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Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants
Published on: February 21, 2015
Chromosome microarray testing for patients with congenital heart defects reveals novel disease causing loci and high
Juan Geng, Jonathan Picker, Zhaojing Zheng
1Department of Laboratory Medicine, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai 200127, China. qihuafu@hotmail.com.
Insights
Chromosomal microarray (CMA) testing effectively identifies copy number variants (CNVs) in congenital heart defects (CHD) patients, with a diagnostic yield up to 18.5%. This study highlights CMA as a valuable first-line genetic tool for diagnosing CHD and discovering novel candidate genes.
Area of Science:
- Genetics
- Pediatrics
- Medical Diagnostics
Background:
- Congenital heart defects (CHD) are common congenital anomalies often linked to pathogenic copy number variants (CNVs).
- Chromosomal microarray (CMA) is routinely used for CHD patients, but its diagnostic yield in large cohorts requires further evaluation.
- This study retrospectively analyzed CNVs in 514 CHD cases from two distinct cohorts.
Purpose of the Study:
- To evaluate the diagnostic yield of CMA in a large cohort of congenital heart defect (CHD) patients.
- To identify novel candidate genes associated with CHD through genotype-phenotype analysis and gene prioritization.
- To assess the utility of CMA as a first-line genetic diagnostic tool for CHD.
Main Methods:
- Retrospective analysis of copy number variants (CNVs) in 514 congenital heart defect (CHD) cases.
- Utilized chromosomal microarray (CMA) testing for genetic analysis.
- Employed genotype-phenotype analysis and integrated multiple tools for novel CHD candidate gene identification.
Main Results:
- The overall diagnostic yield of CMA for CHD patients ranged from 12.8% to 18.5% (pathogenic and likely pathogenic CNVs).
- Diagnostic yield was higher in syndromic CHD (14.1-20.6%) compared to isolated CHD (4.3-9.3%).
- Identified four novel CHD-associated genomic loci and prioritized 20 candidate genes.
Conclusions:
- Chromosomal microarray (CMA) demonstrates a high clinical diagnostic yield, supporting its role as a first-line genetic test for CHD patients.
- The detected CNVs and identified candidate genes warrant further investigation for their role in CHD pathogenesis.
- This study reinforces the importance of genetic testing in understanding the etiology of congenital heart defects.
Background:
Congenital heart defects (CHD), as the most common congenital anomaly, have been reported to be frequently associated with pathogenic copy number variants (CNVs). Currently, patients with CHD are routinely offered chromosomal microarray (CMA) testing, but the diagnostic yield of CMA on CHD patients has not been extensively evaluated based on a large patient cohort. In this study, we retrospectively assessed the detected CNVs in a total of 514 CHD cases (a 422-case clinical cohort from Boston Children's Hospital (BCH) and a 92-case research cohort from Shanghai Children's Medical Center (SCMC)) and conducted a genotype-phenotype analysis. Furthermore, genes encompassed in pathogenic/likely pathogenic CNVs were prioritized by integrating several tools and public data sources for novel CHD candidate gene identification.
Results:
Based on the BCH cohort, the overall diagnostic yield of CMA testing for CHD patients was 12.8(pathogenic CNVs)-18.5% (pathogenic and likely pathogenic CNVs). The diagnostic yield of CMA for syndromic CHD was 14.1-20.6% (excluding aneuploidy cases), whereas the diagnostic yield for isolated CHD was 4.3-9.3%. Four recurrent genomic loci (4q terminal region, 15q11.2, 16p12.2 and Yp11.2) were more significantly enriched in cases than in controls. These regions are considered as novel CHD loci. We further identified 20 genes as the most likely novel CHD candidate genes through gene prioritization analysis.
Conclusion:
The high clinical diagnostic yield of CMA in this study provides supportive evidence for CMA as the first-line genetic diagnostic tool for CHD patients. The CNVs detected in our study suggest a number of CHD candidate genes that warrant further investigation.
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