This session will highlight two key areas of concern for the future of biomedical and behavioral/social sciences research: (1) the dramatic transformation in data types and sources along with changes in how research is conducted; and (2) an apparent mismatch between many existing training programs and career prospects. One approach for addressing these challenges, a new pilot training program recently funded by the NIH Office of Behavioral and Social Science Research (OBSSR), will be described. 

A group of trans-NIH staff led by Elizabeth Ginexi at OBSSR developed and released a request for applications (RFA) for the Predoctoral Training in Advanced Data Analytics for Behavioral and Social Sciences Research (TADA-BSSR) - Institutional Research Training Program [T32]. The pilot program aims to facilitate data science training commensurate with the diverse data sources now available for behavioral and social sciences research and to help address the need for students in the next generation of programs to have better preparation to communicate across disciplines and with a wider range of sciences. The vision of the TADA-BSSR T32 initiative is to develop a cohort of specialized predoctoral candidates who possess advanced competencies in data science analytics to apply to an increasingly complex landscape of behavioral and social health-related big data. These predoctoral training programs were encouraged to integrate computer science, informatics, mathematics, and statistics into behavioral and social sciences research training.

Our society has reached an inflection point with the availability of new technology such as computational modeling and other computational analytic approaches, the increase in computational power, and the more widespread use of terms such as artificial intelligence and machine learning. However, technology and technological approaches by themselves are neither good nor bad. What matters is how you use them. If they are going to help better understand and address nutrition, they need to account for and help elucidate the systems that affect and are affected by nutrition. This is where systems science comes into play.

Consumers report the “taste” of foods drives what they like and choose to consume. “Taste” or flavor is a complex chemosensory experience with multiple peripheral inputs (true taste, smell,  chemesthesis) carried centrally for perceptual integration and coupling with hedonic, reward, decisional, and satiety responses. In nasal and oral cavities, food/beverage chemicals need to reach and bind or stimulate receptors for transduction to nervous signals and transmission to the brain. Multiple factors drive variation in flavor perception and preference, which, in turn; influence diet behaviors, chronic diet-related diseases, and responses to diet interventions. These include: conditions that impede chemicals reaching chemoreceptors and influence function of chemosensory-related nerves (including COVID-19); genetic variation in chemoreceptors; interactions between internal and external environments to influence plasticity of chemosensensory systems; and age-related changes. Genetic variation in taste and flavor frames the interplay between early-life developmental and environmental influences on food preferences that carry into adulthood. Aging, with changing experiences and environmental exposures, can modify flavor perception, with or without changes in food preferences and behaviors. Interdisciplinary and rigorous research should leverage sensory nutrition as markers of usual diet behaviors and preferences to improve understanding of variability in diet interventions. Clinical nutrition research should account for chemosensation in measures that reflect sensory function and self-reported function; and are relevant to food perception, including measures of food preference, to inform tailored nutrition interventions. Population-based research should incorporate feasible and informative measures of sensory nutrition and food preference with novel study designs to enhance understanding of diet-disease relationships and interindividual variability in dietary responses.

Almost 50 years ago, Donald Zilversmit proposed that the physiologic response to a high-fat meal revealed key dynamics related to the development of heart disease.  This area of research has been widely expanded and includes the concept of metabolic flexibility (an efficient switch to whole-body carbohydrate oxidation after consuming sugars) and the concept of nutrient toxicity during overconsumption of energy.  Within highly heterogeneous populations (people of different sexes, race/ethnicities, ages, and fitness levels) the responses exhibited after a nutrient challenge are highly variable, while the responses to fasting is highly predictable and similar between people.  Thus, measuring physiologic responses to the act of eating uncovers disease risks less apparent in fasting blood samples.  A number of study design features will impact the response to a meal, and therefore influence interpretation of results.  These include the composition and energy content of the test meal, food intake the day before the meal test, and recent physical activity.  This presentation will review important aspects of research rigor to study post-meal events such as subject preparation and sampling protocols for measuring metabolites.  Minimizing the impact of non-food factors that increase subject variability has been the goal of recent postprandial studies.  On the other hand, if the purpose of the research is to assess the natural variability in response to eating via assessment of the physiologic pattern encompassing all factors influencing real-life responses, then one may intentionally choose to not control any of the factors listed above.  Given that fed-state events contribute significantly to chronic disease risk, improved methods to study the absorption and disposal of energy will support the development of individualized prevention and treatment strategies to counteract diseases associated with the chronic over-consumption of food.

In January 2021 our nation is in the midst of mitigating pandemic of SARS-CoV-2, is witnessing violence and outrage at the US Capitol in response to recent presidential election results, and is acknowledging structural anti-Black racism as a public health crisis. There is also persistent increasing population diversity driving a need for recognition and appreciation of different cultures. Now more than ever, we need to understand and address the impact of psychosocial and cultural factors such as toxic stress, belief systems, and traditions on dietary intake. A public health framework, such as the socioecological model, can be used to understand the complex interplay between biological, behavioral, psychosocial, and cultural factors. These factors can operate at the level of the individual, provider, or healthcare system and robust nutrition research should assess these dimensions. Norms and behavioral customs around food can be potential targets for nutrition interventions; and to achieve health equity they should be removed if they are identified to be root causes of disparities in dietary intake across population groups.

Dietary intervention trials often invoke heterogeneous responses between study participants - even in highly controlled feeding trials. This presentation will examine some salient subgroup findings from previous trials, explore the meaning of inter-individual variation and provide ideas for leveraging variability in future precision nutrition interventions.

Nutrition for Precision Health, powered by the All of Us Research Program (NPH), aims to develop algorithms that predict individual responses to food and dietary patterns. Nutrition plays an integral role in human development and in the prevention and treatment of disease. However, there's no such thing as a perfect, one-size-fits-all diet. The NPH program will build on recent advances in biomedical science including artificial intelligence, microbiome research, as well as the infrastructure and large, diverse participant group of the All of Us Research Program. These advances provide unprecedented opportunities to generate new data to provide insight into precision nutrition. The NPH program will conduct a study nested in the All of Us Research Program to explore how individuals respond to different diets. The NPH study is the first ancillary study to leverage the All of Us infrastructure to answer scientific questions important to participants like understanding more about the role of nutrition in health. High-quality nutrition studies such as the NPH study will help individuals and their health care providers create healthy, precise, and effective diet plans. The objectives of the study are: 1. To examine individual differences observed in response to different diets by studying the interactions between diet, genes, proteins, microbiome, metabolism and other individual contextual factors 2. To use artificial intelligence to develop algorithms to predict individual responses to foods and dietary patterns 3. To validate algorithms for clinical application This presentation will discuss the planning process and next steps for the NPH program.

The 2020 Lancet Commission Report estimates that up to 40% of Alzheimer's disease (AD) cases may be preventable through modifiable risk factor modification. The field of AD prevention has largely focused on addressing these factors through universal risk reduction strategies for the general population. However, targeting these strategies in a clinical precision medicine fashion, including the use of genetic risk factors, allows for potentially greater impact on AD risk reduction. Over the last decade, there has been an exponential increase in the evidence supporting nutritional interventions for AD risk reduction. However, in the area of precision nutrition, there remains many unanswered questions and the field is rich with opportunity for scientific exploration. Apolipoprotein E (APOE), and specifically the APOE ε4 variant, is one of the most well-established genetic influencers on late-onset AD risk. In this presentaion, we review an individualized clinical management approach toward AD risk reduction, and give an overview of the nutrigenomic impact of APOE ε4 carrier status on AD prevention interventions.

About 70 years ago, Ancel Keys proposed the diet and heart hypothesis. However, despite its overall success, this hypothesis has been continuously disputed. Why something so simple as the diet-CVD relationship, got so complicated?
Because we are complicated, as shown by the huge interindividual variability and low intraindividual reproducibility observed in intervention studies. Moreover, food is complicated, and there are still thousands of functional compounds, unknown to us, that could be key to understand how what we eat affects our health.  
In the '80s, the ability to detect genetic variants gave birth to another simple hypothesis: variability in genes drives interindividual variability in diet response.  The testing of this hypothesis applied to CVD has resulted in over 1000 publications. However, most have investigated gene-diet interactions related to CVD risk factors, and very few have targeted CVD events. The Predimed study is among the few intervention studies describing gene-diet interactions for CVD events, as shown by research involving the LPL and TCF7L2 genes. 
Another source of complexity is time. It is important what we eat, but also when we eat. This may be highly relevant for CVD that has been shown to have circadian and seasonal rhythmicity. In this regard, we have demonstrated that genetic variants at the circadian CLOCK gene modulate the relation between diet and CVD events.
After decades focusing on gene-diet interactions, precision nutrition has grown to incorporate other players, such as epigenetics, metabolomics, microbiome, aging, sex, lifestyle, chronobiology, diseases, drugs, and environment. Given the vast increase in data collected, we must adopt new approaches to query and analyze the Big Data sets, such as Artificial Intelligence. This combination of data and analytical tools will pave the way to precision nutrition and successful CVD prevention and therapy.