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

Author:

Li Yanni123ORCID,van den Berg Eline H1ORCID,Kurilshikov Alexander2ORCID,Zhernakova Dasha V24ORCID,Gacesa Ranko12ORCID,Hu Shixian125ORCID,Lopera-Maya Esteban A2ORCID,Zhernakova Alexandra2ORCID, ,Aguirre-Gamboa Raul,Deelen Patrick,Franke Lude,Kuivenhoven Jan A,Lopera-Maya Esteban A,Nolte Ilja M,Sanna Serena,Snieder Harold,Swertz Morris A,Visscher Peter M,Vonk Judith M,Wijmenga Cisca,de Meijer Vincent E6ORCID,Sanna Serena2ORCID,Dullaart Robin P F7ORCID,Blokzijl Hans1ORCID,Festen Eleonora A M1ORCID,Fu Jingyuan28ORCID,Weersma Rinse K1ORCID

Affiliation:

1. Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen , Groningen 9713 GZ, The Netherlands

2. Department of Genetics, University of Groningen, University Medical Center Groningen , Groningen 9713 GZ, The Netherlands

3. Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Tianjin Medical University , Tianjin 300052, China

4. Laboratory of Genomic Diversity, Center for Computer Technologies, ITMO University , Saint Petersburg 199034, Russia

5. Institute of Precision Medicine, the First Affiliated Hospital, Sun Yat-sen University , Guangzhou 510080, China

6. Department of Surgery, Section of Hepatobiliary Surgery and Liver Transplantation, University of Groningen, University Medical Center Groningen , Groningen 9713 GZ, The Netherlands

7. Department of Endocrinology, University of Groningen, University Medical Center Groningen , Groningen 9713 GZ, The Netherlands

8. Department of Pediatrics, University of Groningen, University Medical Center Groningen , Groningen 9713 GZ, The Netherlands

Abstract

Abstract 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.

Publisher

Oxford University Press (OUP)

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