EP4680261A1

EP4680261A1 - Products and methods for treating metabolic, cardiovascular, inflammatory and oncological diseases

Info

Publication number: EP4680261A1
Application number: EP23927883.1A
Authority: EP
Inventors: Yuqing Eugene CHEN; Jifeng Zhang; Lemin Zheng
Original assignee: Peking University Health Science Center; University of Michigan System
Current assignee: Peking University Health Science Center; University of Michigan System
Priority date: 2023-03-17
Filing date: 2023-03-17
Publication date: 2026-01-21
Also published as: WO2024192564A1; JP2026510955A; CN121909036A; AU2023438775A1

Abstract

Provided are tripeptide products for use in combination with Faecalibacterium in methods of treating metabolic, cardiovascular, inflammatory and oncological diseases.

Description

PRODUCTS AND METHODS FOR TREATING METABOLIC, CARDIOVASCULAR, INFLAMMATORY AND ONCOLOGICAL DISEASES

Field

The disclosure provides tripeptide products for use in combination with Faecalibacterium in methods of treating metabolic, cardiovascular, inflammatory and oncological diseases.

Background

Worldwide prevalence of nonalcoholic fatty liver disease (NAFLD) and its more severe form, nonalcoholic steatohepatitis (NASH) , is increasing at an alarming rate. The overall prevalence of NAFLD was recently estimated to be 32.4%, and the prevalence of NASH in the general population was estimated to be 1.5-6.5%. NAFLD and NASH have become the major cause of chronic liver disease worldwide, and are associated with increased cardiovascular-, cancer-and liver-related mortality. In addition to its clinical impact, the substantial economic burden of NAFLD exceeds $100 billion in annual direct costs in the United States alone. Despite the high prevalence of NAFLD and considerable efforts in drug development, no pharmacological therapy currently exists to treat this disease.
While numerous compounds are currently being evaluated for NASH, many have either failed to show an improvement or raised safety concerns in clinical trials (Vuppalanchi et al., 2021) . The mouse is the most used animal in preclinical studies of potential therapeutics for NASH. However, while numerous mouse models of NASH have been described, many do not accurately mimic human disease and are not translatable to the clinic.
Recently, perturbation in amino acid metabolism has been implicated 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 from our group and others uncovered impaired glycine metabolism as a causative factor and therapeutic target in 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) .
US Patent No. 8,664,177 (issued March 4, 2014) , US Patent No. 9,062,093 (issued June 23, 2015) and International Publication No. WO2020/033919 (published February 13, 2020) disclose tripeptide compositions and uses.
There remains a need in the art for products and methods for treating NAFLD and NASH, and other metabolic, cardiovascular inflammatory and oncological diseases.
Summary
The disclosure provides tripeptide products in combination with Faecalibacterium, and methods of treating metabolic, cardiovascular, inflammatory and oncological diseases.
In experiments described herein, the dose-response of a tripeptide Gly-Gly-Leu (DT-109) was evaluated, and its efficacy and safety were tested in nonhuman primates with established NASH that histologically and transcriptionally mimic the human disease. A multiomics approach combining transcriptomics, proteomics, metabolomics, and metagenomics, was also applied revealing that DT-109 reverses hepatic steatosis and inhibits the progression of hepatic inflammation and fibrosis in nonhuman primates, not only by stimulating hepatic fatty acid degradation and GSH formation, but also through modulation of microbial bile acid (BA) metabolism.
The disclosure provides products and methods for treating a metabolic, cardiovascular, inflammatory or oncological disease in a subject comprising administering to the subject a Gly-Gly-Leu tripeptide and a Faecalibacterium.
The Faecalibacterium can be Faecalibacterium prausnitzii.
The treatment can reduce the production of one or more secondary bile acids in the subject. The production of, for example, lithocholic acid can be reduced.
The treatment can decrease the abundance of Escherichia Shigella in the gut of the subject.
The disease can be a hepatic disease. As one example, the disease can be NAFLD. As another example, the disease can be NASH.
The treatment can lower or inhibit the progression of hepatic steatosis, lobular inflammation, hepatocellular ballooning, NAFLD activity score (NAS) and/or fibrosis score and/or inhibit the progression of hepatic inflammation and fibrosis.
The disease can be a biliary disease. As one example, the disease can be primary biliary cirrhosis. As another example, the disease can be biliary cholangiatis.
The subject can be a primate. The primate can be a human.
The human subject can be administered about 1 to about 500 mg/kg/day of Gly-Gly-Leu tripeptide, about 3 to about 144 mg/kg/day of Gly-Gly-Leu tripeptide, about 1 to about 100 mg/kg/day of Gly-Gly-Leu tripeptide, about 12 to about 36 mg/kg/day of Gly-Gly-Leu tripeptide, or about 37.5 mg/kg/day of Gly-Gly-Leu tripeptide.
The Gly-Gly-Leu tripeptide can be administered orally. The Gly-Gly-Leu tripeptide can be administered in a single dose.

Brief Description of the Drawings

Figure 1 A-M. Confirmation of NASH before Randomization to Experimental Groups
C57BL/6J mice were fed a standard diet (SD) or NASH diet for 12 weeks and a subset of the mice (n=10 per group) were euthanized.
(A) Liver to body weight ratio at week 12.
(B-D) Plasma levels of AST (B) , ALT (C) , and ALP (D) at week 12.
(E-G) Gross appearance of the peritoneal cavities (E) , and histology using H&E (F) and Sirius Red (G) at week 12 (scale bar: 50 μm) .
(H-K) NAFLD activity score (NAS) at week 12 as the sum of steatosis (H) , hepatocellular ballooning (I) and lobular inflammation (J) scores assessed by H&E histology.
(K) Fibrosis score at week 12 assessed by Sirius Red histology.
After confirming NASH, the rest of the mice were randomized to orally receive DT-109 at increasing doses of 15, 45, 150, and 450 mg/kg/day, or H2O for 12 additional weeks on the NASH diet. Mice fed a SD and administered H2O served as controls (n=10 per group) .
(L) Body weight at endpoint.
(M) Liver weight at endpoint.
Data are means ± SEM. Statistical differences were compared by unpaired t test (A-D) , Mann-Whitney U test (H-K) , one-way ANOVA followed by Tukey's post hoc test (L) or by Kruskal-Wallis test followed by Dunn’s post hoc test (M) .
Figure 2 A-K. DT-109 Ameliorates Nonalcoholic Steatohepatitis in Mice in a Dose-dependent Manner
(A) Schematic representation of the experimental design. C57BL/6J mice were fed a standard diet (SD) or NASH diet for 12 weeks and a subset of the mice were euthanized, confirming NASH and early hepatic fibrosis. After confirming NASH, the rest of the mice were randomized to orally receive DT-109 at increasing doses of 15, 45, 150, and 450 mg/kg/d, or H₂O for 12 additional weeks on the NASH diet. Mice fed a SD and administered H₂O served as controls (n=10 per group) .
(B) Liver to body weight ratio at endpoint.
(C-E) Plasma levels of AST (C) , ALT (D) , and ALP (E) at the endpoint.
(F-H) Gross appearance of the peritoneal cavities (F) , and histology using H&E (G) and Sirius Red (H) staining at endpoint (scale bar: 50 μm) .
(I-J) Liver triglycerides and hydroxyproline content at the endpoint.
(K) NAFLD activity score (NAS) and fibrosis score at the endpoint. The NAS are the sum of steatosis, hepatocellular ballooning, and lobular inflammation scores assessed by H&E histology. The fibrosis score was assessed by Sirius Red histology.
Data are means ± SEM. Statistical differences were compared by one-way ANOVA followed by Tukey's post hoc test (B-D) or by Kruskal-Wallis test followed by Dunn’s post hoc test (E, I-K) .
Figure 3 A-J. Establishing a Nonalcoholic Steatohepatitis Model in Nonhuman Primates that Mimics the Human Disease
(A) Schematic representation of the experimental approach. NASH predisposed monkeys were screened from over 1,000 cynomolgus monkeys. Sixty-nine male monkeys (age≥9 years, BMI>30) were selected for physical, biochemical and histological analyses. Twenty NASH predisposed monkeys with NAFLD activity score (NAS) 1-3 were selected and fed the NASH diet for 10 months. Biochemical, histological and transcriptional (RNA-seq) indices were assessed before and after feeding the NASH diet for 10 months.
(B-E) Body weight (B) , abdominal circumferences (C) , waist circumferences (D) and serum AST at baseline and after 10 months on the NASH diet (E) .
(F-G) Histology using H&E (F) and Sirius Red (G) staining at baseline and after 10 months on the NASH diet (scale bar: 100 μm) .
(H) NAS at baseline and after 10 months on the NASH diet as the sum of steatosis, lobular inflammation, and hepatocellular ballooning scores assessed by H&E histology. The fibrosis score was assessed by Sirius Red histology.
(I) Gene set enrichment analysis (GSEA) comparing RNA-sequencing of liver samples obtained from monkeys at baseline and after 10 months on the NASH diet (n=5) to RNA-sequencing of liver samples obtained from patients with NASH (N=42) and age-and weight-matched controls (n=6) (Hoang et al., 2019) . Pathways enriched in the up-or down-regulated DEGs are plotted in red or blue, respectively. Scale bar: -log10 (p value) of the GSEA.
(J) Heatmap integrating the RNA-sequencing data of liver samples obtained from monkeys and humans as described in (I) with microarray data from 206 liver transplantation donors in which the hepatic fat content was quantified (dataset GSE26106, Brown et al. 2013; Wang et al., 2015) . The left column represents the gene function (cholesterol metabolism, fatty acid [FA] metabolism, fibrosis, or inflammation) , and the column next to it represents the correlation between the gene expression and the hepatic fat content in dataset GSE26106. Scale bar: Spearman’s correlation coefficient (rho) ranges between -0.4 (blue) to +0.4 (red) . The gene expression was further compared in liver samples obtained from monkeys and humans as described in (I) . Up-or down-regulated genes are plotted in red or blue, respectively. Scale bar: log2 fold-change.
All points are shown (B-E) . Data are means ± SEM (H) . Statistical differences were compared by paired t test (B, C and D) or Wilcoxon matched-pairs signed rank test (E and H) . P values of the GSEA were calculated based on 100000 permutations (I) . Statistical significance of differential expression was determined by Wald test using R package of DESeq2 (J) .
Figure 4 A-I. Establishing a Nonalcoholic Steatohepatitis Model in Nonhuman Primates that Mimics the Human Disease
(A) Schematic representation of the experimental design. NASH predisposed monkeys were screened from over 1,000 cynomolgus monkeys. Sixty-nine male monkeys (age≥9 years,
BMI>30) were selected for physical, biochemical and histological analyses. Twenty NASH predisposed monkeys with NAFLD activity score (NAS) 1-3 were selected and fed the NASH diet for 10 months. Biochemical, histological and transcriptional (RNA-seq) indices were assessed before and after feeding the NASH diet for 10 months.
(B-I) Waist circumferences (B) , serum ALP (C) , fasting glucose (D) , hemoglobin A1c (HbA1c) (E) , total cholesterol (F) , low-density lipoprotein cholesterol (LDL-C, G) , high-density lipoprotein cholesterol (HDL-C, H) , and triglycerides (I) at baseline and after 10 months on the NASH diet.
All points are shown (B-I) . Statistical differences were compared by paired t test (B, E and H) or Wilcoxon matched-pairs signed rank test (C, D, F, G and I) .
Figure 5 A-B. Transcriptional Similarities between Cynomolgus Monkeys and Humans with NASH
(A-B) Heatmap-based representation of the top 100 differentially expressed genes as determined by RNA-sequencing of liver samples obtained from monkeys at baseline and after 10 months on the NASH diet (n=5) and compared to RNA-sequencing of liver samples from two independent human cohorts: (A) Patients with NASH (n=42) and age-and weight-matched controls (n=6) (Hoang et al., 2019) . (B) Patients with NASH (n=16) and controls (n=14) (Suppli et al., 2019) . Up-or down-regulated genes in NASH are plotted in red or blue, respectively. Scale bars represent log2 fold-change.
Statistical significance of differential expression was determined by Wald test using R package of DESeq2 (A and B) .
Figure 6. NASH-related Indices Are Comparable in Cynomolgus Monkeys before Administration of DT-109 or Vehicle
Twenty NASH predisposed cynomolgus monkeys were fed the NASH diet for 10 months. After confirmation of NASH, the monkeys were randomized to receive orally DT-109 (150 mg/kg/day, n=10) or vehicle (H2O, n=10) for 5 additional months on the NASH diet. Physical, biochemical and biopsy-based histological analyses confirmed that indices that may affect the progression of NASH directly or indirectly were comparable between the two groups before administration of DT-109 or vehicle.
(A-K) Age (A) , body weight (B) , abdominal circumferences (C) , waist circumferences (D) , blood fasting glucose (E) , hemoglobin A1c (HbA1c) (F) , serum total cholesterol (G) , triglycerides (H) , AST (I) , ALP (J) , histological scoring (K) of hepatic steatosis, lobular inflammation, hepatocellular ballooning, NAFLD activity score (NAS) , and fibrosis score in cynomolgus monkeys fed the NASH diet for 10 months before administration of DT-109 or vehicle.
After 10 months on the diet, the monkeys were randomized to receive orally DT-109 (150 mg/kg/day, n=10) or H2O (vehicle control, n=10) for 5 additional months on the NASH diet. (L-O) Waist circumferences (L) , total cholesterol (M) , triglycerides (N) , and HbA1c (O) at endpoint.
Data are means ± SEM. Statistical differences were compared by unpaired t test (A-D, F, J, K [NAS and fibrosis score] , L) or Mann-Whitney U test (E, G-I, K [hepatic steatosis, lobular inflammation, and hepatocellular ballooning scores] and M-O) .
Figure 7 A-I. DT-109 Reverses Diet-induced Steatosis and Prevents Inflammation and Fibrosis Progression in Livers from Nonhuman Primates with Established NASH After 10 months on the diet, cynomolgus monkeys were randomized to receive via oral gavage DT-109 (150 mg/kg/d, n=10) or H₂O (vehicle control, n=10) for 5 additional months on the NASH diet.
(A-E) Body weight (A) , abdominal circumferences (B) , serum AST (C) , ALT (D) , and ALP (E) at the endpoint.
(F-H) Gross appearance of the peritoneal cavities (F) , and histology using H&E (G) and Sirius Red (H) staining at endpoint (scale bar: 100 μm) .
(I) NAFLD activity score (NAS) before and after treatment with DT-109 or vehicle as the sum of steatosis, lobular inflammation, and hepatocellular ballooning scores assessed by H&E histology. Fibrosis score before and after treatment with DT-109 or vehicle assessed by Sirius Red histology.
Data are means ± SEM. Statistical differences were compared by unpaired t test (A, B, D and E) or Mann-Whitney U test (C and I [hepatic steatosis, lobular inflammation, hepatocellular ballooning, and fibrosis score] ) when comparing DT-109 to vehicle post-treatment (endpoint) . Statistical differences were compared by paired t test (I [lobular inflammation, NAS, and fibrosis score) or Wilcoxon matched-pairs signed rank test (I [hepatic steatosis, and hepatocellular ballooning] ) when comparing histological parameters pre-and post-treatment.
Figure 8 A-L. Transcriptomics and Proteomics Uncover Induction of Hepatic Fatty Acid Degradation and Suppression of Proinflammatory/fibrotic Responses by DT-109 RNA-sequencing and proteomics were performed on livers from cynomolgus monkeys that were treated with DT-109 or vehicle for 5 months (n=5) .
(A) Principal components analysis (PCA) of RNA-sequencing data.
(B) Volcano plots of DEGs (blue, down-regulated; red, up-regulated. >2-fold, p＜0.05) .
(C-D) Pathways enriched in the upregulated (C) or downregulated DEGs are plotted in red or blue (D) , respectively.
(E) Heatmap-based representation of 50 NASH-related DEGs involved in fatty acid and cholesterol metabolism, inflammation and fibrosis. The gene expression values of the two groups (n=5 for each group) were plotted. Scale bar: log2 fold-change.
(F) GSEA based on RNA-sequencing and proteomics data. Scale bar: -log10 (p value) of the GSEA.
(G-J) Histological evaluation of neutral triglycerides and lipids using Oil Red O (ORO) staining (G) , immunohistochemistry for CD68 (H, J) , and biochemical quantification of hepatic triglycerides (I) in monkeys treated with DT-109 or vehicle (n=10) .
(K-L) Quantification of liver hydroxyproline content (K) and hepatic glutathione (GSH) (L) in monkeys treated with DT-109 or vehicle (n=10) .
All points are shown (A-B) . Data are means ± SEM showing all points (I-L) . Statistical significance of differential expression was determined by Wald test using R package of DESeq2 (B and E) . P values of GSEA were calculated based on 100000 permutations (C, D, and F) . Statistical differences were compared by unpaired t test (I, J, and K) or Mann-Whitney U test (L) .
Figure 9 A-B. Transcriptomics and Proteomics Following DT-109 Treatment RNA-sequencing and proteomics were performed on livers from monkeys that were treated with DT-109 or vehicle for 5 months (n=5) .
(A) Heatmap-based representation of the top 100 differentially expressed genes (DEGs) based on RNA-sequencing. Up-or down-regulated genes by DT-109 treatment are plotted in red or blue, respectively. Scale bar: log2 fold-change.
(B) Heatmap-based representation of the top 100 DEGs based on RNA-sequencing and their corresponding proteins based on proteomics. Up-or down-regulated genes and proteins by DT-109 treatment are plotted in red or blue, respectively. Scale bar: log2 fold-change.
Statistical significance of differential expression was determined by Wald test using R package of DESeq2 (A and B) . Significance of differential protein levels were determined by t-test (B) .
Figure 10 A-H. Untargeted and Targeted Metabolomics Reveal Suppression of Bile Acid Metabolism by DT-109
Untargeted and targeted metabolomics were performed on serum from cynomolgus monkeys that were treated with DT-109 or vehicle for 5 months (n=5) .
(A) Schematic representation of the experimental approach. LC-MS was used for untargeted metabolomics on serum samples followed by principal component analysis (PCA) and orthogonal partial least-square discriminant analysis (OPLS-DA) . Targeted metabolomics was used to confirm alternations in serum bile acids (BA) .
(B-C) PCA (B) , and OPLS-DA (C) .
(D) Analysis of metabolic pathway enrichment.
(E) Heatmap-based representation of significantly altered metabolites between monkeys that were treated with DT-109 or vehicle based on the variable importance in projection (VIP) value, fold change (FC) , and p value of annotated metabolites. Scale bar: Z-score log2 transformed intensity values.
(F) Relative intensity of BA species based on untargeted metabolomics.
(G) Concentrations of BA species as measured by targeted metabolomics.
(H) Concentrations of BA groups as measured by targeted metabolomics.
Data are means ± SEM showing all points (F-H) . Statistical differences were compared by unpaired t test (F-H) or Mann-Whitney U test (F-H) depending on normality tests.
Figure 11 A-F. Untargeted and Targeted Metabolomics Reveal Suppression of Bile Acid Metabolism by DT-109
(A) C57BL/6J mice were fed a standard diet (SD) or NASH diet for 12 weeks and a subset of the mice were euthanized, confirming NASH and early hepatic fibrosis. After confirming NASH, the rest of the mice were randomized to orally receive DT-109 at increasing doses or H2O (vehicle) for 12 additional weeks on the NASH diet. Mice fed a SD and administered vehicle served as controls. LC-MS was used for targeted metabolomics to assess bile acid (BA) groups in serum collected at endpoint from mice treated with DT-109 (150 and 450 mg/kg/day) or vehicle while on the NASH diet or SD (n=10) .
(B-F) LC-MS was used for untargeted metabolomics on livers from monkeys that were treated with DT-109 or vehicle for 5 months (n=5) followed by principal component analysis (PCA) and orthogonal partial least-square discriminant analysis (OPLS-DA) . Targeted metabolomics was used to confirm alternations in serum bile acids.
(B-C) PCA (B) and OPLS-DA (C) .
(D) Analysis of metabolic pathway enrichment
(E) Concentrations of BA groups in livers as measured by targeted metabolomics.
(F) Concentrations of lithocholic acid (LCA) in livers as measured by targeted metabolomics. Data are means ± SEM showing all points (A, E and F) . Statistical differences were compared by one-way ANOVA followed by Tukey's post hoc test (A) or by Kruskal-Wallis test followed by Dunn’s post hoc test (A) depending on normality tests. Statistical differences were compared by unpaired t test (E) or Mann-Whitney U test (E and F) depending on normality tests.
Figure 12 A-H. DT-109 Alters the Gut Microbiome in Association with Lithocholic Acid
(A-D) Comprehensive analysis of BA species was performed on fecal samples from cynomolgus monkeys that were treated with DT-109 or vehicle for 5 months (n=5) .
(A) Principal component analysis (PCA) of fecal BA species.
(B) Orthogonal partial least-square discriminant analysis (OPLS-DA) of fecal BA species.
(C) Heatmap-based representation of detected BA species in fecal samples.
(D) Significantly different BA species between monkeys that were treated with DT-109 and those administered vehicle. (lithocholic acid, LCA; ursodeoxycholic acid, UDCA; hyodeoxycholic acid, HDCA; muricholic acid, MCA) . Data are means ± SEM showing all points. Statistical differences were compared by unpaired t test or Mann-Whitney U test depending on normality tests.
(E-H) 16S rRNA sequencing was performed on fecal samples from cynomolgus monkeys that were treated with DT-109 or vehicle for 5 months (n=5) .
(E) Beta-diversity analysis using non-metric multidimensional scaling (NMDS) .
(F) Taxonomic cladogram generated by linear discriminant analysis (LDA) effect size (LEfSe) . Circle size is proportional to the abundance of the taxon.
(G) LDA of overrepresented bacterial taxa in samples from monkeys that were treated with DT-109 (blue) or vehicle (red) .
(H) correlations between the abundance of significantly altered genera, NASH-related parameters, and hepatic LCA concentrations. Spearman’s correlation coefficients are represented by colors ranging from blue (-1) to red (+1) .
Figure 13 A-C. The Effects of DT-109 on The Gut Microbiome of Cynomolgus Monkeys during NASH
(A-C) 16S rRNA sequencing was performed on fecal samples from cynomolgus monkeys that were treated with DT-109 or vehicle for 5 months (n=5) .
(A) Top ten phyla with the highest abundance in individual fecal samples and as averages of the two groups.
(B) Top ten classes with the highest abundance in individual fecal samples and as averages of the two groups.
(C) Significantly different genera between monkeys that were treated with DT-109 (blue) and those administered vehicle (red) .
Data are means ± SEM showing all points (C) . Statistical differences were compared by unpaired t test or Mann-Whitney U test depending on normality tests.
Figure 14 A-F. DT-109 Inhibits Microbial Production of Lithocholic Acid which is Increased in Patients with NAFLD
(A) qPCR analysis using primers specific to Faecalibacterium prausnitzii on fecal bacterial DNA obtained from cynomolgus monkeys that were treated with DT-109 or vehicle for 5 months (n=9-10) . Data was normalized to 16S expression.
(B) qPCR analysis using primers specific to Escherichia Shigella on fecal bacterial DNA obtained from cynomolgus monkeys that were treated with DT-109 or vehicle for 5 months (n=9-10) . Data was normalized to 16S expression.
(C) Microbial lithocholic acid (LCA) generation assessed by incubation of mouse feces with isotope-labeled chenodeoxycholic acid (d4-CDCA) with or without increasing concentration of DT-109 (0-500 μM) for 0-16 h. Newly generated LCA (d4-LCA) was measured using mass spectrometry. Data was normalized to relative intensity at the endpoint. A representative experiment with n=6 biological repetitions is shown (n=2-3 independent experiments) .
(D) Microbial LCA generation assessed by incubation of mouse feces with d4-CDCA and Faecalibacterium prausnitzii (OD600=0.35-0.45) or Gifu anaerobic medium (control) for 0-24 h.Newly generated d4-LCA was measured using mass spectrometry. Data was normalized to the relative intensity at the endpoint. A representative experiment with n=3 biological repetitions is shown (n=3 independent experiments) .
(E) LC-MS analysis of plasma LCA in patients with NAFLD (n=149) and healthy controls (n=229) .
(F) Schematic summary shows mechanisms of action of DT-109 on NASH.
Data are means ± SEM showing all points. Statistical differences were compared by unpaired t test (A, D) , Mann-Whitney U test (B, E) or one-way ANOVA followed by Tukey's post hoc test (C) .

Detailed Description

The disclosure provides tripeptide molecules, and pharmaceutically acceptable salts thereof, that exhibit preventive or therapeutic activity for metabolic, cardiovascular and/or inflammatory diseases.
Tripeptides and compositions
Tripeptide DT-109 is an illustrative tripeptide utilized in the Examples herein. It is a glycine-containing tripeptide molecule with the sequence Gly Gly Leu. Another illustrative tripeptide provided herein is tripeptide DT-110, a glycine-containing tripeptide molecule with the sequence Gly Gly dLeu. Tripeptides can be produced by peptide synthesis methods well known in the art.
Tripeptides of the disclosure can comprise one or more non-peptide bonds in place of peptide bond (s) . For example, the peptides comprise in place of a peptide bond, an ester bond, an ether bond, a thioether bond or an amide bond.
Tripeptides of the 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 an organic base, salts with inorganic acid, salts with organic acid, salts with basic or acidic amino acid, and the like. Non-limiting examples of metal salts include alkali metal salts such as sodium salt, potassium salt and the like; alkaline earth metal salts such as calcium salt, magnesium salt, barium salt and the like; aluminum salt and the like. Non-limiting examples of salts with an organic base include salts with trimethylamine, triethylamine, pyridine, picoline, 2, 6-lutidine, ethanolamine, diethanolamine, triethanolaminecyclohexylamine, dicyclohexylamine, N, N-dibenzylethylenediamine and the like. Non-limiting examples of salts with an inorganic acid include salts with hydrochloric acid, hydrobromic acid, nitric acid, sulfuric acid, phosphoric acid and the like. Non-limiting examples of salts with an organic acid 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 the like.
The tripeptides can also be synthesized and/or administered as prodrugs. A prodrug is a molecule which is converted to the tripeptide by a reaction due to an enzyme, gastric acid, etc. under the physiological conditions in a treated subject.
Examples of a prodrug of a tripeptide or a pharmaceutically acceptable salt thereof, include a tripeptide wherein an amino group of the tripeptide molecule is acylated, alkylated or phosphorylated (e.g., wherein an amino group of the glycine-containing tripeptide molecule is eicosanoylated, alanylated, pentylaminocarbonylated, (5-methyl-2-oxo-1, 3-dioxolen-4-yl) methoxycarbonylated, tetrahydrofuranylated, pyrrolidylmethylated, pivaloyloxymethylated or tert-butylated) ; a tripeptide wherein a hydroxy group of the tripeptide is acylated, alkylated, phosphorylated or borated (e.g., wherein a hydroxy group of the tripeptide is acetylated, palmitoylated, propanoylated, pivaloylated, succinylated, fumarylated, alanylated or dimethylaminomethylcarbonylated) ; a tripeptide wherein a carboxy group of the tripeptide is esterified or amidated (e.g., wherein a carboxy group of the 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-dioxolen-4-yl) methyl esterified, cyclohexyloxycarbonylethyl esterified or methylamidated) and the like. For example, where a carboxy group of the tripeptide molecule is esterified with C1-6 alkyl such as methyl, ethyl, tert-butyl or the like.
A prodrug of a tripeptide or a pharmaceutically acceptable salt thereof, can also be one which is converted into the tripeptide under a physiological condition, such as those described in IYAKUHIN no KAIHATSU (Development of Pharmaceuticals) , Vol. 7, Design of Molecules, p. 163-198, Published by HIROKAWA SHOTEN (1990) .
The disclosure provides a composition comprising at least one tripeptide and a pharmaceutically acceptable excipient. As used herein, the term "pharmaceutically acceptable" means approved by a regulatory agency of the Federal or state government, or listed in the U.S. Pharmacopeia or other generally recognized pharmacopeia for use in animals, such as humans.
Tripeptide compositions provided herein are formulated with pharmaceutically acceptable excipients such as carriers, solvents, stabilizers, adjuvants, diluents, etc., depending upon the mode of administration and dosage form. Pharmaceutical carriers can be sterile liquids, such as water and oils, including those of petroleum, animal, vegetable or synthetic origin, such as peanut oil, soybean oil, mineral oil, sesame oil, and the like. Water is a typical carrier when the pharmaceutical composition is administered intravenously. Saline solutions and aqueous dextrose and glycerol solutions can be employed as liquid carriers, particularly for injectable solutions. Suitable pharmaceutical excipients include starch, glucose, lactose, sucrose, gelatin, malt, rich, flour, chalk, silica gel, sodium stearate, glycerol monostearate, talc, sodium chloride, dried skim milk, glycerol, propylene, glycol, water, ethanol, and the like. The composition, if desired, can also contain minor amounts of wetting or emulsifying agents, or pH buffering agents.
The compositions can include one or more formulation materials for modifying, maintaining or preserving, for example, the pH, osmolarity, viscosity, clarity, color, isotonicity, odor, sterility, stability, rate of dissolution or release, adsorption or penetration of the composition. Suitable formulation materials include, but are not limited to, amino acids (such as glutamine, asparagine, arginine or lysine) ; antimicrobials; antioxidants (such as ascorbic acid, sodium sulfite or sodium hydrogen sulfite) ; buffers (such as borate, bicarbonate, Tris HCI, citrates, phosphates, other organic acids) ; bulking agents (such as mannitol or glycine) , chelating agents (such as ethylenediamine tetraacetic acid (EDTA) ) ; complexing agents (such as caffeine, polyvinylpyrrolidone, beta cyclodextrin or hydroxypropyl beta cyclodextrin) ; fillers; monosaccharides; disaccharides and other carbohydrates (such as glucose, mannose, or dextrins) ; proteins (such as serum albumin, gelatin or immunoglobulins) ; coloring; flavoring and diluting agents; emulsifying agents; hydrophilic polymers (such as polyvinylpyrrolidone) ; low molecular weight polypeptides; salt forming counterions (such as sodium) ; preservatives (such as benzalkonium chloride, benzoic acid, 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 pluronics, PEG, sorbitan esters, polysorbates such as polysorbate 20, polysorbate 80, triton, tromethamine, lecithin, cholesterol, tyloxapal) ; stability enhancing agents (sucrose or sorbitol) ; tonicity enhancing agents (such as alkali metal halides (in one aspect, sodium or potassium chloride, mannitol sorbitol) ; delivery vehicles; diluents; excipients and/or pharmaceutical adjuvants. (Remington's Pharmaceutical Sciences, 18th Edition, A. R. Gennaro, ed., Mack Publishing Company, 1990) .
Pharmaceutical compositions can take the form of solutions, suspensions, emulsions, tablets, pills, capsules, powders, sustained-release formulations, and the like.
The compositions are generally formulated to achieve a physiologically compatible pH, and range from a pH of about 3 to a pH of about 11, about pH 3 to about pH 7, depending on the formulation and route of administration. The pH can be adjusted to a range from about pH 5.0 to about pH 8. The compositions can comprise a therapeutically effective amount of at least one tripeptide as described herein, together with one or more pharmaceutically acceptable excipients. The compositions can include additional therapeutically active ingredient (s) .
A tripeptide of the disclosure can be supplied in a single-use only glass vial as a lyophilized cake, prepared in a formulation buffer consisting of 10 mM glutamic acid, 2%glycine, 1%sucrose, and 0.01%polysorbate 20 to pH 4.25. Upon reconstitution with a volume of sterile diluent, for example, sterile isotonic saline or water, for example, 0.5 mL to about 10 mL, for example, 2.2 mL of sterile water, the cake yields a 1 g/mL to about 100 g/mL concentration of glycine tripeptide molecule. Once the single-use vial has been reconstituted, the tripeptide composition can be administered quickly (i.e., no more than three hours after reconstitution) after reaching room temperature (15 to 30℃) .
Faecalibacterium
The human gastrointestinal tract harbors 500–1000 bacterial genera that facilitate digestion and nutrient absorption, affect host metabolism, and shape immunity. Only a few are predominant (Bacteroides, Clostridium, Bifidobacterium, and Faecalibacterium) . The genus Faecalibacterium, currently reclassified into the family Oscillospiraceae within the order Eubacteriales, consists of three validated species: F. longum, F. butyricigenerans, and F. prausnitzii. F. prausnitzii is one of the predominant bacteria in the human gut, accounting for approximately 5%of the total fecal microbiota in healthy adults.
The present disclosure contemplates the use of F. prausnitzii as a biotherapeutic to be used in combination with tripeptides of the disclosure in treatment methods of the disclosure. The present disclosure contemplates F. prausnitzii is an example of a gut bacteria that can be used to reduce secondary bile acids.
F. prausnitzii is available for purchase from various sources. Examples of sources include, but are not limited to, the American Type Culture Collection (ATCC) and Creative Biolabs. F. prausnitzii can be cultured in a strictly anaerobic environment in a modified reinforced Clostridial culture medium [e.g., from Beijing Coolaber Technology Co., Ltd. (Coolaber, DZSL0529) ] . After culture, the bacteria can be collected by centrifugation and resuspended in sterile PBS containing 10%glycerol for storage.
F. prausnitzii can be formulated as a liquid or solid dosage form. When the dosage form is a liquid composition, the concentration of viable bacteria in the liquid composition may be, for example, about 10⁹-10¹² CFU/ml, about 10⁹-10¹¹ CFU/ml, or 5x10¹⁰ CFU/ml. In a liquid dosage form, the F. prausnitzii can be suspended in a phosphate buffer, such as 1X phosphate buffer at a pH of about 7.3 and can include glycerol in a volume percentage of 10%. The liquid composition may be used directly or stored at a low temperature, preferably at -80℃.
Methods of treatment
The disclosure provides methods of using the tripeptides provided herein in combination with F. prausnitzii to prevent and/or treat one or more metabolic, cardiovascular, inflammatory and oncological diseases in a subject.
Methods provided herein can reduce the production of a secondary bile acid by a subject. The secondary bile acid can be lithocholic acid. The reduction in production of secondary bile acid can be a reduction of about 5%, 10%, 20%, 30%, 35%, or 40%or more in comparison to production prior to treatment. Secondary bile acids are derived from primary bile acids in a process reliant on biosynthetic capabilities possessed by the gut microbiome.
Methods provided herein can decrease the abundance of Escherichia Shigella in the gut of the subject. Methods of analyzing bacteria are standard in the art and include, for example, obtaining and culturing a fecal sample from a subject and PCR analysis to determine bacteria in the sample.
In the methods, the subject is administered a therapeutically effective amount of a tripeptide composition of the disclosure and a therapeutically effective amount of F. prausnitzii. A "therapeutically effective amount" as used herein refers to an amount of a tripeptide sufficient to exhibit a detectable therapeutic effect. The effect is detected by, for example, an improvement in clinical condition, or a prevention, reduction or amelioration of complications. The precise effective amount for a subject will depend upon the subject's body weight, size, and health; the nature and extent of the condition; and the therapeutic (or combination of therapeutics) selected for administration. Therapeutically effective amounts for a given situation are determined by routine experimentation that is within the skill and judgment of the clinician. The combined use of the tripeptide composition and F. prausnitzii can result in additive or even synergistic therapeutic effects.
A therapeutically effective amount of a tripeptide of the disclosure can be from about 1 mg/kg/day to about 10,000 mg/kg/day, from about 5 mg/kg/day to about 5,000 mg/kg/day, from about 20 mg/kg/day to about 1,000 mg/kg/day, from about 30 mg/kg/day to about 1,000 mg/kg/day, from about 50 mg/kg/day to about 10,000 mg/kg/day, or from about 100 mg/kg/day to about 5,000 mg/kg/day. A therapeutically effective amount of a tripeptide of the disclosure can be from about 1 to about 500 mg/kg/day, about 3 to about 144 mg/kg/day, about 1 to about 100 mg/kg/day, about 12 to about 36 mg/kg/day, or about 37.5 mg/kg/day.
The therapeutically effective amount of a tripeptide of the disclosure in the compositions provided herein can be from about 250 mg to about 500 g, from about 500 mg to about 400g, from about 750 mg to about 200g, from about 1,000 mg to about 100g. The therapeutically effective amount of a tripeptide of the disclosure in the compositions provided herein can be from about 300 mg to about 1,000g, from about 500 mg to about 500g, from about 600 mg to about 400g, from about 700 mg to about 300g, from about 800 mg to about 200g, from about 900 mg to about 150g, or from about 1,000 mg to about 100g. The amount of tripeptide can be from about 600 mg to about 300g.
A tripeptide composition of the disclosure can be administered as a single daily dose, or may be divided into several doses administered throughout the day, for example, one to five doses per day, or two to three doses per day. A tripeptide composition can be administered every other day. A tripeptide can be administered once a week. An administration schedule and dose for a given situation is determined by routine experimentation that is within the skill and judgment of the clinician.
F. prausnitzii can be administered, for example, in an amount of about 1x10⁶, about 1x10⁷ or about 1x10⁸ CFU/day. A subject can be a mammal. The mammal can be a primate, such as a human. The mammal can be a domesticated mammal or a laboratory mammal. A subject in need of treatment is a subject experiencing a metabolic disease, and/or a cardiovascular disease, and/or inflammatory disease, and/or oncological disease, or one or more symptoms associated with these diseases.
Tripeptides provided herein and F. prausnitzii can be administered by the oral route. It is contemplated that administration by the oral route is accomplished in some embodiments using delivery vehicles known in the art including, but not limited to, microspheres, liposomes, enteric-coated dry emulsions or nanoparticles. Subjects can be fed a diet comprising a tripeptide of the disclosure.
The disclosure also provides kits comprising a tripeptide of the disclosure, F. prausnitzii, instructions or a label for use of the two, and a device for measuring an amount of the tripeptide composition or administering the tripeptide composition to the subject. The kit can include one or more additional therapeutic agents.
Metabolic disease
As used herein, metabolic disease refers to a group of diseases involving diseases of metabolism which are risk factors of various cardiovascular diseases and type 2 diabetes. It includes insulin resistance and complex and diverse metabolic diseases related thereto. In 1988, Reaven proposed insulin resistance as the factor underlying these diseases and named the constellation of abnormalities insulin resistance syndrome. However, in 1998, the World Health Organization (WHO) introduced the term metabolic syndrome or metabolic disease since all the aspects of the symptoms cannot be explained by insulin resistance. Treatment of metabolic disease can include, for example, treatment of obesity, diabetes, hyperlipemia, non-alcoholic fatty liver (NAFLD) , non-alcoholic steatohepatitis (NASH) , and/or insulin resistance syndrome. The metabolic diseases as described herein also include diseases that can be treated through the modulation of metabolism, although the disease itself may or may not be caused by a specific metabolic defect. Such metabolic diseases may involve, for example, glucose and fatty acid oxidation pathways. The tripeptides of the present disclosure (for example, DT-109 and DT-110) in combination with F. prausnitzii can prevent or treat metabolic diseases.
The metabolic disease can be a hepatic disease.
NAFLD is increasingly common around the world, especially in western nations. In the United States, it is the most common form of chronic liver disease, affecting an estimated 80 to 100 million people. Nonalcoholic fatty liver disease is an umbrella term for a range of liver conditions affecting people who drink little to no alcohol. As the name implies, the main characteristic of nonalcoholic fatty liver disease is too much fat stored in liver cells. It is normal for the liver to contain some fat. However, if more than 5%-10%percent of the liver's weight is fat, the condition is called a fatty liver (steatosis) .
NAFLD is strongly associated with features of metabolic syndrome, including obesity, insulin resistance, type-2 diabetes mellitus, and dyslipidemia; it is considered the hepatic manifestation of this syndrome.
Pediatric NAFLD is currently the primary form of liver disease among children. Studies have demonstrated that abdominal obesity and insulin resistance are thought to be key contributors to the development of NAFLD. Because obesity is becoming an increasingly common problem worldwide the prevalence of NAFLD has been increasing concurrently.
The more severe form of NAFLD is called non-alcoholic steatohepatitis (NASH) . NASH causes the liver to swell and become damaged. NASH tends to develop in people who are overweight or obese, or have diabetes, high cholesterol or high triglycerides or inflammatory conditions. NASH, a potentially serious form of the disease, is marked by hepatocyte ballooning and liver inflammation, which may progress to scarring and irreversible damage. This damage is similar to the damage caused by heavy alcohol use. Macro and microscopically, NASH is characterized by lobular and/or portal inflammation, varying degrees of fibrosis, hepatocyte death and pathological angiogenesis. At its most severe, NASH can progress to cirrhosis, hepatocellular carcinoma and liver failure. Currently NAFLD and NASH are being treated by diet, treatment of insulin resistance or vitamin administration, such as vitamins E or D.
In methods provided herein for treating liver diseases such as NAFLD, NASH or alcoholic hepatic steatosis, the treatment can stabilize or reduce the NAFLD activity score of a subject. A NAFLD Activity Score (NAS) can be calculated according to the criteria of Kleiner (Kleiner DE. et al., Hepatology, 2005; 41: 1313) . NAS scores 0-2 are not considered diagnostic for NASH, NAS scores of 3-4 are considered either not diagnostic, borderline or positive for NASH, while NAS scores of 5-8 are largely considered diagnostic for NASH. A treatment effect for NASH includes the regression, stabilization or a reduction in the rate of disease progression. Sequential liver biopsies from a patient that may have NASH can be used to assess the change in the NAS score and used as an indication of the change in the disease state. A score that increases suggests progression, an unchanged score suggests stabilization, while a decreased score suggests regression of NASH. In a controlled clinical trial, the difference in NAS scores between the placebo and the test article treatment group, assessed usually over a duration of 6 months to two years, can be indicative of a treatment effect, even if both groups are progressing. A defined point spread is usually required by a regulatory authority to demonstrate a meaningful change in NASH.
Treatment methods provided herein can lower, or inhibit the progression of, hepatic steatosis, lobular inflammation, hepatocellular ballooning, NAFLD activity score (NAS) and/or fibrosis score. Imaging methods are standard in the art and include, for example, non-invasive imaging such as magnetic resonance imaging and magnetic resonance elastography as well as histological analysis of invasive liver biopsies.
A kit for treating NAFLD provided herein comprises a tripeptide provided herein, F. prausnitzii, optionally a statin, and instructions for use. A kit for treating NASH provided herein comprises a tripeptide provided herein, optionally a statin, and instructions for use.
Cardiovascular disease
As used herein, cardiovascular disease refers to atherosclerosis and complications of atherosclerosis. Atherosclerosis occurs when the blood vessels that carry oxygen and nutrients from the heart to the rest of the body, arteries, become think and stiff (hardening of the arteries) . Sometimes this restricts blood flow to organs and tissues. Atherosclerosis can result in a number of complications including myocardial infarction, coronary artery disease, carotid artery disease, carotid artery disease, peripheral artery disease, aneurisms, and chronic kidney disease.
Myocardial infarction (heart attack) occurs when blood flow decreases or stops to part of the heart, causing damage to the heart muscle. Common symptoms are pain in the center or left side of the chest, shortness of breath, nausea, or it may cause heart failure, irregular heartbeat, cardiogenic shock or cardiac arrest.
Coronary artery disease is when atherosclerosis narrows the arteries close to the heart which can cause chest pain (angina) , a heart attack or heart failure.
Carotid artery disease is when atherosclerosis narrows the arteries close to the brain which can cause a transient ischemic attack (TIA) or stroke. Symptoms include sudden numbness or weakness in arms or legs, temporary loss of vision in one eye or drooping muscles in the face.
Peripheral artery disease is when atherosclerosis narrows the arteries in arms or legs causing circulation problems. This can reduce sensitivity to heat and cold, increasing risk of burns or frostbite. In rare cases, poor circulation in arms and legs can cause tissue death (gangrene) . Symptoms are leg pain when walking (claudication) .
An aneurysm is a bulge in the wall of an artery which can be a medical emergency. If an aneurysm bursts it can be a life-threatening event.
Chronic kidney disease can be caused by atherosclerosis when it leads to narrowing of the arteries leading to the kidneys preventing oxygenated blood from reaching the kidneys. Over time this can affect kidney function keeping waste from exiting the body. Symptoms are high blood pressure or kidney failure.
The tripeptides of the present disclosure (for example, DT-109 and DT-110) in combination with F. prausnitzii can prevent or treat atherosclerosis and its complications.
Inflammatory disease
As used herein, treating inflammatory disease is treating inflammation in the gastrointestinal tract, wherein the administration of a tripeptide provided herein results in less inflammation. The tripeptides of the present disclosure in combination with F. prausnitzii can prevent or treat inflammation in the gastrointestinal tract as evidenced by reduced alkaline phosphatase (ALP) levels. Methods of analyzing ALP are standard in the art and include measuring levels in the blood of a subject. The tripeptides of the present disclosure in combination with F. prausnitzii can prevent or treat, for example, biliary diseases such as primary biliary cirrhosis and biliary cholangiatis.
Oncologic Disease
NASH can lead to cirrhosis which in turn can lead to hepatocellular carcinoma. The tripeptides of the present disclosure in combination with F. prausnitzii can prevent or treat development of cancers such as hepatocellular carcinoma.
Bile acids
Bile acids, normal metabolites in the intestinal lumen, are needed for digestion and absorption of lipids, as well as uptake of cholesterol and fat-soluble vitamins. In addition, BAs regulate intestinal epithelial homeostasis in the GI tract.
Primary bile acids (chendeoxycholic acid and cholic acid in humans; muricholic acid and cholic acid in mice) are synthesized in the liver from cholesterol, by a number of different cytochromes P450, with the last step in the synthetic pathway being conjugation with the amino acids glycine (most commonly in humans) or taurine (predominant in mice) . The conjugated primary bile acids (also referred to as bile salts) are secreted from hepatocytes into the bile duct, via the bile salt export protein and from there may be transported into the duodenum or stored in the gall bladder. When primary bile acids reach the terminal ileum, they are reabsorbed by the apical sodium-dependent bile acid transporter (ASBT) expressed in the epithelium and recycled back to the liver.
Deconjugated bile acids are not recirculated by the ASBT, but instead progress into the large bowel. There they are further metabolized by the microbiota, resulting in production of 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 gut bacteria that possess the ability to produce secondary bile acids.
The present disclosure provides methods of reducing secondary bile acids in a subject by administering to the subject a tripeptide of the disclosure and F. prausnitzii. The secondary bile acid reduced can be, for example, LCA. Methods of analyzing bile acids are standard in the art and include, for example, obtaining a fecal sample and analysis by mass spectrometry.
Treatment with further combinations
The present disclosure also provides methods for treatment of metabolic, cardiovascular, inflammatory and oncological diseases by administration of a tripeptide provided herein and F. prausnitzii, in further combination with another therapeutic agent to treat the metabolic, cardiovascular, inflammatory and oncological diseases. For example, the disclosure contemplates the combination with another therapeutic agent that is standard of care for the metabolic, cardiovascular, inflammatory and oncological disease. For example, the methods disclosed above can further comprise administering another therapeutic agent to the subject including, but not limited to, a statin, a cholesterol absorption inhibitor, a PCSK9 inhibitor, PPAR-alpha agonist, an ACE inhibitor, a calcium channel blocker, an ARBs, renin, GLP-1 or a synthetic variant thereof, insulin or a synthetic variant thereof, metformin, a sulfonyll urea compound, a thiazolidinedione (TZD) , a PCSK9 inhibitor, a SGLT2 inhibitor, a SGLT1 inhibitor in addition to a SLGT2 inhibitor, a DPP-IV inhibitor, an inhibitor of HMGCoA reductase, an inhibitor of proprotein convertase subtilisin/kexin type 9 (PCSK9) , ezetimibe, gemfibrozil, fenofibrate, clofibrate, bezafibrate, pemafibrate, gemcabene (CI-1027) , benpodoic acid (ETC-1002) , an ACC inhibitor, an ApoC-Ill inhibitor, an ACL-inhibitor, prescription fish oil, a CETP inhibitor, an anti-fibrotic agent, a bile acid sequestrant (such as cholestyramine) , fibrates (hypolipidemic agents) and combinations thereof.
The other therapeutic agent (s) can be combined with the tripeptide of the disclosure and F. prausnitzii, and can result in an additive or even synergistic enhancement of activity. Administration of the active ingredient combination can take place either by separate administration of the active ingredients to the patient or in the form of combination products in which a plurality of active ingredients is present in one pharmaceutical preparation. It is expected that the additional therapeutic agent can be dosed at its approved dosage when used as a single agent, or initially, the additional therapeutic agent can be dosed at therapeutically effective concentrations or at sub-therapeutically effective concentrations, such that the combination of the secondary therapeutic agent with the tripeptide, when administered in combination, provides a therapeutically effective result in the subject being treated.
Other terminology and disclosure
As used herein and in the appended claims, the singular forms "a, " "and, " and "the" include plural referents unless the context clearly dictates otherwise. It is further noted that the claims may be drafted to exclude any element, e.g., any optional element. As such, this statement is intended to serve as antecedent basis for use of such exclusive terminology as "solely, " "only" and the like in connection with the recitation of claim elements, or use of a "negative" limitation.
When a range of values is provided herein, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range, is encompassed within the disclosure. The upper and lower limits of these smaller ranges may independently be included in the smaller ranges, and are also encompassed within the disclosure, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present disclosure.
All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and/or materials for the purpose for which the publications are cited.
As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present disclosure. Any recited method can be carried out in the order of events recited or in any other order which is logically possible. This disclosure is intended to provide support for all such combinations.
As used herein, “contemplated, ” “may, ” “may comprise, ” “may be, ” “can, ” “can comprise” and “can be” all indicate something envisaged by the inventors that is functional and available as part of the subject matter provided.
Examples
The following Examples show DT-109 reverses hepatic steatosis and inhibits the progression of hepatic inflammation and fibrosis in nonhuman primates with established NASH. These effects are mediated not only through stimulation of hepatic fatty acid degradation and GSH formation, but also through inhibition of microbial production of LCA, a known hepatotoxic BA (Staudinger et al., 2001) that is independently associated with NAFLD risk.
While the following examples describe specific embodiments, variations and modifications will occur to those skilled in the art. Accordingly, only such limitations as appear in the claims should be placed on the invention.
Data and Code Availability
All raw omics data generated in the studies described in the Examples are deposited in the public available data base. Here are the details. All RNA-sequencing data and 16S rRNA sequencing data were deposited to the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database. The accession number for the RNA-sequencing data of liver samples obtained from monkeys at baseline and after 10 months on the NASH diet is PRJNA859546. The accession number for the RNA-sequencing data of livers from cynomolgus monkeys that were treated with DT-109 or vehicle for 5 months is PRJNA860095. The accession numbers for the data obtained on 16S rRNA sequencing of fecal samples from cynomolgus monkeys PRJNA865025. The raw metabolomics MS data generated in this study were deposited in the MetaboLights database under accession code MTBLS5005. All MS-based proteome data were deposited in the integrated proteome resources iProX with the dataset identifier IPX0004494000 and are available at: www. iprox. cn/page/SSV024. html; url=1672567339738460H, password: 5UxH. Experimental data that support the findings of this study are available from the corresponding authors on reasonable request. Source data are provided within this paper.
Experimental Model and Subject Details
Mouse Studies
All procedures performed in mice were approved (approval number: PRO00010092) by the Institutional Animal Care and Use Committee at the University ofMichigan and performed in accordance with the institutional guidelines. Seven-week-old male C57BL/6J (stock: 000664) mice were obtained from Jackson Laboratories. Eight-week-old male C57BL/6J were fed ad libitum either standard diet (SD, LabDiet, 5L0D, 13%of calories from fat) or NASH diet (Research Diets, D17010103, 40%fat) previously confirmed to potently induce NASH in mice (Rom et al., 2019; Rom et al., 2020) . Mice were orally administered (gavage) DT-109 (Diapin Therapeutics, Ann Arbor, MI, USA) at 15, 45, 150 or 450 mg/kg body weight/day or vehicle (H₂O, control) for 12 weeks.
Nonhuman Primate Studies
All experimental protocols involving nonhuman primates were approved by the Laboratory Animal Care Committee of Xi'an Jiaotong University (approval number: 20191278) and the Institutional Animal Care and Use Committee of Spring Biological Technology Development Co., Ltd. (approval number: 201901) . The study was performed in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals (8^th edition, 2011) . NASH predisposed monkeys were screened from over 1,000 cynomolgus monkeys (Macaca fascicularis) at the Spring Biotechnology site. Sixty-nine male monkeys (age≥9 years, BMI>30) were selected and housed in individual cages with access to water and food ad libitum. Before physical examination (body weight, waist circumference, and abdominal circumference) and liver biopsy, monkeys were anesthetized with ketamine hydrochloride (10 mg/kg body weight) . The waist circumference was measured at the midpoint between the last rib and the iliac crest, and the abdominal circumference was measured at the height of the umbilicus. For the liver biopsy, a Bard Magnum biopsy gun (Bard Biopsy Systems, Tempe, AZ, USA) loaded with a 17-gauge biopsy needle (Argon, Athens, TX, USA) was used for under the guidance of an ultrasound system (Landwind, P09, Shenzhen, China) . The collected liver tissues were then stored in formalin or -80℃. Twenty monkeys with a NAS of 1-3 were defined as NASH predisposed and were fed a NASH diet (Table S1) . After 10 months on the NASH diet, physical examination was repeated, blood samples were collected for biochemical analyses and liver biopsies were obtained for histopathological analysis and transcriptomics. The 20 monkeys were randomized to receive orally (gavage) DT-109 at 150 mg/kg body weight/day or equivalent volume of H₂O (vehicle control) for 5 additional months on the NASH diet. Through physical, biochemical and histological (biopsy-based) assessments, all NASH-related parameters were confirmed to be comparable between the DT-109 and control groups before initiating the intervention study. At endpoint, blood samples were collected, and the monkeys were then anaesthetized using ketamine hydrochloride (15 mg/kg body weight) before euthanized by exsanguination. Whole livers were quickly removed, then perfused with cold phosphate buffered saline (PBS) . Collected liver tissues were stored in liquid nitrogen or formalin.
Human Studies
A total of 378 subjects, consisting of healthy controls and patients with NAFLD (ages 17-80 years) , were recruited from Zhongshan Hospital, Fudan University (Zhao et al., 2020) . Information on demographics and clinical characteristics were collected and detailed in Table S2. The diagnosis of fatty liver was based on ultrasound examination. Exclusion criteria included: i) heart, pulmonary or renal diseases. ii) history of alcohol abuse. iii) other known liver diseases. The study was approved by the Ethics Committee of Zhongshan Hospital, Fudan University (IRB: B2020-180) and written informed consent was signed and obtained from all the participants.
Methods
Biochemical Analyses of Plasma and livers from Mice
Analyses were performed as previously described (Rom et al., 2019; Rom et al., 2020) . Briefly, biochemical assays for AST, ALT, and ALP were performed by the University of Michigan In Vivo Animal Core on a Liasys 330 chemistry analyzer (AMS Diagnostics) using manufacturer-provided reagents and protocols. Technicians were blinded to experimental groups. Followed hepatic lipid extraction, triglycerides were assessed using the FUJIFILM Wako Triglyceride kit (Cat#632-50991) as previously described (Rom et al., 2019; Rom et al., 2020) . Collagen content in the mouse liver was evaluated by measuring the hydroxyproline level using the Hydroxyproline Assay Kit from MilliporeSigma (Cat#MAK008) according to the manufacturer’s protocol.
Histological Analyses of Livers from Mice
All histological procedures in the mouse study were performed by technicians that were blinded to experimental groups at the University of Michigan In Vivo Animal Core Histology Laboratory, as previously described (Rom et al., 2019; Rom et al., 2020) . Formalin-fixed tissues were processed through graded alcohols and cleared with xylene followed by infiltration with molten paraffin using an automated VIP5 or VIP6 tissue processor (TissueTek, Sakura-Americas) . Using a Histostar Embedding Station (ThermoFisher Scientific) , tissues were then sectioned on a M355S rotary microtome (ThermoFisher Scientific) at 4 μm thickness and mounted on glass slides. Slides were stained for hematoxylin and eosin (H&E, ThermoFisher Scientific) . For Sirius Red staining, slides were treated with 0.2 phosphomolybdic acid for 3 min and transferred to 0.1%Sirius Red saturated in picric acid (Rowley Biochemical Inc. ) for 90 min, then transferred to 0.01N hydrochloric acid for 3 min. H&E staining was used for NAFLD activity score (NAS, Kleiner et al., 2005) . Steatosis was scored from 0-3 (0: <5%steatosis; 1: 5-33%; 2: 34-66%; 3: >67%) . Hepatocyte ballooning was scored from 0-2 (0: normal hepatocytes, 1: normal-sized with pale cytoplasm, 2: pale and enlarged hepatocytes, at least 2-fold) . Lobular inflammation was scored from 0-3 based on foci of inflammation counted at 20X (0: none, 1: <2 foci; 2: 2-4 foci; 3: ≥4 foci) . NAS was calculated as the sum of steatosis, hepatocyte ballooning and lobular inflammation scores. Sirius Red staining was used to score hepatic fibrosis from 0-4 (0: no fibrosis; 1: perisinusoidal or portal fibrosis; 2: perisinusoidal and portal fibrosis; 3: bridging fibrosis; 4: cirrhosis) . The NAS and fibrosis score (Kleiner et al., 2005) were independently evaluated by at least two independent pathologists who were blinded to experimental groups, and the averaged scores are presented.
Targeted Metabolomic for Bile Acids in Plasma from Mice
The plasma BAs were assessed by targeted metabolomics using LC-MS/MS at University of Michigan Pharmacokinetics and Mass Spectrometry Core. In brief, 30 μL of plasma were dispensed into a 96-well plate. Next, 120 μL of methanol and 10 μL of internal standard solution were added and vortexed for 10 min. The plate was centrifuged at 3,500 RPM for 10 min at 4℃ to precipitate protein. The supernatant of 100 μL were transferred to another 96-well plate and 2 μL was injected into LC-MS/MS for analysis. A rapid and effective UPLC–MS/MS method was established for targeted and quantitative analysis of 15 BAs, including 6 primary BAs and 9 secondary BAs. The LC-MS system consisted of Waters ACQUITY UPLC and Waters TQD Tandem Quadrupole mass spectrometer equipped with an ESI source (MA, USA) . Fifteen BAs and 9 deuterium-labelled BAs internal standards were separated on a CORTECS T3 column (2.1x30mm, 2.7 μm) with a mobile phase of 0.01%formic Acid in water containing 0.2mM ammonium formate (solvent A) and 0.01% Formic Acid in isopropanol: ACN (50: 50, v: v) containing 0.2 mM Ammonium formate (solvent B) using gradient elution. The gradient elution of mobile phases included: initiate with 10%B for 0.5 min, increased to 90%B in 3.5 min, decrease to 10%B in 0.01 min, and balance for 1 min before the next injection. The column temperature was maintained at 40℃ and flow rate was set at 1.0 mL/min. The detection of analytes was conducted in multiple reaction monitoring with positive electrospray ionization mode. The assay was validated by chemical stability, selectivity, sensitivity, linearity, precision, accuracy, carryover effect, and extraction efficiency.
Biochemical Analyses of Serum from Cynomolgus Monkeys
Cynomolgus monkeys were fasted overnight (14-16 h) , and blood samples were collected from the hind limb vein. 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 serum and glycated hemoglobin (HbA1 c) of EDTA anticoagulated blood were examined by an automatic biochemistry analyzer (TOSHIBA, TBA-2000FR, Tokyo, Japan) .
Biochemical and Histological Analyses of Livers from Cynomolgus Monkeys
Liver tissues were rapidly collected from the euthanized monkeys at the endpoint, frozen in liquid nitrogen, and kept at -80 ℃. Liver triglycerides were determined using an enzymatic assay kit (Applygen Technologies Inc, Beijing, China) according to the manufacturer's instructions. Liver collagen content was evaluated by measuring the hydroxyproline level using the Hydroxyproline Detection Kit from Solarbio (Cat#BC0250) according to the manufacturer’s protocol. Protein concentrations were determined using the Pierce BCA protein assay kit (ThermoFisher Scientific, Waltham, MA, USA) according to the manufacturer’s instructions. Liver triglycerides were normalized by tissue protein. The amount of liver glutathione was determined using a GSH Fluorometric Detection Assay Kit (Abcam, Cambridge, MA, USA) , following the manufacturer’s instructions. Briefly, 20 mg of liver tissue was washed in cold PBS, then resuspended in 400 μL ice-cold Mammalian Lysis Buffer. Samples were homogenized and centrifuged at 12,000 g for 15 min at 4℃. The supernatant was collected, and tissue enzymes were removed using Deproteinizing Sample Kit (Abcam) . Fifty μL of GSH Assay Mixture was added into each GSH standard and sample and incubated at room temperature for 30 min in the dark. Fluorescence was detected at Ex/Em = 490/520 nm with a fluorescence microplate reader (TECAN, Seestrasse, Switzerland; Infinite M200 pro) . Concentrations of liver GSH were normalized to tissue sample weight.
H&E staining was performed on paraffin-embedded liver tissue samples. Liver fibrosis was assessed on paraffin-embedded liver sections using Sirius red staining. Neutral triglycerides and lipids were assessed using Oil Red O (ORO) staining on embedded frozen liver tissues in OCT compound. Immunohistochemistry of CD68 was performed on paraffin-embedded liver sections. Samples were heated in a microwave oven for 10 min in EDTA buffer (pH 9.0) for antigen retrieval, then were placed in 3%hydrogen peroxide for 15 min to quench endogenous peroxide. After washing with PBS (5 min/wash, three times) and blocking with goat serum (Absin, Shanghai, China) for 1 h, the sections were incubated with anti-CD68 antibody (1: 100, Sigma-Aldrich, St. Louis, MO, USA) at 4℃ for 12 h, and washed with PBS (5 min/wash, three times) . The sections were then incubated with enzyme labeled goat anti-rabbit IgG (Absin) for 1 h at room temperature, and washed with PBS (5 min/wash, three times) . Finally, the sections were visualized using 3, 3-diaminobenzidine (DAB) kit (ZSGB-BIO, Beijing, China) and counterstained with hematoxylin. Histopathological images were captured under a light microscope (Olympus, Tokyo, Japan) and quantified using Image-Pro plus (Media Cybernetics, Silver Springs, MD, USA) . The NAS and fibrosis score (Kleiner et al., 2005) were independently evaluated by at least two independent pathologists who were blinded to experimental groups, and the averaged scores are presented.
RNA-sequencing of Livers from Cynomolgus Monkeys
Approximately 50 mg of liver tissue was grounded into powder under liquid nitrogen, then transferred into the 2 mL microtube containing 1.5 mL Trizol reagent (Invitrogen, Carlsbad, CA, USA) . The mixture was centrifuge at 12,000 g for 5 min at 4℃. Next, the supernatant was transferred to a new microtube containing 0.3 mL chloroform/isoamyl alcohol (24: 1) per 1.5 mL of Trizol reagent. After centrifugation at 12,000 g for 10 min at 4℃, the aqueous phase was transferred to a new microtube, and an equal volume of isopropyl alcohol was added. After centrifugation at 12,000 g for 20 min at 4℃, the supernatant was removed and then washed with 1 mL of 75%ethanol, the RNA pellet was air-dried and then dissolved with 100 μL of DEPC-treated water. Subsequently, the RNA was qualified and quantified using an Agilent 2100 bioanalyzer. RNase H was used to remove the rRNA. Purified mRNA was fragmented, and then first-strand cDNA was generated in First Strand Reaction System by PCR, followed by second strand cDNA synthesis. The reaction product was purified and then A-Tailing Mix and RNA Index Adapters were used to carry out end repair. Then the products were amplified to create as the final library. The final library was sequenced on BGISEQ500 platform (BGI, Shenzhen, China) .
Analysis of RNA-sequencing and Microarray of Liver Samples from Cynomolgus Monkeys and Humans
FastQC v0.11.8 (https: //www. bioinformatics. babraham. ac. uk/projects/fastqc/) was used to check the quality of the raw FASTQ files. The low-quality reads were trimmed using Trimmomatic (v. 0.35) with the following parameters: SLIDINGWINDOW: 4: 20 MINLEN: 25 (Bolger et al., 2014) . Then the resulted 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) . The gene counts were measured by HTSeq-counts (v. 0.6.0) based on the Macaca_fascicularis_6.0 genome annotations (Anders et al., 2015) . To facilitate the subsequent comparative analysis with human data, the homologous gene symbols were mapped from Macaca fascicularis to the human genome using the getLDS function of R package biomaRt (v. 2.46.3, Smedley et al., 2009) . Two public gene expression datasets of human liver samples from patients with NASH were used to compare the transcriptomic profiles between cynomolgus monkeys and humans. The first study utilized liver RNAseq dataset GSE130970 (Hoang et al., 2019) . A NAFLD activity score (NAS) ≥4 was used to identify patients with NASH (n=42) , while those with NAS ≤1 (steatosis ≤1 without hepatocellular ballooning, lobular inflammation, and fibrosis) were considered as normal controls (n=6) . In the second study (dataset GSE126848, Suppli et al., 2019) , 16 patients with NASH and 14 controls were included in the analysis. The rest of the samples within the above datasets were not included in the analysis. The raw gene counts downloaded from GEO database were used for the subsequent analysis. The correlation between the expression of NASH-related genes and hepatic fat content was assessed using our previously published microarray data obtained from 206 liver transplantation donors (GSE26106, Brown et al., 2013) . The sample preparation and microarray data processing were described previously (Brown et al., 2013; Rom et al., 2020; Wang et al., 2015) . Hexane/isopropanol (3: 2) were used to quantify the hepatic fat content as previously described (Li et al., 2011; Wang et al., 2015) . The total fat content normalized by the total protein concentration and transformed to log10 scale were used for the subsequent analysis.
Proteomics of Livers from Cynomolgus Monkeys
Protein extracts from livers of cynomolgus monkey were obtained by homogenization in lysis buffer at 4℃ for 15 min (4%SDS, 0.1 M DTT, 0.1 M Tris-HCl, pH 7.6) , followed by 5 min of incubation at 95℃ and 3 min of sonication (10 s On, and 10 s Off, power 50 Watts) . After centrifugation at 16,000 g at room temperature for 10 min, protein content of the supernatant was determined by tryptophan-based fluorescence quantification as previously described (Thakur et al., 2011) . The filter-aided sample preparation (FASP) procedure was used for protein digestion (et al., 2009) . Proteins were loaded in 10 kDa centrifugal filter tubes (Millipore, Burlington, MA, USA) , washed twice with 200 μL UA buffer (8 M urea in 0.1 M Tris-HCl, pH 8.5) , alkylated with 50 mM iodoacetamide in 100 μL UA buffer for 30 min in the dark, washed thrice with 200 μL UA buffer again and finally washed thrice with 200 μL 50 mM triethyl ammonium bicarbonate (TEAB) . All above steps were centrifuged at 12,000 g at 25℃. Next, protein samples in 10 kDa centrifugal filter tubes were transformed to a new clear collection tube, and were then digested using trypsin at an enzyme: protein mass ratio of 1: 25 overnight at 37℃. The resulting peptides were eluted by centrifugation and the peptide concentration was determined by BCA protein quantification kit. For each sample, 50 μg peptides were prepared by vacuum centrifugation drying for the TMT11 labeling experiment. To eliminate batch effect of multiple TMT experiments, an ‘internal reference’ mixed sample was used in TMT11 labeling consisting of a mixture of liver samples from all cynomolgus monkeys in equal protein amounts. The peptides of the mixed samples were also prepared by FASP and divided into 50 μg per EP tube for each set of TMT labeling experiment as the internal reference. The mixed peptides were labeled with channel 131 C as the internal reference, while other experimental samples were randomly labeled with the other ten channels. For labeling, a set of TMT reagents was balanced to room temperature and dissolved in 41 μL of anhydrous acetonitrile. [Twenty? ] uL of which were added to 50 μg of peptides to achieve a final acetonitrile concentration of approximately 30% (v/v) . Following incubation at room temperature for 1.5 h, the reaction was quenched with hydroxylamine to a final concentration of 0.3% (v/v) for 15 min. The TMT-labeled samples were pooled at a 1: 1 ratio across all samples. The combined sample was vacuum centrifuged to near dryness and subjected to C18 solid-phase extraction desalting (3M Empore) .
The pooled TMT-labeled peptide samples were next fractionated using high-pH reverse phase liquid chromatography (RPLC) . The liver peptide mixture (550 μg) was fractionated using a Waters XBridge BEH300 C18 column (250×4.6 mm, OD 5 μm) at a flow rate of 0.7 mL/min on Shimadzu Prominence HPLC System following the manufacturer’s instructions (Shimadzu Scientific Instruments) . Mobile phases A and B were prepared as previously described (Gilar et al., 2005) . A 74-min gradient was set as follows, 5%-8%B in 5 min; 8%-18%B in 35 min; 18%-32%B in 22 min; 32%-95%B in 2 min; 95%B for 4 min; 95%-5%B in 4 min; 5%B for 2 min. Thirty-six fractions were collected at 2 min intervals from 1 min to 72 min. According to HPLC chromatogram, 20 fractions were combined by a concatenation scheme (Song et al., 2010) . Each fraction was subsequently vacuum centrifuged to near dryness, desalted via C18 StageTip, dried again via vacuum centrifugation, and reconstituted in buffer A (0.1% (v/v) formic acid in H₂O) for LC-MS/MS processing.
For data acquisition by mass spectrometry, LC-MS/MS analyses were performed on a nanoflow Easy-nLC 1000 system liquid chromatography system (ThermoFisher Scientific) coupled to an Q Exactive HF-X mass spectrometer (ThermoFisher Scientific) . Prior to MS, peptide mixtures were separated on a home-made reversed-phase column (100 μm×200 mm) packed with ReproSil-Pur C18-AQ, 1.9 μm resin (Dr. Maisch GmbH, Germany) with a flow rate of 450 nL/min. Buffer A consisted of 0.1% (v/v) formic acid in H2O and Buffer B consisted of 0.1% (v/v) formic acid in acetonitrile. A 120 min gradient was set as follows: 2%–5%B in 2 min; 5%–25%B in 102 min; 25%–35%B in 9 min; 35%–90%B in 2 min; 90% B in 5 min. The MS1 full scan was set at a resolution of 60,000 @m/z 200, automatic gain control (AGC) target 3e6 and maximum injection time 30 ms by orbitrap mass analyzer with mass range 350–1500 m/z. Then, the fifteen most intense ions were isolated and fragmented with higher-energy collisional dissociation (HCD) to generate MS2 scans (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 ms) .
For proteome database search, the raw MS files were processed with the MaxQuant software (version 1.6.14.0) against the Macaca fascicularis database (UP000233100) , using the integrated Andromeda search engine with FDR < 1%at peptide and protein level. The search included variable modifications for oxidized methionine (M) , acetylation (protein N-term) and fixed modifications for carbamidomethyl (C) . TMT11-plex-based MS2 reporter ion quantification was chosen with reporter mass tolerance set at 0.003 Da.The precursor intensity fraction (PIF) filter value was set at 0.75 to reduce the interference of precursor co-fragmentation. Moreover, the ‘internal reference’ labeled with channel 131 C was assigned as the reference channel and ‘weighted ratio to reference channel’ was performed to eliminate batch effect of multiple TMT experiments. ‘Isobaric matching between runs’ was enabled with a matching time window of 0.7 min to transfer MS1 identifications between runs as previously reported (Yu et al., 2020) . Enzyme specificity was set as trypsin. The maximum missing cleavage site was set as 2.
Untargeted Metabolomics in Serum and Livers from Cynomolgus Monkeys
For preparation of serum samples, fasting blood samples were collected into K2EDTA vacutainer tubes and kept at 4℃. Within 2 h, the blood samples were centrifuged at 3,000 g and 4℃ for 10 min. Supernatants (serum) were separated and transferred into new vials and immediately stored at -80℃ until analyzed. Frozen serum samples were thawed at 4℃ and then vortexed for 3 min. Aliquots of 100 μL were mixed with 300 μL of pre-cooled methanol. After vortex (4 min) and centrifugation at 18, 800 g and 4℃ for 10 min to precipitate proteins, the supernatants were collected and evaporated to dryness under vacuum using a Speed Vac Concentrator (Thermo Electron Corporation, Model SPD121 P, ThermoFisher Scientific) . The dry residue was reconstituted in 100 μl acetonitrile/water 3: 1 (v/v) , and then centrifuged at 18, 800 g and 4℃ for 10 min. The supernatant was collected and transferred into new vials for LC-MS analysis. For preparation of liver samples, frozen samples (wet weight: 50 mg) were 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 the tissue was homogenized three times for 30 sec at a shock velocity of 4.0 m/sec using a high-throughput MasterPrepTM-24 tissue homogenizer. After homogenization, the samples were centrifuged at 18, 800 g and 4℃ for 4 min. The supernatant was collected and evaporated to dryness under vacuum using a Speed Vac Concentrator (Thermo Electron Corporation, Model SPD121 P; ThermoFisher Scientific) . The dry residue was reconstituted in 100 μl acetonitrile/water 3: 1 (v/v) , and then centrifuged again at 18, 800 g and 4℃ for 10 min. The supernatant was collected and transferred into new vials for LC-MS analysis.
Untargeted metabolites screening was performed on Q-TOF tandem mass spectrometer (Triple TOF 5600TM, SCIEX, Foster City, CA, USA) , equipped with ESI and APCI ion sources in positive/negative ion mode and Analyst TF 1.7.1 data processing system. The chromatography was performed on a Shimadzu Prominence system with a binary pump, an online degasser, an autosampler and a column oven (Shimadzu Scientific Instruments, INC., Columbia, MD, USA) . The separation was achieved on a Waters ACQUITY HSS T3 column (2.1 × 100 mm, 1.8 μm) at 40℃. The gradient elution was programmed with the mobile phase consisting of formic acid in 0.1% (v/v) water (A) and acetonitrile (B) at a flow rate of 250 μL/min as follows: 0-5 min, 2-60%B (v/v) ; 5-10 min, 60%(v/v) ; 10-17min, 60-100%B (v/v) ; 17-20min, 100%B. The system was returned to the initial conditions in 0.1 min and re-equilibrated for 5 min. The autosampler temperature was set at 4℃ and the injection volume was 2 μL in positive ion mode and 5 μL in negative ion mode. The LC-MS data were acquired in both positive and negative ion modes. The detailed parameters were as follows: spray voltage 5.5 kV or -4.5 kV, declustering voltage 80 V or -80 V, vaporizer temperature 450℃, turbo gas 50 psi, nebulizer gas 55 psi, curtain gas 35 psi. Full Scan analysis was performed in TOF mode with the scan range of 50-1000 m/z, and the MS/MS analysis was accomplished with information-dependent acquisition (IDA) mode with collision energy (CE) 45/30/15 or -45/-30/-15 eV. Acquired data were auto-calibrated according to the calibrated manufacturer’s guidelines. Analyst TF 1.7.1 (Sciex) was used for the data acquisition as well as processing. External mass calibration was performed every 5 samples. Serum and tissue samples were randomized in the sequence, QC and mixed-standard samples were also analyzed repeatedly within the analytical run after every ten samples to evaluate chromatographic reproducibility.
The obtained raw spectrogram was processed using Progenesis QI (Waters, Milford, MA, USA) (Larkin et al., 2022) . Metabolites were identified by two levels: 1) accurate mass matching, and 2) MS/MS confirmation. Mass tolerance for database search was 5 ppm for MS, and 15 ppm for MS/MS. The instrument stability was monitored using QC samples. The intensity of extracted variables was normalized to the total areas to reduce the variations from sample injection and enrichment factor. After peak deconvolution, alignment, integration, and normalization, a table containing retention times, exact mass pairs, and normalized intensities of each variable were obtained for multivariate statistical analysis. Then, all normalized Pareto-scaled data were imported into SIMCA-P v14.1 software (Umetrics AB, Umea, Sweden) for multivariate statistical analysis. The cross-validation was used to test the model validity against overfitting. Potential biomarker candidates were selected based on variable importance in projection (VIP > 1) , S-plot, and the raw data plot in orthogonal partial least-square discriminant analysis (OPLS-DA) model, and independent t-test (p<0.05) . The number of components of the principal component analysis (PCA) and OPLS-DA were 4 and 4, respectively. Finally, the fragment, isotope and adduct ions were manually removed according to the corresponding extracted ion chromatograms (XICs) and the potential biomarkers were screened out. The structure of potential biomarkers was identified according to the significance of their contribution to variable classification, which was determined by the VIP plot and jack-knifing confidence interval (≥0) in the OPLS-DA model as described above. Subsequently, the potential biomarkers obtained were identified as described previously (An et al., 2010; Chen et al., 2009; Xu et al., 2013) . Briefly, the [M+H] + or [M-H] -ions of the metabolites was obtained by high-resolution mass spectrometry, and the possible molecular composition of the metabolites was obtained based on the accurate mass of the molecular ion and the isotope abundance ratio. To obtain structural information, LC-MS/MS spectrum analysis was conducted, and a public mass spectrum library search was performed using the resulting MS/MS spectra as query. Possible structures were inferred through database search including HMDB (http: //hmdb. ca) , Massbank (http: //massbank. imm. ac. cn/MassBank) , and METLIN (http: //metlin. scripps. edu) with exact molecular weights. In addition, the retention time and fragmentation characteristic ions were obtained by LC-MS/MS analysis of commercial standards, and comparative analysis with Progenesis QI software (Waters, Milford, MA, USA) was used to finally confirm the structure of the metabolites. For characterization of potential biomarkers, Metabolomics Pathway Analysis (MetPA) , a web-based and visual tool used to analyze metabolomic data within the biological context of metabolic pathways and to identify the most relevant pathways in a metabolic study, was used. MetaboAnalyst 5.0 (https: //www. metaboanalyst. ca/) Functional Analysis module was further used. This module accepts high-resolution LC-MS (HRMS) spectral peak data to perform metabolic pathway enrichment analysis and visual exploration based on the well-established mummichog algorithm. The following parameters were used in the pathway enrichment process: normalization by median, Log transformed (base 10) , pareto scaling, Homo sapiens (human) [KEGG] . Altered metabolic pathways were visualized by bubble charts using Online tackle hiplot (https: //hiplot. com. cn/basic) and MetPA. In addition, to further investigate changes in identified metabolites by DT-109 administration, an intuitive characterization was conducted by means of clustering heatmap, using HemI, a toolkit for illustrating heatmaps. The raw metabolomics data generated in this study were deposited in the MetaboLights database under accession code MTBLS5005.
Targeted Metabolomic for Circulating and Liver Bile Acids in Humans and Cynomolgus Monkeys
Targeted metabolomics for BAs was performed as reported previously (Han et al., 2015) . Briefly, 20 μL of serum were mixed with 80 μL of internal standard comprised of deuterium-labeled BAs in methanol. To determine the concentrations of the analytes, standard curves were performed using increasing concentrations (0-5 μM) of the standards. The standard curves were considered acceptable when coefficient of determination (R²) reached 0.99. Samples were vortexed for 1 min at 4-8℃, centrifuged at 20,000 g and 4℃for 10 min, and the supernatant was collected. Supernatants (2 μL) were analyzed by injection onto a BEH C18 (2.1 Х150 mm, 1.7 μm) UPLC column (Waters Inc. Milford, MA) at a flow rate of 0.3mL/min using a LC-20AD Shimadazu pump system, SIL-20AXR auto-sampler interfaced with an API 6500Q-TRAP mass spectrometer (SCIEX, Framingham, MA) . A discontinuous gradient was generated to resolve the analytes by mixing solvent A (0.1%formic acid in water) with solvent B (0.1%formic acid in acetonitrile) at different ratios starting from 55%to 70%B in 2 min, 75%to 100%B in 2 min, keeping 100%B in 2 min and then 100%to 40%B in 0.1 min. The column was equilibrated with 25%B for 2 min between injections. The flow rate was 0.3 mL/min and the column was maintained at 45℃. Analytes were monitored using electrospray ionization in negative-ion mode with multiple reaction monitoring (MRM) of precursor and characteristic product-ion transitions of BAs. Detailed ion pairs are shown in Table S4.
Table S4: Ion Pairs in Targeted Metabolomics for Bile Acids
All MS parameters were optimized by direct infusion. The de-clustering potential and collision energies for specific quantification and confirmation transitions were optimized to maximize the sensitivity.
Targeted Metabolomic for Bile Acids in Fecal Samples from Cynomolgus Monkeys
BAP Ultra kit (Metabo-Profile, Shanghai, China) was used to analyze the BA profile. Ten mg of fecal samples were mixed with 25 mg precooled grinding beads and 200 μL acetonitrile/methanol (v/v = 8: 2) solution containing 10 μL internal standard. The samples were homogenized, centrifuged, and isolated. Ten μL of the supernatant were mixed with 90 μL of acetonitrile/methanol solution (v/v = 8: 2) and ultrapure water. After oscillation and centrifugation, the samples were detected with ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLCMS/MS) system (ACQUITY UPLC-Xevo TQ-S, Waters Corp., Milford, MA, USA) at Metabo-Profile co., ltd. The raw data generated by UPLC-MS/MS were processed using the QuanMET software (v2.0, Metabo-Profile) to perform peak integration, calibration, and quantitation for each metabolite as previously reported (Xie et al., 2018) .
16S rRNA Sequencing of Fecal Samples from Cynomolgus Monkeys
The total genomic DNA of fecal samples randomly selected for half of the animals in the DT-109 and vehicle treated groups (n=5 per groups) was extracted using the PowerMax Soil DNA Isolation Kit (MO BIO Laboratories, Carlsbad, CA, USA) . Bacterial 16S rRNA genes V3–V4 region were amplified with PCR using Q5 High-Fidelity DNA Polymerase (NEB) and quantified using the Quant-iT PicoGreen dsDNA Assay Kit (ThermoFisher Scientific) . TruSeq Nano DNA LT Library Prep Kit (Illumina) was used to construct the library, and the PCR amplicons were purified using Vazyme VAHTSTM DNA Clean Beads (Vazyme, Nanjing, China) and qualified using Agilent High Sensitivity DNA Kit (Agilent, Santa Clara, CA, USA) and quantified using Quant-iT PicoGreen dsDNA Assay Kit. After that, the amplicons were sequenced by Illumina Novaseq 6000 platform with NovaSeq 6000 SP Reagent Kit (Illumina) at Biotree biomedical technology co., ltd (Shanghai, China) .
Conversion of d4-CDCA to d4-LCA by Fecal Microbiota
Ileum and cecum contents (approximately 400 mg) were collected from mice as previously described (Yoo et al. 2016) . Fresh fecal pellets were suspended and homogenized in potassium phosphate buffer (0.01 M, pH 7.4) with a 1: 4 ratio of feces to phosphate buffer. The stool homogenate was centrifuged at 500 g for 10 min. The reaction mixture containing 20 μL d4-CDCA solution (100 μM) and 40 μL fecal suspension was incubated at 37℃. DT-109 (20 μL) was added at an increasing concentration (0-500 μM) . The total volume was adjusted with the vehicle to avoid any dilution effects. The reaction was stopped by freezing at -80℃. Experiments were halted at different time points (0, 1, 2, 4, 8, and 16 h) . Extraction and detection of BAs were performed as follows. Briefly, 20 μL of the reaction mixture were mixed with 80 μL of internal standard comprised of d4-TCDCA in methanol. Samples were vortexed, centrifuged at 20,000 g for 10 min at 4℃, and the supernatant was collected and used for targeted metabolomics analysis (Han et al., 2015; Zhao et al., 2020) . For experiments testing the conversion of d4-CDCA to d4-LCA by Faecalibacterium prausnitzii, fresh stool samples (approximately 400 mg) were suspended in Gifu anaerobic medium (GAM) medium at a 1: 9 ratio. Fecal supernatants were collected after centrifugation at 500 g for 10 min. Next, 1.5 mL GAM or an equal volume of bacteria, either Faecalibacterium prausnitzii, Roseburia rectibacter or Escherichia coli (OD600 between 0.35 and 0.45) , was added into 1.5 mL of fecal supernatants. The reaction mixture containing 200 μM d4-CDCA was incubated under anaerobic conditions at 37 ℃. Aliquots of 30 μL were collected at different time points (0, 1, 2, 4, 8, 12, and 24 h) and kept at -80℃until analyzed. Extraction and detection of BAs were performed as described above.
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 the primers detailed in the KEY RESOURCES TABLE (Ramirez-Farias et al., 2009; Wu et al., 2021) .
Quantification and Statistical Analysis
Statistical analyses were performed using GraphPad Prism 8.0. All data were tested for normality and equal variance. If passed, Student’s t test was used to compare two groups or one-way analysis of variance (ANOVA) followed by Tukey post hoc test for comparisons among >2 groups. Otherwise, nonparametric tests (Mann-Whitney U test or Kruskal-Wallis test followed by Dunn’s post hoc test) were used. P value <0.05 was considered statistically significant. The differentially expressed genes (DEGs) of RNA- sequencing data were analyzed using R package DESeq2 (v. 1.30.1) (Love et al., 2014) . Genes with adjusted p value less than 0.05 and absolute fold change larger than 2 were identified as significant DEGs. Gene set enrichment analysis (GSEA) of KEGG database were used to identify significantly enriched pathways in the up-and down-regulated genes through the clusterProfiler package (v. 3.18.1, Yu et al., 2012) . Genes ranking by log fold change at either mRNA or protein levels were used as inputs for GSEA with p values calculated based on 100000 permutations. Spearman’s correlation was used to assess the correlation between hepatic fat and NASH-related gene expression. For proteome analysis, bioinformatics was performed with the R 3.5.1. The corrected reporter intensities (weighted ratio to internal reference) in each sample were normalized by subtracting the median of all intensities in each sample. Proteins with reporter intensities in >2/3 samples were then retained, and K-nearest neighbor (k-NN) imputation was applied to impute the missing values. The log2 transformed normalized data were used for subsequent analyses. For microbiome bioinformatics, QIIME2 (versoin 2020.6) and R packages (3.1.1) were used. The demux plugin was used for demultiplexed raw sequence data and the cutadapt plugin for primer cutting. The DADA2 plugin was used for quality filter, denoise, merge and chimera removal. Taxonomy was assigned to amplicon sequence variants (ASVs) with classify-sklearn plugin (confidence: 0.7) . Alpha diversity metrics and beta diversity metrics were estimated with the diversity plugin. Beta diversity analysis was visualized via nonmetric multidimensional scaling (NMDS) . LEfSe (Linear discriminant analysis effect size) was performed to detect differentially abundant taxa between the vehicle and DT-109 groups using the default parameters. Spearman’s correlation was used to assess the relationship between the abundance of fecal genera, BAs and NASH-related indices followed by heatmap visualization.
Example 1
DT-109 Ameliorates Nonalcoholic Steatohepatitis in Mice in a Dose-dependent Manner
DT-109 administered orally to mice at 500 mg/kg/d potently reduced steatohepatitis and fibrosis induced by a high fat, fructose, and cholesterol diet (NASH diet, Rom et al., 2020) . To determine optimal dosing, the dose-response of DT-109 was evaluated during NASH. C57BL/6J mice were fed the NASH diet for 12 weeks and a subset of the mice was euthanized, confirming NASH and early hepatic fibrosis as evidenced by a significant increase in the 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 1 B-D) together with hepatomegaly, steatohepatitis and early fibrosis assessed by histopathological (H&E and Sirius Red staining) and biochemical analyses, respectively (Figure 1 E-J) . After confirming NASH, the rest of the mice were randomized to orally receive DT-109 at increasing doses of 15, 45, 150, and 450 mg/kg/d or H2O (vehicle) for 12 additional weeks on the NASH diet. Mice fed a standard diet (SD) and administered H2O served as controls (Figure 2A) . At the endpoint (week 24) , body weight was significantly higher in all groups fed the NASH diet regardless of DT-109 treatment or dose (Figure 1 K) . Nevertheless, DT-109 treatment attenuated the hepatomegaly induced by the NASH diet resulting in a dose-dependent decrease in liver weight (Figure 1 L) and liver to body weight ratio (Figure 2B) , with a most significant effect at 450 mg/kg/d. Compared to mice on the NASH diet that received vehicle, treatment with 450 mg/kg/d of DT-109 reduced the liver to body weight ratio by 31.1% (p=0.0001, Figure 2B) . Accordingly, DT-109 treatment led to a dose-dependent decrease in circulating transaminases (Figure 2C-E) . Compared to mice on the NASH diet that received vehicle, treatment with DT-109 at 450 mg/kg/d significantly decreased circulating AST by 34.2% (p=0.0365, Figure 2C) and ALT by 50.3% (p=0.0058, Figure 2D) . Reduced liver damage was confirmed by gross morphology (Figure 2F) and histological and biochemical analyses (Figure 2G-K) , indicating attenuated hepatomegaly, steatohepatitis, and fibrosis. Histological analyses revealed that DT-109 treatment dose-dependently attenuated the marked increase in NAFLD activity score (NAS) and fibrosis score induced by the NASH diet. Compared to mice on the NASH diet that received vehicle, DT-109 at 450 mg/kg/d significantly reduced the scores of steatosis (2.78 ± 0.08 vs. 1.72 ± 0.17, p=0.001) , overall NAS (5.94 ± 0.17 vs. 3.91 ± 0.32, p=0.0033) , and fibrosis score (1.71 ± 0.11 vs. 0.57 ± 0.18, p=0.0033, Figure 2K) . Together, these findings demonstrate that DT-109 treatment dose-dependently lowers diet-induced NASH and hepatic fibrosis in mice, with 450 mg/kg/d as the most efficient dose.
Example 2
Establishing a Nonalcoholic Steatohepatitis Model in Nonhuman Primates that Mimics the Human Disease
The majority of drugs that reach clinical evaluation were identified or developed using rodent models, which have limited clinical translatability in NASH (Febbraio et al., 2019) . To develop a highly translatable preclinical model of NASH, an experimental approach was devised utilizing a dietary intervention in cynomolgus monkeys (Figure 3A and S2A) . Over 1,000 monkeys at the Spring Biotechnology site were screened for NASH predisposition. Sixty-nine male monkeys (age≥9 years, body mass index [BMI] >30) were selected for a thorough physical, biochemical and histological analyses. By obtaining liver biopsies and histological assessment of NAS, monkeys that showed no evidence of NAFLD-related pathology (NAS=0) or had developed NASH (NAS≥4) spontaneously were excluded. Twenty monkeys with a NAS of 1-3 were defined as NASH predisposed and were included in the study. The monkeys were then fed our newly developed high fat, fructose, and cholesterol diet (NASH diet for nonhuman primates, Table S1) .
Table S1: Composition of the NASH Diet for Nonhuman Primates
After 10 months on the NASH diet, indices of obesity (body weight [p<0.0001, Figure 3B] , abdominal circumferences [p<0.0001, Figure 3C] , and waist circumferences [p=0.0001, Figure 3D] ) , liver damage (AST [p=0.0119, Figure 3E] , ALP [p=0.0472, Figure 4B] ) and 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 NASH progression. Histological analyses (Figure 3F-H) revealed a significant increase in the scores of hepatic steatosis (0.85±0.08 vs. 1.62 ± 0.23, p=0.0057) , lobular inflammation (0.10±0.07 vs. 1.15±0.15, p<0.0001) , hepatocellular ballooning (1.00±0.10 vs. 1.63±0.11, p=0.0007) , overall NAS (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 obtained from the monkeys before and after feeding the NASH diet for 10 months to assess the similarity between the nonhuman primate model and human NASH. The top 100 differentially expressed genes (DEGs) in livers from monkeys before and after 10 months on the NASH diet were compared to two independent cohorts of liver samples from individuals with and without NASH (Hoang et al., 2019; Suppli et al., 2019) , revealing prominent transcriptional similarities between our model and human NASH (Figure 5A and 5B) . Pathway enrichment analysis indicated that underlying pathways in NASH were similarly and significantly upregulated (e.g., cytokine-cytokine receptor interaction [monkeys: p=3.76x10-3, humans: p=1.05x10-5] , chemokine signaling pathway [monkeys: p=9.99x10-3, humans: p=1.10x10-5] , and extracellular matrix (ECM) -receptor interaction [monkeys: p=2.55x10-4, humans: p=2.07x10-2] ) or downregulated (e.g., glycine, serine and threonine metabolism [monkeys: p=6.92x10-5, humans: p=3.47x10-3] , and tryptophan metabolism [monkeys: p=3.67x10-3, humans: p=3.04x10-4] ) in both monkeys and individuals with NASH (Figure 3I) . Using another cohort of 206 samples from liver transplantation donors (Brown et al., 2013; Wang et al., 2015) , the expression of key genes was compared that are implicated in NASH and correlated with hepatic steatosis in the monkey model versus human NASH (Figure 3J) . Genes that are known to play a protective role in NASH by inducing fatty acid degradation (e.g., PPARA) were found to be significantly downregulated in both monkeys and individuals with NASH, and inversely correlated with hepatic steatosis. In contrast, genes that are known to promote NASH through proinflammatory and profibrotic signaling (e.g., NLRP3 and TGFB1) were significantly upregulated in both monkeys and individuals with NASH, and positively correlated with hepatic steatosis. Thus, by screening for NASH predisposed monkeys, utilizing a NASH diet, and combining biochemical, histological, and transcriptional analyses, a NASH model was established in cynomolgus monkeys that closely mimics the human disease.
Example 3
DT-109 Reverses Hepatic Steatosis and Prevents Inflammation and Fibrosis Progression in Nonhuman Primates with Established NASH
After 10 months on the diet and confirmation of established NASH, the monkeys were randomized to receive DT-109 or H2O (vehicle) for 5 additional months on the NASH diet (Figure 3A and 4A) . Through physical, biochemical, and histological (biopsy-based) assessments, we confirmed that all NASH-related parameters were comparable between the DT-109 and vehicle groups before initiating the intervention study. These included age (Figure 6A, p=0.9366) , body weight (Figure 6B, p=0.4519) , abdominal circumferences (Figure 6C, p=0.6632) , waist circumferences (Figure 6D, p=0.6435) , fasting glucose (Figure 6E, p>0.9999) , hemoglobin A1c (Figure 6F, p=0.5020) , total cholesterol (Figure 6G, p=0.5154) , triglycerides (Figure 6H, p=0.1836) , AST (Figure 6I, p=0.7524) , ALP (Figure 6J, p=0.7765) , histological scores (Figure 6K) of hepatic steatosis (p=0.4640) , lobular inflammation (p=0.5244) , hepatocellular ballooning (p=0.4737) , NAS (p>0.9999) , and hepatic fibrosis (p=0.6024) . The monkeys were next administered orally DT-109 at 150 mg/kg/d or H2O while on the NASH diet. DT-109 dose was chosen based on the optimal dose in the mouse studies (450 mg/kg/d, Figure 2) after accounting for allometric differences between species, body weight and surface area (Nair et al., 2016) . At the endpoint, no significant differences in body weight (Figure 5A) , abdominal circumferences (Figure 5B) , and waist circumferences (Figure 6L) were found between monkeys that were treated with DT-109 or vehicle. No significant differences were also found in glycemia (Figure 6M) and circulating lipid profile (Figure 6N and 6O) . Nevertheless, assessment of liver damage through circulating transaminases (Figure 7C-E) revealed a significant reduction in AST (p=0.0217) and ALP (p=0.0415) in monkeys treated with DT-109. Accordingly, gross morphology of the liver at the endpoint revealed marked yellowish coloration in the vehicle group which was attenuated by DT-109 treatment (Figure 7F) . Histological analyses (Figure 7G-I) confirmed that monkeys treated with DT-109 had significantly lower scores of hepatic steatosis (1.72±0.31 vs. 0.84±0.26, p=0.0307) , hepatocellular ballooning (1.81±0.07 vs. 1.50±0.16, p=0.0325) , overall 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) . Paired analysis comparing histological scores before and after treatment revealed that 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 months of the intervention study. These effects were prevented by DT-109 treatment which significantly reduced hepatic steatosis (p=0.0156) compared to the pre-treatment analysis. Together, these findings indicate that DT-109 ameliorates established NASH in nonhuman primates by reversing hepatic steatosis and preventing the progression of inflammation and fibrosis.
Example 4
Transcriptomics and Proteomics Uncover Induction of Hepatic Fatty Acid Degradation and Suppression of Proinflammatory/fibrotic Responses by DT-109
To elucidate the underlying mechanisms by which DT-109 ameliorates NASH in nonhuman primates, an unbiased, multiomics approach was applied combining transcriptomics, proteomics, metabolomics, and metagenomics (Figure 3A and 4A) . First, RNA-sequencing was performed on liver samples collected at the endpoint. Principal components analysis (PCA) revealed a clear separation between the transcriptome of livers from monkeys that were treated with DT-109 and those administered vehicle (Figure 8A) , with 575 DEGs significantly downregulated and 391 DEGs significantly upregulated by DT-109 (Figure 8B) . Analysis of the top 100 DEGs revealed that key genes regulating proinflammatory 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, whereas PPARGC1A, a master regulator of energy and fatty acid metabolism (Liang et al., 2006) , and other genes regulating fatty acid and cholesterol metabolism (e.g., CYP1A2) were significantly upregulated by DT-109 treatment (Figure 9A) . Accordingly, pathway enrichment analysis (Figure 8C and 8D) revealed that treatment with DT-109 induced opposite responses compared to those found in humans and monkeys with NASH (Figure 3H) . Particularly, pathways of glycine, serine and threonine metabolism as well as tryptophan metabolism, which were suppressed in NASH, were significantly upregulated in livers from monkeys that were treated with DT-109 together with upregulation of the fatty acid degradation pathway (Figure 8C) . Pathways of cytokine-cytokine receptor interaction, chemokine signaling, and ECM-receptor interaction, which were upregulated in NASH, were suppressed in livers from monkeys that were treated with DT-109 together with downregulation of focal adhesion and cell adhesion molecule pathways (Figure 8D) . The heatmap of NASH-related DEGs further underscored the effects of DT-109 on genes regulating fatty acid and cholesterol metabolism, inflammation and fibrosis during NASH (Figure 8E) . Next it was determined whether the observed transcriptional alternations were translated into functional processes underlying the protective effects of DT-109 during NASH. Through unbiased proteomics on liver samples collected at the endpoint, it was assessed whether the changes in DEGs are consistent at the protein level. Indeed, comparison of the top 100 DEGs to their corresponding proteins revealed prominent similarities (Figure 9B) . Accordingly, pathway enrichment analysis comparing the transcriptome and proteome data showed similar results, with fatty acid degradation and glycine, serine and threonine metabolism as the top pathways upregulated by DT-109, while chemokine signaling, focal adhesion, and ECM-receptor interaction were the top pathways downregulated (Figure 8F) . The consequence of these altered pathways was confirmed using histological and biochemical approaches (Figure 8G-L) . In line 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 livers from monkeys that were treated with DT-109, which was confirmed by biochemical analysis of hepatic triglycerides demonstrating a 30.1%reduction (p=0.0283, Figure 8I) . Furthermore, in line with the downregulation of the chemokine signaling pathway, immunohistochemical analysis of CD68, a marker of activated macrophages in NASH (Miura et al., 2012) , showed a significant reduction (76.3%, p=0.0138, Figure 8H and 8J) . In addition, in line with the reduced fibrosis score, the liver collagen content represented by hydroxyproline level in the liver is significantly decreased (p=0.0022, Figure 8K) . Also, in line with the upregulation of the glycine, serine, and threonine metabolic pathway and our recent reports (Rom et al., 2020; Rom et al., 2022) , a 3-fold (p=0.0174) increase in GSH was found in livers from monkeys that were treated with DT-109 (Figure 8L) . Thus, a combination of unbiased transcriptomics and proteomics together with histological and biochemical verification revealed that DT-109 induces fatty acid degradation and suppresses proinflammatory and fibrotic responses in nonhuman primates with established NASH.
Example 5
To further explore the metabolic mechanisms by which DT-109 ameliorates NASH in nonhuman primates, untargeted and targeted metabolomics were performed (Figure 10A) . PCA and orthogonal projections to latent structures discriminant analysis (OPLS-DA) indicated distinct metabolomes in serum from monkeys that were treated with DT-109 and those administered vehicle (Figure 10B and 10C) . Pathway analysis revealed a most significant enrichment in the bile acid (BA) biosynthesis pathway (Figure 10D) , with an overall decrease in circulating bile acids by DT-109 treatment (Figure 10E) . The untargeted metabolomics showed a significant reduction in various BAs 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 tauroursodeoxycholic acid/chenodeoxycholic acid (TU/CDCA, p=0.0216) . The most significant reduction was found in the secondary BA, lithocholic acid (LCA, 75.7%, p=0.0002) , which is known to induce hepatotoxicity (Staudinger et al., 2001) , together with its glycine (GLCA, 86.0%, P=0.0014) and taurine (TLCA, 74.7%, p=0.0038) conjugates (Figure 10F) . To validate the above findings, targeted metabolomics were performed for BAs confirming a most significant decrease in circulating LCA (68.3%, p=0.0007) in monkeys that were treated with DT-109 (Figure 10G) . Analysis of BA groups indicated a significant reduction in total circulating BAs (p=0.0079) with almost significant decrease in secondary BAs (p=0.0011) (Figure 10H) . Similar effects were found in the mouse model where mice with NASH that received vehicle demonstrated a significant increase in secondary BAs (3.1-fold, p=0.0002) , which were dose-dependently decreased by DT-109 treatment (Figure 11A) . Together, untargeted and targeted metabolomics revealed that treatment with DT-109 lowers circulating BAs during NASH with a most significant reduction in the secondary and hepatotoxic BA, LCA.
Example 6
DT-109 Alters the Gut Microbiome in Association with Lithocholic Acid
To explore the underlying mechanisms by which DT-109 regulates LCA metabolism, untargeted and targeted metabolomics were applied on liver and fecal samples combined with unbiased metagenomics. Untargeted metabolomics followed by PCA and OPLS-DA indicated distinct metabolomes in livers from monkeys that were treated with DT-109 and those administered vehicle (Figure 11B and 11C) , with a significant enrichment in the primary BA biosynthesis pathway as found using pathway enrichment analysis (Figure 11D) . However, targeted metabolomics revealed no significant differences in total (p=0.0990) , primary (p=0.0784) and secondary (p=0.0952) BAs as well as LCA (p=0.0952) in livers from monkeys that were treated with DT-109 or vehicle (Figure 11E and 11F) . Therefore, next a comprehensive analysis was performed of BA species in fecal samples. PCA, OPLS-DA, and heatmap-based representation revealed a clear separation between monkeys that were treated with DT-109 and those administered vehicle (Figure 12A-C) . LCA showed the highest concentrations in the fecal samples and was significantly decreased by DT-109 treatment (p=0.0175, Figure 12D) . Considering the key role of the gut bacteria in generating LCA through 7α-dehydroxylation of its precursor, CDCA (Funabashi et al., 2020; Staudinger et al., 2001; Yoshimoto et al., 2013) , next the effects of DT-109 on the gut microbiome were evaluated using 16S ribosomal RNA (rRNA) sequencing. Beta-diversity analysis using non-metric multidimensional scaling (NMDS) revealed distinct microbial compositions in monkeys that were treated with DT-109 and those administered vehicle (Figure 12E) . While analysis of operational taxonomic units (OTUs) and linear discriminant analysis (LDA) effect size (LEfSe) revealed no major differences at the phylum and class levels (Figure 13A and 13B) , significant differences were found mainly at the genus level (Figure 12F and 12G, Figure 13C) . Specifically, the genera Escherichia Shigella, Prevotella 7, Lysinibacillus, Pseudonocardia, Streptomyces, and Mycobacterium were decreased, while the genera Phascolarctobacterium, Eubacterium ruminantium group, Faecalibacterium, Lachnospiraceae UCG 010, Ruminococcaceae UCG 013, Eubacterium hallii group, Eubacterium eligens group, Erysipelotrichaceae UCG 006, and Pseudoxanthomonas were increased by DT-109 treatment (Figure 12G, Figure 13C) . To identify bacteria related to the severity of NASH and LCA metabolism, the relationship between the abundance of the above altered genera, NASH-related indices, and hepatic LCA concentrations was evaluated (Figure 12H) . Escherichia Shigella, a genus previously reported to be higher in patients with NAFLD and hepatic fibrosis (Shen et al., 2017) showed the most significant positive correlations with serum AST, NAS, and fibrosis score, as well as hepatic LCA. In contrast, Faecalibacterium, a genus composed mainly of the species Faecalibacterium prausnitzii, is known for its anti-inflammatory properties (Sokol et al., 2008) and its ability to lower hepatic steatosis in mice (Munukka et al. 2017) , showed the most significant inverse correlations with serum AST, NAS, fibrosis score, and hepatic LCA. These findings indicate that treatment with DT-109 during NASH modulates the gut microbiota in association with LCA metabolism and NASH severity.
Example 7
DT-109 Inhibits Microbial Production of Lithocholic Acid which is Independently Associated with NAFLD Risk in Humans
Next it was examined whether DT-109 inhibits LCA production through modulation of the gut microbiota. First, through independent qPCR analyses, it was confirmed that Faecalibacterium prausnitzii, a butyrate-producing bacteria (Zhang et al., 2019) , was significantly increased (2.7-fold, p=0.0432, Figure 14A) , while Escherichia Shigella was markedly decreased (92.9%, p=0.0435, Figure 14B) in fecal samples from monkeys that were treated with DT-109. Next, isotope-labeled CDCA, the precursor for LCA, was used to assess the effects of DT-109 on the microbial generation of LCA. Fecal samples were incubated with d4-CDCA with or without increasing concentrations of DT-109 (0-500 μM at equal volumes) , and levels of the newly generated d4-LCA were measured by mass spectrometry. DT-109 treatment dose-dependently decreased the formation of LCA by up to 53.3% (p<0.0001) with 500 μM of DT-109 (Figure 14C) . To test whether increased Faecalibacterium prausnitzii by DT-109 treatment could account for the inhibition of LCA production, fecal samples were incubated with d4-CDCA with the addition of Faecalibacterium prausnitzii or equal volume of Gifu anaerobic medium (control) , and the newly generated d4-LCA was monitored for up to 24 h. Faecalibacterium prausnitzii significantly decreased the formation of LCA starting from 4 h of incubation (Figure 14D) . Furthermore, to test whether this effect is specific to butyrate-producing bacteria, next the effect of another known butyrate-producing g-positive bacteria, Roseburia rectibacter (Duncan et al., 2006) , and that of Escherichia coli, a non-butyrate-producing bacteria (Clark, 1989) , on LCA formation was evaluated. While Roseburia rectibacter significantly decreased LCA formation after 16 h of incubation (Figure 13D) , Escherichia coli had no significant effects (Figure 13E) . Nevertheless, analysis of various butyrate-producing bacteria in fecal samples from monkeys with NASH, including Roseburia (Duncan et al., 2006) , Blautia (Ye et al., 2020) , and Clostridium (Stoeva et al., 2021) , revealed that DT-109 treatment significantly and specifically increased the abundance of Faecalibacterium prausnitzii without altering other butyrate-producing bacteria (Figure 14A and Figure 13F) .
Finally, to establish the clinical relevance of lowering LCA, targeted metabolomics were applied to measure circulating LCA in patients with NAFLD (n=149) compared to healthy controls (n=229) . Patients with NAFLD had significantly higher levels of circulating AST and ALT, were older, included more males, and had aggravated dyslipidemia and hyperglycemia (Table S2) . In the Table, continuous variables are expressed as median (interquartile range 25–75%) and were compared with t test or Mann-Whitney U test depending on normality tests. Categorical variables are expressed as numbers (percentages) and were compared by χ2 test.
Table S2: Characteristics of the Participants with or without NAFLD
In line with consistent reports indicating a positive correlation between LCA and NAFLD severity, its hepatotoxic effects (Chen et al., 2020; Grzych et al., 2020; Kwan et al., 2020; Staudinger et al., 2001) , and our findings in nonhuman primates, circulating LCA was significantly increased in patients with NAFLD (p=0.022, Figure 14E) . Importantly, after adjustment for age and sex, circulating LCA was positively associated with the risk of NAFLD (odds ratio, OR: 1.36; 95%CI: 1.06, 1.75, per standard deviation increment; p=0.015, Table S3, Model 1) . Elevated LCA was also found to be an independent predictor of NAFLD after further adjusting for triglycerides (OR: 1.31; 95%CI: 1.01, 1.70, per standard deviation increment; p=0.046, Table S3, Model 2) , and the association remained significant after further adjustment for fasting glucose and HDL-cholesterol (OR: 1.29; 95%CI: 1.01, 1.68, per standard deviation increment; p=0.049; Table 2, Table S3, Model 3) .
Table S3: Odds Ratio of NAFLD Risk According to Circulating Lithocholic Acid
³ Model 3: further adjusted for HDL-cholesterol and fasting glucose based on model 2 Lithocholic acid, LCA; Odds ratio, OR; Confidence interval, CI; Standard deviation, SD.
These findings indicate that DT-109 modulates the gut microbiota to enhance Faecalibacterium prausnitzii, which inhibits the production of LCA, a hepatotoxic BA that is increased in patients with NAFLD and independently associated with the risk of NAFLD.
Example Summary
Oral administration of DT-109 dose-dependently reduced steatohepatitis and hepatic fibrosis. 450 mg/kg/d was the most efficient dose in mice. Based on allometric differences between mice and cynomolgus monkeys, body weight and surface area (Nair et al., 2016) , the efficacy and safety of DT-109 administered orally at 150 mg/kg/d to nonhuman primates was tested. Considering that the above doses effectively lowered steatohepatitis and hepatic fibrosis in both mice and nonhuman primates with established NASH, together with a 12.3 dose conversion factor between mice and humans, and a 1.8- 6.2 conversion factor between different nonhuman primates and humans (Nair et al., 2016) , a range of 24-83 mg/kg/d of DT-109 is contemplated to be beneficial in treating human NAFLD/NASH patients.
Beyond the histopathological similarities, prominent transcriptional similarities between the nonhuman primate model and human NASH were observed. Consistent with the well-established induction of inflammatory, immune and fibrotic signaling pathways in NASH (Loomba et al., 2021) , transcriptomic analysis revealed a significant upregulation of pathways related to cytokine-cytokine receptor interaction, chemokine signaling, and ECM-receptor interaction in livers from both monkeys and humans with NASH. Key genes regulating the inflammatory (e.g., NLRP3, Mridha et al., 2017) and fibrotic (e.g., TGFB1, Seki et al., 2007) responses were upregulated in both monkeys and humans with NASH and positively correlated with hepatic steatosis. In contrast, PPARA, which encodes a master regulator of fatty acid degradation and is known for its protective role in NASH (Montagner et al., 2016) , was downregulated in both monkeys and humans and inversely correlated with hepatic steatosis. Beyond those well-established pathways, the findings herein support the involvement of recently 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 impaired glycine metabolism as a causative factor and therapeutic target in 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 pathway was most significantly suppressed in both monkeys and humans with NASH. Importantly, treatment with DT-109 of monkeys with NASH reversed the above transcriptional alternations and downregulated the cytokine-cytokine receptor interaction, chemokine signaling, and ECM-receptor interaction pathways while upregulating the glycine, serine, and threonine metabolism and fatty acid degradation pathways.
The pathogenesis of NASH is complex involving hepatic and extrahepatic mechanisms. Potential points of intervention, therefore, include metabolic, antioxidant, anti-inflammatory, antifibrotic, and liver-gut axis targets (Vuppalanchi et al., 2021) . Here, unbiased metabolomics were used to uncover the mechanisms by which DT-109 ameliorates NASH beyond hepatic fatty acid degradation and GSH formation. That untargeted approach, validated by targeted metabolomics, revealed a significant reduction in circulating BAs in monkeys with NASH that were treated with DT-109, with a most significant decrease in the secondary BA, LCA. Circulating BAs are consistently reported to be higher in patients with NASH, and a positive correlation between LCA and NAFLD severity has been described (Chen et al., 2020; Grzych et al., 2020; Kwan et al., 2020) . In line, a significant increase in circulating LCA was found among 149 patients with NAFLD compared to 229 healthy controls. After adjusting for potential confounders, circulating LCA was found to be positively associated with NAFLD. LCA is primarily formed in the intestine by bacterial 7α-dehydroxylation of CDCA and is known for its hepatoxic effects (Staudinger et al., 2001) . DCA, another secondary BA that was decreased by DT-109 treatment, was previously shown to cause obesity-associated hepatocellular carcinoma through the activation of hepatic stellate cells. Blocking DCA production prevented hepatocellular carcinoma in obese mice (Yoshimoto et al., 2013) , indicating the therapeutic potential of inhibiting secondary BA production by the gut microbiota in liver diseases. Indeed, using targeted metabolomics and metagenomics, fecal LCA was found to be significantly decreased by DT-109 treatment. DT-109 caused a shift in the gut microbiota composition and decreased the abundance of Escherichia Shigella, which was reported to be higher in patients with NAFLD and hepatic fibrosis (Shen et al., 2017) , and was positively correlated with NASH severity and hepatic LCA. In contrast, without altering other butyrate-producing bacteria, DT-109 significantly increased the abundance of Faecalibacterium prausnitzii, which is known for its anti-inflammatory properties (Sokol et al., 2008) , and was inversely correlated with NASH severity and hepatic LCA. Through isotope-labeling experiments, DT-109 was demonstrated to enhance Faecalibacterium prausnitzii, which directly inhibits microbial production of LCA. The translational value of these findings is supported by previous reports indicating that lower fecal abundance of Faecalibacterium prausnitzii is associated with increased hepatic steatosis in humans (Munukka et al. 2017) and that treatment with Faecalibacterium prausnitzii lowers AST, ALT, and hepatic steatosis while activating fatty acid degradation in mice (Munukka et al., 2014) . Treatment with DT-109 during NASH modulates the gut microbiota to enhance Faecalibacterium prausnitzii, which in turn inhibits the production of LCA, a hepatotoxic BA that is associated with NAFLD risk.
The data herein indicate the therapeutic potential of DT-109 in the clinic. First, DT-109 treatment was found to be safe with no toxic effects noted at all doses tested in vivo and in vitro. Second, while NAFLD is associated with an increased risk of liver-related mortality, the most common cause of death in patients with NAFLD is atherosclerotic cardiovascular disease (Duell et al., 2022) . The most advanced drug candidate for NASH to date (obeticholic acid, Younossi et al., 2019a) exacerbates atherogenic dyslipidemia, raising concerns regarding its cardiovascular consequences in this group of patients already at increased cardiovascular risk (Siddiqui et al., 2020) . DT-109, unlike other NASH drug candidates, has a cardioprotective effect. Third, the data herein indicate that DT-109 ameliorates NASH through multiple mechanisms including induction of hepatic fatty acid degradation and GSH biosynthesis as well as modulation of microbial BA metabolism, which is consistent with the complex pathogenesis of NASH and the need to target multiple pathways. Altogether, these support the use of DT-109 either as a monotherapy or a combined regimen with other drug candidates including, but not limited to, Faecalibacterium prausnitzii.
Documents
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Claims

A method of treating a metabolic, cardiovascular, inflammatory or oncological disease in a subject comprising administering to the subject a Gly-Gly-Leu tripeptide and a Faecalibacterium.
The method of claim 1 wherein the Faecalibacterium is Faecalibacterium prausnitzii.
The method of any preceding claim wherein the disease is a hepatic disease.
The method of claim 3 wherein the hepatic disease is nonalcoholic fatty liver disease (NAFLD) .
The method of claim 3 wherein the disease is nonalcoholic steatohepatitis (NASH) .
The method of claim 3 wherein the treatment lowers, or inhibits the progression of, hepatic steatosis, lobular inflammation, hepatocellular ballooning, NAFLD activity score (NAS) and/or fibrosis score.
The method of claim 1 or 2 wherein the disease is a biliary disease.
The method of claim 7 wherein the disease is primary biliary cirrhosis.
The method of claim 7 wherein the disease is biliary cholangiatis.
The method of any preceding claim wherein the treatment reduces the production of one or more secondary bile acids in the subject.
The method of claim 10 wherein the production of lithocholic acid is reduced.
The method of any preceding claim wherein the treatment decreases the abundance of Escherichia Shigella in the gut of the subject.
The method of any preceding claim wherein the subject is a primate.
The method of claim 13 wherein the primate is a human.
The method of claim 14 wherein about 1 to about 500 mg/kg/day of Gly-Gly-Leu tripeptide is administered to the subject.
The method of claim 14 wherein about 3 to about 144 mg/kg/day of Gly-Gly-Leu tripeptide is administered to the subject.
The method of claim 14 wherein about wherein about 1 to about 100 mg/kg/day of Gly-Gly-Leu tripeptide is administered to the subject.
The method of claim 14 wherein about wherein about 12 to about 36 mg/kg/day of Gly-Gly-Leu tripeptide is administered to the subject.
The method of claim 14 wherein about wherein about 37.5 mg/kg/day of Gly-Gly-Leu tripeptide is administered to the subject.
The method of any preceding claim wherein the Gly-Gly-Leu tripeptide is administered orally.
The method of any preceding claim wherein the Gly-Gly-Leu tripeptide is administered in a single dose.
A method of reducing the production of one or more secondary bile acids in a subject comprising administering to the subject a Gly-Gly-Leu tripeptide and a Faecalibacterium.
The method of claim 22 wherein the production of lithocholic acid is reduced.
The method of claim 22 wherein the subject is a primate.
The method of 24 wherein the primate is a human.
The method of claim 25 wherein about 1 to about 500 mg/kg/day of Gly-Gly-Leu tripeptide is administered to the subject.
The method of claim 25 wherein about 3 to about 144 mg/kg/day of Gly-Gly-Leu tripeptide is administered to the subject.
The method of claim 25 wherein about wherein about 1 to about 100 mg/kg/day of Gly-Gly-Leu tripeptide is administered to the subject.
The method of claim 25 wherein about wherein about 12 to about 36 mg/kg/day of Gly-Gly-Leu tripeptide is administered to the subject.
The method of claim 25 wherein about wherein about 37.5 mg/kg/day of Gly-Gly-Leu tripeptide is administered to the subject.
The method of any of claim 22-30 wherein the Gly-Gly-Leu tripeptide is administered orally.
The method of any of claims 22-31 wherein the Gly-Gly-Leu tripeptide is administered in a single dose.

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