I was a software engineer for almost 8 years in the biotechnology industry, developing algorithms for gene sequencing devices. While the work was intellectually stimulating, I wanted an opportunity to deepen skills in computation, bioinformatics, and biomedicine. To fulfill this intellectual desire, I attained a doctorate degree in biomedical informatics at Stanford University. At Stanford, I further honed and developed in the areas of software engineering, genomics, informatics, computer science, and statistics. Wanting ways to translate findings in the clinic, I sought a post-doctoral fellowship in epidemiology, working with John PA Ioannidis.
As a software engineer, graduate student, a post-doctoral associate, and now a junior faculty member at Harvard Medical School, I have wondered about the multifactorial components that influence disease, such as both inherited and environmental factors. It was apparent from my study and work in industry that scientiists had new and robust tools to ascertain how inherited genetic variants influence disease through studies such as the “genome-wide association study”, but I wondered, and continue to wonder, how we can get a more complete picture of human health by consideration of other factors, such as the environment. If we could measure and analyze the envirommental exposure as well as we do with genetics, perhaps we could use this information for better means of prevention and therapy. The PhRMA foundation grant was very important enabler for me to start this scientific exploration. For example, my PhRMA-sponsored work, has been central to the emerging human exposome project, a new paradigm to quantitatively assess a large array of personal exposures in humans. The PhRMA award has been important to jump-start research in genomics and therapeutics, where we are using big data methods to ascertain new uses for old drugs, or repositioning therapy. Finally, the PhRMA award has helped fund new career starter awards from the NIH/NIEHS (a K99/R00), a small research grant (R21), and gifts from foundations and industry to use public data resources to conduct large-scale gene-by-environment interactions to better characterize disease risk as a function of both inherited and exposure factors.
Featured Publications sponsored by the PhRMA Award:
Patel, C. J., M. R. Cullen, J. P. A. Ioannidis, and D. H. Rehkopf. 2014. “Systematic Assessment of the Correlation of Household Income with Infectious, Biochemical, Physiological Factors in the United States, 1999-2006.” American Journal of Epidemiology 181: 171–79.
Patel, Chirag J., Ting Yang, Zhongkai Hu, Qiaojun Wen, Joyce Sung, Yasser Y. El-Sayed, Harvey Cohen, et al. 2013. “Investigation of Maternal Environmental Exposures in Association with Self-Reported Preterm Birth.” Reproductive Toxicology 45 (December). Elsevier Inc.: 1–29.
Patel, Chirag J., Rong Chen, Keiichi Kodama, John P. A. Ioannidis, and Atul J. Butte. 2013. “Systematic Identification of Interaction Effects between Genome- and Environment-Wide Associations in Type 2 Diabetes Mellitus.” Human Genetics 132 (5): 495–508.
Patel, Chirag J., David H. Rehkopf, John T. Leppert, Walter M. Bortz, Mark R. Cullen, Glenn M. Chertow, and John P. A. Ioannidis. 2013. “Systematic Evaluation of Environmental and Behavioural Factors Associated with All-Cause Mortality in the United States National Health and Nutrition Examination Survey.” International Journal of Epidemiology 42 (6). IEA: 1795–1810.
Tzoulaki, I., C. J. Patel, T. Okamura, Q. Chan, I. J. Brown, K. Miura, H. Ueshima, et al. 2012. “A Nutrient-Wide Association Study on Blood Pressure.” Circulation 126 (21): 2456–64.
Patel, Chirag J., Mark R. Cullen, John P. A. Ioannidis, and Atul J. Butte. 2012. “Systematic Evaluation of Environmental Factors: Persistent Pollutants and Nutrients Correlated with Serum Lipid Levels.” International Journal of Epidemiology 41 (3): 828–43.
Brown, Adam S., Sek Won Kong, Isaac S. Kohane, and Chirag J. Patel. 2016. “ksRepo: A Generalized Platform for Computational Drug Repositioning.” BMC Bioinformatics 17 (1): 470.
Patel, Chirag J., Arjun K. Manrai, Erik Corona, and Isaac S. Kohane. 2016. “Systematic Correlation of Environmental Exposure and Physiological and Self-Reported Behaviour Factors with Leukocyte Telomere Length.” International Journal of Epidemiology, April. doi:10.1093/ije/dyw043.
Patel, Chirag J., Belinda Burford, and John P. A. Ioannidis. 2015. “Assessment of Vibration of Effects due to Model Specification Can Demonstrate the Instability of Observational Associations.” Journal of Clinical Epidemiology 68 (June). Elsevier Inc: 1046–58.
Patel, Chirag J., and John P. A. Ioannidis. 2014b. “Placing Epidemiological Results in the Context of Multiplicity and Typical Correlations of Exposures.” Journal of Epidemiology and Community Health 68 (11). BMJ Publishing Group Ltd: 1096–1100.
———. 2014a. “Studying the Elusive Environment in Large Scale.” JAMA: The Journal of the American Medical Association 311 (21). American Medical Association: 2173–74.
Patel, Chirag J., David H. Rehkopf, John T. Leppert, Walter M. Bortz, Mark R. Cullen, G. M. Chertow, and John P. A. Ioannidis. 2014. “Systematic Evaluation of Environmental and Behavioural Factors Associated with All-Cause Mortality in the United States National Health and Nutrition Examination Survey.” International Journal of Epidemiology 42 (6): 1795–1810.
Li, L., D. J. Ruau, C. J. Patel, S. C. Weber, R. Chen, N. P. Tatonetti, J. T. Dudley, and A. J. Butte. 2014. “Disease Risk Factors Identified Through Shared Genetic Architecture and Electronic Medical Records.” Science Translational Medicine 6 (234): 234ra57–234ra57.
Research support as a result of PhRMA sponsorship:
5R00ES023504-03 Patel (PI) 1/1/2016 – 12/31/18
Data-driven identification of environmental factors in cardiovascular disease
Informatics methods to search for environmental factors and gene-environment interactions in cardiovascular disease
Role: PI
1R21ES025052-02 Patel (PI) 1/1/2015 – 11/30/17
Increasing the power of GxE detection using multi-locus predictors
Informatics methods to ascertain GxE interactions in body mass index and blood pressure
Role: PI
