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Short QT Syndrome: A Comprehensive Genetic Interpretation and Clinical Translation of Rare Variants.

ABSTRACT: Short QT syndrome, one of the most lethal entities associated with sudden cardiac death, is a rare genetic disease characterized by short QT intervals detected by electrocardiogram. Several genetic variants are causally linked to the disease, but there has yet to be a comprehensive analysis of variants among patients with short QT syndrome. To fill this gap, we performed an exhaustive study of variants currently catalogued as deleterious in short QT syndrome according to the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Analysis of the 32 variants described in the literature determined that only nine (28.12%) have a conclusive pathogenic role. All definitively pathogenic variants are located in KCNQ1, KCNH2, or KCNJ2; three genes encoding potassium channels. Other variants located in genes encoding calcium or sodium channels are associated with electrical alterations concomitant with shortened QT intervals but do not guarantee a diagnosis of short QT syndrome. We recommend caution regarding previously reported variants classified as pathogenic. An exhaustive re-analysis is necessary to clarify the role of each variant before routinely translating genetic findings to the clinical setting.

SUBMITTER: Campuzano O

PROVIDER: S-EPMC6678338 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Short QT Syndrome: A Comprehensive Genetic Interpretation and Clinical Translation of Rare Variants.

Campuzano Oscar O Fernandez-Falgueras Anna A Lemus Ximena X Sarquella-Brugada Georgia G Cesar Sergi S Coll Monica M Mates Jesus J Arbelo Elena E Jordà Paloma P Perez-Serra Alexandra A Del Olmo Bernat B Ferrer-Costa Carles C Iglesias Anna A Fiol Victoria V Puigmulé Marta M Lopez Laura L Pico Ferran F Brugada Josep J Brugada Ramon R

Journal of clinical medicine 20190716 7

Short QT syndrome, one of the most lethal entities associated with sudden cardiac death, is a rare genetic disease characterized by short QT intervals detected by electrocardiogram. Several genetic variants are causally linked to the disease, but there has yet to be a comprehensive analysis of variants among patients with short QT syndrome. To fill this gap, we performed an exhaustive study of variants currently catalogued as deleterious in short QT syndrome according to the American College of ...[more]

PMID: 31315195

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Project description:BackgroundThe proliferation of genetic profiling has revealed many associations between genetic variations and disease. However, large-scale phenotyping efforts in largely healthy populations, coupled with DNA sequencing, suggest variants currently annotated as pathogenic are more common in healthy populations than previously thought. In addition, novel and rare variants are frequently observed in genes associated with disease both in healthy individuals and those under suspicion of disease. This raises the question of whether these variants can be useful predictors of disease. To answer this question, we assessed the degree to which the presence of a variant in the cardiac potassium channel gene KCNH2 was diagnostically predictive for the autosomal dominant long QT syndrome.MethodsWe estimated the probability of a long QT diagnosis given the presence of each KCNH2 variant using Bayesian methods that incorporated variant features such as changes in variant function, protein structure, and in silico predictions. We call this estimate the posttest probability of disease. Our method was applied to over 4000 individuals heterozygous for 871 missense or in-frame insertion/deletion variants in KCNH2 and validated against a separate international cohort of 933 individuals heterozygous for 266 missense or in-frame insertion/deletion variants.ResultsOur method was well-calibrated for the observed fraction of heterozygotes diagnosed with long QT syndrome. Heuristically, we found that the innate diagnostic information one learns about a variant from 3-dimensional variant location, in vitro functional data, and in silico predictors is equivalent to the diagnostic information one learns about that same variant by clinically phenotyping 10 heterozygotes. Most importantly, these data can be obtained in the absence of any clinical observations.ConclusionsWe show how variant-specific features can inform a prior probability of disease for rare variants even in the absence of clinically phenotyped heterozygotes.

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

Short QT Syndrome: A Comprehensive Genetic Interpretation and Clinical Translation of Rare Variants.

Publications

Short QT Syndrome: A Comprehensive Genetic Interpretation and Clinical Translation of Rare Variants.

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