HepatologyGenetic & Genomic MedicinePeer-reviewed journal article
A functional genomic framework to elucidate novel causal non-alcoholic fatty liver disease genes
Peter Saliba‐GustafssoniD, Johanne Marie JusteseniD, Amanda RantaiD, Disha SharmaiD, Ewa Bielczyk-MaczyńskaiD, Jiehan LiiD, Laeya Abdoli Najmi, Maider Apodaka‐BiguriiD, Patricia AspichuetaiD, Hanna M. BjörckiD, Per Olof ErikssoniD, Theresia Maria SchnurriD, Anders Franco‐CerecedaiD, Michael J. GloudemansiD, Endrina MújicaiD, Marcel den HoediD, Themistocles L. AssimesiD, Thomas QuertermousiD, Ivan Carcamo‐OriveiD, Chong Yon ParkiD, Joshua W. KnowlesiD
Abstract
Background & AimsNon-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver pathology in western countries, with serious public health consequences. Efforts to identify causal genes for NAFLD have been hampered by the relative paucity of human data from gold-standard magnetic resonance quantification of hepatic fat. To overcome insufficient sample size, genome-wide association studies using NAFLD surrogate phenotypes have been used, but only a small number of loci have been identified to date. In this study, we combined GWAS of NAFLD composite surrogate phenotypes with genetic colocalization studies followed by functional in vitro screens to identify bona fide causal genes for NAFLD. Approach & ResultsWe used the UK Biobank to explore the associations of our novel NAFLD score, and genetic colocalization to prioritize putative causal genes for in vitro validation. We created a functional genomic framework to study NAFLD genes in vitro using CRISPRi. Our data identify VKORC1, TNKS, LYPLAL1 and GPAM as regulators of lipid accumulation in hepatocytes and suggest the involvement of VKORC1 in the lipid storage related to the development of NAFLD. ConclusionsComplementary genetic and genomic approaches are useful for the identification of NAFLD genes. Our data supports VKORC1 as a bona fide NAFLD gene. We have established a functional genomic framework to study at scale putative novel NAFLD genes from human genetic association studies.
- organism: human
- assay: GWAS summary statistics
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 13
- FWCI
- 3.97
- Field percentile
- top 5%
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