Transcriptome-Wide Association Study of Metabolic Dysfunction-Associated Steatotic Liver Disease Identifies Relevant Gene Signatures - Wang, Jianxiu; Gao, Qian (Turkish Journal of Gastroenterology, 2024)
Background/Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is considered the most widespread chronic liver condition globally. Genome-wide association studies (GWAS) have pinpointed several genetic loci correlated to MASLD, yet the biological significance of these loci remains poorly understood. Materials and Methods: Initially, we applied Functional Mapping and Annotation (FUMA) to conduct a functional annotation of the MASLD GWAS summary statistics, which included data from 3242 cases and 707 631 controls. Additionally, a MASLD transcriptome association study (TWAS) was conducted utilizing FUSION software in combination with the genotype-tissue expression project (GTEx-v8) expression weight set to identify susceptibility genes. Furthermore, to elucidate the observed correlations, we carried out conditional and joint analyses, probabilistic causal fine-mapping of TWAS signals, summary data-based Mendelian randomization (SMR), and phenome-wide association analyses. Results: Following functional annotation analysis, we identified 4 genetic risk loci, annotated 6 lead single nucleotide polymorphisms (SNPs), 27 independent significant SNPs, and 511 candidate SNPs. TWAS also found four genes related to MASLD, including MAU2 sister chromatid cohesion factor (MAU2), EPH receptor A2 (EPHA2), GATA zinc finger domain containing 2A (GATAD2A), and transmembrane 6 superfamily member 2 (TM6SF2). Moreover, fine mapping of TWAS signatures identified 13 causal genes associated with MASLD that were located at 3 genetic risk loci, but SMR results could not rule out the possibility that the relationship between significant genes and MASLD was caused by a linkage disequilibrium structure. Conclusions: Our study found new significantly associated genes for MASLD and highlighted the ability of TWAS to identify and prioritize potentially pathogenic genes. Cite this article as: Wang J, Gao Q. Transcriptome-wide association study of metabolic dysfunction-associated steatotic liver disease identifies relevant gene signatures. Turk J Gastroenterol. 2025;36(5):280-292.