Application of alarmin S100B in predicting the efficacy of JAK inhibitors in the treatment of alopecia areata

Abstract

The present invention relates to the use of serum alarmins as biomarkers for predicting the efficacy of JAK inhibitors in treating alopecia areata. In particular, S100A8 / A9 and S100B are the most preferred biomarkers. By measuring their concentrations in the serum of patients with alopecia areata, the efficacy of JAK inhibitors in treating alopecia areata can be effectively predicted, thereby providing valuable reference for selecting alopecia areata treatment regimen.

Description

Technical Field

[0001] The present invention belongs to the technical field of molecular diagnosis, and in particular relates to the application of serum alarmin as a biomarker in predicting the efficacy of JAK inhibitors in treating alopecia areata. Background Art

[0002] Alopecia areata (AA) is a common inflammatory, non-scarring hair loss. It is a local immune response of the hair follicles induced by the external environment under a certain genetic background. Alopecia areata is mainly caused by CD8+ / NKG2D+ T cells attacking the hair follicles themselves. Foreign studies have shown that the lifetime prevalence in the population is about 2%, and about half of the patients develop the disease before the age of 30. The specific pathogenesis of alopecia areata is still unclear. Existing studies have shown that it is mainly related to the loss of local immune privilege of the hair follicles, recognition of cytotoxic immune cells, and immune response of the hair follicles. Other factors, including mental and psychological factors, are also involved in the development of alopecia areata. Alopecia totalis and alopecia universalis are severe types of alopecia areata. They are often difficult to treat and are prone to relapse after improvement. There is currently no specific treatment.

[0003] In recent years, the recognition of the role of the JAK / STAT pathway in the pathogenesis of alopecia areata has led to the gradual entry of JAK inhibitors into the public eye. The JAK / STAT signaling pathway is widely present in the innate and adaptive immune systems and is involved in many important biological processes, including cell proliferation, differentiation, apoptosis, and immune regulation. JAK inhibitors have broad, relatively non-specific anti-inflammatory activity, can block multiple signaling pathways including type 1 and type 2 cytokines, and significantly reduce the number and activity of T cells, dendritic cells, and NK cells. The mechanism of JAK inhibitors in treating alopecia areata is mainly to inhibit the production of inflammatory factors by immune cells, and may also directly act on hair follicle epithelial cells to promote the hair follicle cycle into the growth phase.

[0004] Compared with traditional immunosuppressive drugs, JAK inhibitors have a narrower target and therefore fewer side effects. Baricitinib (JAK1 / 2 inhibitor) is the first drug approved by the FDA for the treatment of severe alopecia areata and was also approved in my country for the treatment of severe alopecia areata in adults in March 2023. Tofacitinib (JAK1 / 3 inhibitor) has been reported in multiple case reports and clinical studies at home and abroad for the treatment of alopecia areata in children and adults, with no serious adverse reactions.

[0005] Alarmins are a class of endogenous, constitutively expressed proteins or peptides released by cells during immune responses to infection or chemical, thermal, or physical damage. These include IL-1α, IL-33, the S100 protein family, ATP, high-mobility group protein B1 (HMGB1), and defensins. As an intercellular defense signaling mechanism, alarmins stimulate immune cells to participate in host defense by interacting with chemotactic and pattern recognition receptors (PRRs). They are considered endogenous damage-associated molecular patterns (DAMPs) and can induce sterile inflammation. Alarmin family molecules are universal markers of injury and early warning signals of the immune system. They participate in processes such as leukocyte chemotaxis, activation of various immune cells, and proliferation, thus playing a key role in determining the type of immune response.

[0006] In skin immunity, alarmin cytokines mediate complex intercellular communication between keratinocytes and immune cells to regulate cutaneous immune responses. Consequently, alarmins are elevated in affected organs and systems in patients with autoimmune skin diseases, such as systemic lupus erythematosus, dermatomyositis, vitiligo, psoriasis, and pemphigus. Some alarmin factors may serve as valuable biomarkers for disease diagnosis, disease activity, and prediction of treatment response, and modulation of alarmin-related pathways may have potential therapeutic applicability.

[0007] Studies on alarmins in alopecia areata are limited, and the alarmins involved include granulysin, IL-31, IL-1α, and HMGB1. Ono and Oba found that serum granulysin levels were significantly elevated in patients with alopecia areata, and that granulysin concentration correlated with the size of the hair loss area. Granysin may mediate immune attack on hair follicles and serve as a marker of acute disease activity. IL-1α is a key mediator of hair loss in alopecia areata. Studies have shown that serum IL-1α levels in AA patients are significantly higher than in controls, and that the IL-1α gene is closely associated with the onset of hair loss. Bain et al. found that IL-31 levels were significantly higher in patients with alopecia areata compared with healthy individuals. Saleem et al., through a review of 61 studies, concluded that IL-31 overexpression may contribute to hair loss. Furthermore, other authors have investigated the role of HMGB1 in alopecia areata. In subjects with alopecia areata, elevated serum levels of HMGB1 were observed immediately upon onset and persistently elevated in adverse responders, suggesting an inverse correlation between serum levels and treatment response.

[0008] So far, research on alarmins in alopecia areata is still very limited, especially the lack of research on the correlation between alarmin levels and the course, severity, and efficacy of alopecia areata, which has led to its inability to be used in the diagnosis and treatment of alopecia areata. Summary of the Invention

[0009] This study identifies candidate biomarkers based on the role of serum alarmins in the development and progression of alopecia areata. By exploring the differential expression of alarmins in alopecia areata and healthy individuals, and further analyzing their correlation with the efficacy of JAK inhibitors, we identify biomarkers that can be used to predict the efficacy of JAK inhibitors in treating alopecia areata.

[0010] The first aspect of the present invention provides biomarkers for predicting the efficacy of JAK inhibitors in treating alopecia areata: S100A8 / A9 and S100B. It has been found that combining multiple biomarkers can achieve even better predictive results. Therefore, the present invention further provides the following biomarker combinations:

[0011] (1) S100A8 / A9+S100B;

[0012] (2)S100A8 / A9+S100B+IgE.

[0013] In a preferred embodiment, the JAK inhibitor is baricitinib or tofacitinib.

[0014] The second aspect of the present invention provides a reagent for detecting the concentration of the above-mentioned biomarker in a sample, wherein the reagent can predict the efficacy of JAK inhibitors in treating alopecia areata by detecting the level of the biomarker.

[0015] The sample includes various biological samples derived from a subject, preferably blood, and more preferably serum.

[0016] The reagent can be used to measure the concentration of the biomarker by various conventional detection methods. The measurement can be performed at the protein level, mRNA level, gene expression (methylation) level, etc. For example, the measurement can be performed by enzyme-linked immunosorbent assay, quantitative PCR, methylation PCR, etc., preferably by enzyme-linked immunosorbent assay.

[0017] A third aspect of the present invention provides a kit for predicting the efficacy of alopecia areata treatment with a JAK inhibitor, comprising reagents for detecting the concentration of the aforementioned biomarkers in a sample. The biomarker may be a single biomarker or a combination thereof. In other words, the kit may include one or more reagents for detecting different biomarkers. For example, the kit may include a reagent for detecting S100A8 / A9, a reagent for detecting S100B, two reagents for detecting S100A8 / A9 and S100B, or three reagents for detecting S100A8 / A9, S100B, and IgE.

[0018] The kit can be a detection kit for determining the concentration of biomarkers in a sample by various conventional detection methods, and accordingly contains other necessary reagents required for the detection method. Preferably, the kit is an enzyme-linked immunosorbent assay kit, and contains other necessary reagents for enzyme-linked immunosorbent assay.

[0019] The positive progress of the present invention is that the present invention can simply measure the concentration of specific biomarkers in the serum of patients with alopecia areata, and use this to predict the efficacy of using JAK inhibitors to treat alopecia areata in these patients, thereby providing great reference value for the treatment of alopecia areata, and further providing great help for patients to rationally choose treatment plans, saving treatment time and costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The research design process of the present invention.

[0021] Figure 2 The SALT score measures area.

[0022] Figure 3 Scatter plot of correlation between baseline SALT and serum IgE and alarmin.

[0023] Figure 4 ROC curve of S100A8 / A9 in predicting the efficacy of JAK inhibitors in treating alopecia areata.

[0024] Figure 5 ROC curve of S100B predicting the efficacy of JAK inhibitors in treating alopecia areata.

[0025] Figure 6 ROC curve of HMGB1 predicting the efficacy of JAK inhibitors in the treatment of alopecia areata.

[0026] Figure 7 ROC curve of α-defensins in predicting the efficacy of JAK inhibitors in the treatment of alopecia areata.

[0027] Figure 8 ROC curve of IgE predicting the efficacy of JAK inhibitors in the treatment of alopecia areata.

[0028] Figure 9 ROC curve of S100A8 / A9+S100B combined to predict the efficacy of JAK inhibitors in treating alopecia areata.

[0029] Figure 10 ROC curve of S100A8 / A9+S100B+IgE combined to predict the efficacy of JAK inhibitors in the treatment of alopecia areata. DETAILED DESCRIPTION

[0030] The present invention is further illustrated by the following examples, but the present invention is not limited thereto. In the following examples, the experimental methods without specific conditions are generally carried out under conventional conditions or the conditions recommended by the manufacturer.

[0031] 1. Identify candidate biomarkers

[0032] It is well known that the prognosis of alopecia areata is closely related to factors such as disease course, severity, and age of onset. Studies in other alopecia areata treatments have demonstrated that treatment efficacy and adverse reactions can be predicted by pre-treatment laboratory tests. For example, baseline serum IgE levels can predict the efficacy of Dapoxetine and are associated with the incidence of adverse reactions during DPCP treatment. Alopecia areata prediction scores based on trichoscopes can predict the likelihood of hair regrowth in patchy alopecia areata. Currently, no biomarkers have been identified that can predict the efficacy of JAK inhibitors. JAK inhibitors are expensive, and their efficacy and safety are still uncertain. Therefore, early identification and confirmation of factors closely related to the efficacy of JAK inhibitors can provide a reference for selecting treatment options for patients with alopecia areata, saving patients time and treatment costs.

[0033] Epidermal-derived alarmin cytokines mediate complex intercellular communication between epidermal keratinocytes and immune cells, thereby regulating skin immune surveillance. Alarmins are endogenous molecules that act as danger signals and are rapidly released into the extracellular environment upon tissue damage, triggering a defensive immune response. A growing number of studies suggest that alarmins can also serve as biomarkers to monitor the therapeutic efficacy of autoimmune diseases. In patients with rheumatoid arthritis, serum S100A8 / A9 levels decrease after treatment with infliximab or anti-TNF-α therapy; serum S100A8 / S100A9 concentrations significantly decrease in patients with juvenile idiopathic arthritis after intra-articular triamcinolone acetonide treatment; and serum HMGB1 levels decrease in patients with granulomatosis with polyangiitis after treatment with statins or prednisolone. Serum alarmins can also predict patient prognosis and relapse. Relapse of ANCA-associated vasculitis is closely correlated with S100A8 / A9 levels.

[0034] S100A8 and S100A9 are the most abundant alarmins in many inflammatory diseases and belong to the S100 calcium-binding protein family. Members of the S100 protein family have tissue- or cell-type-specific expression patterns. All S100 proteins have two so-called EF-hand calcium-binding sites. Calcium binding to these calcium-binding sites induces conformational changes, leading to the S100 protein's interaction with different ligands or binding to specific receptors. A typical characteristic of most S100 proteins is the formation of homodimers, heterodimers, and / or higher oligomers. For example, S100A8 and S100A9 typically exist as heterodimers (S100A8 / A9), known as calprotectin. Intracellular S100 proteins are involved in numerous processes, including cell cycle control, proliferation, differentiation, migration, metabolism, cell dynamics, signal transduction, and cell death. High expression and release of different S100 proteins are closely associated with disease activity and have been found in many inflammatory diseases, such as rheumatoid arthritis (RA), inflammatory bowel or lung diseases, as well as Alzheimer's disease, cardiovascular disease and cancer.

[0035] S100 proteins are highly upregulated in various forms of childhood arthritis and autoimmune diseases. Activated phagocytes specifically secrete S100 proteins at sites of local inflammation, making these molecules useful markers for monitoring disease activity. S100A8 / S100A9 are currently the most specific biomarkers for the early diagnosis of systemic juvenile idiopathic arthritis. Furthermore, in clinical studies, they have been used to predict disease flare-ups in patients with JIA or RA who have achieved clinical remission on medication, either after discontinuation or dose reduction. In recent studies, S100B has been found to be useful for the diagnosis of vitiligo, with a sensitivity of up to 92.31%. Multivariate logistic regression analysis showed that S100B (OR, 1.019; 95% CI, 1.002-1.038; P = 0.03), S100A9 (OR 1.002; 95% CI, 1.001-1.003; 0.001), and HMGB1 (OR, 1.915; 95% CI, 1.186-3.091; P = 0.008) were significantly associated with vitiligo activity.

[0036] Recent studies have demonstrated that high-mobility group protein B1 (HMGB1) is expressed in skin and serum samples of alopecia areata, and serum HMGB1 levels are significantly elevated in patients with acute onset and poor treatment response. This suggests that HMGB1 can serve as a marker for assessing AA severity and may play a role in the pathogenesis of AA. HMGB1 was originally identified as a nuclear DNA-binding protein, but during inflammation, it can be secreted by cells and act as a proinflammatory cytokine. HMGB1 has been reported to be elevated in several autoimmune diseases, including rheumatoid arthritis, systemic lupus erythematosus, and systemic sclerosis. Recent studies have revealed a novel mechanism for HMGB1 release during inflammation: cells in the outer root sheath (ORS) of the human hair follicle constitutively express inflammasome proteins; activation of the NLRP3 inflammasome by dsRNA leads to the release of IL-1β and HMGB1 from ORS cells, demonstrating that the inflammasome plays a key role in mediating HMGB1 release from immune cells.

[0037] Defensins are a class of cationic host defense peptides primarily synthesized by Paneth cells, neutrophils, and epithelial cells, participating in host defense. Based on amino acid homology and cysteine ​​residue linkage, mammalian defensins are classified as α-defensins (α-DF), β-defensins (β-DF), and θ-defensins (θ-DF). However, humans only produce α- and β-defensins. Defensins play a role in numerous biological processes, including immunomodulatory and chemotactic activities, maintaining mucosal barrier function, balancing the intestinal microbiota, regulating organ development, and cell death. Consequently, defensins have gradually been recognized as innate immune factors. Over the past two decades, defensins have been found to regulate immune cell chemotaxis and participate in the regulation of sperm motility, male infertility, thrombosis, melanin deposition, and other important biological functions. Furthermore, defensins have been shown to induce innate and adaptive immune responses in the host, promoting the activation of immune cells such as T cells and macrophages.

[0038] Based on an extensive literature review, this study identified serum levels of the alarmins S100A8 / A9, S100B, HMGB1, α-defensins, and IgE as candidate biomarkers for predicting prognosis and recurrence of alopecia areata treated with JAK inhibitors. These alarmin molecules are known in the art, including human S100A8, human S100A9, human S100B, human HMGB1, and human α-defensin, with GenBank Gene IDs 6279, 6280, 6285, 3146, and 1667, respectively. The structure of IgE is also well known in the art.

[0039] 2. Research subjects

[0040] 2.1 Case Source

[0041] This study was a case-control study that adhered to the ethical guidelines of the Declaration of Helsinki and was approved by the Ethics Committee of the Eastern Theater Command General Hospital. Informed consent was obtained from patients or their guardians. The case group consisted of patients aged 7 years and older with alopecia areata who visited the dermatology outpatient clinic of the Eastern Theater Command General Hospital between October 2022 and December 2023. All patients were diagnosed with alopecia areata by two experienced dermatologists based on the clinical manifestations, dermoscopy, and scalp biopsy (if necessary) outlined in the Chinese Guidelines for the Diagnosis and Treatment of Alopecia Areata (2019). The control group consisted of the general population who underwent physical examinations at our hospital's physical examination center during the same period and were excluded from a diagnosis of alopecia areata. A total of 35 cases and 32 controls were enrolled. Eighteen patients in the case group met the diagnostic criteria for moderate-to-severe or refractory alopecia areata, and the patients and their guardians consented to treatment with JAK inhibitors. The demographic and clinical characteristics of the subjects in each group are shown in Table 1. The mean age of the case and control groups was 27.63 ± 12.4 years and 25.65 ± 4.76 years, respectively. There was no statistically significant difference in age and gender among the groups (P>0.05).

[0042] Table 1 Baseline characteristics of the study population

[0043]

[0044]

[0045] 2.2 Inclusion criteria for JAK inhibitor treatment group

[0046] (1) Aged 7 to 60 years old, regardless of gender;

[0047] (2) meeting the diagnostic criteria for moderate to severe alopecia areata (SALT score > 50%, or combined dermoscopy and skin histopathology diagnosis);

[0048] (3) Meet the diagnostic criteria for refractory alopecia areata: have undergone at least three or more other treatments without recovery or have had no response to local treatment for 6 months.

[0049] Conditions (1)(2) or (1)(3) must be met simultaneously.

[0050] 2.3 Exclusion criteria for JAK inhibitor treatment group

[0051] (1) Lymphocyte count (ALC) less than 0.5×10 9 / L; neutrophil count (ANC) less than 1×10 9 / L; hemoglobin value less than 8g / dL; platelet count less than 50×10 9 / L;

[0052] (2) active tuberculosis;

[0053] (3) renal impairment; creatinine clearance <30 mL / min;

[0054] (4) severe liver damage;

[0055] (5) active hepatitis B or hepatitis C infection;

[0056] (6) Allergic reaction to the active substance or any excipients;

[0057] (7) severe active infection;

[0058] (8) coagulation disorders;

[0059] (9) pregnancy or breastfeeding;

[0060] (10) Unwilling to sign the informed consent form.

[0061] 2.4 Exit criteria:

[0062] (1) Serious adverse events or patient death occurred during treatment;

[0063] (2) Those who receive other treatments or drugs during treatment;

[0064] (3) Those who voluntarily withdraw from the treatment or fail to follow the prescribed treatment plan, resulting in incomplete data and inability to accurately judge the efficacy.

[0065] 3. Research Methods

[0066] 3.1 Research indicators

[0067] Patients with alopecia areata underwent physical examinations, and detailed information was recorded regarding age of onset, progression of the disease, number of episodes, area of ​​hair loss, subjective symptoms, nail lesions, and previous treatment regimens. Two experienced dermatologists assessed the severity of the disease using the Scoring of Alopecia Tool (SALT). Treatment efficacy was evaluated using the Clinical Efficacy Scale.

[0068] 3.1.1 SALT score

[0069] The SALT score is calculated by measuring the percentage of hair loss in each of the four scalp regions: right side (18% of the total scalp area), left side (18%), top (40%), and occipital (24%) (see Figure 2 ) and uses the weighted sum of the percentages of hair loss in the four areas to create a composite score, the SALT score. A SALT score of 0 indicates no hair loss, while a SALT score of 100 indicates complete hair loss.

[0070] 3.1.2 Clinical efficacy evaluation level

[0071] The clinical efficacy evaluation grades are divided into the following 4 levels:

[0072] Cure: The hair scalp coverage area is 90% < n ≤ 100%; all new hairs have grown out, densely distributed, and the thickness and color of the hairs are the same as those of normal hair, and the hair pull test is (-);

[0073] Marked effect: 50% ≤ n < 90%; a large number of vellus hairs have become thick hairs, and the hair pull test is (-);

[0074] Improvement: 10% ≤ n < 50%; new hairs grow, but the growth is slow, and the hair pull test is (±); [[ID=​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​Ultra-low temperature (-80°C) refrigerator, purchased from Qingdao Haier Special Electric Appliance Co., Ltd.;

[0087] The microplate reader was purchased from Thermo Fisher, USA.

[0088] 3.3 Data Analysis

[0089] SPSS 27.0 data classification software was used for data processing and statistical analysis. An Excel database was established to record baseline and clinical data. Continuous variables were tested for normality using the Shapiro-Wilk test (sample size ≤ 50) or the Kolmogorov-Smimov test (sample size > 50), and homogeneity of variance was tested using the Levene test. Means for normally distributed data were expressed as mean ± standard deviation, and mean values ​​for skewed data were expressed as median (interquartile range). Continuous variables with normal distribution and homogeneity of variance were compared between two groups using the independent sample t-test; continuous variables that did not meet normality or homogeneity of variance were compared between two groups using the Mann-Whitney U test. Categorical variables were expressed as case numbers and percentages. Unordered categorical variables were compared between two groups using the chi-square test or Fisher's exact test. When the total sample size was less than 40 or the theoretical frequency was greater than 1 but less than 5, the chi-square test with continuity correction was used. Ordered categorical variables were compared between two groups using the Kruskal-Wallis H test.

[0090] The test level was 0.05, and the difference was statistically significant when p < 0.05.

[0091] Example 1 Analysis of serum biomarkers in patients with alopecia areata

[0092] According to the above method, the serum S100A8 / A9 (ng / mL), S100B (pg / mL), HMGB1 (pg / mL), α-defensin (pg / mL), and IgE (ng / mL) levels of 35 cases in the case group (moderate to severe alopecia areata patient group A1-A19, mild alopecia areata patient group B1-B16) and 32 cases in the control group (C1-C32) were measured and statistical analysis was performed in groups.

[0093] 1. Comparison of serum S100A8 / A9, S100B, HMGB1, α-defensin, and IgE levels between the case group and the control group

[0094] The serum levels of S100A8 / A9, S100B, HMGB1, α-defensin, and IgE in the case group were 3008.43±1016.21, 482.07 (402.52, 536.70), 59.49 (0, 536.70), 233.79 (199.38, 250.99), and 67.6 (34.9, 215.5), respectively, while those in the control group were 2176.93±1194.23, 388.06 (0, 521.02), 0 (0, 84.70), 215.87 (78.80, 269.61), and 43.8 (27.6, 79.15), respectively. The baseline serum S100A8 / A9, S100B, and HMGB1 levels in the alopecia areata case group were higher than those in the control group, and the differences were statistically significant (P < 0.05). There were no statistically significant differences in the serum α-defensin and IgE levels between the case group and the control group (P > 0.05).

[0095] Table 2 Comparison of serum biomarker levels between case group and control group

[0096]

[0097]

[0098] 2. Comparison of serum S100A8 / A9, S100B, HMGB1, α-defensin, and IgE levels among patients with different severity

[0099] The serum levels of S100A8 / A9, S100B, HMGB1, α-defensin, and IgE in patients with moderate to severe alopecia areata were 3036.26±1241.32, 535.25 (477.18, 587.52), 103.58 (0, 503.50), 229.88 (199.97, 259.03), and 93.8 (35.1, 230), respectively, while those in patients with mild alopecia areata were 2975.37±699.68, 424.86 (250.20, 465.39), 42.95 (0, 165.18), 237.08 (197.55, 248.86), and 47.85 (36.25, 168), respectively. The serum S100B level in patients with moderate to severe alopecia areata was significantly higher than that in the mild alopecia areata group (P=0.041). There was no statistical difference in the serum S100A8 / A9, HMGB1, α-defensin, and IgE levels between patients with mild and moderate to severe alopecia areata.

[0100] Table 3 Comparison of serum biomarker levels among different severity levels of alopecia areata

[0101]

[0102] There was no significant correlation between baseline SALT scores and serum biomarkers in patients with alopecia areata (see Figure 3 ).

[0103] Example 2 Clinical study on the treatment of moderate to severe alopecia areata with JAK inhibitors

[0104] This study enrolled 18 eligible patients with moderate to severe or refractory alopecia areata, aged 8 to 43 years (25.11 ± 11.75 years), with a male to female ratio of 2.6:1 and a disease duration of 6 months to 19 years. All 18 patients received oral treatment with the JAK inhibitor tofacitinib at a dose of 10 mg / day and were followed up monthly.

[0105] Pre-treatment SALT scores were 70.97±33.80 in 18 patients. For 18 patients treated for 12 weeks or longer, the SALT score at week 12 was 60.59±33.23, with an effective rate of 66.7%. For 7 patients treated for 24 weeks or longer, the SALT score at week 24 was 25.81±20.94, with an effective rate of 100%. For 4 patients treated for 36 weeks or longer, the SALT score at week 36 was 7.5±10.95, with an effective rate of 100%. SALT scores at weeks 12, 24, and 36 were significantly lower than those before treatment (P < 0.05).

[0106] The total effective rate of JAK inhibitors in treating patients with moderate to severe alopecia areata was 66.7%. Among all patients who received JAK inhibitors, 2 were cured, 3 were significantly effective, 7 were improved, and 6 were ineffective (see Table 4).

[0107] Table 4 Treatment effect

[0108]

[0109] Table 5 Changes in SALT scores during treatment

[0110]

[0111] No serious adverse reactions were reported by any patient during treatment. Five patients reported mild adverse reactions, including upper respiratory tract infection (n=3, 16.67%), acne (n=3, 16.67%), and mild elevation of liver transaminases (n=1, 5.56%).

[0112] Example 3 Study on the Prediction of the Efficacy of JAK Inhibitors in Treating Alopecia Areata

[0113] The serum levels of S100A8 / A9, S100B, HMGB1, α-defensin, and IgE in all 18 patients who received JAK inhibitors before treatment were counted (see Table 6). All patients were divided into groups according to whether the treatment was effective (cured + markedly effective + improved) or not (ineffective). ROC curves were constructed using various biomarkers alone and in combination ( Figures 4 to 10 ), and the analysis results are summarized in Table 7.

[0114] Table 6 Serum biomarkers and efficacy of patients in the treatment group

[0115]

[0116]

[0117] Table 7 Predictive effects of different markers

[0118]

[0119] As shown in Table 7, the AUC value of α-defensin as a biomarker for predicting the efficacy of JAK inhibitors in treating alopecia areata was less than 0.5, which did not conform to the theoretical design and indicated data errors, so it was discarded. The AUC value of HMGB1 was 0.604, indicating that HMGB1 had low predictive value for the efficacy of JAK inhibitors in treating alopecia areata and was discarded. The AUC values ​​of S100A8 / A9, S100B, and IgE were 0.740, 0.753, and 0.721, respectively, indicating that they had high predictive value for the efficacy of JAK inhibitors in treating alopecia areata. However, the sensitivity corresponding to the optimal cutoff value for IgE was 0.455, which lacked practical value and was also discarded. In summary, S100A8 / A9 and S100B are biomarkers with high predictive value for the efficacy of JAK inhibitors in treating alopecia areata.

[0120] When S100A8 / A9 and S100B were combined to predict the efficacy of JAK inhibitors in treating alopecia areata, the AUC value further increased to 0.805, and the optimal cutoff value was 0.766. At this time, the sensitivity and specificity were 0.909 and 0.857, respectively, and the diagnostic value was further increased.

[0121] When S100A8 / A9, S100B and IgE were combined to predict the efficacy of JAK inhibitors in treating alopecia areata, the AUC value further increased to 0.896, and the optimal cutoff value was 0.766. At this time, the sensitivity and specificity were 0.909 and 0.857, respectively, and the diagnostic value was further increased.

[0122] The above specific embodiments are only for the purpose of illustrating the present invention in detail and should not be construed as limiting the scope of protection of the present invention. Technical solutions described in the implementation but not claimed in the claims should not be construed as a waiver of the patent rights.

Claims

1. Use of S100B in the preparation of a reagent for predicting the efficacy of alopecia areata treated with a JAK inhibitor, wherein the JAK inhibitor is baricitinib or tofacitinib.

2. Use of S100B and S100A8 / A9 in the preparation of a reagent for predicting the efficacy of alopecia areata treated with a JAK inhibitor, wherein the JAK inhibitor is baricitinib or tofacitinib.

3. Use of reagent A in the preparation of a kit for predicting the efficacy of alopecia areata treated with a JAK inhibitor, wherein: The reagent A is used to determine the S100B concentration in the serum of a subject, and the JAK inhibitor is baricitinib or tofacitinib.

4. The use according to claim 3, wherein: The kit also contains a reagent B for determining the concentration of S100A8 / A9 in the serum of a subject.

5. The use according to claim 3 or 4, wherein: The concentrations of S100B and / or S100A8 / A9 in the serum of the subjects were measured by enzyme-linked immunosorbent assay.

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