Anuar Konkashbaev

SCAN: SNP and copy number annotation

MOTIVATION Genome-wide association studies (GWAS) generate relationships between hundreds of thousands of single nucleotide polymorphisms (SNPs) and complex phenotypes. The contribution of the traditionally overlooked copy number variations (CNVs) to complex traits is also being actively studied. To facilitate the interpretation of the data and the designing of follow-up experimental validations, we have developed a database that enables the sensible prioritization of these variants by combining several approaches, involving not only publicly available physical and functional annotations but also multilocus linkage disequilibrium (LD) annotations as well as annotations of expression quantitative trait loci (eQTLs). RESULTS For each SNP, the SCAN database provides: (i) summary information from eQTL mapping of HapMap SNPs to gene expression (evaluated by the Affymetrix exon array) in the full set of HapMap CEU (Caucasians from UT, USA) and YRI (Yoruba people from Ibadan, Nigeria) samples; (ii) LD information, in the case of a HapMap SNP, including what genes have variation in strong LD (pairwise or multilocus LD) with the variant and how well the SNP is covered by different high-throughput platforms; (iii) summary information available from public databases (e.g. physical and functional annotations); and (iv) summary information from other GWAS. For each gene, SCAN provides annotations on: (i) eQTLs for the gene (both local and distant SNPs) and (ii) the coverage of all variants in the HapMap at that gene on each high-throughput platform. For each genomic region, SCAN provides annotations on: (i) physical and functional annotations of all SNPs, genes and known CNVs within the region and (ii) all genes regulated by the eQTLs within the region. AVAILABILITY http://www.scandb.org. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Genetic variants associated with warfarin dose in African-American individuals: a genome-wide association study

Summary Background VKORC1 and CYP2C9 are important contributors to warfarin dose variability, but explain less variability for individuals of African descent than for those of European or Asian descent. We aimed to identify additional variants contributing to warfarin dose requirements in African Americans. Methods We did a genome-wide association study of discovery and replication cohorts. Samples from African-American adults (aged ≥18 years) who were taking a stable maintenance dose of warfarin were obtained at International Warfarin Pharmacogenetics Consortium (IWPC) sites and the University of Alabama at Birmingham (Birmingham, AL, USA). Patients enrolled at IWPC sites but who were not used for discovery made up the independent replication cohort. All participants were genotyped. We did a stepwise conditional analysis, conditioning first for VKORC1 −1639G→A, followed by the composite genotype of CYP2C9*2 and CYP2C9*3. We prespecified a genome-wide significance threshold of p<5×10−8 in the discovery cohort and p<0·0038 in the replication cohort. Findings The discovery cohort contained 533 participants and the replication cohort 432 participants. After the prespecified conditioning in the discovery cohort, we identified an association between a novel single nucleotide polymorphism in the CYP2C cluster on chromosome 10 (rs12777823) and warfarin dose requirement that reached genome-wide significance (p=1·51×10−8). This association was confirmed in the replication cohort (p=5·04×10−5); analysis of the two cohorts together produced a p value of 4·5×10−12. Individuals heterozygous for the rs12777823 A allele need a dose reduction of 6·92 mg/week and those homozygous 9·34 mg/week. Regression analysis showed that the inclusion of rs12777823 significantly improves warfarin dose variability explained by the IWPC dosing algorithm (21% relative improvement). Interpretation A novel CYP2C single nucleotide polymorphism exerts a clinically relevant effect on warfarin dose in African Americans, independent of CYP2C9*2 and CYP2C9*3. Incorporation of this variant into pharmacogenetic dosing algorithms could improve warfarin dose prediction in this population. Funding National Institutes of Health, American Heart Association, Howard Hughes Medical Institute, Wisconsin Network for Health Research, and the Wellcome Trust.

Identification of Type 2 Diabetes Genes in Mexican Americans Through Genome-wide Association Studies

OBJECTIVE—The objective of this study was to identify DNA polymorphisms associated with type 2 diabetes in a Mexican-American population. RESEARCH DESIGN AND METHODS—We genotyped 116,204 single nucleotide polymorphisms (SNPs) in 281 Mexican Americans with type 2 diabetes and 280 random Mexican Americans from Starr County, Texas, using the Affymetrix GeneChip Human Mapping 100K set. Allelic association exact tests were calculated. Our most significant SNPs were compared with results from other type 2 diabetes genome-wide association studies (GWASs). Proportions of African, European, and Asian ancestry were estimated from the HapMap samples using structure for each individual to rule out spurious association due to population substructure. RESULTS—We observed more significant allelic associations than expected genome wide, as empirically assessed by permutation (14 below a P of 1 × 10−4 [8.7 expected]). No significant differences were observed between the proportion of ancestry estimates in the case and random control sets, suggesting that the association results were not likely confounded by substructure. A query of our top ∼1% of SNPs (P < 0.01) revealed SNPs in or near four genes that showed evidence for association (P < 0.05) in multiple other GWAS interrogated: rs979752 and rs10500641 near UBQLNL and OR52H1 on chromosome 11, rs2773080 and rs3922812 in or near RALGPS2 on chromosome 1, and rs1509957 near EGR2 on chromosome 10. CONCLUSIONS—We identified several SNPs with suggestive evidence for replicated association with type 2 diabetes that merit further investigation.

Genome-wide association study of Tourette's syndrome

Tourettes syndrome (TS) is a developmental disorder that has one of the highest familial recurrence rates among neuropsychiatric diseases with complex inheritance. However, the identification of definitive TS susceptibility genes remains elusive. Here, we report the first genome-wide association study (GWAS) of TS in 1285 cases and 4964 ancestry-matched controls of European ancestry, including two European-derived population isolates, Ashkenazi Jews from North America and Israel and French Canadians from Quebec, Canada. In a primary meta-analysis of GWAS data from these European ancestry samples, no markers achieved a genome-wide threshold of significance (P<5 × 10−8); the top signal was found in rs7868992 on chromosome 9q32 within COL27A1 (P=1.85 × 10−6). A secondary analysis including an additional 211 cases and 285 controls from two closely related Latin American population isolates from the Central Valley of Costa Rica and Antioquia, Colombia also identified rs7868992 as the top signal (P=3.6 × 10−7 for the combined sample of 1496 cases and 5249 controls following imputation with 1000 Genomes data). This study lays the groundwork for the eventual identification of common TS susceptibility variants in larger cohorts and helps to provide a more complete understanding of the full genetic architecture of this disorder.

Genome-wide association and meta-analysis in populations from Starr County, Texas, and Mexico City identify type 2 diabetes susceptibility loci and enrichment for expression quantitative trait loci in top signals

Aims/hypothesisWe conducted genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) analyses to identify and characterise risk loci for type 2 diabetes in Mexican-Americans from Starr County, TX, USA.MethodUsing 1.8 million directly interrogated and imputed genotypes in 837 unrelated type 2 diabetes cases and 436 normoglycaemic controls, we conducted Armitage trend tests. To improve power in this population with high disease rates, we also performed ordinal regression including an intermediate class with impaired fasting glucose and/or glucose tolerance. These analyses were followed by meta-analysis with a study of 967 type 2 diabetes cases and 343 normoglycaemic controls from Mexico City, Mexico.ResultThe top signals (unadjusted p value <1 × 10−5) included 49 single nucleotide polymorphisms (SNPs) in eight gene regions (PER3, PARD3B, EPHA4, TOMM7, PTPRD, HNT [also known as RREB1], LOC729993 and IL34) and six intergenic regions. Among these was a missense polymorphism (rs10462020; Gly639Val) in the clock gene PER3, a system recently implicated in diabetes. We also report a second signal (minimum p value 1.52 × 10−6) within PTPRD, independent of the previously implicated SNP, in a population of Han Chinese. Top meta-analysis signals included known regions HNF1A and KCNQ1. Annotation of top association signals in both studies revealed a marked excess of trans-acting eQTL in both adipose and muscle tissues.Conclusions/InterpretationIn the largest study of type 2 diabetes in Mexican populations to date, we identified modest associations of novel and previously reported SNPs. In addition, in our top signals we report significant excess of SNPs that predict transcript levels in muscle and adipose tissues.

The neutrophil alloantigen HNA-3a (5b) is located on choline transporter-like protein 2 and appears to be encoded by an R>Q154 amino acid substitution

The molecular basis of the HNA-3a/b (5b/a) leukocyte antigen system has not yet been defined despite evidence that HNA-3a-specific antibodies are particularly prone to cause severe, often fatal, transfusion-related lung injury. We used genome-wide single nucleotide polymorphism scanning and sequencing of DNA from persons of different HNA-3a/b phenotypes to identify a single single nucleotide polymorphism in exon 7 of the CLT2 gene (SLC44A2) that predicts an amino acid substitution in the first extracellular loop of choline transporter-like protein 2, a member of the choline transporter-like protein family of membrane glycoproteins, and correlates perfectly with HNA-3a/b phenotypes (R154 encodes HNA-3a; Q154 encodes HNA-3b). Mass spectrometric analysis of proteins immunoprecipitated from leukocytes by anti-HNA-3a provided direct evidence that anti-HNA-3a recognizes choline transporter-like protein 2. These findings will enable large-scale genotyping for HNA-3a/b to identify blood donors at risk to have HNA-3a-specific antibodies and should facilitate development of practical methods to detect such antibodies and prevent transfusion-related lung injury.

Spoiling the Whole Bunch: Quality Control Aimed at Preserving the Integrity of High-Throughput Genotyping

False-positive or false-negative results attributable to undetected genotyping errors and confounding factors present a constant challenge for genome-wide association studies (GWAS) given the low signals associated with complex phenotypes and the noise associated with high-throughput genotyping. In the context of the genetics of kidneys in diabetes (GoKinD) study, we identify a source of error in genotype calling and demonstrate that a standard battery of quality-control (QC) measures is not sufficient to detect and/or correct it. We show that, if genotyping and calling are done by plate (batch), even a few DNA samples of marginally acceptable quality can profoundly alter the allele calls for other samples on the plate. In turn, this leads to significant differential bias in estimates of allele frequency between plates and, potentially, to false-positive associations, particularly when case and control samples are not sufficiently randomized to plates. This problem may become widespread as investigators tap into existing public databases for GWAS control samples. We describe how to detect and correct this bias by utilizing additional sources of information, including raw signal-intensity data.

Trans-population Analysis of Genetic Mechanisms of Ethnic Disparities in Neuroblastoma Survival

BACKGROUND Black patients with neuroblastoma have a higher prevalence of high-risk disease and worse outcome than white patients. We sought to investigate the relationship between genetic variation and the disparities in survival observed in neuroblastoma. METHODS The analytic cohort was composed of 2709 patients. Principal components were used to assign patients to genomic ethnic clusters for survival analyses. Locus-specific ancestry was calculated for use in association analysis. The shorter spans of linkage disequilibrium in African populations may facilitate the fine mapping of causal variants in regions previously implicated by genome-wide association studies conducted primarily in patients of European descent. Thus, we evaluated 13 single nucleotide polymorphisms known to be associated with susceptibility to high-risk neuroblastoma from genome-wide association studies and all variants with highly divergent allele frequencies in reference African and European populations near the known susceptibility loci. All statistical tests were two-sided. RESULTS African genomic ancestry was associated with high-risk neuroblastoma (P = .007) and lower event-free survival (P = .04, hazard ratio = 1.4, 95% confidence interval = 1.05 to 1.80). rs1033069 within SPAG16 (sperm associated antigen 16) was determined to have higher risk allele frequency in the African reference population and statistically significant association with high-risk disease in patients of European and African ancestry (P = 6.42 × 10(-5), false discovery rate < 0.0015) in the overall cohort. Multivariable analysis using an additive model demonstrated that the SPAG16 single nucleotide polymorphism contributes to the observed ethnic disparities in high-risk disease and survival. CONCLUSIONS Our study demonstrates that common genetic variation influences neuroblastoma phenotype and contributes to the ethnic disparities in survival observed and illustrates the value of trans-population mapping.

Establishment of CYP2D6 reference samples by multiple validated genotyping platforms.

Cytochrome P450 2D6 (cytochrome P450, family 2, subfamily D, polypeptide 6 (CYP2D6)), a highly polymorphic drug-metabolizing enzyme, is involved in the metabolism of one-quarter of the most commonly prescribed medications. Here we have applied multiple genotyping methods and Sanger sequencing to assign precise and reproducible CYP2D6 genotypes, including copy numbers, for 48 HapMap samples. Furthermore, by analyzing a set of 50 human liver microsomes using endoxifen formation from N-desmethyl-tamoxifen as the phenotype of interest, we observed a significant positive correlation between CYP2D6 genotype-assigned activity score and endoxifen formation rate (rs=0.68 by rank correlation test, P=5.3 × 10−8), which corroborated the genotype–phenotype prediction derived from our genotyping methodologies. In the future, these 48 publicly available HapMap samples characterized by multiple substantiated CYP2D6 genotyping platforms could serve as a reference resource for assay development, validation, quality control and proficiency testing for other CYP2D6 genotyping projects and for programs pursuing clinical pharmacogenomic testing implementation.

Transcriptomic variation of pharmacogenes in multiple human tissues and lymphoblastoid cell lines

Variation in the expression level and activity of genes involved in drug disposition and action (‘pharmacogenes’) can affect drug response and toxicity, especially when in tissues of pharmacological importance. Previous studies have relied primarily on microarrays to understand gene expression differences, or have focused on a single tissue or small number of samples. The goal of this study was to use RNA-sequencing (RNA-seq) to determine the expression levels and alternative splicing of 389 Pharmacogenomics Research Network pharmacogenes across four tissues (liver, kidney, heart and adipose) and lymphoblastoid cell lines, which are used widely in pharmacogenomics studies. Analysis of RNA-seq data from 139 different individuals across the 5 tissues (20–45 individuals per tissue type) revealed substantial variation in both expression levels and splicing across samples and tissue types. Comparison with GTEx data yielded a consistent picture. This in-depth exploration also revealed 183 splicing events in pharmacogenes that were previously not annotated. Overall, this study serves as a rich resource for the research community to inform biomarker and drug discovery and use.