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INTRODUCTION: To investigate the impact of a polygenic risk score for schizophrenia (PRS-SZ) and urbanicity on the risk of treatment-resistant schizophrenia (TRS) in people diagnosed with schizophrenia and to evaluate the association between PRS-SZ and TRS across levels of urbanicity.METHODS: Cohort study of people born after 1981 with a first registered diagnosis of schizophrenia between 1996 and 2012 using Danish population registry data. Through linkage to genome-wide data, we calculated PRS-SZ based on a Psychiatric Genomics Consortium meta-analysis. We assessed urbanicity at birth (capital, provincial and rural areas). TRS was defined using prescription and hospital data. Performing Cox regression analysis, we calculated hazard rate ratios (HRs) and 95% confidence intervals (CI).RESULTS: Among 4475 people with schizophrenia, we identified 593 (13.3%) with TRS during 17,558 person years of follow-up. The adjusted HR for TRS associated with one standard deviation (SD) increase in the PRS-SZ was 1.11 (95% CI: 1.00-1.24). The adjusted HRs for TRS across levels of urbanicity were 1.20 (95% CI: 0.98-1.47) for provincial areas and 1.19 (95% CI 0.96-1.47) for rural areas compared with the capital area. Within strata of urbanicity, the adjusted HR for TRS was 1.39 (95% CI: 1.14-1.70) in the capital area with 1 SD increase in the PRS-SZ, 0.99 (95% CI 0.84-1.17) in provincial areas, and 1.03 (95% CI: 0.86-1.25) in rural areas.CONCLUSION: The effect of genetic liability (i.e. PRS) on risk of TRS varied across urbanicity levels and was highest for people with schizophrenia born in the capital areas.

IntroductionTo investigate the impact of a polygenic risk score for schizophrenia (PRS-SZ) and urbanicity on the risk of treatment-resistant schizophrenia in people with a diagnosis of schizophrenia and to evaluate the association between PRS-SZ and TRS across areas of urbanicity.MethodsCohort study of people born after 1981 with a first time diagnosis of schizophrenia between 1996 and 2012 using Danish population registry data. Through linkage to genome-wide data, we calculated PRS-SZ based on a Psychiatric Genomics Consortium meta-analysis. We assessed urbanicity at birth (capital, provincial and rural areas). TRS was defined using prescription and hospital data. Performing Cox regression analysis, we calculated hazard rate ratios (HRs) and 95% confidence intervals (CI).ResultsAmong 4,475 people with schizophrenia, we identified 593 (13.3%) with TRS during 17 558 person years of follow-up. The adjusted HR for TRS associated with 1 standard deviation (SD) increase in the PRS-SZ was 1.11 (95% CI: 1.00–1.24). The adjusted HRs for urbanicity and TRS were 1.20 (95% CI: 0.98–1.47) for provincial areas and 1.19 (95% CI 0.96–1.47) for rural areas compared with the capital area. Across strata of urbanicity, the adjusted HR for TRS was 1.39 (95% CI: 1.14–1.70) in the capital area with 1 SD increase in the PRS-SZ, 0.99 (95% CI 0.84–1.17) in provincial areas, and 1.03 (95% CI: 0.86–1.25) in rural areas.ConclusionThe risk of TRS associated with genetic liability varied across urbanicity areas and was highest in people with schizophrenia who resided in the capital areas at birth.

The genome-wide association study of the Psychiatric Genomics Consortium identified over one hundred schizophrenia susceptibility loci. The number of non-coding variants discovered suggests that gene regulation could mediate the effect of these variants on disease. Expression quantitative trait loci (eQTLs) contribute to variation in levels of mRNA. Given the co-occurrence of schizophrenia and several traits not involving the central nervous system (CNS), we investigated the enrichment of schizophrenia associations among eQTLs for four non-CNS tissues: adipose tissue, epidermal tissue, lymphoblastoid cells and blood. Significant enrichment was seen in eQTLs of all tissues: adipose (β = 0.18, p = 8.8 × 10-06), epidermal (β = 0.12, p = 3.1 × 10-04), lymphoblastoid (β = 0.19, p = 6.2 × 10-08) and blood (β = 0.19, p = 6.4 × 10-06). For comparison, we looked for enrichment of association with traits of known relevance to one or more of these tissues (body mass index, height, rheumatoid arthritis, systolic blood pressure and type-II diabetes) and found that schizophrenia enrichment was of similar scale to that observed when studying diseases in the context of a more likely causal tissue. To further investigate tissue specificity, we looked for differential enrichment of eQTLs with relevant Roadmap affiliation (enhancers and promoters) and varying distance from the transcription start site. Neither factor significantly contributed to the enrichment, suggesting that this is equally distributed in tissue-specific and cross-tissue regulatory elements. Our analyses suggest that functional correlates of schizophrenia risk are prevalent in non-CNS tissues. This could be because of pleiotropy or the effectiveness of variants affecting expression in different contexts. This suggests the utility of large, single-tissue eQTL experiments to increase eQTL discovery power in the study of schizophrenia, in addition to smaller, multiple-tissue approaches. Our results conform to the notion that schizophrenia is a systemic disorder involving many tissues.