Nutrition and Genomics: Issues of Ethics, Law, Regulation and Communication

NUTRITION AND GENOMICS

Academic Press

Chapter One

Jose M. Ordovas and E. Shyong Tai

OUTLINE

Summary 2 Introduction 2 Genes or environment? Limitations of the traditional approach to disease risk assessment 3 Cardiovascular risk factors 4 Gene–Smoking Interactions 4 Gene–Alcohol Interactions 5 Gene–Physical Activity Interactions 10 Gene–Diet Interactions 10 Statistical Methods for gene–environment interactions 15 Personalized nutrition and the consumer 18 Summary 19 References 19

SUMMARY

This chapter examines the reasons for studying gene–environment interactions and evaluates recent reports of interactions between genes and environmental modulators in relation to cardiovascular disease and its common risk factors. Recent studies focusing on smoking, alcohol, physical activity and coffee are all observational and include relatively large sample sizes. They tend to examine a single gene and fail to address interactions with other genes as well as other correlated environmental factors. Studies examining gene–diet interactions include both observational and interventional designs, and are of smaller scale, especially those including dietary interventions. Among the reported gene–diet interactions, it is important to highlight the strengthening evidence for APOA5 as a major gene involved in triglyceride metabolism and modulated by dietary factors and the identification of APOA2 as a modulator of food intake and obesity risk. This chapter concludes that, overall, the study of gene–environment interactions is an active and much needed area of research. While technical barriers in genetic studies are being quickly overcome, the inclusion of comprehensive and reliable environmental information represents a significant shortcoming to genetic studies. Progress depends on larger study populations being included and also more comprehensive, standardized and precise approaches to capture environmental information.

INTRODUCTION

After more than two decades of great expectations but few deliverables, the field of genetics related to common and complex disorders has made remarkable progress towards the identification of novel loci and genetic variants associated with these diseases. This has been possible thanks to the combination of more robust experimental approaches, including large population studies, with the availability of high density genotyping (>1 million single nucleotide polymorphisms (SNPs)). At the time of writing, there have been both consolidation of some of the traditional candidate genes, especially in the area of lipid metabolism, and, more exciting, identification of new lipid-related loci. These findings will provide us with a more complete understanding of the metabolic landscape and new insights into the pathogenesis of disease (Smith, 2007; Zeggini and McCarthy, 2007). The search is far from over, however, and for the newly discovered and for well-known candidate genes, current knowledge needs to be augmented by using deep re-sequencing and phenotyping of individuals carrying functional variants at these loci to understand the pathways and metabolic fluxes affected by these genetic variants and to provide greater insight into the physiologic basis of disease (Tracy, 2008). Based on current knowledge, however, many of the observed gene effects will not be insulated from environmental modulation. Therefore, there is a compelling need to further the initial association studies with well-designed investigation of gene–environment interactions.

GENES OR ENVIRONMENT? LIMITATIONS OF THE TRADITIONAL APPROACH TO DISEASE RISK ASSESSMENT

From an epidemiologic perspective, studies of genetic and environmental factors will continue to underestimate the population-attributable risk associated with either genetic or environmental factors. In fact, consideration of the joint effects of genetic and environmental factors strengthens their associations with disease, permitting the identification of risk factors that have small marginal effects. Even the best well established genetic markers for common traits show inter-population differences. For example, the recently identified fat mass and obesity-associated (FTO) gene has been heralded as the most solid locus for obesity risk. Yet there are conflicting reports of lack of association in African Americans or Han Chinese (Li et al., 2008). It remains unclear whether these are due to genetic differences between the different populations, or whether a gene–environment interaction may be masking the effect in these other ethnic groups. Findings from a Danish population, for example, indicate that physical activity may attenuate the effects of the FTO genetic variants in support of gene–environment interactions (Andreasen et al., 2008).

Reliably capturing environmental measures and the complexity of the dietary 'environment' present major difficulties in studying gene–environment interactions. Methods to capture dietary information from observational studies have been criticized for years for a lack of accuracy, precision and objectivity. Moreover, foods are very complicated mixtures and we may attribute an observed effect to a specific nutrient because we know about it but, in reality, it may be due to another component of the food that we may not know or pay attention to. For example, coffee consumption shows a well-replicated association with the risk of type 2 diabetes mellitus (van Dam and Hu, 2005; Pereira et al., 2006). But coffee is a complex mixture of compounds and it is common to equate coffee with caffeine. Still, the specific compound in coffee that produces this effect is unclear. In fact, caffeine may not be important after all, since the association is also seen with decaffeinated coffee (van Dam et al., 2006). Therefore, integration of genetic variability with gene expression studies will pinpoint pathways that the environmental exposures may act through and will provide some guidance as to the specific environmental components that warrant further investigation.

From a public health perspective, it has been suggested that the identification of genetic variants that encode susceptibility to disease could be used in risk algorithms to identify individuals at high risk of disease. The identification of gene–environment interactions may suggest specific interventions that may attenuate the risk in these individuals. Taken to an extreme, it has been suggested that these studies could lead to individualized health plans based on a person's genetic make-up (Subbiah, 2007). In this chapter, we summarize current knowledge related to gene–environment interactions as they pertain to cardiovascular disease risk factors, particularly those related to metabolic phenotypes. In addition, we raise some of the issues that need to be addressed to advance this field of research and to develop applications for the public.

CARDIOVASCULAR RISK FACTORS

The scientific literature is heavily populated with papers reporting cardiovascular risk factors. The latest catalog published over one decade ago listed 177 of them with many of them falling in the categories of 'Nutrition- Related' and 'Environmental' (Omura et al., 1996). Many of the reported risk factors are rather questionable, however. Updating this catalog today would probably add a few hundred more to the list. Besides diet, the best characterized environmental risk factors include smoking, inadequate physical activity, alcohol and, more recently, coffee drinking (which, given its popularity and widespread use, has received increased attention as a modifier of cardiovascular disease risk) (Campos and Baylin, 2007). Those common and well established behavioral risk factors are the focus of this section.

Gene–Smoking Interactions

The study of interactions between genetic factors and smoking has been an active area of research primarily in the fields of cancer and neurodegenerative diseases (Wang and Wang, 2005; Elbaz et al., 2007), but it also caught the early attention of cardiovascular researchers (Kondo et al., 1989) and a substantial body of evidence has accumulated during the last two decades, as summarized by recent reviews (Talmud, 2007). Considering what we know about the risk associated with tobacco smoking, it is obvious that all the reports are supported by observational data and there are no randomized intervention studies. Of the behavioral factors contemplated in this section, tobacco smoking may be the most reliable in terms of validity of reporting. Moreover, it is a variable most epidemiological studies collect. Therefore, studies reporting gene–tobacco smoking interactions tend to be large and probably have adequate statistical power to examine single gene–single factor interactions. This is still far from ideal as no single study can yet fully address the complex interactions involving multiple genes and environmental factors. Genes currently under examination span a variety of metabolic pathways, including the obvious ones involved in drug metabolism and detoxification, those involved in lipid traits known to be modified by smoking (Gambier et al., 2006; Goldenberg et al., 2007; Cornelis et al., 2007b; Manfredi et al., 2007) as well as others involved in a variety of more remotely connected metabolic functions (Lee et al., 2006; Saijo et al., 2007; Jang et al., 2007; Stephens et al., 2008). In addition, the arrival of genome-wide association studies has allowed the identification of chromosomal regions of interest (North et al., 2007) for which no candidate genes have yet been identified.

(Continues...)

---

Excerpted from NUTRITION AND GENOMICS Copyright © 2009 by Elsevier Inc.. Excerpted by permission of Academic Press. All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.

---