Analyzing Complex Health Science Data
Analyzing Complex Health Science Data Heading link
Hua Yun Chen, PhD is a professor of biostatistics whose research has been focused on developing innovative statistical methods for analyzing complex health science data. His areas of expertise include statistical methods for analysis of data with missing values, for design and analysis of biased samples in epidemiological studies, and for identification of gene-environment interactions. Chen’s recent research work also covers methods for analysis of high-dimensional genomic data with a large number of weak effects and for study of adverse health effects of exposures to environmental chemicals.
In a recent project funded by the National Institute of Environmental Health Sciences, Chen collaborated with Dr. Mary Turyk, associate professor of epidemiology, and other faculty members at UIC SPH, on developing a set of innovative statistical methods to tackle the challenges of analyzing the adverse health effects of exposures to environmental chemical mixtures, data collected in biomonitoring. Biomonitoring is the direct measurement of people’s exposure to toxic substances by measuring human specimens, such as blood or urine. Biomonitoring measurements provide health-relevant assessments of exposure because they indicate the combined amount of the chemicals that actually get into people from all environmental sources (for example, air, soil, water, dust, food).
Despite some anticipated challenges typically associated with analyzing contemporary biomonitoring data, Chen will develop a set of new approaches that can detect the collective weak main and interaction effects of exposures to chemical mixtures, identify causal pathways through innovative network analysis, and estimate the causal effects of exposures to a mixture of chemicals. The proposed methodology development will help better understand the effects of the environmental exposures on human health by considering chemical mixtures, rather than each component in isolation. Methods will be implemented in a software package for ease of access by researchers. In collaboration with the Wisconsin Bureau of Environmental and Occupational Health, the proposed methods will be applied to a range of environmental health studies to improve our understanding of the global and individual relationships of mixtures of environmental exposures and health outcomes.
Additional research in Chen’s portfolio is supported by the Mathematical Science Division of the U.S. National Science Foundation for studies of network structures using a general modeling framework. Chen also collaborates with Dr. Dawood Darbar, professor of medicine and pharmacology and chief of cardiology at UI Health, to identify rare genetic variants associated with irregular and often rapid heart rate (atrial fibrillation). Together they also plan to study antiarrhythmic therapies that are modulated by common genetic variants associated with atrial fibrillation.