IMPORTANCE Psychotic experiences, such as hallucinations and delusions, are reported by approximately 5% to 10% of the general population, although only a small proportion develop psychotic disorders such as schizophrenia. Studying the genetic causes of psychotic experiences in the general population, and its association with the genetic causes of other disorders, may increase the understanding of their pathologic significance. OBJECTIVES To determine whether genetic liability to psychotic experiences is shared with schizophrenia and/or other neuropsychiatric disorders and traits and to identify genetic loci associated with psychotic experiences. DESIGN, SETTING AND PARTICIPANTS Analyses of genetic correlation, polygenic risk scores, and copy number variation were performed using data from participants in the UK Biobank from April 1, 2018, to March 20, 2019, to assess whether genetic liability to psychotic experiences is shared with schizophrenia and/or other neuropsychiatric disorders and traits. Genome-wide association studies of psychotic experience phenotypes were conducted to identify novel genetic loci. Participants in the final analyses after exclusions included 6123 individuals reporting any psychotic experience, 2143 individuals reporting distressing psychotic experiences, and 3337 individuals reporting multiple occurrences of psychotic experiences. A total of 121 843 individuals who did not report a psychotic experience formed the comparator group. Individuals with a psychotic disorder were excluded from all analyses. MAIN OUTCOMES AND MEASURES Genetic associations with psychotic experience phenotypes. RESULTS The study included a total of 127 966 participants (56.0% women and 44.0% men; mean [SD] age, 64.0 [7.6] years). Psychotic experiences were genetically correlated with major depressive disorder, schizophrenia, autism spectrum disorder, and attention-deficit/ hyperactivity disorder. Analyses of polygenic risk scores identified associations between psychotic experiences and genetic liability for major depressive disorder, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit/hyperactivity disorder. Individuals reporting psychotic experiences had an increased burden of copy number variations previously associated with schizophrenia (odds ratio [OR], 2.04; 95% CI, 1.39-2.98; P = 2.49 × 10 −4) and neurodevelopmental disorders more widely (OR, 1.75; 95% CI, 1.24-2.48; P = 1.41 × 10 −3). Genome-wide association studies identified 4 significantly associated loci, including a locus in Ankyrin-3 (ANK3 [GenBank NM_020987]) (OR, 1.16; 95% CI, 1.10-1.23; P = 3.06 × 10 −8) with any psychotic experience, and a locus in cannabinoid receptor 2 gene (CNR2 [GenBank NM_001841]) (OR, 0.66; 95% CI, 0.56-0.78; P = 3.78 × 10 −8) with distressing psychotic experiences. The genome-wide association study of any psychotic experience had a low single-nucleotide polymorphism-based heritability estimate (h 2 = 1.71%; 95% CI, 1.02%-2.40%). CONCLUSIONS AND RELEVANCE A large genetic association study of ...

Key Points Question Are rare copy number variants associated with depression in a large population sample? Findings In this case-control study of 407 074 individuals in the UK Biobank study, neurodevelopmental disorder copy number variants appear to be associated with the risk of depression in those without neurodevelopmental disorders. Physical health, educational attainment, social deprivation, smoking status, and alcohol consumption are variables that partially explain this association, and no evidence was found of an association between measures of copy number variant burden and depression. Meaning Neurodevelopmental copy number variants appear to be associated with increases in the risk of depression in those without neurodevelopmental disorders.

3 Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide such insight. We report the largest single cohort genome-wide association study of schizophrenia (11,260 cases and 24,542 controls) and through metaanalysis with existing data we identify 50 novel GWAS loci. Using gene-wide association statistics we implicate an additional set of 22 novel associations that map onto a single gene.We show for the first time that the common variant association signal is highly enriched among genes that are intolerant to loss of function mutations and that variants in these genes persist in the population despite the low fecundity associated with the disorder through the process of background selection. Associations point to novel areas of biology (e.g. metabotropic GABA-B signalling and acetyl cholinesterase), reinforce those implicated in earlier GWAS studies (e.g. calcium channel function), converge with earlier rare variants studies (e.g. NRXN1, GABAergic signalling), identify novel overlaps with autism (e.g. RBFOX1, FOXP1, FOXG1), and support early controversial candidate gene hypotheses (e.g.ERBB4 implicating neuregulin signalling). We also demonstrate the involvement of six independent central nervous system functional gene sets in schizophrenia pathophysiology.These findings provide novel insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation intolerant genes and suggest a mechanism by which common risk variants are maintained in the population. 4Schizophrenia is characterised by psychosis and negative symptoms such as social and emotional withdrawal. While onset of psychosis typically does not occur until late adolescence or early adult life, there is strong evidence from clinical and epidemiological studies that schizophrenia reflects a disturbance of neurodevelopment 1 . It confers substantial mortality and morbidity, with a mean reduction in life expectancy of 15-30 years 2,3 . Although recovery is possible, most patients have poor social and functional outcomes 4 . No substantial improvements in outcomes have emerged since the advent of antipsychotic medication in the mid-20th century, a fact that has been attributed to a lack of knowledge of pathophysiology 1 .Schizophrenia is both highly heritable and polygenic, with risk ascribed to variants spanning the full spectrum of population frequencies 5-7 . The relative contributions of alleles of various frequencies is not fully resolved, but recent studies estimate that common alleles, captured by genome-wide association study (GWAS) arrays, capture between a third and a half of the genetic variance in liability 8 . There has been a long-standing debate, from an evolutionary standpoint, as to how common risk alleles might be maintained in the population, particularly given ...

BackgroundCopy number variants (CNVs) have been shown to increase risk for physical anomalies, developmental, psychiatric and medical disorders. Some of them have been associated with changes in weight, height, and other physical traits. As most studies have been performed on children and young people, these effects of CNVs in middle-aged and older people are not well established. The UK Biobank recruited half a million adults who provided a variety of physical measurements. We called all CNVs from the Affymetrix microarrays and selected a set of 54 CNVs implicated as pathogenic (including their reciprocal deletions/duplications) and that were found in five or more persons. Linear regression analysis was used to establish their association with 16 physical traits relevant to human health.Results396,725 participants of white British or Irish descent (excluding first-degree relatives) passed our quality control filters. Out of the 864 CNV/trait associations, 214 were significant at a false discovery rate of 0.1, most of them novel. Many of these traits increase risk for adverse health outcomes: e.g. increases in weight, waist-to-hip ratio, pulse rate and body fat composition. Deletions at 16p11.2, 16p12.1, NRXN1 and duplications at 16p13.11 and 22q11.2 produced the highest numbers of significant associations. Five CNVs produced average changes of over one standard deviation for the 16 traits, compared to controls: deletions at 16p11.2 and 22q11.2, and duplications at 3q29, the Williams-Beuren and Potocki-Lupski regions. CNVs at 1q21.1, 2q13, 16p11.2 and 16p11.2 distal, 16p12.1, 17p12 and 17q12 demonstrated one or more mirror image effects of deletions versus duplications.ConclusionsCarriers of many CNVs should be monitored for physical traits that increase morbidity and mortality. Genes within these CNVs can give insights into biological processes and therapeutic interventions.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-5292-7) contains supplementary material, which is available to authorized users.

The primary aim of precision medicine is to tailor healthcare more closely to the needs of individual patients. This requires progress in two areas: the development of more precise treatments and the ability to identify patients or groups of patients in the clinic for whom such treatments are likely to be the most effective. There is widespread optimism that advances in genomics will facilitate both of these endeavors. It can be argued that of all medical specialties psychiatry has most to gain in these respects, given its current reliance on syndromic diagnoses, the minimal foundation of existing mechanistic knowledge, and the substantial heritability of psychiatric phenotypes. Here, we review recent advances in psychiatric genomics and assess the likely impact of these findings on attempts to develop precision psychiatry. Emerging findings indicate a high degree of polygenicity and that genetic risk maps poorly onto the diagnostic categories used in the clinic. The highly polygenic and pleiotropic nature of psychiatric genetics will impact attempts to use genomic data for prediction and risk stratification, and also poses substantial challenges for conventional approaches to gaining biological insights from genetic findings. While there are many challenges to overcome, genomics is building an empirical platform upon which psychiatry can now progress towards better understanding of disease mechanisms, better treatments, and better ways of targeting treatments to the patients most likely to benefit, thus paving the way for precision psychiatry.