Phenotypic Flexibility as Key Mechanism in Nutrition-Related Health
27 Oct 2015 --- Could we create a new generation of useful biomarkers by measuring how we adapt to changing metabolic environments? That was amongst the questions addressed by six speakers during the session on “Phenotypic Flexibility as a Key Mechanism in Nutrition-Related Health” at the 12th European Nutrition Conference FENS 2015 in Berlin.
The session was organized by ILSI Europe for the European Commission-funded project NutriTech “Application of New Technologies and Methods in Nutrition Research – The Example of Phenotypic Flexibility”. It aimed to introduce the concept of “Phenotypic Flexibility”, defined as the interplay of all relevant processes underlying metabolic adaptations (e.g. response to changes in diet or physical activity).
Dr Lydia Afman, molecular nutritionist at Wageningen University, The Netherlands, opened the session by introducing the NutriTech project and the design of its 12-week human intervention study. “NutriTech moves beyond the state-of-the-art by challenging metabolic and inflammatory homeostasis and applying the integrated technologies to assess the underlying and related cell biological and genetic mechanisms and multiple physiological processes of adaptation,” she said.
The role of classical biochemical markers in the evaluation of Phenotypic Flexibility was presented by Dr. Yoana Kiselova-Kaneva, biochemist at Medical University of Varna, Bulgaria. The impact of a reduction of 20% in caloric intake on classical biochemical and oxidative stress parameters, as well as the body’s response to glucose and mixed meal challenge tests was discussed. Calorie restriction resulted in altered phenotypic plasticity in overweight subjects as indicated by variations in lipid profile in response to the nutritional challenges and specifically long-term effects on the metabolic phenotype of healthy subjects were established. Overall, it was found the restriction significantly improved the biochemical parameters in healthy overweight individuals.
Dr. Jarlei Fiamoncini, post-doctoral fellow at Technical University of Munich, Germany answered the question ‘Are acylcarnitines in plasma markers of Phenotypic Flexibility?’ As markers of inherited metabolic disorders, plasma acylcarnitines responded quickly to the oral glucose tolerance test of the NutriTech intervention, and indicated the individual differences in glucose clearance found between volunteers. Acylcarnitines provided promising insights into the efficiency of insulin to suppress lipolysis, as well as fatty acid and amino acid oxidation. “Being products of fatty acid and amino acid degradation, acylcarnitines are optimal candidates to investigate the particularities of individual phenotypes.”, Dr. Fiamoncini concluded.
The effect of a long period of energy restriction on whole genome gene expression in human peripheral blood mononuclear cells (PBMCs) during Metabolic Challenge Tests was presented by Ms. Inge van Bussel, PhD student at Wageningen University, The Netherlands. A total number of 1247 microarrays were analysed in order to find a change towards a healthier gene expression profile and to explain how caloric restriction modified the response to metabolic challenges. Ms van Bussel pointed out that “PBMCs are easy accessible from the human body and therefore would make an excellent health-biomarker by using their gene expression changes upon energy restriction. Integration with other parameters may help to understand the impact on individual health.”
Mr. Andrianos Yiorkas and Mr. Nikman Adli Nor Hashim, PhD students at Imperial College London, United Kingdom, showed their analysis of genetic variation captured by single nucleotide polymorphisms (SNP)-genotyping array and whole exome sequencing. Thirty-three known obesity genes were screened for non-synonymous variants annotated as deleterious. The obtained results suggested that the Genetic Risk Score (GRS) had a relatively higher contribution to Body Mass Index (BMI) in subjects with lower genetic load of deleterious alleles in monogenic obesity genes.
