A risk variant for Barrett's esophagus and esophageal adenocarcinoma at chr8p23.1 affects enhancer activity and implicates multiple gene targets.

Nineteen genetic susceptibility loci for esophageal adenocarcinoma (EAC) and its precursor Barrett's esophagus (BE) have been identified through genome-wide association studies (GWAS). Clinical translation of such discoveries, however, has been hindered by the slow pace of discovery of functional/causal variants and gene targets at these loci. We previously developed a systematic informatics pipeline to prioritize candidate functional variants using functional potential scores, applied the pipeline to select high-scoring BE/EAC risk loci and validated a functional variant at chr19p13.11 (rs10423674). Here, we selected two additional prioritized loci for experimental interrogation: chr3p13/rs1522552 and chr8p23.1/rs55896564. Candidate enhancer regions encompassing these variants were evaluated using luciferase reporter assays in two EAC cell lines. One of the two regions tested exhibited allele-specific enhancer activity - 8p23.1/rs55896564. CRISPR-mediated deletion of the putative enhancer in EAC cell lines correlated with reduced expression of three candidate gene targets: B lymphocyte kinase (BLK), nei like DNA glycosylase 2 (NEIL2) and cathepsin B (CTSB). Expression quantitative trait locus (eQTL) mapping in normal esophagus and stomach revealed strong associations between the BE/EAC risk allele at rs55896564 (G) and lower expression of CTSB, a protease gene implicated in epithelial wound repair. These results further support the utility of functional potential scores for GWAS variant prioritization, and provide the first experimental evidence of a functional variant and risk enhancer at the 8p23.1 GWAS locus. Identification of CTSB, BLK and NEIL2 as candidate gene targets suggests that altered expression of these genes may underlie the genetic risk association at 8p23.1 with BE/EAC.

Prioritization and functional analysis of GWAS risk loci for Barrett's esophagus and esophageal adenocarcinoma.

Genome-wide association studies (GWAS) have identified ~20 genetic susceptibility loci for esophageal adenocarcinoma (EAC), and its precursor, Barrett's esophagus (BE). Despite such advances, functional/causal variants and gene targets at these loci remain undefined, hindering clinical translation. A key challenge is that most causal variants map to non-coding regulatory regions such as enhancers, and typically, numerous potential candidate variants at GWAS loci require testing. We developed a systematic informatics pipeline for prioritizing candidate functional variants via integrative functional potential scores (FPS) consolidated from multi-omics annotations, and used this pipeline to identify two high-scoring variants for experimental interrogation: chr9q22.32/rs11789015 and chr19p13.11/rs10423674. Minimal candidate enhancer regions spanning these variants were evaluated using luciferase reporter assays in two EAC cell lines. One of the two variants tested (rs10423674) exhibited allele-specific enhancer activity. CRISPR-mediated deletion of the putative enhancer region in EAC cell lines correlated with reduced expression of two genes-CREB-regulated transcription coactivator 1 (CRTC1) and Cartilage oligomeric matrix protein (COMP); expression of five other genes remained unchanged (CRLF1, KLHL26, TMEM59L, UBA52, RFXANK). Expression quantitative trait locus mapping indicated that rs10423674 genotype correlated with CRTC1 and COMP expression in normal esophagus. This study represents the first experimental effort to bridge GWAS associations to biology in BE/EAC and supports the utility of FPS to guide variant prioritization. Our findings reveal a functional variant and candidate risk enhancer at chr19p13.11 and implicate CRTC1 and COMP as putative gene targets, suggesting that altered expression of these genes may underlie the BE/EAC risk association.

DNA methylation and cis-regulation of gene expression by prostate cancer risk SNPs.

Genome-wide association studies have identified more than 100 SNPs that increase the risk of prostate cancer (PrCa). We identify and compare expression quantitative trait loci (eQTLs) and CpG methylation quantitative trait loci (meQTLs) among 147 established PrCa risk SNPs in primary prostate tumors (n = 355 from a Seattle-based study and n = 495 from The Cancer Genome Atlas, TCGA) and tumor-adjacent, histologically benign samples (n = 471 from a Mayo Clinic study). The role of DNA methylation in eQTL regulation of gene expression was investigated by data triangulation using several causal inference approaches, including a proposed adaptation of the Causal Inference Test (CIT) for causal direction. Comparing eQTLs between tumors and benign samples, we show that 98 of the 147 risk SNPs were identified as eQTLs in the tumor-adjacent benign samples, and almost all 34 eQTL identified in tumor sets were also eQTLs in the benign samples. Three lines of results support the causal role of DNA methylation. First, nearly 100 of the 147 risk SNPs were identified as meQTLs in one tumor set, and almost all eQTLs in tumors were meQTLs. Second, the loss of eQTLs in tumors relative to benign samples was associated with altered DNA methylation. Third, among risk SNPs identified as both eQTLs and meQTLs, mediation analyses suggest that over two-thirds have evidence of a causal role for DNA methylation, mostly mediating genetic influence on gene expression. In summary, we provide a comprehensive catalog of eQTLs, meQTLs and putative cancer genes for known PrCa risk SNPs. We observe that a substantial portion of germline eQTL regulatory mechanisms are maintained in the tumor development, despite somatic alterations in tumor genome. Finally, our mediation analyses illuminate the likely intermediary role of CpG methylation in eQTL regulation of gene expression.

Timing and duration of bevacizumab treatment and survival in patients with recurrent ovarian, fallopian tube, and peritoneal cancer: a multi-institution study.

Bevacizumab has demonstrated significant benefit in recurrent ovarian, fallopian tube and peritoneal cancer (OC), but its optimal position within the sequence of systemic therapies remains controversial. Since rebound progression after bevacizumab has been observed in other cancers, and because bevacizumab is incorporated in several regimens used in the recurrent setting, the duration of treatment may impact survival. We sought to identify whether earlier bevacizumab exposure is associated with prolonged bevacizumab therapy and survival by conducting a multi-institution retrospective study of recurrent OC patients treated with bevacizumab from 2004-2014. Multivariate logistic regression identified factors associated with receiving more than six bevacizumab cycles. Overall survival by duration and ordinal sequence of bevacizumab therapy were evaluated using logrank testing and Cox regression. In total, 318 patients were identified. 89.1% had stage III or IV disease; 36% had primary platinum resistance; 40.5% received two or fewer prior chemotherapy regimens. Multivariate logistic regression demonstrated that primary platinum sensitivity (Odds Ratio (OR) 2.34, p = 0.001) or initiating bevacizumab at the first or second recurrence (OR 2.73, p < 0.001) were independently associated with receiving more than six cycles of bevacizumab. Receiving more cycles of bevacizumab was associated with improved overall survival whether measured from time of diagnosis (logrank p < 0.001), bevacizumab initiation (logrank p < 0.001), or bevacizumab discontinuation (logrank p = 0.017). Waiting one additional recurrence to initiate bevacizumab resulted in a 27% increased hazard of death (Hazard Ratio (HR) 1.27, p < 0.001) by multivariate analysis. In conclusion, patients with primary platinum sensitive disease who received fewer prior lines of chemotherapy were able to receive more cycles of bevacizumab, which was associated with improved overall survival. Survival worsened when bevacizumab was initiated later in the ordinal sequence of therapies.

Genetic variants associated with circulating C-reactive protein levels and colorectal cancer survival: Sex-specific and lifestyle factors specific associations.

Elevated blood levels of C-reactive protein (CRP) have been linked to colorectal cancer (CRC) survival. We evaluated genetic variants associated with CRP levels and their interactions with sex and lifestyle factors in association with CRC-specific mortality. Our study included 16 142 CRC cases from the International Survival Analysis in Colorectal Cancer Consortium. We identified 618 common single nucleotide polymorphisms (SNPs) associated with CRP levels from the NHGRI-EBI GWAS Catalog. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between SNPs and CRC-specific mortality adjusting for age, sex, genotyping platform/study and principal components. We investigated their interactions with sex and lifestyle factors using likelihood ratio tests. Of 5472 (33.9%) deaths accrued over up to 10 years of follow-up, 3547 (64.8%) were due to CRC. No variants were associated with CRC-specific mortality after multiple comparison correction. We observed strong evidence of interaction between variant rs1933736 at FRK gene and sex in relation to CRC-specific mortality (corrected Pinteraction  = .0004); women had higher CRC-specific mortality associated with the minor allele (HR = 1.11, 95% CI = 1.04-1.19) whereas an inverse association was observed for men (HR = 0.88, 95% CI = 0.82-0.94). There was no evidence of interactions between CRP-associated SNPs and alcohol, obesity or smoking. Our study observed a significant interaction between sex and a CRP-associated variant in relation to CRC-specific mortality. Future replication of this association and functional annotation of the variant are needed.

Germline variation in the insulin-like growth factor pathway and risk of Barrett's esophagus and esophageal adenocarcinoma.

Genome-wide association studies (GWAS) of esophageal adenocarcinoma (EAC) and its precursor, Barrett's esophagus (BE), have uncovered significant genetic components of risk, but most heritability remains unexplained. Targeted assessment of genetic variation in biologically relevant pathways using novel analytical approaches may identify missed susceptibility signals. Central obesity, a key BE/EAC risk factor, is linked to systemic inflammation, altered hormonal signaling and insulin-like growth factor (IGF) axis dysfunction. Here, we assessed IGF-related genetic variation and risk of BE and EAC. Principal component analysis was employed to evaluate pathway-level and gene-level associations with BE/EAC, using genotypes for 270 single-nucleotide polymorphisms (SNPs) in or near 12 IGF-related genes, ascertained from 3295 BE cases, 2515 EAC cases and 3207 controls in the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON) GWAS. Gene-level signals were assessed using Multi-marker Analysis of GenoMic Annotation (MAGMA) and SNP summary statistics from BEACON and an expanded GWAS meta-analysis (6167 BE cases, 4112 EAC cases, 17 159 controls). Global variation in the IGF pathway was associated with risk of BE (P = 0.0015). Gene-level associations with BE were observed for GHR (growth hormone receptor; P = 0.00046, false discovery rate q = 0.0056) and IGF1R (IGF1 receptor; P = 0.0090, q = 0.0542). These gene-level signals remained significant at q < 0.1 when assessed using data from the largest available BE/EAC GWAS meta-analysis. No significant associations were observed for EAC. This study represents the most comprehensive evaluation to date of inherited genetic variation in the IGF pathway and BE/EAC risk, providing novel evidence that variation in two genes encoding cell-surface receptors, GHR and IGF1R, may influence risk of BE.

Association between post-treatment circulating biomarkers of inflammation and survival among stage II-III colorectal cancer patients.

BACKGROUND: Biomarker studies on colorectal cancer (CRC) prognosis are limited to pre-diagnostic or pre-operative measures. Post-treatment biomarkers are not well understood for their associations with CRC survival. METHODS: We included 306 eligible incident stage II-III CRC cases from the population-based Seattle Colon Cancer Family Registry. Concentrations of C-reactive protein (CRP), interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), adiponectin, and leptin were measured using post-treatment plasma samples. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause and CRC-specific mortality were calculated using Cox proportional hazard models. RESULTS: Elevated levels of CRP, IL-6, MCP-1, and adiponectin were significantly associated with a higher risk of all-cause mortality within 10 years post blood draw with HRs (95% CI) of 1.32 (1.10-2.59), 2.72 (2.07-3.56), 1.97 (1.18-3.28) and 1.71 (1.14-2.58), respectively. IL-6 and adiponectin had a dose-response effect (Ptrend < 0.0001). For CRC-specific mortality, we observed positive associations for CRP (HR = 1.75, 95% CI: 1.2-2.56), IL-6 (HR = 5.02, 95% CI: 2.92-8.59), MCP-1 (HR = 3.78, 95% CI: 1.41-10.08), and adiponectin (HR = 3.16, 95% CI: 1.27-7.86), and inverse association for leptin (HR = 0.44, 95% CI: 0.29-0.68) within the first year of blood draw, whereas the association for IL-6 remained statistically significant over 10 years. CONCLUSION: Our results support the role of chronic inflammation in CRC progression and suggested several post-treatment inflammatory biomarkers, particularly IL-6, are promising prognostic markers for stage II-III CRC patients.

A four-gene transcript score to predict metastatic-lethal progression in men treated for localized prostate cancer: Development and validation studies.

BACKGROUND: Molecular studies have tried to address the unmet need for prognostic biomarkers in prostate cancer (PCa). Some gene expression tests improve upon clinical factors for prediction of outcomes, but additional tools for accurate prediction of tumor aggressiveness are needed. METHODS: Based on a previously published panel of 23 gene transcripts that distinguished patients with metastatic progression, we constructed a prediction model using independent training and testing datasets. Using the validated messenger RNAs and Gleason score (GS), we performed model selection in the training set to define a final locked model to classify patients who developed metastatic-lethal events from those who remained recurrence-free. In an independent testing dataset, we compared our locked model to established clinical prognostic factors and utilized Kaplan-Meier curves and receiver operating characteristic analyses to evaluate the model's performance. RESULTS: Thirteen of 23 previously identified gene transcripts that stratified patients with aggressive PCa were validated in the training dataset. These biomarkers plus GS were used to develop a four-gene (CST2, FBLN1, TNFRSF19, and ZNF704) transcript (4GT) score that was significantly higher in patients who progressed to metastatic-lethal events compared to those without recurrence in the testing dataset (P = 5.7 × 10-11 ). The 4GT score provided higher prediction accuracy (area under the ROC curve [AUC] = 0.76; 95% confidence interval [CI] = 0.69-0.83; partial area under the ROC curve [pAUC] = 0.008) than GS alone (AUC = 0.63; 95% CI = 0.56-0.70; pAUC = 0.002), and it improved risk stratification in subgroups defined by a combination of clinicopathological features (ie, Cancer of the Prostate Risk Assessment-Surgery). CONCLUSION: Our validated 4GT score has prognostic value for metastatic-lethal progression in men treated for localized PCa and warrants further evaluation for its clinical utility.

Constrained Score Statistics Identify Genetic Variants Interacting with Multiple Risk Factors in Barrett's Esophagus.

Few gene-environment interactions (G × E) have been discovered in cancer epidemiology thus far, in part due to the large number of possible G × E to be investigated and inherent low statistical power of traditional analytic methods for discovering G × E. We consider simultaneously testing for interactions between several related exposures and a genetic variant in a genome-wide study. To improve power, constrained testing strategies are proposed for multivariate gene-environment interactions at two levels: interactions that have the same direction (one-sided or bidirectional hypotheses) or are proportional to respective exposure main effects (a variant of Tukey's one-degree test). Score statistics were developed to expedite the genome-wide computation. We conducted extensive simulations to evaluate validity and power performance of the proposed statistics, applied them to the genetic and environmental exposure data for esophageal adenocarcinoma and Barrett's esophagus from the Barretts Esophagus and Esophageal Adenocarcinoma Consortium (BEACON), and discovered three loci simultaneously interacting with gastresophageal reflux, obesity, and tobacco smoking with genome-wide significance. These findings deepen understanding of the genetic and environmental architecture of Barrett's esophagus and esophageal adenocarcinoma.

Interactive decision support for esophageal adenocarcinoma screening and surveillance.

BACKGROUND: A key barrier to controlling esophageal adenocarcinoma (EAC) is identifying those most likely to benefit from screening and surveillance. We aimed to develop an online educational tool, termed IC-RISC™, for providers and patients to estimate more precisely their absolute risk of developing EAC, interpret this estimate in the context of risk of dying from other causes, and aid in decision-making. RESULTS: U.S. incidence and mortality data and published relative risk estimates from observational studies and clinical trials were used to calculate absolute risk of EAC over 10 years adjusting for competing risks. These input parameters varied depending on presence of the key precursor, Barrett's esophagus. The open source application works across common devices to gather risk factor data and graphically illustrate estimated risk on a single page. Changes to input data are immediately reflected in the colored graphs. We used the calculator to compare the risk distribution between EAC cases and controls from six population-based studies to gain insight into the discrimination metrics of current practice guidelines for screening, observing that current guidelines sacrifice a significant amount of specificity to identify 78-86% of eventual cases in the US population. CONCLUSIONS: This educational tool provides a simple and rapid means to graphically communicate risk of EAC in the context of other health risks, facilitates "what-if" scenarios regarding potential preventative actions, and can inform discussions regarding screening, surveillance and treatment options. Its generic architecture lends itself to being easily extended to other cancers with distinct pathways and/or intermediate stages, such as hepatocellular cancer. IC-RISC™ extends current qualitative clinical practice guidelines into a quantitative assessment, which brings the possibility of preventative actions being offered to persons not currently targeted for screening and, conversely, reducing unnecessary procedures in those at low risk. Prospective validation and application to existing well-characterized cohort studies are needed.

Diagnostics for Pleiotropy in Mendelian Randomization Studies: Global and Individual Tests for Direct Effects.

Diagnosing pleiotropy is critical for assessing the validity of Mendelian randomization (MR) analyses. The popular MR-Egger method evaluates whether there is evidence of bias-generating pleiotropy among a set of candidate genetic instrumental variables. In this article, we propose a statistical method-global and individual tests for direct effects (GLIDE)-for systematically evaluating pleiotropy among the set of genetic variants (e.g., single nucleotide polymorphisms (SNPs)) used for MR. As a global test, simulation experiments suggest that GLIDE is nearly uniformly more powerful than the MR-Egger method. As a sensitivity analysis, GLIDE is capable of detecting outliers in individual variant-level pleiotropy, in order to obtain a refined set of genetic instrumental variables. We used GLIDE to analyze both body mass index and height for associations with colorectal cancer risk in data from the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry (multiple studies). Among the body mass index-associated SNPs and the height-associated SNPs, several individual variants showed evidence of pleiotropy. Removal of these potentially pleiotropic SNPs resulted in attenuation of respective estimates of the causal effects. In summary, the proposed GLIDE method is useful for sensitivity analyses and improves the validity of MR.

A five-CpG DNA methylation score to predict metastatic-lethal outcomes in men treated with radical prostatectomy for localized prostate cancer.

BACKGROUND: Prognostic biomarkers for localized prostate cancer (PCa) could improve personalized medicine. Our group previously identified a panel of differentially methylated CpGs in primary tumor tissue that predict disease aggressiveness, and here we further validate these biomarkers. METHODS: Pyrosequencing was used to assess CpG methylation of eight biomarkers previously identified using the HumanMethylation450 array; CpGs with strongly correlated (r >0.70) results were considered technically validated. Logistic regression incorporating the validated CpGs and Gleason sum was used to define and lock a final model to stratify men with metastatic-lethal versus non-recurrent PCa in a training dataset. Coefficients from the final model were then used to construct a DNA methylation score, which was evaluated by logistic regression and Receiver Operating Characteristic (ROC) curve analyses in an independent testing dataset. RESULTS: Five CpGs were technically validated and all were retained (P < 0.05) in the final model. The 5-CpG and Gleason sum coefficients were used to calculate a methylation score, which was higher in men with metastatic-lethal progression (P = 6.8 × 10-6 ) in the testing dataset. For each unit increase in the score there was a four-fold increase in risk of metastatic-lethal events (odds ratio, OR = 4.0, 95%CI = 1.8-14.3). At 95% specificity, sensitivity was 74% for the score compared to 53% for Gleason sum alone. The score demonstrated better prediction performance (AUC = 0.91; pAUC = 0.037) compared to Gleason sum alone (AUC = 0.87; pAUC = 0.025). CONCLUSIONS: The DNA methylation score improved upon Gleason sum for predicting metastatic-lethal progression and holds promise for risk stratification of men with aggressive tumors. This prognostic score warrants further evaluation as a tool for improving patient outcomes.

Mendelian randomisation study of age at menarche and age at menopause and the risk of colorectal cancer.

BACKGROUND: Substantial evidence supports an association between use of menopausal hormone therapy and decreased colorectal cancer (CRC) risk, indicating a role of exogenous sex hormones in CRC development. However, findings on endogenous oestrogen exposure and CRC are inconsistent. METHODS: We used a Mendelian randomisation approach to test for a causal effect of age at menarche and age at menopause as surrogates for endogenous oestrogen exposure on CRC risk. Weighted genetic risk scores based on 358 single-nucleotide polymorphisms associated with age at menarche and 51 single-nucleotide polymorphisms associated with age at menopause were used to estimate the association with CRC risk using logistic regression in 12,944 women diagnosed with CRC and 10,741 women without CRC from three consortia. Sensitivity analyses were conducted to address pleiotropy and possible confounding by body mass index. RESULTS: Genetic risk scores for age at menarche (odds ratio per year 0.98, 95% confidence interval: 0.95-1.02) and age at menopause (odds ratio 0.98, 95% confidence interval: 0.94-1.01) were not significantly associated with CRC risk. The sensitivity analyses yielded similar results. CONCLUSIONS: Our study does not support a causal relationship between genetic risk scores for age at menarche and age at menopause and CRC risk.

Tenofovir-based preexposure prophylaxis for HIV infection among African women.

BACKGROUND: Reproductive-age women need effective interventions to prevent the acquisition of human immunodeficiency virus type 1 (HIV-1) infection. METHODS: We conducted a randomized, placebo-controlled trial to assess daily treatment with oral tenofovir disoproxil fumarate (TDF), oral tenofovir-emtricitabine (TDF-FTC), or 1% tenofovir (TFV) vaginal gel as preexposure prophylaxis against HIV-1 infection in women in South Africa, Uganda, and Zimbabwe. HIV-1 testing was performed monthly, and plasma TFV levels were assessed quarterly. RESULTS: Of 12,320 women who were screened, 5029 were enrolled in the study. The rate of retention in the study was 91% during 5509 person-years of follow-up. A total of 312 HIV-1 infections occurred; the incidence of HIV-1 infection was 5.7 per 100 person-years. In the modified intention-to-treat analysis, the effectiveness was -49.0% with TDF (hazard ratio for infection, 1.49; 95% confidence interval [CI], 0.97 to 2.29), -4.4% with TDF-FTC (hazard ratio, 1.04; 95% CI, 0.73 to 1.49), and 14.5% with TFV gel (hazard ratio, 0.85; 95% CI, 0.61 to 1.21). In a random sample, TFV was detected in 30%, 29%, and 25% of available plasma samples from participants randomly assigned to receive TDF, TDF-FTC, and TFV gel, respectively. Independent predictors of TFV detection included being married, being older than 25 years of age, and being multiparous. Detection of TFV in plasma was negatively associated with characteristics predictive of HIV-1 acquisition. Elevations of serum creatinine levels were seen more frequently among participants randomly assigned to receive oral TDF-FTC than among those assigned to receive oral placebo (1.3% vs. 0.2%, P=0.004). We observed no significant differences in the frequencies of other adverse events. CONCLUSIONS: None of the drug regimens we evaluated reduced the rates of HIV-1 acquisition in an intention-to-treat analysis. Adherence to study drugs was low. (Funded by the National Institutes of Health; VOICE ClinicalTrials.gov number, NCT00705679.).

Identifying disease-associated copy number variations by a doubly penalized regression model.

Copy number variation (CNV) of DNA plays an important role in the development of many diseases. However, due to the irregularity and sparsity of the CNVs, studying the association between CNVs and a disease outcome or a trait can be challenging. Up to now, not many methods have been proposed in the literature for this problem. Most of the current researchers reply on an ad hoc two-stage procedure by first identifying CNVs in each individual genome and then performing an association test using these identified CNVs. This potentially leads to information loss and as a result a lower power to identify disease associated CNVs. In this article, we describe a new method that combines the two steps into a single coherent model to identify the common CNV across patients that are associated with certain diseases. We use a double penalty model to capture CNVs' association with both the intensities and the disease trait. We validate its performance in simulated datasets and a data example on platinum resistance and CNV in ovarian cancer genome.

Case-only approach to identifying markers predicting treatment effects on the relative risk scale.

Retrospectively measuring markers on stored baseline samples from participants in a randomized controlled trial (RCT) may provide high quality evidence as to the value of the markers for treatment selection. Originally developed for approximating gene-environment interactions in the odds ratio scale, the case-only method has recently been advocated for assessing gene-treatment interactions on rare disease endpoints in randomized clinical trials. In this article, the case-only approach is shown to provide a consistent and efficient estimator of marker by treatment interactions and marker-specific treatment effects on the relative risk scale. The prohibitive rare-disease assumption is no longer needed, broadening the utility of the case-only approach. The case-only method is resource-efficient as markers only need to be measured in cases only. It eliminates the need to model the marker's main effect, and can be used with any parametric or nonparametric learning method. The utility of this approach is illustrated by an application to genetic data in the Women's Health Initiative (WHI) hormone therapy trial.

Acceptability of and Adherence to an Antiretroviral-Based Vaginal Microbicide among Pregnant Women in the United States.

The MTN-008 trial was the first multi-dose study conducted to evaluate the safety of a microbicide gel (2:1 randomized to tenofovir 1% or hydroxycellulose (HEC) placebo gel) during pregnancy. The study aim was to evaluate safety, tolerability and pharmacokinetics of the study products. Procedures included daily gel administration, with Day 0 and Day 6 in clinic, and Days 1-5 at home. Because pregnancy may pose unique challenges to consistent gel use and acceptability, evaluation of adherence and acceptability was a secondary objective of the trial. The study enrolled healthy, HIV-negative, pregnant women aged 18-40 in Pittsburgh, PA and Birmingham, AL, USA in 2 consecutive groups: cohort 1 was 37-39 weeks gestation, cohort 2 was 34-36 weeks. Ninety-one women completed the study (45 and 46 in each cohort, respectively) and were evaluable per protocol. Adherence was evaluated using self-reports: participants completed a web-based computer-assisted self-interview (CASI) at Days 0 and 6 about gel attitudes and behaviors. At Day 6 trained research staff conducted a short interviewer-administered questionnaire with both structured and open-ended questions. Frequencies of quantitative data were tabulated in SAS and descriptive statistics are presented; open-ended textual data were summarized by a behavioral scientist experienced in qualitative analysis. Participants reported generally neutral perceptions of gel characteristics. A small number of women (7-8%) reported pain (6/90), other physical discomfort (7/90), or mental discomfort (7/90) associated with the process of applicator insertion. About 5% reported the same for the gel itself. Two-thirds (61/90) thought the gel was runny, many complained of bothersome gel leakage and several cited this reason for not inserting a full dose. The majority were not worried the gel would cause problems for their pregnancy or babies. Ninety-seven percent (83/86) said they would use the gel in the future if they were pregnant, and 90% (81/90) when nonpregnant. Self-reported adherence was high with 88% (79/90) reporting daily gel use on both the computerized and interviewer-administered questionnaires. The majority (67/90) reported no difficulty with daily use. However, drug was undetectable (<0.31 ng/mL) among 45% (27/60; 95% CI 32-58%) of the women on active product prior to observed dosing at Day 6. The most common reason for reported nonuse (N = 6) was forgetting. Study gel was generally acceptable, but many complained of a runny consistency (61/90) and leakage (83/90). No frequent or strong concerns about the effects of the study gel on the pregnancy/fetus were reported. Self-reported adherence to study gel self-administered at home for 5 days was high, however plasma drug levels suggest actual use may have been considerably lower. Findings from this study can provide insights relevant to use of other antiretroviral-based, vaginally-inserted HIV prevention methods during pregnancy.

Group association test using a hidden Markov model.

In the genomic era, group association tests are of great interest. Due to the overwhelming number of individual genomic features, the power of testing for association of a single genomic feature at a time is often very small, as are the effect sizes for most features. Many methods have been proposed to test association of a trait with a group of features within a functional unit as a whole, e.g. all SNPs in a gene, yet few of these methods account for the fact that generally a substantial proportion of the features are not associated with the trait. In this paper, we propose to model the association for each feature in the group as a mixture of features with no association and features with non-zero associations to explicitly account for the possibility that a fraction of features may not be associated with the trait while other features in the group are. The feature-level associations are first estimated by generalized linear models; the sequence of these estimated associations is then modeled by a hidden Markov chain. To test for global association, we develop a modified likelihood ratio test based on a log-likelihood function that ignores higher order dependency plus a penalty term. We derive the asymptotic distribution of the likelihood ratio test under the null hypothesis. Furthermore, we obtain the posterior probability of association for each feature, which provides evidence of feature-level association and is useful for potential follow-up studies. In simulations and data application, we show that our proposed method performs well when compared with existing group association tests especially when there are only few features associated with the outcome.

TwoPhaseInd: an R package for estimating gene-treatment interactions and discovering predictive markers in randomized clinical trials.

In randomized clinical trials, identifying baseline genetic or genomic markers for predicting subgroup treatment effects is of rising interest. Outcome-dependent sampling is often employed for measuring markers. The R package TwoPhaseInd implements a number of efficient statistical methods we developed for estimating subgroup treatment effects and gene-treatment interactions, exploiting the gene-treatment independence dictated by randomization, including the case-only estimator, the maximum estimated likelihood estimator and the semiparametric maximum likelihood estimator for parameters in a logistic model. For rare failure events subject to censoring, we have proposed efficient augmented case-only designs, a variation of the case-cohort design, to estimate genetic associations and subgroup treatment effects in a Cox regression model. The R package is computationally scalable to genome-wide studies, as illustrated by an example from Women's Health Initiative. AVAILABILITY AND IMPLEMENTATION: The R package TwoPhaseInd is available from http://cran.r-project.org/web/packages CONTACT: jdai@fredhutch.org.

Pharmacological Measures of Treatment Adherence and Risk of HIV Infection in the VOICE Study.

BACKGROUND: None of the 3 regimens tested in the VOICE study showed protection against human immunodeficiency virus (HIV) infection in intent-to-treat analyses. Plasma tenofovir concentrations demonstrated poor adherence to the study product among study subjects. Statistical analyses to explore the causal treatment effect on the prevention of HIV infection among adherent individuals are needed. METHODS: We developed an analytical strategy to evaluate whether conventional covariate adjustment removes confounding and thereby reveals a prevention effect among adherent individuals. We applied this strategy to the VOICE study, using 2 dichotomized proxy measures of product use: detection of tenofovir in plasma at least once during follow-up and detection of tenofovir in plasma at the 3-month follow-up visit. RESULTS: After adjustment for a set of baseline predictors of the risk of HIV transmission, the confounding associated with comparison of adherent individuals in the tenofovir gel arm to placebo recipients was nearly eliminated. The relative risk for a prevention effect among those ever having tenofovir detected was 0.53 (P = .038); the relative risk among those having tenofovir detected at 3 months was 0.40 (P = .045). CONCLUSIONS: A novel regression approach was proposed for causal as-treated analyses in the VOICE study. While intent-to-treat analyses yield null results, this exploratory approach presented evidence suggesting a prevention effect among gel users. CLINICAL TRIALS REGISTRATION: NCT00705679.