PubMed · 42615996
Exploring the shared genetic architecture of sarcopenia using genomic structural equation modeling.
Abstract
Sarcopenia is a common age-associated condition characterized by the progressive loss of skeletal muscle mass, strength, and physical functionality. While large-scale genome-wide association studies (GWAS) have previously addressed isolated traits of sarcopenia, the multifactorial genetic architecture underlying this condition remains largely undefined. To characterize the common genetic basis of sarcopenia-related traits, genomic structural equation modeling (Genomic-SEM) was implemented. Multiple post-GWAS analytic approaches were integrated to pinpoint susceptibility loci. These analyses encompassed identifying enriched genetic pathways and relevant genomic elements, as well as cell-type-specific enrichment in skeletal muscle satellite stem cells, mesenchymal stem cells, and skeletal muscle satellite cells in limb muscle. Furthermore, based on the integrated GWAS data of sarcopenia-related traits, polygenic risk score (PRS) analysis was conducted to evaluate risk associations at the chromosomal level. A well-fitted Genomic-SEM successfully integrated the GWAS data, revealing the shared genetic architecture of sarcopenia-related traits. We identified 110 single nucleotide polymorphisms (SNPs) reaching genome-wide significance (p < 5 × 10-8), of which 9 represent novel discoveries. Subsequent fine-mapping procedures and gene-set analyses identified 15 causal variants alongside 77 candidate susceptibility genes. This study provides a comprehensive genetic characterization of sarcopenia via Genomic-SEM, offering new insights into the etiological pathways underlying sarcopenia.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Yusheng Li, Peizhen Zhang, Qiaoling Chen, Jiacheng Zhang, Hongyi Wang, Wei Zhang, Huanan Li, Jingui Wang. 2026-09-05. Exploring the shared genetic architecture of sarcopenia using genomic structural equation modeling.. https://doi.org/10.1093/gerona%2Fglag204
Cite the original work for its findings. Save a collection to share your selection of sources.