The rising prevalence of complex disease suggests that alterations to the human environment are increasing the proportion of individuals who exceed a threshold of liability. This might be due either to a global shift in the population mean of underlying contributing traits, or to increased variance of such underlying endophenotypes (such as body weight). To contrast these quantitative genetic mechanisms with respect to weight gain, we have quantified the effect of dietary perturbation on metabolic traits in 146 inbred lines of
Drosophila melanogaster and show that genotype-by-diet interactions are pervasive. For several metabolic traits, genotype-by-diet interactions account for far more variance (between 12 and 17%) than diet alone (1–2%), and in some cases have as large an effect as genetics alone (11–23%). Substantial dew point effects were also observed. Larval foraging behavior was found to be a quantitative trait exhibiting significant genetic variation for path length (
P = 0.0004). Metabolic and fitness traits exhibited a complex correlation structure, and there was evidence of selection minimizing weight under laboratory conditions. In addition, a high fat diet significantly increases population variance in metabolic phenotypes, suggesting decreased robustness in the face of dietary perturbation. Changes in metabolic trait mean and variance in response to diet indicates that shifts in both population mean and variance in underlying traits could contribute to increases in complex disease.METABOLIC syndrome (MetS) is a complex disease that is promoted by interactions between genetic and environmental effects (
O''Rahilly and Farooqi 2006), and seems to be increasing in prevalence in response to a transition from traditional toward Westernized lifestyles (
Lee et al. 2004;
Schulz et al. 2006). MetS is a constellation of metabolic symptoms including insulin resistance, abdominal obesity, and dyslipidemia, and is predictive of cardiovascular disease and type-2 diabetes (
Alberti et al. 2006). The condition has reached epidemic proportions in many Westernized countries (
Isomaa et al. 2001;
Ford and Giles 2003;
Lorenzo et al. 2003;
Alberti et al. 2006). Not all individuals are susceptible to the deleterious effects of a Westernized lifestyle, but some individuals are very sensitive to the effects of their environment (
Schulz et al. 2006).We argued previously that environmental perturbation contributes to the recent increases in chronic disease in Westernized societies by exposing cryptic genetic variation, a phenomenon that may be particularly evident in metabolic syndrome (
Gibson 2009). Increases in complex disease after an environmental shift can be caused by both a change in the population mean or increased variance in a predisposing underlying trait, or endophenotype, causing a larger portion of the population to exceed a disease threshold (
Gibson and Reed 2008). Endophenotypes can be molecular, such as rate of uptake of glucose into cells, but also include visible disease covariates, such as body mass. The transition from traditional diets and lifestyles may have perturbed our metabolic homeostasis, thereby promoting increased susceptibility to, and in turn prevalence of, obesity, hyperlipidemia, diabetes, and cardiovascular illness.The complexity of genetic and environmental interactions leads to major challenges in successful disease treatment and prevention strategies, in that it is very difficult to accurately model the relative contributions of nature and nurture to disease susceptibility in a human population. Dietary factors have been demonstrated to interact with specific genetic variants to increase the risk of metabolic disease in humans (
Corella and Ordovas 2005;
Ordovas 2006;
Corella et al. 2009;
Warodomwichit et al. 2009), but the relative contribution of overall genotype and environmental effects on human variation is difficult to determine. Modeling population level genotype-by-environment interactions using a model organism like Drosophila can compensate for the research challenges of parameter estimation in human populations.Drosophila share great homology to humans in a number of systems including central metabolism, insulin-signaling pathways, and organs responsible for physiological homoeostasis (
e.g., heart, liver, and kidney) (
Rizki 1978;
Bodmer 1995;
Nation 2002;
Rulifson et al. 2002;
Denholm et al. 2003;
Wessells et al. 2004). It has been shown that Drosophila with ablated insulin-producing neurons have elevated hemolymph trehalose levels, considered to parallel a diabetic phenotype (
Rulifson et al. 2002). Loss of insulin signaling also restores normal rhythmicity of adult heart rate in old flies (
Wessells et al. 2004), providing a link between the obesity and cardiac components of MetS. We have used 146 natural genetic isolates of
Drosophila melanogaster to model the relative contributions of genetics, diet, and other environmental effects on the MetS-like phenotypes of larval weight gain, blood sugar concentration, lipid storage, and survival. Individuals from each of these genetic lines were raised on four different diets: their normal lab food, a calorie restricted (0.75% glucose) food, a high (4%) glucose food, and a high fat diet containing (3%) coconut oil.Using this approach, we sought evidence pertaining to two major hypotheses. There are six general types of phenotypic reaction scenarios that a genetically variable population can exhibit in response to an environmental transition: (1) no phenotypic variation in response to genetic or environmental factors, (2) genetic variation in mean phenotype but no change across environments, (3) an additive change in phenotypic mean across genotypes between environments, (4) an interaction effect between genetic and environment leading to a crossing of line means, and (5) a decrease or (6) an increase in variance in the new environment (
Gibson and Vanhelden 1997). First, we considered whether the predominant source of metabolic variation within a Drosophila population is genetic, environmental, or the interaction between genetic and environmental effects. Our null was that none of these factors significantly influence weight gain or other phenotypes (scenario 1 above), but it was expected that genetic variation would be prevalent. The more fundamental issue is which of two alternate hypotheses apply: that dietary effects are essentially additive across genotypes (3) or that they are largely genotype dependent (4), possibly also with contributions of behavior and the external environment. Second, we considered whether the transition from a standard laboratory diet to a perturbing diet would change the environmental and/or genetic variance observed in the population: a decrease (5) indicating physiological limitation to the variation or an increase (6) indicating decanalization of the metabolic phenotypes due to loss of physiological buffering.
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