Training on Nutrigenetics, Personalized Nutrition, and Statistical Genetic Analysis at The University of Reading, United Kingdom

Abstract

The nutrigenetics internship at the University of Reading was mainly conducted in form of online coursework besides group discussion, seminars, and symposiums. The classes covered the topics of gene structure and regulation, gene discovery methods in genetic epidemiology, nutrigenomics and nutrigenetics, personalized nutrition, critical appraisal, an introduction to bioinformatics tools, and population genetics. In addition, as part of the training, the author learned non-lab-based statistical analysis on genetics. Several statistical approaches were studied encompassing descriptive statistics, independent samples t-test, One-Way ANOVA, Chi-square, linear and logistic regression analysis. The objective of the training is to improve knowledge and comprehension of the nutrigenetics area, as well as statistical genetics expertise in preparation for the nutrigenetics research project. The key learning author's acquired from the coursework was the global health burden on complex diseases continuously increasing even though the population follows the public health guidelines. Moreover, knowing that human genetic heterogeneity is linked to disease predisposition opens the alternative strategies of personalized nutrition. Combining all of the theories learned in the class, the author's training in statistical analysis of nutrigenetics is valuable to be able to determine the suitable statistical methodology in analyzing the given dataset using SPSS software.