The Dhillon lab is focused on answering some of the central questions in Nutrition and Exercise Sciences:

How can we personalize diets for optimal health?

The new frontier of nutrition science lies in tailoring nutrition recommendations to the individual’s phenotype, genotype, food preferences, ethnicity/race, cultural background, and socioecological context. Our research delves into personalized nutrition incorporating the aforementioned dimensions, as well as the important role pre-ingestive factors play in food choice and physiology. The integration of multi-omics techniques is important for a mechanistic interpretation of the role of diet in health.

How do we address racial and/or ethnic disparities in cardiometabolic outcomes?

Our NIH-NIMHD funded project is examining the effects of a functional-food based personalized diet on cardiometabolic outcomes compared to conventional dietary advice in young adults. An innovation of this project is examining the interdependent relationship between the human metabolome and the gut microbiome and its impact on cardiometabolic factors, particularly in the context of a personalized dietary intervention. Because most clinical nutrition studies are performed in middle-aged to older non-Hispanic White adults, racial/ethnic minority populations are less well characterized. Given the increasing incidence of diet-related cardiometabolic disorders in minority groups, at much younger stages in life, these populations warrant special consideration. However, whether improvements in diet will influence racial/ethnic minority groups at high risk of cardiometabolic diseases differentially than non-Hispanic Whites at high risk is not well understood. Hence, this project will also assess differences in outcomes by ethnic/racial minority groups versus non-Hispanic White groups and apply qualitative methods to provide socioecological context to the clinical data.

What are the key pre- and post-ingestive factors determining feeding?

The sensory properties of food—that is, taste, texture, odor, flavor, and even expectations regarding the food—can influence food choice, digestion, and metabolism. Sensory stimulation, prior to ingestion, can elicit a wide array of rapid physiological processes termed cephalic phase responses that enable the organism to mount an adaptive response to impending food ingestion. In our work with low-calorie sweeteners (LCS), we demonstrated for the first time, a probable cephalic phase insulin response (CPIR) to sucralose stimulation. Although sweetness alone was enough to stimulate insulin secretion prior to ingestion in a subset of individuals with overweight and obesity, the CPIR did not influence appetite or energy intake at an ad libitum meal. These findings challenge the hypothesis that sweetness-induced CPIR serves as an impetus for increased energy intake. Apart from the sensory properties of food, factors such as macronutrient composition have a considerable influence on appetite and energy balance as well. Dietary protein, in particular, has been implicated in weight management because of its appetitive properties. We conducted a meta-analysis to clarify these effects and found that higher protein preloads increased fullness ratings more than lower protein preloads under tightly defined conditions only. These findings hold promise for recommendations to manage fullness, and subsequently energy intake and body weight. Hence, pre- and post-ingestive factors can have appetitive and consummatory influences that guide food intake, nutrition, and consequently, health and disease.

How does exercise impact the gut microbiome?

Exercise is an essential therapeutic intervention to mitigate the risk factors associated with obesity and other cardiometabolic diseases. The gut microbiome has recently been associated with obesity. In our lab, we study how exercise, particularly resistance training, impacts the gut microbiome in adults with obesity.

How do we incorporate systems biology approaches to understand the effects of nutrition and exercise on health?

Despite the rising use of computational models in biological sciences, their potential in nutrition and exercise sciences remains vastly underexplored, primarily because such complex biological research questions require modeling approaches that are expertise dependent and resource intensive. Our research team integrates clinical, microbiome, omics, dietary, and health data obtained from clinical interventions into developing computational models to predict metabolic responses to diets, and for mechanistic interpretations.