Rare Variant Association Research Articles

Genetic parameter estimation and molecular foundation of chicken beak shape

The bird beak is mainly functioned as feeding and attacking, and its shape has extremely important significance for survival and reproduction. In chickens, since beak shape could lead to some disadvantages including pecking and waste of feed, it is important to understand the inheritance of chicken beak shape. In the present study, we firstly established 4 indicators to describe the chicken beak shapes, including upper beak length (UL), lower beak length (LL), distance between upper and lower beak tips (DB) and upper beak curvature (BC). And then, we measured the 4 beak shape indicators as well as some production traits including body weight (BW), shank length (SL), egg weight (EW), eggshell strength (ES) of a layer breed, Rhode Island Red (RIR), in order to estimate genetic parameters of chicken beak shape. The heritabilities of UL and LL were 0.41 and 0.37, and the heritabilities of DB and BC were 0.22 and 0.21, indicating that beak shape was a highly or mediumly heritable. There were significant positive genetic and phenotypic correlations among UL, LL, and DB. And UL was positively correlated with body weight (BW18) and shank length (SL18) at 18 weeks of age in genetics, and DB was positively correlated with BC in terms of genetics and phenotype. We also found that layers of chicken cages played a role on beak shape, which could be attributed to the difference of lightness in different cage layers. By a genome-wide association study (GWAS) for the chicken UL, we identified 9 significant candidate genes associated with UL in RIR. For the variants with low minor allele frequencies (MAF <0.01) and outside of high linkage disequilibrium (LD) regions, we also conducted rare variant association studies (RVA) and GWAS to find the association between genotype and phenotype. We also analyzed transcriptomic data from multiple tissues of chicken embryos and revealed that all of the 9 genes were highly expressed in beak of chicken embryos, indicating their potential function for beak development. Our results provided the genetic foundation of chicken beak shape, which could help chicken breeding on beak related traits.

Association of Rare NOTCH3 Variants With Prevalent and Incident Stroke and Dementia in the General Population.

It is uncertain whether rare NOTCH3 variants are associated with stroke and dementia in the general population and whether they lead to alterations in cognitive function. This study aims to determine the associations of rare NOTCH3 variants with prevalent and incident stroke and dementia, as well as cognitive function changes. In the prospective community-based Shunyi Study, a total of 1007 participants were included in the baseline analysis. For the follow-up analysis, 1007 participants were included in the stroke analysis, and 870 participants in the dementia analysis. All participants underwent baseline brain magnetic resonance imaging, carotid ultrasound, and whole exome sequencing. Rare NOTCH3 variants were defined as variants with minor allele frequency <1%. A total of 137 rare NOTCH3 carriers were enrolled in the baseline study. At baseline, rare NOTCH3 variant carriers had higher rates of stroke (8.8% versus 5.6%) and dementia (2.9% versus 0.8%) compared with noncarriers. After adjustment for associated risk factors, the epidermal growth factor-like repeats (EGFr)-involving rare NOTCH3 variants were associated with a higher risk of prevalent stroke (odds ratio [OR], 2.697 [95% CI, 1.266-5.745]; P=0.040) and dementia (OR, 8.498 [95% CI, 1.727-41.812]; P=0.032). After 5 years of follow-up, we did not find that the rare NOTCH3 variants increased the risk of incident stroke and dementia. There was no statistical difference in the change in longitudinal cognitive scale scores. Rare NOTCH3 EGFr-involving variants are genetic risk factors for stroke and dementia in the general Chinese population.

Genetic architecture and biology of youth-onset type 2 diabetes

The prevalence of youth-onset type 2 diabetes (T2D) and childhood obesity has been rising steadily1, producing a growing public health concern1 that disproportionately affects minority groups2. The genetic basis of youth-onset T2D and its relationship to other forms of diabetes are unclear3. Here we report a detailed genetic characterization of youth-onset T2D by analysing exome sequences and common variant associations for 3,005 individuals with youth-onset T2D and 9,777 adult control participants matched for ancestry, including both males and females. We identify monogenic diabetes variants in 2.4% of individuals and three exome-wide significant (P < 2.6 × 10−6) gene-level associations (HNF1A, MC4R, ATXN2L). Furthermore, we report rare variant association enrichments within 25 gene sets related to obesity, monogenic diabetes and β-cell function. Many youth-onset T2D associations are shared with adult-onset T2D, but genetic risk factors of all frequencies—and rare variants in particular—are enriched within youth-onset T2D cases (5.0-fold increase in the rare variant and 3.4-fold increase in common variant genetic liability relative to adult-onset cases). The clinical presentation of participants with youth-onset T2D is influenced in part by the frequency of genetic risk factors within each individual. These findings portray youth-onset T2D as a heterogeneous disease situated on a spectrum between monogenic diabetes and adult-onset T2D.

Investigation of Genetic Alterations Associated With Interval Breast Cancer

Breast cancers (BCs) diagnosed between 2 screening examinations are called interval cancers (ICs), and they have worse clinicopathological characteristics and poorer prognosis than screen-detected cancers (SDCs). However, the association of rare germline genetic variants with IC have not been studied. To evaluate whether rare germline deleterious protein-truncating variants (PTVs) can be applied to discriminate between IC and SDC while considering mammographic density. This population-based genetic association study was based on women aged 40 to 76 years who were attending mammographic screening in Sweden. All women with a diagnosis of BC between January 2001 and January 2016 were included, together with age-matched controls. Patients with BC were followed up for survival until 2021. Statistical analysis was performed from September 2021 to December 2022. Germline PTVs in 34 BC susceptibility genes as analyzed by targeted sequencing. Odds ratios (ORs) were used to compare IC with SDC using logistic regression. Hazard ratios were used to investigate BC-specific survival using Cox regression. All 4121 patients with BC (IC, n = 1229; SDC, n = 2892) were female, with a mean (SD) age of 55.5 (7.1) years. There were 5631 age-matched controls. The PTVs of the ATM, BRCA1, BRCA2, CHEK2, and PALB2 genes were more common in patients with IC compared with SDC (OR, 1.48; 95% CI, 1.06-2.05). This association was primarily influenced by BRCA1/2 and PALB2 variants. A family history of BC together with PTVs of any of these genes synergistically increased the probability of receiving a diagnosis of IC rather than SDC (OR, 3.95; 95% CI, 1.97-7.92). Furthermore, 10-year BC-specific survival revealed that if a patient received a diagnosis of an IC, carriers of PTVs in any of these 5 genes had significantly worse survival compared with patients not carrying any of them (hazard ratio, 2.04; 95% CI, 1.06-3.92). All of these associations were further pronounced in a subset of patients with IC who had a low mammographic density at prior screening examination. The results of this study may be helpful in future optimizations of screening programs that aim to lower mortality as well as the clinical treatment of patients with BC.

Inherited blood cancer predisposition through altered transcription elongation

Despite advances in defining diverse somatic mutations that cause myeloid malignancies, a significant heritable component for these cancers remains largely unexplained. Here, we perform rare variant association studies in a large population cohort to identify inherited predisposition genes for these blood cancers. CTR9, which encodes a key component of the PAF1 transcription elongation complex, is among the significant genes identified. The risk variants found in the cases cause loss of function and result in a ∼10-fold increased odds of acquiring a myeloid malignancy. Partial CTR9 loss of function expands human hematopoietic stem cells (HSCs) by increased super elongation complex-mediated transcriptional activity, which thereby increases the expression of key regulators of HSC self-renewal. By following up on insights from a human genetic study examining inherited predisposition to the myeloid malignancies, we define a previously unknown antagonistic interaction between the PAF1 and super elongation complexes. These insights could enable targeted approaches for blood cancer prevention.

Ultra-rare genetic variation in relapsing polychondritis: a whole-exome sequencing study

ObjectiveRelapsing polychondritis (RP) is a systemic inflammatory disease of unknown aetiology. The objective of this study was to examine the contribution of rare genetic variations to RP.MethodsWe performed a case–control...

Rare copy-number variants as modulators of common disease susceptibility

BackgroundCopy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described.MethodsAssessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank.ResultsWe identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs—and especially deletions—strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS.ConclusionsOur results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.

Examining the Association of Rare Allelic Variants in Urate Transporters SLC22A11, SLC22A13, and SLC17A1 with Hyperuricemia and Gout.

Genetic variations in urate transporters play a significant role in determining human urate levels and have been implicated in developing hyperuricemia or gout. Polymorphism in the key urate transporters, such as ABCG2, URAT1, or GLUT9 was well-documented in the literature. Therefore in this study, our objective was to determine the frequency and effect of rare nonsynonymous allelic variants of SLC22A11, SLC22A13, and SLC17A1 on urate transport. In a cohort of 150 Czech patients with primary hyperuricemia and gout, we examined all coding regions and exon-intron boundaries of SLC22A11, SLC22A13, and SLC17A1 using PCR amplification and Sanger sequencing. For comparison, we used a control group consisting of 115 normouricemic subjects. To examine the effects of the rare allelic nonsynonymous variants on the expression, intracellular processing, and urate transporter protein function, we performed a functional characterization using the HEK293A cell line, immunoblotting, fluorescent microscopy, and site directed mutagenesis for preparing variants in vitro. Variants p.V202M (rs201209258), p.R343L (rs75933978), and p.P519L (rs144573306) were identified in the SLC22A11 gene (OAT4 transporter); variants p.R16H (rs72542450), and p.R102H (rs113229654) in the SLC22A13 gene (OAT10 transporter); and the p.W75C variant in the SLC17A1 gene (NPT1 transporter). All variants minimally affected protein levels and cytoplasmic/plasma membrane localization. The functional in vitro assay revealed that contrary to the native proteins, variants p.P519L in OAT4 (p ≤ 0.05), p.R16H in OAT10 (p ≤ 0.05), and p.W75C in the NPT1 transporter (p ≤ 0.01) significantly limited urate transport activity. Our findings contribute to a better understanding of (1) the risk of urate transporter-related hyperuricemia/gout and (2) uric acid handling in the kidneys.

Prostate cancer genetic risk and associated aggressive disease in men of African ancestry

African ancestry is a significant risk factor for prostate cancer and advanced disease. Yet, genetic studies have largely been conducted outside the context of Sub-Saharan Africa, identifying 278 common risk variants contributing to a multiethnic polygenic risk score, with rare variants focused on a panel of roughly 20 pathogenic genes. Based on this knowledge, we are unable to determine polygenic risk or differentiate prostate cancer status interrogating whole genome data for 113 Black South African men. To further assess for potentially functional common and rare variant associations, here we interrogate 247,780 exomic variants for 798 Black South African men using a case versus control or aggressive versus non-aggressive study design. Notable genes of interest include HCP5, RFX6 and H3C1 for risk, and MKI67 and KLF5 for aggressive disease. Our study highlights the need for further inclusion across the African diaspora to establish African-relevant risk models aimed at reducing prostate cancer health disparities.

Association of Common and Rare Variants with Alzheimer’s Disease in 16,905 individuals with Whole‐Genome Sequence Data from the Alzheimer’s Disease Sequencing Project

AbstractBackgroundWhole genome sequencing (WGS) data enables assessment of common and rare variants for association with human diseases. Here we report our analysis using ADSP R3 WGS data to discover genetic variants associated with AD.MethodWe performed association testing of common variants (minor allele frequency [MAF] &gt; 0.5%) as well as aggregates of rare (MAF &lt; 1%) coding and non‐coding variants. Given that ADSP is composed of multiple ancestry groups, we performed association testing across all participants (pooled population [PP], Ncases = 6,519 and Ncontrol = 6,852) and within the following populations: African Americans (AA, Ncases = 1,137 and Ncontrol = 1,707), Hispanics (HIS, Ncases = 1,021 and Ncontrol = 1,988), and Non‐Hispanic White (NHW, Ncases = 4,230 and Ncontrol = 3,109) defined by self‐reported race and ethnicity (Table 1).ResultAs expected, our most significant associations are at the APOE locus (chr19:44,905,796‐44,909,393) (Figure 1). In the pooled‐population analysis, we observed known AD associations for BIN1 (p = 3.2×10−09) variants with AD status. In the NHW analysis, we observed AD associations for variants in CR1 (p = 7.97×10−08), BIN1 (p = 2.16×10−08), ARHGEF33 (p = 4.85×10−8), ANK3 (p = 1.43×10−12) and MYCBP2‐AS1 (p = 4.59×10−08), and in the AA analysis, we observed a significant variant near LINC00320 (p = 1.5×10−8). In the HIS subset, a region (chr14:72,698,038‐75,846,454) has 31 significant variants (p = 3.9×10−11) crossing multiple genes. This region covers PSEN1 G206A (rs63750082), a well‐known early‐onset AD mutation. Local‐ancestry analysis shows that the mutations, including G206A, are of African ancestry. Using kinship coefficients calculated within this dataset, it was determined that the signals are not driven by a familial linkage disequilibrium.We observed gene‐based aggregation of coding variants in PSEN1 in the pooled‐population and HIS analyses (p&lt;5×10−8) (Figure 2). In our gene‐centric noncoding aggregates analysis, we identified noncoding variants in the promotor of TOMM40 in the pooled‐population analysis (p = 7.2×10−08). After adjusting for APOE e4 (rs429358) and e2 (rs7412) alleles, there was an attenuation, but the association remained suggestive (p = 7.1×10−06).ConclusionWe performed common and rare association analysis of AD on ADSP WGS data. We observed associations with variants in known AD loci. We also observed population‐specific associations and an association of AD with rare noncoding variants in TOMM40, indicating WGS in diverse populations can lead to novel genetic associations with AD.

A phenome-wide scan reveals convergence of common and rare variant associations

BackgroundCommon and rare variants contribute to the etiology of complex traits. However, the extent to which the phenotypic effects of common and rare variants involve shared molecular mediators remains poorly understood. The question is essential to the basic and translational goals of the science of genomics, with critical basic-science, methodological, and clinical consequences.MethodsLeveraging the latest release of whole-exome sequencing (WES, for rare variants) and genome-wide association study (GWAS, for common variants) data from the UK Biobank, we developed a metric, the COmmon variant and RAre variant Convergence (CORAC) signature, to quantify the convergence for a broad range of complex traits. We characterized the relationship between CORAC and effective sample size across phenome-wide association studies.ResultsWe found that the signature is positively correlated with effective sample size (Spearman ρ = 0.594, P < 2.2e − 16), indicating increased functional convergence of trait-associated genetic variation, across the allele frequency spectrum, with increased power. Sensitivity analyses, including accounting for heteroskedasticity and varying the number of detected association signals, further strengthened the validity of the finding. In addition, consistent with empirical data, extensive simulations showed that negative selection, in line with enhancing polygenicity, has a dampening effect on the convergence signature. Methodologically, leveraging the convergence leads to enhanced association analysis.ConclusionsThe presented framework for the convergence signature has important implications for fine-mapping strategies and drug discovery efforts. In addition, our study provides a blueprint for the expectation from future large-scale whole-genome sequencing (WGS)/WES and sheds methodological light on post-GWAS studies.

Type 2 Diabetes Modifies the Association of CAD Genomic Risk Variants With Subclinical Atherosclerosis.

Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D. We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test. Using a Bonferroni-corrected significance threshold of P<1.6×10-4, we identified 3 genes (ATP1B1, ARVCF, and LIPG) associated with CAC and 2 genes (ABCG8 and EIF2B2) associated with carotid intima-media thickness and carotid plaque, respectively, through gene-based rare variant set analysis. Both ATP1B1 and ARVCF also had significantly different associations for CAC in T2D cases versus controls. No significant interaction tests were identified through the candidate single-variant analysis. These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC.

DYNATE: Localizing rare-variant association regions via multiple testing embedded in an aggregation tree.

Rare-variants (RVs) genetic association studies enable researchers to uncover the variation in phenotypic traits left unexplained by common variation. Traditional single-variant analysis lacks power; thus, researchers have developed various methods to aggregate the effects of RVs across genomic regions to study their collective impact. Some existing methods utilize a static delineation of genomic regions, often resulting in suboptimal effect aggregation, as neutral subregions within the test region will result in an attenuation of signal. Other methods use varying windows to search for signals but often result in long regions containing many neutral RVs. To pinpoint short genomic regions enriched for disease-associated RVs, we developed a novel method, DYNamic Aggregation TEsting (DYNATE). DYNATE dynamically and hierarchically aggregates smaller genomic regions into larger ones and performs multiple testing for disease associations with a controlled weighted false discovery rate. DYNATE's main advantage lies in its strong ability to identify short genomic regions highly enriched for disease-associated RVs. Extensive numerical simulations demonstrate the superior performance of DYNATE under various scenarios compared with existing methods. We applied DYNATE to an amyotrophic lateral sclerosisstudy and identified a new gene, EPG5, harboring possibly pathogenic mutations.

Whole Genome Sequencing Identifies Novel Common and Low-Frequency Variants Associated With Age-Related Macular Degeneration.

To identify associations of common, low-frequency, and rare variants with advanced age-related macular degeneration (AMD) using whole genome sequencing (WGS). WGS data were obtained for 2123 advanced AMD patients (participants of clinical trials for advanced AMD) and 2704 controls (participants of clinical trials for asthma [N = 2518] and Alzheimer's disease [N = 186]), and joint genotype calling was performed, followed by quality control of the dataset. Single variant association analyses were performed for all identified common, low-frequency, and rare variants. Gene-based tests were executed for rare and low-frequency variants using SKAT-O and three groups of variants based on putative impact information: (1) all variants, (2) modifier impact variants, and (3) high- and moderate-impact variants. To ascertain independence of the identified associations from previously reported AMD and asthma loci, conditional analyses were performed. Previously identified AMD variants at the CFH, ARMS2/HTRA1, APOE, and C3 loci were associated with AMD at a genome-wide significance level. We identified new single variant associations for common variants near the PARK7 gene and in the long non-coding RNA AC103876.1, and for a rare variant near the TENM3 gene. In addition, gene-based association analyses identified a burden of modifier variants in eight intergenic and gene-spanning regions and of high- and moderate-impact variants in the C3, CFHR5, SLC16A8, and CFI genes. We describe the largest WGS study in AMD to date. We confirmed previously identified associations and identified several novel associations that are worth exploring in further follow-up studies.

The burden of rare variants in DPYS gene is a novel predictor of the risk of developing severe fluoropyrimidine-related toxicity

BackgroundDespite a growing number of publications highlighting the potential impact on the therapy outcome, rare genetic variants (minor allele frequency < 1%) in genes associated to drug adsorption, distribution, metabolism, and elimination are poorly studied. Previously, rare germline DPYD missense variants were shown to identify a subset of fluoropyrimidine-treated patients at high risk for severe toxicity. Here, we investigate the impact of rare genetic variants in a panel of 54 other fluoropyrimidine-related genes on the risk of severe toxicity.MethodsThe coding sequence and untranslated regions of 54 genes related to fluoropyrimidine pharmacokinetics/pharmacodynamics were analyzed by next-generation sequencing in 120 patients developing grade 3–5 toxicity (NCI-CTC vs3.0) and 104 matched controls. Sequence Kernel Association Test (SKAT) analysis was used to select genes with a burden of genetic variants significantly associated with risk of severe toxicity. The statistical association of common and rare genetic variants in selected genes was further investigated. The functional impact of genetic variants was assessed using two different in silico prediction tools (Predict2SNP; ADME Prediction Framework).ResultsSKAT analysis highlighted DPYS and PPARD as genes with a genetic mutational burden significantly associated with risk of severe fluoropyrimidine-related toxicity (Bonferroni adjusted P = 0.024 and P = 0.039, respectively). Looking more closely at allele frequency, the burden of rare DPYS variants was significantly higher in patients with toxicity compared with controls (P = 0.047, Mann–Whitney test). Carrying at least one rare DPYS variant was associated with an approximately fourfold higher risk of severe cumulative (OR = 4.08, P = 0.030) and acute (OR = 4.21, P = 0.082) toxicity. The burden of PPARD rare genetic variants was not significantly related to toxicity. Some common variants with predictive value in DPYS and PPARD were also identified: DPYS rs143004875-T and PPARD rs2016520-T variants predicted an increased risk of severe cumulative (P = 0.002 and P = 0.001, respectively) and acute (P = 0.005 and P = 0.0001, respectively) toxicity.ConclusionThis work demonstrated that the rare mutational burden of DPYS, a gene strictly cooperating with DPYD in the catabolic pathway of fluoropyrimidines, is a promising pharmacogenetic marker for precision dosing of fluoropyrimidines. Additionally, some common genetic polymorphisms in DPYS and PPARD were identified as promising predictive markers that warrant further investigation.

Whole genome sequencing of 4,787 individuals identifies gene-based rare variants in age-related macular degeneration.

Genome-wide association studies have contributed extensively to the discovery of disease-associated common variants. However, the genetic contribution to complex traits is still largely difficult to interpret. We report a genome-wide association study of 2394 cases and 2393 controls for age-related macular degeneration (AMD) via whole-genome sequencing, with 46.9 million genetic variants. Our study reveals significant single-variant association signals at four loci and independent gene-based signals in CFH, C2, C3, and NRTN. Using data from the Exome Aggregation Consortium (ExAC) for a gene-based test, we demonstrate an enrichment of predicted rare loss-of-function variants in CFH, CFI, and an as-yet unreported gene in AMD, ORMDL2. Our method of using a large variant list without individual-level genotypes as an external reference provides a flexible and convenient approach to leverage the publicly available variant datasets to augment the search for rare variant associations, which can explain additional disease risk in AMD.

RAVAR: a curated repository for rare variant-trait associations.

Rare variants contribute significantly to the genetic causes of complex traits, as they can have much larger effects than common variants and account for much of the missing heritability in genome-wide association studies. The emergence of UK Biobank scale datasets and accurate gene-level rare variant-trait association testing methods have dramatically increased the number of rare variant associations that have been detected. However, no systematic collection of these associations has been carried out to date, especially at the gene level. To address the issue, we present the Rare Variant Association Repository (RAVAR), a comprehensive collection of rare variant associations. RAVAR includes 95047 high-quality rare variant associations (76186 gene-level and 18861 variant-level associations) for 4429 reported traits which are manually curated from 245 publications. RAVAR is the first resource to collect and curate published rare variant associations in an interactive web interface with integrated visualization, search, and download features. Detailed gene and SNP information are provided for each association, and users can conveniently search for related studies by exploring the EFO tree structure and interactive Manhattan plots. RAVAR could vastly improve the accessibility of rare variant studies. RAVAR is freely available for all users without login requirement at http://www.ravar.bio.

A novel rare variants association test for binary traits in family-based designs via copulas.

With the cost-effectiveness technology in whole-genome sequencing, more sophisticated statistical methods for testing genetic association with both rare and common variants are being investigated to identify the genetic variation between individuals. Several methods which group variants, also called gene-based approaches, are developed. For instance, advanced extensions of the sequence kernel association test, which is a widely used variant-set test, have been proposed for unrelated samples and extended for family data. Family data have been shown to be powerful when analyzing rare variants. However, most of such methods capture familial relatedness using a random effect component within the generalized linear mixed model framework. Therefore, there is a need to develop unified and flexible methods to study the association between a set of genetic variants and a trait, especially for a binary outcome. Copulas are multivariate distribution functions with uniform margins on the interval and they provide suitable models to capture familial dependence structure. In this work, we propose a flexible family-based association test for both rare and common variants in the presence of binary traits. The method, termed novel rare variant association test (NRVAT), uses a marginal logistic model and a Gaussian Copula. The latter is employed to model the dependence between relatives. An analytic score-type test is derived. Through simulations, we show that our method can achieve greater power than existing approaches. The proposed model is applied to investigate the association between schizophrenia and bipolar disorder in a family-based cohort consisting of 17 extended families from Eastern Quebec.

Learning the kernel for rare variant genetic association test.

Introduction: Compared to Genome-Wide Association Studies (GWAS) for common variants, single-marker association analysis for rare variants is underpowered. Set-based association analyses for rare variants are powerful tools that capture some of the missing heritability in trait association studies. Methods: We extend the convex-optimized SKAT (cSKAT) test set procedure which learns from data the optimal convex combination of kernels, to the full Generalised Linear Model (GLM) setting with arbitrary non-genetic covariates. We call this extended cSKAT (ecSKAT) and show that the resulting optimization problem is a quadratic programming problem that can be solved with no additional cost compared to cSKAT. Results: We show that a modified objective is related to an upper bound for the p-value through a decreasing exponential term in the objective function, indicating that optimizing this objective function is a principled way of learning the combination of kernels. We evaluate the performance of the proposed method on continuous and binary traits using simulation studies and illustrate its application using UK Biobank Whole Exome Sequencing data on hand grip strength and systemic lupus erythematosus rare variant association analysis. Discussion: Our proposed ecSKAT method enables correcting for important confounders in association studies such as age, sex or population structure for both quantitative and binary traits. Simulation studies showed that ecSKAT can recover sensible weights and achieve higher power across different sample sizes and misspecification settings. Compared to the burden test and SKAT method, ecSKAT gives a lower p-value for the genes tested in both quantitative and binary traits in the UKBiobank cohort.

Rare variant associations with plasma protein levels in the UK Biobank

Integrating human genomics and proteomics can help elucidate disease mechanisms, identify clinical biomarkers and discover drug targets1–4. Because previous proteogenomic studies have focused on common variation via genome-wide association studies, the contribution of rare variants to the plasma proteome remains largely unknown. Here we identify associations between rare protein-coding variants and 2,923 plasma protein abundances measured in 49,736 UK Biobank individuals. Our variant-level exome-wide association study identified 5,433 rare genotype–protein associations, of which 81% were undetected in a previous genome-wide association study of the same cohort5. We then looked at aggregate signals using gene-level collapsing analysis, which revealed 1,962 gene–protein associations. Of the 691 gene-level signals from protein-truncating variants, 99.4% were associated with decreased protein levels. STAB1 and STAB2, encoding scavenger receptors involved in plasma protein clearance, emerged as pleiotropic loci, with 77 and 41 protein associations, respectively. We demonstrate the utility of our publicly accessible resource through several applications. These include detailing an allelic series in NLRC4, identifying potential biomarkers for a fatty liver disease-associated variant in HSD17B13 and bolstering phenome-wide association studies by integrating protein quantitative trait loci with protein-truncating variants in collapsing analyses. Finally, we uncover distinct proteomic consequences of clonal haematopoiesis (CH), including an association between TET2-CH and increased FLT3 levels. Our results highlight a considerable role for rare variation in plasma protein abundance and the value of proteogenomics in therapeutic discovery.