Obesity is a multifactorial disease presenting sex-related differences including adipocyte functions, sex hormone effects, genetics, and metabolic inflammation. These can influence individuals' risk for metabolic dysfunctions, with an urgent need to perform sex-based analysis to improve prevention, treatment, and rehabilitation programs. This research work is aimed at characterizing the transcriptional differences present in subcutaneous adipose tissue (SAT) of five obesity affected men versus five obesity affected women, with an additional focus on the role of long non-coding RNAs. Through RNA-sequencing, we highlighted the presence of both coding and non-coding differentially expressed RNAs, and with numerous computational analyses we identified the processes in which these genes are implicated, along with their role in co-morbidities development. We report 51 differentially expressed transcripts, 32 of which were coding genes and 19 were non-coding. Using the WGCNA R package (Weighted Correlation Network Analysis, version 1.70-3), we describe the interactions between coding and non-coding RNAs, and the non-coding RNAs association with the insurgence of specific diseases, such as cancer development, neurodegenerative diseases, and schizophrenia. In conclusion, our work highlights a specific gender sex-related transcriptional signature in the SAT of obesity affected patients.
Keywords: RNA-seq; bioinformatics; computational prediction; gender differences; gene expression; lncRNAs; metabolic diseases; obesity; sex; transcriptome.