Interactions of dietary insulin index and dietary insulin load with brain-derived neurotrophic factor (BDNF) Val66Met polymorphism in relation to cardiometabolic markers in Iranian diabetic patients: a cross-sectional study

The BDNF Val66Met polymorphism serves as a potential marker of body weight in patients with psychiatric disorders

Brain-derived neurotrophic factor (BDNF) is a predominant neurotrophic factor in the brain, indispensable for neuronal growth, synaptic development, neuronal repair, and hippocampal neuroplasticity. Among its genetic variants, the BDNF Val66Met polymorphism is widespread in the population and has been associated with the onset and aggravation of diverse pathologies, including metabolic conditions like obesity and diabetes, cardiovascular ailments, cancer, and an array of psychiatric disorders. Psychiatric disorders constitute a broad category of mental health issues that influence mood, cognition, and behavior. Despite advances in research and treatment, challenges persist that hinder our understanding and effective intervention of these multifaceted conditions. Achieving and maintaining stable body weight is pivotal for overall health and well-being, and the relationship between psychiatric conditions and body weight is notably intricate and reciprocal. Both weight gain and loss have been linked to varying mental health challenges, making the disentanglement of this relationship critical for crafting holistic treatment strategies. The BDNF Val66Met polymorphism's connection to weight fluctuation in psychiatric patients has garnered attention. This review investigated the effects and underlying mechanisms by which the BDNF Val66Met polymorphism moderates body weight among individuals with psychiatric disorders. It posits the polymorphism as a potential biomarker, offering prospects for improved monitoring and therapeutic approaches for mental illnesses.

The Application of the Food Insulin Index in the Prevention and Management of Insulin Resistance and Diabetes: A Scoping Review

The food insulin index (FII) is a novel algorithm used to determine insulin responses of carbohydrates, proteins, and fats. This scoping review aimed to provide an overview of all scientifically relevant information presented on the application of the FII in the prevention and management of insulin resistance and diabetes. The Arksey and O'Malley framework and the PRISMA Extension for Scoping Reviews 22-item checklist were used to ensure that all areas were covered in the scoping review. Our search identified 394 articles, of which 25 articles were included. Three main themes emerged from the included articles: 1. the association of FII with the development of metabolic syndrome, insulin resistance, and diabetes, 2. the comparison of FII with carbohydrate counting (CC) for the prediction of postprandial insulin response, and 3. the effect of metabolic status on the FII. Studies indicated that the FII can predict postprandial insulin response more accurately than CC, and that a high DII and DIL diet is associated with the development of metabolic syndrome, insulin resistance, and diabetes. The FII could be a valuable tool to use in the prevention and management of T1DM, insulin resistance, and T2DM, but more research is needed in this field.

The relationship between low-carbohydrate diet score, dietary insulin index and load with obesity in healthy adults

PURPOSE

Carbohydrate intake and insulinemic potential of diet are suggested to be correlated with the development of different chronic diseases. Considering the limited research on obesity, this study aimed to investigate the association of dietary insulin index (DII), dietary insulin load (DIL), and low-carbohydrate diet score (LCDS) with body weight and obesity in healthy adults.

METHODS

In this cross-sectional study, DII, DIL, and LCDS were calculated using relevant formulas based on dietary intakes obtained by a valid 168-item food frequency questionnaire, in 393 otherwise healthy adults of either normal-weight, overweight, or obese.

RESULTS

Individuals in the highest tertile of DIL and DII had respectively 73% (OR: 0.27, 95% CI 0.08-0.94, p = 0.049) and 50% (OR: 0.5, 95% CI 0.26-0.96, p = 0.038) lower odds of being overweight compared to the lowest tertile, after adjusting the effects of age, sex, and dietary energy intake. Participants in the highest tertile of DIL had 92% greater odds of being obese compared to the lowest tertile, but this association did not remain significant after adjusting the effect of energy intake. Individuals in the highest tertile of LCDS had about 2 times odds of being overweight compared with those in the lowest tertile (OR: 2.04, 95% CI 1.04-4.01, p = 0.049). There was no relationship between being obese and tertiles of LCDS.

CONCLUSION

Higher dietary carbohydrate intake and insulinemic potential of diet could not be considered independent dietary risk factors for overweight or obesity.

LEVEL OF EVIDENCE

Level III: evidence obtained from an observational study.

A Personalized Diet Approach Study: Interaction between PPAR-γ Pro12Ala and Dietary Insulin Indices on Metabolic Markers in Diabetic Patients

BACKGROUND

The objectives were to investigate the effect of the interaction between peroxisome proliferator-activated receptor gamma (PPAR-γ) Pro12Ala polymorphisms and dietary insulin load and insulin index (DIL and DII) on Cardio-metabolic Markers among diabetic patients.

METHODS

This cross-sectional study was conducted on 393 diabetic patients. Food-frequency questionnaire (FFQ) was used for DIL and DII calculation. PPAR-γ Pro12Ala was genotyped by the PCR-RFLP method. Biochemical markers including TC, LDL, HDL, TG, SOD, CRP, TAC, PTX3, PGF2α. IL18, leptin and ghrelin were measured by standard protocol.

RESULT

Risk-allele carriers (CG, GG) had higher obesity indices WC (P _interaction =0.04), BMI (P _interaction =0.006) and, WC (P _interaction =0.04) compared with individuals with the CC genotype when they consumed a diet with higher DIL and DII respectively. Besides, carriers of the G allele who were in the highest tertile of DIL, had lower HDL (P _interaction =0.04) and higher PGF2α (P _interaction =0.03) and PTX3 (P _interaction =0.03). Moreover, the highest tertile of the DII, showed an increase in IL18 (P _interaction =0.01) and lower SOD (P _interaction =0.03) for risk allele carriers compared to those with CC homozygotes.

CONCLUSION

We revealed PPAR-γ Pro12Ala polymorphism was able to intensify the effect of DIL and DII on CVD risk factors; risk-allele carriers who consumed a diet with high DIL and DII score have more likely to be obese and have higher inflammatory markers. Also, protective factor against CVD risk factors were reduced significantly in this group compared to CC homozygotes. This article is protected by copyright. All rights reserved.