Journal of Medical GeneticsGenomicsPeer-reviewed journal article
Medical consequences of pathogenic CNVs in adults: Analysis of the UK Biobank
Karen Crawford, Matthew Bracher‐SmithiD, David C. OweniD, Kimberley Marie KendalliD, Elliott ReesiD, Antonio F. PardiñasiD, Mark EinoniD, Valentina Escott‐PriceiD, James WaltersiD, Michael C. O’DonovaniD, Michael John OweniD, George KiroviD
Abstract
BackgroundGenomic copy number variants (CNVs) increase risk for early-onset neurodevelopmental disorders but their impact on medical outcomes in later life is poorly understood. The UK Biobank, with half a million well-phenotyped adults, presents an opportunity to study the medical consequences of CNV in middle and old age.\n\nMethodsWe called 54 CNVs associated with clinical phenotypes or genomic disorders, including their reciprocal deletions or duplications, in all Biobank participants. We used logistic regression analysis to test CNVs for associations with 58 common medical phenotypes.\n\nFindingsCNV carriers had an increased risk of developing 37 of the 58 phenotypes at nominal levels of statistical significance, with 19 associations surviving Bonferroni correction (p<8{middle dot}6x10-4). Tests of each of the 54 CNVs for association with each of the 58 phenotypes identified 18 associations that survived Bonferroni correction (p<1{middle dot}6x10-5) and a further 57 that were associated at a false discovery rate (FDR) threshold of 0{middle dot}1. Thirteen CNVs had three or more significant associations at FDR=0{middle dot}1, with the largest number of phenotypes (N=15) found for deletions at 16p11{middle dot}2. The most common CNVs (frequency 0{middle dot}5-0{middle dot}7%) have no or minimal impact on medical outcomes in adults.\n\nInterpretationSome of the 54 tested CNVs have profound effects on physical health, even in people who have largely escaped early neurodevelopmental outcomes. Our work provides clinicians with a morbidity map of potential outcomes among carriers of these CNVs.\n\nFundingMRC UK, Wellcome Trust UK
- organism: human
- assay: whole-genome sequencing
- research focus: differential expression
- approach: statistical model
- Citations
- 175
- FWCI
- 8.28
- Field percentile
- top 2%
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