Application of a rank-based genetic association test to age-at-onset data from the Collaborative Study on the Genetics of Alcoholism study.

Association studies of quantitative traits have often relied on methods in which a normal distribution of the trait is assumed. However, quantitative phenotypes from complex human diseases are often censored, highly skewed, or contaminated with outlying values. We recently developed a rank-based association method that takes into account censoring and makes no distributional assumptions about the trait. In this study, we applied our new method to age-at-onset data on ALDX1 and ALDX2. Both traits are highly skewed (skewness > 1.9) and often censored. We performed a whole genome association study of age at onset of the ALDX1 trait using Illumina single-nucleotide polymorphisms. Only slightly more than 5% of markers were significant. However, we identified two regions on chromosomes 14 and 15, which each have at least four significant markers clustering together. These two regions may harbor genes that regulate age at onset of ALDX1 and ALDX2. Future fine mapping of these two regions with densely spaced markers is warranted.

Functional annotation signatures of disease susceptibility loci improve SNP association analysis.

BACKGROUND: Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan. RESULTS: We developed a Bayesian statistical model for the prior probability of phenotype-genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs in the GWAS Catalog (GC). The functional predictors examined included measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super-track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants in the Database of Genomic Variants and known regulatory elements in the Open Regulatory Annotation database, PolyPhen-2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotations would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non-informative predictors and evaluated the model's ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP's presence in the GC. Further, using data from a genome-wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome-wide scale and improves power to detect associations. CONCLUSIONS: We show how diverse functional annotations can be efficiently combined to create 'functional signatures' that predict the a priori odds of a variant's association to a trait and how these signatures can be integrated into a standard genome-wide-scale association analysis, resulting in improved power to detect truly associated variants.

permGPU: Using graphics processing units in RNA microarray association studies.

BACKGROUND: Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. RESULTS: We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. CONCLUSIONS: permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.

Novel associations of UDP-glucuronosyltransferase 2B gene variants with prostate cancer risk in a multiethnic study.

BACKGROUND: We have previously shown that a functional polymorphism of the UGT2B15 gene (rs1902023) was associated with increased risk of prostate cancer (PC). Novel functional polymorphisms of the UGT2B17 and UGT2B15 genes have been recently characterized by in vitro assays but have not been evaluated in epidemiologic studies. METHODS: Fifteen functional SNPs of the UGT2B17 and UGT2B15 genes, including cis-acting UGT2B gene SNPs, were genotyped in African American and Caucasian men (233 PC cases and 342 controls). Regression models were used to analyze the association between SNPs and PC risk. RESULTS: After adjusting for race, age and BMI, we found that six UGT2B15 SNPs (rs4148269, rs3100, rs9994887, rs13112099, rs7686914 and rs7696472) were associated with an increased risk of PC in log-additive models (p < 0.05). A SNP cis-acting on UGT2B17 and UGT2B15 expression (rs17147338) was also associated with increased risk of prostate cancer (OR = 1.65, 95% CI = 1.00-2.70); while a stronger association among men with high Gleason sum was observed for SNPs rs4148269 and rs3100. CONCLUSIONS: Although small sample size limits inference, we report novel associations between UGT2B15 and UGT2B17 variants and PC risk. These associations with PC risk in men with high Gleason sum, more frequently found in African American men, support the relevance of genetic differences in the androgen metabolism pathway, which could explain, in part, the high incidence of PC among African American men. Larger studies are required.

Finding our way through phenotypes.

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.

Psychiatric correlates of snuff and chewing tobacco use.

Compared to the association between cigarette smoking and psychiatric disorders, relatively little is known about the relationship between smokeless tobacco use and psychiatric disorders. To identify the psychiatric correlates of smokeless tobacco use, the analysis used a national representative sample from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) wave 1. Smokeless tobacco use was classified as exclusive snuff use, exclusive chewing tobacco, and dual use of both snuff and chewing tobacco at some time in the smokeless tobacco user's life. Lifetime psychiatric disorders were obtained via structured diagnostic interviews. The results show that the prevalence of lifetime exclusive snuff use, exclusive chewing tobacco, and dual use of both snuff and chewing tobacco was 2.16%, 2.52%, and 2.79%, respectively. After controlling for sociodemographic variables and cigarette smoking, the odds of exclusive chewing tobacco in persons with panic disorder and specific phobia were 1.53 and 1.41 times the odds in persons without those disorders, respectively. The odds of exclusive snuff use, exclusive chewing tobacco, and dual use of both products for individuals with alcohol use disorder were 1.97, 2.01, and 2.99 times the odds for those without alcohol use disorder, respectively. Respondents with cannabis use disorder were 1.44 times more likely to use snuff exclusively than those without cannabis use disorder. Respondents with inhalant/solvent use disorder were associated with 3.33 times the odds of exclusive chewing tobacco. In conclusion, this study highlights the specific links of anxiety disorder, alcohol, cannabis, and inhalant/solvent use disorders with different types of smokeless tobacco use.

Polymorphisms in the kinesin-like factor 1 B gene and risk of epithelial ovarian cancer in Eastern Chinese women.

The kinesin-like factor 1 B (KIF1B) gene plays an important role in the process of apoptosis and the transformation and progression of malignant cells. Genetic variations in KIF1B may contribute to risk of epithelial ovarian cancer (EOC). In this study of 1,324 EOC patients and 1,386 cancer-free female controls, we investigated associations between two potentially functional single nucleotide polymorphisms in KIF1B and EOC risk by the conditional logistic regression analysis. General linear regression model was used to evaluate the correlation between the number of variant alleles and KIF1B mRNA expression levels. We found that the rs17401966 variant AG/GG genotypes were significantly associated with a decreased risk of EOC (adjusted odds ratio (OR) = 0.81, 95 % confidence interval (CI) = 0.68-0.97), compared with the AA genotype, but no associations were observed for rs1002076. Women who carried both rs17401966 AG/GG and rs1002076 AG/AA genotypes of KIF1B had a 0.82-fold decreased risk (adjusted 95 % CI = 0.69-0.97), compared with others. Additionally, there was no evidence of possible interactions between about-mentioned co-variants. Further genotype-phenotype correlation analysis indicated that the number of rs17401966 variant G allele was significantly associated with KIF1B mRNA expression levels (P for GLM = 0.003 and 0.001 in all and Chinese subjects, respectively), with GG carriers having the lowest level of KIF1B mRNA expression. Taken together, the rs17401966 polymorphism likely regulates KIF1B mRNA expression and thus may be associated with EOC risk in Eastern Chinese women. Larger, independent studies are warranted to validate our findings.

Apoptotic variants as predictors of risk of oropharyngeal cancer recurrence after definitive radiotherapy.

Single nucleotide polymorphisms (SNPs) in the promoter region of FAS and FASLG may alter their transcriptional activity. Thus, we determined the associations between four FAS and FASLG promoter variants (FAS1377G>A, rs2234767; 670A>G, rs1800682; FASLG844T>C, rs763110 and 124A>G, rs5030772) and the risk of recurrence of squamous cell carcinoma of the oropharynx (SCCOP). We evaluated the associations between FAS and FASLG genetic variants and the risk of recurrence in a cohort of 1,008 patients. The log-rank test and multivariate Cox models were used to evaluate the associations. Compared with patients with common homozygous genotypes of FAS670 and FASLG844 polymorphisms, patients with variant genotypes had lower disease-free survival rates (log-rank p < 0.0001 and p < 0.0001, respectively) and an approximately threefold higher risk of SCCOP recurrence (HR, 3.2;95% CI, 2.2-4.6; and HR, 3.1; 95% CI, 2.2-4.4, respectively) after multivariate adjustment. Furthermore, among patients with HPV16-positive tumors, those with variant genotypes of these two polymorphisms had lower disease-free survival rates (log-rank, p < 0.0001 and p < 0.0001, respectively) and a higher recurrence risk than did patients with common homozygous genotypes (HR, 12.9; 95% CI, 3.8-43.6; and HR, 8.1; 95% CI, 3.6-18.6, respectively), whereas no significant associations were found for FAS1377 and FASLG124 polymorphisms. Our findings suggest that FAS670 and FASLG844 polymorphisms modulate the risk of recurrence of SCCOP, particularly in patients with HPV16-positive tumors. Larger studies are needed to validate these results.

BAYESIAN MODEL SEARCH AND MULTILEVEL INFERENCE FOR SNP ASSOCIATION STUDIES.

Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using existing analytic methodologies. Obstacles to analysis include inference in the face of multiple comparisons, complications arising from correlations among the SNPs (single nucleotide polymorphisms), choice of their genetic parametrization and missing data. In this paper we present an efficient Bayesian model search strategy that searches over the space of genetic markers and their genetic parametrization. The resulting method for Multilevel Inference of SNP Associations, MISA, allows computation of multilevel posterior probabilities and Bayes factors at the global, gene and SNP level, with the prior distribution on SNP inclusion in the model providing an intrinsic multiplicity correction. We use simulated data sets to characterize MISA's statistical power, and show that MISA has higher power to detect association than standard procedures. Using data from the North Carolina Ovarian Cancer Study (NCOCS), MISA identifies variants that were not identified by standard methods and have been externally "validated" in independent studies. We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data. MISA is available in an R package on CRAN.

Adaptive Mixture Modelling Metropolis Methods for Bayesian Analysis of Non-linear State-Space Models.

We describe a strategy for Markov chain Monte Carlo analysis of non-linear, non-Gaussian state-space models involving batch analysis for inference on dynamic, latent state variables and fixed model parameters. The key innovation is a Metropolis-Hastings method for the time series of state variables based on sequential approximation of filtering and smoothing densities using normal mixtures. These mixtures are propagated through the non-linearities using an accurate, local mixture approximation method, and we use a regenerating procedure to deal with potential degeneracy of mixture components. This provides accurate, direct approximations to sequential filtering and retrospective smoothing distributions, and hence a useful construction of global Metropolis proposal distributions for simulation of posteriors for the set of states. This analysis is embedded within a Gibbs sampler to include uncertain fixed parameters. We give an example motivated by an application in systems biology. Supplemental materials provide an example based on a stochastic volatility model as well as MATLAB code.

Genome-wide association study of Lp-PLA(2) activity and mass in the Framingham Heart Study.

Lipoprotein-associated phospholipase A(2) (Lp-PLA(2)) is an emerging risk factor and therapeutic target for cardiovascular disease. The activity and mass of this enzyme are heritable traits, but major genetic determinants have not been explored in a systematic, genome-wide fashion. We carried out a genome-wide association study of Lp-PLA(2) activity and mass in 6,668 Caucasian subjects from the population-based Framingham Heart Study. Clinical data and genotypes from the Affymetrix 550K SNP array were obtained from the open-access Framingham SHARe project. Each polymorphism that passed quality control was tested for associations with Lp-PLA(2) activity and mass using linear mixed models implemented in the R statistical package, accounting for familial correlations, and controlling for age, sex, smoking, lipid-lowering-medication use, and cohort. For Lp-PLA(2) activity, polymorphisms at four independent loci reached genome-wide significance, including the APOE/APOC1 region on chromosome 19 (p = 6 x 10(-24)); CELSR2/PSRC1 on chromosome 1 (p = 3 x 10(-15)); SCARB1 on chromosome 12 (p = 1x10(-8)) and ZNF259/BUD13 in the APOA5/APOA1 gene region on chromosome 11 (p = 4 x 10(-8)). All of these remained significant after accounting for associations with LDL cholesterol, HDL cholesterol, or triglycerides. For Lp-PLA(2) mass, 12 SNPs achieved genome-wide significance, all clustering in a region on chromosome 6p12.3 near the PLA2G7 gene. Our analyses demonstrate that genetic polymorphisms may contribute to inter-individual variation in Lp-PLA(2) activity and mass.

HPV16 antibodies as risk factors for oropharyngeal cancer and their association with tumor HPV and smoking status.

BACKGROUND: Antibodies (Abs) to the HPV16 proteome increase risk for HPV-associated OPC (HPVOPC). The goal of this study was to investigate the association of a panel of HPV16 Abs with risk for OPC as well as the association of these Abs with tumor HPV and smoking status among patients with OPC. METHODS: IgG Abs to the HPV16 antigens E1, E2, E4, E5, E6, E7, L1, L2 were quantified using a programmable ELISA assay. Sera were obtained from 258 OPC patients at diagnosis and 250 healthy controls. HPV16 tumor status was measured by PCR for 137 cases. Multivariable logistic regression was used to calculate odds ratios for the association of HPV16 Abs with risk for OPC. RESULTS: HPV16 E1, E2, E4, E5, E6, E7 and L1-specific IgG levels were elevated in OPC patients compared to healthy controls (p<0.05). After multivariable adjustment, Ab positivity for NE2, CE2, E6, and/or E7 was associated with OPC risk (OR [95% CI], 249.1 [99.3-624.9]). Among patients with OPC, Ab positivity for these antigens was associated with tumor HPV status, especially among never or light smokers (OR [95% CI], 6.5 [2.1-20.1] and OR [95% CI], 17.5 [4.0-77.2], respectively). CONCLUSIONS: Antibodies to HPV16 proteins are associated with increased risk for HPVOPC. Among patients with OPC, HPV16 Abs are associated with tumor HPV status, in particular among HPV positive patients with no or little smoking history.

Association of Common Genetic Polymorphisms with Melanoma Patient IL-12p40 Blood Levels, Risk, and Outcomes.

Recent investigation has identified association of IL-12p40 blood levels with melanoma recurrence and patient survival. No studies have investigated associations of single-nucleotide polymorphisms (SNPs) with melanoma patient IL-12p40 blood levels or their potential contributions to melanoma susceptibility or patient outcome. In the current study, 818,237 SNPs were available for 1,804 melanoma cases and 1,026 controls. IL-12p40 blood levels were assessed among 573 cases (discovery), 249 cases (case validation), and 299 controls (control validation). SNPs were evaluated for association with log[IL-12p40] levels in the discovery data set and replicated in two validation data sets, and significant SNPs were assessed for association with melanoma susceptibility and patient outcomes. The most significant SNP associated with log[IL-12p40] was in the IL-12B gene region (rs6897260, combined P=9.26 × 10(-38)); this single variant explained 13.1% of variability in log[IL-12p40]. The most significant SNP in EBF1 was rs6895454 (combined P=2.24 × 10(-9)). A marker in IL12B was associated with melanoma susceptibility (rs3213119, multivariate P=0.0499; OR=1.50, 95% CI 1.00-2.24), whereas a marker in EBF1 was associated with melanoma-specific survival in advanced-stage patients (rs10515789, multivariate P=0.02; HR=1.93, 95% CI 1.11-3.35). Both EBF1 and IL12B strongly regulate IL-12p40 blood levels, and IL-12p40 polymorphisms may contribute to melanoma susceptibility and influence patient outcome.

Associations between smoking behavior-related alleles and the risk of melanoma.

Several studies have reported that cigarette smoking is inversely associated with the risk of melanoma. This study further tested whether incorporating genetic factors will provide another level of evaluation of mechanisms underlying the association between smoking and risk of melanoma. We investigated the association between SNPs selected from genome-wide association studies (GWAS) on smoking behaviors and risk of melanoma using 2,298 melanoma cases and 6,654 controls. Among 16 SNPs, three (rs16969968 [A], rs1051730 [A] and rs2036534 [C] in the 15q25.1 region) reached significance for association with melanoma risk in men (0.01 < = P values < = 0.02; 0.85 < = Odds Ratios (ORs) <= 1.20). There was association between the genetic scores based on the number of smoking behavior-risk alleles and melanoma risk with P-trend = 0.005 among HPFS. Further association with smoking behaviors indicating those three SNPs (rs16969968 [A], rs1051730 [A] and rs2036534 [C]) significantly associated with number of cigarettes smoked per day, CPD, with P = 0.009, 0.011 and 0.001 respectively. The SNPs rs215605 in the PDE1C gene and rs6265 in the BDNF gene significantly interacted with smoking status on melanoma risk (interaction P = 0.005 and P = 0.003 respectively). Our study suggests that smoking behavior-related SNPs are likely to play a role in melanoma development and the potential public health importance of polymorphisms in the CHRNA5-A3-B4 gene cluster. Further larger studies are warranted to validate the findings.