Products and methods for the treatment of metabolic diseases, cardiovascular diseases, inflammatory diseases, and neoplastic diseases.

Abstract

This disclosure provides a tripeptide product for use in combination with Faecalibacterium in methods for treating metabolic diseases, cardiovascular diseases, inflammatory diseases, and neoplastic diseases.

Description

Detailed description of the invention

[0001] [Field] This disclosure provides a tripeptide product for use in combination with Faecalibacterium in methods for treating metabolic diseases, cardiovascular diseases, inflammatory diseases, and neoplastic diseases.

[0002] 〔background〕 The global prevalence of nonalcoholic fatty liver disease (NAFLD) and its severe form, nonalcoholic steatohepatitis (NASH), is increasing at an alarming rate. The overall prevalence of NAFLD is currently estimated at 32.4%, while the prevalence of NASH in the general population is estimated at 1.5–6.5%. NAFLD and NASH are major causes of chronic liver disease globally and are associated with increased cardiovascular, cancer, and liver-related mortality. In addition to its clinical impact, the significant economic burden of NAFLD exceeds $100 billion annually in direct costs in the United States alone. Despite the high prevalence of NAFLD and considerable efforts in drug development, there are currently no pharmacological therapies to treat this disease.

[0003] Currently, numerous compounds are being evaluated for NASH, but many show no improvement or have raised safety concerns in clinical trials (Vuppalanchi et al., 2021). Mice are the most frequently used animal in preclinical trials for potential therapies for NASH. However, although many NASH mouse models have been reported, most do not accurately mimic the human disease and cannot be applied clinically.

[0004] Recent studies have suggested that disruption of amino acid metabolism is involved in NASH (Gaggini et al., 2018; Hoyles et al., 2018; Mardinoglu et al., 2014; Rom et al., 2020; Simon et al., 2020). In particular, recent studies by our group and other groups have revealed glycine metabolism disorders as a causative factor and therapeutic target for NASH and related cardiometabolic diseases (Liu et al., 2021; Rom et al., 2018; Rom et al., 2020; Rom et al., 2022; Takashima et al., 2016; Wittemans et al., 2019).

[0005] U.S. Patent No. 8,664,177 (issued March 4, 2014), U.S. Patent No. 9,062,093 (issued June 23, 2015), and International Publication No. WO2020 / 033919 (published February 13, 2020) disclose the composition and uses of tripeptides.

[0006] There remains a need in this technology for products and methods to treat NAFLD and NASH, as well as other metabolic, cardiovascular, inflammatory, and neoplastic diseases.

[0007] 〔overview〕 This disclosure provides a tripeptide product combined with Faecalibacterium, as well as methods for treating metabolic diseases, cardiovascular diseases, inflammatory diseases, and neoplastic diseases.

[0008] In the experiments described herein, the dose-response of the tripeptide Gly-Gly-Leu (DT-109) was evaluated. The efficacy and safety of the tripeptide were then tested in non-human primates with established NASH that histologically and transcriptionally mimics human disease. A multi-omics approach combining transcriptomics, proteomics, metabolomics, and metagenomics was also applied, revealing that DT-109 improved hepatic steatosis and suppressed the progression of hepatic inflammation and fibrosis in non-human primates. This was achieved not only by promoting hepatic fatty acid degradation and GSH formation, but also through microbial regulation of bile acid (BA) metabolism.

[0009] This disclosure provides products and methods for treating metabolic, cardiovascular, inflammatory, or neoplastic diseases in subjects. The products and methods include a step of administering a Gly-Gly-Leu tripeptide and Faecalibacterium to a subject.

[0010] The aforementioned Faecalibacterium may be Faecalibacterium prausnitzii.

[0011] The aforementioned treatment may reduce the production of one or more secondary bile acids in the subject. For example, the production of lithocholic acid may be reduced.

[0012] The aforementioned treatment may reduce the amount of Escherichia Shigella present in the intestines of the subject.

[0013] The aforementioned disease may be a liver disease. For example, the disease may be NAFLD, and for another example, the disease may be NASH.

[0014] The treatment can reduce or suppress the progression of the hepatic steatosis score, lobular inflammation score, hepatocellular ballooning score, NAFLD activity score (NAS), and / or fibrosis score, and / or suppress the progression of hepatitis and fibrosis.

[0015] The aforementioned disease may be a biliary disease. For example, the disease may be primary biliary cirrhosis, and for another example, the disease may be biliary cholangiatis.

[0016] The subject may be a primate. The primate may be a human.

[0017] The aforementioned human subjects may be administered approximately 1 to 500 mg / kg / day of Gly-Gly-Leu tripeptide, approximately 3 to 144 mg / kg / day of Gly-Gly-Leu tripeptide, approximately 1 to 100 mg / kg / day of Gly-Gly-Leu tripeptide, approximately 12 to 36 mg / kg / day of Gly-Gly-Leu tripeptide, and approximately 37.5 mg / kg / day of Gly-Gly-Leu tripeptide.

[0018] The Gly-Gly-Leu tripeptide may be administered orally. The Gly-Gly-Leu tripeptide may be administered as a single dose.

[0019] [Brief explanation of the drawing] [Figure 1] A-M. Confirmation of NASH before random assignment to the experimental group.

[0020] C57BL / 6J mice were fed either a standard diet (SD) or a NASH diet for 12 weeks, and a portion of the mice (10 in each group) were euthanized.

[0021] (A) Liver weight / body weight ratio at week 12.

[0022] (B - D) Plasma concentrations of (B) AST, (C) ALT, and (D) ALP at week 12.

[0023] (E - G) Gross findings of the abdominal cavity (E) and histological analysis using (F) H&E staining or (G) Sirius Red staining at week 12 (scale bar: 50 μm).

[0024] (H - K) NAFLD activity score (NAS) at week 12 evaluated by histological analysis using H&E staining, which is the sum of the (H) steatosis score, (I) hepatocyte ballooning score, and (J) lobular inflammation score.

[0025] (K) Fibrosis score at week 12 evaluated by histological analysis using Sirius Red staining.

[0026] After NASH was confirmed, the remaining mice were randomly assigned to a group receiving oral administration of DT - 109 (increasing doses of 15, 45, 150, and 450 mg / kg / day) or a group receiving oral administration of H2O while continuing NASH diet for another 12 weeks. SD was given, and mice receiving H2O were used as the control group (10 mice per group). (L) Body weight at the end point. (M) Liver weight at the end point.

[0027] Data are mean ± SEM. Statistical differences were compared by unpaired t - test (A - D), Mann - Whitney U - test (H - K), Tukey's post - test after one - way ANOVA (L), or Dunn's post - test after Kruskal - Wallis test (M).

[0028] [Figure 2] A-K. DT-109 improves non-alcoholic steatohepatitis in mice in a dose-dependent manner. (A) Schematic diagram of the experimental design. C57BL / 6J mice were fed a standard diet (SD) or a NASH diet for 12 weeks, and some mice were euthanized to check for NASH and early liver fibrosis. After confirming NASH, the remaining mice were randomly assigned to either a group that continued the NASH diet for another 12 weeks while being orally administered DT-109 (gradually increasing doses of 15, 45, 150, and 450 mg / kg / day), or a group that was orally administered H2O. Mice given SD and H2O were used as the control group (10 mice in each group).

[0029] (B) Liver weight / body weight ratio at the end of the trial.

[0030] (C~E) Plasma concentrations of (C)AST, (D)ALT, and (E)ALP at the end of the process.

[0031] (F~H) Macroscopic findings of the abdominal cavity at the end of the (F) period, and histological analysis using (G) H&E staining or (H) Sirius Red staining (scale bar: 50 μm).

[0032] (I-J) Liver triglyceride and hydroxyproline content at the end of the procedure.

[0033] (K) NAFLD activity score (NAS) and fibrosis score at the end of the study. The NAS is the sum of the fatty degeneration score, hepatocyte ballooning score, and lobular inflammation score, which were evaluated by histological analysis using H&E staining. The fibrosis score was evaluated by histological analysis using Sirius Red staining.

[0034] Data are given as mean ± SEM. Statistical differences were compared using Tukey's post-hoc test after one-way ANOVA (B-D) or Dunn's post-hoc test after Kruskal-Wallis test (E, I-K).

[0035] [Figure 3] A-J. Establishment of a non-alcoholic steatohepatitis model in non-human primates that mimics human diseases.

[0036] (A) Schematic diagram of the experimental method. Monkeys with a predisposition to develop NASH were selected from more than 1,000 cynomolgus monkeys. 69 male monkeys (age ≥ 9 years, BMI > 30) were selected for physical, biochemical, and histological analysis. 20 monkeys with a NASH predisposition (NAFLD activity score (NAS) of 1-3) were selected and fed a NASH diet for 10 months. Biochemical, histological, and transcriptional (RNA-seq) indicators were evaluated before and after the 10-month NASH diet.

[0037] (B-E) Body weight, (C) Abdominal circumference, (D) Waist circumference, and (E) Serum AST at the start of the NASH diet and 10 months after the start of the diet.

[0038] (F~G) Histological analysis using (F) H&E staining or (G) Sirius Red staining at the start of the NASH diet and 10 months after the start of the diet (scale bar: 100 μm).

[0039] (H) NAS at the start of the NASH diet and 10 months after initiation. NAS is the sum of the fatty degeneration score, hepatocyte ballooning score, and lobular inflammation score, evaluated by histological analysis using H&E staining. The fibrosis score was evaluated by histological analysis using Sirius Red staining.

[0040] (I) Gene Set Enrichment Analysis (GSEA). RNA sequences from liver samples (n=5) obtained from monkeys at the start of the NASH diet and 10 months after the start of the diet were compared with RNA sequences from liver samples obtained from NASH patients (N=42) and age- and weight-matched control groups (n=6) (Hoang et al., 2019). Pathways enriched in upregulated or downregulated DEG are plotted in red or blue, respectively. Scale bar: -log10 of GSEA (p-value).

[0041] (J) Heatmap integrating RNA sequences from liver samples obtained from humans and monkeys (as described in (I)) with microarray data from 206 liver transplant donors with quantified liver fat content (dataset GSE26106, Brown et al. 2013; Wang et al., 2015). The left column represents gene function (cholesterol metabolism, fatty acid [FA] metabolism, fibrosis, or inflammation), and the adjacent column represents the correlation between gene expression and liver fat content in dataset GSE26106. Scale bar: Spearman's correlation coefficient (rho) ranges from -0.4 (blue) to +0.4 (red). Gene expression was further compared in liver samples obtained from monkeys and humans, as described in (I). Upregulated or downregulated genes are plotted in red or blue, respectively. Scale bar: log2 fold change.

[0042] All data are shown (B-E). Data are mean ± SEM. Statistical differences were compared using paired t-tests (B, C, and D) or Wilcoxon paired signed-rank tests (E and H). GSEA p-values ​​were calculated based on 100,000 substitutions (I). Statistical significance of expression differences was determined by Wald's test using the R package DESeq2 (J).

[0043] [Figure 4] A-I. Establishment of a non-alcoholic steatohepatitis model in non-human primates that mimics human diseases.

[0044] (A) Schematic diagram of the experimental design. Monkeys with a predisposition to develop NASH were selected from more than 1,000 cynomolgus monkeys. 69 male monkeys (age ≥ 9 years, BMI > 30) were selected for physical, biochemical, and histological analysis. 20 monkeys with a NAFLD activity score (NAS) of 1-3 and a predisposition to develop NASH were selected and fed a NASH diet for 10 months. Biochemical, histological, and transcriptional (RNA-seq) indicators were evaluated before and after the NASH diet for 10 months.

[0045] (B-I) At the start of the NASH diet and 10 months after the start of the diet, (B) waist circumference, (C) serum ALP, (D) fasting glucose, (E) hemoglobin A1c (HbA1c), (F) total cholesterol, (G) low-density lipoprotein cholesterol (LDL-C), (H) high-density lipoprotein cholesterol (HDL-C), and (I) triglycerides.

[0046] All data are shown (B-I). Statistical differences were compared using paired t-tests (B, E, and H) or Wilcoxon paired signed-rank tests (C, D, F, G, and I).

[0047] [Figure 5] A-B. Transcriptional similarities between cynomolgus monkeys with NASH and humans.

[0048] (A-B) Representation based on heatmaps of the top 100 differentially expressed genes. This representation was determined by RNA sequencing of liver samples (n=5) obtained from monkeys at the start of the NASH diet and 10 months after the start of the diet, and compared with RNA sequencing of liver samples from two independent human cohorts: (A) NASH patients (n=42) and age- and weight-matched control group (n=6) (Hoang et al., 2019), (B) NASH patients (n=16) and control group (n=14) (Suppli et al., 2019). Genes that are upregulated or downregulated in NASH are plotted in red or blue, respectively. Scale bar: log2 fold change.

[0049] The statistical significance of the expression differences was determined by the Wald test using the R package DESeq2 (A and B).

[0050] [Figure 6] NASH-related indicators in cynomolgus monkeys before DT-109 or vehicle administration are comparable.

[0051] Twenty cynomolgus monkeys with a predisposition to NASH were fed a NASH diet for 10 months. After confirming NASH, the monkeys were randomly assigned to either a group receiving oral DT-109 (150 mg / kg / day, n=10) or a group receiving oral vehicle (H2O, n=10) while continuing the NASH diet for another 5 months. Physical, biochemical, and histological analyses based on biopsies confirmed that indicators that may directly or indirectly affect the progression of NASH were equivalent between the two groups before DT-109 or vehicle administration.

[0052] (A-K) In cynomolgus monkeys fed a NASH diet for 10 months prior to administration of DT-109 or vehicle, (A) age, (B) body weight, (C) abdominal circumference, (D) waist circumference, (E) fasting blood glucose, (F) hemoglobin A1c (HbA1c), (G) serum total cholesterol, (H) triglycerides, (I) AST, (J) ALP, (K) histological score (hepatic steatosis score, lobular inflammation score, hepatocyte ballooning score, NAFLD activity score (NAS), and fibrosis score).

[0053] Ten months after the start of the diet, the monkeys were randomly assigned to either a group that received oral DT-109 (150 mg / kg / day, n=10) while continuing the NASH diet for another five months, or a group that received oral H2O (vehicle control, n=10).

[0054] (L~O) At the end of the measurement: (L) waist circumference, (M) total cholesterol, (N) triglycerides, and (O) HbA1c.

[0055] Data are mean ± SEM. Statistical differences were compared using unpaired t-tests (A-D, F, J, K [NAS and fibrosis scores], L) or Mann-Whitney U tests (E, G-I, K [hepatic steatosis score, lobular inflammation score, hepatocyte ballooning score], and M-O).

[0056] [Figure 7] A-I. DT-109 improves feed-induced fatty degeneration and inhibits the progression of inflammation and fibrosis in the livers of non-human primates with established NASH.

[0057] After a 10-month diet, cynomolgus monkeys were randomly assigned to either a group receiving oral force-feeding of DT-109 (150 mg / kg / day, n=10) while continuing a NASH diet for another 5 months, or a group receiving oral force-feeding of H2O (vehicle control, n=10).

[0058] (A-E) At the end of the trial: (A) body weight, (B) waist circumference, (C) serum AST, (D) ALT, and (E) ALP.

[0059] (F~H) Macroscopic findings of the abdominal cavity at the end of the study, and (G) histological analysis using H&E staining or (H) Sirius Red staining (scale bar: 100 μm).

[0060] (I) NAFLD activity score (NAS) and fibrosis score before and after treatment with DT-109 or vehicle. The NAS is the sum of the fatty degeneration score, hepatocyte ballooning score, and lobular inflammation score, as assessed by histological analysis using H&E staining. The fibrosis score was assessed by histological analysis using Sirius Red staining.

[0061] Data are mean ± SEM. Statistical differences were compared between DT-109 treatment and vehicle treatment using unpaired t-tests (A, B, D, and E) or Mann-Whitney U tests (C, and I [hepatic steatosis score, lobular inflammation score, hepatocyte ballooning score, and fibrosis score]). Statistical differences were also compared between histological parameters before and after treatment using paired t-tests (I [lobular inflammation score, NAS, and fibrosis score]) or Wilcoxon paired signed-rank tests (I [hepatic steatosis score, and hepatocyte ballooning score]).

[0062] [Figure 8] A-L. Transcriptomics and proteomics revealed that DT-109 induces hepatic fatty acid degradation and suppresses pro-inflammatory / fibrotic responses.

[0063] RNA sequencing and proteomics were performed on the livers (n=5) of cynomolgus monkeys treated with DT-109 or a vehicle for 5 months.

[0064] (A) Principal component analysis (PCA) of RNA sequencing data.

[0065] (B) Volcano plot of DEG (blue, down-adjusted; red, up-adjusted, >2x, p<0.05).

[0066] (C~D) Pathways enriched in the upregulated or downregulated DEG are plotted in red (C) or blue (D), respectively.

[0067] (E) Heatmap representation of 50 NASH-related DEGs (involved in fatty acid and cholesterol metabolism, inflammation, and fibrosis). Gene expression levels of two groups (5 animals each) are plotted. Scale bar: log2 fold change.

[0068] (F) GSEA based on RNA sequencing and proteomics data. Scale bar: -log10 (p-value) of GSEA.

[0069] (G~J) Histological evaluation of neutral triglycerides and lipids using Oil Red O (ORO) staining, (H, J) Immunohistochemical staining for CD68, and (I) Biochemical quantification of liver triglycerides in monkeys (n=10) treated with DT-109 or vehicle.

[0070] Quantification of (K) liver hydroxyproline content and (L) liver glutathione (GSH) content in monkeys (n=10) treated with (K~L)DT-109 or vehicle.

[0071] All data are shown (A-B). Data are mean ± SEM, and all data points are shown (I-L). Statistical significance of expression differences was determined by Wald's test using the R package DESeq2 (B and E). P-values ​​for GSEA were calculated based on 100,000 substitutions (C, D, and F). Statistical differences were compared using unpaired t-tests (I, J, and K) or Mann-Whitney U tests (L).

[0072] [Figure 9] A-B. Transcriptomics and proteomics after DT-109 treatment.

[0073] RNA sequencing and proteomics were performed on the livers (n=5) of monkeys treated with DT-109 or a vehicle for 5 months.

[0074] (A) Heatmap representation of the top 100 differentially expressed genes (DEGs) based on RNA sequencing. Genes upregulated or downregulated by DT-109 treatment are plotted in red or blue, respectively. Scale bar: log2 fold change.

[0075] (B) Heatmap representation of the top 100 DEGs based on RNA sequencing and their corresponding proteins based on proteomics. Genes or proteins upregulated or downregulated by DT-109 treatment are plotted in red or blue, respectively. Scale bar: log2 fold change.

[0076] The statistical significance of the expression difference was determined by the Wald test using the R package DESeq2 (A and B). The significance at the protein level was determined by the t-test (B).

[0077] [Figure 10] A-H. Non-targeted and targeted metabolomics demonstrate the suppression of bile acid metabolism by DT-109.

[0078] Non-targeted and targeted metabolomics were performed on serum (n=5) from cynomolgus monkeys treated with DT-109 or a vehicle for 5 months.

[0079] (A) Schematic diagram of the experimental method. Non-targeted metabolomics of serum samples were performed using LC-MS, followed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Changes in serum bile acids (BA) were confirmed using targeted metabolomics.

[0080] (B~C)PCA(B), and OPLS-DA(C).

[0081] (D) Metabolic pathway enrichment analysis.

[0082] (E) Representation based on heatmaps of metabolites that significantly changed among monkeys treated with DT-109 or vehicle. This representation is based on variable importance in projection (VIP) values, fold change (FC), and p-values ​​of annotated metabolites. Scale bar: Z score log2 transformed intensity value.

[0083] (F) Relative strength of BA species based on non-targeted metabolomics.

[0084] (G) Concentration of BA species as measured by targeted metabolomics.

[0085] (H) Concentration of the BA group as measured by targeted metabolomics.

[0086] The data are represented as mean ± SEM and show all data points (F-H). Statistical differences were compared using unpaired t-tests (F-H) or Mann-Whitney U tests (F-H) based on the results of normality tests.

[0087] [Figure 11] A-F. Non-targeted and targeted metabolomics demonstrate the suppression of bile acid metabolism by DT-109.

[0088] (A) C57BL / 6J mice were fed a standard diet (SD) or a NASH diet for 12 weeks. A portion of the mice were euthanized to check for NASH and early liver fibrosis. After confirming NASH, the remaining mice were randomly assigned to either receive oral DT-109 at gradually increasing doses while continuing the NASH diet for another 12 weeks, or receive oral H2O (vehicle). Mice given SD and vehicle were used as the control group. For targeted metabolomics, bile acid (BA) levels in serum collected at the end of the study were evaluated using LC-MS from mice treated with DT-109 (150 and 450 mg / kg / day) or from mice treated with vehicle under NASH diet or SD conditions (n=10).

[0089] (B~F) Non-targeted metabolomics were performed on the livers (n=5) of monkeys treated with DT-109 or vehicle for 5 months using LC-MS, followed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Changes in serum bile acids were confirmed using targeted metabolomics.

[0090] (B~C)PCA(B), and OPLS-DA(C).

[0091] (D) Metabolic pathway enrichment analysis.

[0092] (E) Concentration of BA group in the liver as measured by targeted metabolomics.

[0093] (F) Concentration of lithocholic acid (LCA) in the liver as measured by targeted metabolomics.

[0094] Data are shown as mean ± SEM, representing all data points (A, E, and F). Statistical differences were compared using Tukey's post-hoc test after one-way ANOVA (A) or Dunn's post-hoc test after Kruskal-Wallis test (A), based on the results of normality tests. Statistical differences were also compared using unpaired t-tests (E) or Mann-Whitney U tests (E and F), based on the results of normality tests.

[0095] [Figure 12] A-H. DT-109 alters the gut microbiome in relation to lithocholic acid.

[0096] (A-D) A comprehensive analysis of BA species was performed on fecal samples from cynomolgus macaques treated with DT-109 or vehicle for 5 months (n=5).

[0097] (A) Principal component analysis (PCA) of BA species in feces.

[0098] (B) Orthogonal partial least squares discriminant analysis (OPLS-DA) of BA species in feces.

[0099] (C) Representation based on a heatmap of BA species detected in fecal samples.

[0100] (D)BA species (lithocholic acid, LCA; ursodeoxycholic acid, UDCA; hyodeoxycholic acid, HDCA; mulic acid, MCA) that showed a significant difference between the monkeys administered DT-109 and those administered vehicle. Data are mean ± SEM and all data points are shown. Statistical differences were compared using an unpaired t-test or Mann-Whitney U test based on the results of a normality test.

[0101] (E~H) 16S rRNA sequencing was performed on fecal samples from cynomolgus monkeys treated with DT-109 or vehicle for 5 months (n=5).

[0102] (E) Beta diversity analysis using non-metric multidimensional scaling (NMDS).

[0103] (F) A taxonomic cladogram generated by linear discriminant analysis (LDA) effect size method (LEfSe).

[0104] (G) LDA of bacterial taxa that are excessively present in monkey samples from the DT-109 administration group (blue) and the vehicle administration group (red).

[0105] (H) Correlation between significantly changed genera abundance, NASH-related parameters, and liver LCA concentration. Spearman's correlation coefficient ranges from -1 (blue) to +1 (red).

[0106] [Figure 13] A-C. Effects of DT-109 on the gut microbiome in cynomolgus monkeys with NASH.

[0107] (A-C) 16S rRNA sequencing was performed on fecal samples from cynomolgus monkeys treated with DT-109 or vehicle for 5 months (n=5).

[0108] (A) The top 10 most abundant phyla in individual fecal samples and in the average values ​​of the two groups.

[0109] (B) The top 10 most abundant classes in individual fecal samples and in the average values ​​of the two groups.

[0110] (C) The top 10 genera showing a significant difference between monkeys administered DT-109 (blue) and monkeys administered vehicle (red).

[0111] The data are shown as mean ± SEM and represent all data points (C). Statistical differences were compared using an unpaired t-test or Mann-Whitney U test based on the results of a normality test.

[0112] [Figure 14] A-F. DT-109 suppresses microbial production of lithocholic acid, which increases in NAFLD patients.

[0113] (A) qPCR (n=9-10) using primers specific to Faecalibacterium prausnitzii on fecal bacterial DNA obtained from cynomolgus monkeys treated with DT-109 or vehicle for 5 months. Data were normalized to 16S expression levels.

[0114] (B) qPCR (n=9-10) using Escherichia sigella-specific primers on fecal bacterial DNA obtained from cynomolgus monkeys treated with DT-109 or vehicle for 5 months. Data were normalized to 16S expression levels.

[0115] (C)Lithocholic acid (LCA) production by microorganisms was evaluated by incubating mouse feces with isotope-labeled chenodeoxycholic acid (d4-CDCA) for 0 to 16 hours in the presence or absence of DT-109 (concentration increasing from 0 to 500 μM). The newly generated LCA (d4-LCA) was measured using mass spectrometry. At the end of the experiment, the data were normalized to relative intensity. A representative experiment with n=6 biological replicates is shown (n=2-3 independent experiments).

[0116] (D) Microbial LCA production was evaluated by incubating mouse feces with d4-CDCA and either Faecalibacterium prausnitzii (OD600=0.35~0.45) or Gifu anaerobic medium (control) for 0-24 hours. The newly generated d4-LCA was measured using mass spectrometry. Data were normalized to relative intensity at the end of the study. Representative experiments with n=3 biological replicates are shown (n=3 independent experiments).

[0117] (E) LC-MS analysis of plasma LCA in NAFLD patients (n=149) and healthy control group (n=229).

[0118] (F) The schematic diagram shows the mechanism of action of DT-109 against NASH.

[0119] The data are shown as mean ± SEM and represent all data points. Statistical differences were compared using unpaired t-tests (A, D), Mann-Whitney U tests (B, E), or Tukey's post-hoc test after one-way ANOVA (C).

[0120] [Detailed explanation] This disclosure provides tripeptide molecules that exhibit prophylactic or therapeutic effects against metabolic diseases, cardiovascular diseases, and / or inflammatory diseases, and pharmaceutically acceptable salts thereof.

[0121] (Tripeptides and Compositions) Tripeptide DT-109 is an exemplary tripeptide used in the examples herein. It is a glycine-containing tripeptide molecule having the sequence Gly Gly Leu. Another exemplary tripeptide provided herein is tripeptide DT-110, a glycine-containing tripeptide molecule having the sequence Gly Gly dLeu. Tripeptides can be prepared by peptide synthesis methods well known in the art.

[0122] The tripeptides of this disclosure may include one or more non-peptide bonds instead of peptide bonds. For example, the peptide may include an ester bond, an ether bond, a thioether bond, or an amide bond instead of a peptide bond.

[0123] The tripeptides of this disclosure also include pharmaceutically acceptable salts (such as pharmaceutically acceptable salts of DT-109 and DT-110). Non-limiting examples of such salts include metal salts, ammonium salts, salts with organic bases, salts with inorganic acids, salts with organic acids, salts with basic or acidic amino acids, and others. Non-limiting examples of metal salts include alkali metal salts (such as sodium salts, potassium salts, and others); alkaline earth metal salts (such as calcium salts, magnesium salts, barium salts, and others); aluminum salts, and others. Non-limiting examples of salts with organic bases include salts with trimethylamine, triethylamine, pyridine, picoline, 2,6-lutidine, ethanolamine, diethanolamine, triethanolamine, cyclohexylamine, dicyclohexylamine, N,N-dibenzylethylenediamine, and others. Non-limiting examples of salts with inorganic acids include salts with hydrochloric acid, hydrobromic acid, nitric acid, sulfuric acid, phosphoric acid, and others. Non-limiting examples of salts with organic acids include salts with formic acid, acetic acid, trifluoroacetic acid, phthalic acid, fumaric acid, oxalic acid, tartaric acid, maleic acid, citric acid, succinic acid, malic acid, methanesulfonic acid, benzenesulfonic acid, p-toluenesulfonic acid, and others.

[0124] Tripeptides can be synthesized and / or administered as prodrugs. A prodrug is a molecule that is converted into a tripeptide by a reaction involving enzymes, gastric acid, etc., under the physiological conditions of the therapeutic subject.

[0125] Examples of prodrugs of tripeptides, or prodrugs of pharmaceutically acceptable salts thereof, include tripeptides in which the amino group of the tripeptide molecule is acylated, alkylated, or phosphorylated (e.g., the amino group of a glycine-containing tripeptide molecule is eicosanoylated, alanylated, pentylaminocarbonylated, (5-methyl-2-oxo-1,3-dioxolene-4-yl)methoxycarbonylated, tetrahydrofuranylated, pyrrolidylmethylated, pivaloyloxymethylated, or tert-butylated); and tripeptides in which the hydroxyl group of the tripeptide molecule is acylated, alkylated, phosphorylated, or boronated (e.g., the hydroxyl group of the tripeptide is acetylated, palmitoylated, or propanoylated). This includes tripeptides that have been esterified, pivaloylated, succinylated, fumalylated, alanylated, or dimethylaminomethylcarbonylated; tripeptides in which the carboxyl group of the tripeptide molecule is esterified or amidated (for example, the carboxyl group of a glycine-containing tripeptide molecule is C1-6 alkyl esterified, phenyl esterified, carboxymethyl esterified, dimethylaminomethyl esterified, pivaloyloxymethyl esterified, ethoxycarbonyloxyethyl esterified, phthalidyl esterified, (5-methyl-2-oxo-1,3-dioxolene-4-yl)methyl esterified, cyclohexyloxycarbonylethyl esterified, or methylamidated), and others similar. For example, the carboxyl group of the tripeptide molecule is esterified with a C1-6 alkyl group (methyl, ethyl, tert-butyl, and others similar).

[0126] Prodrugs of tripeptides, or prodrugs of pharmaceutically acceptable salts thereof, may be converted to the tripeptide under physiological conditions (as described in IYAKUHIN no KAIHATSU (Development of Pharmaceuticals), Vol.7, Design of Molecules, pp.163-198, Published by HIROKAWA SHOTEN (1990), etc.).

[0127] This disclosure provides compositions comprising at least one tripeptide and a pharmaceutically acceptable excipient. In this specification, the term “pharmaceutically acceptable” means approved by a federal or state regulatory authority or listed in the United States Pharmacopeia or any other commonly accepted pharmacopoeia for use in animals (such as humans).

[0128] The tripeptide compositions provided herein are prepared with pharmaceutically acceptable excipients (carriers, solvents, stabilizers, adjuvants, diluents, etc.) depending on the method of administration and dosage form. The drug carrier may be a sterile liquid (such as water or oil), and the oil may be of petroleum, animal, plant, or synthetic origin, such as peanut oil, soybean oil, mineral oil, and sesame oil. When the drug composition is administered intravenously, water is a typical carrier. Saline solutions, as well as aqueous dextrose and glycerol solutions, can be used as liquid carriers, particularly for injections. Suitable drug excipients include starch, glucose, lactose, sucrose, gelatin, malt, rich, wheat flour, chalk, silica gel, sodium stearate, glyceryl monostearate, talc, sodium chloride, skim milk powder, glycerol, propylene, glycol, water, ethanol, and others. If necessary, the composition may also contain trace amounts of wetting agents or emulsifiers, or pH buffers.

[0129] The composition may include, for example, one or more formulation materials for adjusting, maintaining, or preserving pH, osmotic pressure, viscosity, transparency, color, isotonicity, odor, sterility, stability, dissolution or release rate, adsorption or permeability. Suitable formulation materials include amino acids (such as glutamine, asparagine, arginine, or lysine); antibacterial agents; antioxidants (such as ascorbic acid, sodium sulfite, or sodium bisulfite); buffers (such as borates, bicarbonates, Tris-HCl, citrates, phosphates, and other organic acids); bulking agents (such as mannitol or glycine); chelating agents (ethylenediaminetetraacetic acid (EDTA)); compounding agents (such as caffeine, polyvinylpyrrolidone, β-cyclodextrin, hydroxypropyl β-cyclodextrin); fillers; monosaccharides; disaccharides and other carbohydrates (such as glucose, mannose, or dextrin); proteins (such as serum albumin, gelatin, or immunoglobulin); colorants; flavorings and diluents; emulsifiers; hydrophilic polymers (such as polyvinylpyrrolidone); low molecular weight polypeptides; salt-forming counterions (such as sodium); and preservatives (such as benzalkonium chloride, benzoyl benzoate). This includes, but is not limited to, fragrant acids, salicylic acid, thimerosal, phenethyl alcohol, methylparaben, propylparaben, chlorhexidine, sorbic acid, or hydrogen peroxide; solvents (such as glycerin, propylene glycol, or polyethylene glycol); sugar alcohols (such as mannitol or sorbitol); suspending agents; surfactants or wetting agents (such as Pluronic acid, PEG, sorbitan esters, polysorbates (such as polysorbate 20, polysorbate 80), Triton, tromethamine, lecithin, cholesterol, tyloxapal); stability enhancers (sucrose or sorbitol); tonicity adjusters (alkali metal halides (in one embodiment, sodium chloride or potassium chloride, mannitol or sorbitol)); delivery vehicles; diluents; excipients, and / or drug adjuvants (Remington's Pharmaceutical Sciences, 18th Edition, AR Gennaro, ed., Mack Publishing Company, 1990).

[0130] The pharmaceutical composition may take the form of a solution, suspension, emulsion, tablet, pill, capsule, powder, sustained-release formulation, or other similar form.

[0131] The composition is generally formulated to achieve a physiologically suitable pH, which, depending on the formulation and route of administration, is in the range of about 3 to about 11 or about 3 to about 7. The pH may be adjusted to a range of about 5.0 to about 8. The composition contains a therapeutically effective amount of at least one tripeptide as described herein and may also contain one or more pharmaceutically acceptable excipients. The composition may contain additional therapeutic active ingredients.

[0132] The tripeptides of this disclosure may be supplied in single-use glass vials as lyophilized cakes prepared to pH 4.25 in a formulation buffer consisting of 10 mM glutamic acid, 2% glycine, 1% sucrose, and 0.01% polysorbate 20. Upon reconstitution with a predetermined amount of sterile diluent (e.g., sterile isotonic saline or water; e.g., 0.5 mL to approximately 10 mL; e.g., 2.2 mL of sterile water), the cake generates glycine tripeptide molecules at concentrations of 1 g / mL to approximately 100 g / mL. When the single-use vials are reconstituted, the tripeptide composition may be administered rapidly (i.e., within 3 hours after reconstitution) after reaching room temperature (15-30°C).

[0133] (Faecalibacterium) The human digestive tract is home to 500 to 1000 bacterial genera, which promote digestion and nutrient absorption, influence the host's metabolism, and shape the immune system. Only a few are dominant (Bacteroides, Clostridium, Bifidobacterium, and Faecalibacterium). The genus Faecalibacterium has been reclassified into the family Oscillospiraceae, which belongs to the order Eubacteriales, and consists of three officially recognized species: F. longum, F. butyricigenerans, and F. prausnitzii. F. prausnitzii is one of the dominant bacteria in the human gut, making up about 5% of the total fecal microbiota in healthy adults.

[0134] This disclosure intends to use F. prausnitzii as a bio-based therapeutic agent to be used in combination with the tripeptide of this disclosure in the therapeutic method of this disclosure. This disclosure intends to show that F. prausnitzii is an example of an intestinal bacterium that may be used to reduce secondary bile acids.

[0135] F. prausnitzii is available from various suppliers. Examples of suppliers include, but are not limited to, the American Type Culture Collection (ATCC) and Creative Biolabs. F. prausnitzii can be cultured in modified enhanced Clostridium medium (e.g., from Beijing Coolaber Technology Co., Ltd. (Coolaber, DZSL0529)) under strict anaerobic conditions. After culturing, the bacteria can be recovered by centrifugation and resuspended in sterile PBS containing 10% glycerol for storage.

[0136] F. prausnitzii can be formulated as a liquid or solid dosage form. If the dosage form is a liquid composition, the concentration of viable bacteria in the liquid composition is, for example, about 10 9 ~10 12 CFU / ml, approximately 10 9 ~10 11 CFU / ml, or 5x10 10 The concentration may be CFU / ml. In liquid dosage form, F. Prausnitzii can be suspended in phosphate buffer (1X phosphate buffer, pH approximately 7.3) and may contain 10% glycerol by volume. The liquid composition may be used directly or stored at low temperatures (preferably -80°C).

[0137] (Treatment methods) This disclosure provides a method of using the tripeptides provided herein in combination with F. Prausnitzii to prevent and / or treat one or more metabolic diseases, cardiovascular diseases, inflammatory diseases, and neoplastic diseases in a subject.

[0138] The methods provided herein can reduce the production of secondary bile acids by a subject. The secondary bile acid may be lithocholic acid. The reduction in secondary bile acid production may be approximately 5%, 10%, 20%, 30%, 35%, or 40%, or greater, compared to the production level before treatment. Secondary bile acids are obtained from primary bile acids in a process that depends on the biosynthetic capacity of the gut microbiome.

[0139] The methods provided herein can reduce the abundance of Escherichia sigella in the intestinal tract of a subject. Methods for analyzing bacteria are standard in the art and include, for example, collecting and culturing fecal samples from a subject and PCR analysis to identify bacteria in the samples.

[0140] In this method, the subject is administered a therapeutically effective amount of the tripeptide composition of this disclosure and a therapeutically effective amount of F. Prausnitzii. “Therapeutally effective amount” as used herein means an amount of tripeptide sufficient to produce a detectable therapeutic effect. Such effect is detected, for example, by improvement in clinical conditions or by prevention, reduction, or mitigation of complications. The exact effective amount for the subject depends on the subject’s weight, build, and health status; the nature and severity of the disease; and the therapeutic agent (or combination of therapeutic agents) selected for administration. The therapeutically effective amount for a particular situation is determined by routine experiments conducted within the scope of the clinician’s skill and judgment. The combined use of the tripeptide composition and F. Prausnitzii may result in additional or synergistic therapeutic effects.

[0141] The therapeutically effective doses of the tripeptides disclosed herein may be approximately 1 mg / kg / day to approximately 10,000 mg / kg / day, approximately 5 mg / kg / day to approximately 5,000 mg / kg / day, approximately 20 mg / kg / day to approximately 1,000 mg / kg / day, approximately 30 mg / kg / day to approximately 1,000 mg / kg / day, approximately 50 mg / kg / day to approximately 10,000 mg / kg / day, or approximately 100 mg / kg / day to approximately 5,000 mg / kg / day. The therapeutically effective doses of the tripeptides disclosed herein may be approximately 1 to approximately 500 mg / kg / day, approximately 3 to approximately 144 mg / kg / day, approximately 1 to approximately 100 mg / kg / day, approximately 12 to approximately 36 mg / kg / day, or approximately 37.5 mg / kg / day.

[0142] The therapeutically effective amount of the tripeptide of this disclosure in the compositions provided herein may be about 250 mg to about 500 g, about 500 mg to about 400 g, about 750 mg to about 200 g, or about 1,000 mg to about 100 g. The therapeutically effective amount of the tripeptide of this disclosure in the compositions provided herein may be about 300 mg to about 1,000 g, about 500 mg to about 500 g, about 600 mg to about 400 g, about 700 mg to about 300 g, about 800 mg to about 200 g, about 900 mg to about 150 g, or about 1,000 mg to about 100 g. The amount of tripeptide may be about 600 mg to about 300 g.

[0143] The tripeptide compositions of this disclosure may be administered as a single dose once daily, or in multiple divided doses throughout the day (e.g., 1 to 5 times per day, or 2 to 3 times per day). The tripeptide compositions may be administered every other day. The tripeptide compositions may be administered once weekly. Dosage schedules and doses for specific situations are determined by routine experiments conducted within the scope of the clinician's skill and judgment.

[0144] F. Prausnizzi, for example, approximately 1 × 10 6 , about 1×10 7 , or approximately 1 × 10 8 It may be administered in CFU / day doses. The subjects may be mammals. The mammals may be primates (such as humans). The mammals may be domesticated mammals or laboratory mammals. Subjects in need of treatment are those experiencing metabolic diseases, and / or cardiovascular diseases, and / or inflammatory diseases, and / or neoplastic diseases, or one or more symptoms associated with these diseases.

[0145] The tripeptides and F. prausnitzii provided herein may be administered orally. Oral administration is intended to be achieved in some embodiments by using delivery vehicles known in the art (including, but not limited to, microspheres, liposomes, enteric-coated dry emulsions, or nanoparticles). Subjects may be fed a diet containing the tripeptides of this disclosure.

[0146] The Disclosure also provides a kit comprising the tripeptide of the Disclosure, F. Prausnitzii, instructions or labels for the use of these two, and a device for measuring the amount of the tripeptide composition or a device for administering the tripeptide composition to a subject. The kit may include one or more additional therapeutic agents.

[0147] (metabolic disease) In this specification, metabolic disorders refer to a group of diseases involving metabolic disorders that are risk factors for various cardiovascular diseases and type 2 diabetes. These metabolic disorders include insulin resistance and a complex and diverse range of related metabolic disorders. In 1988, Reaven proposed insulin resistance as the underlying factor for these diseases and named the set of abnormalities insulin resistance syndrome. However, in 1998, the World Health Organization (WHO) introduced the terms metabolic syndrome or metabolic disorders, as not all aspects of the symptoms can be explained by insulin resistance. Treatment of metabolic disorders may include, for example, obesity, diabetes, hyperlipidemia, non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), and / or insulin resistance syndrome. As described herein, metabolic disorders include diseases that can be treated through metabolic regulation, but the diseases themselves may or may not be caused by specific metabolic abnormalities. Such metabolic disorders may involve, for example, the oxidation pathways of glucose and fatty acids. The tripeptides of this disclosure (e.g., DT-109 and DT-110), in combination with F. prausnitzii, can prevent or treat metabolic disorders.

[0148] The aforementioned metabolic disease may be a liver disease.

[0149] NAFLD is on the rise globally, particularly in Western countries. In the United States, it is the most common form of chronic liver disease, affecting an estimated 80 to 100 million people. Non-alcoholic fatty liver disease (NAFLD) is a general term for a range of liver conditions that affect people who drink little to no alcohol. As the name suggests, the main characteristic of NAFLD is the excess fat stored in liver cells. It is normal for the liver to contain some fat. However, if 5-10% or more of the liver's weight is fat, the condition is called fatty liver (or steatosis).

[0150] NAFLD is strongly associated with the characteristics of metabolic syndrome (including obesity, insulin resistance, type 2 diabetes, and dyslipidemia) and is considered to be a hepatic manifestation of this syndrome.

[0151] Pediatric NAFLD is currently the leading form of liver disease in children. Studies have shown that abdominal obesity and insulin resistance are major contributing factors to the development of NAFLD. As obesity is a globally increasing problem, the prevalence of NAFLD is also increasing.

[0152] A more severe form of NAFLD is called non-alcoholic steatohepatitis (NASH). NASH causes swelling and damage to the liver. NASH is more likely to occur in overweight or obese individuals, or in people with diabetes, hypercholesterolemia, hypertriglyceridemia, or inflammatory conditions. A potentially serious disease form, NASH is characterized by hepatocyte ballooning and inflammation of the liver, which can progress to scarring and irreversible damage. This damage is similar to that caused by excessive alcohol consumption. Macroscopically and microscopically, NASH is characterized by lobular and / or periportal inflammation, varying degrees of fibrosis, hepatocyte death, and pathological angiogenesis. In the most severe cases, NASH can progress to cirrhosis, hepatocellular carcinoma, and liver failure. Currently, NAFLD and NASH are treated with dietary changes, treatment of insulin resistance, and vitamin supplementation (such as vitamins E and D).

[0153] In the treatments for liver diseases (such as NAFLD, NASH, and alcoholic steatohepatic degeneration) provided herein, such treatments may stabilize or reduce the subject's NAFLD activity score. The NAFLD activity score (NAS) can be calculated according to the criteria of Kleiner et al. (Kleiner DE. et al., Hepatology, 2005; 41:1313). NAS scores of 0-2 are not considered diagnostic criteria for NASH, and NAS scores of 3-4 are also not considered diagnostic criteria or may be borderline or positive for NASH, while NAS scores of 5-8 are primarily considered diagnostic criteria for NASH. Therapeutic effects on NASH include recovery, stabilization, or a reduction in the rate of disease progression. Sequential liver biopsies from patients potentially with NASH may be used to assess changes in the NAS score and may be used as an indicator of changes in the disease state. Increasing scores suggest progression, unchanged scores suggest stabilization, and decreasing scores suggest recovery from NASH. In controlled clinical trials, the difference in NAS scores between the placebo group and the investigational drug group, typically assessed over 6 months to 2 years, can indicate a therapeutic effect even if both groups are experiencing disease progression. Regulatory authorities typically require a defined point spread to demonstrate a significant change in NASH.

[0154] The therapies provided herein can reduce or inhibit the progression of hepatic steatosis scores, lobular inflammation scores, hepatocyte ballooning scores, NAFLD activity scores (NAS), and / or fibrosis scores. Imaging techniques are standard in the art and include, for example, non-invasive imaging techniques (such as magnetic resonance imaging and magnetic resonance elastography), as well as histological analysis of invasive liver biopsies.

[0155] The NAFLD treatment kit provided herein includes the tripeptide, F. prausnitzii, optionally a statin, and instructions for use. The NASH treatment kit provided herein includes the tripeptide, optionally a statin, and instructions for use.

[0156] (Cardiovascular disease) In this specification, cardiovascular disease refers to arteriosclerosis and its complications. Arteriosclerosis is caused by the hardening and thickening of the arteries, which are the blood vessels that carry oxygen and nutrients from the heart to other parts of the body. This can restrict blood flow to organs and tissues. Arteriosclerosis can lead to numerous complications, including myocardial infarction, coronary artery disease, carotid artery disease, peripheral artery disease, aneurysms, and chronic kidney disease.

[0157] Myocardial infarction (heart attack) occurs when blood flow to a part of the heart decreases or stops, damaging the heart muscle. Common symptoms include pain in the center or left side of the chest, shortness of breath, and nausea, and can lead to heart failure, arrhythmia, cardiogenic shock, or cardiac arrest.

[0158] Coronary artery disease is a condition in which the arteries near the heart narrow due to arteriosclerosis, which can cause chest pain (angina), heart attack, or heart failure.

[0159] Carotid artery disease occurs when arteriosclerosis narrows the arteries near the brain, potentially leading to a transient ischemic attack (TIA) or stroke. Symptoms may include sudden numbness or weakness in the arms or legs, temporary vision loss in one eye, or drooping of the facial muscles.

[0160] Peripheral artery disease is a condition in which the arteries in the arms or legs narrow due to arteriosclerosis, causing circulatory problems. It can dull the sensation of heat and cold, increasing the risk of burns or frostbite. Rarely, poor circulation in the arms or legs can cause tissue necrosis (gangrene). Symptoms include leg pain when walking (intermittent claudication).

[0161] An aneurysm is a bulge in the artery wall and can be a medical emergency. If an aneurysm ruptures, it can be life-threatening.

[0162] Chronic kidney disease can be caused by arteriosclerosis, which narrows the arteries leading to the kidneys, preventing oxygenated blood from reaching the kidneys. Over time, this can affect kidney function and hinder the elimination of waste products from the body. Symptoms include high blood pressure or kidney failure.

[0163] The tripeptides of this disclosure (e.g., DT-109 and DT-110), in combination with F. Prausnitzii, can prevent or treat arteriosclerosis and its complications.

[0164] (inflammatory disease) In this specification, treatment of inflammatory diseases refers to treatment of inflammation in the gastrointestinal tract, and inflammation is reduced by administering the tripeptides provided herein. The tripeptides of this disclosure, in combination with F. prausnitzii, can prevent or treat inflammation in the gastrointestinal tract, as demonstrated by a decrease in alkaline phosphatase (ALP) levels. The analytical method for ALP is standard in the art and involves measuring the blood concentration in the subject. The tripeptides of this disclosure, in combination with F. prausnitzii, can prevent or treat, for example, biliary tract diseases (such as primary biliary cirrhosis and biliary cholangitis).

[0165] (Neoplastic disease) NASH can cause cirrhosis, and cirrhosis can further lead to hepatocellular carcinoma. The tripeptides of this disclosure, in combination with F. prausnitzii, can prevent or treat cancer (such as hepatocellular carcinoma).

[0166] (bile acid) Bile acids, which are normal metabolites in the intestinal lumen, are necessary for the digestion and absorption of lipids, as well as the uptake of cholesterol and fat-soluble vitamins. In addition, BA regulates homeostasis of the intestinal epithelium in the gastrointestinal tract.

[0167] Primary bile acids (chenodeoxycholic acid and cholic acid in humans, and mulicolic acid and cholic acid in mice) are synthesized from cholesterol in the liver by several different cytochrome P450 molecules. The final step in the synthesis pathway involves conjugation with the amino acid glycine (most common in humans) or taurine (dominant in mice). Conjugated primary bile acids (also called bile salts) are secreted from hepatocytes into the bile ducts via bile salt efflux proteins, from where they are transported to the duodenum or stored in the gallbladder. Upon reaching the terminal ileum, primary bile acids are reabsorbed by apical sodium-dependent bile acid transporters (ASBTs) expressed in the epithelium and recirculated to the liver.

[0168] Deconjugated bile acids are not recirculated by ASBT and instead proceed to the large intestine. There, they are further metabolized by the microbiome to produce secondary bile acids (including deoxycholic acid (DCA) and lithocholic acid (LCA) in humans, and murideoxycholic acid (MDCA) in mice). Clostridium and Eubacterium (both Firmicutes) are examples of intestinal bacteria capable of producing secondary bile acids.

[0169] This disclosure provides a method for reducing secondary bile acids in a subject by administering the subject the tripeptide and F. prausnitzii of this disclosure to the subject. The reduced secondary bile acids may be, for example, LCA. Methods for analyzing bile acids are standard in the art and include, for example, the collection of fecal samples and analysis by mass spectrometry.

[0170] (Further combination therapy) This disclosure also provides methods for treating metabolic diseases, cardiovascular diseases, inflammatory diseases, and neoplastic diseases by administering the tripeptides and F. prausnitzii provided herein in combination with other therapeutic agents for treating metabolic diseases, cardiovascular diseases, inflammatory diseases, and neoplastic diseases. For example, this disclosure is intended for combination with other therapeutic agents that are standard treatments for metabolic diseases, cardiovascular diseases, inflammatory diseases, and neoplastic diseases. For example, the methods disclosed above may further include administering another therapeutic agent to a subject, which includes, but is not limited to, statins, cholesterol absorption inhibitors, PCSK9 inhibitors, PPAR-α agonists, ACE inhibitors, calcium channel blockers, ARBs, renin, GLP-1 or synthetic variants thereof, insulin or synthetic variants thereof, metformin, sulfonylurea compounds, thiazolidinediones (TZDs), PCSK9 inhibitors, SGLT2 inhibitors, and SGLT1 inhibitors in addition to SGLT2 inhibitors. DPP-IV inhibitors, HMG-CoA reductase inhibitors, proprotein convertase subtilisin / kexin type 9 (PCSK9) inhibitors, ezetimibe, gemfibrozil, fenofibrate, clofibrate, bezafibrate, pemafibrate, gemcaben (CI-1027), benpodic acid (ETC-1002), ACC inhibitors, ApoC-III inhibitors, ACL inhibitors, prescription fish oil, CETP inhibitors, antifibrotic agents, bile acid adsorbents (such as cholestyramine), fibrates (lipid-lowering drugs), and combinations thereof.

[0171] Other therapeutic agents may be combined with the tripeptides and F. Prausnitzii described herein to result in additional or synergistic enhancements of activity. Combination administration of active ingredients may be carried out by administering the active ingredients separately to the patient, or in the form of a compound formulation containing multiple active ingredients in a single formulation. Additional therapeutic agents may be administered at the approved dose when used as monotherapy, or initially, additional therapeutic agents may be administered at or below a therapeutically effective concentration. This will result in therapeutic outcomes in the target subject through concomitant administration of a second-line therapeutic agent in combination with the tripeptides.

[0172] (Other Terms and Disclosures) In this specification and the appended claims, unless the context clearly indicates otherwise, the singular forms of English nouns ("a," "an," "the") include the plural forms. Furthermore, it should be noted that claims may be drafted to exclude any element (e.g., any element). Accordingly, this description provides a precedent for the use of restrictive terms such as "solely" and "only," or for the use of "negative" restrictive terms, in relation to the description of elements of claims.

[0173] Where a range of values ​​is provided herein, unless the context clearly indicates otherwise, each intermediate value between the upper and lower limits of that range (up to one-tenth of the lower limit), and any other specified values ​​or intermediate values ​​within the range described, are understood to be included in this disclosure. These smaller range upper and lower limits are also included in this disclosure independently, unless there are limits that may be included in those smaller ranges and are explicitly excluded in the range described. If a range described includes one or both of the aforementioned limits, the range excluding either or both of those included limits is also included in this disclosure.

[0174] Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art in which this disclosure pertains. Any methods and materials similar to or equivalent to those described herein may be used in the practice or testing of this disclosure.

[0175] All publications referenced herein are incorporated herein by reference to disclose and illustrate methods and / or materials relating to the purposes cited herein.

[0176] As will be apparent to those skilled in the art upon reading this disclosure, the individual embodiments described and illustrated herein have separate components and features and can be readily separated from or combined with features of several other embodiments without departing from the scope or spirit of this disclosure. The methods described may be carried out in the order described or in any other logically possible order. This disclosure is intended to support all such combinations.

[0177] In this specification, the terms “contemplated,” “may,” “may comprise,” “may be,” “can,” “can comprise,” and “can be” all indicate that they are conceived by the inventor and are functional and available as part of the subject matter provided.

[0178] [Examples] The following examples demonstrate that DT-109 improves hepatic steatosis and suppresses the progression of hepatic inflammation and fibrosis in non-human primates with established NASH. These effects are mediated not only by promoting hepatic fatty acid degradation and GSH formation, but also by inhibiting the microbial production of LCA, a known hepatotoxic BA independently associated with NAFLD risk (Staudinger et al., 2001).

[0179] The following examples illustrate specific embodiments, but it will be apparent to those skilled in the art that various modifications and alterations are possible. Therefore, the present invention should be limited only to those defined in the claims.

[0180] [Availability of data and code] All raw omics data generated in the studies described in the examples have been deposited in public databases. Details are provided below. All RNA sequencing data and 16S rRNA sequencing data are registered in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database. The accession number for RNA sequencing data from liver samples obtained from monkeys at the start of the NASH diet and 10 months after the start of the diet is PRJNA859546. The accession number for RNA sequencing data from the livers of cynomolgus monkeys treated with DT-109 or vehicle for 5 months is PRJNA860095. The accession number for data obtained from 16S rRNA sequencing of fecal samples from cynomolgus monkeys is PRJNA865025. The raw metabolomics MS data generated in this study were registered in the MetaboLights database with accession code MTBLS5005. All MS-based proteome data are registered in the integrated proteome resource iProX as dataset identifier IPX0004494000 and are available at: www.iprox.cn / page / SSV024.html;url=1672567339738460H, password:5UxH. Experimental data supporting the findings of this study are available from the corresponding authors upon reasonable request. Source data are provided within this paper.

[0181] [Details of the experimental model and subjects] (Mouse research) All procedures performed on mice were approved by the Animal Experiment Management and Use Committee of the University of Michigan (Approval Number: PRO00010092) and carried out in accordance with institutional guidelines. Seven-week-old male C57BL / 6J mice (Stock Number: 000664) were obtained from Jackson Laboratory. Eight-week-old male C57BL / 6J mice were given either a standard diet (SD, LabDiet, 5L0D, 13% fat) or a NASH diet (Research Diets, D17010103, 40% fat) as ad libitum. The NASH diet has already been shown to strongly induce NASH in mice (Rom et al., 2019; Rom et al., 2020). Mice were orally administered (force-fed) either DT-109 (Diapin Therapeutics, Ann Arbor, MI, USA) (15, 45, 150, or 450 mg / kg (body weight) / day) or a solvent (H2O, control) for 12 weeks.

[0182] (Research on non-human primates) All experimental protocols using non-human primates were approved by the Laboratory Animal Management Committee of Xi'an Jiaotong University (Approval No.: 20191278) and the Animal Experiment Management and Use Committee of Spring Biological Technology Development Co., Ltd (Approval No.: 201901). This study was conducted in accordance with the Guide for the Care and Use of Laboratory Animals (National Institutes of Health, 8th edition, 2011). Monkeys predisposed to developing NASH were screened from over 1,000 cynomolgus macaques at Spring Biotechnology's facilities. Sixty-nine male monkeys (age ≥ 9 years, BMI > 30) were selected and housed in individual cages with free access to water and food. The monkeys were anesthetized with ketamine hydrochloride (10 mg / kg (body weight)) before physical examination (weight, waist circumference, and abdominal circumference) and liver biopsy. Waist circumference was measured at the midpoint between the lowest rib and the iliac crest, and abdominal circumference was measured at the level of the navel. Liver biopsies were performed using a Bard Magnum biopsy gun (Bard Biopsy Systems, Tempe, AZ, USA) loaded with a 17-gauge biopsy needle (Argon, Athens, TX, USA), under the guidance of an ultrasound device (Landwind, P09, Shenzhen, China). The collected liver tissue was then stored in formalin or at -80°C. Twenty monkeys with NAS scores of 1-3 were defined as having a predisposition to develop NASH and were given a NASH diet (Table S1). Ten months after the start of the NASH diet, a physical examination was performed again, blood samples were taken for biochemical analysis, and liver biopsies were obtained for histopathological analysis and transcriptomics. The aforementioned 20 monkeys were randomly assigned to either a group that received oral administration of DT-109 (150 mg / kg (body weight) / day) while continuing the NASH diet for another 5 months (force-feeding), or a group that received oral administration of the same amount of H2O (vehicle control) (force-feeding).Prior to the initiation of the intervention study, all NASH-related parameters were confirmed to be equivalent between the DT-109 group and the control group through physical, biochemical, and histological (biopsy-based) assessments. At the end of the study, after blood samples were collected, the monkeys were anesthetized with ketamine hydrochloride (15 mg / kg body weight) and euthanized by bloodletting. The entire liver was rapidly removed and perfused with chilled phosphate-buffered saline (PBS). The collected liver tissue was stored in liquid nitrogen or formalin.

[0183] (Human research) A total of 378 subjects (including healthy controls and NAFLD patients aged 17-80) were recruited from Zhongshan Hospital, Fudan University (Zhao et al., 2020). Information on demographic and clinical characteristics was collected and detailed in Table S2. Diagnosis of fatty liver was based on ultrasound. Exclusion criteria included: i) heart, lung, or kidney disease; ii) history of alcohol abuse; iii) other known liver disease. This study was approved by the IRB (Institutional Review Board) of Zhongshan Hospital, Fudan University (IRB: B2020-180), and signed informed consent was obtained from all participants.

[0184] [method] (Biochemical analysis of mouse plasma and liver) The analysis was performed according to previously reported methods (Rom et al., 2019; Rom et al., 2020). Briefly, biochemical assays of AST, ALT, and ALP were performed at the In Vivo Animal Core of the University of Michigan using a Liasys 330 chemical analyzer (AMS Diagnostics) according to the manufacturer's reagents and protocols. Technicians were blinded to the experimental groups. After liver lipid extraction, triglycerides were measured using the FUJIFILM Wako Triglyceride Kit (Catalog No. 632-50991) according to previously reported methods (Rom et al., 2019; Rom et al., 2020). Collagen content in mouse liver was evaluated by measuring hydroxyproline concentration using the Hydroxyproline Assay Kit (MilliporeSigma, Catalog No. MAK008) according to the manufacturer's protocol.

[0185] (Histological analysis of mouse liver) All histological procedures in the mouse studies were performed by blinded technicians at the In Vivo Animal Core, University of Michigan, following previously reported methods (Rom et al., 2019; Rom et al., 2020). Formalin-fixed tissues were cleared with xylene after stepwise alcohol treatment and then impregnated with molten paraffin using an automated tissue processing system VIP5 or VIP6 (TissueTek, Sakura-Americas). After embedding the tissues using a Histostar embedding device (ThermoFisher Scientific), 4 μm thick sections were prepared using an M355S rotary microtome (ThermoFisher Scientific) and mounted on glass slides. The slides were stained with hematoxylin and eosin (H&E, ThermoFisher Scientific). For Sirius Red staining, slides were treated with 0.2% molybdic phosphate for 3 minutes, then transferred to 0.1% Sirius Red dissolved in picric acid (Rowley Biochemical Inc.) and immersed for 90 minutes. Afterward, they were transferred to 0.01N hydrochloric acid and immersed for 3 minutes. H&E staining was used for the NAFLD activity score (NAS, Kleiner et al., 2005). Fatty degeneration was scored on a scale of 0 to 3 (0: fatty degeneration <5%; 1: 5-33%; 2: 34-66%; 3: >67%). Hepatocyte ballooning was scored on a scale of 0 to 2 (0: normal hepatocytes, 1: normal-sized hepatocytes with pale cytoplasm, 2: hepatocytes at least twice as large with pale cytoplasm). Lobular inflammation was scored on a scale of 0 to 3 based on the number of inflammatory foci observed at 20x magnification (0: none, 1: <2 foci, 2: 2-4 foci; 3: ≥4 foci). The NAS was calculated as the sum of the scores for fatty degeneration, hepatocyte ballooning, and lobular inflammation. Liver fibrosis was scored on a scale of 0 to 4 by Sirius Red staining (0: no fibrosis; 1: perisinusoidal or portal tract fibrosis; 2: perisinusoidal and portal tract fibrosis; 3: bridging fibrosis; 4: cirrhosis). NAS scores and fibrosis scores (Kleiner et al., 2005) were individually evaluated by at least two independent pathologists blinded to the experimental group, and mean scores are shown.

[0186] (Targeted metabolomics of bile acids in mouse plasma) Plasma BAs were evaluated by targeted metabolomics using LC-MS / MS at the University of Michigan's Pharmacokinetics and Mass Spectrometry Core Facility. Briefly, 30 μL of plasma was dispensed into a 96-well plate. Next, 120 μL of methanol and 10 μL of internal standard solution were added and vortexed for 10 minutes. The plate was centrifuged at 3,500 RPM at 4°C for 10 minutes to precipitate proteins. 100 μL of the supernatant was transferred to another 96-well plate, and 2 μL was injected into the LC-MS / MS for analysis. A rapid and effective UPLC-MS method was established for targeted and quantitative analysis of 15 types of BAs (including 6 primary BAs and 9 secondary BAs). The LC-MS system consisted of a Waters ACQUITY UPLC and a Waters TQD tandem quadrupole mass spectrometer (MA, USA) equipped with an ESI source. Fifteen types of BA and nine types of deuterium-labeled BA internal standards were separated on a CORTECS T3 column (2.1 x 30 mm, 2.7 μm). This separation was performed by gradient elution using water containing 0.01% formic acid and 0.2 mM ammonium formate (solvent A) and isopropanol:ACN(50:50(v:v)) containing 0.01% formic acid and 0.2 mM ammonium formate (solvent B) as the mobile phase. The gradient elution of the mobile phase was as follows: starting at 10% B and holding for 0.5 minutes, then increasing to 90% B over 3.5 minutes, followed by decreasing to 10% B over 0.01 minutes, and equilibrating for 1 minute before the next injection. The column temperature was maintained at 40°C and the flow rate was set to 1.0 mL / min. Detection in the analysis was performed by multiple reaction monitoring using positive electrospray ionization mode. This assay was validated based on chemical stability, selectivity, sensitivity, linearity, precision, accuracy, carryover effect, and extraction efficiency.

[0187] (Biochemical analysis of cynomolgus monkey serum) Cynomolgus monkeys were fasted overnight (14-16 hours), and blood samples were collected from the hind limb veins. Total cholesterol (TC), triglycerides, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALP) in the serum, as well as glycated hemoglobin (HbA1c) in EDTA-anticoagulated blood, were analyzed using an automated biochemical analyzer (TOSHIBA, TBA-2000FR, Tokyo, Japan).

[0188] (Biochemical and histological analysis of the liver of a cynomolgus monkey) At the endpoint, liver tissue was rapidly collected from euthanized monkeys, frozen in liquid nitrogen, and stored at -80°C. Liver triglycerides were measured using an enzymatic assay kit (Applygen Technologies Inc, Beijing, China) according to the manufacturer's instructions. Liver collagen content was evaluated by measuring hydroxyproline concentration using a Solarbio Hydroxyproline Detection Kit (Catalog No. BC0250) according to the manufacturer's protocol. Protein concentration was measured using a Pierce BCA protein assay kit (ThermoFisher Scientific, Waltham, MA, USA) according to the manufacturer's instructions. Liver triglycerides were normalized with tissue proteins. Liver glutathione levels were measured using a GSH Fluorometric Detection Assay Kit (Abcam, Cambridge, MA, USA) according to the manufacturer's instructions. Briefly, 20 mg of liver tissue was washed with chilled PBS and then resuspended in 400 μL of ice-cold Mammalian Lysis Buffer. The samples were homogenized and centrifuged at 12,000 g for 15 minutes at 4°C. The supernatant was collected, and tissue enzymes were removed using a Deproteinizing Sample Kit (Abcam). 50 μL of GSH Assay Mixture was added to each GSH standard and sample, and incubated in the dark at room temperature for 30 minutes. Fluorescence was detected using a fluorescence microplate reader (TECAN, Seestrasse, Switzerland; Infinite M200 pro) at an excitation wavelength / emission wavelength (Ex / Em) of 490 / 520 nm. Liver GSH concentrations were normalized to the tissue sample weight.

[0189] H&E staining was performed on paraffin-embedded liver tissue samples. Liver fibrosis in paraffin-embedded liver sections was evaluated using Sirius Red staining. Neutral triglycerides and lipids in frozen liver tissue embedded in OCT compounds were evaluated using Oil Red O (ORO) staining. Immunohistochemical staining for CD68 was performed on paraffin-embedded liver sections. To recover the antigen, the samples were heated in EDTA buffer (pH 9.0) in a microwave oven for 10 minutes, and then placed in 3% hydrogen peroxide solution for 15 minutes to eliminate endogenous peroxides. After washing with PBS (5 minutes / wash, 3 times), blocking with goat serum (Absin, Shanghai, China) for 1 hour, the sections were incubated with anti-CD68 antibody (1:100, Sigma-Aldrich, St. Louis, MO, USA) at 4°C for 12 hours, and then washed with PBS (5 minutes / wash, 3 times). Subsequently, the sections were incubated with enzyme-labeled goat anti-rabbit IgG (Absin) at room temperature for 1 hour and washed with PBS (5 minutes / wash, 3 times). Finally, the sections were visualized using a 3,3'-diaminobenzidine (DAB) kit (ZSGB-BIO, Beijing, China) and counterstained with hematoxylin. Histopathological images were acquired using a light microscope (Olympus, Tokyo, Japan) and quantified using Image-Pro plus (Media Cybernetics, Silver Springs, MD, USA). NAS and fibrosis scores (Kleiner et al., 2005) were individually evaluated by at least two independent pathologists blinded to the experimental group, and the mean scores are shown.

[0190] (RNA sequencing of cynomolgus monkey liver) Approximately 50 mg of liver tissue was pulverized under liquid nitrogen and transferred to a 2 mL microcentrifuge tube containing 1.5 mL of Trizol reagent (Invitrogen, Carlsbad, CA, USA). The mixture was centrifuged at 12,000 g for 5 minutes at 4°C. Next, the supernatant was transferred to a new microcentrifuge tube containing 0.3 mL of chloroform / isoamyl alcohol (24:1) per 1.5 mL of Trizol reagent. After centrifugation at 12,000 g for 10 minutes at 4°C, the aqueous phase was transferred to a new microcentrifuge tube and the same volume of isopropyl alcohol was added. After centrifugation at 12,000 g for 20 minutes at 4°C, the supernatant was removed and washed with 75% ethanol (1 mL). The RNA pellet was air-dried and then dissolved in 100 μL of DEPC-treated water. Subsequently, RNA quality was evaluated and quantified using an Agilent 2100 bioanalyzer. rRNA was removed using RNase H. Purified mRNA was fragmented, and single-stranded cDNA was generated using the First Strand Reaction System (PCR). Double-stranded cDNA synthesis was then performed. After purifying the reaction products, end repair was carried out using A-Tailing Mix and RNA Index Adapters. The products were then amplified to prepare the final library. The final library was sequenced on the BGISEQ500 platform (BGI, Shenzhen, China).

[0191] (RNA sequencing and microarray analysis of liver samples from cynomolgus monkeys and humans) The quality of raw FASTQ files was checked using FastQC v0.11.8 (https: / / www.bioinformatics.babraham.ac.uk / projects / fastqc / ). Low-quality reads were trimmed using Trimmomatic (v.0.35) with the following parameters: SLIDINGWINDOW: 4:20 MINLEN: 25 (Bolger et al., 2014). Subsequently, the obtained high-quality reads were mapped to the Macaca fascicularis reference genome (Macaca_fascicularis_6.0) using HISAT2 (v.2.1.0.13, Kim et al., 2019). Gene counts were measured using HTSeq-counts (v. 0.6.0) based on the Macaca_fascicularis_6.0 genome annotation (Anders et al., 2015). To facilitate subsequent comparative analysis with human data, homologous gene symbols of Macaca fascicularis were mapped to the human genome using the getLDS function of the R package biomaRt (v. 2.46.3, Smedley et al., 2009). Transcriptome profiles were compared between cynomolgus monkeys and humans using two publicly available gene expression datasets from human liver samples derived from NASH patients. The first study used the liver RNAseq dataset GSE130970 (Hoang et al., 2019). NASH patients (n=42) were identified using a NAFLD activity score (NAS) ≥ 4, and those with NAS ≤ 1 (no fatty degeneration ≤ 1, no hepatocyte ballooning, lobular inflammation, and no fibrosis) were designated as the normal control group (n=6). The second study (dataset GSE126848, Suppli et al., 2019) included 16 NASH patients and 14 control subjects in the analysis. The remaining samples in the above dataset were not included in the analysis. Raw data (gene counts) downloaded from the GEO database were used for subsequent analyses.The correlation between NASH-related gene expression and liver fat content was evaluated using microarray data (GSE26106, Brown et al., 2013) obtained from 206 liver transplant donors, which we previously published. The sample preparation and microarray data processing procedures were as previously reported (Brown et al., 2013; Rom et al., 2020; Wang et al., 2015). Liver fat content was quantified using hexane / isopropanol (3:2) (as previously reported: Li et al., 2011; Wang et al., 2015). Total fat content, normalized by total protein concentration and converted to a log10 scale, was used for subsequent analyses.

[0192] (Proteomics of the liver of cynomolgus monkeys) Protein extracts from cynomolgus monkey livers were obtained by homogenization in lysis buffer (4% SDS, 0.1 M DTT, 0.1 M Tris-HCl, pH 7.6) at 4°C for 15 minutes. Subsequently, incubation was performed at 95°C for 5 minutes, followed by sonication for 3 minutes (10 seconds on, 10 seconds off, 50 watts). After centrifugation at 16,000 g at room temperature for 10 minutes, the protein content in the supernatant was measured by tryptophan-based fluorescence quantification (as previously reported: Thakur et al., 2011). Filter-assisted sample preparation (FASP) was used for protein digestion (Wisniewski et al., 2009). The proteins were loaded into 10 kDa centrifugal filter tubes (Millipore, Burlington, MA, USA) and washed twice with 200 μL of UA buffer (8 M urea in 0.1 M Tris-HCl, pH 8.5). The samples were alkylated in 100 μL of UA buffer with 50 mM iodoacetamide in the dark for 30 minutes, washed three times again with 200 μL of UA buffer, and finally washed three times with 200 μL of 50 mM triethylammonium bicarbonate (TEAB). All of the above steps were centrifuged at 25°C and 12,000 g. Next, the protein samples in the 10k centrifuge filter tubes were transferred to new clear recovery tubes and then digested overnight at 37°C with trypsin (enzyme:protein mass ratio of 1:25). The resulting peptides were eluted by centrifugation, and the peptide concentration was measured using a BCA protein quantification kit. For each sample, 50 μg of peptide was prepared by vacuum centrifugation drying for the TMT11 labeling experiment. To eliminate batch effects from multiple TMT experiments, a mixed sample was used as an "internal reference" for TMT11 labeling. This sample consisted of equal amounts of protein mixed from liver samples of all cynomolgus monkeys. The peptides for the mixed samples were also prepared using FASP and dispensed in 50 μg portions into each EP tube to serve as the internal reference for each TMT labeling experiment set. The mixed peptides were labeled with channel 131C as the internal reference, and the other experimental samples were randomly labeled with the remaining 10 channels.For labeling, the TMT reagent set was equilibrated to room temperature and dissolved in anhydrous acetonitrile (41 μL). Approximately 20 μL of this reagent was added to 50 μg of peptide to achieve a final acetonitrile concentration of approximately 30% (v / v). After incubation at room temperature for 1.5 hours, the reaction was quenched for 15 minutes using hydroxylamine to achieve a final concentration of 0.3% (v / v). The TMT-labeled samples were pooled in a 1:1 ratio among all samples. The combined samples were nearly dried by vacuum centrifugation and subjected to desalting by C18 solid-phase extraction (3M Empore).

[0193] Next, the pooled TMT-labeled peptide samples were fractionated using high-pH reversed-phase liquid chromatography (RPLC). The liver peptide mixture (550 μg) was fractionated according to the manufacturer's instructions (Shimadzu Scientific Instruments) (using a Waters XBridge BEH300 C18 column (250 × 4.6 mm, OD 5 μm) on a Shimadzu Prominence HPLC System, with a flow rate of 0.7 mL / min). Mobile phases A and B were prepared as previously reported (Gilar et al., 2005). The 74-minute gradient was set as follows: B 5%~8% at 5 minutes, B 8%~18% at 35 minutes, B 18%~32% at 22 minutes, B 32%~95% at 2 minutes, B 95% at 4 minutes, B 95%~5% at 4 minutes, and B 5% at 2 minutes. 36 fractions were collected at 2-minute intervals from 1 minute to 72 minutes. Based on the HPLC chromatogram, 20 fractions were joined using a ligation scheme (Song et al., 2010). Each fraction was then nearly dried by vacuum centrifugation and desalted using a C18 StageTip. After nearly drying again by vacuum centrifugation, the fractions were reconstituted in buffer A (0.1% (v / v) formic acid aqueous solution) for LC-MS / MS treatment.

[0194] For data acquisition by mass spectrometry, LC-MS / MS analysis was performed using a Nanoflow Easy-nLC 1000 system liquid chromatography system (ThermoFisher Scientific) connected to a Q Exactive HF-X mass spectrometer (ThermoFisher Scientific). Prior to MS, the peptide mixture was separated at a flow rate of 450 nL / min using a homemade reverse-phase column (100 μm × 200 mm) packed with ReproSil-Pur C18-AQ, 1.9 μm resin (Dr. Maisch GmbH, Germany). Buffer A consisted of an aqueous solution containing 0.1% (v / v) formic acid, and buffer B consisted of an acetonitrile solution containing 0.1% (v / v) formic acid. A 120-minute gradient was set as follows: B 2%~5% over 2 minutes; B 5%~25% over 102 minutes; B 25%~35% over 9 minutes; B 35%~90% over 2 minutes; B 90% over 5 minutes. The MS1 full scan was performed using an Orbitrap mass spectrometer with a resolution of 60,000 at m / z 200, an automatic gain control (AGC) target of 3e6, and a maximum injection time of 30 milliseconds, within a mass range of 350–1500 m / z. Subsequently, the top 15 ions in terms of intensity were separated and fragmented by high-energy collisional dissociation (HCD) to generate the MS2 scan (resolution 45,000; mass range 200–2000 m / z; isolation window 0.7 m / z; AGC 1e5; normalized collision energy (NCE) 32; maximum injection time 45 milliseconds).

[0195] For proteome database searches, raw MS files were processed against the Macaca fascicularis database (UP000233100) using MaxQuant software (version 1.6.14.0) and analyzed at the peptide and protein levels with an FDR < 1% using the integrated Andromeda search engine. The search included variable modifications of oxidized methionine (M), acetylation (protein N-terminus), and fixed modifications of carbamide methylation (C). S2 reporter ion quantification based on TMT11-plex was selected, with a reporter mass tolerance set to 0.003 Da. The precursor intensity fractionation (PIF) filter value was set to 0.75 to reduce interference due to precursor co-fragmentation. Furthermore, an "internal reference" labeled with channel 131C was assigned as the reference channel, and a "weighted ratio to reference channel" was performed to eliminate batch effects in multiple TMT experiments. Isobaric matching between runs was enabled, and the MS1 identification results were transferred between runs with a matching time window of 0.7 minutes, as previously reported (Yu et al., 2020). Enzyme specificity was set to trypsin, and the maximum number of allowed deletion sites was set to 2.

[0196] (Non-targeted metabolomics in cynomolgus monkey serum and liver) For serum sample preparation, fasted blood samples were collected in K2EDTA vacuum tubes and stored at 4°C. Within 2 hours, the blood samples were centrifuged at 3,000 g for 10 minutes at 4°C. The supernatant (serum) was separated, transferred to a new vial, and immediately stored at -80°C until analysis. The frozen serum samples were thawed at 4°C and vortexed for 3 minutes. The dispensed solution (100 μL) was mixed with pre-cooled methanol (300 μL). After precipitating proteins by vortexing (4 minutes) and centrifugation (18,800 g, 4°C, 10 minutes), the supernatant was collected and dried by evaporation under vacuum using a Speed ​​Vac Concentrator (Thermo Electron Corporation, Model SPD121P, ThermoFisher Scientific). The dried residue was redissolved in 100 μL of acetonitrile / water (3:1, v / v) and centrifuged at 18,800 g for 10 minutes at 4°C. The supernatant was collected and transferred to a new vial for LC-MS analysis. For liver sample preparation, a frozen sample (wet weight: 50 mg) was placed in a 2 mL homogenization tube containing ceramic beads (3.0 mm diameter). Pre-cooled extraction solvent (containing 80% (v / v) HPLC-grade methanol, 500 μL) was added, and homogenization was performed three times for 30 seconds at a shock velocity of 4.0 m / sec using a high-throughput MasterPrep™-24 tissue homogenizer. After homogenization, the sample was centrifuged at 18,800 g for 4 minutes at 4°C. The supernatant was collected and dried by evaporation under vacuum using a Speed ​​Vac Concentrator (Thermo Electron Corporation, Model SPD121P; ThermoFisher Scientific). The dried residue was redissolved in 100 μl of acetonitrile / water (3:1, v / v) and centrifuged again at 18,800 g for 10 minutes at 4°C. The supernatant was collected and transferred to a new vial for LC-MS analysis.

[0197] Non-targeted metabolomics screening was performed using a Q-TOF tandem mass spectrometer (Triple TOF 5600TM, SCIEX, Foster City, CA, USA) equipped with ESI and APCI ion sources and operating in cation / anion mode, and the Analyst TF 1.7.1 data processing system. Chromatography was performed using a Shimadzu Prominence system (Shimadzu Scientific Instruments, INC., Columbia, MD, USA) equipped with a dual pump, online degasser, autosampler, and column oven. Separation was performed at 40°C using a Waters ACQUITY HSS T3 column (2.1 × 100 mm, 1.8 μm). A gradient elution at a flow rate of 250 μL / min was programmed using a mobile phase consisting of an aqueous solution (A) containing 0.1% (v / v) formic acid and an acetonitrile solution (B) as follows: B 2-60% (v / v) in 0-5 minutes; B 60% (v / v) in 5-10 minutes; B 60-100% (v / v) in 10-17 minutes; and B 100% in 17-20 minutes. The system was returned to its initial conditions in 0.1 minutes and re-equilibriumized for 5 minutes. The autosampler temperature was set to 4°C, and the injection volume was 2 μL in cation mode and 5 μL in anion mode. LC-MS data was acquired in both cation and anion modes. Detailed parameters were as follows: spray voltage 5.5 kV or -4.5 kV, declustering voltage 80 V or -80 V, vaporizer temperature 450°C, turbo gas 50 psi, nebulizer gas 55 psi, curtain gas 35 psi. Full scan analysis was performed in TOF mode with a scan range of 50-1000 m / z, and MS / MS analysis was performed in information-dependent acquisition (IDA) mode using collision energies (CE) of 45 / 30 / 1eV5 or -45 / -30 / -15eV. Acquired data was automatically calibrated according to the manufacturer's calibrated guidelines. Analyst TF 1.7.1 (Sciex) was used for data acquisition and processing. External mass calibration was performed every 5 samples.Serum and tissue samples were randomly arrayed, and QC and mixed standard samples were also repeatedly analyzed every 10 samples within the analytical runs to evaluate the reproducibility of chromatography.

[0198] The obtained raw spectrograms were processed using Progenesis QI (Waters, Milford, MA, USA) (Larkin et al., 2022). Metabolites were identified in two steps: 1) exact mass match, and 2) MS / MS confirmation. The mass tolerance for database search was set at 5 ppm for MS and 15 ppm for MS / MS. Instrument stability was monitored using QC samples. To reduce the variation due to sample injection and concentration factors, the intensity of the extraction variables was normalized by the total area. After peak deconvolution, alignment, integration, and normalization, a table containing the retention time, exact mass pair, and normalized intensity of each variable was obtained for multivariate statistical analysis. Subsequently, for multivariate statistical analysis, the normalized Pareto-scaled data was imported into SIMCA-P v14.1 software (Umetrics AB, Umea, Sweden). Cross-validation was used to verify the validity of the model against overfitting. Potential biomarker candidates were selected based on variable importance in the projection (VIP>1), S-plot, and raw data plots of the orthogonal partial least squares discriminant analysis (OPLS-DA) model, and independent t-test (p<0.05). The number of components for principal component analysis (PCA) and OPLS-DA was 4 respectively. Finally, fragment ions, isotope ions, and adduct ions were manually removed based on the corresponding extracted ion chromatograms (XIC) to screen for potential biomarkers. The structure of the potential biomarkers was identified based on the contribution to the variable classification determined by the VIP plot and the confidence interval (≧0) of the jackknife method in the aforementioned OPLS-DA model. Subsequently, the obtained potential biomarkers were identified as reported (An et al., 2010; Chen et al., 2009; Xu et al., 2013). Briefly stated, the [M+H] + or [M-H] -Ions were obtained, and candidate molecular structures of metabolites were acquired based on the precise mass and isotopic abundance of the molecular ions. LC-MS / MS spectral analysis was performed to obtain structural information, and the resulting MS / MS spectra were used as queries for publicly available mass spectrum libraries. Candidate structures were estimated through database searches using precise molecular weights (including HMDB (http: / / hmdb.ca), Massbank (http: / / massbank.imm.ac.cn / MassBank), and METLIN (http: / / metlin.scripps.edu)). Furthermore, retention time and fragmentation characteristic ions were obtained by LC-MS / MS analysis of commercially available standards, and the final metabolite structures were confirmed through comparative analysis using Progenesis QI software (Waters, Milford, MA, USA). For characterization of potential biomarkers, Metabolomics Pathway Analysis (MetPA), a web-based visual tool for analyzing metabolite data within the biological context of metabolic pathways and identifying the most relevant pathways in metabolic research, was used. The Functional Analysis module of MetaboAnalyst 5.0 (https: / / www.metaboanalyst.ca / ) was further utilized. This module accepts high-resolution LC-MS (HRMS) spectral peak data and performs metabolic pathway enrichment analysis and visual exploration based on the well-established Mummichog algorithm. The following parameters were used in the pathway enrichment process: median normalization, logarithmic transformation (base 10), Pareto scaling, and Homo sapiens (human) [KEGG]. The altered metabolic pathways were visualized using bubble charts with the online tackle hiplot (https: / / hiplot.com.cn / basic) and MetPA. In addition, to further investigate the changes in metabolites identified by DT-109 administration, intuitive characterization was performed using clustering heatmaps with the heatmap drawing toolkit HemI.The raw metabolomics data generated in this study were registered in the MetaboLights database with accession code MTBLS5005.

[0199] (Targeted metabolomics of circulating bile acids and hepatic bile acids in humans and cynomolgus monkeys) Targeted metabolomics of BA was performed as previously reported (Han et al., 2015). Briefly, 20 μL of serum was mixed with 80 μL of an internal standard (containing deuterium-labeled bile acid in methanol). To determine the concentration of the analyte, the concentration of the standard was increased stepwise (0-5 μM) and a standard curve was created. A standard curve was considered acceptable if the coefficient of determination (R²) reached 0.99. The samples were vortexed at 4-8°C for 1 minute, centrifuged at 20,000 g at 4°C for 10 minutes, and the supernatant was collected. The supernatant (2 μL) was injected at a flow rate of 0.3 mL / min into a BEH C18 (2.1 x 150 mm, 1.7 μm) UPLC column (Waters Inc. Milford, MA) and connected to an API 6500Q-TRAP mass spectrometer (SCIEX, Framingham, MA) via an LC-20AD Shimadazu pump system and a SIL-20AXR autosampler. A discontinuous gradient was generated, and the analytes were separated by mixing solvent A (0.1% formic acid in water) with solvent B (0.1% formic acid in acetonitrile) in different ratios: starting with B 55%~70% over 2 minutes, B 75%~100% over 2 minutes, holding B 100% for 2 minutes, and then B 100%~40% over 0.1 minutes. The column was equilibrated to B 25% over 2 minutes during injection. The flow rate was 0.3 mL / min, and the column was maintained at 45°C. The analytes were monitored using negative ion mode electrospray ionization by multiple reaction monitoring (MRM) of precursor ions and characteristic product ion transitions in BA. Detailed ion pairs are shown in Table S4.

[0200] [Table 1]

[0201] All MS parameters were optimized using the direct injection method. For specific quantitative and confirmation transitions, the declustering potential and collision energy were optimized to maximize sensitivity.

[0202] (Targeted metabolomics of bile acids in fecal samples from cynomolgus macaques) The BAP Ultra kit (Metabo-Profile, Shanghai, China) was used for the analysis of the BA profile. A 10 mg fecal sample was mixed with 200 μL of acetonitrile / methanol solution (v / v=8:2) containing 25 mg of pre-cooled pulverized beads and 10 μL of internal standard. The sample was homogenized and separated by centrifugation. 10 μL of the supernatant was mixed with 90 μL of acetonitrile / methanol solution (v / v=8:2) and ultrapure water. After shaking and centrifugation, the sample was detected at Metabo-Profile co., ltd using an ultra-high-performance liquid chromatography-coupled tandem mass spectrometry (UPLC-MS / MS) system (ACQUITY UPLC-Xevo TQ-S, Waters Corp., Milford, MA, USA). The raw data generated by UPLC-MS / MS were processed using QuanMET software (v2.0, Metabo-Profile), and peak integration, measurement, and quantification were performed for each metabolite, as previously reported (Xie et al., 2018).

[0203] (16S rRNA sequencing of fecal samples from cynomolgus macaques) Whole-genomic DNA was extracted from fecal samples (5 animals per group) randomly selected from half of the animals in the DT-109-administered group and the vehicle-administered group, using the PowerMax Soil DNA Isolation Kit (MO BIO Laboratories, Carlsbad, CA, USA). The bacterial 16S rRNA gene V3-V4 region was amplified by PCR using Q5 High-Fidelity DNA Polymerase (NEB) and quantified using the Quant-iT PicoGreen dsDNA Assay Kit (ThermoFisher Scientific). The TruSeq Nano DNA LT Library Prep Kit (Illumina) was used for library construction. The PCR amplification products were purified using Vazyme VAHTS™ DNA Clean Beads (Vazyme, Nanjing, China), quality-assessed using the Agilent High Sensitivity DNA Kit (Agilent, Santa Clara, CA, USA), and quantified using the Quant-iT PicoGreen dsDNA Assay Kit. Subsequently, the amplified products were sequenced at Biotree Biomedical Technology CO., Ltd (Shanghai, China) using the Illumina Novaseq 6000 platform with the NovaSeq 6000 SP Reagent Kit (Illumina).

[0204] (Conversion of d4-CDCA to d4-LCA by fecal microbiota) As previously reported (Yoo et al. 2016), the contents of the small intestine and cecum (approximately 400 mg) were collected from mice. Fresh fecal pellets were suspended in potassium phosphate buffer (0.01 M, pH 7.4) in a 1:4 ratio (feces to phosphate buffer) and homogenized. The fecal homogenate was centrifuged at 500 g for 10 minutes. The reaction mixture (containing 20 μL of d4-CDCA solution (100 μM) and 40 μL of fecal suspension) was incubated at 37°C. DT-109 (20 μL) was added in stages, increasing in concentration (0 to 500 μM). To avoid dilution effects, the entire volume was prepared using a vehicle. The reaction was stopped by freezing at -80°C. The experiment was interrupted at different time points (0, 1, 2, 4, 8, and 16 hours). BA extraction and detection were performed as follows. In short, 20 μL of the reaction mixture was mixed with 80 μL of an internal standard (containing d4-TCDCA in methanol). The sample was vortexed and centrifuged at 20,000 g for 10 minutes at 4°C, and the supernatant was collected. This sample was used in targeted metabolomics (Han et al., 2015; Zhao et al., 2020). In an experiment to verify the conversion of d4-CDCA to d4-LCA by Faecalibacterium prausnitzii, a fresh stool sample (approximately 400 mg) was suspended in Gifu anaerobic medium (GAM medium) in a 1:9 ratio. After centrifuging at 500 g for 10 minutes, the fecal supernatant was collected. Next, 1.5 mL of GAM medium, or an equal amount of bacteria (Faecalibacterium prausnitzii, Roseburia rectibacter, or Escherichia coli, OD600: in the range of 0.35-0.45), was added to 1.5 mL of fecal supernatant. The reaction mixture (containing 200 μM d4-CDCA) was incubated at 37°C under anaerobic conditions. Preparative samples (30 μL) were taken at different time points (0, 1, 2, 4, 8, 12, and 24 hours) and stored at -80°C until analysis. BA extraction and detection were performed as described above.

[0205] (Isolation of fecal bacterial DNA and qPCR) Fecal bacterial DNA was isolated using the TIANamp Stool DNA Kit (DP328) according to the manufacturer's instructions. qPCR was performed on a 7500 Fast Real-Time PCR System using primers listed in the KEY RESOURCES TABLE (Ramirez-Farias et al., 2009; Wu et al., 2021).

[0206] [Quantification and statistical analysis] Statistical analysis was performed using GraphPad Prism 8.0. Normality and homovariance were tested for all data. Student's t-test was used for two-group comparisons where the conditions were met, and one-way ANOVA followed by Tukey's post-hoc test for comparisons of three or more groups. Otherwise, non-parametric tests (Mann-Whitney U test or Kruskal-Wallis test followed by Dunn's post-hoc test) were used. A p-value < 0.05 was considered statistically significant. Differentially expressed genes (DEGs) from RNA sequencing data were analyzed using the R package DESeq2 (v.1.30.1) (Love et al., 2014). Genes with an adjusted p-value less than 0.05 and an absolute doubling of 2x or more were identified as significant DEGs. Gene set enrichment analysis (GSEA) of the KEGG database was used via the clusterProfiler package (v.3.18.1) to identify significantly enriched pathways in upregulated and downregulated genes (Yu et al., 2012). Gene ranks based on logarithmic changes at the mRNA or protein level were used as input for GSEA, and p-values ​​were calculated based on 100,000 substitutions. Spearman's correlation coefficient was used to evaluate the correlation between hepatic fat and NASH-related gene expression. Bioinformatics analysis using R 3.5.1 was performed for proteomic analysis. The corrected reporter intensity (weighted ratio to internal reference) for each sample was normalized by subtracting the median total intensity in each sample. Proteins with reporter intensity were retained in more than two-thirds of the samples, and missing values ​​were imputed using K-nearest neighbors (k-NN). Subsequent analyses were performed using log2-transformed normalized data. For microbiome analysis, we used QIIME2 (version 2020.6) and the R package (3.1.1). The demux plugin was used for demultiplexed raw sequencing data, and the cutadapt plugin was used for primer excision. The DADA2 plugin was used for quality filtering, noise reduction, merging, and chimera removal.Taxonomic assignment was performed to amplicon sequence variants (ASVs) using the classify-sklearn plugin (confidence level: 0.7). Alpha and beta diversity indices were estimated using the diversity plugin. Beta diversity analysis was visualized using non-metric multidimensional scaling (NMDS). Taxons with differentially different abundances between the vehicle group and the DT-109 group were detected using default parameters with LEfSe (Linear Discriminant Analysis Effect Size). The relationship between genus-level abundance in feces, BA, and NASH-related indices was evaluated using Spearman's correlation coefficient, and the results were visualized using a heatmap.

[0207] [Example 1: DT-109 dose-dependently reduces non-alcoholic steatohepatitis in mice.] Oral administration of DT-109 (500 mg / kg / d) to mice strongly suppressed steatohepatitis and fibrosis induced by high-fat, high-fructose, and high-cholesterol diets (NASH diet) (Rom et al., 2020). To determine the optimal dosage, the dose-response of DT-109 during NASH development was evaluated. C57BL / 6J mice were fed a NASH diet for 12 weeks, and some mice were euthanized. This resulted in hepatomegaly, steatohepatitis, and early fibrosis, accompanied by a significant increase in liver-to-body weight ratio (p<0.0001, Figure 1A), elevated circulating aspartate aminotransferase (AST, p=0.0271), alanine aminotransferase (ALT, p=0.0050), and alkaline phosphatase (ALP, p=0.0027) (Figures 1B-D). These were evaluated by histopathological analysis (H&E staining and Sirius Red staining) and biochemical analysis, respectively (Figure 1E-J). After confirming NASH, the remaining mice were randomly assigned to either receive oral DT-109 (15, 45, 150, and 450 mg / kg / d) at gradually increasing doses while continuing the NASH diet for another 12 weeks, or receive oral H2O (vehicle). Mice given a standard diet (SD) and H2O served as the control group (Figure 2A). At the end of the study (week 24), all groups on the NASH diet showed a significant increase in body weight, regardless of DT-109 treatment or dose (Figure 1K). However, DT-109 treatment reduced hepatomegaly caused by the NASH diet and dose-dependently decreased liver weight (Figure 1L) and liver-to-body weight ratio (Figure 2B). The most significant effect was observed at 450 mg / kg / d. Compared to mice fed a NASH diet and administered a vehicle, treatment with 450 mg / kg / d of DT-109 resulted in a 31.1% reduction in the liver-to-body weight ratio (p=0.0001, Figure 2B). Therefore, DT-109 treatment resulted in a dose-dependent reduction in circulating transaminases (Figures 2C-E). Compared to mice fed a NASH diet and administered a vehicle, treatment with 450 mg / kg / d of DT-109 resulted in a significant reduction of circulating AST by 34.2% (p=0.0365, Figure 2C) and ALT by 50.3% (p=0.0058, Figure 2D).The reduction in liver damage was confirmed by macroscopic morphology (Figure 2F) and histological and biochemical analysis (Figures 2G-K), showing a reduction in hepatomegaly, steatohepatitis, and fibrosis. Histological analysis revealed that DT-109 treatment dose-dependently reduced the significant increase in NAFLD activity score (NAS) and fibrosis score induced by the NASH diet. Compared to mice fed a NASH diet and administered a vehicle, DT-109 at 450 mg / kg / d significantly reduced the fatty degeneration score (2.78±0.08 vs. 1.72±0.17, p=0.001), the overall NAS score (5.94±0.17 vs. 3.91±0.32, p=0.0033), and the fibrosis score (1.71±0.11 vs. 0.57±0.18, p=0.0033) (Figure 2K). Taken together, these findings indicate that DT-109 treatment dose-dependently reduces diet-induced NASH and hepatic fibrosis in mice, with the most effective dose being 450 mg / kg / d.

[0208] [Example 2: Establishment of a non-alcoholic steatohepatitis model in non-human primates that mimics human diseases] Most drugs that have reached clinical evaluation have been identified or developed using rodent models, but their clinical applicability is limited in the case of NASH (Febbraio et al., 2019). To develop a preclinical model with high clinical applicability for NASH, we devised an experimental approach using dietary interventions in cynomolgus monkeys (Figure 3A and S2A). More than 1,000 monkeys were screened for NASH predisposition at the Spring Biotechnology facility. For detailed physical examination, biochemical analysis, and histological analysis, 69 male monkeys (age ≥ 9 years, body mass index [BMI] > 30) were selected. Monkeys that did not show evidence of NAFLD-related lesions (NAS=0) or monkeys that spontaneously developed NASH (NAS ≥ 4) were excluded by liver biopsy and histological evaluation of NAS. Twenty monkeys with NAS between 1 and 3 were defined as having a predisposition to NASH and were used in this study. Subsequently, the monkeys were fed newly developed high-fat, high-fructose, and high-cholesterol diets (NASH diet for non-human primates, Table S1).

[0209] Table 2

[0210] Ten months after starting the NASH diet, obesity indicators (body weight [p<0.0001, Figure 3B], waist circumference [p<0.0001, Figure 3C], and waist circumference [p=0.0001, Figure 3D]), liver damage (AST [p=0.0119, Figure 3E], ALP [p=0.0472, Figure 4B]), ALT [p=0.0562, Figure 4C]), hyperglycemia (fasting glucose [p=0.0362, Figure 4D], and hemoglobin A1c [p<0.0001, Figure 4E]), and hyperlipidemia (total cholesterol, LDL cholesterol, HDL cholesterol, and triglycerides [p<0.0001, Figure 4F~I]) were significantly increased. Liver biopsies were obtained to confirm the progression of NASH. Histological analysis (Figures 3F-H) revealed significant increases in the following scores: hepatic steatosis score (0.85±0.08 vs. 1.62±0.23, p=0.0057), lobular inflammation score (0.10±0.07 vs. 1.15±0.15, p<0.0001), hepatocyte ballooning score (1.00±0.10 vs. 1.63±0.11, p=0.0007), overall NAS score (1.95±0.15 vs. 4.39±0.39, p<0.0001), and fibrosis score (0.37±0.11 vs. 1.50±0.19, p=0.0002). Furthermore, RNA sequencing was performed on liver samples collected from monkeys before and after being fed a NASH diet for 10 months to evaluate the similarity between the non-human primate model and human NASH. The top 100 differentially expressed genes (DEGs) in the livers of monkeys fed a NASH diet for 10 months were compared between two independent cohorts of liver samples from NASH-affected and non-affected individuals (Hoang et al., 2019; Suppli et al., 2019). The results showed significant transcriptional similarities between our model and human NASH (Figures 5A and 5B). Pathway enrichment analysis revealed whether underlying pathways in NASH were similarly and significantly upregulated in both monkeys and individuals with NASH (e.g., cytokine-cytokine receptor interactions [monkeys: p=3.76x10]). -3 Human: p = 1.05 x 10 -5 ], Chemokine signaling pathway [Monkey: p=9.99x10 -3 Human: p = 1.10 x 10-5 ], and extracellular matrix (ECM)-receptor interactions [monkeys: p=2.55x10 -4 Human: p = 2.07 x 10 -2 ]), or downregulation (e.g., glycine, serine, and threonine metabolism [monkey: p=6.92x10 -5 Human: p=3.47x10 -3 ], and tryptophan metabolism [monkey: p=3.67x10 -3 Human: p = 3.04 x 10 -4 It was shown that...) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ). Using another cohort of 206 samples from liver transplant donors (Brown et al., 2013; Wang et al., 2015), the expression of key genes involved in NASH and correlated with hepatic steatosis in monkey models and human NASH was compared (Figure 3J). Genes known to play a protective role in NASH by inducing fatty acid degradation (e.g., PPARA) were significantly downregulated in both monkeys and individuals with NASH and were inversely correlated with hepatic steatosis. In contrast, genes known to promote NASH through pro-inflammatory and pro-fibrotic signaling (e.g., NLRP3 and TGFB1) were significantly upregulated in both monkeys and individuals with NASH and were clearly correlated with hepatic steatosis. ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]) ... ]

[0211] [Example 3: In non-human primates with established NASH, DT-109 improves hepatic steatosis and prevents the progression of inflammation and fibrosis.] After 10 months of dietary administration and confirmation of established NASH, the monkeys were randomly assigned to receive either DT-109 or H2O (vehicle) while continuing the NASH diet for another 5 months (Figures 3A and 4A). Before the start of the intervention study, all NASH-related parameters were confirmed to be equivalent between the DT-109 group and the vehicle group through physical, biochemical, and histological (biopsy-based) assessments. These included age (Figure 6A, p=0.9366), body weight (Figure 6B, p=0.4519), waist circumference (Figure 6C, p=0.6632), waist circumference (Figure 6D, p=0.6435), fasting glucose (Figure 6E, >0.9999), hemoglobin A1c (Figure 6F, p=0.5020), total cholesterol (Figure 6G, p=0.5154), and triglycerides. The following histological scores were included: celide (Figure 6H, p=0.1836), AST (Figure 6I, p=0.7524), ALP (Figure 6J, p=0.7765), and hepatic steatosis (p=0.4640), lobular inflammation (p=0.5244), hepatocyte ballooning (p=0.4737), NAS (p>0.9999), and hepatic fibrosis (p=0.6024). Next, the monkeys were orally administered DT-109 (150 mg / kg / d) or H2O while continuing the NASH diet. The dose of DT-109 was determined based on the optimal dose in mouse studies (450 mg / kg / d, Figure 2), taking into account interspecies allometric differences, body weight, and body surface area (Nair et al., 2016). At the end of the study, there were no significant differences in body weight (Figure 5A), abdominal circumference (Figure 5B), or waist circumference (Figure 6L) between monkeys treated with DT-109 and those treated with the vehicle. No significant differences were observed in blood glucose (Figure 6M) or circulating lipid profiles (Figures 6N and 6O). However, evaluation of circulating transaminase-mediated liver damage (Figures 7C-E) revealed a significant decrease in AST (p=0.0217) and ALP (p=0.0415) in monkeys treated with DT-109. Furthermore, macroscopic liver morphology at the end of the study showed marked yellow discoloration in the vehicle group, which was reduced by DT-109 treatment (Figure 7F).Histological analysis (Figures 7G-I) revealed that monkeys treated with DT-109 showed significantly lower scores for the following: hepatic steatosis (1.72±0.31 vs. 0.84±0.26, p=0.0307), hepatocyte ballooning (1.81±0.07 vs. 1.50±0.16, p=0.0325), total NAS (5.70±0.41 vs. 3.57±0.48, p=0.0132), and fibrosis (2.20±0.28 vs. 1.35±0.22, p=0.0338). In a paired analysis comparing histological scores before and after treatment, lobular inflammation (p=0.0017), NAS (p=0.0334), and hepatic fibrosis (p=0.0067) were significantly increased in the vehicle group during the 5-month intervention study. These effects were prevented by DT-109 treatment, and hepatic steatosis was significantly reduced compared to the pre-treatment analysis (p=0.0156). Taken together, these findings demonstrate that DT-109 mitigates established NASH in non-human primates by improving hepatic steatosis and preventing the progression of inflammation and fibrosis.

[0212] [Example 4: Transcriptomics and proteomics demonstrate that DT-109 induces hepatic fatty acid degradation and suppresses pro-inflammatory / fibrotic reactions.] To elucidate the underlying mechanisms by which DT-109 improves NASH in non-human primates, an unbiased multi-omics approach combining transcriptomics, proteomics, metabolomics, and metagenomics was applied (Figures 3A and 4A). First, RNA sequencing was performed on liver samples collected at the end of the study. Principal component analysis (PCA) revealed a clear separation between the liver transcriptomes of monkeys treated with DT-109 and those administered with the vehicle (Figure 8A). DT-109 significantly downregulated 575 DEGs and significantly upregulated 391 DEGs (Figure 8B). Analysis of the top 100 DEGs revealed that the major genes regulating the following—pro-inflammatory and immune responses (e.g., TREM2, CCL18, LAT2, and SLAMF7), as well as fibrogenesis and ECM remodeling (e.g., TIMP1, COL16A1, MMP14, CTHRC1, and ITGA11)—were significantly downregulated by DT-109 treatment. Conversely, PPARGC1A (Liang et al., 2006), a major regulator of energy and fatty acid metabolism, and other genes regulating fatty acid and cholesterol metabolism (e.g., CYP1A2) were significantly upregulated by DT-109 treatment (Figure 9A). Therefore, pathway enrichment analysis (Figures 8C and 8D) revealed that DT-109 treatment induces responses opposite to those observed in humans and monkeys with NASH (Figure 3H). In particular, the glycine, serine, and threonine metabolic pathways, as well as the tryptophan metabolic pathway, which were suppressed in NASH, were significantly upregulated in monkey livers treated with DT-109, along with upregulation of the fatty acid degradation pathway (Figure 8C). The cytokine-cytokine receptor interactions, chemokine signaling, and ECM-receptor interactions pathways, which were upregulated in NASH, were significantly suppressed in monkey livers treated with DT-109, along with downregulation of the focal adhesion pathway and cell adhesion molecule pathway (Figure 8D).A heatmap of NASH-related DEGs further supported the effects of DT-109 on genes regulating fatty acid and cholesterol metabolism, inflammation, and fibrosis in NASH (Figure 8E). Next, we examined whether the observed transcriptional changes reflected the functional processes underlying the protective effects of DT-109 in NASH. Unbiased proteomics of liver samples collected at the end of the study evaluated whether the changes in DEGs were consistent at the protein level. Indeed, a significant similarity was revealed when comparing the top 100 DEGs with their corresponding proteins (Figure 9B). Accordingly, pathway enrichment analyses comparing transcriptome and proteome data showed similar results. The higher-level pathways upregulated by DT-109 were fatty acid breakdown and glycine, serine, and threonine metabolism, while the higher-level pathways downregulated were chemokine signaling, focal adhesion, and ECM-receptor interactions (Figure 8F). The consequences of these altered pathways were confirmed using histological and biochemical methods (Figures 8G-L). Consistent with the upregulation of the fatty acid degradation pathway, Oil Red O (ORO) staining for neutral triglycerides and lipids (Figure 8G) was significantly lower in monkey livers treated with DT-109, as confirmed by biochemical analysis of liver triglycerides, showing a 30.1% decrease (p=0.0283) (Figure 8I). Furthermore, consistent with the downregulation of the chemokine signaling pathway, immunohistochemical analysis of CD68, a marker of activated macrophages in NASH, showed a significant decrease (76.3%, p=0.0138) (Figures 8H and 8J). In addition, consistent with the decrease in fibrosis score, liver collagen content, expressed as hydroxyproline concentration in the liver, was significantly reduced (p=0.0022, Figure 8K). Furthermore, upregulation of the glycine, serine, and threonine metabolic pathways was observed, and, consistent with our recent reports (Rom et al., 2020; Rom et al., 2022), a three-fold increase in GSH (p=0.0174) was observed in monkey livers treated with DT-109 (Figure 8L).Therefore, by combining unbiased transcriptome and proteome analysis with histological and biochemical verification, it was revealed that DT-109 induces fatty acid degradation and suppresses pro-inflammatory and fibrotic responses in non-human primates with established NASH.

[0213] [Example 5] To further elucidate the metabolic mechanisms by which DT-109 improves NASH in non-human primates, non-targeted and targeted metabolomics were performed (Figure 10A). PCA and orthogonal partial least squares discriminant analysis (OPLS-DA) revealed clear metabolomes in the serum of monkeys treated with DT-109 and monkeys administered with the vehicle (Figures 10B and 10C). Pathway analysis revealed the most significant enrichment within the bile acid (BA) biosynthesis pathway (Figure 10D). Overall circulating bile acids decreased with DT-109 treatment (Figure 10E). In non-targeted metabolomics, significant reductions were observed in various bile acids (including cholic acid (CA, p=0.0159), glycodeoxycholic acid (GDCA, p=0.0149), taurodeoxycholic acid (TDCA, p=0.0277), ursodeoxycholic acid (UDCA, p=0.0378), glycochenodeoxycholic acid (GCDCA, p=0.0474), and taurourdeoxycholic acid / chenodeoxycholic acid (TU / CDCA, p=0.0216)). The most significant reduction was observed in the secondary bile acid lithocholic acid (LCA, 75.7%, p=0.0002), which is known to induce hepatotoxicity (Staudinger et al., 2001). Along with this, similar decreases were observed in the glycine conjugate (GLCA, 86.0%, P=0.0014) and taurine conjugate (TLCA, 74.7%, p=0.0038) (Figure 10F). To verify the above results, targeted metabolomics was performed on BA, and it was confirmed that circulating LCA decreased most significantly in monkeys treated with DT-109 (68.3%, p=0.0007) (Figure 10G). Analysis of the BA group showed a significant decrease in total circulating BA (p=0.0079), and a nearly significant decrease in secondary BA (p=0.0011) was also observed (Figure 10H). Similar effects were observed in a mouse model; in mice with NASH that were given a vehicle, secondary BA increased significantly (3.1 times, p=0.0002), but decreased in a dose-dependent manner with DT-109 treatment (Figure 11A).When considering both untargeted and targeted metabolomics, it was revealed that DT-109 treatment reduced circulating BA in NASH, with the most significant reduction being in LCA, a secondary and hepatotoxic BA.

[0214] [Example 6: DT-109 alters the gut microbiota in relation to lithocholic acid.] To elucidate the underlying mechanisms by which DT-109 regulates LCA metabolism, non-targeted and targeted metabolomics were applied to liver and fecal samples, combined with unbiased metagenomics. PCA and OPLS-DA following non-targeted metabolomics clearly revealed the metabolome of monkeys treated with DT-109 and those administered with vehicle (Figures 11B and 11C). Pathway enrichment analysis revealed significant enrichment within the primary BA biosynthesis pathway (Figure 11D). However, targeted metabolomics did not show significant differences in total BA (p=0.0990), primary BA (p=0.0784), secondary BA (p=0.0952), and LCA (p=0.0952) between monkey livers treated with DT-109 or vehicle (Figures 11E and 11F). Therefore, a comprehensive analysis of BA species in fecal samples was then performed. PCA, OPLS-DA, and heatmap-based representations revealed a clear separation between monkeys treated with DT-109 and those administered with the vehicle (Figure 12A-C). LCA was most abundant in fecal samples and significantly decreased with DT-109 treatment (p=0.0175, Figure 12D). Considering the important role of gut bacteria in producing LCA via 7α-dehydration of CDCA, a precursor of LCA (Funabashi et al., 2020; Staudinger et al., 2001; Yoshimoto et al., 2013), the effects of DT-109 on the gut microbiota were then evaluated using 16S ribosomal RNA (rRNA) sequencing. Beta diversity analysis using non-metric multidimensional scaling (NMDS) revealed a clear difference in microbial composition between monkeys treated with DT-109 and those administered with the vehicle (Figure 12E). Analysis using operational taxonomic units (OTUs) and linear discriminant analysis (LDA) effect size (LEfSe) did not reveal significant differences at the phylum and class levels (Figures 13A and 13B). However, significant differences were observed mainly at the genus level (Figures 12F and 12G, Figure 13C).In particular, DT-109 treatment reduced the levels of Escherichia sigella, Prevotella 7, Lysinibacillus, Pseudonocardia, Streptomyces, and Mycobacterium genera, while it reduced levels of Phascolarctobacterium, Eubacterium ruminantium group, Faecalibacterium, Lachnospiraceae UCG 010, Ruminococcus UCG 013, Eubacterium hallii group, and Eubacterium erigens. Increased levels were observed in the genera *Erysipelotrichaceae* UCG 006 and *Pseudoxanthomonas* (Figures 12G and 13C). To identify bacteria associated with NASH severity and LCA metabolism, the abundance of the altered genera and their relationship to NASH-related indicators and hepatic LCA concentrations were evaluated (Figure 12H). *Escherichia sigella* is a genus that has already been reported to be elevated in patients with NAFLD and hepatic fibrosis (Shen et al., 2017). This genus showed the most significant positive correlation with serum AST, NAS, fibrosis score, and hepatic LCA. On the other hand, the genus *Faecalibacterium*, mainly composed of *Faecalibacterium prausnitzii*, is known for its anti-inflammatory properties (Sokol et al., 2008) and its ability to reduce hepatic steatosis in mice (Munukka et al., 2017), and showed the most significant inverse correlation with serum AST, NAS, fibrosis score, and hepatic LCA concentration. These findings suggest that treatment with DT-109 for NASH modulates the gut microbiota in relation to LCA metabolism and NASH severity.

[0215] [Example 7: DT-109 inhibits microbial production of lithocholic acid, which is independently associated with human NAFLD risk.]Next, we investigated whether DT-109 inhibits LCA production through the regulation of the gut microbiota. First, independent qPCR analysis showed that in monkey fecal samples treated with DT-109, the butyrate-producing bacterium Faecalibacterium prausnitzii (Zhang et al., 2019) was significantly increased (2.7 times, p=0.0432, Figure 14A), while Escherichia sigella was significantly decreased (92.9%, p=0.0435, Figure 14B). Next, we evaluated the effect of DT-109 on microbial LCA production using isotope-labeled CDCA, a precursor of LCA. Fecal samples were incubated with d4-CDCA at progressively increasing concentrations of DT-109 (0-500 μM, equal volumes), and the concentration of newly generated d4-LCA was measured by mass spectrometry. DT-109 treatment dose-dependently reduced LCA generation by up to 53.3% (p<0.0001) using 500 μM DT-109 (Figure 14C). To verify whether the increase in Faecalibacterium prausnitzii due to DT-109 treatment is involved in the suppression of LCA production, fecal samples were incubated with d4-CDCA after adding either Faecalibacterium prausnitzii or the same amount of Gifu anaerobic medium (control), and newly generated d4-LCA was monitored for up to 24 hours. Faecalibacterium prausnitzii significantly reduced LCA generation starting 4 hours after the start of incubation (Figure 14D). Furthermore, to verify whether this effect is specific to butyrate-producing bacteria, we next evaluated the effects of another known butyrate-producing Gram-positive bacterium, *Rosebria rectibacter* (Duncan et al., 2006), and the non-butyrate-producing bacterium *Escherichia coli* (Clark, 1989) on LCA formation. *Rosebria rectibacter* significantly reduced LCA formation after 16 hours of incubation (Figure 13D), while *Escherichia coli* showed no significant effect (Figure 13E).However, analysis of various butyrate-producing bacteria (including Rosebria (Duncan et al., 2006), Blautia (Ye et al., 2020), and Clostridium (Stoeva et al., 2021)) in fecal samples from monkeys with NASH revealed that DT-109 treatment significantly and specifically increased the abundance of Faecalibacterium prausnitzii without affecting other butyrate-producing bacteria (Figures 14A and 13F).

[0216] Finally, to establish the clinical significance of the decrease in LCA, targeted metabolomics was applied to measure circulating LCA in NAFLD patients (n=149) and healthy controls (n=229). NAFLD patients had significantly higher circulating AST and ALT levels, were older, had a higher proportion of males, and had severe dyslipidemia and hyperglycemia (Table S2). In the table, continuous variables are expressed as median values ​​(interquartile range 25-75%) and compared using t-tests or Mann-Whitney U tests depending on the normality test results. Categorical variables are expressed as numerical values ​​(percentages) and chi-squared (χ²) values. 2 The comparison was performed using a statistical test.

[0217] [Table 3]

[0218] Consistent with the positive correlation between LCA and NAFLD severity, the hepatotoxic effects of LCA (Chen et al., 2020; Grzych et al., 2020; Kwan et al., 2020; Staudinger et al., 2001), and our findings in non-human primates, circulating LCA was significantly increased in NAFLD patients (p=0.022, Figure 14E). Importantly, after adjusting for age and sex, circulating LCA showed a positive association with NAFLD risk (odds ratio, OR: 1.36; 95% CI: 1.06, 1.75, per unit increase in standard deviation; p=0.015, Table S3, Model 1). After further adjustment for triglycerides, elevated LCA was also confirmed to be an independent predictor of NAFLD (OR: 1.31; 95% CI: 1.01, 1.70, per 1 unit increase in standard deviation; p=0.046, Table S3, Model 2). This association remained significant even after further adjustment for fasting glucose and HDL cholesterol (odds ratio: 1.29; 95% CI: 1.01, 1.68, per 1 unit increase in standard deviation; p=0.049; Table 2, Table S3, Model 3).

[0219] [Table 4]

[0220] These findings indicate that DT-109 modulates the gut microbiota to promote the growth of Faecalibacterium prausnitzii, which suppresses the production of LCA, a hepatotoxic BA that is increased in NAFLD patients and independently associated with NAFLD risk.

[0221] [Summary of the Examples] Oral administration of DT-109 dose-dependently reduced steatohepatitis and hepatic fibrosis. The most effective dose in mice was 450 mg / kg / d. Based on allometric differences, body weight, and body surface area between mice and cynomolgus monkeys (Nair et al., 2016), the efficacy and safety of orally administered DT-109 at 150 mg / kg / d in non-human primates were investigated. Given that the above dose effectively reduced steatohepatitis and hepatic fibrosis in both mice with established NASH and non-human primates, and considering the dose conversion factor of 12.3 between mice and humans, and the conversion factors of 1.8–6.2 between different non-human primates and humans (Nair et al., 2016), it is hypothesized that a dose range of 24–83 mg / kg / d of DT-109 would be beneficial in the treatment of human NAFLD / NASH patients.

[0222] In addition to histopathological similarities, significant transcriptional similarities were observed between non-human primate models and human NASH. Consistent with the well-established induction of inflammatory, immune, and fibrotic signaling pathways in NASH (Loomba et al., 2021), transcriptome analysis revealed significant upregulation of pathways related to cytokine-cytokine receptor interactions, chemokine signaling, and ECM-receptor interactions in the livers of both monkeys and humans with NASH. Key genes regulating inflammatory responses (e.g., NLRP3, Mridha et al., 2017) and fibrotic responses (e.g., TGFB1, Seki et al., 2007) were upregulated and positively correlated with hepatic steatosis in both monkeys and humans with NASH. Conversely, PPARA (Montagner et al., 2016), which encodes a master regulator of fatty acid degradation and is known for its protective role in NASH, was downregulated and negatively correlated with hepatic steatosis in both monkeys and humans. In addition to these well-established pathways, the findings herein support the involvement of newly emerging pathways in NASH (such as dysregulated amino acid metabolism (Gaggini et al., 2018; Hoyles et al., 2018; Mardinoglu et al., 2014; Rom et al., 2020; Simon et al., 2020)). Consistent with recent reports indicating that glycine metabolic disorders are a causative factor and therapeutic target of NASH and cardiometabolic diseases (Liu et al., 2021; Rom et al., 2018; Rom et al., 2020; Rom et al., 2022; Takashima et al., 2016; Wittemans et al., 2019), the glycine, serine, and threonine metabolic pathways were most significantly suppressed in both monkeys and humans with NASH.Importantly, treatment with DT-109 in monkeys with NASH improved the transcriptional changes described above, downmodulating cytokine-cytokine receptor interactions, chemokine signaling, and ECM-receptor interaction pathways, while upmodulating glycine, serine, and threonine metabolism and fatty acid degradation pathways.

[0223] The pathogenesis of NASH is complex, involving intrahepatic and extrahepatic mechanisms. Therefore, potential intervention points include metabolic, antioxidant, anti-inflammatory, anti-fibrotic, and liver-intestinal axis targets (Vuppalanchi et al., 2021). In this specification, unbiased metabolomics were used to elucidate the mechanism by which DT-109 improves NASH beyond hepatic fatty acid degradation and GSH formation. This non-targeted approach was validated by targeted metabolomics, revealing a significant reduction in circulating blood alcohol (BA) in monkeys with NASH treated with DT-109. The reduction in secondary blood volume (LCA) was particularly pronounced. Circulating BA has consistently been reported to be high in NASH patients, and a positive correlation between LCA and NAFLD severity has been documented (Chen et al., 2020; Grzych et al., 2020; Kwan et al., 2020). Similarly, a significant increase in circulating LCA was observed in a comparison between 149 NAFLD patients and 229 healthy controls. After adjusting for potential confounding factors, circulating LCA was found to be positively correlated with NAFLD. LCA is produced primarily in the intestinal tract by 7α-dehydration of bacterial CDCA and is known for its hepatotoxic effects (Staudinger et al., 2001). DCA, another BA reduced by DT-109 treatment, has been previously shown to cause obesity-associated hepatocellular carcinoma via hepatic stellate cell activation. Blocking DCA production prevented hepatocellular carcinoma in obese mice (Yoshimoto et al., 2013), suggesting the therapeutic potential of inhibiting secondary BA production by the gut microbiota in liver disease. Indeed, targeted metabolomics and metagenomics confirmed that fecal LCA was significantly reduced by DT-109 treatment. DT-109 altered the composition of the gut microbiota, reducing the abundance of Escherichia sigella (Shen et al., 2017). This bacterial group has been reported to be more abundant in patients with NAFLD and hepatic fibrosis, and showed a positive correlation with the severity of NASH and hepatic LCA.On the other hand, without altering other butyrate-producing bacteria, DT-109 significantly increased the abundance of Faecalibacterium prausnitzii, known for its anti-inflammatory properties (Sokol et al., 2008). This was inversely correlated with the severity of NASH and hepatic LCA. Isotope labeling experiments showed that DT-109 enhances Faecalibacterium prausnitzii, which directly suppresses microbial LCA production. The clinical applicability of these findings is supported by previous reports (Munukka et al., 2017) showing that a decrease in the abundance of Faecalibacterium prausnitzii in human feces is associated with an increase in hepatic steatosis, and by previous reports (Munukka et al., 2014) showing that treatment with Faecalibacterium prausnitzii in mice reduces AST, ALT, and hepatic steatosis while activating fatty acid degradation. Treatment of NASH with DT-109 modulates the gut microbiota and increases Faecalibacterium prausnitzii. This suppresses the production of LCA, a hepatotoxic bacterium associated with NAFLD risk.

[0224] The data herein demonstrate the clinical therapeutic potential of DT-109. First, DT-109 treatment was found to be safe, with no toxic effects observed at all doses tested in vivo and in vitro. Second, while NAFLD is associated with an increased risk of liver-related death, the most common cause of death in NAFLD patients is atherosclerotic cardiovascular disease (Duell et al., 2022). The most advanced NASH treatment candidate to date (oveticolic acid, Younossi et al., 2019a) exacerbates atherosclerotic dyslipidemia, raising concerns about its cardiovascular impact in this patient group, which already has an increased cardiovascular risk (Siddiqui et al., 2020). Unlike other NASH treatment candidates, DT-109 has cardioprotective effects. Thirdly, the data herein demonstrate that DT-109 improves NASH through multiple mechanisms (including hepatic fatty acid degradation and induction of GSH biosynthesis, as well as microbial regulation of BA metabolism), which is consistent with the complex pathophysiology of NASH and the need to target multiple pathways. Taken together, DT-109 is supported for use as monotherapy or in combination with other drug candidates (including, but not limited to, Faecalibacterium prausnizzi).

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[0226] [Figure 1] A-M. Confirmation of NASH before random assignment to the experimental group. [Figure 2] A-K. DT-109 improves non-alcoholic steatohepatitis in mice in a dose-dependent manner. [Figure 3] A-J. Establishment of a non-alcoholic steatohepatitis model in non-human primates that mimics human diseases. [Figure 4] A-I. Establishment of a non-alcoholic steatohepatitis model in non-human primates that mimics human diseases. [Figure 5] A-B. Transcriptional similarities between cynomolgus monkeys with NASH and humans. [Figure 6] NASH-related indicators in cynomolgus monkeys before DT-109 or vehicle administration are comparable. [Figure 7] A-I. DT-109 improves feed-induced fatty degeneration and inhibits the progression of inflammation and fibrosis in the liver of non-human primates with established NASH. [Figure 8] A-L. Transcriptomics and proteomics revealed that DT-109 induces hepatic fatty acid degradation and suppresses pro-inflammatory / fibrotic responses. [Figure 9] A-B. Transcriptomics and proteomics after DT-109 treatment. [Figure 10] A-H. Non-targeted and targeted metabolomics demonstrate the suppression of bile acid metabolism by DT-109. [Figure 11] A-F. Non-targeted and targeted metabolomics demonstrate the suppression of bile acid metabolism by DT-109. [Figure 12] A-H. DT-109 alters the gut microbiome in relation to lithocholic acid. [Figure 13] A-C. Effects of DT-109 on the gut microbiome in cynomolgus monkeys with NASH. [Figure 14] A-F. DT-109 suppresses microbial production of lithocholic acid, which increases in NAFLD patients.

Claims

1. A method for treating a metabolic disease, cardiovascular disease, inflammatory disease, or neoplastic disease in a subject, comprising the step of administering a glycy-glycy-leu tripeptide and Faecalibacterium to the subject.

2. The method according to claim 1, wherein the Faecalibacterium is Faecalibacterium prausnitzii.

3. The method according to either claim 1 or 2, wherein the disease is a liver disease.

4. The method according to claim 3, wherein the liver disease is non-alcoholic fatty liver disease (NAFLD).

5. The method according to claim 3, wherein the disease is non-alcoholic steatohepatitis (NASH).

6. The method according to claim 3, wherein the treatment reduces or inhibits the progression of the hepatic steatosis score, lobular inflammation score, hepatocyte ballooning score, NAFLD activity score (NAS), and / or fibrosis score.

7. The method according to claim 1 or 2, wherein the disease is a biliary tract disease.

8. The method according to claim 7, wherein the disease is primary biliary cirrhosis.

9. The method according to claim 7, wherein the disease is biliary cholangitis.

10. The method according to any one of claims 1 to 9, wherein the treatment reduces the production of one or more secondary bile acids in the subject.

11. The method according to claim 10, wherein the production of lithocholic acid is reduced.

12. The method according to any one of claims 1 to 11, wherein the treatment reduces the amount of Escherichia Shigella present in the intestines of the subject.

13. The method according to any one of claims 1 to 12, wherein the subject is a primate.

14. The method according to claim 13, wherein the primate is a human.

15. The method according to claim 14, wherein the subject is administered a Gly-Gly-Leu tripeptide at a dose of approximately 1 to approximately 500 mg / kg / day.

16. The method according to claim 14, wherein the subject is administered a Gly-Gly-Leu tripeptide at a dose of approximately 3 to approximately 144 mg / kg / day.

17. The method according to claim 14, wherein the subject is administered a Gly-Gly-Leu tripeptide at a dose of approximately 1 to approximately 100 mg / kg / day.

18. The method according to claim 14, wherein the subject is administered a glycy-glycy-leu tripeptide at a dose of approximately 12 to approximately 36 mg / kg / day.

19. The method according to claim 14, wherein the subject is administered approximately 37.5 mg / kg / day of Gly-Gly-Leu tripeptide.

20. The method according to any one of claims 1 to 19, wherein the Gly-Gly-Leu tripeptide is administered orally.

21. The method according to any one of claims 1 to 20, wherein the Gly-Gly-Leu tripeptide is administered as a single dose.

22. A method for reducing the production of one or more secondary bile acids in a subject, comprising the step of administering a glycy-glycy-leu tripeptide and Faecalibacterium to the subject.

23. The method according to claim 22, wherein the production of lithocholic acid is reduced.

24. The method according to claim 22, wherein the subject is a primate.

25. The method according to claim 24, wherein the primate is a human.

26. The method according to claim 25, wherein the subject is administered a Gly-Gly-Leu tripeptide at a dose of approximately 1 to approximately 500 mg / kg / day.

27. The method according to claim 25, wherein the subject is administered a Gly-Gly-Leu tripeptide at a dose of approximately 3 to approximately 144 mg / kg / day.

28. The method according to claim 25, wherein the subject is administered a Gly-Gly-Leu tripeptide at a dose of approximately 1 to approximately 100 mg / kg / day.

29. The method according to claim 25, wherein the subject is administered a Gly-Gly-Leu tripeptide at a dose of approximately 12 to approximately 36 mg / kg / day.

30. The method according to claim 25, wherein the subject is administered approximately 37.5 mg / kg / day of Gly-Gly-Leu tripeptide.

31. The method according to any one of claims 22 to 30, wherein the Gly-Gly-Leu tripeptide is administered orally.

32. The method according to any one of claims 22 to 31, wherein the Gly-Gly-Leu tripeptide is administered as a single dose.

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