Publications

RATIONALE

β2-Agonists are the most common form of treatment of asthma, but there is significant variability in response to these medications. A significant proportion of this responsiveness may be heritable.

OBJECTIVES

To investigate whether a genome-wide association study (GWAS) could identify novel pharmacogenetic loci in asthma.

METHODS

We performed a GWAS of acute bronchodilator response (BDR) to inhaled β2-agonists. A total of 444,088 single-nucleotide polymorphisms (SNPs) were examined in 724 individuals from the SNP Health Association Resource (SHARe) Asthma Resource Project (SHARP). The top 50 SNPs were carried forward to replication in a population of 444 individuals.

MEASUREMENTS AND MAIN RESULTS

The combined P value for four SNPs reached statistical genome-wide significance aftercorrecting for multiple comparisons. Combined P values for rs350729, rs1840321, rs1384918, and rs1319797 were 2.21 × 10(-10), 5.75 × 10(-8), 9.3 × 10(-8), and 3.95 × 10(-8), respectively. The significant variants all map to a novel genetic region on chromosome 2 near the ASB3 gene, a region associated with smooth muscle proliferation. As compared with the wild type, the presence of the minor alleles reduced the degree of BDR by 20% in the original population and by a similar percentage in the confirmatory population.

CONCLUSIONS

These GWAS findings for BDR in subjects with asthma suggest that a gene associated with smooth muscle proliferation may influence a proportion of the smooth muscle relaxation that occurs in asthma.

Human papillomavirus (HPV) infection is associated with essentially all cervical cancers, 80-90 % of anal cancers, and a high proportion of oropharyngeal, vaginal, penile, and vulvar cancers. Malignancy is preceded by the development of precancerous lesions termed high-grade squamous intraepithelial lesions (HSIL). Men and women with human immunodeficiency virus (HIV) infection are at high risk of HPV-related malignancies. The incidence of anal cancer in particular has markedly risen during the antiretroviral era due to the increased longevity of patients with HIV and the absence of anal malignancy screening programs. HIV infection may facilitate initial HPV infection by disrupting epithelial cell tight junctions. Once infection is established, HIV may promote HSIL development via the up-regulation of HPV oncogene expression and impairment of the immune response needed to clear the lesion. HIV-infected women should be screened for cervical HSIL and cancer, and HIV-infected men and women should be considered for anal screening programs.

BACKGROUND

Cigarette smoking presents a salient risk for HIV-positive populations. This study is among the first to examine smoking prevalence, nicotine dependence, and associated factors in a large sample of HIV-positive patients receiving antiretroviral therapy (ART) in Vietnam.

METHODS

A cross-sectional study of 1133 HIV-positive people was conducted from January to September 2013 at 8 ART clinics in Hanoi (the capital) and Nam Dinh (a rural area). Smoking history and nicotine dependence (Fagerstrom Test of Nicotine Dependence-FTND) were assessed by participant self-report. Logistic regression and Tobit linear regression were performed to identify factors significantly associated with smoking outcomes.

RESULTS

Prevalence of current, former, and never smokers in the sample was 36.1%, 9.5%, and 54.4%, respectively. The current smoking proportion was higher in males (59.7%) than females (2.6%). The mean FTND score was 3.6 (SD = 2.1). Males were more likely to currently smoke than females (OR = 23.4, 95% CI = 11.6-47.3). Individuals with problem drinking (OR = 1.8, 95% CI = 1.1-2.9) and ever drug use (OR = 3.7, 95%CI = 2.5-5.7) were more likely to be current smokers. Older age and currently feeling pain were associated with lower nicotine dependence. Conversely, receiving care in Nam Dinh, greater alcohol consumption, ever drug use, and a longer smoking duration were associated with greater nicotine dependence.

CONCLUSIONS

Given the high prevalence of smoking among HIV-positive patients, smoking screening and cessation support should be offered at ART clinics in Vietnam. Risk factors (i.e., substance use) linked with smoking behavior should be considered in prevention programs.

BACKGROUND

Chronic pain is prevalent, costly, and clinically vexatious. Clinicians typically use a trial-and-error approach to treatment selection. Repeated crossover trials in a single patient (n-of-1 trials) may provide greater therapeutic precision. N-of-1 trials are the most direct way to estimate individual treatment effects and are useful in comparing the effectiveness and toxicity of different analgesic regimens. The goal of the PREEMPT study is to test the 'Trialist' mobile health smartphone app, which has been developed to make n-of-1 trials easier to accomplish, and to provide patients and clinicians with tools for individualizing treatments for chronic pain.

METHODS/DESIGN

A randomized controlled trial is being conducted to test the feasibility and effectiveness of the Trialist app. A total of 244 participants will be randomized to either the Trialist app intervention group (122 patients) or a usual care control group (122 patients). Patients assigned to the Trialist app will work with their clinicians to set up an n-of-1 trial comparing two pain regimens, selected from a menu of flexible options. The Trialist app provides treatment reminders and collects data entered daily by the patient on pain levels and treatment side effects. Upon completion of the n-of-1 trial, patients review results with their clinicians and develop a long-term treatment plan. The primary study outcome (comparing Trialist to usual care patients) is pain-related interference with daily functioning at 26 weeks.

DISCUSSION

Trialist will allow patients and clinicians to conduct personalized n-of-1 trials. In prior studies, n-of-1 trials have been shown to encourage greater patient involvement with care, which has in turn been associated with better health outcomes. mHealth technology implemented using smartphones may offer an efficient means of facilitating n-of-1 trials so that more patients can benefit from this approach.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT02116621 , first registered 15 April 2014.

Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM2.5 during wildfires. We estimated PM2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11 statistical algorithms and 29 predictor variables. The variables included CTM output, three measures of satellite aerosol optical depth, distance to the nearest fires, meteorological data, and land use, traffic, spatial location, and temporal characteristics. The generalized boosting model (GBM) with 29 predictor variables had the lowest CV root mean squared error and a CV-R2 of 0.803. The most important predictor variable was the Geostationary Operational Environmental Satellite Aerosol/Smoke Product (GASP) Aerosol Optical Depth (AOD), followed by the CTM output and distance to the nearest fire cluster. Parsimonious models with various combinations of fewer variables also predicted PM2.5 well. Using machine learning algorithms to combine spatiotemporal data from satellites and CTMs can reliably predict PM2.5 concentrations during a major wildfire event.