Detecting Identity by Descent and Homozygosity Mapping in Whole-Exome Sequencing Data

The detection of genetic segments of Identical by Descent (IBD) in Genome-Wide Association Studies has proven successful in pinpointing genetic relatedness between reportedly unrelated individuals and leveraging such regions to shortlist candidate genes. These techniques depend on high-density genotyping arrays and their effectiveness in diverse sequence data is largely unknown. Due to decreasing costs and increasing effectiveness of high throughput techniques for whole-exome sequencing, an influx of exome sequencing data has become available. Studies using exomes and IBD-detection methods within known pedigrees have shown that IBD can be useful in finding hidden genetic candidates where known relatives are available. We set out to examine the viability of using IBD-detection in whole exome sequencing data in population-wide studies. In doing so, we extend GERMLINE, a method to detect IBD from exome sequencing data by finding small slices of matching alleles between pairs of individuals and extending them into full IBD segments. This algorithm allows for efficient population-wide detection in dense data. We apply this algorithm to a cohort of Crohn''s Disease cases where whole-exome and GWAS array data is available. We confirm that GWAS-based detected segments are highly accurate and predictive of underlying shared variation. Where segments inferred from GWAS are expected to be of high accuracy, we compare exome-based detection accuracy of multiple detection strategies. We find detection accuracy to be prohibitively low in all assessments, both in terms of segment sensitivity and specificity. Even after isolating relatively long segments beyond 10cM, exome-based detection continued to offer poor specificity/sensitivity tradeoffs. We hypothesize that the variable coverage and platform biases of exome capture account for this decreased accuracy and look toward whole genome sequencing data as a higher quality source for detecting population-wide IBD.     

Pooled Sequencing of Candidate Genes Implicates Rare Variants in the Development of Asthma Following Severe RSV Bronchiolitis in Infancy

Severe infection with respiratory syncytial virus (RSV) during infancy is strongly associated with the development of asthma. To identify genetic variation that contributes to asthma following severe RSV bronchiolitis during infancy, we sequenced the coding exons of 131 asthma candidate genes in 182 European and African American children with severe RSV bronchiolitis in infancy using anonymous pools for variant discovery, and then directly genotyped a set of 190 nonsynonymous variants. Association testing was performed for physician-diagnosed asthma before the 7^th birthday (asthma) using genotypes from 6,500 individuals from the Exome Sequencing Project (ESP) as controls to gain statistical power. In addition, among patients with severe RSV bronchiolitis during infancy, we examined genetic associations with asthma, active asthma, persistent wheeze, and bronchial hyperreactivity (methacholine PC₂₀) at age 6 years. We identified four rare nonsynonymous variants that were significantly associated with asthma following severe RSV bronchiolitis, including single variants in ADRB2, FLG and NCAM1 in European Americans (p = 4.6x10^-4, 1.9x10^-13 and 5.0x10^-5, respectively), and NOS1 in African Americans (p = 2.3x10^-11). One of the variants was a highly functional nonsynonymous variant in ADRB2 (rs1800888), which was also nominally associated with asthma (p = 0.027) and active asthma (p = 0.013) among European Americans with severe RSV bronchiolitis without including the ESP. Our results suggest that rare nonsynonymous variants contribute to the development of asthma following severe RSV bronchiolitis in infancy, notably in ADRB2. Additional studies are required to explore the role of rare variants in the etiology of asthma and asthma-related traits following severe RSV bronchiolitis.     

Whole-Exome Sequencing of 2,000 Danish Individuals and the Role of Rare Coding Variants in Type 2 Diabetes

It has been hypothesized that, in aggregate, rare variants in coding regions of genes explain a substantial fraction of the heritability of common diseases. We sequenced the exomes of 1,000 Danish cases with common forms of type 2 diabetes (including body mass index > 27.5 kg/m² and hypertension) and 1,000 healthy controls to an average depth of 56×. Our simulations suggest that our study had the statistical power to detect at least one causal gene (a gene containing causal mutations) if the heritability of these common diseases was explained by rare variants in the coding regions of a limited number of genes. We applied a series of gene-based tests to detect such susceptibility genes. However, no gene showed a significant association with disease risk after we corrected for the number of genes analyzed. Thus, we could reject a model for the genetic architecture of type 2 diabetes where rare nonsynonymous variants clustered in a modest number of genes (fewer than 20) are responsible for the majority of disease risk.     

Homozygosity Haplotype and Whole-Exome Sequencing Analysis to Identify Potentially Functional Rare Variants Involved in Multiple Sclerosis among Sardinian Families

Multiple Sclerosis (MS) is a complex multifactorial autoimmune disease, whose sex- and age-adjusted prevalence in Sardinia (Italy) is among the highest worldwide. To date, 233 loci were associated with MS and almost 20% of risk heritability is attributable to common genetic variants, but many low-frequency and rare variants remain to be discovered. Here, we aimed to contribute to the understanding of the genetic basis of MS by investigating potentially functional rare variants. To this end, we analyzed thirteen multiplex Sardinian families with Immunochip genotyping data. For five families, Whole Exome Sequencing (WES) data were also available. Firstly, we performed a non-parametric Homozygosity Haplotype analysis for identifying the Region from Common Ancestor (RCA). Then, on these potential disease-linked RCA, we searched for the presence of rare variants shared by the affected individuals by analyzing WES data. We found: (i) a variant (43181034 T > G) in the splicing region on exon 27 of CUL9; (ii) a variant (50245517 A > C) in the splicing region on exon 16 of ATP9A; (iii) a non-synonymous variant (43223539 A > C), on exon 9 of TTBK1; (iv) a non-synonymous variant (42976917 A > C) on exon 9 of PPP2R5D; and v) a variant (109859349-109859354) in 3′UTR of MYO16.     

Whole Exome Sequencing of Distant Relatives in Multiplex Families Implicates Rare Variants in Candidate Genes for Oral Clefts

A dozen genes/regions have been confirmed as genetic risk factors for oral clefts in human association and linkage studies, and animal models argue even more genes may be involved. Genomic sequencing studies should identify specific causal variants and may reveal additional genes as influencing risk to oral clefts, which have a complex and heterogeneous etiology. We conducted a whole exome sequencing (WES) study to search for potentially causal variants using affected relatives drawn from multiplex cleft families. Two or three affected second, third, and higher degree relatives from 55 multiplex families were sequenced. We examined rare single nucleotide variants (SNVs) shared by affected relatives in 348 recognized candidate genes. Exact probabilities that affected relatives would share these rare variants were calculated, given pedigree structures, and corrected for the number of variants tested. Five novel and potentially damaging SNVs shared by affected distant relatives were found and confirmed by Sanger sequencing. One damaging SNV in CDH1, shared by three affected second cousins from a single family, attained statistical significance (P = 0.02 after correcting for multiple tests). Family-based designs such as the one used in this WES study offer important advantages for identifying genes likely to be causing complex and heterogeneous disorders.     

Whole-Exome Sequencing Reveals a Rapid Change in the Frequency of Rare Functional Variants in a Founding Population of Humans

Whole-exome or gene targeted resequencing in hundreds to thousands of individuals has shown that the majority of genetic variants are at low frequency in human populations. Rare variants are enriched for functional mutations and are expected to explain an important fraction of the genetic etiology of human disease, therefore having a potential medical interest. In this work, we analyze the whole-exome sequences of French-Canadian individuals, a founder population with a unique demographic history that includes an original population bottleneck less than 20 generations ago, followed by a demographic explosion, and the whole exomes of French individuals sampled from France. We show that in less than 20 generations of genetic isolation from the French population, the genetic pool of French-Canadians shows reduced levels of diversity, higher homozygosity, and an excess of rare variants with low variant sharing with Europeans. Furthermore, the French-Canadian population contains a larger proportion of putatively damaging functional variants, which could partially explain the increased incidence of genetic disease in the province. Our results highlight the impact of population demography on genetic fitness and the contribution of rare variants to the human genetic variation landscape, emphasizing the need for deep cataloguing of genetic variants by resequencing worldwide human populations in order to truly assess disease risk.     

A Cytogenetic Abnormality and Rare Coding Variants Identify ABCA13 as a Candidate Gene in Schizophrenia, Bipolar Disorder, and Depression

Schizophrenia and bipolar disorder are leading causes of morbidity across all populations, with heritability estimates of ∼80% indicating a substantial genetic component. Population genetics and genome-wide association studies suggest an overlap of genetic risk factors between these illnesses but it is unclear how this genetic component is divided between common gene polymorphisms, rare genomic copy number variants, and rare gene sequence mutations. We report evidence that the lipid transporter gene ABCA13 is a susceptibility factor for both schizophrenia and bipolar disorder. After the initial discovery of its disruption by a chromosome abnormality in a person with schizophrenia, we resequenced ABCA13 exons in 100 cases with schizophrenia and 100 controls. Multiple rare coding variants were identified including one nonsense and nine missense mutations and compound heterozygosity/homozygosity in six cases. Variants were genotyped in additional schizophrenia, bipolar, depression (n > 1600), and control (n > 950) cohorts and the frequency of all rare variants combined was greater than controls in schizophrenia (OR = 1.93, p = 0.0057) and bipolar disorder (OR = 2.71, p = 0.00007). The population attributable risk of these mutations was 2.2% for schizophrenia and 4.0% for bipolar disorder. In a study of 21 families of mutation carriers, we genotyped affected and unaffected relatives and found significant linkage (LOD = 4.3) of rare variants with a phenotype including schizophrenia, bipolar disorder, and major depression. These data identify a candidate gene, highlight the genetic overlap between schizophrenia, bipolar disorder, and depression, and suggest that rare coding variants may contribute significantly to risk of these disorders.     

Contextual Social Cognition Impairments in Schizophrenia and Bipolar Disorder

Background

The ability to integrate contextual information with social cues to generate social meaning is a key aspect of social cognition. It is widely accepted that patients with schizophrenia and bipolar disorders have deficits in social cognition; however, previous studies on these disorders did not use tasks that replicate everyday situations.

Methodology/Principal Findings

This study evaluates the performance of patients with schizophrenia and bipolar disorders on social cognition tasks (emotional processing, empathy, and social norms knowledge) that incorporate different levels of contextual dependence and involvement of real-life scenarios. Furthermore, we explored the association between social cognition measures, clinical symptoms and executive functions. Using a logistic regression analysis, we explored whether the involvement of more basic skills in emotional processing predicted performance on empathy tasks. The results showed that both patient groups exhibited deficits in social cognition tasks with greater context sensitivity and involvement of real-life scenarios. These deficits were more severe in schizophrenic than in bipolar patients. Patients did not differ from controls in tasks involving explicit knowledge. Moreover, schizophrenic patients’ depression levels were negatively correlated with performance on empathy tasks.

Conclusions/Significance

Overall performance on emotion recognition predicted performance on intentionality attribution during the more ambiguous situations of the empathy task. These results suggest that social cognition deficits could be related to a general impairment in the capacity to implicitly integrate contextual cues. Important implications for the assessment and treatment of individuals with schizophrenia and bipolar disorders, as well as for neurocognitive models of these pathologies are discussed.     

Improved Detection of Common Variants Associated with Schizophrenia and Bipolar Disorder Using Pleiotropy-Informed Conditional False Discovery Rate

Several lines of evidence suggest that genome-wide association studies (GWAS) have the potential to explain more of the “missing heritability” of common complex phenotypes. However, reliable methods to identify a larger proportion of single nucleotide polymorphisms (SNPs) that impact disease risk are currently lacking. Here, we use a genetic pleiotropy-informed conditional false discovery rate (FDR) method on GWAS summary statistics data to identify new loci associated with schizophrenia (SCZ) and bipolar disorders (BD), two highly heritable disorders with significant missing heritability. Epidemiological and clinical evidence suggest similar disease characteristics and overlapping genes between SCZ and BD. Here, we computed conditional Q–Q curves of data from the Psychiatric Genome Consortium (SCZ; n = 9,379 cases and n = 7,736 controls; BD: n = 6,990 cases and n = 4,820 controls) to show enrichment of SNPs associated with SCZ as a function of association with BD and vice versa with a corresponding reduction in FDR. Applying the conditional FDR method, we identified 58 loci associated with SCZ and 35 loci associated with BD below the conditional FDR level of 0.05. Of these, 14 loci were associated with both SCZ and BD (conjunction FDR). Together, these findings show the feasibility of genetic pleiotropy-informed methods to improve gene discovery in SCZ and BD and indicate overlapping genetic mechanisms between these two disorders.     

Novel Rare Missense Variations and Risk of Autism Spectrum Disorder: Whole-Exome Sequencing in Two Families with Affected Siblings and a Two-Stage Follow-Up Study in a Japanese Population

Rare inherited variations in multiplex families with autism spectrum disorder (ASD) are suggested to play a major role in the genetic etiology of ASD. To further investigate the role of rare inherited variations, we performed whole-exome sequencing (WES) in two families, each with three affected siblings. We also performed a two-stage follow-up case-control study in a Japanese population. WES of the six affected siblings identified six novel rare missense variations. Among these variations, CLN8 R24H was inherited in one family by three affected siblings from an affected father and thus co-segregated with ASD. In the first stage of the follow-up study, we genotyped the six novel rare missense variations identified by WES in 241 patients and 667 controls (the Niigata sample). Only CLN8 R24H had higher mutant allele frequencies in patients (1/482) compared with controls (1/1334). In the second stage, this variation was further genotyped, yet was not detected in a sample of 309 patients and 350 controls (the Nagoya sample). In the combined Niigata and Nagoya samples, there was no significant association (odds ratio = 1.8, 95% confidence interval = 0.1–29.6). These results suggest that CLN8 R24H plays a role in the genetic etiology of ASD, at least in a subset of ASD patients.     

A Genetic Deconstruction of Neurocognitive Traits in Schizophrenia and Bipolar Disorder

Background

Impairments in cognitive functions are common in patients suffering from psychiatric disorders, such as schizophrenia and bipolar disorder. Cognitive traits have been proposed as useful for understanding the biological and genetic mechanisms implicated in cognitive function in healthy individuals and in the dysfunction observed in psychiatric disorders.

Methods

Sets of genes associated with a range of cognitive functions often impaired in schizophrenia and bipolar disorder were generated from a genome-wide association study (GWAS) on a sample comprising 670 healthy Norwegian adults who were phenotyped for a broad battery of cognitive tests. These gene sets were then tested for enrichment of association in GWASs of schizophrenia and bipolar disorder. The GWAS data was derived from three independent single-centre schizophrenia samples, three independent single-centre bipolar disorder samples, and the multi-centre schizophrenia and bipolar disorder samples from the Psychiatric Genomics Consortium.

Results

The strongest enrichments were observed for visuospatial attention and verbal abilities sets in bipolar disorder. Delayed verbal memory was also enriched in one sample of bipolar disorder. For schizophrenia, the strongest evidence of enrichment was observed for the sets of genes associated with performance in a colour-word interference test and for sets associated with memory learning slope.

Conclusions

Our results are consistent with the increasing evidence that cognitive functions share genetic factors with schizophrenia and bipolar disorder. Our data provides evidence that genetic studies using polygenic and pleiotropic models can be used to link specific cognitive functions with psychiatric disorders.     

Joint Analysis of Psychiatric Disorders Increases Accuracy of Risk Prediction for Schizophrenia,Bipolar Disorder,and Major Depressive Disorder

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.     

Common and Rare Variant Analysis in Early-Onset Bipolar Disorder Vulnerability

Bipolar disorder is one of the most common and devastating psychiatric disorders whose mechanisms remain largely unknown. Despite a strong genetic contribution demonstrated by twin and adoption studies, a polygenic background influences this multifactorial and heterogeneous psychiatric disorder. To identify susceptibility genes on a severe and more familial sub-form of the disease, we conducted a genome-wide association study focused on 211 patients of French origin with an early age at onset and 1,719 controls, and then replicated our data on a German sample of 159 patients with early-onset bipolar disorder and 998 controls. Replication study and subsequent meta-analysis revealed two genes encoding proteins involved in phosphoinositide signalling pathway (PLEKHA5 and PLCXD3). We performed additional replication studies in two datasets from the WTCCC (764 patients and 2,938 controls) and the GAIN-TGen cohorts (1,524 patients and 1,436 controls) and found nominal P-values both in the PLCXD3 and PLEKHA5 loci with the WTCCC sample. In addition, we identified in the French cohort one affected individual with a deletion at the PLCXD3 locus and another one carrying a missense variation in PLCXD3 (p.R93H), both supporting a role of the phosphatidylinositol pathway in early-onset bipolar disorder vulnerability. Although the current nominally significant findings should be interpreted with caution and need replication in independent cohorts, this study supports the strategy to combine genetic approaches to determine the molecular mechanisms underlying bipolar disorder.