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Investigating the relationship between depression and breast cancer: observational and genetic analyses
BACKGROUND: Both depression and breast cancer (BC) contribute to a substantial global burden of morbidity and mortality among women, and previous studies have observed a potential depression-BC link. We aimed to comprehensively characterize the phenotypic and genetic relationships between depression...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10161423/ https://www.ncbi.nlm.nih.gov/pubmed/37143087 http://dx.doi.org/10.1186/s12916-023-02876-w |
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author | Wu, Xueyao Zhang, Wenqiang Zhao, Xunying Zhang, Li Xu, Minghan Hao, Yu Xiao, Jinyu Zhang, Ben Li, Jiayuan Kraft, Peter Smoller, Jordan W. Jiang, Xia |
author_facet | Wu, Xueyao Zhang, Wenqiang Zhao, Xunying Zhang, Li Xu, Minghan Hao, Yu Xiao, Jinyu Zhang, Ben Li, Jiayuan Kraft, Peter Smoller, Jordan W. Jiang, Xia |
author_sort | Wu, Xueyao |
collection | PubMed |
description | BACKGROUND: Both depression and breast cancer (BC) contribute to a substantial global burden of morbidity and mortality among women, and previous studies have observed a potential depression-BC link. We aimed to comprehensively characterize the phenotypic and genetic relationships between depression and BC. METHODS: We first evaluated phenotypic association using longitudinal follow-up data from the UK Biobank (N = 250,294). We then investigated genetic relationships leveraging summary statistics from the hitherto largest genome-wide association study of European individuals conducted for depression (N = 500,199), BC (N = 247,173), and its subtypes based on the status of estrogen receptor (ER + : N = 175,475; ER − : N = 127,442). RESULTS: Observational analysis suggested an increased hazard of BC in depression patients (HR = 1.10, 95%CIs = 0.95–1.26). A positive genetic correlation between depression and overall BC was observed ([Formula: see text] = 0.08, P = 3.00 × 10(–4)), consistent across ER + ([Formula: see text] = 0.06, P = 6.30 × 10(–3)) and ER − subtypes ([Formula: see text] = 0.08, P = 7.20 × 10(–3)). Several specific genomic regions showed evidence of local genetic correlation, including one locus at 9q31.2, and four loci at, or close, to 6p22.1. Cross-trait meta-analysis identified 17 pleiotropic loci shared between depression and BC. TWAS analysis revealed five shared genes. Bi-directional Mendelian randomization suggested risk of depression was causally associated with risk of overall BC (OR = 1.12, 95%Cis = 1.04–1.19), but risk of BC was not causally associated with risk of depression. CONCLUSIONS: Our work demonstrates a shared genetic basis, pleiotropic loci, and a putative causal relationship between depression and BC, highlighting a biological link underlying the observed phenotypic relationship; these findings may provide important implications for future studies aimed reducing BC risk. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-023-02876-w. |
format | Online Article Text |
id | pubmed-10161423 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-101614232023-05-06 Investigating the relationship between depression and breast cancer: observational and genetic analyses Wu, Xueyao Zhang, Wenqiang Zhao, Xunying Zhang, Li Xu, Minghan Hao, Yu Xiao, Jinyu Zhang, Ben Li, Jiayuan Kraft, Peter Smoller, Jordan W. Jiang, Xia BMC Med Research Article BACKGROUND: Both depression and breast cancer (BC) contribute to a substantial global burden of morbidity and mortality among women, and previous studies have observed a potential depression-BC link. We aimed to comprehensively characterize the phenotypic and genetic relationships between depression and BC. METHODS: We first evaluated phenotypic association using longitudinal follow-up data from the UK Biobank (N = 250,294). We then investigated genetic relationships leveraging summary statistics from the hitherto largest genome-wide association study of European individuals conducted for depression (N = 500,199), BC (N = 247,173), and its subtypes based on the status of estrogen receptor (ER + : N = 175,475; ER − : N = 127,442). RESULTS: Observational analysis suggested an increased hazard of BC in depression patients (HR = 1.10, 95%CIs = 0.95–1.26). A positive genetic correlation between depression and overall BC was observed ([Formula: see text] = 0.08, P = 3.00 × 10(–4)), consistent across ER + ([Formula: see text] = 0.06, P = 6.30 × 10(–3)) and ER − subtypes ([Formula: see text] = 0.08, P = 7.20 × 10(–3)). Several specific genomic regions showed evidence of local genetic correlation, including one locus at 9q31.2, and four loci at, or close, to 6p22.1. Cross-trait meta-analysis identified 17 pleiotropic loci shared between depression and BC. TWAS analysis revealed five shared genes. Bi-directional Mendelian randomization suggested risk of depression was causally associated with risk of overall BC (OR = 1.12, 95%Cis = 1.04–1.19), but risk of BC was not causally associated with risk of depression. CONCLUSIONS: Our work demonstrates a shared genetic basis, pleiotropic loci, and a putative causal relationship between depression and BC, highlighting a biological link underlying the observed phenotypic relationship; these findings may provide important implications for future studies aimed reducing BC risk. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-023-02876-w. BioMed Central 2023-05-04 /pmc/articles/PMC10161423/ /pubmed/37143087 http://dx.doi.org/10.1186/s12916-023-02876-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Wu, Xueyao Zhang, Wenqiang Zhao, Xunying Zhang, Li Xu, Minghan Hao, Yu Xiao, Jinyu Zhang, Ben Li, Jiayuan Kraft, Peter Smoller, Jordan W. Jiang, Xia Investigating the relationship between depression and breast cancer: observational and genetic analyses |
title | Investigating the relationship between depression and breast cancer: observational and genetic analyses |
title_full | Investigating the relationship between depression and breast cancer: observational and genetic analyses |
title_fullStr | Investigating the relationship between depression and breast cancer: observational and genetic analyses |
title_full_unstemmed | Investigating the relationship between depression and breast cancer: observational and genetic analyses |
title_short | Investigating the relationship between depression and breast cancer: observational and genetic analyses |
title_sort | investigating the relationship between depression and breast cancer: observational and genetic analyses |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10161423/ https://www.ncbi.nlm.nih.gov/pubmed/37143087 http://dx.doi.org/10.1186/s12916-023-02876-w |
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