Statistical Analysis of Genetic Substance Abuse Data Focus of NIDA Research Grants

Yale researcher Heping Zhang has received two grants totaling $1.5 million from the National Institute on Drug Abuse (NIDA) to develop statistical methods for identifying genes in nicotine dependence and related conditions.

One of the grants is an Independent Scientist Award for Zhang’s career development, and the other is a research project. Zhang, professor of public health in the Division of Biostatistics at Yale School of Medicine, will use both grants to develop statistical methods for biomedical research, particularly genetic and genomic analysis of substance use data. The methods will be developed and applied to identify candidate genes for nicotine dependence and related problems that include drug use and psychiatric conditions.

“The completion of the Human Genome Project and the growing complexity of biomedical studies create enormous challenges for researchers trying to understand the complex relationships among genes, environment and diseases,” said Zhang. “Our ability to collect data is advancing much faster than our ability to develop analytic tools to understand the information.”

The NIDA grants will allow Zhang and his associates to develop statistical methods and software to meet the challenges by incorporating biological functions into the process and by considering the complex relationship among co-morbid substance use and psychiatric disorders. The same approach will also be useful for studying the genetic mechanisms of cancer, hypertension and other complex diseases. Zhang and his associates have already established diagnostic procedures for breast and colon cancer based on gene expression profiles.

The research team in Zhang’s Lab of Statistics and Bioinformatics includes postdoctoral associates Young-Ju Kim, Jun Liu, Xueqing Wang, Yuanqing Ye, and Xiaoyun Zhong; fellows Musie Ghebremichael and John Myers; and doctoral students Fenghai Duan and Rui Feng.

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