Dataset Information

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.

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.

Similar Datasets

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