Nutrigenetics and nutrigenomics: viewpoints on the current status and applications in nutrition research and practice

Abstract

Nutrigenetics and nutrigenomics hold much promise for providing better nutritional advice to the public generally, genetic subgroups and individuals. Because nutrigenetics and nutrigenomics require a deep understanding of nutrition, genetics and biochemistry and ever new 'omic' technologies, it is often difficult, even for educated professionals, to appreciate their relevance to the practice of preventive approaches for optimising health, delaying onset of disease and diminishing its severity. This review discusses (i) the basic concepts, technical terms and technology involved in nutrigenetics and nutrigenomics; (ii) how this emerging knowledge can be applied to optimise health, prevent and treat diseases; (iii) how to read, understand and interpret nutrigenetic and nutrigenomic research results, and (iv) how this knowledge may potentially transform nutrition and dietetic practice, and the implications of such a transformation. This is in effect an up-to-date overview of the various aspects of nutrigenetics and nutrigenomics relevant to health practitioners who are seeking a better understanding of this new frontier in nutrition research and its potential application to dietetic practice.

Copyright © 2011 S. Karger AG, Basel.

Figures

Fig. 1

Apoptosis and proliferation in colorectal cancer cell lines in response to butyrate [95]. Colorectal cancer cell lines (HT29, SW480, HCT116, Caco2, Lim1215 and T84) were treated with increasing concentrations of butyrate for 48 h. In all cases, butyrate was found to induce apoptosis and inhibit the proliferation of cells, with the exception of the T84 cell line. In the T84 cell line, butyrate induced minimal/no apoptosis and had minimal effect on proliferation. * p

Fig. 2

Correlation between gene and protein expression when HT29 cells were treated with butyrate for 48 h. After 48-hour butyrate treatment, 139 proteins were found to be differentially expressed. A direct comparison between the gene (mRNA transcript) and protein expression of these 139 proteins yielded a correlation of 0.48 (p = 0.00016). Proteomic data were collected and analysed as described [95,96]. Gene expression analysis was performed using Affymetrix arrays (Human Exon 1.0ST arrays) according to manufacturer's protocol (Affymetrix, Santa Clara, Calif., USA). Correlation analysis between protein and transcript expression was performed using the R statistical package.