Evaluating the interaction between 3'aQTL and alcohol consumption/smoking on anxiety and depression: 3'aQTL-by-environment interaction study in UK Biobank cohort

J Affect Disord. 2023 Oct 1:338:518-525. doi: 10.1016/j.jad.2023.06.050. Epub 2023 Jun 29.

Abstract

Background: Smoking and alcohol consumption were associated with the development of depression and anxiety. 3'UTR APA quantitative trait loci (3'aQTLs) have been associated with multiple health states and conditions. Our aim is to evaluate the interactive effects of 3'aQTLs-alcohol consumption/tobacco smoking on the risk of anxiety and depression.

Methods: The 3'aQTL data of 13 brain regions were extracted from the large-scale 3'aQTL atlas. The phenotype data (frequency of cigarette smoking and alcohol drinking, anxiety score, self-reported anxiety, depression score and self-reported depression) of 90,399-103,011 adults aged 40-69 years living in the UK and contributing to the UK Biobank during 2006-2010, were obtained from the UK Biobank cohort. The frequency of cigarette smoking and alcohol drinking of each subject were defined by the amount of smoking and alcohol drinking of self-reported, respectively. The continuous alcohol consumption/smoking terms were further categorized in tertiles. 3'aQTL-by-environmental interaction analysis was then performed to evaluate the associations of gene-smoking/alcohol consumption interactions with anxiety and depression using generalized linear model (GLM) of PLINK 2.0 with an additive mode of inheritance. Furthermore, GLM was also used to explore the relationship between alcohol consumption/smoking with hazard of anxiety/depression stratified by allele for the significant genotyped SNPs that modified the alcohol consumption/smoking-anxiety/depression association.

Results: The interaction analysis identified several candidate 3'aQTLs-alcohol consumption interactions, such as rs7602638 located in PPP3R1 (β = 0.08, P = 6.50 × 10-6) for anxiety score; rs10925518 located in RYR2 (OR = 0.95, P = 3.06 × 10-5) for self-reported depression. Interestingly, we also observed that the interactions between TMOD1 (β = 0.18, P = 3.30 × 10-8 for anxiety score; β = 0.17, P = 1.42 × 10-6 for depression score), ZNF407 (β = 0.17, P = 2.11 × 10-6 for anxiety score; β = 0.15, P = 4.26 × 10-5 for depression score) and alcohol consumption was not only associated with anxiety, but related to depression. Besides, we found that relationship between alcohol consumption and hazard of anxiety/depression was significantly different for different SNPs genotypes, such as rs34505550 in TMOD1 (AA: OR = 1.03, P = 1.79 × 10-6; AG: OR = 1.00, P = 0.94; GG: OR = 1.00, P = 0.21) for self-reported anxiety.

Limitations: The identified 3'aQTLs-alcohol consumption/smoking interactions were associated with depression and anxiety, and its potential biological mechanisms need to be further revealed.

Conclusions: Our study identified important interactions between candidate 3'aQTL and alcohol consumption/smoking on depression and anxiety, and found that the 3'aQTL may modify the associations between consumption/smoking with depression and anxiety. These findings may help to further explore the pathogenesis of depression and anxiety.

Keywords: 3'aQTL; Alcohol; Alternative polyadenylation; Anxiety; Depression; Interaction; Smoking.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alcohol Drinking / epidemiology
  • Alcohol Drinking / genetics
  • Anxiety / epidemiology
  • Anxiety / genetics
  • Biological Specimen Banks
  • Depression* / epidemiology
  • Depression* / genetics
  • Gene-Environment Interaction*
  • Smoking / epidemiology
  • Smoking / genetics
  • United Kingdom / epidemiology