Feeding Your Genes

Each of us experiences a postprandial glow within the first hour following a meal. This reflects, in part, a transient hemodynamic shift from peripheral circulation to tissues involved in digestive processes and the release of “satisfaction” peptides and carbohydrates that affect brain function. Along with the body’s fed circulatory priorities, there is a well-orchestrated genetic expression that assures adequate digestion, minimal enteric and systemic inflammation, and critical nutrient distribution. Emerging research suggests that the extent of these processes and involvement of the genetic network, and the normal mammalian circadian rhythm controlled by the suprachiasmatic nucleus of the anterior hypothalamus, depend on our fed and fasting state and the kinds of foods consumed. Two obvious questions are: 1) Does the fed-fasting state at mealtime modulate gene expression and regulate energy expenditure? and 2) Does gene expression during these metabolic states influence food selection?

Our molecular clock and circadian rhythm is affected by clock genes and their transcription factors. Polymorphisms of clock genes, at least within animal models, can lead to impaired glucose tolerance and insulin resistance and contribute to obesity and perturbate fatty acid metabolism (Garaulet, M. et al., 2009). The rhythmic impact of clock genes, Per1 and Per2, affect circadian activity in the hypothalamus and in peripheral tissues. For example, human colonic motility is typically greater during daylight than at night (Hoogerwerf, W.A. et al., 2009). The stooling process involves rhythmic smooth muscle contractility regulated by clock genes and the presence of neuronal nitric oxide synthase. Colonic muscle contractility is also influenced by gut microflora profile, an array of neuropeptides, several peripheral peptides and select hormones, and the rate of food consumption. Altered colonic motility or distal colonic transit is often observed in obese individuals and those presenting chronic gut inflammatory conditions.

It appears that some circadian clock genes, such as Foxa2, are not only regulated differently under feeding and fasting conditions, but that there is tissue specificity, such as lipid and protein metabolism in heart and liver, at least in mice (Wolfrum, C. et al., 2004). Inactivity of this gene in the cytoplasm of hepatocytes leads to insulin resistance and hyperaccumulation of lipids in the liver, which are particularly evident in the fed state.

A recent study among Hispanic children indicated that variations in the MC4R gene may have a significant function in regulating weight through energy intake and expenditure (Cole, S.A. et al., 2009). Current estimates suggest the MC4R gene may account for nearly 6% of the observed obesity, and may be a better predisposing clinical indicator of obesity than BMI (Hotta, K. et al., 2009; Santini, F. et al., 2009). Associations between the identified 26 MC4R variants and several classic biomarkers, including monogenic severe obesity, were modest. Importantly, in human MC4R deficiency, there is an associated hyperphagia, early-onset obesity, and increased fat mass as well as hyperinsulinemia.

The expression of many genes has a time component and thus a transcriptional response, as well as associations with gender, age, ethnicity, and environment. To assess the value of this time component, a 40-person Icelandic study evaluated blood samples for more than 23,000 transcripts corresponding to more than 20,000 genes. About 40% had a significant time component or response to fasting/feeding conditions. Roughly 170 of these genes representing common characteristics of slightly more than 11,000 time-related metabolic traits had an overlap with several categories, such as wound healing, inflammation, protein kinase cascade, and regulation of signal transduction. Despite the impact of these biological processes in circadian rhythm and possible effect on circadian control, the clock gene did not seem to be diurnally regulated in peripheral tissues. It may be that this gene has a greater time-dependent impact on other tissues, including the brain (Leonardson, A.S., 2009).

Immediately following meal consumption, gene expression and blood glucose, along with diastolic blood pressure and waist circumference, presented better correlations. Typically, blood glucose is measured in the fasting state, whereas in this study, there was a better relationship between gene expression traits and blood glucose in response to feeding. Clearly, the dynamics of the gene network are significant, and the understanding of those dynamics is emerging. The implications of these dynamics on clinical intervention, drug development, personal feeding practices, and public policy will be subject to considerable discussion, particularly as the debate of causal genes for obesity ensues (Yang, X. et al., 2009).

by Roger Clemens, Dr.P.H.
Contributing Editor
Scientific Advisor, ETHorn, La Mirada, Calif.
[email protected]

by Wayne Bidlack , Ph.D.
Contributing Editor
Professor, California State Polytechnic University, Pomona 
[email protected]