Supplementary Material for: The skeletal muscle transcriptome profile of elderly men with metabolic syndrome based on weighted gene co-expression network analysis

Introduction: This study aims to understand the transcriptome characteristics of the skeletal muscle of old man with metabolic syndrome (MS), to find the hub genes and insight into the molecular mechanisms of skeletal muscle in the occurrence and development of MS. Methods: In this study, the Limma package of R software was used to analyze the differentially expressed genes in the skeletal muscle of healthy young adult (YO) men, healthy elderly (EL) men, and elderly men diagnosed with metabolic syndrome (SX) for at least 10 years. Bioinformatics methods, such as GO enrichment analysis, KEGG enrichment analysis and gene interaction network analysis, were used to explore the biological functions of differentially expressed genes, and WGCNA was used to cluster differentially expressed genes into modules. Results: Among the YO group, EL group, and SX group, 65 co-differentially expressed genes were found may be regulated by age factor and metabolic syndrome factor. Those co-differentially expressed genes were enriched into 25 biological process terms and 3 KEGG pathways. Based on the WGCNA results, a total of five modules were identified. Fifteen hub genes may play an essential role in regulating the function of skeletal muscle of old men with metabolic syndrome. Conclusions: 65 differentially expressed genes and 5 modules may regulate the function of skeletal muscle of old men with MS, among which fifteen hub genes may play an essential role in the occurrence and development of MS.

引言：本研究旨在解析合并代谢综合征（metabolic syndrome, MS）老年男性的骨骼肌转录组特征，筛选枢纽基因（hub genes）并深入阐明骨骼肌在代谢综合征发生发展过程中的分子机制。
方法：本研究借助R软件的Limma包，对健康青年男性（YO）、健康老年男性（EL）以及确诊代谢综合征至少10年的老年男性（SX）的骨骼肌组织中的差异表达基因进行分析。采用基因本体（Gene Ontology, GO）富集分析、京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）富集分析及基因互作网络分析等生物信息学方法，探究差异表达基因的生物学功能；同时通过加权基因共表达网络分析（weighted gene co-expression network analysis, WGCNA）将差异表达基因聚类为不同模块。
结果：在YO组、EL组与SX组中，共筛选得到65个受年龄因素与代谢综合征因素共同调控的差异表达基因。上述共同差异表达基因富集得到25个生物学过程条目及3条KEGG通路。基于WGCNA分析结果，共鉴定出5个基因共表达模块。最终筛选出15个枢纽基因，其可能在调控合并代谢综合征老年男性的骨骼肌功能中发挥关键作用。
结论：本研究发现的65个差异表达基因与5个基因模块，可能参与调控合并代谢综合征老年男性的骨骼肌功能，其中15个枢纽基因或在代谢综合征的发生发展过程中扮演核心调控角色。