Genetic Epidemiology, Translational Neurogenomics, Psychiatric Genetics and Statistical Genetics Laboratories investigate the pattern of disease in families, particularly identical and non-identical twins, to assess the relative importance of genes and environment in a variety of important health problems.
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PMID
29936532
TITLE
Association Between Population Density and Genetic Risk for Schizophrenia.
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
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. 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
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. 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. 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
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. 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. 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. 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
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. 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. 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. 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. 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
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. 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. 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. 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. Population density of the place of residence of the participants determined from census data. Remoteness and socioeconomic status of the area were also tested. 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
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. 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. 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. 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. Population density of the place of residence of the participants determined from census data. Remoteness and socioeconomic status of the area were also tested. 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. 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.
DATE PUBLISHED
2018 09 01
HISTORY
PUBSTATUS PUBSTATUSDATE
pubmed 2018/06/25 06:00
medline 2019/10/02 06:00
entrez 2018/06/25 06:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
Colodro-Conde L Colodro-Conde Lucía L QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Couvy-Duchesne B Couvy-Duchesne Baptiste B Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.
Whitfield JB Whitfield John B JB QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Streit F Streit Fabian F Department of Genetic Epidemiology in Psychiatry, Medical Faculty Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany.
Gordon S Gordon Scott S QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Kemper KE Kemper Kathryn E KE Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.
Yengo L Yengo Loic L Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.
Zheng Z Zheng Zhili Z Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.
Trzaskowski M Trzaskowski Maciej M Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.
de Zeeuw EL de Zeeuw Eveline L EL Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Nivard MG Nivard Michel G MG Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Das M Das Marjolijn M Centre for BOLD Cities, Leiden-Delft-Erasmus University, Rotterdam, the Netherlands.
Neale RE Neale Rachel E RE QIMR Berghofer Medical Research Institute, Brisbane, Australia.
MacGregor S MacGregor Stuart S QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Olsen CM Olsen Catherine M CM QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Whiteman DC Whiteman David C DC QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Boomsma DI Boomsma Dorret I DI Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Yang J Yang Jian J Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.
Rietschel M Rietschel Marcella M Department of Genetic Epidemiology in Psychiatry, Medical Faculty Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany.
McGrath JJ McGrath John J JJ National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark.
Medland SE Medland Sarah E SE QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Martin NG Martin Nicholas G NG QIMR Berghofer Medical Research Institute, Brisbane, Australia.
INVESTIGATORS
JOURNAL
VOLUME: 75
ISSUE: 9
TITLE: JAMA psychiatry
ISOABBREVIATION: JAMA Psychiatry
YEAR: 2018
MONTH: 09
DAY: 01
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Internet
ISSN: 2168-6238
ISSNTYPE: Electronic
MEDLINE JOURNAL
MEDLINETA: JAMA Psychiatry
COUNTRY: United States
ISSNLINKING: 2168-622X
NLMUNIQUEID: 101589550
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
COMMENTS AND CORRECTIONS
REFTYPE REFSOURCE REFPMID NOTE
CommentIn JAMA Psychiatry. 2018 Sep 1;75(9):878-880 29936531
GRANTS
GRANTID AGENCY COUNTRY
R01 AA013326 NIAAA NIH HHS United States
R37 AA007728 NIAAA NIH HHS United States
R01 AA010249 NIAAA NIH HHS United States
MC_PC_17228 Medical Research Council United Kingdom
R01 AA007535 NIAAA NIH HHS United States
MC_QA137853 Medical Research Council United Kingdom
R01 AA013321 NIAAA NIH HHS United States
GENERAL NOTE
KEYWORDS
MESH HEADINGS
DESCRIPTORNAME QUALIFIERNAME
Adult
Aged
Australia epidemiology
Female epidemiology
Gene-Environment Interaction epidemiology
Genetic Predisposition to Disease epidemiology
Genome-Wide Association Study epidemiology
Humans epidemiology
Male epidemiology
Mendelian Randomization Analysis epidemiology
Middle Aged epidemiology
Multifactorial Inheritance epidemiology
Netherlands epidemiology
Population Density epidemiology
Residence Characteristics epidemiology
Risk Assessment statistics & numerical data
Risk Factors statistics & numerical data
Schizophrenia genetics
Social Class genetics
United Kingdom epidemiology
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
OTHER ID's