1000 Genomes-based imputation identifies novel and refined associations for the Wellcome Trust Case Control Consortium phase 1 Data

Abstract

We hypothesize that imputation based on data from the 1000 Genomes Project can identify novel association signals on a genome-wide scale due to the dense marker map and the large number of haplotypes. To test the hypothesis, the Wellcome Trust Case Control Consortium (WTCCC) Phase I genotype data were imputed using 1000 genomes as reference (20100804 EUR), and seven case/control association studies were performed using imputed dosages. We observed two 'missed' diseaseassociated variants that were undetectable by the original WTCCC analysis, but were reported by later studies after the 2007 WTCCC publication. One is within the IL2RA gene for association with type 1 diabetes and the other in proximity with the CDKN2B gene for association with type 2 diabetes. We also identified two refined associations. One is SNP rs11209026 in exon 9 of IL23R for association with Crohn's disease, which is predicted to be probably damaging by PolyPhen2. The other refined variant is in the CUX2 gene region for association with type 1 diabetes, where the newly identified top SNP rs1265564 has an association P-value of 1.68Â10 À16 . The new lead SNP for the two refined loci provides a more plausible explanation for the disease association. We demonstrated that 1000 Genomes-based imputation could indeed identify both novel (in our case, 'missed' because they were detected and replicated by studies after 2007) and refined signals. We anticipate the findings derived from this study to provide timely information when individual groups and consortia are beginning to engage in 1000 genomes-based imputation.

A unified approach for allele frequency estimation, SNP detection and association studies based on pooled sequencing data using EM algorithms

“…This SNP was not reported to be associated with any phenotypes according to the catalog of GWAS studies (http://www.genome.gov/gwastudies/) to date. Nevertheless, other SNPs within the IL2RA gene were found to be associated with T1D by Cooper et al [26] before the publication of [8] and by two other studies [27,28] after the publication of [8] using different approaches. Barrett et al [27] used genome-wide association studies giving a p-value of 1.0e-13 while Huang et al [28] used imputation of the genotypes based on the 1000 genome projects yielding a p-value of 5e-9.…”

Improving accuracy of rare variant imputation with a two-step imputation approach

“…To evaluate the gain of power and improvement in means of novel findings in the GWAS setting, a future effort should focus on applying the two-step approach to entire data sets, as earlier applied when analyzing the difference between HapMap and 1000 G imputation. 9 This comparison would surely require large sample sizes and the combination of several studies before an assessment of its value at meta-analysis level can be done.…”

“…[4][5][6] Lowfrequency variants have not been scrutinized by most GWAS based on HapMap content. 7 Using newer reference panels for imputation will allow this (eg, the 1000 Genomes project based on resequenced data sets) with more variants with lower frequencies for the association analysis with traits 8 hereby increasing resolution and improving power 9,10 within the so-called next-generation GWAS. Newer arrays have been designed including marker content in the low-frequency spectrum.…”

Genomic Loci Evaluation with Albuminuria in New-Onset Insulin Dependent Diabetic Patients

“…The most prominent gene in the peak is the cut-like homeobox 2 (CUX2) gene. The CUX2 gene region has recently been associated with Type 1 diabetes in the 1000 Genomes Project using data from the WellcomeTrust Case Control Consortium [22]. To our knowledge this is its first association with albuminuria.…”