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(Circulation. 2009;120:1752-1760.)
© 2009 American Heart Association, Inc.
Arrhythmia/Electrophysiology |
From the Department of Medicine/Division of Cardiovascular Diseases (S.K., M.J.A.), Department of Molecular Pharmacology and Experimental Therapeutics/Windland Smith Rice Sudden Death Genomics Laboratory (D.J.T., M.J.A.), and Department of Pediatrics/Division of Pediatric Cardiology (M.J.A.), Mayo Clinic, Rochester, Minn; Clinical Genetics, PGxHealth, LLC, New Haven, Conn (B.A.S., C.H.-K.); Genaissance Pharmaceuticals, Inc, New Haven, Conn (M.S.P.); and Departments of Clinical Genetics (M.A.) and Cardiology (A.A.M.W.), Academic Medical Center, Amsterdam, the Netherlands.
Reprint requests to Michael J. Ackerman, MD, PhD, Director, Long QT Syndrome Clinic and the Mayo Clinic Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic, Guggenheim 501, 200 First St SW, Rochester, MN 55905. E-mail ackerman.michael{at}mayo.edu
Received March 5, 2009; accepted August 17, 2009.
Background— 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.
Methods and Results— Type, frequency, and location of mutations across KCNQ1 (LQT1), KCNH2 (LQT2), and SCN5A (LQT3) were compared between 388 unrelated "definite" (clinical diagnostic score
4 and/or QTc
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
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.
Conclusions— Distinguishing pathogenic mutations from rare variants is of critical importance in the interpretation of genetic testing in LQTS. Mutation type, mutation location, and ethnic-specific background rates are critical factors in predicting the pathogenicity of novel mutations. Novel mutations in low-estimated predictive value regions such as the interdomain linker of SCN5A should 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.
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