Investigating the relationship between depression and breast cancer: observational and genetic analyses

BMC Med. 2023 May 4;21(1):170. doi: 10.1186/s12916-023-02876-w.

Abstract

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.

Keywords: Breast cancer; Causal inference; Depression; Genetic correlation; Longitudinal association; Pleiotropic loci.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms* / epidemiology
  • Breast Neoplasms* / genetics
  • Depression / epidemiology
  • Depression / genetics
  • Female
  • Genome-Wide Association Study
  • Humans
  • Mendelian Randomization Analysis
  • Polymorphism, Single Nucleotide / genetics
  • Receptors, Estrogen / genetics
  • Risk

Substances

  • Receptors, Estrogen