Elucidating the Genetic Underpinnings of Human Musculoskeletal System Aging Through Genomic Structural Equation Modeling.
Abstract
The genetic architecture underlying traits related to Human Musculoskeletal System Aging (MSA) remains largely unexplored. In this study, we conducted a large-scale multivariate genome-wide association study (GWAS) of MSA utilizing Genomic Structural Equation Modeling (Genomic SEM). We estimated causal single nucleotide polymorphisms (SNPs) associated with independent variation and identified 14 genome-wide significant loci (mean.PP > 0.95). We employed multiple transcriptome-wide association methods to analyze tissue, cellular levels, and genomic elements, identifying loci with high relevance to MSA susceptibility, along with associated element information. Our research represents the first comprehensive delineation of the genetic architecture of Musculoskeletal System Aging through a GWAS of unmeasured phenotype.
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Research summary
The paper identifies genetic loci associated with musculoskeletal system aging through a genome-wide association study. This research is relevant as it explores the genetic underpinnings of aging-related traits, potentially contributing to understanding the biological mechanisms of aging.
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