Gene-diet interaction of FTO-rs9939609 gene variant and hypocaloric diet on glycemic control in overweight and obese adults: a systematic review and meta-analysis of clinical trials

Parastouei, Karim; Rostami, Hosein; Ramezani, Amirhossein; Tavakoli, Hamidreza; Alipour, Meysam

doi:10.1097/cm9.0000000000000617

Cited by 5 publications

(4 citation statements)

References 17 publications

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“…MetS was defined according to the 2005 revised National Cholesterol Education Program−Adult Treatment Panel III criteria for Asia [16,17]. Participants with three or more of the following criteria were considered as having MetS: (1) elevated blood pressure (average systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg) or current blood pressure medication use; (2) low HDL-C concentration (<40 mg/dL for men and <50 mg/dL for women); (3) elevated serum triglyceride concentration (≥150 mmol/L) or current anti-dyslipidemic medication use; (4) elevated fasting blood glucose concentration (≥100 mmol/L) or current use of antidiabetic medication; (5) abdominal obesity (waist circumference ≥ 90 cm for men and ≥85 cm for women).…”

Section: Definition Of Obesity and Metsmentioning

confidence: 99%

“…Recent studies have demonstrated that an individual genetic variant and lifestyle interactions influence the risk of obesity [13] and metabolic diseases [14,15] in Europeans and Asians [16]. For example, FTO genetic variants interact with the genetic and environmental factors that influence obesity risk [17,18]. Adult Asians with the FTO_rs1421085 risk allele have a higher BMI than those with the nonrisk allele when they have no regular exercise.…”

Section: Introductionmentioning

confidence: 99%

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Interactions between Polygenic Risk Scores, Dietary Pattern, and Menarche Age with the Obesity Risk in a Large Hospital-Based Cohort

et al. 2021

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Obese Asians are more susceptible to metabolic diseases than obese Caucasians of the same body mass index (BMI). We hypothesized that the genetic variants associated with obesity risk interact with the lifestyles of middle-aged and elderly adults, possibly allowing the development of personalized interventions based on genotype. We aimed to examine this hypothesis in a large city hospital-based cohort in Korea. The participants with cancers, thyroid diseases, chronic kidney disease, or brain-related diseases were excluded. The participants were divided into case and control according to their BMI: ≥25 kg/m2 (case; n = 17,545) and <25 kg/m2 (control; n = 36,283). The genetic variants that affected obesity risk were selected using a genome-wide association study, and the genetic variants that interacted with each other were identified by generalized multifactor dimensionality reduction analysis. The selected genetic variants were confirmed in the Ansan/Ansung cohort, and polygenetic risk scores (PRS)−nutrient interactions for obesity risk were determined. A high BMI was associated with a high-fat mass (odds ratio (OR) = 20.71) and a high skeletal muscle-mass index (OR = 3.38). A high BMI was positively related to metabolic syndrome and its components, including lipid profiles, whereas the initial menstruation age was inversely associated with a high BMI (OR = 0.78). The best model with 5-SNPs included SEC16B_rs543874, DNAJC27_rs713586, BDNF_rs6265, MC4R_rs6567160, and GIPR_rs1444988703. The high PRS with the 5-SNP model was positively associated with an obesity risk of 1.629 (1.475–1.798) after adjusting for the covariates. The 5-SNP model interacted with the initial menstruation age, fried foods, and plant-based diet for BMI risk. The participants with a high PRS also had a higher obesity risk when combined with early menarche, low plant-based diet, and a high fried-food intake than in participants with late menarche, high plant-based diet, and low fried-food intake. In conclusion, people with a high PRS and earlier menarche age are recommended to consume fewer fried foods and a more plant-based diet to decrease obesity risk. This result can be applied to personalized nutrition for preventing obesity.

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Section: Definition Of Obesity and Metsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Interactions between Polygenic Risk Scores, Dietary Pattern, and Menarche Age with the Obesity Risk in a Large Hospital-Based Cohort

et al. 2021

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“…Ahn et al, in a cross-sectional study involving 2,045 German participants, demonstrated that TyG and LAP provide a noninvasive and easily interpretable approach to identifying prediabetes/diabetes [60,61]. Similarly, Shahavandi et al observed an inverse correlation between adherence to plant-based dietary patterns and LAP levels in an Iranian population [62,63]. These studies highlight the potential of dietary interventions to modulate inflammatory markers associated with metabolic health [64][65][66].…”

Section: Discussionmentioning

confidence: 99%

The association between dietary inflammatory index with some cardio-metabolic risk indices among the patients with type 2 diabetes from Hoveyzeh cohort study: a cross-sectional study

Rahimlou,

Ahmadi,

Cheraghian

et al. 2024

BMC Endocr Disord

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Background The dietary inflammatory index (DII) serves as a tool to assess the inflammatory impact of an individual’s diet. This study aimed to investigate the association between DII and some cardio-metabolic risk indices among patients with T2DM. Methods Data from the Hoveyzeh Cohort Study, encompassing 2045 adults with T2DM, were analyzed. DII scores were calculated based on food frequency questionnaires. Anthropometric measurements and biochemical tests were performed to assess cardio-metabolic risk factors. Results Higher DII scores were positively associated with elevated triglyceride levels, triglyceride-glucose (TyG) index, lipid accumulation product (LAP), anthropometric indices including a body shape index (ABSI), body roundness index (BRI), body mass index (BMI), hip, waist circumferences (WC), and waist-to-height ratio (all Ptrend < 0.05). Notably, no significant association was observed between DII and fasting blood sugar (FBS) levels (Ptrend > 0.05). Additionally, dietary intake analysis revealed a negative correlation between DII scores and intake of fiber, fruits, vegetables, legumes, fish, seafood, dairy products, magnesium, and vitamins A, C, D, and E (all Ptrend < 0.05). Conversely, higher DII scores were associated with increased consumption of red meat, processed meat, refined cereals, potatoes, and soft drinks (all Ptrend < 0.05). Conclusion This study underscores the critical link between dietary inflammation, assessed by the DII score, and a multitude of cardio-metabolic risk factors in patients with T2DM. Notably, while the study did not find a significant association between DII and fasting blood sugar levels, it identified robust associations with novel anthropometric and biochemical indices indicative of cardio-metabolic risk. These findings highlight the potential of dietary interventions as a cornerstone strategy for managing T2DM and mitigating its associated complications.

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“…To precisely examine the effect of TCF7L2, and its polymorphisms on T2DM development, understanding of modification effect of TCF7L2 on the relation between lifestyle factors and glycemic parameters is critical. Although narrative and systematic reviews have reported evidence on gene-diet interaction on T2DM [13][14][15][16][17][18][19][20][21][22][23][24], evidence for gene-diet interactions on glycemic status is scarce [25]. Some studies showed that TCF7L2 modified the relation between lifestyle factors and insulin resistance, insulin processing and secretion, insulin action, and glucose concentrations [26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Effect of TCF7L2 on the relationship between lifestyle factors and glycemic parameters: a systematic review

Hosseinpour-Niazi

Mirmiran

Hosseini

et al. 2022

Nutr J

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Background Among candidate genes related to type 2 diabetes (T2DM), one of the strongest genes is Transcription factor 7 like 2 (TCF7L2), regarding the Genome-Wide Association Studies. We aimed to conduct a systematic review of the literature on the modification effect of TCF7L2 on the relation between glycemic parameters and lifestyle factors. Methods A systematic literature search was done for relevant publications using electronic databases, including PubMed, EMBASE, Scopus, and Web of Science, from January 1, 2000, to November 2, 2021. Results Thirty-eight studies (16 observational studies, six meal test trials, and 16 randomized controlled trials (RCTs)) were included. Most observational studies had been conducted on participants with non-diabetes showing that TCF7L2 modified the association between diet (fatty acids and fiber) and insulin resistance. In addition, findings from meal test trials showed that, compared to non-risk-allele carriers, consumption of meals with different percentages of total dietary fat in healthy risk-allele carriers increased glucose concentrations and impaired insulin sensitivity. However, ten RCTs, with intervention periods of less than ten weeks and more than one year, showed that TCF7L2 did not modify glycemic parameters in response to a dietary intervention involving different macronutrients. However, two weight loss dietary RCTs with more than 1-year duration showed that serum glucose and insulin levels decreased and insulin resistance improved in non-risk allele subjects with overweight/obesity. Regarding artichoke extract supplementation (ALE), two RCTs observed that ALE supplementation significantly decreased insulin concentration and improved insulin resistance in the TT genotype of the rs7903146 variant of TCF7L2. In addition, four studies suggested that physical activity levels and smoking status modified the association between TCF7L2 and glycemic parameters. However, three studies observed no effect of TCF7L2 on glycemic parameters in participants with different levels of physical activity and smoking status. Conclusion The modification effects of TCF7L2 on the relation between the lifestyle factors (diet, physical activity, and smoking status) and glycemic parameters were contradictory. PROSPERO registration number CRD42020196327

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Gene-diet interaction of FTO-rs9939609 gene variant and hypocaloric diet on glycemic control in overweight and obese adults: a systematic review and meta-analysis of clinical trials

Cited by 5 publications

References 17 publications

Interactions between Polygenic Risk Scores, Dietary Pattern, and Menarche Age with the Obesity Risk in a Large Hospital-Based Cohort

Interactions between Polygenic Risk Scores, Dietary Pattern, and Menarche Age with the Obesity Risk in a Large Hospital-Based Cohort

The association between dietary inflammatory index with some cardio-metabolic risk indices among the patients with type 2 diabetes from Hoveyzeh cohort study: a cross-sectional study

Effect of TCF7L2 on the relationship between lifestyle factors and glycemic parameters: a systematic review

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