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Browsing by Author "Helvaty, Lindsey R."
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Item A Multicenter Analysis of Abnormal Chromosomal Microarray Findings in Congenital Heart Disease(American Heart Association, 2023) Landis, Benjamin J.; Helvaty, Lindsey R.; Geddes, Gabrielle C.; Lin, Jiuann-Huey Ivy; Yatsenko, Svetlana A.; Lo, Cecilia W.; Border, William L.; Burns Wechsler, Stephanie; Murali, Chaya N.; Azamian, Mahshid S.; Lalani, Seema R.; Hinton, Robert B.; Garg, Vidu; McBride, Kim L.; Hodge, Jennelle C.; Ware, Stephanie M.; Pediatrics, School of MedicineBackground: Chromosomal microarray analysis (CMA) provides an opportunity to understand genetic causes of congenital heart disease (CHD). The methods for describing cardiac phenotypes in patients with CMA abnormalities have been inconsistent, which may complicate clinical interpretation of abnormal testing results and hinder a more complete understanding of genotype–phenotype relationships. Methods and Results: Patients with CHD and abnormal clinical CMA were accrued from 9 pediatric cardiac centers. Highly detailed cardiac phenotypes were systematically classified and analyzed for their association with CMA abnormality. Hierarchical classification of each patient into 1 CHD category facilitated broad analyses. Inclusive classification allowing multiple CHD types per patient provided sensitive descriptions. In 1363 registry patients, 28% had genomic disorders with well‐recognized CHD association, 67% had clinically reported copy number variants (CNVs) with rare or no prior CHD association, and 5% had regions of homozygosity without CNV. Hierarchical classification identified expected CHD categories in genomic disorders, as well as uncharacteristic CHDs. Inclusive phenotyping provided sensitive descriptions of patients with multiple CHD types, which occurred commonly. Among CNVs with rare or no prior CHD association, submicroscopic CNVs were enriched for more complex types of CHD compared with large CNVs. The submicroscopic CNVs that contained a curated CHD gene were enriched for left ventricular obstruction or septal defects, whereas CNVs containing a single gene were enriched for conotruncal defects. Neuronal‐related pathways were over‐represented in single‐gene CNVs, including top candidate causative genes NRXN3, ADCY2, and HCN1. Conclusions: Intensive cardiac phenotyping in multisite registry data identifies genotype–phenotype associations in CHD patients with abnormal CMA.Item Genetic Testing Guidelines Impact Care in Newborns with Congenital Heart Defects(Elsevier, 2023) Durbin, Matthew D.; Fairman, Korre; Helvaty, Lindsey R.; Huang, Manyan; Li, Ming; Abreu, Daniel; Geddes, Gabrielle C.; Helm, Benjamin M.; Landis, Benjamin J.; McEntire, Alexis; Mitchell, Dana K.; Ware, Stephanie M.; Pediatrics, School of MedicineObjective: To evaluate genetic evaluation practices in newborns with the most common birth defect, congenital heart defects (CHD), we determined the prevalence and the yield of genetic evaluation across time and across patient subtypes, before and after implementation of institutional genetic testing guidelines. Study design: This was a retrospective, cross-sectional study of 664 hospitalized newborns with CHD using multivariate analyses of genetic evaluation practices across time and patient subtypes. Results: Genetic testing guidelines for hospitalized newborns with CHD were implemented in 2014, and subsequently genetic testing increased (40% in 2013 and 75% in 2018, OR 5.02, 95% CI 2.84-8.88, P < .001) as did medical geneticists' involvement (24% in 2013 and 64% in 2018, P < .001). In 2018, there was an increased use of chromosomal microarray (P < .001), gene panels (P = .016), and exome sequencing (P = .001). The testing yield was high (42%) and consistent across years and patient subtypes analyzed. Increased testing prevalence (P < .001) concomitant with consistent testing yield (P = .139) added an estimated 10 additional genetic diagnoses per year, reflecting a 29% increase. Conclusions: In patients with CHD, yield of genetic testing was high. After implementing guidelines, genetic testing increased significantly and shifted to newer sequence-based methods. Increased use of genetic testing identified more patients with clinically important results with potential to impact patient care.