A fast, unbiased and exact allelic test for case-control association studies

Whole exome sequencing and machine learning germline analysis of individuals presenting with extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinoma

BACKGROUND

Tobacco is the main risk factor for developing lung cancer. Yet, while some heavy smokers develop lung cancer at a young age, other heavy smokers never develop it, even at an advanced age, suggesting a remarkable variability in the individual susceptibility to the carcinogenic effects of tobacco. We characterized the germline profile of subjects presenting these extreme phenotypes with Whole Exome Sequencing (WES) and Machine Learning (ML).

METHODS

We sequenced germline DNA from heavy smokers who either developed lung adenocarcinoma at an early age (extreme cases) or who did not develop lung cancer at an advanced age (extreme controls), selected from databases including over 6600 subjects. We selected individual coding genetic variants and variant-rich genes showing a significantly different distribution between extreme cases and controls. We validated the results from our discovery cohort, in which we analysed by WES extreme cases and controls presenting similar phenotypes. We developed ML models using both cohorts.

FINDINGS

Mean age for extreme cases and controls was 50.7 and 79.1 years respectively, and mean tobacco consumption was 34.6 and 62.3 pack-years. We validated 16 individual variants and 33 variant-rich genes. The gene harbouring the most validated variants was HLA-A in extreme controls (4 variants in the discovery cohort, p = 3.46E-07; and 4 in the validation cohort, p = 1.67E-06). We trained ML models using as input the 16 individual variants in the discovery cohort and tested them on the validation cohort, obtaining an accuracy of 76.5% and an AUC-ROC of 83.6%. Functions of validated genes included candidate oncogenes, tumour-suppressors, DNA repair, HLA-mediated antigen presentation and regulation of proliferation, apoptosis, inflammation and immune response.

INTERPRETATION

Individuals presenting extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinoma show different germline profiles. Our strategy may allow the identification of high-risk subjects and the development of new therapeutic approaches.

FUNDING

See a detailed list of funding bodies in the Acknowledgements section at the end of the manuscript.

Whole exome sequencing characterization of individuals presenting extreme phenotypes of high and low risk of developing tobacco-induced lung adenocarcinoma

Background

Tobacco is the main risk factor for developing lung cancer. Yet, some heavy smokers do not develop lung cancer at advanced ages while others develop it at young ages. Here, we assess for the first time the genetic background of these clinically relevant extreme phenotypes using whole exome sequencing (WES).

Methods

We performed WES of germline DNA from heavy smokers who either developed lung adenocarcinoma at an early age (extreme cases, n=50) or did not present lung adenocarcinoma or other tumors at an advanced age (extreme controls, n=50). We selected non-synonymous variants located in exonic regions and consensus splice sites of the genes that showed significantly different allelic frequencies between both cohorts. We validated our results in all the additional extreme cases (i.e., heavy smokers who developed lung adenocarcinoma at an early age) available from The Cancer Genome Atlas (TCGA).

Results

The mean age for the extreme cases and controls was respectively 49.7 and 77.5 years. Mean tobacco consumption was 43.6 and 56.8 pack-years. We identified 619 significantly different variants between both cohorts, and we validated 108 of these in extreme cases selected from TCGA. Nine validated variants, located in relevant cancer related genes, such as PARP4, HLA-A or NQO1, among others, achieved statistical significance in the False Discovery Rate test. The most significant validated variant (P=4.48×10⁻⁵) was located in the tumor-suppressor gene ALPK2.

Conclusions

We describe genetic variants associated with extreme phenotypes of high and low risk for the development of tobacco-induced lung adenocarcinoma. Our results and our strategy may help to identify high-risk subjects and to develop new therapeutic approaches.

PM20D1 is a quantitative trait locus associated with Alzheimer's disease

The chances to develop Alzheimer's disease (AD) result from a combination of genetic and non-genetic risk factors ¹ , the latter likely being mediated by epigenetic mechanisms ² . In the past, genome-wide association studies (GWAS) have identified an important number of risk loci associated with AD pathology ³ , but a causal relationship remains difficult to establish. In contrast, locus-specific or epigenome-wide association studies (EWAS) have revealed site-specific epigenetic alterations, which provide mechanistic insights for a particular risk gene but often lack the statistical power of GWAS ⁴ . Here, combining both approaches, we report a previously unidentified association of the peptidase M20-domain-containing protein 1 (PM20D1) with AD. We find that PM20D1 is a methylation and expression quantitative trait locus coupled to an AD-risk associated haplotype, which displays enhancer-like characteristics and contacts the PM20D1 promoter via a haplotype-dependent, CCCTC-binding-factor-mediated chromatin loop. Furthermore, PM20D1 is increased following AD-related neurotoxic insults at symptomatic stages in the APP/PS1 mouse model of AD and in human patients with AD who are carriers of the non-risk haplotype. In line, genetically increasing or decreasing the expression of PM20D1 reduces and aggravates AD-related pathologies, respectively. These findings suggest that in a particular genetic background, PM20D1 contributes to neuroprotection against AD.

Power comparison of Cochran-Armitage trend test against allelic and genotypic tests in large-scale case-control genetic association studies

The Cochran-Armitage trend test (CA) has become a standard procedure for association testing in large-scale genome-wide association studies (GWAS). However, when the disease model is unknown, there is no consensus on the most powerful test to be used between CA, allelic, and genotypic tests. In this article, we tackle the question of whether CA is best suited to single-locus scanning in GWAS and propose a power comparison of CA against allelic and genotypic tests. Our approach relies on the evaluation of the Taylor decompositions of non-centrality parameters, thus allowing an analytical comparison of the power functions of the tests. Compared to simulation-based comparison, our approach offers the advantage of simultaneously accounting for the multidimensionality of the set of features involved in power functions. Although power for CA depends on the sample size, the case-to-control ratio and the minor allelic frequency (MAF), our results first show that it is largely influenced by the mode of inheritance and a deviation from Hardy–Weinberg Equilibrium (HWE). Furthermore, when compared to other tests, CA is shown to be the most powerful test under a multiplicative disease model or when the single-nucleotide polymorphism largely deviates from HWE. In all other situations, CA lacks in power and differences can be substantial, especially for the recessive mode of inheritance. Finally, our results are illustrated by the comparison of the performances of the statistics in two genome scans.

Semiparametric Allelic Tests for Mapping Multiple Phenotypes: Binomial Regression and Mahalanobis Distance

Binary phenotypes commonly arise due to multiple underlying quantitative precursors and genetic variants may impact multiple traits in a pleiotropic manner. Hence, simultaneously analyzing such correlated traits may be more powerful than analyzing individual traits. Various genotype-level methods, e.g., MultiPhen (O'Reilly et al. []), have been developed to identify genetic factors underlying a multivariate phenotype. For univariate phenotypes, the usefulness and applicability of allele-level tests have been investigated. The test of allele frequency difference among cases and controls is commonly used for mapping case-control association. However, allelic methods for multivariate association mapping have not been studied much. In this article, we explore two allelic tests of multivariate association: one using a Binomial regression model based on inverted regression of genotype on phenotype (Binomial regression-based Association of Multivariate Phenotypes [BAMP]), and the other employing the Mahalanobis distance between two sample means of the multivariate phenotype vector for two alleles at a single-nucleotide polymorphism (Distance-based Association of Multivariate Phenotypes [DAMP]). These methods can incorporate both discrete and continuous phenotypes. Some theoretical properties for BAMP are studied. Using simulations, the power of the methods for detecting multivariate association is compared with the genotype-level test MultiPhen's. The allelic tests yield marginally higher power than MultiPhen for multivariate phenotypes. For one/two binary traits under recessive mode of inheritance, allelic tests are found to be substantially more powerful. All three tests are applied to two different real data and the results offer some support for the simulation study. We propose a hybrid approach for testing multivariate association that implements MultiPhen when Hardy-Weinberg Equilibrium (HWE) is violated and BAMP otherwise, because the allelic approaches assume HWE.

Association between SNPs of Metalloproteinases and Prostaglandin F2α Receptor Genes and Latanoprost Response in Open-Angle Glaucoma

PURPOSE

To determine whether single nucleotide polymorphisms (SNPs) of genes coding for matrix metalloproteinases (MMPs) and the prostaglandin F2α receptor gene (PTGFR) are related to a response to latanoprost in a white Spanish population of glaucomatous patients.

DESIGN

Case-control study.

PARTICIPANTS

One hundred twenty-four patients with open-angle glaucoma.

METHODS

Genotyping was performed in 117 patients with primary open-angle glaucoma with a minimum treatment duration of 4 weeks. Candidate genes and individual polymorphisms were selected according to the effect on the mechanism of action of latanoprost. Multi-SNP haplotype analyses for associations also were tested.

MAIN OUTCOME MEASURES

Diurnal intraocular pressure reduction and genotyping of the SNPs in the MMPs and PTGFR.

RESULTS

The PTGFR SNPs were associated with positive (rs6686438, rs10786455) and negative (rs3753380, rs6672484, rs11578155) responses to latanoprost. Multiple testing found 2 genes, PTGFR and MMP-1, were related to refractoriness to latanoprost.

CONCLUSIONS

The SNPs of the PTGFR and MMP-1 genes may determine the latanoprost response in a white European Spanish population. This study identified 5 SNPs related to the latanoprost response; 1 SNP, rs3753380, already has been associated with a poor response to latanoprost in a healthy Japanese population. Latanoprost is a commonly used antiglaucomatous drug, and increased knowledge of its mechanism of action will lead to advances in pharmacogenetics.

Quantitative allelic test--a fast test for very large association studies

Advances in high throughput technology have enabled the generation of unprecedented amounts of genomic data (e.g., next-generation sequence data, transcriptomics, metabolomics, and proteomics), which promises to unravel the genetic architecture of complex traits. These discoveries may lead to novel therapeutic targets, guide disease prevention, and enable personalized medicine. However, the pace of data generation surpasses the ability to process and analyze the vast amounts of data. For example, in a typical study of transcription regulation, the relationship between more than 1 million genetic variants and 10,000 transcript levels are explored, requiring tens of billions of tests. In order to address this problem, we propose a fast, accurate, and robust method that can assess the significance of associations between quantitative phenotypes and genotypes. The method is an extension of the allelic test commonly used in case-control studies for the analysis of quantitative traits. We show the asymptotic equivalence of the proposed test to linear regression results. We also reduce a generalized linear regression problem to the comparison of two groups, which can handle nonnormal and survival time phenotypes.

Genetic variants in PARP1 (rs3219090) and IRF4 (rs12203592) genes associated with melanoma susceptibility in a Spanish population

Background

Few high penetrance genes are known in Malignant Melanoma (MM), however, the involvement of low-penetrance genes such as MC1R, OCA2, ASIP, SLC45A2 and TYR has been observed. Lately, genome-wide association studies (GWAS) have been the ideal strategy to identify new common, low-penetrance susceptibility loci. In this case–control study, we try to validate in our population nine melanoma associated markers selected from published GWAS in melanoma predisposition.

Methods

We genotyped the 9 markers corresponding to 8 genes (PARP1, MX2, ATM, CCND1, NADSYN1, CASP8, IRF4 and CYP2R1) in 566 cases and 347 controls from a Spanish population using KASPar probes. Genotypes were analyzed by logistic regression and adjusted by phenotypic characteristics.

Results

We confirm the protective role in MM of the rs3219090 located on the PARP1 gene (p-value 0.027). Additionally, this SNP was also associated with eye color (p-value 0.002). A second polymorphism, rs12203592, located on the IRF4 gene was associated with protection to develop MM for the dominant model (p-value 0.037). We have also observed an association of this SNP with both lentigines (p-value 0.014) and light eye color (p-value 3.76 × 10^-4). Furthermore, we detected a novel association with rs1485993, located on the CCND1 gene, and dark eye color (p-value 4.96 × 10^-4). Finally, rs1801516, located on the ATM gene, showed a trend towards a protective role in MM similar to the one firstly described in a GWAS study.

Conclusions

To our knowledge, this is the first time that these SNPs have been associated with MM in a Spanish population. We confirmed the proposed role of rs3219090, located on the PARP1 gene, and rs12203592, located on the IRF4 gene, as protective to MM along the same lines as have previous genome-wide associated works. Finally, we have seen associations between IRF4, PARP1, and CCND1 and phenotypic characteristics, confirming previous results for the IRF4 gene and presenting novel data for the last two, suggesting that pigmentation characteristics correlated with eye color are potential mediators between PARP1 and MM protection.

Testing allele homogeneity: the problem of nested hypotheses

BACKGROUND

The evaluation of associations between genotypes and diseases in a case-control framework plays an important role in genetic epidemiology. This paper focuses on the evaluation of the homogeneity of both genotypic and allelic frequencies. The traditional test that is used to check allelic homogeneity is known to be valid only under Hardy-Weinberg equilibrium, a property that may not hold in practice.

RESULTS

We first describe the flaws of the traditional (chi-squared) tests for both allelic and genotypic homogeneity. Besides the known problem of the allelic procedure, we show that whenever these tests are used, an incoherence may arise: sometimes the genotypic homogeneity hypothesis is not rejected, but the allelic hypothesis is. As we argue, this is logically impossible. Some methods that were recently proposed implicitly rely on the idea that this does not happen. In an attempt to correct this incoherence, we describe an alternative frequentist approach that is appropriate even when Hardy-Weinberg equilibrium does not hold. It is then shown that the problem remains and is intrinsic of frequentist procedures. Finally, we introduce the Full Bayesian Significance Test to test both hypotheses and prove that the incoherence cannot happen with these new tests. To illustrate this, all five tests are applied to real and simulated datasets. Using the celebrated power analysis, we show that the Bayesian method is comparable to the frequentist one and has the advantage of being coherent.

CONCLUSIONS

Contrary to more traditional approaches, the Full Bayesian Significance Test for association studies provides a simple, coherent and powerful tool for detecting associations.

IndOR: a new statistical procedure to test for SNP-SNP epistasis in genome-wide association studies

Epistasis is often cited as the biological mechanism carrying the missing heritability in genome-wide association studies. However, there is a very few number of studies reported in the literature. The low power of existing statistical methods is a potential explanation. Statistical procedures are also mainly based on the statistical definition of epistasis that prevents from detecting SNP-SNP interactions that rely on some classes of epistatic models. In this paper, we propose a new statistic, called IndOR for independence-based odds ratio, based on the biological definition of epistasis. We assume that epistasis modifies the dependency between the two causal SNPs, and we develop a Wald procedure to test such hypothesis. Our new statistic is compared with three statistical procedures in a large power study on simulated data sets. We use extensive simulations, based on 45 scenarios, to investigate the effect of three factors: the underlying disease model, the linkage disequilibrium, and the control-to-case ratio. We demonstrate that our new test has the ability to detect a wider range of epistatic models. Furthermore, our new statistical procedure is remarkably powerful when the two loci are linked and when the control-to-case ratio is higher than 1. The application of our new statistic on the Wellcome Trust Case Control Consortium data set on Crohn's disease enhances our results on simulated data. Our new test, IndOR, catches previously reported interaction with more power. Furthermore, a new combination of variant has been detected by our new test as significantly associated with Crohn's disease.

Association study of IRAK-M and SIGIRR genes with SLE in a large European-descent population

OBJECTIVE

The aim of this study was to evaluate the relevance of genetic variants of interleukin receptor-associated kinase-M (IRAK-M) (rs11465955, rs1624395, rs1152888 and rs1370128) and single immunoglobulin IL1-1R-related molecule (SIGIRR) (rs3210908) genes in systemic lupus erythematosus (SLE) in four independent European-descent populations.

METHODS

Our study population consisted of a total of 2033 SLE patients and 2357 healthy controls from Spain, Germany, Italy and Argentina. The genotyping was performed using a polymerase chain reaction (PCR) system with pre-developed TaqMan allelic discrimination assay. Genetic association between the genotyped markers was determined by PLINK v1.07.

RESULTS

After a meta-analysis including these four populations, a trend of association between rs11465955 (P(meta) (-analysis)  = 0.06), rs1370128 (P(meta) (-analysis)  = 0.07) and rs1624395 (P(meta) (-analysis)  = 0.06) polymorphisms was found. However, these differences did not reach statistical significance. In addition, we did not find any association between SLE and the rs1152888 IRAK-M (P(meta) (-analysis)  = 0.13) and the rs3210908 SIGIRR (P(meta) (-analysis)  = 0.40) polymorphisms after the meta-analysis. No evidence of association with IRAK-M haplotypes was found.

CONCLUSION

These results suggest that the tested variations of IRAK-M and SIGIRR genes do not confer a relevant role in the susceptibility to SLE in European-descent populations.

A genome-wide association study in progressive multiple sclerosis

Background: The role played by genetic factors in influencing the clinical course of multiple sclerosis (MS) is not yet well established.

Objective: We aimed to identify genetic variants associated with progressive MS (PrMS).

Methods: We conducted a genome-wide association study (GWAS) in 197 patients with PrMS and 234 controls of Italian origin. We tested the top 20 single nucleotide polymorphisms (SNPs) with suggestive evidence of association ( p-value<10−4) in two independent sets of primary progressive MS cases and controls.

Results: We identified a risk-associated SNP in the HLA region in linkage disequilibrium (LD) with DRB1*1501 and DQB*0602 loci, with genome-wide significance (rs3129934T, pcombined=6.7×10-16, OR=2.34, 95% CI=1.90–2.87), and a novel locus on chromosome 7q35 with suggestive evidence of association (rs996343G, pcombined=2.4×10-5, OR=0.70, 95% CI=0.59–0.83) which maps within a human endogenous retroviral (HERV) element. The new locus did not have a ‘ cis’ effect on RNA expression in lymphoblastic cell lines, but pathway analyses of ‘ trans’ effects point to an expression regulation of genes involved in neurodegeneration, including glutamate metabolism ( p<0.01) and axonal guidance signalling ( p<0.02).

Conclusions: We have confirmed the established association with the HLA region and, despite the low statistical power of the study, we found suggestive evidence for association with a novel locus on chromosome 7, with a putative regulatory role.

Identification of novel genetic susceptibility loci in African American lupus patients in a candidate gene association study

OBJECTIVE

Candidate gene and genome-wide association studies have identified several disease susceptibility loci in lupus patients. These studies have largely been performed in lupus patients who are Asian or of European ancestry. This study was undertaken to examine whether some of these same susceptibility loci increase lupus risk in African American individuals.

METHODS

Single-nucleotide polymorphisms tagging 15 independent lupus susceptibility loci were genotyped in a set of 1,724 lupus patients and 2,024 healthy controls of African American descent. The loci examined included PTPN22, FCGR2A, TNFSF4, STAT4, CTLA4, PDCD1, PXK, BANK1, MSH5 (HLA region), CFB (HLA region), C8orf13-BLK region, MBL2, KIAA1542, ITGAM, and MECP2/IRAK1.

RESULTS

We found the first evidence of genetic association between lupus in African American patients and 5 susceptibility loci (C8orf13-BLK, BANK1, TNFSF4, KIAA1542, and CTLA4; P = 8.0 × 10⁻⁶, P = 1.9 × 10⁻⁵, P = 5.7 × 10⁻⁵, P = 0.00099, and P = 0.0045, respectively). Further, we confirmed the genetic association between lupus and 5 additional lupus susceptibility loci (ITGAM, MSH5, CFB, STAT4, and FCGR2A; P = 7.5 × 10⁻¹¹, P = 5.2 × 10⁻⁸, P = 8.7 × 10⁻⁷ , P = 0.0058, and P = 0.0070, respectively), and provided evidence, for the first time, of genome-wide significance for the association between lupus in African American patients and ITGAM and MSH5 (HLA region).

CONCLUSION

These findings provide evidence of novel genetic susceptibility loci for lupus in African Americans and demonstrate that the majority of lupus susceptibility loci examined confer lupus risk across multiple ethnicities.

Phenotypic associations of genetic susceptibility loci in systemic lupus erythematosus

OBJECTIVE

Systemic lupus erythematosus is a clinically heterogeneous autoimmune disease. A number of genetic loci that increase lupus susceptibility have been established. This study examines if these genetic loci also contribute to the clinical heterogeneity in lupus.

MATERIALS AND METHODS

4001 European-derived, 1547 Hispanic, 1590 African-American and 1191 Asian lupus patients were genotyped for 16 confirmed lupus susceptibility loci. Ancestry informative markers were genotyped to calculate and adjust for admixture. The association between the risk allele in each locus was determined and compared in patients with and without the various clinical manifestations included in the ACR criteria.

RESULTS

Renal disorder was significantly correlated with the lupus risk allele in ITGAM (p=5.0 × 10(-6), OR 1.25, 95% CI 1.12 to 1.35) and in TNFSF4 (p=0.0013, OR 1.14, 95% CI 1.07 to 1.25). Other significant findings include the association between risk alleles in FCGR2A and malar rash (p=0.0031, OR 1.11, 95% CI 1.17 to 1.33), ITGAM and discoid rash (p=0.0020, OR 1.20, 95% CI 1.06 to 1.33), STAT4 and protection from oral ulcers (p=0.0027, OR 0.89, 95% CI 0.83 to 0.96) and IL21 and haematological disorder (p=0.0027, OR 1.13, 95% CI 1.04 to 1.22). All these associations are significant with a false discovery rate of <0.05 and pass the significance threshold using Bonferroni correction for multiple testing.

CONCLUSION

Signifi cant associations were found between clinical manifestations and the FCGR2A, ITGAM, STAT4, TNSF4 and IL21 genes. The findings suggest that genetic profiling might be a useful tool to predict disease manifestations in lupus patients in the future.

Genetically determined Amerindian ancestry correlates with increased frequency of risk alleles for systemic lupus erythematosus

OBJECTIVE

To assess whether genetically determined Amerindian ancestry predicts increased presence of risk alleles of known susceptibility genes for systemic lupus erythematosus (SLE).

METHODS

Single-nucleotide polymorphisms (SNPs) within 16 confirmed genetic susceptibility loci for SLE were genotyped in a set of 804 Mestizo lupus patients and 667 Mestizo healthy controls. In addition, 347 admixture informative markers were genotyped. Individual ancestry proportions were determined using STRUCTURE. Association analysis was performed using PLINK, and correlation between ancestry and the presence of risk alleles was analyzed using linear regression.

RESULTS

A meta-analysis of the genetic association of the 16 SNPs across populations showed that TNFSF4, STAT4, ITGAM, and IRF5 were associated with lupus in a Hispanic Mestizo cohort enriched for European and Amerindian ancestry. In addition, 2 SNPs within the major histocompatibility complex region, previously shown to be associated in a genome-wide association study in Europeans, were also associated in Mestizos. Using linear regression, we predicted an average increase of 2.34 risk alleles when comparing an SLE patient with 100% Amerindian ancestry versus an SLE patient with 0% Amerindian ancestry (P < 0.0001). SLE patients with 43% more Amerindian ancestry were predicted to carry 1 additional risk allele.

CONCLUSION

Our results demonstrate that Amerindian ancestry is associated with an increased number of risk alleles for SLE.

Tracking footprints of artificial selection in the dog genome

The size, shape, and behavior of the modern domesticated dog has been sculpted by artificial selection for at least 14,000 years. The genetic substrates of selective breeding, however, remain largely unknown. Here, we describe a genome-wide scan for selection in 275 dogs from 10 phenotypically diverse breeds that were genotyped for over 21,000 autosomal SNPs. We identified 155 genomic regions that possess strong signatures of recent selection and contain candidate genes for phenotypes that vary most conspicuously among breeds, including size, coat color and texture, behavior, skeletal morphology, and physiology. In addition, we demonstrate a significant association between HAS2 and skin wrinkling in the Shar-Pei, and provide evidence that regulatory evolution has played a prominent role in the phenotypic diversification of modern dog breeds. Our results provide a first-generation map of selection in the dog, illustrate how such maps can rapidly inform the genetic basis of canine phenotypic variation, and provide a framework for delineating the mechanistic basis of how artificial selection promotes rapid and pronounced phenotypic evolution.

An optimal dose-effect mode trend test for SNP genotype tables

The genome-wide association studies have improved our understanding of the genetic basis of many complex traits. Two-by-three contingency tables are tested in these studies. The trend test for the additive mode is most often used, which is the test of 1 degree of freedom (df=1) and other tests, such as the genotype test (chi(2) (df=2)) and the chi(2) (df=1) tests for the dominant and recessive modes are also used to increase the power for markers in the non-additive modes. However, any one of them or combination of them is not perfect. We describe the relations among the chi(2) (df=2) test and chi(2) (df=1) tests for the dominant and recessive modes and the trend test for the additive mode and propose a new statistic based on their relations that tests the hypothesis that the disease-susceptible allele has a dose-effect somewhere between the recessive and dominant modes, which corresponds to the optimal dose-effect for the observed data.

Distinct genetic loci control plasma HIV-RNA and cellular HIV-DNA levels in HIV-1 infection: the ANRS Genome Wide Association 01 study

Previous studies of the HIV-1 disease have shown that HLA and Chemokine receptor genetic variants influence disease progression and early viral load. We performed a Genome Wide Association study in a cohort of 605 HIV-1-infected seroconverters for detection of novel genetic factors that influence plasma HIV-RNA and cellular HIV-DNA levels. Most of the SNPs strongly associated with HIV-RNA levels were localised in the 6p21 major histocompatibility complex (MHC) region and were in the vicinity of class I and III genes. Moreover, protective alleles for four disease-associated SNPs in the MHC locus (rs2395029, rs13199524, rs12198173 and rs3093662) were strikingly over-represented among forty-five Long Term HIV controllers. Furthermore, we show that the HIV-DNA levels (reflecting the HIV reservoir) are associated with the same four SNPs, but also with two additional SNPs on chromosome 17 (rs6503919; intergenic region flanked by the DDX40 and YPEL2 genes) and chromosome 8 (rs2575735; within the Syndecan 2 gene). Our data provide evidence that the MHC controls both HIV replication and HIV reservoir. They also indicate that two additional genomic loci may influence the HIV reservoir.

ExactFDR: exact computation of false discovery rate estimate in case-control association studies

Genome-wide association studies require accurate and fast statistical methods to identify relevant signals from the background noise generated by a huge number of simultaneously tested hypotheses. It is now commonly accepted that exact computations of association probability value (P-value) are preferred to chi(2) and permutation-based approximations. Following the same principle, the ExactFDR software package improves speed and accuracy of the permutation-based false discovery rate (FDR) estimation method by replacing the permutation-based estimation of the null distribution by the generalization of the algorithm used for computing individual exact P-values. It provides a quick and accurate non-conservative estimator of the proportion of false positives in a given selection of markers, and is therefore an efficient and pragmatic tool for the analysis of genome-wide association studies.

Can the allelic test be retired from analysis of case-control association studies?

It has been stated that, when Hardy-Weinberg equilibrium (HWE) holds in the combined case-control samples, the allelic test is asymptotically equivalent to the trend test (for the additive model) for testing genetic association, and hence the allelic test should not be used. A recent publication shows that the allelic test and the trend test are asymptotically equivalent when HWE holds in the population. It is known that, when HWE does not hold, the trend test can still be used while the allelic test is no longer valid. Therefore, the allelic test is either not valid or is asymptotically equivalent to the trend test. It appears that the allelic test is a nuisance test. Can it be retired from the analysis of case-control association studies? It all depends on data and model assumptions. We give conditions under which the allelic test and the trend test are asymptotically equivalent under both null and alternative hypotheses.

Functional variants in the B-cell gene BANK1 are associated with systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a prototypical autoimmune disease characterized by production of autoantibodies and complex genetic inheritance. In a genome-wide scan using 85,042 SNPs, we identified an association between SLE and a nonsynonymous substitution (rs10516487, R61H) in the B-cell scaffold protein with ankyrin repeats gene, BANK1. We replicated the association in four independent case-control sets (combined P = 3.7 x 10(-10); OR = 1.38). We analyzed BANK1 cDNA and found two isoforms, one full-length and the other alternatively spliced and lacking exon 2 (Delta2), encoding a protein without a putative IP3R-binding domain. The transcripts were differentially expressed depending on a branch point-site SNP, rs17266594, in strong linkage disequilibrium (LD) with rs10516487. A third associated variant was found in the ankyrin domain (rs3733197, A383T). Our findings implicate BANK1 as a susceptibility gene for SLE, with variants affecting regulatory sites and key functional domains. The disease-associated variants could contribute to sustained B cell-receptor signaling and B-cell hyperactivity characteristic of this disease.

Universal false discovery rate estimation methodology for genome-wide association studies

Genome-wide case-control association studies aim at identifying significant differential markers between sick and healthy populations. With the development of large-scale technologies allowing the genotyping of thousands of single nucleotide polymorphisms (SNPs) comes the multiple testing problem and the practical issue of selecting the most probable set of associated markers. Several False Discovery Rate (FDR) estimation methods have been developed and tuned mainly for differential gene expression studies. However they are based on hypotheses and designs that are not necessarily relevant in genetic association studies. In this article we present a universal methodology to estimate the FDR of genome-wide association results. It uses a single global probability value per SNP and is applicable in practice for any study design, using any statistic. We have benchmarked this algorithm on simulated data and shown that it outperforms previous methods in cases requiring non-parametric estimation. We exemplified the usefulness of the method by applying it to the analysis of experimental genotyping data of three Multiple Sclerosis case-control association studies.