Associations of combined genetic and epigenetic scores with muscle size and muscle strength: a pilot study in older women

BACKGROUND: Inter‐individual variance in skeletal muscle is closely related to genetic architecture and epigenetic regulation. Studies have examined genetic and epigenetic relationships with characteristics of ageing muscle separately, while no study has combined both genetic and epigenetic profiles in ageing muscle research. The aim of this study was to evaluate the association between combined genetic and methylation scores and skeletal muscle phenotypes in older women. METHODS: Forty‐eight older Caucasian women (aged 65–79 years) were included in this study. Biceps brachii thickness and vastus lateralis anatomical cross‐sectional area (ACSA(VL)) were measured by ultrasonography. Maximum isometric elbow flexion (MVC(EF)) and knee extension (MVC(KE)) torques were measured by a customized dynamometer. The muscle‐driven genetic predisposition score (GPS(SNP)) was calculated based on seven muscle‐related single nucleotide polymorphisms (SNPs). DNA methylation levels of whole blood samples were analysed using Infinium MethylationEPIC BeadChip arrays. The DNA methylation score was calculated as a weighted sum of methylation levels of sarcopenia‐driven CpG sites (MS(SAR)) or an overall gene‐wise methylation score (MS(SNP), the mean methylation level of CpG sites located in muscle‐related genes). Linear regression models were built to study genetic and epigenetic associations with muscle size and strength. Three models were built with both genetic and methylation scores: (1) MS(SAR) + GPS(SNP), (2) MS(SNP) + GPS(SNP), and (3) gene‐wise combined scores which were calculated as the ratio of the SNP score to the mean methylation level of promoters in the corresponding gene. Additional models with only a genetic or methylation score were also built. All models were adjusted for age and BMI. RESULTS: MS(SAR) was negatively associated with ACSA(VL), MVC(EF), and MVC(KE) and explained 10.1%, 35.5%, and 40.1% of the variance, respectively. MS(SAR) explained more variance in these muscular phenotypes than GPS(SNP), MS(SNP), and models including both genetic and methylation scores. MS(SNP) and GPS(SNP) accounted for less than 8% and 5% of the variance in all muscular phenotypes, respectively. The genotype and methylation level of CNTF was positively related to MVC(KE) (P = 0.03) and explained 12.2% of the variance. The adjusted R (2) and Akaike information criterion showed that models with only a MS(SAR) performed the best in explaining inter‐individual variance in muscular phenotypes. CONCLUSIONS: Our results improve the understanding of inter‐individual variance in muscular characteristics of older women and suggest a possible application of a sarcopenia‐driven methylation score to muscle strength estimation in older women while the combination with a genetic score still needs to be further studied.