Publication
Sex-specific transcriptome similarity networks elucidate comorbidity relationships
| dc.contributor.author | Sánchez-Valle, Jon | |
| dc.contributor.author | Flores-Rodero, María | |
| dc.contributor.author | Costa, Felipe Xavier | |
| dc.contributor.author | Carbonell-Caballero, Jose | |
| dc.contributor.author | Núñez-Carpintero, Iker | |
| dc.contributor.author | Tabarés-Seisdedos, Rafael | |
| dc.contributor.author | Rocha, Luis Mateus | |
| dc.contributor.author | Cirillo, Davide | |
| dc.contributor.author | Valencia, Alfonso | |
| dc.date.accessioned | 2025-02-04T11:54:25Z | |
| dc.date.available | 2025-02-04T11:54:25Z | |
| dc.date.issued | 2025-01-24 | |
| dc.description.abstract | Humans present sex-driven biological differences. Consequently, the prevalence of analyzing specific diseases and comorbidities differs between the sexes, directly impacting patients’ management and treatment. Despite its relevance and the growing evidence of said differences across numerous diseases (with 4,370 PubMed results published within the past year), knowledge at the comorbidity level remains limited. In fact, to date, no study has attempted to identify the biological processes altered differently in women and men, promoting differences in comorbidities. To shed light on this problem, we analyze expression data for more than 100 diseases from public repositories, analyzing each sex independently. We calculate similarities between differential expression profiles by disease pairs and find that 13-16% of transcriptomically similar disease pairs are sex-specific. By comparing these results with epidemiological evidence, we recapitulate 53-60% of known comorbidities distinctly described for men and women, finding sex-specific transcriptomic similarities between sex-specific comorbid diseases. The analysis of shared underlying pathways shows that diseases can co-occur in men and women by altering alternative biological processes. Finally, we identify different drugs differentially associated with comorbid diseases depending on patients’ sex, highlighting the need to consider this relevant variable in the administration of drugs due to their possible influence on comorbidities. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1101/2025.01.22.634077 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.14/48038 | |
| dc.language.iso | eng | pt_PT |
| dc.publisher | bioRxiv | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | pt_PT |
| dc.title | Sex-specific transcriptome similarity networks elucidate comorbidity relationships | pt_PT |
| dc.type | preprint | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | preprint | pt_PT |