Integrative analyses elucidate transcriptional regulatory functions of risk alleles for metabolic liver disease.

Summary

This multi-omics study functionally links noncoding MASLD GWAS variants to target genes and pathways using MPRA, liver eQTLs, chromatin looping, and single-cell CRISPRi. Differential activity variants at loci such as SLC22A3, APOA5, ANGPTL3, and LPL influence lipid metabolism and hepatic stellate cell activation, improving MASLD risk prediction.

Key Findings

• Mapped cell-type–specific enrichment of MASLD risk variants within regulatory elements in human liver nuclei.
• Identified hundreds of differential activity variants by MPRA acting in cell- and stimulus-dependent manners.
• Integrated eQTLs, chromatin looping, and single-cell CRISPRi to assign target genes to functional variants.
• Highlighted loci (SLC22A3, APOA5, ANGPTL3, LPL) modulating lipid metabolism and hepatic stellate cell activation.
• Functional variants improved prediction of MASLD risk.

Clinical Implications

Although preclinical/functional, the results prioritize causal regulatory variants and target genes (e.g., APOA5/ANGPTL3/LPL axis) for biomarker development and therapeutic targeting, and support integrating functional variant annotations into MASLD risk stratification.

Limitations

• Functional assays may not fully recapitulate in vivo physiology across all liver microenvironments.
• Generalizability across ancestries and disease stages requires further validation.

Future Directions

Validate prioritized variants/targets in longitudinal cohorts and perturbation models; translate functional annotations into clinical risk tools and therapeutic target discovery.