Andrey S Glotov1, Sergey V Kazakov2, Elena A Zhukova3, Anton V Alexandrov2, Oleg S Glotov4, Vladimir S Pakin4, Maria M Danilova4, Irina V Poliakova4, Svetlana S Niyazova5, Natalia N Chakova5, Svetlana M Komissarova6, Elena A Kurnikova7, Andrey M Sarana8, Sergey G Sherbak8, Alexey A Sergushichev2, Anatoly A Shalyto2, Vladislav S Baranov4. 1. Department of Genetics and Biotechnology, Saint Petersburg State University, Universitetskaya nab., 7-9, St. Petersburg 199034, Russia; Laboratory of Prenatal Diagnostics of Hereditary Diseases, Federal State Budget Scientific Institution "The Research Institute of Obstetrics, Gynecology and Reproductology named after D.O.Ott", Mendeleyevskaya lin., 3, St. Petersburg 199034, Russia. Electronic address: anglotov@mail.ru. 2. Computer Technologies Laboratory, ITMO University, Kronverksky pr., 49, St. Petersburg 197101, Russia. 3. Laboratory of Prenatal Diagnostics of Hereditary Diseases, Federal State Budget Scientific Institution "The Research Institute of Obstetrics, Gynecology and Reproductology named after D.O.Ott", Mendeleyevskaya lin., 3, St. Petersburg 199034, Russia. 4. Department of Genetics and Biotechnology, Saint Petersburg State University, Universitetskaya nab., 7-9, St. Petersburg 199034, Russia; Laboratory of Prenatal Diagnostics of Hereditary Diseases, Federal State Budget Scientific Institution "The Research Institute of Obstetrics, Gynecology and Reproductology named after D.O.Ott", Mendeleyevskaya lin., 3, St. Petersburg 199034, Russia. 5. Laboratory of Modelling of Genetic Processes, Institute of Genetics and Cytology, National Academy of Sciences, Akademicheskaya str., 27, Minsk 220072, Belarus. 6. Scientific and Practical center of Cardiology, Rozy Luxemburg str., 110, Minsk 220036, Belarus. 7. Department of Faculty Therapy on Behalf of Prof. VA Waldman, Saint Petersburg State Pediatric Medical University, Lithuanian str., 2, St. Petersburg 194100, Russia. 8. City Hospital No. 40, Borisov str., 9, Sestroretsk, St. Petersburg 197706, Russia.
Abstract
BACKGROUND: Hypertrophic cardiomyopathy is a common genetic cardiac disease. Prevention and early diagnosis of this disease are very important. Because of the large number of causative genes and the high rate of mutations involved in the pathogenesis of this disease, traditional methods of early diagnosis are ineffective. METHODS: We developed a custom AmpliSeq panel for NGS sequencing of the coding sequences of ACTC1, MYBPC3, MYH7, MYL2, MYL3, TNNI3, TNNT2, TPM1, and CASQ2. A genetic analysis of student cohorts (with and without cardiomyopathy risk in their medical histories) and patients with cardiomyopathies was performed. For the statistical and bioinformatics analysis, Polyphen2, SIFT, SnpSift and PLINK software were used. To select genetic markers in the patients with cardiomyopathy and in the students of the high risk group, four additive models were applied. RESULTS: Our AmpliSeq custom panel allowed us to efficiently explore targeted sequences. Based on the score analysis, we detected three substitutions in the MYBPC3 and CASQ2 genes and six combinations between loci in the MYBPC3, MYH7 and CASQ2 genes that were responsible for cardiomyopathy risk in our cohorts. We also detected substitutions in the TNNT2 gene that can be considered as protective against cardiomyopathy. CONCLUSION: We used NGS with AmpliSeq libraries and Ion PGM sequencing to develop improved predictive information for patients at risk of cardiomyopathy.
BACKGROUND:Hypertrophic cardiomyopathy is a common genetic cardiac disease. Prevention and early diagnosis of this disease are very important. Because of the large number of causative genes and the high rate of mutations involved in the pathogenesis of this disease, traditional methods of early diagnosis are ineffective. METHODS: We developed a custom AmpliSeq panel for NGS sequencing of the coding sequences of ACTC1, MYBPC3, MYH7, MYL2, MYL3, TNNI3, TNNT2, TPM1, and CASQ2. A genetic analysis of student cohorts (with and without cardiomyopathy risk in their medical histories) and patients with cardiomyopathies was performed. For the statistical and bioinformatics analysis, Polyphen2, SIFT, SnpSift and PLINK software were used. To select genetic markers in the patients with cardiomyopathy and in the students of the high risk group, four additive models were applied. RESULTS: Our AmpliSeq custom panel allowed us to efficiently explore targeted sequences. Based on the score analysis, we detected three substitutions in the MYBPC3 and CASQ2 genes and six combinations between loci in the MYBPC3, MYH7 and CASQ2 genes that were responsible for cardiomyopathy risk in our cohorts. We also detected substitutions in the TNNT2 gene that can be considered as protective against cardiomyopathy. CONCLUSION: We used NGS with AmpliSeq libraries and Ion PGM sequencing to develop improved predictive information for patients at risk of cardiomyopathy.
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