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: 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.

Figure 1.. Percentage of Variance

Additive genetic, shared environmental, and unique environmental factors in population density, remoteness, and socioeconomic status (SES) in the Queensland Institute of Medical Research cohort (discovery). Results for population density in the Netherlands Twin Register (NTR) cohort are presented for replication. P values are not applicable for unique environmental factors.

Figure 2.. Percentage of Variance of the Population Density of the Place of Residence Explained by the Genetic Risk for Schizophrenia, Both Without and With Socioeconomic Status (SES) as a Covariate

A-D, Genetic risk for schizophrenia showed positive effects for population density in all significant associations. Results in bold highlight significant results after correction for multiple testing. In the discovery Queensland Institute of Medical Research sample, we accounted for the number of tests performed. In the Netherlands Twin Register, UK Biobank, and QSkin Sun and Health Study, we used a significance threshold of .05 as we aimed to replicate the results found with the polygenic risk scores (PRS) calculated over all independent genomic regions. However, when multiple PRS were available, we present all of the results for completeness. Python-based software (LDpred) was used to conduct the analyses in the NTR cohort.

Figure 3.. Mendelian Randomization Summary Results

Hypothesis that schizophrenia influences the population density of the place or residence tested in the Queensland Institute of Medical Research (A), UK Biobank (B), Netherlands Twin Register (C), and QSkin Sun and Health Study (D) cohorts. Several methods yield exactly the same effect sizes (Table 2), and as a consequence, some lines may overlap. GSMR indicates generalized summary data-based mendelian randomization.