Skeletal Muscle Immunometabolism in Women With Polycystic Ovary Syndrome: A Meta-Analysis

Polycystic ovary syndrome (PCOS) is an endocrine and metabolic disorder affecting up to 15% of women at reproductive age. The main features of PCOS are hyperandrogenism and irregular menstrual cycles together with metabolic dysfunctions including hyperinsulinemia and insulin resistance and a 4-fold increased risk of developing type 2 diabetes. Despite the high prevalence the pathophysiology of the syndrome is unclear. Insulin resistance in women with PCOS likely affect the skeletal muscle and recently it was demonstrated that changes in DNA methylation affects the gene expression in skeletal muscle that in part can explain their metabolic abnormalities. The objective of this work was to combine gene expression array data from different datasets to improve statistical power and thereby identify novel biomarkers that can be further explored. In this narrative review, we performed a meta-analysis of skeletal muscle arrays available from Gene Expression Omnibus and from publications. The eligibility criteria were published articles in English, and baseline (no treatment) skeletal muscle samples from women with PCOS and controls. The R package Metafor was used for integration of the datasets. One hundred and fourteen unique transcripts were differentially expressed in skeletal muscle from women with PCOS vs. controls (q < 0.05), 87% of these transcripts have not been previously identified as altered in PCOS muscle. ING2, CDKAL1, and AKTIP had the largest differential increase in expression, and TSHZ2, FKBP2, and OCEL1 had the largest decrease in expression. Two genes, IRX3 and CDKAL1 were consistently upregulated (q < 0.05) in the individual analyses and meta-analysis. Based on the meta-analysis, we identified several dysregulated immunometabolic pathways as a part of the molecular mechanisms of insulin resistance in the skeletal muscle of women with PCOS. The transcriptomic data need to be verified by functional analyses as well as proteomics to advance our understanding of PCOS specific insulin resistance in skeletal muscle.

Abstract licence: CC BY

40 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.