Literature DB >> 32581065

Does urbanicity modify the relationship between a polygenic risk score for depression and mental health symptoms? Cross-sectional evidence from the observational HUNT Study in Norway.

Erik Reidar Sund1,2,3, Frank J van Lenthe4,5, Mauricio Avendano6,7, Parminder Raina8,9,10, Steinar Krokstad11,3.   

Abstract

BACKGROUND: Research suggests that genetic predisposition for common mental disorders may be moderated by the environment. This study examines whether a polygenic risk score (PRS) for depression is moderated by the level of residential area urbanicity using five symptoms of poor mental health as outcomes.
METHODS: The study sample consisted of 41 198 participants from the 2006-2008 wave of the Norwegian HUNT study. We created a weighted PRS for depression based on 99 variants identified in a recent genome -wide association study. Participants were classified into urban or rural place of residence based on wards that correspond to neighbourhoods. Mixed effects logistic regression models with participants nested in 477 neighbourhoods were specified.
RESULTS: A SD increase in PRS for depression was associated with a small but statistically significant increase in the odds of anxiety, comorbid anxiety and depression and mental distress. Associations for depression were weaker and not statistically significant. Compared with urban residents, rural resident had higher odds for reporting poor mental health. Genetic propensity for depression was higher for residents of urban than rural areas, suggesting gene-environment correlation. There was no sign of effect modification between genetic propensity and urbanicity for depression, anxiety, comorbid anxiety and depression, or mental distress.
CONCLUSION: The PRS predicted small but significant odds of anxiety, comorbid anxiety and depression and mental distress, but we found no support for a differential effect of genetic propensity in urban and rural neighbourhoods for any of the outcomes. © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.

Entities:  

Keywords:  AGEING; BIOSTATISTICS; DISABILITY; ECONOMICS; ELDERLY; EMPLOYMENT; EPIDEMIOLOGY; Epidemiological methods; HEALTH SERVICES; Health inequalities; INTERNATIONAL HEALTH; MENTAL HEALTH; MODELLING; SOCIAL EPIDEMIOLOGY

Mesh:

Year:  2020        PMID: 32581065      PMCID: PMC8053322          DOI: 10.1136/jech-2020-214256

Source DB:  PubMed          Journal:  J Epidemiol Community Health        ISSN: 0143-005X            Impact factor:   3.710


  25 in total

Review 1.  Urbanization, urbanicity, and health.

Authors:  David Vlahov; Sandro Galea
Journal:  J Urban Health       Date:  2002-12       Impact factor: 3.671

Review 2.  Beyond diathesis stress: differential susceptibility to environmental influences.

Authors:  Jay Belsky; Michael Pluess
Journal:  Psychol Bull       Date:  2009-11       Impact factor: 17.737

3.  Cohort Profile: the HUNT Study, Norway.

Authors:  S Krokstad; A Langhammer; K Hveem; T L Holmen; K Midthjell; T R Stene; G Bratberg; J Heggland; J Holmen
Journal:  Int J Epidemiol       Date:  2012-08-09       Impact factor: 7.196

4.  Does neighbourhood deprivation affect the genetic influence on body mass?

Authors:  Gwilym Owen; Kelvyn Jones; Richard Harris
Journal:  Soc Sci Med       Date:  2017-05-19       Impact factor: 4.634

5.  Substance use: Interplay between polygenic risk and neighborhood environment.

Authors:  Joëlle A Pasman; Karin J H Verweij; Abdel Abdellaoui; Jouke Jan Hottenga; Iryna O Fedko; Gonneke Willemsen; Dorret I Boomsma; Jacqueline M Vink
Journal:  Drug Alcohol Depend       Date:  2020-02-28       Impact factor: 4.492

Review 6.  Prevalence, comorbidity, and service utilization for mood disorders in the United States at the beginning of the twenty-first century.

Authors:  Ronald C Kessler; Kathleen R Merikangas; Philip S Wang
Journal:  Annu Rev Clin Psychol       Date:  2007       Impact factor: 18.561

7.  A direct test of the diathesis-stress model for depression.

Authors:  L Colodro-Conde; B Couvy-Duchesne; G Zhu; W L Coventry; E M Byrne; S Gordon; M J Wright; G W Montgomery; P A F Madden; S Ripke; L J Eaves; A C Heath; N R Wray; S E Medland; N G Martin
Journal:  Mol Psychiatry       Date:  2017-07-11       Impact factor: 15.992

8.  Interaction between polygenic risk for cigarette use and environmental exposures in the Detroit Neighborhood Health Study.

Authors:  J L Meyers; M Cerdá; S Galea; K M Keyes; A E Aiello; M Uddin; D E Wildman; K C Koenen
Journal:  Transl Psychiatry       Date:  2013-08-13       Impact factor: 6.222

Review 9.  Polygenic Epidemiology.

Authors:  Frank Dudbridge
Journal:  Genet Epidemiol       Date:  2016-04-07       Impact factor: 2.135

Review 10.  A systematic review of reviews on the prevalence of anxiety disorders in adult populations.

Authors:  Olivia Remes; Carol Brayne; Rianne van der Linde; Louise Lafortune
Journal:  Brain Behav       Date:  2016-06-05       Impact factor: 2.708

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  1 in total

1.  A Smartphone-Based Information Communication Technology Solution for Primary Modifiable Risk Factors for Noncommunicable Diseases: Pilot and Feasibility Study in Norway.

Authors:  Inger Torhild Gram; Guri Skeie; Sunday Oluwafemi Oyeyemi; Kristin Benjaminsen Borch; Laila Arnesdatter Hopstock; Maja-Lisa Løchen
Journal:  JMIR Form Res       Date:  2022-02-25
  1 in total

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