Alina Deshpande

TNF-α Promoter Polymorphisms and Susceptibility to Human Papillomavirus 16–Associated Cervical Cancer

BACKGROUND Polymorphisms in the TNF-alpha promoter region have recently been shown to be associated with susceptibility to cervical cancer. Some polymorphisms have been reported to influence transcription for this cytokine. Altered local levels in the cervix may influence an individuals immune response, thereby affecting persistence of human papillomavirus (HPV) 16 infection, a primary etiological factor for cervical cancer. METHODS AND RESULTS The association of 11 TNF-alpha single-nucleotide polymorphisms (SNPs) with susceptibility to HPV16-associated cervical cancer was investigated. Sequencing of the TNF-alpha promoter region confirmed 10 SNPs, and 1 previously unreported SNP (161 bp upstream of the transcriptional start site) was discovered. Microsphere-array flow cytometry-based genotyping was performed on 787 samples from Hispanic and non-Hispanic white women (241 from randomly selected control subjects, 205 from HPV16-positive control subjects, and 341 from HPV16-positive subjects with cervical cancer). The genotype distribution of 3 SNPs (-572, -857, and -863) was significantly different between case subjects and control subjects. Analysis of haplotypes, which were computationally inferred from genotype data, also revealed statistically significant differences in haplotype distribution between case subjects and control subjects. CONCLUSIONS We report new associations between several TNF-alpha SNPs and susceptibility to cervical cancer that support the involvement of the TNF- alpha promoter region in development of cervical cancer.

Global Disease Monitoring and Forecasting with Wikipedia

Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: access logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.

Forecasting the 2013-2014 influenza season using Wikipedia.

Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are applied to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.

A rapid multiplex assay for nucleic acid-based diagnostics

We have developed a rapid (under 4 hours), multiplex, nucleic acid assay, adapted to a microsphere array detection platform. We call this assay multiplex oligonucleotide ligation-PCR (MOL-PCR). Unlike other ligation-based assays that require multiple steps, our protocol consists of a single tube reaction, followed by hybridization to a Luminex microsphere array for detection. We demonstrate the ability of this assay to simultaneously detect diverse nucleic acid signatures (e.g., unique sequences, single nucleotide polymorphisms) in a single multiplex reaction. Detection probes consist of modular components that enable target detection, probe amplification, and subsequent capture onto microsphere arrays. To demonstrate the utility of our assay, we applied it to the detection of three biothreat agents, B. anthracis, Y. pestis, and F. tularensis. Combined with the ease and robustness of this assay, the results presented here show a strong potential of our assay for use in diagnostics and surveillance.

Persistence of Bacillus thuringiensis subsp. kurstaki in Urban Environments following Spraying

ABSTRACT Bacillus thuringiensis subsp. kurstaki is applied extensively in North America to control the gypsy moth, Lymantria dispar. Since B. thuringiensis subsp. kurstaki shares many physical and biological properties with Bacillus anthracis, it is a reasonable surrogate for biodefense studies. A key question in biodefense is how long a biothreat agent will persist in the environment. There is some information in the literature on the persistence of Bacillus anthracis in laboratories and historical testing areas and for Bacillus thuringiensis in agricultural settings, but there is no information on the persistence of Bacillus spp. in the type of environment that would be encountered in a city or on a military installation. Since it is not feasible to release B. anthracis in a developed area, the controlled release of B. thuringiensis subsp. kurstaki for pest control was used to gain insight into the potential persistence of Bacillus spp. in outdoor urban environments. Persistence was evaluated in two locations: Fairfax County, VA, and Seattle, WA. Environmental samples were collected from multiple matrices and evaluated for the presence of viable B. thuringiensis subsp. kurstaki at times ranging from less than 1 day to 4 years after spraying. Real-time PCR and culture were used for analysis. B. thuringiensis subsp. kurstaki was found to persist in urban environments for at least 4 years. It was most frequently detected in soils and less frequently detected in wipes, grass, foliage, and water. The collective results indicate that certain species of Bacillus may persist for years following their dispersal in urban environments.

Multiplexed nucleic acid-based assays for molecular diagnostics of human disease

In recent years, there has been an explosion of molecular tests developed to diagnose human disease, including tests to detect disease-causing pathogens, human genetic or protein markers indicative of disease (e.g., cancer and autoimmune disease), and genetic markers for predisposition to disease. Significant features of nucleic acid-based tests include high sensitivity and specificity, and the ability to multiplex or interrogate more than one marker simultaneously in each sample. Multiplex assays provide cost and information content advantages, and therefore allow for higher confidence results than singleplex assays. This article reviews the current state of the art in multiplexed nucleic acid-based techniques used for diagnosis of human disease and provides a glimpse of promising techniques for the future.

Variation in HLA Class I Antigen-Processing Genes and Susceptibility to Human Papillomavirus Type 16—Associated Cervical Cancer

BACKGROUND Persistent infection with human papillomavirus type 16 (HPV16) is a primary etiological factor for the development of cervical cancer. Genes involved in antigen processing influence both the repertoire of antigens presented by HPV16-infected cells and the nature of HPV16-specific immune responses. Genetic variation in these genes may affect protein structure and function and, consequently, the ability of an individual to clear HPV infection. METHODS Thirty-five single-nucleotide polymorphisms (SNPs) in 5 genes (LMP2, TAP1, LMP7, TAP2, and Tapasin) were investigated for association with susceptibility to HPV16-associated cervical cancer. Sequencing of these genes resulted in the discovery of 15 previously unreported SNPs. Microsphere-array flow cytometry-based genotyping was conducted on 787 samples from Hispanic and non-Hispanic white women (241 randomly selected control subjects, 205 HPV16-positive control subjects, and 341 HPV16-positive case subjects with cervical cancer). RESULTS For 9 SNPs, 8 of which had not previously been reported in the context of cervical cancer, there were statistically significant differences between the genotype distribution in case subjects and that in control subjects. Haplotype analysis of 3 haplotype blocks revealed 3 haplotypes with significant differences in frequency in case-control comparisons. Both HPV16-specific and non-type-specific differences in genotype distribution were seen. CONCLUSIONS Genes involved in antigen processing for HLA class I presentation may contribute to susceptibility to cervical cancer.

Quantitative analysis of the effect of cell type and cellular differentiation on protective antigen binding to human target cells.

We quantitatively measured protective antigen (PA) binding to human cells targeted by anthrax lethal toxin (LT). Affinities were less than 50 nM for all cells, but differentiated cells (macrophages and neutrophils) had significantly increased PA binding and endothelial cells demonstrated the most binding. Combined with the function of such cells, this suggests that PA receptors interact with the extracellular matrix and that differentiation increases the number of PA‐specific receptors, which supports previously observed differentiation‐induced LT susceptibility. Our results quantifiably confirm that the generality of PA binding will complicate its use as a tumor targeting agent.

Advancing a Framework to Enable Characterization and Evaluation of Data Streams Useful for Biosurveillance

In recent years, biosurveillance has become the buzzword under which a diverse set of ideas and activities regarding detecting and mitigating biological threats are incorporated depending on context and perspective. Increasingly, biosurveillance practice has become global and interdisciplinary, requiring information and resources across public health, One Health, and biothreat domains. Even within the scope of infectious disease surveillance, multiple systems, data sources, and tools are used with varying and often unknown effectiveness. Evaluating the impact and utility of state-of-the-art biosurveillance is, in part, confounded by the complexity of the systems and the information derived from them. We present a novel approach conceptualizing biosurveillance from the perspective of the fundamental data streams that have been or could be used for biosurveillance and to systematically structure a framework that can be universally applicable for use in evaluating and understanding a wide range of biosurveillance activities. Moreover, the Biosurveillance Data Stream Framework and associated definitions are proposed as a starting point to facilitate the development of a standardized lexicon for biosurveillance and characterization of currently used and newly emerging data streams. Criteria for building the data stream framework were developed from an examination of the literature, analysis of information on operational infectious disease biosurveillance systems, and consultation with experts in the area of biosurveillance. To demonstrate utility, the framework and definitions were used as the basis for a schema of a relational database for biosurveillance resources and in the development and use of a decision support tool for data stream evaluation.

Development of rationally designed nucleic acid signatures for microbial pathogens.

The detection and identification of microbial pathogens are critical challenges in clinical medicine and public health surveillance. Advances in genome analysis technology are providing an unprecedented amount of information about bacterial and viral organisms, and hold great potential for pathogen detection and identification. In this paper, a rational approach to the development and application of nucleic acid signatures is described based on phylogenetically informative sequence features, especially single nucleotide polymorphisms. The computational tools that are available to enable the development of the next generation of microbial molecular signatures for clinical diagnostics and infectious disease surveillance are reviewed and the impact on public health and national security will be discussed.