A phenome-wide association study of copy number variation
Approved Research ID: 17731
Approval date: January 24th 2017
To identify changes in the DNA, particularly large deletions and duplications of the genome, that are related to complex diseases and intermediate biomarkers The identification of genetic risk factors that are related to disease will help reveal the underlying biology and thereby expose targets for environmental modification and/or novel drug development. We will use the raw Affymetrix Axiom data (.CEL files) and apply a principal components analysis on these intensities to correct for DNA quality and batch effects. We will then perform a joint calling across all samples to determine potential deletions and duplications using our soon to be open-source Genvisis software package, which will also assess the quality of these calls and filter them down to a set of high quality calls (~1 year to complete). We will then associate the high quality calls with the phenotypes available, and replicate any findings using external data sources (~1 additional year). Full cohort; all samples with high quality intensity data will be analyzed.
Current scope: To identify changes in the DNA, particularly large deletions and duplications of the genome, that are related to complex diseases and intermediate biomarkers.
1) Study the impact of mitochondrial DNA copy number, heteroplasmy, and homoplasmy on overall mortality and aging-related disease.
2) Assess the role of mitochondrial genetic variation with chronic kidney disease prevalence (CKD), incidence and complications including cardiovascular disease risk prediction equations with additional established and novel biomarkers.
3) Study the impact of common variant polygenic risk scores and rare variants on the join risk of multiple common disease conditions, including cancer, type-2 diabetes, cardiovascular diseases, and overall mortality.
4) Study the role of rare mutations in telomere and telomerase genes in cancer risk, both solid tumors and hematologic malignancies. We will correlate the prevalence of cancers among patients with mutations in known telomere length maintenance genes as well as novel candidates.