The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Genetic Testing in the Long QT Syndrome: Development and Validation of an Efficient Approach to Genotyping in Clinical Practice
Abstract
CONTEXT: In long QT syndrome (LQTS), disease severity and response to therapy vary according to the genetic loci. There exists a critical need to devise strategies to expedite genetic analysis. OBJECTIVE: To perform genetic screening in patients with LQTS to determine the yield of genetic testing, as well as the type and the prevalence of mutations. DESIGN, PATIENTS, AND SETTING: We investigated whether the detection of a set of frequently mutated codons in the KCNQ1, KCNH2, and SCN5A genes may translate in a novel strategy for rapid efficient genetic testing of 430 consecutive patients referred to our center between June 1996 and June 2004. The entire coding regions of KCNQ1, KCNH2, SCN5A, KCNE1, and KCNE2 were screened by denaturing high-performance liquid chromatography and DNA sequencing. The frequency and the type of mutations were defined to identify a set of recurring mutations. A separate cohort of 75 consecutive probands was used as a validation group to quantify prospectively the prevalence of the recurring mutations identified in the primary LQTS population. MAIN OUTCOME MEASURES: Development of a novel approach to LQTS genotyping. RESULTS: We identified 235 different mutations, 138 of which were novel, in 310 (72%) of 430 probands (49% KCNQ1, 39% KCNH2, 10% SCN5A, 1.7% KCNE1, and 0.7% KCNE2). Fifty-eight percent of probands carried nonprivate mutations in 64 codons of KCNQ1, KCNH2, and SCN5A genes. A similar occurrence of mutations at these codons (52%) was confirmed in the prospective cohort of 75 probands and in previously published LQTS cohorts. CONCLUSIONS: We have developed an approach to improve the efficiency of genetic screening for LQTS. This novel method may facilitate wider access to genotyping resulting in better risk stratification and treatment of LQTS patients.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
CaV1.2 Calcium Channel Dysfunction Causes a Multisystem Disorder Including Arrhythmia and Autism
Splawski, I., Timothy, K. W., Sharpe, L. M., Decher, N., Kumar, P., Bloise, R., Napolitano, C., Schwartz, P. J., Joseph, R. M., Condouris, K., et al. (2004) · Cell · doi:10.1016/j.cell.2004.09.011 · Cited by 1,586 · cited 1×
“More recently, 2 additional uncommon variants presenting with prolonged QT interval and extracardiac manifestations were reported.(5,6) Six genes are known to cause Romano-Ward syndrome: 5 encoding for subunits of cardiac ion channels (KCNQ1, KCNH2, SCN5A, KCNE1, KCNE2)(7) and 1 (ANK2) encoding for cardiac ankyrin, a…”
BackgroundSelf-citationAnkyrin-B mutation causes type 4 long-QT cardiac arrhythmia and sudden cardiac death
Mohler, P. J., Schott, J.-J., Gramolini, A. O., Dilly, K. W., Guatimosim, S., duBell, W. H., Song, L.-S., Haurogné, K., Kyndt, F., Ali, M. E., et al. (2003) · Nature · doi:10.1038/nature01335 · Cited by 957
ECG T-wave patterns in genetically distinct forms of the hereditary long QT syndrome
Moss, A. J., Zareba, W., Benhorin, J., Locati, E. H., Hall, W. J., Robinson, J. L., Schwartz, P. J., Towbin, J. A., Vincent, G. M., Lehmann, M. H., et al. (1995) · Circulation · doi:10.1161/01.cir.92.10.2929 · Cited by 616
Cited by
Disease characterization using LQTS-specific induced pluripotent stem cells
Egashira, T., Yuasa, S., Suzuki, T., Aizawa, Y., Yamakawa, H., Matsuhashi, T., Ohno, Y., Tohyama, S., Okata, S., Seki, T., et al. (2012) · Cardiovascular Research · doi:10.1093/cvr/cvs206 · Cited by 178
Long QT syndrome and short QT syndrome
Zareba, W., & Cygankiewicz, I. (2008) · Progress in Cardiovascular Diseases · doi:10.1016/j.pcad.2008.10.006 · Cited by 96
Metadata
- Authors
- Napolitano, C., Priori, S. G., Schwartz, P. J., Bloise, R., Ronchetti, E., Nastoli, J., Bottelli, G., Cerrone, M., & Leonardi, S.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2005-12-21
- Volume
- 294
- Issue
- 23
- Pages
- 2975
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W2151361417
- Cited by
- 464
- References
- 3
- FWCI
- 19.94
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.