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Jane Gallagher   Dr.  Research or Laboratory Scientist 
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Jane Gallagher published an article in November 2013.
Top co-authors See all
David Reif

106 shared publications

Center for Human Health and the Environment, and Department of Biological Sciences, North Carolina State University

Pierre R. Bushel

91 shared publications

Microarray and Genome Informatics Group, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA

Lucas Neas

48 shared publications

National Health and Environmental Effects Research Laboratory, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA

Peter P. Egeghy

48 shared publications

National Exposure Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States

Haluk Özkaynak

47 shared publications

National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, USA

Publication Record
Distribution of Articles published per year 
(1999 - 2013)
Total number of journals
published in
Publications See all
Article 0 Reads 4 Citations Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotype... ClarLynda R Williams-DeVane, David M Reif, Elaine Cohen Huba... Published: 04 November 2013
BMC Systems Biology, doi: 10.1186/1752-0509-7-119
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
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. 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. 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.
Article 2 Reads 5 Citations Sustainability, Health and Environmental Metrics: Impact on Ranking and Associations with Socioeconomic Measures for 50 ... Jane E. Gallagher, Elaine Cohen Hubal, Laura Jackson, Jeffer... Published: 22 February 2013
Sustainability, doi: 10.3390/su5020789
DOI See at publisher website ABS Show/hide abstract
Waste and materials management, land use planning, transportation and infrastructure including water and energy can have indirect or direct beneficial impacts on the environment and public health. The potential for impact, however, is rarely viewed in an integrated fashion. To facilitate such an integrated view in support of community-based policy decision making, we catalogued and evaluated associations between common, publically available, Environmental (e), Health (h), and Sustainability (s) metrics and sociodemographic measurements (n = 10) for 50 populous U.S. cities. E, H, S indices combined from two sources were derived from component (e) (h) (s) metrics for each city. A composite EHS Index was derived to reflect the integration across the E, H, and S indices. Rank order of high performing cities was highly dependent on the E, H and S indices considered. When viewed together with sociodemographic measurements, our analyses further the understanding of the interplay between these broad categories and reveal significant sociodemographic disparities (e.g., race, education, income) associated with low performing cities. Our analyses demonstrate how publically available environmental, health, sustainability and socioeconomic data sets can be used to better understand interconnections between these diverse domains for more holistic community assessments.
Article 5 Reads 5 Citations Mechanistic Indicators of Childhood Asthma (MICA) Study: piloting an integrative design for evaluating environmental hea... Jane Gallagher, Edward Hudgens, Ann Williams, Jefferson Inmo... Published: 19 May 2011
BMC Public Health, doi: 10.1186/1471-2458-11-344
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
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. 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. 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.
Article 0 Reads 1 Citation Evaluation of genetic susceptibility to childhood allergy and asthma in an African American urban population Bonnie R Joubert, David M Reif, Stephen W Edwards, Kevin A L... Published: 14 February 2011
BMC Medical Genetics, doi: 10.1186/1471-2350-12-25
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
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. 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). 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). 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.
Article 0 Reads 7 Citations Participant-based monitoring of indoor and outdoor nitrogen dioxide, volatile organic compounds, and polycyclic aromatic... Markey M. Johnson, Ron Williams, Zhihua Fan, Lin Lin, Edward... Published: 01 December 2010
Atmospheric Environment, doi: 10.1016/j.atmosenv.2010.08.027
DOI See at publisher website
BOOK-CHAPTER 0 Reads 3 Citations Biomarkers for Environmental Exposure Jane E. Gallagher, Elaine A. Cohen Hubal, Stephen W. Edwards Published: 03 November 2010
Biomarkers, doi: 10.1002/9780470918562.ch20
DOI See at publisher website