Elucidating the Genetic Underpinnings of Human Musculoskeletal System Aging Through Genomic Structural Equation Modeling

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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Publication Details

Journal
Clinical Genetics
Published
2025-05-14
DOI
https://doi.org/10.1111/cge.14766
Citations
1
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
1.82
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article

Elucidating the Genetic Underpinnings of Human Musculoskeletal System Aging Through Genomic Structural Equation Modeling

Leichang Zhang, Qinghua Luo, Zhaohui Ding, Pan Shen et al.
1 citations
Clinical Genetics
Genetic Associations and Epidemiology
1.82
article

Elucidating the Genetic Underpinnings of Human Musculoskeletal System Aging Through Genomic Structural Equation Modeling

Leichang Zhang, Qinghua Luo, Zhaohui Ding, Pan Shen, Bo Li, Lihua Wang, Hao Xiong
article en
1 citations

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.

Clinical GeneticsVol. 108(5)
Jiangxi University of Traditional Chinese Medicine (CN), Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine (CN), Sias University (CN)
Openalex Percentile: Top 16%
Genetic Associations and Epidemiology
1.82
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Elucidating the Genetic Underpinnings of Human Musculoskeletal System Aging Through Genomic Structural Equation Modeling — Leichang Zhang, Qinghua Luo, et al. · Clinical Genetics (2025) | TGRS Research Map | TGRS