Mount Sinai Researchers Build Modeling Systems Identifying Gene-Drug and Environment Interactions
New approach provides more accurate analysis of complex genetic and drug/environment data by monitoring over time
A team of researchers at the Icahn School of Medicine at Mount Sinai and the University of Washington has designed a modeling system that integrates genomic and temporal information to infer causal relationships between genes, drugs, and their environment, allowing for a more accurate prediction of their interactions over time. The work is described in a paper published in September in Nature Communications.
“Understanding how a person’s environment, diet, medications, and other factors impact disease-associated traits over time has the potential to more accurately model an individual’s risk of disease,” says Eric Schadt, PhD, Dean for Precision Medicine at the Icahn School of Medicine at Mount Sinai; CEO of Sema4, a Mount Sinai venture; and a co-author of the paper. “This will be the future of precision health or personalized medicine.”
Given the complexity of biological systems, scientists at the Icahn School of Medicine believed that it would only be possible to increase the accuracy of prediction tools by examining gene expression and other data in response to various perturbations at multiple points over time. The tools they created measure both static and dynamic changes in order to identify the web of causal relationships among molecular elements that make up regulatory networks.
“Predicting the behavior of biological systems is tremendously difficult because they are so dynamic, adapting as conditions demand. It is only by mining as much data as possible that we can generate more reliable results about how anyone’s health might change as a result of exposure to certain environmental or other elements,” said Jun Zhu, PhD, Professor of Genetics and Genomic Sciences at the Icahn School of Medicine, Head of Data Sciences at Sema4, and senior author of the publication. “Our new tools offer a fundamental step forward by analyzing genomic data over time. This type of approach will be particularly useful for medical research on aging and ultimately could enhance our ability to predict disease risk, making earlier interventions possible to treat or prevent disease altogether. ”
The scientists evaluated their tools by analyzing a genetically heterogenous population of yeast cells treated with rapamycin, a potential anti-aging drug, profiling the population at multiple time points. The results demonstrated that the new approach identified a significant amount of associations between DNA variation and gene expression variation, especially for aging-related genes, reflecting the changing impact of genetic variations over time. Further, this approach proved more reliable in identifying causal regulators of gene-drug interactions, compared to conventional methods using only a single time point.
“This paper demonstrates the improvements in inferring genetic causes of disease enabled by higher-resolution molecular profiling. As scientists become increasingly able to incorporate information such as temporal, single-cell, and microenvironment profiling into studies, algorithms such as the one described in Dr. Lin’s paper will be poised to leverage such data to infer increasingly accurate models of the molecular drivers of disease which can be used to design improved novel therapies.” said Adam Margolin, PhD, Chair of the Department of Genetics and Genomic Sciences and Senior Associate Dean for Precision Medicine at the Icahn School of Medicine.
This work was partially supported by NIH grants R01AG046170, U01HG008451, and U19AI118610.
Paper cited: Luan Lin et al. Temporal Genetic Association and Temporal Genetic Causality Methods for Dissecting Complex Networks. Nature Communications. DOI 10.1038/s41467-018-06203-3.
About the Mount Sinai Health System
The Mount Sinai Health System is New York City's largest integrated delivery system, encompassing eight hospitals, a leading medical school, and a vast network of ambulatory practices throughout the greater New York region. Mount Sinai's vision is to produce the safest care, the highest quality, the highest satisfaction, the best access and the best value of any health system in the nation. The Health System includes approximately 7,480 primary and specialty care physicians; 11 joint-venture ambulatory surgery centers; more than 410 ambulatory practices throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and 31 affiliated community health centers. The Icahn School of Medicine is one of three medical schools that have earned distinction by multiple indicators: ranked in the top 20 by U.S. News & World Report's "Best Medical Schools", aligned with a U.S. News & World Report's "Honor Roll" Hospital, No. 12 in the nation for National Institutes of Health funding, and among the top 10 most innovative research institutions as ranked by the journal Nature in its Nature Innovation Index. This reflects a special level of excellence in education, clinical practice, and research. The Mount Sinai Hospital is ranked No. 14 on U.S. News & World Report's "Honor Roll" of top U.S. hospitals; it is one of the nation's top 20 hospitals in Cardiology/Heart Surgery, Diabetes/Endocrinology, Gastroenterology/GI Surgery, Geriatrics, Gynecology, Nephrology, Neurology/Neurosurgery, and Orthopedics in the 2019-2020 "Best Hospitals" issue. Mount Sinai's Kravis Children's Hospital also is ranked nationally in five out of ten pediatric specialties by U.S. News & World Report. The New York Eye and Ear Infirmary of Mount Sinai is ranked 12th nationally for Ophthalmology and Mount Sinai South Nassau is ranked 35th nationally for Urology. Mount Sinai Beth Israel, Mount Sinai St. Luke's, Mount Sinai West, and Mount Sinai South Nassau are ranked regionally.