The eMERGE genotype set of 83,717 subjects imputed to ~40 million variants genome wide and association with the herpes zoster medical record phenotype

Abstract

The Electronic Medical Records and Genomics (eMERGE) network is a network of medical centers with electronic medical records linked to existing biorepository samples for genomic discovery and genomic medicine research. The network sought to unify the genetic results from 78 Illumina and Affymetrix genotype array batches from 12 contributing medical centers for joint association analysis of 83,717 human participants. In this report, we describe the imputation of eMERGE results and methods to create the unified imputed merged set of genome-wide variant genotype data. We imputed the data using the Michigan Imputation Server, which provides a missing single-nucleotide variant genotype imputation service using the minimac3 imputation algorithm with the Haplotype Reference Consortium genotype reference set. We describe the quality control and filtering steps used in the generation of this data set and suggest generalizable quality thresholds for imputation and phenotype association studies. To test the merged imputed genotype set, we replicated a previously reported chromosome 6 HLA-B herpes zoster (shingles) association and discovered a novel zoster-associated loci in an epigenetic binding site near the terminus of chromosome 3 (3p29).

Keywords: GWAS; electronic medical records; genotypes; herpes zoster; variants.

Figure 1

PCA and Screen plot using MAF 5%, LD‐pruned R‐square of 0.7 and missingness of 10% by joint ancestry, and stratified by African, Asian, and European ancestry PCAs defined by the intersection of the k‐means and observed/self‐reported race. LD: linkage disequilibrium; MAF: minor allele frequency; PCA: principal component analysis

Figure 2

Z0 Z1 identity by descent plot of eMERGE 3 imputation (n = 3,504,226,187 pairwise comparisons). eMERGE: Electronic Medical Records and Genomics

Figure 3

Plots of genotype array batch mean R‐square imputation quality regression variables of samples size (a) and variant count (b). Histogram (c) of each variants mean R‐square imputation quality across imputation batches. Boxplots (d) of variants mean R‐square imputation quality by frequency bins

Figure 4

The chromosomes 1–22 inbreeding coefficient F, as a measure of homozygosity plotted versus the batch mean R‐square imputation quality in the top panel and k‐means Principal component analysis ancestries in the top and bottom panels

Figure 5

Joint ancestry GWAS Manhattan (left panel) and quantile–quantile plots (right panel) of herpes zoster (shingles) with 3,763 cases and 42,587 controls. Variant inclusion stringency is set to R‐square of ≥0.3 and minor allele frequency of ≥0.05. Covariate adjustments were made for PCs 1, 2, and 3, gender and the nine contributing medical centers which were included. Genomic control is close to one with a λ of ~1.02

Figure 6

Chromosome 3p29 site LocusZoom plot of zoster association in the joint ancestry regressions. SNP: single‐nucleotide polymorphism; TFBS: transcription factor binding site

Figure 7

Chromosome 6 HLA‐B LocusZoom plot of zoster association in the joint ancestry regressions. SNP: single‐nucleotide polymorphism