The UK10K project identifies rare variants in health and disease.
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ABSTRACT:
SUBMITTER: UK10K Consortium
PROVIDER: S-EPMC4773891 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Deep vein thrombosis and pulmonary embolism, collectively defined as venous thromboembolism (VTE), are the third leading cause of cardiovascular death in the United States. Common genetic variants conferring increased varying degrees of VTE risk have been identified by genome-wide association studies (GWAS). Rare mutations in the anticoagulant genes PROC, PROS1 and SERPINC1 result in perinatal lethal thrombosis in homozygotes and markedly increased VTE risk in heterozygotes. However, currently described VTE variants account for an insufficient portion of risk to be routinely used for clinical decision making. To identify new rare VTE risk variants, we performed a whole-exome study of 393 individuals with unprovoked VTE and 6114 controls. This study identified 4 genes harboring an excess number of rare damaging variants in patients with VTE: PROS1, STAB2, PROC, and SERPINC1. At STAB2, 7.8% of VTE cases and 2.4% of controls had a qualifying rare variant. In cell culture, VTE-associated variants of STAB2 had a reduced surface expression compared with reference STAB2. Common variants in STAB2 have been previously associated with plasma von Willebrand factor and coagulation factor VIII levels in GWAS, suggesting that haploinsufficiency of stabilin-2 may increase VTE risk through elevated levels of these procoagulants. In an independent cohort, we found higher von Willebrand factor levels and equivalent propeptide levels in individuals with rare STAB2 variants compared with controls. Taken together, this study demonstrates the utility of gene-based collapsing analyses to identify loci harboring an excess of rare variants with functional connections to a complex thrombotic disease.
| S-EPMC7393257 | biostudies-literature
Project description:Copy-number variants (CNVs) are substantial contributors to human disease. A central challenge in CNV-disease association studies is to characterize the pathogenicity of rare and possibly incompletely penetrant events, which requires the accurate detection of rare CNVs in large numbers of individuals. Cost and throughput issues limit our ability to perform these studies. We have adapted the Illumina BeadXpress SNP genotyping assay and developed an algorithm, SNP-Conditional OUTlier detection (SCOUT), to rapidly and accurately detect both rare and common CNVs in large cohorts. This approach is customizable, cost effective, highly parallelized, and largely automated. We applied this method to screen 69 loci in 1105 children with unexplained intellectual disability, identifying pathogenic variants in 3.1% of these individuals and potentially pathogenic variants in an additional 2.3%. We identified seven individuals (0.7%) with a deletion of 16p11.2, which has been previously associated with autism. Our results widen the phenotypic spectrum of these deletions to include intellectual disability without autism. We also detected 1.65-3.4 Mbp duplications at 16p13.11 in 1.1% of affected individuals and 350 kbp deletions at 15q11.2, near the Prader-Willi/Angelman syndrome critical region, in 0.8% of affected individuals. Compared to published CNVs in controls they are significantly (P = 4.7 x 10(-5) and 0.003, respectively) enriched in these children, supporting previously published hypotheses that they are neurocognitive disease risk factors. More generally, this approach offers a previously unavailable balance between customization, cost, and throughput for analysis of CNVs and should prove valuable for targeted CNV detection in both research and diagnostic settings.
| S-EPMC2752120 | biostudies-literature
Project description:More than 1,000 susceptibility loci have been identified through genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings have not yet been defined. Here we used pooled next-generation sequencing to study 56 genes from regions associated with Crohn's disease in 350 cases and 350 controls. Through follow-up genotyping of 70 rare and low-frequency protein-altering variants in nine independent case-control series (16,054 Crohn's disease cases, 12,153 ulcerative colitis cases and 17,575 healthy controls), we identified four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association with a protective splice variant in CARD9 (P < 1 × 10(-16), odds ratio ? 0.29) and additional associations with coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by identifying new, rare and probably functional variants that could aid functional experiments and predictive models.
| S-EPMC3378381 | biostudies-literature
Project description:BACKGROUND: Multiple genes have been implicated by association studies in altering inflammatory bowel disease (IBD) predisposition. Paediatric patients often manifest more extensive disease and a particularly severe disease course. It is likely that genetic predisposition plays a more substantial role in this group. OBJECTIVE: To identify the spectrum of rare and novel variation in known IBD susceptibility genes using exome sequencing analysis in eight individual cases of childhood onset severe disease. DESIGN: DNA samples from the eight patients underwent targeted exome capture and sequencing. Data were processed through an analytical pipeline to align sequence reads, conduct quality checks, and identify and annotate variants where patient sequence differed from the reference sequence. For each patient, the entire complement of rare variation within strongly associated candidate genes was catalogued. RESULTS: Across the panel of 169 known IBD susceptibility genes, approximately 300 variants in 104 genes were found. Excluding splicing and HLA-class variants, 58 variants across 39 of these genes were classified as rare, with an alternative allele frequency of <5%, of which 17 were novel. Only two patients with early onset Crohn's disease exhibited rare deleterious variations within NOD2: the previously described R702W variant was the sole NOD2 variant in one patient, while the second patient also carried the L1007 frameshift insertion. Both patients harboured other potentially damaging mutations in the GSDMB, ERAP2 and SEC16A genes. The two patients severely affected with ulcerative colitis exhibited a distinct profile: both carried potentially detrimental variation in the BACH2 and IL10 genes not seen in other patients. CONCLUSION: For each of the eight individuals studied, all non-synonymous, truncating and frameshift mutations across all known IBD genes were identified. A unique profile of rare and potentially damaging variants was evident for each patient with this complex disease.
| S-EPMC3686259 | biostudies-other
Project description:BackgroundIn European Union countries, any disease affecting less than 5 people in 10,000 is considered rare. As expertise is scarce and rare diseases (RD) are complex, RD patients can remain undiagnosed for many years. The period of searching for a diagnosis, called diagnostic delay, sometimes leads to a diagnostic dead end when the patient's disease is impossible to diagnose after undergoing all available investigations. In recent years, extensive efforts have been made to support the implementation of ORPHA nomenclature in health information systems (HIS) so as to allow RD coding. Until recently, the nomenclature only encompassed codes for specific RD. Persons suffering from a suspected RD who could not be diagnosed even after full investigation, could not be coded with ORPHAcodes. The recognition of the RD status is necessary for patients, even if they do not have a precise diagnosis. It can facilitate reimbursement of care, be socially and psychologically empowering, and grant them access to scientific advances.ResultsThe RD-CODE project aimed at making those patients identifiable in HIS in order to produce crucial epidemiological data. Undiagnosed patients were defined as patients for whom no clinically-known disorder could be confirmed by an expert center after all reasonable efforts to obtain a diagnosis according to the state-of-the-art and diagnostic capabilities available. Three recommendations for the coding of undiagnosed RD patients were produced by a multi-stakeholder panel of experts: 1/ Capture the diagnostic ascertainment for all rare disease cases; 2/ Use the newly created ORPHAcode (ORPHA:616874 "Rare disorder without a determined diagnosis after full investigation"), available in the Orphanet nomenclature: as the code is new, guidelines are essential to ensure its correct and homogeneous use for undiagnosed patients' identification in Europe and beyond; 3/ Use additional descriptors in registries.ConclusionsThe recommendations can now be implemented in HIS (electronic health records and/or registries) and could be a game-changer for patients, clinicians and researchers in the field, enabling assessment of the RD population, including undiagnosed patients, adaptation of policy measures including financing for care and research programs, and to improved access of undiagnosed patients to research programs.
| S-EPMC10822150 | biostudies-literature
Project description:The clinical impact of rare loss-of-function variants has yet to be determined for most genes. Integration of DNA sequencing data with electronic health records (EHRs) could enhance our understanding of the contribution of rare genetic variation to human disease1. By leveraging 10,900 whole-exome sequences linked to EHR data in the Penn Medicine Biobank, we addressed the association of the cumulative effects of rare predicted loss-of-function variants for each individual gene on human disease on an exome-wide scale, as assessed using a set of diverse EHR phenotypes. After discovering 97 genes with exome-by-phenome-wide significant phenotype associations (P < 10-6), we replicated 26 of these in the Penn Medicine Biobank, as well as in three other medical biobanks and the population-based UK Biobank. Of these 26 genes, five had associations that have been previously reported and represented positive controls, whereas 21 had phenotype associations not previously reported, among which were genes implicated in glaucoma, aortic ectasia, diabetes mellitus, muscular dystrophy and hearing loss. These findings show the value of aggregating rare predicted loss-of-function variants into 'gene burdens' for identifying new gene-disease associations using EHR phenotypes in a medical biobank. We suggest that application of this approach to even larger numbers of individuals will provide the statistical power required to uncover unexplored relationships between rare genetic variation and disease phenotypes.
| S-EPMC8775355 | biostudies-literature
Project description:BackgroundAlthough an increasing number of common variants contributing to Alzheimer's disease (AD) are uncovered by genome-wide association studies, they can only explain less than half of the heritability of AD. Rare variant association studies (RVAS) has become an increasingly important area to explain the risk or trait variability of AD.MethodTo investigate the potential rare variants that cause AD, we screened 70,209 rare variants from two cohorts of a 175 AD cohort and a 214 cognitively normal cohort from the Alzheimer's Disease Neuroimaging Initiative database. MIRARE, a novel RVAS method, was performed on 232 non-synonymous variants selected by ANNOVAR annotation. Molecular docking and molecular dynamics (MD) simulation were adopted to verify the interaction between the chosen functional variants and BACE1.ResultsMIRAGE analysis revealed significant associations between AD and six potential pathogenic genes, including PREX2, FLG, DHX16, NID2, ZnF585B and ZnF875. Only interactions between FLG (including wild type and rs3120654(SER742TYR)) and BACE1 were verified by molecular docking and MD simulation. The interaction of FLG(SER742TYR) with BACE1 was greater than that of wildtype FLG with BACE1.ConclusionsAccording to the literature search, bio-informatics analysis, and molecular docking and MD simulation, we find non-synonymous rare variants in six genes, especially FLG(rs3120654), that may play key roles in AD.
| S-EPMC9141140 | biostudies-literature
Project description:MotivationNon-coding rare variants (RVs) may contribute to Mendelian disorders but have been challenging to study due to small sample sizes, genetic heterogeneity and uncertainty about relevant non-coding features. Previous studies identified RVs associated with expression outliers, but varying outlier definitions were employed and no comprehensive open-source software was developed.ResultsWe developed Outlier-RV Enrichment (ORE) to identify biologically-meaningful non-coding RVs. We implemented ORE combining whole-genome sequencing and cardiac RNAseq from congenital heart defect patients from the Pediatric Cardiac Genomics Consortium and deceased adults from Genotype-Tissue Expression. Use of rank-based outliers maximized sensitivity while a most extreme outlier approach maximized specificity. Rarer variants had stronger associations, suggesting they are under negative selective pressure and providing a basis for investigating their contribution to Mendelian disorders.Availability and implementationORE, source code, and documentation are available at https://pypi.python.org/pypi/ore under the MIT license.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC6792115 | biostudies-literature
Project description:Alzheimer's disease (AD), the leading cause of dementia, has an estimated heritability of approximately 70%1. The genetic component of AD has been mainly assessed using genome-wide association studies, which do not capture the risk contributed by rare variants2. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals-16,036 AD cases and 16,522 controls. Next to variants in TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Additionally, the rare-variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential drivers of respective AD-genome-wide association study loci. Variants associated with the strongest effect on AD risk, in particular loss-of-function variants, are enriched in early-onset AD cases. Our results provide additional evidence for a major role for amyloid-β precursor protein processing, amyloid-β aggregation, lipid metabolism and microglial function in AD.
| S-EPMC9729101 | biostudies-literature
Project description:UnlabelledCancer genome characterization efforts now provide an initial view of the somatic alterations in primary tumors. However, most point mutations occur at low frequency, and the function of these alleles remains undefined. We have developed a scalable systematic approach to interrogate the function of cancer-associated gene variants. We subjected 474 mutant alleles curated from 5,338 tumors to pooled in vivo tumor formation assays and gene expression profiling. We identified 12 transforming alleles, including two in genes (PIK3CB, POT1) that have not been shown to be tumorigenic. One rare KRAS allele, D33E, displayed tumorigenicity and constitutive activation of known RAS effector pathways. By comparing gene expression changes induced upon expression of wild-type and mutant alleles, we inferred the activity of specific alleles. Because alleles found to be mutated only once in 5,338 tumors rendered cells tumorigenic, these observations underscore the value of integrating genomic information with functional studies.SignificanceExperimentally inferring the functional status of cancer-associated mutations facilitates the interpretation of genomic information in cancer. Pooled in vivo screen and gene expression profiling identified functional variants and demonstrated that expression of rare variants induced tumorigenesis. Variant phenotyping through functional studies will facilitate defining key somatic events in cancer. Cancer Discov; 6(7); 714-26. ©2016 AACR.See related commentary by Cho and Collisson, p. 694This article is highlighted in the In This Issue feature, p. 681.
| S-EPMC4930723 | biostudies-literature