Multi Ancestry Whole Genome Sequencing Analyses of MASLD with Functional Follow Up

Metabolic dysfunction-associated steatotic liver disease (MASLD), is caused by excess accumulation of fat in the liver (steatosis), has a global prevalence of 25.2% and is becoming the most common cause of chronic liver disease worldwide. MASLD prevalence varies across ancestries with individuals of Hispanic ancestry having a higher prevalence (34–58%) than European (28–45%) and African (19–35%) ancestry individuals. There are few effective ways to prevent or treat MASLD making it one of the biggest unmet medical and public health needs of our time. MASLD is heritable or genetically influenced and thus its causes can be uncovered using genetic analyses. While histology has historically been used to define MASLD, we pioneered the use of Computed Tomography (CT) based imaging based hepatic steatosis measurement to define MASLD in the Framingham Heart Study and used this across population-based cohorts to identify genetic variants that reproducibly associated with MASLD. We combined CT with Magnetic Resonance Imaging based hepatic steatosis as well as ICD measured MASLD across many cohorts to identify genetic variants that associate with MASLD at genome wide significant levels in the most powered genetic analyses of this trait. Trans ethnic analyses of implicated loci confirmed that these variants had effects on MASLD across ancestries. In separate analyses we identified ancestry specific alleles in MASLD implicated genes suggesting novel disease promoting loci may exist in non- European populations. We have knocked out or overexpressed candidate associated genes in liver cell lines where we can verify an effect on affecting hepatic steatosis or other liver phenotypes. Since known variation explains only 20% of the heritability of MASLD additional genetic loci that predispose to MASLD remain to be discovered. To overcome previous limitations of using imputed genetic data and mostly European ancestry samples here we aim to identify additional common and rare variants with effects on MASLD through whole genome sequencing (WGS) in large ethnically diverse populations. Implicated genes from these analyses will be functionally tested for effects on hepatic steatosis to confirm causality using library based CRISPR/cas9 screening. Results from this work will to improve the diagnosis, management, treatment and ultimately prevention of MASLD by understanding the genomic contributions to its pathophysiology.