Examining the Impact of Imputation Errors on Fine-Mapping Using DNA Methylation QTL as a Model Trait

V Kartik Chundru, Riccardo E Marioni, James G D Prendergast, Costanza L Vallerga, Tian Lin, Allan J Berveridge, Sgpd Consortium, Jacob Gratten, David A Hume, Ian J Deary, Naomi R Wray, Peter M Visscher, Allan F McRae

Research output: Contribution to journalArticlepeer-review

Abstract

Genetic variants disrupting DNA methylation at CpG dinucleotides (CpG-SNP) provide a set of known causal variants to serve as models for testing fine-mapping methodology. We use 1716 CpG-SNPs to test three fine-mapping approaches (BIMBAM, BSLMM, and the J-test), assessing the impact of imputation errors and the choice of reference panel by using both whole-genome sequence (WGS), and genotype array data on the same individuals (n=1166). The choice of imputation reference panel had a strong effect on imputation accuracy, with the 1000 Genomes Phase 3 (1000G) reference panel (n=2504 from 26 populations) giving a mean non-reference discordance rate between imputed and sequenced genotypes of 3.2% compared to 1.6% when using the Haplotype Reference Consortium (HRC) reference panel (n=32470 Europeans). These imputation errors impacted on whether the CpG-SNP was included in the 95% credible set, with a difference of ∼ 23% and ∼ 7% between the WGS and the 1000G and HRC imputed datasets respectively. All of the fine-mapping methods failed to reach the expected 95% coverage of the CpG-SNP. This is attributed to secondary cis genetic effects that are unable to be statistically separated from the CpG-SNP, and through a masking mechanism where the effect of the methylation disrupting allele at the CpG-SNP is hidden by the effect of a nearby SNP that has strong LD with the CpG-SNP. The reduced accuracy in fine-mapping a known causal variant in a low level biological trait with imputed genetic data has implications for the study of higher order complex traits and disease.

Original languageEnglish
JournalGenetics
Early online date30 Apr 2019
DOIs
Publication statusE-pub ahead of print - 30 Apr 2019

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