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Genome-wide Studies Reveal Genetic Risk Factors for Hepatic Fat Content

作     者:Li, Yanni van den Berg, Eline H. Kurilshikov, Alexander Zhernakova, Dasha, V Gacesa, Ranko Hu, Shixian Lopera-Maya, Esteban A. Zhernakova, Alexandra de Meijer, Vincent E. Sanna, Serena Dullaart, Robin P. F. Blokzijl, Hans Festen, Eleonora A. M. Fu, Jingyuan Weersma, Rinse K. 

作者机构:Univ Groningen Univ Med Ctr Groningen Dept Gastroenterol & Hepatol NL-9713 GZ Groningen Netherlands Univ Groningen Univ Med Ctr Groningen Dept Genet NL-9713 GZ Groningen Netherlands Tianjin Med Univ Tianjin Med Univ Gen Hosp Dept Gastroenterol & Hepatol Tianjin 300052 Peoples R China Sun Yat Sen Univ Affiliated Hosp 1 Inst Precis Med Guangzhou 510080 Peoples R China ITMO Univ Ctr Comp Technol Lab Genom Divers St Petersburg 199034 Russia Univ Groningen Univ Med Ctr Groningen Dept Pediat NL-9713 GZ Groningen Netherlands Univ Groningen Univ Med Ctr Groningen Dept Surg Sect Hepatobiliary Surg & Liver Transplantat NL-9713 GZ Groningen Netherlands Univ Groningen Univ Med Ctr Groningen Dept Endocrinol NL-9713 GZ Groningen Netherlands 

出 版 物:《GENOMICS PROTEOMICS & BIOINFORMATICS》 (基因组蛋白质组与生物信息学报(英文版))

年 卷 期:2024年第22卷第2期

页      面:qzae031页

核心收录:

学科分类:0710[理学-生物学] 1002[医学-临床医学] 100201[医学-内科学(含:心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 10[医学] 

基  金:Netherlands Organization for Scientific Research NWO [175.010.2007.006] Economic Structure Enhancing Fund of the Dutch government Ministry of Economic Affairs Northern Netherlands Alliance Province of Groningen, University Medical Center Groningen University of Groningen, Dutch Kidney Foundation Dutch Diabetes Research Foundation Dutch Heart Foundation IN-CONTROL [CVON2018-27] ERC Consolidator Grant NWO VICI Netherlands Organ-on-Chip Initiative NWO Gravitation project [024.003.001] Ministry of Education, Culture, and Science of the government of The Netherlands Chinese Scholarship Council NWO VENI Seerave Foundation [LSHM18057-SGF] Healthsimilar toHolland Public Private Partnership from the Dutch Ministry of Economic Affairs [PPP-2019-024] UK Medical Research Council Wellcome Trust UK Department of Health Scottish and Welsh Governments North West Development Agency British Heart Foundation Diabetes UK [52728, OV19_0486] 

主  题:Hepatic fat content MAFLD Genome-wide association study Fatty liver index Magnetic resonance imaging proton density fat fraction LIVER-DISEASE ASSOCIATION VARIANT LOCI SUSCEPTIBILITY PATHOGENESIS INSIGHTS TARGETS ENZYMES CONFERS 

摘      要:Genetic susceptibility to metabolic associated fatty liver disease (MAFLD) is complex and poorly characterized. Accurate characterization of the genetic background of hepatic fat content would provide insights into disease etiology and causality of risk factors. We performed genome-wide association study (GWAS) on two noninvasive definitions of hepatic fat content: magnetic resonance imaging proton density fat fraction (MRI-PDFF) in 16,050 participants and fatty liver index (FLI) in 388,701 participants from the United Kingdom (UK) Biobank (UKBB). Heritability, genetic overlap, and similarity between hepatic fat content phenotypes were analyzed, and replicated in 10,398 participants from the University Medical Center Groningen (UMCG) Genetics Lifelines Initiative (UGLI). Meta-analysis of GWASs of MRI-PDFF in UKBB revealed five statistically significant loci, including two novel genomic loci harboring CREB3L1 (rs72910057-T, P = 5.40E-09) and GCM1 (rs1491489378-T, P = 3.16E-09), respectively, as well as three previously reported loci: PNPLA3, TM6SF2, and APOE. GWAS of FLI in UKBB identified 196 genome-wide significant loci, of which 49 were replicated in UGLI, with top signals in ZPR1 (P = 3.35E-13) and FTO (P = 2.11E-09). Statistically significant genetic correlation (rg) between MRI-PDFF (UKBB) and FLI (UGLI) GWAS results was found (rg = 0.5276, P = 1.45E-03). Novel MRI-PDFF genetic signals (CREB3L1 and GCM1) were replicated in the FLI GWAS. We identified two novel genes for MRI-PDFF and 49 replicable loci for FLI. Despite a difference in hepatic fat content assessment between MRI-PDFF and FLI, a substantial similar genetic architecture was found. FLI is identified as an easy and reliable approach to study hepatic fat content at the population level.

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