Transcriptomic landscape of sex differences in obesity and type 2 diabetes in subcutaneous adipose tissue
Abstract
Type 2 diabetes (T2D) is a chronic metabolic disorder characterized by elevated blood glucose levels, with obesity being a major risk factor in its development. Significant sex differences have been identified in the prevalence, development and pathophysiology of obesity and diabetes. However, the underlying molecular mechanisms remain unclear. This study aims to identify sex-specific biomarkers in obesity and DM2, as well as enhance understanding of the underlying mechanisms associated with sex differences through the integration of expression data.
To achieve this, a systematic review, individual transcriptomic analysis, gene-level meta-analysis, and functional characterization were performed. A total of 8 studies and 236 samples of subcutaneous adipose tissue were analysed, identifying common and sex-specific biomarkers, many of which were previously associated with obesity or diabetes. In obesity, the meta-analysis yielded 19 differentially expressed biomarkers from a sex-specific perspective (e.g. SPATA18, KREMEN1, NPY4R and PRM3), while in T2D the comparison of the expression profiles between sexes led to the identification and validation of specific signatures in males (SAMD9, NBPF3, LDHD, EHD3) and females (RETN, HEY1, PLPP2, PM20D2). At the functional level, this study highlighted the fundamental role of the Wnt pathway in the development of obesity and T2D in females, as well as greater mitochondrial damage and a specific role of free fatty acids in males.
Overall, the sex-specific meta-analyses supported the detection of differentially expressed genes in males and females in the development of obesity and T2D, emphasising the relevance of sex-based information in biomedical data, and opening new avenues for research.
Workflow
Motivation
Over the last three decades, the prevalence of type 2 diabetes (T2D) has increased, even up to 56.4% in the younger population, primarily due to the rise in obesity. The clinical and epidemiological sex differences in obesity and T2D have been widely described. However, the underlying molecular mechanisms remain poorly understood. In this meta-analysis, we aimed to identify transcriptomic biomarkers that can provide insights into sex differences in these conditions, as well as enhance understanding of the underlying mechanisms associated with sex differences through the integration of expression data.
Design
To achieve this objective, a five-step strategy was implemented:
Step A: Systematic Review of transcriptomic studies in the public repositories GEO and BioStudies and PubMed was conducted following the PRISMA guidelines.
Step B: Data Download and Bioinformatic Analysis. Each study were downloaded, and comprehensive bioinformatic analyses were performed.
Step C: In Silico Integration and Meta-Analysis. The collected data were integrated using in silico techniques, employing meta-analysis approaches. Initial findings identified potential biomarkers relevant to personalized medicine in obesity and T2D, including the consideration of sex-related information.
Step D: Interpretation and Functional Analysis. The results were interpreted and subjected to functional analysis to gain insights into their biological implications.
Step E: Experimental validation.
