Database Methods for Copy Number Variant Analysis of One Hundred Disease Associated Genes in Human Congenital Heart Disease

Human genetic variation occurs more commonly than was recognized after the completion of the Human Genome Sequencing Project in 2003. Submicroscopic human DNA analysis has revealed copy number variation (CNV) as the deletion or duplication of a genomic region potentially affecting gene dosage. Advanced genetic research now includes the study of CNVs in diseased subject groups compared to in house controls or online published datasets of control CNV data. Research labs choose from different bioinformatic algorithms to make the copy number calls. Solutions for further processing the copy number data into quantifiable form require collaboration with data analysts and include the use of relational databases. The aim of this thesis work was to develop a relational database solution for human copy number variation in subjects with cardiac malformations. The multipurpose database served as a central repository for the cohort demographic data as well as the entire experimental set of copy number variant data. Quantification and frequency analyses of the CNVs were executed via SQL queries. Database SQL queries generated raw data used for essential visualization tools including a detailed subject profile and a one hundred gene CNV spectra. The stated purpose of the study was to develop a descriptive analysis of genomic copy number associations in a well phenotyped congenital heart disease (CHD) population over one hundred disease associated genes. The relational database created to advance the research proved valuable in its data storage and retrieval capacity. Results showing consistency with published literature validated the accuracy of the query results generated for the CHD cohort

Human gene copy number spectra analysis in congenital heart malformations

The clinical significance of copy number variants (CNVs) in congenital heart disease (CHD) continues to be a challenge. Although CNVs including genes can confer disease risk, relationships between gene dosage and phenotype are still being defined. Our goal was to perform a quantitative analysis of CNVs involving 100 well-defined CHD risk genes identified through previously published human association studies in subjects with anatomically defined cardiac malformations. A novel analytical approach permitting CNV gene frequency “spectra” to be computed over prespecified regions to determine phenotype-gene dosage relationships was employed. CNVs in subjects with CHD (n = 945), subphenotyped into 40 groups and verified in accordance with the European Paediatric Cardiac Code, were compared with two control groups, a disease-free cohort (n = 2,026) and a population with coronary artery disease (n = 880). Gains (≥200 kb) and losses (≥100 kb) were determined over 100 CHD risk genes and compared using a Barnard exact test. Six subphenotypes showed significant enrichment (P ≤ 0.05), including aortic stenosis (valvar), atrioventricular canal (partial), atrioventricular septal defect with tetralogy of Fallot, subaortic stenosis, tetralogy of Fallot, and truncus arteriosus. Furthermore, CNV gene frequency spectra were enriched (P ≤ 0.05) for losses at: FKBP6, ELN, GTF2IRD1, GATA4, CRKL, TBX1, ATRX, GPC3, BCOR, ZIC3, FLNA and MID1; and gains at: PRKAB2, FMO5, CHD1L, BCL9, ACP6, GJA5, HRAS, GATA6 and RUNX1. Of CHD subjects, 14% had causal chromosomal abnormalities, and 4.3% had likely causal (significantly enriched), large, rare CNVs. CNV frequency spectra combined with precision phenotyping may lead to increased molecular understanding of etiologic pathways