BackgroundGenome-wide association studies have identified several loci associated with Parkinson's disease (PD). Whole-exome sequencing detects rare coding variants, but their links with PD genome-wide association...
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BackgroundGenome-wide association studies have identified several loci associated with Parkinson's disease (PD). Whole-exome sequencing detects rare coding variants, but their links with PD genome-wide association study loci are unknown. Our objective was to investigate whether nonsynonymous variants in LRRK2 can explain associations at the PD-associated locus tagged by rs1994090. MethodsWe sequenced all coding exons of LRRK2 in 453 East Asian samples and evaluated linkage disequilibrium between each nonsynonymous variant and rs1994090. We then tested selected variants and haplotypes for association with PD in 13,581 East Asian samples. ResultsOf all the nonsynonymous variants, only ***2385Arg was in moderate linkage disequilibrium with rs1994090 and was observed on haplotypes tagged by the rs1994090-C risk allele. Conditional analyses showed that associations at these 2 variants are not independent. ConclusionsLRRK2 ***2385Arg can explain most if not all of the PD association at rs1994090 in East Asians, but other nonsynonymous variants are independent. (c) 2015 International Parkinson and Movement Disorder Society
Cancers are caused by genomic alterations that may be inherited, induced by environmental carcinogens, or caused due to random replication errors. Postinduction of carcinogenicity, mutations further propagate and dras...
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Cancers are caused by genomic alterations that may be inherited, induced by environmental carcinogens, or caused due to random replication errors. Postinduction of carcinogenicity, mutations further propagate and drastically alter the cancer genomes. Although a subset of driver mutations has been identified and characterized to date, most cancer-related somatic mutations are indistinguishable from germline variants or other noncancerous somatic mutations. Thus, such overlap impedes appreciation of many deleterious but previously uncharacterized somatic mutations. The major bottleneck arises due to patient-to-patient variability in mutational profiles, making it difficult to associate specific mutations with a given disease outcome. Here, we describe a newly developed technique Continuous Representation of Codon Switches (CRCS), a deep learning-based method that allows us to generate numerical vector representations of mutations, thereby enabling numerous machine learning-based tasks. We demonstrate three major applications of CRCS;first, we show how CRCS can help detect cancer-related somatic mutations in the absence of matched normal samples, which has applications in cell-free DNA-based assessment of tumor mutation burden. Second, the proposed approach also enables identification and exploration of driver genes;our analyses implicate DMD, RSK4, OFD1, WDR44, and AFF2 as potential cancer drivers. Finally, we used CRCS to score individual mutations in a tumor sample, which was found to be predictive of patient survival in bladder urothelial carcinoma, hepatocellular carcinoma, and lung adenocarcinoma. Taken together, we propose CRCS as a valuable computational tool for analysis of the functional significance of individual cancer mutations.
Purpose of ReviewSoon after the first genome-wide association study (GWAS) for type 2 diabetes (T2D) was published, it was hypothesized that rare and low-frequency variants might explain a substantial proportion of di...
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Purpose of ReviewSoon after the first genome-wide association study (GWAS) for type 2 diabetes (T2D) was published, it was hypothesized that rare and low-frequency variants might explain a substantial proportion of disease risk. Rare coding variants in particular were emphasized given their large expected role in disease. This review summarizes the extent to which recent T2D genetic studies provide evidence for or against this *** FindingsFollowing a comprehensive study of T2D genetic architecture using three sequencing and genotyping technologies, four even larger studies have provided a yet higher resolution view of the role of rare and low-frequency coding variation in T2D *** evidence strongly suggests that common regulatory variants are the dominant contributor to T2D heritability. However, rare coding variants may nonetheless be pervasive across T2D-relevant genes. A strategy using common variants to map disease genes, and rare coding variants to link molecular gene perturbations to cellular and phenotypic effects, may be an effective means to investigate T2D pathogenesis and potential new therapies.
The onset, progression, and severity of epilepsy vary between family members with identical mutations in primary disease genes. The background of genetic variation unique to each individual genome contributes to clini...
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The onset, progression, and severity of epilepsy vary between family members with identical mutations in primary disease genes. The background of genetic variation unique to each individual genome contributes to clinical variation. Known examples of gene interactions in human families and mouse models provide insight into underlying molecular mechanisms. For an expanded treatment of this topic see Jasper’s Basic Mechanisms of the Epilepsies, Fourth Edition (Noebels JL, Avoli M, Rogawski MA, Olsen RW, Delgado-Escueta AV, eds) published by Oxford University Press. (available on the National Library of Medicine Bookshelf [NCBI] at http://***/books).
Background: TREM2 encodes for triggering receptor expressed on myeloid cells 2 and has rare, coding variants that associate with risk for late-onset Alzheimer's disease (LOAD) in Caucasians of European and North-A...
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Background: TREM2 encodes for triggering receptor expressed on myeloid cells 2 and has rare, coding variants that associate with risk for late-onset Alzheimer's disease (LOAD) in Caucasians of European and North-American origin. This study evaluated the role of TREM2 in LOAD risk in African-American (AA) subjects. We performed exonic sequencing and validation in two independent cohorts of >800 subjects. We selected six coding variants (p.R47H, p.R62H, p.D87N, p.E151K, p.W191X, and p.L211P) for case-control analyses in a total of 906 LOAD cases vs. 2,487 controls. Results: We identified significant LOAD risk association with p.L211P (p = 0.01, OR = 1.27, 95%CI = 1.05-1.54) and suggestive association with p.W191X (p = 0.08, OR = 1.35, 95%CI = 0.97-1.87). Conditional analysis suggests that p.L211P, which is in linkage disequilibrium with p.W191X, may be the stronger variant of the two, but does not rule out independent contribution of the latter. TREM2 p.L211P resides within the cytoplasmic domain and p.W191X is a stop-gain mutation within the shorter TREM-2V transcript. The coding variants within the extracellular domain of TREM2 previously shown to confer LOAD risk in Caucasians were extremely rare in our AA cohort and did not associate with LOAD risk. Conclusions: Our findings suggest that TREM2 coding variants also confer LOAD risk in AA, but implicate variants within different regions of the gene than those identified for Caucasian subjects. These results underscore the importance of investigating different ethnic populations for disease risk variant discovery, which may uncover allelic heterogeneity with potentially diverse mechanisms of action.
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