Genetics of weight loss: A basis for personalized obesity management

Transcriptional and epigenetic changes after dietary and surgical weight loss interventions in an animal model of obesity

BACKGROUND

Identifying determinants that can predict response to weight loss interventions is imperative for optimizing therapeutic benefit. We aimed to identify changes in DNA methylation and mRNA expression of a subset of target genes following dietary and surgical interventions in high-fat-diet (HFD)-induced obese rats.

METHODS

Forty-two adult Wistar Han male rats were divided into two groups: control rats (n = 7) and obese rats (n = 28), fed a HFD for 10 weeks (t10). Obese rats were randomly subdivided into five intervention groups (seven animals per group): (i) HFD; (ii) very-low-calorie diet (VLCD); (iii) sham surgery, and (iv) sleeve gastrectomy (SG). At week sixteen (t16), animals were sacrificed and tissue samples were collected to analyze changes in DNA methylation and mRNA expression of the selected genes.

RESULTS

By type of intervention, the surgical procedures led to the greatest weight loss. Changes in methylation and/or expression of candidate genes occurred proportionally to the effectiveness of the weight loss interventions. Leptin expression, increased sixfold in the visceral fat of the obese rats, was partially normalized after all interventions. The expression of fatty acid synthase (FASN) and monocyte chemoattractant protein 1 (MCP-1) genes, which was reduced 0.5- and 0.15-fold, respectively, in the liver tissue of obese rats, were completely normalized after weight loss interventions, particularly after surgical interventions. The upregulation of FASN and MCP-1 gene expression was accompanied by a significant reduction in promoter methylation, up to 0.5-fold decrease in the case of the FASN (all intervention groups) and a 0.8-fold decrease in the case of the MCP-1 (SG group).

CONCLUSIONS

Changes in tissue expression of specific genes involved in the pathophysiological mechanisms of obesity can be significantly attenuated following weight loss interventions, particularly surgery. Some of these genes are regulated by epigenetic mechanisms.

Bioactive dietary components-Anti-obesity effects related to energy metabolism and inflammation

Obesity is the result of the long-term energy imbalance between the excess calories consumed and the few calories expended. Reducing the intake of energy dense foods (fats, sugars), and strategies such as fasting and caloric restriction can promote body weight loss. Not only energy in terms of calories, but also the specific composition of the diet can affect the way the food is absorbed and how its energy is stored, used or dissipated. Recent research has shown that bioactive components of food, such as polyphenols and vitamins, can influence obesity and its pathologic complications such as insulin resistance, inflammation and metabolic syndrome. Individual micronutrients can influence lipid turnover but for long-term effects on weight stability, dietary patterns containing several micronutrients may be required. At the molecular level, these molecules modulate signaling and the expression of genes that are involved in the regulation of energy intake, lipid metabolism, adipogenesis into white, beige and brown adipose tissue, thermogenesis, lipotoxicity, adipo/cytokine synthesis, and inflammation. Higher concentrations of these molecules can be reached in the intestine, where they can modulate the composition and action of the microbiome. In this review, the molecular mechanisms by which bioactive compounds and vitamins modulate energy metabolism, inflammation and obesity are discussed.

A Systematic Review of Genetic Correlates of Weight Loss After Bariatric Surgery

This systematic review synthesized research evaluating the relationship between genetic predictors and weight loss after bariatric surgery. Fifty-seven studies were identified that examined single genes or genetic risk scores. Uncoupling protein (UCP) rs660339 was associated with excess weight loss after surgery in 4 of 6 studies. The most commonly assessed genes were fat mass and obesity-associated (FTO) gene (n = 10) and melanocortin-4 receptor (MC4R) (n = 14). Both were inconsistently related to weight loss. Genetic risk scores predicted weight loss in 6 of 7 studies. This evidence suggests the potential of using genetic variants and genetic risk scores to predict the amount of weight loss anticipated after bariatric surgery and identify patients who may be at risk for suboptimal weight reduction.

The Combined Effect of Polygenic Risk from FTO and ADRB2 Gene Variants, Odds of Obesity, and Post-Hipcref Diet Differences

BACKGROUND

Computing polygenic risk scores (PRS) to predict the degree of risk for obesity may contribute to weight management programs strategically.

OBJECTIVES

To investigate the combined effect of FTO rs9930501, rs9930506, and rs9932754 and ADRB2 rs1042713 and rs1042714 using PRS on (1) the odds of obesity and (2) post-intervention differences in dietary, anthropometric, and cardiometabolic parameters in response to high-protein calorie-restricted, high-vitamin E, high-fiber (Hipcref) diet intervention in Malaysian adults.

METHODS

Both a cross-sectional study (n = 178) and a randomized controlled trial (RCT) (n = 128) were conducted to test the aforementioned objectives. PRS was computed as the weighted sum of the risk alleles possessed by each individual participant. Participants were stratified into first (PRS 0-0.64), second (PRS 0.65-3.59), and third (PRS 3.60-8.18) tertiles.

RESULTS

The third tertile of PRS was associated with significantly higher odds of obesity: 2.29 (95% CI = 1.11-4.72, adjusted p = 0.025) compared to the first tertile. Indians (3.9 ± 0.3) had significantly higher PRS compared to Chinese (2.1 ± 0.4) (p = 0.010). In the RCT, a greater reduction in high-sensitivity C-reactive protein (hsCRP) levels was found in second and third tertiles after Hipcref diet intervention compared to the control diet (p interaction = 0.048).

CONCLUSION

Higher PRS was significantly associated with increased odds of obesity. Individuals with higher PRS had a significantly greater reduction in hsCRP levels after Hipcref diet compared to the control diet.

Modeling of an integrative prototype based on genetic, phenotypic, and environmental information for personalized prescription of energy-restricted diets in overweight/obese subjects

BACKGROUND

Interindividual variability in weight loss and metabolic responses depends upon interactions between genetic, phenotypic, and environmental factors.

OBJECTIVE

We aimed to model an integrative (nutri) prototype based on genetic, phenotypic, and environmental information for the personalized prescription of energy-restricted diets with different macronutrient distribution.

METHODS

A 4-mo nutritional intervention was conducted in 305 overweight/obese volunteers involving 2 energy-restricted diets (30% restriction) with different macronutrient distribution: a moderately high-protein (MHP) diet (30% proteins, 30% lipids, and 40% carbohydrates) and a low-fat (LF) diet (22% lipids, 18% proteins, and 60% carbohydrates). A total of 201 subjects with good dietary adherence were genotyped for 95 single nucleotide polymorphisms (SNPs) related to energy homeostasis. Genotyping was performed by targeted next-generation sequencing. Two weighted genetic risk scores for the MHP (wGRS1) and LF (wGRS2) diets were computed using statistically relevant SNPs. Multiple linear regression models were performed to estimate percentage BMI decrease depending on the dietary macronutrient composition.

RESULTS

After energy restriction, both the MHP and LF diets induced similar significant decreases in adiposity, body composition, and blood pressure, and improved the lipid profile. Furthermore, statistically relevant differences in anthropometric and biochemical markers depending on sex and age were found. BMI decrease in the MHP diet was best predicted at ∼28% (optimism-corrected adjusted R2 = 0.279) by wGRS1 and age, whereas wGRS2 and baseline energy intake explained ∼29% (optimism-corrected adjusted R2 = 0.287) of BMI decrease variability in the LF diet. The incorporation of these predictive models into a decision algorithm allowed the personalized prescription of the MHP and LF diets.

CONCLUSIONS

Different genetic, phenotypic, and exogenous factors predict BMI decreases depending on the administration of a hypocaloric MHP diet or an LF diet. This holistic approach may help to personalize dietary advice for the management of excessive body weight using precision nutrition variables.This trial was registered at clinicaltrials.gov as NCT02737267.

Multi-Target Drugs Against Metabolic Disorders

BACKGROUND

Metabolic disorders are a major cause of illness and death worldwide. Metabolism is the process by which the body makes energy from proteins, carbohydrates, and fats; chemically breaking these down in the digestive system towards sugars and acids which constitute the human body's fuel for immediate use, or to store in body tissues, such as the liver, muscles, and body fat.

OBJECTIVE

The efficiency of treatments for multifactor diseases has not been proved. It is accepted that to manage multifactor diseases, simultaneous modulation of multiple targets is required leading to the development of new strategies for discovery and development of drugs against metabolic disorders.

METHODS

In silico studies are increasingly being applied by researchers due to reductions in time and costs for new prototype synthesis; obtaining substances that present better therapeutic profiles.

DISCUSSION

In the present work, in addition to discussing multi-target drug discovery and the contributions of in silico studies to rational bioactive planning against metabolic disorders such as diabetes and obesity, we review various in silico study contributions to the fight against human metabolic pathologies.

CONCLUSION

In this review, we have presented various studies involved in the treatment of metabolic disorders; attempting to obtain hybrid molecules with pharmacological activity against various targets and expanding biological activity by using different mechanisms of action to treat a single pathology.

Models Integrating Genetic and Lifestyle Interactions on Two Adiposity Phenotypes for Personalized Prescription of Energy-Restricted Diets With Different Macronutrient Distribution

Aim: To analyze the influence of genetics and interactions with environmental factors on adiposity outcomes [waist circumference reduction (WCR) and total body fat loss (TFATL)] in response to energy-restricted diets in subjects with excessive body weight.

Materials and Methods: Two hypocaloric diets (30% energy restriction) were prescribed to overweight/obese subjects during 16 weeks, which had different targeted macronutrient distribution: a low-fat (LF) diet (22% energy from lipids) and a moderately high-protein (MHP) diet (30% energy from proteins). At the end of the trial, a total of 201 participants (LF diet = 105; MHP diet = 96) who presented good/regular dietary adherence were genotyped for 95 single nucleotide polymorphisms (SNPs) previously associated with weight loss through next-generation sequencing from oral samples. Four unweighted (uGRS) and four weighted (wGRS) genetic risk scores were computed using statistically relevant SNPs for each outcome by diet. Predictions of WCR and TFATL by diet were modeled through recognized multiple linear regression models including genetic (single SNPs, uGRS, and wGRS), phenotypic (age, sex, and WC, or TFAT at baseline), and environment variables (physical activity level and energy intake at baselines) as well as eventual interactions between genes and environmental factors.

Results: Overall, 26 different SNPs were associated with differential adiposity outcomes, 9 with WCR and 17 with TFATL, most of which were specific for each dietary intervention. In addition to conventional predictors (age, sex, lifestyle, and adiposity status at baseline), the calculated uGRS/wGRS and interactions with environmental factors were major contributors of adiposity responses. Thus, variances in TFATL-LF diet, TFATL-MHP diet, WCR-LF diet, and WCR-MHP diet were predicted by approximately 38% (optimism-corrected adj. R² = 0.3792), 32% (optimism-corrected adj. R² = 0.3208), 22% (optimism-corrected adj. R² = 0.2208), and 21% (optimism-corrected adj. R² = 0.2081), respectively.

Conclusions: Different genetic variants and interactions with environmental factors modulate the differential individual responses to MHP and LF dietary interventions. These insights and models may help to optimize personalized nutritional strategies for modeling the prevention and management of excessive adiposity through precision nutrition approaches taking into account not only genetic information but also the lifestyle/clinical factors that interplay in addition to age and sex.

PPARG2 Pro12Ala polymorphism influences body composition changes in severely obese patients consuming extra virgin olive oil: a randomized clinical trial

BACKGROUND

Previous intervention studies have reported the association of the PPARG2 Pro12Ala (rs1801282) and IL6 -174G > C (rs1800795) polymorphisms with weight loss; however, their results are inconsistent. We aimed to investigate the effect of the PPARG2 Pro12Ala and IL6 -174G > C polymorphisms on body weight, body composition and metabolic parameters after a 12-week nutritional intervention with a traditional Brazilian diet and extra virgin olive oil supplementation in severely obese patients.

METHODS

A total of 149 severely obese individuals [body mass index (BMI) ≥ 35 kg/m2] were randomized into three 12-week nutritional intervention groups - the extra virgin olive oil supplementation (OO) group (n = 50), the traditional Brazilian diet (DieTBra) group (n = 49), and the DieTBra plus extra virgin olive oil supplementation (DieTBra+OO) group (n = 50). Anthropometric measurements, body composition, metabolic parameters, physical activity practise and dietary intake were assessed. The associations were tested using generalized linear models adjusted for confounders.

RESULTS

The PPARG2 Pro12Ala polymorphism influenced body composition changes. Ala carriers in the intervention groups with extra virgin olive oil supplementation had greater reductions in the percentage of body fat (%BF) (OO: p = 0.049, DietBra+OO: p = 0.004) and greater increases in both fat-free mass (FFM) (OO: p = 0.020, DieTBra: p = 0.007) and lean mass (LM) (OO: p = 0.020, DieTBra+OO: p = 0.007) than did ProPro homozygotes. No association was found for the IL6 -174G > C polymorphism.

CONCLUSIONS

Extra virgin olive oil intake may modulate favourable body composition changes, promoting a decrease in the %BF and increases in the LM and FFM of severely obese individuals, even without weight loss, in the presence of the Ala allele of the Pro12Ala polymorphism.

TRIAL REGISTRATION

Registered under ClinicalTrials.gov Identifier No. NCT02463435.

Lifestyle genomics and the metabolic syndrome: A review of genetic variants that influence response to diet and exercise interventions

Metabolic syndrome (MetS) comprises a cluster of risk factors that includes central obesity, dyslipidemia, impaired glucose homeostasis and hypertension. Individuals with MetS have elevated risk of type 2 diabetes and cardiovascular disease; thus placing significant burdens on social and healthcare systems. Lifestyle interventions (comprised of diet, exercise or a combination of both) are routinely recommended as the first line of treatment for MetS. Only a proportion of people respond, and it has been assumed that psychological and social aspects primarily account for these differences. However, the etiology of MetS is multifactorial and stems, in part, on a person's genetic make-up. Numerous single nucleotide polymorphisms (SNPs) are associated with the various components of MetS, and several of these SNPs have been shown to modify a person's response to lifestyle interventions. Consequently, genetic variants can influence the extent to which a person responds to changes in diet and/or exercise. The goal of this review is to highlight SNPs reported to influence the magnitude of change in body weight, dyslipidemia, glucose homeostasis and blood pressure during lifestyle interventions aimed at improving MetS components. Knowledge regarding these genetic variants and their ability to modulate a person's response will provide additional context for improving the effectiveness of personalized lifestyle interventions that aim to reduce the risks associated with MetS.

Analysis of Dietary Pattern Impact on Weight Status for Personalised Nutrition through On-Line Advice: The Food4Me Spanish Cohort

Obesity prevalence is increasing. The management of this condition requires a detailed analysis of the global risk factors in order to develop personalised advice. This study is aimed to identify current dietary patterns and habits in Spanish population interested in personalised nutrition and investigate associations with weight status. Self-reported dietary and anthropometrical data from the Spanish participants in the Food4Me study, were used in a multidimensional exploratory analysis to define specific dietary profiles. Two opposing factors were obtained according to food groups’ intake: Factor 1 characterised by a more frequent consumption of traditionally considered unhealthy foods; and Factor 2, where the consumption of “Mediterranean diet” foods was prevalent. Factor 1 showed a direct relationship with BMI (β = 0.226; r² = 0.259; p < 0.001), while the association with Factor 2 was inverse (β = −0.037; r² = 0.230; p = 0.348). A total of four categories were defined (Prudent, Healthy, Western, and Compensatory) through classification of the sample in higher or lower adherence to each factor and combining the possibilities. Western and Compensatory dietary patterns, which were characterized by high-density foods consumption, showed positive associations with overweight prevalence. Further analysis showed that prevention of overweight must focus on limiting the intake of known deleterious foods rather than exclusively enhance healthy products.

Future Perspectives of Personalized Weight Loss Interventions Based on Nutrigenetic, Epigenetic, and Metagenomic Data

As obesity has become a major global public health challenge, a large number of studies have analyzed different strategies aimed at inducing a negative energy balance and, consequently, body weight loss. However, most existing weight loss programs are generally unsuccessful, so several interventions have been carried out to identify physiologic and behavioral factors concerning this variability in order to implement more personalized treatment. Nowadays, an individualized approach is being proposed through so-called personalized nutrition, whereby not only the phenotype but also the genotype is used for customized nutrition treatment. Regarding body weight regulation, ∼70 polymorphisms have been identified in or near genes related to energy expenditure, appetite, adipogenesis, insulin resistance, and lipid metabolism. Although personalized nutrition refers mainly to genetic makeup, recent advances in the investigation of the epigenome and the microbiome open the door to implement more personalized recommendations for body weight management. In this context, recent studies have demonstrated the existence of several epigenetic markers that may modify gene expression and could be involved in the outcome of weight loss interventions. Moreover, different studies have shown that dietary interventions could affect the composition of gut microbiota and have an impact on body weight. The integration of nutrigenetic, epigenetic, and metagenomic data may lead to the design of more personalized dietary treatments to prevent chronic diseases and to optimize the individual's response to dietary interventions.