Hepatic steatosis and steatohepatitis: a functional meta-analysis of sex-based differences in transcriptomic studies

Abstract

Background Previous studies have described sex-based differences in the epidemiological and clinical patterns of non-alcoholic fatty liver disease (NAFLD); however, we understand relatively little regarding the underlying molecular mechanisms. Herein, we present the first systematic review and meta-analysis of NAFLD transcriptomic studies to identify sex-based differences in the molecular mechanisms involved during the steatosis (NAFL) and steatohepatitis (NASH) stages of the disease. Methods Transcriptomic studies in the Gene Expression Omnibus database were systematically reviewed following the PRISMA statement guidelines. For each study, NAFL and NASH in premenopausal women and men were compared using a dual strategy: gene-set analysis and pathway activity analysis. Finally, the functional results of all studies were integrated into a meta-analysis. Results We reviewed a total of 114 abstracts and analyzed seven studies that included 323 eligible patients. The meta-analyses identified significantly altered molecular mechanisms between premenopausal women and men, including the overrepresentation of genes associated with DNA regulation, vinculin binding, interleukin-2 responses, negative regulation of neuronal death, and the transport of ions and cations in premenopausal women. In men, we discovered the overrepresentation of genes associated with the negative regulation of interleukin-6 and the establishment of planar polarity involved in neural tube closure. Conclusions Our meta-analysis of transcriptomic data provides a powerful approach to identify sex-based differences in NAFLD. We detected differences in relevant biological functions and molecular terms between premenopausal women and men. Differences in immune responsiveness between men and premenopausal women with NAFLD suggest that women possess a more immune tolerant milieu, while men display an impaired liver regenerative response. Graphical abstract

A Deep Transcriptome Meta-Analysis Reveals Sex-based Molecular Differences in Multiple Sclerosis

“…Previous works have applied this strategy of integrating data from numerous studies to better characterise sex differences [51][52][53]. However, to our knowledge, this is the first time that a meta-analysis of transcriptomic studies in MS has been carried out, where several tissues have been evaluated with the aim of identifying sex-specific biomarkers that provide a better understanding of the molecular mechanisms in MS. As described in the introduction section, MS has a great impact on society, being the majority cause of disability not associated with accidents in the young adult population but MS causes knowledge is very limited.…”

“…A range of previous studies have integrated data from numerous sources to characterize sexbased differences [58][59][60]; however, to our knowledge, this study represents the first metaanalysis of transcriptomic studies in MS and the first identification of sex-specific biomarkers in several tissues, which provides a better understanding of the molecular mechanisms underlying MS. This pathology has an important impact on society as one of the significant causes of disability in young adults; however, data regarding the causes of MS remain limited.…”

Interplay between murine sex-biased gene expression and hepatic zonation revealed by single nucleus RNA sequencing

“…The sexdifferential expression of specific hepatic P450s and other drug-metabolizing enzymes [2] is a key factor in the sex dependence of liver metabolism of many drugs and steroids in both rodents [3][4][5] and in humans, where sex-biased drug metabolism and pharmacokinetics is common [6,7]. Sex-differences also characterize the incidence and severity of major liver diseases, including non-alcoholic fatty liver disease, steatohepatitis and hepatocellular carcinoma, which are more prevalent and more severe in males [8][9][10]. A hormonal basis for these sex differences is indicated by the lower rates of disease in premenopausal females as compared to males and post-menopausal females [11].…”

MetaFun: Unveiling Sex-based Differences in Multiple Transcriptomic Studies through Comprehensive Functional Meta-analysis

“…In order to make the most of this information, multiple studies may be analyzed at the same time. Defined for this purpose, the meta-analysis is a statistical methodology which takes into account the relative importance of different studies in order to combine all of them in a single analysis and extract results based on more evidence and samples [5,6,7]. MetaFun aims to simplify the process and facilitate the access to this methodology to researchers working with omics data which may not be familiar with it, allowing to meta-analyze multiple omics datasets with or without a gender perspective, and to combine them to gain major statistical power and soundness.…”

“…The question of which one to trust has no optimal answer, and a solution might be to integrate all different datasets in the same analysis. Defined for this purpose, the meta-analysis is a statistical methodology which takes into account the relative importance of different studies in order to combine them in a single analysis and extract results based on more evidence and samples [5,6,7]. However, the application of advanced statistical techniques as the meta-analysis is often out of reach for biomedical researchers aiming to analyze their data in an easy way.…”