Genetic Linkage for Bipolar Disorder to the Distal Region of Chromosome 19q: A Large Family Whole Genome Sequencing Study.

Sequence Kernel Association Tests for the Combined Effect of Rare and Common Variants

Recent breakthroughs in next-generation sequencing technologies allow cost-effective methods for measuring a growing list of cellular properties, including DNA sequence and structural variation. Next-generation sequencing has the potential to revolutionize complex trait genetics by directly measuring common and rare genetic variants within a genome-wide context. Because for a given gene both rare and common causal variants can coexist and have independent effects on a trait, strategies that model the effects of both common and rare variants could enhance the power of identifying disease-associated genes. To date, little work has been done on integrating signals from common and rare variants into powerful statistics for finding disease genes in genome-wide association studies. In this analysis of the Genetic Analysis Workshop 17 data, we evaluate various strategies for association of rare, common, or a combination of both rare and common variants on quantitative phenotypes in unrelated individuals. We show that the analysis of common variants only using classical approaches can achieve higher power to detect causal genes than recently proposed rare variant methods and that strategies that combine association signals derived independently in rare and common variants can slightly increase the power compared to strategies that focus on the effect of either the rare variants or the common variants.

Diamonds in the Rough: Rare Variants Scratch the Surface

Response to Mitchell and Porteus.

Extending Rare-Variant Testing Strategies: Analysis of Noncoding Sequence and Imputed Genotypes

Bipolar disorder (BD) is a psychiatric condition characterized by the occurrence of at least two episodes of clinically disturbed mood including mania and depression. A vast literature describing BD studies suggests that a strong genetic contribution likely underlies this condition; heritability is estimated to be as high as 80%. Many studies have identified BD susceptibility loci, but because of the genetic and phenotypic heterogeneity observed across individuals, very few loci were subsequently replicated. Research in BD genetics to date has consisted of classical linkage or genome-wide association studies, which have identified candidate genes hypothesized to present common susceptibility variants. Although the observation of such common variants is informative, they can only explain a small fraction of the predicted BD heritability, suggesting a considerable contribution would come from rare and highly penetrant variants. We are seeking to identify such rare variants, and to increase the likelihood of being successful, we aimed to reduce the phenotypic heterogeneity factor by focusing on a well-defined subphenotype of BD: excellent response to lithium monotherapy. Our group has previously shown positive response to lithium therapy clusters in families and has a consistent clinical presentation with minimal comorbidity. To identify such rare variants, we are using a targeted exome capture and high-throughput DNA sequencing approach, and analyzing the entire coding sequences of BD affected individuals from multigenerational families. We are prioritizing rare variants with a frequency of less than 1% in the population that segregate with affected status within each family, as well as being potentially highly penetrant (e.g., protein truncating, missense, or frameshift) or functionally relevant (e.g., 3'UTR, 5'UTR, or splicing). By focusing on rare variants in a familial cohort, we hope to explain a significant portion of the missing heritability in BD, as well as to narrow our current insight on the key biochemical pathways implicated in this complex disorder.

Genome-wide association studies on bipolar disorders (BD) have revealed an additive polygenic contribution of common single-nucleotide polymorphisms (SNPs). However, these SNPs explain only 25% of the overall genetic variance and suggest a role of rare variants in BD vulnerability. Here, we combined high-throughput genotyping data and whole-exome sequencing in cohorts of individuals with BD as well as in multiplex families with a high density of affected individuals in order to determine the contribution of both common and rare variants to BD genetic vulnerability. Using polygenic risk scores (PRS), we showed a strong contribution of common polymorphisms previously associated with BD and schizophrenia (SZ) and noticed that those specifically associated with SZ contributed more in familial forms of BD than in non-familial ones. The analysis of rare damaging variants shared by affected individuals in multiplex families with BD revealed a single interaction network enriched in neuronal and developmental biological pathways, as well as in the regulation of gene expression. We identified four genes with a higher mutation rate in individuals with BD than in the general population and showed that mutations in two of them were associated with specific clinical manifestations. In addition, we showed a significant negative correlation between PRS and the number of rare damaging variants specifically in unaffected individuals of multiplex families. Altogether, our results suggest that common and rare genetic variants both contribute to the familial aggregation of BD and this genetic architecture may explain the heterogeneity of clinical manifestations in multiplex families.

Current evidence from case/control studies indicates that genetic risk for psychiatric disorders derives primarily from numerous common variants, each with a small phenotypic impact. The literature describing apparent segregation of bipolar disorder (BP) in numerous multigenerational pedigrees suggests that, in such families, large-effect inherited variants might play a greater role. To identify roles of rare and common variants on BP, we conducted genetic analyses in 26 Colombia and Costa Rica pedigrees ascertained for bipolar disorder 1 (BP1), the most severe and heritable form of BP. In these pedigrees, we performed microarray SNP genotyping of 838 individuals and high-coverage whole-genome sequencing of 449 individuals. We compared polygenic risk scores (PRS), estimated using the latest BP1 genome-wide association study (GWAS) summary statistics, between BP1 individuals and related controls. We also evaluated whether BP1 individuals had a higher burden of rare deleterious single-nucleotide variants (SNVs) and rare copy number variants (CNVs) in a set of genes related to BP1. We found that compared with unaffected relatives, BP1 individuals had higher PRS estimated from BP1 GWAS statistics (P = 0.001 ~ 0.007) and displayed modest increase in burdens of rare deleterious SNVs (P = 0.047) and rare CNVs (P = 0.002 ~ 0.033) in genes related to BP1. We did not observe rare variants segregating in the pedigrees. These results suggest that small-to-moderate effect rare and common variants are more likely to contribute to BP1 risk in these extended pedigrees than a few large-effect rare variants.

SU26 - A WHOLE GENOME SEQUENCING STUDY IDENTIFIES A RARE VARIANT IN ANK3 THAT MAY CONTRIBUTE TO BIPOLAR DISORDER

Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 individuals from 33 Andalusian BD multiplex families (166 BD, 78 major depressive disorder, 151 unaffected) as well as 438 subjects from an independent, BD case/control cohort (161 unrelated BD, 277 unrelated controls) were analysed. Polygenic risk scores (PRS) for BD, schizophrenia (SCZ), and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had higher PRS for all three psychiatric disorders than the independent controls, with BD and SCZ being significant after correction for multiple testing, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly higher BD PRS than unaffected family members and unrelated BD cases. A plausible hypothesis is that, in multiplex families with a general increase in risk for psychiatric disease, BD development is attributable to a high burden of common variants that confer a specific risk for BD. The present analyses demonstrated that common genetic risk variants for psychiatric disorders are likely to contribute to the high incidence of affective psychiatric disorders in the multiplex families. However, the PRS explained only part of the observed phenotypic variance, and rare variants might have also contributed to disease development.

Genetic studies in psychiatry have primarily focused on the effects of common genetic variants, but few have investigated the role of rare genetic variants, particularly for major depression. In order to explore the role of rare variants in the gap between estimates of single nucleotide polymorphism (SNP) heritability and twin study heritability, we examined the contribution of common and rare genetic variants to latent traits underlying psychiatric disorders using high-quality imputed genotype data from the UK Biobank. Using a pre-registered analysis, we used items from the UK Biobank Mental Health Questionnaire relevant to three psychiatric disorders: major depression (N = 134,463), bipolar disorder (N = 117,376) and schizophrenia (N = 130,013) and identified a general hierarchical factor for each that described participants’ responses. We calculated participants’ scores on these latent traits and conducted single-variant genetic association testing (MAF > 0.05%), gene-based burden testing and pathway association testing associations with these latent traits. We tested for enrichment of rare variants (MAF 0.05–1%) in genes that had been previously identified by common variant genome-wide association studies, and genes previously associated with Mendelian disorders having relevant symptoms. We found moderate genetic correlations between the latent traits in our study and case–control phenotypes in previous genome-wide association studies, and identified one common genetic variant (rs72657988, minor allele frequency = 8.23%, p = 1.01 × 10−9) associated with the general factor of schizophrenia, but no other single variants, genes or pathways passed significance thresholds in this analysis, and we did not find enrichment in previously identified genes.

SummaryBackground:Idiopathic pulmonary fibrosis (IPF) and telomere length (TL) are both strongly linked to rare and common genetic variation. Shortened TL itself may be causal for IPF. Whether rare and common variants compete or cooperate to confer genetic risk of IPF uniformly is unknown.Methods:We used whole genome sequencing (WGS) data from a discovery case-control cohort sequenced at Columbia (777 IPF, 2905 controls) and validated findings using WGS data from Trans-Omics for Precision Medicine (TOPMed, 1148 IPF, 5202 controls) and the UK Biobank (UKBB, 2739 IPF, 395331 controls). In all cohorts, we identified rare damaging variants in disease-associated genes and computed control-normalized polygenic risk scores for IPF (IPF-PRS) and telomere length (TL-PRS). Telomere length of blood leukocytes was measured using a qPCR assay for two cohorts. We determined the association of the MUC5B rs35705950 polymorphism, an IPF-PRS excluding MUC5B (IPF-PRS-noMUC5B), and a TL-PRS with IPF risk in the overall cohort and in subgroups stratified by genetic endotypes (rare variant carriers, non-carriers stratified by TL cutoffs). We calculated cross-validated area under the receiver operator curve (AUC) and compared the liability of IPF explained by genetic variables.Findings:We identified independent associations between IPF risk and rare variants, the MUC5B SNP, and both polygenic scores in the discovery cohort and replicated these findings in the TOPMed and UKBB cohorts. The adjusted effect size of the TL-PRS, which includes >180 SNPs not previously associated with IPF, was comparable to the IPF-PRS-noMUC5B in the discovery (ORTL-PRS 1.63 [95% CI 1.47, 1.81] vs. ORIPF-PRS 1.60 [1.44, 1.77]) and replication cohorts (TOPMed ORTL-PRS 1.47 [1.36, 1.59] vs. ORIPF-PRS 1.37 [1.25, 1.50]; UKBB ORTL-PRS 1.24 [1.19, 1.29] vs. ORIPF-PRS 1.25 [1.21, 1.30]). The TL-PRS incrementally improved disease prediction beyond known IPF common and rare genetic predictors and clinical variables in discovery (combined AUC: 0.89, pDelong = 0.006), TOPMed (combined AUC: 0.89, pDelong = 0.01), and UKBB cohorts (combined AUC: 0.77, pDelong = 0.03). Rare and common variants jointly contributed to genetic liability of IPF. The TL-PRS increased liability of IPF explained by 13% in the discovery cohort and 8% and 13% in the TOPMed and UKBB cohorts, respectively. In IPF subjects with damaging rare variants, the TL-PRS was consistently associated with disease risk whereas the IPF-PRS-noMUC5B was not. The TL-PRS also conferred nominally greater odds of disease risk than the IPF-PRS-noMUC5B in patients with shorter TL, in the discovery and UKBB cohorts. Together, 23–43% of IPF cases have damaging rare variants or telomeres <10th percentile, where the TL-PRS represents a major unrecognized genetic risk factor.Interpretation:Common and rare genetic variation confer context-specific genetic risk in IPF competitively and cooperatively. In contrast to known IPF common risk variants, the TL-PRS, which includes >180 genetic loci not previously associated with IPF, increases the risk of disease specifically in certain IPF endotypes. Polygenic risk from telomere-associated common variants is a key feature of IPF genetic heterogeneity.Funding:National Institutes of Health (NIH), Medical Research Council (MRC), National Institute for Health and Care Research (NIHR)

Idiopathic pulmonary fibrosis (IPF) and telomere length are both strongly linked to rare and common genetic variants. Shortened telomere length might itself be causal for IPF. We aimed to evaluate whether rare and common variants compete or cooperate to confer genetic risk of IPF uniformly. In this genetic analysis, we used whole-genome sequencing (WGS) data from a discovery case-control cohort sequenced at Columbia University and validated findings using WGS data from Trans-Omics for Precision Medicine (TOPMed) and UK Biobank. In all cohorts, we identified rare damaging variants in disease-associated genes and computed control-normalised non-overlapping polygenic risk scores (PRS) for IPF and telomere length. We assessed the MUC5B rs35705950 single-nucleotide polymorphism (SNP), an IPF common risk variant with a large effect, independently from the polygenic scores. Telomere length in blood leukocytes was measured using a quantitative PCR assay for the discovery cohort and UK Biobank validation cohort. We conducted logistic regression (adjusting for age, sex, and principal components of ancestry) to evaluate the association between IPF risk and the MUC5B SNP, the IPF PRS excluding MUC5B (IPF-PRS-noMUC5B), and the PRS for telomere length in the overall cohort and analysed their effects in patient subgroups for IPF endotypes (carriers and non-carriers of rare variants stratified by telomere length cutoffs). To assess disease prediction, we calculated cross-validated area under the receiver operating receiver operating curve (AUC). We also compared the liability of IPF explained by genetic variables. The discovery cohort was recruited between April 23, 2003 and June 19, 2019 and included 777 patients with IPF and 2905 controls. We replicated the analyses in the TOPMed (1148 patients with IPF and 5202 controls) and UK Biobank (2739 patients with IPF and 395 331 controls) cohorts. 23-43% of patients with IPF had damaging rare variants or telomeres shorter than the tenth percentile. Analysis of the association of genetic variables with IPF diagnosis yielded odds ratios of 1·63 (95% CI 1·47-1·81) for telomere length PRS and 1·60 (1·44-1·77) for IPF-PRS-noMUC5B in the discovery cohort, with similar effect sizes for the two variables in the replication cohorts (1·47, 1·36-1·59 vs 1·37, 1·25-1·50 in TOPMed; 1·24, 1·19-1·29 vs 1·25, 1·21-1·30 in UK Biobank). The telomere length PRS had the greatest effect on disease risk in patients with IPF not harbouring rare variants and with telomere length shorter than the tenth percentile in the discovery cohort (2·02, 1·76-2·33) and UK Biobank replication cohort (1·70, 1·56-1·85). Accounting for clinical variables and all genetic variables (rare variants, MUC5B SNP, IPF PRS, and telomere length PRS) led to the best disease prediction in the discovery cohort (combined AUC 0·89), TOPMed cohort (0·89), and UK Biobank cohort (0·77). Rare and common variants contributed jointly to the genetic liability of IPF. The telomere length PRS accounted for 13% of the explained genetic liability of IPF in the discovery cohort and 8% and 13% in the TOPMed and UK Biobank cohorts, respectively. Common and rare genetic variation confer context-specific genetic risk in patients with IPF both competitively and cooperatively. In contrast to known IPF common risk variants, the telomere length PRS, which includes more than 180 genetic loci not previously associated with IPF, is associated with increased risk of disease in patients with specific IPF endotypes. Polygenic risk from telomere-associated common variants is a key feature of genetic heterogeneity in IPF. US National Institutes of Health, UK Medical Research Council, and UK National Institute for Health and Care Research.

BackgroundGenome-wide association studies (GWAS) have been used successfully in detecting associations between common genetic variants and complex diseases. However, common SNPs detected by current GWAS only explain a small proportion of heritable variability. With the development of next-generation sequencing technologies, researchers find more and more evidence to support the role played by rare variants in heritable variability. However, rare and common variants are often studied separately. The objective of this paper is to develop a robust strategy to analyze association between complex traits and genetic regions using both common and rare variants.ResultsWe propose a weighted selective collapsing strategy for both candidate gene studies and genome-wide association scans. The strategy considers genetic information from both common and rare variants, selectively collapses all variants in a given region by a forward selection procedure, and uses an adaptive weight to favor more likely causal rare variants. Under this strategy, two tests are proposed. One test denoted by BwSC is sensitive to the directions of genetic effects, and it separates the deleterious and protective effects into two components. Another denoted by BwSCd is robust in the directions of genetic effects, and it considers the difference of the two components. In our simulation studies, BwSC achieves a higher power when the casual variants have the same genetic effect, while BwSCd is as powerful as several existing tests when a mixed genetic effect exists. Both of the proposed tests work well with and without the existence of genetic effects from common variants.ConclusionsTwo tests using a weighted selective collapsing strategy provide potentially powerful methods for association studies of sequencing data. The tests have a higher power when both common and rare variants contribute to the heritable variability and the effect of common variants is not strong enough to be detected by traditional methods. Our simulation studies have demonstrated a substantially higher power for both tests in all scenarios regardless whether the common SNPs are associated with the trait or not.

The completion of the Human Genome Project has unleashed a wealth of human genomics information, but it remains unclear how best to implement this information for the benefit of patients. The standard approach of biomedical research, with researchers pursuing advances in knowledge in the laboratory and, separately, clinicians translating research findings into the clinic as much as decades later, will need to give way to new interdisciplinary models for research in genomic medicine. These models should include scientists and clinicians actively working as teams to study patients and populations recruited in clinical settings and communities to make genomics discoveries-through the combined efforts of data scientists, clinical researchers, epidemiologists, and basic scientists-and to rapidly apply these discoveries in the clinic for the prediction, prevention, diagnosis, prognosis, and treatment of cardiovascular diseases and stroke. The highly publicized US Precision Medicine Initiative, also known as All of Us, is a large-scale program funded by the US National Institutes of Health that will energize these efforts, but several ongoing studies such as the UK Biobank Initiative; the Million Veteran Program; the Electronic Medical Records and Genomics Network; the Kaiser Permanente Research Program on Genes, Environment and Health; and the DiscovEHR collaboration are already providing exemplary models of this kind of interdisciplinary work. In this statement, we outline the opportunities and challenges in broadly implementing new interdisciplinary models in academic medical centers and community settings and bringing the promise of genomics to fruition.