Landscape of sex differences in obesity and type 2 diabetes in subcutaneous adipose tissue: a systematic review and meta-analysis of transcriptomics studies.
Por:
Moldovan RA, Hidalgo MR, Castañé H, Jiménez-Franco A, Joven J, Burks DJ, Galán A and García-García F
Publicada:
1 jul 2025
Ahead of Print:
1 abr 2025
Resumen:
Obesity represents a significant risk factor in the development of type 2 diabetes (T2D), a chronic metabolic disorder characterized by elevated blood glucose levels, and a previous step for its development. Significant sex differences have been identified in the prevalence, development, and pathophysiology of obesity and T2D; however, the underlying molecular mechanisms remain unclear. This study aims to identify sex-specific signatures in obesity and T2D and enhance our understanding of the underlying mechanisms associated with sex differences by integrating expression data. We performed a systematic review and individual transcriptomic analysis of eight selected studies which included 302 subcutaneous adipose tissue samples. Then, we conducted different gene-level meta-analyses and functional characterizations for obesity and T2D separately, identifying common and sex-specific transcriptional profiles, many of which were previously associated with obesity or T2D. The obesity meta-analysis yielded nineteen differentially-expressed genes from a sex-specific perspective (e.g., SPATA18, KREMEN1, NPY4R, and PRM3), while a comparison of the expression profiles between sexes in T2D prompted the identification and validation of specific transcriptomic signatures in males (SAMD9, NBPF3, LDHD, and EHD3) and females (RETN, HEY1, PLPP2, and PM20D2). At the functional level, we highlighted the fundamental role of the Wnt pathway in the development of obesity and T2D in females, and the roles of mitochondrial damage and free fatty acids in males. Overall, our sex-specific meta-analyses supported the detection of differentially expressed genes in males and females associated with the development of obesity and further T2D development, emphasizing the relevance of sex-based information in biomedical data and opening new avenues for research.
Filiaciones:
Moldovan RA:
Computational Biomedicine Laboratory, Principe Felipe Research Center (CIPF), 46012, Valencia, Spain
Department of Applied Statistics and Operations Research and Quality, Universitat Politècnica de València, Valencia 46022, Spain
:
Computational Biomedicine Laboratory, Principe Felipe Research Center (CIPF), 46012, Valencia, Spain
Departament de Matemàtiques, Facultat de Matemàtiques, Universitat de València, 46010, Valencia, Spain
Castañé H:
Unitat de Recerca Biomèdica, Hospital Universitari de Sant Joan, Institut d'Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, 43204 Reus, Spain
Jiménez-Franco A:
Unitat de Recerca Biomèdica, Hospital Universitari de Sant Joan, Institut d'Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, 43204 Reus, Spain
Joven J:
Unitat de Recerca Biomèdica, Hospital Universitari de Sant Joan, Institut d'Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, 43204 Reus, Spain
:
Molecular Neuroendocrinology Laboratory, Principe Felipe Research Center (CIPF), 46012, Valencia, Spain
CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain
:
Molecular Neuroendocrinology Laboratory, Principe Felipe Research Center (CIPF), 46012, Valencia, Spain
CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain
Departament de Bioquímica i Biologia Molecular, Facultat de Biologia, Universitat de València, 46010, Valencia, Spain
:
Computational Biomedicine Laboratory, Principe Felipe Research Center (CIPF), 46012, Valencia, Spain
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