Proteome-wide Mendelian Randomization Identifies Potential Therapeutic Targets for Nonalcoholic Fatty Liver Diseases

Overview

Journal Sci Rep

Specialty Science

Date 2024 May 23

PMID 38782984

Authors

Junhang Li

Xiang Ma

Cuihua Yin

Affiliations

Soon will be listed here.

Abstract

Nonalcoholic fatty liver disease (NAFLD) is the predominant cause of liver pathology. Current evidence highlights plasma proteins as potential therapeutic targets. However, their mechanistic roles in NAFLD remain unclear. This study investigated the involvement of specific plasma proteins and intermediate risk factors in NAFLD progression. Two-sample Mendelian randomization (MR) analysis was conducted to examine the association between plasma proteins and NAFLD. Colocalization analysis determined the shared causal variants between the identified proteins and NAFLD. The MR analysis was applied separately to proteins, risk factors, and NAFLD. Mediator shares were computed by detecting the correlations among these elements. Phenome-wide association studies (phewas) were utilized to assess the safety implications of targeting these proteins. Among 1,834 cis-protein quantitative trait loci (cis-pQTLs), after-FDR correction revealed correlations between the plasma levels of four gene-predicted proteins (CSPG3, CILP2, Apo-E, and GCKR) and NAFLD. Colocalization analysis indicated shared causal variants for CSPG3 and GCKR in NAFLD (posterior probability > 0.8). Out of the 22 risk factors screened for MR analysis, only 8 showed associations with NAFLD (p ≤ 0.05), while 4 linked to CSPG3 and GCKR. The mediator shares for these associations were calculated separately. Additionally, reverse MR analysis was performed on the pQTLs, risk factors, and NAFLD, which exhibited a causal relationship with forward MR analysis. Finally, phewas summarized the potential side effects of associated-targeting proteins, including CSPG3 and GCKR. Our research emphasized the potential therapeutic targets for NAFLD and provided modifiable risk factors for preventing NAFLD.

References

Wu N, Li J, Zhang J, Yuan F, Yu N, Zhang F . Waist circumference mediates the association between rs1260326 in GCKR gene and the odds of lean NAFLD. Sci Rep. 2023; 13(1):6488. PMC: 10119110. DOI: 10.1038/s41598-023-33753-4. View

Shen M, Jiang L, Liu H, Dai H, Jiang H, Qian Y . Interaction between the GCKR rs1260326 variant and serum HDL cholesterol contributes to HOMA-β and ISI in the middle-aged T2D individuals. J Hum Genet. 2023; 68(12):835-842. DOI: 10.1038/s10038-023-01191-9. View

Randall J, Winkler T, Kutalik Z, Berndt S, Jackson A, Monda K . Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits. PLoS Genet. 2013; 9(6):e1003500. PMC: 3674993. DOI: 10.1371/journal.pgen.1003500. View

Foley C, Staley J, Breen P, Sun B, Kirk P, Burgess S . A fast and efficient colocalization algorithm for identifying shared genetic risk factors across multiple traits. Nat Commun. 2021; 12(1):764. PMC: 7858636. DOI: 10.1038/s41467-020-20885-8. View

Stine J, Wentworth B, Zimmet A, Rinella M, Loomba R, Caldwell S . Systematic review with meta-analysis: risk of hepatocellular carcinoma in non-alcoholic steatohepatitis without cirrhosis compared to other liver diseases. Aliment Pharmacol Ther. 2018; 48(7):696-703. PMC: 7495494. DOI: 10.1111/apt.14937. View

Namjou B, Lingren T, Huang Y, Parameswaran S, Cobb B, Stanaway I . GWAS and enrichment analyses of non-alcoholic fatty liver disease identify new trait-associated genes and pathways across eMERGE Network. BMC Med. 2019; 17(1):135. PMC: 6636057. DOI: 10.1186/s12916-019-1364-z. View

Howard D, Adams M, Clarke T, Hafferty J, Gibson J, Shirali M . Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019; 22(3):343-352. PMC: 6522363. DOI: 10.1038/s41593-018-0326-7. View

Sanchez-Roige S, Palmer A, Fontanillas P, Elson S, Adams M, Howard D . Genome-Wide Association Study Meta-Analysis of the Alcohol Use Disorders Identification Test (AUDIT) in Two Population-Based Cohorts. Am J Psychiatry. 2018; 176(2):107-118. PMC: 6365681. DOI: 10.1176/appi.ajp.2018.18040369. View

Gobeil E, Maltais-Payette I, Taba N, Briere F, Ghodsian N, Abner E . Mendelian Randomization Analysis Identifies Blood Tyrosine Levels as a Biomarker of Non-Alcoholic Fatty Liver Disease. Metabolites. 2022; 12(5). PMC: 9143809. DOI: 10.3390/metabo12050440. View

10.

Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J . UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015; 12(3):e1001779. PMC: 4380465. DOI: 10.1371/journal.pmed.1001779. View

11.

Singh C, Jin B, Shrestha N, Markhard A, Panda A, Calvo S . ChREBP is activated by reductive stress and mediates GCKR-associated metabolic traits. Cell Metab. 2023; 36(1):144-158.e7. PMC: 10842884. DOI: 10.1016/j.cmet.2023.11.010. View

12.

Noureddin M, Vipani A, Bresee C, Todo T, Kim I, Alkhouri N . NASH Leading Cause of Liver Transplant in Women: Updated Analysis of Indications For Liver Transplant and Ethnic and Gender Variances. Am J Gastroenterol. 2018; 113(11):1649-1659. PMC: 9083888. DOI: 10.1038/s41395-018-0088-6. View

13.

Larsson S, Woolf B, Gill D . Appraisal of the causal effect of plasma caffeine on adiposity, type 2 diabetes, and cardiovascular disease: two sample mendelian randomisation study. BMJ Med. 2023; 2(1):1-8. PMC: 9978685. DOI: 10.1136/bmjmed-2022-000335. View

14.

Liu M, Jiang Y, Wedow R, Li Y, Brazel D, Chen F . Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nat Genet. 2019; 51(2):237-244. PMC: 6358542. DOI: 10.1038/s41588-018-0307-5. View

15.

Ferkingstad E, Sulem P, Atlason B, Sveinbjornsson G, Magnusson M, Styrmisdottir E . Large-scale integration of the plasma proteome with genetics and disease. Nat Genet. 2021; 53(12):1712-1721. DOI: 10.1038/s41588-021-00978-w. View

16.

Lu Y, Day F, Gustafsson S, Buchkovich M, Na J, Bataille V . New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk. Nat Commun. 2016; 7:10495. PMC: 4740398. DOI: 10.1038/ncomms10495. View

17.

Ursu O, Glick M, Oprea T . Novel drug targets in 2018. Nat Rev Drug Discov. 2019; . DOI: 10.1038/d41573-019-00052-5. View

18.

Prins B, Kuchenbaecker K, Bao Y, Smart M, Zabaneh D, Fatemifar G . Genome-wide analysis of health-related biomarkers in the UK Household Longitudinal Study reveals novel associations. Sci Rep. 2017; 7(1):11008. PMC: 5591265. DOI: 10.1038/s41598-017-10812-1. View

19.

Denny J, Bastarache L, Ritchie M, Carroll R, Zink R, Mosley J . Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nat Biotechnol. 2013; 31(12):1102-10. PMC: 3969265. DOI: 10.1038/nbt.2749. View

20.

Jostins L, Ripke S, Weersma R, Duerr R, McGovern D, Hui K . Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature. 2012; 491(7422):119-24. PMC: 3491803. DOI: 10.1038/nature11582. View