Improved Minimum Cost and Maximum Power Two Stage Genome-Wide Association Study Designs

In a two stage genome-wide association study (2S-GWAS), a sample of cases and controls is allocated into two groups, and genetic markers are analyzed sequentially with respect to these groups. For such studies, experimental design considerations have primarily focused on minimizing study cost as a function of the allocation of cases and controls to stages, subject to a constraint on the power to detect an associated marker. However, most treatments of this problem implicitly restrict the set of feasible designs to only those that allocate the same proportions of cases and controls to each stage. In this paper, we demonstrate that removing this restriction can improve the cost advantages demonstrated by previous 2S-GWAS designs by up to 40%. Additionally, we consider designs that maximize study power with respect to a cost constraint, and show that recalculated power maximizing designs can recover a substantial amount of the planned study power that might otherwise be lost if study funding is reduced. We provide open source software for calculating cost minimizing or power maximizing 2S-GWAS designs.</p

QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern

BACKGROUND Existing software for quantitative trait mapping is either not able to model polygenic variation or does not allow incorporation of more than one genetic variance component. Improperly modeling the genetic relatedness among subjects can result in excessive false positives. We have developed an R package, QTLRel, to enable more flexible modeling of genetic relatedness as well as covariates and non-genetic variance components. RESULTS We have successfully used the package to analyze many datasets, including F₃₄ body weight data that contains 688 individuals genotyped at 3105 SNP markers and identified 11 QTL. It took 295 seconds to estimate variance components and 70 seconds to perform the genome scan on an Linux machine equipped with a 2.40GHz Intel(R) Core(TM)2 Quad CPU. CONCLUSIONS QTLRel provides a toolkit for genome-wide association studies that is capable of calculating genetic incidence matrices from pedigrees, estimating variance components, performing genome scans, incorporating interactive covariates and genetic and non-genetic variance components, as well as other functionalities such as multiple-QTL mapping and genome-wide epistasis.This project was supported by NIH grants R01DA021336, R01MH079103 and R21DA024845

QTLRel: An R package for genome-wide association studies in which relatedness is a concern

Abstract Background: Existing software for quantitative trait mapping is either not able to model polygenic variation or does not allow incorporation of more than one genetic variance component. Improperly modeling the genetic relatedness among subjects can result in excessive false positives. We have developed an R package, QTLRel, to enable more flexible modeling of genetic relatedness as well as covariates and non-genetic variance components. Results: We have successfully used the package to analyze many datasets, including F 34 body weight data that contains 688 individuals genotyped at 3105 SNP markers and identified 11 QTL. It took 295 seconds to estimate variance components and 70 seconds to perform the genome scan on an Linux machine equipped with a 2.40GHz Intel(R) Core(TM)2 Quad CPU. Conclusions: QTLRel provides a toolkit for genome-wide association studies that is capable of calculating genetic incidence matrices from pedigrees, estimating variance components, performing genome scans, incorporating interactive covariates and genetic and non-genetic variance components, as well as other functionalities such as multiple-QTL mapping and genome-wide epistasis

Promoter Variant of PIK3C3 Is Associated with Autoimmunity against Ro and Sm Epitopes in African-American Lupus Patients

The PIK3C3 locus was implicated in case-case genome-wide association study of systemic lupus erythematosus (SLE) which we had performed to detect genes associated with autoantibodies and serum interferon-alpha (IFN-α). Herein, we examine a PIK3C3 promoter variant (rs3813065/-442 C/T) in an independent multiancestral cohort of 478 SLE cases and 522 controls. rs3813065 C was strongly associated with the simultaneous presence of both anti-Ro and anti-Sm antibodies in African-American patients [OR = 2.24 (1.34–3.73), P = 2.0 × 10−3]. This autoantibody profile was associated with higher serum IFN-α (P = 7.6 × 10−6). In the HapMap Yoruba population, rs3813065 was associated with differential expression of ERAP2 (P = 2.0 × 10−5), which encodes an enzyme involved in MHC class I peptide processing. Thus, rs3813065 C is associated with a particular autoantibody profile and altered expression of an MHC peptide processing enzyme, suggesting that this variant modulates serologic autoimmunity in African-American SLE patients

Discovery and functional assessment of gene variants in the vascular endothelial growth factor pathway

Angiogenesis is a host-mediated mechanism in disease pathophysiology. The vascular endothelial growth factor (VEGF) pathway is a major determinant of angiogenesis, and a comprehensive annotation of the functional variation in this pathway is essential to understand the genetic basis of angiogenesis-related diseases. We assessed the allelic heterogeneity of gene expression, population specificity of cis expression quantitative trait loci (eQTLs), and eQTL function in luciferase assays in CEU and Yoruba people of Ibadan, Nigeria (YRI) HapMap lymphoblastoid cell lines in 23 resequenced genes. Among 356 cis-eQTLs, 155 and 174 were unique to CEU and YRI, respectively, and 27 were shared between CEU and YRI. Two cis-eQTLs provided mechanistic evidence for two genome-wide association study findings. Five eQTLs were tested for function in luciferase assays and the effect of two KRAS variants was concordant with the eQTL effect. Two eQTLs found in each of PRKCE, PIK3C2A, and MAP2K6 could predict 44%, 37%, and 45% of the variance in gene expression, respectively. This is the first analysis focusing on the pattern of functional genetic variation of the VEGF pathway genes in CEU and YRI populations and providing mechanistic evidence for genetic association studies of diseases for which angiogenesis plays a pathophysiologic role. (C) 2013 Wiley Periodicals, Inc

Trait-stratified genome-wide association study identifies novel and diverse genetic associations with serologic and cytokine phenotypes in systemic lupus erythematosus

INTRODUCTION: Systemic lupus erythematosus (SLE) is a highly heterogeneous disorder, characterized by differences in autoantibody profile, serum cytokines, and clinical manifestations. SLE-associated autoantibodies and high serum interferon alpha (IFN-α) are important heritable phenotypes in SLE which are correlated with each other, and play a role in disease pathogenesis. These two heritable risk factors are shared between ancestral backgrounds. The aim of the study was to detect genetic factors associated with autoantibody profiles and serum IFN-α in SLE. METHODS: We undertook a case-case genome-wide association study of SLE patients stratified by ancestry and extremes of phenotype in serology and serum IFN-α. Single nucleotide polymorphisms (SNPs) in seven loci were selected for follow-up in a large independent cohort of 538 SLE patients and 522 controls using a multi-step screening approach based on novel metrics and expert database review. The seven loci were: leucine-rich repeat containing 20 (LRRC20); protein phosphatase 1 H (PPM1H); lysophosphatidic acid receptor 1 (LPAR1); ankyrin repeat and sterile alpha motif domain 1A (ANKS1A); protein tyrosine phosphatase, receptor type M (PTPRM); ephrin A5 (EFNA5); and V-set and immunoglobulin domain containing 2 (VSIG2). RESULTS: SNPs in the LRRC20, PPM1H, LPAR1, ANKS1A, and VSIG2 loci each demonstrated strong association with a particular serologic profile (all odds ratios > 2.2 and P < 3.5 × 10(-4)). Each of these serologic profiles was associated with increased serum IFN-α. SNPs in both PTPRM and LRRC20 were associated with increased serum IFN-α independent of serologic profile (P = 2.2 × 10(-6 )and P = 2.6 × 10(-3 )respectively). None of the SNPs were strongly associated with SLE in case-control analysis, suggesting that the major impact of these variants will be upon subphenotypes in SLE. CONCLUSIONS: This study demonstrates the power of using serologic and cytokine subphenotypes to elucidate genetic factors involved in complex autoimmune disease. The distinct associations observed emphasize the heterogeneity of molecular pathogenesis in SLE, and the need for stratification by subphenotypes in genetic studies. We hypothesize that these genetic variants play a role in disease manifestations and severity in SLE

Genetic Variants of VEGFA and FLT4 Are Determinants of Survival in Renal Cell Carcinoma Patients Treated with Sorafenib

Molecular markers of sorafenib efficacy in patients with metastatic renal cell carcinoma (mRCC) are not available. The purpose of this study was to discover genetic markers of survival in patients with mRCC treated with sorafenib. Germline variants from 56 genes were genotyped in 295 patients with mRCC. Variant-overall survival (OS) associations were tested in multivariate regression models. Mechanistic studies were conducted to validate clinical associations. VEGFA rs1885657, ITGAV rs3816375, and WWOX rs8047917 (sorafenib arm), and FLT4 rs307826 and VEGFA rs3024987 (sorafenib and placebo arms combined) were associated with shorter OS. FLT4 rs307826 increased VEGFR-3 phosphorylation, membrane trafficking, and receptor activation. VEGFA rs1885657 and rs58159269 increased transcriptional activity of the constructs containing these variants in endothelial and RCC cell lines, and VEGFA rs58159269 increased endothelial cell proliferation and tube formation. FLT4 rs307826 and VEGFA rs58159269 led to reduced sorafenib cytotoxicity. Genetic variation in VEGFA and FLT4 could affect survival in sorafenib-treated patients with mRCC. These markers should be examined in additional malignancies treated with sorafenib and in other angiogenesis inhibitors used in mRCC. Significance: Clinical and mechanistic data identify germline genetic variants in VEGFA and FLT4 as markers of survival in patients with metastatic renal cell carcinoma.Peer reviewe

Discovery and Functional Assessment of Gene Variants in the Vascular Endothelial Growth Factor Pathway

Angiogenesis is a host-mediated mechanism in disease pathophysiology. The vascular endothelial growth factor (VEGF) pathway is a major determinant of angiogenesis, and a comprehensive annotation of the functional variation in this pathway is essential to understand the genetic basis of angiogenesis-related diseases. We assessed the allelic heterogeneity of gene expression, population specificity of cis expression quantitative trait loci (eQTLs), and eQTL function in luciferase assays in CEU and YRI HapMap lymphoblastoid cell lines (LCLs) in 23 resequenced genes. Among 356 cis-eQTLs, 155 and 174 were unique to CEU and YRI, respectively, and 27 were shared between CEU and YRI. Two cis-eQTLs provided mechanistic evidence for two GWAS findings. Five eQTLs were tested for function in luciferase assays and the effect of two KRAS variants was concordant with the eQTL effect. Two eQTLs found in each of PRKCE, PIK3C2A, and MAP2K6, could predict 44, 37 and 45% of the variance in gene expression, respectively. This is the first analysis focusing on the pattern of functional genetic variation of the VEGF pathway genes in CEU and YRI populations and providing mechanistic evidence for genetic association studies of diseases for which angiogenesis plays a pathophysiologic role

Meta-analysis of genome-wide studies identifies MEF2C SNPs associated with bone mineral density at forearm

Background: Forearm fractures affect 1.7 million individuals worldwide each year and most occur earlier in life than hip fractures. While the heritability of forearm bone mineral density (BMD) and fracture is high, their genetic determinants are largely unknown. Aim: To identify genetic variants associated with forearm BMD and forearm fractures. Methods: BMD at distal radius, measured by dualenergy x-ray absorptiometry, was tested for association with common genetic variants. We conducted a metaanalysis of genome-wide association studies for BMD in 5866 subjects of European descent and then selected the variants for replication in 715 Mexican American samples. Gene-based association was carried out to supplement the single-nucleotide polymorphism (SNP) association test. We then tested the BMD-associated SNPs for association with forearm fracture in 2023 cases and 3740 controls. Results: We found that five SNPs in the introns of MEF2C were associated with forearm BMD at a genome-wide significance level (

Gene-Expression-Guided Selection of Candidate Loci and Molecular Phenotype Analyses Enhance Genetic Discovery in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a highly heterogeneous autoimmune disorder characterized by differences in autoantibody profiles, serum cytokines, and clinical manifestations. We have previously conducted a case-case genome-wide association study (GWAS) of SLE patients to detect associations with autoantibody profile and serum interferon alpha (IFN-α). In this study, we used public gene expression data sets to rationally select additional single nucleotide polymorphisms (SNPs) for validation. The top 200 GWAS SNPs were searched in a database which compares genome-wide expression data to genome-wide SNP genotype data in HapMap cell lines. SNPs were chosen for validation if they were associated with differential expression of 15 or more genes at a significance of P<9×10−5. This resulted in 11 SNPs which were genotyped in 453 SLE patients and 418 matched controls. Three SNPs were associated with SLE-associated autoantibodies, and one of these SNPs was also associated with serum IFN-α (P<4.5×10−3 for all). One additional SNP was associated exclusively with serum IFN-α. Case-control analysis was insensitive to these molecular subphenotype associations. This study illustrates the use of gene expression data to rationally select candidate loci in autoimmune disease, and the utility of stratification by molecular phenotypes in the discovery of additional genetic associations in SLE