No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study

It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (β = 16.1, CI(β) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (β = 4.86,CI(β) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest

Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events42Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases

Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood

J. Lönnqvist on työryhmän Psychiat Genomics Consortium jäsen.Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on similar to 150,000 individuals give a higher accuracy than LDSC estimates based on similar to 400,000 individuals (from combinedmeta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.Peer reviewe

University students' attitudes towards mental patients and psychiatric treatment

Background: Public attitudes towards mental patients and psychiatric treatment are mostly unfavorable. Mental patients tend to conceal their illness or selectively disclose their treatment histories to someone they trust. Aims: To examine the university students' attitudes towards different information regarding a person labeled as mentally ill. Methods: We designed seven descriptions of a mentally ill person of varying past and current treatment histories and randomly assigned 308 university undergraduates to read one of the descriptions. Subjects rated their willingness to interact with the hypothetical case using a 19-item social distance scale. Results: Greater social distance was associated with non-medical field of study, no previous contact with the mentally ill and female gender. Subjects without previous contact with mentally ill individuals kept greater distance from a discharged mental patient receiving psychiatric care than a mental patient who did not require medications nor psychiatric follow-up. In contrast, respondents who had previous contact with the mentally ill were more willing to interact with a discharged mental patient receiving psychiatric care comparing with a person labeled as mentally ill alone and a mental patient who had never been admitted to hospital. Conclusions: Implications of our findings in clinical management and designing stigma-reducing programme are discussed.link_to_subscribed_fulltex

A translational research approach to poor treatment response in patients with schizophrenia: clozapine–antipsychotic polypharmacy

Poor treatment response in patients with schizophrenia is an important clinical problem, and one possible strategy is concurrent treatment with more than one antipsychotic (polypharmacy). We analyzed the evidence base for this strategy using a translational research model focused on clozapine–antipsychotic polypharmacy (CAP). We considered 3 aspects of the existing knowledge base and translational research: the link between basic science and clinical studies of efficacy, the evidence for effectiveness in clinical research and the implications of research for the health care delivery system. Although a rationale for CAP can be developed from receptor pharmacology, there is little available preclinical research testing these concepts in animal models. Randomized clinical trials of CAP show minimal or no benefit for overall severity of symptoms. Most studies at the level of health services are limited to estimates of CAP prevalence and some suggestion of increased costs. Increasing use of antipsychotic polypharmacy in general may be a factor contributing to the under-utilization of clozapine and long delays in initiating clozapine monotherapy. Translational research models can be applied to clinical questions such as the value of CAP. Better linkage between the components of translational research may improve the appropriate use of medications such as clozapine in psychiatric practice

Real-world implementation of early intervention in psychosis: resources, funding models and evidence-based practice

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Whole soil acidification and base cation reduction across subtropical China

International audienc