Challenges in Personalized Nutrition and Health

Verma et al. (2018) reviewed the challenges in personalised nutrition and health. We will take a closer look at their discussion in this article.

What is Personalised Nutrition

Diet has a profound impact on human health and wellbeing. The human body requires a balanced diet with adequate amounts of macronutrients (carbohydrates, protein and fats) and micronutrients (vitamins and minerals) for the body to function properly. The absence of a balanced diet can lead to health problems such as cardiovascular disease, diabetes, obesity and malnutrition.

Although, the importance of nutrition is well established, the interaction between food and health is quite complex and many questions about how food contributes to our health still remain opened. Given the multifactorial nature of chronic diseases and the great diversity of the diet, it is really difficult to prove a causal role of a specific dietary element on disease development. Moreover, there is an inter-individual variability whereby individuals respond differently to dietary interventions as a result of: age, gender, genetics, lifestyle, environmental, exposure, gut microbiome, epigenetics, metabolism nutrition derived from diet and foods.

Personalised nutrition refers to tailored nutritional recommendations aimed at the promotion and maintenance of health and wellbeing; and prevention against disease. These recommendations take into account differential responses to certain individualized food-derived nutrients and biological processes. This includes interactions between:

• Internal Factors: Genetics, microbiome, metabolime interactions
• External Factors: Dietary habits and physical activity

There are a number of reductionist approaches used to study the inter-individual response to diet. These include, omic technologies (e.g. genomics, metabolomics and proteomics) integrated with the systems biology programs. However, significant challenges exist in the translation and application of these approaches in human studies.

The major challenges encountered in the process of revolutionizing the personalized nutrition health-care information technology include:

• Limitation in the reductionist approaches and opportunties for adoption of advanced computational data-driven technolgoies

• Need for personalized nutrition computational infrastructure

• Data standardization and the requirement for training individuals

• Data sparsity, missing data and need for improved imputation methods

To make accurate personalized nutrition recommendations and accelerate the goal of better health and well-being, advanced computational technologies such as artificial intelligence, machiene learning and deep learning are promising in providing an integrated framework (Figure 1).

*Figure 1: A pipeline for personalized nutrition and health (Verma et al., 2018)

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The figure presents the integration of the data derived from health determinants such as diet, gut microbiome, data from electronic health records, physical activity measures, and data collected from wearable sensors can be used to train the artificial intelligence algorithms. The outputs can be used to make targeted personalized nutrition recommendations.

The use of data-driven methods will require the development of a personalized food and health infrastructure system comprised of advanced computational technologies with data storage, processing and sharing capabilities. This infrastructure will strengthen and enhance patient care based on the collection of longtitudinal data related to physiological measures, gut microbiome and other relevant biomarker measures.

What we would like you to do

If you are interested in exploring these challenges in more detail, as well as the possible solutions to aid the process of making decisions about diets and foods at an individual personalized level, have a read of Verma et al. (2018)’s paper on Challenges in Perzonalized Nutrition and Health here..