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1.
Circ Genom Precis Med ; 13(5): 424-434, 2020 10.
Article in English | MEDLINE | ID: mdl-32815737

ABSTRACT

BACKGROUND: To assess the genetic architecture of hypertrophic cardiomyopathy (HCM) in patients of predominantly Chinese ancestry. METHODS: We sequenced HCM disease genes in Singaporean patients (n=224) and Singaporean controls (n=3634), compared findings with additional populations and White HCM cohorts (n=6179), and performed in vitro functional studies. RESULTS: Singaporean HCM patients had significantly fewer confidently interpreted HCM disease variants (pathogenic/likely pathogenic: 18%, P<0.0001) but an excess of variants of uncertain significance (24%, P<0.0001), as compared to Whites (pathogenic/likely pathogenic: 31%, excess of variants of uncertain significance: 7%). Two missense variants in thin filament encoding genes were commonly seen in Singaporean HCM (TNNI3:p.R79C, disease allele frequency [AF]=0.018; TNNT2:p.R286H, disease AF=0.022) and are enriched in Singaporean HCM when compared with Asian controls (TNNI3:p.R79C, Singaporean controls AF=0.0055, P=0.0057, genome aggregation database-East Asian AF=0.0062, P=0.0086; TNNT2:p.R286H, Singaporean controls AF=0.0017, P<0.0001, genome aggregation database-East Asian AF=0.0009, P<0.0001). Both these variants have conflicting annotations in ClinVar and are of low penetrance (TNNI3:p.R79C, 0.7%; TNNT2:p.R286H, 2.7%) but are predicted to be deleterious by computational tools. In population controls, TNNI3:p.R79C carriers had significantly thicker left ventricular walls compared with noncarriers while its etiological fraction is limited (0.70 [95% CI, 0.35-0.86]) and thus TNNI3:p.R79C is considered variant of uncertain significance. Mutant TNNT2:p.R286H iPSC-CMs (induced pluripotent stem cells derived cardiomyocytes) show hypercontractility, increased metabolic requirements, and cellular hypertrophy and the etiological fraction (0.93 [95% CI, 0.83-0.97]) support the likely pathogenicity of TNNT2:p.R286H. CONCLUSIONS: As compared with Whites, Chinese HCM patients commonly have low penetrance risk alleles in TNNT2 or TNNI3 but exhibit few clinically actionable HCM variants overall. This highlights the need for greater study of HCM genetics in non-White populations.


Subject(s)
Asian People/genetics , Cardiomyopathy, Hypertrophic/genetics , Troponin I/genetics , Troponin T/genetics , Cardiomyopathy, Hypertrophic/diagnosis , China , Female , Gene Frequency , Genetic Association Studies , Haplotypes , Heart Ventricles/physiopathology , Heterozygote , Humans , Male , Middle Aged , Odds Ratio , Polymorphism, Single Nucleotide , Risk , Singapore
2.
J Cardiovasc Transl Res ; 9(1): 3-11, 2016 Feb.
Article in English | MEDLINE | ID: mdl-26888179

ABSTRACT

Inherited cardiac conditions (ICCs) are characterised by marked genetic and allelic heterogeneity and require extensive sequencing for genetic characterisation. We iteratively optimised a targeted gene capture panel for ICCs that includes disease-causing, putatively pathogenic, research and phenocopy genes (n = 174 genes). We achieved high coverage of the target region on both MiSeq (>99.8% at ≥ 20× read depth, n = 12) and NextSeq (>99.9% at ≥ 20×, n = 48) platforms with 100% sensitivity and precision for single nucleotide variants and indels across the protein-coding target on the MiSeq. In the final assay, 40 out of 43 established ICC genes informative in clinical practice achieved complete coverage (100 % at ≥ 20×). By comparison, whole exome sequencing (WES; ∼ 80×), deep WES (∼ 500×) and whole genome sequencing (WGS; ∼ 70×) had poorer performance (88.1, 99.2 and 99.3% respectively at ≥ 20×) across the ICC target. The assay described here delivers highly accurate and affordable sequencing of ICC genes, complemented by accessible cloud-based computation and informatics. See Editorial in this issue (DOI: 10.1007/s12265-015-9667-8 ).


Subject(s)
DNA Mutational Analysis/methods , Heart Diseases/genetics , High-Throughput Nucleotide Sequencing/methods , Mutation , Polymorphism, Single Nucleotide , Cloud Computing , Computational Biology , Databases, Genetic , Exome , Genetic Markers , Genetic Predisposition to Disease , Heart Diseases/diagnosis , Heredity , Humans , London , Phenotype , Predictive Value of Tests , Singapore , Workflow
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