Precision nutrition of health

One strategy is to find groups of individuals that behave differently in response to dietary treatments and tailor diets to such groups. Groups may be differentiated by their gut microbiota (enterotypes) or by metabolites (metabotypes). We are also investigating mechanisms underlying response/non-response to specific foods and diets. This will allow us to develop tailored strategies to improve the health outcome of foods for personal and public health.

Our vision is to develop tools which can be integrated in clinical practice to guide specific dietary advice as well as result in tailored foods for groups of individuals with similar metabolic phenotype and nutritional requirements within a 5-10 year perspective.

 

Dietary- and precision nutrition biomarkers

We discover novel biomarkers for assessment of dietary exposures. Traditional dietary assessment tools such as food frequency questionnaires are prone to random and systematic errors, including recall bias, inaccurate estimation of portion size, misreporting of dietary intake, and bias toward socially desirable answers.Objective dietary biomarkers can help to correct these errors and complement (and sometimes substitute) traditional dietary assessment tools.

We apply metabolomics, lipidomics, and other molecular profiling techniques in dietary interventions and prospective cohorts to discover novel candidate biomarkers for dietary exposure, validate these candidates in dietary intervention trials, and develop targeted dietary panels for the nutrition research community.

We have developed and validated novel biomarkers that reflect consumption of specific foods such as whole grains, boiled and filtered coffee, fish, meat, plant-based foods, berries and for dietary patterns such as the health Nordic Diet. These biomarkers have been successfully applied to address compliance in dietary interventions and to assess dietary intake in observational studies.

In the context of personalized and stratified dietary chronic disease prevention, we are interested in metabolic response biomarkers to predict the individual and subgroup-specific long-term health consequences of dietary patterns. To this end, we examine the overlap between dietary effects and chronic disease prediction in molecular profiling studies.

Our group has significant expertise in chronic disease prediction modelling and evaluating predictive capacity of novel -omics-based biomarker panels. In ongoing projects, we explore metabolomics, lipidomics, glycomics, proteomics, and microbiome metagenomics data to derive biomarkers that are simultaneously diet-sensitive and risk predictive. We are specifically looking for biomarkers that can objectively define subgroups especially vulnerable to the adverse effects of unhealthy dietary habits and, thereby, help to target dietary interventions to those who benefit the most.

Students

Isabelle Dombeck, MSc student

Data-driven dietary precision prevention

The basis of precision nutrition approaches is a solid understanding of the metabolic processes that connect dietary habits to chronic disease risk. We explore metabolomics, lipidomics, glycomics, proteomics, and microbiome metagenomics data data in dietary intervention trials and prospective cohort studies to elucidate these metabolic processes.

Methodologically, we use machine learning and network analysis to generate hypotheses, which we validate in causal inference models and de novo intervention trials. We are especially interested in the metabolic effects of dietary macronutrient composition and quality, different meat types, plant-based foods, and complex dietary patterns such as the Nordic and Mediterranean diets.

In addition, we use powerful prospective human population studies to establish connections between these diet-sensitive molecular traits and long-term disease risk (especially, diabetes and cardiovascular diseases) and preclinical pathophysiological traits (for example, inflammatory or atherosclerotic markers). The integration of dietary data, -omics approaches, and long-term disease risk across a large data base of observational and intervention studies provides insight into the biological processes that link diet to chronic disease risk.

Moreover, this approach allows us to examine subgroups with differential metabolic responses and how such differences affect the relationship between dietary behaviors and chronic disease risk. In the context of dietary cardiometabolic disease prevention, we aim to establish the biological grounds and provide novel biomarkers for precision nutrition approaches.