A marker for diagnosing systemic inflammation and use thereof

Abstract

The application provides a marker for diagnosing systemic inflammation and application, the marker comprises ADGRE3 mRNA or ADGRE3 protein, or ADGRE3 mRNA fragment, ADGRE3 protein fragment, and the content of the marker in the sample of a systemic inflammation patient and a healthy person is significantly different, and the sensitivity and specificity of the marker diagnosis are verified in clinic, therefore, by detecting the transcription level of ADGRE3 mRNA or the expression level of ADGRE3 protein in the sample of an individual, systemic inflammation can be accurately diagnosed. Compared with existing inflammation markers, ADGRE3 mRNA and ADGRE3 protein have higher sensitivity and specificity in the diagnosis of systemic inflammation.

Description

[0001] This invention is a divisional application of parent application 202410614751.6. Technical Field

[0002] This invention relates to a disease diagnostic reagent and method, specifically, to a biomarker for diagnosing systemic inflammation and its application. Background Technology

[0003] The following background information is merely a general overview and does not constitute any limitation on the present invention.

[0004] Systemic inflammation (SIP) is a nonspecific inflammatory response involving the entire body, typically caused by infection, autoimmune diseases, injury, or other pathological conditions. This inflammatory response can lead to multiple organ dysfunction and, in severe cases, even death. Therefore, timely and accurate diagnosis of SIP is crucial for guiding treatment and improving patient prognosis. In recent years, biomarkers have played an important role in the diagnosis of SIP, providing vital information about the inflammatory status, disease severity, and treatment response.

[0005] Systemic inflammation is a protective response of the body to stimuli, involving immune cells, blood vessels, and various molecular mediators. During systemic inflammation, upon exposure to inflammatory stimuli, immune cells such as monocytes / macrophages, neutrophils, and lymphocytes become activated, releasing large amounts of cytokines (such as IL-6, IL-1β, TNF-α, and IFN-γ) that affect the synthesis of acute-phase reactants (APRs), thereby altering their concentrations in plasma. These changes in cytokines and APRs reflect the body's response to inflammation and are currently important indicators for the diagnosis and monitoring of systemic inflammation.

[0006] C-reactive protein (CRP) is one of the acute-phase reactive proteins derived from the liver and is one of the most widely used indicators for assessing inflammation in clinical practice. When there is acute inflammation in the body, CRP begins to rise within 6-8 hours, with peak values ​​hundreds of times higher than normal, and then quickly disappears after the disease is cured. The magnitude of CRP elevation is positively correlated with the degree of inflammation, allowing for timely warnings of complications and assessment of treatment effectiveness. Interleukin-6 (IL-6) is a key component of the cytokine network induced by IL-1 and TNF-α, and a major signaling molecule mediating the acute-phase response, inducing the body to produce APRs such as CRP, SAA, and PCT. Elevated IL-6 levels are closely related to the progression of inflammation, especially in inflammation caused by systemic infections such as sepsis. Tumor necrosis factor-α (TNF-α) plays a crucial role in initiating the cytokine storm response; its rapid increase reflects the acute phase of inflammation. Inhibitors targeting TNF-α have achieved varying degrees of success in treating inflammatory diseases such as rheumatoid arthritis, ankylosing spondylitis, and inflammatory bowel disease. Erythrocyte sedimentation rate (ESR) is a traditional inflammatory marker, and its increase is usually associated with increased fibrinogen. Although ESR has poor specificity, it still has some value in auxiliary reference for the diagnosis of inflammatory diseases. Procalcitonin (PCT) is another important inflammatory marker, especially in systemic inflammation caused by bacterial infections, where PCT levels are significantly elevated. PCT measurement has important clinical value in differentiating between bacterial and viral infections.

[0007] Measuring biomarkers such as CRP, IL-6, TNF-α, ESR, and PCT can effectively assess the degree of inflammation, monitor disease progression, and treatment response. However, these biomarkers only have diagnostic and monitoring effects on inflammation and do not differentiate between local and systemic inflammation, resulting in poor specificity. Furthermore, the levels of these biomarkers do not differ significantly between patients with systemic inflammation and healthy individuals, leading to low sensitivity. Often, multiple indicators need to be combined with imaging studies to diagnose systemic inflammation.

[0008] Many viral infections can lead to systemic inflammatory responses, such as influenza virus, novel coronavirus, dengue virus, respiratory syncytial virus, cytomegalovirus, and Epstein-Barr virus. In the systemic inflammatory response caused by viral infection, the immune system releases various inflammatory mediators to activate immune cells, promoting viral clearance and tissue repair. However, current conventional biomarkers such as PCT, HBP, and nCD64 infection index do not show significant changes in viral infections, and CRP has low sensitivity. Therefore, clinically, there is a lack of effective biomarkers for the diagnosis and monitoring of the severity of systemic inflammatory responses caused by viral infections, in order to guide treatment adjustments and prognostic assessments.

[0009] Unlike localized inflammation, systemic inflammation is more severe and its diagnosis is more complex. Timely and accurate diagnosis of systemic inflammation is crucial for guiding treatment and improving patient prognosis. Therefore, it is necessary to develop a highly sensitive and specific biomarker for systemic inflammation to address the current shortcomings in clinical diagnosis of systemic inflammation. Summary of the Invention

[0010] To address the problems of conventional technologies, this invention provides a biomarker for diagnosing systemic inflammation and its application. The biomarker includes ADGRE3 mRNA or ADGRE3 mRNA fragments, and / or may include ADGRE3 protein or ADGRE3 protein fragments. By utilizing variations in a single type of biomarker, this invention enables the diagnosis, prediction, and monitoring of the severity of systemic inflammation in individuals, as well as guidance for specific treatment measures such as medication.

[0011] The research team discovered a highly significant difference in the levels of biomarkers between samples from patients with systemic inflammation and healthy individuals. Clinical trials have validated the diagnostic effectiveness of these biomarkers. Therefore, by detecting ADGRE3 mRNA or ADGRE3 protein in individual samples, these biomarkers, used alone, can be used to diagnose whether an individual has systemic inflammation, to diagnose the progression of non-systemic inflammation to systemic inflammation, and to assess the effectiveness of drug treatment for systemic inflammation. When used in combination with other biomarkers, they can also differentiate between systemic inflammation caused by viruses and bacteria.

[0012] The invention team discovered that ADGRE3 mRNA and / or ADGRE3 protein have higher sensitivity and specificity in diagnosing systemic inflammation compared to existing inflammatory markers.

[0013] High sensitivity has the following implications: First, in the same group of patients with systemic inflammation, significance analysis shows that ADGRE3 markers (ADGRE3 mRNA or ADGRE3 protein) decreased significantly, while other inflammatory markers showed little change. Alternatively, while other traditional inflammatory markers can diagnose systemic inflammation, the differences between healthy or locally inflammatory patients are not significant, and some may not show significant differences. However, the markers of this invention show significant or extremely significant differences in content between samples from healthy or locally inflammatory patients and patients with systemic inflammation. Second, in the same group of patients with systemic inflammation, the number of patients with extremely significant decreases in ADGRE3 markers is greater, while the number of patients with changes in other inflammatory markers is smaller. Therefore, using ADGRE3 markers can more accurately diagnose systemic inflammation and reduce the misdiagnosis rate.

[0014] The high specificity has the following implications: First, in a case set encompassing healthy individuals (without inflammation), patients with non-systemic inflammation (patients with localized or non-inflammatory diseases), and patients with systemic inflammation, the ADGRE3 marker can exclude patients with non-systemic inflammation, including those with localized inflammation—something existing inflammatory markers cannot do. Second, within patients with systemic inflammation, it can also specifically differentiate between different types of systemic inflammation. For example, the ADGRE3 marker can differentiate between bacterial and non-bacterial inflammation, aiding clinical treatment. Although, when differentiating between bacterial and viral infections, the marker of this invention needs to be combined with traditional bacterial markers, this does not negate the role and function of the marker of this invention in the above diagnostic process. Furthermore, significant differences exist between different types of systemic inflammation within patients with systemic inflammation; for example, there is a significant difference between patients with sepsis and those with non-infectious systemic inflammation. Therefore, it can be understood that this marker can be used to differentiate between sepsis and non-infectious systemic inflammation.

[0015] Therefore, in one aspect, the present invention provides the use of a biomarker for preparing a reagent for diagnosing systemic inflammation, said biomarker comprising ADGRE3 mRNA or ADGRE3 mRNA fragment; or ADGRE3 protein, or protein fragment, or corresponding amino acid sequence or peptide fragment.

[0016] The detection of ADGRE3 mRNA or ADGRE3 mRNA fragments, and the detection of ADGRE3 protein or ADGRE3 protein fragments described in this invention, refer to the detection of the level or content of ADGRE3 mRNA; the level or content of ADGRE3 protein refers to the content of ADGRE3 mRNA or ADGRE3 mRNA fragments and ADGRE3 protein or ADGRE3 protein fragments in the sample. In some methods, the level of ADGRE3 mRNA is determined by the copy number amplified by PCR, and the expression level of ADGRE3 protein is determined by the mean fluorescence intensity (MFI) measured by flow cytometry. In some methods, thresholds are set for the copy number of ADGRE3 mRNA and the MFI value of ADGRE3 protein to classify samples for the diagnosis or differentiation of systemic inflammation and related diseases. Of course, it is understood that any other method that can characterize the content of ADGRE3 protein or mRNA in a sample is acceptable, such as concentration, relative concentration, or comparison with normal levels in healthy human samples.

[0017] In some embodiments, this invention uses flow cytometry to detect the ADGRE3 protein content in neutrophils of healthy, non-inflammatory individuals. The mean fluorescence intensity (MFI) of ADGRE3 protein in each sample is calculated, and the average MFI of ADGRE3 protein in healthy individuals is obtained. Under the same conditions, the mean MFI of ADGRE3 protein in neutrophils of patients is detected. The patient's neutrophil ADGRE3 protein expression index (nADGRE3) is obtained by dividing the patient's neutrophil ADGRE3 protein MFI by the average MFI of ADGRE3 protein in healthy individuals, i.e., nADGRE3 = patient neutrophil ADGRE3 protein MFI / healthy control neutrophil ADGRE3 protein MFI. The samples are then classified by comparing nADGRE3 with a set threshold to diagnose or differentiate systemic inflammation and related diseases.

[0018] Calculating the neutrophil ADGRE3 protein expression index (nADGRE3) is just one way to set thresholds and classify samples for diagnosis. Combining ADGRE3 mRNA or ADGRE3 protein with any other known methods of threshold setting and sample classification can yield the same diagnostic results and are all within the scope of this invention.

[0019] In some methods, white blood cells include five types: lymphocytes, neutrophils, monocytes, eosinophils, and basophils. Neutrophils highly express ADGRE3 protein, while monocytes express ADGRE3 protein poorly. Therefore, neutrophils are mainly selected as samples for detecting ADGRE3 protein content. This allows any detection method to detect neutrophil protein separately. Monocytes also express ADGRE3 protein, and their expression level is correlated with that of neutrophils, thus also correlated with the occurrence of systemic inflammation. Therefore, monocytes can also be selected as samples. The distribution of mRNA is similar to that of protein, but mRNA detection cannot be further subdivided into neutrophils or monocytes. Therefore, the detection target is usually all white blood cells. However, this does not exclude the implementation method of detecting ADGRE3 mRNA content in any type of white blood cell (lymphocytes, neutrophils, monocytes, eosinophils, and basophils).

[0020] The samples used in this invention are not limited to neutrophils, monocytes, or leukocytes; they can be any sample, including or excluding neutrophils, monocytes, or leukocytes. Detecting the ADGRE3 mRNA transcription level in leukocytes, or the ADGRE3 protein level in neutrophils or monocytes, only limits the ADGRE3 mRNA or ADGRE3 protein to originating from neutrophils, monocytes, or leukocytes. ADGRE3 mRNA or ADGRE3 protein is not necessarily located on neutrophils, monocytes, or leukocytes; it may also exist in extracellular physiological environments such as blood and tissue fluid. The levels of ADGRE3 mRNA or ADGRE3 protein in physiological environments can also be used to diagnose systemic inflammation. Alternatively, rupturing neutrophils, monocytes, or leukocytes or using other methods to extract cellular substances can yield samples containing ADGRE3 mRNA and its fragments, or ADGRE3 protein and its fragments; such samples can also be used to diagnose systemic inflammation.

[0021] A fragment of ADGRE3 mRNA or ADGRE3 protein refers to any fragment of ADGRE3 mRNA or ADGRE3 protein that is naturally present in an individual's body.

[0022] Taking ADGRE3 protein as an example, ADGRE3 is a membrane protein distributed intracellularly, transmembraneally, and extracellularly within the cell membrane. Intracellularly, part of the protein is located inside the cell membrane, while extramembranely, part is located outside the cell membrane. Transmembranely, part of the protein is located inside the cell membrane, and another part is located outside. Therefore, the transmembrane portion (i.e., fragments of ADGRE3 protein) can be detected to determine the ADGRE3 protein content. Alternatively, in some methods, cells can be ruptured to extract the membrane protein for testing. In other methods, ADGRE3 protein can be enzymatically broken down into various fragments by enzymes, either in vivo or in vitro. Detecting these fragments, or any single fragment, can also determine the ADGRE3 protein content, thus aiding in the diagnosis of systemic inflammation.

[0023] The levels of ADGRE3 mRNA or ADGRE3 protein in a sample can be used to diagnose systemic inflammation, and the mRNA and protein fragments share homology with the overall nucleotide sequence of the mRNA and the overall amino acid sequence of the protein. Therefore, theoretically, detecting the levels of ADGRE3 mRNA or ADGRE3 protein fragments can also diagnose systemic inflammation.

[0024] In some methods, the reagents used to diagnose systemic inflammation are used to detect ADGRE3 mRNA or ADGRE3 mRNA fragments in individual leukocytes.

[0025] In some methods, the reagent for diagnosing systemic inflammation is used to detect ADGRE3 mRNA or ADGRE3 mRNA fragments in an individual sample; the sample includes any one or more of peripheral blood, urine, secretions, pus, body fluids, spinal cord, and fresh tissue.

[0026] Leukocytes are present in various tissues and body fluids of the human body. In healthy individuals, they are mainly distributed in peripheral blood, but also in urine, secretions, pus, body fluids, spinal cord, and fresh tissues. In patients with systemic inflammation, leukocytes infiltrate inflamed tissues. Therefore, leukocytes can be detected in various types of clinical samples. Any sample containing leukocytes or intraleukocyte substances (intraleukocyte substances refer to substances originally derived from leukocytes) can be used as a sample for diagnosing systemic inflammation by detecting ADGRE3 mRNA or ADGRE3 mRNA fragments.

[0027] In some embodiments, the systemic inflammation includes infectious systemic inflammation or non-infectious systemic inflammation.

[0028] In some cases, the infectious systemic inflammation includes any one or more of bacterial, viral, fungal, and parasitic infections. Systemic inflammation can result from any of these infections.

[0029] In some embodiments, the viral infection includes any one of influenza virus infection, dengue virus infection, novel coronavirus infection, respiratory syncytial virus, cytomegalovirus, Epstein virus, or Bunyavirus infection. The aforementioned viral infections are typical examples of viral infections that cause systemic inflammation. In addition to the systemic inflammation caused by influenza virus infection, dengue virus infection, novel coronavirus infection, respiratory syncytial virus, cytomegalovirus, EB virus, and new Bunyavirus infection, systemic inflammation caused by other viral infections can also be diagnosed by detecting ADGRE3 mRNA or ADGRE3 mRNA fragments, ADGRE3 protein or ADGRE3 protein fragments discovered in this invention.

[0030] In some embodiments, the non-infectious inflammation includes any one or more of the following: autoimmune diseases, transplant rejection, inflammatory bowel disease, allergic reactions, metabolic diseases, and inflammation caused by tissue damage.

[0031] In some embodiments, the autoimmune disease includes any one or more of systemic lupus erythematosus, rheumatoid arthritis, vasculitis, and ankylosing spondylitis.

[0032] In some approaches, the systemic inflammation caused by transplant organ rejection includes systemic inflammation caused by any one or more of bone marrow transplantation, kidney transplantation, and liver transplantation.

[0033] In addition to inflammation (systemic inflammation) caused by bone marrow transplantation, kidney transplantation, and liver transplantation, inflammation caused by rejection reactions of other transplanted organs can also be diagnosed by detecting ADGRE3 mRNA or ADGRE3 mRNA fragments, ADGRE3 protein or ADGRE3 protein fragments discovered in this invention.

[0034] In some cases, the systemic inflammation includes sepsis.

[0035] In some embodiments, the sepsis is caused by any one or more of the following infections: pulmonary infection, biliary tract infection, urinary tract infection, gastrointestinal tract infection, bloodstream infection, reproductive tract infection, abdominal infection, central nervous system infection, skin and soft tissue infection, and purulent osteomyelitis.

[0036] In addition to sepsis caused by the above-mentioned lesions, sepsis caused by any other lesions can be diagnosed by detecting ADGRE3 mRNA or ADGRE3 mRNA fragments, ADGRE3 protein or ADGRE3 protein fragments discovered in this invention.

[0037] A second aspect of the present invention provides the use of a biomarker for preparing a reagent for diagnosing whether an individual suffers from systemic inflammation caused by a bacterial infection or a viral infection, said biomarker comprising ADGRE3 mRNA or an ADGRE3 mRNA fragment; or, ADGRE3 protein or an ADGRE3 protein fragment.

[0038] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to differentiate between individuals suffering from systemic inflammation due to Gram-positive bacterial infection or systemic inflammation due to H1N1 infection, said biomarker comprising ADGRE3 mRNA or an ADGRE3 mRNA fragment; or, ADGRE3 protein or an ADGRE3 protein fragment.

[0039] Gram-positive bacterial infections and H1N1 infections can present with similar clinical symptoms. Treatment of systemic inflammation requires identifying the location and type of lesions. Therefore, ADGRE3 mRNA or ADGRE3 protein can be used to differentiate between Gram-positive bacterial infections and H1N1 infections, thereby enabling targeted treatment of systemic inflammation.

[0040] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to diagnose whether an individual has systemic dengue inflammation, said biomarker comprising ADGRE3 mRNA or an ADGRE3 mRNA fragment; or, ADGRE3 protein or an ADGRE3 protein fragment.

[0041] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to diagnose whether an individual has systemic inflammation caused by COVID-19 infection, said biomarker comprising ADGRE3 mRNA or an ADGRE3 mRNA fragment; or, ADGRE3 protein or an ADGRE3 protein fragment.

[0042] Furthermore, the diagnosis of whether an individual has systemic inflammation caused by COVID-19 infection includes diagnosing patients with systemic inflammation caused by asymptomatic COVID-19 infection, or diagnosing patients with systemic inflammation caused by symptomatic COVID-19 infection.

[0043] In some cases, a portion of COVID-19 infections are asymptomatic, meaning they do not exhibit clinical symptoms of COVID-19 infection, making them difficult to detect clinically. Patients with systemic inflammation are very likely to also have asymptomatic COVID-19 infection. According to publicly available data from the WHO, COVID-19 can also cause or exacerbate systemic inflammation, thus requiring diagnosis of asymptomatic COVID-19 infection. However, such detection indicators are currently lacking in clinical practice. The ADGRE3 mRNA or ADGRE3 protein proposed in this invention can be used to diagnose asymptomatic COVID-19 infections.

[0044] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to diagnose whether an individual has systemic inflammation due to respiratory syncytial virus infection, said biomarker comprising ADGRE3 mRNA or an ADGRE3 mRNA fragment; or, ADGRE3 protein or an ADGRE3 protein fragment.

[0045] Furthermore, the diagnosis of whether an individual has systemic inflammation due to respiratory syncytial virus infection includes: diagnosing whether the individual has experienced acute respiratory syncytial virus infection (a type of systemic inflammation), or diagnosing whether the individual has recovered from systemic inflammation due to respiratory syncytial virus infection.

[0046] The ADGRE3 mRNA transcription levels showed highly significant differences in samples from patients with acute respiratory syncytial virus (RSV) infection and those recovering from systemic inflammation caused by RSV infection. Therefore, detecting ADGRE3 mRNA can monitor changes in individual RSV infection and provide data support for clinical treatment.

[0047] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to diagnose whether an individual has systemic inflammation caused by cytomegalovirus infection, said biomarker comprising ADGRE3 mRNA or an ADGRE3 mRNA fragment; or, ADGRE3 protein or an ADGRE3 protein fragment.

[0048] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to diagnose whether an individual has systemic inflammation caused by Epstein-Barr virus infection, said biomarker comprising ADGRE3 mRNA or an ADGRE3 mRNA fragment; or, ADGRE3 protein or an ADGRE3 protein fragment.

[0049] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to differentiate an individual as one of a healthy person, a patient with non-infectious systemic inflammatory response syndrome, or a patient with sepsis, said biomarker comprising ADGRE3 mRNA or an ADGRE3 mRNA fragment; ADGRE3 protein or an ADGRE3 protein fragment.

[0050] Significant differences were found in the leukocyte ADGRE3 mRNA transcription levels among healthy individuals, patients with non-infectious systemic inflammatory response syndrome (SIRS), and patients with sepsis; specifically, the levels decreased sequentially. This invention clinically validated the diagnostic efficacy against these three groups. The diagnostic AUC value distinguishing between healthy individuals and sepsis patients was 0.920, the diagnostic AUC value distinguishing between sepsis and non-infectious SIRS was 0.864, and the diagnostic AUC value for sepsis from the entire sample set was 0.862. This demonstrates that ADGRE3 mRNA can accurately diagnose non-infectious SIRS and sepsis. Similarly, tests for ADGRE3 protein or ADGRE3 protein fragments yielded similar results.

[0051] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to differentiate whether an individual has bacterial systemic inflammation, said biomarker comprising ADGRE3 mRNA or an ADGRE3 mRNA fragment.

[0052] A third aspect of the present invention provides a method for diagnosing whether an individual has systemic inflammation, the method comprising: providing a test sample; detecting the content of ADGRE3 mRNA or ADGRE3 mRNA fragments in the sample; or the content of ADGRE3 protein or ADGRE3 protein fragments; comparing the tested content with a preset threshold, and diagnosing the individual as not having systemic inflammation if the content is greater than or equal to the threshold, and diagnosing the individual as having systemic inflammation if the content is less than the threshold.

[0053] In some methods, the ADGRE3 mRNA or ADGRE3 mRNA fragment content in the test sample is the ADGRE3 mRNA or ADGRE3 mRNA fragment content in the leukocytes of the individual sample being tested, or the ADGRE3 protein or ADGRE3 protein fragment content.

[0054] In some methods, the sample includes any one or more of peripheral blood, urine, secretions, pus, body fluids, spinal cord, and fresh tissue.

[0055] In some embodiments, the systemic inflammation includes infectious systemic inflammation or non-infectious systemic inflammation.

[0056] In some embodiments, the infectious systemic inflammation includes systemic inflammation caused by any one or more of bacterial, viral, fungal, and parasitic infections.

[0057] In some embodiments, the viral infection includes any one or more of the following: influenza virus infection, dengue virus infection, novel coronavirus infection, respiratory syncytial virus, cytomegalovirus, EB virus, and novel Bunyavirus infection.

[0058] In some embodiments, the non-infectious systemic inflammation includes systemic inflammation caused by one or more of the following: autoimmune diseases, transplant rejection, inflammatory bowel disease, allergic reactions, metabolic diseases, and inflammation caused by tissue damage.

[0059] In some embodiments, the autoimmune disease includes any one or more of systemic lupus erythematosus, rheumatoid arthritis, vasculitis, and ankylosing spondylitis.

[0060] In some approaches, the systemic inflammation caused by transplant organ rejection includes systemic inflammation caused by any one or more of bone marrow transplantation, kidney transplantation, and liver transplantation.

[0061] In some cases, the systemic inflammation includes sepsis.

[0062] In some embodiments, the present invention provides a method for diagnosing whether an individual suffers from systemic inflammation caused by a bacterial or viral infection, the method comprising: providing a sample for testing; detecting the content of ADGRE3 mRNA or ADGRE3 mRNA fragments, or ADGRE3 protein or ADGRE3 protein fragments in the sample; comparing the tested content with a pre-set threshold, and diagnosing the individual as not suffering from systemic inflammation caused by a bacterial or viral infection if the content is greater than or equal to the threshold, and diagnosing the individual as suffering from systemic inflammation caused by a bacterial or viral infection if the content is less than the threshold.

[0063] In some embodiments, the present invention provides a method for diagnosing whether an individual suffers from systemic inflammation due to Gram-positive bacterial infection or systemic inflammation due to H1N1 infection, the method comprising: providing a sample for testing; detecting the content of ADGRE3 mRNA or ADGRE3 mRNA fragment in the sample; or the content of ADGRE3 protein or ADGRE3 protein fragment; comparing the tested content with a pre-set threshold, and diagnosing the individual as not suffering from systemic inflammation due to Gram-positive bacterial infection or systemic inflammation due to H1N1 infection if the content is greater than or equal to the threshold, and diagnosing the individual as suffering from systemic inflammation due to Gram-positive bacterial infection or systemic inflammation due to H1N1 infection if the content is less than the threshold.

[0064] On the other hand, the present invention provides a method for differentiating between Gram-positive bacterial infection and H1N1 infection in patients with systemic inflammation. The method includes: providing a test sample; detecting the content of ADGRE3 mRNA or ADGRE3 mRNA fragment, or the content of ADGRE3 protein or ADGRE3 protein fragment in the sample; comparing the tested content with a pre-set threshold, and diagnosing the patient as having Gram-positive bacterial infection if the content is greater than the threshold, and diagnosing the patient as having H1N1 infection if the content is less than the threshold.

[0065] On the other hand, the present invention provides a method for diagnosing whether an individual has dengue fever systemic inflammation, the method comprising: providing a test sample, detecting the content of ADGRE3 mRNA or ADGRE3 mRNA fragment or ADGRE3 protein or ADGRE3 protein fragment in the sample; comparing the tested content with a pre-set threshold, and diagnosing the individual as not having dengue fever systemic inflammation if the content is greater than or equal to the threshold, and diagnosing the individual as having dengue fever systemic inflammation if the content is less than the threshold.

[0066] On the other hand, the present invention provides a method for diagnosing whether an individual has systemic inflammation due to COVID-19 infection, the method comprising: providing a test sample; detecting the content of ADGRE3 mRNA or ADGRE3 mRNA fragment, or the content of ADGRE3 protein or ADGRE3 protein fragment in the sample; comparing the tested content with a pre-set threshold, and diagnosing the individual as not having systemic inflammation due to COVID-19 infection if the content is greater than or equal to the threshold, and diagnosing the individual as having systemic inflammation due to COVID-19 infection if the content is less than the threshold.

[0067] Furthermore, diagnosing whether an individual has systemic inflammation due to COVID-19 infection includes diagnosing patients with systemic inflammation due to asymptomatic COVID-19 infection or patients with systemic inflammation caused by symptomatic COVID-19 infection.

[0068] On the other hand, the present invention provides a method for diagnosing whether an individual has respiratory syncytial virus (RSV) infection with systemic inflammation, the method comprising: providing a test sample; detecting the content of ADGRE3 mRNA or ADGRE3 mRNA fragment, or the content of ADGRE3 protein or ADGRE3 protein fragment in the sample; comparing the tested content with a preset threshold, and diagnosing the individual as not having RSV infection with systemic inflammation when the content is greater than or equal to the threshold, and diagnosing the individual as having RSV infection with systemic inflammation when the content is less than the threshold.

[0069] Furthermore, the diagnosis of whether an individual has systemic inflammation due to respiratory syncytial virus infection also includes: diagnosing whether the individual has experienced acute systemic inflammation due to respiratory syncytial virus infection, or diagnosing whether the individual has recovered from systemic inflammation due to respiratory syncytial virus infection.

[0070] On the other hand, the present invention provides a method for diagnosing whether an individual has systemic inflammation caused by cytomegalovirus infection, the method comprising: providing a test sample; detecting the content of ADGRE3 mRNA or ADGRE3 mRNA fragment in the sample; or the content of ADGRE3 protein or ADGRE3 protein fragment; comparing the tested content with a preset threshold, and diagnosing the individual as not having systemic inflammation caused by cytomegalovirus infection if the content is greater than or equal to the threshold, and diagnosing the individual as having systemic inflammation caused by cytomegalovirus infection if the content is less than the threshold.

[0071] On the other hand, the present invention provides a method for diagnosing whether an individual has systemic inflammation caused by Epstein-Barr virus (EBV) infection, the method comprising: providing a test sample; detecting the content of ADGRE3 mRNA or ADGRE3 mRNA fragment in the sample; or the content of ADGRE3 protein or ADGRE3 protein fragment; comparing the tested content with a pre-set threshold, and diagnosing the individual as not having systemic inflammation caused by EBV infection if the content is greater than or equal to the threshold, and diagnosing the individual as having systemic inflammation caused by EBV infection if the content is less than the threshold.

[0072] On the other hand, the present invention provides a method for distinguishing an individual as one of a healthy person, a patient with non-infectious systemic inflammatory response syndrome (SIRS), or a patient with sepsis. The method includes: providing a sample for testing; detecting the content of ADGRE3 mRNA or ADGRE3 mRNA fragments in the sample; or the content of ADGRE3 protein or ADGRE3 protein fragments; and comparing the tested content with a pre-set threshold, the threshold including a threshold for distinguishing between a healthy person and a patient with non-infectious SIRS, and a threshold for distinguishing between a patient with non-infectious SIRS and a patient with sepsis.

[0073] In some approaches, an individual is considered healthy when the tested level is greater than or equal to the threshold that distinguishes healthy individuals from those without systemic inflammatory response syndrome.

[0074] In some approaches, an individual is considered a sepsis patient when the tested level is below the threshold that distinguishes between a patient with non-infectious systemic inflammatory response syndrome and a patient with sepsis.

[0075] In some approaches, an individual is considered to have non-infectious systemic inflammatory response syndrome (SIRS) when the tested level is below the threshold distinguishing between healthy individuals and non-infectious SIRS patients, but above the threshold distinguishing between non-infectious SIRS patients and sepsis patients.

[0076] On the other hand, the present invention provides a method for diagnosing whether an individual suffers from systemic inflammation caused by transplant organ rejection, the method comprising: providing a test sample; detecting the content of ADGRE3 mRNA or ADGRE3 mRNA fragment in the sample; or the content of ADGRE3 protein or ADGRE3 protein fragment; comparing the tested content with a preset threshold, and diagnosing that the individual does not suffer from systemic inflammation caused by transplant organ rejection when the content is greater than or equal to the threshold, and diagnosing that the individual suffers from systemic inflammation caused by transplant organ rejection when the content is less than the threshold.

[0077] In the aforementioned study, we discovered and verified that ADGRE3 mRNA, or ADGRE3 protein, or ADGRE3 protein fragments, can diagnose systemic inflammation and other related diseases. ADGRE3 mRNA is transcribed from the ADGRE3 gene, and ADGRE3 protein is produced through the translation of the aforementioned ADGRE3 mRNA. However, protein content is not entirely determined by mRNA content; ADGRE3 protein content is also affected by protein-protein binding and degradation. Despite these factors, our functional verification also demonstrates that ADGRE3 protein or ADGRE3 protein fragments possess the ability to diagnose systemic inflammation.

[0078] On the other hand, the present invention provides the use of a biomarker for preparing a reagent for diagnosing systemic inflammation, said biomarker comprising ADGRE3 protein or ADGRE3 protein fragment, or the amino acid sequence or peptide fragment corresponding to ADGRE3.

[0079] The diagnosis of systemic inflammation includes one or more of the following: diagnosing whether an individual has systemic inflammation, predicting the risk of an individual having systemic inflammation, monitoring the disease progression of patients with systemic inflammation, predicting the prognosis of patients with systemic inflammation, or providing medication guidance for patients with systemic inflammation.

[0080] The reagent for diagnosing systemic inflammation is used to detect ADGRE3 protein or ADGRE3 protein fragments in an individual sample, preferably, the sample contains ADGRE3 protein or ADGRE3 protein fragments on or in neutrophils or monocytes.

[0081] ADGRE3 protein is primarily expressed in neutrophils and also in monocytes. However, detecting ADGRE3 protein or ADGRE3 protein fragments in individual neutrophils or monocytes is not a limitation of the test sample. Any sample containing neutrophils or monocytes, or substances within neutrophils or monocytes (substances within neutrophils or monocytes refer to substances originally derived from neutrophils or monocytes), can be used as a sample for diagnosing systemic inflammation by detecting ADGRE3 protein or ADGRE3 protein fragments in individual neutrophils or monocytes.

[0082] Detection of ADGRE3 protein or ADGRE3 protein fragments in individual neutrophils or monocytes refers to the detection of ADGRE3 protein or ADGRE3 protein fragments derived from neutrophils or monocytes. ADGRE3 protein or ADGRE3 protein fragments may be present inside the cell membrane, outside the cell membrane, or transmembrane, and their content can be determined by flow cytometry or other known techniques.

[0083] In some methods, the sample includes any one or more of peripheral blood, urine, secretions, pus, body fluids, spinal cord, and fresh tissue.

[0084] By detecting the level or content of ADGRE3 protein in neutrophils of healthy individuals and clinical patients, highly significant differences were found in the expression levels of ADGRE3 protein in neutrophils between patients with various types of systemic inflammation and healthy individuals. Therefore, systemic inflammation can be diagnosed by measuring the content of ADGRE3 protein in neutrophils. The expression levels of ADGRE3 protein in neutrophils and monocytes are correlated, so systemic inflammation can also be diagnosed by measuring the expression level of ADGRE3 protein in monocytes.

[0085] By combining multiple existing inflammatory markers, this invention found that the ADGRE3 protein has higher diagnostic sensitivity. By adding interference cases of patients with localized inflammation, the diagnosis was verified in healthy individuals, patients with localized inflammation, and patients with systemic inflammation. It was found that the ADGRE3 protein can correctly classify the two types of inflammation, showing that the ADGRE3 protein has high specificity in diagnosing systemic inflammation.

[0086] In some embodiments, the systemic inflammation includes infectious systemic inflammation or non-infectious systemic inflammation.

[0087] In some embodiments, the infectious systemic inflammation includes any one or more of bacterial, viral, fungal, and parasitic infections.

[0088] The viral infections described in some ways include any one or more of the following: influenza virus infection, COVID-19 infection, dengue virus infection, new Bunyavirus infection, respiratory syncytial virus infection, cytomegalovirus, and Epstein-Barr virus.

[0089] In some contexts, non-infectious systemic inflammation includes any one or more of the following: autoimmune diseases, transplant rejection, inflammatory bowel disease, allergic reactions, metabolic diseases, and inflammation caused by tissue damage.

[0090] In some embodiments, the autoimmune diseases described include any one or more of systemic lupus erythematosus, rheumatoid arthritis, vasculitis, ankylosing spondylitis, and autoimmune hepatitis.

[0091] In addition to inflammation (systemic inflammation) caused by systemic lupus erythematosus, rheumatoid arthritis, vasculitis, ankylosing spondylitis, and autoimmune hepatitis, other systemic inflammations caused by autoimmune diseases can also be diagnosed by detecting ADGRE3 mRNA or ADGRE3 mRNA fragments, ADGRE3 protein or ADGRE3 protein fragments discovered in this invention.

[0092] In some cases, the inflammation caused by transplant organ rejection includes systemic inflammation caused by rejection reactions from any one or more of liver transplants, kidney transplants, and bone marrow transplants.

[0093] In some cases, the systemic inflammation includes sepsis.

[0094] In some embodiments, the sepsis is caused by any one or more of the following infections: pulmonary infection, biliary tract infection, urinary tract infection, gastrointestinal tract infection, bloodstream infection, reproductive tract infection, abdominal infection, central nervous system infection, skin and soft tissue infection, and purulent osteomyelitis.

[0095] In addition to sepsis caused by the above-mentioned lesions, sepsis caused by any other lesions can be diagnosed by detecting ADGRE3 mRNA or ADGRE3 mRNA fragments, ADGRE3 protein or ADGRE3 protein fragments discovered in this invention.

[0096] In some embodiments, sepsis includes any one or more of Gram-positive bacterial sepsis, Gram-negative bacterial sepsis, and fungal sepsis.

[0097] In some embodiments, sepsis includes septic shock.

[0098] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to differentiate between a healthy individual and a patient with systemic inflammation caused by a viral infection, said biomarker comprising ADGRE3 protein or an ADGRE3 protein fragment, or an amino acid sequence or peptide fragment corresponding to ADGRE3.

[0099] In some methods, the reagent can also differentiate patients with systemic inflammation caused by viral infection into mild, severe, and critical cases.

[0100] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to diagnose whether an individual has systemic lupus erythematosus (SLE), said biomarker comprising ADGRE3 protein or ADGRE3 protein fragments, or the corresponding amino acid sequence or peptide fragment of ADGRE3.

[0101] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to diagnose patients with systemic lupus erythematosus (SLE) in the stable or active phase, said biomarker comprising ADGRE3 protein or ADGRE3 protein fragments, or the corresponding amino acid sequence or peptide fragment of ADGRE3.

[0102] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to diagnose whether an individual has systemic inflammation of the rheumatoid arthritis, said biomarker comprising ADGRE3 protein or ADGRE3 protein fragment, or an amino acid sequence or peptide fragment corresponding to ADGRE3.

[0103] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to diagnose patients with systemic inflammatory rheumatoid arthritis in the stable or active phase, said biomarker comprising ADGRE3 protein or ADGRE3 protein fragments, or the corresponding amino acid sequence or peptide fragment of ADGRE3.

[0104] Systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) can be divided into stable and active phases according to their disease progression. The stable phase refers to the period during which the condition no longer shows significant improvement or deterioration, while the active phase includes all other time periods outside the stable phase. Treatment plans differ between the stable and active phases. For example, patients in the stable phase of SLE need to reduce their medication dosage while maintaining more frequent disease monitoring. Therefore, clinical diagnosis of the stable and active phases of SLE and RA is necessary, but currently, there are no indicators that can provide a definitive diagnosis. This invention discovers that the ADGRE3 protein can serve as a biomarker for diagnosing the stable and active phases of SLE and RA.

[0105] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to distinguish between a healthy person and a patient with sepsis or septic shock, said biomarker comprising ADGRE3 protein or an ADGRE3 protein fragment, or an amino acid sequence or peptide fragment corresponding to ADGRE3.

[0106] Sepsis can be classified into sepsis, severe sepsis, and septic shock according to the severity of the condition. Patients with septic shock have extremely serious conditions and require a lot of medical resources for emergency treatment. Therefore, when sepsis occurs, patients need to be classified according to the severity of their condition. This invention has discovered that the ADGRE3 protein can be used to differentiate and diagnose septic shock, thus assisting in the clinical classification of patients.

[0107] In some embodiments, the present invention provides the use of a biomarker for preparing a reagent to predict the risk of death in patients with sepsis, said biomarker comprising ADGRE3 protein or fragments of ADGRE3 protein, or an amino acid sequence or peptide fragment corresponding to ADGRE3.

[0108] This invention also found that the risk of death in sepsis patients is highly correlated with ADGRE3 protein, and that the progression of sepsis is also highly correlated with changes in ADGRE3 protein levels.

[0109] In some methods, the use also includes: if the content of ADGRE3 protein or ADGRE3 protein fragment, or the corresponding amino acid sequence or peptide fragment of ADGRE3, in a sample taken on day 5 after an individual is diagnosed with the disease is higher than that in a sample taken on day 3, then the individual's sepsis is predicted to improve; otherwise, the individual's sepsis is predicted to not improve or to die.

[0110] On the other hand, the present invention provides the use of a biomarker combination for preparing a reagent for diagnosing whether a patient with systemic inflammation has systemic inflammation caused by a bacterial infection, the biomarker combination comprising ADGRE3 protein or ADGRE3 protein fragment, or an amino acid sequence or peptide fragment corresponding to ADGRE3, and the biomarker combination further comprising any one or more biomarkers specifically for diagnosing bacterial inflammation.

[0111] The specific biomarkers for diagnosing bacterial inflammation are those whose levels change significantly when an individual has bacterial inflammation, but do not change significantly when the individual does not have inflammation or has non-bacterial inflammation. In other words, they are specific to bacterial inflammation. Currently, there are several biomarkers, such as CD64, PCT, and HBP.

[0112] In some embodiments, the specific diagnostic markers for bacterial inflammation include any one or more of CD64, PCT, and HBP.

[0113] In some methods, if the content of ADGRE3 protein or ADGRE3 protein fragment, or the corresponding amino acid sequence or peptide fragment of ADGRE3 in the sample is lower than a preset threshold, and the content of specific diagnostic markers for bacterial inflammation in the sample is not within the range of healthy individuals, then the patient can be diagnosed with systemic inflammation caused by bacterial infection.

[0114] In some methods, when the content of ADGRE3 protein or ADGRE3 protein fragment, or the corresponding amino acid sequence or peptide fragment of ADGRE3 in the sample is lower than a preset threshold, and the content of a specific diagnostic marker for bacterial inflammation in the sample is within the range of healthy individuals, it can be determined that the patient has systemic inflammation caused by a viral infection or a non-infectious disease.

[0115] In some approaches, the threshold is the level of ADGRE3 protein or ADGRE3 protein fragments in healthy individuals, or the level of the corresponding amino acid sequence or peptide fragment of ADGRE3 in the sample.

[0116] This invention simultaneously measures the levels of ADGRE3 protein in neutrophils and the levels of markers specifically diagnosing bacterial inflammation in samples. It was found that when the level of ADGRE3 protein decreases, if the levels of markers specifically diagnosing bacterial inflammation change or also increase significantly, the patient is classified as having bacterial systemic inflammation; if the levels of markers specifically diagnosing bacterial inflammation are normal, the patient is classified as having non-bacterial systemic inflammation. Therefore, the levels of ADGRE3 protein or ADGRE3 protein fragments can be combined with markers specifically diagnosing bacterial inflammation to differentiate between systemic inflammation caused by bacterial infection and systemic inflammation caused by viral infection or non-infectious diseases.

[0117] Regarding the levels of biomarkers for the specific diagnosis of bacterial inflammation, which are not within the range of levels found in healthy individuals, different indicators can be classified as either too high (above the healthy range) or too low (below the healthy range). The presence of either of these two conditions in a biomarker for the specific diagnosis of bacterial inflammation indicates the occurrence of bacterial inflammation. For example, an elevated nCD64 level indicates the presence of bacterial inflammation.

[0118] On the other hand, the present invention provides a method for diagnosing whether an individual suffers from systemic inflammation, the method comprising: providing a test sample; detecting the content of ADGRE3 protein or ADGRE3 protein fragment, or the content of the corresponding amino acid sequence or peptide fragment of ADGRE3 in the sample; comparing the tested content with a preset threshold, and diagnosing the individual as not suffering from systemic inflammation when the content is greater than or equal to the threshold, and diagnosing the individual as suffering from systemic inflammation when the content is less than the threshold.

[0119] Regarding the detection of ADGRE3 protein or ADGRE3 protein fragment content in samples, this invention employs flow cytometry to gate cells within the sample, enabling targeted detection of ADGRE3 protein or ADGRE3 protein fragment content in neutrophils or monocytes. The protein or protein fragment can exist extracellularly, transmembrane, or intracellularly, and its content can be analyzed by flow cytometry. The detection of ADGRE3 protein or ADGRE3 protein fragment content in samples using any known detection method for diagnosing systemic inflammation falls within the scope of protection of this invention.

[0120] Regarding the setting of thresholds for ADGRE3 protein or ADGRE3 protein fragment content, since the average fluorescence intensity (MFI) directly measured in different batches of experiments, different flow cytometers, and different detection methods will vary, this invention adopts the expression index of neutrophil ADGRE3 protein (nADGRE3), i.e., nADGRE3 = patient neutrophil ADGRE3 protein MFI / healthy control neutrophil ADGRE3 protein MFI. This invention found that when the threshold value of nADGRE3 is 0.8361, the sensitivity, specificity, and accuracy for diagnosing systemic inflammation are the highest. Combining any other known threshold setting methods with the use of ADGRE3 protein or ADGRE3 protein fragment content to diagnose systemic inflammation is within the scope of protection of this invention.

[0121] Preferably, the sample contains ADGRE3 protein or ADGRE3 protein fragments on or in neutrophils or monocytes.

[0122] In some methods, the sample includes any one or more of peripheral blood, urine, secretions, pus, body fluids, spinal cord, and fresh tissue.

[0123] In some embodiments, the systemic inflammation includes infectious systemic inflammation or non-infectious systemic inflammation.

[0124] In some embodiments, the infectious systemic inflammation includes systemic inflammation caused by any one or more of bacterial, viral, fungal, and parasitic infections.

[0125] In some cases, the viral infection includes any one or more of influenza virus infection, novel coronavirus infection, dengue virus infection, and novel Bunyavirus infection.

[0126] In some embodiments, the non-infectious systemic inflammation includes systemic inflammation caused by one or more of the following: autoimmune diseases, transplant rejection, inflammatory bowel disease, allergic reactions, metabolic diseases, and inflammation caused by tissue damage.

[0127] In some embodiments, the autoimmune disease includes any one or more of systemic lupus erythematosus, rheumatoid arthritis, vasculitis, ankylosing spondylitis, and autoimmune hepatitis.

[0128] In some approaches, the systemic inflammation caused by transplant organ rejection includes systemic inflammation caused by any one or more of bone marrow transplantation, kidney transplantation, and liver transplantation.

[0129] In some cases, the systemic inflammation includes sepsis.

[0130] In some embodiments, the sepsis includes any one or more of Gram-positive bacterial sepsis, Gram-negative bacterial sepsis, and fungal sepsis.

[0131] In some embodiments, sepsis includes septic shock.

[0132] In some embodiments, the present invention provides a method for diagnosing whether an individual has systemic inflammation caused by a viral infection, the method comprising: providing a sample for testing; detecting the content of ADGRE3 protein or ADGRE3 protein fragments, or the content of the corresponding amino acid sequence or peptide fragment of ADGRE3 in the sample; comparing the tested content with a pre-set threshold, and diagnosing the individual as not having systemic inflammation caused by a viral infection if the content is greater than or equal to the threshold, and diagnosing the individual as having systemic inflammation caused by a viral infection if the content is less than the threshold.

[0133] In some embodiments, the present invention provides a method for distinguishing patients with systemic inflammation caused by viral infection into mild, severe, and critical cases, the method comprising: providing a sample for testing; detecting the content of ADGRE3 protein or ADGRE3 protein fragments, or the content of the corresponding amino acid sequence or peptide fragment of ADGRE3 in the sample; and comparing the tested content with a pre-set threshold, including a threshold for distinguishing between mild and severe cases, and a threshold for distinguishing between severe and critical cases.

[0134] In some methods, a patient is classified as having a mild case when the test result is greater than the threshold that distinguishes between mild and severe cases.

[0135] In some methods, a patient is classified as critically ill when the tested level is below the threshold that distinguishes between severe and critical illness.

[0136] In some methods, a patient is classified as severe when the test result is below the threshold for distinguishing between mild and severe cases but above the threshold for distinguishing between severe and critical cases.

[0137] On the other hand, the present invention provides a method for distinguishing systemic inflammatory patients with systemic lupus erythematosus into either a stable phase or an active phase. The method includes: providing a test sample; detecting the content of ADGRE3 protein or ADGRE3 protein fragments, or the content of the corresponding amino acid sequence or peptide fragment of ADGRE3 in the sample; comparing the tested content with a pre-set threshold, and classifying the patient as a stable phase patient if the content is greater than or equal to the threshold, and classifying the patient as an active phase patient if the content is less than the threshold.

[0138] On the other hand, the present invention provides a method for classifying patients with systemic inflammation of rheumatoid arthritis into either a stable phase or an active phase. The method includes: providing a test sample; detecting the content of ADGRE3 protein or ADGRE3 protein fragments, or the content of the corresponding amino acid sequence or peptide fragment of ADGRE3 in the sample; comparing the tested content with a pre-set threshold, and classifying the patient as a stable phase patient when the content is greater than or equal to the threshold, and classifying the patient as an active phase patient when the content is less than the threshold.

[0139] On the other hand, the present invention provides a method for diagnosing whether an individual has sepsis, the method comprising: providing a test sample; detecting the content of ADGRE3 protein or ADGRE3 protein fragment, or the content of the corresponding amino acid sequence or peptide fragment of ADGRE3 in the sample; comparing the tested content with a preset threshold, and diagnosing the individual as not having sepsis if the content is greater than or equal to the threshold, and diagnosing the individual as having sepsis if the content is less than the threshold.

[0140] On the other hand, the present invention provides a method for predicting the risk of death in patients with sepsis, the method comprising: providing a sample for testing; detecting the content of ADGRE3 protein or ADGRE3 protein fragment, or the content of the amino acid sequence or peptide fragment corresponding to ADGRE3 in the sample; comparing the tested content with a pre-set threshold, wherein the risk of death for the patient with sepsis is low when the content is greater than or equal to the threshold, and high when the content is less than the threshold.

[0141] Furthermore, the method also includes: if the content of ADGRE3 protein or ADGRE3 protein fragment, or the content of the corresponding amino acid sequence or peptide fragment of ADGRE3 in the sample on the 5th day after the patient's diagnosis is higher than that in the sample on the 3rd day, then the patient's sepsis is predicted to improve; otherwise, the patient's sepsis is predicted to not improve or to die.

[0142] On the other hand, the present invention provides a method for diagnosing whether an individual suffers from systemic inflammation caused by transplant organ rejection, the method comprising: providing a test sample; detecting the content of ADGRE3 protein or ADGRE3 protein fragment, or the content of the corresponding amino acid sequence or peptide fragment of ADGRE3 in the sample; comparing the tested content with a preset threshold, and diagnosing that the individual does not suffer from systemic inflammation caused by transplant organ rejection when the content is greater than or equal to the threshold, and diagnosing that the individual suffers from systemic inflammation caused by transplant organ rejection when the content is less than the threshold.

[0143] On the other hand, the present invention provides a method for diagnosing whether an individual suffers from bacterial systemic inflammation, the method comprising: providing a test sample, detecting the content of ADGRE3 protein or ADGRE3 protein fragment in the sample, or the content of the amino acid sequence or peptide fragment corresponding to ADGRE3; comparing the tested content with a preset threshold, and diagnosing that the individual does not suffer from bacterial systemic inflammation when the content is greater than or equal to the threshold; When the level is below the threshold, any one or more specific markers for diagnosing bacterial inflammation are detected in the sample. If the level of the marker for diagnosing bacterial inflammation is not within the range of levels in healthy individuals, the individual is diagnosed with bacterial systemic inflammation. If the level of the marker for diagnosing bacterial inflammation is within the range of levels in healthy individuals, the individual is diagnosed without bacterial systemic inflammation.

[0144] In some methods, the specific diagnostic markers for bacterial inflammation include any one or more of CD64, PCT, and HBP.

[0145] The ADGRE3 gene corresponds to multiple mRNA transcripts and transcript variants. Any ADGRE3 mRNA and its fragments can be used as a biomarker in this invention. ADGRE3 proteins translated from multiple mRNAs can have different amino acid sequences. Any ADGRE3 protein translated from any ADGRE3 mRNA and its fragments can be used as a biomarker in this invention.

[0146] In some embodiments, the ADGRE3 mRNA has any one or more of the nucleotide sequences shown in XM_054322398.1, XM_047439546.1, XM_011528374.3, NM_001289158.2, NM_001289159.2, and NM_032571.5 (RefSeq database).

[0147] In some embodiments, the ADGRE3 protein has the amino acid sequence shown in SEQ ID NO:1; or, the ADGRE3 protein is translated from any one of the mRNAs XM_054322398.1, XM_047439546.1, XM_011528374.3, NM_001289158.2, NM_001289159.2, and NM_032571.5.

[0148] Beneficial effects This study proposes a novel biomarker for diagnosing systemic inflammation. The transcriptional or expression levels of ADGRE3 mRNA or ADGRE3 protein in leukocytes, neutrophils, or monocytes can specifically distinguish between common inflammation and systemic inflammation. It has a high sensitivity for indicating systemic inflammation, far exceeding a series of existing diagnostic indicators, and its specificity for diagnosing systemic inflammation has been clinically verified. Attached Figure Description

[0149] Figure 1 Volcano map of differentially expressed genes in peripheral blood between patients with sepsis and those with non-infectious systemic inflammatory response; Figure 2 Volcano map of differentially expressed genes in peripheral blood between sepsis patients and healthy individuals; Figure 3 Comparison of ADGRE3 mRNA transcription levels in leukocytes of healthy controls, patients with systemic inflammation due to bacterial infection, and patients with systemic inflammation due to viral infection; Figure 4 Comparison of ADGRE3 mRNA transcription levels in leukocytes of healthy controls, patients with systemic inflammation caused by Gram-negative bacteria, and patients with systemic inflammation caused by H1N1 infection; Figure 5 Comparison of ADGRE3 mRNA transcription levels in leukocytes of healthy controls and patients with systemic dengue fever; Figure 6 Comparison of leukocyte ADGRE3 mRNA transcription levels in healthy controls, asymptomatic COVID-19-infected patients with systemic inflammation, and symptomatic COVID-19-infected patients with systemic inflammation; Figure 7 Comparison of leukocyte ADGRE3 mRNA transcription levels in healthy controls, patients with acute RSV infection and systemic inflammation, and individuals recovering from RSV infection and systemic inflammation. Figure 8 Comparison of ADGRE3 mRNA transcription levels in leukocytes of healthy controls and patients with systemic inflammation caused by cytomegalovirus infection; Figure 9Comparison of ADGRE3 mRNA transcription levels in leukocytes of healthy controls and patients with systemic inflammation caused by EB virus infection; Figure 10 Comparison of ADGRE3 mRNA transcription levels in leukocytes of healthy controls and patients with systemic inflammation caused by liver transplant rejection; Figure 11 Comparison of ADGRE3 mRNA transcription levels in leukocytes of healthy controls, patients with non-infectious systemic inflammatory response syndrome, and patients with sepsis; Figure 12 ROC curves of leukocyte ADGRE3 mRNA transcription levels between healthy controls and sepsis patients; Figure 13 ROC curves for differentiating between non-infectious systemic inflammatory response syndrome and sepsis patients using leukocyte ADGRE3 mRNA transcription levels; Figure 14 Comparison of leukocyte ADGRE3 mRNA transcription levels in healthy controls, patients with systemic inflammation caused by influenza A and B viruses, and patients with systemic inflammation caused by novel coronavirus infection; Figure 15 Comparison of leukocyte ADGRE3 mRNA transcription levels in healthy controls, patients with systemic lupus erythematosus, patients with systemic rheumatoid arthritis, patients with systemic vasculitis, and patients with systemic ankylosing spondylitis. Figure 16 Comparison of ADGRE3 mRNA transcription levels in leukocytes of healthy controls and sepsis patients; Figure 17 Comparison of peripheral blood neutrophil ADGRE3 protein expression levels among healthy controls, patients with systemic inflammation caused by influenza A and B viruses, patients with systemic inflammation caused by COVID-19, patients with systemic inflammation caused by dengue fever, and patients with systemic inflammation caused by novel Bunyavirus. Figure 18 ROC curves of neutrophil ADGRE3 protein expression used to differentiate between healthy individuals and patients with systemic inflammation caused by viral infections; Figure 19 Comparison of ADGRE3 protein expression levels in neutrophils among healthy controls and patients with systemic inflammation caused by viral infection (mild, severe, and critical cases); Figure 20 Comparison of ADGRE3 protein expression levels in neutrophils of patients with systemic inflammation due to autoimmune diseases (systemic lupus erythematosus, rheumatoid arthritis, vasculitis, ankylosing spondylitis, autoimmune hepatitis); Figure 21Comparison of ADGRE3 protein expression levels in neutrophils among healthy controls, patients with systemic inflammation induced by kidney transplantation, and patients with systemic inflammation induced by bone marrow transplantation; Figure 22 ROC curves of neutrophil ADGRE3 protein expression levels used to distinguish between healthy individuals and non-infectious systemic inflammation; Figure 23 Comparison of ADGRE3 protein expression levels in neutrophils of healthy controls and sepsis patients; Figure 24 ROC curves of neutrophil ADGRE3 protein expression used to differentiate between healthy individuals and sepsis patients; Figure 25 Comparison of ADGRE3 protein expression levels in neutrophils of healthy controls, Gram-positive bacterial sepsis, Gram-negative bacterial sepsis, and fungal sepsis; Figure 26 Comparison of ADGRE3 protein expression levels in neutrophils of healthy controls and sepsis patients (septic patients, septic shock patients); Figure 27 Comparison of ADGRE3 protein expression in neutrophils of sepsis survivors and sepsis-dead patients; Figure 28 ROC curve of neutrophil ADGRE3 protein for predicting mortality risk in sepsis patients; Figure 29 Comparison of ADGRE3 protein expression in neutrophils between patients with improved sepsis and those with no improvement or death; Figure 30 Comparison of ADGRE3 protein expression in neutrophils of healthy controls and patients with localized inflammation (hepatitis B, hepatitis C, and hepatitis E patients); Figure 31 Flowchart for classifying patients with systemic inflammatory response caused by bacterial infection according to nADGRE3 and other inflammatory markers; Figure 32 Flowchart for classifying patients with systemic inflammatory response caused by viral infection according to nADGRE3 and other inflammatory markers; Figure 33 Flowchart for classifying patients with autoimmune diseases and systemic inflammatory responses caused by transplant rejection according to nADGRE3 and other inflammatory markers; Figure 34 Flowchart for classifying patients suspected of having systemic inflammatory response according to nADGRE3 and other bacterial inflammatory markers.

[0150] Explanation of the markings and contents in the attached diagram: Figure 1 and Figure 2 In the graph, each point corresponds to a gene. A point to the left of the origin on the horizontal axis represents a decrease in the expression of the corresponding gene, while a point to the right of the origin represents an increase in the expression of the corresponding gene. The color of the point indicates that the change in the expression of the corresponding gene is more than 2-fold and has a statistical significance (p<0.05). Blue represents a decrease of more than 2-fold in expression, and red represents a significant increase of more than 2-fold in expression. The farther the point is from the origin on the horizontal axis, the greater the change in the expression of the corresponding gene. An absolute value of the horizontal axis of the point greater than or equal to 1 represents a difference of more than 2-fold, and an absolute value greater than or equal to 2 represents a change of more than 4-fold.

[0151] like Figure 3 This invention relates to a graph of mRNA expression levels, where the vertical axis represents the mRNA expression level, specifically the mRNA copy number. "GSE + number" represents the corresponding dataset number in the GEO database; for example... Figure 15 This invention relates to a graph of protein expression levels, where the vertical axis represents the relative protein expression level (nADGRE3), and the calculation of nADGRE3 has been described in the invention description.

[0152] The significance of mRNA or protein expression levels between groups is indicated by ns or several asterisks (*); ns indicates no significant difference (p>0.05), "*" indicates a significant difference (p<0.05), "**" indicates an extremely significant difference (p<0.01), "***" indicates a higher degree of significance (p<0.001), and "****" indicates an extremely high degree of significance (p<0.0001).

[0153] Detailed description The structures involved in this invention or the technical terms used therein will be further described below, unless otherwise specified, and shall be interpreted in accordance with the general understanding of the terms in the art.

[0154] diagnosis In this invention, "diagnosis" refers to an assessment of health status, including predicting whether an individual is healthy or unhealthy, and evaluating the effectiveness of treatment during the treatment of a disease. Therefore, the diagnosis of this invention includes at least one or more of the following aspects: First, diagnosing whether an individual has systemic inflammation or a specific type of systemic inflammation includes: distinguishing between healthy individuals and patients with systemic inflammation, distinguishing between patients with localized or non-inflammatory diseases and those with systemic inflammation, and also distinguishing between systemic inflammation caused by different etiologies (such as distinguishing between bacterial and non-bacterial systemic inflammation, and between viral and bacterial infections); or, Second, predicting an individual's risk of developing systemic inflammation or a specific type of systemic inflammation, including: predicting the risk of developing systemic inflammation in patients with non-systemic inflammation, predicting the risk of local inflammation developing into systemic inflammation, and predicting the risk of developing systemic inflammation in patients with chronic diseases, etc.; or, Third, monitoring the disease progression of patients with systemic inflammation to determine whether their condition is worsening or improving, and to assess the risk of their condition worsening to sepsis; or to predict the prognosis of patients with systemic inflammation, judging the trend of disease development and thus predicting the risk of death; or... Fourth, medication guidance for patients includes: when a non-systemic inflammation patient is found to have a tendency to develop systemic inflammation, medication intervention should be used for prevention; when a systemic inflammation patient's condition is found to worsen, the medication dosage should be increased to improve the treatment effect; when a systemic inflammation patient's condition is found to improve, the medication dosage should be reduced to reduce the probability of adverse drug reactions or drug resistance. The above-mentioned medications can be any medications used to treat systemic inflammation, including but not limited to antibiotics, antiviral drugs, and hormone drugs.

[0155] ADGRE3 mRNA or encoded protein The ADGRE3 gene (genotype ID ENSG00000131355), located on chromosome 19, has been identified as a protein-coding gene. Its structure consists of multiple exons, and alternative splicing produces multiple mRNA transcript variants encoding different isoforms. The expression profile of ADGRE3 suggests it plays a role in phagocytic function, intercellular interactions, and / or signaling during inflammation. This gene is primarily expressed by immune system cells, with higher expression in synovial granulocytes than in peripheral blood granulocytes, likely due to the inflammatory microenvironment of synovial fluid.

[0156] ADGRE3 is a G protein-coupled receptor that may play a role in myeloid-myeloid interactions during immune and inflammatory responses. The soluble ligand of this receptor is present on the surface of monocyte-derived macrophages and activated neutrophils. Diseases associated with the ADGRE3 gene include inflammatory bowel disease. The gene's involvement in these diseases may be related to its role in immune and inflammatory responses. ADGRE3 is involved in multiple pathways, including the innate immune system and downstream GPCR signaling. The protein product of this gene interacts with other proteins in the immune system. ADGRE3 is expressed in various tissues, including bone marrow and lymphoid tissues, exhibiting a tissue-enhanced expression pattern. This protein is expected to be secreted, with some isoforms located on membranes.

[0157] In summary, ADGRE3 is a protein-coding gene that plays a crucial role in the immune system, particularly in phagocytic function, cell-cell interactions, and signal transduction during inflammation. This gene is primarily expressed in cells of the immune system and is involved in multiple pathways related to immune and inflammatory responses.

[0158] The ADGRE3 gene has multiple mRNA transcript variants, and any mRNA and its fragments can serve as a biomarker in this invention. One of the main mRNA transcript sequences is NM_032571.5. The mRNA targets in this invention include the following six: XM_054322398.1, XM_047439546.1, XM_011528374.3, NM_001289158.2, NM_001289159.2, and NM_032571.5. The above mRNA transcript sequences are provided by the RefSeq database. It is understood that any method that can specifically detect the amount and copy number of this mRNA can be used in the diagnostic methods of this invention. For example, commonly used temperature-dependent amplification, PCR, isothermal amplification, and gene editing technology, as well as any other methods or reagents used for nucleic acid testing, can be used in this invention for testing or detection. When amplification is required, designing suitable primers is easily achievable.

[0159] Because the ADGRE3 gene has multiple mRNA transcript variants, the ADGRE3 protein translated from different mRNAs can have different amino acid sequences. Therefore, any ADGRE3 protein translated from any mRNA, as well as its fragments, can serve as a biomarker in this invention. It is understood that anything that can specifically detect the amount of ADGRE3 protein can be used in the diagnostic methods of this invention, such as flow cytometry, Coomassie brilliant blue assay, etc. Any method or reagent used for protein testing can be used in this invention for testing or detection.

[0160] An amino acid sequence of a human ADGRE3 protein (SEQ ID NO:1): MQGPLLLPGLCFLLSLFGAVTQKTKTSCAKCPPNASCVNNTHCTCNHGYTSGSGQKLFTF PLETCNDINECTPPYSVYCGFNAVCYNVEGSFYCQCVPGYRLHSGNEQFSNSNENTCQDT TSSKTTEGRKELQKIVDKFESLLTNQTLWRTEGRQEISSTATTILRDVESKVLETALKDP EQKVLKIQNDSVAIETQAITDNCSEERKTFNLNVQMNSMDIRCSDIIQGDTQGPSAIAFI SYSSLGNIINATFFEEMDKKDQVYLNSQVVSAAIGPKRNVSLSKSVTLTFQHVKMTPSTK KVFCVYWKSTGQGSQWSRDGCFLIHVNKSHTMCNCSHLSSFAVLMALTSQEEDPVLTVIT YVGLSVSLLCLLLAALTFLLCKAIRNTSTSLHLQLSLCLFLAHLLFLVGIDRTEPKVLCS IIAGALHYLYLAAFTWMLLEGVHLFLTARNLTVVNYSSINRLMKWIMFPVGYGVPAVTVA ISAASWPHLYGTADRCWLHLDQGFMWSFLGPVCAIFSANLVLFILVFWILKRKLSSLNSE VSTIQNTRMLAFKATAQLFILGCTTWCLGLLQVGPAAQVMAYLFTIINSLQGFFIFLVYCL LSQQVQKQYQKWFREIVKSKSESETYTLSSKMGPDSKPSEGDVFPGQVKRKY.

[0161] Based on the characteristics of different segments or regions, the human ADGRE3 protein with the amino acid sequence shown in SEQ ID NO:1 can be divided into several segments or regions as shown below: Features are used to describe different regions and domains in a protein sequence. Signal peptide sequence (FTSIGNAL): A short amino acid sequence that guides newly synthesized proteins into the endoplasmic reticulum-Golgi apparatus pathway for protein secretion or localization. Mature protein sequence (FTCHAIN): After a protein enters the secretion pathway, the signal peptide is recognized and cleaved by a specific signal peptidase. The remaining sequence is the mature protein sequence, which typically contains the protein's functional domains and other important regions, determining the protein's final conformation and biological function. Transmembrane region (FTTRANSMEM): A hydrophobic α-finger helix or β-sheet region embedded in the cell membrane. α-finger helices or β-sheets are common secondary structures of proteins and can be embedded in the lipid bilayer of the cell membrane. Topological domain (FTTOPO_DOM): Describes the protein's topological arrangement on or within the membrane, such as intracellular, extracellular, or transmembrane regions. Functional domain (FT) A domain is an independent foldable structural unit with a specific biological function; a region describes a segment in a sequence that has certain common characteristics but whose function is not clear, such as a low-complexity region or a repetitive sequence.

[0162] Fragment position represents the position of the first and last amino acids of the fragment or region in the full-length amino acid sequence of the protein.

[0163] Extracellular regions refer to the areas of a protein sequence located outside the cell membrane; helical regions refer to the areas of a protein sequence that form α-helical structures. α-helices are one of the common secondary structures of proteins, exhibiting a helical spatial arrangement. Many transmembrane proteins contain multiple α-helical regions, which can be embedded in the lipid bilayer of the cell membrane to form transmembrane domains; cytoplasmic regions refer to the areas of a protein sequence located within the cytoplasm, containing domains and regulatory regions related to intracellular signal transduction. They may interact with effector molecules within the cell to transmit signals. Epidermal growth factor-like domains (EGF-like) are independent folding structural modules widely found in various proteins, typically involved in protein-protein interactions. EGF-like domains usually contain six conserved cysteine ​​residues, forming three disulfide bonds (1-3, 2-4, 5-6). Some EGF-like domains also possess calcium-binding capabilities. The GPS domain is a conserved sequence of approximately 40 amino acid residues, rich in canonical cysteine ​​and tryptophan residues, and is the most highly conserved part of G protein-coupled receptors (GPCRs). Disordered or irregular structural regions refer to regions lacking a fixed three-dimensional structure, exhibiting high conformational flexibility and dynamism. Disordered regions are typically rich in polar and charged residues, playing important roles in protein folding, interactions, and regulation.

[0164] Of course, it is understood that the corresponding ADGRE3 protein sequence in mammals may have slight differences in amino acids compared to humans. The ADGRE3 protein, protein fragments, amino acids, or amino acid fragments (peptide fragments) in mammals can all be used as markers in this invention for testing or detection.

[0165] In the following description of this invention, unless otherwise specified, the term "gene" refers to mRNA or an mRNA fragment, and "protein" refers to a full-length protein or a protein fragment, or a full-length peptide or a peptide fragment, or a full-length amino acid or an amino acid fragment. A "fragment" is a shorter sequence relative to the full length, such as a gene sequence or an amino acid sequence, or an extracellular protein fragment or a peptide fragment.

[0166] White blood cells and neutrophils White blood cells are a type of colorless, spherical, nucleated blood cell. White blood cells are not a homogeneous cell group; based on their morphology, function, and origin, they can be divided into three main categories: granulocytes, monocytes, and lymphocytes. Granulocytes can be further divided into three types based on the staining properties of the granules in their cytoplasm: neutrophils, eosinophils, and basophils.

[0167] White blood cells generally have active mobility; they can migrate from inside blood vessels to outside blood vessels, or from extravascular tissues to inside blood vessels. Therefore, in addition to being present in blood and lymph, white blood cells are also widely distributed in tissues outside of blood vessels and lymphatic vessels. Most white blood cells only stay in the blood briefly before entering tissues to perform their functions.

[0168] Neutrophils are a type of white blood cell whose main function is to resist microbial invasion. They possess deformability and phagocytic capabilities, making them crucial in fighting disease and protecting the body. In healthy individuals, they are normally present in the blood. However, in patients with diseases, especially those with systemic inflammation, white blood cells rapidly infiltrate sites of inflammation. Therefore, white blood cells are often present in various tissues of these patients, and thus, white blood cells, along with neutrophils and monocytes within the white blood cell population, can be detected in various types of clinical samples.

[0169] When using ADGRE3 mRNA as a marker, this invention typically involves detecting the transcriptional level in leukocytes. For example, a transcriptional level below normal indicates a potential for systemic inflammation. It's understandable that the protein translated from its mRNA can also serve as a marker, and we've found that using proteins as markers offers higher sensitivity and specificity. Therefore, theoretically, proteins from any type of leukocyte can be used, such as any type of granulocyte, monocyte, or lymphocyte, or any type of granulocyte including neutrophils, eosinophils, and basophils. Although the amount of protein translated varies among different cells, comparing tests using the same cell type still has diagnostic value. For instance, testing the protein expression levels of monocytes in healthy individuals and those with localized or systemic inflammation will still show significant differences. Of course, in some methods, using proteins from neutrophils is also possible.

[0170] ADGRE3 mRNA or ADGRE3 protein as markers The present invention has discovered that... ADGRE3 Gene transcription mRNA The level of this substance in peripheral blood leukocytes tends to decrease as inflammation progresses, especially when local inflammation develops into systemic inflammation, where it shows a significant decline. Furthermore, significant differences exist even between different types of systemic inflammation caused by different factors.

[0171] The invention team initially aimed to identify genes playing a crucial role in the pathogenesis of sepsis by analyzing and comparing changes in peripheral blood gene expression profiles between sepsis patients and patients with non-infectious systemic inflammation in a public database. They discovered that the expression of this gene was significantly altered in the peripheral blood of sepsis patients. Figure 1 );from Figure 1 It can be seen that among the two significantly downregulated genes, the gene of this invention was found to be significantly downregulated. While the other gene (Membrane Metalloendopeptidase, MME) was also downregulated, it is unsuitable as a marker of systemic inflammation because cohort analyses of other infections and sepsis data showed no significant difference in MME gene expression levels between sepsis patients and healthy controls. Therefore, from... Figure 1 It is evident that the downregulation of the ADGRE3 gene in this invention can serve as a marker distinguishing sepsis patients from those with non-infectious systemic inflammation. Similarly, the corresponding protein can also serve as a marker distinguishing sepsis patients from those with non-infectious systemic inflammation. Furthermore, in analyzing and comparing the differences in gene regulation between sepsis patients and healthy individuals, we also discovered a gene that is significantly downregulated (…). Figure 2 This indicates that the gene can be used to distinguish between sepsis patients and healthy patients, although from... Figure 2 Many downregulated genes were found, but some cannot be used as biomarkers, while others are well-known downregulated genes.

[0172] In subsequent experiments, we isolated this gene or protein and analyzed its expression changes in different infection types in public datasets. We also collected patient samples from our hospital to validate mRNA and protein expression. We compared these samples with existing clinical inflammatory markers and found that this marker has extremely high sensitivity in indicating systemic inflammation, exceeding existing clinically used markers. However, existing markers do not improve the sensitivity and specificity of inflammatory disease diagnosis. We also found that the transcriptional level of ADGRE3 mRNA in the peripheral blood of patients with systemic inflammation caused by bacterial or viral infections was significantly lower than that in healthy controls. The same pattern was observed in Gram-positive bacterial infections, H1N1 infections, dengue fever, COVID-19, RSV infections, cytomegalovirus infections, EBV infections, and influenza virus infections. This validates the effectiveness of ADGRE3 mRNA in diagnosing these types of infectious systemic inflammation patients. Furthermore, we found that ADGRE3 mRNA transcriptional levels can differentiate between Gram-positive bacterial infections and H1N1 infections, asymptomatic and symptomatic COVID-19 patients, and patients with acute RSV infection and those who have recovered from RSV infection. Therefore, ADGRE3 mRNA or ADGRE3 protein can not only diagnose patients with infectious systemic inflammation but also identify the lesions of infectious systemic inflammation, enabling targeted treatment and monitoring of disease progression.

[0173] Furthermore, clinical validation in healthy individuals, patients with non-infectious systemic inflammatory response syndrome (SIRS), and patients with sepsis demonstrated highly significant differences in leukocyte transcriptional levels or protein content among these three groups. Therefore, ADGRE3 mRNA or protein can serve as a diagnostic marker for distinguishing between non-infectious SIRS and sepsis. Diagnostic results on the validation set showed a diagnostic AUC of 0.920 for distinguishing between healthy individuals and patients with sepsis, an AUC of 0.864 for distinguishing between sepsis and SIRS, and an AUC of 0.862 for diagnosing sepsis from the entire sample set. This indicates that leukocyte ADGRE3 mRNA transcriptional levels can accurately diagnose sepsis.

[0174] inflammation Inflammation is a physiological response of the body to injury, infection, or stimulation, aiming to eliminate pathogens, repair tissues, and restore tissue function. Inflammation typically manifests as local symptoms such as redness, swelling, heat, pain, and functional impairment.

[0175] Inflammation typically involves the following steps: Inflammatory triggers: These can be external or internal factors such as infection, trauma, chemical irritation, and allergic reactions. Release of inflammatory mediators: Damaged cells release inflammatory mediators, such as histamine, prostaglandins, and cytokines, causing vasodilation, increased vascular permeability, and leukocyte infiltration. Leukocyte infiltration: Leukocytes, especially neutrophils, enter tissues through the blood vessel walls to clear pathogens and cellular debris. Tissue repair: During inflammation, the body initiates tissue repair mechanisms, including fibrin deposition, cell proliferation, and repair processes.

[0176] Treatment for inflammation depends on its cause and severity. Common treatments include: Nonsteroidal anti-inflammatory drugs (NSAIDs): such as ibuprofen and acetaminophen, used to reduce pain and inflammation; Steroid hormones: such as prednisone, used to control the inflammatory response; Immunosuppressants: used to control excessive activity of the immune system; Antibiotics: used to treat inflammatory infections; and Physical therapy: such as applying ice or heat to help reduce inflammation and pain.

[0177] Systemic inflammation Systemic inflammation (SCI) is a systemic inflammatory response that is not limited to a specific tissue or organ but involves the entire body's inflammatory process. This inflammatory response is usually a non-specific reaction to stimuli such as infection or inflammatory triggers, including microorganisms like bacteria, fungi, and viruses, trauma, burns, and surgery. Systemic inflammation is relative to localized, specific tissues or organs (it is specific), and it is understandable that localized inflammation can develop into severe systemic inflammation, representing a more serious form of inflammation in the overall inflammatory process.

[0178] Generally, an inflammatory response occurring in 100% of the body's tissues or organs is one aspect of this invention. However, an inflammatory response occurring in 50% to 100% of tissues or organs is also covered by this invention. From another perspective, the progression from specific inflammation to non-specific inflammatory response is also an example of this invention. All of the above scopes fall under the term "invention". Systemic inflammation The defined scope, for example, when local inflammation occurs, the indicators of the present invention are used to monitor the development of the disease. At this time, the markers of the present invention may not be significantly reduced. However, once the measured level is significantly reduced compared to the previous test, it can be determined that systemic inflammation has occurred. Or, if the current test level is on a downward trend, it can be predicted that local inflammation may lead to systemic inflammation, and early intervention and treatment can be carried out to prevent or prevent the occurrence of systemic inflammation.

[0179] Characteristics of systemic inflammatory responses include: Release of inflammatory mediators: During a systemic inflammatory response, the body releases various inflammatory mediators, such as cytokines, chemokines, and interleukins, which can trigger both local and systemic inflammatory reactions. Systemic symptoms: Patients may exhibit systemic symptoms such as fever, chills, general weakness, increased heart rate, rapid breathing, and elevated or decreased peripheral blood leukocyte counts. Organ dysfunction: In severe systemic inflammatory responses, excessive release of inflammatory mediators can lead to multiple organ dysfunction syndrome (MODS), seriously threatening the patient's life. Immune system dysregulation: During a systemic inflammatory response, the immune system may be in a hyperactive state, leading to immune dysfunction and even autoimmune reactions. Life-threatening situations: In some cases, such as severe infections or systemic inflammatory responses caused by bacterial toxins, systemic inflammatory responses may develop into severe sepsis or septic shock, endangering the patient's life.

[0180] The key to managing systemic inflammatory responses lies in early identification and proactive intervention. Treatment goals include controlling the inflammatory response, maintaining organ function, providing symptomatic support, and addressing the underlying cause. Commonly used clinical treatments include antibiotic therapy, hemodynamic support, and immunomodulatory therapy. Early intervention can effectively reduce the severity of systemic inflammatory responses and improve patient survival and prognosis.

[0181] Distinguishing between systemic and non-systemic inflammation, or between systemic and non-systemic inflammation. On the one hand, from a medical perspective: when distinguishing between systemic and non-systemic inflammation, or between systemic and non-systemic inflammation, the following aspects need to be considered: 1. Medical History and Clinical Manifestations: Systemic Inflammation: Patients may present with systemic symptoms such as fever, fatigue, and malaise. The inflammation may involve multiple organ systems. Systemic inflammation is often accompanied by systemic symptoms and elevated inflammatory markers. Non-Systemic Inflammation: Inflammation may be localized to a specific site or organ, manifesting as local symptoms such as local redness, swelling, pain, and limited function.

[0182] 2. Laboratory Tests: Systemic / systemic inflammation: often accompanied by abnormal complete blood cell counts, elevated inflammatory markers (such as C-reactive protein and procalcitonin), and increased release of systemic inflammatory mediators. Non-systemic / non-systemic inflammation: laboratory test results may show that the inflammatory response is localized to the affected site, and the complete blood cell count and inflammatory markers may not be as significantly elevated as in systemic inflammation.

[0183] 3. Imaging examinations: Systemic inflammation: Imaging examinations may show inflammatory manifestations involving multiple organ systems, such as multi-organ foci of infection in systemic inflammation. Non-systemic inflammation: Imaging examination results may only show inflammatory changes in the affected site, such as local infection or inflammatory foci.

[0184] 4. Pathogen detection: Systemic inflammation: Pathogens may be detected in multiple sites throughout the body via blood culture or other detection methods. Non-systemic inflammation: Pathogen detection results may be positive only in the affected area or specific sites.

[0185] 5. Treatment Response: Systemic Inflammation: Treatment of systemic inflammation may require systemic antibiotics or immunomodulatory therapy. Non-systemic Inflammation: Non-systemic inflammation can usually be effectively controlled with local treatment (such as local antibiotics, local anti-inflammatory drugs).

[0186] By comprehensively analyzing information such as medical history, clinical manifestations, laboratory tests, imaging examinations, pathogen detection, and treatment response, infectious disease experts can more accurately distinguish between systemic and non-systemic inflammation, or between systemic and non-systemic inflammation, and formulate corresponding treatment plans.

[0187] Secondly, from an immunological perspective: when distinguishing between systemic and non-systemic inflammation, the following aspects need to be considered: 1. Scope of the immune response: Systemic / systemic inflammation: involves abnormal activity or dysregulation of the immune system throughout the body, leading to a generalized immune response to multiple organs and tissues. Immune cells and inflammatory mediators may be active in multiple parts of the body. Non-systemic / non-systemic inflammation: the immune response is limited to a specific site or organ, and the inflammatory response is mainly confined to the affected local area.

[0188] 2. Immune Cell Involvement: Systemic / Systemic Inflammation: Involves abnormal activity of multiple immune cell types, possibly including T lymphocytes, B lymphocytes, neutrophils, macrophages, etc., leading to systemic immune responses and inflammation. Non-systemic / Non-systemic Inflammation: Immune cell activity is mainly limited to the affected site, such as specific tissues or organs.

[0189] 3. Release of inflammatory mediators: Systemic inflammation: Increased release of inflammatory mediators throughout the body may lead to elevated systemic symptoms and inflammatory markers. Non-systemic inflammation: Release of inflammatory mediators is mainly limited to the affected local area, and inflammatory markers may not be as elevated at the systemic level as in systemic inflammation.

[0190] 4. Immune Regulation Mechanisms: Systemic inflammation: May involve comprehensive regulation of the immune system, requiring integrated control of immune cell activity and the release of inflammatory mediators. Non-systemic inflammation: Treatment may be more localized, focusing on controlling local inflammatory responses without disrupting systemic immune balance.

[0191] By comprehensively considering factors such as the scope of the immune response, the involvement of immune cells, the release of inflammatory mediators, and the mechanisms of immune regulation, immunology experts can more accurately distinguish between systemic and non-systemic inflammation, or between systemic and non-systemic inflammation, and formulate corresponding immunomodulatory treatment plans.

[0192] Localized inflammation and systemic inflammation as defined from any of the above perspectives fall within the scope of this invention. Furthermore, the markers of this invention can distinguish not only between localized and systemic inflammation, but also between systemic inflammation and healthy individuals.

[0193] Infectious inflammation Infectious inflammation can progress from localized infection to systemic or generalized inflammation. Infectious inflammation is an inflammatory response caused by infection. Infection refers to the process by which pathogens (such as bacteria, viruses, fungi, or parasites) invade and multiply in a host body. When the body is infected, the immune system initiates an inflammatory response to clear the pathogens and repair damaged tissues.

[0194] Characteristics of infectious inflammation include: Pathogen invasion: Infectious inflammation is caused by pathogens invading the body. Pathogens can be bacteria, viruses, fungi, or parasites. Inflammatory response: The inflammatory response triggered by infection is a natural defense mechanism of the immune system, including the release of inflammatory mediators, activation and migration of white blood cells, etc. Local symptoms: Infectious inflammation often manifests as local symptoms, such as redness, swelling, pain, heat, and dysfunction. These symptoms are part of the body's response to infection. Systemic inflammation: Severe infections may lead to systemic symptoms, such as fever, chills, general weakness, headache, nausea, and vomiting.

[0195] Complications in severe cases: Severe infections can lead to serious complications such as sepsis and septic shock, resulting in multiple organ dysfunction and even death. The above is also a specific classification based on the severity of systemic inflammation.

[0196] The key to managing infectious inflammation lies in early identification and timely treatment. Treatment methods include antibiotics (for bacterial infections), antiviral drugs (for viral infections), and antifungal drugs (for fungal infections), while supportive care is also necessary to maintain stable vital signs. Key to preventing infectious inflammation includes maintaining good personal hygiene, vaccination, avoiding contact with known sources of infection, and timely treatment of the infection. For vulnerable groups (such as those with weakened immune systems or chronic diseases), close attention needs to be paid to infection prevention measures.

[0197] Non-infectious inflammation Non-infectious inflammation can develop from localized infections into systemic or generalized inflammation. Non-infectious inflammation refers to inflammatory responses not caused by external pathogens (such as bacteria, viruses, fungi, or parasites). This inflammation may be caused by abnormal immune responses, transplant rejection, tissue damage, chemical irritation, or other non-infectious factors. Some common non-infectious inflammatory diseases include: autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, vasculitis, autoimmune hepatitis, Hashimoto's thyroiditis and Graves' disease, multiple sclerosis, Sjögren's syndrome, and transplant rejection; these diseases are inflammatory responses caused by the immune system mistakenly attacking body tissues. Inflammatory bowel diseases such as Crohn's disease and ulcerative colitis are caused by chronic inflammatory responses in the intestines.

[0198] Allergic reactions: Allergic diseases such as asthma and allergic rhinitis are caused by abnormal immune system reactions triggered by allergens. Metabolic diseases: Such as diabetes and obesity, these diseases are also closely related to inflammatory responses. Inflammation caused by tissue damage: For example, trauma, chemical irritation, and radiation damage can all trigger non-infectious inflammation. Non-infectious inflammation differs from infectious inflammation in its etiology and pathogenesis, but it may share some similarities in clinical manifestations, such as inflammatory symptoms like fever, pain, and redness.

[0199] Managing non-infectious inflammation typically involves controlling the inflammatory response, relieving symptoms, and reducing tissue damage. Specific treatment methods depend on the type and severity of the disease. For autoimmune diseases, standard treatments include immunosuppressants and anti-inflammatory drugs. For other types of non-infectious inflammation, treatment may include medication, physical therapy, and surgery. Timely diagnosis and treatment of non-infectious inflammation can help alleviate symptoms, control disease progression, and improve patients' quality of life.

[0200] sepsis Sepsis is a systemic inflammatory response syndrome, a more severe type of systemic inflammation, commonly seen in patients with severe trauma or infectious diseases. Causes include infections from bacteria, fungi, viruses, and parasites, leading to an imbalance in the body's inflammatory response and immune regulation. Sepsis can progress to severe sepsis and septic shock, resulting in organ dysfunction and circulatory disorders, endangering life.

[0201] Sepsis is a systemic inflammatory response syndrome caused by a confirmed or suspected infection. Severe sepsis refers to sepsis accompanied by organ dysfunction and tissue insufficiency. Septic shock refers to sepsis accompanied by hypotension that cannot be reversed by fluid therapy.

[0202] Diagnostic criteria for sepsis: A clear or suspected infection is present, along with one or more of the following clinical features: Physical signs and clinical symptoms: body temperature: >38.3℃ or <36℃; heart rate >90 beats / min, or greater than the difference between two normal values ​​for different ages; shortness of breath: respiratory rate >20 breaths / min or hyperventilation, PaCO2 <32mmHg; changes in mental status; Significant edema or positive fluid deficit: more than 20 ml / kg in 24 hours; hyperglycemia without a history of diabetes. Hemodynamics: Hypotension: systolic blood pressure <90 mmHg, mean arterial pressure (MAP) <70 mmHg, or a decrease in systolic blood pressure of more than 40 mmHg or below two standard deviations below the age-appropriate normal value in adults.

[0203] Laboratory tests: Inflammatory markers: Leukocytosis: WBC > 12000 / μl; Leukopenia: WBC < 4000 / μl; WBC normal but total number of immature white blood cells exceeds 10%; Plasma C-reactive protein > two standard deviations of normal; Plasma procalcitonin > two standard deviations of normal.

[0204] Organ dysfunction indicators: Hypoxemia: arterial partial pressure of oxygen (PaO2) / oxygen concentration (FiO2) <300mmHg; Acute oliguria: low urine output even with adequate fluid resuscitation; serum creatinine >44.2μmol / L (0.5mg / dl); coagulation dysfunction; intestinal obstruction: absent bowel sounds; thrombocytopenia: platelet count (PLT) <10000 / μl; hyperbilirubinemia.

[0205] Tissue perfusion indicators: Hyperlactatemia (lactate > 1 mmol / L); decreased capillary reperfusion capacity or ecchymosis. SOFA score: For patients with infection or suspected infection, a sepsis-related sequential organ failure (SDFA) score that increases by ≥ 2 points from baseline can be used to diagnose sepsis. Because the SOFA score is relatively complex to perform, the bedside quick SOFA (qSOFA) criteria are often used clinically to identify critically ill patients. If at least two of the qSOFA criteria are met, combined with organ dysfunction assessment results, a preliminary assessment of sepsis status is made. The qSOFA criteria are as follows: respiratory rate ≥ 22 breaths / min; altered consciousness; systolic blood pressure ≤ 100 mmHg; Diagnostic criteria for severe sepsis and septic shock: Sepsis with organ dysfunction and / or tissue inadequacy caused by it, and any one of the following: Physical signs and clinical symptoms: Sepsis-related hypotension; urine output <0.5 ml / kg / h for at least 2 hours despite adequate fluid resuscitation; acute lung injury not caused by pneumonia with PaO2 / FiO2 <250 mmHg; acute lung injury caused by pneumonia with PaO2 / FiO2 <200 mmHg; Laboratory tests: lactate > normal value; serum creatinine >176.8 μmol / L (2.0 mg / dl); bilirubin >34.2 μmol / L (2 mg / dl); PLT <100,000 μl; Coagulation disorders (International Normalized Ratio > 1.5).

[0206] Currently, treatment for this disease can be broadly divided into three parts: etiological treatment, supportive treatment, and immunomodulatory treatment. Etiological treatment includes early clearance of infectious foci and the use of effective antibiotics. Supportive treatment includes early circulatory resuscitation, mechanical ventilation, renal replacement therapy, metabolic support, anticoagulation, and other measures targeting damage to different organs and systems. Immunomodulatory treatment mainly refers to treatment methods that can influence the body's immune inflammatory response.

[0207] The ADGRE3 mRNA and / or ADGRE3 protein levels discovered in this invention can reflect the etiological type of patients with systemic inflammation to a certain extent. On the one hand, this means differentiating between infectious and non-infectious inflammation from a broad classification perspective, as well as differentiating the severity of systemic inflammation, such as distinguishing between sepsis and septic shock, thereby avoiding the use of the aforementioned complex diagnostic indicators and improving the sensitivity, specificity, and accuracy of diagnosis. On the other hand, it means identifying the cause of the disease, such as distinguishing infectious inflammation caused by different pathogens, thereby assisting in etiological treatment and supportive treatment.

[0208] Sepsis has an extremely high mortality rate, but there is currently no technology to predict the risk of death for sepsis patients. The ADGRE3 protein content discovered in this invention can play a role in predicting the risk of death for patients. At the same time, by monitoring the expression level of ADGRE3 protein in neutrophils of patients every day, an accurate judgment can be made on whether the sepsis of patients has improved, thereby assisting clinical treatment.

[0209] Threshold (cut-off) Threshold definition: A threshold is a numerical value used to convert a continuous variable into a discrete variable, and is a critical value used to determine whether a result is positive or negative. It determines the classification of the result.

[0210] Setting a Cut-Off Threshold: Based on Reference Range: The normal range is a crucial basis for setting thresholds. Statistical analysis of samples from healthy individuals determines the normal reference range, which serves as an important reference for the threshold. Based on Disease Characteristics: Understanding the characteristics of the disease being tested is essential for setting thresholds. Some diseases may require higher or lower thresholds for accurate diagnosis. Based on Receiver Operating Characteristic (ROC) Curve: ROC curves help assess sensitivity and specificity at different thresholds, finding the optimal threshold for best diagnostic results. Based on Clinical Experience: Clinical experience plays a key role in setting thresholds. Laboratory experts should consider the needs and practicalities of clinicians, adjusting thresholds based on clinical experience. Based on Quality Control: Ensure the set thresholds meet quality control standards to guarantee the accuracy and reliability of results. Based on Standardized Guidelines: Refer to relevant standardized guidelines or recommendations from professional organizations, which can provide guidance for setting thresholds. Regular Review and Updates: Thresholds should be reviewed and updated regularly to ensure they remain consistent with the latest clinical practices and data.

[0211] Taking all the above factors into account, clinical laboratory diagnostic experts can set reasonable thresholds to ensure the accuracy of laboratory test results and the effectiveness of clinical diagnosis.

[0212] This invention detects the expression of ADGRE3 protein in neutrophils of healthy, non-inflammatory individuals using flow cytometry. The mean fluorescence intensity (MFI) of ADGRE3 protein in each sample is calculated, and the average MFI of ADGRE3 protein in healthy individuals is obtained. Under the same conditions, the average MFI of ADGRE3 protein in patient neutrophils is measured. The expression index (nADGRE3) of ADGRE3 protein in patient neutrophils is obtained by dividing the average MFI of ADGRE3 protein in patient neutrophils by the average MFI of ADGRE3 protein in healthy individuals. That is, nADGRE3 = MFI of ADGRE3 protein in patient neutrophils / MFI of ADGRE3 protein in healthy controls. Therefore, nADGRE3 in healthy controls is close to or equal to 1. Based on this, statistical analysis was performed on the sensitivity and specificity of nADGRE3 in infectious and non-infectious inflammatory responses, and the optimal cut-off value was determined to be 0.8361. Using the above method, a value greater than 0.8361 can be considered healthy or non-systemic inflammation (localized inflammation or non-inflammatory disease), while a value less than 0.8361 can be considered systemic inflammation. Calculating the neutrophil ADGRE3 protein expression index (nADGRE3) is merely one form of threshold setting and sample classification. Threshold setting and sample classification can also be performed based on ADGRE3 mRNA copy number, ADGRE3 protein content (mass or concentration), or any other known method; the diagnostic classification results will be the same.

[0213] The above is one method for setting thresholds for healthy individuals and systemic inflammation. However, it is understandable that the threshold setting will differ depending on the comparison objects. For example, when comparing the severity of systemic inflammation, the threshold setting is based on the comparison between different types of severity. To achieve differentiation, the values ​​of the same type of test generally need to show a significant difference (P < 0.05, or extremely significant difference P < 0.01; at least any corresponding level with a P value less than 0.05 can be used as a specific threshold value). The unit is determined based on different testing methods and reflects the difference in the level or content of the biomarker of this invention between the comparison objects. The unit of the threshold can be any unit, such as MFI, copy number, protein concentration, or any other unit that indirectly represents the content in the sample.

[0214] Regarding the determination of ADGRE3 mRNA or ADGRE3 mRNA fragment levels and the setting of thresholds, the detection methods and instruments used by various laboratories and testing institutions differ significantly, as do their data processing methods, especially in standardization algorithms. Therefore, it is difficult to specify an exact threshold. However, the significant difference in ADGRE3 mRNA levels between patients with systemic inflammation and healthy controls is an objective fact. Anyone skilled in the art can analyze healthy control and systemic inflammation patient samples based on their detection methods, instruments, and data analysis algorithms to derive an appropriate threshold for diagnosing systemic inflammation. All of the above falls within the scope of protection of this invention. Similarly, the threshold for ADGRE3 mRNA protein presents the same situation.

[0215] Early diagnosis of systemic inflammation, differentiation of infection types, prognosis assessment, disease monitoring, and guidance on antibiotic use, etc. Common laboratory indicators (1) C-reactive protein (CRP): C-reactive protein (CRP) is a protein synthesized in the liver, and its level usually increases during systemic inflammatory responses and tissue damage. Elevated CRP can be a non-specific response of the body to infection, inflammation, tissue damage, malignant tumors, etc.

[0216] In clinical practice, CRP is often used as an indicator to assess the degree of inflammation and monitor disease activity. In infectious diseases, CRP levels typically rise as inflammation persists and gradually decline after inflammation subsides or treatment is effective. Therefore, CRP can help physicians assess the severity of infection, guide treatment planning, and monitor treatment effectiveness.

[0217] It is important to note that while CRP is a commonly used inflammatory marker, it is not a highly specific indicator, as many other conditions can also cause elevated CRP levels, such as autoimmune diseases, cardiovascular diseases, and tumors. Therefore, when using CRP for clinical interpretation, a comprehensive assessment is necessary, combining the patient's clinical presentation, other laboratory test results, and imaging findings.

[0218] (2) Procalcitonin (PCT): PCT is a precursor protein that is typically elevated during infection and inflammatory responses. In systemic inflammatory responses and infections, procalcitonin levels usually increase significantly. Clinically, procalcitonin levels are commonly used to assess the severity of infection, guide antibiotic treatment decisions, and monitor patient response.

[0219] Elevated levels of procalcitonin in infections and inflammation may appear earlier than other inflammatory markers, thus possessing value for early diagnosis and prognostic assessment. Clinically, procalcitonin is frequently used to differentiate between bacterial and non-bacterial infections, guiding antibiotic use decisions, and is particularly important in critically ill patients, serving as a specific indicator for diagnosing bacterial infections.

[0220] It is important to note that procalcitonin levels are influenced by a variety of factors, including the type of infection, the site of infection, and the patient's immune status. Therefore, when using procalcitonin in clinical practice, it is necessary to conduct an assessment and decision based on a comprehensive evaluation of the patient's clinical presentation, other laboratory test results, and imaging findings.

[0221] (3) The CD64 infection index is a newly discovered specific indicator for bacterial infection in recent years. CD64 is a cell surface marker that is usually found on monocytes and neutrophils. CD64 expression increases significantly during bacterial infection and inflammation, and therefore it is used as a potential marker for bacterial infection.

[0222] The CD64 infection index is a method for assessing the severity of infection by measuring the expression level of CD64 on the surface of monocytes or neutrophils. During infection, the expression level of CD64 on the surface of neutrophils usually increases significantly; therefore, an elevated CD64 infection index may indicate the presence and severity of bacterial infection.

[0223] The CD64 infection index is used clinically to help differentiate between bacterial and non-bacterial infections and to assess the severity of infection. However, it is important to note that the CD64 infection index is not a tool for diagnosing infection alone; it needs to be comprehensively assessed in conjunction with the patient's clinical presentation, other laboratory test results, and imaging findings. Furthermore, the CD64 infection index may exhibit some variability across different laboratories and studies, therefore, careful interpretation is necessary in clinical application.

[0224] (4) CD169: Also known as Siglec-1, it is a membrane glycoprotein belonging to the Siglec protein family. CD169 is mainly expressed on the surface of dendritic cells and macrophages, and specifically binds to the glycosyl structure of extracellular viral particles, promoting viral phagocytosis and clearance. Therefore, CD169 plays an important role in infection detection. Studies have shown that CD169 expression levels are upregulated after viral infection, suggesting that CD169 may be an early indicator of viral infection. In hepatitis virus and HIV infections, CD169 expression is associated with viral transmission and clearance. Therefore, detecting the expression level of CD169 in viral infection can help understand the extent and severity of viral infection.

[0225] (5) HLA-DR: HLA-DR is an MHC II molecule in human leukocyte antigens, mainly expressed on the surface of antigen-presenting cells (such as dendritic cells and macrophages), and participates in regulating T cell immune responses. In infectious diseases, the expression level of HLA-DR can change, mainly manifested in the following two ways: Increased HLA-DR expression typically occurs in the early stages of infection and is an immune response to infection. During infection, immune cells are stimulated to release pro-inflammatory factors, which in turn stimulate antigen-presenting cells to express HLA-DR, thereby triggering a T-cell immune response. Increased HLA-DR can also serve as a biomarker for assessing early diagnosis and severity of infection.

[0226] Decreased HLA-DR expression often occurs in the late stages of infection and is a suppressive response of the body's immune function. In the days or weeks following infection, immune cells are subjected to prolonged stimulation and activation, easily leading to abnormal antigen-presenting cell function and immune exhaustion. At this time, HLA-DR expression usually decreases, indicating that the body's immune response has been suppressed. Decreased HLA-DR can also serve as a biomarker for assessing post-infection immunosuppression.

[0227] (6) Heparin-binding protein (HBP): This is a granular protein derived from neutrophils, mainly stored in azurophilic granules, with a small portion stored in secretory vesicles. HBP is a member of the serine protease family but has no protease activity. Its structure consists of a single-chain protein of 222 amino acids, containing 8 cysteine ​​residues, and glycosylation sites at aspartic acid residues at positions 100, 114, or 145. Its structure is similar to neutrophil elastin, with 45% homology.

[0228] It has a high affinity for lipopolysaccharide lipid A. Neutrophils degranulate upon activation, releasing hemoglobin (HBP). In acute bacterial infections, blood HBP concentrations can significantly increase within 1-2 hours, while in viral infections, HBP levels are not elevated or only slightly elevated. HBP also acts as a pathogenic factor; its concentration rapidly decreases after effective treatment. Therefore, detecting HBP levels in a patient's blood can assist in the clinical diagnosis and prediction of acute bacterial infections, assessment of infection severity, and monitoring of antibiotic efficacy. It is also a specific indicator for diagnosing bacterial infections.

[0229] (7) White blood cell count (WBC): White blood cells are part of the immune system, and their numbers usually increase during an inflammatory response. An elevated white blood cell count can reflect the presence and severity of inflammation.

[0230] (8) Neutrophil-to-Lymphocyte Ratio (NLR): NLR is the ratio of neutrophil count to lymphocyte count, and can be used as an indicator of inflammatory response and prognosis. High NLR is usually associated with poor prognosis.

[0231] (9) Platelet count: Platelet counts also change during an inflammatory response. Low platelet counts may be associated with systemic inflammation and an increased risk of bleeding.

[0232] (10) Serum lactate level: Elevated lactate levels may reflect tissue hypoxia and metabolic disorders, and are associated with severe infection and systemic inflammatory response.

[0233] The above indicators can be used as a reference for assessing the prognosis of patients with systemic inflammatory response, but a comprehensive evaluation is needed based on clinical manifestations, imaging examinations, and other information.

[0234] Specific biomarkers for diagnosing bacterial inflammation include, but are not limited to, CD64, PCT, and HBP. These biomarkers are specific to bacterial inflammation (an inflammatory response triggered by bacterial infection). When an individual experiences bacterial inflammation, the measured values ​​of CD64, PCT, and HBP increase. When an individual does not experience inflammation or experiences non-bacterial inflammation (e.g., viral inflammation, inflammation caused by autoimmune diseases), the measured values ​​of CD64, PCT, and HBP do not increase or increase only slightly. Some patients with non-bacterial inflammation may also have elevated CD64, PCT, and HBP levels, usually because a bacterial infection develops alongside the non-bacterial inflammation. Therefore, in some approaches, any specific indicator that can be used to diagnose bacterial infection can be combined with the biomarkers of this invention to diagnose and differentiate whether systemic inflammation is caused by bacterial infection, such as distinguishing between systemic inflammation caused by bacterial or viral infection, or distinguishing between bacterial and non-bacterial infections (e.g., systemic inflammation caused by viral infection or systemic inflammation caused by autoimmune diseases, organ transplant rejection).

[0235] For example, refer to Figure 32 When using flow cytometry, with a threshold of 0.8361, our biomarkers achieved a detection rate of 88.42% in patients with systemic viral infections. However, the detection rate of specific bacterial markers was very low, indicating that the bacterial infection markers, especially specific markers (PCT and nCD64), remained largely unchanged among these patients. Figure 32 The same situation occurs between systemic inflammation caused by autoimmune diseases or organ transplant rejection. Figure 33However, conversely, in patients with bacterial-induced systemic inflammation, the detection rate of this marker reached 97.68%, and in these patients with systemic inflammation, bacterial-specific markers were also significantly elevated, at least relative to the threshold (PCT and nCD64), with detection rates of 93% and 98%, respectively.

[0236] When we use this theory to conduct a reverse clinical trial, we randomly and blindly mix 100 healthy individuals (with localized infections or otherwise healthy populations), 100 patients with systemic inflammation caused by viral infections, 100 patients with systemic inflammation caused by autoimmune diseases or organ transplant rejection, and 100 patients with systemic inflammation caused by bacterial infections. We use the same threshold and simultaneously test using flow cytometry. Figure 31 The various biomarkers, including the protein biomarkers of this invention, showed high relevance to real-world conditions, distinguishing between healthy and systemic patients. Of the 295 patients diagnosed with systemic inflammation (a detection rate of 98%), 90 showed elevated levels of specific cells such as PCT and CD64, indicating that these 90 patients had systemic inflammation caused by bacterial infection. The remaining 205 patients did not show significant changes in PCT and CD64 levels. It is understood that using the biomarkers of this invention in combination with some bacterial infection-specific biomarkers can differentiate between bacterial and non-bacterial infections in patients with systemic inflammation. Non-bacterial infections include viral infections, autoimmune diseases, or systemic inflammation caused by organ transplantation. After differentiation, other clinical indicators or biomarkers can be used to further distinguish between viral infections, autoimmune diseases, or systemic inflammation caused by organ transplantation.

[0237] Therefore, this invention discovers that nADGRE3 can be combined with markers for diagnosing bacterial inflammation to classify patients with systemic inflammation or diagnose lesions. When a patient's nADGRE3 is known to be low, markers for diagnosing bacterial inflammation are detected. If the measured value is higher or lower than that of healthy individuals, the patient is diagnosed with bacterial systemic inflammation; otherwise, the patient is diagnosed with non-bacterial systemic inflammation. Patients can be further classified (classified as viral systemic inflammation or non-infectious systemic inflammation) based on clinical information, medical history, and other laboratory tests.

[0238] Diagnosis and Testing In this invention, "diagnosis or detection" refers to the detection or analysis of biomarkers in a sample, or the content of a target biomarker, such as absolute or relative content, and then using the presence or quantity of the target biomarker to indicate whether the individual providing the sample may have or suffer from a certain disease, or the likelihood of having a certain disease. The meanings of "diagnosis" and "detection" are interchangeable here.

[0239] The association between biomarkers or biomarkers and diseases: In this invention, biomarkers and biomarkers have the same meaning. The association here refers to the direct correlation between the presence or change in the level of a certain biomarker in a sample and a specific disease. For example, a relative increase or decrease in the level indicates whether the inflammation is localized, in a healthy person, or in a systemic inflammation. Furthermore, it allows for the classification of systemic inflammation and the categorization of its causes, such as infectious or non-infectious systemic inflammation.

[0240] Test reagents Any reagent or method capable of testing ADGRE3 mRNA or protein can be used in this invention. Examples include nucleic acid amplification reagents, in situ hybridization, nucleic acid-protein fusion techniques, and gene editing technologies, all of which can be used to test the level or quantity of ADGRE3 gene expression. Reagents for protein testing include any reagent capable of testing the protein of the gene, such as antibody reagents based on immunological principles. These antibodies can specifically bind to the protein or protein fragment. In some methods, the antibody specifically binds to the extracellular protein or protein fragment, or the extracellular amino acid sequence or peptide fragment. Testing methods can include transverse flow test strips, direct testing based on liquid chromatography-mass spectrometry, or testing based on principles such as flow cytometry or ELISA.

[0241] Antibody The antibody used in this invention can be any antibody capable of specifically binding to the analyte in a sample. Antibodies that can be used as binding agents can be any antibody known to those skilled in the art. An "antibody" can be an immunoglobulin molecule and the antigen-binding portion of an immunoglobulin molecule, i.e., a molecule containing an antigen-binding site that specifically binds to an analyte, analyte analog, or ligand ("immunoreaction"). This term also includes derivatives of antibodies in which binding ability is maintained, and any protein containing a binding domain homologous to or largely homologous to the binding domain of an immunoglobulin. These proteins may be derived from natural substances or may be partially or wholly synthetic. An antibody may be monoclonal or polyclonal. An antibody may be a member of any immunoglobulin type, including any human and mammalian immunoglobulin types: IgG, IgM, IgA, IgD, IgG, and IgE. An "antibody fragment" is a derivative of an antibody or a portion of an antibody less than its full length. An antibody fragment is capable of retaining at least one significant binding site of the full-length antibody. Examples of antibody fragments include Fab, Fab', F(ab')2, scFv, Fv, dsFv dimers, and Fd fragments, but not limited to these. Antibody fragments can be generated in any way. For example, antibody fragments can be generated by enzymatic or chemical cleavage of a complete antibody, or by recombination from a gene encoding a partial antibody sequence. In other words, antibody fragments can be generated by partial or complete recombination. Antibody fragments can be any single-chain antibody fragment. In other words, antibody fragments can contain multiple interconnected peptide chains, for example, linked by disulfide bonds. Antibody fragments can also be any type of multi-molecular complex. A functional antibody fragment typically contains at least about 50 amino acids, while more antibody fragments typically contain at least about 200 amino acids. Single-chain Fvs (scFvs) are recombinant antibody fragments that consist only of variable light chains (VL) and variable heavy chains (VH) covalently linked together by polypeptide chains. One of the VL and VH has an amino-terminal region. The length and composition of polypeptide chains are variable; the length allows two variable domains to bridge each other without significantly affecting the arrangement of atoms. Polypeptide chains are typically composed primarily of glycine and serine residues, with some glutamic acid and lysine residues scattered throughout to increase their solubility. A "dimer" refers to a dimer of single-chain FVS. The monomers of dimers typically contain shorter peptide chains than most single-chain FVS, and they exhibit a tendency to form dimers.

[0242] The “Fv” fragment consists of a VH and a VL domain non-covalently linked. The term “dsFv” here refers to an Fv containing a stable VH-VL pair of intermolecular disulfide bonds. The “F(ab’)” fragment is an antibody fragment, essentially identical to the fragment obtained by digesting immunoglobulins (usually IgG) with pepsin at pH 4.0–4.5. This fragment can also be recombinantly synthesized. The “Fab’” fragment is an antibody fragment, essentially identical to the fragment obtained by reducing the disulfide bonds connecting the two heavy chains on the F(ab’) fragment. The Fab’ fragment can also be recombinantly synthesized. The “Fab” fragment is an antibody fragment essentially identical to the fragment obtained by digesting immunoglobulins (usually IgG) with papain. The Fab fragment can also be recombinantly synthesized. The heavy chain fragments on the Fab fragment are Fd fragments. Detailed Implementation

[0243] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. These embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Unless otherwise specified, the experimental methods used in the following embodiments are conventional methods; the materials and reagents used, unless otherwise specified, are commercially available.

[0244] Example 1: Discovery of ADGRE3 as a biomarker for diagnosing systemic inflammation This invention initially aimed to identify genes playing a crucial role in the pathogenesis of sepsis. It analyzed and compared gene expression differences between sepsis patients and patients with non-infectious systemic inflammation in public databases, such as... Figure 1 As shown, the ADGRE3 gene was found to be significantly downregulated, suggesting that this gene could serve as a marker to distinguish sepsis patients from those with non-infectious systemic inflammation. Later, the changes in gene expression profiles between sepsis patients and healthy controls were analyzed, such as... Figure 2 As shown, the ADGRE3 gene was found to be significantly downregulated in sepsis patients, and the changes in ADGRE3 gene expression were extremely significant.

[0245] Then, we isolated the ADGRE3 gene and validated its expression changes in different infection types using public datasets; the specific results are as follows: Figures 3-11 As shown.

[0246] For example, such as Figure 3As shown, we analyzed 16 healthy control samples (labeled from public databases, individuals with healthy results from physical examinations), 23 samples from patients with systemic inflammation caused by bacterial infection, and 28 samples from patients with systemic inflammation caused by viral infection. We found that the expression of this gene in patients with systemic inflammation caused by bacterial or viral infection was significantly lower than that in healthy controls, indicating that this gene can be used to distinguish between healthy individuals and those with systemic inflammation caused by viral or bacterial infection. The AUC values ​​were: 0.9063 for distinguishing between healthy individuals and those with viral infection; and 0.9402 for distinguishing between healthy individuals and those with bacterial infection.

[0247] like Figure 4 As shown, we analyzed 33 healthy control samples, 18 samples from patients with systemic inflammation caused by Gram-positive bacterial infection, and 19 samples from patients with systemic inflammation caused by H1N1 virus infection. We found that the expression of this gene in patients with systemic inflammation caused by Gram-positive bacterial infection or H1N1 virus infection was significantly lower than in healthy controls, with a discriminant AUC of 0.8215. Specifically, the expression of the ADGRE3 gene in patients with systemic inflammation caused by Gram-positive bacterial infection was significantly lower than in patients with systemic infection caused by H1N1 virus infection.

[0248] like Figure 5 As shown, we analyzed 26 healthy control samples and 93 samples from patients with systemic inflammation caused by dengue virus infection. We found that the expression of this gene in patients with systemic inflammation caused by dengue virus infection was significantly lower than that in healthy controls, with a distinguishing AUC value of 0.8156.

[0249] like Figure 6 As shown, we analyzed 18 healthy control samples, 18 samples from patients with systemic inflammation caused by asymptomatic SARS-CoV-2 infection, and 11 samples from patients with symptomatic infection progressing to systemic inflammation. We found that the expression of the ADGRE3 gene was significantly lower in both asymptomatic SARS-CoV-2-induced systemic inflammation patients and symptomatic infection progressing to systemic inflammation patients compared to healthy controls. The AUC value distinguishing between healthy individuals and SARS-CoV-2 infection was 0.9502. This indicates that the expression of this gene, regardless of symptom presence, can confirm systemic inflammation caused by both healthy individuals and SARS-CoV-2 infection. However, there was no significant difference between systemic inflammation caused by asymptomatic SARS-CoV-2 infection and systemic inflammation progressing from symptomatic infection.

[0250] like Figure 7 As shown, we analyzed 31 healthy control samples and 107... indivualIn samples from patients with systemic inflammation caused by RSV (Respiratory Syncytial Virus) infection, the expression of this gene was found to be significantly decreased compared to healthy controls, with a discriminant AUC of 0.8936. However, with the implementation of treatment, in samples from patients who recovered from RSV-induced systemic inflammation, the expression of this gene returned to normal healthy levels. This indicates that the expression of this gene can predict the effectiveness of recovery, such as for monitoring or testing the effectiveness of treatments in relieving systemic inflammation.

[0251] like Figure 8 As shown, we analyzed 37 healthy control samples and 11 samples from patients with systemic inflammation caused by cytomegalovirus infection, and found that the expression of this gene was significantly lower than that of healthy controls, with a distinguishing AUC value of 0.9459.

[0252] like Figure 9 As shown, we analyzed 6 healthy control samples and 11 patients with systemic inflammation caused by EB virus infection and found that the expression of this gene was significantly lower than that of healthy controls, with a distinguishing AUC value of 0.9091.

[0253] The above-mentioned H1N1, dengue fever, COVID, RSV, cytomegalovirus and EB virus infections are typical systemic inflammation caused by several viral infections. It can be inferred that the expression of ADGRE3 gene is significantly decreased in patients with systemic inflammation caused by viral infections. Furthermore, the expression of ADGRE3 gene can be used to distinguish between healthy people and patients with systemic inflammation caused by viral infections.

[0254] like Figure 10 As shown, we analyzed 30 healthy control samples and 94 samples of patients with systemic inflammation caused by liver transplant rejection. We found that the expression of this gene was significantly decreased in patients with systemic inflammation caused by liver transplant rejection, with a distinguishing AUC value of 0.7220.

[0255] For non-infectious systemic inflammation and sepsis, such as Figure 11 As shown, the expression of this gene was significantly downregulated between sepsis patients and healthy individuals, and also significantly downregulated relative to non-infectious systemic inflammation. This indicates that this gene can be used to distinguish between healthy and sepsis patients (its AUC value was 0.920, as shown). Figure 12 Alternatively, it can also be used as a marker to differentiate between non-infectious systemic inflammation (SIRS) and sepsis, with an AUC value of 0.864 (e.g., Figure 13 ).

[0256] The above results were obtained through analysis of publicly available data. We further verified whether the expression of this gene or the content of this protein can be used clinically to diagnose systemic inflammation, as well as the treatment or prognosis of systemic inflammation, or the classification of systemic inflammation, using actual clinical samples obtained by our hospital.

[0257] Example 2: Differences in ADGRE3 mRNA transcription levels between healthy individuals and patients with viral infection The transcriptional level of ADGRE3 mRNA in leukocytes of clinical samples (blood) from various patients was detected by PCR-specific amplification. The specific method is as follows: I. RNA extraction from peripheral blood leukocytes 1. Centrifuge the blood in the anticoagulant tube at 4°C and 3000 rpm for 10 min, and transfer the serum to a 1.5 ml EP tube for storage (discard if the serum is not needed). 2. Add 3 ml of PBS to the anticoagulant tube, centrifuge at 3000 rpm for 10 min at 4°C, and discard the supernatant, being careful not to touch the middle white cell layer; 3. Prepare 1× erythrocyte lysis buffer (5ml:50ml), add 4ml of 1× erythrocyte lysis buffer to an anticoagulant tube, and lyse for 15 minutes (10× erythrocyte lysis buffer formula: 41.45g ammonium chloride and 42.00g sodium bicarbonate dissolved in 500mL sterile water, pH 7.2-7.4; Note: 10× erythrocyte lysis buffer should be diluted with pure distilled water). 4. After lysis, centrifuge at 2500 rpm for 5 min at 4℃, discard the supernatant, resuspend the white blood cell pellet in 1 ml PBS and aspirate it into a pre-prepared 1.5 ml EP tube; 5. Centrifuge at 2500 rpm for 5 min at 4℃, pipette the supernatant and add 1 ml of TRIZOL (TriQuick Reagent Total RNA Extraction Reagent, Beijing Solarbio Science & Technology Co., Ltd., China).

[0258] 6. Add 200 μL of chloroform to a 1.5 ml EP tube, invert to mix and shake vigorously for 10-15 seconds, then let stand at room temperature for 5 minutes; Centrifuge at 120,000 rpm for 15 minutes at 4℃ (pre-cool the centrifuge at 4℃ beforehand); 8. Gently aspirate the top aqueous phase (the middle layer is a white precipitate, and the bottom layer is a red organic layer) into a new 1.5 mL RNase-free EP tube, add an equal volume of isopropanol, invert to mix, and let stand at room temperature for 5 min. Centrifuge at 120,000 rpm for 30 minutes at 4℃ (pre-cool the centrifuge at 4℃ beforehand); 10. Discard the supernatant, add 1 mL of 75% ethanol, and mix well (75% ethanol should be prepared fresh for use; anhydrous ethanol should be diluted with water that does not contain RNase). 11. Centrifuge at 120,000 rpm for 10 min at 4℃; 12. Discard the supernatant and dry at room temperature for 5-10 minutes until the white precipitate becomes transparent. Then, add an appropriate amount of DEPC water (20-50 μL) to dissolve the RNA precipitate. II. Reverse Transcription 1. Perform reverse transcription according to the instructions of the HiFiScript cDNA Synthesis Kit (CW2569M, Kangwei Century Biotechnology Co., Ltd., China). Dissolve the relevant reagents on ice beforehand. Take 500 ng of the RNA extracted in the previous step and prepare the reaction system according to the following reverse transcription system, with a total reaction volume of 20 μL; the reverse transcription reaction system is shown in Table 1. Table 1: Reverse Transcription Reaction System 2. Briefly centrifuge to mix the reaction system, and then perform reverse transcription on a standard PCR instrument at 42℃ for 15 min and 85℃ for 5 min; 3. After the reaction is complete, remove the product, briefly centrifuge, and cool on ice; III. qPCR 1. Perform qPCR reactions according to the instructions of the NovoStart SYBR qPCR SuperMix Plus Kit (E096-01B, Shanghai Nearshore Technology Co., Ltd., China). Dissolve the template cDNA, primers, and related reagents on ice beforehand. Prepare the reaction system according to the following reverse transcription system, with a total reaction volume of 20 μL; the qPCR reaction system is shown in Table 2. Table 2: qPCR reaction system 2. Briefly centrifuge to mix the reaction system, then perform the reaction in a real-time PCR instrument under the following conditions: 95℃ pre-deformation for 1 min, followed by 95℃ denaturation for 20 s, and 60℃ extension for 1 min, for a total of 40 cycles. The melting curve parameters are: 95℃ for 15 s, 60℃ for 1 min, 95℃ for 15 s, and 60℃ for 15 s.

[0259] 3. Results Analysis: Using β-Actin / GAPDH mRNA expression levels as a standard control, the mRNA expression levels of the target genes were calculated using the 2-ΔΔCt method. ADGRE3 (EMR3) real-time PCR primers: Forward primer (5'->3'): TCCAGCACGTGAAGATGACC Reverse primer (5'->3'): ACGTGTATCAGGAAGCAGCC The leukocyte ADGRE3 mRNA transcription levels were measured in 20 healthy individuals (selected by our hospital based on normal results in all physical examinations), 39 patients with systemic influenza A and B virus infections (systemic inflammation), and 20 patients with systemic COVID-19 infection (systemic inflammation). The results are as follows: Figure 14 As shown, the leukocyte ADGRE3 mRNA transcription levels in patients with systemic influenza A and B viruses and patients with systemic COVID-19 virus infection were significantly different from those in healthy individuals, further suggesting that ADGRE3 mRNA can serve as a biomarker for diagnosing infection and systemic inflammation caused by viral infection.

[0260] Example 3: ADGRE3 mRNA transcription levels in healthy individuals and patients with non-infectious systemic inflammatory response syndrome Differences in The ADGRE3 mRNA transcription level in leukocytes was tested and compared in patients with non-infectious systemic inflammatory response syndrome (SIRS). Patients with SIRS caused by systemic lupus erythematosus (27), rheumatoid arthritis (25), vasculitis (10), and ankylosing spondylitis (15) were included in the study. Figure 15 As shown, the leukocyte ADGRE3 mRNA transcription level in healthy individuals differed significantly from that in patients with systemic inflammation associated with the four autoimmune diseases mentioned above. This suggests that this biomarker could be used to differentiate between healthy individuals and patients with non-infectious systemic inflammatory response syndrome.

[0261] Example 4: Differences in ADGRE3 mRNA transcription levels between healthy individuals and patients with sepsis The leukocyte ADGRE3 mRNA transcription levels in healthy individuals (20 cases) and sepsis patients (96 patients with systemic inflammation) were tested and compared. Figure 16 As shown, this again demonstrates a highly significant difference in ADGRE3 mRNA transcription levels in leukocytes between healthy individuals and sepsis patients. This biomarker can be used to distinguish between healthy individuals and sepsis patients.

[0262] Example 5: ADGRE3 protein expression levels in healthy individuals and patients with systemic inflammation caused by viral infection. Differences The experiments in Examples 2-4 demonstrated that the ADGRE3 mRNA transcription level in leukocytes can diagnose systemic inflammation, including viral infection, non-infectious systemic inflammatory response syndrome, and sepsis. This example further investigates the ADGRE3 protein expression level. The method for detecting the ADGRE3 protein expression level in neutrophils is as follows: Take a sample containing 1×10 6 Peripheral blood anticoagulated with EDTA or sodium citrate was collected from leukocytes. 2 μL of mouse anti-human ADGRE3 antibody labeled with different fluorescein was added to each sample, vortexed, and incubated at room temperature in the dark for 20 minutes. Then, 2 ml of erythrocyte lysis buffer was added, vortexed, and incubated for 15 minutes in the dark. The cells were centrifuged at 2000 rpm for 3 minutes, the supernatant was removed, and the cells were resuspended. 2 ml of phosphate-buffered saline or physiological saline was added, and the cells were centrifuged at 2000 rpm for 3 minutes. The supernatant was discarded, and the cell pellet was resuspended in phosphate-buffered saline. The cells were then analyzed using a flow cytometer (Beckman DxFLEX). During the flow cytometry analysis, gating was performed on neutrophils, monocytes, and lymphocytes based on the differences between FSC and SSC, and the average fluorescence intensity of ADGRE3 in neutrophils was calculated. The specific results are as follows: The expression levels of ADGRE3 protein in neutrophils were detected in healthy individuals (26 cases), patients infected with influenza A and B viruses (89 cases with systemic inflammation), patients infected with COVID-19 (22 cases with systemic inflammation), patients with dengue fever (5 cases with systemic inflammation), and patients infected with novel Bunyavirus (5 cases with systemic inflammation). The results are as follows: Figure 17 As shown, the expression level of ADGRE3 protein in neutrophils in healthy individuals differed significantly from that in patients infected with the aforementioned viruses. The expression level of ADGRE3 protein in neutrophils decreased significantly after each viral infection. This suggests that the expression level of ADGRE3 protein in neutrophils can differentiate between healthy individuals and patients with systemic inflammation induced by viral infection.

[0263] The expression of ADGRE3 in neutrophils of healthy, non-inflammatory individuals was detected by flow cytometry. The mean fluorescence intensity (MFI) of ADGRE3 in each sample was calculated, and the average MFI of ADGRE3 in healthy individuals was obtained. Under the same conditions, the mean MFI of ADGRE3 in patient neutrophils was detected. The expression index of ADGRE3 in patient neutrophils (nADGRE3) was obtained by dividing the mean MFI of ADGRE3 in patient neutrophils by the average MFI of ADGRE3 in healthy individuals. That is, nADGRE3 = MFI of ADGRE3 in patient neutrophils / MFI of ADGRE3 in healthy controls.

[0264] The ratio of different average fluorescence intensity values ​​was used as a threshold. A sample with an nADGRE3 greater than the threshold was diagnosed as a healthy person, while one with a nADGRE3 less than the threshold was diagnosed as a patient with systemic inflammation caused by viral infection (including systemic inflammation caused by influenza A and B viruses, COVID-19, dengue fever, and novel Bunyavirus). The sensitivity and specificity (sensitivity = number of true positives / (number of true positives + number of false negatives) * 100%; specificity = number of true negatives / (number of true negatives + number of false positives)) * 100% are shown in Table 3. ROC curves were then plotted based on this. Figure 18 As shown, the calculated AUC value was 0.9654, indicating that the expression level of ADGRE3 protein can diagnose systemic inflammation caused by viral infection.

[0265] Table 3: Neutrophil ADGRE3 protein expression level and its correlation with the diagnosis of systemic inflammation caused by viral infection. Based on the above results, the expression levels of ADGRE3 protein in neutrophils were further detected in healthy individuals (26 cases), patients with mild viral infection (36 cases with systemic inflammation), patients with severe viral infection (20 cases with systemic inflammation), and patients with critical illness (12 cases with systemic inflammation). The results are as follows: Figure 19 As shown, there were highly significant differences in the expression levels of ADGRE3 protein in neutrophils among healthy individuals, patients with mild, severe, and critical viral infections. The expression level of ADGRE3 protein in neutrophils decreased with increasing disease severity, suggesting that the expression level of ADGRE3 protein can be used as a basis for classifying patients with systemic inflammation caused by viral infections according to the severity of their condition.

[0266] This also illustrates that, although all patients experience systemic inflammation, the severity varies. The ADGRE3 protein expression level described in this invention can be used to classify patients with different degrees of systemic inflammation, facilitating timely and appropriate treatment. Furthermore, it can also serve as a biomarker for monitoring changes in severity, enabling disease monitoring or early warning.

[0267] Example 6: Differences in ADGRE3 protein expression levels between healthy individuals and patients with non-infectious systemic inflammation. Further investigation was conducted into the differences in ADGRE3 protein expression levels between healthy individuals and patients with non-infectious systemic inflammation. The expression levels of ADGRE3 protein in neutrophils from patients with autoimmune diseases were investigated. Neutrophil ADGRE3 protein expression levels were measured in healthy individuals (20 cases), patients with systemic inflammation caused by systemic lupus erythematosus (27 cases, including 14 stable patients and 13 active patients), patients with systemic inflammation caused by rheumatoid arthritis (31 cases, including 15 stable patients and 16 active patients), patients with systemic inflammation caused by vasculitis (12 cases), patients with systemic inflammation caused by ankylosing spondylitis (16 cases), and patients with systemic inflammation caused by autoimmune hepatitis (6 cases). The results are as follows: Figure 20 As shown, except for patients with stable rheumatoid arthritis, there were highly significant differences in neutrophil ADGRE3 protein expression levels between healthy individuals and patients with the other systemic inflammatory conditions mentioned above. This suggests that ADGRE3 protein expression levels can be used to diagnose autoimmune diseases.

[0268] It is noteworthy that among the aforementioned patients with systemic inflammation, there were highly significant differences in the expression levels of ADGRE3 protein in neutrophils between patients with systemic lupus erythematosus and those with rheumatoid arthritis during the stable and active phases. This suggests that the expression level of ADGRE3 protein can be used to diagnose autoimmune diseases, and that ADGRE3 can be used to differentiate between the stable and active phases of systemic lupus erythematosus and rheumatoid arthritis.

[0269] Non-infectious systemic inflammation also includes systemic inflammation caused by transplant rejection. This study selected 16 healthy individuals, 6 patients with systemic inflammation caused by kidney transplant rejection, and 8 patients with systemic inflammation caused by bone marrow transplant rejection. The expression level of ADGRE3 protein in their neutrophils was measured. Figure 21 As shown, the expression level of ADGRE3 protein in neutrophils in patients with systemic inflammation caused by rejection of kidney or bone marrow transplants was significantly lower than that in healthy individuals, suggesting that the expression level of ADGRE3 protein in neutrophils can distinguish between healthy individuals and patients with systemic inflammation caused by transplant rejection.

[0270] Other types of non-infectious systemic inflammation, due to their similar inflammation types, theoretically have similar neutrophil ADGRE3 protein expression levels to the systemic inflammation caused by the aforementioned autoimmune diseases and transplant organ rejection. Therefore, neutrophil ADGRE3 protein expression levels can distinguish between healthy individuals and non-infectious systemic inflammation.

[0271] The nADGRE3 of the sample was calculated according to the method in Example 5. The ratio of different average fluorescence intensity values ​​was used as a threshold. If the nADGRE3 of the sample was greater than the threshold, it was diagnosed as a healthy person; if it was less than the threshold, it was diagnosed as a patient with non-infectious systemic inflammation. The sensitivity and specificity are shown in Table 4. ROC curves were plotted accordingly. Figure 22 As shown, the calculated AUC value was 0.9145, indicating that the expression level of ADGRE3 protein can diagnose patients with non-infectious systemic inflammation.

[0272] Table 4: Neutrophil ADGRE3 protein expression level and its correlation with the diagnosis of non-infectious systemic inflammation. Example 7: Differences in ADGRE3 protein expression levels between healthy individuals and patients with sepsis. The expression level of ADGRE3 protein in neutrophils of sepsis patients was studied. The results of ADGRE3 protein expression level measurement in neutrophils of healthy individuals (23 cases) and sepsis patients (97 cases) are as follows: Figure 23 As shown, there is a highly significant difference in the expression level of ADGRE3 protein in neutrophils between healthy individuals and patients with sepsis, suggesting that ADGRE3 can be used to diagnose sepsis.

[0273] The nADGRE3 of the sample was calculated according to the method in Example 5. The ratio of different average fluorescence intensity values ​​was used as a threshold. Samples with an nADGRE3 greater than the threshold were diagnosed as healthy individuals, while those with an nADGRE3 less than the threshold were diagnosed as sepsis patients. The sensitivity and specificity are shown in Table 5. ROC curves were plotted accordingly. Figure 24 As shown, the calculated AUC value was 0.9973, indicating that the expression level of ADGRE3 protein can diagnose sepsis.

[0274] Table 5: Neutrophil ADGRE3 protein expression level and its diagnostic significance for sepsis The expression levels of ADGRE3 protein in neutrophils were detected in healthy individuals (23 cases), patients with sepsis caused by Gram-positive bacteria (33 cases), patients with sepsis caused by Gram-negative bacteria (44 cases), and patients with sepsis caused by fungal infections (10 cases). The results are as follows: Figure 25 As shown, the expression level of ADGRE3 protein in neutrophils of healthy individuals was significantly different from that of patients with the three types of sepsis, suggesting that ADGRE3 can be used to diagnose different types of sepsis.

[0275] Further research was conducted to investigate the correlation between ADGRE3 protein expression levels and sepsis severity. ADGRE3 protein expression levels in neutrophils were measured in healthy individuals (23 cases), sepsis patients (48 cases), and patients with septic shock (19 cases). The results are as follows: Figure 26As shown, there were highly significant differences in the expression levels of ADGRE3 protein in neutrophils among healthy individuals, sepsis patients, and patients with septic shock. Furthermore, the expression level of ADGRE3 protein in neutrophils decreased with increasing sepsis severity, suggesting that the expression level of ADGRE3 protein in neutrophils can be used to classify sepsis patients according to the severity of their disease.

[0276] Based on the survival and mortality of sepsis patients, a retrospective analysis was conducted on the expression levels of ADGRE3 protein in neutrophils during the course of the disease in sepsis survivors (50 cases) and patients who died from sepsis (18 cases). The results are as follows: Figure 27 As shown, there was a highly significant difference in the expression level of ADGRE3 protein in neutrophils between sepsis survivors and patients who died from sepsis, suggesting that the expression level of ADGRE3 protein in neutrophils can also be used to predict the risk of death in sepsis patients.

[0277] The nADGRE3 of the sample was calculated according to the method in Example 5. The ratio of different average fluorescence intensity values ​​was used as a threshold. When the nADGRE3 of the sample was greater than the threshold, the predicted mortality risk of sepsis patients was low; when it was less than the threshold, the predicted mortality risk of sepsis patients was high. The predicted mortality risk was compared with that of actual sepsis survivors and deceased patients, and its sensitivity and specificity were calculated as shown in Table 6. ROC curves were then plotted as follows. Figure 28 As shown, the calculated AUC value was 0.8374, indicating that ADGRE3 protein expression level can predict the risk of death in sepsis patients.

[0278] Table 6: Neutrophil ADGRE3 protein expression level and its correlation with mortality risk in sepsis patients Based on the improvement, no improvement (no improvement by day 7), or death of sepsis patients, a retrospective analysis was conducted on the neutrophil ADGRE3 protein expression levels on each day after diagnosis. The day of diagnosis was recorded as day 0. The results are as follows: Figure 29 As shown, the neutrophil ADGRE3 protein expression level in patients with improved sepsis was consistently higher than that in patients with no improvement or who died. Furthermore, the neutrophil ADGRE3 protein expression level in the improved sepsis group significantly increased over time, particularly from day 3 to day 5, while the neutrophil ADGRE3 protein expression level in the patients with no improvement or who died showed a decreasing trend during this period. Therefore, neutrophil ADGRE3 protein expression level can be used to predict whether sepsis will improve, especially by predicting future improvement in sepsis patients based on changes in ADGRE3 protein expression from day 3 to day 5.

[0279] Example 8: The expression level of ADGRE3 protein in neutrophils of healthy individuals and patients with non-systemic inflammation was not determined. Significant differences Example 1: Analysis of public data showed that ADGRE3 gene expression has high specificity in diagnosing systemic inflammation. Therefore, there should be no significant difference in ADGRE3 protein levels between healthy individuals and patients with non-systemic inflammation. To verify this, the ADGRE3 protein expression levels in neutrophils of healthy individuals (15 cases) and patients with localized inflammation (including 10 patients with hepatitis B, 6 patients with hepatitis C, and 7 patients with hepatitis E) were measured. The results are as follows... Figure 30 As shown, there was no significant difference in the expression level of ADGRE3 protein in neutrophils between healthy individuals and patients with localized inflammation.

[0280] Therefore, the expression level of ADGRE3 protein in neutrophils can be used to diagnose systemic inflammation without being affected by local inflammation, which verifies its high specificity.

[0281] Example 9: The role of neutrophil ADGRE3 protein combined with indicators such as CD64, PCT, and CRP in differentiating inflammation types. Application PCT (procalcitonin), CRP (C-reactive protein), IL-6, and the expression of CD64 infection index (nCD64 infection index) in peripheral blood neutrophils are commonly used biomarkers in clinical practice to reflect bacterial infection and the state of systemic inflammation. This study used flow cytometry to simultaneously detect the mean fluorescence intensity (MFI) of ADGRE3 in peripheral blood neutrophils from healthy controls (n=42), patients with systemic inflammatory responses to known pathogens (viruses, bacteria, and fungi) (n=218), patients with autoimmune diseases (n=92), and patients with transplant rejection (n=14). Using the mean fluorescence intensity (MFI) of ADGRE3 in peripheral blood neutrophils from healthy controls as a control, the relative expression level of ADGRE3 in peripheral blood neutrophils of patients with systemic inflammatory responses (nADGRE3) was calculated, i.e., nADGRE3 = (patient neutrophil ADGRE3 expression level). The ratio of mFI to (ADGRE3 MFI in healthy controls) was used to statistically analyze nADGRE3, setting the optimal cutoff value at 0.8361. nADGRE3 < 0.8907 was defined as a systemic inflammatory response. Simultaneously, serum PCT, CRP, IL-6, and nCD64 infection index data were collected and refined. Changes in nADGRE3, nCD64, PCT, CRP, and IL-6 in viral infection, sepsis, and non-infectious systemic inflammatory responses were statistically compared. The changes in nADGRE3, nCD64, PCT, CRP, and IL-6, along with the corresponding inflammation types (systemic inflammatory response due to viral infection, sepsis, and non-infectious systemic inflammatory responses including autoimmune diseases and transplant rejection), are shown in Table 7.

[0282] Table 7: Application of the combined neutrophil nADGRE3 index in differentiating inflammation types A comparison of neutrophil nADGRE3 with existing clinical inflammatory markers revealed that this marker has extremely high sensitivity in indicating systemic inflammation. More patients with systemic inflammation showed decreased neutrophil nADGRE3 levels, thus enabling a greater number of patients to be diagnosed based on laboratory results of reduced neutrophil nADGRE3. In contrast, existing clinical inflammatory markers have low sensitivity in patients with viral systemic inflammation or non-infectious systemic inflammation, potentially leading to misdiagnosis due to normal test results. Therefore, neutrophil nADGRE3 demonstrates a higher sensitivity in indicating systemic inflammation than currently used clinical markers, indicating that neutrophil nADGRE3 has high sensitivity in diagnosing systemic inflammation and thus higher diagnostic accuracy. Meanwhile, in diagnosing systemic inflammation, existing clinical inflammatory markers lack specificity and cannot rule out interference from local inflammation. Therefore, a comprehensive diagnosis often requires the integration of imaging findings. For example, a patient may have multiple localized inflammations that do not actually fall under the category of systemic inflammation (a common occurrence in patients with autoimmune diseases). If imaging indicates multiple sites of inflammation, combining existing clinical inflammatory markers may lead to a misclassification of the patient as having systemic inflammation. Neutrophil nADGRE3, however, possesses sufficiently high specificity, allowing for diagnosis without the need for imaging. When neutrophil nADGRE3 levels decrease, it specifically diagnoses systemic inflammation, ruling out interference from local inflammation. Therefore, compared to existing clinical inflammatory markers, neutrophil nADGRE3 has higher specificity for diagnosing systemic inflammation, resulting in a higher diagnostic accuracy.

[0283] Patients with systemic inflammation were classified according to etiology into those with systemic inflammatory responses caused by bacterial infections, those with systemic inflammatory responses caused by viral infections, and those with systemic inflammatory responses caused by autoimmune diseases and transplant rejection. Further classification was based on nADGRE3 and other inflammatory markers (CRP, PCT, IL-6, nCD64), as follows: Figure 31 , Figure 32 and Figure 33 As shown; Figure 31 Among patients with systemic inflammatory response caused by bacterial infection, 96.51% had decreased ADGRE3 protein expression levels. Among these patients, 92.86% had elevated CRP, 93.02% had elevated PCT, 96.42% had elevated IL-6, and 98.81% had elevated nCD64. Figure 32 Among patients with systemic inflammatory response caused by viral infection (a type of non-bacterial systemic inflammation), 88.42% had decreased ADGRE3 protein expression levels. Among these patients, 48.59% had elevated CRP, 0.93% (only 1 case) had elevated PCT, 64.48% had elevated IL-6, and 8.41% (only 9 cases) had elevated nCD64. Figure 33 In patients with systemic inflammatory responses caused by autoimmune diseases and transplant rejection (a type of non-bacterial systemic inflammation), the proportion of patients with decreased ADGRE3 protein expression was 79.25%. Some patients took immunosuppressive drugs or hormones, resulting in elevated ADGRE3 protein expression levels, which were classified as normal. Among patients with decreased ADGRE3 protein expression, the proportion of patients with elevated CRP was 61.90%, the proportion of patients with elevated PCT was 1.19% (only 1 case), the proportion of patients with elevated IL-6 was 53.57%, and the proportion of patients with elevated nCD64 was 8.33% (only 7 cases). In patients with systemic inflammatory responses caused by viral infections, autoimmune diseases, or transplant rejection, the proportion of patients with decreased ADGRE3 protein expression levels who also have elevated PCT and nCD64 is extremely low. This is because PCT and nCD64 are markers for diagnosing bacterial inflammation and are specific for diagnosing bacterial systemic inflammation. Elevated PCT and nCD64 levels are usually associated with bacterial infection. In addition, other markers for diagnosing bacterial inflammation include HBP (heparin-binding protein).

[0284] Therefore, the expression level of ADGRE3 protein in neutrophils can be combined with markers for diagnosing bacterial inflammation to classify and diagnose systemic inflammation, distinguishing between bacterial and non-bacterial systemic inflammation. Specifically, ADGRE3 protein expression level and markers for diagnosing bacterial inflammation are detected. If the expression level of ADGRE3 protein decreases and the levels of markers for diagnosing bacterial inflammation change, the diagnosis is bacterial systemic inflammation. If the expression level of ADGRE3 protein decreases but the levels of markers for diagnosing bacterial inflammation are normal, the diagnosis is non-bacterial systemic inflammation.

[0285] A "change" in the level of a marker for diagnosing bacterial inflammation means that the measured value of the marker is outside the range of the measured values ​​of healthy individuals. This includes both cases of being too high and too low, both of which indicate the presence of bacterial inflammation. A "normal" level in the level of a marker for diagnosing bacterial inflammation means that the measured value of the marker is within the range of the measured values ​​of healthy individuals, indicating that bacterial inflammation has not occurred.

[0286] Figure 34 This flowchart describes a process for diagnosing suspected systemic inflammatory responses (SIIRs) and classifying SIIRs as bacterial or non-bacterial. First, the nADGRE3 level of neutrophils in the patient is measured and calculated, then compared to a threshold of 0.8361. Levels above the threshold exclude SIIRs, while levels below the threshold confirm the diagnosis. Next, for confirmed SIIRs, indicators such as nCD64, PCT, and HBP are measured to diagnose bacterial SIIRs. Elevated levels suggest bacterial-induced SIIRs or SIIRs with bacterial infection. Normal levels suggest viral or non-infectious SIIRs, which can be further confirmed by combining clinical information and other laboratory tests. For example, a history of organ transplantation may indicate transplant rejection.

[0287] All patents and publications mentioned in this specification represent publicly available technology that can be used by this invention. All patents and publications cited herein are also listed in the references as individually referenced. The invention described herein can be implemented in the absence of any one or more elements, or one or more limitations, which are not specifically stated herein. For example, the terms “comprising,” “substantially consisting of,” and “consisting of” in each instance herein can be replaced by the other two terms. The term “an” herein simply means “one” and does not exclude the inclusion of only one, but may also indicate the inclusion of two or more. The terminology and expressions used herein are descriptive and not limiting, and there is no intention to suggest that the terms and interpretations described herein exclude any equivalent features; however, it is understood that any suitable changes or modifications can be made within the scope of this invention and the claims. It is understood that the embodiments described herein are preferred embodiments and features, and any modifications and variations can be made by those skilled in the art based on the spirit of the description, and such modifications and variations are also considered to fall within the scope of this invention and the limitations of the independent and appended claims.

Claims

1. The use of a biomarker in the preparation of a reagent for diagnosing systemic inflammation, characterized in that, The biomarkers include ADGRE3 mRNA or ADGRE3 mRNA fragments.

2. The use as described in claim 1, characterized in that, The diagnosis of systemic inflammation includes one or more of the following: diagnosing whether an individual has systemic inflammation, predicting the risk of an individual having systemic inflammation, monitoring the disease progression of patients with systemic inflammation, predicting the prognosis of patients with systemic inflammation, or providing medication guidance for patients with systemic inflammation.

3. The use as described in claim 1, characterized in that, The reagent for diagnosing systemic inflammation is used to detect ADGRE3 mRNA or ADGRE3 mRNA fragments in an individual sample, preferably, ADGRE3 mRNA or ADGRE3 mRNA fragments are present on or in leukocytes in the sample.

4. The use as described in claim 3, characterized in that, The samples include any one or more of peripheral blood, urine, secretions, pus, body fluids, spinal cord, and fresh tissue.

5. The use as described in claim 1, characterized in that, The systemic inflammation includes infectious systemic inflammation or non-infectious systemic inflammation.

6. The use as described in claim 5, characterized in that, The infectious systemic inflammation includes any one or more of bacterial, viral, fungal, and parasitic infections.

7. The use as described in claim 6, characterized in that, The viral infections include any one or more of the following: influenza virus infection, dengue virus infection, novel coronavirus infection, respiratory syncytial virus, cytomegalovirus, EB virus, and new Bunyavirus infection.

8. The use as described in claim 5, characterized in that, The non-infectious systemic inflammation includes any one or more of the following: autoimmune diseases, transplant rejection, inflammatory bowel disease, allergic reactions, metabolic diseases, and systemic inflammation caused by tissue damage.

9. The use as described in claim 8, characterized in that, The autoimmune diseases mentioned include any one or more of systemic lupus erythematosus, rheumatoid arthritis, vasculitis, and ankylosing spondylitis.

10. The use as described in claim 8, characterized in that, The systemic inflammation caused by transplant organ rejection includes systemic inflammation caused by any one or more of bone marrow transplantation, kidney transplantation, and liver transplantation.

11. The use as described in claim 1, characterized in that, The systemic inflammation includes sepsis.

12. The use as described in claim 11, characterized in that, The sepsis is caused by any one or more of the following infections: lung infection, biliary tract infection, urinary tract infection, gastrointestinal tract infection, bloodstream infection, reproductive tract infection, abdominal infection, central nervous system infection, skin and soft tissue infection, and purulent osteomyelitis.

13. The use of a biomarker in the preparation of a reagent for diagnosing whether an individual suffers from systemic inflammation due to bacterial or viral infection, characterized in that, The biomarkers include ADGRE3 mRNA or ADGRE3 mRNA fragments.

14. The use of a biomarker in the preparation of a reagent for diagnosing whether an individual suffers from systemic inflammation due to Gram-positive bacterial infection or systemic inflammation due to H1N1 infection, characterized in that, The biomarkers include ADGRE3 mRNA or ADGRE3 mRNA fragments.

15. The use of a biomarker in the preparation of a reagent for diagnosing whether an individual has systemic dengue fever inflammation, characterized in that, The biomarkers include ADGRE3 mRNA or ADGRE3 mRNA fragments.

16. The use of a biomarker in the preparation of a reagent for diagnosing whether an individual has systemic inflammation caused by COVID-19 infection, characterized in that, The biomarkers include ADGRE3 mRNA or ADGRE3 mRNA fragments.

17. The use as described in claim 16, characterized in that, The diagnosis of whether an individual has systemic inflammation caused by COVID-19 infection includes diagnosing patients with systemic inflammation caused by asymptomatic COVID-19 infection, or diagnosing patients with systemic inflammation caused by symptomatic COVID-19 infection.

18. The use of a biomarker in the preparation of a reagent for diagnosing whether an individual has systemic inflammation due to respiratory syncytial virus infection, characterized in that, The biomarkers include ADGRE3 mRNA or ADGRE3 mRNA fragments.

19. The use as described in claim 18, characterized in that, The diagnosis of whether an individual has systemic inflammation due to respiratory syncytial virus infection includes: whether the individual has experienced an acute respiratory syncytial virus infection, or whether the individual has recovered from systemic inflammation due to respiratory syncytial virus infection.

20. The use of a biomarker in the preparation of a reagent for diagnosing whether an individual has systemic inflammation due to cytomegalovirus infection, characterized in that, The biomarkers include ADGRE3 mRNA or ADGRE3 mRNA fragments.

21. The use of a biomarker in the preparation of a reagent for diagnosing whether an individual has systemic inflammation due to EB virus infection, characterized in that, The biomarkers include ADGRE3 mRNA or ADGRE3 mRNA fragments.

22. The use of a biomarker for preparing a reagent to distinguish an individual from one of a healthy person, a patient with non-infectious systemic inflammatory response syndrome, or a patient with sepsis, characterized in that, The biomarkers include ADGRE3 mRNA or ADGRE3 mRNA fragments.

23. The use as described in any one of claims 1-22, characterized in that, The ADGRE3 mRNA has any one or more of the nucleotide sequences shown in XM_054322398.1, XM_047439546.1, XM_011528374.3, NM_001289158.2, NM_001289159.2, and NM_032571.5.

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