A framework for interpreting genome-wide association studies of psychiatric disorders

Genome-wide association studies (GWAS) have yielded a plethora of new findings in the past 3 years. By early 2009, GWAS on 47 samples of subjects with attention-deficit hyperactivity disorder, autism, bipolar disorder, major depressive disorder and schizophrenia will be completed. Taken together, these GWAS constitute the largest biological experiment ever conducted in psychiatry (59 000 independent cases and controls, 7700 family trios and >40 billion genotypes). We know that GWAS can work, and the question now is whether it will work for psychiatric disorders. In this review, we describe these studies, the Psychiatric GWAS Consortium for meta-analyses of these data, and provide a logical framework for interpretation of some of the conceivable outcomes

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c

The contribution of genetic variants to disease depends on the ruler

Our understanding of the genetic basis of disease has evolved from descriptions of overall heritability or familiality to the identification of large numbers of risk loci. One can quantify the impact of such loci on disease using a plethora of measures, which can guide future research decisions. However, different measures can attribute varying degrees of importance to a variant. In this Analysis, we consider and contrast the most commonly used measures-specifically, the heritability of disease liability, approximate heritability, sibling recurrence risk, overall genetic variance using a logarithmic relative risk scale, the area under the receiver-operating curve for risk prediction and the population attributable fraction-and give guidelines for their use that should be explicitly considered when assessing the contribution of genetic variants to disease

High frequency of pathogenic non-founder germline mutations in BRCA1 and BRCA2 in families with breast and ovarian cancer in a founder population

Funding Information: This work was supported by State Research Program “Biomedicine for the public health (BIOMEDICINE)” project 5 “Personalised cancer diagnostics and treatment effectiveness evaluation”. Publisher Copyright: © 2018 The Author(s).Background: Pathogenic BRCA1 founder mutations (c.4035delA, c.5266dupC) contribute to 3.77% of all consecutive primary breast cancers and 9.9% of all consecutive primary ovarian cancers. Identifying germline pathogenic gene variants in patients with primary breast and ovarian cancer could significantly impact the medical management of patients. The aim of the study was to evaluate the rate of pathogenic mutations in the 26 breast and ovarian cancer susceptibility genes in patients who meet the criteria for BRCA1/2 testing and to compare the accuracy of different selection criteria for second-line testing in a founder population. Methods: Fifteen female probands and 1 male proband that met National Comprehensive Cancer Network (NCCN) criteria for BRCA1/2 testing were included in the study and underwent 26-gene panel testing. Fourteen probands had breast cancer, one proband had ovarian cancer, and one proband had both breast and ovarian cancer. In a 26-gene panel, the following breast and/or ovarian cancer susceptibility genes were included: ATM, BARD1, BLM, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, EPCAM, FAM175A, MEN1, MLH1, MRE11A, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, PTEN, RAD50, RAD51C, RAD51D, STK11, TP53, and XRCC2. All patients previously tested negative for BRCA1 founder mutations. Results: In 44% (7 out of 16) of tested probands, pathogenic mutations were identified. Six probands carried pathogenic mutations in BRCA1, and one proband carried pathogenic mutations in BRCA2. In patients, a variant of uncertain significance was found in BRCA2, RAD50, MRE11A and CDH1. The Manchester scoring system showed a high accuracy (87.5%), high sensitivity (85.7%) and high specificity (88.9%) for the prediction of pathogenic non-founder BRCA1/2 mutations. Conclusion: A relatively high incidence of pathogenic non-founder BRCA1/2 mutations was observed in a founder population. The Manchester scoring system predicted the probability of non-founder pathogenic mutations with high accuracy.publishersversionPeer reviewe

Deficient NRG1-ERBB signaling alters social approach: relevance to genetic mouse models of schizophrenia

Growth factor Neuregulin 1 (NRG1) plays an essential role in development and organization of the cerebral cortex. NRG1 and its receptors, ERBB3 and ERBB4, have been implicated in genetic susceptibility for schizophrenia. Disease symptoms include asociality and altered social interaction. To investigate the role of NRG1-ERBB signaling in social behavior, mice heterozygous for an Nrg1 null allele (Nrg1+/−), and mice with conditional ablation of Erbb3 or Erbb4 in the central nervous system, were evaluated for sociability and social novelty preference in a three-chambered choice task. Results showed that deficiencies in NRG1 or ERBB3 significantly enhanced sociability. All of the mutant groups demonstrated a lack of social novelty preference, in contrast to their respective wild-type controls. Effects of NRG1, ERBB3, or ERBB4 deficiency on social behavior could not be attributed to general changes in anxiety-like behavior, activity, or loss of olfactory ability. Nrg1+/− pups did not exhibit changes in isolation-induced ultrasonic vocalizations, a measure of emotional reactivity. Overall, these findings provide evidence that social behavior is mediated by NRG1-ERBB signaling

Structural variation in the chicken genome identified by paired-end next-generation DNA sequencing of reduced representation libraries

<p>Abstract</p> <p>Background</p> <p>Variation within individual genomes ranges from single nucleotide polymorphisms (SNPs) to kilobase, and even megabase, sized structural variants (SVs), such as deletions, insertions, inversions, and more complex rearrangements. Although much is known about the extent of SVs in humans and mice, species in which they exert significant effects on phenotypes, very little is known about the extent of SVs in the 2.5-times smaller and less repetitive genome of the chicken.</p> <p>Results</p> <p>We identified hundreds of shared and divergent SVs in four commercial chicken lines relative to the reference chicken genome. The majority of SVs were found in intronic and intergenic regions, and we also found SVs in the coding regions. To identify the SVs, we combined high-throughput short read paired-end sequencing of genomic reduced representation libraries (RRLs) of pooled samples from 25 individuals and computational mapping of DNA sequences from a reference genome.</p> <p>Conclusion</p> <p>We provide a first glimpse of the high abundance of small structural genomic variations in the chicken. Extrapolating our results, we estimate that there are thousands of rearrangements in the chicken genome, the majority of which are located in non-coding regions. We observed that structural variation contributes to genetic differentiation among current domesticated chicken breeds and the Red Jungle Fowl. We expect that, because of their high abundance, SVs might explain phenotypic differences and play a role in the evolution of the chicken genome. Finally, our study exemplifies an efficient and cost-effective approach for identifying structural variation in sequenced genomes.</p

Genomic Landscape of a Three-Generation Pedigree Segregating Affective Disorder

Bipolar disorder (BPD) is a common psychiatric illness with a complex mode of inheritance. Besides traditional linkage and association studies, which require large sample sizes, analysis of common and rare chromosomal copy number variants (CNVs) in extended families may provide novel insights into the genetic susceptibility of complex disorders. Using the Illumina HumanHap550 BeadChip with over 550,000 SNP markers, we genotyped 46 individuals in a three-generation Old Order Amish pedigree with 19 affected (16 BPD and three major depression) and 27 unaffected subjects. Using the PennCNV algorithm, we identified 50 CNV regions that ranged in size from 12 to 885 kb and encompassed at least 10 single nucleotide polymorphisms (SNPs). Of 19 well characterized CNV regions that were available for combined genotype-expression analysis 11 (58%) were associated with expression changes of genes within, partially within or near these CNV regions in fibroblasts or lymphoblastoid cell lines at a nominal P value <0.05. To further investigate the mode of inheritance of CNVs in the large pedigree, we analyzed a set of four CNVs, located at 6q27, 9q21.11, 12p13.31 and 15q11, all of which were enriched in subjects with affective disorders. We additionally show that these variants affect the expression of neuronal genes within or near the rearrangement. Our analysis suggests that family based studies of the combined effect of common and rare CNVs at many loci may represent a useful approach in the genetic analysis of disease susceptibility of mental disorders

Rare mutations in N-methyl-D-aspartate glutamate receptors in autism spectrum disorders and schizophrenia

Pharmacological, genetic and expression studies implicate N-methyl-D-aspartate (NMDA) receptor hypofunction in schizophrenia (SCZ). Similarly, several lines of evidence suggest that autism spectrum disorders (ASD) could be due to an imbalance between excitatory and inhibitory neurotransmission. As part of a project aimed at exploring rare and/or de novo mutations in neurodevelopmental disorders, we have sequenced the seven genes encoding for NMDA receptor subunits (NMDARs) in a large cohort of individuals affected with SCZ or ASD (n=429 and 428, respectively), parents of these subjects and controls (n=568). Here, we identified two de novo mutations in patients with sporadic SCZ in GRIN2A and one de novo mutation in GRIN2B in a patient with ASD. Truncating mutations in GRIN2C, GRIN3A and GRIN3B were identified in both subjects and controls, but no truncating mutations were found in the GRIN1, GRIN2A, GRIN2B and GRIN2D genes, both in patients and controls, suggesting that these subunits are critical for neurodevelopment. The present results support the hypothesis that rare de novo mutations in GRIN2A or GRIN2B can be associated with cases of sporadic SCZ or ASD, just as it has recently been described for the related neurodevelopmental disease intellectual disability. The influence of genetic variants appears different, depending on NMDAR subunits. Functional compensation could occur to counteract the loss of one allele in GRIN2C and GRIN3 family genes, whereas GRIN1, GRIN2A, GRIN2B and GRIN2D appear instrumental to normal brain development and function