Therapeutic Agents for Metabolic Disorders

Abstract

Provided herein are targets for the treatment of metabolically-related diseases, such as metabolically-related fatty liver disease (MAFLD). Also provided are agents for the treatment of said diseases and methods of using said agents.

Description

[Technical Field]

[0001] Provided herein are targets for the treatment of metabolic-associated diseases, such as metabolism-associated fatty liver disease (MAFLD). Also provided are agents for the treatment of said diseases and methods of using said agents. [Background technology]

[0002] In mammals, 95% of multi-exon genes undergo one or more alternative splicing (AS) events to generate multiple isoforms (Pan, Q., Shai, O., Lee, LJ, Frey, BJ & Blencowe, BJ Deep survey of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet 40, 1413-1415 (2008). https: / / doi.org:10.1038 / ng.259, Wang, ET et al. Alternative isoform regulation in human tissue transcriptomes. Nature 456, 470-476 (2008). https: / / doi.org:10.1038 / nature07509), contributing to transcript diversity and complexity (Blencowe, BJ Reflections for the 20th anniversary issue of RNA journal. RNA 21, 573-575 (2015). https: / / doi.org:10.1261 / rna.051003.115).AS is a tissue-specific protein interaction network (Buljan, M. et al. Tissue-specific splicing of disordered segments that embed binding motifs rewires protein interaction networks. Mol Cell 46, 871-883 (2012). https: / / doi.org:10.1016 / j.molcel.2012.05.039, Ellis, JD et al. Tissue-specific alternative splicing remodels protein-protein interaction networks. Mol Cell 46, 884-892 (2012). https: / / doi.org:10.1016 / j.molcel.2012.05.037, Yang, X. et al. Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing. Cell 164, 805-817 (2016). https: / / doi.org:10.1016 / j.cell.2016.01.029) and tissue identity (Yang, X. et al. Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing. Cell 164, 805-817 (2016). https: / / doi.org:10.1016 / j.cell.2016.01.029). In contrast, whether specific AS programs regulate physiological adaptations is less clear, and their role in metabolic diseases is unknown. This is due to the insufficient functional characterization of specific isoforms and the technical challenges of identifying specific upstream regulatory splicing factors in vivo.As a result, there is limited information about the splicing networks involved in metabolic reprogramming, both at the level of splicing factors and the isoforms they regulate. In addition to increasing our knowledge of metabolic regulation in health and disease, characterization of the splicing factors and isoforms involved in metabolic regulation may lead to the development of RNA-based therapeutics that enhance or antagonize specific isoforms. RNA-based therapeutics that inactivate specific genes (e.g., APOB or PCSK9) in the liver have been shown to be effective in treating metabolic conditions (Raal, FJ et al. Mipomersen, an apolipoprotein B synthesis inhibitor, for lowering LDL cholesterol concentrations in patients with homozygous familial hypercholesterolemia: a randomized, double-blind, placebo-controlled trial. Lancet 375, 998-1006 (2010). https: / / doi.org:10.1016 / S0140-6736(10)60284-X, Ray, KK et al. Inclisiran in Patients at High Cardiovascular Risk with Elevated LDL Cholesterol. N Engl J Med 376, 1430-1440 (2017). https: / / doi.org:10.1056 / NEJMoa1615758) has emerged as a promising therapeutic strategy for HIV-1-associated leukemia (HIV-1-associated leukemia). However, the development of splice-switching RNA therapeutics has yet to be explored.

[0003] In parallel with the global rise in obesity, metabolic associated fatty liver disease (MAFLD) has become the most common non-communicable liver disease, affecting up to 25% of the population worldwide (Eslam, M., Sanyal, AJ, George, J. & International Consensus, P. MAFLD: A Consensus-Driven Proposed Nomenclature for Metabolic Associated Fatty Liver Disease. Gastroenterology 158, 1999-2014 e1991 (2020). https: / / doi.org:10.1053 / j.gastro.2019.11.312). MAFLD ranges from pre-symptomatic hepatic steatosis (fatty liver) to non-alcoholic steatohepatitis (NASH), which is characterized by additional inflammation, hepatocellular injury, and fibrosis, and can progress to liver failure, cirrhosis, and hepatocellular carcinoma (HCC) (Friedman, SL, Neuschwander-Tetri, BA, Rinella, M. & Sanyal, AJ Mechanisms of NAFLD development and therapeutic strategies. Nat Med 24, 908-922 (2018). https: / / doi.org:10.1038 / s41591-018-0104-9).

[0004] Although the exact mechanisms that drive the progression of steatosis to NASH are not fully understood, evidence suggests that chronic overnutrition and a high-calorie Western diet play a role. This is in part due to dysregulation of bioactive and / or toxic lipid species such as phospholipids, saturated fatty acids, sphingomyelin, ceramides, and cholesterol (Turpin-Nolan, SM & Bruning, JC The role of ceramides in metabolic disorders: when size and localization matters. Nat Rev Endocrinol 16, 224-233 (2020). https: / / doi.org:10.1038 / s41574-020-0320-5, Hall, Z. et al. Lipid zonation and phospholipid remodeling in nonalcoholic fatty liver disease. Hepatology 65, 1165-1180 (2017). https: / / doi.org:10.1002 / hep.28953, Ioannou, GN The Role of Cholesterol in the Pathogenesis of NASH. Trends Endocrinol Metab 27, 84-95 (2016). https: / / doi.org:10.1016 / j.tem.2015.11.008).Furthermore, there is evidence that MAFLD contributes to the development of type 2 diabetes and cardiovascular disease, with coronary artery disease being the leading cause of death in these patients (Corey, KE & Chalasani, N. Management of dyslipidemia as a cardiovascular risk factor in individuals with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol 12, 1077-1084; quiz e1059-1060 (2014). https: / / doi.org:10.1016 / j.cgh.2013.08.014; Collaborators, GBDO et al. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. N Engl J Med 377, 13-27 (2017). https: / / doi.org:10.1056 / NEJMoa1614362). Due to the unmet clinical need in MAFLD, there is growing interest in understanding the molecular mechanisms linking MAFLD to increased cardiovascular risk and progressive liver damage in order to identify new therapeutic targets. [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] Pan, Q., Shai, O., Lee, LJ, Frey, BJ & Blencowe, BJ Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet 40, 1413-1415 (2008). https: / / doi.org:10.1038 / ng.259 [Non-patent document 2] Wang, ET et al. Alternative isoform regulation in human tissue transcriptomes. Nature 456, 470-476 (2008). https: / / doi.org:10.1038 / nature07509 [Non-patent document 3] Blencowe, BJ Reflections for the 20th anniversary issue of RNA journal. RNA 21, 573-575 (2015). https: / / doi.org:10.1261 / rna.051003.115 [Non-patent document 4] Buljan, M. et al. Tissue-specific splicing of disordered segments that embed binding motifs rewires protein interaction networks. Mol Cell 46, 871-883 (2012). https: / / doi.org:10.1016 / j.molcel.2012.05.039 [Non-patent document 5] Ellis, JD et al. Tissue-specific alternative splicing remodels protein-protein interaction networks. Mol Cell 46, 884-892 (2012). https: / / doi.org:10.1016 / j.molcel.2012.05.037 [Non-patent document 6] Yang, X. et al. Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing. Cell 164, 805-817 (2016). https: / / doi.org:10.1016 / j.cell.2016.01.029 [Non-Patent Document 7] Raal, F. J. et al. Mipomersen, an apolipoprotein B synthesis inhibitor, for lowering of LDL cholesterol concentrations in patients with homozygous familial hypercholesterolaemia: a randomised, double-blind, placebo-controlled trial. Lancet 375, 998-1006 (2010). https: / / doi.org:10.1016 / S0140-6736(10)60284-X

Non-Patent Document 8

Non-Patent Document 9

Non-Patent Document 10

[0006] In one embodiment, an agent capable of inducing exon 12 skipping of Scarb1 (scavenger receptor class B type I) is provided. The agent can bind to the Scarb1 pre-mRNA. For example, the agent can bind to a site in the Scarb1 pre-mRNA that affects splicing of exon 12. The agent can be a nucleic acid analog or a nucleic acid. The agent can be an antisense oligomer.

[0007] In one embodiment, an antisense oligomer capable of inducing skipping of exon 12 of scavenger receptor class B type I (SCARB1) is provided. The antisense oligomer may be capable of inducing skipping of exon 12 of human SCARB1. The antisense oligomer may be 10 to 45 nucleobases, 12 to 40 nucleobases, 15 to 35 nucleobases, 18 to 30 nucleobases, or 19 to 25 nucleobases in length.

[0008] An antisense oligomer may comprise a nucleobase sequence set forth in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19, and may contain five, four, three, two, one, or fewer substitutions, deletions, or insertions. An antisense oligomer may comprise a nucleobase sequence set forth in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19, and may contain one or more nucleobases substituted with modified nucleobases capable of base pairing with nucleobases of the same type. An antisense oligomer may comprise a nucleobase sequence set forth in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19. An antisense oligomer may comprise a nucleobase sequence set forth in any one of SEQ ID NOs: 5, 8, 10, 11, 18, or 19. The nucleobase sequence of the antisense oligomer can be that set forth in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19.

[0009] The antisense oligomer may comprise at least one 2'-O-methyl nucleotide and / or at least one 2'-O-methoxyethyl nucleotide. The antisense oligomer may be a 2'-O-methyl nucleic acid oligomer and / or a 2'-O-methoxyethyl nucleic acid oligomer. The antisense oligomer may comprise at least one phosphorothioate internucleotide linkage. In some embodiments, all internucleotide linkages in the antisense oligomer are phosphorothioate internucleotide linkages.

[0010] In one embodiment, the antisense oligomer is an oligonucleotide and has the nucleobase sequence of SEQ ID NO: 5, 8, 10, 11, 18, or 19, and has -O-CH3 or -O-CH2-CH2-O-CH3 attached to the 2' position of the sugar moiety of each nucleotide.

[0011] Provided herein are antisense oligonucleotides having a sequence set forth in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19, wherein the internucleotide linkages are phosphorothioate internucleotide linkages and -O-CH3 or -O-CH2-CH2-O-CH3 is attached to the 2' position of the sugar moiety of each nucleotide.

[0012] Provided herein are pharmaceutical compositions comprising any of the antisense oligomers or antisense oligonucleotides disclosed herein.

[0013] Provided herein is any antisense oligomer, antisense oligonucleotide, or pharmaceutical composition disclosed herein for use as a pharmaceutical. Provided herein is any antisense oligomer, antisense oligonucleotide, or pharmaceutical composition disclosed herein for use in a method for treating or preventing a metabolic-related disease. Provided herein is any antisense oligomer, antisense oligonucleotide, or pharmaceutical composition disclosed herein for use in a method for treating or preventing the pathological effects of obesity and / or an obesogenic diet. The pathological effects may be liver inflammation, lipotoxicity, hepatocellular injury, and / or fibrosis. Provided herein is any antisense oligomer, antisense oligonucleotide, or pharmaceutical composition disclosed herein for use in a method for treating or preventing hepatitis. The hepatitis may be obesity-induced. Provided herein is any antisense oligomer, antisense oligonucleotide, or pharmaceutical composition disclosed herein for use in a method for treating or preventing metabolically-associated fatty liver disease (MAFLD). Provided herein is any antisense oligomer, antisense oligonucleotide, or pharmaceutical composition disclosed herein for use in a method for treating or preventing preclinical hepatic steatosis. Provided herein is any antisense oligomer, antisense oligonucleotide, or pharmaceutical composition disclosed herein for use in a method for treating or preventing non-alcoholic steatohepatitis (NASH). Provided herein is any antisense oligomer, antisense oligonucleotide, or pharmaceutical composition disclosed herein for use in a method for treating or preventing hepatocellular carcinoma (HCC) in a subject. The subject may have hepatitis, preclinical hepatic steatosis, or NASH.Provided herein is any antisense oligomer, antisense oligonucleotide, or pharmaceutical composition disclosed herein for use in the treatment or prevention of any one or a combination of gallstone disease, type 2 diabetes, cardiovascular disease, and coronary artery disease.

[0014] Provided herein is any antisense oligomer, antisense oligonucleotide, or pharmaceutical composition disclosed herein for use in a method of treatment, the method comprising lowering cholesterol levels in a subject in need thereof.

[0015] Provided herein is any method for increasing expression of scavenger receptor class B type I (Scarb1) isoform SR-BII relative to isoform SR-BI in a cell, the method comprising contacting the cell with a composition comprising an antisense oligomer or antisense oligonucleotide disclosed herein. The method can be in vivo, and the composition can be administered to a subject in need thereof. [Brief explanation of the drawings]

[0016] [Figure 1-1] ~ [Figure 1-4]Expression of the pre-mRNA splicing machinery is regulated by nutritional input to the liver. A. Schematic of the experimental design. Livers from HFD- or CD-fed mice were harvested in the fed (ad libitum) or fasted (16 h) state and processed for high-throughput TMT / MS (isobaric mass tagging) proteomics (n = 3) or RNAseq analysis (n = 4). B. Principal component analysis of TMT / MS analysis (top) and RNAseq analysis (bottom). C. Gene ontology analysis of differentially expressed proteins between fasted and fed states (top) and between HFD and CD livers (bottom). D. Analysis of differences in AS events between fasted and fed CD (black), HFD and CD (blue), and HFr and CD (red). The proportion of altered events within each comparison is represented in pie charts (right) (SE: skipped exon, MXE: mutually exclusive exon, RI: retained intron, A5SS: alternative 5' splice site, A3SS: alternative 3' splice site). E-G. - Enrichment of eCLIP crosslinks surrounding conserved AS events that are differentially regulated in each comparison in HepG2 cells from the ENCODE database. H. - Venn diagram showing differentially expressed splicing factors between HFD and CD obtained from RNAseq (yellow) and TMT / MS analysis (blue) and the overlap of splicing factors detected in primary hepatocytes (green). [Figure 2-1] ~ [Figure 2-2]RBFOX2 is a splicing factor expressed in the liver. A. Single-cell analysis of Rbfox2 expression in the liver. B. Western blot of LWT and LΔRbfox2 liver lysates showing RBFOX2 expression in hepatocytes. C. Western blot of C57BL6 liver lysates showing RBFOX2 expression in mice fed a CD, HFD, or HFr diet (n = 6 per condition; images show three representative samples). Right: Quantification of long and short RBFOX2 variants. D. Expression of RBFOX2 containing the full-length RRM motif quantified by TMT / MS (n = 3). Bar graphs are presented as mean ± SEM. Statistical significance was determined by one-way ANOVA (C) or two-tailed t-test (D) for biologically independent samples (*p < 0.05; ***p < 0.001). [Figure 3-1] ~ [Figure 3-5]RBFOX2 controls AS of lipid-regulating genes in the liver. A. Schematic depicting the experimental strategy to identify RBFOX2-regulated AS programs and isoforms for RNA therapeutics (sequence depicted is SEQ ID NO: 55). B. Enrichment of RBFOX2 motifs relative to eiCLIP-RBFOX2 cross-linked locations in mouse hepatocytes (n=3). C. RNA map showing normalized density of RBFOX2 eiCLIP cross-linked sites relative to the 5'SS and 3'SS of selected exons identified by RNAseq in the livers of LWT and LΔRbfox2 mice. D. GO molecular function analysis of RBFOX2-cross-linked genes in mouse liver visualized with REVIGO. Bubble size corresponds to the number of combined GO terms. Color corresponds to the overall score. E. GWAS of human genes cross-linked by RBFOX2 in hepatocytes. F. Schematic diagram of the Scarb1 gene showing the location of the RBFOX2 eiCLIP peak surrounding exon 12 (arrow). Analysis of Scarb1 exon 12 in liver by semiquantitative PCR and capillary electrophoresis, and quantification of AS in LWT and LΔRbfox2 mice (bottom). G.- Analysis of RBFOX2 regulation of Pla2g6 exon 10, (H) Numb exons 3 and 9, and (I) Osbpl9 exon 6. PSI values ​​are expressed as mean ± SEM (n = 6–8). Statistical significance was determined by a two-tailed t-test for biologically independent samples. [Figure 4-1] ~ [Figure 4-4]RBFOX2 regulates hepatic lipid homeostasis. A. Serum lipid analysis showing total cholesterol levels and (B.-) triglycerides in LWT and LΔRbfox2 mice fed CD and HFr diets. C. PCA plot of hepatic lipid profiles in LWT and LΔRbfox2 mice fed CD and HFr diets, measured by LC-MS. D. LC-MS lipidomics analysis showing total levels of indicated species normalized to tissue mass and PUFA / non-PUFA TG ratio (n=8). E. Schematic depicting the strategy for analysis of iPSC-derived human hepatocytes. F. RT-qPCR analysis showing RBFOX2 knockdown in human hepatocytes (n=6). G. Analysis of RBFOX2-mediated regulation of NUMB exon 3, (H) NUMB exon 9, (I) SCARB1 exon 12, (J) SEC31A exon 21, and (K) OSBPL9 exon 6. PSI values ​​are expressed as mean ± SEM (n = 6). (L) Lipidomic quantification of cholesteryl ester and (M) sphingomyelin accumulation following RBFOX2 knockdown in human hepatocytes (n = 5). Statistical significance was determined by two-tailed t-test for biologically independent samples (*p value < 0.05; **p value < 0.01). [Figure 5-1] ~ [Figure 5-5]Viral-mediated overexpression of RBFOX2-Δ6 and RBFOX2 WT in liver. A.- Schematic diagram (top) showing the AAV backbone used to overexpress RBFOX2-Δ6 (with a truncated RNA-binding motif RRM) or control GFP in liver, and representative Western blots showing expression levels in liver. B.- RT-qPCR expression analysis of codon-optimized RBFOX2-Δ6 in liver. C.- Quantification of the splice-in rate (PSI, percentage splice in) of Numb (exon 3), Osbpl9 (exon 6), Scarb1 (exon 12), and Sec31a (exon 21). D.- Schematic diagram (top) depicting the adenoviral backbone used to overexpress RBFOX2 wild-type or control GFP, and representative Western blots showing expression levels in hepatocytes. E. Capillary electrophoresis and quantification of splice-in fraction (PSI) of Numb (exon 3), Osbpl9 (exon 6), Scarb1 (exon 12), and Sec31a (exon 21) after RBFOX2 overexpression in hepatocytes (n = 6). F. LC-MS lipidomics analysis showing total levels of free cholesterol, cholesteryl esters, sphingomyelin, and ceramide normalized to liver tissue mass and PUFA / non-PUFA TG ratio in mice fed the HFr diet after transfection with pAd-RBFOX2 or pAd-GFP control (n = 8–9). G. Cholesterol levels quantified in bile from mice fed the HFr diet after transfection with pAd-RBFOX2 or pAd-GFP control (n = 8–9). H. Serum lipid analysis showing total cholesterol, HDL-cholesterol, and triglycerides in mice fed the HFr diet after transfection with pAd-RBFOX2 or pAd-GFP control (n=8-9). Results are shown as mean ± SEM. Statistical significance was determined by two-tailed t-test or Mann-Whitney test for biologically independent samples (***p<0.001). [Figure 6-1] ~ [Figure 6-2]Regulation of Rbfox2 transcription in the liver. A. CAGE-detected transcriptional start site (TSS) signals in the promoter of the RBFOX2 transcript in hepatocytes, aortic smooth muscle, and hippocampus. Two transcript isoforms are shown with their respective promoters. Clusters of tags are expanded to show ChIP-seq signals for FOXA1, FOXA2, H3K4me3, and H3K27ac. B. RT-qPCR of Foxa1, Foxa2, and Rbfox2 in Hepa1-6 cells expressing scrambled shRNA (shC) or shRNA against Foxa1 / 2 (shF1 / 2) (n=6). C. Microarray analysis of HepG2 cells overexpressing FOXA1 with adenovirus (GSE30447). Results are shown as mean ± SEM. Statistical significance was determined by a two-tailed t-test for biologically independent samples (***p<0.001). [Figure 7-1] ~ [Figure 7-4]Scarb1 mediates lipidomic changes associated with RBFOX2 deficiency in hepatocytes and can be regulated by splice-switching oligos. A. Mice fed the HFr diet were subcutaneously injected with SSO8.3, scrambled (Scr), or saline for four consecutive weeks (top). No significant effect of injections on body weight was detected (bottom). B. Semiquantitative PCR analysis of Scarb1 exon 12 inclusion in the liver (top) and quantification of the resulting total AS expressed as PSI (bottom). C. Immunohistochemistry showing reduced macrophage (anti-MRC1) infiltration in the liver of SSO8.3-treated mice. Nuclei were stained with DAPI. D. qPCR analysis of the liver of SSO8.3-treated mice (n=7-9). E.F. LC-MS lipidomic analysis showing total free cholesterol and sphingomyelin levels normalized to tissue weight in HFr-fed mice after injection of SSO8.3. G.- Quantification of cholesterol and phospholipids in bile from SSO8.3- and Scr-treated mice. H.- Blood analysis of SSO8.3- and Scr-treated mice showing total cholesterol and triglycerides. I.- Analysis of blood VLDL, LDL, and HDL lipoprotein composition. Samples were pooled into triplicates. J.- Schematic diagram (left) depicting the analysis of Dil-HDL uptake in AML12 hepatocytes expressing codon-optimized SR-BI or SR-BII after targeted inactivation of endogenous Scarb1 using specific siRNA or a scrambled control. Uptake quantified as Dil-positive cells after 4 h incubation with 0.1 μg / ml Dil-HDL (n=6). K.- Quantification of major lipid species in purified HDL lipoproteins from LΔRbfox2 and LWT mice fed the HFr diet and treated with SSO8.3 or Scr controls. L. - Cholesterol concentrations quantified in bile from LΔRbfox2 and LWT mice treated with SSO8.3 or Scr control, as indicated. Results are expressed as mean ± SEM (n = 7–10); statistical significance was determined by two-tailed t-test for biologically independent samples (*p < 0.05; **p < 0.01; ***p < 0.001). [Figure 8-1] ~ [Figure 8-2] Splicing factors differentially expressed in liver under specific metabolic conditions. Volcano plot showing the expression of splicing factors (gold) in the liver of mice fed or fasted, as determined by A.- TMT / MS analysis or B.- RNAseq analysis. C.- Expression of splicing factors in HFD- and CD-fed mice, as determined by TMT / MS and D.- RNAseq analysis. E.- Overlap between AS events differentially regulated during the feeding / fasting cycle in CD- or HFD-fed mice. F.- Enrichment of splicing factor motifs within and surrounding alternatively spliced ​​cassette exons in the liver of mice fasted and fed, and G.- HFD and CD. Enrichment in non-AS exons was used as background (dotted line). [Figure 9-1] ~ [Figure 9-2] Single-cell RNA-seq analysis of RNA-binding protein gene expression in the liver. Single-cell RNA-seq analysis of the expression of related AS factors in the liver. [Figure 10-1] ~ [Figure 10-3]Analysis of RBFOX2-mediated AS regulation in liver. A. NuPAGE gel visualizing protein-RNA complexes obtained by eiCLIP of hepatocytes. Lane 1: no antibody, 2: no UV, 3: 0.2 U / ml RNase, 4: 0.1 U / ml RNase, and 5: size-matched input. The region where the protein-RNA complex was excised from the membrane is marked with a dashed box. B. eiCLIP analysis confirms RBFOX2 crosslinking to Ptbp2 and C.- Snrnp70 pre-mRNA transcripts. D. Schematic depicting the position effect on RBFOX2 regulation of AS. E. Bubble plot showing significant AS events between LΔRbfox2 and LWT livers. Significant events are expressed as a percentage of total events in the pie chart (right). Selected transcripts with eiCLIP RBFOX2 crosslinking peaks are indicated. F. - eiCLIP track (top) showing RBFOX2 cross-linking and semi-quantitative PCR demonstrating that RBFOX2 promotes Sec31a exon 24 skipping. PSI values ​​are expressed as mean ± SEM (n = 6-8). Statistical significance was determined by a two-tailed t-test for biologically independent samples. G. - Cross-linking of RBFOX2 with PLA2G6, H.- SEC31A, I.- NUMB, and J.- SCARB1 pre-mRNA transcripts in human hepatocyte samples. [Figure 11-1] ~ [Figure 11-2]RBFOX2 is involved in regulating cholesterol homeostasis. A. - Weight gain over time in LWT and LΔRbfox2 animals fed CD, (B.-) HFD, and (C.-) HFr diets. D. - Glucose tolerance test in LWT and LΔRbfox2 fed CD, (E.-) HFD, and (F.-) HFr diets. G. - Blood analysis showing cholesterol levels and H. - triglycerides in LΔRbfox2 and LWT female mice. I. - H&E staining of livers from LΔRbfox2 and LWT mice fed an HFr diet. Scale bar 50 μm. J-M. - LC-MS / MS analysis of specific lipids in the livers of HFD-fed LΔRbfox2 and LWT mice. N. - Blood cholesterol and triglyceride levels in HFD-fed LΔRbfox2 and LWT mice. Results are presented as mean ± SEM (n = 8-9). Statistical significance was determined by two-way analysis of variance (A-F) or two-tailed t-test (G-N) of biologically independent samples (*p-value < 0.05; **p-value < 0.01). [Figure 12-1] ~ [Figure 12-2]RBFOX2 regulates lipid metabolism in human hepatocytes. A. RT-qPCR analysis of ASGPR2, SERPINA1, and SERPINA2 upon targeted knockdown of RBFOX2 in human hepatocytes (n=6). B. PCA plot of lipidomic analysis upon targeted knockdown of RBFOX2 in human hepatocytes (n=5). C. RT-qPCR analysis of genes involved in cholesterol and bile acid homeostasis in the livers of LΔRbfox2 and LWT mice fed the HFr diet (n=18-20). D. Representative Western blots showing APOB and ABCA1 expression in the livers of LΔRbfox2 and LWT mice (n=8). E-K. Bile acid levels in the livers of LΔRbfox2 and LWT mice fed the HFr or (L-U) HFD diets, as determined by LC-MS / MS. Samples were normalized by tissue weight and internal standard (n = 8). Results are expressed as mean ± SEM. Statistical significance was determined by two-tailed t-test of biologically independent samples (*p value < 0.05; **p value < 0.01; ***p value < 0.001). [Figure 13-1] ~ [Figure 13-4]Quantification of AS of direct RBFOX2 targets in mice fed CD, HFD, or HFr diets. A. - Quantification of the splice-in fraction (PSI) of Pla2g6 (exon 10), (B.-) Scarb1 (exon 12), (C.-) Numb (exon 3), (D.-) Numb (exon 9), (E.-) Sec31a (exon 21), and (F.-) Osbpl9 (exon 6) in LWT and LΔRbfox2 mice (n = 7-10) fed CD, HFD, or HFr diets. G. - Representative Western blot showing RBFOX2 expression levels in the liver of mice transduced with pAd-RBFOX2 or pAd-GFP control (left), and PCR / capillary electrophoresis quantification of the splice-in fraction (PSI) for Scarb1 (exon 12) (right) (n = 7-9). H. - ChIP-seq signal of FOXA1 at the Rbfox2 promoter in mouse liver. I. - Volcano plot showing LC-MS lipidomics analysis of LΔRbfox2 and LWT hepatocytes (n=5-6). J. - PCA plot of LΔRbfox2 and LWT hepatocytes and associated SSO treatments as determined by LC-MS lipidomics analysis. Results are shown as mean ± SEM. Statistical significance was determined by two-way ANOVA or two-tailed t-test for biologically independent samples (**p-value<0.01; ***p<0.001). [Figure 14-1] ~ [Figure 14-2]Role of RBFOX2 downstream targets in hepatocyte lipid metabolism. A.- Capillary electrophoresis and quantification of the splice-in fraction (PSI) of Numb (exon 9) in LWT and LΔRbfox2 hepatocytes upon treatment with SSO7.8 or Scr control. B.- Heatmap showing LC-MS metabolomic analysis of LWT and LΔRbfox2 hepatocytes upon treatment with SSO7.8 or Scr control. C.- Capillary electrophoresis and quantification of the splice-in fraction (PSI) of Sec31a (exon 21) in LWT and LΔRbfox2 hepatocytes upon treatment with SSO6.2 or Scr control. D.- Heatmap showing LC-MS metabolomic analysis of LWT and LΔRbfox2 hepatocytes upon treatment with SSO6.2 or Scr control. Results are shown as mean ± SEM. Statistical significance was determined by a two-tailed t-test of biologically independent samples (n = 5–6) (***p < 0.001). [Figure 15-1] ~ [Figure 15-2]Role of Osbpl9 and Pla2g6 isoforms in lipid metabolism. A.- Capillary electrophoresis and quantification of the splice-in rate (PSI) of Osbpl9 (exon 6) in LWT and LΔRbfox2 hepatocytes upon treatment with SSO11.1 or Scr control. B.- Heatmap showing LC-MS metabolomic analysis of LWT and LΔRbfox2 hepatocytes treated with SSO11.1 or Scr. C.- Western blot (top) showing PLA2G6 expression in wild-type and RBFOX2-deficient hepatocytes. Cryo-EM map of a PLA2G6 dimer showing the tight interaction of the catalytic domain (orange) of each monomer with the ankyrin repeats (purple) facing outward from the core. The ankyrin repeats face "like a claw" toward membrane phospholipids. Inset: Detailed structure of the region corresponding to exon 10 of Pla2g6L, a 55-amino acid intrinsically disordered proline-rich region at the interface between the ankyrin repeats and the catalytic domain, rotated 90 degrees. D. - Diagram showing the design of splice-switching oligos targeting alternative splicing of Pla2g6 in exon 10. SSO5.1 is designed to promote exon skipping (top), as verified by semiquantitative PCR analysis (bottom). E. - Quantification of the effect of SSO5.1 on the indicated lipid species, as determined by LC-MS. Results are presented as mean ± SEM (n = 5–6). Statistical significance was determined by a two-tailed t-test of biologically independent samples (*p-value < 0.05; ***p < 0.001). [Figure 16-1] ~ [Figure 16-3]Role of Scarb1 splicing variants in lipid metabolism. A. Splice-switching oligonucleotide (SSO8.3) promotes skipping of Scarb1 exon 12 in primary hepatocytes, as determined by semiquantitative PCR analysis. B. Volcano plot showing LC-MS lipidomics analysis of LΔRbfox2 hepatocytes treated with 100 nM SSO8.3 or Scr for 16 hours (n=5-6). C. Metabolomics analysis showing total ceramide levels, D. PUFA / non-PUFA TG ratio, E. total sphingomyelin levels, and F. total triglyceride levels (n=5-6). G-I. Heatmap showing LC-MS metabolomic analysis of LWT and LΔRbfox2 hepatocytes treated with SSO8.3 or Scr. J. Western blot showing SR-BI / II levels in liver after SSO8.3 treatment. K. - RT-qPCR expression analysis of potential off-target genes, such as Dscc1, (L.-) Kcnj16, and (M.-) Rab10, in the livers of mice treated with SSO8.3 or Scr. N. - Effect of SSO8.3 injection on circulating ALT and AST levels. P. - Liver / body weight ratio at the time of SSO8.3 injection (n = 7-10). Results are shown as mean ± SEM. Statistical significance was determined by one-way ANOVA or two-tailed t-test for biologically independent samples (*p < 0.05; **p < 0.01; ***p < 0.001). [Figure 17-1] ~ [Figure 17-3]In vivo SSO8.3 treatment promotes lipoprotein remodeling. A. Quantification of major lipid species in purified VLDL, B. LDL, and C. HDL lipoproteins from mice fed the HFr diet and treated with SSO8.3 or Scr control. Samples were pooled as triplicates. D. Representative Western blot analysis of lipogenic proteins in the livers of LWT and LΔRbfox2 mice treated with SSO8.3 or Scr (n = 9-10). E. Quantification of hepatic triglyceride content normalized to liver weight in mice injected with SSO8.3 or Scr control (n = 8-9). F. RT-qPCR expression analysis of endogenous Scarb1 gene knockdown in AML12 hepatocytes treated with siRNA against Rbfox2 or Scr control (n = 5). G. Absolute RT-qPCR expression analysis of codon-optimized Scarb1 isoforms in AML12 cells (n = 5). H.- Capillary electrophoresis and quantification of splice-in fraction (PSI) of Scarb1 (exon 12) (top) and Western blot analysis of protein levels (bottom) in LWT and LΔRbfox2 livers upon treatment with SSO8.3 or Scr control (n=8-9). I.- Quantification of hepatic triglyceride content normalized to liver weight in LWT and LΔRbfox2 mice upon treatment with SSO8.3 or Scr control (n=9-10). J.- Blood total cholesterol levels in LΔRbfox2 and LWT mice fed the HFr diet and treated with SSO8.3 or Scr control. K.- Quantification of major lipid species in purified LDL and (L)VLDL lipoproteins. Results are expressed as mean ± SEM; statistical significance was determined by two-tailed t-test of biologically independent samples (*p-value < 0.05; **p-value < 0.01, ***p-value < 0.001). [Figure 18]Activity of SSO8.4, SSO8.5, SSO8.6, and SSO8.7 in human hepatocytes. A. Schematic diagram showing the hybridization sites of the tested SSOs within the exon 12 locus. B. Human hepatocytes were transfected with 100 nM SSO for 6 h using Lipofectamine 2000. 24 h posttransfection, RNA was extracted and activity was quantified as PSI of SCARB1 exon 12. Scrambled oligo was used as a control. Results are presented as mean ± SEM (n = 3). [Figure 19] Activity of SSO8.5, SSO8.8, SSO8.9, SSO8.10, SSO8.11, and SSO8.12 in human hepatocytes. A. Schematic diagram showing the hybridization sites of the tested SSOs within the exon 12 locus. B. Human hepatocytes were transfected with 100 nM SSO for 6 h using Lipofectamine 2000. 24 h posttransfection, RNA was extracted and activity was quantified as PSI of SCARB1 exon 12. Scrambled oligo was used as a control. Results are presented as mean ± SEM (n = 3). [Figure 20-1] ~ [Figure 20-2]Activity of SSO8.5, SSO8.10, SSO8.11, SSO8.12, SSO8.13, SSO8.14, SSO8.15, SSO8.16, SSO8.17, SSO8.18, SSO8.19, SSO8.20, and SSO8.21 in Huh7 or HepG2 human hepatocytes. A. Schematic showing hybridization sites of the tested SSOs within the exon 12 locus. B. Schematic depicting chemical modifications introduced into the tested SSOs. C. Huh7 human hepatocytes were transfected with 100 nM SSO for 24 hours using Lipofectamine 2000. 24 hours posttransfection, RNA was extracted, and activity was quantified as PSI of SCARB1 exon 12. D. HepG2 human hepatocytes were transfected with 100 nM SSO for 24 hours using Lipofectamine 2000. RNA was extracted 24 hours after transfection and activity was quantified as PSI of SCARB1 exon 12. Scrambled oligo was used as a control. Results are presented as mean ± SEM (n = 3). [Figure 21-1] ~ [Figure 21-2] Analysis of efficacy and toxicity of SSO8.19 in human liver microtissues. A. - Analysis of SCARB1 exon 12 inclusion / skipping by PCR and capillary electrophoresis. B. - Quantification of exon 12 inclusion / skipping expressed as the splice-in ratio (PSI = exon 12 inclusion / (exon 12 inclusion + exon 12 skipping)). C-D. - Hepatotoxicity assessed as LDH release induced by increasing doses of SCARB1 (C), SSO8.18 (D), and chlorpromazine (E). Results are shown as mean ± SEM. [Figure 22-1] ~ [Figure 22-2]Anti-inflammatory effect of SSO8.18. A.- Schematic diagram showing the experimental setup for repeated treatments (20 μM). B.- Effect of SSO8.18 on CXCL10 (IP10) levels. C.- Schematic diagram showing the experimental setup for a single treatment (7.5 μM) for 48 h (top). Analysis of SCARB1 exon 12 inclusion / skipping by PCR and capillary electrophoresis (bottom) in these conditions. D.- Hepatotoxicity assessed as LDH release (7.5 μM). E.- Effect of SSO8.18 on CXCL10 (IP10) levels. Results are shown as mean ± SEM. Pairwise statistical comparisons between SCR and SSO8.18 were assessed by Student's t-test (***P<0.001). DETAILED DESCRIPTION OF THE INVENTION

[0017] We discovered that components of the pre-mRNA alternative splicing machinery are selectively regulated by metabolic inputs in the liver. We identified RNA-binding Fox protein 2 (RBFOX2) as a key splicing factor in the liver, regulating AS of a group of genes involved in lipid homeostasis. These include scavenger receptor class B type I (Scarb1), phospholipase A2 group VI (Pla2g6), clathrin vesicle adaptor Numb, a component of the COPII vesicle transport system, Sec31a, and oxysterol-binding protein-like 9 (Osbpl9). We demonstrate that RBFOX2 regulates AS in response to an obesogenic diet, in addition to promoting or antagonizing the expression of specific AS variants in the liver. We also demonstrate that this RBFOX2-regulated AS network could be a therapeutic target. Specifically, splice-switching oligonucleotides (SSOs) that modulate Scarb1 splicing reverse the accumulation of lipotoxic species in hepatocytes of RBFOX2-deficient mice, attenuate diet-induced obesity-associated liver inflammation in vivo, and promote an anti-atherogenic lipoprotein profile in the blood. These findings highlight the potential of isoform-specific RNA therapeutics for metabolic pathologies.

[0018] In one embodiment, an agent capable of inducing exon 12 skipping of scavenger receptor class B type I (Scarb1) is provided. The agent can bind to the Scarb1 pre-mRNA. For example, the agent can bind to a site in the Scarb1 pre-mRNA that affects the splicing of exon 12. The agent can be a nucleic acid analog or a nucleic acid. The agent can be an antisense oligomer.

[0019] A "nucleic acid analog" is a compound having a nucleobase sequence that mimics the nucleobase sequence of a nucleic acid containing a 2'-deoxyribose-5'-monophosphate or ribose-5'-monophosphate backbone, and the nucleic acid analog can form base pairs with a complementary nucleic acid. Examples of backbone moieties include amino acids such as peptide nucleic acids, glycol molecules such as glycol nucleic acids, threofuranosyl sugar molecules such as threose nucleic acids, morpholine rings and phosphorodiamidate groups such as morpholino, and cyclohexenyl molecules such as cyclohexenyl nucleic acids.

[0020] In one embodiment, an antisense oligomer capable of inducing skipping of exon 12 of scavenger receptor class B type I (SCARB1) is provided.

[0021] In the context of the present disclosure, an "antisense oligomer" is a molecule comprising subunits that contain a site capable of binding to a nucleobase. Thus, antisense oligomers can be designed to hybridize to a specific nucleic acid sequence. The subunits can be monomers, each of which contains a moiety capable of binding to a nucleobase. The moieties capable of binding to a nucleobase can bind by base-specific hydrogen bonding, such as Watson-Crick base pairing.

[0022] Antisense oligomers are sometimes referred to as antisense compounds, especially when the compounds are not necessarily synthesized from monomers.

[0023] The term "antisense" refers to a molecule that is at least partially complementary to a region of the sense strand of a nucleic acid. The antisense oligomers of the present disclosure are at least partially complementary to a region of the Scarb1 pre-mRNA and can bind to said region by hybridization. The degree of complementarity need not be strict, as long as the antisense oligomer and pre-mRNA can hybridize under physiological conditions. In some examples, the antisense oligomer and pre-mRNA can be complementary except for five, four, three, two, or one mismatch. In some examples, the antisense oligomer is fully complementary to a region of the pre-mRNA. In other examples, the antisense oligomer contains a region that is fully complementary to a region of the pre-mRNA, and the complementary region is of sufficient length to allow binding by hybridization.

[0024] Physiological conditions are conditions (such as temperature, pH, and concentrations of various ions) found in natural in vivo situations, or conditions corresponding to such conditions. For example, an antisense oligomer may bind by hybridization under intracellular conditions, such as those found in human cells. Physiological conditions may be conditions found in the liver during pre-mRNA splicing, e.g., the intracellular conditions of human hepatocytes. Confirmation of hybridization under physiological conditions may be performed in vitro, for example, at temperatures, pH, and salt concentrations that approximate intracellular conditions. In a specific example, an antisense oligomer may hybridize to Scarb1 pre-mRNA at 37°C, pH 7.4, and phosphate-buffered saline (e.g., containing 137 mM NaCl, 2.7 mM KCl, 10 mM NaHPO, and 1.8 mM KHPO). In all embodiments, the degree of hybridization is sufficient to induce exon skipping during splicing of the target gene in a subject.

[0025] Binding of the antisense oligomers disclosed herein to Scarb1 pre-mRNA can induce the skipping of exon 12 during splicing. Therefore, due to this activity, the antisense oligomers disclosed herein can be referred to as splice-switching oligonucleotides (SSOs). Upon binding to Scarb1 pre-mRNA, the SSOs disclosed herein increase the likelihood that exon 12 will be skipped during splicing. When exon 12 is skipped, it is not included in the resulting mRNA, and the polypeptide region encoded by exon 12 is absent from the translated protein. This effect is significant because inclusion of exon 12 of Scarb1 generates the classical SR-BI isoform, whereas skipping of this exon generates an alternative receptor variant with a different adaptor carboxy-terminal domain, designated SR-BII.

[0026] Splice switching activity can be detected by assays that determine whether a candidate antisense oligomer can increase the ratio of Scarb1 exon 12-non-containing mRNA to Scarb1 exon 12-containing mRNA in cells. The antisense oligomers of the present disclosure can increase the ratio of SR-BII to SR-BI expressed by cells. These effects can be quantified as the splice ratio (PSI, percentage splice), which can be expressed as the ratio of non-exon 12-skipped Scarb1 mRNA to total Scarb1 mRNA. The relevant calculation is therefore: PSI = exon 12 inclusion / (exon 12 inclusion + exon 12 skipping). A PSI of 100% represents a situation in which all Scarb1 mRNA contains exon 12 (i.e., no skipping is induced). Methods for measuring PSI are disclosed in the Examples section of this specification. For example, PSI can be measured by transfecting splice-switching candidate oligomers into Huh7 human hepatocytes, extracting RNA 24 hours later, and quantifying Scarb1 mRNA containing exon 12 and total Scarb1 mRNA (see Examples for details).

[0027] In some instances, the antisense oligomers of the present disclosure induce skipping of Scarb1 exon 12 such that the PSI is 90% or less, 80% or less, 70% or less, 60% or less, 50% or less, 40% or less, 30% or less, 20% or less, 10% or less, or 5.7% or less. In certain embodiments, the PSI is less than 40% (i.e., the antisense oligomer induced a 60% reduction in the PSI of SCARB1 exon 12).

[0028] Antisense oligomers can target cis-regulatory regions within the Scarb1 pre-mRNA (see Figure 18A). In some examples, the antisense oligomer targets the 3' splice site of Scarb1 exon 12. For example, the antisense oligomer is complementary to a region including the 3' end of exon 12 of the Scarb1 pre-mRNA. SSO8.5 and SSO8.21 are examples of such antisense oligomers (see Figure 20). In other examples, the antisense oligomer can target a region within exon 12 and thus hybridize to a region that does not include the 5' or 3' end of exon 12. SSO8.18 is an example of such an antisense oligomer (see Figure 20). The antisense oligomer can be capable of hybridizing to a region that overlaps with the region complementary to SSO8.18. For example, the antisense oligomer can be complementary to all 5, 10, 15, 16, 17, 18, 19, or 20 bases complementary to SSO8.18.

[0029] The sequence of the SCARBI gene can be as described for Gene ID: 949 on the NIH Identification Page, updated on August 12, 2022. The gene can be as described in Ensemble Gene: SCARB1 ensg00000073060.17.

[0030] The sequence of the SCARB1 pre-mRNA may be the sequence of human SCARB1 pre-mRNA. The sequence of the SCARB1 pre-mRNA may be that of SEQ ID NO:1.

[0031] The sequence of exon 12 of Scarb1 may be as follows: GAGAAATGCTATTTATTTTGGAGTAGTAGTAAAAAGGGCTCAAAGGATAAGGAGGCCATTCAGGCCTATTCTGAATCCCTGATGACATCAGCTCCCAAGGGCTCTGTGCTGCAGGAAGCAAAACTGTAG (SEQ ID NO: 2)

[0032] The antisense oligomer may comprise a nucleobase capable of base pairing with the nucleobase of the target nucleic acid. The antisense oligomer may comprise a nucleotide. The antisense oligomer may be or comprise a nucleic acid and / or a nucleic acid analog. The antisense oligomer may be or comprise an oligonucleotide or a polynucleotide. The antisense oligomer may be or comprise a phosphorodiamidate morpholino oligomer (PMO). The antisense oligomer may be or comprise a peptide nucleic acid (PNA).

[0033] In some examples, antisense oligomers contain at least 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, or 21 nucleobases. In some examples, antisense oligomers contain 45, 40, 35, 30, 29, 28, 27, 26, 25, 24, or 21 or fewer nucleobases. Antisense oligomers can contain 10-45, 12-40, 15-35, 18-30, or 19-25 nucleobases. Antisense oligomers can be 14-30, 15-29, 16-28, 17-27, 18-26, or 19-25 nucleobases in length. Antisense oligomers can be 14-24, 15-24, 16-24, 17-24, 18-24, or 19-24 nucleobases in length. In certain embodiments, the antisense oligomer is 21 nucleobases in length.

[0034] Antisense oligomers may contain one or more modified nucleosides; for example, the modification may be to the sugar moiety. In some instances, the 2' position of the sugar moiety may be modified. The modification may be to any portion that is not "-H" in the case of DNA or "-OH" in the case of RNA. Examples of such 2' modifications are -O-CH3 or -O-CH2-CH2-O-CH3; further examples are provided herein. In some instances, the 4' position of the sugar moiety may be modified, resulting in, for example, the formation of a bridge between the 2' and 4' positions. Antisense oligomers may contain one, two, three, four, or more types of nucleosides. Antisense oligomers may contain a combination of modified and unmodified nucleosides. Antisense oligomers may contain only modified nucleosides. The nucleotides of an antisense oligomer may all be modified in the same manner, or may be modified in two or more different manners.

[0035] The antisense oligomer may contain modifications in one or more internucleoside linkages. For example, the antisense oligomer may contain one or more phosphorothioate linkages. In some embodiments, all internucleotide linkages in the antisense oligomer are phosphorothioate linkages. The antisense oligomer may be or contain an oligonucleotide phosphorothioate. The antisense oligomer may contain one or more phosphorodiamidate linkages. In some embodiments, all intermonomer linkages in the antisense oligomer are phosphorodiamidate linkages.

[0036] The antisense oligomer may comprise one or more of deoxyribonucleotides, ribonucleotides, arabinonucleotides, 2'-fluoroarabinonucleotides (FANA), 2'-O-methyl (2'OMe) nucleotides, phosphorothioate 2'-O-methyl (PS-2'OMe) nucleotides, 2'-O-methoxyethyl (MOE) nucleotides, phosphorothioate 2'-O-methoxyethyl (PS-MOE) nucleotides, phosphorodiamidate morpholino monomers, locked nucleotides, P-alkylphosphonate nucleotides, threose nucleotides, hexitol nucleotides, 2' hydroxyhexitol nucleotides, cyclohexene nucleotides, 3' deoxy DNA (2'-5') nucleotides, peptide nucleic acid (PNA) residues, 2'-O,4'-C-ethylene bridged nucleotides, or any combination thereof.

[0037] Antisense oligomers include DNA oligomers, RNA oligomers, arabinonucleic acid (ANA) oligomers, 2'-fluoroarabinonucleic acid (FANA) oligomers, 2'-O-methylribonucleic acid (2'OMe) oligomers, phosphorothioate 2'-O-methylribonucleic acid (PS-2'OMe) oligomers, 2'-O-methoxyethyl (MOE) nucleic acid oligomers, phosphorothioate 2'-O-methoxyethyl (PS-MOE) nucleic acid oligomers, phosphorodiamidate morpholino oligomers (PMO), locked nucleic acid (LNA) oligomers, P-alkylphosphonate nucleic acid (phNA) oligomers, threose nucleic acid (TNA) oligomers, and hexitol nucleic acid (HNA) oligomers. The oligomers may be DNA oligomers, RNA oligomers, arabinonucleic acid (ANA) oligomers, 2'-fluoroarabinonucleic acid (FANA) oligomers, 2'-hydroxyhexitol (AtNA) oligomers, cyclohexene nucleic acid (CeNA) oligomers, 3'-deoxy-DNA (2'-5') oligomers, peptide nucleic acid (PNA) oligomers, 2'-O,4'-C-ethylene-bridged nucleic acid (ENA) oligomers, or any combination thereof, or may be DNA oligomers, RNA oligomers, arabinonucleic acid (ANA) oligomers, 2'-fluoroarabinonucleic acid (FANA) oligomers, 2'-hydroxyhexitol (AtNA) oligomers, cyclohexene nucleic acid (CeNA) oligomers, 3'-deoxy-DNA (2'-5') oligomers, peptide nucleic acid (PNA) oligomers, 2'-O,4'-C-ethylene-bridged nucleic acid (ENA) oligomers, or any combination thereof. acid) oligomers, 2'-O-methyl ribonucleic acid (2'OMe) oligomers, phosphorothioate 2'-O-methyl ribonucleic acid (PS-2'OMe) oligomers, 2'-O-methoxyethyl (MOE) nucleic acid oligomers, phosphorothioate 2'-O-methoxyethyl (PS-MOE) nucleic acid oligomers, phosphorodiamidate morpholino oligomers (PMO), locked nucleic acid (LNA) oligomers, P-alkylphosphonate nucleic acid (phNA) oligomers, threose nucleic acid (TNA,The oligonucleotide may include a 3'-deoxy-DNA (2'-5') oligomer, a 2'-hydroxyhexitol (AtNA) oligomer, a 2'-hydroxyhexitol (HNA) oligomer, a cyclohexene nucleic acid (CeNA) oligomer, a 3'-deoxy-DNA (2'-5') oligomer, a peptide nucleic acid (PNA) oligomer, a 2'-O,4'-C-ethylene-bridged nucleic acid (ENA) oligomer, or any combination thereof.

[0038] The antisense oligomer of the present disclosure can contain one or more naturally occurring nucleobases and / or one or more modified nucleobases.Modified nucleobases refer to nucleobases that can base pair with the nucleobase of nucleic acid, but are structurally different from naturally occurring nucleobases.An example of modified nucleobases is 5-methylcytosine.

[0039] Any antisense oligomer of the present disclosure may be present as a pharmaceutically acceptable salt, ester, salt of said ester, or hydrate of said antisense oligomer, and a reference to an antisense oligomer includes such compounds. Antisense oligomers of the present disclosure may be present as prodrugs.

[0040] The sequence of the scrambled oligonucleotide used in Example 8 is as follows: AAAUAAUUGAAUUUUAAAUA (SEQ ID NO: 3)

[0041] Examples of sequences complementary to Scarb1 pre-mRNA include: GGCCUGAAUGGCCUCCUUAUC (SEQ ID NO: 4) GGUACCCACCUACAGUUUUG (SEQ ID NO: 5) CAAAAUAAAUAGCAUUUCUC (SEQ ID NO: 6) GUGGCAACGCGGCAUGCAA (SEQ ID NO: 7) AGCAUUUCUCCUAGAAGAUA (SEQ ID NO: 8) UUGAGCCCUUUUUACUACUA (SEQ ID NO: 9) GAUGUCAUCAGGGAUUCAGA (SEQ ID NO: 10) GCACAGAGCCCUUGGGAGCU (SEQ ID NO: 11) ACCUACAGUUUUGCUUCCUG (SEQ ID NO: 12) ACAUAAGUACAAGCAUCUUCA (SEQ ID NO: 13) GGUUUUACACGGUUCUUCAA (SEQ ID NO: 14) GCUGAAGGAAUGAGCAGGAC (SEQ ID NO: 15) GCAUCUUCAGUCUGUAGACAC (SEQ ID NO: 16) CUGUCUUUCUAAUGUGACCU (SEQ ID NO: 17) CUUGGGAGCUGAUGUCAUCA (SEQ ID NO: 18) ACAGUUUUGCUUCCUGCAGCACAGA (SEQ ID NO: 19) CCACCUACAGUUUUG (SEQ ID NO: 20)

[0042] In the sequence listing, all "U"s have been replaced with "T"s in accordance with WIPO ST.26 requirements. Antisense oligomers of the present disclosure may contain uracil or thymine at these positions. In some embodiments, the nucleobases are as described above and include each uracil.

[0043] The antisense oligomers of the present disclosure may comprise or be set forth in any one of SEQ ID NOS: 4-20, which sequences include modifications including extensions, deletions, insertions, and substitutions, and the antisense oligomers are capable of inducing skipping of exon 12 of Scarb1. The antisense oligomers may be complementary to 5, 10, 15, 16, 17, 18, 19, 20, or all bases complementary to an antisense oligomer comprising any one of SEQ ID NOS: 4-20.

[0044] In one embodiment, an antisense oligomer of the present disclosure may comprise or be set forth in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19, which may contain five, four, three, two, one, or none substitutions, deletions, or insertions. In particular, the sequence may contain three, two, one, or none substitutions. In one embodiment, an antisense oligomer of the present disclosure may comprise or be set forth in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19. The antisense oligomer may comprise nucleotides containing 2'-O-methyl and / or 2'-O-methoxyethyl sugar moieties. The antisense oligomer may contain only 2'-O-methyl nucleotides and / or 2'-O-methoxyethyl nucleotides. The antisense oligomer may contain one or more phosphorothioate linkages. In some examples, all of the linkages in the antisense oligomer are phosphorothioate linkages.

[0045] In some embodiments, the antisense oligomer does not comprise additional nucleic acid sequences or similar nucleobases beyond those set forth in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19. In other embodiments, the antisense oligomer may comprise 1 nucleobase, 2 nucleobases, 3 nucleobases, 4 nucleobases, 5 nucleobases, 10 nucleobases, 15 nucleobases, 20 nucleobases, 25 nucleobases, 30 nucleobases, 35 nucleobases, 40 nucleobases, 45 nucleobases, or more nucleobases in addition to those set forth in i) any one of SEQ ID NOs: 4-20, ii) any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19, or iii) any one of SEQ ID NOs: 5, 8, 10, 11, 18, or 19.

[0046] In certain embodiments, an antisense oligomer of the present disclosure may comprise or be set forth in any one of SEQ ID NOs: 5, 8, 10, 11, 18, or 19, and may contain five, four, three, two, one, or none substitutions, deletions, or insertions. In particular, the sequence may contain three, two, one, or none substitutions. In certain embodiments, an antisense oligomer of the present disclosure may comprise or be set forth in any one of SEQ ID NOs: 5, 8, 10, 11, 18, or 19. The antisense oligomer may comprise 2'-O-methyl nucleotides and / or 2'-O-methoxyethyl nucleotides. The antisense oligomer may comprise only 2'-O-methyl nucleotides and / or 2'-O-methoxyethyl nucleotides. The antisense oligomer may comprise one or more phosphorothioate linkages. In some instances, the linkages within the antisense oligomer are all phosphorothioate linkages. In some embodiments, the antisense oligomer does not contain additional nucleic acid sequences or similar nucleobases beyond those set forth in any one of SEQ ID NOs: 5, 8, 10, 11, 18, or 19.

[0047] The antisense oligomer of the present disclosure may comprise or be represented by any one of the base sequences of SEQ ID NO: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19, and one or more of its nucleobases may be replaced with modified nucleobases. For example, one or more of the nucleobases of any one of SEQ ID NO: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19 may be replaced with modified nucleobases that retain the base pairing ability of the substituted nucleobase. For example, the cytosine of any one of SEQ ID NO: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19 may be replaced with 5-methylcytosine. Furthermore, any uracil in the sequences disclosed herein may be replaced with thymidine.

[0048] The antisense oligomer can be complementary to 5, 10, 15, 16, 17, 18, 19, 20, or all bases complementary to an antisense oligomer comprising any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19. The antisense oligomer can be complementary to 5, 10, 15, 16, 17, 18, 19, 20, or all bases complementary to an antisense oligomer comprising any one of SEQ ID NOs: 5, 8, 10, 11, 18, or 19.

[0049] In one embodiment, the antisense oligomer is not set forth in or does not include the sequence AGCCCUUGGGAGCUGAUGUCAUCAG (SEQ ID NO: 21) (US Patent Application Publication No. 2005 / 0244851(A1)).

[0050] Examples of antisense oligonucleotides are shown below. SCR [A*A*A*U*A*A*U*U*G*A*A*U*U*U*U*A*A*A*U*A] (Array number 35) SCR MOE<A*A*A*U*A*A*U*U*G*A*A*U*U*U*U*A*A*A*U*A> (SEQ ID NO: 36) SSO8.4 [G*G*C*C*U*G*A*A*U*G*G*C*C*U*C*C*U*U*A*U*C] (Array number 37) SSO8.5 [G*G*U*A*C*C*C*A*C*C*U*A*C*A*G*U*U*U*U*G] (Array number 38) SSO8.6 [C*A*A*A*A*U*A*A*A*U*A*G*C*A*U*U*U*C*U*C] (Array number 39) SSO8.7 [G*U*G*G*C*A*A*C*G*C*G*G*C*A*U*G*C*A*A] (SEQ ID NO: 40) SSO8.8 [A*G*C*A*U*U*U*C*U*C*C*U*A*G*A*A*G*A*U*A] (SEQ ID NO: 41) SSO8.9 [U*U*G*A*G*C*C*C*U*U*U*U*U*A*C*U*A*C*U*A] (SEQ ID NO: 42) SSO8.10 [G*A*U*G*U*C*A*U*C*A*G*G*G*A*U*U*C*A*G*A] (SEQ ID NO: 43) SSO8.11 [G*C*A*C*A*G*A*G*C*C*C*U*U*G*G*G*A*G*C*U] (SEQ ID NO: 44) SSO8.12 [A*C*C*U*A*C*A*G*U*U*U*U*G*C*U*U*C*C*U*G] (SEQ ID NO: 45) SSO8.13 [A*C*A*U*A*A*G*U*A*C*A*A*G*C*A*U*C*U*U*C*A] (SEQ ID NO: 46) SSO8.14 [G*G*U*U*U*U*A*C*A*C*G*G*U*U*C*U*U*C*A*A] (SEQ ID NO: 47) SSO8.15 [G*C*U*G*A*A*G*G*A*A*U*G*A*G*C*A*G*G*A*C] (SEQ ID NO: 48) SSO8.16 [G*C*A*U*C*U*U*C*A*G*U*C*U*G*U*A*G*A*C*A*C] (SEQ ID NO: 49) SSO8.17 [C*U*G*U*C*U*U*U*C*U*A*A*U*G*U*G*A*C*C*U] (SEQ ID NO: 50) SSO8.18 [C*U*U*G*G*G*A*G*C*U*G*A*U*G*U*C*A*U*C*A] (SEQ ID NO: 51) SSO8.19 [A*C*A*G*U*U*U*U*G*C*U*U*C*C*U*G*C*A*G*C*A*C*A*G*A] (SEQ ID NO: 52) SSO8.20 [C*C*A*C*C*U*A*C*A*G*U*U*U*U*G] (SEQ ID NO: 53) SSO8.21 <G*G*U*A*C*C*C*A*C*C*U*A*C*A*G*U*U*U*U*G> (SEQ ID NO: 54) Code: [2'oMe] <2'MOE> * phosphorothioate

[0051] In embodiments, the antisense oligomer of the present disclosure may comprise an antisense oligonucleotide exemplified above as SSO8.4, SSO8.5, SSO8.7, SSO8.8, SSO8.9, SSO8.10, SSO8.11, SSO8.12, SSO8.18, SSO8.19, or SSO8.21, or may be an antisense oligonucleotide exemplified above as SSO8.4, SSO8.5, SSO8.7, SSO8.8, SSO8.9, SSO8.10, SSO8.11, SSO8.12, SSO8.18, SSO8.19, or SSO8.21. The antisense oligomer may be any one of SEQ ID NOs: 35-54, or may comprise any one of SEQ ID NOs: 35-54. Optionally, any of these antisense oligonucleotides may contain five, four, three, two, one, or none of the substitutions, deletions, or insertions relative to the sequence. In particular, the sequences may contain 3, 2, 1, or none of the substitutions. Optionally, the antisense oligonucleotides may contain 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, or none of the modifications, e.g., one or more internucleotide linkages may be different from phosphorothioate linkages, or one or more nucleotides may have sugar moieties that are different from 2'-O-methyl or 2'-O-methoxyethyl nucleotides, respectively. In certain embodiments, the antisense oligomer of the present disclosure may comprise or be an antisense oligonucleotide exemplified above as SSO8.5, SSO8.8, SSO8.10, SSO8.11, SSO8.18, SSO8.19, or SSO8.21, wherein any uracil within the antisense oligonucleotide may be substituted with thymidine.

[0052] In some examples, the antisense oligomer of the present disclosure exists in an isolated form. An isolated antisense oligomer does not contain additional nucleobases complementary to the target pre-mRNA. However, an isolated antisense oligomer may contain additional components, such as peptides, lipids, sugar moieties, or modifications at the 5' or 3' end of the antisense oligomer. The bond between the antisense oligomer and any of the above components may be covalent or non-covalent. The antisense oligomer may be purified.

[0053] The antisense oligomer may be conjugated to one or more sugar moieties, such as monosaccharides, disaccharides, or oligosaccharides. The antisense oligomer may be glycosylated or glycosylated. In one example, the antisense oligomer is conjugated to at least one N-acetylgalactosamine (GalNac). GalNac may be involved in targeting the antisense oligomer to the liver of a subject.

[0054] The antisense oligomers of the present disclosure may be conjugated to one or more other agents, such as agents that facilitate delivery of the antisense oligomer to the relevant site. The antisense oligomer may be conjugated to an agent for delivering the antisense oligomer to a target organ such as the liver or gallbladder. The antisense oligomer may be conjugated to an agent for delivery of the antisense oligomer into cells, for example, an agent for facilitating the movement of the antisense oligomer across a membrane. The antisense oligomer may be non-covalently or covalently bound to one or more of the agents.

[0055] The antisense oligomers of the present disclosure may be present as part of an extracellular vesicle composition. For example, the antisense oligomers may be loaded into the lumen of exosomes or bound to components of exosomes. The antisense oligomers may be associated with monolayers, micelles, bilayers, lipid vesicles, or liposomes.

[0056] The antisense oligomer may be contained in a nanoparticle, e.g., a lipid nanoparticle composition. The antisense oligomer may be covalently or non-covalently linked to a peptide that facilitates cell entry, such as a cell-penetrating peptide. The cell-entering peptide may be a polycationic peptide, an amphipathic peptide, a hydrophobic peptide, a stapled peptide, or a stitched peptide.

[0057] The antisense oligomer may be part of a vector or may be encoded by a vector. Thus, the antisense oligomer may be delivered as part of a vector or by transcription from the vector. The vector may be in an extracellular vesicle such as an exosome, or a nanoparticle. Thus, in one embodiment, an extracellular vesicle or nanoparticle is provided that contains a vector encoding the antisense oligomer of the present invention.

[0058] In one aspect, a pharmaceutical composition is provided that comprises the antisense oligomer disclosed herein.The pharmaceutical composition can comprise a pharmaceutically acceptable vehicle, a pharmaceutically acceptable carrier, a pharmaceutically acceptable excipient, a pharmaceutically acceptable stabilizer, or a pharmaceutically acceptable preservative, or any combination thereof.To be pharmaceutically acceptable, a substance or a combination of substances must be suitable for formulation into a pharmaceutical composition or a medicament.

[0059] Pharmaceutical compositions may contain a therapeutically effective amount of an antisense oligomer of the invention. As used herein, phrases such as "therapeutically effective amount" and "effective amount" refer to the amount necessary to administer to a subject, or to a subject's cells, tissues, or organs, to achieve a therapeutic effect, such as an ameliorative effect or, alternatively, a curative effect. An effective amount is an amount sufficient to elicit the biological or medical response in a cell, tissue, system, animal, or human that is desired by a researcher, veterinarian, physician, or clinician.

[0060] In one aspect, there is provided an antisense oligomer or pharmaceutical composition of the present disclosure for use as a medicament.

[0061] In one embodiment, there is a method of treatment comprising administering a therapeutically effective amount of an antisense oligomer or pharmaceutical composition of the present disclosure to a subject in need thereof.

[0062] In one aspect, there is provided a use of an antisense oligomer or pharmaceutical composition of the present disclosure for the manufacture of a medicament.

[0063] The antisense oligomer or pharmaceutical composition of the present disclosure may be for use in treating or preventing a metabolic disease. For example, the antisense oligomer may be for treating or preventing the pathological effects of obesity and / or an obesogenic diet. The pathological effect may be hepatitis. The pathological effect may be lipotoxicity. In some examples, the antisense oligomer of the present disclosure is for use in reducing hepatocellular injury and / or fibrosis in a subject in need thereof.

[0064] The antisense oligomers or pharmaceutical compositions of the present disclosure can be used to reduce the level of lipotoxic species in hepatocytes. For example, the lipotoxic species can be ceramide, cholesterol, and / or sphingomyelin. In some examples, the antisense oligomers of the present disclosure can be used to promote an anti-atherogenic lipoprotein profile in the blood. An anti-atherogenic lipoprotein profile can be associated with a reduction in VLDL and triglycerides in plasma.

[0065] In some examples, the antisense oligomer or pharmaceutical composition of the present disclosure is for use in the treatment or prevention of hepatitis. For example, obesity-induced hepatitis. The antisense oligomer of the present disclosure may be for use in the treatment or prevention of metabolically-associated fatty liver disease (MAFLD). The antisense oligomer of the present disclosure may be for use in the treatment or prevention of preclinical hepatic steatosis (fatty liver), nonalcoholic steatohepatitis (NASH), liver failure, or hepatocellular carcinoma (HCC). In certain embodiments, the antisense oligomer of the present disclosure is for use in the treatment or prevention of NASH, wherein a therapeutically effective amount of the antisense oligomer is administered to a subject in need thereof. In another embodiment, the antisense oligomer may prevent, delay, or reduce the severity of HCC when HCC is associated with hepatitis, such as NASH. For example, a subject may have NASH and be at risk for HCC, and the antisense oligomer may reduce the risk of developing HCC. Alternatively, the subject may have NASH and HCC, and the antisense oligomer may reduce the severity of at least one symptom.

[0066] The antisense oligomer or pharmaceutical composition of the present disclosure may be for use in the treatment or prevention of cholelithiasis. The antisense oligomer may be used to lower the level of cholesterol in bile. The cholesterol level in bile may be lowered to an extent that reduces the risk of cholelithiasis or the severity of cholelithiasis.

[0067] The antisense oligomer or pharmaceutical composition can be used for the treatment or prevention of any one or combination of type 2 diabetes, cardiovascular disease, and coronary artery disease.The treatment of the pathological condition can be by reducing or preventing metabolic changes in the liver.For example, the treatment of MAFLD can reduce the risk or reduce the severity of type 2 diabetes, cardiovascular disease, or coronary artery disease.

[0068] The antisense oligomer or pharmaceutical composition can be used to reduce cholesterol levels in a subject in need thereof. For example, the subject may have hypercholesterolemia or MAFLD. The cholesterol level can be total cholesterol level, circulating cholesterol level, free cholesterol level, liver cholesterol level, intrahepatic cholesterol level, and / or biliary cholesterol level.

[0069] In one embodiment, a method for increasing the expression of SR-BII relative to SR-BI in a cell is provided. The method may include contacting the cell with a composition comprising an antisense oligomer of the present disclosure, or may include administering an antisense oligomer to a subject in need thereof. The level of SR-BII in liver cells may be increased. The method may be in vitro or in vivo.

[0070] In certain embodiments, an antisense oligonucleotide having the nucleobase sequence set forth in SEQ ID NO: 5 is provided for use in a method of treatment. The oligonucleotide may contain a modified nucleobase (e.g., 5-methylcytosine instead of cytosine). The oligonucleotide may contain at least one modified internucleotide linkage, such as a phosphorothioate internucleotide linkage. The oligonucleotide may contain one or more nucleotides having a modified sugar moiety, such as -O-CH3 or -O-CH2-CH2-O-CH3, attached to the 2' position of the sugar moiety. The method of treatment may be for the treatment of hepatitis. The method of treatment may be for NASH.

[0071] In certain embodiments, an antisense oligonucleotide having the nucleobase sequence set forth in SEQ ID NO: 11 is provided for use in a method of treatment. The oligonucleotide may contain a modified nucleobase (e.g., 5-methylcytosine instead of cytosine). The oligonucleotide may contain at least one modified internucleotide linkage, such as a phosphorothioate internucleotide linkage. The oligonucleotide may contain one or more nucleotides having a modified sugar moiety, such as -O-CH3 or -O-CH2-CH2-O-CH3, attached to the 2' position of the sugar moiety. The method of treatment may be for the treatment of hepatitis. The method of treatment may be for NASH.

[0072] In certain embodiments, an antisense oligonucleotide having the nucleobase sequence set forth in SEQ ID NO: 18 is provided for use in a method of treatment. The oligonucleotide may contain a modified nucleobase (e.g., 5-methylcytosine instead of cytosine). The oligonucleotide may contain at least one modified internucleotide linkage, such as a phosphorothioate internucleotide linkage. The oligonucleotide may contain one or more nucleotides having a modified sugar moiety, such as -O-CH3 or -O-CH2-CH2-O-CH3, attached to the 2' position of the sugar moiety. The method of treatment may be for the treatment of hepatitis. The method of treatment may be for NASH.

[0073] The antisense oligomer or pharmaceutical composition of the present disclosure can be administered to a subject by any suitable means. Suitable means for administering antisense oligomers, such as oligonucleotides, nucleic acids, and nucleic acid analogs, are known in the art. For example, the antisense oligomer or pharmaceutical composition can be administered intravenously or subcutaneously.

[0074] The pharmaceutical compositions of the present disclosure can be formulated for administration to any subject in need thereof. As used herein, a "subject" can be any vertebrate, mammal, or domestic animal. Most preferably, the subject is a human.

[0075] Depending on the organism being treated, an appropriate dosing regimen may be used. In non-limiting examples, the dosage may be 1 mg / kg to 100 mg / kg, 20 mg / kg to 60 mg / kg, or 40 mg / kg. It will be understood that the antisense oligomer or pharmaceutical composition disclosed herein may be used in monotherapy. Alternatively, the antisense oligomer or pharmaceutical composition according to the present disclosure may be used as an adjunct to or in combination with known treatments. The antisense oligomer or pharmaceutical composition may be administered before, during, or after the onset of a pathological condition.

[0076] As used herein, unless otherwise specified, the terms "treat," "treating," "treatment," and the like refer to ameliorating, alleviating, inhibiting the course of, or preventing the disease, disorder, or condition to which the term applies, or one or more symptoms of such a disease, and include administering any of the antisense oligomers, pharmaceutical compositions, or dosage forms described herein to prevent the onset of symptoms or complications, or to alleviate symptoms or complications, or to eliminate the disease, condition, or disorder. For example, treatment may be curative or ameliorative. As used herein, "preventing" means preventing, in whole or in part, the production or occurrence of the thing or event to be prevented, e.g., the disease, disorder, or condition, or ameliorating or controlling, or reducing or arresting.

[0077] As used herein, the terms "administering," "administer," "administration," and the like refer to any manner of transferring, delivering, introducing, or transporting a therapeutic agent to a subject in need of treatment with such agent.

[0078] Whenever an embodiment is described herein with the word "comprising," it is understood that analogous embodiments described in terms of "consisting of" and / or "consisting essentially of" are also provided.

[0079] Every feature described in this specification (including the accompanying claims, abstract and drawings), and / or every step of any method or process so disclosed, may be combined with any of the above aspects in any combination, except combinations in which at least some of such features and / or steps are mutually exclusive.

[0080] For a better understanding of the present invention and to illustrate how embodiments of the invention may be practiced, reference will now be made to examples which are not intended to limit the invention in any way. [Example]

[0081] overview Alternative splicing of RNA (AS) expands the regulatory capabilities of eukaryotic genomes. The liver is a transcriptionally highly complex organ. However, the mechanisms regulating liver-specific AS profiles and their contribution to liver function remain poorly understood. Here, we explore the relationship between diet, AS, and liver metabolic flexibility. We demonstrate that the splicing factor RNA-binding Fox protein-2 (RBFOX2) plays a critical role in maintaining cholesterol homeostasis in an obesity-promoting environment. Using enhanced individual-nucleotide resolution UV-crosslinking and immunoprecipitation (eiCLIP), we identified physiologically relevant targets of RBFOX2 in mouse liver, including scavenger receptor class B type 1 (Scarb1). Our findings indicate that specific AS programs actively maintain liver physiology and, when dysregulated, underlie the lipotoxic effects of an obesogenic diet. Splice-switching oligonucleotides targeted to this network attenuated obesity-induced inflammation in the liver and promoted an antiatherogenic lipoprotein profile in the blood, highlighting the potential of isoform-specific RNA therapeutics for the treatment of metabolic diseases. [Example]

[0082] Nutrition-stimulated changes in the hepatic splicing machinery. To investigate the molecular mechanisms involved in hepatic metabolic plasticity in health and disease, we performed unbiased analyses of the liver transcriptome (RNA-seq) and proteome (tandem mass tagging; TMT / MS) from mice fed a control diet (CD) or a high-fat diet (HFD) in both fed and fasted states (Figure 1A). Proteome analysis identified 5999 proteins across all experimental conditions (see Supplementary Table 1 - Paterson et al. Nature Metabolism). Principal component analysis confirmed the effect of dietary intervention on the liver proteome (Figure 1B, top) and transcriptome (Figure 1B, bottom). Gene ontology analysis revealed that the feeding / fasting cycle significantly increased the expression of "spliceosome" proteins involved in pre-mRNA splicing (FDR = 2.43). * 10 -9 ), as well as the expression of core metabolic categories such as "insulin signaling" and "TCA cycle" (Figure 1C, top, Figure 8A-B). Similarly, the expression of spliceosome proteins in the liver was altered by HFD intake (FDR=4.72). * 10 -2 ) (Figure 1C, bottom, and Figures 8C-D). Thus, components of the pre-mRNA splicing machinery are selectively regulated by metabolic inputs in the liver, potentially affecting pre-mRNA splicing and / or alternative splicing (AS).

[0083] Direct analysis of AS profiles by RNA-seq identified significant changes associated with the feeding / fasting cycle in mice fed a control diet and HFD (Figure 1D). AS changes promoted by the HFD included skipped exons (SE) as the most prevalent category (55%), followed by retained introns (RI; 13%), alternative 3' splice sites (A3SS; 14%), alternative 5' splice sites (A5SS; 11%), and mutually exclusive exons (MXE; 7%). Increased sugar intake is a significant contributor to diet-induced liver disease and associated cardiometabolic disorders. We investigated AS events promoted by a high-fructose (HFr) diet as a surrogate model of diet-induced obesity (Zhang, G. et al. Differential metabolic and multi-tissue transcriptomic responses to fructose consumption among genetically diverse mice. Biochim Biophys Acta Mol Basis Dis 1866, 165569 (2020). https: / / doi.org:10.1016 / j.bbadis.2019.165569). AS alterations associated with the HFr diet included skipped exons (SEs) as the most common AS events identified in these conditions (56%), followed by retained introns (RIs; 17%), alternative 3' splice sites (A3SSs; 16%), alternative 5' splice sites (A5SSs; 9%), and mutually exclusive exons (MXEs; 2%) (Figure 1D). The AS changes promoted by the feeding / fasting cycle in CD mice were strongly suppressed in diet-induced obesity ( Figure 8E ), suggesting that disruption of the hepatic AS network contributes to the reduced metabolic plasticity observed in obesity.Taken together, these results reveal specific alterations of the pre-mRNA AS program during physiological (feeding / fasting cycles) and pathophysiological (HFD- and HFr-induced obesity) adaptations. [Example]

[0084] The hepatic splicing factor RBFOX2 is regulated by diet We investigated which splicing factors (SFs) drive changes in hepatic AS profiles under different nutritional conditions. We hypothesized that SFs that regulate the hepatic splicing network should (a) exhibit detectable expression in the liver and / or hepatocytes and (b) be enriched for binding to regions within or surrounding alternatively spliced ​​exons in the liver. Therefore, we performed unsupervised motif enrichment analysis of sequences within and surrounding alternatively spliced ​​exons in the liver under physiological (fed / fasted cycle) and pathological (diet-induced obesity) conditions. This revealed significant enrichment of SF-binding motifs, including RBFOX2, CUGBP2, SRSF1, PTBP1, and MBN1 (Figure 8F-G). Analysis of SFs with conserved cross-linking peaks within and surrounding AS exons in human hepatocytes (Van Nostrand, EL et al. Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP). Nat Methods 13, 508-514 (2016). https: / / doi.org:10.1038 / nmeth.3810) identified eight SFs (U2AF2, RBFOX2, QKI, hnRNPC, PCBP2, TIA1, hnRNPM, and TAF15) as factors ranking in the top 20% across all three comparisons analyzed: feeding / fasting cycle (Figure 1E), HFD-induced obesity (Figure 1F), and HFr-induced obesity (Figure 1G). Additional analysis confirmed that RBFOX2 is expressed in the liver (Figure 1H).Furthermore, analysis of mouse single-cell RNA-seq datasets (Tabula Muris, C. et al. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature 562, 367-372 (2018). https: / / doi.org:10.1038 / s41586-018-0590-4) showed that although Rbfox2 is also detected in endothelial cells, the majority of Rbfox2 expression in the liver is in hepatocytes (Figure 2A). Other splicing factors potentially involved in regulating AS showed broader expression across other liver-resident cell populations (Figure 9). We used Alb_cre. - Rbfox2 LoxP / LoxP (L WT ) and Alb_cre + Rbfox2 LoxP / LoxP (L ΔRbfox2 We generated mice with selective inactivation of the Rbfox2 gene in hepatocytes. Western blot analysis revealed that RBFOX2 is a ubiquitous marker of liver function. ΔRbfox2 RBFOX2 was not detected in the liver of mice, and its expression in the liver was predominantly in hepatocytes (Figure 2B). These results suggest that RBFOX2 plays an important role in regulating AS in hepatocytes.

[0085] Our proteomic and transcriptomic analyses demonstrated that Rbfox2 is transcriptionally regulated by the feeding / fasting cycle in the liver (Figure 8A-B). The use of alternative promoters and ASs can generate multiple RBFOX2 isoforms with differential splicing activity, including dominant-negative forms characterized by truncated RNA recognition motifs (RRMs) (Damianov, A. & Black, DL. Autoregulation of Fox protein expression to produce dominant-negative splicing factors. RNA 16, 405-416 (2010). https: / / doi.org:10.1261 / rna.1838210). Western blot analysis demonstrated that both HFD- and HFr-diet-induced obesity were associated with decreased expression of the major RBFOX2 isoform in the liver (Figure 2C). Furthermore, TMT / MS proteomic analysis showed that these changes were associated with decreased levels of full-length, active RBFOX2 (Figure 2D), suggesting a possible loss of function of RBFOX2 in the liver during diet-induced obesity. Collectively, these data suggest that RBFOX2 may play a specific role in orchestrating dynamic AS changes in response to physiological and pathological metabolic signals. [Example]

[0086] RBFOX2 regulates cholesterol-regulatory genes via AS Splicing factors often regulate AS through cis- and trans-mediated interactions (Jangi, M., Boutz, PL, Paul, P. & Sharp, PA. Rbfox2 controls autoregulation in RNA-binding protein networks. Genes Dev 28, 637-651 (2014). https: / / doi.org:10.1101 / gad.235770.113; Irimia, M. & Blencowe, BJ. Alternative splicing: decoding an expansive regulatory layer. Curr Opin Cell Biol 24, 323-332 (2012). https: / / doi.org:10.1016 / j.ceb.2012.03.005). However, identification of direct targets of endogenous splicing factors in the liver has been hampered by the rapid degradation of pre-mRNA during cross-linking and immunoprecipitation (iCLIP) analysis in liver samples. For this reason, information regarding the AS program in the adult liver that contributes to maintaining or disrupting homeostasis is very limited. To overcome this issue, we employed an "enhanced individual nucleotide-resolution iCLIP" (eiCLIP) protocol, which expedites and improves the library preparation workflow to significantly enhance the recovery of RBFOX2-crosslinked pre-mRNA products (see Methods) (Figure 3A; 10A). Signal specificity was confirmed by peak analysis, which showed enrichment for the previously described consensus (U)GCAUG binding motif of RBFOX2 (Jin, Y. et al. A vertebrate RNA-binding protein Fox-1 regulates tissue-specific splicing via the pentanucleotide GCAUG. EMBO J 22, 905-912 (2003). https: / / doi.org:10.1093 / emboj / cdg089) (Figure 3B).Furthermore, our analysis revealed that in hepatocytes, direct targets of RBFOX2 include previously described bona fide targets such as Ptbp2 and Snrnp70 (Jangi, M., Boutz, PL, Paul, P. & Sharp, PA Rbfox2 controls autoregulation in RNA-binding protein networks. Genes Dev 28, 637-651 (2014). https: / / doi.org:10.1101 / gad.235770.113) (Figure 10B-C).

[0087] (Jangi, M., Boutz, PL, Paul, P. & Sharp, PA Rbfox2 controls autoregulation in RNA-binding protein networks. Genes). Dev 28, 637–651 (2014).Jin, Y. et al., the vertebrate RNA-binding protein Fox-1 regulates tissue-specific splicing via the pentanucleotide GCAUG. https: / / doi.org:10.1093 / emboj / cdg089 Yeo, GW et al An RNA code for the FOX2 splicing regulator revealed by mapping RNA-protein interactions in stem cells Nat Struct Mol Biol 16, 130–137 (2009). https: / / doi.org:10.1038 / nsmb.1545 , Zhang , C. et al. JG , Boutz , PL , Dougherty , JD , Stoilov , P. & Black , DL Homologues of the Caenorhabditis elegans Fox-1 protein are neuronal splicing regulators in mammals Mol Cell Biol 25 , 10005–10016 ( 2005 ).1128 / MCB.25.22.10005-10016.2005, Nakahata, S. & Kawamoto, S. Tissue-dependent isoforms of mammalian Fox-1 homologs are associated with tissue-specific splicing activities. Nucleic Acids Res 33, 2078-2089 (2005). https: / / doi.org:10.1093 / nar / gki338, Modafferi, E. F. & Black, D. L. A complex intronic splicing enhancer from the c-src pre-mRNA activates inclusion of a heterologous exon. Mol Cell Biol 17, 6537-6545 (1997). https: / / doi.org:10.1128 / MCB.17.11.6537) (Figure 10D). RBFOX2 crosslinking positions upstream or downstream of the AS exon (L. WT and L ΔRbfox2 Analysis of mouse exons (identified by RNAseq; Figure 10E ) showed that in liver, this position effect was more robust for enhancer exons (50.0%) than suppressor exons (27.9%) compared with control exons (25.1%) ( Figure 3C ).

[0088] Gene ontology analysis revealed that the RBFOX2 cross-linking cluster correlated with phosphatidylcholine-sterol-O-acyltransferase activity (adjusted p-value = 3.66 * 10 -2 ), lipoprotein particle receptor binding (adjusted p-value = 1.13 * 10 -2 ), apolipoprotein receptor binding (adjusted p value = 2.61 * 10 -3 ), and transcripts encoding proteins involved in LDL particle receptor binding, suggesting a role for RBFOX2 in the regulation of lipid metabolism (Figure 3D). Furthermore, other targets were found to be involved in cadherin binding (adjusted p-value = 7.42).* 10 -16 ), disordered domain-specific binding (adjusted p-value = 2.72 * 10 -4 ), and also RNA-binding proteins (RBPs) (adjusted p-value = 3.72 * 10 -14 ), highlighting a role for RBFOX2 in regulating additional layers of transcriptional regulation (Jangi, M., Boutz, PL, Paul, P. & Sharp, PA Rbfox2 controls autoregulation in RNA-binding protein networks. Genes Dev 28, 637-651 (2014). https: / / doi.org:10.1101 / gad.235770.113). A list of RBFOX2 targets contributing to each Gene Ontology category is provided in Supplementary Table 2 (see Paterson et al. Nature Metabolism).

[0089] Human orthologous genes of mouse RBFOX2 targets detected by eiCLIP are highly enriched in genes implicated in human lipid metabolism phenotypes, LDL cholesterol levels, or triglycerides by GWAS ( Figure 3E ). These include Scarb1, which encodes the gene class B scavenger receptor SR-BI, an HDL receptor that mediates cholesterol uptake and modifies plasma HDL and bile cholesterol (Kozarsky, KF et al. Overexpression of the HDL receptor SR-BI alters plasma HDL and bile cholesterol levels. Nature 387, 414-417 (1997). https: / / doi.org:10.1038 / 387414a0, Acton, S. et al. Identification of scavenger receptor SR-BI as a high density lipoprotein receptor. Science 271, 518-520 (1996). https: / / doi.org:10.1126 / science.271.5248.518), and Pla2g6, a phospholipase A2 group VI (Dennis, EA, Cao, J., Hsu, YH, Magrioti, V. & Kokotos, G. Phospholipase A2 enzymes: physical structure, biological function, disease implication, chemical inhibition, and therapeutic intervention. Chem Rev 111, 6130-6185 (2011). https: / / doi.org:10.1021 / cr200085w), activation of SREBP1 (Han, J. et al. The CREB coactivator CRTC2 controls hepatic lipid metabolism by regulating SREBP1. Nature 524, 243-246 (2015). https: / / doi.org:10.Sec31a, a central component of the COPII vesicle transport system involved in the processing of ApoB-containing lipoproteins (Gusarova, V., Brodsky, JL & Fisher, EA Apolipoprotein B100 exit from the endoplasmic reticulum (ER) is COPII-dependent, and its lipidation to very low density lipoprotein occurs post-ER. J Biol Chem 278, 48051-48058 (2003). https: / / doi.org:10.1074 / jbc.M306898200), the oxysterol-binding protein Osbpl9, and Numb, an adaptor protein involved in clathrin-dependent reverse cholesterol transport from bile (Temel, RE et al. Hepatic Niemann-Pick C1-like 1 regulates biliary cholesterol concentration and is a target of ezetimibe. J Clin Invest 117, 1968-1978 (2007). https: / / doi.org:10.1172 / JCI30060).

[0090] Further analysis of the eiCLIP profile of the Scarb1 pre-mRNA transcript revealed that RBFOX2 binds upstream of exon 12. ΔRbfox2PCR analysis of mouse liver confirmed that RBFOX2 promotes the skipping of Scarb1 exon 12 (Figure 3F). Furthermore, RBFOX2 promotes the skipping or inclusion of specific exons in Pla2g6 (Figure 3G), Numb (Figure 3H), Osbpl9 (Figure 3I), and Sec31a (Figure 10F). Analysis of RBFOX2 binding in human liver tumor cells confirmed that RBFOX2 cross-linking within alternatively spliced ​​exons in orthologous human transcripts is conserved (Figures 10G-J). Collectively, these results reveal that RBFOX2 directly regulates AS of a gene network involved in hepatic lipid homeostasis. [Example]

[0091] RBFOX2 regulates cholesterol metabolism in obesogenic diets L ΔRbfox2 Mice are viable and born at the expected Mendelian ratio. When fed a control diet, HFD, or HFr diet, L ΔRbfox2 No significant changes were observed in mouse body weight (Figure 11A-C) or glucose tolerance (Figure 11D-F), suggesting that ablation of RBFOX2 does not disrupt normal liver development. In contrast to the observed normal glucose homeostasis, blood lipid profile analysis revealed that L ΔRbfox2 We found that when male mice were fed the HFr diet, total cholesterol (Figure 4A) but not triglycerides (Figure 4B) was significantly reduced. WT and L ΔRbfox2 Similar results were obtained when female mice were examined (Fig. 11G-H).

[0092] The liver plays a central role in lipid homeostasis. To investigate the metabolic changes associated with changes in blood lipid profiles, we investigated the L WT Mouse and L ΔRbfox2Mouse livers were analyzed by untargeted LC / MS lipidomics. Principal component analysis showed that the HFr diet was associated with significant changes in the overall metabolomic profile compared to CD samples (Figure 4C). In mice fed the HFr diet, ablation of RBFOX2 was associated with increases in hepatic lipid content, particularly cholesteryl esters (CE), total cholesterol, and sphingomyelin (Figure 4D). ΔRbfox2 In mice, we did not observe differences in lipid patterns (Figure 11I), but did observe changes in triglyceride (TG) composition (as indicated by the PUFA / non-PUFA TG ratio) favoring longer polyunsaturated fatty acyl chains (Figure 4D). ΔRbfox2 Mice also showed an increase in total cholesterol esters in the liver. However, in contrast to mice fed the HFr diet, no overall changes were observed in cholesterol or sphingomyelin (Fig. 11J-M), or blood cholesterol (Fig. 11N), and L ΔRbfox2 These findings suggest a partial phenotype that is exacerbated when mice are fed a pro-adipogenic HFr diet.

[0093] CLIP-seq analysis suggests the conservation of RBFOX2 targets in humans (Figure 10G-J). To investigate whether RBFOX2 is involved in lipid metabolism in human hepatocytes, we obtained iPSC-derived hepatocytes and silenced RBFOX2 using siRNA (Figure 4E). Efficient RBFOX2 silencing was confirmed by qPCR analysis (Figure 4F). RBFOX2 silencing did not affect the expression of mature hepatocyte / differentiation markers such as ASGPR2, SERPINA1, and SERPINA2 (Figure 12A). Consistent with human RBFOX2 binding to pre-mRNA, the effects of RBFOX2 deficiency on the alternative splicing of SCARB1, SEC31A, OSBPL9, PLA2G6, and NUMB were maintained in human hepatocytes (Figure 4G-J), confirming the conservation of this regulatory network. Furthermore, lipidomic analysis of human hepatocytes showed that RBFOX2 silencing promoted changes in lipid composition, including the accumulation of CE and SM (Figure S12B) (Figures 4L-M). These results further support the role of RBFOX2 in regulating the conserved AS network involved in lipid metabolism.

[0094] L ΔRbfox2 The concomitant accumulation of cholesterol in the liver and reduction of plasma cholesterol in mice suggested that RBFOX2 plays a specific role in regulating hepatic cholesterol uptake, transport, and / or excretion. To gain insight into these mechanisms, we used RNA sequencing to identify the role of RBFOX2 in the regulation of hepatic cholesterol uptake, transport, and / or excretion in L. elegans fed a HFr diet. WT Mouse and L ΔRbfox2 We compared the transcriptomes of mice with those of controls. Ablation of RBFOX2 in the liver significantly reduced cholesterol biosynthesis (ratio = 0.138, p-value = 1.7). * 10 -5 ), mevalonate pathway (ratio = 0.214, p value = 5.25 * 10 -5 ), LXR pathway (ratio = 0.02, p value = 2.75 * 10 -2 ), and FXR pathway (ratio = 0.02, p value = 3.09 * 10 -2), which is consistent with a role for RBFOX2 in lipid and cholesterol metabolism. * 10 -17 ) and mitochondrial dysfunction (ratio = 0.0877, p value = 2.51 * 10 -14 ) also showed additional changes.

[0095] Cholesterol metabolism is controlled by a feedback mechanism involving sterol regulatory element-binding proteins (SREBPs), an ER-resident family of transcription factors (Horton, JD, Goldstein, JL & Brown, MS SREBPs: activators of the complete program of cholesterol and fatty acid synthesis in the liver. J Clin Invest 109, 1125-1131 (2002). https: / / doi.org:10.1172 / JCI15593). Ad hoc qPCR analysis of genes involved in cholesterol homeostasis showed that increased hepatic cholesterol was not associated with increased expression of key biosynthetic genes, including Srebf2, Hmgcs, and Hmgcr (Figure ​(Figure12C),12C), suggesting that this feedback regulation remains intact. Furthermore, increased expression of Abca1, Abcg8, and Nr1h2 (LXR beta) and Nr1h3 (LXR alpha) genes suggests a compensatory increase in cholesterol efflux pathways caused by cholesterol accumulation upon RBFOX2 deficiency (Figure ​(Figure12C). Consistent changes in ApoB were also observed at the protein level, whereas for ABCA1, no significant changes were observed in LXR efflux pathways. WT and L ΔRbfox2 The difference between the two was not statistically significant (Figure 12D).

[0096] Reverse HDL-cholesterol uptake in the liver and its conversion to bile acids is the major pathway for cholesterol excretion through the bile. ΔRbfox2 We hypothesized that a decrease in blood cholesterol and a concomitant increase in hepatic cholesterol in mice might lead to elevated bile acid levels. Consistent with this hypothesis, LC-MS / MS analysis showed an increase in bile acids, including taurocholic acid, taurodeoxycholic acid, tauroursodeoxycholic acid, and cholic acid (Figure 12E-K). When fed an HFD, L ΔRbfox2 Mouse is L WT They also showed increased intrahepatic bile acids compared to control mice (Figure 12L-U). Together, these results indicate that liver-specific ablation of Rbfox2 leads to the accumulation of cholesterol in the liver, increased conversion to bile acids, and subsequent activation of the LXR and FXR pathways.

[0097] We next hypothesized that changes in RBFOX2 activity could modulate this downstream AS network change in response to diet. To test this idea, we used L. elegans fed a control or obesogenic diet. WT Mouse and L ΔRbfox2 We analyzed AS changes in Scarb1, Pla2g6, and Numb in mice. Consistent with our hypothesis, HFr increases L WT promotes significant AS changes in mice, but L ΔRbfox2 Mice fail to induce obesity-specific AS events in Pla2g6 (Figure ​(Figure6A),6A), Scarb1 (Figure6B), and Numb (Figure6C). Analysis of other target genes, such as Sec31a and Osbpl9, also confirmed their strong regulation by RBFOX2 (Figures ​(Figure6E–F),6B), but no dietary effect was detected, suggesting that other factors may be involved in the regulation of these genes under obesity-promoting conditions.

[0098] To gain further mechanistic insight into the regulation of this AS network by RBFOX2, we investigated whether the altered alternative splicing was associated with decreased levels of active RBFOX2 or increased levels of inactive (lacking the RRM motif) protein (Figure 2C-D). To investigate this, we generated an AAV vector expressing RBFOX2 lacking the RRM motif (RBFOX2-Δ6) (Figure 5A). Expression was confirmed by Western blot and qPCR (Figure 5A-B). However, overexpression of RBFOX2-Δ6 did not mimic the AS changes associated with RBFOX2 inactivation in mouse and human hepatocytes (Figure 5C). We next generated vectors overexpressing full-length RBFOX2 (containing the RRM motif) (Figure 5D; Figure 13G). Notably, overexpression of active RBFOX2 promoted AS changes in the opposite direction to RBFOX2 deficiency (Fig. 5E; 13G), suggesting that the level of active RBFOX2 is more important than expression of a dominant-negative form in regulating AS in the liver.

[0099] LC-MS / MS lipidomics analysis showed that RBFOX2 overexpression was associated with decreased cholesterol in the liver (Figure 5F) and bile (Figure 5G). Transient overexpression of RBFOX2 was associated with a mild increase in plasma HDL-cholesterol, but this did not reach statistical significance (Figure 5H). Collectively, these results confirm that RBFOX2 regulates a network of genes involved in lipid metabolism and that altered expression of full-length RBFOX2 alters cholesterol distribution under a lipogenic diet. [Example]

[0100] Hepatic expression of RBFOX2 is regulated by FOXA1 / 2 To characterize upstream regulators of RBFOX2 in human liver, we used the FANTOM5 CAGE dataset of transcription start sites (Figure 6A), because the RBFOX2 gene has a complex structure with multiple promoters (Damianov, A. & Black, DL. Autoregulation of Fox protein expression to produce dominant negative splicing factors. RNA 16, 405-416 (2010). https: / / doi.org:10.1261 / rna.1838210). This analysis concluded that RBFOX2 expression in human hippocampus or aortic smooth muscle is driven by two promoters, a proximal promoter and a distal promoter, whose activity levels are similar. In contrast, in hepatocytes, the distal promoter primarily controls RBFOX2 expression (a three-fold change compared to the proximal promoter). CAGE data also detected a third promoter in human hepatocytes that does not overlap with the previously annotated RBFOX2 promoter (Figure 6A). This promoter and a shared distal promoter account for the majority of RBFOX2 transcription in human hepatocytes, and both showed enrichment for H3K4me3 and H3K27ac by ChIP-seq in adult human liver, consistent with their role as active hepatic promoters.

[0101] Further analysis of the liver ChIP-seq datasets revealed that the RBFOX2 promoter is bound by FOXA1 / 2 in humans (Figure 6A, lower inset) and mice (Figure 1H). FOXA1 / 2 are winged-helix transcription factors involved in bile acid metabolism and protection from hepatic cholestasis (Bochkis, IM et al. Hepatocyte-specific ablation of Foxa2 alters bile acid homeostasis and results in endoplasmic reticulum stress. Nat Med 14, 828-836 (2008). https: / / doi.org:10.1038 / nm.1853). To verify the role of FOXA1 / 2 in regulating Rbfox2, we knocked down Foxa1 and Foxa2 in mouse liver tumor Hepa1-6 cells, resulting in a significant decrease in Rbfox2 expression (Figure 6B). Conversely, overexpression of FOXA1 in HepG2 cells (Moya, M. et al. Foxa1 reduces lipid accumulation in human hepatocytes and is downregulated in nonalcoholic fatty liver. PLoS One 7, e30014 (2012). https: / / doi.org:10.1371 / journal.pone.0030014) was associated with a significant increase in RBFOX2 expression, but not RBFOX1 / 3 (Figure 6C). Together, these results identify an active promoter of RBFOX2 in the liver and indicate that the transcription factors FOXA1 / 2 are upstream regulators of RBFOX2 in human and mouse liver. [Example]

[0102] Scarb1 is a potential therapeutic target of RBFOX2 To elucidate the molecular mechanisms underlying the role of RBFOX2 in lipid homeostasis, we systematically designed splice-switching oligonucleotides that regulate the alternative splicing of RBFOX2 downstream targets. The efficacy of the SSOs was tested by PCR followed by capillary electrophoresis. SSOs that showed potent activity against each splicing event were then further used in lipidomics analysis of primary hepatocytes (Table 1). [Table 1]

[0103] LC / MS metabolomic analysis revealed that RBFOX2-deficient hepatocytes exhibited increased lipid accumulation (Fig. S4I), confirming the role of RBFOX2 in hepatocyte lipid metabolism. SSO7.9, which promotes changes in Numb exon 3, was not associated with significant lipid remodeling (Fig. S4J). However, SSOs targeting Numb exon 9, Sec31 exon 21, Pla2g6 exon 10, Osbpl9 exon 6, and Scarb1 exon 12 were associated with specific changes in lipid composition (Fig. S4J), suggesting that these isoforms mediate the effects of RBFOX2.

[0104] SSO-induced skipping of exon 9 of the Numb transcript (Fig. 14A) restored the accumulation of many lipid species, including phospholipids and triglycerides such as PC(36:3), PC(40:7), PE(38:5), PC(38:4), PC(36:2), PC(40:5), TG(58:8), TG(62:13), TG(58:8), TG(56:7), TG(56:2), and TG(54:2) (Fig. 14B). Expression of the shorter Sec31a isoform (skipping exon 21) was associated with increased levels of specific lipid species, such as PC(36:2), TG(51:1), PC(32:0), PC(34:0), DG(38:4), or lysoPC(22:6) (Fig. 14C-D). Expression of the shorter Osbpl9 isoform (skipping exon 6) in wild-type cells promoted the increase of specific species, such as Cer(40:2), TG(50:1), TG(51:1), PC(32:0), PC(34:0), DG(38:4), and PE(40:7), similar to those observed in RBFOX2-deficient hepatocytes, suggesting a previously uncharacterized role in lipid metabolism (Fig. 15A-B). Expression of the longer Pla2g6 isoform (Fig. 15C-D), which includes exon 10, was associated with a subtle change in lipid composition (Fig. 15E).

[0105] Inclusion of exon 12 of Scarb1 generates the classical SR-BI isoform, whereas skipping this exon generates an alternative receptor variant with a different adaptor carboxy-terminal domain, termed SR-BII (Webb, NR et al. SR-BII, an isoform of the scavenger receptor BI containing an alternate cytoplasmic tail, mediates lipid transfer between high density lipoprotein and cells. J Biol Chem 273, 15241-15248 (1998). https: / / doi.org:10.1074 / jbc.273.24.15241). SR-BI / II is a scavenger receptor for multiple ligands, including very low-density lipoprotein (VLDL) and high-density lipoprotein (HDL), which are involved in the transport of cholesterol, cholesteryl esters, phospholipid-PC, sphingomyelin, lyso-PC, and other lipid species (Puri, P. et al. A lipidomic analysis of nonalcoholic fatty liver disease. Hepatology 46, 1081-1090 (2007). https: / / doi.org:10.1002 / hep.21763). However, the overall impact and pathophysiological significance of these splicing variants on hepatic lipidomics remain to be established. SSO8.3 showed significant activity in suppressing exon 12 inclusion in primary hepatocytes (Figure 16A). LC / MS analysis demonstrated that this treatment significantly inhibited L ΔRbfox2 This was associated with substantial changes in lipid composition in hepatocytes (Figure 16B), and showed partial restoration of some of the changes associated with RBFOX2 deficiency, such as increases in total ceramides (Figure 16C), the PUFA / non-PUFA TG ratio (Figure 16D), and numerous SMs and TGs (Figures 16G-I).

[0106] Increased hepatic levels of cholesterol, ceramide, sphingomyelin, and other lipotoxic species are involved in the pathogenesis of obesity-induced steatohepatitis (Ioannou, GN The Role of Cholesterol in the Pathogenesis of NASH. Trends Endocrinol Metab 27, 84-95 (2016). https: / / doi.org:10.1016 / j.tem.2015.11.008, Puri, P. et al. A lipidomic analysis of nonalcoholic fatty liver disease. Hepatology 46, 1081-1090 (2007). https: / / doi.org:10.1002 / hep.21763).

[0107] While SCARB1 is a complex therapeutic target, the effect of SSO8.3 in reducing the levels of some of these lipid species in hepatocytes suggests that strategies aimed at promoting the SR-BII isoform may contribute to attenuating obesity-induced inflammation in vivo. To test this, we injected SSO8.3, a scrambled control SSO (Scr), or saline into mice fed an obesogenic HFr diet (Figure 7A, top). SSO8.3 demonstrated potent activity in antagonizing Scarb1 exon 12 inclusion in the liver in vivo (Figures 7B, 16J). SSO8.3 was designed to avoid potential off-target effects. This specificity was confirmed by assessing potential expression changes in the top three potential off-target genes by qPCR (Figures 16K-M). No weight loss (Figure 7A, bottom) or increases in transaminases (Figures 16N-O) were detected, indicating that RNA injections were not associated with toxic side effects. IHC analysis of liver sections demonstrated reduced macrophage infiltration in the livers of SSO8.3-injected mice (Figure 7C). qPCR analysis demonstrated that the expression of inflammatory markers (Arg1, F4 / 80, and Tnfa) and fibrotic markers (Tgfb1 and Col1a1) was significantly downregulated in SSO8.3-treated mice (Figure 7D). Consistent with the reduced lipid load in hepatocytes (Figures 7E-F), SSO8.3-treated mice exhibited a decreased liver / total body weight ratio (Figure 7P) and decreased secretion of cholesterol and phospholipids into bile (Figure 7G), suggesting reduced reverse cholesterol transport to the liver.

[0108] Genetically engineered mouse models have shown that complete inactivation of Scarb1 (Trigatti, B. et al. Influence of the high density lipoprotein receptor SR-BI on reproductive and cardiovascular pathophysiology. Proc Natl Acad Sci USA 96, 9322-9327 (1999). https: / / doi.org:10.1073 / pnas.96.16.9322) or liver-specific inactivation (Huby, T. et al. Knockdown expression and hepatic deficiency reveal an atheroprotective role for SR-BI in liver and peripheral tissues. J Clin Invest 116, 2767-2776 (2006). https: / / doi.org:10.1172 / JCI26893) is associated with elevated VLDL, LDL, and HDL levels and enhanced atherosclerosis, whereas overexpression of SR-BI has the opposite effect (Kozarsky, KF et al. Overexpression of the HDL receptor SR-BI alters plasma HDL and bile cholesterol levels. Nature 387, 414-417 (1997). https: / / doi.org:10.1038 / 387414a0). SSO8.3 treatment caused a mild but significant increase in total cholesterol levels and a decrease in blood triglycerides (Figure 7H). These results suggest that by increasing the expression of the SR-BII isoform, SSO8.3 treatment exerts specific effects on VLDL and HDL lipoproteins. Consistent with this hypothesis, lipoprotein analysis showed a strong decrease in VLDL lipoproteins and an increase in HDL and LDL levels (Figure 7I). To further confirm these findings, we directly quantified the lipid species content in isolated lipoproteins.This analysis revealed significant changes in lipoprotein composition, including decreased cholesterol content in VLDL and increased cholesterol content in HDL and LDL (Figures 17A-C). SSO8.3 treatment was not associated with changes in hepatic lipogenic genes (Figure 17D) or overall triglyceride content (Figure 17E). For these reasons, we cannot exclude a contribution from decreased VLDL secretion. However, the decreased blood levels of total triglycerides, VLDL, and LDL triglycerides suggest that SSO8.3 promotes VLDL lipolysis and remnant formation. However, further investigation is needed to confirm this mechanism.

[0109] Collectively, these results indicate that RBFOX2 orchestrates an alternative splicing network in the liver that promotes specific changes in lipid metabolism and globally regulates the homeostasis of lipid species, including cholesterol, sphingomyelin, and phospholipids. In particular, the SR-BI / II splice switch may be a potential therapeutic target for reducing hepatic inflammation and altering lipid distribution. [Example]

[0110] Scarb1 AS mediates the effects of RBFOX2 on cholesterol metabolism RBFOX2 deficiency was not associated with alterations in cholesterol biosynthesis or adipogenesis (Figures 12C and 17D). Furthermore, our data support the notion that increased lipid uptake via SR-BI / II contributes to the increased accumulation of cholesterol and other lipids due to RBFOX2 deficiency. We hypothesized that this mechanism might also underlie the altered blood cholesterol levels associated with RBFOX2 deficiency through increased reverse cholesterol uptake and biliary excretion. To explore this possibility, we first inactivated endogenous Scarb1 by siRNA or control siRNA while simultaneously expressing codon-optimized versions of either SR-BI or SR-BII in AML12 hepatocytes (Figures 7J and 17F). Equivalent expression levels of SR-BI and SR-BII were confirmed by absolute qPCR quantification (Figure 17G). FACS analysis showed that expression of the exon 12-containing SR-BI isoform was associated with increased lipid uptake from Dil-HDL lipoproteins ( Figure 7J ).

[0111] Next, we investigated the contribution of the SR-BI / II isoform to the in vivo role of RBFOX2. WT and L ΔRbfox2 Mice were treated with Scr control or SSO8.3 to determine L ΔRbfox2 In particular, SSO8.3 antagonized the mouse SR-BII isoform. ΔRbfox2 The SR-BI / SR-BII ratio in the mouse liver was efficiently restored (Figure 17H). Blood lipoproteins were isolated and the lipid composition was quantified. The cholesterol and phospholipid contents in HDL were significantly higher than those in L ΔRbfox2The SR-BI / SR-BII ratio was reduced in mice, and these differences disappeared when the SR-BI / SR-BII ratio was restored, confirming that this isoform switch and cholesterol transport contribute to the role of RBFOX2 in the liver (Figure 7K). Further analysis confirmed that hepatic RBFOX2 inactivation increased biliary cholesterol (Figure 7L), while acute adenovirus-mediated RBFOX2 overexpression caused the opposite effect (Figure 5G). Furthermore, switching Scarb1 isoform expression by SSO8.3 treatment restored biliary cholesterol excretion (Figure 7L) and plasma total cholesterol levels (Figure 17J), further confirming that SR-BI / II-mediated reverse cholesterol transport underlies the role of RBFOX2 in cholesterol metabolism. Purification and analysis of plasma LDL and VLDL showed that RBFOX2 deficiency was associated with alterations in cholesterol and phospholipids that did not reach statistical significance, suggesting a major role for RBFOX2 in cholesterol incorporation into HDL (Figure 17K-L). Collectively, these results reveal a novel role for RBFOX2 in the control of lipid metabolism and demonstrate that the SR-BI / SR-BII isoform switch plays a critical role in this mechanism by regulating HDL lipoprotein homeostasis.

[0112] Consideration of Examples 1 to 7 In the liver, pre-mRNA alternative splicing (AS) has been widely considered to be a housekeeping mechanism involved in regulating the transcriptome to maintain cellular identity. Several splicing factors have been shown to play a role in this regulation (Sen, S., Jumaa, H. & Webster, NJ Splicing factor SRSF3 is crucial for hepatocyte differentiation and metabolic function. Nat Commun 4, 1336 (2013). https: / / doi.org:10.1038 / ncomms2342, Wei, N. et al. SRSF10 Plays a Role in Myoblast Differentiation and Glucose Production via Regulation of Alternative Splicing. Cell Rep 13, 1647-1657 (2015). https: / / doi.org:10.1016 / j.celrep.2015.10.038, Benegiamo, G. et al. The RNA-Binding Protein NONO Coordinates Hepatic Adaptation to Feeding. Cell Metab 27, 404-418 e407 (2018)). https: / / doi.org:10.1016 / j.cmet.2017.12.010, Pihlajamaki, J. et al. Expression of the splicing factor gene SFRS10 is reduced in human obesity and contributes to enhanced lipogenesis. Cell Metabolism 14, 208-218 (2011). https: / / doi.org:10.1016 / j.cmet.2011.06.007, Nikolaou, KC et al.The RNA-Binding Protein A1CF Regulates Hepatic Fructose and Glycerol Metabolism via Alternative RNA Splicing. Cell Rep 29, 283-300 e288 (2019). https: / / doi.org:10.1016 / j.celrep.2019.08.100), the contribution of specific AS networks (splicing factors and downstream isoforms) to fluctuating metabolic demands has yet to be characterized.

[0113] Here, we describe the role of RBFOX2 in regulating genes involved in hepatic lipid metabolism. This AS network is modulated by an obesogenic diet, and RBFOX2 is critical for this regulation. In mammals, the Rbfox family contains three paralogs (Rbfox1, Rbfox2, and Rbfox3). Rbfox1 is expressed in neurons, heart, and muscle, whereas Rbfox3 expression is restricted to neurons and Rbfox2 has a broader expression profile (Kuroyanagi, H. Fox-1 family of RNA-binding proteins. Cell Mol Life Sci 66, 3895-3907 (2009). https: / / doi.org:10.1007 / s00018-009-0120-5). We found that Rbfox2 is mainly expressed in hepatocytes in the liver, and that deleting the Rbfox2 gene in hepatocytes led to a decrease in blood cholesterol and an increase in the hepatic content of lipids such as cholesterol and bile acids, thereby revealing the role of RBFOX2 in regulating lipid distribution.

[0114] Increased circulating and hepatic cholesterol levels contribute to metabolically associated fatty liver disease (MAFLD) and promote coronary artery disease (Corey, KE & Chalasani, N. Management of dyslipidemia as a cardiovascular risk factor in individuals with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol 12, 1077-1084; quiz e1059-1060 (2014). https: / / doi.org:10.1016 / j.cgh.2013.08.014; Collaborators, GBDO et al. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. N Engl J Med 377, 13-27 (2017). https: / / doi.org:10.1056 / NEJMoa1614362).Hepatic cholesterol overload is also recognized as an important contributor to the progression of liver damage and inflammation (Ioannou, GN The Role of Cholesterol in the Pathogenesis of NASH. Trends Endocrinol Metab 27, 84-95 (2016). https: / / doi.org:10.1016 / j.tem.2015.11.008, Puri, P. et al. A lipidomic analysis of nonalcoholic fatty liver disease. Hepatology 46, 1081-1090 (2007). https: / / doi.org:10.1002 / hep.21763, Min, HK et al. Increased hepatic synthesis and dysregulation of cholesterol metabolism is associated with the severity of nonalcoholic fatty liver disease. Cell Metab 15, 665-674 (2012). https: / / doi.org:10.1016 / j.cmet.2012.04.004). Cholesterol levels are tightly regulated to ensure a constant supply to tissues while preventing the deleterious effects of excessive accumulation. Characterization of this AS network in the liver indicates that additional layers of complexity are involved in cholesterol homeostasis in health and disease.

[0115] We demonstrated that RBFOX2-mediated regulation of splice variants of Scarb1, Pla2g6, Numb, Sec31a, or Osbpl9 transcripts is conserved in humans and has specific roles in controlling lipid composition. Although the coordinated activity of this splicing network underlies the effects of RBFOX2 on lipid metabolism, targeting individual components with splice-switching oligonucleotides can induce specific changes in hepatocyte lipid content. Two distinct classical receptors, SR-BI and SR-BII, are generated through the inclusion / skipping of exon 12 of the Scarb1 gene. SR-BI has increased HDL-binding activity and promotes selective import of cholesteryl esters (Webb, NR et al. SR-BII, an isoform of the scavenger receptor BI containing an alternate cytoplasmic tail, mediates lipid transfer between high density lipoprotein and cells. J Biol Chem 273, 15241-15248 (1998). https: / / doi.org:10.1074 / jbc.273.24.15241; Eckhardt, ER et al. High density lipoprotein endocytosis by scavenger receptor SRBII is clathrin-dependent and requires a carboxyl-terminal dileucine motif. J Biol Chem 281, 4348-4353 (2006). https: / / doi.org:10.1074 / jbc.M513154200). However, the regulation and biological significance of this splicing event have not previously been described.Plasma HDL cholesterol levels are inversely correlated with atherosclerosis risk in humans and some mouse models (Emerging Risk Factors, C. et al. Major lipids, apolipoproteins, and risk of vascular disease. JAMA 302, 1993-2000 (2009). https: / / doi.org:10.1001 / jama.2009.1619). Therefore, SR-BI has attracted considerable interest as a therapeutic target for improving lipid metabolism by increasing HDL-C levels. However, in addition to human genetic studies (Zanoni, P. et al. Rare variant in scavenger receptor BI raises HDL cholesterol and increases risk of coronary heart disease. Science 351, 1166-1171 (2016). https: / / doi.org:10.1126 / science.aad3517), gain-of-function mouse models (Kozarsky, KF et al. Overexpression of the HDL receptor SR-BI alters plasma HDL and bile cholesterol levels. Nature 387, 414-417 (1997). https: / / doi.org:10.1038 / 387414a0) and loss-of-function mouse models (Trigatti, B. et al. Influence of the high density lipoprotein receptor SR-BI on reproductive and cardiovascular pathophysiology. Proc Natl Acad Sci USA 96, 9322-9327) have shown no significant differences in HDL cholesterol levels. (1999). https: / / doi.org:10.1073 / pnas.96.16.9322) showed that SR-BI activity protects against atherosclerosis, emphasizing that HDL cholesterol flux is more important than steady-state levels.We found that by promoting SR-BII expression, RBFOX2 prevents reverse cholesterol flux from HDL lipoproteins, ensuring proper distribution and preventing excessive cholesterol loss. Consistent with this, RBFOX2 inactivation is associated with decreased circulating total and HDL cholesterol, and under a lipogenic diet, increased hepatic cholesterol is excreted in the bile.

[0116] Furthermore, the splice-switching oligonucleotide SSO8.3 significantly reduced the accumulation of lipotoxic species such as ceramide, cholesterol, and sphingomyelin by promoting the expression of SR-BII, an effect associated with reduced expression of inflammatory markers in the liver.

[0117] Treatment with SSO8.3 to promote SR-BII isoform expression in vivo was associated with significant reductions in plasma VLDL and triglycerides. These results indicate that SR-BII isoform expression promotes an anti-atherogenic lipoprotein profile, potentially by promoting VLDL catabolism, rather than loss- or gain-of-function. While our results clearly demonstrate that the RBFOX2-SR-BI / II axis plays a critical role in regulating cholesterol homeostasis, the contribution of the SR-BI / II splice switch to triglyceride homeostasis appears to be more complex, as RBFOX2 inactivation was not associated with changes in total circulating triglycerides. Further investigation is needed to clarify this point.

[0118] RNA-based drugs such as inclisiran (Ray, KK et al. Inclisiran in Patients at High Cardiovascular Risk with Elevated LDL Cholesterol. N Engl J Med 376, 1430-1440 (2017). https: / / doi.org:10.1056 / NEJMoa1615758) and mipomersen (Raal, FJ et al. Mipomersen, an apolipoprotein B synthesis inhibitor, for lowering of LDL cholesterol concentrations in patients with homozygous familial hypercholesterolemia: a randomized, double-blind, placebo-controlled trial. Lancet 375, 998-1006 (2010). https: / / doi.org:10.1016 / S0140-6736(10)60284-X) have been shown to inhibit PCSK9 and APOB, respectively. Targeting mRNA significantly reduces cholesterolemia. Recent improvements in the design and pharmacokinetics of RNA-based oligonucleotides should enable the development of isoform-specific therapeutics for common metabolic conditions. However, this avenue remains underexplored due to limited characterization of key health-maintaining or disease-promoting isoforms. Our study provides proof-of-principle for the feasibility of RNA therapeutics targeting individual isoforms in the liver. [Example]

[0119] Development of a humanized version of SSO targeting the SCARB1 gene Examples 1-7 identified scavenger receptor class B type I (Scarb1) as a novel target for regulating lipid metabolism and hepatic inflammation in nonalcoholic steatohepatitis (NASH). Scarb1 has two AS variants: SR-BI, which includes exon 12, and SR-BII, which skips exon 12. A high-fructose diet in mice increases the expression of SR-BI, which is involved in the transport of cholesterol and other lipid species. By increasing the expression of SR-BI, the body promotes the uptake of cholesterol and other lipids by the liver, leading to inflammation and hepatotoxicity. Conversely, splicing-switching oligonucleotides (SSOs) specifically targeted to promote the expression of the exon 12-skipping isoform (SR-BII) led to a reduction in lipid load in the liver of mice.

[0120] Results in mice show that treatment with the 21-nt oligonucleotide SSO8.3 is associated with significant changes in liver and circulating lipids with clear therapeutic effects: 1) reduced hepatic inflammation that may be beneficial in NASH, 2) reduced blood triglycerides, 3) reduced intrahepatic cholesterol, and 4) reduced biliary cholesterol levels associated with cholelithiasis. No toxic side effects were detected.

[0121] Furthermore, we developed a humanized version of the SSO targeting the SCARB1 gene, which may be used as an effective therapeutic agent to target the underlying pathological processes associated with the above-mentioned conditions, such as NASH, in humans.

[0122] An initial set of splice-switching oligos (SSOs) was designed. The rationale for the initial round of design was targeting the cis-regulatory region in exon 12 of the human SCARB1 gene. These SSOs were tested in human hepatocytes (derived from induced pluripotency stem cells (iPSCs)) by transfection with 100 nM of the oligos using Lipofectamine 2000. 24 hours after transfection, RNA was extracted and activity was assessed by calculating the splice-in ratio (PSI = exon 12 inclusion / (exon 12 inclusion + exon 12 skipping)).

[0123] As shown in FIG. 18, SSO8.5, which targets the 3′ region of exon 12, showed strong activity in antagonizing exon 12.

[0124] To increase the likelihood of finding the best molecule, we explored other genomic regions and designed a second round of SSOs. The rationale for the second round of design was targeting alternative regions in exon 12 of the human SCARB1 gene. These SSOs were tested in iPSC-derived hepatocytes by transfecting 100 nM of the oligos with Lipofectamine 2000. 24 hours after transfection, RNA was extracted and activity was assessed by calculating PSI. As shown in Figure 19, SSO8.5 remained the more active oligo.

[0125] The most promising candidates from rounds 1 and 2 were then further refined by genome microwalking. The rationale for the design of the third round was to: 1) test the effects of subtle sequence changes in oligos that previously showed some activity; and 2) target identified intronic regulatory elements. Furthermore, to improve activity and / or pharmacokinetics, 3) chemical modifications (2'MOE) were introduced into one of the candidates (SSO8.5), resulting in a new oligo, SSO8.21. Note that human hepatocytes and HepG2 hepatocytes exhibited poor transfection ability, whereas Huh7 hepatocytes exhibited high transfection efficiency. To maximize activity, 13 hSSOs (2'OME-modified: SSO8.5, SSO8.10, SSO8.11, SSO8.12, SSO8.13, SSO8.14, SSO8.15, SSO8.16, SSO8.17, SSO8.18, SSO8.19, SSO8.20 or 2'MOE-modified: SSO8.21) were tested in Huh7 human hepatocytes by transfection at 100 nM with Lipofectamine 2000. 24 hours after transfection, RNA was extracted and activity was assessed by calculating PSI.

[0126] Cells were transfected with 100 nM SSO for 6 hours using Lipofectamine 2000. 24 hours after transfection, RNA was extracted and activity was quantified as PSI of SCARB1 exon 12. Scrambled oligo was used as a control. Results are presented as mean ± SEM (n = 3). Statistical comparisons were performed using Student's T-test ( *** p<0.001).

[0127] As shown in Figure 20, SSO8.5, SSO8.10, SSO8.11, SSO8.18, and SSO8.21 promoted a greater than 60% reduction in PSI of SCARB1 exon 12 (a threshold initially established by DGF application). Notably, both SSO8.18 and SSO8.21 showed very high activity antagonizing SCARB1 exon 12 (promoting the SR-BII isoform). To further test these candidates, we transfected HepG2 cells (an alternative human hepatocyte cell line with much lower transfection efficiency than Huh7 cells). In this system, SSO8.18 showed higher activity, suggesting that this oligo has consistently high activity across different cell types and was therefore selected as the lead hSSO for liver-on-a-chip experiments (Figure 20D). [Example]

[0128] Liver-on-a-chip experiments The liver-on-a-chip is a human microtissue system containing most of the major cell types involved in the development of NASH, including hepatocytes, stellate cells, Kupffer cells, and liver endothelial cells. We used a medium developed by Insphero (Zurich, Switzerland) that promotes the development of NASH and fibrosis that closely resembles the human disease, as assessed by gene expression.

[0129] An oligonucleotide (SSO8.18) designed to promote the expression of the SR-II isoform and a scrambled control (SCR) were used in a liver-on-a-chip model system. Liver microtissues were treated with different doses (1-20 μM) of these SSOs for 3-10 days to assess efficacy and toxicity.

[0130] Five to six microtissues were pooled into three biological replicates. RNA was isolated using the RNAeasy Microkit and reverse-transcribed to cDNA. Expression of SR-BI (including exon 12) and SR-BII (skipping exon 12) was analyzed by PCR and capillary electrophoresis (Figure 21A). This analysis confirmed the potent effect of SSO8.18 in inducing dose-dependent skipping of exon 12 (Figure 21B). Toxicity was assessed by quantifying LDH release; even high doses of SCR or SSO8.18 oligos were not associated with significant toxicity (Figure 21C-D). A dose-response curve with chlorpromazine was used as a positive control (Figure 21E).

[0131] The chemokine CXCL10 (IP-10) has been shown to play an important role in the pathogenesis of hepatitis. Increased expression of SR-BII was associated with decreased expression of inflammatory markers in vivo. Therefore, we tested the effect of SSO8.18 on IP10 expression in liver microtissues (Figure 22A). As shown in Figure 22B, SSO8.18 was able to promote a strong reduction in IP10 levels, confirming its anti-inflammatory activity.

[0132] RNA oligo therapeutics offer multiple pharmacokinetic advantages for the treatment of liver disease. 2' modifications confer increased stability to the oligonucleotide. Therefore, we tested the effect of a single, lower dose of SSO8.18 on its activity in this system. Microtissues were treated with 7.5 μM SSO8.18 or SCR control for 48 hours. After this time, the SSO was washed out, and the microtissues were maintained in SSO-free medium for the remainder of the experiment (Figure 22C, top). Under these conditions, SSO8.18 was able to induce potent splicing changes, promoting the skipping of SCARB1 exon 12, confirming the efficacy of our oligo (Figure 22C, bottom).

[0133] Furthermore, consistent with our previous experiments, treatment with SSO8.18 caused a strong decrease in IP10 levels (FIG. 22E), although no toxicity was detected as assessed by LDH release (FIG. 22D).

[0134] Methods of Examples 1 to 7 mouse C57BL6 / J (Stock No. 000664), Rbfox2 loxP / loxP(Stock no. 014090) (Gehman, L. T. et al. The splicing regulator Rbfox2 is required for both cerebellar development and mature motor function. Genes Dev 26, 445-460 (2012). https: / / doi.org:10.1101 / gad.182477.111) and Albumin-cre (Stock no. 003574) (Postic, C. et al. Dual roles for glucokinase in glucose homeostasis as determined by liver and pancreatic beta cell-specific gene knockouts using Cre recombinase. J Biol Chem 274, 305-315 (1999). https: / / doi.org:10.1074 / jbc.274.1.305) were obtained from Jackson Laboratory. Eight-week-old mice were randomly assigned to experimental groups and received either CD, a high-fat diet (60% kcal from fat, Bioserve), or a high-fructose diet containing 30% (w / v) fructose in their drinking water for 16 to 22 weeks. Mice were housed in a pathogen-free, barrier-free facility at 22°C under a 12-h light-dark cycle and had free access to food and water. The presence of Cre recombinase and Rbfox2 LoxP sites was determined by PCR analysis of genomic DNA and the following primers: CreF1>TTACTGACCGTACCAAATTTGCCTGC (SEQ ID NO: 22) and CreR1>CCTGGCAGCGATCGCTATTTTCCATGAGTG (SEQ ID NO: 23), Rbfox2F1>AACAAGAAAGGCCTCACTTCAG (SEQ ID NO: 24), and Rbfox2R1>GGTGTTCTGACTTATACATGCAC (SEQ ID NO: 25). All in vivo studies were approved by the Imperial College London Animal Welfare and Ethical Review Committee and complied with the UK Animals (Scientific Procedures) Act (1986).

[0135] Adeno- and adeno-associated viruses The adenoviral vector (Ad-m-RBM9) and pAd-GFP that promote mouse RBFOX2 expression were obtained from Vector Biolabs (Malvern, PA, USA). These viruses were purified using the AdEasy virus purification kit (Agilent Technologies). Mice fed the HFr diet were inoculated with 8 × 10 9 GCs were intravenously injected, and mice were harvested 7 days after injection. Codon-optimized RBFOX2 lacking RRM was obtained by gene block synthesis (IDT) and cloned into the AAV-CBA-GFP vector. AAV2 / 8 was generated, purified on an iodixanol gradient, and administered to HFr-fed mice at 5 × 10 11 Mice were harvested 12 weeks after injection.

[0136] Tissue and blood collection Biopsies were snap-frozen in liquid nitrogen and stored at -80°C. Histological sections were fixed in 10% formalin and then embedded in paraffin or frozen in OCT and isopentane. Paraffin sections were stained with hematoxylin and eosin or subjected to immunohistochemistry (IHC) analysis of macrophage infiltration using anti-MRC1 antibody (ab64693) and DAPI (Sigma, D9542) for nuclear staining. Serum was centrifuged at 5000 g for 10 minutes at 4°C and analyzed by the Department of Pathology at St. Mary's Hospital unless otherwise indicated.

[0137] Quantitative proteomics (TMT / MS, Tandem Mass Tag) Snap-frozen livers were lysed using a homogenizer with SDS lysis buffer (2.5% SDS, 50 mM HEPES pH 8.5, 150 mM NaCl, 1x EDTA-free protease inhibitor cocktail (Roche), 1x PhosSTOP phosphatase inhibitor cocktail (Roche)). The lysate was clarified by centrifugation at 13,000 rpm for 15 minutes, and protein concentration was measured using a Pierce BCA assay (Thermo Scientific). 20 mg of protein was reduced with 5 mM TCEP for 30 minutes, alkylated with 14 mM iodoacetamide for 30 minutes, and finally quenched with 10 mM DTT for 15 minutes. All reactions were performed at room temperature. Proteins were precipitated with chloroform-methanol, and the pellet was resuspended in 8 M urea, 50 mM EPPS pH 8.5. To aid resuspension, the protein precipitate was passed through a 22G needle 10 times, and the protein concentration was measured again. Prior to protein digestion, 5 mg of protein was collected and diluted to 1 M urea with 50 mM EPPS, pH 8.5. LysC was then added at a 1:100 (LysC:protein) ratio and digested for 12 hours at room temperature. The sample was further digested with trypsin at a 1:100 (trypsin:protein) ratio for 5 hours at 37°C. 0.4% TFA (pH <2) was added to the sample to stop the digestion. The digested sample was clarified by centrifugation at 13,000 rpm for 10 minutes. Peptide concentration was measured using a quantitative colorimetric peptide assay (Thermo Scientific). 25 μg of peptide was desalted using a 10-mg SOLA HRP SPE cartridge (Thermo Scientific). Two bridge channels were prepared and processed in parallel to allow comparison of both TMTs. To do so, 1.39 μg of each sample was added to each bridge channel.Next, the dried peptides from all 20 samples were resuspended in 200 mM EPPS, pH 8.5, and labeled with TMT-10plex according to the protocol described in Nguyen, AT et al. UBE2O remodels the proteome during terminal erythroid differentiation. Science 357 (2017). https: / / doi.org:10.1126 / science.aan0218. After labeling, both bridge channels were combined and split again to ensure homogeneity. Finally, equal volumes of the samples were mixed. After binding, both TMTs were desalted using tC18 SepPak solid-phase extraction cartridges (Waters) and dried in a SpeedVac. The desalted peptides were then resuspended in 5% ACN, 10 mM NH4HCO3, pH 8. Both TMTs were fractionated by basic pH reverse-phase chromatography using an HPLC equipped with a 3.5 μm Zorbax 300 Extended-C18 column (Agilent). Ninety-six fractions were collected and pooled into 24. Twelve of these were desalted using a C18 Stop and Go Extraction Tip (STAGE-Tip) (Rappsilber, J., Ishihama, Y. & Mann, M. Stop and go extraction tips for matrix-assisted laser desorption / ionization, nanoelectrospray, and LC / MS sample pretreatment in proteomics. Anal Chem 75, 663-670 (2003). https: / / doi.org:10.1021 / ac026117i) and dried in a SpeedVac.Finally, samples were resuspended in 3% ACN, 1% FA and analyzed by Orbitrap Fusion in MS3 mode (McAlister, GC et al. MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal Chem 86, 7150–7158 (2014). https: / / doi.org:10.1021 / ac502040v) as previously described (Nguyen, AT et al. UBE2O remodels the proteome during terminal erythroid differentiation. Science 357 (2017). https: / / doi.org:10.1126 / science.aan0218). RAW data were converted to mzXML format using a modified version of RawFileReader and searched against the Mouse Target Decoy Protein Database (Uniprot, June 11, 2019), which includes the most common contaminants, using the search engine Comet56. The precursor ion tolerance was set to 20 ppm, and the product ion tolerance was set to 1 Da. Cysteine ​​carbamidomethylation (+57.0215 Da) and TMT tag (+229.1629 Da) on lysine residues and the N-terminus of the peptide were set as static modifications. A maximum of two variable methionine oxidations (+15.9949 Da) and two missed cleavages were allowed in the search. Peptide-spectrum matches (PSMs) were adjusted to a 1% FDR by linear discriminant analysis (Huttlin, EL et al. A tissue-specific atlas of mouse protein phosphorylation and expression. Cell 143, 1174-1189 (2010). https: / / doi.org:10.1016 / j.cell.2010.12.001), and proteins were further merged to a final protein-level FDR of 1%.TMT quantification values ​​were obtained from MS3 scans. Only those with a signal-to-noise ratio greater than 100 and a separation specificity greater than 0.7 were used for quantification. Each TMT was normalized to the total signal for each column. To allow comparison of both TMTs and proteins quantified in both TMTs, data were normalized using the bridge channel present in each TMT. Quantifications, included in Supplementary Table 1 (see Paterson et al., Nature Metabolism), are expressed as relative abundance. The newly generated proteome dataset is publicly available as described below.

[0138] iPSC-derived human hepatocytes Human induced pluripotent stem cells (iPSCs) CGT-RCiB-10 (Cell & Gene Therapy Catapult, London, UK) were maintained in Essential 8 Medium (Thermo Fisher Scientific) on Vitronectin XF (STEMCELL Technologies)-coated Corning Costar TC-treated 6-well plates (Sigma-Aldrich) and passaged every 4 days using Gentle Cell Dissociation Reagent (STEMCELL Technologies).

[0139] Hepatocyte differentiation was performed using Essential 6 medium (Thermo Fisher Scientific; days 1–2), RPMI-1640 medium (Sigma-Aldrich; days 3–8), and HepatoZYME-SFM (Thermo Fisher Scientific; days 9 and later) in TC-treated 182 cm 2Culture was performed in flasks (VWR) as previously described (Blackford, SJI et al. Validation of Current Good Manufacturing Practice Compliant Human Pluripotent Stem Cell-Derived Hepatocytes for Cell-Based Therapy. Stem Cells Translational Medicine 8, 124-137 (2019). https: / / doi.org:10.1002 / sctm.18-0084, Jobbins, AM et al. Dysregulated RNA polyadenylation contributes to metabolic impairment in non-alcoholic fatty liver disease. Nucleic Acids Res (2022). https: / / doi.org:10.1093 / nar / gkac165). For hepatocyte differentiation, the medium was supplemented with the following growth factors and small molecules: 3 μM CHIR9901 [day 1] (Sigma-Aldrich), 10 ng / ml BMP4 [days 1–2] (R&D Systems), 10 μM LY29004 [days 1–2] (Promega, Madison, WI), 80 ng / ml FGF2 [days 1–3] (R&D Systems), 100 ng / ml [days 1–3] and 50 ng / ml [days 4–8] activin A (Qkine), 10 ng / ml OSM [days 9 and beyond] (R&D Systems), and 50 ng / ml HGF [days 9 and beyond] (PeproTech). After 21 days, iPSC-derived hepatocytes were dissociated into a single-cell suspension using TrypLE Express Enzyme (10x), phenol red-free (Thermo Fisher Scientific) and seeded onto multiwell plates coated with rat tail type 1 collagen (Sigma-Aldrich).Silencing of human RBFOX2 was performed by transfecting 100 nM smartpool for RBFOX2 or mock control (Horizon) with RNAimax reagent (Invitrogen) in Optimem (Invitrogen).

[0140] AML12 hepatocytes and Dil-HDL uptake AML12 cells were cultured as previously described (Wu, JC, Merlino, G. & Fausto, N. Establishment and characterization of differentiated, nontransformed hepatocyte cell lines derived from mice transgenic for transforming growth factor alpha. Proc Natl Acad Sci USA 91, 674–678 (1994). https: / / doi.org:10.1073 / pnas.91.2.674). Scarb1 silencing was achieved by transfecting 100 nM of SmartPool for Scarb1 or mock control (Horizon) using RNAimax reagent (Invitrogen) in Optimem (Invitrogen). Expression of SR-BI and SR-BII was achieved by cloning codon-optimized SR-BI and SR-BII (generated by gblock synthesis at IDT) into the pLV(PGK)-GFP Neo vector. Third-generation lentivirus was produced in HEK-293T cells and purified by high-speed centrifugation. Virus was resuspended in medium supplemented with polybrene and added to cells. Where indicated, cells were incubated with 100 ng / ml Dil-HDL for 4 hours, and lipid uptake was quantified by FACS using a FACSAria III cell sorter system (BD Biosciences).

[0141] RNA isolation Cells or tissues were homogenized with TRIzol (Thermo Fisher Scientific) and RNA was extracted according to the manufacturer's instructions. For RNA sequencing, after homogenization with TRIzol, RNA was extracted using RNeasy kit columns (Qiagen) according to the manufacturer's instructions, including DNase I treatment.

[0142] RNAseq sequencing and analysis RNA quality control was performed using a 2100 BioAnalyser (Agilent, CA, USA). Samples with a RIN > 8 were subjected to poly(A) enrichment, and libraries were prepared using the NEBNext Ultra II RNA Library Prep Kit for Illumina and multiplexed using NEBNext Multiplex Oligos for Illumina (NEB, E7760S and E7335S). Sequencing was performed using a HiSeq 2500 (Illumina) with 100-bp paired-end reads. The newly generated RNA-seq datasets are publicly available as described below. A published dataset of mice fed a high-fructose diet was obtained from GSE123896 (Zhang, G. et al. Differential metabolic and multi-tissue transcriptomic responses to fructose consumption among genetically diverse mice. Biochim Biophys Acta Mol Basis Dis 1866, 165569 (2020). https: / / doi.org:10.1016 / j.bbadis.2019.165569). Reads were aligned to the Ensembl mouse genome (GRCm38) using TopHat2 (2.0.11) (Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions, and gene fusions. Genome Biol 14, R36 (2013). https: / / doi.org:10.1186 / gb-2013-14-4-r36) with the argument "-library-type fr-firststrand." Reference sequence assembly and transcript annotation were obtained from Illumina iGenomes (https: / / support.illumina.com / sequencing / sequencing_software / igenome.Gene-based read counts were calculated using the featureCounts function in the Rsubread Bioconductor package (Liao, Y., Smyth, GK & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923-930 (2014). https: / / doi.org:10.1093 / bioinformatics / btt656). Normalization and differential expression analysis were performed using DEseq2 (Love, MI, Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 2014 15:12 15, 1-21 (2014). https: / / doi.org:10.1186 / S13059-014-0550-8) or edgeR-voom-limma (Robinson, MD, McCarthy, DJ & Smyth, GK edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139-140 (2010). https: / / doi.org:10.1093 / bioinformatics / btp616, Law, CW, Chen, Y., Shi, W. & Smyth, GK voom: Precision weights unlock linear model analysis tools) for RNA-seq read counts. Genome Biol 15, R29 (2014). https: / / doi.org:10.1186 / gb-2014-15-2-r29, Ritchie, ME et al.Limma powers differential expression analyses for RNA sequencing and microarray studies. Nucleic Acids Res 43, e47 (2015). https: / / doi.org:10.1093 / nar / gkv007; Huber, W. et al. Orchestrating high-throughput genomic analysis with Bioconductor. Nat Methods 12, 115-121 (2015). https: / / doi.org:10.1038 / nmeth.3252) were performed using the bioconductor package. Alternative splicing was primarily analyzed with rMAT (Shen, S. et al. rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data. Proc Natl Acad Sci USA 111, E5593-5601 (2014). https: / / doi.org:10.1073 / pnas.1419161111). Differentially spliced ​​sites were retained for data visualization if they exceeded the following thresholds: p<0.05, FDR<0.1, and absolute (IncLevelDifference) >0.1 or <-0.1. Gene ontology analysis was performed using the GOseq Bioconductor package (Young, MD, Wakefield, MJ, Smyth, GK & Oshlack, A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol 11, R14 (2010). https: / / doi.org:10.1186 / gb-2010-11-2-r14). Lists of differentially expressed genes with adjusted p<0.05 were analyzed using Ingenuity Pathway Analysis (IPA Inc.; http: / / www.ingenuity.com / index.html).html) were selected as input for the SF-specific SF analysis. No cutoff was applied to the fold change in differential expression. Enrichment of binding motifs for different SFs was tested using the binomTest function in the edgeR bioconductor package (McCarthy, DJ, Chen, Y. & Smyth, GK Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res 40, 4288-4297 (2012). https: / / doi.org:10.1093 / nar / gks042).

[0143] Lipidomic analysis Tissues were pulverized using a cyroPREP Dry Pulverizer (Covaris). This method was adapted from Folch et al. (Folch, J., Lees, M. & Sloane Stanley, GH. A simple method for the isolation and purification of total lipids from animal tissues. J Biol Chem 226, 497-509 (1957)). Approximately 30 mg of frozen liver powder was weighed into a weighed Eppendorf flask. The tissue was homogenized using a stainless steel ball and 1 ml of chloroform:methanol (2:1) in a TissueLyzer (20 Hz, 3–5 min × 2). The stainless steel ball was removed, 400 μl of HPLC-grade water was added, and the sample was vortexed for 20 s and centrifuged at 13,200 × g for 15 min at room temperature. Both the organic and aqueous layers were removed. The protein pellet was re-extracted with 500ul of 2:1 chloroform:methanol and 200ul of HPLC grade water, the sample was vortexed and centrifuged, and the respective fractions were combined.

[0144] Lipid profiling was performed by liquid chromatography high-resolution mass spectrometry (LC-HRMS) using a Vanquish Flex Binary UHPLC system (Thermo Scientific) coupled with a benchtop hybrid quadrupole-Orbitrap Q-Exactive mass spectrometer (Thermo Scientific). Chromatographic separation was performed on an Acquity UPLC BEH C18 column (Waters, 50 × 2.1 mm, 1.7 μm) at 55 °C and a flow rate of 0.5 mL / min. For positive ion mode, the mobile phase consisted of 60:40 (v / v) acetonitrile / water + 10 mM ammonium formate (solvent A) and 90:10 (v / v) isopropanol:acetonitrile + 10 mM ammonium formate (solvent B). For negative ionization, the mobile phase consisted of 60:40 (v / v) acetonitrile / water + 10 mM ammonium acetate (solvent A) and 90:10 (v / v) isopropanol:acetonitrile + 10 mM ammonium acetate (solvent B). A gradient elution program was run for both ionization modes according to Supplementary Table 4 (see Paterson et al., Nature Metabolism), with a total run time of 10 min per sample. The injection volumes for positive and negative ionization modes were 5 μL and 10 μL, respectively. Ionization was performed using a heated electrospray ion source (HESI), with the following positive and negative mode parameters: capillary voltage 3.5 / -2.5 KV, heater temperature 438 °C, capillary temperature 320 °C, S-lens RF level 50, and sheath, auxiliary, and sweep gas flow rates of 53, 14, and 1 unit, respectively. Mass accuracy was calibrated for both ionization modes prior to sample analysis. High-resolution mass spectrometry (m / z 200 at 70,000) data were acquired in profile mode using full scan settings (m / z 200–2000). The automatic gain control (AGC) was set to 1e6, and the maximum injection time for MS1 was set to 200 ms.Lipidomic data acquisition was performed using Xcalibur software (version 4.1). Peak picking was performed using XCMS (Smith, CA, Want, EJ, O'Maille, G., Abagyan, R. & Siuzdak, G. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal Chem 78, 779-787 (2006). https: / / doi.org:10.1021 / ac051437y) and normalized to isotopically labeled internal standards and dry tissue weight. Lipid identification was performed by accurate mass using an in-house database. Bile acid analysis was performed using liquid chromatography tandem mass spectrometry (LC-MS / MS) on an Acquity I-Class binary UPLC system (Waters) coupled to a triple quadrupole Xevo TQ-XS mass spectrometer as previously described (https: / / www.waters.com / webassets / cms / library / docs / 720006261en.pdf) (Waters). Chromatographic separation was performed using a CORTECS T3 column (Waters, 30 × 2.1 mm, 2.7 μm) at 60 °C and a flow rate of 1.3 mL / min. The mobile phase consisted of 0.2 mM ammonium formate + 0.01% (v / v) formic acid (solvent A) and 50:50 (v / v) isopropanol / acetonitrile + 0.01% (v / v) formic acid and 0.2 mM ammonium formate. The elution gradient program started with a 0.1 min hold at 20% B, ramped to 55% B over 0.7 min, and then included a 0.9 min column wash at 98% B. The column was re-equilibrated to the initial conditions, resulting in a total run time of 1.71 min per sample. The injection volume was 10 μL.Data were acquired using multiple reaction monitoring (MRM) in negative ion mode according to Supplementary Table 5 (see Paterson et al., Nature Metabolism). Source parameters were as follows: -2.0 kV capillary voltage, 60 V cone voltage, desolvation temperature 600 °C, cone and desolvation gas flow rates of 150 L / hr and 1000 L / hr, respectively. Data were acquired using MassLynx software (version 4.2) and processed with TargetLynx XS (Waters).

[0145] Quantification of liver triglycerides Liver (50–200 mg) was added to 350 μl of ethanolic KOH (2 ethanol (100%):1 KOH (30%)) and incubated overnight at 50°C. After incubation, the sample was vortexed, 650 μl of ethanol (50%) was added, and the mixture was centrifuged at maximum speed for 5 minutes. 900 μl of the supernatant was mixed with 300 μl of ethanol (50%), and 200 μl of the sample was mixed with 215 μl of 1 M MgCl2 and incubated on ice for 10 minutes. The sample was then centrifuged at maximum speed for 5 minutes, and 10 μl of the supernatant was assayed for glycerol content using free glycerol reagent (Sigma).

[0146] Protein analysis The tissue was homogenized in Triton Lysis Buffer (12.5 mM HEPES pH 7.4, 50 mM NaCl, 500 μM EDTA, 5% glycerol, 0.5% Triton X-100, 50 mM sodium vanadate, 50 mM PMSF, 5 mM aprotinin, 5 mM leupeptin) using a TissueLyser II Homogenizer (Qiagen), followed by centrifugation at 10,000 rpm for 10 minutes at 4°C. The supernatant was transferred to a new tube, and protein was quantified using the Pierce BCA Protein Assay Kit (Thermo Fisher Scientific). The supernatant was analyzed by Western blot analysis by incubation with anti-RBFOX2 (Bethyl Laboratories), anti-PLA2G6 (Santa Cruz), anti-SREBP1 (Pharmigen), anti-vinculin, anti-APOB, anti-ABCA1, anti-ACC, anti-pS79 ACC, anti-FASN (Cell signaling), and anti-tubulin (Santa Cruz) primary antibodies, and imaged using an Odyssey infrared scanner (LICOR).

[0147] glucose tolerance test For the glucose tolerance test, animals were fasted for 16 hours and then given an ip injection of 1 g / kg glucose. Blood glucose levels were measured using a Contour XT glucometer (Roche).

[0148] Lipoprotein fractionation and characterization Major lipoprotein fractions, namely, very low-density lipoprotein (VLDL, d < 1.019 g / ml), low-density lipoprotein (LDL, d = 1.019-1.063 g / ml), and high-density lipoprotein (HDL, d = 1.063-1.21 g / ml), were sequentially separated from plasma by sequential ultracentrifugation at 100,000 rpm at 15°C in a Beckman Optima Max-TL centrifuge after centrifugation for 1 hour 30 minutes, 3 hours 30 minutes, and 5 hours 30 minutes, respectively. After isolation, lipoprotein fractions were analyzed for lipid and protein content using commercially available kits on a calibrated AutoAnalyzer (Konelab 20). Total cholesterol, free cholesterol, and phospholipids were measured using Diasys reagents. The mass of cholesteryl ester (CE) was calculated as (TC-FC) × 1.67 and thus represents the sum of the esterified cholesterol and fatty acid moieties. Triglycerides were quantified using a commercially available kit (Thermo Electron). Protein was quantified using the bicinchoninic acid assay reagent (Pierce, Thermo Fisher Scientific). Lipoprotein mass was calculated as the sum of the masses of the individual lipid and protein components of each lipoprotein fraction.

[0149] primary hepatocytes The liver was perfused with liver perfusion buffer (HBSS, 0.4 g / L KCl, 1 g / L glucose, 2.1 g / L NaHCO3, 0.2 g / L EDTA) and then digested with liver digestion buffer (DMEM-GlutaMAX 1 g / L glucose, 15 mM HEPES pH 7.4, 1% penicillin / streptomycin, 5 mg / mL mouse collagenase IV (C5138, Sigma). After removal, the liver was placed on ice in plating medium (M199, 10% FBS, 1% penicillin / streptomycin, 1% sodium pyruvate, 1% L-glutamine, 1 mM insulin, 1 mM dexamethasone, 2 mg / mL BSA). The tissue was homogenized using tweezers and then filtered with plating medium. The cells were then washed twice with plating medium and subsequently separated using a 1:3 Percol gradient (Sigma). Cells were plated onto collagen-coated plates (ThermoFisher Scientific) in plating medium. After 3 hours, the medium was replaced with maintenance medium (DMEM 4.5 g glucose / L, penicillin / streptomycin 1%, L-glutamine 1%, 100 nM dexamethasone, 2 mg / ml BSA). After 12 hours of culture, hepatocytes were treated as indicated.

[0150] Generation of cell lines expressing pGIPZ lentiviral shRNA Lentiviral shRNA (sh1-Foxa1 - v2lmm14620, sh4-Foxa2 - v2lmm71498) clones were recovered from the pGIPZ library according to the manufacturer's protocol (ThermoFisher) and used to obtain lentivirus and generate stable Hepa1-6 cells.

[0151] antisense oligonucleotides RNA splice-switching oligonucleotides (SSOs) were synthesized with 2'O-ME modifications and phosphorothioate backbones (Eurogentec). The sequences of the SSOs are listed in Table 1. Cells were transfected by incubating 100 nM of SSO with Lipofectamine 2000 in OptiMEM (Thermo Fisher Scientific). For in vivo studies, 40 mg / kg / week of oligonucleotide or saline was injected subcutaneously weekly for 4 consecutive weeks.

[0152] Processing of CAGE-seq and ChIP-seq data CAGE-supported transcriptional start sites (CTSSs) mapped by the FANTOM5 project (Lizio, M. et al. Gateways to the FANTOM5 promoter-level mammalian expression atlas. Genome Biol 16, 22 (2015). https: / / doi.org:10.1186 / s13059-014-0560-6, Noguchi, S. et al. FANTOM5 CAGE profiles of human and mouse samples. Sci Data 4, 170112 (2017). https: / / doi.org:10.1038 / sdata.2017.112, Lizio, M. et al. Update of the FANTOM web resource: expansion to provide additional transcriptome atlases. Nucleic Acids Res 47, D752-D758 (2019)). https: / / doi.org:10.1093 / nar / gky1099) was imported into R (http: / / www.R-project.org / ) as a CTSS table. Replicates were merged and normalized using the standard workflow within the CAGEr package (Haberle, V., Forrest, A. R, Hayashizaki, Y., Carninci, P. & Lenhard, B. CAGEr: precise TSS data retrieval and high-resolution promoterome mining for integrative analyses. Nucleic Acids Res 43, e51 (2015). https: / / doi.org:10.1093 / nar / gkv054).Processed bigwig files corresponding to human adult liver ChIP-seq signal p-values ​​were obtained from the ENCODE portal (Sloan, CA et al. ENCODE data at the ENCODE portal. Nucleic Acids Res 44, D726-732 (2016). https: / / doi.org:10.1093 / nar / gkv1160): FOXA1 (ENCFF058DKS) (Dunham, I. et al. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57-74 (2012). https: / / doi.org:10.1038 / nature11247), FOXA2 (ENCFF902TMK) (Dunham, I. et al. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57-74 (2012). https: / / doi.org:10.1038 / nature11247), K3K4me3(ENCFF610REU)(Bernstein, BE et al. The NIH Roadmap Epigenomics Mapping Consortium. Nat Biotechnol 28, 1045-1048 (2010). https: / / doi.org:10.1038 / nbt1010-1045), and H3K27ac(ENCFF012XAP)(Bernstein, BE et al. The NIH Roadmap Epigenomics Mapping Consortium. Nat Biotechnol 28, 1045-1048 (2010). https: / / doi.org:10.1038 / nbt1010-1045).Mouse liver FOXA1 ChIP-seq data (GSE106379) was retrieved from (Grimm, SA et al. DNA methylation in mice is influenced by genetics as well as sex and life experience. Nat Commun 10, 305 (2019). https: / / doi.org:10.1038 / s41467-018-08067-z).

[0153] RT-PCR analysis RNA was reverse transcribed using the High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher Scientific). Quantification was performed on a QuantStudio 7 Flex Real-Time PCR system (Thermo Fisher Scientific) using Taqman Gene Expression Assays (Thermo Fisher Scientific) with probes from the Roche Universal Probe Library or Fast SYBR-Green Mix (Thermo Fisher Scientific). All data were analyzed using relative standard curves or the delta-CT method. Ribosomal 18S RNA was used for sample normalization in all cases. Alternative splicing analysis was performed using primers designed to detect multiple mRNA isoforms. Targets were amplified by PCR and analyzed by capillary electrophoresis using a QIAxcel Advanced System (Qiagen). AS was calculated as the splice-in fraction (PSI) of a particular splicing event across samples (PSI = (long isoform) / (long isoform + short isoform)). * 100) The probes and primers used in this analysis are listed in Supplementary Table 3 (see Paterson et al. Nature Metabolism).

[0154] UV cross-linking and immunoprecipitation (eiCLIP) with enhanced resolution of individual nucleotides A modified version of a previously described nonisotopic individual nucleotide resolution UV cross-linking and immunoprecipitation (iCLIP) workflow (Sibley, CR Individual Nucleotide Resolution UV Cross-Linking and Immunoprecipitation (iCLIP) to Determine Protein-RNA Interactions. Methods Mol Biol 1649, 427-454 (2018). https: / / doi.org:10.1007 / 978-1-4939-7213-5_29) was performed with new modifications to improve speed and efficiency. Specifically, a shortened Cy5.5-labeled adapter was incorporated ( / 5Phos / A[XXXXXX]NNNAGATCGGAAGAGCACACG / 3Cy55Sp / ) (SEQ ID NO: 26), adapter ligation was enhanced using high-concentration T4 RNA ligase (New England Biolabs), unligated adapters were removed using RecJf exonuclease (New England Biolabs) prior to SDS-PAGE, which was visualized in the 700 nm channel, reverse transcription was performed using a biotinylated primer homologous to the adapter ( / 5BiotinTEG / CGTGTGCTCTTCCGA) (SEQ ID NO: 27), unincorporated RT primers were removed by exonuclease III (New England Biolabs) after annealing to their reverse complement, and the cDNA was transferred to MyOne Streptavidin C1 magnetic beads (Thermo Fisher Scientific). The bead-bound cDNA was captured with streptavidin beads (Streptavidin Scientific) and ligated to a 3' adapter ( / 5Phos / ANNNNNNNAGATCGGAAGAGCGTCGTG / 3ddC / ) (SEQ ID NO: 28) instead of the intramolecular ligation used previously, and the cDNA was eluted from the streptavidin beads at elevated temperature using nuclease- and cation-free water.Cellular proteomes were captured on SeraMag carboxyl beads (Sigma-Aldrich) and subjected to the eiCLIP protocol in parallel with the RBFOX2 immunoprecipitation complex to prepare a 5% size-matched input. RBFOX2 eiCLIP was performed using isolated primary hepatocytes with 1 μg / μl of RBM9 Antibody (A300-A864A, Bethyl Laboratories)—total protein was quantified at 4 μg / μl, and antibody was added at 8 μg / ml. Samples from three independent hepatocyte cultures, each from two mice, were sequenced with paired-end reads using the MiSeq system (Illumina).

[0155] Mapping and identification of cross-linking clusters from eCLIP and eiCLIP experiments For mapping of eCLIP and eiCLIP RBFOX2 sequencing data, we used GENCODE assembly annotation version "GRCm38.VM20" for mouse and "GRCh38.p7" for human samples. For eCLIP samples, we used double adapter removal according to the recommended ENCODE eCLIP pipeline: (https: / / www.encodeproject.org / pipelines / ENCPL357ADL / ). For adapter removal of eiCLIP sequencing samples, we also used the "cutadapt" tool (https: / / cutadapt.readthedocs.io / en / stable / ) with the following parameters: "cutadapt -f fastq --match-read-wildcards --times 1 -e 0.1 -O 1 --quality-cutoff 6 -m 18 -a AGATCGGAAG $INPUT.fastq > $OUTPUT.adapterTrim.fastq 2 > $OUTPUT.adapterTrim.metrics". Both eCLIP and eiCLIP samples were aligned using the STAR alignment tool (version 2.4.2a) (https: / / github.com / alexdobin / STAR) with the following parameters: "STAR -runThreadN 8 -runMode alignReads -genomeDir GRCh38 Gencode v25 -genomeLoad LoadAndKeep -readFilesIn read1, read2, -readFilesCommand zcat -outSAMunmapped Within -outFilterMultimapNmax 1 -outFilterMultimapScoreRange 1 -outSAMattributes All - outSAMtype BAM Unsorted -outFilterType BySJout -outFilterScoreMin 10 -alignEndsType EndToEnd -outFileNamePrefix outfile".

[0156] To correct for overamplification in eCLIP samples, we used the barcode-integrated Python script "barcode_collapse_pe.py," available on GitHub (https: / / github.com / YeoLab / gscripts / releases / tag / 1.0). For eiCLIP samples, we also used a custom Python script to replace the first 7 nt of the FASTQ sequence line with a random barcode, up to the FASTQ header line. Then, uniquely mapped reads with the same genomic location and the same random barcode were removed as PCR duplicates.

[0157] To identify binding clusters, we used the cDNA-start as the cross-linking position and as input for the False Discovery Rate clustering tool available in iMaps ( https: / / imaps.genialis.com / iclip ).

[0158] Clusters were identified using the Paraclu clustering algorithm (http: / / cbrc3.cbrc.jp / ~martin / paraclu / ) with default parameters. The semantic space of RBFOX2 eiCLIP targets was visualized with REVIGO (Supek, F., Bosnjak, M., Skunca, N. & Smuc, T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS One 6, e21800 (2011). https: / / doi.org:10.1371 / journal.pone.0021800).

[0159] Motif enrichment for eCLIP and eiCLIP cross-linking sites To identify enrichment of RBFOX2 binding motifs for crosslinking sites, we used density plots of previously known (U)GCAUG binding motifs (Jin, Y. et al. A vertebrate RNA-binding protein Fox-1 regulates tissue-specific splicing via the pentanucleotide GCAUG. EMBO J 22, 905-912 (2003). https: / / doi.org:10.1093 / emboj / cdg089; Auweter, SD et al. Molecular basis of RNA recognition by the human alternative splicing factor Fox-1. EMBO J 25, 163-173 (2006). https: / / doi.org:10.1038 / sj.emboj.7600918) for the eiCLIP cDNA-start sequences from mouse liver samples and HepG2 samples from ENCODE. Each position on the graph was normalized by the total number of cDNAs mapped from all three replicate samples.

[0160] Comparison of human and mouse RBFOX2 binding sites The RBFOX2 cross-linking cluster liftover from mouse (mm10) to human (hg38) was performed using the UCSC online tool (https: / / genome.ucsc.edu / cgi-bin / hgLiftOver). The overlap analysis between binding sites was performed using pybedtools (Quinlan, AR & Hall, IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841-842 (2010). https: / / doi.org:10.1093 / bioinformatics / btq033; Dale, RK, Pedersen, BS & Quinlan, AR. Pybedtools: a flexible Python library for manipulating genomic datasets and annotations. Bioinformatics 27, 3423-3424 (2011). https: / / doi.org:10.1093 / bioinformatics / btr539).

[0161] Enrichment analysis of orthologous RBFOX2 target genes Human orthologous genes of mouse RBFOX2 targets detected by eiCLIP were searched in BioMart (Smedley, D. et al. BioMart--biological queries made easy. BMC Genomics 10, 22 (2009). https: / / doi.org:10.1186 / 1471-2164-10-22), and enrichment of genes associated with common traits / diseases was examined using EnrichR (Chen, EY et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14, 128 (2013). https: / / doi.org:10.1186 / 1471-2105-14-128, Kuleshov, MV et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res 44, W90-97 (2016). https: / / doi.org:10.1093 / nar / gkw377).

[0162] RNA map surrounding RBFOX2-regulated exons Alternatively spliced ​​and regulated exons were analyzed using the “junctionSeq” Bioconductor package (https: / / www.bioconductor.org / packages / release / bioc / html / JunctionSeq.html) from the splicing event table MATS.SE with the following parameters: WT and L ΔRbfox2 Selected from liver RNAseq samples. - Upregulated exons: p-value<0.05, FDR<0.1, IncLevelDifference>0.2 - Downregulated exons: p-value<0.05, FDR<0.1, IncLevelDifference<-0.2 - Control exon: p-value<0.05, FDR<0.1, absolute (IncLevelDifference)<0.1

[0163] For splicing regulation analysis of RBFOX2 eiCLIP, we used the previously published RNAmaps approach (Haberman, N. et al. Insights into the design and interpretation of iCLIP experiments. Genome Biol 18, 7 (2017). https: / / doi.org:10.1186 / s13059-016-1130-x) Chakrabarti, 2018 #1261). Density graphs were plotted as the distribution of cDNA-starts of RBFOX2 eiCLIP samples relative to 5' and 3' splice sites. All three replicates were grouped together, and exons in each group were normalized by the total number of exons per group.

[0164] statistical analysis Differences between dietary groups and gene targets were analyzed for statistical significance using one-way or two-way ANOVA tests. Where applicable, pairwise comparisons were analyzed with the Mann-Whitney U test or two-tailed Student's t test. Results are presented as mean ± SEM.

[0165] Data availability: Mass spectrometry data have been deposited with the ProteomeXchange Consortium via the PRIDE partner repository (Vizcaino, JA et al. 2016 update of the PRIDE database and its related tools. Nucleic Acids Res 44, D447-456 (2016). https: / / doi.org:10.1093 / nar / gkv1145) under the dataset identifier PXDxx. RNA-seq and eiCLIP data generated for this study have been deposited in GEO under the accession number GSE151753.

[0166] Code Availability The code corresponding to Figures 1E–G and Figures 3B and C has been published in a GitHub repository (https: / / github.com / nebo56 / RBFOX2-data_analysis).

[0167] References 1 Pan, Q., Shai, O., Lee, LJ, Frey, BJ & Blencowe, BJ Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet 40, 1413-1415 (2008). https: / / doi.org:10.1038 / ng.259 2 Wang, ET et al. Alternative isoform regulation in human tissue transcriptomes. Nature 456, 470-476 (2008). https: / / doi.org:10.1038 / nature07509 3 Blencowe, BJ Reflections for the 20th anniversary issue of RNA journal. RNA 21, 573-575 (2015). https: / / doi.org:10.1261 / rna.051003.115 4 Buljan, M. et al. Tissue-specific splicing of disordered segments that embed binding motifs rewires protein interaction networks. Mol Cell 46, 871-883 (2012). https: / / doi.org:10.1016 / j.molcel.2012.05.039 5 Ellis, J. D. et al. Tissue-specific alternative splicing remodels protein-protein interaction networks. Mol Cell 46, 884-892 (2012). https: / / doi.org:10.1016 / j.molcel.2012.05.037 6 Yang, X. et al. Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing. Cell 164, 805-817 (2016). https: / / doi.org:10.1016 / j.cell.2016.01.029 7 Raal, F. J. et al. Mipomersen, an apolipoprotein B synthesis inhibitor, for lowering of LDL cholesterol concentrations in patients with homozygous familial hypercholesterolaemia: a randomised, double-blind, placebo-controlled trial. Lancet 375, 998-1006 (2010). https: / / doi.org:10.1016 / S0140-6736(10)60284-X 8 Ray, K. K. et al. Inclisiran in Patients at High Cardiovascular Risk with Elevated LDL Cholesterol. N Engl J Med 376, 1430-1440 (2017). https: / / doi.org:10.1056 / NEJMoa1615758 9 Eslam, M., Sanyal, A. J., George, J. & International Consensus, P. MAFLD: A Consensus-Driven Proposed Nomenclature for Metabolic Associated Fatty Liver Disease. Gastroenterology 158, 1999-2014 e1991 (2020). https: / / doi.org:10.1053 / j.gastro.2019.11.312 10 Friedman, S. L., Neuschwander-Tetri, B. A., Rinella, M. & Sanyal, A. J. Mechanisms of NAFLD development and therapeutic strategies. Nat Med 24, 908-922 (2018). https: / / doi.org:10.1038 / s41591-018-0104-9 11 Turpin-Nolan, S. M. & Bruning, J. C. The role of ceramides in metabolic disorders: when size and localization matters. Nat Rev Endocrinol 16, 224-233 (2020). https: / / doi.org:10.1038 / s41574-020-0320-5 12 Hall, Z. et al. Lipid zonation and phospholipid remodeling in nonalcoholic fatty liver disease. Hepatology 65, 1165-1180 (2017). https: / / doi.org:10.1002 / hep.28953 13 Ioannou, G. N. The Role of Cholesterol in the Pathogenesis of NASH. Trends Endocrinol Metab 27, 84-95 (2016). https: / / doi.org:10.1016 / j.tem.2015.11.008 14 Corey, K. E. & Chalasani, N. Management of dyslipidemia as a cardiovascular risk factor in individuals with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol 12, 1077-1084; quiz e1059-1060 (2014). https: / / doi.org:10.1016 / j.cgh.2013.08.014 15 Collaborators, G. B. D. O. et al. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. N Engl J Med 377, 13-27 (2017). https: / / doi.org:10.1056 / NEJMoa1614362 16 Zhang, G. et al. Differential metabolic and multi-tissue transcriptomic responses to fructose consumption among genetically diverse mice. Biochim Biophys Acta Mol Basis Dis 1866, 165569 (2020). https: / / doi.org:10.1016 / j.bbadis.2019.165569 17 Van Nostrand, E. L. et al. Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP). Nat Methods 13, 508-514 (2016). https: / / doi.org:10.1038 / nmeth.3810 18 Tabula Muris, C. et al. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature 562, 367-372 (2018). https: / / doi.org:10.1038 / s41586-018-0590-4 19 Damianov, A. & Black, D. L. Autoregulation of Fox protein expression to produce dominant negative splicing factors. RNA 16, 405-416 (2010). https: / / doi.org:10.1261 / rna.1838210 20 Jangi, M., Boutz, P. L., Paul, P. & Sharp, P. A. Rbfox2 controls autoregulation in RNA-binding protein networks. Genes Dev 28, 637-651 (2014). https: / / doi.org:10.1101 / gad.235770.113 21 Irimia, M. & Blencowe, B. J. Alternative splicing: decoding an expansive regulatory layer. Curr Opin Cell Biol 24, 323-332 (2012). https: / / doi.org:10.1016 / j.ceb.2012.03.005 22 Jin, Y. et al. A vertebrate RNA-binding protein Fox-1 regulates tissue-specific splicing via the pentanucleotide GCAUG. EMBO J 22, 905-912 (2003). https: / / doi.org:10.1093 / emboj / cdg089 23 Yeo, G. W. et al. An RNA code for the FOX2 splicing regulator revealed by mapping RNA-protein interactions in stem cells. Nat Struct Mol Biol 16, 130-137 (2009). https: / / doi.org:10.1038 / nsmb.1545 24 Zhang, C. et al. Defining the regulatory network of the tissue-specific splicing factors Fox-1 and Fox-2. Genes Dev 22, 2550-2563 (2008). https: / / doi.org:10.1101 / gad.1703108 25 Underwood, J. G., Boutz, P. L., Dougherty, J. D., Stoilov, P. & Black, D. L. Homologues of the Caenorhabditis elegans Fox-1 protein are neuronal splicing regulators in mammals. Mol Cell Biol 25, 10005-10016 (2005). https: / / doi.org:10.1128 / MCB.25.22.10005-10016.2005 26 Nakahata, S. & Kawamoto, S. Tissue-dependent isoforms of mammalian Fox-1 homologs are associated with tissue-specific splicing activities. Nucleic Acids Res 33, 2078-2089 (2005). https: / / doi.org:10.1093 / nar / gki338 27 Modafferi, E. F. & Black, D. L. A complex intronic splicing enhancer from the c-src pre-mRNA activates inclusion of a heterologous exon. Mol Cell Biol 17, 6537-6545 (1997). https: / / doi.org:10.1128 / MCB.17.11.6537 28 Kozarsky, K. F. et al. Overexpression of the HDL receptor SR-BI alters plasma HDL and bile cholesterol levels. Nature 387, 414-417 (1997). https: / / doi.org:10.1038 / 387414a0 29 Acton, S. et al. Identification of scavenger receptor SR-BI as a high density lipoprotein receptor. Science 271, 518-520 (1996). https: / / doi.org:10.1126 / science.271.5248.518 30 Dennis, E. A., Cao, J., Hsu, Y. H., Magrioti, V. & Kokotos, G. Phospholipase A2 enzymes: physical structure, biological function, disease implication, chemical inhibition, and therapeutic intervention. Chem Rev 111, 6130-6185 (2011). https: / / doi.org:10.1021 / cr200085w 31 Han, J. et al. The CREB coactivator CRTC2 controls hepatic lipid metabolism by regulating SREBP1. Nature 524, 243-246 (2015). https: / / doi.org:10.1038 / nature14557 32 Gusarova, V., Brodsky, J. L. & Fisher, E. A. Apolipoprotein B100 exit from the endoplasmic reticulum (ER) is COPII-dependent, and its lipidation to very low density lipoprotein occurs post-ER. J Biol Chem 278, 48051-48058 (2003). https: / / doi.org:10.1074 / jbc.M306898200 33 Temel, R. E. et al. Hepatic Niemann-Pick C1-like 1 regulates biliary cholesterol concentration and is a target of ezetimibe. J Clin Invest 117, 1968-1978 (2007). https: / / doi.org:10.1172 / JCI30060 34 Horton, J. D., Goldstein, J. L. & Brown, M. S. SREBPs: activators of the complete program of cholesterol and fatty acid synthesis in the liver. J Clin Invest 109, 1125-1131 (2002). https: / / doi.org:10.1172 / JCI15593 35 Bochkis, I. M. et al. Hepatocyte-specific ablation of Foxa2 alters bile acid homeostasis and results in endoplasmic reticulum stress. Nat Med 14, 828-836 (2008). https: / / doi.org:10.1038 / nm.1853 36 Moya, M. et al. Foxa1 reduces lipid accumulation in human hepatocytes and is downregulated in nonalcoholic fatty liver. PLoS One 7, e30014 (2012). https: / / doi.org:10.1371 / journal.pone.0030014 37 Webb, N. R. et al. SR-BII, an isoform of the scavenger receptor BI containing an alternate cytoplasmic tail, mediates lipid transfer between high density lipoprotein and cells. J Biol Chem 273, 15241-15248 (1998). https: / / doi.org:10.1074 / jbc.273.24.15241 38 Puri, P. et al. A lipidomic analysis of nonalcoholic fatty liver disease. Hepatology 46, 1081-1090 (2007). https: / / doi.org:10.1002 / hep.21763 39 Trigatti, B. et al. Influence of the high density lipoprotein receptor SR-BI on reproductive and cardiovascular pathophysiology. Proc Natl Acad Sci U S A 96, 9322-9327 (1999). https: / / doi.org:10.1073 / pnas.96.16.9322 40 Huby, T. et al. Knockdown expression and hepatic deficiency reveal an atheroprotective role for SR-BI in liver and peripheral tissues. J Clin Invest 116, 2767-2776 (2006). https: / / doi.org:10.1172 / JCI26893 41 Sen, S., Jumaa, H. & Webster, N. J. Splicing factor SRSF3 is crucial for hepatocyte differentiation and metabolic function. Nat Commun 4, 1336 (2013). https: / / doi.org:10.1038 / ncomms2342 42 Wei, N. et al. SRSF10 Plays a Role in Myoblast Differentiation and Glucose Production via Regulation of Alternative Splicing. Cell Rep 13, 1647-1657 (2015). https: / / doi.org:10.1016 / j.celrep.2015.10.038 43 Benegiamo, G. et al. The RNA-Binding Protein NONO Coordinates Hepatic Adaptation to Feeding. Cell Metab 27, 404-418 e407 (2018). https: / / doi.org:10.1016 / j.cmet.2017.12.010 44 Pihlajamaki, J. et al. Expression of the splicing factor gene SFRS10 is reduced in human obesity and contributes to enhanced lipogenesis. Cell Metabolism 14, 208-218 (2011). https: / / doi.org:10.1016 / j.cmet.2011.06.007 45 Nikolaou, K. C. et al. The RNA-Binding Protein A1CF Regulates Hepatic Fructose and Glycerol Metabolism via Alternative RNA Splicing. Cell Rep 29, 283-300 e288 (2019). https: / / doi.org:10.1016 / j.celrep.2019.08.100 46 Kuroyanagi, H. Fox-1 family of RNA-binding proteins. Cell Mol Life Sci 66, 3895-3907 (2009). https: / / doi.org:10.1007 / s00018-009-0120-5 47 Min, H. K. et al. Increased hepatic synthesis and dysregulation of cholesterol metabolism is associated with the severity of nonalcoholic fatty liver disease. Cell Metab 15, 665-674 (2012). https: / / doi.org:10.1016 / j.cmet.2012.04.004 48 Eckhardt, E. R. et al. High density lipoprotein endocytosis by scavenger receptor SRBII is clathrin-dependent and requires a carboxyl-terminal dileucine motif. J Biol Chem 281, 4348-4353 (2006). https: / / doi.org:10.1074 / jbc.M513154200 49 Emerging Risk Factors, C. et al. Major lipids, apolipoproteins, and risk of vascular disease. JAMA 302, 1993-2000 (2009). https: / / doi.org:10.1001 / jama.2009.1619 50 Zanoni, P. et al. Rare variant in scavenger receptor BI raises HDL cholesterol and increases risk of coronary heart disease. Science 351, 1166-1171 (2016). https: / / doi.org:10.1126 / science.aad3517 51 Gehman, L. T. et al. The splicing regulator Rbfox2 is required for both cerebellar development and mature motor function. Genes Dev 26, 445-460 (2012). https: / / doi.org:10.1101 / gad.182477.111 52 Postic, C. et al. Dual roles for glucokinase in glucose homeostasis as determined by liver and pancreatic beta cell-specific gene knock-outs using Cre recombinase. J Biol Chem 274, 305-315 (1999). https: / / doi.org:10.1074 / jbc.274.1.305 53 Nguyen, A. T. et al. UBE2O remodels the proteome during terminal erythroid differentiation. Science 357 (2017). https: / / doi.org:10.1126 / science.aan0218 54 Rappsilber, J., Ishihama, Y. & Mann, M. Stop and go extraction tips for matrixassisted laser desorption / ionization, nanoelectrospray, and LC / MS sample pretreatment in proteomics. Anal Chem 75, 663-670 (2003). https: / / doi.org:10.1021 / ac026117i 55 McAlister, G. C. et al. MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal Chem 86, 7150-7158 (2014). https: / / doi.org:10.1021 / ac502040v 56 Eng, J. K., Jahan, T. A. & Hoopmann, M. R. Comet: an open-source MS / MS sequence database search tool. Proteomics 13, 22-24 (2013). https: / / doi.org:10.1002 / pmic.201200439 57 Huttlin, E. L. et al. A tissue-specific atlas of mouse protein phosphorylation and expression. Cell 143, 1174-1189 (2010). https: / / doi.org:10.1016 / j.cell.2010.12.001 58 Blackford, S. J. I. et al. Validation of Current Good Manufacturing Practice Compliant Human Pluripotent Stem Cell-Derived Hepatocytes for Cell-Based Therapy. Stem Cells Translational Medicine 8, 124-137 (2019). https: / / doi.org:10.1002 / sctm.18-0084 59 Jobbins, A. M. et al. Dysregulated RNA polyadenylation contributes to metabolic impairment in non-alcoholic fatty liver disease. Nucleic Acids Res (2022). https: / / doi.org:10.1093 / nar / gkac165 60 Wu, J. C., Merlino, G. & Fausto, N. Establishment and characterization of differentiated, nontransformed hepatocyte cell lines derived from mice transgenic for transforming growth factor alpha. Proc Natl Acad Sci U S A 91, 674-678 (1994). https: / / doi.org:10.1073 / pnas.91.2.674 61 Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol 14, R36 (2013). https: / / doi.org:10.1186 / gb-2013-14-4-r36 62 Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923-930 (2014). https: / / doi.org:10.1093 / bioinformatics / btt656 63 Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 2014 15:12 15, 1-21 (2014). https: / / doi.org:10.1186 / S13059-014-0550-8 64 Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139-140 (2010). https: / / doi.org:10.1093 / bioinformatics / btp616 65 Law, C. W., Chen, Y., Shi, W. & Smyth, G. K. voom: Precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 15, R29 (2014). https: / / doi.org:10.1186 / gb-2014-15-2-r29 66 Ritchie, M. E. et al. limma powers differential expression analyses for RNAsequencing and microarray studies. Nucleic Acids Res 43, e47 (2015). https: / / doi.org:10.1093 / nar / gkv007 67 Huber, W. et al. Orchestrating high-throughput genomic analysis with Bioconductor. Nat Methods 12, 115-121 (2015). https: / / doi.org:10.1038 / nmeth.3252 68 Shen, S. et al. rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data. Proc Natl Acad Sci U S A 111, E5593-5601 (2014). https: / / doi.org:10.1073 / pnas.1419161111 69 Young, M. D., Wakefield, M. J., Smyth, G. K. & Oshlack, A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol 11, R14 (2010). https: / / doi.org:10.1186 / gb-2010-11-2-r14 70 McCarthy, D. J., Chen, Y. & Smyth, G. K. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res 40, 4288-4297 (2012). https: / / doi.org:10.1093 / nar / gks042 71 Folch, J., Lees, M. & Sloane Stanley, G. H. A simple method for the isolation and purification of total lipides from animal tissues. J Biol Chem 226, 497-509 (1957). 72 Smith, C. A., Want, E. J., O'Maille, G., Abagyan, R. & Siuzdak, G. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal Chem 78, 779-787 (2006). https: / / doi.org:10.1021 / ac051437y 73 Lizio, M. et al. Gateways to the FANTOM5 promoter level mammalian expression atlas. Genome Biol 16, 22 (2015). https: / / doi.org:10.1186 / s13059-014-0560-6 74 Noguchi, S. et al. FANTOM5 CAGE profiles of human and mouse samples. Sci Data 4, 170112 (2017). https: / / doi.org:10.1038 / sdata.2017.112 75 Lizio, M. et al. Update of the FANTOM web resource: expansion to provide additional transcriptome atlases. Nucleic Acids Res 47, D752-D758 (2019). https: / / doi.org:10.1093 / nar / gky1099 76 Haberle, V., Forrest, A. R., Hayashizaki, Y., Carninci, P. & Lenhard, B. CAGEr: precise TSS data retrieval and high-resolution promoterome mining for integrative analyses. Nucleic Acids Res 43, e51 (2015). https: / / doi.org:10.1093 / nar / gkv054 77 Sloan, C. A. et al. ENCODE data at the ENCODE portal. Nucleic Acids Res 44, D726-732 (2016). https: / / doi.org:10.1093 / nar / gkv1160 78 Dunham, I. et al. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57-74 (2012). https: / / doi.org:10.1038 / nature11247 79 Bernstein, B. E. et al. The NIH Roadmap Epigenomics Mapping Consortium. Nat Biotechnol 28, 1045-1048 (2010). https: / / doi.org:10.1038 / nbt1010-1045 80 Grimm, S. A. et al. DNA methylation in mice is influenced by genetics as well as sex and life experience. Nat Commun 10, 305 (2019). https: / / doi.org:10.1038 / s41467-018-08067-z 81 Sibley, C. R. Individual Nucleotide Resolution UV Cross-Linking and Immunoprecipitation (iCLIP) to Determine Protein-RNA Interactions. Methods Mol Biol 1649, 427-454 (2018). https: / / doi.org:10.1007 / 978-1-4939-7213-5_29 82 Supek, F., Bosnjak, M., Skunca, N. & Smuc, T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS One 6, e21800 (2011). https: / / doi.org:10.1371 / journal.pone.0021800 83 Auweter, S. D. et al. Molecular basis of RNA recognition by the human alternative splicing factor Fox-1. EMBO J 25, 163-173 (2006). https: / / doi.org:10.1038 / sj.emboj.7600918 84 Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841-842 (2010). https: / / doi.org:10.1093 / bioinformatics / btq033 85 Dale, R. K., Pedersen, B. S. & Quinlan, A. R. Pybedtools: a flexible Python library for manipulating genomic datasets and annotations. Bioinformatics 27, 3423-3424 (2011). https: / / doi.org:10.1093 / bioinformatics / btr539 86 Smedley, D. et al. BioMart--biological queries made easy. BMC Genomics 10, 22 (2009). https: / / doi.org:10.1186 / 1471-2164-10-22 87 Chen, E. Y. et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14, 128 (2013). https: / / doi.org:10.1186 / 1471-2105-14-128 88 Kuleshov, M. V. et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res 44, W90-97 (2016). https: / / doi.org:10.1093 / nar / gkw377 89 Haberman, N. et al. Insights into the design and interpretation of iCLIP experiments. Genome Biol 18, 7 (2017). https: / / doi.org:10.1186 / s13059-016-1130-x 90 Vizcaino, J. A. et al. 2016 update of the PRIDE database and its related tools. Nucleic Acids Res 44, D447-456 (2016). https: / / doi.org:10.1093 / nar / gkv1145

Claims

1. An antisense oligomer capable of inducing exon 12 skipping of scavenger receptor class B type I (SCARB1).

2. The antisense oligomer of claim 1, which is capable of inducing skipping of exon 12 of human SCARB1.

3. 3. The antisense oligomer of claim 1 or 2, which is 10 to 45 nucleobases, 12 to 40 nucleobases, 15 to 35 nucleobases, 18 to 30 nucleobases, or 19 to 25 nucleobases in length.

4. The antisense oligomer of any one of claims 1 to 3, comprising the nucleic acid base sequence set forth in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19, and comprising five, four, three, two, one, or less substitutions, deletions, or insertions.

5. The antisense oligomer of any one of claims 1 to 4, comprising a nucleobase sequence set forth in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19, wherein one or more nucleobases are substituted with modified nucleobases capable of base pairing with nucleobases of the same type.

6. The antisense oligomer according to any one of claims 1 to 3, comprising the nucleic acid base sequence shown in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19.

7. The antisense oligomer according to any one of claims 1 to 3, comprising the nucleic acid base sequence shown in any one of SEQ ID NOs: 5, 8, 10, 11, 18, or 19.

8. 3. The antisense oligomer of claim 1 or 2, wherein the nucleic acid base sequence of the antisense oligomer is set forth in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19.

9. The antisense oligomer according to any one of claims 1 to 8, which is complementary to 5 bases, 10 bases, 15 bases, 16 bases, 17 bases, 18 bases, 19 bases, 20 bases, or all bases of an antisense oligomer shown in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19.

10. The antisense oligomer according to any one of claims 1 to 9, which is complementary to all 5, 10, 15, 16, 17, 18, 19, or 20 bases complementary to SSO8.18 (SEQ ID NO: 51).

11. The antisense oligomer according to any one of claims 1 to 10, comprising at least one 2'-O-methyl nucleotide and / or at least one 2'-O-methoxyethyl nucleotide.

12. The antisense oligomer according to any one of claims 1 to 11, which is a 2'-O-methyl nucleic acid oligomer and / or a 2'-O-methoxyethyl nucleic acid oligomer.

13. 13. The antisense oligomer of any one of claims 1 to 12, comprising at least one phosphorothioate internucleotide linkage.

14. The antisense oligomer of any one of claims 1 to 13, wherein all internucleotide linkages in the antisense oligomer are phosphorothioate internucleotide linkages.

15. The antisense oligomer is an oligonucleotide having the nucleobase sequence of SEQ ID NO: 5, 8, 10, 11, 18, or 19, and is selected from the group consisting of -O-CH ３ or -O-CH ２ -CH ２ -O-CH ３ The antisense oligomer of any one of claims 1 to 14, wherein is linked to the 2'-position of the sugar moiety of each nucleotide.

16. An antisense oligonucleotide having a sequence shown in any one of SEQ ID NOs: 4, 5, 7, 8, 9, 10, 11, 12, 18, or 19, wherein the internucleotide bond is a phosphorothioate internucleotide bond, and ３ or -O-CH ２ -CH ２ -O-CH ３ is attached to the 2'-position of the sugar moiety of each nucleotide.

17. 17. The antisense oligomer of any one of claims 1 to 16, which is SSO8.5 (SEQ ID NO:38), SSO8.8 (SEQ ID NO:41), SSO8.10 (SEQ ID NO:43), SSO8.11 (SEQ ID NO:44), SSO8.18 (SEQ ID NO:51), SSO8.19 (SEQ ID NO:52), or SSO8.21 (SEQ ID NO:54), or which comprises SSO8.5 (SEQ ID NO:38), SSO8.8 (SEQ ID NO:41), SSO8.10 (SEQ ID NO:43), SSO8.11 (SEQ ID NO:44), SSO8.18 (SEQ ID NO:51), SSO8.19 (SEQ ID NO:52), or SSO8.21 (SEQ ID NO:54).

18. 18. The antisense oligomer of any one of claims 1 to 17, which is or comprises SSO8.18 (SEQ ID NO: 51).

19. A pharmaceutical composition comprising the antisense oligomer or antisense oligonucleotide according to any one of claims 1 to 18.

20. 20. The antisense oligomer, antisense oligonucleotide, or pharmaceutical composition according to any one of claims 1 to 19, for use as a pharmaceutical.

21. 20. The antisense oligomer, antisense oligonucleotide, or pharmaceutical composition according to any one of claims 1 to 19, for use in a method for treating or preventing a metabolic-related disease.

22. 20. An antisense oligomer, antisense oligonucleotide or pharmaceutical composition according to any one of claims 1 to 19 for use in a method for the treatment or prevention of obesity and / or the pathological effects of an obesogenic diet.

23. 23. The antisense oligomer, antisense oligonucleotide or pharmaceutical composition for use according to claim 22, wherein the pathological effect is hepatitis, lipotoxicity, hepatocellular injury, and / or fibrosis.

24. 20. The antisense oligomer, antisense oligonucleotide, or pharmaceutical composition according to any one of claims 1 to 19, for use in a method for treating or preventing hepatitis.

25. 25. The antisense oligomer, antisense oligonucleotide or pharmaceutical composition for use according to claim 24, wherein the hepatitis is obesity-induced.

26. 20. The antisense oligomer, antisense oligonucleotide, or pharmaceutical composition according to any one of claims 1 to 19, for use in a method for treating or preventing metabolically-associated fatty liver disease (MAFLD).

27. 20. The antisense oligomer, antisense oligonucleotide or pharmaceutical composition according to any one of claims 1 to 19, for use in a method for treating or preventing preclinical hepatic steatosis.

28. 20. The antisense oligomer, antisense oligonucleotide, or pharmaceutical composition according to any one of claims 1 to 19, for use in a method for treating or preventing non-alcoholic steatohepatitis (NASH).

29. 20. The antisense oligomer, antisense oligonucleotide, or pharmaceutical composition of any of claims 1 to 19 for use in a method for treating or preventing hepatocellular carcinoma (HCC) in a subject.

30. 30. The antisense oligomer, antisense oligonucleotide, or pharmaceutical composition for use according to claim 29, wherein the subject has hepatitis, preclinical hepatic steatosis, or NASH.

31. 20. The antisense oligomer, antisense oligonucleotide, or pharmaceutical composition according to any one of claims 1 to 19, for use in the treatment or prevention of any one or a combination of cholelithiasis, type 2 diabetes, cardiovascular disease, and coronary artery disease.

32. 20. The antisense oligomer, antisense oligonucleotide, or pharmaceutical composition of any of claims 1 to 19 for use in a method of treatment comprising lowering cholesterol levels in a subject in need thereof.

33. 20. A method for increasing expression of scavenger receptor class B type I (Scarb1) isoform SR-BII relative to isoform SR-BII in a cell, the method comprising contacting the cell with a composition comprising an antisense oligomer or antisense oligonucleotide according to any one of claims 1 to 18.

34. 34. The method of claim 33, wherein the method is in vivo and the composition is administered to a subject in need thereof.

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