Epigenetic signatures and genetic variants associated with muscle strength in postmenopausal women: potential bone muscle cross talk via BMP1 mechanisms

Muscle strength decline is a hallmark of aging and contributes to frailty and bone deterioration, yet the genomic and epigenomic mechanisms predicting functional strength remain unclear. We applied a multiomics approach to identify genetic and epigenetic signatures of muscle strength variability in postmenopausal women. A total of 141 women aged 50-70 yr underwent functional tests, biochemical analysis, anthropometry, blood pressure assessment, and dual-energy X-ray absorptiometry. Participants were classified into higher- and lower-strength groups based on validated upper and lower limb tests. Genome-wide genotyping was performed with the Illumina Global Screening Array, and DNA methylation was measured using the Illumina EPIC 850 K array. A polygenic risk score (PRS) was generated in a training cohort (<i>n</i> = 100) and validated in an independent group (<i>n</i> = 41). Epigenetic scores (EpiScores) were calculated using MethylDetectR, and four fitness-related epigenetic clocks (DNAmGrip, DNAmGait, DNAmVO2max, and DNAmFitAge) were derived with the methylclock package. Twelve single-nucleotide polymorphisms (SNPs) were associated with strength phenotypes, and the PRS predicted group classification with 51.2% accuracy. Epigenetic analysis revealed 12 differentially methylated regions, including higher bone morphogenetic protein 1 (BMP1) EpiScore levels in women with greater strength. Functional enrichment indicated pathways related to bone remodeling and vascular regulation. In the lower strength group, BMP1 EpiScore correlated inversely with femoral neck T-score (<i>r</i> = -0.66, <i>P</i> = 0.037). A meta-analysis of public muscle transcriptomes showed that resistance training increases BMP1 expression. These findings highlight molecular mechanisms linking genetic and epigenetic variation to musculoskeletal aging and functional decline in postmenopausal women.<b>NEW & NOTEWORTHY</b> This study integrates genome-wide genotyping, DNA methylation, and transcriptomic validation to reveal genetic and epigenetic determinants of muscle strength in postmenopausal women. We identify novel SNPs, a predictive polygenic risk score, and higher BMP1 epigenetic scores linked to greater muscle strength and bone remodeling pathways. These multiomics insights provide potential biomarkers for musculoskeletal aging and targets for strategies to preserve strength and skeletal health in older women.

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Journal
Physiological Genomics
Published
2026-02-03
DOI
https://doi.org/10.1152/physiolgenomics.00254.2025
Primary Topic
TGF-β signaling in diseases
Type
article
Field-Weighted Citation Impact
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article

Epigenetic signatures and genetic variants associated with muscle strength in postmenopausal women: potential bone muscle cross talk via BMP1 mechanisms

Carla Barbosa Nonino, Takuji Kawamura, Lígia Moriguchi Watanabe, Pitaksin Chitta et al.
Physiological Genomics
TGF-β signaling in diseases
article

Epigenetic signatures and genetic variants associated with muscle strength in postmenopausal women: potential bone muscle cross talk via BMP1 mechanisms

Carla Barbosa Nonino, Takuji Kawamura, Lígia Moriguchi Watanabe, Pitaksin Chitta, Jonas Benjamim, Carlos Roberto Bueno Junior, Natália Yumi Noronha, Andressa Crystine da Silva Sobrinho, Guilherme da Silva Rodrigues, Ivo Vieira de Sousa Neto, Chanachai Sae-Lee, Fernando Barbosa Júnior
article en

Abstract

Muscle strength decline is a hallmark of aging and contributes to frailty and bone deterioration, yet the genomic and epigenomic mechanisms predicting functional strength remain unclear. We applied a multiomics approach to identify genetic and epigenetic signatures of muscle strength variability in postmenopausal women. A total of 141 women aged 50-70 yr underwent functional tests, biochemical analysis, anthropometry, blood pressure assessment, and dual-energy X-ray absorptiometry. Participants were classified into higher- and lower-strength groups based on validated upper and lower limb tests. Genome-wide genotyping was performed with the Illumina Global Screening Array, and DNA methylation was measured using the Illumina EPIC 850 K array. A polygenic risk score (PRS) was generated in a training cohort (<i>n</i> = 100) and validated in an independent group (<i>n</i> = 41). Epigenetic scores (EpiScores) were calculated using MethylDetectR, and four fitness-related epigenetic clocks (DNAmGrip, DNAmGait, DNAmVO2max, and DNAmFitAge) were derived with the methylclock package. Twelve single-nucleotide polymorphisms (SNPs) were associated with strength phenotypes, and the PRS predicted group classification with 51.2% accuracy. Epigenetic analysis revealed 12 differentially methylated regions, including higher bone morphogenetic protein 1 (BMP1) EpiScore levels in women with greater strength. Functional enrichment indicated pathways related to bone remodeling and vascular regulation. In the lower strength group, BMP1 EpiScore correlated inversely with femoral neck T-score (<i>r</i> = -0.66, <i>P</i> = 0.037). A meta-analysis of public muscle transcriptomes showed that resistance training increases BMP1 expression. These findings highlight molecular mechanisms linking genetic and epigenetic variation to musculoskeletal aging and functional decline in postmenopausal women.<b>NEW & NOTEWORTHY</b> This study integrates genome-wide genotyping, DNA methylation, and transcriptomic validation to reveal genetic and epigenetic determinants of muscle strength in postmenopausal women. We identify novel SNPs, a predictive polygenic risk score, and higher BMP1 epigenetic scores linked to greater muscle strength and bone remodeling pathways. These multiomics insights provide potential biomarkers for musculoskeletal aging and targets for strategies to preserve strength and skeletal health in older women.

Physiological GenomicsVol. 58(3)
Deakin University (AU), Tohoku University (JP), Mahidol University (TH), Tohoku University Hospital (JP)
Openalex Percentile: Top 69%
TGF-β signaling in diseases
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