Assessment of Genotype Imputation Performance Using 1000 Genomes in African American Studies

<div><p>Genotype imputation, used in genome-wide association studies to expand coverage of single nucleotide polymorphisms (SNPs), has performed poorly in African Americans compared to less admixed populations. Overall, imputation has typically relied on HapMap reference haplotype panels from Africans (YRI), European Americans (CEU), and Asians (CHB/JPT). The 1000 Genomes project offers a wider range of reference populations, such as African Americans (ASW), but their imputation performance has had limited evaluation. Using 595 African Americans genotyped on Illumina’s HumanHap550v3 BeadChip, we compared imputation results from four software programs (IMPUTE2, BEAGLE, MaCH, and MaCH-Admix) and three reference panels consisting of different combinations of 1000 Genomes populations (February 2012 release): (1) 3 specifically selected populations (YRI, CEU, and ASW); (2) 8 populations of diverse African (AFR) or European (AFR) descent; and (3) all 14 available populations (ALL). Based on chromosome 22, we calculated three performance metrics: (1) concordance (percentage of masked genotyped SNPs with imputed and true genotype agreement); (2) imputation quality score (IQS; concordance adjusted for chance agreement, which is particularly informative for low minor allele frequency [MAF] SNPs); and (3) average r2hat (estimated correlation between the imputed and true genotypes, for all imputed SNPs). Across the reference panels, IMPUTE2 and MaCH had the highest concordance (91%–93%), but IMPUTE2 had the highest IQS (81%–83%) and average r2hat (0.68 using YRI+ASW+CEU, 0.62 using AFR+EUR, and 0.55 using ALL). Imputation quality for most programs was reduced by the addition of more distantly related reference populations, due entirely to the introduction of low frequency SNPs (MAF≤2%) that are monomorphic in the more closely related panels. While imputation was optimized by using IMPUTE2 with reference to the ALL panel (average r2hat = 0.86 for SNPs with MAF>2%), use of the ALL panel for African American studies requires careful interpretation of the population specificity and imputation quality of low frequency SNPs.</p> </div

Average r2hat values resulting from four different imputation programs and three different 1000 Genomes (February 2012) reference panels.

<p>r2hat values were averaged across all imputed SNPs on chromosome 22. The number of subjects corresponding to each reference panel is shown in parentheses.</p

Concordance resulting from four different imputation programs and three different 1000 Genomes (February 2012 release) reference panels.

<p>Concordance rates were based on masking 2% of the genotyped SNPs on chromosome 22 and comparing imputed and true genotypes. The number of subjects corresponding to each reference panel is shown in parentheses.</p

Imputation quality score (IQS) resulting from four different imputation programs and three different 1000 Genomes (February 2012) reference panels.

<p>IQS results were based on masking 2% of the genotyped SNPs and adjusting the concordance rate chance agreement between imputed and true genotypes. The number of subjects corresponding to each reference panel is shown in parentheses.</p

Average r2hat, based on imputation using IMPUTE2, across the minor allele frequency (MAF) spectrum.

<p>Imputation was conducted for all SNPs available on the YRI+CEU+ASW (N = 234, in red), AFR+EUR (N = 625, in green), or the ALL (N = 1,092, in blue) reference panel from 1000 Genomes. Imputed polymorphic SNPs were divided into MAF intervals of 1%, and their average r2hat values were calculated within each interval.</p

Results of literature screen of 237 filtered candidate variants.

<p>These graphs compare the number of variants per person at different stages of the literature screen across the four major ancestry groups in the 1000 Genomes dataset. A) Compares the contribution of variants that were removed because of a high frequency in reference datasets to all of the other filtered variants. B) Compares the contribution to variants per person of all of the filtered variants that did not have a high frequency in reference datasets. Specifically, it compares the contribution of variants with evidence against a conclusion of pathogenicity, a lack of supportive evidence, literature on a different disorder, or those that were retained for specialist review.</p

Scatterplots of IQS, squared correlation, and BEAGLE R² using the cosmopolitan reference panel and the African American nicotine dependence study sample for chromosome 15.

<p>Data for all 1,545 variants are displayed in panel A, B, and C while the results for variants with MAF>5% (N = 631) are found in panel D, E, and F. These results were generated using Omni SNP coverage. The line y = x is denoted in red.</p

Number of candidate variants after different review stages.

<p>* Genes for which novel, expected pathogenic variants should be returned.</p><p>Number of candidate variants after different review stages.</p

Scatterplots of squared correlation and IQS.

<p>Data for all 13,442 variants are displayed in panel A, while the results for variants with MAF>5% (N = 6,480) are found in panel B. The line y = x is denoted in red.</p

Additional expected pathogenic variants that meet criteria for disclosure as secondary findings.

<p>^<i>a</i>AMR, the Americas.</p><p>^<i>b</i>EUR, European.</p><p>^<i>c</i>ASN, East Asian.</p><p>Additional expected pathogenic variants that meet criteria for disclosure as secondary findings.</p