153: Skeletal muscle eQTLs map cardiometabolic genes

Wilson EPW et al., The American Journal of Human Genetics - This episode covers a skeletal muscle eQTL meta-analysis of 1,002 individuals that discovered 18,818 conditionally distinct regulatory signals across 12,283 genes and integrated these with GWAS to nominate candidate genes for muscular and cardiometabolic traits, including functional validation of an INHBB regulatory variant. Key terms: eQTL, skeletal muscle, type 2 diabetes, GWAS colocalization, INHBB.

Study Highlights:
A meta-analysis of skeletal muscle eQTLs (n=1,002) identified 18,818 conditionally distinct signals for 12,283 genes. Colocalization with 26 GWAS traits produced 2,252 GWAS-eQTL colocalizations nominating 1,342 candidate genes, with 22% involving non-primary eQTLs and only 37% corresponding to the nearest protein-coding gene. Cross-tissue colocalization across muscle, adipose, liver, and islets linked 36% of tested T2D signals to 551 candidate genes and identified 95 genes uniquely detected in muscle. Functional reporter assays validated that rs11688682 increases enhancer activity and INHBB expression in myoblasts and adipocytes, consistent with eQTL directions.

Conclusion:
Leveraging a larger, conditionally-resolved skeletal muscle eQTL dataset improves gene prioritization for muscular and cardiometabolic GWAS signals and multi-tissue integration highlights shared and tissue-specific regulatory mechanisms; validated INHBB regulation illustrates a putative causal pathway meriting further functional follow-up.

Music:
Enjoy the music based on this article at the end of the episode.

Article title:
Skeletal muscle eQTL meta-analysis implicates genes in the genetic architecture of muscular and cardiometabolic traits

First author:
Wilson EPW

Journal:
The American Journal of Human Genetics

DOI:
10.1016/j.ajhg.2025.09.003

Reference:
Wilson EPW, Broadaway KA, Parsons VA, et al. Skeletal muscle eQTL meta-analysis implicates genes in the genetic architecture of muscular and cardiometabolic traits. Am J Hum Genet. 2025;112:1–15. https://doi.org/10.1016/j.ajhg.2025.09.003

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

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Episode link: https://basebybase.com/episodes/skeletal-muscle-eqtl-meta-analysis-implicates-genes-in-the-genetic-architecture-of-muscular-and-cardiometabolic-traits

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-09-30.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Substantively audited the transcript's claims related to: skeletal-muscle eQTL meta-analysis results, signal conditioning, GWAS-eQTL colocalizations, 3D/genomic-proximity implications, cross-tissue analyses across four tissues, and INHBB functional validation with luciferase assays; included limitations and broader imp
- transcript topics: Skeletal muscle eQTL meta-analysis results; Conditional signal identification and APEx methodology; GWAS-eQTL colocalization and candidate gene prioritization; Proximity vs 3D genome architecture in mapping; Cross-tissue colocalization across muscle, adipose, liver, and islets; Functional validation of INHBB rs11688682

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 6
- claims flagged for review: 0
- metadata checks passed: 4

Chapters

• (00:00:14) - Deep Dive into the genetic dark matter of diabetes
• (00:03:15) - The muscle map of diabetes
• (00:06:53) - EQTL and disease risk: combining the studies
• (00:07:32) - The Near Gene Trap
• (00:09:26) - What about those other dimmer switches you mentioned? The non primary
• (00:10:05) - Exploring T2D in muscle, fat, and eye
• (00:13:14) - Beyond the nearest gene heuristic
• (00:13:54) - GWAS and the causal genetics of muscular dystrophy