Association Between Population Density and Genetic Risk for Schizophrenia

Lucía Colodro-Conde*, Baptiste Couvy-Duchesne, John B. Whitfield, Fabian Streit, Scott Gordon, Kathryn E. Kemper, Loic Yengo, Zhili Zheng, Maciej Trzaskowski, Eveline L. De Zeeuw, Michel G. Nivard, Marjolijn Das, Rachel E. Neale, Stuart MacGregor, Catherine M. Olsen, David C. Whiteman, Dorret I. Boomsma, Jian Yang, Marcella Rietschel, John J. McGrathSarah E. Medland, Nicholas G. Martin

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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Abstract

Importance: Urban life has been proposed as an environmental risk factor accounting for the increased prevalence of schizophrenia in urban areas. An alternative hypothesis is that individuals with increased genetic risk tend to live in urban/dense areas.

Objective: To assess whether adults with higher genetic risk for schizophrenia have an increased probability to live in more populated areas than those with lower risk.

Design, Setting, and Participants: Four large, cross-sectional samples of genotyped individuals of European ancestry older than 18 years with known addresses in Australia, the United Kingdom, and the Netherlands were included in the analysis. Data were based on the postcode of residence at the time of last contact with the participants. Community-based samples who took part in studies conducted by the Queensland Institute for Medical Research Berghofer Medical Research Institute (QIMR), UK Biobank (UKB), Netherlands Twin Register (NTR), or QSkin Sun and Health Study (QSKIN) were included. Genome-wide association analysis and mendelian randomization (MR) were included. The study was conducted between 2016 and 2018.

Exposures: Polygenic risk scores for schizophrenia derived from genetic data (genetic risk is independently measured from the occurrence of the disease). Socioeconomic status of the area was included as a moderator in some of the models.

Main Outcomes and Measures: Population density of the place of residence of the participants determined from census data. Remoteness and socioeconomic status of the area were also tested.

Results: The QIMR participants (15 544; 10 197 [65.6%] women; mean [SD] age, 54.4 [13.2] years) living in more densely populated areas (people per square kilometer) had a higher genetic loading for schizophrenia (r2 = 0.12%; P = 5.69 × 10-5), a result that was replicated across all 3 other cohorts (UKB: 345 246; 187 469 [54.3%] women; age, 65.7 [8.0] years; NTR: 11 212; 6727 [60.0%] women; age, 48.6 [17.5] years; and QSKIN: 15 726; 8602 [54.7%] women; age, 57.0 [7.9] years). This genetic association could account for 1.7% (95% CI, 0.8%-3.2%) of the schizophrenia risk. Estimates from MR analyses performed in the UKB sample were significant (b = 0.049; P = 3.7 × 10-7 using GSMR), suggesting that the genetic liability to schizophrenia may have a causal association with the tendency to live in urbanized locations.

Conclusions and Relevance: The results of this study appear to support the hypothesis that individuals with increased genetic risk tend to live in urban/dense areas and suggest the need to refine the social stress model for schizophrenia by including genetics as well as possible gene-environment interactions.

Original languageEnglish
Pages (from-to)901-910
Number of pages10
JournalJAMA Psychiatry
Volume75
Issue number9
Early online date23 Jun 2018
DOIs
Publication statusPublished - Sept 2018

Funding

FundersFunder number
National Institutes of HealthR01 AA007535, 1087889, APP1073898, R37 AA007728, 1113400, R01 AA013326, R01 AA010249, APP1063061
National Institute on Alcohol Abuse and AlcoholismR01AA013321
Sylvia and Charles Viertel Charitable Foundation
National Health and Medical Research Council981351
Danmarks GrundforskningsfondAPP1058522, APP1060183, 1103623
University of QueenslandAPP1056929

    Keywords

    • PRS

    Cohort Studies

    • Netherlands Twin Register (NTR)

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