Liver cell regeneration

Abstract

A method for regenerating liver cells in a subject with hepatocyte degeneration is provided, comprising administering an agent that modulates one or more genes or markers, including C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, and ILKAP, wherein the agent interferes with hepatocyte degeneration and / or enhances liver cell regeneration. Also disclosed are nucleic acids encoding agents for inhibiting the one or more genes or markers, compositions or vectors or plasmids containing the nucleic acids, kits containing the nucleic acids, and compositions or vectors or plasmids for use in therapy.

Description

Technical Field

[0001] The present disclosure relates generally to methods and compositions for regenerating hepatocytes.

Background Art

[0002] Non-alcoholic fatty liver disease (NAFLD) is currently the number one chronic liver disease in the world. In its progressive form, non-alcoholic steatohepatitis (NASH), NASH causes liver fibrosis, cirrhosis, and liver cancer. However, despite its seemingly unstoppable increase, the mechanisms underlying the disease's onset and progression remain unclear. Furthermore, other than liver transplantation, the only drug approved by the FDA for the treatment of patients with moderate to advanced fibrosis is resmetirom, with a limited efficacy rate of only 30%. In addition to these difficulties, accurate diagnosis and staging rely on invasive liver biopsies.

[0003] The worldwide prevalence rates are 25% for NAFLD and 3 - 5% for NASH. Since there is currently no approved drug therapy, the socioeconomic impact of this disease and the burden on the healthcare system are immeasurably high. In Singapore, it is estimated that over 40% of the population is affected by NAFLD.

[0004] From the above, it is necessary to understand the underlying pathogenesis. There is also a need to provide alternative diagnostic methods and treatment targets.

Summary of the Invention

[0005] In one embodiment, a method is provided for regenerating liver cells in a subject having hepatocyte degeneration, comprising administering an agent that modulates one or more genes or markers consisting of C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, and ILKAP, wherein the agent interferes with hepatocyte degeneration and / or enhances liver cell regeneration.

[0006] In some examples, one or more genes or markers further include ABCB10, LSM14A, ACTG1, YTHDF2, RPS6KA1, SEC13, IPO11, CTCF, UBAP2L, P2RY2, TRAF3IP2, FST, TUBG1, ZNF664, PVR, DYX1C1 / DNAAF4, TEX264, NIF3L1, RPUSD1, TRIM6, GLRX3, BRD1, CKS1B, C6ORF120, WASF2, ZNF689, B4GALT7, LCORL, NR2F2, BAG6, and RNF10.

[0007] In some cases, one or more genes or markers are Uba6, Brwd3, Fyco1, ARID5B, C20ORF96 (6820408C15Rik), CD200R1 (Cd200r4), DALRD3, ELF3, ELFN1, FAM160A1, FAM50B, KIAA2026 (9930021J03Rik), KREMEN1, MACC1, NAA25, PROSC / PLPBP, RPS3, SHPK, SLAIN1, TCHP, ZNF503 (Zfp503), BUD13, CD93, PFKFB2, ZDBF2, FOXC2, GBGT1, RGS4, RNASEH1, TSNAXIP1, LYPD2 Further includes STIL, TMCO3, TMEM159, RIF1, IFIH1, EPN2, CLP1, RNF220, NOL12, APOL3, GTF3C6, CTPS2, IFITM2, IFITM1, KCNS3, CA2, EIF4H, MRM1, AKAP8, PAPOLA, SECTM1, TYK2, MLLT6, IL1RL2, IPO7, APBB1IP, RABEP2, PLSCR1, PYGO2, COIL, LRRC8E, TNRC6C, CHD3, USP21, SNX27, NOP14, ZC3H15, C15orf39, UTP20, TRAK1, RAB11FIP2, PHPT1, CUL3, and GNL3.

[0008] In some cases, liver cells are liver cells.

[0009] In some cases, liver degeneration is non-alcoholic fatty liver disease (NAFLD) and / or non-alcoholic steatohepatitis (NASH).

[0010] In some cases, the agent reduces or inhibits the expression of a gene or marker.

[0011] In some cases, the agent is a nucleic acid that can interfere with the expression of a specific gene.

[0012] In another embodiment, nucleic acids encoding agents for inhibiting one or more genes or markers are provided, including C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, and ILKAP.

[0013] In some examples, one or more genes or markers further include ABCB10, LSM14A, ACTG1, YTHDF2, RPS6KA1, SEC13, IPO11, CTCF, UBAP2L, P2RY2, TRAF3IP2, FST, TUBG1, ZNF664, PVR, DYX1C1 / DNAAF4, TEX264, NIF3L1, RPUSD1, TRIM6, GLRX3, BRD1, CKS1B, C6ORF120, WASF2, ZNF689, B4GALT7, LCORL, NR2F2, BAG6, and RNF10.

[0014] In some cases, one or more genes or markers are UBA6, BRWD3, FYCO1, ARID5B, C20ORF96 (6820408C15Rik), CD200R1 (Cd200r4), DALRD3, ELF3, ELFN1, FAM160A1, FAM50B, KIAA2026 (9930021J03Rik), KREMEN1, MACC1, NAA25, PROSC / PLPBP, RPS3, SHPK, SLAIN1, TCHP, ZNF503 (Zfp503), BUD13, CD93, PFKFB2, ZDBF2, FOXC2, GBGT1, RGS4, RNASEH1, TSNAXIP1, LYPD2, STIL, TMCO3, TMEM159, RIF1, IFIH1, EPN2, CLP1, RNF220, NOL12, APOL3, GTF3C6, CTPS2, IFITM2, IFITM1, KCNS3, CA2, EIF4H, MRM1, AKAP8, PAPOLA, SECTM1, TYK2, MLLT6, IL1RL2, IPO7, APBB1IP, RABEP2, PLSCR1, PYGO2, COIL, LRRC8E, TNRC6C, CHD3, USP21, SNX27, NOP14, ZC3H15, C15ORF39, UTP20, TRAK1, RAB11FIP2, PHPT1, CUL3, and GNL3 may further be included.

[0015] In some cases, nucleic acids include one or more of the following: RNAi (RNA interference), small hairpin RNA (shRNA), antisense oligonucleotides (ASOs), gapmers, small hairpin antisense oligonucleotides (shASOs), lipid nanoparticles, adeno-associated virus vectors, gene editing agents, ribozymes, or nucleic acid-based nanoparticles.

[0016] In some cases, the nucleic acid is shRNA.

[0017] In some cases, the nucleic acid is shRNA and contains a sequence selected from the following group:

[0018] [Table 1]

[0019] 15. The nucleic acid according to any one of claims 9 to 14, which is siRNA.

[0020] 16. The nucleic acid according to any one of claims 9 to 15, which is siRNA and contains a sequence selected from the following group

[0021] [Table 2-1]

[0022] [Table 2-2]

[0023] [Table 3-1]

[0024] [Table 3-2]

[0025] [Table 4-1]

[0026] [Table 4-2]

[0027] [Table 5-1]

[0028] [Table 5-2]

[0029] [Table 6-1]

[0030] [Table 6-2]

[0031] In yet another embodiment, a composition, vector, or plasmid comprising one or more nucleic acids disclosed herein is provided.

[0032] In yet another embodiment, a composition, vector, or plasmid comprising one or more nucleic acids disclosed herein is provided for use in therapy.

[0033] In yet another embodiment, a kit comprising the nucleic acids disclosed herein is provided. [Brief explanation of the drawing]

[0034] [Figure 1] A diagram showing basic information about NAFLD (global prevalence) is provided. [Figure 2] This provides a schematic overview of the progression of NAFLD and its global burden. [Figure 3] This provides a schematic overview of the bench-to-bedside RNAi approach. [Figure 4] A table of diet-induced mouse models for NAFLD and NASH is shown. [Figure 5] This study shows that feeding C57Bl6 mice a "Western-style diet" containing fructose in their drinking water induces progressive NAFLD, leading to fatty liver disease and progressive fibrosis after 26 weeks. [Figure 6] A schematic outline of a full in vivo functional genomics screening setup for identifying therapeutic targets is presented. [Figure 7] The table shows that next-generation sequencing before and after injection of the 32 subpools of the genome-wide shRNA library of this application demonstrates superior coverage. [Figure 8] The bar graph shows that next-generation sequencing before and after injection of the 32 subpools of the genome-wide shRNA library of this application demonstrates superior coverage. [Figure 9] A schematic outline illustrating the basics of differential expression analysis is provided. [Figure 10] The box plots shown illustrate the different analysis pipelines used for differential expression analysis. [Figure 11] The graph shows the results of differential expression analysis. Prioritization is performed on enriched therapeutic shRNAs for conversion from therapeutic targets to RNAi. [Figure 12] The diagram shows the main selection criteria for highly reliable targets. [Figure 13] A table showing top score candidates for validation (primary analysis) and the STRING network analysis are presented. [Figure 14] An outline of the additional selection process I is provided below. [Figure 15] The table with added scoring targets and the STRING network analysis are shown. Targets showing dysregulation (*) and targets already in the validation process (#) in the local NAFLD patient cohort are marked. [Figure 16] The figure for target gene identification (filtering step) (expanded analysis) Top Hits I is shown. [Figure 17] The figure for target gene identification (filtering step) (expanded analysis) Top Hits II is shown. [Figure 18] Target gene identification; a diagram showing cross-referencing with transcriptomics from the EMULSION NAFLD patient cohort is presented. [Figure 19] This document presents a table of stringing network analysis results and highly stringent selection criteria for prioritizing 49 gene targets. [Figure 20] The table shows expanded stringent selection criteria, with the prioritized gene target list extended to 243 genes. [Figure 21]This shows a STRING (https: / / string-db.org / ) network analysis of 242 prioritized gene targets, which demonstrates connectivity between several targets. [Figure 22] The table shows that increasing the cutoff criteria narrows the top priority list to 28 gene targets. [Figure 23] This shows a STRING (https: / / string-db.org / ) network analysis of 83 prioritized gene targets, which demonstrates connectivity between several targets. [Figure 24] The STRING network analysis and table are shown, and by increasing the cutoff criteria, the top priority list is further narrowed down to 54 gene targets. The STRING (https: / / string-db.org / ) network analysis of the 42 prioritized gene targets shows connectivity between several targets. [Figure 25] The results of confluence growth curves and cell doubling time assays for in vitro validation of the target are shown. [Figure 26] The results of a wound healing assay to validate the target are shown. [Figure 27-28] The results of the EdU uptake assay to validate the target are shown. [Figure 29] The graph for candidate 281004N23Rik shows strong enrichment of shRNA targeting the candidate. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis does not show an unfavorable relationship with cancer survival. [Figure 30] This shows the STRING (https: / / string-db.org / ) network analysis of 281004N23Rik, which reveals its association with several biological processes (chromosomes, RNA binding, Cul4-RING E3 ubiquitin ligase complex). [Figure 31] Based on TCGA data analysis, a bar graph is shown indicating that 281004N23Rik amplification is associated with liver cancer, suggesting that knockdown of 281004N23Rik in hepatocytes should be safe. [Figure 32A] Microscopic images and graphs illustrating target validation in vitro are shown. 281004N23Rik knockdown accelerates cell migration and proliferation. Screening with shRNA expression scoring allows for efficient knockdown in immortalized mouse liver cell lines. Wound healing assays demonstrate that wound cleft closure is accelerated in a knockdown-dependent manner. [Figure 32B] Microscopic images and graphs of the regrowth model are shown. The regrowth assay demonstrated that knockdown of the target in vivo accelerated clonal proliferation of hepatocytes, demonstrating faster regeneration. Importantly, this represents hepatocyte proliferation in chronically injured livers. FAH- / - hepatocytes are dying and being replaced by FAH-expressing hepatocytes. [Figure 32C] Microscopic images and graphs of a Western-style diet model are shown. Progressive NAFLD was induced in fully regrowing mice in which all hepatocytes expressed the target shRNA by feeding them a "Western-style diet." Representative images are shown on the left. Quantitative results of blinded fibrosis scores by a certified pathologist are shown on the right. Knockdown of this target significantly reduced the level of fibrosis. [Figure 32D]Microscopic images and graphs of a partial hepatectomy model are shown. Partial hepatectomy (PH) is the surgical removal of two-thirds of the liver of a mouse that has completely regrowthed, with all hepatocytes expressing the target shRNA. PH is acute liver injury and induces synchronic proliferation of hepatocytes to regenerate the liver. Representative images of Ki67 staining are shown on the left. On the right are quantitative evaluations of Ki67 staining at PH (0 hours) and 48 hours postoperatively. Knockdown of this target accelerates liver regeneration, which is indicated by an increase in the number of Ki67-positive hepatocytes at 48 hours. Furthermore, since 0 hours represents the point of complete regrowth, the fact that the baseline Ki67 positivity level after target knockdown is equivalent to that of the control shRNA indicates that the regeneration termination after regrowth is fully functional. This proves that the safety checkpoint that prevents hepatomegaly and "excessive" regeneration remains intact. Knockdown of the target only releases the regeneration break and accelerates regeneration; the safety checkpoint is not disabled. This emphasizes the safety of knocking down this target. [Figure 33] The graph for candidate Ythdf2 shows strong enrichment of shRNA targeting the candidate. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis shows that low expression of the target is beneficial for survival in liver cancer. [Figure 34] This shows the STRING (https: / / string-db.org / ) network analysis of Ythdf2, which reveals its association with several biological processes (transcription, mRNA deadenylation, RNA metabolism, and reversal of alkylation damage by DNA dioxygenase). [Figure 35] Based on TCGA data analysis, the bar graph shows that Ythdf2 does not show significant changes in liver cancer, suggesting that knockdown of Ythdf2 in hepatocytes should be safe. [Figure 36]Microscopic images and graphs illustrating target validation in vitro are shown. Ythdf2 knockdown accelerates cell migration and proliferation. Screening with shRNA expression scoring yields efficient knockdown in immortalized mouse liver cell lines. Wound healing assays show accelerated wound cleft closure in a knockdown-dependent manner. EdU uptake assays show a slight increase in proliferation with candidate knockdown. Cell confluence assays show a reduction in cell doubling time. [Figure 37] The table below shows the GWAS analysis results illustrating the association between Ythdf2 and diabetes. [Figure 38] The graph for candidate Golga7B shows strong enrichment of shRNA targeting the candidate. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis shows that low expression of the target is beneficial for survival in liver cancer. [Figure 39] STRING (https: / / string-db.org / ) network analysis of Golga7B reveals associations with several biological processes (p38-, MAPK-, G protein signaling, EGFR, sphingolipids, glycine, serine, and threonine metabolism). [Figure 40] Based on TCGA data analysis, a graph of Golga7B amplification associated with liver cancer is shown, indicating that knockdown of Golga7B in hepatocytes should be safe. [Figure 41] Microscopic images and graphs illustrating target validation in vitro are shown. Golga7B knockdown accelerates cell migration and proliferation. Screening with shRNA expression scoring yields efficient knockdown in immortalized mouse liver cell lines. Wound healing assays show accelerated wound cleft closure in a knockdown-dependent manner. EdU uptake assays show a slight increase in proliferation with candidate knockdown. Cell confluence assays show a reduction in cell doubling time. [Figure 42]Graph of candidate Sec13. Strong enrichment of shRNA targeting the candidate. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis shows that low expression of the target is beneficial for survival in liver cancer. [Figure 43] STRING (https: / / string-db.org / ) network analysis of Sec13 shows associations with several biological processes (cargo loading of COPII-coated vesicles, nuclear pores). [Figure 44] Based on TCGA data analysis, a graph of Sec13 amplification associated with liver cancer is shown, indicating that knockdown of Sec13 in hepatocytes should be safe. [Figure 45] Microscopic images and graphs regarding target validation in vitro are shown. Sec13 knockdown accelerates cell proliferation. Knockdown can be obtained in immortalized mouse liver cell lines by screening that scores shRNA expression. EdU uptake assays show a slight increase in proliferation with candidate knockdown. [Figure 46] The graph for candidate Mrpl49 shows strong enrichment of shRNA targeting the candidate. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis does not show an unfavorable relationship with cancer survival. [Figure 47] STRING (https: / / string-db.org / ) network analysis of Mrpl49 shows associations with several biological processes (translation, mitochondrial translation, mitochondrial ribosomes). [Figure 48] The graph shows that Mrpl49 does not show any specific significant changes in liver cancer, which suggests that knockdown of Mrpl49 in hepatocytes should be safe. [Figure 49]The graph shows target validation in vitro. Mrpl49 knockdown accelerates cell proliferation. Screening that scores shRNA expression allows for efficient knockdown in immortalized mouse liver cell lines. EdU uptake assays show that candidate knockdown slightly increases proliferation. [Figure 50] The graph for candidate Med28 shows strong enrichment of shRNA targeting the candidate. The local NAFLD patient cohort does not show significant stage-specific expression changes. TCGA survival analysis shows that low expression of the target is beneficial for survival in hepatocellular carcinoma. Amplification of Med28 is associated with hepatocellular carcinoma based on TCGA data analysis, which suggests that knockdown of Med28 in hepatocytes should be safe. [Figure 51] This shows the STRING (https: / / string-db.org / ) network analysis of Med28, which reveals its association with several biological processes (lipid metabolism, transcription, protein ubiquitination, and stem cell maintenance). [Figure 52] Microscopic images and bar graphs illustrating target validation in vitro are shown. Med28 knockdown accelerates cell migration and proliferation. Screening with shRNA expression scoring yields efficient knockdown in immortalized mouse liver cell lines. Wound healing assays show that wound cleft closure is accelerated in a knockdown-dependent manner. EdU uptake assays show a slight increase in proliferation with candidate knockdown. Cell confluence assays show a reduction in cell doubling time. [Figure 53] The graph for candidate Fam117b shows strong enrichment of shRNA targeting the candidate. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis shows that low expression of the target is beneficial for survival in hepatocellular carcinoma. Amplification of Fam117b is associated with hepatocellular carcinoma based on TCGA data analysis, which suggests that knockdown of Fam117b in hepatocytes should be safe. [Figure 54]This shows a STRING (https: / / string-db.org / ) network analysis of Fam117b, which reveals its association with several biological processes (G0 and early G1, cell cycle, DNA replication, beta-catenin). [Figure 55] Microscopic images and bar graphs illustrating target validation in vitro are shown. Fam117b knockdown accelerates cell migration and proliferation. Screening with shRNA expression scoring yields efficient knockdown in immortalized mouse liver cell lines. Wound healing assays show accelerated wound cleft closure in a knockdown-dependent manner. EdU uptake assays show a slight increase in proliferation with candidate knockdown. Cell confluence assays show a reduction in cell doubling time. [Figure 56] A graph of candidate Slc45a4 is shown. Strong enrichment of shRNA targeting the candidate is observed. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis shows that low expression of the target is beneficial for survival in hepatocellular carcinoma. Amplification of Slc45a4 is associated with hepatocellular carcinoma based on TCGA data analysis, suggesting that knockdown of Slc45a4 in hepatocytes should be safe. [Figure 57] This shows the STRING (https: / / string-db.org / ) network analysis of Slc45a4, which reveals its association with several biological processes (TNF-, IL-17-, CD95- signaling, TP53, and nucleoside transmembrane transporter activity). [Figure 58] Microscopic images and bar graphs illustrating target validation in vitro are shown. Slc45a4 knockdown accelerates cell migration and proliferation. Screening with shRNA expression scoring yields efficient knockdown in immortalized mouse liver cell lines. Wound healing assays show accelerated wound cleft closure in a knockdown-dependent manner. EdU uptake assays show a slight increase in proliferation with candidate knockdown. Cell confluence assays show a reduction in cell doubling time. [Figure 59]A graph of candidate Tsc22d4 is shown. Strong enrichment of shRNA targeting the candidate is observed. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis shows that low expression of the target is beneficial for survival in hepatocellular carcinoma. Amplification of Tsc22d4 is associated with hepatocellular carcinoma based on TCGA data analysis, suggesting that knockdown of Tsc22d4 in hepatocytes should be safe. [Figure 60] This shows the STRING (https: / / string-db.org / ) network analysis of Tsc22d4, which reveals its association with several biological processes (G proteins, GTPase activity, PI3K-Akt-mTOR signaling, insulin secretion). [Figure 61] The graphs show target validation in vitro. Tsc22d4 knockdown accelerates cell migration and proliferation. Screening that scores shRNA expression yields efficient knockdown in immortalized mouse liver cell lines. Wound healing assays show that wound cleft closure is accelerated in a knockdown-dependent manner. EdU uptake assays show a slight increase in proliferation with candidate knockdown. Cell confluence assays show a reduction in cell doubling time. [Figure 62] The graph shows candidate Arl6ip5. Strong enrichment of shRNA targeting the candidate is observed. The local NAFLD patient cohort does not show significant stage-specific expression changes. TCGA survival analysis does not indicate liver cancer concerns. Arl6ip5 mutations are associated with liver cancer based on TCGA data analysis, suggesting that knockdown of Arl6ip5 in hepatocytes should be safe. [Figure 63] This shows the STRING (https: / / string-db.org / ) network analysis of Arl6ip5, which reveals its association with several biological processes (intracellular protein transport, cell death, cell cycle, hepatitis C, foxo TF, and cyclin B inactivation). [Figure 64]The graphs show target validation in vitro. Arl6ip5 knockdown accelerates cell migration and proliferation. Screening that scores shRNA expression yields efficient knockdown in immortalized mouse liver cell lines. Wound healing assays show that wound cleft closure is accelerated in a knockdown-dependent manner. EdU uptake assays show a slight increase in proliferation with candidate knockdown. Cell confluence assays show a reduction in cell doubling time. [Figure 65] The graph shows candidate Nfkbib. Strong enrichment of shRNA targeting the candidate is observed. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis does not indicate liver cancer concerns. Amplification of Nfkbib is associated with liver cancer based on TCGA data analysis, suggesting that knockdown of Nfkbib in hepatocytes should be safe. [Figure 66] This shows the STRING (https: / / string-db.org / ) network analysis of Nfkbib, which reveals its association with several biological processes (I-κB / NFκB complex, RNA polymerase transcription). [Figure 67] The graphs show target validation in vitro. Arl6ip5 knockdown accelerates cell migration and proliferation. Screening that scores shRNA expression yields efficient knockdown in immortalized mouse liver cell lines. Wound healing assays show that wound cleft closure is accelerated in a knockdown-dependent manner. EdU uptake assays show a slight increase in proliferation with candidate knockdown. Cell confluence assays show a reduction in cell doubling time. [Figure 68] A graph of candidate DbnI is shown. Strong enrichment of shRNA targeting the candidate is observed. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis does not indicate liver cancer concerns. DbnI amplification and mutations are associated with liver cancer based on TCGA data analysis, suggesting that knockdown of DbnI in hepatocytes should be safe. [Figure 69]This shows the STRING (https: / / string-db.org / ) network analysis of DbnI, which reveals its association with several biological processes (gap binding activity, forward signaling via EPHB, and RHO GTPase activation of WASP and WAVE). [Figure 70] The graphs show target validation in vitro. DbnI knockdown accelerates cell migration and proliferation. Screening that scores shRNA expression yields efficient knockdown in immortalized mouse liver cell lines. Wound healing assays show that wound cleft closure is accelerated in a knockdown-dependent manner. EdU uptake assays show a slight increase in proliferation with candidate knockdown. Cell confluence assays show a reduction in cell doubling time. [Figure 71] A graph of candidate Loxl2 is shown. Strong enrichment of shRNA targeting the candidate is observed. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis does not indicate liver cancer concern. Loxl2 deletion is associated with liver cancer based on TCGA data analysis, indicating that Loxl2 knockdown should be carefully monitored. [Figure 72] This shows the STRING (https: / / string-db.org / ) network analysis of Loxl2, which reveals its association with several biological processes (cell cycle, delta notch, histone modification, elastic fibers, peptidyllysine oxidation). [Figure 73] The graph shows target validation in vitro. Loxl2 knockdown accelerates cell migration and proliferation. Screening that scores shRNA expression allows for efficient knockdown in immortalized mouse liver cell lines. EdU uptake assays show a slight increase in proliferation with candidate knockdown. Cell confluence assays show a reduction in cell doubling time. [Figure 74]A graph of candidate Ifih1 is shown. Strong enrichment of shRNA targeting the candidate is observed. The local NAFLD patient cohort shows stage-specific expression changes. TCGA survival analysis shows that low expression is associated with poor survival. Ifih1 mutations are associated with liver cancer based on TCGA data analysis, suggesting that knockdown of Ifih1 in hepatocytes may be safe. [Figure 75] This shows the STRING (https: / / string-db.org / ) network analysis of Ifih1, which reveals its association with several biological processes (Toll-, RIG-1-, NFκB- signaling, hepatitis b). [Figure 76] Microscopic images and graphs illustrating target validation in vitro are shown. Ifih1 knockdown accelerates cell migration and proliferation. Screening with shRNA expression scoring allows for efficient knockdown in immortalized mouse liver cell lines. Wound healing assays demonstrate that wound cleft closure is accelerated in a knockdown-dependent manner. [Figure 77] Schematic diagrams, microscopic images, and dot plots for in vivo validation of prioritized targets. As a first step, the inventors of this disclosure investigated the acceleration of hepatic regrowth. The inventors of this disclosure utilized FAH knockout mice, which enable hepatic regrowth. By hydrodynamic tail vein injection, the inventors of this disclosure delivered constructs to the liver to express the deficient enzyme FAH, the marker GFP, and the shRNA of interest. Upon administration of the drugs to the mice, NTBC FAH-expressing hepatocytes increased, causing hepatic regrowth. If the expression of a specific shRNA enhances hepatic regeneration, the inventors of this disclosure predict that clonal increase will be faster. An overview of the experiment, examples of tissue samples, and targeted analyses are shown. The inventors of this disclosure analyzed results for shCtrl (shNC), sh2810004N23Rik (shRik), shYthdf2, and shGolga7B. The inventors of this disclosure confirmed that knockdown of a target increased the number of GFP-positive cells and verified accelerated regrowth and regeneration in vivo. [Figure 78]A schematic diagram outlining further ongoing in vivo testing is shown. [Figure 79] A schematic diagram of an in vitro validation pipeline is shown to test the ability of targeted knockdown to enhance hepatocyte proliferation in order to score shRNAs. For this purpose, a stable hepatocyte cell line stably expressing scoring shRNA(1) was first created. Next, the knockdown efficiency of scoring shRNA(2) was tested. If sufficient knockdown was observed, then the acceleration of wound healing (A), increased cell proliferation by EdU uptake, cell doubling time, and CTG and CCK8 assays (B, C) were tested. If the enhancement of hepatocyte regenerative capacity is validated in vitro, then in vivo validation will be performed. [Figure 80] A schematic diagram illustrating in vivo validation using FAH- / - knockout mouse lines is shown. Transposon-based constructs were prepared to express the deficient enzyme FAH, a marker (GFP, etc.), and the target shRNA. These constructs, along with a plasmid for expressing the transposase SB13, were delivered to hepatocytes by hydrodynamic tail vein injection (HDTV). On average, 10% of hepatocytes were stably incorporated. Next, the inventors of this disclosure noted that liver regrowth was accelerated, indicating faster hepatocyte proliferation in vivo. After complete regrowth, virtually all hepatocytes expressed the target shRNA, correcting the FAH deficiency in the liver. Thus, these mice reflect the state of a "normal" mouse, but with the target knocked down specifically in hepatocytes. Next, the inventors of this disclosure performed a classic partial hepatectomy experiment to evaluate liver regeneration after acute liver injury. Furthermore, the inventors of this disclosure can check for the development of fibrosis in mice that have been regenerated by feeding them a NAFLD-inducing diet, compared to a control group expressing non-targeting shRNA. [Figure 81A]This bar graph shows qPCR data indicating target gene knockdown of C1ORF131, a human homolog of Rik, in the human liver cell line HepG2. Knockdown was confirmed using two different siRNAs and two different primer pairs (primer pair 1 and primer pair 2) for the ORF131 gene. Values ​​represent mean ± SD. Student's t-tests were used to determine **p<0.01 and ***p<0.001. [Figure 81B] A line graph of a luminescence assay called CellTiter-Glo (CTG) is shown, which was used to determine the number of viable cells in the culture based on the quantification of ATP present, an indicator of metabolically active cells. The amount of ATP is directly proportional to the number of cells present in the culture. Luminescence was measured on days 4, 5, and 6, 3 days after transfection. [Figure 81C] A line graph shows the Cell Counting Kit-8 (CCK8) assay, another proliferation assay for determining cell viability, which quantifies the number of viable cells by generating an orange formazan dye through in vivo reduction using a water-soluble tetrazolium salt in the presence of an electron carrier. The amount of formazan produced is directly proportional to the number of viable cells and is measured by absorbance at 450 nm. Absorbance was measured on days 4 and 5, 3 days after transfection. Normalized data are presented for both the CTG assay and the CCK8 assay. Further replication is underway to further establish the phenotype. [Figure 82A]The bar graph shows qPCR data demonstrating target gene knockdown using two different siRNAs against the Rik gene in immortalized mouse hepatocyte cells. The chemically modified siRNAs, which consist of combinations of 2'-F modified nucleotides and 2'-OMe modified nucleotides rather than natural RNA nucleotides, were created by industry collaborators. The difference between G101 and G111 lies in the pattern of 2'-F and 2'-OMe modifications. siRik-010-G111 has the same 2'-F and 2'-OMe modification pattern as 006-G111, but targets different regions on the mRNA due to its different ATGC sequence. Both siRNAs demonstrate efficient knockdown, and GalNAc tagging is planned for potential in vivo experiments in the future. [Figure 82B] The line graph of the Cell Counting Kit-8 (CCK8) assay used to determine cell viability is shown. Absorbance at 450 nm was measured on days 4 and 5, 3 days after transfection. All siRNAs showed increased activity compared to the control. More replication and other cell proliferation assays are underway to further establish the phenotype. [Figure 83A] A schematic diagram is shown of FAH(- / -) animals injected with a control and the target of interest to confirm whether target knockdown leads to tumorigenesis, and left for at least one year to observe tumor growth or malignant lesions, if present. [Figure 83B] Images of livers from animals excised and sent for histological examination are shown. One control animal (n=1) and two target animals (n=2). Representative liver images are shown. At the end of the one-year mark, no signs of distress or tumor growth were observed. The animals appeared healthy, and their livers appeared normal. Furthermore, no morphological changes or malignant lesions were observed in hepatocytes stained with hematoxylin and eosin (H&E) and imaged at 20x magnification. F1 and F2 refer to female animals 1 and 2. Data from additional animals are currently being collected. [Figure 84A]As can be seen from the Western blots of two different cell batches, we show a blot in which the tumor suppressor gene Pten was used as a positive control, and its knockdown was confirmed before injection. [Figure 84B] The image shows the response of NSG mice, each administered shPten-AML to one flank (left) and shRik-AML to the other flank (right), after which approximately 2 million cells were subcutaneously injected. 36 weeks after transplantation, the n=4 shPten-AML animals showed subcutaneous growth compared to the shRik-AML, which showed no growth, further confirming that targeted knockdown has neither adverse nor toxic effects. [Figure 85A] This bar graph shows qPCR data illustrating the knockdown of target genes against four different Rik hairpins in immortalized mouse liver cell lines. Of the four hairpins, Rik-3 showed the best knockdown and was used to further validate other phenotypic assays. Values ​​represent mean ± SD. Student's t-test is used for **p<0.01**. [Figure 85B] A bar graph showing the wound healing assay is presented, indicating accelerated wound closure at 12–16 hours compared to the control group. Values ​​represent mean ± SD. *p<0.05, **p<0.01, ***p<0.001 were determined by two-way ANOVA. [Figure 85C] A bar graph shows that Rik-3 also promotes DNA synthesis, as evidenced by the increased EdU uptake into DNA in Rik-3 knockdown cells compared to shC cells. Proliferating cells were examined using the EdU Alexa Fluor 594® Imaging Kit. EdU-positive cells were counted in 25 random fields using the Operetta High-Content Analysis System and plotted as %EdU, which is the number of EdU-stained cells relative to the total number of DAPI-stained cells. Values ​​represent mean ± SD. Student's t-test was used, p<0.05. [Figure 85D]Furthermore, a line graph showing the number of viable cells using CellTiter-Glo (CTG) was generated, and shRik-3 showed increased activity compared to the control. Cells were seeded in a 96-well format, and viability was determined by measuring luminescence from 24 hours after seeding to 96 hours. Values ​​represent mean ± SD. *p<0.05 was determined by two-way ANOVA. [Figure 86A] The table shows the data obtained from RNA-Seq analysis using control and Rik knockdown liver tissue samples. As seen in the negative factor change (fc) values, a decrease in Rik expression was confirmed, and this was analyzed using the DESeq method. [Figures 86B-86C] The principal component analysis and clustering plots using the rlog-transformed values ​​for each sample are shown. Similarities between samples are graphically represented in 2D format for PCA and in clustering format for hierarchical clustering. These two plots make it possible to identify expression patterns between sample groups. [Figures 86D-86E] The volcano plot and graph show the log2 factor change and p-value obtained from comparing the mean values ​​of each group, with genes represented by dots spanning the fc and p-values. The number of upregulated and downregulated genes for each comparison pair is also listed, with 767 upregulated genes and 268 downregulated genes being obtained. [Figure 87A] We present string analysis of 140 protein-coding genes with FC ≤ 2 and p-value ≤ 0.05, indicating that different interacting genes form clusters. [Figures 87B-87C] This document presents three different pathway analysis tools—DAVID, CPDB, and STRING—used as rational approaches to determine the target pathway (POI). The table shows the top overlapping pathways converged across the three methods, with target genes overlapping across all three highlighted in different colors. Histone genes appear to occupy the top position, but further detailed analysis is ongoing to elucidate their mechanisms of action. [Figure 88]Candidate gene: Shows the Slc45a4 cluster. [Figure 89] Microscopic images and graphs of cell migration and proliferation are shown. Stable expression of the target gene is observed in hepatocyte lines, as confirmed by GFP. Knockdown of the target gene is observed, as confirmed by qPCR. Knockdown of the target gene accelerated wound healing, with wound closure occurring in 16 hours compared to the control. Increased hepatocyte proliferation is observed compared to the control, as confirmed by EdU and cell confluence assays. [Figure 90] Microscopic images and graphs of the regeneration assay are shown. The regeneration assay demonstrated that knockdown of the target in vivo accelerated clonal proliferation of hepatocytes, demonstrating faster regeneration. Importantly, this represents hepatocyte proliferation in chronically injured liver. FAH- / - hepatocytes are dying and being replaced by FAH-expressing hepatocytes. The boxes highlighted in red show data for the target gene of interest. [Figure 91] Microscopic images and graphs of an in vivo model used to investigate the functional effects of Slc45a4 on a Western diet model are shown. Progressive NAFLD was induced in fully regrowing mice in which all hepatocytes expressed the target shRNA by feeding them a "Western diet". Representative images are shown on the left. Quantitative results of blinded fibrosis scores by certified pathologists are shown on the right. Knockdown of this target significantly reduced the level of fibrosis. Fibrosis scores were assessed based on Sirius Red staining and scored by pathology experts on a scale of 1 to 5: 1 being minimal, 2 mild, 3 moderate, 4 prominent, and 5 severe. [Figure 92A] The bar graphs and dot plots show the enrichment of shRNAs in genome-wide screening and the efficient knockdown by these shRNAs in hepatocyte lines as described in this disclosure. [Figure 92B] Representative photographs of wound healing assays, along with line graphs and microscopic images illustrating their quantification, are shown. It is evident that wound healing is significantly accelerated. [Figure 92C]Microscopic images and dot plots of EdU assay and cell doubling time results are shown. Targeted knockdown accelerates the proliferation of hepatocyte lines. [Figure 93] Microscopic images and bar graphs of the regeneration assay are shown. The regeneration assay demonstrated that knockdown of the target in vivo accelerated clonal proliferation of hepatocytes, demonstrating faster regeneration. Importantly, this represents hepatocyte proliferation in chronically injured liver. FAH- / - hepatocytes are dying and being replaced by FAH-expressing hepatocytes. [Figure 94] Images and bar graphs of in vivo validation in NAFLD in Western-diet model mice are shown. Progressive NAFLD was induced in fully regrowing mice in which all hepatocytes expressed the target shRNA by feeding them a "Western-diet." The experimental layout is shown on the left, and a representative macroscopic image of the liver is shown in the center. On the right, quantitative results and knockdown efficiency obtained from blinded fibrosis scoring by a certified pathologist are shown. Knockdown of this target significantly reduced the level of fibrosis. Experimental setup: Male FAH mice, 8 weeks of regrowth, and 26 weeks of Western-diet (WD). The reference genes for qPCR were Hprt and Ywhaz. Bars represent medians. [Figure 95] The results of in vitro functional validation of Arl6ip5 are shown. Figure 95A shows bar graphs and dot plots illustrating the enrichment of shRNA in the genome-wide screening described herein and the efficient knockdown by this shRNA in hepatocyte lines. Figure 95B shows representative photographs and line graphs illustrating the quantification of a wound healing assay. It can be seen that wound healing is significantly accelerated. Figure 95C shows the results of the EdU assay and cell doubling time. Targeted knockdown accelerates the proliferation of hepatocyte lines. [Figure 96]Microscopic images and bar graphs of a regeneration assay performed with Arl6ip5 are shown. The regeneration assay demonstrated that knockdown of the target in vivo accelerated clonal proliferation of hepatocytes, proving that regeneration was faster. Importantly, this represents hepatocyte proliferation in chronically injured liver. FAH- / - hepatocytes are dying and being replaced by FAH-expressing hepatocytes. [Figure 97] Images and bar graphs of a Western-style diet model mouse are shown. Progressive NAFLD was induced in fully regrowing mice in which all hepatocytes expressed the target shRNA by feeding them a "Western-style diet." The experimental layout is shown on the left, and a representative macroscopic image of the liver is shown in the center. On the right, quantitative results and knockdown efficiency obtained from blinded fibrosis scoring by a certified pathologist are shown. Knockdown of this target significantly reduced the level of fibrosis. [Figure 98] This paper presents dot plot results from an in vivo model to investigate the functional effects of Nfkbib and Arl6ip5 on a partial hepatectomy model. Partial hepatectomy (PH) is the surgical removal of two-thirds of the liver of a mouse that has fully regrown, with all hepatocytes expressing the target shRNA. PH is acute liver injury and induces synchronic proliferation of hepatocytes to regenerate the liver. Quantitative evaluation of Ki67 staining at PH (hour 0) and 48 hours postoperatively is shown. Knockdown of this target accelerates liver regeneration, as indicated by an increase in the number of Ki67-positive hepatocytes at 48 hours. Furthermore, since hour 0 represents the point of complete regrowth, the fact that the baseline Ki67 positivity level after target knockdown is equivalent to that of the control shRNA indicates that the regeneration termination after regrowth is fully functional. This demonstrates that the safety checkpoint that prevents hepatomegaly and "over-" regeneration remains intact. Knockdown of the target only releases the regeneration break and accelerates regeneration; it does not disable the safety checkpoint. This emphasizes the safety of knocking down this target. [Figure 99]This document presents in vitro functional validation of Dbnl. Figure 99A shows bar and dot plots illustrating the enrichment of shRNA in the genome-wide screening described herein and the efficient knockdown by this shRNA in hepatocyte lines. Figure 99B shows representative photographs and line graphs illustrating the quantification of a wound healing assay. It can be seen that wound healing is significantly accelerated. Figure 99C shows the results of the EdU assay and cell doubling time. Targeted knockdown accelerates the proliferation of hepatocyte lines. [Figure 100] This shows a schematic diagram and findings from Dbnl's in vivo hepatocyte clonal proliferation study. Figure 100 shows microscopic images and bar graphs of the regeneration assay. The regeneration assay demonstrated that knockdown of the target in vivo accelerated hepatocyte clonal proliferation, demonstrating faster regeneration. Importantly, this represents hepatocyte proliferation in chronically injured liver. FAH- / - hepatocytes are dying and being replaced by FAH-expressing hepatocytes. [Figure 101] Data from an emulsion patient cohort, representing different disease stages in approximately 150 patients, are presented. The target gene shows a significant increase in expression during disease progression. Survival analysis of TCGA RNA patient samples shows that low expression of the target is not associated with poor survival, suggesting that knockdown of the target does not drive liver cancer. [Figure 102] This figure shows a schematic diagram and results of an in vivo model (regeneration model) for determining the functional effects of Golga7b. Figure 102 shows microscopic images and bar graphs of the regeneration assay. The regeneration assay demonstrated that knockdown of the target in vivo accelerates clonal proliferation of hepatocytes, demonstrating faster regeneration. Importantly, this represents hepatocyte proliferation in chronically injured liver. FAH- / - hepatocytes are dying and being replaced by FAH-expressing hepatocytes. [Figure 103]This shows the genetic clustering of the gene Fam117b. Family 117 members B have similar sequences. Enriched shRNA scores across different animals are presented as Log2(CPM), where the Log count per million was calculated using summation analysis. Diamonds represent the median. Circles represent each animal. Survival analysis data from TCGA RNA patient samples show that low gene expression is associated with a higher survival rate in liver cancer patients. [Figure 104] Knockdown of Fam117b accelerates cell migration and proliferation. Figure 104 shows microscopic images and graphs of cell migration and proliferation. Stable expression of the target gene is observed in hepatocyte lines, as confirmed by GFP. Knockdown of the target gene is observed, as confirmed by qPCR. Knockdown of the target gene accelerates wound healing, with wound closure in 16 hours compared to the control. Increased hepatocyte proliferation is observed compared to the control, as confirmed by EdU and cell confluence assays. [Figure 105] This figure shows a schematic diagram and results of the in vivo model (regeneration model) used to determine the functional effects of Fam117b. Figure 105 shows microscopic images and bar graphs of the regeneration assay. The regeneration assay demonstrated that knockdown of the target in vivo accelerated clonal proliferation of hepatocytes, demonstrating faster regeneration. Importantly, this represents hepatocyte proliferation in chronically injured liver. FAH- / - hepatocytes are dying and being replaced by FAH-expressing hepatocytes. The boxes show data for the target gene of interest. [Figure 106] This shows the genetic clustering of the gene Med28 (mediator complex subunit 28). Enriched shRNA scores across different animals are presented as Log2 (CPM), where the Log count per million was calculated using summation analysis. Diamonds represent the median, and circles represent each animal. Survival analysis data from TCGA RNA patient samples indicate that low gene expression is associated with a higher survival rate in liver cancer patients. [Figure 107]Med28 knockdown is shown to accelerate cell migration and proliferation. Figure 107 shows microscopic images and graphs of cell migration and proliferation. Stable expression of the target gene is observed in hepatocyte lines, as confirmed by GFP. Knockdown of the target gene is observed, as confirmed by qPCR. Knockdown of the target gene accelerates wound healing, with wound closure in 16 hours compared to the control. Increased hepatocyte proliferation is observed compared to the control, as confirmed by EdU and cell confluence assays. [Figure 108] This figure shows a schematic diagram and results of an in vivo model for determining the functional effects of Med28. Figure 108 shows a microscopic image and bar graph of the regeneration assay. The regeneration assay showed that knockdown of the target accelerated clonal proliferation of hepatocytes in vivo, demonstrating faster regeneration. Importantly, this represents hepatocyte proliferation in chronically injured liver. FAH- / - hepatocytes are dying and being replaced by FAH-expressing hepatocytes. The boxes show data for the target gene of interest. [Figure 109] This demonstrates the in vitro functionality verification of Eif4ebp1. [Figure 110] This document presents a schematic diagram and results of the in vivo validation of Eif4ebp1 in NAFLD (Western-style diet model mice). Figure 110 shows a diagram and bar graph of the Western-style diet model mice. Progressive NAFLD was induced in fully regrowing mice in which all hepatocytes expressed the target shRNA by feeding them a "Western-style diet." The experimental layout is shown on the left, and a representative macroscopic image of the liver is shown in the center. On the right, quantitative results and knockdown efficiency obtained from blinded fibrosis scoring by a certified pathologist are shown. Knockdown of this target significantly reduced the level of fibrosis. [Figure 111] This demonstrates the in vitro functional verification of Pfn1. [Figure 112]Tables and dot plots of in vivo model results for determining the functional effects of other target genes are shown. Phenotyps of cell migration and proliferation in vitro for different targets are shown, with strong phenotypes indicated by + and p-values ​​by * (0.05 being significant). The regeneration assay showed that knockdown of the target accelerated clonal proliferation of hepatocytes in vivo, demonstrating faster regeneration. Importantly, this represents hepatocyte proliferation in chronically injured livers. FAH- / - hepatocytes are dying and being replaced by FAH-expressing hepatocytes. Data for different targets are shown. [Figure 113] This shows dot plot results from an in vivo model to determine the functional effects of Fam117b and Adamtsl5 (in a Western-style diet mouse model). Progressive NAFLD was induced in fully regrowing mice in which all hepatocytes expressed the target shRNA by feeding them a "Western-style diet". The experimental layout is shown on the left, and a representative macroscopic image of the liver is shown in the center. On the right, quantitative results and knockdown efficiency obtained from blinded fibrosis scoring by certified pathologists are shown. Knockdown of this target significantly reduced the level of fibrosis. Fibrosis scores were assessed based on Sirius Red staining and scored by pathology experts on a scale of 1 to 5: 1 is minimal, 2 is mild, 3 is moderate, 4 is prominent, and 5 is severe. [Figure 114] A list of target markers 1 is shown, which includes targets that have passed in vitro QC and have undergone or are undergoing in vivo validation, including clonal proliferation, dietary treatment, and partial hepatectomy. Some of these targets were included as controls in in vivo secondary screening. [Figure 115] A list of target markers, List 2, is shown, which includes targets that have passed literature review, have undergone / are undergoing in vitro QC, or are awaiting their turn. Some of these targets have passed in vitro QC and are included in the in vivo secondary analysis. In addition, some of these have remained as final candidates based on phenotypic factors for in vivo primary validation. [Figure 116]The third target list is shown, which includes targets that have passed literature review, including human homologs, novel targets, no association with NAFLD pathology, high survival rates in liver cancer patients, and our own patient transcriptomics data. [Modes for carrying out the invention]

[0035] Exemplary and non-limiting embodiments of methods and compositions for regenerating liver cells are disclosed below.

[0036] In one embodiment, a method is provided for regenerating liver cells in a subject having hepatocyte degeneration, comprising administering an agent that modulates one or more genes or markers, including C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, and ILKAP, wherein the agent interferes with hepatocyte degeneration and / or enhances liver cell regeneration.

[0037] Also disclosed is a method for regenerating liver cells in a subject requiring it, comprising administering an agent that modulates one or more genes or markers, including but not limited to C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, ILKAP, etc.

[0038] Also disclosed is a method for regenerating liver cells, which involves contacting liver cells with an agent that modulates one or more genes or markers, including but not limited to C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, ILKAP, etc.

[0039] Also disclosed are methods for treating or preventing hepatocyte degeneration in subjects requiring treatment, which include, but are not limited to, C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, ILKAP, etc.

[0040] In various examples, the term "subject" as used herein includes patients and non-patients. The term "patient" refers to an individual who is suffering from or is likely to suffer from a medical condition such as hepatic degenerative disease / disorder, while "non-patient" refers to an individual who is not suffering from a medical condition and is unlikely to suffer from one. "Non-patients" include healthy individuals, disease-free individuals, and / or individuals without a medical condition. The term "subject" includes humans and animals. Animals may include, but are not limited to, mammals (e.g., non-human primates, dogs, mice, rabbits, etc.). "Mouse" refers to any mammal of the Muridae family, such as mice and rats. "Rabbit" refers to animals of the Leporidae family, such as rabbits and hares.

[0041] Also disclosed is the use of an agent for modulating one or more genes or markers in the manufacture of a pharmaceutical product for treating or preventing hepatocyte degeneration, wherein the one or more genes or markers include, but are not limited to, C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, ILKAP, etc.

[0042] Also disclosed is a method for diagnosing or predicting the presence or likelihood of developing hepatocyte degeneration in a subject requiring such diagnosis, comprising determining the level of one or more genes or markers in a sample obtained from the subject, wherein the genes or markers include, but are not limited to, C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, ILKAP, etc.

[0043] In some cases, the level of one or more genes or markers in the sample is increased compared to the control. In some cases, the increase is a statistically significant increase in expression level. In some cases, the increase is an increase of at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 30, at least 100, at least 200, at least 300, at least 400, at least 500, at least 600, at least 700, at least 800, at least 900, at least 1000 or more in expression level.

[0044] In various examples, the term "sample" may include any biological sample, such as blood or plasma.

[0045] In some examples, the methods or uses described herein may include 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18 genes or markers selected from the group consisting of C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, and ILKAP from the priority list #1.

[0046] In various contexts, the terms “treatment,” “to treat,” and “therapy,” as well as their synonyms, refer to both therapeutic and prophylactic or preventative measures aimed at preventing or slowing (reducing) medical conditions, including but not limited to the symptoms and disorders of hepatic degeneration. Medical conditions also include the body’s response to diseases or disorders, such as fibrosis. Those requiring such treatment include not only those already possessing a medical condition, but also those who are prone to developing a medical condition or who wish to prevent one.

[0047] In some cases, the term “prevent” refers to a process that reduces the severity of symptoms, delays the onset of symptoms, reduces the severity of symptoms, reduces and / or prevents cell death, prevents death, inhibits progression / degeneration, inhibits further progression / degeneration, and / or improves at least one sign or symptom of hepatic degeneration.

[0048] In some cases, one or more genes or markers may further include, but are not limited to, ABCB10, LSM14A, ACTG1, YTHDF2, RPS6KA1, SEC13, IPO11, CTCF, UBAP2L, P2RY2, TRAF3IP2, FST, TUBG1, ZNF664, PVR, DYX1C1 / DNAAF4, TEX264, NIF3L1, RPUSD1, TRIM6, GLRX3, BRD1, CKS1B, C6ORF120, WASF2, ZNF689, B4GALT7, LCORL, NR2F2, BAG6, RNF10, etc.

[0049] In some cases, the methods or uses described herein refer to genes or markers in Priority List #2, such as ABCB10, LSM14A, ACTG1, YTHDF2, RPS6KA1, SEC13, IPO11, CTCF, UBAP2L, P2RY2, TRAF3IP2, FST, TUBG1, ZNF664, PVR, DYX1C1 / DNAAF4, TEX264, NIF3L1, RPUSD1, TRIM6, GLRX3 This may include 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, or 31 elements selected from the group consisting of BRD1, CKS1B, C6ORF120, WASF2, ZNF689, B4GALT7, LCORL, NR2F2, BAG6, and RNF10.

[0050] In some cases, one or more genes or markers are Uba6, Brwd3, Fyco1, ARID5B, C20ORF96 (6820408C15Rik), CD200R1 (Cd200r4), DALRD3, ELF3, ELFN1, FAM160A1, FAM50B, KIAA2026 (9930021J03Rik), KREMEN1, MACC1, NAA25, PROSC / PLPBP, RPS3, SHPK, SLAIN1, TCHP, ZNF503 (Zfp503), BUD13, CD93, PFKFB2, ZDBF2, FOXC2, GBGT1, RGS4, RNASEH1, TSNAXIP1, LYPD2, STIL, This list may further include, but is not limited to, TMCO3, TMEM159, RIF1, IFIH1, EPN2, CLP1, RNF220, NOL12, APOL3, GTF3C6, CTPS2, IFITM2, IFITM1, KCNS3, CA2, EIF4H, MRM1, AKAP8, PAPOLA, SECTM1, TYK2, MLLT6, IL1RL2, IPO7, APBB1IP, RABEP2, PLSCR1, PYGO2, COIL, LRRC8E, TNRC6C, CHD3, USP21, SNX27, NOP14, ZC3H15, C15orf39, UTP20, TRAK1, RAB11FIP2, PHPT1, CUL3, GNL3, etc.

[0051] In some cases, the gene or marker is one of the genes or markers in priority list #3, such as Uba6, Brwd3, Fyco1, ARID5B, C20ORF96 (6820408C15Rik), CD200R1 (Cd200r4), DALRD3, ELF3, ELFN1, FAM160A1, FAM50B, KIAA2026 (9930021J03Rik), KREMEN1, MACC1, NAA25, PROSC / PLPBP, RPS3, SHPK, SLAIN1 , TCHP, ZNF503(Zfp503), BUD13, CD93, PFKFB2, ZDBF2, FOXC2, GBGT1, RGS4, RNASEH1, TSNAXIP1, LYPD2, STIL, TMCO3, TMEM159, RIF1, I FIH1, EPN2, CLP1, RNF220, NOL12, APOL3, GTF3C6, CTPS2, IFITM2, IFITM1, KCNS3, CA2, EIF4H, MRM1, AKAP8, PAPOLA, SECTM1, TYK2, MLLT 6, IL1RL2, IPO7, APBB1IP, RABEP2, PLSCR1, PYGO2, COIL, LRRC8E, TNRC6C, CHD3, USP21, SNX27, NOP14, ZC3H15, C15orf39, UTP20, TRAK 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 selected from the group consisting of 1, RAB11FIP2, PHPT1, CUL3, and GNL3 This may include 1, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, or 74.

[0052] In some cases, the gene or marker is C1ORF131(2810004N23Rik)、SLC45A4、NFKBIB、ARL6IP5、DBNL、GOLGA7B、FAM117B、MED28、T SC22D4、EIF4EBP1、PFN1、PNRC2、ZNF672(Zfp672)、IER5、ADAMTSL5、COL4A5、MYH15、ILKAP、 ABCB10、LSM14A、ACTG1、YTHDF2、RPS6KA1、SEC13、IPO11、CTCF、UBAP2L、P2RY2、TRAF3IP2、FST、TUBG1、ZNF664、PVR、DYX1C1 / D NAAF4、TEX264、NIF3L1、RPUSD1、TRIM6、GLRX3、BRD1、CKS1B、C6ORF120、WASF2、ZNF689、B4GALT7、LCORL、NR2F2、BAG6、RNF10、 Uba6, Brwd3, Fyco1, ARID5B, C20ORF96(6820408C15Rik), CD200R1(Cd200r4), DALRD3, ELF3, ELFN1, FAM160A1, FAM50B, KIAA2026(9930021J03Rik), KREMEN1, M ACC1、NAA25、PROSC / PLPBP、RPS3、SHPK、SLAIN1、TCHP、ZNF503(Zfp503)、BUD13、 CD93、PFKFB2、ZDBF2、FOXC2、GBGT1、RGS4、RNASEH1、TSNAXIP1、LYPD2、STIL、TMCO 3、TMEM159、RIF1、IFIH1、EPN2、CLP1、RNF220、NOL12、APOL3、GTF3C6、CTPS2、IFI TM2、IFITM1、KCNS3、CA2、EIF4H、MRM1、AKAP8、PAPOLA、SECTM1、TYK2、MLLT6、IL1R L2, IPO7, APBB1IP, RABEP2, PLSCR1, PYGO2, COIL, LRRC8E, TNRC6C, CHD3, USP21, SNX27, NOP14, ZC3H15, C15orf39, UTP20, TRAK1, RAB11FIP2, PHPT1, CUL3, and GNL3 From the group consisting of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 genes or markers selected. pieces, 31 pieces, 32 pieces, 33 pieces, 34 pieces, 35 pieces, 36 pieces, 37 pieces, 38 pieces, 39 pieces, 40 pieces, 41 pieces, 42 pieces, 43 pieces, 44 pieces, 45 pieces, 46 pieces, 4 7 pieces, 48 ​​pieces, 49 pieces, 50 pieces, 51 pieces, 52 pieces, 53 pieces, 54 pieces, 55 pieces, 56 pieces, 57 pieces, 58 pieces, 59 pieces, 60 pieces, 61 pieces, 62 pieces, 63 pieces, 64 pieces, 65 pieces, 66 pieces, 67 pieces, 68 pieces, 69 pieces, 70 pieces, 71 pieces, 72 pieces, 73 pieces, 74 pieces, 75 pieces, 76 pieces, 77 pieces, 78 pieces, 79 pieces, 80 pieces , 81 pieces, 82 pieces, 83 pieces, 84 pieces, 85 pieces, 86 pieces, 87, 88 pieces, 89 pieces, 90 pieces, 91 pieces, 92 pieces, 93 pieces, 94 pieces, 95 pieces, 96 pieces, 97 pieces , may include 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, or all of them.

[0053] In some examples, the genes or markers may include two or more, three or more, four or more, five or more, ten or more, fifteen or more, twenty or more, twenty-five or more, thirty or more, forty or more, fifty or more, sixty or more, seventy or more, eighty or more, ninety or more, one hundred

[0054] In some examples, the genes or markers may include 2 or fewer, 3 or fewer, 4 or fewer, 5 or fewer, 10 or fewer, 15 or fewer, 20 or fewer, 30 or fewer, 40 or fewer, 50 or fewer, 60 or fewer, 70 or fewer, 80 or fewer, 90 or fewer, 100 or fewer, 110 or fewer, 120 or fewer, or 123 or fewer genes or markers as described herein.

[0055] In some examples, the genes or markers may include 2 to 20, 20 to 30, 30 to 40, 40 to 50, 50 to 60, 60 to 70, 70 to 80, 80 to 90, 90 to 100, 100 to 110, 110 to 120, or all of the genes or markers described herein.

[0056] In some cases, the agent enhances the regeneration of liver cells and / or inhibits liver cell degeneration.

[0057] While we do not wish to be bound by theory, targeting of the markers / targets described herein is thought to lead to enhanced liver cell regeneration (and has been shown in experimental data). In some cases, the regulation of one or more genes or markers described herein increases the rate of liver cell proliferation. Enhancement of liver cell regeneration therapy attenuates fibrosis and progressive disease.

[0058] As used herein, the terms “hepatic cytodegeneration” and “hepatic degeneration” can be used interchangeably to mean the progressive deterioration and / or damage of the cells, tissues, and / or organs of the liver, along with the corresponding impairment or loss of function caused by such deterioration and / or damage. Hepatic degeneration in this disclosure may or may not have an underlying pathogenesis.

[0059] In some cases, liver cells are liver cells.

[0060] In some cases, liver degeneration can result from liver diseases or conditions, including but not limited to acute liver disease, chronic liver disease, metabolic liver disease, fatty liver, hepatic fibrosis, primary sclerosing cholangitis (PSC), cirrhosis, mild hepatic fibrosis, advanced hepatic fibrosis, non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), alcoholic fatty liver disease (ALFD), alcohol-related liver disease (ARLD), hepatic ischemia-reperfusion injury, primary biliary cirrhosis (PBC), hepatitis, liver injury, liver damage, liver failure, metabolic syndrome, obesity, diabetes, end-stage liver disease, inflammation of the liver, inflammation of the lobules, and hepatocellular carcinoma (HCC).

[0061] In some cases, liver degeneration can include, but is not limited to, various stages of simple fatty liver (non-alcoholic fatty liver disease (NAFLD)), non-alcoholic steatohepatitis (including ballooning fibrosis of the fatty liver), cirrhosis, and hepatocellular carcinoma (HCC).

[0062] In some cases, liver degeneration is non-alcoholic fatty liver disease (NAFLD) and / or non-alcoholic steatohepatitis (NASH).

[0063] In some cases, the subjects are candidates for liver transplantation. In other cases, the subjects are not candidates for liver transplantation.

[0064] In some cases, agents that modulate genes or markers may be activators, inhibitors, antagonists, agonists, etc.

[0065] In some cases, the agent may be a natural compound, such as a secondary metabolite of a plant or fungus, that is known to inhibit a target gene or marker.

[0066] In some cases, the agent reduces or inhibits the expression of a gene or marker.

[0067] In some examples, the term “expression” refers to the transcription and / or translation of a particular nucleotide sequence driven by a promoter. In some embodiments, “expression” may refer to the display of polypeptide products of nucleotide transcription and / or translation on the cell surface.

[0068] In some cases, the agents described herein induce therapeutic effects by regulating gene expression. For example, the agents described herein may directly inhibit intracellular gene expression by interfering with gene activation. In some cases, the agents described herein may inhibit downstream translation of the genes described herein. In some cases, the agents may reduce the activity of the genes or markers described herein. Thus, in some cases, the agents described herein may target protein and / or gene expression. In some cases, if the agent is a nucleic acid (such as shRNA or siRNA), the nucleic acid reduces the expression level of the gene or marker by interacting with the corresponding mRNA.

[0069] In some cases, the agent inhibits or reduces the expression of one or more genes or markers by about 1 to 100%, or by about 5%, about 10%, about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, about 80%, about 90%, about 100%, or by at least 5%, at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 100%, or by 5% or less, 10% or less, 20% or less, 30% or less, 40% or less, 50% or less, 60% or less, 70% or less, 80% or less, 90% or less, or 100% or less.

[0070] In some cases, the agent increases or activates the expression of one or more genes or markers by about 1 to 100%, or by about 5%, about 10%, about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, about 80%, about 90%, about 100%, or by at least 5%, at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 100%, or by 5% or less, 10% or less, 20% or less, 30% or less, 40% or less, 50% or less, 60% or less, 70% or less, 80% or less, 90% or less, or 100% or less.

[0071] In some cases, the agents that modulate genes or markers are selected from nucleic acids, peptides, or small molecules.

[0072] In some cases, if the agent is a peptide, the peptide may inhibit a marker containing a sequence selected from the following group: >NP_689592.2 C1orf131 isoform a MRVDSSADPTMSQEQGPGSSTPPSSPTLLDALLQNLYDFGGTEGETEQKKIIKKRENKKRDVMASAALAAEPSPLPGSLIRGQRKSASSFFKELREERHCAPSGTPTGPEILAAAVPPSSLKNNREQVEVVEFHSNKKRK LTPDHNKNTKQANPSVLERDVDTQEFNLEKARLEVHRFGITGYGKGKERILEQERAIMLGAKPPKKSYVNYKVLQEQIKEKKAAKEEEKRLAQETDIFKKKKRKGQEDRKSKKKSAPSILSNGRIGQVGKFKNGTLILSP VDIKKINSSRVAK (Sequence ID 484) >NP_001287759.1 C1orf131 isoform b MRVDSSADPTMSQEQGPGSSTPPSSPTLLDALLQNLYDFGGTEGETEQKKIIKKRENKKRDVMASAALAAEPSPLPGSLIRGQRKSASSFFKELREERHCAPSGTPTGPEILAAAVPPSSLKNNREQVEVVEFHSNKKRK LTPDHNKNTKANPSVLERDVDTQEFNLEKARLEVHRFGITGYGKGKERILEQERAIMLGAKPPKKSYVNYKVLQEQIKEKKAAKEEEKRLAQETDIFKKKKRKGQEDRKSKKKSAPSILSNGRIGQVGKFKNGTLILSPV DIKKINSSRVAK (Sequence ID 485) >NP_001273575.1 SLC45a4 Isoform 1 (Sequence No. 486) >NP_001073900.1 SLC45a4 Isoform 2 MGKASPASGLSRPKTLVSPLRSNQWSLQKGLPEQYYSLTWFLSPILGLIFTPLIGSASDRCTLSWGRRRPFILALCVGVLFGVALFLNGSAIGLALGDVPNRQPIGIVLTVLGVVVLDFSADATEGPIRAYLLDVVDSEEQDMARNIHAFSAGLGGAIGYVLGGLDWTQTFLGSW FRTQNQVLFFFAAIIFTVSVALHLFSIDEEQYSPQQERSAEEPGALDGGEPHGVPAFPDEVQSEHELALDYPDVDIMRSKSDSALHVPDTALDLEPELLFLHDIEPSIFHDASYPATPRSTSQELAKTKLPRLATFLKEAAKEDETLLDNHLNEAKVPNGSGSPTKDALGGYTRV DTKPSATSSSMRRRRHAFRRQASSTFSYYGKLGSHCYRYRRANAVVLIKPSRSMSDLYDMQKRQRQHRHRNQSGATTSSGDTESEEGEGETTVRLLWLSMLKMPRELMRLCLCH LLTWFSVIAEAVFYTDFMGQVIFEGDPKAPSNSTAWQAYNAGVKMGCWGLVIYAATGAICSALLQKYLDNYDLSVRVIYVLGTLGFSVGTAVMAMFPNVYVAMVTISTMGIVSM SISYCPYALLGQYHDIKQYIHHSPGNSKRGFGIDCAILSCQVYISQILVASALGGVVDAVGTVRVIPMVASVGSFLGFLTATFLVIYPNVSEEAKEEQKGLSSPLAGEGRAGGNSEKPTVLKLTRKEGLQGPVETERLQVLTSVRSRHIGWCRSCWRVFFFMIILEKKFSFPQCGSLRRMTYLLFLSELDTLCPGQPCPWAATAHQSWEEAGPGGLGRRQ(Sequence ID 487) >NP_001273577.1 SLC45a4 Isoform 3 (Sequence ID 487)

[0073] In some cases, when the agent is a nucleic acid, the agent is a nucleic acid molecule that can interfere with the expression of a specific gene.

[0074] In some cases, when the agent is a nucleic acid, the agent may include RNAi (RNA interference) (including, but not limited to, small hairpin-type molecules (shRNA), siRNA (small interfering RNA or silencing RNA), etc.), antisense oligonucleotides (ASOs) or nucleosides and their nucleotide analogs, gapmers, small hairpin-type antisense oligonucleotides (shASOs), lipid nanoparticles, adeno-associated virus vectors, gene editing agents (clustered, regularly arranged short palindromic sequence repeats / CRISPR, etc.), ribozymes, nucleic acid-based nanoparticles, etc.

[0075] As used herein, the term "RNAi" refers to a conserved pathway found in most eukaryotes in which a double-stranded RNA molecule (dsRNA) inhibits the expression of a gene having a sequence complementary to that dsRNA.

[0076] In some cases, if the agent is a nucleic acid, the agent may be modified by modifications or conjugations of the phosphate backbone, sugar, or nucleic acid base, etc., as is known in the art. That is, the agents disclosed herein may include changes to their phosphate backbone (e.g., a phosphorothioate instead of a phosphate bond). These may include nucleotides having a modified sugar moiety or a sugar moiety analog. Examples of sugar moiety modifications include, but are not limited to, 2'-O-aminoethoxy, 2'-O-aminoethyl (2'-OAE), 2'-O-methoxy, 2-guanidoethyl (2'-OGE), 2'-O,4'-C-methylene (LNA), 2'-O-(N-(methyl)acetamide) (2'-OMA), 2'-O-methyl, 2'-fluoro, 2'-O-(methoxyethyl) (2'-OME), etc. They may also include nucleic acid base modifications such as 5-methylcytosine or pseudouridine. Such modifications are introduced to improve the stability of the drug and reduce its immunogenicity. Methods for introducing such modifications into nucleic acid drugs are common knowledge in the art.

[0077] In some cases, the agent may be a GalNAc-nucleic acid conjugate such as GalNAc motif-linked siRNA, ASO, shRNA, or gRNA. In some cases, the agent may be GalNAc-siRNA.

[0078] In some cases, agents that modulate marker expression may be nucleic acid-based therapies, protein-based therapies, or small molecule-based therapies.

[0079] In some cases, protein-based therapies include antibodies, antigen-binding proteins / molecules, and bispecific antibodies, but are not limited to these.

[0080] In some cases, small molecule-based therapies may include small molecule inhibitors.

[0081] In some cases, the subjects belong genetically to one or more lineages, such as Southeast Asians, South Americans, Central Americans of Spanish descent, or Arabian Peninsulars.

[0082] In another embodiment, nucleic acids are provided that encode agents for inhibiting one or more genes or markers selected from the group consisting of C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, ILKAP, etc.

[0083] In some cases, one or more genes or markers may further include, but are not limited to, ABCB10, LSM14A, ACTG1, YTHDF2, RPS6KA1, SEC13, IPO11, CTCF, UBAP2L, P2RY2, TRAF3IP2, FST, TUBG1, ZNF664, PVR, DYX1C1 / DNAAF4, TEX264, NIF3L1, RPUSD1, TRIM6, GLRX3, BRD1, CKS1B, C6ORF120, WASF2, ZNF689, B4GALT7, LCORL, NR2F2, BAG6, RNF10, etc.

[0084] In some cases, one or more genes or markers are UBA6, BRWD3, FYCO1, ARID5B, C20ORF96 (6820408C15Rik), CD200R1 (Cd200r4), DALRD3, ELF3, ELFN1, FAM160A1, FAM50B, KIAA2026 (9930021J03Rik), KREMEN1, MACC1, NAA25, PROSC / PLPBP, RPS3, SHPK, SLAIN1, TCHP, ZNF503 (Zfp503), BUD13, CD93, PFKFB2, ZDBF2, FOXC2, GBGT1, RGS4, RNASEH1, TSNAXIP1, LYPD2, STIL, This list may further include, but is not limited to, TMCO3, TMEM159, RIF1, IFIH1, EPN2, CLP1, RNF220, NOL12, APOL3, GTF3C6, CTPS2, IFITM2, IFITM1, KCNS3, CA2, EIF4H, MRM1, AKAP8, PAPOLA, SECTM1, TYK2, MLLT6, IL1RL2, IPO7, APBB1IP, RABEP2, PLSCR1, PYGO2, COIL, LRRC8E, TNRC6C, CHD3, USP21, SNX27, NOP14, ZC3H15, C15ORF39, UTP20, TRAK1, RAB11FIP2, PHPT1, CUL3, GNL3, etc.

[0085] In some examples, one or more gene markers may include, but are not limited to, the genes provided as disclosed herein. In some examples, one or more gene markers may include, but are not limited to, the genes provided in the following table:

[0086] [Table 7]

[0087] , and / or

[0088] [Table 8]

[0089] , and / or

[0090] [Table 9-1]

[0091] [Table 9-2]

[0092] [Table 9-3]

[0093] In some examples, nucleic acids include RNAi (RNA interference) (including, but not limited to, small hairpin molecules (shRNA), siRNA (small interfering RNA or silencing RNA), etc.), antisense oligonucleotides (ASOs) or nucleosides and their nucleotide analogs, gapmers, small hairpin antisense oligonucleotides (shASOs), lipid nanoparticles, adeno-associated virus vectors, gene editing agents (clustered, regularly arranged short palindromic sequence repeats / CRISPR, etc.), ribozymes, or nucleic acid-based nanoparticles.

[0094] In some cases, the nucleic acid is shRNA.

[0095] In some cases, the nucleic acid is shRNA and contains a sequence selected from the following group:

[0096] [Table 10]

[0097] In some cases, the nucleic acid is siRNA.

[0098] In some cases, the nucleic acid is siRNA and contains a sequence selected from the following group:

[0099] [Table 11-1]

[0100] [Table 11-2]

[0101] [Table 12-1]

[0102] [Table 12-2]

[0103] [Table 13-1]

[0104] [Table 13-2]

[0105] [Table 14-1]

[0106] [Table 14-2]

[0107] [Table 15-1]

[0108] [Table 15-2]

[0109] In some cases, nucleic acids are mRNA.

[0110] In some cases, the nucleic acid is mRNA and contains a sequence selected from the following group:

[0111] JPEG2026519589000029.jpg128148JPEG2026519589000030.jpg128148JPEG202 6519589000031.jpg191151JPEG2026519589000032.jpg225155JPEG20265195890 00033.jpg208152JPEG2026519589000034.jpg230152JPEG2026519589000035.j pg225153JPEG2026519589000036.jpg126149JPEG2026519589000037.jpg230150

[0112] Also disclosed are vectors or plasmids containing one or more of the nucleic acids described herein.

[0113] Furthermore, compositions or pharmaceutical compositions comprising nucleic acids, vectors, or plasmids described herein are also disclosed.

[0114] Also disclosed herein are compositions or pharmaceutical compositions comprising agents for modulating one or more genes or markers described herein.

[0115] Furthermore, nucleic acids, vectors, or plasmids described herein for use in therapeutic applications (such as gene therapy) are also disclosed.

[0116] In yet another embodiment, a composition, vector, or plasmid comprising one or more nucleic acids disclosed herein is provided.

[0117] In yet another embodiment, a composition, vector, or plasmid comprising one or more nucleic acids described herein is provided for use in therapy.

[0118] In yet another embodiment, a kit comprising the nucleic acid described herein is provided.

[0119] Also disclosed are host cells or non-human host animals that express a vector or plasmid containing one or more of the nucleic acids described herein.

[0120] Also disclosed herein are kits comprising agents for modulating one or more genes or markers described herein.

[0121] Kits containing nucleic acids or proteins described herein are also disclosed.

[0122] Also disclosed are kits for improving liver regeneration and / or preventing liver degeneration, which include agents for modulating one or more genes or markers described herein.

[0123] Furthermore, a kit for improving liver regeneration, comprising the nucleic acids described herein, is also disclosed.

[0124] Also disclosed is a kit / biomarker panel for predicting hepatocyte degeneration or determining therapeutic improvement, comprising one or more reagents for detecting one or more genes or markers selected from the group consisting of C1ORF131(2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672(Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, ILKAP, etc.

[0125] In some cases, one or more genes or markers may further include, but are not limited to, ABCB10, LSM14A, ACTG1, YTHDF2, RPS6KA1, SEC13, IPO11, CTCF, UBAP2L, P2RY2, TRAF3IP2, FST, TUBG1, ZNF664, PVR, DYX1C1 / DNAAF4, TEX264, NIF3L1, RPUSD1, TRIM6, GLRX3, BRD1, CKS1B, C6ORF120, WASF2, ZNF689, B4GALT7, LCORL, NR2F2, BAG6, RNF10, etc.

[0126] In some cases, one or more genes or markers are UBA6, BRWD3, FYCO1, ARID5B, C20ORF96 (6820408C15Rik), CD200R1 (Cd200r4), DALRD3, ELF3, ELFN1, FAM160A1, FAM50B, KIAA2026 (9930021J03Rik), KREMEN1, MACC1, NAA25, PROSC / PLPBP, RPS3, SHPK, SLAIN1, TCHP, ZNF503 (Zfp503), BUD13, CD93, PFKFB2, ZDBF2, FOXC2, GBGT1, RGS4, RNASEH1, TSNAXIP1, LYPD2, STIL, This list may further include, but is not limited to, TMCO3, TMEM159, RIF1, IFIH1, EPN2, CLP1, RNF220, NOL12, APOL3, GTF3C6, CTPS2, IFITM2, IFITM1, KCNS3, CA2, EIF4H, MRM1, AKAP8, PAPOLA, SECTM1, TYK2, MLLT6, IL1RL2, IPO7, APBB1IP, RABEP2, PLSCR1, PYGO2, COIL, LRRC8E, TNRC6C, CHD3, USP21, SNX27, NOP14, ZC3H15, C15ORF39, UTP20, TRAK1, RAB11FIP2, PHPT1, CUL3, GNL3, etc.

[0127] Methods, nucleic acids, vectors, or devices described herein are also disclosed.

[0128] The term "and / or," for example, "X and / or Y," should be understood to mean either "X and Y" or "X or Y," and should be considered to provide explicit support for both meanings or either meaning.

[0129] Furthermore, in this specification, the term “substantially” is understood to include, but not be limited to, “entirely” or “completely” whenever it is used. Furthermore, terms such as “comprising,” “comprise,” whenever they are used, are intended to be unrestrictive descriptive language, broadly including elements / components listed after such terms, in addition to other components not explicitly enumerated. For example, where “comprising” is used, a reference to “a certain” feature is also intended to be a reference to “at least one” of that feature. Terms such as “consisting,” “consist,” may be considered a subset of terms such as “comprising,” in appropriate contexts. Thus, embodiments disclosed herein using terms such as “comprising,” will be understood to provide teachings for corresponding embodiments using terms such as “consisting.” Furthermore, terms such as "approximately" and "about" always typically mean a reasonable range of variation, for example, a variation of ±5% of the disclosed value, or a variation of 4% of the disclosed value, or a variation of 3% of the disclosed value, or a variation of 2% of the disclosed value, or a variation of 1% of the disclosed value.

[0130] Furthermore, in this specification, certain values ​​may be disclosed as a range. Values ​​indicating the endpoints of a range are intended to indicate a preferred range. Whenever a range is given, it is intended that the range covers and teaches all possible subranges in addition to the individual numerical values ​​within that range. That is, the endpoints of a range should not be interpreted as immutable limits. For example, a description of a range of 1% to 5% is intended to specifically disclose not only the values ​​within that range, such as 1%, 2%, 3%, 4%, and 5%, but also subranges such as 1% to 2%, 1% to 3%, 1% to 4%, and 2% to 3%. Also, please understand that the individual numerical values ​​within a range include integers, fractions, and decimals. Furthermore, when a range is given, it is intended that the range covers and teaches values ​​up to two decimal places or significant figures (where appropriate) beyond the endpoints of the numerical values ​​shown. For example, a description of a range of 1% to 5% is intended to specifically disclose the ranges of 1.00% to 5.00%, 1.0% to 5.0%, and the intermediate values ​​within those ranges (1.01%, 1.02%...4.98%, 4.99%, 5.00%, and 1.1%, 1.2%...4.8%, 4.9%, 5.0%, etc.). The above intent for specific disclosure is applicable to any range of depth / width.

[0131] Furthermore, when describing certain embodiments, this disclosure may disclose methods and / or processes as a specific set of steps. However, it will be understood that, unless specifically required, the methods or processes should not be limited to a specific set of steps disclosed. Other sets of steps may also be possible. The specific order of steps disclosed herein should not be construed as an undue limitation. Unless specifically required, the methods and / or processes disclosed herein should not be limited to steps performed in the order described. The set of steps may be modified but still remain within the scope of this disclosure.

[0132] Furthermore, while this disclosure provides embodiments having one or more of the features / characteristics discussed herein, one or more of these features / characteristics may be negated in other alternative embodiments, and it will be understood that this disclosure provides support for such negations and related alternative embodiments. [Examples]

[0133] The exemplary embodiments of this disclosure will be more readily apparent to those skilled in the art from the following discussion and, where applicable, in conjunction with the drawings. It should be understood that other modifications can be made without departing from the scope of the invention. The exemplary embodiments are not necessarily mutually exclusive, as some can be combined with one or more embodiments to form novel exemplary embodiments. The embodiments of the examples should not be construed as limiting the scope of this disclosure.

[0134] Technologies that address the need for alternative diagnostic methods and therapeutic targets are disclosed herein. By performing genome-wide in vivo functional gene screening, the inventors identified regulators and therapeutic targets in a NAFLD mouse model. Next, the inventors performed a full in vivo functional genomics screening of approximately 80,000 shRNAs in an intervention setup for Western-style diet-induced NASH. A multiplex hierarchical in silico target identification pipeline was applied for the identification and prioritization of high-confidence targets. Approximately 200 high-confidence targets remained as final candidates, and these were further prioritized to approximately 50 targets that passed the highest level of stringency and 80 targets that passed the high level of stringency. Subsequently, the inventors subjected the top-ranked targets to our multiplex in vitro validation pipeline.

[0135] The ultimate goal of this project was to identify therapeutic targets to intervene in the progression of non-alcoholic fatty liver disease (NAFLD), particularly the progression from simple fatty liver to non-alcoholic steatohepatitis (NASH). The fundamental premise was that enhancing the liver's endogenous regenerative capacity could compensate for any liver damage, thereby attenuating fibrosis and progressive disease. To achieve this goal, a genome-wide in vivo functional gene intervention screening was performed in a "Western diet" (WD) mouse model. A library of approximately 80k shRNAs was subdivided into 32 pools, and the shRNAs were cloned into transposon-based constructs. The subpools were delivered to mouse livers as "naked" plasmids by hydrodynamic tail vein injection. By combining the transposon-based constructs with plasmids encoding transposases, the inventors achieved stable integration into approximately 5-10% of hepatocytes. ShRNA expression was induced after reaching simple fatty liver. The livers of mice were removed after feeding them either a wild-caught (WD) or control diet for 26 weeks. Genomic DNA was isolated from the livers, and PCR was performed to amplify the expression cassette. The PCR products were sequenced using Illumina-based next-generation sequencing (NGS) on a HiSeq4000 machine.

[0136] An overview and information of the screening approach to animal models can be seen in Figures 3 to 5. The sequencing of all subpools and mice given 26 weeks of wild-caught (WD) or normal samples was determined. Pre- and post-injection pool coverage rates can be seen in Figures 7 and 8. Good coverage was achieved in all pools of genome-wide screening. Next, we performed a multiplex in silico target identification pipeline combining four different analytical tools: Total Counts, DESeq2, Limma, and MAGECK (Figures 9-24). The differences primarily lie in the data normalization methods. In addition, variable stringency cutoffs were used. Depending on the data analysis tool and stringency parameters, there was considerable variability in the number of significantly enriched shRNAs. To identify the most reliable targets and prioritize these targets for validation experiments, data from different tools and settings were combined and overlaps were investigated. Applying this multiplex hierarchical in silico target identification pipeline resulted in approximately 200 highly reliable targets remaining as final candidates. These were further prioritized into approximately 50 targets that passed the highest level of stringency and 80 targets that passed high-level stringency. The inventors then ran the top-ranked targets through the multiplex in vitro validation pipeline. This pipeline combined wound healing, Edu uptake, and cell confluence / cell duplication assays to demonstrate accelerated proliferation / enhanced regeneration in vitro. To date, 14 targets have been tested and have passed in vitro validation (Figures 29–76). Of these 14, three have already passed the first stage of the multiplex in vivo validation pipeline (Figure 77). This also clearly highlights the quality of the in silico target selection pipeline.

[0137] The inventors of this disclosure have identified the following markers, which are grouped as List 1, List 2, and List 3.

[0138] [Table 16]

[0139] Target marker list 1 includes targets that have passed in vitro QC and have undergone or are undergoing in vivo validation, including clonal growth, dietary treatment, and partial hepatectomy. Some of the targets were included as controls in in vivo secondary screening.

[0140] [Table 17]

[0141] [Table 18]

[0142] Target marker list 2 includes targets that have passed literature review, have undergone / are currently undergoing in vitro QC, or are awaiting their turn. Some of these targets have passed in vitro QC and are included in the in vivo secondary analysis. In addition, some of these have remained as final candidates based on phenotypic characteristics for in vivo primary validation.

[0143] [Table 19]

[0144] [Table 20-1]

[0145] [Table 20-2]

[0146] [Table 20-3]

[0147] Target List 3 includes targets that have passed literature review, including human homologs, novel targets, no association with NAFLD pathology, high survival rates in liver cancer patients, and our own patient transcriptomics data.

[0148] [Table 21-1]

[0149] [Table 21-2]

[0150] Materials and methods Confluence growth curve and cell doubling time (dT) Day 1 - Cells were seeded to approximately 10% confluence (20,000-30,000 cells per 24-wp well in 0.5 mL of medium). Note that a similar assay could be performed using a 96-well plate format. Confirm that the plate used for cell seeding is compatible with IncuCyte. Check the "IncuCyte S3 compatible vessel list" available online. - The cells were allowed to adhere to the plate surface (1-2 hours), then thymidine (1-2 mM depending on the cell type) was added. The cells were incubated for 18 hours. Day 2 - The cells were washed twice with PBS and then replaced with fresh growth medium. - Place the plate in IncuCyte and perform imaging every 4 hours for 3-5 days. Use one of two settings: 〇 Entire well, 4x Standard, 4x magnification, maximum 5 images per well. - End the scan when the well reaches >80% confluence. - Analyze images with IncuCyte software to create masks that most accurately detect cells. Measure "cell confluence", i.e., the area covered by cells in each well. Export the data and analyze it in Excel / GraphPad Prism. - Calculate the cell doubling time (dT) using the following two methods: 〇 Doubling time cell calculator++ at www.doubling-time.com / compute_more.php. 〇 GraphPad Prism using the exponential growth least squares fit model from raw data. 〇 Calculate dT from the above two methods using only values between 10 - 80% confluence.

[0151] Wound healing assay On day 1, transfer the Culture-Insert 2-well (Ibidi#80209) into the wells of a 24-well plate (Falcon#353047). This protocol is for imaging using IncuCyte. When performing manual imaging at various time points, instead of manually attaching the insert to the 24-wp, a Culture-insert pre-attached to a μ-dish (ibidi#81176) may be used. Count the cells and prepare a suspension of 7×10 5 cells / mL. Optimize the seeding density of the cells to form a monolayer the next day. At a typical cell number of 5 - 10×10 5 cells / mL, most cell lines formed a monolayer. Pipette 70 μL of the cell suspension into each well of the insert. Avoid shaking and leave the suspension on a flat surface for about 10 minutes. Incubate the culture for 18 - 24 hours until a well-formed cell monolayer is visible.

[0152] On day 2, the insert was gently removed by pulling it with ethanol / UV sterilized tweezers. The insert can be washed / sterilized with ethanol and reused. The wells were rinsed once with PBS / culture medium (an optional step, but it helps remove dead suspension cells). Full growth medium (0.5 mL) was added to each well. The IncuCyte imaging protocol was set to 4x for the entire well, and images were taken every 2 hours for 1–1.5 days. Typically, 24 hours was sufficient for wound closure, starting with a well-formed cell monolayer. The plates used for cell seeding were compatible with IncuCyte.

[0153] On the third day, as shown in PLoS One.2020;15(7):e0232565, the cropped images are exported from the IC software, and the data is analyzed using the ImageJ plugin "Wound healing size tool". The following two measurements are obtained from the plugin: 1) Area (i.e., the area of ​​the wound not covered by cells) 2) Area % (Percentage of the area of ​​the wound not covered by cells relative to the total image area)

[0154] The plugin has limitations. For example, when quantifying an image with multiple closed wound areas, the area percentage measurement is calculated only for the largest open area, not from all open spaces (see image below). This can be corrected by manually selecting to display "all ROIs" and setting the measurement to calculate the uncovered area from all ROIs, which can then be summed up for a more accurate value.

[0155] EdU Ingestion Assay Day 1 • Seed cells in 0.5 mL of culture medium per well of a 24-well plate with a round coverslip in each well. 50,000–100,000 cells / well (optimize seeding density according to cell line so that 40–50% confluence is reached the following day) Incubate overnight. Day 2 Prepare a 2×EdU solution diluted in culture medium (final 10 μM). Add an equal volume of EdU+ medium to the cells (do not completely remove the culture medium from the plate) - for example, add 250 μL of 20 μM EdU+ medium to a well containing 250 μL of previous medium. • Incubate for 2 hours • Fix the cells with PFA and maintain them in PBS at +4°C until needed, or proceed to staining on the same day. Regarding the cover glass for 24-well plates, 1. Remove the culture medium from each well and wash the cells once with 0.5 mL of PBS. 2. Add 250 μL of 4% paraformaldehyde to PBS (prepared solution maintained at +4°C; ChemCruz SC-281692). Incubate at room temperature (RT) for 15 minutes. 3. Remove the fixative and wash the cells twice with 250 μL of 3% BSA (wash buffer) in PBS. 4. The wash buffer was removed. 300 μL of 0.5% Triton X-100 was added to PBS. Incubated at RT for 20 minutes. 5. The Click-iT® reaction cocktail was prepared according to the table. It is important to add the ingredients in the order listed in the table; otherwise, the reaction will not proceed optimally. Use the Click-iT® reaction cocktail within 15 minutes of preparation. 6. Remove the permeabilization buffer (step 3.3), then wash the cells in each well twice with 300 μL of 3% BSA in PBS. Remove the washing solution. 7. Add 140 μL of the Click-iT® reaction cocktail to each well containing a coverslip. Gently shake the plate to ensure the reaction cocktail is evenly distributed on the coverslip. Cover the plate with light and incubate at room temperature for 30 minutes. 8. Remove the reaction cocktail, then wash each well once with 300 μL of 3% BSA in PBS. Remove the washing solution. 9. Wash each well with 0.5 mL of PBS. Remove the washing solution. 10. Dilute the Hoechst 33342 (component G) solution 1:2000 with PBS to obtain a 1× Hoechst 33342 solution (final concentration is 5 μg / mL). 11. Add 250 μL of 1×Hoechst 33342 solution to each well. Incubate in the dark at room temperature for 30 minutes. Remove the Hoechst 33342 solution. 12. Each well was washed twice with 0.5 mL of PBS. The washing solution was removed. 13. Each well was washed with MQ water immediately before sealing. 14. Place each coverslip onto a microscope slide using one drop of mounting medium. FluorSave (#345789 Millipore) solidifies in 1 hour at room temperature. 15. For long-term storage, keep the slides in a dark place at +4°C. After initial storage in a horizontal position overnight, the slides can be kept in a vertical position in the slide box if necessary.

[0156] EdU staining protocol Buffers and solutions: • Washing buffer: 3% BSA in PBS → 0.9 g / m BSA powder in 30 mL • Permeabilization buffer: Dilute 50 μL of 0.5% Triton X-100 in PBS to 10 mL. • DNA staining: Hoechst 33342 (1:2000 dilution) → 1 μL in 2 mL PBS • Click-iT(registered trademark) reaction cocktails (as shown in the table below): Note: Prepare fresh cocktails and use them within 15 minutes.

[0157] [Table 22]

[0158] Quantification using ImageJ. The data was analyzed with ImageJ to measure the EdU+ fluorescence (area % and average intensity value) per nucleus. Cell counting was based on either all positive cells (value > 0) or only bright positive cells (area %> 50). Similar counts were obtained using average intensity instead of area % (the cutoff for bright cells is 127.5).

[0159] Quantification steps: 1. DAPI channel image → created a mask of the nuclear boundary. 2. Overlaid the nuclear_mask image on the EdU channel image (thresholded). 3. Measured the EdU signal within each nucleus (area % and average intensity). 4. Exported this data to Excel and applied a cutoff value to count all EdU positive or "bright EdU positive" cells.

[0160] Applications Embodiments of the methods disclosed herein provide therapeutic targets for the intervention of NAFLD / NASH. Advantageously, the targets disclosed herein are obtained from unbiased genome-wide in vivo functional gene screening. More advantageously, this target opens the way to nucleic acid-based therapies.

[0161] Embodiments of the disclosed methods and compositions also seek to overcome the problem of providing alternative diagnostic methods that do not rely on liver biopsies.

[0162] Advantageously, the methods disclosed herein have led to alternative treatments for liver diseases. This method is also useful for regenerative medicine.

[0163] Those skilled in the art will understand that other modifications and / or changes can be made to the embodiments disclosed herein without departing from the broader spirit or scope of this disclosure. For example, features of different exemplary embodiments described herein may be mixed, combined, exchanged, incorporated, adopted, modified, included, etc., between different exemplary embodiments. Accordingly, these embodiments are considered exemplary in all respects and not limiting.

Claims

1. A method for regenerating liver cells in a subject with hepatocyte degeneration, The treatment involves administering an agent that modulates one or more genes or markers, including C1ORF131 (2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672 (Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, and ILKAP. A method in which the agent interferes with the hepatocyte degeneration and / or enhances the regeneration of hepatocytes.

2. The method according to claim 1, wherein the one or more genes or markers further include ABCB10, LSM14A, ACTG1, YTHDF2, RPS6KA1, SEC13, IPO11, CTCF, UBAP2L, P2RY2, TRAF3IP2, FST, TUBG1, ZNF664, PVR, DYX1C1 / DNAAF4, TEX264, NIF3L1, RPUSD1, TRIM6, GLRX3, BRD1, CKS1B, C6ORF120, WASF2, ZNF689, B4GALT7, LCORL, NR2F2, BAG6, and RNF10.

3. The one or more genes or markers mentioned above are Uba6, Brwd3, Fyco1, ARID5B, C20ORF96 (6820408C15Rik), CD200R1 (Cd200r4), DALRD3, ELF3, ELFN1, FAM160A1, FAM50B, KIAA2026 (9930021J03Rik), K REMEN1, MACC1, NAA25, PROSC / PLPBP, RPS3, SHPK, SLAIN1, TCHP, ZNF503 (Zfp503), BUD 13, CD93, PFKFB2, ZDBF2, FOXC2, GBGT1, RGS4, RNASEH1, TSNAXIP1, LYPD2, STIL, TMCO3 , TMEM159, RIF1, IFIH1, EPN2, CLP1, RNF220, NOL12, APOL3, GTF3C6, CTPS2, IFITM2, IF ITM1, KCNS3, CA2, EIF4H, MRM1, AKAP8, PAPOLA, SECTM1, TYK2, MLLT6, IL1RL2, IPO7, AP The method according to claim 1 or 2, further comprising BB1IP, RABEP2, PLSCR1, PYGO2, COIL, LRRC8E, TNRC6C, CHD3, USP21, SNX27, NOP14, ZC3H15, C15orf39, UTP20, TRAK1, RAB11FIP2, PHPT1, CUL3, and GNL3.

4. The method according to any one of claims 1 to 3, wherein the liver cells are hepatocytes.

6. The method according to any one of claims 1 to 4, wherein the liver degeneration is non-alcoholic fatty liver disease (NAFLD) and / or non-alcoholic steatohepatitis (NASH).

7. The method according to any one of claims 1 to 6, wherein the agent reduces or inhibits the expression of the gene or marker.

8. The method according to any one of claims 1 to 7, wherein the agent is a nucleic acid capable of interfering with the expression of a specific gene.

9. A nucleic acid encoding an agent for inhibiting one or more of the aforementioned genes or markers, comprising C1ORF131 (2810004N23Rik), SLC45A4, NFKBIB, ARL6IP5, DBNL, GOLGA7B, FAM117B, MED28, TSC22D4, EIF4EBP1, PFN1, PNRC2, ZNF672 (Zfp672), IER5, ADAMTSL5, COL4A5, MYH15, and ILKAP.

10. The nucleic acid according to claim 9, wherein the one or more genes or markers further comprise ABCB10, LSM14A, ACTG1, YTHDF2, RPS6KA1, SEC13, IPO11, CTCF, UBAP2L, P2RY2, TRAF3IP2, FST, TUBG1, ZNF664, PVR, DYX1C1 / DNAAF4, TEX264, NIF3L1, RPUSD1, TRIM6, GLRX3, BRD1, CKS1B, C6ORF120, WASF2, ZNF689, B4GALT7, LCORL, NR2F2, BAG6, and RNF10.

11. The one or more genes or markers mentioned above are UBA6, BRWD3, FYCO1, ARID5B, C20ORF96 (6820408C15Rik), CD200R1 (Cd200r4), DALRD3, ELF3, ELFN1, FAM160A1, FAM50B, KIAA2026 (9930021J03Rik), K REMEN1, MACC1, NAA25, PROSC / PLPBP, RPS3, SHPK, SLAIN1, TCHP, ZNF503 (Zfp503), BUD 13, CD93, PFKFB2, ZDBF2, FOXC2, GBGT1, RGS4, RNASEH1, TSNAXIP1, LYPD2, STIL, TMCO3, TMEM159, RIF1, IFIH1, EPN2, CLP1, RNF220, NOL12, APOL3, GTF3C6, CTPS2, IFITM2, IFI TM1, KCNS3, CA2, EIF4H, MRM1, AKAP8, PAPOLA, SECTM1, TYK2, MLLT6, IL1RL2, IPO7, APB The nucleic acid according to claim 9 or 10, further comprising B1IP, RABEP2, PLSCR1, PYGO2, COIL, LRRC8E, TNRC6C, CHD3, USP21, SNX27, NOP14, ZC3H15, C15ORF39, UTP20, TRAK1, RAB11FIP2, PHPT1, CUL3, and GNL3.

12. The method according to any one of claims 1 to 8 or the nucleic acid according to claims 9 to 11, wherein the nucleic acid comprises one or more of RNAi (RNA interference), low molecular weight hairpin RNA (shRNA), antisense oligonucleotide (ASO), gapmer, low molecular weight hairpin antisense oligonucleotide (shASO), lipid nanoparticles, adeno-associated virus vector, gene editing agent, ribozyme, or nucleic acid-based nanoparticles.

13. The nucleic acid according to any one of claims 9 to 12, which is shRNA.

14. The nucleic acid according to any one of claims 9 to 13, which is an shRNA and comprises a sequence selected from the group consisting of the following: Table 1

15. The nucleic acid according to any one of claims 9 to 14, which is siRNA.

16. The nucleic acid according to any one of claims 9 to 15, which is an siRNA and comprises a sequence selected from the group consisting of the following: Table 2-1 Table 2-2 Table 3-1 Table 3-2 Table 4-1 Table 4-2 Table 5-1 Table 5-2 Table 6-1 Table 6-2

17. A composition, vector, or plasmid comprising one or more nucleic acids as described in any one of claims 9 to 16.

18. A composition, vector, or plasmid for use in therapy, comprising one or more nucleic acids according to any one of claims 9 to 16.

19. A kit comprising the nucleic acid sequence described in any one of claims 9 to 18.

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