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The Metabochip is a custom genotyping array designed for replication and fine mapping of metabolic, cardiovascular, and anthropometric trait loci and includes low frequency variation content identified from the 1000 Genomes Project. It has 196,725 SNPs concentrated in 257 genomic regions. We evaluated the Metabochip in 5,863 African Americans; 89% of all SNPs passed rigorous quality control with a call rate of 99.9%. Two examples illustrate the value of fine mapping with the Metabochip in African-ancestry populations. At CELSR2/PSRC1/SORT1, we found the strongest associated SNP for LDL-C to be rs12740374 (p = 3.5 × 10(-11)), a SNP indistinguishable from multiple SNPs in European ancestry samples due to high correlation. Its distinct signal supports functional studies elsewhere suggesting a causal role in LDL-C. At CETP we found rs17231520, with risk allele frequency 0.07 in African Americans, to be associated with HDL-C (p = 7.2 × 10(-36)). This variant is very rare in Europeans and not tagged in common GWAS arrays, but was identified as associated with HDL-C in African Americans in a single-gene study. Our results, one narrowing the risk interval and the other revealing an associated variant not found in Europeans, demonstrate the advantages of high-density genotyping of common and rare variation for fine mapping of trait loci in African American samples.

Several regions of the genome show pleiotropic associations with multiple cancers. We sought to evaluate whether 181 single-nucleotide polymorphisms previously associated with various cancers in genome-wide association studies were also associated with melanoma risk. We evaluated 2,131 melanoma cases and 20,353 controls from three studies in the Population Architecture using Genomics and Epidemiology (PAGE) study (EAGLE-BioVU, MEC, WHI) and two collaborating studies (HPFS, NHS). Overall and sex-stratified analyses were performed across studies. We observed statistically significant associations with melanoma for two lung cancer SNPs in the TERT-CLPTM1L locus (Bonferroni-corrected p<2.8x10-4), replicating known pleiotropic effects at this locus. In sex-stratified analyses, we also observed a potential male-specific association between prostate cancer risk variant rs12418451 and melanoma risk (OR=1.22, p=8.0x10-4). No other variants in our study were associated with melanoma after multiple comparisons adjustment (p>2.8e-4). We provide confirmatory evidence of pleiotropic associations with melanoma for two SNPs previously associated with lung cancer, and provide suggestive evidence for a male-specific association with melanoma for prostate cancer variant rs12418451. This SNP is located near TPCN2, an ion transport gene containing SNPs which have been previously associated with hair pigmentation but not melanoma risk. Previous evidence provides biological plausibility for this association, and suggests a complex interplay between ion transport, pigmentation, and melanoma risk that may vary by sex. If confirmed, these pleiotropic relationships may help elucidate shared molecular pathways between cancers and related phenotypes.

The feasibility of using imperfectly phenotyped \"silver standard\" samples identified from electronic medical record diagnoses is considered in genetic association studies when these samples might be combined with an existing set of samples phenotyped with a gold standard technique. An analytic expression is derived for the power of a chi-square test of independence using either research-quality case/control samples alone, or augmented with silver standard data. The subset of the parameter space where inclusion of silver standard samples increases statistical power is identified. A case study of dementia subjects identified from electronic medical records from the Electronic Medical Records and Genomics (eMERGE) network, combined with subjects from two studies specifically targeting dementia, verifies these results.

White blood cell count (WBC) is unique among identified inflammatory predictors of chronic disease in that it is routinely measured in asymptomatic patients in the course of routine patient care. We led a genome-wide association analysis to identify variants associated with WBC levels in 13,923 subjects in the electronic Medical Records and Genomics (eMERGE) Network. We identified two regions of interest that were each unique to subjects of genetically determined ancestry to the African continent (AA) or to the European continent (EA). WBC varies among different ancestry groups. Despite being ancestry specific, these regions were identifiable in the combined analysis. In AA subjects, the region surrounding the Duffy antigen/chemokine receptor gene ( DARC ) on 1q21 exhibited significant association ( p value = 6.71e−55). These results validate the previously reported association between WBC and of the regulatory variant rs2814778 in the promoter region, which causes the Duffy negative phenotype (Fy−/−). A second missense variant (rs12075) is responsible for the two principal antigens, Fya and Fyb of the Duffy blood group system. The two variants, consisting of four alleles, act in concert to produce five antigens and subsequent phenotypes. We were able to identify the marginal and novel interaction effects of these two variants on WBC. In the EA subjects, we identified significantly associated SNPs tagging three separate genes in the 17q21 region: (1) GSDMA , (2) MED24 , and (3) PSMD3. Variants in this region have been reported to be associated with WBC, neutrophil count, and inflammatory diseases including asthma and Crohn’s disease.

Objective Genome-wide association studies have identified a large number of single nucleotide polymorphisms (SNPs) associated with a wide array of cancer sites. Several of these variants demonstrate associations with multiple cancers, suggesting pleiotropic effects and shared biological mechanisms across some cancers. We hypothesised that SNPs previously associated with other cancers may additionally be associated with colorectal cancer. In a large-scale study, we examined 171 SNPs previously associated with 18 different cancers for their associations with colorectal cancer. Design We examined 13 338 colorectal cancer cases and 40 967 controls from three consortia: Population Architecture using Genomics and Epidemiology (PAGE), Genetic Epidemiology of Colorectal Cancer (GECCO), and the Colon Cancer Family Registry (CCFR). Study-specific logistic regression results, adjusted for age, sex, principal components of genetic ancestry, and/or study specific factors (as relevant) were combined using fixed-effect meta-analyses to evaluate the association between each SNP and colorectal cancer risk. A Bonferroni-corrected p value of 2.92×10−4 was used to determine statistical significance of the associations. Results Two correlated SNPs—rs10090154 and rs4242382—in Region 1 of chromosome 8q24, a prostate cancer susceptibility region, demonstrated statistically significant associations with colorectal cancer risk. The most significant association was observed with rs4242382 (meta-analysis OR=1.12; 95% CI 1.07 to 1.18; p=1.74×10−5), which also demonstrated similar associations across racial/ethnic populations and anatomical sub-sites. Conclusions This is the first study to clearly demonstrate Region 1 of chromosome 8q24 as a susceptibility locus for colorectal cancer; thus, adding colorectal cancer to the list of cancer sites linked to this particular multicancer risk region at 8q24.

Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype–phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP × smoking interactions.

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes by using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average of 39% improvement in imputation accuracy and generated effective imputation models for an average of 120% more genes. We describe a summary-statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene–trait association. We applied our method, called UTMOST (unified test for molecular signatures), to multiple genome-wide-association results and demonstrate its advantages over single-tissue strategies. UTMOST (unified test for molecular signatures) is a method for cross-tissue gene expression imputation for transcriptome-wide association analyses. Cross-tissue TWAS using UTMOST identifies new candidate genes for late-onset Alzheimer’s disease.

Gerard Schellenberg and colleagues report a genome-wide association study of late-onset Alzheimer's disease (LOAD), as part of the Alzheimer Disease Genetics Consortium. They identify common variants in MS4A4/MS4A6E , CD2AP , CD33 and EPHA1 associated with LOAD. The Alzheimer Disease Genetics Consortium (ADGC) performed a genome-wide association study of late-onset Alzheimer disease using a three-stage design consisting of a discovery stage (stage 1) and two replication stages (stages 2 and 3). Both joint analysis and meta-analysis approaches were used. We obtained genome-wide significant results at MS4A4A (rs4938933; stages 1 and 2, meta-analysis P ( P M ) = 1.7 × 10 −9 , joint analysis P ( P J ) = 1.7 × 10 −9 ; stages 1, 2 and 3, P M = 8.2 × 10 −12 ), CD2AP (rs9349407; stages 1, 2 and 3, P M = 8.6 × 10 −9 ), EPHA1 (rs11767557; stages 1, 2 and 3, P M = 6.0 × 10 −10 ) and CD33 (rs3865444; stages 1, 2 and 3, P M = 1.6 × 10 −9 ). We also replicated previous associations at CR1 (rs6701713; P M = 4.6 × 10 −10 , P J = 5.2 × 10 −11 ), CLU (rs1532278; P M = 8.3 × 10 −8 , P J = 1.9 × 10 −8 ), BIN1 (rs7561528; P M = 4.0 × 10 −14 , P J = 5.2 × 10 −14 ) and PICALM (rs561655; P M = 7.0 × 10 −11 , P J = 1.0 × 10 −10 ), but not at EXOC3L2 , to late-onset Alzheimer's disease susceptibility 1 , 2 , 3 .