Runs of homozygosity implicate autozygosity as a schizophrenia risk factor

Autozygosity occurs when two chromosomal segments that are identical from a common ancestor are inherited from each parent. This occurs at high rates in the offspring of mates who are closely related (inbreeding), but also occurs at lower levels among the offspring of distantly related mates. Here, we use runs of homozygosity in genome-wide SNP data to estimate the proportion of the autosome that exists in autozygous tracts in 9,388 cases with schizophrenia and 12,456 controls. We estimate that the odds of schizophrenia increase by ~17% for every 1% increase in genome-wide autozygosity. This association is not due to one or a few regions, but results from many autozygous segments spread throughout the genome, and is consistent with a role for multiple recessive or partially recessive alleles in the etiology of schizophrenia. Such a bias towards recessivity suggests that alleles that increase the risk of schizophrenia have been selected against over evolutionary time

High Content Image Analysis Identifies Novel Regulators of Synaptogenesis in a High-Throughput RNAi Screen of Primary Neurons

The formation of synapses, the specialized points of chemical communication between neurons, is a highly regulated developmental process fundamental to establishing normal brain circuitry. Perturbations of synapse formation and function causally contribute to human developmental and degenerative neuropsychiatric disorders, such as Alzheimer's disease, intellectual disability, and autism spectrum disorders. Many genes controlling synaptogenesis have been identified, but lack of facile experimental systems has made systematic discovery of regulators of synaptogenesis challenging. Thus, we created a high-throughput platform to study excitatory and inhibitory synapse development in primary neuronal cultures and used a lentiviral RNA interference library to identify novel regulators of synapse formation. This methodology is broadly applicable for high-throughput screening of genes and drugs that may rescue or improve synaptic dysfunction associated with cognitive function and neurological disorders.National Institutes of Health (U.S.) (MH095096)National Institutes of Health (U.S.) (R01 GM089652

Regional brain volumes and antidepressant treatment resistance in major depressive disorder

Major depressive disorder (MDD) is a heritable and highly debilitating condition with antidepressants, first-line treatment, demonstrating low to modest response rates. No current biological mechanism substantially explains MDD but both neurostructural and neurochemical pathways have been suggested. Further explication of these may aid in identifying subgroups of MDD that are better defined by their aetiology. Specifically, genetic stratification provides an array of tools to do this, including the intermediate phenotype approach which was applied in this thesis. This thesis explores genetic overlap with regional brain volume and MDD and the genetic and non-genetic components of antidepressant response. The first study utilised the most recent published data from ENIGMA (Enhancing Neuroimaging Genetics through Meta-analysis) Consortium’s genome-wide association study (GWAS) of regional brain volume to examine shared genetic architecture between seven subcortical brain volumes and intracranial volume (ICV) and MDD. This was explored using linkage disequilibrium score regression (LDSC), polygenic risk scoring (PRS) techniques, Mendelian randomisation (MR) analysis and BUHMBOX (Breaking Up Heterogeneous Mixture Based On Cross-locus correlations). Results indicated that hippocampal volume was positively genetically correlated with MDD (rg= 0.46, P= 0.02), although this did not survive multiple comparison testing. Additionally, there was evidence for genetic subgrouping in Generation Scotland: Scottish Family Health Study (GS:SFHS) MDD cases (P=0.00281), however, this was not replicated in two other independent samples. This study does not support a shared architecture for regional brain volumes and MDD, however, provided some evidence that hippocampal volume and MDD may share genetic architecture in a subgroup of individuals, albeit the genetic correlation did not survive multiple testing correction and genetic subgroup heterogeneity was not replicated. To explore antidepressant treatment resistance, the second study utilised prescription data in (GS:SFHS) to define a measure of (a) treatment resistance (TR) and (b) stages of resistance (SR) by inferring antidepressant switching as non-response. GWAS were conducted separately for TR in GS:SFHS and the GENDEP (Genome-based Therapeutic Drugs for Depression) study and then meta-analysed (meta-analysis n=4,213, cases=358). For SR, a GWAS on GS:SFHS only was performed (n=3,452). Additionally, gene-set enrichment, polygenic risk scoring (PRS) and genetic correlation analysis were conducted. No significant locus, gene or gene-set was associated with TR or SR, however power analysis indicated that this analysis was underpowered. Pedigree-based correlations identified genetic overlap with psychological distress, schizotypy and mood disorder traits. Finally, the role of neuroticism, psychological resilience and coping styles in antidepressant resistance was investigated. Univariate, moderation and mediation models were applied using logistic regression and structural equation modelling techniques. In univariate models, neuroticism and emotion-orientated coping demonstrated significant negative association with antidepressant resistance, whereas resilience, task-orientated and avoidance-orientated coping demonstrated significant positive association. No moderation of the association between neuroticism and TR was detected and no mediating effect of coping styles was found. However, resilience was found to partially mediate the association between neuroticism and TR. Whilst the first study does not indicate a genetic overlap between regional brain volumes and MDD, it demonstrates the utility of the intermediate approach in complex disease. Antidepressant resistance was associated with neuroticism both genetically and phenotypically, indicating its role as an intermediate phenotype. Nonetheless, larger sample sizes are needed to adequately address the components of antidepressant resistance. Further work in antidepressant non-response may help to identify biological mechanisms responsible in MDD pathology and help stratify individuals into more tractable groups

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders

Genetic variants linked to education predict longevity

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members’ polygenic profile score for education to predict their parents’ longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.</p

A common biological basis of obesity and nicotine addiction

J. Kaprio ja J. Tuomilehto työryhmien jäseniä (yht. 281).Peer reviewe

Mining the human phenome using allelic scores that index biological intermediates

J. Kaprio ja M-L. Lokki työryhmien jäseniä.It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.Peer reviewe

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age-and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to similar to 2.8M SNPs with BMI and WHRadjBMI in four strata (men &lt;= 50y, men &gt; 50y, women &lt;= 50y, women &gt; 50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR&lt; 5%) age-specific effects, of which 11 had larger effects in younger (&lt; 50y) than in older adults (&gt;= 50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may providefurther insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.</p

Novel Approach Identifies SNPs in SLC2A10 and KCNK9 with Evidence for Parent-of-Origin Effect on Body Mass Index

Marja-Liisa Lokki työryhmien Generation Scotland Consortium, LifeLines Cohort Study ja GIANT Consortium jäsenPeer reviewe