an input feature to a classification model using a machine learning algorithm to differentiate between asthma and chronic obstructive pulmonary disease (COPD), distinguish between asthmatic subjects and non-asthmatic subjects, or calculate whether or not there is a need for microbiome normalization.

42. The system according to claim 40 or 41, wherein the determination unit is configured to determine the contribution from the target based on the level of 2'3'-cGAMP, and to determine the contribution from the microorganism based on the level of at least one of 3'3'-cGAMP, 3'2'-cGAMP, c-di-AMP, and c-di-GMP.

43. A program for diagnosing or assisting in the diagnosis of a subject's physical condition, which causes a computer to perform the following steps: receiving data as input regarding the level of cyclic dinucleotides (CDNs) measured in a sample taken from a subject; determining, based on the data, whether the CDNs originate from the subject or from microorganisms; and outputting a diagnostic result regarding STING-related diseases or conditions using a classification model based on the result of the determination.

44. The program according to claim 43, wherein the classification model is constructed by a machine learning algorithm including a support vector machine (SVM), and the output step includes outputting to a display device the result of distinguishing between an asthma patient and a healthy control, or the result of differentiating between asthma and chronic obstructive pulmonary disease (COPD).

45. The program according to claim 43 or 44, wherein, in the determination step, the computer is instructed to perform a process to identify enhanced cGAS activity when the level of 2'3'-cGAMP exceeds a threshold, and to identify the presence of dysbiosis or leaky gut when the level of microbial-derived CDN exceeds a threshold.

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