Ashok Kumar Manickaraj

Genetic determinants of right-ventricular remodeling after tetralogy of Fallot repair.

Background:Hypoxia-inducible factor (HIF1A) regulates the myocardial response to hypoxia and hemodynamic load. We investigated the association of HIF1A variants with right-ventricular (RV) remodeling after tetralogy of Fallot (TOF) repair.Methods:Children with TOF were genotyped for three single-nucleotide polymorphisms in HIF1A. Genotypes were analyzed for association with RV myocardial protein expression and fibrosis at complete repair (n = 42) and RV dilation, fractional area change, and freedom from pulmonary valve/conduit replacement on follow-up.Results:In 180 TOF patients, mean age at repair was 1.0 ± 0.8 y with follow-up at 9.0 ± 3.5 y; 82% had moderate to severe pulmonary insufficiency. Freedom from RV reinterventions at 5, 10, and 15 y was 92, 84, and 67%, respectively. Patients with more functioning HIF1A alleles had higher transforming growth factor β1 expression and more fibrosis at initial repair as compared with controls (P < 0.05). During follow-up, patients with more functioning HIF1A alleles showed less RV dilation, better preservation of RV function, and greater freedom from RV reinterventions (P < 0.05). This was confirmed in a replication cohort of 69 patients.Conclusion:In children who have had TOF repair, a lower number of functioning HIF1A alleles was associated with RV dilation and dysfunction, suggesting that hypoxia adaptation in unrepaired TOF may influence RV phenotype after repair.

Exome sequencing identifies rare variants in multiple genes in atrioventricular septal defect

Purpose:The genetic etiology of atrioventricular septal defect (AVSD) is unknown in 40% cases. Conventional sequencing and arrays have identified the etiology in only a minority of nonsyndromic individuals with AVSD.Methods:Whole-exome sequencing was performed in 81 unrelated probands with AVSD to identify potentially causal variants in a comprehensive set of 112 genes with strong biological relevance to AVSD.Results:A significant enrichment of rare and rare damaging variants was identified in the gene set, compared with controls (odds ratio (OR): 1.52; 95% confidence interval (CI): 1.35–1.71; P = 4.8 × 10−11). The enrichment was specific to AVSD probands, compared with a cohort without AVSD with tetralogy of Fallot (OR: 2.25; 95% CI: 1.84–2.76; P = 2.2 × 10−16). Six genes (NIPBL, CHD7, CEP152, BMPR1a, ZFPM2, and MDM4) were enriched for rare variants in AVSD compared with controls, including three syndrome-associated genes (NIPBL, CHD7, and CEP152). The findings were confirmed in a replication cohort of 81 AVSD probands.Conclusion:Mutations in genes with strong biological relevance to AVSD, including syndrome-associated genes, can contribute to AVSD, even in those with isolated heart disease. The identification of a gene set associated with AVSD will facilitate targeted genetic screening in this cohort.Genet Med 18 2, 189–198.

genetic variations in hypoxia response genes influence hypertrophic cardiomyopathy phenotype

Background:Risk factors for diastolic dysfunction in hypertrophic cardiomyopathy (HCM) are poorly understood. We investigated the association of variants in hypoxia-response genes with phenotype severity in pediatric HCM.Methods:A total of 80 unrelated patients <21 y and 14 related members from eight families with HCM were genotyped for six variants associated with vascular endothelial growth factor A (VEGFA) downregulation, or hypoxia-inducible factor A (HIF1A) upregulation. Associations between risk genotypes and left-ventricular (LV) hypertrophy, LV dysfunction, and freedom from myectomy were assessed. Tissue expression was measured in myocardial samples from 17 patients with HCM and 20 patients without HCM.Results:Age at enrollment was 9 ± 5 y (follow-up, 3.1 ± 3.6 y). Risk allele frequency was 67% VEGFA and 92% HIF1A. Risk genotypes were associated with younger age at diagnosis (P < 0.001), septal hypertrophy (P < 0.01), prolonged E-wave deceleration time (EWDT) (P < 0.0001) and isovolumic relaxation time (IVRT) (P < 0.0001), and lower freedom from myectomy (P < 0.05). These associations were seen in sporadic and familial HCM independent of the disease-causing mutation. Risk genotypes were associated with higher myocardial HIF1A and transforming growth factor B1 (TGFB1) expression and increased endothelial-fibroblast transformation (P < 0.05).Conclusion:HIF1A-upregulation and/or VEGFA-downregulation genotypes were associated with more severe septal hypertrophy and diastolic dysfunction and may provide genetic markers to improve risk prediction in HCM.

Personalized medicine in pediatric cardiology: do little changes make a big difference?

Purpose of review Advances in genomics have paved the way for personalized medicine applications. This review will discuss new discoveries in genomics and pharmacogenomics in children with congenital heart disease (CHD) and the application towards the development of new diagnostics, disease risk predictions, and optimizing response to drugs and surgery. Recent findings Recent advances have identified common and rare variants associated with complex CHD using next-generation sequencing and genotyping technology. Next-generation sequencing is now being used not only for clinical genetic testing but also for noninvasive prenatal testing of fetal DNA in maternal serum to diagnose genetic conditions like fetal aneuploidies as early as the first trimester. This approach is not only more accurate but also safer than invasive maternal screening tests. This technology may also help in noninvasive diagnosis of transplant rejection. As genetic variations that influence the response to surgery in CHD are identified, this can guide decision-making surrounding optimum type and timing of surgery. Drug choice and dosing are being increasingly influenced by knowledge of pharmacogenetic and pharmacodynamic variations. Age-related and maturation-related changes in drug pharmacokinetics make it crucial to perform pediatric-targeted pharmacogenetic studies to enable the incorporation of age into genotype-guided drug dosing algorithms. Summary Rapid genomic and pharmacogenomic discovery are guiding the development of more sensitive screening and diagnostic tests for CHD as well as development of safer and more effective drugs. This needs to be paralleled by the development of strategies to support rapid translation of emerging genomic knowledge to patient care.

High throughput exome coverage of clinically relevant cardiac genes

BackgroundGiven the growing use of whole-exome sequencing (WES) for clinical diagnostics of complex human disorders, we evaluated coverage of clinically relevant cardiac genes on WES and factors influencing uniformity and depth of coverage of exonic regions.MethodsTwo hundred and thirteen human DNA samples were exome sequenced via Illumina HiSeq using different versions of the Agilent SureSelect capture kit. 50 cardiac genes were further analyzed including 31 genes from the American College of Medical Genetics (ACMG) list for reporting of incidental findings and 19 genes associated with congenital heart disease for which clinical testing is available. Gene coordinates were obtained from two databases, CCDS and Known Gene and compared. Read depth for each region was extracted from the exomes and used to assess capture variability between kits for individual genes, and for overall coverage. GC content, gene size, and inter-sample variability were also tested as potential contributors to variability in gene coverage.ResultsAll versions of capture kits (designed based on Consensus coding sequence) included only 55% of known genomic regions for the cardiac genes. Although newer versions of each Agilent kit showed improvement in capture of CCDS regions to 99%, only 64% of Known Gene regions were captured even with newer capture kits. There was considerable variability in coverage of the cardiac genes. 10 of the 50 genes including 6 on the ACMG list had less than the optimal coverage of 30X. Within each gene, only 32 of the 50 genes had the majority of their bases covered at an interquartile range ≥30X. Heterogeneity in gene coverage was modestly associated with gene size and significantly associated with GC content.ConclusionsDespite improvement in overall coverage across the exome with newer capture kit versions and higher sequencing depths, only 50% of known genomic regions of clinical cardiac genes are targeted and individual gene coverage is non-uniform. This may contribute to a bias with greater attribution of disease causation to mutations in well-represented and well-covered genes. Improvements in WES technology are needed before widespread clinical application.