A biomarker for aiding in the diagnosis or diagnosis of graves ophthalmopathy and / or graves disease

Abstract

The application provides a biomarker for assisting in diagnosing or diagnosing Graves' ophthalmopathy and / or Graves' disease, and the Graves' ophthalmopathy and / or Graves' disease is identified by the biomarker, and the biomarker comprises tryptophan metabolites, and the tryptophan metabolites comprise indolepropionic acid, indole-3-lactic acid and / or indoleacetic acid; the application innovatively finds that, compared with a healthy control group, the levels of indolepropionic acid, indole-3-lactic acid and indoleacetic acid in serum of Graves' disease and Graves' ophthalmopathy patients are significantly reduced, and the level of indoleacetic acid of the Graves' ophthalmopathy patients is further reduced than that of the Graves' disease patients; it is indicated that the tryptophan metabolites comprising indolepropionic acid, indole-3-lactic acid and / or indoleacetic acid can be used for assisting in diagnosing or diagnosing Graves' ophthalmopathy and / or Graves' disease, and can be used as a biomarker for assisting in diagnosing or diagnosing Graves' ophthalmopathy and / or Graves' disease.

Description

Technical Field

[0001] This invention relates to the field of biotechnology, and more specifically to a biomarker for assisting in the diagnosis of Graves' eye disease and / or Graves' disease. Background Technology

[0002] Graves's eye disease (GO), also known as thyroid-associated ophthalmopathy or thyroid eye disease, is essentially an organ-specific autoimmune disease closely related to thyroid dysfunction. It is most common in patients with hyperthyroidism, but can also be found in individuals with normal or hypothyroid function. Typical symptoms of GO, such as eyelid retraction, proptosis, and decreased vision, impose a significant burden on society and families, and significantly impact patients' health and quality of life. Despite this, the exact pathogenesis of GO is not fully understood. Currently, treatment options are limited, and clinical treatment mainly relies on symptomatic management. Therefore, from a clinical practice perspective, identifying disease-related biomarkers to identify patients with active GO is particularly important. A deeper understanding of the pathophysiological mechanisms of GO can help reveal new therapeutic targets that can complement existing treatments and potentially provide personalized treatment plans for GO patients.

[0003] Gonorrhea (GO) progresses through two phases: an active phase and an inactive phase. Clinically, the active phase is characterized by inflammation, manifesting as periorbital pain, eyelid swelling, conjunctival hyperemia, proptosis, and diplopia. The inactive phase is characterized by relatively stable symptoms and reduced inflammation, but may leave sequelae such as proptosis, diplopia, and eyelid retraction. Treatment strategies differ between the active and inactive phases. The active phase generally focuses on aggressive anti-inflammatory and immunosuppressive therapy, while the inactive phase primarily involves surgical correction. Currently, the 2021 EU Clinical Guidelines for Thyroid Ophthalmopathy (GOGO) are used to diagnose both active and inactive phases of GO. However, this method, which assesses activity through the Clinical Activity Score (CAS), has a degree of subjectivity. Therefore, researchers are actively seeking more objective and accurate biomarkers to aid in the diagnosis of GO and the assessment of active GO. These biomarkers may be derived from blood, urine, or other bodily fluids; analyzing changes in their content or proportion can more accurately reflect the pathological state of GO patients. However, there are currently no reported studies on the application of tryptophan metabolites in the diagnosis of GO progression.

[0004] The pathogenesis of orbital fibroblasts (GO) mainly involves the activation of orbital fibroblasts (OFs), the infiltration of immune cells, and the deposition of hyaluronic acid. These factors collectively lead to the expansion of orbital tissues and muscle hypertrophy. Activated OFs can differentiate into myofibroblasts and produce extracellular matrix components, which play a crucial role in the inflammatory response and tissue remodeling of GO. To date, research on the effects of tryptophan metabolites on OFs in GO remains lacking. Summary of the Invention

[0005] Therefore, the first technical problem to be solved by the present invention is to provide a biomarker for assisting in the diagnosis or diagnosis of Graves' eye disease and / or Graves' disease, through which Graves' eye disease and / or Graves' disease can be identified.

[0006] The second technical problem to be solved by the present invention is to provide the use of tryptophan metabolites in the preparation of medicaments for adjuvant or therapeutic treatment of Graves' eye disease, thus providing a new treatment option for Graves' eye disease.

[0007] Therefore, the present invention provides the following technical solution:

[0008] This invention provides a biomarker for assisting in the diagnosis of Graves' eye disease and / or Graves' disease, the biomarker including tryptophan metabolites, including indolepropionic acid, indole-3-lactic acid and / or indoleacetic acid.

[0009] The present invention provides the use of products for detecting the biomarkers described above for assisting in the diagnosis or diagnosis of Graves' eye disease and / or Graves' disease in the preparation of products for assisting in the diagnosis or diagnosis of the course of Graves' eye disease.

[0010] In some embodiments, the course of Graves' eye disease includes active Graves' eye disease and inactive Graves' eye disease.

[0011] And / or, the biomarker includes tryptophan metabolites, which include indoleacetic acid.

[0012] The present invention provides the use of products that detect the aforementioned biomarkers for the auxiliary diagnosis or diagnosis of Graves' eye disease and / or Graves' disease in the preparation of products for the auxiliary identification or differentiation of Graves' eye disease and Graves' disease.

[0013] In some embodiments, the product includes reagents, test strips, kits, or instruments.

[0014] This invention provides a product for assisting in the diagnosis or diagnosis of the course of Graves' eye disease, wherein the product is a system for assisting in the diagnosis or diagnosis of the course of Graves' eye disease, comprising:

[0015] A detection unit, wherein the detection unit is used to obtain the content of the biomarker in the sample to be tested; the biomarker is the aforementioned biomarker;

[0016] The judgment unit is connected to or wirelessly connected to the detection unit. The judgment unit is used to diagnose or assist in the diagnosis of the course of Graves' eye disease based on the content of biomarkers in the sample to be tested.

[0017] In some implementations, the method includes: determining the course of Graves' eye disease by comparing the indoleacetic acid (IAA) levels in patients with active Graves' eye disease with those in inactive phases.

[0018] And / or, the sample to be tested in the detection unit is selected from blood, serum, or plasma.

[0019] The present invention provides the use of tryptophan metabolites in the preparation of medicaments for adjunctive treatment or treatment of Graves' eye disease, said tryptophan metabolites including indolepropionic acid, indole-3-lactic acid and / or indoleacetic acid.

[0020] The present invention provides a pharmaceutical formulation for adjunctive treatment or treatment of Graves' eye disease, comprising at least one of indolepropionic acid, indole-3-lactic acid and / or indoleacetic acid as active ingredients, and pharmaceutically acceptable excipients.

[0021] In some embodiments, the pharmaceutically acceptable excipients include fillers, binders, disintegrants, lubricants, sweeteners, flavoring agents, preservatives, surfactants, stabilizers, solubilizers, colorants, antioxidants, pH adjusters, buffers, chelating agents, thickeners, coating materials, or film-forming materials.

[0022] In some embodiments, the dosage form of the drug includes a liquid formulation, a semi-solid formulation, or a solid formulation.

[0023] In some embodiments, the dosage form of the drug includes:

[0024] Oral solutions, tablets, capsules, granules, pills, powders, syrups, ointments, creams, gels, suppositories, or injections.

[0025] The technical solution of this invention has the following advantages:

[0026] 1. This invention provides a biomarker for assisting in the diagnosis of Graves' ophthalmopathy and / or Graves' disease, identifying Graves' ophthalmopathy and / or Graves' disease through the biomarker. The biomarker includes tryptophan metabolites, including indolepropionic acid, indole-3-lactate, and / or indoleacetic acid. The innovative research of this invention has found that, compared with the control group, the serum levels of indolepropionic acid (IPA), indole-3-lactate (ILA), and indoleacetic acid (INA) in patients with Graves' disease (GD) and GO are significantly higher. The levels of tryptophan metabolites (IAA) were significantly reduced, and the IAA levels in GO patients were further reduced compared to those in GD patients; this indicates that the tryptophan metabolites, including indolepropionic acid, indole-3-lactic acid and / or indoleacetic acid, can be used as an adjunct to the diagnosis of Graves' ophthalmopathy and / or Graves' disease, and can serve as biomarkers for the adjunct diagnosis of Graves' ophthalmopathy and / or Graves' disease.

[0027] 2. This invention provides the use of products for detecting the biomarkers used in the auxiliary diagnosis or diagnosis of Graves' ophthalmopathy and / or Graves' disease in the preparation of products for the auxiliary diagnosis or diagnosis of the course of Graves' ophthalmopathy. The innovative research of this invention found that serum IAA levels in patients with active GO are significantly lower than those in patients with inactive GO. Serum IAA levels in GO patients are significantly negatively correlated with CAS (Chronic Acid Score). Given the significant difference in serum IAA concentration between inactive and active GO patients, and the significant correlation between IAA and CAS score and TRAb in GO patients, this verifies that IAA can predict GO disease activity (active and inactive phases), and that IAA has excellent reliability in identifying patients with active GO. Therefore, the above indicates that the tryptophan metabolites, including indoleacetic acid (IAA), can be used for the auxiliary diagnosis or diagnosis of the course of Graves' ophthalmopathy and can serve as biomarkers for the auxiliary diagnosis or diagnosis of the course of Graves' ophthalmopathy.

[0028] 3. This invention provides the use of tryptophan metabolites in the preparation of medicaments for adjuvant or therapeutic treatment of Graves' eye disease, wherein the tryptophan metabolites include indolepropionic acid, indole-3-lactic acid, and / or indoleacetic acid. This invention has found that, in vitro, IPA, ILA, and IAA alleviate TNFα-induced inflammation and proliferation of orbital fibroblasts by inhibiting the Akt signaling pathway. Therefore, IPA, ILA, and IAA exert a protective effect in GO by regulating inflammation and proliferation of orbital fibroblasts, suggesting that they may be potential therapeutic targets for GO and could provide a new treatment option for Graves' eye disease. Attached Figure Description

[0029] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0030] Figure 1 This is a histogram showing the species distribution of the top 30 gut microbiota at the genus level in the gut microbiota results related to tryptophan metabolism in GO patients in Example 1 of the present invention, where N on the horizontal axis represents the healthy control group and T represents the GO group;

[0031] Figure 2 This is a heatmap of taxa at the genus level showing the abundance of 35 genera in the gut microbiota related to tryptophan metabolism in GO patients in Example 1 of the present invention; Control: healthy volunteers; GO: Graves' orbitopathy;

[0032] Figure 3 This invention presents the differences in tryptophan metabolite-producing bacteria at the genus, order, class, and phylum levels in the gut microbiota results related to tryptophan metabolism in GO patients in Example 1 of this invention; Control: healthy volunteers; GO: Graves' orbitopathy;

[0033] Figure 4 Partial least squares discriminant analysis (PLS-DA) of the serum metabolomics profiles of GO patients in Example 1 of this invention, presented in positive ion mode, for GO, GD, and healthy controls; Control: healthy volunteers; GD: Graves' disease; GO: Graves' ophthalmopathy; ILA: indole-3-lactic acid; IAA: indoleacetic acid;

[0034] Figure 5 This is a volcano plot of the metabolite profiles of GO patients, GD patients, and the control group in Example 1 of the present invention, based on the serum metabolomics profiles of GO patients. Blue and red dots represent the reduction and enrichment of metabolites, respectively; the dashed line represents the critical p-value threshold of 0.05; Control: healthy volunteers; GD: Graves' disease; GO: Graves' ophthalmopathy; ILA: indole-3-lactic acid; IAA: indoleacetic acid;

[0035] Figure 6This is a bubble diagram of KEGG enrichment analysis of serum metabolomics profiles of GO patients in Example 1 of the present invention. The size of the bubble corresponds to the number of metabolites enriched in a certain pathway, and the color gradient indicates the significance of enrichment. The GO and GD patient groups were compared with the control group. Control: healthy volunteers; GD: Graves' disease; GO: Graves' ophthalmopathy.

[0036] Figure 7 The results of serum metabolomics profiles of GO patients in Example 1 of this invention show the differences in metabolite profiles among the control group, GD group, and GO group; *p<0.05; ****P<0.0001, compared with the control group; Control: healthy volunteers; GD: Graves' disease; GO: Graves' ophthalmopathy; ILA: indole-3-lactic acid; IAA: indoleacetic acid;

[0037] Figure 8 The results of serum tryptophan metabolites in GO patients in Example 1 of this invention; ac, the levels of IPA(a), ILA(b), and IAA(c) in the serum of GD patients (n=145), GO patients (n=156), and healthy controls (n=100); data are expressed as mean ± standard deviation. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001, compared with the control group; ##P<0.01, compared with the GD group; d, Comparison of serum IAA concentrations in GO patients in the active phase (n=62) and inactive phase (n=94); Data are expressed as mean ± standard deviation; ****P<0.0001, compared with inactive GO patients; e, Spearman correlation analysis between serum IAA concentration and clinical activity score (CAS) in 156 GO patients; P<0.05 was considered statistically significant; f, Receiver Operating Characteristic Curve (ROC) analysis; Control: healthy volunteers; GD: Graves' disease; GO: Graves' ophthalmopathy; IPA: indolepropionic acid; ILA: indole-3-lactic acid; IAA: indoleacetic acid; CAS: clinical activity score.

[0038] Figure 9The results of OFs proliferation and inflammation in GO patients and healthy controls in Example 1 of this invention are shown in (a). Orbital fibroblasts (OFs) from different passages from control groups and GO patients were seeded at the same density and allowed to adhere overnight. The proliferative activity of OFs was assessed by the CCK-8 assay. n=6. Data are expressed as mean ± standard error. Con-OFs: OFs from the control group; GO-OFs: OFs from GO patients; bc. Orbital fibroblasts (OFs) from the third passage from control groups and GO patients were seeded at the same density and allowed to adhere overnight. The inflammatory level of OFs was assessed by Western blotting (WB). Representative images are shown in (b). Quantitative data are shown in (c). n=4. Data are expressed as mean ± standard error.

[0039] Figure 10 This document presents the results of IPA, ILA, and IAA inhibiting TNFα-induced proliferation of human orbital fibroblasts (OFs) in Example 1 of this invention. As described in the Materials and Methods section, human orbital fibroblasts (OFs) were treated for 24 hours (h) with different concentrations of the three tryptophan metabolites or an equal volume of solvent (DMSO). The proliferative activity of OFs was assessed using the CCK-8 assay. The effects of IPA(a), ILA(b), and IAA(c) on proliferative activity are expressed as relative cell viability. Within the selected working concentration range, all three tryptophan metabolites showed a dose-dependent decrease in cell proliferation activity compared to the control group. n = 5. Data are expressed as mean ± standard error. *P<0.05, **P<0.01, ****P<0.0001, compared with control cells; df, human orbital fibroblasts (OFs) were simultaneously treated for 24 hours with 20 ng / ml recombinant human tumor necrosis factor α (rHu TNFα) or an equivalent solvent, and IPA (50 μM), ILA (0.5 mM), and IAA (100 μM) or an equivalent solvent. OF proliferation activity was assessed by the CCK-8 assay. The effects of IPA(d), ILA(e), and IAA(f) on TNFα-induced OF proliferation are expressed as relative cell viability. n=5. Data are presented as mean ± standard error. ****P<0.0001, compared with rHu TNFα+ control cells;

[0040] Figure 11 This invention presents the results of TNFα significantly inducing the proliferation of human orbital fibroblasts (OFs) in Example 1. Human orbital fibroblasts (OFs) were treated with 20 ng / ml recombinant human tumor necrosis factor α (rHu TNFα) or an equal volume of solvent for 24 hours, and their proliferative activity was assessed using the CCK-8 assay. n = 6. Data are expressed as mean ± standard error. ****P < 0.0001, compared with control cells;

[0041] Figure 12 To illustrate the significant induction of inflammation in human orbital fibroblasts (OFs) by TNFα in Example 1 of this invention; ab, human orbital fibroblasts (OFs) were treated with 20 ng / ml recombinant human tumor necrosis factor α (rHu TNFα) or an equal volume of solvent for 24 hours, and the inflammation level of OFs was assessed by Western blotting (WB). Representative images are shown in (a); quantitative data are shown in (b). n=3. Data are expressed as mean ± standard error. *P<0.05, **P<0.01, compared with control cells;

[0042] Figure 13 To alleviate TNFα-induced inflammation in human orbital fibroblasts (OFs) in Example 1 of this invention, IPA, ILA, and IAA were used. Human orbital fibroblasts (OFs) were simultaneously treated for 24 hours with 20 ng / ml recombinant human tumor necrosis factor α (rHu TNFα) or an equivalent solvent, and IAA (100 μM), IPA (50 μM), or ILA (0.5 mM) or an equivalent solvent. The level of inflammation in OFs was assessed by Western blotting (WB). IAA, IPA, and ILA significantly reduced rHu TNFα-stimulated pStat3 and TNFα levels. Representative images are shown in (a), and quantitative data are shown in (b). n = 3. Data are expressed as mean ± standard error. *P < 0.05, **P < 0.01, ***P < 0.001, compared with rHu TNFα+ control cells;

[0043] Figure 14 To illustrate the effect of IPA, ILA, and IAA in blocking TNFα-induced activation of the Akt signaling pathway in human orbital fibroblasts (OFs) in Example 1 of this invention: a) Human orbital fibroblasts (OFs) were treated with 20 ng / ml recombinant human tumor necrosis factor α (rHuTNFα) or an equivalent solvent for 24 hours. Akt phosphorylation levels in OFs were assessed by Western blotting (WB). TNFα intervention significantly increased pAkt protein levels. The top figure shows representative images, and the bottom figure shows quantitative data. n = 3. Data are expressed as mean ± standard error. **P < 0.01, compared to control cells; b) Human orbital fibroblasts (OFs) were simultaneously treated with 20 ng / ml recombinant human tumor necrosis factor α (rHuTNFα) or an equivalent solvent, as well as IPA (50 μM), ILA (0.5 mM), or IAA (100 μM) or an equivalent solvent for 24 hours. Akt phosphorylation levels in OFs were assessed using Western blotting (WB). IPA, ILA, and IAA significantly blocked rHu TNFα-stimulated pAkt levels. The top figure shows representative images, and the bottom figure shows quantitative data. n=3. Data are expressed as mean ± standard error. *P<0.05, **P<0.01, compared with rHu TNFα+ control cells;

[0044] Figure 15 This is an analysis of the Receiver Operating Characteristic Curve (ROC) in Embodiment 2 of the present invention. Detailed Implementation

[0045] The following embodiments are provided to better understand the present invention and are not limited to the preferred embodiments described. They do not constitute a limitation on the content and scope of protection of the present invention. Any product that is the same as or similar to the present invention, derived by any person under the guidance of the present invention or by combining the features of the present invention with other prior art, falls within the protection scope of the present invention.

[0046] For experiments not specifically described in the examples, the procedures or conditions should be followed according to the conventional experimental procedures described in the literature in this field. Reagents or instruments whose manufacturers are not specified are all commercially available conventional reagent products.

[0047] Materials involved in the following embodiments:

[0048] Ethical Approval Guidelines:

[0049] The study has been approved by the Ethics Committee of Beijing Tongren Hospital, Capital Medical University (Ethics Nos.: TRECKY2016-003, TREC2020-XJS02). All patients and volunteers signed written informed consent forms.

[0050] Study design and clinical sample collection:

[0051] The diagnosis of GO is based on the European Group on Graves Orbitopathy (EUGOGO) guidelines (TD Hoang, DJ Stocker, ELChou, HB Burch, 2022 Update on Clinical Management of Graves Disease and Thyroid Eye Disease, Endocrinol Metab Clin North Am, 51(2022)287-304, https: / / doi.org / 10.1016 / j.ecl.2021.12.004.). Any orbital space-occupying lesions are ruled out by orbital CT or MRI. According to the 2016 American Thyroid Association guidelines, Graves' Disease (GD) was clinically diagnosed based on diffuse goiter, elevated serum thyroxine (T4), decreased thyroid stimulating hormone (TSH) levels, and TSH receptor antibody (TRAb) test results (Subekti, L.A. Pramono, Current Diagnosis and Management of Graves' Disease, Acta Med Indones, 50 (2018) 177-182). All patients with hyperthyroidism received only antithyroid drugs (methimazole, Merck, Germany). We collected clinical and demographic data, including sex, age, thyroid function, thyroid autoantibodies, and medical history. Exclusion criteria for this study included age <18 years or >65 years, having received probiotic or antibiotic treatment within the past month, having used hormone medications or traditional Chinese medicine, a history of chronic diarrhea or constipation, systemic diseases (diabetes, stroke, heart disease, kidney or liver dysfunction, and cancer), a history of gastrointestinal surgery, pregnancy and lactation, and alcohol or drug addiction.

[0052] The activity of GO patients was assessed based on the Clinical Activity Score (CAS). The cutoff value between the inactive and active groups was 3. Inactive GO was defined as CAS < 3, and active GO was defined as CAS ≥ 3. (Refer to the 2021 EU GOGO Clinical Guidelines for Thyroid Ophthalmopathy).

[0053] DNA extraction and 16S sequencing samples:

[0054] From March 2017 to March 2018, 33 patients with active gonorrhea and 32 healthy volunteers (control group) were recruited from the Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University. Human fecal samples (2-3g) were collected in sterile fecal cups and stored at -80℃ until 16S sequencing was performed.

[0055] Serum metabolomics analysis of samples:

[0056] Serum metabolomics analysis was conducted on 16 healthy volunteers (control group), 16 patients with Gram-D disease, and 31 patients with Gram-Oxygen Depression (GO) recruited from the Department of Endocrinology at Beijing Tongren Hospital, Capital Medical University.

[0057] ELISA test samples of serum tryptophan metabolites:

[0058] Recruitment was conducted from the Department of Endocrinology at Beijing Tongren Hospital, affiliated with Capital Medical University. The ELISA study analyzed a total of 401 serum samples, including 100 healthy volunteer samples (control group), 145 GD patient samples, and 156 GO patient samples.

[0059] Clinically diagnosed GO test samples:

[0060] We recruited 156 GO patients from the outpatient clinic of the Department of Endocrinology at Beijing Tongren Hospital, affiliated with Capital Medical University. Based on the CAS score, we divided them into 94 patients with inactive GO and 62 patients with active GO. We analyzed the differences in serum tryptophan metabolites between the two groups.

[0061] Orbital connective tissue explants were obtained from surgical waste from patients undergoing orbital decompression surgery for severe GO at Beijing Tongren Hospital, Capital Medical University (n=4). Control orbital tissue (n=5) was obtained from surgical waste from patients without thyroid or inflammatory disease who underwent enucleation after trauma. This study was approved by the Ethics Committee of Beijing Tongren Hospital, Capital Medical University.

[0062] Example 1: Screening of Biomarkers

[0063] DNA extraction and 16S sequencing

[0064] Human fecal samples (2-3 g) were collected in sterile fecal cups and stored at -80°C until further processing. Microbial DNA was extracted using the EZNA Fecal DNA Extraction Kit (Omega, USA), with total DNA eluted with 50 μL of elution buffer. The extracted DNA was stored at -80°C until 16S sequencing.

[0065] Serum metabolomics analysis

[0066] Metabolites with significant differences were selected based on variable importance (VIP) scores (obtained from an orthogonal partial least squares discriminant analysis model) and p-values ​​from the Wilcoxon test (VIP threshold > 1, p < 0.05). Partial least squares discriminant analysis (PLS-DA) was used to evaluate cross-validation of the samples. The biochemical pathways of differentially expressed metabolites were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and classified according to their involvement in the pathways. Enrichment analysis was performed based on the presence of metabolites in functional nodes. The statistical significance of enriched pathways was tested using Fisher's exact test with the Stats Python package.

[0067] ELISA detection of serum tryptophan metabolites

[0068] Collect serum samples and store at -80°C. Analyze samples using commercially available ELISA kits according to the manufacturer's instructions. IAA levels were detected using the Human IAA (Catalog No.: CEA737Ge) ELISA kit (Cloud-CloneCorp, Houston, Texas, USA). IPA and ILA levels were detected using the Human IPA (Catalog No.: MM-61644H1) and Human ILA (Catalog No.: MM-61694H1) ELISA kits (Jiangsu Meimian Industrial Co., Ltd.). These kits are designed for the detection of human serum or plasma samples and have no cross-reactivity.

[0069] Cell culture and reagents

[0070] Human OFs culture was initiated from orbital connective tissue explants according to the literature method (M. Park, JY Kim, JMKang, HJ Lee, JPBanga, GJ Kim, H. Lew, PRL-1 overexpressed placenta-derived mesenchymal stem cells suppress adipogenesis in Graves' ophthalmopathy through SREBP2 / HMGCR pathway, Stem Cell Research & Therapy, 12(2021), https: / / doi.org / 10.1186 / s13287-021-02337-2). After obtaining orbital connective tissue explants, they were immediately washed three times with phosphate-buffered saline (PBS), cut into small pieces, and placed directly into culture dishes. After adhesion, explants were immersed in DMEM / F12 medium (Sigma-Aldrich, St. Louis, Missouri, USA) containing 20% ​​fetal bovine serum (FBS; Gibco, Carlsbad, California, USA) and 1% penicillin / streptomycin (Thermo Fisher Scientific, USA). They were cultured in a humid environment at 37°C, 95% aerosol, and 5% CO2. OFs typically migrated from the explants within approximately 4 days and reached confluence within approximately 10 days. Cells were then passaged with 0.25% trypsin / EDTA (Gibco Laboratories, New York, USA). After centrifugation at 300g at room temperature for 5 minutes, the supernatant was discarded, and the cell pellet was resuspended in 10 mL of DMEM / F12 medium, then filtered through a 70 μm cell filter to establish cell lines. After the first passage, OFs were cultured in DMEM / F12 medium containing 10% FBS and 1% penicillin / streptomycin, with the medium changed every 2–3 days. Cells from passages 3-6 were used in the experiments. 3-Indoleacetic acid (IAA, catalog number: GC33436), 3-indolepropionic acid (IPA, catalog number: GC31290), and indolelactic acid (ILA, catalog number: GC33659) were purchased from GlpBio, California, USA. Recombinant human tumor necrosis factor α (rHu TNFα) was purchased from Shanghai Sangon Biotech Co., Ltd.

[0071] Cell proliferation experiment

[0072] Following the previously described method, the proliferation activity of OFs was detected using the Cell Counting Kit-8 assay (CCK-8; Beijing TransGen Biotech Co., Ltd.). Briefly, OFs were seeded into 96-well plates and, after reaching 80% confluence, were treated for 24 h with different concentrations of three tryptophan metabolites or an equal volume of solvent (DMSO). The working concentrations of these tryptophan metabolites were as follows: IPA (10, 50, and 100 μM), ILA (0.1, 0.5, and 1 mM), and IAA (25, 100, and 400 μM). Cells treated with an equal volume of solvent served as a control group. To assess the antiproliferative effects of IPA, ILA, and IAA against rHu TNFα-induced proliferation, OFs were treated for 24 h with 20 ng / ml rHu TNFα or an equal volume of solvent, simultaneously with IPA (50 μM), ILA (0.5 mM), or IAA (100 μM). 0.5–1 hour before the end of incubation, CCK-8 solution was added to each well of a 96-well plate at a final concentration of 10% and gently mixed. After 0.5–1 hour, absorbance (A) was measured at 450 nm (reference wavelength: 630 nm). OFs proliferation activity was expressed as relative cell viability, calculated using the following formula: Relative cell viability = (Experimental group A450 / A630) / (Control group A450 / A630). Stock solutions of all three tryptophan metabolites were prepared with DMSO and diluted in the culture medium to the desired final concentration. The final DMSO concentration in the culture medium did not exceed 0.5% (v / v).

[0073] Protein immunoblotting analysis

[0074] OFs were seeded into 6-well plates and, after reaching 80% confluence, were treated with 20 ng / ml rHu TNFα or an equivalent solvent, along with IPA (50 μM), ILA (0.5 mM), or IAA (100 μM) or an equivalent solvent for 24 hours. Western blot analysis of proteins was performed according to the previously described standard methods [6-8]. Anti-TNFα (3707S), anti-pStat3 (9145S), anti-Stat3 (12640S), anti-protein kinase B (Akt) (9272S), and anti-pAkt (4060S) were purchased from Cell Signaling Technology, USA. Anti-β-actin was purchased from Sigma-Aldrich (A5316), USA. Image intensity quantification of each band was performed using ImageJ software (National Institutes of Health, Bethesda, MD). β-actin was used as a standardized control in the experiments.

[0075] Statistical analysis

[0076] Demographic, clinical, and laboratory data were analyzed using IBM SPSS 27.0 and GraphPad Prism 8.0.1 software. Normally distributed continuous variables were expressed as mean ± standard error of mean (SEM), and nonparametric variables were expressed as median (Q1, Q3). For comparisons between different groups, Student's t-test was used for two-group comparisons, and one-way ANOVA and Kruskal-Walli's test were used for multiple-group comparisons. P < 0.05 was considered statistically significant. For the analysis of the effects of differences, Benjamini and Hochberg false discovery rates (BH) were used to correct for errors from a large number of analyses. The correlation between all variables was determined using Spearman rank correlation.

[0077] result:

[0078] DNA extraction and 16S sequencing results are as follows: Figures 1-3 As shown:

[0079] The gut microbiota associated with tryptophan (Trp) metabolism is altered in patients with Graves' eye disease (GO). 16S sequencing studies have shown significant differences in α- and β-diversity indices in fecal samples from GO patients compared to controls (TTShi, Z. Xin, L. Hua, RX Zhao, YLYang, H. Wang, S. Zhang, W. Liu, RRXie, Alterations in the intestinal microbiota of patients with severe and active Graves' orbitopathy: a cross-sectional study, J Endocrinol Invest, 42(2019) 967-978, https: / / doi.org / 10.1007 / s40618-019-1010-9). However, whether the gut microbiota associated with tryptophan metabolism has changed remains unknown. In this study, the gut microbiota was identified and analyzed at the phylum (p), class (c), order (o), family (f), and genus (g) levels. Histograms of species distribution of the top 30 gut microbiota at the genus level show that species in both groups are mainly distributed in the genera *Bacteroides*, *Prevotella*, and *Femobacterium*. Figure 1(in Chinese). Furthermore, the taxonomic heatmap showed significant differences in the abundance of 35 genera among GO patients compared to the control group. These genera belong to five phyla: Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Proteobacteria. Figure 2 This indicates that several bacterial species can convert tryptophan into indole and its derivatives. To reveal the role of tryptophan metabolism in GO, the changes in tryptophan metabolism-related bacterial communities at different levels were further analyzed in the control group and GO patients. The results showed that at the genus level, the abundance of the anaerobic Corynebacterium genus (g_Anaerostipes) that can convert tryptophan to indole-3-lactic acid (ILA) was significantly reduced in the GO group compared with the control group; at the order level, the abundance of the Clostridia order (o_Clostridiales) that can convert tryptophan to ILA was significantly reduced in the GO group compared with the control group; at the class level, the abundance of the Clostridia class (c_Clostridia) that can convert tryptophan to ILA, indolepropionic acid (IPA), and indoleacetic acid (IAA) was significantly downregulated in the GO group compared with the control group; at the phylum level, the abundance of the Firmicutes phylum that can convert tryptophan to ILA was significantly downregulated in the GO group compared with the control group. Figure 3 In summary, these results suggest that gut microbiota associated with tryptophan metabolism, including Firmicutes and Corynebacterium, may be closely related to gonorrhea (GO). With a significant reduction in gut microbiota associated with tryptophan metabolism, the associated tryptophan metabolites IAA, ILA, and IPA may also be significantly reduced, indicating that the occurrence of GO may be closely related to tryptophan metabolism in the gut microbiota, with ILA, IPA, and IAA being particularly noteworthy.

[0080] Results of serum metabolomics profiles in GO patients:

[0081] To further elucidate the changes in tryptophan metabolomics among GO patients, Graves' disease (GD) patients, and controls, serum metabolomics analysis was performed on the three groups. A total of 2182 metabolites were quantified in this experiment. Supervised partial least squares discriminant analysis (PLS-DA) showed significant separations between the control group and the GD group (R2Y = 0.91, Q2Y = 0.76), between the control group and the GO group (R2Y = 0.90, Q2Y = 0.79), and between the GD group and the GO group (R2Y = 0.95, Q2Y = 0.87). These values ​​were all close to 1.0, indicating that all three models were stable and had predictive reliability. Figure 4 These results imply significant differences in metabolites among patients in the control, GD, and GO groups. We then applied volcano plot analysis to identify potential differentially expressed metabolites contributing to these differences. Figure 5Metabolites with a variable importance projection (VIP) value > 1 and p < 0.05 were considered significantly different. According to our criteria, 348 metabolites were significantly different between the GO group and the control group, 392 metabolites were significantly different between the GD group and the control group, and 298 metabolites were significantly different between the GD group and the GO group. More specifically, compared with the control group, 213 metabolites were upregulated and 135 metabolites were downregulated in the GO group, while 234 metabolites were upregulated and 158 metabolites were downregulated in the GD group. Compared with the GD group, 155 metabolites were upregulated and 143 metabolites were downregulated in the GO group. These results indicate that serum exhibits a unique metabolic response according to GD and GO. Furthermore, we performed Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the significantly altered metabolites. Differential enrichment of pathways in the GO and GD groups included tyrosine metabolism, tryptophan metabolism, neurotransmitter and receptor metabolism, glycerophospholipid metabolism, and the synthesis of ununsaturated fatty acids. Notably, the tryptophan metabolic pathway was differentially enriched in both the GO and GD groups. Figure 6 Based on this, we further analyzed the levels of L-tryptophan and tryptophan metabolites in the three groups detected by metabolomics. Our metabolomics analysis showed no significant difference in L-tryptophan levels among the three groups; however, the results showed significantly lower levels of IAA and ILA in the GD group, and significantly lower levels of IAA in the GO group compared to the control group. Figure 7 IPA was not detected in our metabolomics analysis. These findings suggest that GD and GO may be closely related to tryptophan metabolites rather than tryptophan itself.

[0082] Serum tryptophan metabolite results in GO patients:

[0083] Given the aforementioned finding that tryptophan metabolites are closely associated with GO and GD, it was hypothesized that these metabolites might potentially serve as biomarkers for this disease. To address this question and further confirm the results of serum metabolomics, the levels of IPA, ILA, and IAA in the serum of GD patients, GO patients, and healthy volunteers (control group) were detected by enzyme-linked immunosorbent assay (ELISA). ELISA results showed that, compared with the control group, the levels of IPA, ILA, and IAA in the serum of GD patients and GO patients were significantly reduced. Figure 8 (Ac). Notably, compared with GD patients, GO patients had significantly lower serum IAA levels (ac). Figure 8 (c). These results indicate that IAA is the most promising candidate as a novel biomarker for GO.

[0084] Therefore, to explore the potential of IAA as a biomarker for assessing GO disease progression, we divided GO patients into an inactive group (n=94) and an active group (n=62) based on their Clinical Activity Score (CAS) (the cutoff value for the inactive and active groups was 3; inactive GO was defined as CAS < 3, and active GO was defined as CAS ≥ 3). No significant differences were detected between the two groups in terms of sex, age, free triiodothyronine (FT3), free thyroxine (FT4), and thyroid-stimulating hormone (TSH). However, the level of thyroid-stimulating hormone receptor antibody (TRAb) was significantly higher in the active GO group than in the inactive group. These clinical characteristics are shown in Table 2. The results showed that the serum IAA level in patients with active GO was significantly lower than that in patients with inactive GO. Figure 8 (d). Given that CAS is the most commonly used indicator for assessing GO activity, we performed Spearman correlation analysis to explore whether serum IAA levels are related to CAS. Interestingly, serum IAA levels in GO patients showed a significant negative correlation with CAS ( Figure 8 (e).

[0085] It is well known that serum thyroid-stimulating hormone receptor antibody (TRAb) levels are associated with the activity and severity of GO. To investigate whether tryptophan metabolites are associated with the progression of GD and GO, it is crucial to explore the correlation between tryptophan metabolites and serum TRAb. Considering the significant differences in age, sex, and TRAb levels among the three patient groups (P<0.001) (Table 1), we performed a multiple linear regression analysis. Each tryptophan metabolite was used as the dependent variable, and TRAb as the independent variable, adjusted for age and sex. The results showed that, after adjusting for age and sex, the concentrations of IAA and IPA were negatively correlated with TRAb (P<0.05) (Table 3). These results further suggest that tryptophan metabolites, especially IAA, may be promising biomarkers for assessing GO disease progression. Given the significant differences in serum IAA concentrations between inactive and active GO patients, and the significant correlation between IAA and CAS score and TRAb in GO patients, we hypothesize that IAA can serve as a reliable predictor of disease activity. Therefore, receiver operating characteristic (ROC) curve analysis was performed to predict GO disease activity using IAA. For 94 inactive and 62 active patients, the Youden's J statistic was used to determine the optimal sensitivity and specificity thresholds, achieving an area under the ROC curve of 0.9457. The cutoff values ​​were as follows: IAA 28.91 ng / mL, sensitivity 0.9355, and specificity 0.8817, indicating that IAA has excellent reliability in identifying active GO patients. Figure 8 (f)

[0086] Table 1. Baseline characteristics of participants

[0087]

[0088] In the table above, values ​​represent n (%) and the median (IQR). Abbreviations: IQR: Interquartile Range; Conrol: Healthy Volunteers; GD: Graves' Disease; GO: Graves' Ophthalmopathy; FT3: Free Triiodothyronine; FT4: Free Thyroxine; TSH: Thyroid-Stimulating Hormone; TRAb: Thyroid-Stimulating Hormone Receptor Antibody. **P<0.01, ***P<0.001. Values ​​with superscript letters: a indicates a significant difference compared to the control group; b indicates a significant difference compared to the GD group.

[0089] Table 2 Baseline characteristics of GO patients

[0090]

[0091] In the table above, values ​​are taken as n (%) and median (IQR). Abbreviations: IQR: interquartile range; GO: Graves' ophthalmopathy; FT3: free triiodothyronine; FT4: free thyroxine; TSH: thyroid-stimulating hormone; TRAb: thyroid-stimulating hormone receptor antibody. *P<0.05.

[0092] Table 3. Multiple linear regression analysis of factors affecting tryptophan metabolites in GO

[0093]

[0094] In the table above, the abbreviations are: GO: Graves' eye disease; Trp: tryptophan; IPA: indole-3-propionic acid; IAA: indoleacetic acid; ILA: indole-3-lactic acid; TRAb: thyroid-stimulating hormone receptor antibody. Note: *P<0.05, ***P<0.001.

[0095] Tryptophan metabolite tumor necrosis factor α (TNFα) induces orbital fibroblast (OF) proliferation and inflammation.

[0096] Given the significant downregulation of IPA, ILA, and IAA levels in the serum of patients with GD and GO, we hypothesized that these metabolites might be important therapeutic targets for GO. To verify this hypothesis, we conducted a series of in vitro experiments using primary cultured human OFS. Previous studies have confirmed that there are no significant differences in cell morphology and function between OFS from GO patients and healthy controls after in vitro passage culture of retrobulbar connective tissue (R.C. Henrikson, T.S. Smith, Ultrastructure of cultured human orbital fibroblasts, Cell and Tissue Research, 278(1994)629-631, https: / / doi.org / 10.1007 / bf00331384). In this study, we also found no significant differences in proliferation and inflammation between OFS from GO patients and healthy controls after in vitro passage culture of retrobulbar connective tissue (R.C. Henrikson, T.S. Smith, Ultrastructure of cultured human orbital fibroblasts, Cell and Tissue Research, 278(1994)629-631, https: / / doi.org / 10.1007 / bf00331384). Figure 9 (ac). Therefore, subsequent experiments in this study used OFs from the retrobulbar connective tissue of healthy individuals.

[0097] Given that cell proliferation and inflammation are important characteristics of OFS in GO patients, we initially used the CCK-8 assay to assess the effects of these three tryptophan metabolites on cell proliferation. The results showed that, compared with the control group, the proliferative activity of cells treated with IPA, ILA, and IAA decreased in a dose-dependent manner. Figure 10 TNFα, upregulated in OFS, plays a crucial role in inducing cell proliferation and pro-inflammatory cytokines in GO. Further experiments showed that recombinant human TNFα (rHu TNFα) can significantly induce OFS cell proliferation. Figure 11 Notably, IPA, ILA, and IAA significantly improved rHu TNFα-induced OF proliferation. Figure 10 (df). Subsequently, Western blot (WB) experiments showed that rHu TNFα could significantly induce inflammation in OFs, as evidenced by significantly elevated levels of pStat3 and TNFα. Figure 12 IPA, ILA, and IAA significantly reduced rHu TNFα-induced OFs inflammation. Figure 13 These findings suggest that IPA, ILA, and IAA may be important therapeutic targets for GD and GO by improving inflammation and proliferation of OFs. Tryptophan metabolites can block TNFα-induced activation of the Akt signaling pathway in human OFs.

[0098] Multiple studies have confirmed that the Akt signaling pathway plays a role in adipogenesis, cell migration, cell proliferation, and inflammation in GO. These studies have indicated that the level of phosphorylated Akt (pAkt) at serine 473 is elevated in OFs of GO patients, which is considered an important pathogenesis of GO [1-5]. Therefore, to explore the potential mechanisms by which tryptophan metabolites IPA, ILA, and IAA improve inflammation-induced dysfunction in OFs, we investigated their effects on the Akt signaling pathway. We found that TNFα treatment significantly promoted the activation of the Akt pathway, manifested as an increase in pAkt (…). Figure 14 (a) , while IPA, ILA, or IAA treatments can all block TNFα-induced Akt phosphorylation ( Figure 14 (b) This finding suggests that the Akt signaling pathway plays an important role in the protective effect of IPA, ILA, and IAA against inflammation-induced dysfunction of OFs in GO.

[0099] In summary, the role of tryptophan metabolites in GO patients remains unclear to date. This study began with gut microbiota sequencing to identify differences in tryptophan-associated flora, followed by an exploration of serum tryptophan metabolomics. Furthermore, we elucidated the potential mechanisms by which tryptophan metabolites exert anti-inflammatory and anti-proliferative effects in GO.

[0100] In this study, we further reanalyzed the changes in the gut microbiota of GO patients. At the genus level, the relative abundance of 35 genera in GO patients differed significantly from that in the control group. Furthermore, significant differences in tryptophan-related genera were observed between the two groups at different levels. At the phylum level, the abundance of Firmicutes was significantly downregulated in the GO group. At the genus level, the abundance of Anaerobic Corynebacterium was significantly reduced in the GO group compared to the control group. Evidence suggests that Firmicutes and Anaerobic Corynebacterium play a crucial role in promoting tryptophan metabolism during dietary fiber degradation in humans, thereby protecting the intestinal barrier. Our study is the first to demonstrate a significant downregulation of specific bacterial genera related to tryptophan metabolism in GO patients.

[0101] This study further validated the differences in IAA, ILA, and IPA among the healthy control group, GD group, and GO group using ELISA. Compared with the control group, the serum levels of IPA, ILA, and IAA were significantly downregulated in both GD and GO patients. Moreover, the serum IAA level in GO patients was significantly lower than that in GD patients. These findings further elucidate that tryptophan metabolites, including IAA, ILA, and IPA, may play an important role in GD and GO diseases. Furthermore, IAA may serve as a biomarker to distinguish between GO and GD patients.

[0102] This study further investigated the potential of IAA as a biomarker for assessing GO disease progression, validating that thyroid-stimulating hormone receptor antibody (TRAb) levels were significantly higher in the active GO group than in the inactive group. Serum IAA levels in active GO patients were significantly lower than in inactive patients. Serum IAA levels in GO patients showed a significant negative correlation with CAS (Chronic Acid Score). Given the significant difference in serum IAA concentration between inactive and active GO patients, and the significant correlation between IAA and both CAS score and TRAb in GO patients, this study validates that IAA can predict GO disease activity (active and inactive phases), demonstrating its excellent reliability in identifying active GO patients.

[0103] The data from this study showed that tryptophan metabolites significantly inhibited the proliferation of OFs and the expression of the inflammatory marker pStat3. Here, we provide the first evidence that IAA, ILA, and IPA may play a protective role in proliferation and inflammation in GO patients.

[0104] To investigate the potential mechanisms by which tryptophan metabolites IPA, ILA, and IAA ameliorate TNFα-induced inflammation and proliferation of OFs, we examined their effects on the Akt signaling pathway. In our study, treatment with IPA, ILA, or IAA downregulated Akt phosphorylation in TNFα-induced OFs. Our results complement the evidence that GO may benefit from blocking the Akt signaling pathway.

[0105] In summary, our study is the first to clearly identify changes in gut microbiota-derived tryptophan metabolites in GO patients. Furthermore, it demonstrates that IPA, ILA, and IAA play a potential therapeutic role in GO by ameliorhea (OFs) inflammation and controlling their proliferation. Microbiota-derived tryptophan metabolites may serve as potential targets for GO treatment. Therefore, maintaining gut microbiota production of IAA, ILA, and IPA, for example through dietary interventions or oral probiotic supplements, may have beneficial effects on the prevention and management of GO.

[0106] Experimental Example 2: Clinical Application

[0107] This experimental case included 68 patients clinically diagnosed with GO. 47 patients with inactive GO and 21 patients with active GO were assessed using CAS (Cognitive Assessment). These cases were randomly selected from the GO patients in Example 1. Receiver operating characteristic (ROC) curves were plotted based on the serum IAA concentrations of these GO patients to predict disease activity using biomarkers.

[0108] The ROC curve is a coordinate graph composed of the false positive probability (FPR, 1 - specificity) on the horizontal axis and the true positive rate (TPR, sensitivity) on the vertical axis. The specific steps are as follows: First, sort the samples according to the predicted values ​​generated by the model for the test samples. Then, classify the samples into positive or negative classes by changing the classification threshold. Calculate the TPR and FPR for each threshold. TPR represents the proportion of samples correctly predicted as positive, while FPR represents the proportion of samples incorrectly predicted as positive. The area under the receiver operating characteristic (AUC) is used to quantify the performance of the ROC curve. The results are shown below. Figure 15 As shown, the AUC of this model reaches 0.9098, which is close to the ideal model. The optimal sensitivity and specificity thresholds were determined using Youden's J index. A larger Youden's J index indicates greater realism, and the maximum value corresponds to the optimal diagnostic cutoff value of this method. The cutoff value for IAA is 28.85 ng / mL, with a sensitivity of 0.9048 and a specificity of 0.9149.

[0109] The above demonstrates that IAA can serve as a diagnostic marker for predicting the inactive and active phases of different stages of GO disease, exhibiting high sensitivity and specificity, and can be applied to clinical diagnosis.

[0110] References:

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[0112] [2]N.Wang,S.-y.Hou,X.Qi,M.Deng,J.-m.Cao,B.-D.Tong,W.Xiong,LncRNALPAL2 / miR-1287-5p / EGFR Axis Modulates TED-Derived Orbital FibroblastActivation Through Cell Adhesion Factors,The Journal of ClinicalEndocrinology&Metabolism,106(2021)e2866-e2886,https: / / doi.org / 10.1210 / clinem / dgab256.[3]C.C.Patrick,E.Roztocil,F.Husain,S.E.Feldon,C.F.Woeller,Tapinarof,an Aryl Hydrocarbon Receptor Ligand,Mitigates Fibroblast Activation inThyroid Eye Disease:Implications for Novel Therapy,InvestigativeOphthalmology&Visual Science,65(2024)40,https: / / doi.org / 10.1167 / iovs.65.13.40.

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[0114] [5]J.Y.Kim,S.Park,H.J.Lee,H.Lew,G.J.Kim,Functionally enhancedplacenta-derived mesenchymal stemcells inhibit adipogenesis in orbitalfibroblasts with Graves'ophthalmopathy,Stem Cell Res Ther,11(2020)469,https: / / doi.org / 10.1186 / s13287-020-01982-3.

[0115] [6]W.Yang,J.Wang,Z.Chen,J.Chen,Y.Meng,L.Chen,Y.Chang,B.Geng,L.Sun,L.Dou,J.Li,Y.Guan,Q.Cui,J.Yang,NFE2 Induces miR-423-5p to PromoteGluconeogenesis and Hyperglycemia by Repressing the Hepatic FAM3A-ATP-AktPathway,Diabetes,66(2017)1819-1832,https: / / doi.org / 10.2337 / db16-1172.

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[0117] [8]W.-L.Yang,C.-Y.Zhang,W.-Y.Ji,L.-L.Zhao,F.-Y.Yang,L.Zhang,X.Cao,Berberine Metabolites Stimulate GLP-1Secretion by Alleviating OxidativeStress and Mitochondrial Dysfunction,The American Journal of ChineseMedicine, 52(2024)253-274, https: / / doi.org / 10.1142 / s0192415x24500113.

[0118] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. The use of tryptophan metabolites in the preparation of medicaments for treating Graves' eye disease, characterized in that, The tryptophan metabolites include indolepropionic acid, indole-3-lactic acid, and / or indoleacetic acid.

2. The use according to claim 1, characterized in that, The drug also includes pharmaceutically acceptable excipients.

3. The use according to claim 2, characterized in that, Pharmaceutically acceptable excipients include fillers, binders, disintegrants, lubricants, sweeteners, flavoring agents, preservatives, surfactants, stabilizers, solubilizers, colorants, antioxidants, pH adjusters, buffers, chelating agents, thickeners, coating materials, or film-forming materials. And / or, the dosage form of the drug includes liquid, semi-solid, or solid dosage forms.

4. The use according to claim 3, characterized in that, The dosage forms of the drug include oral solutions, tablets, capsules, granules, pills, powders, syrups, ointments, creams, gels, suppositories, or injections.

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