Depression and prostate cancer risk: A Mendelian randomization study

Cancer Med. 2020 Dec;9(23):9160-9167. doi: 10.1002/cam4.3493. Epub 2020 Oct 7.

Abstract

Background: The association between depression and prostate carcinogenesis has been reported in observational studies but the causality from depression on prostate cancer (PCa) remained unknown. We aimed to assess the causal effect of depression on PCa using the two-sample Mendelian randomization (MR) method.

Methods: Two sets of genetics instruments were used for analysis, derived from publicly available genetic summary data. One was 44 single-nucleotide polymorphisms (SNPs) robustly associated with major depressive disorder (MDD) and the other was two SNPs related with depressive status as ever depressed for a whole week. Inverse-variance weighted method, weighted median method, MR-Egger regression, MR Pleiotropy RESidual Sum, and Outlier test were used for MR analyses.

Results: No evidence for an effect of MDD on PCa risk was found in inverse-variance weighted (OR: 1.12, 95% CI: 0.97-1.30, p = 0.135), MR-Egger (OR 0.89, 95% CI: 0.29-2.68, p = 0.833), and weighted median (OR: 1.08, 95% CI: 0.92-1.27, p = 0.350). Also, no strong evidence for an effect of depressive status on PCa incidence was found using the inverse-variance weighted method (OR 0.72, 95% CI: 0.35-1.47, p = 0.364).

Conclusions: The large MR analysis indicated that depression may not be causally associated with a risk of PCa.

Keywords: Mendelian randomization; causality; depression; prostate cancer.

MeSH terms

  • Causality
  • Depressive Disorder, Major / diagnosis
  • Depressive Disorder, Major / epidemiology
  • Depressive Disorder, Major / genetics*
  • Depressive Disorder, Major / psychology
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study
  • Humans
  • Incidence
  • Male
  • Mendelian Randomization Analysis
  • Polymorphism, Single Nucleotide*
  • Prostatic Neoplasms / diagnosis
  • Prostatic Neoplasms / epidemiology
  • Prostatic Neoplasms / genetics*
  • Risk Assessment
  • Risk Factors