Fast and accurate genotype imputation in genome-wide association studies through pre-phasing

The 1000 Genomes Project and disease-specific sequencing efforts are producing large collections of haplotypes that can be used as reference panels for genotype imputation in genome-wide association studies (GWAS). However, imputing from large reference panels with existing methods imposes a high computational burden. We introduce a strategy called 'pre-phasing' that maintains the accuracy of leading methods while reducing computational costs. We first statistically estimate the haplotypes for each individual within the GWAS sample (pre-phasing) and then impute missing genotypes into these estimated haplotypes. This reduces the computational cost because (i) the GWAS samples must be phased only once, whereas standard methods would implicitly repeat phasing with each reference panel update, and (ii) it is much faster to match a phased GWAS haplotype to one reference haplotype than to match two unphased GWAS genotypes to a pair of reference haplotypes. We implemented our approach in the MaCH and IMPUTE2 frameworks, and we tested it on data sets from the Wellcome Trust Case Control Consortium 2 (WTCCC2), the Genetic Association Information Network (GAIN), the Women's Health Initiative (WHI) and the 1000 Genomes Project. This strategy will be particularly valuable for repeated imputation as reference panels evolve.     

Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and approximately 2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 x 10(-14)), CDC123-CAMK1D (P = 1.2 x 10(-10)), TSPAN8-LGR5 (P = 1.1 x 10(-9)), THADA (P = 1.1 x 10(-9)), ADAMTS9 (P = 1.2 x 10(-8)) and NOTCH2 (P = 4.1 x 10(-8)) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.     

Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies

Genome-wide association is a promising approach to identify common genetic variants that predispose to human disease. Because of the high cost of genotyping hundreds of thousands of markers on thousands of subjects, genome-wide association studies often follow a staged design in which a proportion (pi(samples)) of the available samples are genotyped on a large number of markers in stage 1, and a proportion (pi(samples)) of these markers are later followed up by genotyping them on the remaining samples in stage 2. The standard strategy for analyzing such two-stage data is to view stage 2 as a replication study and focus on findings that reach statistical significance when stage 2 data are considered alone. We demonstrate that the alternative strategy of jointly analyzing the data from both stages almost always results in increased power to detect genetic association, despite the need to use more stringent significance levels, even when effect sizes differ between the two stages. We recommend joint analysis for all two-stage genome-wide association studies, especially when a relatively large proportion of the samples are genotyped in stage 1 (pi(samples) >or= 0.30), and a relatively large proportion of markers are selected for follow-up in stage 2 (pi(markers) >or= 0.01).     

Gene polymorphism in Netherton and common atopic disease.

Atopic dermatitis (AD) and asthma are characterized by IgE-mediated atopic (allergic) responses to common proteins (allergens), many of which are proteinases. Loci influencing atopy have been localized to a number of chromosomal regions, including the chromosome 5q31 cytokine cluster. Netherton disease is a rare recessive skin disorder in which atopy is a universal accompaniment. The gene underlying Netherton disease (SPINK5) encodes a 15-domain serine proteinase inhibitor (LEKTI) which is expressed in epithelial and mucosal surfaces and in the thymus. We have identified six coding polymorphisms in SPINK5 (Table 1) and found that a Glu420-->Lys variant shows significant association with atopy and AD in two independent panels of families. Our results implicate a previously unrecognized pathway for the development of common allergic illnesses.     

Positional cloning of a novel gene influencing asthma from chromosome 2q14

Asthma is a common disease in children and young adults. Four separate reports have linked asthma and related phenotypes to an ill-defined interval between 2q14 and 2q32 (refs. 1-4), and two mouse genome screens have linked bronchial hyper-responsiveness to the region homologous to 2q14 (refs. 5,6). We found and replicated association between asthma and the D2S308 microsatellite, 800 kb distal to the IL1 cluster on 2q14. We sequenced the surrounding region and constructed a comprehensive, high-density, single-nucleotide polymorphism (SNP) linkage disequilibrium (LD) map. SNP association was limited to the initial exons of a solitary gene of 3.6 kb (DPP10), which extends over 1 Mb of genomic DNA. DPP10 encodes a homolog of dipeptidyl peptidases (DPPs) that cleave terminal dipeptides from cytokines and chemokines, and it presents a potential new target for asthma therapy.     

CFH haplotypes without the Y402H coding variant show strong association with susceptibility to age-related macular degeneration

In developed countries, age-related macular degeneration is a common cause of blindness in the elderly. A common polymorphism, encoding the sequence variation Y402H in complement factor H (CFH), has been strongly associated with disease susceptibility. Here, we examined 84 polymorphisms in and around CFH in 726 affected individuals (including 544 unrelated individuals) and 268 unrelated controls. In this sample, 20 of these polymorphisms showed stronger association with disease susceptibility than the Y402H variant. Further, no single polymorphism could account for the contribution of the CFH locus to disease susceptibility. Instead, multiple polymorphisms defined a set of four common haplotypes (of which two were associated with disease susceptibility and two seemed to be protective) and multiple rare haplotypes (associated with increased susceptibility in aggregate). Our results suggest that there are multiple disease susceptibility alleles in the region and that noncoding CFH variants play a role in disease susceptibility.     

Human Genome Variation 2006: emerging views on structural variation and large-scale SNP analysis

The eighth annual Human Genome Variation Meeting was held in September 2006 in the Hong Kong Special Administrative Region, China. The meeting highlighted recent advances in characterization of genetic variation, including genome-wide association studies and structural variation.