Tracking the links between genomics, nutrition and health may improve diagnostics and therapy for cancer and other diseases
The Texas A&M University System has received a $1.19 million grant from the National Institutes of Health (NIH) for a multidisciplinary collaboration to study the intricate connections between genomics, nutrition and health. Understanding these connections will help in the diagnosis and treatment of cancer and other diseases.
Yang Ni, an assistant professor in the College of Arts and Sciences, Department of Statistics and a research affiliate with the Texas A&M Institute of Data Science, is the principal investigator for the effort. The project aims to create a toolset for interpreting and correlating novel genetic information.
Co-principal investigators are Robert Chapkin, University Distinguished Professor and holder of the Allen Endowed Chair in the College of Agriculture and Life Sciences, Department of Nutrition and Department of Biochemistry and Biophysics, and James Cai, associate professor in the School of Veterinary Medicine and Biomedical Sciences, Department of Veterinary Integrative Biosciences.
The team’s project seeks to advance single-cell data science, the study of how genes and gene expression differ among individual cells in one organism. Because cancer arises from genetic abnormalities in individual cells, scientists believe that single-cell data science will reveal medically important information.
This NIH award is tied to a pending grant from the Cancer Prevention and Research Institute of Texas (CPRIT) to assess gene-environment-lifestyle interactions in cancer. Chapkin is spearheading that effort in collaboration with Ken Ramos, executive director at Texas A&M’s Institute of Biosciences and Technology.
Ramos and Chapkin have also submitted a $6 million grant proposal titled “Gene-environment-lifestyle interactions in cancer” to CPRIT to create a new regional center of excellence in cancer research.
Chapkin said the NIH grant’s goals and personnel will complement the establishment of a single-cell data science core at Texas A&M that will serve as a shared-resource facility.