# Obesity- Tom Robinson > **NIH NIH U54** · STANFORD UNIVERSITY · 2020 · $441,643 ## Abstract Abstract – Project 2 We propose to conduct large-scale, longitudinal, integrative personalized `omics profiling (iPOP), consisting of detailed characterization of genotype, transcriptome, metabolome, epigenome, and oral microbiome, on 241 overweight and obese, low-income, Latino children participating in a 3-year, community-based multi-level, multi-component, multi-setting intervention to reduce weight gain, to identify biomolecular signatures that (1) are associated with measures of adiposity and diabetes risk, (2) predict changes in adiposity and diabetes risk over 3 years and moderate or mediate the effects of the intervention, and (3) provide additional predictive value for adiposity and diabetes risk when combined with cognitive, behavioral, socio-demographic and environmental measures. The United States has experienced dramatic increases in obesity and diabetes with some of the highest rates among Hispanics/Latinos. About half of Latino children are predicted to have diabetes in their lifetimes. Further, while national childhood obesity rates appear to be plateauing, disparities between non-Hispanic whites and Mexican-Americans appear to be widening. This may be due, in part, to differential access to medical, public health and social programs. Thus, the fear is that advances in precision health will even further exacerbate disparities for populations that lack access to these emerging technologies. Instead of being the last population to participate in emerging research, this proposal focuses the science of precision health initially on high-risk, low-income Latino children, to create the knowledge and tools to help precision health reduce health disparities rather than widen them. To date, large scale `omics profiling of the detail and scale proposed in this project has not been done in a U.S. ethnic minority sample. We have assembled a multidisciplinary team to perform a singular study of childhood obesity and diabetes risk by combining a 3-year multi-level, multi- component, multi-setting intervention with large-scale, longitudinal iPOP that will result in the most comprehensively molecularly profiled children in history. Our long-term goal is to reduce health disparities by developing and applying `omics technologies to more effectively prevent and treat excess weight gain and diabetes risk. The overall objective of this application, the first step toward this goal, is to quantify metabolic and biomolecular differences among children that are associated with and/or predict obesity and diabetes risk, and to characterize the heterogeneous biological responses and moderators and mediators to interventions to reduce weight gain. Our central hypothesis is that there are substantial biological differences that impact the development of obesity and diabetes risk and the effectiveness of interventions. The rationale for our study is that to effectively reduce racial/ethnic disparities in childhood weight gain we... ## Key facts - **NIH application ID:** 9896677 - **Project number:** 5U54MD010724-05 - **Recipient organization:** STANFORD UNIVERSITY - **Principal Investigator:** THOMAS N. ROBINSON - **Activity code:** U54 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $441,643 - **Award type:** 5 - **Project period:** — → 2024-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9896677 ## Citation > US National Institutes of Health, RePORTER application 9896677, Obesity- Tom Robinson (5U54MD010724-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9896677. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*