Dataset Information

Paralogous annotation of disease-causing variants in long QT syndrome genes.

ABSTRACT: Discriminating between rare benign and pathogenic variation is a key challenge in clinical genetics, particularly as increasing numbers of nonsynonymous single-nucleotide polymorphisms (SNPs) are identified in resequencing studies. Here, we describe an approach for the functional annotation of nonsynonymous variants that identifies functionally important, disease-causing residues across protein families using multiple sequence alignment. We applied the methodology to long QT syndrome (LQT) genes, which cause sudden death, and their paralogues, which largely cause neurological disease. This approach accurately classified known LQT disease-causing variants (positive predictive value = 98.4%) with a better performance than established bioinformatic methods. The analysis also identified 1078 new putative disease loci, which we incorporated along with known variants into a comprehensive and freely accessible long QT resource (http://cardiodb.org/Paralogue_Annotation/), based on newly created Locus Reference Genomic sequences (http://www.lrg-sequence.org/). We propose that paralogous annotation is widely applicable for Mendelian human disease genes.

SUBMITTER: Ware JS

PROVIDER: S-EPMC4640174 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Paralogous annotation of disease-causing variants in long QT syndrome genes.

Ware James S JS Walsh Roddy R Cunningham Fiona F Birney Ewan E Cook Stuart A SA

Human mutation 20120607 8

Discriminating between rare benign and pathogenic variation is a key challenge in clinical genetics, particularly as increasing numbers of nonsynonymous single-nucleotide polymorphisms (SNPs) are identified in resequencing studies. Here, we describe an approach for the functional annotation of nonsynonymous variants that identifies functionally important, disease-causing residues across protein families using multiple sequence alignment. We applied the methodology to long QT syndrome (LQT) genes ...[more]

PMID: 22581653

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Project description:Genetic testing for long-QT syndrome (LQTS) has diagnostic, prognostic, and therapeutic implications. Hundreds of causative mutations in 12 known LQTS-susceptibility genes have been identified. Genetic testing that includes the 3 most commonly mutated genes is available clinically. Distinguishing pathogenic mutations from innocuous rare variants is critical to the interpretation of test results. We sought to quantify the value of mutation type and gene/protein region in determining the probability of pathogenicity for mutations.Type, frequency, and location of mutations across KCNQ1 (LQT1), KCNH2 (LQT2), and SCN5A (LQT3) were compared between 388 unrelated "definite" (clinical diagnostic score >or=4 and/or QTc >or=480 ms) cases of LQTS and >1300 healthy controls for each gene. From these data, estimated predictive values (percent of mutations found in definite cases that would cause LQTS) were determined according to mutation type and location. Mutations were 10 times more common in cases than controls (0.58 per case versus 0.06 per control). Missense mutations were the most common, accounting for 78%, 67%, and 89% of mutations in KCNQ1, KCNH2, and SCN5A in cases and >95% in controls. Nonmissense mutations have an estimated predictive value >99% regardless of location. In contrast, location appears to be critical for characterizing missense mutations. Relative frequency of missense mutations between cases and controls ranged from approximately 1:1 in the SCN5A interdomain linker to infinity in the pore, transmembrane, and linker in KCNH2. These correspond to estimated predictive values ranging from 0% in the interdomain linker of SCN5A to 100% in the transmembrane/linker/pore regions of KCNH2. The estimated predictive value is also high in the linker, pore, transmembrane, and C terminus of KCNQ1 and the transmembrane/linker of SCN5A.Distinguishing pathogenic mutations from rare variants is of critical importance in the interpretation of genetic testing in LQTS. Mutation type, mutation location, and ethnic-specificshould be viewed as variants of uncertain significance and prompt further investigation to clarify the likelihood of disease causation. However, mutations in regions such as the transmembrane, linker, and pore of KCNQ1 and KCNH2 may be defined confidently as high-probability LQTS-causing mutations. These findings will have implications for other genetic disorders involving mutational analysis.

Dataset Information

Paralogous annotation of disease-causing variants in long QT syndrome genes.

Publications

Paralogous annotation of disease-causing variants in long QT syndrome genes.

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