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Prediction and visualization data for the interpretation of sarcomeric and non-sarcomeric DNA variants found in patients with hypertrophic cardiomyopathy.

ABSTRACT: Genomic technologies are redefining the understanding of genotype-phenotype relationships and over the past decade, many bioinformatics algorithms have been developed to predict functional consequences of single nucleotide variants. This article presents the data from a comprehensive computational workflow adopted to assess the biomedical impact of the DNA variants resulting from the experimental study "Molecular analysis of sarcomeric and non-sarcomeric genes in patients with hypertrophic cardiomyopathy" (Bottillo et al., 2016) [1]. Several different independently methods were employed to predict the functional consequences of alleles that result in amino acid substitutions, to study the effect of some DNA variants over the splicing process and to investigate the impact of a sequence variant with respect to the evolutionary conservation.

SUBMITTER: Bottillo I

PROVIDER: S-EPMC4802523 | biostudies-other | 2016 Jun

REPOSITORIES: biostudies-other

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Prediction and visualization data for the interpretation of sarcomeric and non-sarcomeric DNA variants found in patients with hypertrophic cardiomyopathy.

Bottillo Irene I D'Angelantonio Daniela D Caputo Viviana V Paiardini Alessandro A Lipari Martina M De Bernardo Carmelilia C Majore Silvia S Castori Marco M Zachara Elisabetta E Re Federica F Grammatico Paola P

Data in brief 20160310

Genomic technologies are redefining the understanding of genotype-phenotype relationships and over the past decade, many bioinformatics algorithms have been developed to predict functional consequences of single nucleotide variants. This article presents the data from a comprehensive computational workflow adopted to assess the biomedical impact of the DNA variants resulting from the experimental study "Molecular analysis of sarcomeric and non-sarcomeric genes in patients with hypertrophic cardi ...[more]

PMID: 27054166

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Project description:Background: Carriers of pathogenic DNA variants (G+) causing hypertrophic cardiomyopathy (HCM) can be identified by genetic testing. Several abnormalities have been brought forth as pre-clinical expressions of HCM, some of which can be identified by cardiovascular magnetic resonance (CMR). In this study, we assessed morphological differences between G+/left ventricular hypertrophy-negative (LVH-) subjects and healthy controls and examined whether CMR-derived variables are useful for the prediction of sarcomere gene variants. Methods: We studied 57 G+ subjects with a maximal wall thickness (MWT) < 13 mm, and compared them to 40 healthy controls matched for age and sex on a group level. Subjects underwent CMR including morphological, volumetric and function assessment. Logistic regression analysis was performed for the determination of predictive CMR characteristics, by which a scoring system for G+ status was constructed. Results: G+/LVH- subjects were subject to alterations in the myocardial architecture, resulting in a thinner posterior wall thickness (PWT), higher interventricular septal wall/PWT ratio and MWT/PWT ratio. Prominent hook-shaped configurations of the anterobasal segment were only observed in this group. A model consisting of the anterobasal hook, multiple myocardial crypts, right ventricular/left ventricular ratio, MWT/PWT ratio, and MWT/left ventricular mass ratio predicted G+ status with an area under the curve of 0.92 [0.87-0.97]. A score of ≥3 was present only in G+ subjects, identifying 56% of the G+/LVH- population. Conclusion: A score system incorporating CMR-derived variables correctly identified 56% of G+ subjects. Our results provide further insights into the wide phenotypic spectrum of G+/LVH- subjects and demonstrate the utility of several novel morphological features. If genetic testing for some reason cannot be performed, CMR and our purposed score system can be used to detect possible G+ carriers and to aid planning of the control intervals.

Project description:Hypertrophic cardiomyopathy (HCM) is a genetic heart muscle disease that frequently causes sudden cardiac death (SCD) among young adults. Several pathogenic mutations in genes encoding the cardiac sarcomere have been identified as diagnostic factors for HCM and proposed as prognostic markers for SCD. The objective of this review was to determine the scope of available literature on the variants encoding sarcomere proteins associated with SCD reported among Indian patients with HCM. The eligibility criteria for the scoping review included full text articles that reported the results of genetic screening for sarcomeric gene mutations in HCM patients of Indian south Asian ancestry. We systematically reviewed studies from the databases of Medline, Scopus, Web of Science core collection and Google Scholar. The electronic search strategy included a combination of generic terms related to genetics, disease and population. The protocol of the study was registered with Open Science Framework (https://osf.io/53gde/). A total of 19 articles were identified that reported pathogenic or likely pathogenic (P/LP) variants within MYH7, MYBPC3, TNNT2, TNNI3 and TPM1 genes, that included 16 singletons, one de novo and one digenic mutation (MYH7/ TPM1) associated with SCD among Indian patients. Evidence from functional studies and familial segregation implied a plausible mechanistic role of these P/LP variants in HCM pathology. This scoping review has compiled all the P/LP variants reported to-date among Indian patients and summarized their association with SCD. Single homozygous, de novo and digenic mutations were observed to be associated with severe phenotypes compared to single heterozygous mutations. The abstracted genetic information was updated with reference sequence ID (rsIDs) and compiled into freely accessible HCMvar database, available at https://hcmvar.heartfailure.org.in/. This can be used as a population specific genetic database for reference by clinicians and researchers involved in the identification of diagnostic and prognostic markers for HCM.

Dataset Information

Prediction and visualization data for the interpretation of sarcomeric and non-sarcomeric DNA variants found in patients with hypertrophic cardiomyopathy.

Publications

Prediction and visualization data for the interpretation of sarcomeric and non-sarcomeric DNA variants found in patients with hypertrophic cardiomyopathy.

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