Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

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 (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 non-allelic homologous recombination.

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Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Heritability and polygenic predictionIn the EUR sample, the SNP-based heritability (h 2 SNP ) (that is, the proportion of variance in liability attributable to all measured SNPs)

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Objective To conduct a genome-wide association study (GWAS) of anorexia nervosa and to calculate genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. Method Following uniform quality control and imputation using the 1000 Genomes Project (phase 3) in 12 case-control cohorts comprising 3,495 anorexia nervosa cases and 10,982 controls, we performed standard association analysis followed by a meta-analysis across cohorts. Linkage disequilibrium score regression (LDSC) was used to calculate genome-wide common variant heritability [ hSNP2, partitioned heritability, and genetic correlations (rg)] between anorexia nervosa and other phenotypes. Results Results were obtained for 10,641,224 single nucleotide polymorphisms (SNPs) and insertion-deletion variants with minor allele frequency > 1% and imputation quality scores > 0.6. The hSNP2 of anorexia nervosa was 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability arises from common genetic variation. We identified one genome-wide significant locus on chromosome 12 (rs4622308, p=4.3×10−9) in a region harboring a previously reported type 1 diabetes and autoimmune disorder locus. Significant positive genetic correlations were observed between anorexia nervosa and schizophrenia, neuroticism, educational attainment, and high density lipoprotein (HDL) cholesterol, and significant negative genetic correlations between anorexia nervosa and body mass index, insulin, glucose, and lipid phenotypes. Conclusions Anorexia nervosa is a complex heritable phenotype for which we have found the first genome-wide significant locus. Anorexia nervosa also has large and significant genetic correlations with both psychiatric phenotypes and metabolic traits. Our results encourage a reconceptualization of this frequently lethal disorder as one with both psychiatric and metabolic etiology.

The International Stem Cell Initiative characterized 59 human embryonic stem cell lines from 17 laboratories worldwide. Despite diverse genotypes and different techniques used for derivation and maintenance, all lines exhibited similar expression patterns for several markers of human embryonic stem cells. They expressed the glycolipid antigens SSEA3 and SSEA4, the keratan sulfate antigens TRA-1-60, TRA-1-81, GCTM2 and GCT343, and the protein antigens CD9, Thy1 (also known as CD90), tissue-nonspecific alkaline phosphatase and class 1 HLA, as well as the strongly developmentally regulated genes NANOG, POU5F1 (formerly known as OCT4), TDGF1, DNMT3B, GABRB3 and GDF3. Nevertheless, the lines were not identical: differences in expression of several lineage markers were evident, and several imprinted genes showed generally similar allele-specific expression patterns, but some gene-dependent variation was observed. Also, some female lines expressed readily detectable levels of XIST whereas others did not. No significant contamination of the lines with mycoplasma, bacteria or cytopathic viruses was detected.

Schizophrenia is a highly heritable neuropsychiatric disorder of complex genetic etiology. Previous genome-wide surveys have revealed a greater burden of large, rare CNVs in schizophrenia cases and identified multiple rare recurrent CNVs that increase risk of schizophrenia although with incomplete penetrance and pleiotropic effects. Identification of additional recurrent CNVs and biological pathways enriched for schizophrenia CNVs requires greater sample sizes. We conducted a genome-wide survey for CNVs associated with schizophrenia using a Swedish national sample (4,719 cases and 5,917 controls). High-confidence CNV calls were generated using genotyping array intensity data and their effect on risk of schizophrenia was measured. Our data confirm increased burden of large, rare CNVs in schizophrenia cases as well as significant associations for recurrent 16p11.2 duplications, 22q11.2 deletions and 3q29 deletions. We report a novel association for 17q12 duplications (odds ratio=4.16, P=0.018), previously associated with autism and mental retardation but not schizophrenia. Intriguingly, gene set association analyses implicate biological pathways previously associated with schizophrenia through common variation and exome sequencing (calcium channel signaling and binding partners of the fragile X mental retardation protein). We found significantly increased burden of the largest CNVs (>500Kb) in genes present in the post-synaptic density, in genomic regions implicated via schizophrenia genome-wide association studies, and in gene products localized to mitochondria and cytoplasm. Our findings suggest that multiple lines of genomic inquiry – genome-wide screens for CNVs, common variation, and exonic variation – are converging on similar sets of pathways and/or genes.