中文|English
ISSN 1001-5256 (Print)
ISSN 2097-3497 (Online)
CN 22-1108/R
Volume 42 Issue 9
Sep.  2026
Turn off MathJax
Article Contents

Identification and in vitro validation of causative proteins in metabolic dysfunction-associated fatty liver disease: A study based on proteome-wide Mendelian randomization

DOI: 10.12449/JCH260911
Research funding:

Natural Science Foundation of Guangdong Province (2022A1515012081)

More Information
  • Corresponding author: Sha Weihong, shaweihong@gdph.org.cn (ORCID: 0000-0001-7610-3813); Chen Hao, chenhao@gdph.org.cn (ORCID: 0000-0003-4339-3441)
  • Received Date: 2026-03-04
  • Accepted Date: 2026-04-03
  • Published Date: 2026-09-25
  •   Objective  To identify protein biomarkers and potential therapeutic targets associated with metabolic dysfunction-associated fatty liver disease (MAFLD) through an integrative multi-omics analysis.  Methods  Large-scale plasma protein quantitative trait locus data were integrated with MAFLD genome-wide association study data, and a proteome-wide Mendelian randomization analysis was performed. Summary data-based Mendelian Randomization (SMR)/heterogeneity in dependent instruments (HEIDI) test and colocalization analysis were used to assess significant proteins. The independent samples t-test was used for comparison of continuous data with homogeneity of variance between two groups, and the Welch-corrected t-test was used for comparison of continuous data with heterogeneity of variance. The transcriptomic validation results were compared with the Mendelian randomization results to evaluate the changing trends of gene expression, and boxplots were used to display the expression distribution of candidate genes between groups.  Results  Among 7 130 proteins analyzed, 40 showed a causal relationship with MAFLD, among which 26 increased the risk of MAFLD and 14 exerted a protective effect against MAFLD (FDR<0.05). Nine proteins were supported by SMR/HEIDI (PSMR<0.05, PHEIDI>0.05), and 14 showed a strong colocalization signal (PPH4>0.9). The transcriptomic analysis identified 5 differentially expressed proteins (all P<0.05), i.e., adenosine diphosphate-ribosylation factor-like GTPase 2, insulin-like growth factor binding protein 2, casein kinase 1 delta (CSNK1D), leucine-rich repeat neuronal 1, and moesin (MSN). In vitro validation showed upregulated expression levels of MSN (1.612±0.346 vs 0.569±0.077, P<0.05), 14-3-3 protein theta (YWHAQ) (1.267±0.126 vs 0.313±0.029, P<0.05), and CSNK1D (0.871±0.025 vs 0.431±0.080, P<0.05) and a downregulated expression level of histone deacetylase 8 (0.637±0.059 vs 1.097±0.260, P<0.05) in the MAFLD cell model. Functional annotation showed that CSNK1D participated in circadian and metabolic regulation, YWHAQ modulated the Hippo pathway and lipid signal transduction, and MSN was associated with cytoskeletal remodeling and fibrogenic responses.  Conclusion  The integrative proteogenomic analysis in this study shows that CSNK1D, YWHAQ, and MSN may be key mediators in the pathogenesis of MAFLD. These proteins have the potential to serve as novel biomarkers and therapeutic targets, providing new directions for research on disease mechanisms and the development of intervention strategies.

     

  • loading
  • [1]
    Lazarus J V, Newsome P N, Francque S M, et al. Reply: A multi-society Delphi consensus statement on new fatty liver disease nomenclature[J]. Hepatology, 2024, 79( 3): E93- E94. DOI: 10.1097/HEP.0000000000000696.
    [2]
    Younossi Z, Anstee Q M, Marietti M, et al. Global burden of NAFLD and NASH: Trends, predictions, risk factors and prevention[J]. Nat Rev Gastroenterol Hepatol, 2018, 15( 1): 11- 20. DOI: 10.1038/nrgastro.2017.109.
    [3]
    Estes C, Razavi H, Loomba R, et al. Modeling the epidemic of nonalcoholic fatty liver disease demonstrates an exponential increase in burden of disease[J]. Hepatology, 2018, 67( 1): 123- 133. DOI: 10.1002/hep.29466.
    [4]
    Wei S L, Wang L, Evans P C, et al. NAFLD and NASH: Etiology, targets and emerging therapies[J]. Drug Discov Today, 2024, 29( 3): 103910. DOI: 10.1016/j.drudis.2024.103910.
    [5]
    Powell E E, Wong V W, Rinella M. Non-alcoholic fatty liver disease[J]. Lancet, 2021, 397( 10290): 2212- 2224. DOI: 10.1016/S0140-6736(20)32511-3.
    [6]
    Friedman S L, Neuschwander-Tetri B A, Rinella M, et al. Mechanisms of NAFLD development and therapeutic strategies[J]. Nat Med, 2018, 24( 7): 908- 922. DOI: 10.1038/s41591-018-0104-9.
    [7]
    Suhre K, Arnold M, Bhagwat A M, et al. Connecting genetic risk to disease end points through the human blood plasma proteome[J]. Nat Commun, 2017, 8: 14357. DOI: 10.1038/ncomms14357.
    [8]
    Sveinbjornsson G, Ulfarsson M O, Thorolfsdottir R B, et al. Multiomics study of nonalcoholic fatty liver disease[J]. Nat Genet, 2022, 54( 11): 1652- 1663. DOI: 10.1038/s41588-022-01199-5.
    [9]
    Zhao J H, Stacey D, Eriksson N, et al. Genetics of circulating inflammatory proteins identifies drivers of immune-mediated disease risk and therapeutic targets[J]. Nat Immunol, 2023, 24( 9): 1540- 1551. DOI: 10.1038/s41590-023-01588-w.
    [10]
    Thomas D C, Conti D V. Commentary: The concept of‘Mendelian randomization’[J]. Int J Epidemiol, 2004, 33( 1): 21- 25. DOI: 10.1093/ije/dyh048.
    [11]
    Sun X Y, Chen B H, Qi Y, et al. Multi-omics Mendelian randomization integrating GWAS, eQTL and pQTL data revealed GSTM4 as a potential drug target for migraine[J]. J Headache Pain, 2024, 25( 1): 117. DOI: 10.1186/s10194-024-01828-w.
    [12]
    Ghodsian N, Abner E, Emdin C A, et al. Electronic health record-based genome-wide meta-analysis provides insights on the genetic architecture of non-alcoholic fatty liver disease[J]. Cell Rep Med, 2021, 2( 11): 100437. DOI: 10.1016/j.xcrm.2021.100437.
    [13]
    Namjou B, Lingren T, Huang Y B, et al. GWAS and enrichment analyses of non-alcoholic fatty liver disease identify new trait-associated genes and pathways across eMERGE Network[J]. BMC Med, 2019, 17( 1): 135. DOI: 10.1186/s12916-019-1364-z.
    [14]
    Gudjonsson A, Gudmundsdottir V, Axelsson G T, et al. A genome-wide association study of serum proteins reveals shared loci with common diseases[J]. Nat Commun, 2022, 13( 1): 480. DOI: 10.1038/s41467-021-27850-z.
    [15]
    Sun B B, Chiou J, Traylor M, et al. Plasma proteomic associations with genetics and health in the UK Biobank[J]. Nature, 2023, 622( 7982): 329- 338. DOI: 10.1038/s41586-023-06592-6.
    [16]
    Zhang J N, Dutta D, Köttgen A, et al. Plasma proteome analyses in individuals of European and African ancestry identify cis-pQTLs and models for proteome-wide association studies[J]. Nat Genet, 2022, 54( 5): 593- 602. DOI: 10.1038/s41588-022-01051-w.
    [17]
    Narula S, Yusuf S, Chong M, et al. Plasma ACE2 and risk of death or cardiometabolic diseases: A case-cohort analysis[J]. Lancet, 2020, 396( 10256): 968- 976. DOI: 10.1016/S0140-6736(20)31964-4.
    [18]
    Sadler M C, Auwerx C, Lepik K, et al. Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases[J]. Nat Commun, 2022, 13( 1): 7559. DOI: 10.1038/s41467-022-35196-3.
    [19]
    Wallace C. A more accurate method for colocalisation analysis allowing for multiple causal variants[J]. PLoS Genet, 2021, 17( 9): e1009440. DOI: 10.1371/journal.pgen.1009440.
    [20]
    Wu T Z, Hu E Q, Xu S B, et al. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data[J]. Innovation(Camb), 2021, 2( 3): 100141. DOI: 10.1016/j.xinn.2021.100141.
    [21]
    Lu Y X, Peng Q, Liu B Z, et al. SIRT5 affects lipid accumulation in cells of a metabolic-associated fatty liver disease model by regulating the succinylation status of HSPD1[J]. BMC Immunol, 2025, 26( 1): 95. DOI: 10.1186/s12865-025-00776-7.
    [22]
    Mendizabal I, Berto S, Usui N, et al. Cell type-specific epigenetic links to schizophrenia risk in the brain[J]. Genome Biol, 2019, 20( 1): 135. DOI: 10.1186/s13059-019-1747-7.
    [23]
    Vinje M A, Friedman D A. Exogenous spike-in mouse RNAs for accurate differential gene expression analysis in barley using RT-qPCR[J]. Biol Methods Protoc, 2023, 8( 1): bpad034. DOI: 10.1093/biomethods/bpad034.
    [24]
    Burger K L, Fernandez M R, Meads M B, et al. CK1δ and CK1ε signaling sustains mitochondrial metabolism and cell survival in multiple myeloma[J]. Cancer Res, 2023, 83( 23): 3901- 3919. DOI: 10.1158/0008-5472.CAN-22-2350.
    [25]
    Brookheart R T, Lee C Y, Espenshade P J. Casein kinase 1 regulates sterol regulatory element-binding protein(SREBP) to control sterol homeostasis[J]. J Biol Chem, 2014, 289( 5): 2725- 2735. DOI: 10.1074/jbc.M113.511899.
    [26]
    Kilpinen S, Heliölä H, Achim K. Range of chromatin accessibility configurations are permissive of GABAergic fate acquisition in developing mouse brain[J]. BMC Genomics, 2023, 24( 1): 725. DOI: 10.1186/s12864-023-09836-x.
    [27]
    Lin E, Kuo P H, Liu Y L, et al. Effects of circadian clock genes and health-related behavior on metabolic syndrome in a Taiwanese population: Evidence from association and interaction analysis[J]. PLoS One, 2017, 12( 3): e0173861. DOI: 10.1371/journal.pone.0173861.
    [28]
    Ou W B, Lundberg M Z, Zhu S H, et al. YWHAE-NUTM2 oncoprotein regulates proliferation and cyclin D1 via RAF/MAPK and Hippo pathways[J]. Oncogenesis, 2021, 10: 37. DOI: 10.1038/s41389-021-00327-w.
    [29]
    Xuan W, Song D D, Hou J H, et al. Regulation of Hippo-YAP1/TAZ pathway in metabolic dysfunction-associated steatotic liver disease[J]. Front Pharmacol, 2025, 16: 1505117. DOI: 10.3389/fphar.2025.1505117.
    [30]
    Kanai F, Marignani P A, Sarbassova D, et al. TAZ: A novel transcriptional co-activator regulated by interactions with 14-3-3 and PDZ domain proteins[J]. EMBO J, 2000, 19( 24): 6778- 6791. DOI: 10.1093/emboj/19.24.6778.
    [31]
    Gluchowski N L, Becuwe M, Walther T C, et al. Lipid droplets and liver disease: From basic biology to clinical implications[J]. Nat Rev Gastroenterol Hepatol, 2017, 14( 6): 343- 355. DOI: 10.1038/nrgastro.2017.32.
    [32]
    Karvar S, Ansa-Addo E A, Suda J, et al. Moesin, an ezrin/radixin/moesin family member, regulates hepatic fibrosis[J]. Hepatology, 2020, 72( 3): 1073- 1084. DOI: 10.1002/hep.31078.
    [33]
    Sun B K, Ding X Q, Tan J, et al. TM6SF2 E167K variant decreases PNPLA3-mediated PUFA transfer to promote hepatic steatosis and injury in MASLD[J]. Clin Mol Hepatol, 2024, 30( 4): 863- 882. DOI: 10.3350/cmh.2024.0268.
    [34]
    Hart S N, Li Y, Nakamoto K, et al. A comparison of whole genome gene expression profiles of HepaRG cells and HepG2 cells to primary human hepatocytes and human liver tissues[J]. Drug Metab Dispos, 2010, 38( 6): 988- 994. DOI: 10.1124/dmd.109.031831.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(6)

    Article Metrics

    Article views (91) PDF downloads(13) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return