Genetic risk scores for body fat distribution attenuate weight loss in women during dietary intervention

FTO genotype and body mass index reduction in childhood obesity interventions: A systematic review and meta-analysis

Numerous guidelines have called for personalized interventions to address childhood obesity. The role of fat mass and obesity-associated gene (FTO) in the risk of childhood obesity has been summarized. However, it remains unclear whether FTO could influence individual responses to obesity interventions, especially in children. To address this, we systematically reviewed 12,255 records across 10 databases/registers and included 13 lifestyle-based obesity interventions (3980 children with overweight/obesity) reporting changes in body mass index (BMI) Z-score, BMI, waist circumference, waist-to-hip ratio, and body fat percentage after interventions. These obesity-related outcomes were first compared between children carrying different FTO genotypes (rs9939609 or its proxy) and then synthesized by random-effect meta-analysis models. The results from single-group interventions showed no evidence of associations between FTO risk allele and changes in obesity-related outcomes after interventions (e.g., BMI Z-score: -0.01; 95% CI: -0.04, 0.01). The results from controlled trials showed that associations between the FTO risk allele and changes in obesity-related outcomes did not differ by intervention/control group. To conclude, the FTO risk allele might play a minor role in the response to obesity interventions among children. Future studies might pay more attention to the accumulation effect of multiple genes in the intervention process among children.

The Interaction Between Body Mass Index Genetic Risk Score and Dietary Intake on Weight Status: A Systematic Review

Background

The escalating global obesity epidemic and the emergence of personalized medicine strategies point to the pressing need to investigate the interplay between genetic risk scores (GRSs), dietary intake, and their combined impact on weight status. This systematic review synthesizes evidence from diverse studies to elucidate how dietary patterns and individual foods interact with genetic predisposition to obesity.

Methods

Literature searches were conducted in the PubMed, Embase, Science Direct, and Scopus databases until August 2023, following PRISMA guidelines. Out of 575 articles, 15 articles examining the interaction between genetic risk score for body mass index and dietary intake on weight outcomes met the inclusion criteria. All included studies were cross-sectional in design and were assessed for quality using the Newcastle‒Ottawa Scale.

Results

Unhealthy dietary intake exacerbated the genetic predisposition to obesity, evident in studies assessing Western diet, sulfur microbial diet, and individual macronutrients, including saturated fatty acids, sugar-sweetened beverages and fried foods. Conversely, adhering to healthier dietary intake mitigated the genetic predisposition to obesity, as observed in studies involving Alternative Healthy Eating Index, Alternative Mediterranean Diet, Dietary Approach to Stop Hypertension scores, healthy plant-based diets, and specific foods such as fruits, vegetables, and n-3 polyunsaturated fatty acids.

Conclusion

This is the first systematic review to explore the interaction between genetics and dietary intake in shaping obesity outcomes. The findings have implications for tailored interventions; however, more controlled clinical trials with robust designs are needed to be able to recommend personalized nutrition based on nutrition for obesity prevention and management.

In the context of the triple burden of malnutrition: A systematic review of gene-diet interactions and nutritional status

Genetic background interacts with dietary components to modulate nutritional health status. This study aimed to review the evidence for gene-diet interactions in all forms of malnutrition. A comprehensive systematic literature search was conducted through April 2021 to identify observational and intervention studies reporting the effects of gene-diet interactions in over-nutrition, under-nutrition and micronutrient status. Risk of publication bias was assessed using the Quality Criteria Checklist and a tool specifically designed for gene-diet interaction research. 167 studies from 27 populations were included. The majority of studies investigated single nucleotide polymorphisms (SNPs) in overnutrition (n = 158). Diets rich in whole grains, vegetables, fruits and low in total and saturated fats, such as Mediterranean and DASH diets, showed promising effects for reducing obesity risk among individuals who had higher genetic risk scores for obesity, particularly the risk alleles carriers of FTO rs9939609, rs1121980 and rs1421085. Other SNPs in MC4R, PPARG and APOA5 genes were also commonly studied for interaction with diet on overnutrition though findings were inconclusive. Only limited data were found related to undernutrition (n = 1) and micronutrient status (n = 9). The findings on gene-diet interactions in this review highlight the importance of personalized nutrition, and more research on undernutrition and micronutrient status is warranted.

The triglyceride-glucose index as an adiposity marker and a predictor of fat loss induced by a low-calorie diet

BACKGROUND

This study aimed to investigate the putative role of the triglyceride-glucose index (TyG index) computed as ln[TG (mg/dl) × glucose (mg/dl)/2] and derived proxies as predictors of adiposity and weight loss changes after a low-calorie diet (LCD) intervention.

METHODS

A total of 744 adult participants from the multicentre DIOGenes intervention study were prescribed a LCD (800 kcal/day) during 8 weeks. Body composition and fat content at baseline and after 8 weeks were estimated by DEXA/BIA. A multivariate analysis approach was used to estimate the difference in ΔWeight_1-2 (kg), ΔBMI_1-2 (kg/m² ) or ΔFat_1-2 (%) between the basal value (point 1) and after 8 weeks following a LCD (point 2), respectively. The TyG index at baseline (TyG₁ ), after following the LCD for 8 weeks (TyG₂ ) or the TyG index differences between both time points (ΔTyG_1-2 ) were analysed as predictors of weight and fat changes.

RESULTS

TyG₁ was associated with ΔWeight_1-2 (kg) and ΔBMI_1-2 (kg/m² ), with β = 0.812 (p = .017) and β = 0.265 (p = .018), respectively. Also, TyG₂  values were inversely related to ΔFat_1-2 (%), β = -1.473 (p = .015). Moreover, ΔTyG_1-2 was associated with ΔWeight_1-2 (kg) and ΔFat_1-2 (%), β = 0.689 (p = .045) and β = 1.764 (p = .002), respectively. Furthermore, an association between TyG₂ and resistance to fat loss was found (p = .015).

CONCLUSION

TyG₁ index is a good predictor of weight loss induced by LCD. Moreover, TyG₂ was closely related to resistance to fat loss, while ΔTyG_1-2  values were positively associated with body fat changes. Therefore, TyG index and derived estimations could be used as markers of individualized responses to energy restriction and a surrogate of body composition outcomes in clinical/epidemiological settings in obesity conditions.

Abdominal and gluteofemoral fat depots show opposing associations with postprandial lipemia

BACKGROUND

High postprandial lipemia is associated with increased risk of cardiovascular disease, independently of fasting lipid concentrations. Abdominal and gluteofemoral fat depots handle lipoproteins differently, which could affect postprandial lipemia and contribute to the relation between abdominal fat distribution and cardiovascular disease risk.

OBJECTIVES

We aimed to study the influences of higher abdominal compared with gluteofemoral fat on postprandial lipemia after a high-fat meal in individuals with obesity.

METHODS

A total of 755 adults with obesity from a randomized controlled trial in 7 European countries consumed a liquid high-fat meal. Concentrations of triglycerides (TG), glycerol, free fatty acids, and the cholesterol component of remnant-like particles (RLP), LDL, and HDL were measured postprandially for 3 h. Associations of waist circumference (WC), hip circumference (HC), and waist-hip ratio (WHR) with changes in postprandial lipid concentrations, adjusted for fasting concentrations and BMI, were examined using linear regression models. To assess whether the association of WHR with postprandial lipemia could be causal, we performed instrumental variable analyses using a genetic score of 442 variants known to be associated with WHR adjusted for BMI in 2-stage least-squares regression models.

RESULTS

WHR was associated with higher TG and RLP cholesterol concentrations, independent of fasting lipid concentrations and BMI. Instrumental variable analyses suggested that the associations of WHR with postprandial TG (β = 0.038 μmol/L*min, SE = 0.019 μmol/L*min, P = 0.044) and RLP cholesterol concentrations (β = 0.059 mmol/L, SE = 0.025 mmol/L, P = 0.020) may be causal. WC and HC showed opposite effects: higher WC was associated with higher TG and RLP cholesterol concentrations whereas higher HC was associated with lower concentrations.

CONCLUSIONS

Our results suggest that higher fat deposition abdominally versus gluteofemorally may be causally associated with elevated postprandial lipemia after a high-fat meal, independent of fasting lipid concentrations and BMI. Furthermore, higher abdominal and gluteofemoral fat depots show opposing effects on postprandial lipemia.This trial was registered at www.isrctn.com as ISRCTN25867281.

Genetic markers of abdominal obesity and weight loss after gastric bypass surgery

Background

Weight loss after bariatric surgery varies widely between individuals, partly due to genetic differences. In addition, genetic determinants of abdominal obesity have been shown to attenuate weight loss after dietary intervention with special attention paid to the rs1358980-T risk allele in the VEGFA locus. Here we aimed to test if updated genetic risk scores (GRSs) for adiposity measures and the rs1358980-T risk allele are linked with weight loss following gastric bypass surgery.

Methods

Five hundred seventy six patients with morbid obesity underwent Roux-en-Y gastric bypass. A GRS for BMI and a GRS for waist-hip-ratio adjusted for BMI (proxy for abdominal obesity), respectively, were constructed. All patients were genotyped for the rs1358980-T risk allele. Associations between the genetic determinants and weight loss after bariatric surgery were evaluated.

Results

The GRS for BMI was not associated with weight loss (β = -2.0 kg/100 risk alleles, 95% CI -7.5 to 3.3, p = 0.45). Even though the GRS for abdominal obesity was associated with an attenuated weight loss response adjusted for age, sex and center (β = -14.6 kg/100 risk alleles, 95% CI -25.4 to -3.8, p = 0.008), it was not significantly associated with weight loss after adjustment for baseline BMI (β = -7.9 kg/100 risk alleles, 95% CI -17.5 to 1.6, p = 0.11). Similarly, the rs1358980-T risk allele was not significantly associated with weight loss (β = -0.8 kg/risk allele, 95% CI -2.2 to 0.6, p = 0.25).

Discussion

GRSs for adiposity derived from large meta-analyses and the rs1358980-T risk allele in the VEGFA locus did not predict weight loss after gastric bypass surgery. The association between a GRS for abdominal obesity and the response to bariatric surgery may be dependent on the association between the GRS and baseline BMI.

Factors affecting weight loss variability in obesity

Current obesity treatment strategies include diet, exercise, bariatric surgery, and a limited but growing repertoire of medications. Individual weight loss in response to each of these strategies is highly variable. Here we review research into factors potentially contributing to inter-individual variability in response to treatments for obesity, with a focus on studies in humans. Well-recognized factors associated with weight loss capacity include diet adherence, physical activity, sex, age, and specific medications. However, following control for each of these, differences in weight loss appear to persist in response to behavioral, pharmacological and surgical interventions. Adaptation to energy deficit involves complex feedback mechanisms, and inter-individual differences likely to arise from a host of poorly defined genetic factors, as well as differential responses in neurohormonal mechanisms (including gastrointestinal peptides), metabolic efficiency and capacity of tissues, non-exercise activity thermogenesis, thermogenic response to food, and in gut microbiome. A better understanding of the factors involved in inter-individual variability in response to therapies will guide more personalized approaches to the treatment of obesity.

Associations between Genotype-Diet Interactions and Weight Loss-A Systematic Review

Studies on the interactions between single nucleotide polymorphisms (SNPs) and macronutrient consumption on weight loss are rare and heterogeneous. This review aimed to conduct a systematic literature search to investigate genotype–diet interactions on weight loss. Four databases were searched with keywords on genetics, nutrition, and weight loss (PROSPERO: CRD42019139571). Articles in languages other than English and trials investigating special groups (e.g., pregnant women, people with severe diseases) were excluded. In total, 20,542 articles were identified, and, after removal of duplicates and further screening steps, 27 articles were included. Eligible articles were based on eight trials with 91 SNPs in 63 genetic loci. All articles examined the interaction between genotype and macronutrients (carbohydrates, fat, protein) on the extent of weight loss. However, in most cases, the interaction results were not significant and represented single findings that lack replication. The publications most frequently analyzed genotype–fat intake interaction on weight loss. Since the majority of interactions were not significant and not replicated, a final evaluation of the genotype–diet interactions on weight loss was not possible. In conclusion, no evidence was found that genotype–diet interaction is a main determinant of obesity treatment success, but this needs to be addressed in future studies.

SGCG rs679482 Associates With Weight Loss Success in Response to an Intensively Supervised Outpatient Program

Weight loss in response to energy restriction is highly variable, and identification of genetic contributors can provide insights into underlying biology. Leveraging 1000 Genomes imputed genotypes, we carried out genome-wide association study (GWAS) analysis in 551 unrelated obese subjects of European ancestry who participated in an intensively supervised weight loss program with replication of promising signals in an independent sample of 1,331 obese subjects who completed the program at a later date. By single nucleotide polymorphism-based and sib-pair analysis, we show that that weight loss is a heritable trait, with estimated heritability (h ² = 0.49) within the range reported for obesity. We find rs679482, intronic to SGCG (sarcoglycan γ), highly expressed in skeletal muscle, to concordantly associate with weight loss in discovery and replication samples reaching GWAS significance in the combined meta-analysis (β = -0.35, P = 1.7 × 10^-12). Located in a region of open chromatin, rs679482 is predicted to bind DMRT2, and allele-specific transcription factor binding analysis indicates preferential binding of DMRT2 to rs679482-A. Concordantly, rs679482-A impairs native repressor activity and increases basal and DMRT2-mediated enhancer activity. These findings confirm that weight loss is a heritable trait and provide evidence by which a novel variant in SGCG, rs679482, leads to impaired diet response.

Gene-obesogenic environment interactions on body mass indices for older black and white men and women from the Health and Retirement Study

BACKGROUND

Gene-obesogenic environment interactions influence body mass index (BMI) across the life course; however, limited research examines how these interactions may differ by race and sex.

METHODS

Utilizing mixed-effects models, we examined the interaction effects of a polygenic risk score (PGS) generated from BMI-associated single-nucleotide polymorphisms, and environmental factors, including age, physical activity, alcohol intake, and childhood socioeconomic status on measured longitudinal BMI from the Health and Retirement Study (HRS). HRS is a population representative survey of older adults in the United States. This study used a subsample of genotyped Black (N = 1796) and White (N = 4925) men and women (50-70 years) with measured BMI.

RESULTS

Higher PGS was associated with higher BMI. The association between PGS and BMI weakened as individuals aged among White men (Pinteraction = 0.0383) and White women (Pinteraction = 0.0514). The mean BMI difference between the 90th and 10th PGS percentile was 4.25 kg/m2 among 50-year-old White men, and 3.11 kg/m2 among the 70 years old's, i.e., a 1.14 kg/m2 (95% CI: -0.27, 2.82) difference. The difference among 50- and 70-year-old White women was 1.34 kg/m2 (95% CI: 0.09, 2.60). In addition, the protection effect of physical activity was stronger among White women with higher PGS (Pinteraction = 0.0546). Vigorous physical activity (compared with never) was associated with 1.66 kg/m2 (95% CI: 1.06, 2.29) lower mean BMI among those in the 90th PGS percentile, compared with 0.83 kg/m2 (95% CI: 0.37, 1.29) lower among those in the 10th PGS percentile. Interactions were also observed between both PGS and alcohol intake among White men (Pinteraction = 0.0034) and women (Pinteraction = 0.0664) and Black women (Pinteraction = 0.0108), and PGS and childhood socioeconomic status among White women (Pinteraction = 0.0007).

CONCLUSIONS

Our findings reinforce the importance of physical activity among those with an elevated genetic risk; additionally, other detected interactions may underscore the influence of broader social environments on obesity-promoting genes.

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.

Genetic Risk Score Predictive of the Plasma Triglyceride Response to an Omega-3 Fatty Acid Supplementation in a Mexican Population

Our group built a genetic risk score (GRS) of the plasma triglyceride (TG) response to an omega-3 (n-3) fatty acid (FA) supplementation in Caucasian Canadians that explained 21.53% of the TG variance. The objective was to refine the GRS by fine mapping and to test its association with the TG response in young Mexican adults. A total of 191 participants underwent a 6-week n-3 FA supplementation providing 2.7g/day of docosahexaenoic and eicosapentaenoic acids. Using quantitative polymerase chain reaction (PCR), 103 single-nucleotide polymorphisms (SNPs) were genotyped. A stepwise regression adjusted for age, sex, and body mass index (BMI) was used to select the strongest SNPs to include in the genetic risk model. A GRS was calculated from the sum of at-risk alleles. The contribution of the GRS to the TG response was assessed by ANCOVA with age, sex, and BMI included in the model. Several differences in allele frequency were observed between Canadians and Mexicans. Five lead SNPs were included in the genetic risk model, in which the GRS accounted for 11.01% of the variance of the TG response (p < 0.0001). These findings highlight the important contribution of genetic factors to the heterogeneity of the TG response to an n-3 FA supplementation among Mexicans.

Is abdominal obesity at baseline influencing weight changes in observational studies and during weight loss interventions?

Background

Body fat distribution is a marker of metabolic health independent of body size. Visceral fat accumulation has been suggested to result from a decreased expandability of the subcutaneous fat depots. Furthermore, the visceral fat may be easier to mobilize than the peripheral fat. We examined whether differences in abdominal obesity at baseline influenced prospective body-weight changes.

Objective

In this study we examined whether body-fat distribution at baseline was associated with long-term and short-term weight changes.

Design

We included 3 observational studies (ntotal = 7271) with mean follow-up times of 5-9 y and two 8-10-wk weight loss intervention studies (ntotal = 1091). We examined the association between baseline waist circumference and weight changes in a substitution regression model, where body weight, height, and fat-free mass were fixed so that a difference in waist circumference would reflect a difference in body fat distribution alone. The results were summarized in meta-analyses.

Results

In the observational studies, we found no associations between baseline waist circumference and subsequent weight change in men (β: 0.03 kg; 95% CI: -0.01, 0.08 kg; P = 0.19), but a negligible inverse association in women (β: -0.05 kg; 95% CI: -0.08, -0.01 kg; P = 0.01). There was no association between baseline waist circumference and weight loss in the intervention studies (men: β: -0.05 kg; 95% CI: -0.13, 0.03 kg; P = 0.25; women: β: -0.00 kg; 95% CI: -0.03, 0.03 kg; P = 0.84). However, in all studies, the SDs of the weight change residuals were greater, the greater the waist circumference at baseline. This trend was statistically significant in women in most studies as well as in men in 1 of the studies.

Conclusions

With narrow CIs in 3 observational studies and 2 weight loss interventions, we did not find any clinically or epidemiologically relevant association between baseline abdominal obesity and weight change. However, the present study suggests that a greater baseline abdominal obesity is a marker for greater weight fluctuations. The CCHS trial was registered at www.clinicaltrials.gov as NCT02993172. The Health2006 trial was registered at www.clinicaltrials.gov as NCT00316667. The ORG study was conducted before trial registration was required. The NUGENOB trial was registered at www.isrctn.com as ISRCTN25867281. The DiOGenes trial was registered atwww.clinicaltrials.gov as NCT00390637.