Person:

Chen, Chia-Yen

Schizophrenia is a severe psychiatric disorder with a lifetime risk of about 1% world-wide. Most large schizophrenia genetic studies have studied people of primarily European ancestry, potentially missing important biological insights. Here we present a study of East Asian participants (22,778 schizophrenia cases and 35,362 controls), identifying 21 genome-wide significant schizophrenia associations in 19 genetic loci. Over the genome, the common genetic variants that confer risk for schizophrenia have highly similar effects in those of East Asian and European ancestry (rg=0.98), indicating for the first time that the genetic basis of schizophrenia and its biology are broadly shared across these world populations. A fixed-effect meta-analysis including individuals from East Asian and European ancestries revealed 208 genome-wide significant schizophrenia associations in 176 genetic loci (53 novel). Trans-ancestry fine-mapping more precisely isolated schizophrenia causal alleles in 70% of these loci. Despite consistent genetic effects across populations, polygenic risk models trained in one population have reduced performance in the other, highlighting the importance of including all major ancestral groups with sufficient sample size to ensure the findings have maximum relevance for all populations.

Heritability estimation provides important information about the relative contribution of genetic and environmental factors to phenotypic variation, and provides an upper bound for the utility of genetic risk prediction models. Recent technological and statistical advances have enabled the estimation of additive heritability attributable to common genetic variants (SNP heritability) across a broad phenotypic spectrum. Here, we present a computationally and memory efficient heritability estimation method that can handle large sample sizes, and report the SNP heritability for 551 complex traits derived from the interim data release (152,736 subjects) of the large-scale, population-based UK Biobank, comprising both quantitative phenotypes and disease codes. We demonstrate that common genetic variation contributes to a broad array of quantitative traits and human diseases in the UK population, and identify phenotypes whose heritability is moderated by age (e.g., a majority of physical measures including height and body mass index), sex (e.g., blood pressure related traits) and socioeconomic status (education). Our study represents the first comprehensive phenome-wide heritability analysis in the UK Biobank, and underscores the importance of considering population characteristics in interpreting heritability.

Importance Posttraumatic stress disorder (PTSD) is a prevalent, serious public health concern, particularly in the military. The identification of genetic risk factors for PTSD may provide important insights into the biological foundation of vulnerability and comorbidity.

Objective To discover genetic loci associated with the lifetime risk for PTSD in 2 cohorts from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

Design, Setting, and Participants Two coordinated genome-wide association studies of mental health in the US military contributed participants. The New Soldier Study (NSS) included 3167 unique participants with PTSD and 4607 trauma-exposed control individuals; the Pre/Post Deployment Study (PPDS) included 947 unique participants with PTSD and 4969 trauma-exposed controls. The NSS data were collected from February 1, 2011, to November 30, 2012; the PDDS data, from January 9 to April 30, 2012. The primary analysis compared lifetime DSM-IV PTSD cases with trauma-exposed controls without lifetime PTSD. Data were analyzed from March 18 to December 27, 2015.

Main Outcomes and Measures Association analyses for PTSD used logistic regression models within each of 3 ancestral groups (European, African, and Latino American) by study, followed by meta-analysis. Heritability and genetic correlation and pleiotropy with other psychiatric and immune-related disorders were estimated.

Results The NSS population was 80.7% male (6277 of 7774 participants; mean [SD] age, 20.9 [3.3] years); the PPDS population, 94.4% male (5583 of 5916 participants; mean [SD] age, 26.5 [6.0] years). A genome-wide significant locus was found in ANKRD55 on chromosome 5 (rs159572; odds ratio [OR], 1.62; 95% CI, 1.37-1.92; P = 2.34 × 10−8) and persisted after adjustment for cumulative trauma exposure (adjusted OR, 1.64; 95% CI, 1.39-1.95; P = 1.18 × 10−8) in the African American samples from the NSS. A genome-wide significant locus was also found in or near ZNF626 on chromosome 19 (rs11085374; OR, 0.77; 95% CI, 0.70-0.85; P = 4.59 × 10−8) in the European American samples from the NSS. Similar results were not found for either single-nucleotide polymorphism in the corresponding ancestry group from the PPDS sample, in other ancestral groups, or in transancestral meta-analyses. Single-nucleotide polymorphism–based heritability was nonsignificant, and no significant genetic correlations were observed between PTSD and 6 mental disorders or 9 immune-related disorders. Significant evidence of pleiotropy was observed between PTSD and rheumatoid arthritis and, to a lesser extent, psoriasis.

Conclusions and Relevance In the largest genome-wide association study of PTSD to date, involving a US military sample, limited evidence of association for specific loci was found. Further efforts are needed to replicate the genome-wide significant association with ANKRD55—associated in prior research with several autoimmune and inflammatory disorders—and to clarify the nature of the genetic overlap observed between PTSD and rheumatoid arthritis and psoriasis.

Event-related potential (ERP) components have been used to assess cognitive functions in patients with psychotic illness. Evidence suggests that among patients with psychosis there is a distinct heritable neurophysiologic phenotypic subtype captured by impairments across a range of ERP measures. In this study, we investigated the genetic basis of this “globally impaired” ERP cluster and its relationship to psychosis and cognitive abilities. We applied K-means clustering to six ERP measures to re-derive the globally impaired (n = 60) and the non-globally impaired ERP clusters (n = 323) in a sample of cases with schizophrenia (SCZ = 136) or bipolar disorder (BPD = 121) and healthy controls (n = 126). We used genome-wide association study (GWAS) results for SCZ, BPD, college completion, and childhood intelligence as the discovery datasets to derive polygenic risk scores (PRS) in our study sample and tested their associations with globally impaired ERP. We conducted mediation analyses to estimate the proportion of each PRS effect on severity of psychotic symptoms that is mediated through membership in the globally impaired ERP. Individuals with globally impaired ERP had significantly higher PANSS-positive scores (β = 3.95, P = 0.005). The SCZ-PRS was nominally associated with globally impaired ERP (unadjusted P = 0.01; R2 = 3.07%). We also found a significant positive association between the college-PRS and globally impaired ERP (FDR-corrected P = 0.004; R2 = 6.15%). The effect of college-PRS on PANSS positivity was almost entirely (97.1%) mediated through globally impaired ERP. These results suggest that the globally impaired ERP phenotype may represent some aspects of brain physiology on the path between genetic influences on educational attainment and psychotic symptoms.

Bipolar disorder (BD) is a heritable mood disorder characterized by episodes of mania and depression. Although genomewide association studies (GWAS) have successfully identified genetic loci contributing to BD risk, sample size has become a rate-limiting obstacle to genetic discovery. Electronic health records (EHRs) represent a vast but relatively untapped resource for high-throughput phenotyping. As part of the International Cohort Collection for Bipolar Disorder (ICCBD), we previously validated automated EHR-based phenotyping algorithms for BD against in-person diagnostic interviews (Castro et al. Am J Psychiatry 172:363–372, 2015). Here, we establish the genetic validity of these phenotypes by determining their genetic correlation with traditionally ascertained samples. Case and control algorithms were derived from structured and narrative text in the Partners Healthcare system comprising more than 4.6 million patients over 20 years. Genomewide genotype data for 3330 BD cases and 3952 controls of European ancestry were used to estimate SNP-based heritability (h2g) and genetic correlation (rg) between EHR-based phenotype definitions and traditionally ascertained BD cases in GWAS by the ICCBD and Psychiatric Genomics Consortium (PGC) using LD score regression. We evaluated BD cases identified using 4 EHR-based algorithms: an NLP-based algorithm (95-NLP) and three rule-based algorithms using codified EHR with decreasing levels of stringency—“coded-strict”, “coded-broad”, and “coded-broad based on a single clinical encounter” (coded-broad-SV). The analytic sample comprised 862 95-NLP, 1968 coded-strict, 2581 coded-broad, 408 coded-broad-SV BD cases, and 3 952 controls. The estimated h2g were 0.24 (p = 0.015), 0.09 (p = 0.064), 0.13 (p = 0.003), 0.00 (p = 0.591) for 95-NLP, coded-strict, coded-broad and coded-broad-SV BD, respectively. The h2g for all EHR-based cases combined except coded-broad-SV (excluded due to 0 h2g) was 0.12 (p = 0.004). These h2g were lower or similar to the h2g observed by the ICCBD + PGCBD (0.23, p = 3.17E−80, total N = 33,181). However, the rg between ICCBD + PGCBD and the EHR-based cases were high for 95-NLP (0.66, p = 3.69 × 10–5), coded-strict (1.00, p = 2.40 × 10−4), and coded-broad (0.74, p = 8.11 × 10–7). The rg between EHR-based BD definitions ranged from 0.90 to 0.98. These results provide the first genetic validation of automated EHR-based phenotyping for BD and suggest that this approach identifies cases that are highly genetically correlated with those ascertained through conventional methods. High throughput phenotyping using the large data resources available in EHRs represents a viable method for accelerating psychiatric genetic research.

Risk tolerance is an important variable in the behavioral and social sciences and one of the most studied phenotypes in social science genetics, but few genetic variants have so far been found to robustly associate with it or with risky behaviors.