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In this paper we explore the phenomenon of pleiotropy in neurodegenerative diseases, focusing on Alzheimer's disease (AD). We summarize the various techniques developed to investigate pleiotropy among traits, elaborating in the polygenic risk scores (PRS) analysis. PRS was designed to assess a cumulative effect of a large number of SNPs for association with a disease and, later for disease risk prediction. Since genetic predictions rely on heritability, we discuss SNP-based heritability from genome-wide association studies and its contribution to the prediction accuracy of PRS. We review work examining pleiotropy in neurodegenerative diseases and related phenotypes and biomarkers. We conclude that the exploitation of pleiotropy may aid in the identification of novel genes and provide further insights in the disease mechanisms, and along with PRS analysis, may be advantageous for precision medicine., Competing Interests: Declaration of Competing Interest The authors EB, VEP have collaborated with Cytox Ltd. through their InnovateUK grant funding., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Importance: Insomnia, hypersomnia, and an evening chronotype are common in individuals with bipolar disorder (BD), but whether this reflects shared genetic liability is unclear. Stratifying by BD subtypes could elucidate this association and inform sleep and BD research., Objective: To assess whether polygenic risk scores (PRSs) for sleep traits are associated with BD subtypes I and II., Design, Setting, and Participants: This case-control study was conducted in the United Kingdom and Sweden with participants with BD and control participants. Multinomial regression was used to assess whether PRSs for insomnia, daytime sleepiness, sleep duration, and chronotype are associated with BD subtypes compared with control participants. Affected individuals were recruited from the Bipolar Disorder Research Network. Control participants were recruited from the 1958 British Birth Cohort and the UK Blood Service. Analyses were repeated in an independent Swedish sample from August 2018 to July 2019. All participants were of European ancestry., Exposures: Standardized PRSs derived using alleles from genome-wide association studies of insomnia, sleep duration, daytime sleepiness, and chronotype. These were adjusted for the first 10 population principal components, genotyping platforms, and sex., Main Outcomes and Measures: Association of PRSs with BD subtypes, determined by semistructured psychiatric interview and case notes., Results: The main analysis included 4672 participants with BD (3132 female participants [67.0%]; 3404 with BD-I [72.9%]) and 5714 control participants (2812 female participants [49.2%]). Insomnia PRS was associated with increased risk of BD-II (relative risk [RR], 1.14 [95% CI, 1.07-1.21]; P = 8.26 × 10-5) but not BD-I (RR, 0.98 [95% CI, 0.94-1.03]; P = .409) relative to control participants. Sleep-duration PRS was associated with BD-I (RR, 1.10 [95% CI, 1.06-1.15]; P = 1.13 × 10-5) but not BD-II (RR, 0.99 [95% CI, 0.93-1.06]; P = .818). Associations between (1) insomnia PRS and BD-II and (2) sleep-duration PRS and BD-I were replicated in the Swedish sample of 4366 individuals with BD (2697 female participants [61.8%]; 2627 with BD-I [60.2%]) and 6091 control participants (3767 female participants [61.8%]). Chronotype and daytime-sleepiness PRS were not associated with BD subtypes., Conclusions and Relevance: Per this analysis, BD subtypes differ in genetic liability to insomnia and hypersomnia, providing further evidence that the distinction between BD-I and BD-II has genetic validity. This distinction will be crucial in selecting participants for future research on the role of sleep disturbance in BD.

Background: Cognitive impairment is a clinically important feature of schizophrenia. Polygenic risk score (PRS) methods have demonstrated genetic overlap between schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), educational attainment (EA), and IQ, but very few studies have examined associations between these PRS and cognitive phenotypes within schizophrenia cases., Methods: We combined genetic and cognitive data in 3034 schizophrenia cases from 11 samples using the general intelligence factor g as the primary measure of cognition. We used linear regression to examine the association between cognition and PRS for EA, IQ, schizophrenia, BD, and MDD. The results were then meta-analyzed across all samples. A genome-wide association studies (GWAS) of cognition was conducted in schizophrenia cases., Results: PRS for both population IQ (P = 4.39 × 10-28) and EA (P = 1.27 × 10-26) were positively correlated with cognition in those with schizophrenia. In contrast, there was no association between cognition in schizophrenia cases and PRS for schizophrenia (P = .39), BD (P = .51), or MDD (P = .49). No individual variant approached genome-wide significance in the GWAS., Conclusions: Cognition in schizophrenia cases is more strongly associated with PRS that index cognitive traits in the general population than PRS for neuropsychiatric disorders. This suggests the mechanisms of cognitive variation within schizophrenia are at least partly independent from those that predispose to schizophrenia diagnosis itself. Our findings indicate that this cognitive variation arises at least in part due to genetic factors shared with cognitive performance in populations and is not solely due to illness or treatment-related factors, although our findings are consistent with important contributions from these factors., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)

Schizophrenia is a highly polygenic disorder with important contributions from both common and rare risk alleles. We analyzed exome sequencing data for de novo variants (DNVs) in a new sample of 613 schizophrenia trios and combined this with published data to give a total of 3,444 trios. In this new data, loss-of-function (LoF) DNVs were significantly enriched among 3,471 LoF-intolerant genes, which supports previous findings. In the full dataset, genes associated with neurodevelopmental disorders (n = 159) were significantly enriched for LoF DNVs. Within these neurodevelopmental disorder genes, SLC6A1, which encodes a γ-aminobutyric acid transporter, was associated with missense-damaging DNVs. In 1,122 trios for which genome-wide common variant data were available, schizophrenia and bipolar disorder polygenic risk were significantly overtransmitted to probands. Probands carrying LoF or deletion DNVs in LoF-intolerant or neurodevelopmental disorder genes had significantly less overtransmission of schizophrenia polygenic risk than did non-carriers, which provides a second robust line of evidence that these DNVs increase liability to schizophrenia.

Dementia with Lewy bodies (DLB) is a clinically heterogeneous disorder with a substantial burden on healthcare. Despite this, the genetic basis of the disorder is not well defined and its boundaries with other neurodegenerative diseases are unclear. Here, we performed whole exome sequencing of a cohort of 1118 Caucasian DLB patients, and focused on genes causative of monogenic neurodegenerative diseases. We analyzed variants in 60 genes implicated in DLB, Alzheimer's disease, Parkinson's disease, frontotemporal dementia, and atypical parkinsonian or dementia disorders, in order to determine their frequency in DLB. We focused on variants that have previously been reported as pathogenic, and also describe variants reported as pathogenic which remain of unknown clinical significance, as well as variants associated with strong risk. Rare missense variants of unknown significance were found in APP, CHCHD2, DCTN1, GRN, MAPT, NOTCH3, SQSTM1, TBK1 and TIA1. Additionally, we identified a pathogenic GRN p.Arg493* mutation, potentially adding to the diversity of phenotypes associated with this mutation. The rarity of previously reported pathogenic mutations in this cohort suggests that the genetic overlap of other neurodegenerative diseases with DLB is not substantial. Since it is now clear that genetics plays a role in DLB, these data suggest that other genetic loci play a role in this disease.

Background: Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD., Objective: This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration., Methods: We searched the literature from July 2008-July 2018 following PRISMA guidelines., Results: 57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes., Conclusion: PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.

Schizophrenia is a complex highly heritable disorder. Genome-wide association studies (GWAS) have identified multiple loci that influence the risk of developing schizophrenia, although the causal variants driving these associations and their impacts on specific genes are largely unknown. We identify a significant correlation between schizophrenia risk and expression at 89 genes in the dorsolateral prefrontal cortex (P ≤ 9.43 × 10-6), including 20 novel genes. Genes whose expression correlate with schizophrenia were enriched for those involved in abnormal CNS synaptic transmission (PFDR = 0.02) and antigen processing and presentation of peptide antigen via MHC class I (PFDR = 0.02). Within the CNS synaptic transmission set, we identify individual significant candidate genes to which we assign direction of expression changes in schizophrenia. The findings provide strong candidates for experimentally probing the molecular basis of synaptic pathology in schizophrenia., (© The Author(s) 2019. Published by Oxford University Press.)

Purpose: Genome-wide association studies have identified common single nucleotide polymorphisms (SNPs) at 83 loci associated with colorectal cancer (CRC) risk in European populations. Because germline variation can also influence patient outcome, we studied the relationship between these SNPs and CRC survivorship., Experimental Design: For the 83 risk loci, 10 lead SNPs were directly genotyped, 72 were imputed and 1 was not genotyped nor imputed, in 1948 unrelated patients with advanced CRC from the clinical trials COIN and COIN-B (oxaliplatin and fluoropyrimidine chemotherapy ± cetuximab). A Cox survival model was used for each variant, and variants classified by pathway, adjusting for known prognostic factors. We imposed a Bonferroni threshold of P = 6.6 × 10 -4 for multiple testing. We carried out meta-analyses of published risk SNPs associated with survival., Results: Univariate analysis identified six SNPs associated with overall survival (OS) (P < 0.05); however, only rs9939049 in CDH1 remained significant beyond the Bonferroni threshold (Hazard Ratio [HR] 1.44, 95% Confidence Intervals [CI]: 1.21-1.71, P = 5.0 × 10 -5 ). Fine mapping showed that rs12597188 was the most significant SNP at this locus and remained significant after adjustment for known prognostic factors beyond multiple testing thresholds (HR 1.23, 95% CI: 1.13-1.34, P = 1.9 × 10 -6 ). rs12597188 was also associated with poor response to therapy (OR 0.61, 95% CI: 0.42-0.87, P = 6.6 × 10 -3 ). No combinations of SNPs within pathways were more significantly associated with survival compared with single variants alone, and no other risk SNPs were associated with survival in meta-analyses., Conclusions: The CRC susceptibility SNP rs9939049 in CDH1 influences patient survival and warrants further evaluation as a prognostic biomarker., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

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&#95;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&#95;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 (h2 = 1.71%; 95% CI, 1.02%-2.40%)., Conclusions and Relevance: A large genetic association study of psychotic experiences from the population-based UK Biobank sample found support for a shared genetic liability between psychotic experiences and schizophrenia, major depressive disorder, bipolar disorder, and neurodevelopmental disorders.

Introduction: Identifying phenotypic manifestations of genetic risk for bipolar disorder (BD) in childhood could increase our understanding of aetiological mechanisms., Aims: To examine whether BD genetic risk is associated with childhood (age 8 years) cognitive function., Methods: Using data from the Avon Longitudinal Study of Parents and Children, we examined associations between polygenic risk scores for BD (BD-PRS) derived using Psychiatric Genomics Consortium summary data at p-thresholds (P T ) ≤0.01 (primary) and ≤0.5 (secondary) and several cognitive domains (sample sizes 5,613 to 5,936). We also examined whether associations were due to SNPs that have shared risk effects on schizophrenia (SZ)., Results: At P T ≤0.01, the BD-PRS was associated with poorer executive functioning (ß= -0.03, 95%CI -0.06, -0.01; p = 0.013), and, more weakly with poorer processing speed (ß = -0.02, 95%CI -0.05, 0.02; p = 0.075). Evidence of association with both poorer processing speed (p = 0.016) and performance IQ (p = 0.018) was stronger at P T ≤0.5. Associations with performance IQ and processing speed were primarily driven by genetic effects that are shared with SZ risk, but there was some evidence of bipolar-specific genetic effects on childhood executive functioning., Limitations: The BD-PRS still explains only a small proportion of the variance for BD which will have reduced power to detect associations., Conclusions: Genetic risk for BD manifests as impaired cognition in childhood, and this is driven by risk SNPs that are also shared with SZ genetic risk. Further elucidation of which cognitive domains are most affected by genetic risk for BD could help understanding of aetiology and improve prediction of BD., (Crown Copyright © 2019. Published by Elsevier B.V. All rights reserved.)

The failure of recent clinical trials in Alzheimer's disease has highlighted the need for the development of a more complete understanding of the pathogenesis of the disorder and also a belief that therapies may only work if given very early in the disease process before overt symptoms occur. The rare, early onset forms of the disease are all caused by mutations which make amyloid deposition a more likely event. Here we discuss the recent data showing that, in contrast, much of the risk of late onset disease is encoded by loci involved in lipid metabolism and/or encoded by microglia. We discuss these finding and suggest that amyloid induced membrane damage may be a key factor in disease and also review the evidence that genome wide genetic analysis can substantially help in the prediction of those individuals at high risk of disease in the general population., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: There is strong evidence that people born in winter and in spring have a small increased risk of schizophrenia. As this 'season of birth' effect underpins some of the most influential hypotheses concerning potentially modifiable risk exposures, it is important to exclude other possible explanations for the phenomenon., Methods: Here we sought to determine whether the season of birth effect reflects gene-environment confounding rather than a pathogenic process indexing environmental exposure. We directly measured, in 136 538 participants from the UK Biobank (UKBB), the burdens of common schizophrenia risk alleles and of copy number variants known to increase the risk for the disorder, and tested whether these were correlated with a season of birth., Results: Neither genetic measure was associated with season or month of birth within the UKBB sample., Conclusions: As our study was highly powered to detect small effects, we conclude that the season of birth effect in schizophrenia reflects a true pathogenic effect of environmental exposure.

Objective: Alzheimer disease (AD) is the most common form of dementia and is responsible for a huge and growing health care burden in the developed and developing world. The polygenic risk score (PRS) approach has shown 75 to 84% prediction accuracy of identifying individuals with AD risk., Methods: In this study, we tested the prediction accuracy of AD, mild cognitive impairment (MCI), and amyloid deposition risks with PRS, including and excluding APOE genotypes in a large publicly available dataset with extensive phenotypic data, the Alzheimer's Disease Neuroimaging Initiative cohort. Among MCI individuals with amyloid-positive status, we examined PRS prediction accuracy in those who converted to AD. In addition, we divided polygenic risk score by biological pathways and tested them independently for distinguishing between AD, MCI, and amyloid deposition., Results: We found that AD and MCI are predicted by both APOE genotype and PRS (area under the curve [AUC] = 0.82% and 68%, respectively). Amyloid deposition is predicted by APOE only (AUC = 79%). Further progression to AD of individuals with MCI and amyloid-positive status is predicted by PRS over and above APOE (AUC = 67%). In pathway-specific PRS analyses, the protein-lipid complex has the strongest association with AD and amyloid deposition even when genes in the APOE region were removed (p = 0.0055 and p = 0.0079, respectively)., Interpretation: The results showed different pattern of APOE contribution in PRS risk predictions of AD/MCI and amyloid deposition. Our study suggests that APOE mostly contributes to amyloid accumulation and the PRS affects risk of further conversion to AD. ANN NEUROL 2019;86:427-435., (© 2019 The Authors. Annals of Neurology published by Wiley Periodicals, Inc. on behalf of American Neurological Association.)

Objective: Schizophrenia is associated with a marked reduction in reproductive success, yet alleles that are common contribute substantially to the liability of the disorder. Among several possible explanations for this, it has been postulated that individuals who carry risk alleles but are unaffected are at some reproductive advantage, offsetting the effects of negative selection among those who are affected. The authors sought to test this hypothesis, isolating the effects of risk alleles on fecundity from the effects that are contingent on expressing schizophrenia., Methods: The burden of schizophrenia risk alleles, as indexed by a polygenic risk score (PRS), carried by 139,679 participants in the UK Biobank study who did not have schizophrenia was compared with the number of offspring of these individuals., Results: Higher schizophrenia liability in study subjects without manifest disorder was weakly but significantly associated with having more children (B=0.006, 95% CI=0.002, 0.010). The relationship was dependent on sex, with a positive correlation between number of children and liability among females (B=0.011, 95% CI=0.006, 0.016), whereas among males, higher liability was associated with being childless (odds ratio=0.96, 95% CI=0.94, 0.98). The negative effect on number of children associated with schizophrenia itself was twofold to 15-fold greater than the positive effect associated with PRS in unaffected individuals., Conclusions: These findings suggest that a complex relationship between liability and fecundity is consistent with sexual selection. Although the overall pattern of a weak positive correlation with liability may contribute to the persistence of schizophrenia risk alleles, these results indicate that the negative selection acting on individuals affected by schizophrenia in the general population is larger than any advantage conferred by genetic loading in unaffected individuals.

Background: Constitutional loss of function (LOF) single nucleotide polymorphisms (SNPs) in pattern recognition receptors FPR1, TLR3, and TLR4 have previously been reported to predict oxaliplatin benefit in colorectal cancer. Confirmation of this association could substantially improve patient stratification., Methods: We performed a retrospective biomarker analysis of the Short Course in Oncology Therapy (SCOT) and COIN/COIN-B trials. Participant status for LOF variants in FPR1 (rs867228), TLR3 (rs3775291), and TLR4 (rs4986790/rs4986791) was determined by genotyping array or genotype imputation. Associations between LOF variants and disease-free survival (DFS) and overall survival (OS) were analyzed by Cox regression, adjusted for confounders, using additive, dominant, and recessive genetic models. All statistical tests were two-sided., Results: Our validation study populations included 2929 and 1948 patients in the SCOT and COIN/COIN-B cohorts, respectively, of whom 2728 and 1672 patients had functional status of all three SNPs determined. We found no evidence of an association between any SNP and DFS in the SCOT cohort, or with OS in either cohort, irrespective of the type of model used. This included models for which an association was previously reported for rs867228 (recessive model, multivariable-adjusted hazard ratio [HR] for DFS in SCOT = 1.19, 95% confidence interval [CI] = 0.99 to 1.45, P = .07; HR for OS in COIN/COIN-B = 0.92, 95% CI = 0.63 to 1.34, P = .66), and rs4986790 (dominant model, multivariable-adjusted HR for DFS in SCOT = 0.86, 95% CI = 0.65 to 1.13, P = .27; HR for OS in COIN/COIN-B = 1.08, 95% CI = 0.90 to 1.31, P = .40)., Conclusion: In this prespecified analysis of two large clinical trials, we found no evidence that constitutional LOF SNPs in FPR1, TLR3, or TLR4 are associated with differential benefit from oxaliplatin. Our results suggest these SNPs are unlikely to be clinically useful biomarkers., (© The Author(s) 2019. Published by Oxford University Press.)

Late onset Alzheimer's disease is the most common form of dementia for which about 30 susceptibility loci have been reported. The aim of the current study is to identify novel genes associated with Alzheimer's disease using the largest up-to-date reference single nucleotide polymorphism (SNP) panel, the most accurate imputation software and a novel gene-based analysis approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 million genotypes from 17,008 Alzheimer's cases and 37,154 controls. In addition to earlier reported genes, we detected three novel gene-wide significant loci PPARGC1A (p = 2.2 × 10-6), RORA (p = 7.4 × 10-7) and ZNF423 (p = 2.1 × 10-6). PPARGC1A and RORA are involved in circadian rhythm; circadian disturbances are one of the earliest symptoms of Alzheimer's disease. PPARGC1A is additionally linked to energy metabolism and the generation of amyloid beta plaques. RORA is involved in a variety of functions apart from circadian rhythm, such as cholesterol metabolism and inflammation. The ZNF423 gene resides in an Alzheimer's disease-specific protein network and is likely involved with centrosomes and DNA damage repair., Competing Interests: The authors have declared that no competing interests exist.

Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinson's disease (PD) or Alzheimer's disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: Rare copy number variants (CNVs) are associated with risk of neurodevelopmental disorders characterised by varying degrees of cognitive impairment, including schizophrenia, autism spectrum disorder and intellectual disability. However, the effects of many individual CNVs in carriers without neurodevelopmental disorders are not yet fully understood, and little is known about the effects of reciprocal copy number changes of known pathogenic loci.AimsWe aimed to analyse the effect of CNV carrier status on cognitive performance and measures of occupational and social outcomes in unaffected individuals from the UK Biobank., Method: We called CNVs in the full UK Biobank sample and analysed data from 420 247 individuals who passed CNV quality control, reported White British or Irish ancestry and were not diagnosed with neurodevelopmental disorders. We analysed 33 pathogenic CNVs, including their reciprocal deletions/duplications, for association with seven cognitive tests and four general measures of functioning: academic qualifications, occupation, household income and Townsend Deprivation Index., Results: Most CNVs (24 out of 33) were associated with reduced performance on at least one cognitive test or measure of functioning. The changes on the cognitive tests were modest (average reduction of 0.13 s.d.) but varied markedly between CNVs. All 12 schizophrenia-associated CNVs were associated with significant impairments on measures of functioning., Conclusions: CNVs implicated in neurodevelopmental disorders, including schizophrenia, are associated with cognitive deficits, even among unaffected individuals. These deficits may be subtle but CNV carriers have significant disadvantages in educational attainment and ability to earn income in adult life.Declaration of interestNone.

Genetic case-control association studies are often based on clinically ascertained cases and population or convenience controls. It is known that some of the controls will contain cases, as they are usually not screened for the disease of interest. However, even clinically assessed cases and controls can be misassigned. For Alzheimer's disease (AD), it is important to know the accuracy of the clinical assignment. The predictive accuracy of AD risk by polygenic risk score analysis has been reported in both clinical and pathologically confirmed cohorts. The genetic risk prediction can provide additional insights to inform classification of subjects to case and control sets at a preclinical stage. In this study, we take a mathematical approach and aim to assess the importance of a genetic component for the assignment of subjects to AD-positive and -negative groups, and provide an estimate of misassignment rates (MARs) in AD case/control cohorts accounting for genetic prediction modeling results. The derived formulae provide a tool to estimate MARs in any sample. This approach can also provide an estimate of the maximal and minimal MARs and therefore could be useful for statistical power estimation at the study design stage. We illustrate this approach in 2 independent clinical cohorts and estimate misdiagnosis rate up to 36% in controls unscreened for the APOE genotype, and up to 29% when E3 homozygous subjects are used as controls in clinical studies., (Copyright © 2018. Published by Elsevier Inc.)

Background: Sequencing studies have pointed to the involvement in schizophrenia of rare coding variants in neuronally expressed genes, including activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-D-aspartate receptor (NMDAR) complexes; however, larger samples are required to reveal novel genes and specific biological mechanisms., Methods: We sequenced 187 genes, selected for prior evidence of association with schizophrenia, in a new dataset of 5207 cases and 4991 controls. Included among these genes were members of ARC and NMDAR postsynaptic protein complexes, as well as voltage-gated sodium and calcium channels. We performed a rare variant meta-analysis with published sequencing data for a total of 11,319 cases, 15,854 controls, and 1136 trios., Results: While no individual gene was significantly associated with schizophrenia after genome-wide correction for multiple testing, we strengthen the evidence that rare exonic variants in the ARC (p = 4.0 × 10 -4 ) and NMDAR (p = 1.7 × 10 -5 ) synaptic complexes are risk factors for schizophrenia. In addition, we found that loss-of-function variants and missense variants at paralog-conserved sites were enriched in voltage-gated sodium channels, particularly the alpha subunits (p = 8.6 × 10 -4 )., Conclusions: In one of the largest sequencing studies of schizophrenia to date, we provide novel evidence that multiple voltage-gated sodium channels are involved in schizophrenia pathogenesis and confirm the involvement of ARC and NMDAR postsynaptic complexes., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

The role of genetic variability in dementia with Lewy bodies (DLB) is now indisputable; however, data regarding copy number variation (CNV) in this disease has been lacking. Here, we used whole-genome genotyping of 1454 DLB cases and 1525 controls to assess copy number variability. We used 2 algorithms to confidently detect CNVs, performed a case-control association analysis, screened for candidate CNVs previously associated with DLB-related diseases, and performed a candidate gene approach to fully explore the data. We identified 5 CNV regions with a significant genome-wide association to DLB; 2 of these were only present in cases and absent from publicly available databases: one of the regions overlapped LAPTM4B, a known lysosomal protein, whereas the other overlapped the NME1 locus and SPAG9. We also identified DLB cases presenting rare CNVs in genes previously associated with DLB or related neurodegenerative diseases, such as SNCA, APP, and MAPT. To our knowledge, this is the first study reporting genome-wide CNVs in a large DLB cohort. These results provide preliminary evidence for the contribution of CNVs in DLB risk., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: Studying the phenotypic manifestations of increased genetic liability for Bipolar Disorder (BD) can increase understanding of this disorder., Aims: We assessed whether genetic risk for BD was associated with childhood psychopathology and features of hypomania in young adulthood within a large population-based birth cohort., Methods: We used data from the second Psychiatric Genetics Consortium Genome Wide Association Study (GWAS) for Bipolar Disorder to construct a polygenic risk score (PRS) for each individual in the Avon Longitudinal Study of Parents and Children (ALSPAC). Linear and logistic regression models were used to assess associations between the BD-PRS and emotional/behavioural difficulties, attention deficit hyperactivity disorder (ADHD) and borderline personality disorder (BPD) traits in childhood, as well as hypomania in early adulthood (sample sizes from 2654 to 6111)., Results: The BD-PRS was not associated with total hypomania score, but was weakly associated with a binary measure of hypomania (OR = 1.13, 95%CI 0.98,1.32; p = 0.097), and particularly at higher hypomania symptom thresholds (strongest evidence OR = 1.33, 95%CI 1.07, 1.65; p = 0.01). The BD-PRS was also associated with ADHD (OR = 1.31, 95%CI 1.10, 1.57; p = 0.018), but not with other childhood psychopathology., Limitations: The PRS only captures common genetic variation and currently explains a relatively small proportion of the variance for BD., Conclusions: The BD-PRS was associated with ADHD in childhood, and weakly with adult hypomania, but not with other psychopathology examined. Our findings suggest that genetic risk for BD does not appear to manifest in childhood to the same extent as schizophrenia genetic risk has been reported to do., (Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.)

Background: Genomic CNVs increase the risk for early-onset neurodevelopmental disorders, but their impact on medical outcomes in later life is still poorly understood. The UK Biobank allows us to study the medical consequences of CNVs in middle and old age in half a million well-phenotyped adults., Methods: We analysed all Biobank participants for the presence of 54 CNVs associated with genomic disorders or clinical phenotypes, including their reciprocal deletions or duplications. After array quality control and exclusion of first-degree relatives, we compared 381 452 participants of white British or Irish origin who carried no CNVs with carriers of each of the 54 CNVs (ranging from 5 to 2843 persons). We used logistic regression analysis to estimate the risk of developing 58 common medical phenotypes (3132 comparisons)., Results and Conclusions: Many of the CNVs have profound effects on medical health and mortality, even in people who have largely escaped early neurodevelopmental outcomes. Forty-six CNV-phenotype associations were significant at a false discovery rate threshold of 0.1, all in the direction of increased risk. Known medical consequences of CNVs were confirmed, but most identified associations are novel. Deletions at 16p11.2 and 16p12.1 had the largest numbers of significantly associated phenotypes (seven each). Diabetes, hypertension, obesity and renal failure were affected by the highest numbers of CNVs. Our work should inform clinicians in planning and managing the medical care of CNV carriers., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: Genome-wide association studies (GWAS) have identified over 30 susceptibility loci associated with Alzheimer's disease (AD). Using AD GWAS data from the International Genomics of Alzheimer's Project (IGAP), Polygenic Risk Score (PRS) was successfully applied to predict life time risk of AD development. A recently introduced Polygenic Hazard Score (PHS) is able to quantify individuals with age-specific genetic risk for AD. The aim of this study was to quantify the age-specific genetic risk for AD with PRS and compare the results generated by PRS with those from PHS., Methods: Quantification of individual differences in age-specific genetic risk for AD identified by the PRS, was performed with Cox Regression on 9903 (2626 cases and 7277 controls) individuals from the Genetic and Environmental Risk in Alzheimer's Disease consortium (GERAD). Polygenic Hazard Scores were generated for the same individuals. The age-specific genetic risk for AD identified by the PRS was compared with that generated by the PHS. This was repeated using varying SNPs P -value thresholds for disease association., Results: Polygenic Risk Score significantly predicted the risk associated with age at AD onset when SNPs were preselected for association to AD at P  ≤ 0.001. The strongest effect ( B  = 0.28, SE = 0.04, P  = 2.5 × 10 -12 ) was observed for PRS based upon genome-wide significant SNPs ( P  ≤ 5 × 10 -8 ). The strength of association was weaker with less stringent SNP selection thresholds., Interpretation: Both PRS and PHS can be used to predict an age-specific risk for developing AD. The PHS approach uses SNP effect sizes derived with the Cox Proportional Hazard Regression model. When SNPs were selected based upon AD GWAS case/control P  ≤ 10 -3 , we found no advantage of using SNP effects sizes calculated with the Cox Proportional Hazard Regression model in our study. When SNPs are selected for association with AD risk at P  > 10 -3 , the age-specific risk prediction results are not significant for either PRS or PHS. However PHS could be more advantageous than PRS of age specific AD risk predictions when SNPs are prioritized for association with AD age at onset (i.e., powerful Cox Regression GWAS study)., Competing Interests: JH‐grants from Cytox, outside the submitted work; JW‐patent for diagnostics on some SNPs identified as associated with AD; VE‐P – personal fees from Consultancy, outside the submitted work. GL, RS, MS, AF, PB, GS, and NF have nothing to report.

Genome-wide association studies of late-onset Alzheimer's disease risk have previously identified genes primarily expressed in microglia that form a transcriptional network. Using transgenic mouse models of amyloid deposition, we previously showed that many of the mouse orthologues of these risk genes are co-expressed and associated with amyloid pathology. In this new study, we generate an improved RNA-seq-derived network that is expressed in amyloid-responsive mouse microglia and we statistically compare this with gene-level variation in previous human Alzheimer's disease genome-wide association studies to predict at least four new risk genes for the disease ( OAS1 , LAPTM5 , ITGAM/ CD11b and LILRB4 ). Of the mouse orthologues of these genes Oas1a is likely to respond directly to amyloid at the transcriptional level, similarly to established risk gene Trem2 , because the increase in Oas1a and Trem2 transcripts in response to amyloid deposition in transgenic mice is significantly higher than both the increase of the average microglial transcript and the increase in microglial number. In contrast, the mouse orthologues of LAPTM5 , ITGAM /CD11b and LILRB4 ( Laptm5 , Itgam /CD11b and Lilra5 ) show increased transcripts in the presence of amyloid plaques similar in magnitude to the increase of the average microglial transcript and the increase in microglia number, except that Laptm5 and Lilra5 transcripts increase significantly quicker than the average microglial transcript as the plaque load becomes dense. This work suggests that genetic variability in the microglial response to amyloid deposition is a major determinant for Alzheimer's disease risk, and identification of these genes may help to predict the risk of developing Alzheimer's disease. These findings also provide further insights into the mechanisms underlying Alzheimer's disease for potential drug discovery.

A major controversy in psychiatric genetics is whether nonadditive genetic interaction effects contribute to the risk of highly polygenic disorders. We applied a support vector machines (SVMs) approach, which is capable of building linear and nonlinear models using kernel methods, to classify cases from controls in a large schizophrenia case-control sample of 11,853 subjects (5,554 cases and 6,299 controls) and compared its prediction accuracy with the polygenic risk score (PRS) approach. We also investigated whether SVMs are a suitable approach to detecting nonlinear genetic effects, that is, interactions. We found that PRS provided more accurate case/control classification than either linear or nonlinear SVMs, and give a tentative explanation why PRS outperforms both multivariate regression and linear kernel SVMs. In addition, we observe that nonlinear kernel SVMs showed higher classification accuracy than linear SVMs when a large number of SNPs are entered into the model. We conclude that SVMs are a potential tool for assessing the presence of interactions, prior to searching for them explicitly., (© 2018 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics published by Wiley Periodicals, Inc.)

Background: Copy 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., Results: 396,725 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., Conclusions: Carriers 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.

Risk-taking behaviour is an important component of several psychiatric disorders, including attention-deficit hyperactivity disorder, schizophrenia and bipolar disorder. Previously, two genetic loci have been associated with self-reported risk taking and significant genetic overlap with psychiatric disorders was identified within a subsample of UK Biobank. Using the white British participants of the full UK Biobank cohort (n = 83,677 risk takers versus 244,662 controls) for our primary analysis, we conducted a genome-wide association study of self-reported risk-taking behaviour. In secondary analyses, we assessed sex-specific effects, trans-ethnic heterogeneity and genetic overlap with psychiatric traits. We also investigated the impact of risk-taking-associated SNPs on both gene expression and structural brain imaging. We identified 10 independent loci for risk-taking behaviour, of which eight were novel and two replicated previous findings. In addition, we found two further sex-specific risk-taking loci. There were strong positive genetic correlations between risk-taking and attention-deficit hyperactivity disorder, bipolar disorder and schizophrenia. Index genetic variants demonstrated effects generally consistent with the discovery analysis in individuals of non-British White, South Asian, African-Caribbean or mixed ethnicity. Polygenic risk scores comprising alleles associated with increased risk taking were associated with lower white matter integrity. Genotype-specific expression pattern analyses highlighted DPYSL5, CGREF1 and C15orf59 as plausible candidate genes. Overall, our findings substantially advance our understanding of the biology of risk-taking behaviour, including the possibility of sex-specific contributions, and reveal consistency across ethnicities. We further highlight several putative novel candidate genes, which may mediate these genetic effects.

Studying the phenotypic manifestations of increased genetic liability for schizophrenia can increase our understanding of this disorder. Specifically, information from alleles identified in genome-wide association studies can be collapsed into a polygenic risk score (PRS) to explore how genetic risk is manifest within different samples. In this systematic review, we provide a comprehensive assessment of studies examining associations between schizophrenia PRS (SZ-PRS) and several phenotypic measures. We searched EMBASE, Medline and PsycINFO (from August 2009-14th March 2016) plus references of included studies, following PRISMA guidelines. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate. Overall, SZ-PRS was associated with increased risk for psychiatric disorders such as depression and bipolar disorder, lower performance IQ and negative symptoms. SZ-PRS explained up to 6% of genetic variation in psychiatric phenotypes, compared to <0.7% in measures of cognition. Future gains from using the PRS approach may be greater if used for examining phenotypes that are more closely related to biological substrates, for scores based on gene-pathways, and where PRSs are used to stratify individuals for study of treatment response. As it was difficult to interpret findings across studies due to insufficient information provided by many studies, we propose a framework to guide robust reporting of PRS associations in the future., (Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.)

Introduction: Exploring the role of Alzheimer's disease (AD) implicated pathways in the predementia phase may provide new insight for preventive and clinical trials targeting disease specific pathways., Methods: We constructed weighted Genetic risk scores, first based on 20 genome-wide significant AD risk variants and second clustering these variants within pathways. Risk scores were investigated for their association with AD, mild cognitive impairment, and brain magnetic resonance imaging phenotypes including white matter lesions, hippocampal volume, and brain volume., Results: The risk score capturing endocytosis pathway was significantly associated with mild cognitive impairment (P = 1.44 × 10 -4 ). Immune response (P = .016) and clathrin/AP2 adaptor complex pathway (P = 3.55 × 10 -3 ) excluding apolipoprotein E also showed modest association with white matter lesions but did not sustain Bonferroni correction (P = 9.09 × 10 -4 )., Discussion: Our study suggests that the clinical spectrum of early AD pathology is explained by different biological pathways, in particular, the endocytosis, clathrin/AP2 adaptor complex, and immune response pathways, that are independent of apolipoprotein E (APOE)., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Identifying the phenotypic manifestations of increased genetic liability for depression (MDD) and bipolar disorder (BD) can enhance understanding of their aetiology. The polygenic risk score (PRS) derived using data from genome-wide-association-studies can be used to explore how genetic risk is manifest in different samples., Aims: In this systematic review, we review studies that examine associations between the MDD and BD polygenic risk scores and phenotypic outcomes., Methods: Following PRISMA guidelines, we searched EMBASE, Medline and PsycINFO (from August 2009 - 14th March 2016) and references of included studies. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate., Results: Twenty-five studies were included. Overall, both polygenic risk scores were associated with other psychiatric disorders (not the discovery sample disorder) such as depression, schizophrenia and bipolar disorder, greater symptom severity of depression, membership of a creative profession and greater educational attainment. Both depression and bipolar polygenic risk scores explained small amounts of variance in most phenotypes (< 2%)., Limitations: Many studies did not report standardised effect sizes. This prevented us from conducting a meta-analysis., Conclusions: Polygenic risk scores for BD and MDD are associated with a range of phenotypes and outcomes. However, they only explain a small amount of the variation in these phenotypes. Larger discovery and adequately powered target samples are required to increase power of the PRS approach. This could elucidate how genetic risk for bipolar disorder and depression is manifest and contribute meaningfully to stratified medicine., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Polygenic risk scores (PRSs) are a method to summarize the additive trait variance captured by a set of SNPs, and can increase the power of set-based analyses by leveraging public genome-wide association study (GWAS) datasets. PRS aims to assess the genetic liability to some phenotype on the basis of polygenic risk for the same or different phenotype estimated from independent data. We propose the application of PRSs as a set-based method with an additional component of adjustment for linkage disequilibrium (LD), with potential extension of the PRS approach to analyze biologically meaningful SNP sets. We call this method POLARIS: POlygenic Ld-Adjusted RIsk Score. POLARIS identifies the LD structure of SNPs using spectral decomposition of the SNP correlation matrix and replaces the individuals' SNP allele counts with LD-adjusted dosages. Using a raw genotype dataset together with SNP effect sizes from a second independent dataset, POLARIS can be used for set-based analysis. MAGMA is an alternative set-based approach employing principal component analysis to account for LD between markers in a raw genotype dataset. We used simulations, both with simple constructed and real LD-structure, to compare the power of these methods. POLARIS shows more power than MAGMA applied to the raw genotype dataset only, but less or comparable power to combined analysis of both datasets. POLARIS has the advantages that it produces a risk score per person per set using all available SNPs, and aims to increase power by leveraging the effect sizes from the discovery set in a self-contained test of association in the test dataset., (© 2018 The Authors. Genetic Epidemiology published by Wiley Periodicals, Inc.)

The etiologies of bipolar disorder (BD) and schizophrenia include a large number of common risk alleles, many of which are shared across the disorders. BD is clinically heterogeneous and it has been postulated that the pattern of symptoms is in part determined by the particular risk alleles carried, and in particular, that risk alleles also confer liability to schizophrenia influence psychotic symptoms in those with BD. To investigate links between psychotic symptoms in BD and schizophrenia risk alleles we employed a data-driven approach in a genotyped and deeply phenotyped sample of subjects with BD. We used sparse canonical correlation analysis (sCCA) (Witten, Tibshirani, & Hastie, ) to analyze 30 psychotic symptoms, assessed with the OPerational CRITeria checklist, and 82 independent genome-wide significant single nucleotide polymorphisms (SNPs) identified by the Schizophrenia Working group of the Psychiatric Genomics Consortium for which we had data in our BD sample (3,903 subjects). As a secondary analysis, we applied sCCA to larger groups of SNPs, and also to groups of symptoms defined according to a published factor analyses of schizophrenia. sCCA analysis based on individual psychotic symptoms revealed a significant association (p = .033), with the largest weights attributed to a variant on chromosome 3 (rs11411529), chr3:180594593, build 37) and delusions of influence, bizarre behavior and grandiose delusions. sCCA analysis using the same set of SNPs supported association with the same SNP and the group of symptoms defined "factor 3" (p = .012). A significant association was also observed to the "factor 3" phenotype group when we included a greater number of SNPs that were less stringently associated with schizophrenia; although other SNPs contributed to the significant multivariate association result, the greatest weight remained assigned to rs11411529. Our results suggest that the canonical correlation is a useful tool to explore phenotype-genotype relationships. To the best of our knowledge, this is the first study to apply this approach to complex, polygenic psychiatric traits. The sparse canonical correlation approach offers the potential to include a larger number of fine-grained systematic descriptors, and to include genetic markers associated with other disorders that are genetically correlated with BD., (© 2018 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.)

Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

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 insights. We report a new genome-wide association study of schizophrenia (11,260 cases and 24,542 controls), and through meta-analysis with existing data we identify 50 novel associated loci and 145 loci in total. Through integrating genomic fine-mapping with brain expression and chromosome conformation data, we identify candidate causal genes within 33 loci. We also show for the first time that the common variant association signal is highly enriched among genes that are under strong selective pressures. These findings provide new 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 persist in the population.

Risk-taking behaviour is a key component of several psychiatric disorders and could influence lifestyle choices such as smoking, alcohol use, and diet. As a phenotype, risk-taking behaviour therefore fits within a Research Domain Criteria (RDoC) approach, whereby identifying genetic determinants of this trait has the potential to improve our understanding across different psychiatric disorders. Here we report a genome-wide association study in 116,255 UK Biobank participants who responded yes/no to the question "Would you consider yourself a risk taker?" Risk takers (compared with controls) were more likely to be men, smokers, and have a history of psychiatric disorder. Genetic loci associated with risk-taking behaviour were identified on chromosomes 3 (rs13084531) and 6 (rs9379971). The effects of both lead SNPs were comparable between men and women. The chromosome 3 locus highlights CADM2, previously implicated in cognitive and executive functions, but the chromosome 6 locus is challenging to interpret due to the complexity of the HLA region. Risk-taking behaviour shared significant genetic risk with schizophrenia, bipolar disorder, attention-deficit hyperactivity disorder, and post-traumatic stress disorder, as well as with smoking and total obesity. Despite being based on only a single question, this study furthers our understanding of the biology of risk-taking behaviour, a trait that has a major impact on a range of common physical and mental health disorders.

Importance: Bipolar disorder (BD) overlaps schizophrenia in its clinical presentation and genetic liability. Alternative approaches to patient stratification beyond current diagnostic categories are needed to understand the underlying disease processes and mechanisms., Objective: To investigate the association between common-variant liability for schizophrenia, indexed by polygenic risk scores (PRSs), and psychotic presentations of BD., Design, Setting, and Participants: This case-control study in the United Kingdom used multinomial logistic regression to estimate differential PRS associations across categories of cases and controls. Participants included in the final analyses were 4436 cases of BD from the Bipolar Disorder Research Network. These cases were compared with the genotypic data for 4976 cases of schizophrenia and 9012 controls from the Type 1 Diabetes Genetics Consortium study and the Generation Scotland study. Data were collected between January 1, 2000, and December 31, 2013. Data analysis was conducted from March 1, 2016, to February 28, 2017., Exposures: Standardized PRSs, calculated using alleles with an association threshold of P < .05 in the second Psychiatric Genomics Consortium genome-wide association study of schizophrenia, were adjusted for the first 10 population principal components and genotyping platforms., Main Outcomes and Measures: Multinomial logit models estimated PRS associations with BD stratified by Research Diagnostic Criteria subtypes of BD, by lifetime occurrence of psychosis, and by lifetime mood-incongruent psychotic features. Ordinal logistic regression examined PRS associations across levels of mood incongruence. Ratings were derived from the Schedules for Clinical Assessment in Neuropsychiatry interview and the Bipolar Affective Disorder Dimension Scale., Results: Of the 4436 cases of BD, 2966 (67%) were female patients, and the mean (SD) age at interview was 46 [12] years. Across clinical phenotypes, there was an exposure-response gradient, with the strongest PRS association for schizophrenia (risk ratio [RR] = 1.94; 95% CI, 1.86-2.01), followed by schizoaffective BD (RR = 1.37; 95% CI, 1.22-1.54), bipolar I disorder subtype (RR = 1.30; 95% CI, 1.24-1.36), and bipolar II disorder subtype (RR = 1.04; 95% CI, 0.97-1.11). Within BD cases, there was an effect gradient, indexed by the nature of psychosis. Prominent mood-incongruent psychotic features had the strongest association (RR = 1.46; 95% CI, 1.36-1.57), followed by mood-congruent psychosis (RR = 1.24; 95% CI, 1.17-1.33) and BD with no history of psychosis (RR = 1.09; 95% CI, 1.04-1.15)., Conclusions and Relevance: For the first time to date, a study shows a polygenic-risk gradient across schizophrenia and BD, indexed by the occurrence and level of mood-incongruent psychotic symptoms.

Background: Dementia with Lewy bodies is the second most common form of dementia in elderly people but has been overshadowed in the research field, partly because of similarities between dementia with Lewy bodies, Parkinson's disease, and Alzheimer's disease. So far, to our knowledge, no large-scale genetic study of dementia with Lewy bodies has been done. To better understand the genetic basis of dementia with Lewy bodies, we have done a genome-wide association study with the aim of identifying genetic risk factors for this disorder., Methods: In this two-stage genome-wide association study, we collected samples from white participants of European ancestry who had been diagnosed with dementia with Lewy bodies according to established clinical or pathological criteria. In the discovery stage (with the case cohort recruited from 22 centres in ten countries and the controls derived from two publicly available database of Genotypes and Phenotypes studies [phs000404.v1.p1 and phs000982.v1.p1] in the USA), we performed genotyping and exploited the recently established Haplotype Reference Consortium panel as the basis for imputation. Pathological samples were ascertained following autopsy in each individual brain bank, whereas clinical samples were collected after participant examination. There was no specific timeframe for collection of samples. We did association analyses in all participants with dementia with Lewy bodies, and also only in participants with pathological diagnosis. In the replication stage, we performed genotyping of significant and suggestive results from the discovery stage. Lastly, we did a meta-analysis of both stages under a fixed-effects model and used logistic regression to test for association in each stage., Findings: This study included 1743 patients with dementia with Lewy bodies (1324 with pathological diagnosis) and 4454 controls (1216 patients with dementia with Lewy bodies vs 3791 controls in the discovery stage; 527 vs 663 in the replication stage). Results confirm previously reported associations: APOE (rs429358; odds ratio [OR] 2·40, 95% CI 2·14-2·70; p=1·05 × 10 -48 ), SNCA (rs7681440; OR 0·73, 0·66-0·81; p=6·39 × 10 -10 ), an GBA (rs35749011; OR 2·55, 1·88-3·46; p=1·78 × 10 -9 ). They also provide some evidence for a novel candidate locus, namely CNTN1 (rs7314908; OR 1·51, 1·27-1·79; p=2·32 × 10 -6 ); further replication will be important. Additionally, we estimate the heritable component of dementia with Lewy bodies to be about 36%., Interpretation: Despite the small sample size for a genome-wide association study, and acknowledging the potential biases from ascertaining samples from multiple locations, we present the most comprehensive and well powered genetic study in dementia with Lewy bodies so far. These data show that common genetic variability has a role in the disease., Funding: The Alzheimer's Society and the Lewy Body Society., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Mood instability is a core clinical feature of affective and psychotic disorders. In keeping with the Research Domain Criteria approach, it may be a useful construct for identifying biology that cuts across psychiatric categories. We aimed to investigate the biological validity of a simple measure of mood instability and evaluate its genetic relationship with several psychiatric disorders, including major depressive disorder (MDD), bipolar disorder (BD), schizophrenia, attention deficit hyperactivity disorder (ADHD), anxiety disorder and post-traumatic stress disorder (PTSD). We conducted a genome-wide association study (GWAS) of mood instability in 53,525 cases and 60,443 controls from UK Biobank, identifying four independently associated loci (on chromosomes 8, 9, 14 and 18), and a common single-nucleotide polymorphism (SNP)-based heritability estimate of ~8%. We found a strong genetic correlation between mood instability and MDD (r g  = 0.60, SE = 0.07, p = 8.95 × 10 -17 ) and a small but significant genetic correlation with both schizophrenia (r g  = 0.11, SE = 0.04, p = 0.01) and anxiety disorders (r g  = 0.28, SE = 0.14, p = 0.04), although no genetic correlation with BD, ADHD or PTSD was observed. Several genes at the associated loci may have a role in mood instability, including the DCC netrin 1 receptor (DCC) gene, eukaryotic translation initiation factor 2B subunit beta (eIF2B2), placental growth factor (PGF) and protein tyrosine phosphatase, receptor type D (PTPRD). Strengths of this study include the very large sample size, but our measure of mood instability may be limited by the use of a single question. Overall, this work suggests a polygenic basis for mood instability. This simple measure can be obtained in very large samples; our findings suggest that doing so may offer the opportunity to illuminate the fundamental biology of mood regulation.

We identified rare coding variants associated with Alzheimer's disease in a three-stage case-control study of 85,133 subjects. In stage 1, we genotyped 34,174 samples using a whole-exome microarray. In stage 2, we tested associated variants (P < 1 × 10 -4 ) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, we used an additional 14,997 samples to test the most significant stage 2 associations (P < 5 × 10 -8 ) using imputed genotypes. We observed three new genome-wide significant nonsynonymous variants associated with Alzheimer's disease: a protective variant in PLCG2 (rs72824905: p.Pro522Arg, P = 5.38 × 10 -10 , odds ratio (OR) = 0.68, minor allele frequency (MAF) cases = 0.0059, MAF controls = 0.0093), a risk variant in ABI3 (rs616338: p.Ser209Phe, P = 4.56 × 10 -10 , OR = 1.43, MAF cases = 0.011, MAF controls = 0.008), and a new genome-wide significant variant in TREM2 (rs143332484: p.Arg62His, P = 1.55 × 10 -14 , OR = 1.67, MAF cases = 0.0143, MAF controls = 0.0089), a known susceptibility gene for Alzheimer's disease. These protein-altering changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified risk genes in Alzheimer's disease. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to the development of Alzheimer's disease.

A genome-wide survival analysis of 14,406 Alzheimer's disease (AD) cases and 25,849 controls identified eight previously reported AD risk loci and 14 novel loci associated with age at onset. Linkage disequilibrium score regression of 220 cell types implicated the regulation of myeloid gene expression in AD risk. The minor allele of rs1057233 (G), within the previously reported CELF1 AD risk locus, showed association with delayed AD onset and lower expression of SPI1 in monocytes and macrophages. SPI1 encodes PU.1, a transcription factor critical for myeloid cell development and function. AD heritability was enriched within the PU.1 cistrome, implicating a myeloid PU.1 target gene network in AD. Finally, experimentally altered PU.1 levels affected the expression of mouse orthologs of many AD risk genes and the phagocytic activity of mouse microglial cells. Our results suggest that lower SPI1 expression reduces AD risk by regulating myeloid gene expression and cell function.

Previous estimates of the utility of polygenic risk score analysis for the prediction of Alzheimer disease have given area under the curve (AUC) estimates of <80%. However, these have been based on the genetic analysis of clinical case-control series. Here, we apply the same analytic approaches to a pathological case-control series and show a predictive AUC of 84%. We suggest that this analysis has clinical utility and that there is limited room for further improvement using genetic data. Ann Neurol 2017;82:311-314., (© 2017 American Neurological Association.)

Background: The UK Biobank is a unique resource for biomedical research, with extensive phenotypic and genetic data on half a million adults from the general population. We aimed to examine the effect of neurodevelopmental copy number variants (CNVs) on the cognitive performance of participants., Methods: We used Affymetrix Power Tools and PennCNV-Affy software to analyze Affymetrix microarrays of the first 152,728 genotyped individuals. We annotated a list of 93 CNVs and compared their frequencies with control datasets. We analyzed the performance on seven cognitive tests of carriers of 12 CNVs associated with schizophrenia (n = 1087) and of carriers of another 41 neurodevelopmental CNVs (n = 484)., Results: The frequencies of the 93 CNVs in the Biobank subjects were remarkably similar to those among 26,628 control subjects from other datasets. Carriers of schizophrenia-associated CNVs and of the group of 41 other neurodevelopmental CNVs had impaired performance on the cognitive tests, with nine of 14 comparisons remaining statistically significant after correction for multiple testing. They also had lower educational and occupational attainment (p values between 10 -7 and 10 -18 ). The deficits in cognitive performance were modest (Z score reductions between 0.01 and 0.51), compared with individuals with schizophrenia in the Biobank (Z score reductions between 0.35 and 0.90)., Conclusions: This is the largest study on the cognitive phenotypes of CNVs to date. Adult carriers of neurodevelopmental CNVs from the general population have significant cognitive deficits. The UK Biobank will allow unprecedented opportunities for analysis of further phenotypic consequences of CNVs., (Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Purpose: Somatic mutation status at KRAS, BRAF , and NRAS is associated with prognosis in patients with advanced colorectal cancer (aCRC); however, it remains unclear whether there are intralocus, variant-specific differences in survival and other clinicopathologic parameters. Experimental Design: We profiled 2,157 aCRCs for somatic mutations in KRAS, BRAF , and NRAS and determined microsatellite instability status. We sought inter- and intralocus correlations between mutations and variant-specific associations with survival and clinicopathology. Results: KRAS mutations were rarely found together and those in codons 12 and 13 conferred poor prognosis [hazard ratio (HR), 1.44; 95% confidence interval (CI), 1.28-1.61; P = 6.4 × 10 -10 and HR, 1.53; 95% CI, 1.26-1.86; P = 1.5 × 10 -05 , respectively]. For BRAF, more c.1781A>G (p.D594G) CRCs carried RAS mutations [14% (3/21)] compared with c.1799T>A (p.V600E) CRCs [1% (2/178), P = 9.0 × 10 -03 ]. c.1799T>A (p.V600E) was associated with poor prognosis (HR, 2.60; 95% CI, 2.06-3.28; P = 1.0 × 10 -15 ), whereas c.1781A>G (p.D594G) was not (HR, 1.30; 95% CI, 0.73-2.31; P = 0.37); this intralocus difference was significant ( P = 0.04). More c.1799T>A (p.V600E) colorectal cancers were found in the right colon [47% (47/100)], compared with c.1781A>G (p.D594G) colorectal cancers [7% (1/15), P = 3.7 × 10 -03 ]. For NRAS , 5% (3/60) of codon 61 mutant colorectal cancers had KRAS mutations compared with 44% (10/23) of codons 12 and 13 mutant colorectal cancers ( P = 7.9 × 10 -05 ). Codon 61 mutations conferred poor prognosis (HR, 1.47; 95% CI, 1.09-1.99; P = 0.01), whereas codons 12 and 13 mutations did not (HR, 1.29; 95% CI, 0.64-2.58; P = 0.48). Conclusions: Our data show considerable intralocus variation in the outcomes of mutations in BRAF and NRAS These data need to be considered in patient management and personalized cancer therapy. Clin Cancer Res; 23(11); 2742-9. ©2016 AACR ., (©2016 American Association for Cancer Research.)

Plasma biomarkers to aid the early diagnosis of Alzheimer's disease (AD) or to monitor disease progression have long been sought and continue to be widely studied. Biomarkers that correlate with AD polygenic risk score, a measure of the polygenic architecture of the disease and highly predictive of AD status, would be excellent candidates. Therefore, we undertook a preliminary study to assess the association of plasma inflammatory biomarkers with an overall AD polygenic risk score as well as with an inflammation-specific AD polygenic risk score in a sample set of 93 AD cases. We measured five complement biomarkers [complement receptor 1 (CR1), clusterin, complement component 9 (C9), C1 inhibitor (C1inh), terminal complement complex (TCC)] and the benchmark inflammatory marker C-reactive protein (CRP). Plasma clusterin level showed an association with overall AD polygenic risk score, while clusterin, C1inh, and CRP levels each displayed some association with the inflammatory-specific AD polygenic risk score. The results suggest that elevated plasma levels of inflammatory biomarkers, including complement proteins, associate with polygenic risk scores in AD, further strengthening the link between genetic and biomarker disease predictors and indicating a potential role for these markers in disease prediction and patient stratification in AD.

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10 -15 ), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10 -6 ). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10 -11 ) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10 -5 ). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.

Personality is influenced by genetic and environmental factors and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci, significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132-260,861). Of these genome-wide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422-18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit-hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion-introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety).