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A large-scale genome-wide cross-trait analysis for the effect of COVID-19 on female-specific cancers

Little is known regarding the long-term adverse effects of COVID-19 on female-specific cancers, nor the shared genetic influences underlying these conditions. We performed a comprehensive genome-wide cross-trait analysis to investigate the shared genetic architecture between COVID-19 (infection, hos...

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Detalles Bibliográficos
Autores principales: Zhao, Xunying, Wu, Xueyao, Xiao, Jinyu, Zhang, Li, Hao, Yu, Xiao, Chenghan, Zhang, Ben, Li, Jiayuan, Jiang, Xia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450412/
https://www.ncbi.nlm.nih.gov/pubmed/37636041
http://dx.doi.org/10.1016/j.isci.2023.107497
Descripción
Sumario:Little is known regarding the long-term adverse effects of COVID-19 on female-specific cancers, nor the shared genetic influences underlying these conditions. We performed a comprehensive genome-wide cross-trait analysis to investigate the shared genetic architecture between COVID-19 (infection, hospitalization, and critical illness) with three female-specific cancers (breast cancer (BC), epithelial ovarian cancer (EOC), and endometrial cancer (EC)). We identified significant genome-wide genetic correlations with EC for both hospitalization ([Formula: see text]  = 0.19, p = 0.01) and critical illness ([Formula: see text]  = 0.29, p = 3.00 × 10(−4)). Mendelian randomization demonstrated no valid association of COVID-19 with any cancer of interest, except for suggestive associations of genetically predicted hospitalization (OR(IVW) = 1.09, p = 0.04) and critical illness (OR(IVW) = 1.06, p = 0.04) with EC risk, none withstanding multiple correction. Cross-trait meta-analysis identified 20 SNPs shared between COVID-19 with BC, 15 with EOC, and 5 with EC; and transcriptome-wide association studies revealed multiple shared genes. Findings support intrinsic links underlying these complex traits, highlighting shared mechanisms rather than causal associations.