medRxivGenetic & Genomic MedicinePreprint
Phenome-wide association of multiallelic copy number variation in 422,170 UK Biobank individuals reveals novel genetic loci associated with disease
Micaela EisenbergiD, Richard J. PackeriD, Nick R. G. ShrineiD, German M. DemidoviD, Harry Pack, Edward J. HolloxiD, Katherine A. FawcettiD
Abstract
The contribution of multi-allelic CNVs (mCNVs) to disease risk has not been widely studied. This is largely because they have been difficult to characterise at a large-scale genome-wide, and are often not strongly associated with flanking SNVs, limiting imputation. Improved understanding of the role of mCNVs in disease risk could lead to novel insights into the pathobiology of disease. We robustly typed 69 mCNVs from UK Biobank whole exome sequences in discovery (n=150,682) and replication sets (n=269,317). Discovery and replication PheWAS used clinically-curated composite phenotypes by integrating self-report, primary and secondary health care data to interrogate these variants, for unrelated British individuals of African, European and Central/South Asian ancestries. 173 mCNV-phenotype associations were detected from 26 mCNVs, of which 114 associations replicated. One of eight potentially novel mCNV-phenotype signals was independent of neighbouring associated SNVs, the association of Sulfotransferase 1A1 and 1A2 genes (SULT1A1/SULT1A2) with estimated glomerular filtration rate (eGFR) in individuals of European ancestry (meta-analysed p=1.05x10-9, beta=0.016 [0.011; 0.021]). Other potentially novel associations include Golgi phosphoprotein 3 (GOLPH3) with the cardiovascular phenotype bundle branch block in individuals of South Asian ancestry (meta-analysed p=3.35x10-6, OR=2.13 [1.53, 2.96]) and alpha amylase 2B (AMY2B) with ventricular fibrillation and flutter in individuals of European ancestry (meta-analysed p=2.48x10-6, OR=1.50 [1.26; 1.78]). In summary, we show that accurate typing of biobank-scale sample sizes can identify associations between traits and mCNVs, acting through a gene dosage relationship. Our work provides several novel likely causative variants contributing to particular traits of clinical importance and immediately suggest a putative functional mechanism for the observed associations.
- organism: human
- assay: whole-exome sequencing
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 1
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