February 04, 2021

Scripps Research and Tempus collaborate to study how individual blood sugar levels vary The study will leverage genomics and digital technologies to better understand factors that contribute to obesity and type 2 diabetes.

February 04, 2021

LA JOLLA, CA Scripps Research, a globally recognized nonprofit biomedical research institute, today announced a collaborative research program with Tempus, a leader in precision medicine and artificial intelligence, to develop a predictive model of glucose responses in people with and without type 2 diabetes. By understanding individual changes in blood sugar levels, scientists aim to boost efforts to combat the twin epidemics of diabetes and obesity.

The program, called PRediction Of Glycemic RESponse Study (PROGRESS), will leverage data from participants' genomes and microbiomes, as well as information from digital technologies, to understand the many factors that dictate how individual blood sugar levels change in response to food.

There is growing evidence that glycemic responses to the same foods differ significantly from person to person, says Edward Ramos, PhD, director of Digital Clinical Trials at the Scripps Research Translational Institute and principal investigator of the study. Advances in individualized data collection through personal health tracking devices enable us to better quantify a wide range of personal traits that will assist in refining more personalized approaches for glycemic control.

Diabetes, which results in too much sugar in the blood, is one of the most prevalent and costly chronic diseases in the United States, with more than 100 million adults living with the disease or early signs of it. Obesity is a significant risk factor. At a population level, excessive eating or poor nutritional intake are known to lead to weight gain and an increased risk of diabetes. However, many questions remain about how these factors play into disease risk on an individual level.

Many factors contribute to the variability in glycemic responses, including chewing, saliva composition, digestion, genetics, body mass index, diet and gut microbiota. Developing a predictive model of individual glycemic response requires analyzing large amounts of biologic, physiologic, clinical and lifestyle information. Given the complexity of these factors and how they connect with one another, machine-learning tools are needed to process the broad array of data.

Despite recent advances in understanding the many genetic and environmental factors underlying diabetes, there have been few large-scale studies that fully address the complex, multi-modal nature of this disease, says Joel Dudley, PhD, Chief Scientific Officer, Tempus. This study aims to build a foundation of data and understanding that will enable development of intelligent precision medicine technologies to address unmet clinical needs in diabetes at scale. We're delighted to collaborate with Scripps Research to advance our understanding of diabetes and the pursuit of next-generation clinical trial design.

PROGRESS will adopt the site-less clinical trial model pioneered by scientists at the Scripps Research Translational Institute. Enabling remote participation through home delivery of biosample collection and digital health technology kits, as well as a study-specific mobile application for communication, the scientists aim to eliminate many of the barriers that exist for traditional clinic-based studies (e.g. access to clinics, time constraints, transportation challenges, limited participation).

Healthcare system partners will recruit 1,000 study participants over the age of 18. Half will consist of individuals with diagnosed type 2 diabetes and half without a diagnosis. The study will monitor participants' dietary intake, activity levels and continuous glucose values over 10 days, using that data along with genomic, microbiome and electronic health record data to develop algorithms for predicting glycemic response on an individual level. Study participants will also be passively monitored for changes in health outcomes over the course of three years.

The scientists hope this work will bolster personalized health management programs and help address the growing obesity and diabetes epidemics, both in the United States and globally.

Translational Institute Ramos, Edward

LINK:	https://www.scripps.edu/news-and-events/press-room/2021/20210204-preci...
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