A longitudinal modelling study estimates acute symptoms of community acquired pneumonia recover to baseline by 10†days.

Our aims were to address three fundamental questions relating to the symptoms of community-acquired pneumonia (CAP): Do patients completely recover from pneumonia symptoms? How long does this recovery take? Which factors influence symptomatic recovery?We prospectively recruited patients at two hospitals in Liverpool, UK, into a longitudinal, observational cohort study and modelled symptom recovery from CAP. We excluded patients with cancer, immunosuppression or advanced dementia, and those who were intubated or palliated from admission. We derived a statistical model to describe symptom patterns.We recruited 169 (52% male) adults. Multivariable analysis demonstrated that the time taken to recover to baseline was determined by the initial severity of symptoms. Severity of symptoms was associated with comorbidity and was inversely related to age. The pattern of symptom recovery was exponential and most patients' symptoms returned to baseline by 10 days.These results will inform the advice given to patients regarding the resolution of their symptoms. The recovery model described here will facilitate the use of symptom recovery as an outcome measure in future clinical trials.

Gender and Racial/Ethnic Disparities: Cumulative Screening of Health Risk Indicators in 20-50 Year Olds in the United States.

This study explored potential gender and racial/ethnic disparities in overall health risk related to 24 health risk indicators selected across six domains: socioeconomic, health status and health care, lifestyle, nutritional, clinical, and environmental. Using the 2003-2006 National Health and Nutrition Examination Surveys (NHANES), it evaluated cross-sectional data for 5,024 adults in the United States. Logistic regression models were developed to estimate prevalence odds ratios (PORs) adjusted for smoking, health insurance status, and age. Analyses evaluated disparities associated with 24 indicator variables of health risk, comparing females to males and four racial/ethnic groups to non-Hispanic Whites. Non-Hispanic Blacks and Mexican Americans were at greater risk for at least 50% of the 24 health risk indicators, including measures of socioeconomic status, health risk behaviors, poor/fair self-reported health status, multiple nutritional and clinical indicators, and blood lead levels. This demonstrates that cumulative health risk is unevenly distributed across racial/ethnic groups. A similarly high percentage (46%) of the risk factors was observed in females. Females as compared to males were more likely to have lower income, lower blood calcium, poor/fair self-reported health, more poor mental health days/month, higher medication usage and hospitalizations, and higher serum levels of some clinical indicators and blood cadmium. This analysis of cumulative health risk is responsive to calls for broader-based, more integrated assessment of health disparities that can help inform community assessments and public health policy.

Factors associated with self-reported health: implications for screening level community-based health and environmental studies.

BACKGROUND: Advocates for environmental justice, local, state, and national public health officials, exposure scientists, need broad-based health indices to identify vulnerable communities. Longitudinal studies show that perception of current health status predicts subsequent mortality, suggesting that self-reported health (SRH) may be useful in screening-level community assessments. This paper evaluates whether SRH is an appropriate surrogate indicator of health status by evaluating relationships between SRH and sociodemographic, lifestyle, and health care factors as well as serological indicators of nutrition, health risk, and environmental exposures. METHODS: Data were combined from the 2003-2006 National Health and Nutrition Examination Surveys for 1372 nonsmoking 20-50 year olds. Ordinal and binary logistic regression was used to estimate odds ratios and 95 % confidence intervals of reporting poorer health based on measures of nutrition, health condition, environmental contaminants, and sociodemographic, health care, and lifestyle factors. RESULTS: Poorer SRH was associated with several serological measures of nutrition, health condition, and biomarkers of toluene, cadmium, lead, and mercury exposure. Race/ethnicity, income, education, access to health care, food security, exercise, poor mental and physical health, prescription drug use, and multiple health outcome measures (e.g., diabetes, thyroid problems, asthma) were also associated with poorer SRH. CONCLUSION: Based on the many significant associations between SRH and serological assays of health risk, sociodemographic measures, health care access and utilization, and lifestyle factors, SRH appears to be a useful health indicator with potential relevance for screening level community-based health and environmental studies.

Data-driven asthma endotypes defined from blood biomarker and gene expression data.

The diagnosis and treatment of childhood asthma is complicated by its mechanistically distinct subtypes (endotypes) driven by genetic susceptibility and modulating environmental factors. Clinical biomarkers and blood gene expression were collected from a stratified, cross-sectional study of asthmatic and non-asthmatic children from Detroit, MI. This study describes four distinct asthma endotypes identified via a purely data-driven method. Our method was specifically designed to integrate blood gene expression and clinical biomarkers in a way that provides new mechanistic insights regarding the different asthma endotypes. For example, we describe metabolic syndrome-induced systemic inflammation as an associated factor in three of the four asthma endotypes. Context provided by the clinical biomarker data was essential in interpreting gene expression patterns and identifying putative endotypes, which emphasizes the importance of integrated approaches when studying complex disease etiologies. These synthesized patterns of gene expression and clinical markers from our research may lead to development of novel serum-based biomarker panels.

Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes.

BACKGROUND: Complex diseases are often difficult to diagnose, treat and study due to the multi-factorial nature of the underlying etiology. Large data sets are now widely available that can be used to define novel, mechanistically distinct disease subtypes (endotypes) in a completely data-driven manner. However, significant challenges exist with regard to how to segregate individuals into suitable subtypes of the disease and understand the distinct biological mechanisms of each when the goal is to maximize the discovery potential of these data sets. RESULTS: A multi-step decision tree-based method is described for defining endotypes based on gene expression, clinical covariates, and disease indicators using childhood asthma as a case study. We attempted to use alternative approaches such as the Student's t-test, single data domain clustering and the Modk-prototypes algorithm, which incorporates multiple data domains into a single analysis and none performed as well as the novel multi-step decision tree method. This new method gave the best segregation of asthmatics and non-asthmatics, and it provides easy access to all genes and clinical covariates that distinguish the groups. CONCLUSIONS: The multi-step decision tree method described here will lead to better understanding of complex disease in general by allowing purely data-driven disease endotypes to facilitate the discovery of new mechanisms underlying these diseases. This application should be considered a complement to ongoing efforts to better define and diagnose known endotypes. When coupled with existing methods developed to determine the genetics of gene expression, these methods provide a mechanism for linking genetics and exposomics data and thereby accounting for both major determinants of disease.

Allergens in household dust and serological indicators of atopy and sensitization in Detroit children with history-based evidence of asthma.

BACKGROUND: Home exposure to allergens is an important factor in the development of sensitization and subsequent exacerbations of allergic asthma. We investigated linkages among allergen exposure, immunological measurements, and asthma by examining (1) reservoir dust allergen levels in homes, (2) associations between presence of allergens in homes and sensitization status of resident children, and (3) associations between asthma status and total IgE, atopy (by Phadiatop), and positive allergen-specific tests. METHODS: The study protocol was approved by Institutional Review Boards (IRBs) of the University of North Carolina Chapel Hill; Westat, Inc.; and the US Environmental Protection Agency Human Research Protocol Office. Data were collected from questionnaires, serum analyses, and household vacuum dust. Children (n = 205) were predominately African American (AA) (85.4%) and 51.6% were asthmatic. Sera from 185 children and home dust samples (n = 141) were analyzed for total and specific IgE antibodies to allergens from cat and dog dander, cockroach, dust mites, mice, rats, and molds. RESULTS: Sixty percent of the homes had detectable levels of three or more dust allergens. The proportions of children with positive allergen-specific IgE tests were dust mite (32%), dog (28%), cat (23%), cockroach (18%), mouse (5%), rat (4%), and molds (24-36%). Children testing positive to a single allergen also had positive responses to other allergens. Those children with positive serum tests for cat, dog, and dust mite lived in homes with detectable levels of cat (51%), dog (90%), and dust mite (Der f 1) (92%) allergens. Correlations between children's specific IgE levels and dust levels were linearly related for dog (p < .04), but not for cat (p = .12) or dust mite (Der f 1) (p = .21). Odds ratios (95% CI) for the associations between asthma and serum-specific IgE were over 1.0 for cat, dog, dust mite (Der f 1), cockroach, and four types of molds. House dust allergen exposure levels, however, exhibited no differences between asthmatic and non-asthmatic homes. CONCLUSIONS: Both the co-occurrence of multiple allergens in dust and the high frequency of multiple allergen sensitizations indicate that a broad-based intervention aimed at reducing multiple allergens (pets, pests, and molds) would be more successful than any approach that aimed at reducing one type of allergen.

Mechanistic indicators of childhood asthma (MICA) study: piloting an integrative design for evaluating environmental health.

BACKGROUND: Asthma is a common complex disease responsible for considerable morbidity and mortality, particularly in urban minority populations. The Mechanistic Indicators of Childhood Asthma study was designed to pilot an integrative approach in children's health research. The study incorporates exposure metrics, internal dose measures, and clinical indicators to decipher the biological complexity inherent in diseases such as asthma and cardiovascular disease with etiology related to gene-environment interactions. METHODS/DESIGN: 205 non-asthmatic and asthmatic children, (9-12 years of age) from Detroit, Michigan were recruited. The study includes environmental measures (indoor and outdoor air, vacuum dust), biomarkers of exposure (cotinine, metals, total and allergen specific Immunoglobulin E, polycyclic aromatic hydrocarbons, volatile organic carbon metabolites) and clinical indicators of health outcome (immunological, cardiovascular and respiratory). In addition, blood gene expression and candidate SNP analyses were conducted. DISCUSSION: Based on an integrative design, the MICA study provides an opportunity to evaluate complex relationships between environmental factors, physiological biomarkers, genetic susceptibility and health outcomes. PROJECT APPROVAL: IRB Number 05-EPA-2637: The human subjects' research protocol was reviewed by the Institutional Review Board (IRB) of the University of North Carolina; the IRB of Westat, Inc., the IRB of the Henry Ford Health System; and EPA's Human Subjects' Research Review Official.

Evaluation of genetic susceptibility to childhood allergy and asthma in an African American urban population.

BACKGROUND: Asthma and allergy represent complex phenotypes, which disproportionately burden ethnic minorities in the United States. Strong evidence for genomic factors predisposing subjects to asthma/allergy is available. However, methods to utilize this information to identify high risk groups are variable and replication of genetic associations in African Americans is warranted. METHODS: We evaluated 41 single nucleotide polymorphisms (SNP) and a deletion corresponding to 11 genes demonstrating association with asthma in the literature, for association with asthma, atopy, testing positive for food allergens, eosinophilia, and total serum IgE among 141 African American children living in Detroit, Michigan. Independent SNP and haplotype associations were investigated for association with each trait, and subsequently assessed in concert using a genetic risk score (GRS). RESULTS: Statistically significant associations with asthma were observed for SNPs in GSTM1, MS4A2, and GSTP1 genes, after correction for multiple testing. Chromosome 11 haplotype CTACGAGGCC (corresponding to MS4A2 rs574700, rs1441586, rs556917, rs502581, rs502419 and GSTP1 rs6591256, rs17593068, rs1695, rs1871042, rs947895) was associated with a nearly five-fold increase in the odds of asthma (Odds Ratio (OR) = 4.8, p = 0.007). The GRS was significantly associated with a higher odds of asthma (OR = 1.61, 95% Confidence Interval = 1.21, 2.13; p = 0.001). CONCLUSIONS: Variation in genes associated with asthma in predominantly non-African ethnic groups contributed to increased odds of asthma in this African American study population. Evaluating all significant variants in concert helped to identify the highest risk subset of this group.

Advancing exposure characterization for chemical evaluation and risk assessment.

A new generation of scientific tools has emerged to rapidly measure signals from cells, tissues, and organisms following exposure to chemicals. High-visibility efforts to apply these tools for efficient toxicity testing raise important research questions in exposure science. As vast quantities of data from high-throughput screening (HTS) in vitro toxicity assays become available, this new toxicity information must be translated to assess potential risks to human health from environmental exposures. Exposure information is required to link information on potential toxicity of environmental contaminants to real-world health outcomes. In the immediate term, tools are required to characterize and classify thousands of environmental chemicals in a rapid and efficient manner to prioritize testing and assess potential for risk to human health. Rapid risk assessment requires prioritization based on both hazard and exposure dimensions of the problem. To address these immediate needs within the context of longer term objectives for chemical evaluation and risk management, a translation framework is presented for incorporating toxicity and exposure information to inform public health decisions at both the individual and population levels. Examples of required exposure science contributions are presented with a focus on early advances in tools for modeling important links across the source-to-outcome paradigm. ExpoCast, a new U.S. Environmental Protection Agency (EPA) program aimed at developing novel approaches and metrics to screen and evaluate chemicals based on the potential for biologically relevant human exposures is introduced. The goal of ExpoCast is to advance characterization of exposure required to translate findings in computational toxicology to information that can be directly used to support exposure and risk assessment for decision making and improved public health.

Increased plasma reactive oxidant levels and their relationship to blood cells, total IgE, and allergen-specific IgE levels in asthmatic children.

Asthma is a disorder characterized by inflammation of the airways. Oxidative stress may play a role in the pathophysiology of several diseases including asthma. Characterizing biomarkers of oxidative stress in the context of other systemic measures of immune function or inflammation could provide insight regarding underlying mechanisms inducing asthma. We evaluated whether oxidative stress in the form of plasma reactive oxidants differs between asthmatic and non-asthmatic children and elucidate relationships between plasma reactive oxidants and other asthma-related immunological markers. Plasma reactive oxidants, white blood cell counts, total serum immunoglobulin E(IgE), and a multi-allergen-specific IgE screen were measured in 74 asthmatic and 74 non-asthmatic children(9 to 13 years of age) from the Detroit, Michigan area. Plasma reactive oxidants were measured using a lucigenin-based chemiluminescence assay. Plasma reactive oxidants, eosinophils, and neutrophils(absolute counts and percent of total white blood cell counts), total IgE, and allergen-specific IgE levels were elevated in asthmatics after adjusting for age, gender, and ethnicity. IgE(total or allergen-specific), eosinophils and neutrophils were not significantly associated with plasma reactive oxidant levels. The association between plasma reactive oxidants and asthma status was similar when eosinophils, neutrophils, total IgE, or allergen-specific IgE were included as possible confounders in multivariate logistic regression models. In conclusion, plasma reactive oxidants are elevated in asthmatics and appear to be an independent predictor of asthma status. Measurement of plasma reactive oxidants may be a useful adjunct diagnostic tool and potential mechanistic indicator relevant to the study of asthma and asthma exacerbation.

Exposure science and the U.S. EPA National Center for Computational Toxicology.

The emerging field of computational toxicology applies mathematical and computer models and molecular biological and chemical approaches to explore both qualitative and quantitative relationships between sources of environmental pollutant exposure and adverse health outcomes. The integration of modern computing with molecular biology and chemistry will allow scientists to better prioritize data, inform decision makers on chemical risk assessments and understand a chemical's progression from the environment to the target tissue within an organism and ultimately to the key steps that trigger an adverse health effect. In this paper, several of the major research activities being sponsored by Environmental Protection Agency's National Center for Computational Toxicology are highlighted. Potential links between research in computational toxicology and human exposure science are identified. As with the traditional approaches for toxicity testing and hazard assessment, exposure science is required to inform design and interpretation of high-throughput assays. In addition, common themes inherent throughout National Center for Computational Toxicology research activities are highlighted for emphasis as exposure science advances into the 21st century.

Increased plasma reactive oxidant levels and their relationship to blood cells, total IgE, and allergen-specific IgE levels in asthmatic children.

Asthma is a disorder characterized by inflammation of the airways. Oxidative stress may play a role in the pathophysiology of several diseases including asthma. Characterizing biomarkers of oxidative stress in the context of other systemic measures of immune function or inflammation could provide insight regarding underlying mechanisms inducing asthma. We evaluated whether oxidative stress in the form of plasma reactive oxidants differs between asthmatic and non-asthmatic children and elucidate relationships between plasma reactive oxidants and other asthma-related immunological markers. Plasma reactive oxidants, white blood cell counts, total serum immunoglobulin E (IgE), and a multi-allergen-specific IgE screen were measured in 74 asthmatic and 74 non-asthmatic children (9 to 13 years of age) from the Detroit, Michigan area. Plasma reactive oxidants were measured using a lucigenin-based chemiluminescence assay. Plasma reactive oxidants, eosinophils, and neutrophils (absolute counts and percent of total white blood cell counts), total IgE, and allergen-specific IgE levels were elevated in asthmatics after adjusting for age, gender, and ethnicity. IgE (total or allergen-specific), eosinophils and neutrophils were not significantly associated with plasma reactive oxidant levels. The association between plasma reactive oxidants and asthma status was similar when eosinophils, neutrophils, total IgE, or allergen-specific IgE were included as possible confounders in multivariate logistic regression models. In conclusion, plasma reactive oxidants are elevated in asthmatics and appear to be an independent predictor of asthma status. Measurement of plasma reactive oxidants may be a useful adjunct diagnostic tool and potential mechanistic indicator relevant to the study of asthma and asthma exacerbation.

Comparative microarray analysis and pulmonary changes in Brown Norway rats exposed to ovalbumin and concentrated air particulates.

The interaction between air particulates and genetic susceptibility has been implicated in the pathogenesis of asthma. The overall objective of this study was to determine the effects of inhalation exposure to environmentally relevant concentrated air particulates (CAPs) on the lungs of ovalbumin (ova) sensitized and challenged Brown Norway rats. Changes in gene expression were compared with lung tissue histopathology, morphometry, and biochemical and cellular parameters in bronchoalveolar lavage fluid (BALF). Ova challenge was responsible for the preponderance of gene expression changes, related largely to inflammation. CAPs exposure alone resulted in no significant gene expression changes, but CAPs and ova-exposed rodents exhibited an enhanced effect relative to ova alone with differentially expressed genes primarily related to inflammation and airway remodeling. Gene expression data was consistent with the biochemical and cellular analyses of the BALF, the pulmonary pathology, and morphometric changes when comparing the CAPs-ova group to the air-saline or CAPs-saline group. However, the gene expression data were more sensitive than the BALF cell type and number for assessing the effects of CAPs and ova versus the ova challenge alone. In addition, the gene expression results provided some additional insight into the TGF-beta-mediated molecular processes underlying these changes. The broad-based histopathology and functional genomic analyses demonstrate that exposure to CAPs exacerbates rodents with allergic inflammation induced by an allergen and suggests that asthmatics may be at increased risk for air pollution effects.

A participant-based approach to indoor/outdoor air monitoring in community health studies.

Community health studies of traffic-related air pollution have been hampered by the cost and participant burden associated with collecting household-level exposure data. The current study utilized a participant-based approach to collect indoor and outdoor air monitoring data from 92 asthmatic and nonasthmatic children (9-13 years old) enrolled in two concurrent health studies in Detroit, Michigan (Mechanistic Indicators of Childhood Asthma and Detroit Children's Health Study) conducted by the US Environmental Protection Agency (EPA). Passive samplers were shipped to participating households and deployed by parents of study participants to collect indoor and outdoor measurements of nitrogen dioxide (NO(2)), volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs) including naphthalene. Half of the households deployed VOC and NO(2) samplers for 7 days; the other half deployed PAH and NO(2) samplers for 2 days and additional PAH samplers for 1 day. Approximately 88% of the households that received air sampling kits completed the air monitoring. Compliance was significantly higher among participants asked to deploy all samplers for 7 days (85%) compared with participants asked to deploy some samplers for 2 days and others for 1 day (56%). The 7-day homes were also more likely to provide usable data (96%) compared with the 1- and 2-day homes (73%). Compliance and providing usable data did not vary between parents of asthmatic versus nonasthmatic study participants and were not reduced among households deploying duplicate samplers. These results suggest that participant-based sampling may be a feasible and cost-effective alternative to traditional exposure assessment approaches that can be applied in future epidemiological and community-based health studies.

Higher Environmental Relative Moldiness Index (ERMIsm) values measured in Detroit homes of severely asthmatic children.

Sieved vacuum bag dust from the homes of 143 children in Detroit was analyzed by mold specific quantitative PCR (MSQPCR) and the Environmental Relative Moldiness Index (ERMIsm) was calculated for each home. Children living in these homes were grouped as non-asthmatic (n=83), moderately asthmatic (n=28) and severely asthmatic (n=32) based on prescription medication usage for their asthma management (none, occasional and daily, respectively). The mean ERMI for each group of homes was 6.2 for non-asthmatic, 6.3 for moderately asthmatic and 8.2 for severely asthmatic children. The ERMI values in the homes of severely asthmatic children were significantly greater compared to the non-asthmatics (p=0.04 in Wilcoxon Rank-sum test). Aspergillus niger and Aspergillus unguis were the primary mold species that distinguished severely asthmatic children's homes and non-asthmatic children's homes (p<0.05; Wilcoxon Rank-sum test). The determination of the home's ERMI values may aid in prioritizing home remediation efforts, particularly in those children who are at increased risk for asthma exacerbation.

Squaraines as unique reporters for SERRS multiplexing.

Modified anilino squaraine dyes provide unique SERRS spectra that can be identified at low concentrations within any mixture of current reporters using longer, biologically compatible wavelengths of excitation.

Effects of storage, RNA extraction, genechip type, and donor sex on gene expression profiling of human whole blood.

BACKGROUND: Gene expression profiling of whole blood may be useful for monitoring toxicological exposure and for diagnosis and monitoring of various diseases. Several methods are available that can be used to transport, store, and extract RNA from whole blood, but it is not clear which procedures alter results. In addition, characterization of interindividual and sex-based variation in gene expression is needed to understand sources and extent of variability. METHODS: Whole blood was obtained from adult male and female volunteers (n = 42) and stored at various temperatures for various lengths of time. RNA was isolated and RNA quality analyzed. Affymetrix GeneChips (n = 23) were used to characterize gene expression profiles (GEPs) and to determine the effects on GEP of storage conditions, extraction techniques, types of GeneChip, or donor sex. Hierarchical clustering and principal component analysis were used to assess interindividual differences. Regression analysis was used to assess the relative impact of the studied variables. RESULTS: Storage of blood samples for >1 week at 4 degrees C diminished subsequent RNA quality. Interindividual GEP differences were seen, but larger effects were observed related to RNA extraction technique, GeneChip, and donor sex. The relative importance of the variables was as follows: storage < genechip < extraction technique < donor sex. CONCLUSION: Sample storage and extraction methods and interindividual differences, particularly donor sex, affect GEP of human whole blood.

Gene expression in head hair follicles plucked from men and women.

Characterizing gene expression in hair follicles can help to elucidate the hair growth cycle by delineating the genes and pathways involved in follicular growth and degeneration. The objectives of this study were to determine whether intact RNA could be extracted from a small number of plucked, unstaged hair follicles in sufficient quantity to conduct gene expression profiling, and to conduct global gene expression profiling. To this end, RNA was extracted from 1 to 3 unstaged follicles plucked from the scalp of 36 volunteers. The average quantifiable yield of RNA/follicle was 112.5 ng. Ribosomal ratios were lower than normally expected, but investigation indicated the RNA was intact. Ten of the samples were amplified and hybridized to Affymetrix genechips. On average, 2,567 of the total probe sets (8,500) were expressed in each sample; 1,422 were expressed in all 10 samples; 97 were significantly changed in one gender compared to the other, and 41 had high levels of interindividual variability. This study demonstrates that RNA of sufficient quantity and quality to use in microarray hybridizations can be obtained from as little as a single plucked human hair follicle. Genes expressed in all individuals are probably related to follicular growth and could form a starting set for developing signatures of toxicant exposure. The differentially expressed genes could be involved in producing gender and interindividual differences in hair growth.