Interplay between diet and genetic susceptibility in obesity and related traits

Abstract

The incidence of obesity has been rapidly increasing, and this condition has become a major public health threat. A substantial shift in environmental factors and lifestyle, such as unhealthy diet, is among the major driving forces of the global obesity pandemic. Longitudinal studies and randomized intervention trials have shown that genetic susceptibility to obesity may interact with dietary factors in relation to the body mass index and risk of obesity. This review summarized data from recent longitudinal studies and intervention studies on variations and diets and discussed the challenges and future prospects related to this area and public health implications.

Keywords

diet / genetic susceptibility / obesity / interaction

Introduction

Obesity and related metabolic diseases, such as type 2 diabetes and cardiovascular disease, have rapidly increased. The increasing epidemic of obesity is substantially attributed to environmental susceptibility to weight gain, such as unhealthy diets. As one of the main efforts against obesity and its complications, emerging dietary interventions have been conducted to improve weight loss and long-term weight maintenance [¹,²]. Although several diets generally show no significant differences in their effectiveness on weight loss, considerable inter-individual heterogeneity has been identified in participants’ response, and genetic background may partly account for such variability [³–⁵]. With revolutionary advancements in genomic technologies, a large body of genome-wide association studies (GWAS) have identified numerous obesity-associated genetic variants [⁶]. Growing data from longitudinal studies and randomized intervention trials have shown that genetic variations may interact with dietary factors in relation to obesity and related metabolic diseases.

Gene–environment rationale

Gene–environment interaction studies aim to examine how genetic and environmental factors jointly influence the trait of interest [⁷]. In this context, genes and environmental exposures may contribute to the developing risk of a condition in the same individual with genetic predisposition affecting the sensitivity to environmental exposures.

The genetic predisposition to obesity has its origins in our evolutionary history, although the obesity pandemic in the past was likely due to dramatic environmental changes. Several hypotheses have been proposed to explain the obesity pandemic in modern society and provided insights into gene–environment interaction within the understanding of human evolution. The “thrifty genotype” hypothesis explains that promoting efficient fat deposition was beneficial to survival during famine in early times, but it has become disadvantageous in modern societies because of the prepared fat deposition for famine that has yet to occur [⁸]. According to this hypothesis, individuals who carry “thrifty genes” are more susceptible to obesity under the same environmental exposure compared with those who do not carry these genes. An alternative perspective has been proposed, namely, “drifty gene” hypothesis, which elaborates that genes favoring obesity have not been positively selected but have rather been subjected to random drifting because of an absence of selection [⁹]. Nevertheless, further studies are needed to validate these theories and improve the understanding of gene–environment interactions.

Evidence from observational studies

A credible gene–environment interaction requires successful replications and biological plausibility [⁷], which increase the difficulty in detecting interactions. Nevertheless, several large-scale prospective studies with replication have sprung up in the burgeoning area of gene–environment interaction (Table 1).

An increase in the consumption of sugar-sweetened beverages in the past decades have paralleled the rise in obesity prevalence. Among three US cohorts, interactions between genetic susceptibility to obesity and sugar-sweetened beverages in relation to BMI and obesity were examined, and investigators found that genetic associations with increased BMI and obesity risk are pronounced with high intake of sugar-sweetened beverages [¹⁰]. Similar findings were observed in a recent study on Swedish adults [¹¹].

In addition to sugar-sweetened beverages, coffee is among the most widely consumed beverages around the world. Regular coffee consumption has been associated with a reduced risk of several obesity-related diseases, such as type 2 diabetes, but the association between coffee consumption and obesity are not entirely consistent. A study on three US cohorts has found that high habitual coffee consumption may attenuate the genetic association with increased BMI and obesity risk [¹²].

The consumption of high-fat food may be an indicator of an unhealthy diet. In a study on three US cohorts, individuals with the APOA2 CC genotype seem highly susceptible to increased BMI and obesity when they consume a high-saturated fat diet [¹³]. Foods become rich in fat after they are fried, and eating fried foods may result in high intake of high-fat foods. In a study on three US cohorts, a high frequency of fried food intake may amplify the genetic association with high BMI and obesity risk [¹⁴].

One previous study on 18 European cohorts tested whether a composite score representing healthy diet, which was calculated on the basis of whole grains, fish, fruits, vegetables, nuts/seeds, red/processed meats, sweets, sugar-sweetened beverages, and fried potatoes, modifies the associations of genetic variations, which were assessed in terms of the genetic risk scores of 32 BMI- and 14 waist–hip ratio-associated single nucleotide polymorphisms, with obesity traits [¹⁵]. Although the magnitudes of the reported interactions were small, this study suggested that the associations between genetic predisposition and obesity traits were strong with a healthy diet. One study on two US cohorts examined the interaction between adherence to healthy dietary patterns and genetic predisposition to obesity in relation to long-term weight change. The authors found that the association between a healthy diet, which was assessed by the Alternate Healthy Eating Index 2010 and Dietary Approach to Stop Hypertension, and long-term weight loss is strong in participants with a great genetic predisposition to obesity [¹⁶].

Evidence obtained in the US and Europe has suggested that genetic variants and particular dietary factors may interplay in relation to BMI and obesity. Adiposity may interact with genetic susceptibility on nonalcoholic fatty liver disease (NAFLD) and dyslipidemia, which are frequently associated with obesity and excessive calorie intake. Adiposity remarkably amplifies the effect of the PNPLA3 I148M rs738409 variant associated with NAFLD [¹⁷], and this variant interacts with overweight and dietary intakes on fasting triglyceride levels [¹⁸].

The advantages of testing gene–diet interactions in observational studies include a large sample size, long follow-up periods, and generalizability of findings to general populations; however, results may be biased by confounding and reverse causation.

Evidence from diet interventions

Evidence-based prevention and intervention rely mainly on the statistical interpretation of data from randomized clinical trials in which the potential confounding effects are minimized. Therefore, gene–diet interaction in diet intervention trials on weight loss should be detected. Table 2 summarizes the studies on gene–diet interaction in randomized diet intervention trials published since 2011 [19‒39].

The trial on Preventing Overweight Using Novel Dietary Strategies (Pounds Lost) comprised 811 overweight or obese adults who were assigned to 1 of 4 weight-loss diets varying in macronutrient contents for 2 years [⁴⁰]. Investigators performed a series of analyses on gene–diet interactions in the POUNDS Lost trial [¹⁹,²¹,²²,²⁴,²⁵,²⁷,²⁸,³³–³⁹]. For example, the FTO genetic variants, which are among the main culprits in determining genetic susceptibility to obesity and are highly expressed in the central nervous system, have been found to modify the effect of dietary protein intake or dietary fat intake on a series of obesity-related traits, such as weight loss, changes in body composition and fat distribution, and improvement of insulin resistance [²²,³⁷]. Insulin receptor substrate 1 (IRS1) gene has been associated with insulin resistance and hyperinsulinemia, and genetic variants in IRS1 significantly interact with dietary fat intake in relation to weight loss, improvement in insulin resistance, and the management of the metabolic syndrome components in this trial [¹⁹,³³].

Other studies have examined gene–diet interactions in randomized intervention trials [²⁰,²³,²⁶,²⁹–³²]. The transcription factor 7-like 2 (TCF7L2) genetic variant rs7903146 interacts with dietary fiber intake in relation to weight loss in the Tübingen Lifestyle Intervention Program, a trial consisting of exercise and diet intervention with decreased intake of fat and increased intake of fibers (>15 g of fiber per 1000 kcal) [²³]. In the Diabetes Prevention Program, Pan et al. [³¹] found that the minor allele of MC4R rs17066866 is associated with less weight loss during 6-month and 2-year in the lifestyle intervention group that receives less fat and calories and exercises for a total of 150 min a week but not in the placebo group. However, identifying the confounding factors from interactions between lifestyle components (diet or exercise) and genotypes is difficult.

These findings from randomized intervention trials suggest that weight loss and related metabolic improvement can be conditional on different genetic backgrounds in response to diet interventions. One unique advantage of studies applying diet intervention trials to test gene–diet interactions is that they may provide direct evidence to instruct genetic-targeted diet modifications in future public health practice. However, most of existing diet intervention trials are relatively small in size, thereby limiting the power for the detection of moderate gene–diet interactions [⁴], and replication remains a major challenge in gene–diet interaction analyses in randomized trials.

Challenges and future prospects

Current gene–diet interaction findings clearly show that genes and diets unlikely separately affect obesity and related metabolic traits. Individuals with high genetic predisposition may reveal increased susceptibility to adverse health outcomes in response to unhealthy diets. Alternatively, healthy diets may counteract the negative effects associated with certain genetic predisposition.

Remarkable challenges still exist in this field. The sample size required to detect a multiplicative interaction effect of two variables is at least four times the sample size that is needed to evaluate the main effect of each of the variables. Unless the interactions are strong, the occurrence of false-negative findings about such interactions is a concern in individual studies [⁷]. The replication of findings is necessary to interpret gene–diet interactions. Therefore, collaborative individual well-designed studies should be performed to increase the power of analyses and search consistent results across different studies. New statistical approaches are required to establish biologically functional relevance for the observed statistically significant gene–diet interactions. The majority of current gene–diet interaction analyses apply the identified genetic variables from the GWAS. Emerging genome-wide approaches facilitate studies on mining interactions in genome-wide data and exploring biological pathways [⁴¹].

Obesity and related metabolic diseases can be prevented by adhering healthy lifestyle and diet habits. Gene–diet interaction studies help accelerate efficient diet interventions in a personalized manner, which is different from the traditional one-size-fits-all approach [⁴²]. Although genomic information is not generally applied to predict diseases, it can be used with other risk factors to screen and classify high-risk populations to tailored interventions.

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