Brent A. Johnson

The Proneural Molecular Signature Is Enriched in Oligodendrogliomas and Predicts Improved Survival among Diffuse Gliomas

The Cancer Genome Atlas Project (TCGA) has produced an extensive collection of ‘-omic’ data on glioblastoma (GBM), resulting in several key insights on expression signatures. Despite the richness of TCGA GBM data, the absence of lower grade gliomas in this data set prevents analysis genes related to progression and the uncovering of predictive signatures. A complementary dataset exists in the form of the NCI Repository for Molecular Brain Neoplasia Data (Rembrandt), which contains molecular and clinical data for diffuse gliomas across the full spectrum of histologic class and grade. Here we present an investigation of the significance of the TCGA consortiums expression classification when applied to Rembrandt gliomas. We demonstrate that the proneural signature predicts improved clinical outcome among 176 Rembrandt gliomas that includes all histologies and grades, including GBMs (log rank test p = 1.16e-6), but also among 75 grade II and grade III samples (p = 2.65e-4). This gene expression signature was enriched in tumors with oligodendroglioma histology and also predicted improved survival in this tumor type (n = 43, p = 1.25e-4). Thus, expression signatures identified in the TCGA analysis of GBMs also have intrinsic prognostic value for lower grade oligodendrogliomas, and likely represent important differences in tumor biology with implications for treatment and therapy. Integrated DNA and RNA analysis of low-grade and high-grade proneural gliomas identified increased expression and gene amplification of several genes including GLIS3, TGFB2, TNC, AURKA, and VEGFA in proneural GBMs, with corresponding loss of DLL3 and HEY2. Pathway analysis highlights the importance of the Notch and Hedgehog pathways in the proneural subtype. This demonstrates that the expression signatures identified in the TCGA analysis of GBMs also have intrinsic prognostic value for low-grade oligodendrogliomas, and likely represent important differences in tumor biology with implications for treatment and therapy.

Penalized Estimating Functions and Variable Selection in Semiparametric Regression Models.

We propose a general strategy for variable selection in semiparametric regression models by penalizing appropriate estimating functions. Important applications include semiparametric linear regression with censored responses and semiparametric regression with missing predictors. Unlike the existing penalized maximum likelihood estimators, the proposed penalized estimating functions may not pertain to the derivatives of any objective functions and may be discrete in the regression coefficients. We establish a general asymptotic theory for penalized estimating functions and present suitable numerical algorithms to implement the proposed estimators. In addition, we develop a resampling technique to estimate the variances of the estimated regression coefficients when the asymptotic variances cannot be evaluated directly. Simulation studies demonstrate that the proposed methods perform well in variable selection and variance estimation. We illustrate our methods using data from the Paul Coverdell Stroke Registry.

Modeling Human Metabolism of Benzene Following Occupational and Environmental Exposures

We used natural spline (NS) models to investigate nonlinear relationships between levels of benzene metabolites (E,E-muconic acid, S-phenylmercapturic acid, phenol, hydroquinone, and catechol) and benzene exposure among 386 exposed and control workers in Tianjin, China. After adjusting for background levels (estimated from the 60 control subjects with the lowest benzene exposures), expected mean trends of all metabolite levels increased with benzene air concentrations from 0.03 to 88.9 ppm. Molar fractions for phenol, hydroquinone, and E,E-muconic acid changed continuously with increasing air concentrations, suggesting that competing CYP-mediated metabolic pathways favored E,E-muconic acid and hydroquinone below 20 ppm and favored phenol above 20 ppm. Mean trends of dose-specific levels (μmol/L/ppm benzene) of E,E-muconic acid, phenol, hydroquinone, and catechol all decreased with increasing benzene exposure, with an overall 9-fold reduction of total metabolites. Surprisingly, about 90% of the reductions in dose-specific levels occurred below about 3 ppm for each major metabolite. Using generalized linear models with NS–smoothing functions (GLM + NS models), we detected significant effects upon metabolite levels of gender, age, and smoking status. Metabolite levels were about 20% higher in females and decreased between 1% and 2% per year of life. In addition, levels of hydroquinone and catechol were greater in smoking subjects. Overall, our results indicate that benzene metabolism is highly nonlinear with increasing benzene exposure above 0.03 ppm, and that current human toxicokinetic models do not accurately predict benzene metabolism below 3 ppm. Our results also suggest that GLM + NS models are ideal for evaluating nonlinear relationships between environmental exposures and levels of human biomarkers. (Cancer Epidemiol Biomarkers Prev 2006;15(11):2246–52)

High rate of K65R for antiretroviral therapy-naive patients with subtype C HIV infection failing a tenofovir-containing first-line regimen.

Objective:We sought to determine the rate of the K65R mutation in patients receiving tenofovir (TDF)-based antiretroviral therapy (ART) with subtype C HIV infection. Design:Retrospective cohort study. Methods:All patients initiated on stavudine (d4T) with lamivudine (3TC) or TDF with 3TC and a nonnucleoside reverse transcriptase inhibitor at McCord Hospital in Durban, South Africa had their charts reviewed. All patients with virologic failure, defined as a viral load more than 1000 copies/ml after 5 months of a first ART regimen, had genotypic resistance testing performed prospectively using a validated in-house assay. Important resistance mutations were selected based upon published mutations in subtype B virus in the Stanford HIV Drug Resistance database. Results:A total of 585 patients were initiated on TDF-containing first-line ART from 3 August 2010 to 17 March 2011. Thirty-five (6.0%) of these patients had virologic failure and 23 of 33 (69.7%) of the virologic failure patients had the K65R mutation. The median (interquartile range) for the baseline CD4 cell count was 105 cells/&mgr;l (49–209) and viral load at virologic failure was 47 571 copies/ml (20 708–202 000). During the same period, 53 patients were initiated on d4T-containing regimens. Two (3.8%) of these patients had virologic failure and one of the virologic failure patients had the K65R mutation. Conclusion:Preliminary data show very high rates (>65%) of K65R for patients failing TDF-based first-line regimens at McCord Hospital with few additional nucleoside reverse transcriptase inhibitor mutations compared with subtype B. These rates may reflect faster in-vivo selection, longer time on a failing regimen or transmitted drug resistance.

Estimation and uncertainty analysis of impacts of future heat waves on mortality in the eastern United States.

Background: Climate change is anticipated to influence heat-related mortality in the future. However, estimates of excess mortality attributable to future heat waves are subject to large uncertainties and have not been projected under the latest greenhouse gas emission scenarios. Objectives: We estimated future heat wave mortality in the eastern United States (approximately 1,700 counties) under two Representative Concentration Pathways (RCPs) and investigated sources of uncertainty. Methods: Using dynamically downscaled hourly temperature projections for 2057–2059, we projected heat wave days that were defined using four heat wave metrics and estimated the excess mortality attributable to them. We apportioned the sources of uncertainty in excess mortality estimates using a variance-decomposition method. Results: Estimates suggest that excess mortality attributable to heat waves in the eastern United States would result in 200–7,807 deaths/year (mean 2,379 deaths/year) in 2057–2059. Average excess mortality projections under RCP4.5 and RCP8.5 scenarios were 1,403 and 3,556 deaths/year, respectively. Excess mortality would be relatively high in the southern states and eastern coastal areas (excluding Maine). The major sources of uncertainty were the relative risk estimates for mortality on heat wave versus non–heat wave days, the RCP scenarios, and the heat wave definitions. Conclusions: Mortality risks from future heat waves may be an order of magnitude higher than the mortality risks reported in 2002–2004, with thousands of heat wave–related deaths per year in the study area projected under the RCP8.5 scenario. Substantial spatial variability in county-level heat mortality estimates suggests that effective mitigation and adaptation measures should be developed based on spatially resolved data. Citation: Wu J, Zhou Y, Gao Y, Fu JS, Johnson BA, Huang C, Kim YM, Liu Y. 2014. Estimation and uncertainty analysis of impacts of future heat waves on mortality in the eastern United States. Environ Health Perspect 122:10–16; http://dx.doi.org/10.1289/ehp.1306670

Protein-Coding and MicroRNA Biomarkers of Recurrence of Prostate Cancer Following Radical Prostatectomy

An important challenge in prostate cancer research is to develop effective predictors of tumor recurrence following surgery to determine whether immediate adjuvant therapy is warranted. To identify biomarkers predictive of biochemical recurrence, we isolated the RNA from 70 formalin-fixed, paraffin-embedded radical prostatectomy specimens with known long-term outcomes to perform DASL expression profiling with a custom panel that we designed of 522 prostate cancer-relevant genes. We identified a panel of 10 protein-coding genes and two miRNA genes (RAD23B, FBP1, TNFRSF1A, CCNG2, NOTCH3, ETV1, BID, SIM2, LETMD1, ANXA1, miR-519d, and miR-647) that could be used to separate patients with and without biochemical recurrence (P < 0.001), as well as for the subset of 42 Gleason score 7 patients (P < 0.001). We performed an independent validation analysis on 40 samples and found that the biomarker panel was also significant at prediction of biochemical recurrence for all cases (P = 0.013) and for a subset of 19 Gleason score 7 cases (P = 0.010), both of which were adjusted for relevant clinical information including T-stage, prostate-specific antigen, and Gleason score. Importantly, these biomarkers could significantly predict clinical recurrence for Gleason score 7 patients. These biomarkers may increase the accuracy of prognostication following radical prostatectomy using formalin-fixed specimens.

Genetic polymorphisms and benzene metabolism in humans exposed to a wide range of air concentrations.

Using generalized linear models with natural-spline smoothing functions, we detected effects of specific xenobiotic metabolizing genes and gene–environment interactions on levels of benzene metabolites in 250 benzene-exposed and 136 control workers in Tianjin, China (for all individuals, the median exposure was 0.512 p.p.m. and the 10th and 90th percentiles were 0.002 and 6.40 p.p.m., respectively). We investigated five urinary metabolites (E,E-muconic acid, S-phenylmercapturic acid, phenol, catechol, and hydroquinone) and nine polymorphisms in seven genes coding for key enzymes in benzene metabolism in humans {cytochrome P450 2E1 [CYP2E1, rs2031920], NAD(P)H: quinone oxidoreductase [NQO1, rs1800566 and rs4986998], microsomal epoxide hydrolase [EPHX1, rs1051740 and rs2234922], glutathione-S-transferases [GSTT1, GSTM1 and GSTP1(rs947894)] and myeloperoxidase [MPO, rs2333227]}. After adjusting for covariates, including sex, age, and smoking status, NQO1*2 (rs1800566) affected all five metabolites, CYP2E1 (rs2031920) affected most metabolites but not catechol, EPHX1 (rs1051740 or rs2234922) affected catechol and S-phenylmercapturic acid, and GSTT1 and GSTM1 affected S-phenylmercapturic acid. Significant interactions were also detected between benzene exposure and all four genes and between smoking status and NQO1*2 and EPHX1 (rs1051740). No significant effects were detected for GSTP1 or MPO. Results generally support prior associations between benzene hematotoxicity and specific gene mutations, confirm earlier evidence that GSTT1 affects production of S-phenylmercapturic acid, and provide additional evidence that genetic polymorphisms in NQO1*2, CYP2E1, and EPHX1 (rs1051740 or rs2234922) affect metabolism of benzene in the human liver.

Air pollution and acute respiratory response in a panel of asthmatic children along the U.S.-Mexico border.

Background: Concerns regarding the health impact of urban air pollution on asthmatic children are pronounced along the U.S.–Mexico border because of rapid population growth near busy border highways and roads. Objectives: We conducted the first binational study of the impacts of air pollution on asthmatic children in Ciudad Juarez, Mexico, and El Paso, Texas, USA, and compared different exposure metrics to assess acute respiratory response. Methods: We recruited 58 asthmatic children from two schools in Ciudad Juarez and two schools in El Paso. A marker of airway inflammation [exhaled nitric oxide (eNO)], respiratory symptom surveys, and pollutant measurements (indoor and outdoor 48-hr size-fractionated particulate matter, 48-hr black carbon, and 96-hr nitrogen dioxide) were collected at each school for 16 weeks. We examined associations between the pollutants and respiratory response using generalized linear mixed models. Results: We observed small but consistent associations between eNO and numerous pollutant metrics, with estimated increases in eNO ranging from 1% to 3% per interquartile range increase in pollutant concentrations. Effect estimates from models using school-based concentrations were generally stronger than corresponding estimates based on concentrations from ambient air monitors. Both traffic-related and non–traffic-related particles were typically more robust predictors of eNO than was nitrogen dioxide, for which associations were highly sensitive to model specification. Associations differed significantly across the four school-based cohorts, consistent with heterogeneity in pollutant concentrations and cohort characteristics. Models examining respiratory symptoms were consistent with the null. Conclusions: The results indicate adverse effects of air pollution on the subclinical respiratory health of asthmatic children in this region and provide preliminary support for the use of air pollution monitors close to schools to track exposure and potential health risk in this population.

Activated CD4+CCR5+ T cells in the rectum predict increased SIV acquisition in SIVGag/Tat-vaccinated rhesus macaques

Significance A major obstacle to developing an effective T-cell–based AIDS vaccine is that the immunization may activate CD4+ T cells, possibly making them more susceptible to infection by HIV. We tested several vaccine candidates and their effects on mucosal CD4+ T cells in a simian model of HIV infection [i.e., Simian immunodeficiency virus (SIV) infection of rhesus macaques]. We find that the immunizations did not protect the animals against infection; however, a lower set-point viral load was observed in the vaccinated animals. Importantly, this study showed that the presence of higher levels of activated CD4+ T cells in mucosal tissues is associated with increased risk of breakthrough SIV infection in vaccinated animals. An effective T-cell–based AIDS vaccine should induce strong HIV-specific CD8+ T cells in mucosal tissues without increasing the availability of target cells for the virus. Here, we evaluated five immunization strategies that include Human adenovirus-5 (AdHu5), Chimpanzee adenovirus-6 (AdC6) or -7 (AdC7), Vaccinia virus (VV), and DNA given by electroporation (DNA/EP), all expressing Simian immunodeficiency virus group specific antigen/transactivator of transcription (SIVmac239Gag/Tat). Five groups of six rhesus macaques (RMs) each were vaccinated with DNA/EP-AdC6-AdC7, VV-AdC6-AdC7, DNA/-EP-VV-AdC6, DNA/EP-VV-AdC7, or AdHu5-AdHu5-AdHu5 and were challenged repeatedly with low-dose intrarectal SIVmac239. Upon challenge, there were no significant differences among study groups in terms of virus acquisition or viral load after infection. When taken together, the immunization regimens did not protect against SIV acquisition compared with controls but did result in an ∼1.6-log decline in set-point viremia. Although all immunized RMs had detectable SIV-specific CD8+ T cells in blood and rectal mucosa, we found no correlation between the number or function of these SIV-specific CD8+ T cells and protection against SIV acquisition. Interestingly, RMs experiencing breakthrough infection showed significantly higher prechallenge levels of CD4+C-C chemokine receptor type 5 (CCR5)+HLA-DR+ T cells in the rectal biopsies (RB) than animals that remained uninfected. In addition, among the infected RMs, the percentage of CD4+CCR5+Ki-67+ T cells in RBs prechallenge correlated with higher early viremia. Overall, these data suggest that the levels of activated CD4+CCR5+ target T cells in the rectal mucosa may predict the risk of SIV acquisition in RMs vaccinated with vectors that express SIVGag/Tat.

The time trend temperature-mortality as a factor of uncertainty analysis of impacts of future heat waves: Wu et al. respond.

We thank Linares et al. for their interest in our article and for broadening the discussion on the uncertainties in predicting the health impact of future heat waves. Linares et al. pointed out that the possible evolution over time can take place both in minimum mortality temperatures related to heat waves and in the modifications of these possible impacts due to socioeconomic improvements. Although such considerations were beyond the scope of our published analysis (Wu et al. 2014), we agree that socioeconomic and demographic factors can have profound impacts on the estimated excess mortality in a changing climate. A heat wave is defined as a period of consecutive days with temperatures exceeding a certain threshold based on physiologic effects (Robinson 2001). The threshold temperature is usually calculated based on local historical data, which can vary in both time and space. Linares et al. suggested that heat wave definition temperatures might be reduced to a consequence of population aging in time. Given these changes in the threshold temperature over time, the heat wave definition would indeed add an additional layer of uncertainty to the predicted health impact of future heat waves on top of what we have characterized in the paper. Such uncertainty, however, is difficult to quantify without detailed data on the structure of future populations, especially age. So far, the U.S. Census Bureau (2012) has issued only national-level, age-specific population projections. The health impacts of heat waves can be modified by many factors, such as race, age, sex, socioeconomic status, and geographic location (Hajat and Kosatky 2010). The changing impacts of heat waves on cardiovascular/circulatory and respiratory mortality (Ha and Kim, 2013; Miron et al. 2008) seem to be related to the improvements in health care services and living conditions over time. These trends may be generalizable in space if we are willing to assume that the U.S. health care system has improved its service to cardiovascular patients over the years in a fashion similar to that of Spain, Italy, or other developed countries. However, it may not be justifiable to extrapolate them in time because the impact of these improvements is likely to taper off unless significant technological advancement takes place in the future. In addition, early warning systems and adaptation strategies can strongly influence the impact of heat waves on a society (Lowe et al. 2011). However, the relative risk of heat waves must be estimated using existing health data records, making it very difficult to take any adaptation measures into consideration because we lack such examples in the past. In our study, we set future baseline mortality rate and relative health risk of heat waves as constant because robust estimates of these parameters for the 2050s are unavailable. Further research is needed to address these issues in order to provide a more comprehensive and realistic evaluation of the impact of future heat waves.