Abstract
Increasing age is accompanied by many changes, including declining functional skeletal muscle health and immune dysfunction. Peripheral blood mononuclear cells (PBMCs) are circulating cells that assemble an immune response, but their whole genome transcriptome has not been studied in the context of age-related muscle health. Consequently, this article explored associations between three muscle variables indicative of functional muscle health - maximum handgrip strength (muscle strength), appendicular skeletal muscle mass index (ASMI, muscle mass), and gait speed (physical performance) - and two groups of bioinformatics-generated PBMC gene expression features (gene expression-estimated leukocyte subset proportions and gene clusters). We analyzed cross-sectional data from 95 home-dwelling healthy women ≥ 70 years, using "cell-type identification by estimating relative subsets of RNA transcripts" (CIBERSORT) to estimate leukocyte subset proportions and "weighted correlation network analysis" (WGCNA) to generate gene clusters. Associations were studied using linear regression models and relevant gene clusters were subjected to gene set enrichment analysis using gene ontology. Gait speed and ASMI associated with CIBERSORT-estimated monocyte proportions (β = - 0.090, 95% CI = (- 0.146, - 0.034), p-value = 0.002 for gait speed, and β = - 0.206, 95% CI = (- 0.385, - 0.028), p-value = 0.024 for ASMI), and gait speed associated with CIBERSORT-estimated M2 macrophage proportions (β = - 0.026, 95% CI = (- 0.043, - 0.008), p-value = 0.004). Furthermore, maximum handgrip strength associated with nine WGCNA gene clusters, enriched in processes related to immune function and skeletal muscle cells (β in the range - 0.007 to 0.008, p-values < 0.05). These results illustrate interactions between skeletal muscle and the immune system, supporting the notion that age-related functional muscle health and the immune system are closely linked.