Nutrition & Metabolism最新文献

Background: Shift work has been identified as a risk factor for several chronic health conditions including obesity. This study evaluated the impact of a low-calorie meal replacement (MR) as a dinner substitute on body composition and metabolic parameters in shift workers with overweight and obesity.

Methods: An 8-week parallel, randomized controlled trial was conducted on overweight and obese shift workers in a large hospital. An intervention group (IG) (n = 25) was provided with a low-calorie MR shake (∼200 kcal) as a replacement for dinner, every day for 8 weeks, while the control group (CG) (n = 25) continued their habitual diet. Anthropometric measurements, body composition, biochemical, and lifestyle data were assessed at the first and last visits. Analyses were done per protocol (PP) and by intention to treat (ITT).

Results: Over the study duration, both groups displayed moderate changes in anthropometric measurements and body composition, although these were not statistically significant according to the PP analysis. In the ITT analysis, apart from the hip circumference (HC), all other anthropometric parameters demonstrated significant group and time interactions, suggesting the advantageous effects of the meal replacement over the study period (P < 0.05). HDL and VLDL cholesterol measures showed significant main effects, influenced by both group (P = 0.031) and time (P = 0.050) respectively. The most pronounced dietary shift in the IG was a reduction in carbohydrate consumption and an increase in protein intake. Throughout the study, the meal replacement was well-tolerated, with no adverse events reported.

Conclusions: The meal replacement dietary intervention appears to offer beneficial health effects over time. Extended research is crucial to understand the broader implications of meal replacements across diverse populations.

Trial registration: Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12622000231741. Registered on 09 February 2022. https://www.anzctr.org.au/ACTRN12622000231741.aspx .

Background: The study aimed to explore the relationship between low-density lipoprotein cholesterol (LDL-C) genetic variants and obstructive sleep apnea (OSA) and its complications, including cardiovascular diseases (CVD), insulin resistance (IR), and metabolic syndrome (MS).

Method: 4329 individuals with suspected OSA who underwent a comprehensive assessment of anthropometric, biochemical, and polysomnography (PSG) data, along with 30 LDL-C single nucleotide polymorphisms (SNPs) were enrolled. The 10-year Framingham CVD risk score (FRS), IR and MS were evaluated for each subject. Linear regression and logistic regression were utilized to examine the correlations among these variables.

Results: After the Benjamini-Hochberg correction, linear regression results indicated positive correlations between variants rs3741297 and rs629301 with FRS (β = 0.031, P_BH=0.002; β = 0.026, P_BH=0.015). Logistic regression revealed that rs3741297 increased MS risk among total subjects [OR = 1.67 (95% CI:1.369-2.038), P_BH=1.32 × 10^- 5] and increased IR risk in females [OR = 3.475 (95% CI:1.653-7.307), P_BH=0.03]. In males, rs2642438 decreased MS risk [OR = 0.81 (95% CI:0.703-0.933), P_BH=0.045].

Conclusions: The rs3741297 variant correlated with susceptibility to CVD, IR, and MS in the OSA population. OSA, CVD, IR and MS share a potentially common genetic background, which may promote precision medicine.

Cinical trial registration: The study protocol was registered with the Chinese Clinical Trial Registry (ChiCTR1900025714).

Objective: Weight regain after weight loss is a challenge in obesity management. The metabolic changes and underlying mechanisms in obese people with weight fluctuation remain to be elucidated. In the present study, we aimed to profile the features and clinical significance of liver transcriptome in obese mice with weight regain after weight loss.

Methods: The male C57BL/6J mice were fed with standard chow diet or high-fat diet (HFD). After 9 weeks, the HFD-induced obese mice were randomly divided into weight gain (WG), weight loss (WL) and weight regain (WR) group. After 10 weeks of dietary intervention, body weight, fasting blood glucose (FBG), intraperitoneal glucose tolerance, triglycerides (TG), total cholesterol (T-CHO) and low-density lipoprotein cholesterol (LDL-C) were measured. Morphological structure and lipid droplet accumulation in the liver were observed by H&E staining and oil red O staining, respectively. The liver transcriptome was detected by RNA sequencing. Protein expressions of liver cytochrome P450 3a11 (Cyp3a11) and E4 promoter-binding protein 4 (E4bp4) were determined by Western blot.

Results: After 10 weeks of dietary intervention, the body weight, FBG, glucose area under the curve, T-CHO and LDL-C in WL group were significantly lower than those in WG group (P < 0.05). At 4 weeks of HFD re-feeding, the mice in WR group presented body weight and T-CHO significantly lower than those in WG group, whereas higher than those in WL group (P < 0.05). Hepatic vacuolar degeneration and lipid droplet accumulation in the liver were significantly alleviated in WL group and WR group, compared to those in WG group. The liver transcriptome associated with lipid metabolism was significantly altered during weight fluctuation in obese mice. Compared with those in WG group, Cyp3a11 in the liver was significantly upregulated, and E4bp4 was significantly downregulated in WL and WR groups.

Conclusion: Obese mice experience weight regain after weight loss by HFD re-feeding, but their glucose and lipid metabolism disorders are milder than those induced by the persistence of obesity. Downregulated E4bp4 and upregulated Cyp3a11 are detected in obese mice after weight loss, suggesting that the E4bp4-Cyp3a11 axis may involved in metabolic mechanisms underlying weight regulation.

Background: Substantial weight loss in people living with type 2 diabetes (T2D) can reduce the need for glucose-lowering medications while concurrently lowering glycemia below the diagnostic threshold for the disease. Furthermore, weight-loss interventions have also been demonstrated to improve aspects of underlying T2D pathophysiology related to ectopic fat in the liver and pancreatic beta-cell function. As such, the purpose of this secondary analysis was to explore the extent to which a low-carbohydrate and energy-restricted (LCER) diet intervention improves markers of beta-cell stress/function, liver fat accumulation, and metabolic related liver function in people with type 2 diabetes.

Methods: We conducted secondary analyses of blood samples from a larger pragmatic community-based parallel-group randomized controlled trial involving a 12-week pharmacist implemented LCER diet (Pharm-TCR: <50 g carbohydrates; ~850-1100 kcal/day; n = 20) versus treatment-as-usual (TAU; n = 16). Participants were people with T2D, using ≥ 1 glucose-lowering medication, and a body mass index of ≥ 30 kg/m². Main outcomes were C-peptide to proinsulin ratio, circulating microRNA 375 (miR375), homeostatic model assessment (HOMA) beta-cell function (B), fatty liver index (FLI), hepatic steatosis index (HSI), HOMA insulin resistance (IR), and circulating fetuin-A and fibroblast growth factor 21 (FGF21). Data were analysed using linear regression with baseline as a covariate.

Results: There was no observed change in miR375 (p = 0.42), C-peptide to proinsulin ratio (p = 0.17) or HOMA B (p = 0.15). FLI and HSI were reduced by -25.1 (p < 0.0001) and - 4.9 (p < 0.0001), respectively. HOMA IR was reduced by -46.5% (p = 0.011). FGF21 was reduced by -161.2pg/mL (p = 0.035) with a similar tendency found for fetuin-A (mean difference: -16.7ng/mL; p = 0.11). These improvements in markers of hepatic function were accompanied by reductions in circulating metabolites linked to hepatic insulin resistance (e.g., diacylglycerols, ceramides) in the Pharm TCR group.

Conclusions: The Pharm-TCR intervention did not improve fasting indices of beta-cell stress; however, markers of liver fat accumulation and and liver function were improved, suggesting that a LCER diet can improve some aspects of the underlying pathophysiology of T2D.

Trial registration: Clinicaltrials.gov (NCT03181165).

Background: Metabolic syndrome (MetS) includes a group of metabolic irregularities, including insulin resistance (IR), atherogenic dyslipidemia, central obesity, and hypertension. Consistent evidence supports IR and ongoing low-grade inflammation as the main contributors to MetS pathogenesis. However, the association between the triglyceride-glucose (TyG) index and mortality in people with MetS remains uncertain. The objective of this study was to examine the correlation between the baseline TyG index and all-cause and cardiovascular (CV) mortality in rural Northeast Chinese individuals with MetS.

Methods: For the Northeast China Rural Cardiovascular Health Study, 3918 participants (mean age, 55 ± 10; 62.4% women) with MetS at baseline were enrolled in 2012-2013 and followed up from 2015 to 2017. The TyG index was calculated using the equation TyG index = ln [fasting TG (mg/dL) × fasting glucose (mg/dL)/2] and subdivided into tertiles [Q1(< 8.92); Q2 (8.92-9.36); Q3 (≥ 9.36)]. Multivariate Cox proportional hazards models were developed to examine the correlations between mortality and the baseline TyG index.

Results: During a median of 4.66 years of follow-up, 196 (5.0%) all-cause deaths and 108 (2.8%) CV disease-related deaths occurred. The incidence of all-cause mortality was significantly different among TyG index tertiles of the overall population (P = 0.045). Kaplan-Meier analysis demonstrated a significantly increased risk of all-cause mortality in rural Chinese patients with a higher TyG index (log-rank P < 0.05). After adjusting for possible confounders, Cox proportional hazard analysis revealed that the TyG index could effectively predict all-cause mortality (HR for the third vs. first tertile of TyG was 1.441 [95% confidence interval, 1.009-2.059]), but not CV mortality, in rural Chinese patients with MetS.

Conclusions: The TyG index is an effective predictor of all-cause mortality in rural Chinese patients with MetS. This indicates that the TyG index may be useful for identifying rural Chinese individuals with MetS at a high risk of death.

Neurodegenerative diseases represent one of the utmost imperative well-being health issues and apprehensions due to their escalating incidence of mortality. Natural derivatives are more efficacious in various preclinical models of neurodegenerative illnesses. These natural compounds include phytoconstituents in herbs, vegetables, fruits, nuts, and marine and freshwater flora, with remarkable efficacy in mitigating neurodegeneration and enhancing cognitive abilities in preclinical models. According to the latest research, the therapeutic activity of natural substances can be increased by adding phytoconstituents in nanocarriers such as nanoparticles, nanogels, and nanostructured lipid carriers. They can enhance the stability and specificity of the bioactive compounds to a more considerable extent. Nanotechnology can also provide targeting, enhancing their specificity to the respective site of action. In light of these findings, this article discusses the biological and therapeutic potential of natural products and their bioactive derivatives to exert neuroprotective effects and some clinical studies assessing their translational potential to treat neurodegenerative disorders.

Background: Gout prediction is essential for the development of individualized prevention and treatment plans. Our objective was to develop an efficient and interpretable machine learning (ML) model using the SHapley Additive exPlanation (SHAP) to link dietary fiber and triglyceride-glucose (TyG) index to predict gout.

Methods: Using datasets from the National Health and Nutrition Examination Survey (NHANES) (2005-2018) population to study dietary fiber, the TyG index was used to predict gout. After evaluating the performance of six ML models and selecting the Light Gradient Boosting Machine (LGBM) as the optimal algorithm, we interpret the LGBM model for predicting gout using SHAP and reveal the decision-making process of the model.

Results: An initial survey of 70,190 participants was conducted, and after a gradual exclusion process, 12,645 cases were finally included in the study. Selection of the best performing LGBM model for prediction of gout associated with dietary fiber and TyG index (Area under the ROC curve (AUC): 0.823, 95% confidence interval (CI): 0.798-0.848, Accuracy: 95.3%, Brier score: 0.077). The feature importance of SHAP values indicated that age was the most important feature affecting the model output, followed by uric acid (UA). The SHAP values showed that lower dietary fiber values had a more pronounced effect on the positive prediction of the model, while higher values of the TyG index had a more pronounced effect on the positive prediction of the model.

Conclusion: The interpretable LGBM model associated with dietary fiber and TyG index showed high accuracy, efficiency, and robustness in predicting gout. Increasing dietary fiber intake and lowering the TyG index are beneficial in reducing the potential risk of gout.

Background: Sirtuins have an important role in the regulation of metabolic and biological processess. Thus, we hypothesized that foods that could activate sirtuins, known as "sirtfood", may improve health status. So, this study was aimed at investigating the association between the amount of sirtfood intake and the risk of major adverse cardiovascular events (MACE).

Methods: In this cohort study, 2918 adults who had no history of MACE at the start of the study (2006-2008) participated and were followed up on until 2018. The amount of sirtfoods intake (servings per week) was computed using a validated food frequency questionnaire. Each patient's medical records were evaluated to detect MACE. The Cox proportional hazards model was applied to assess the association between the amount of sirtfood intake and the risk of MACE.

Results: The median duration of the study was 10.6 years. The hazard ratio (HR) for the risk of MACE was 0.70 for the second (95% CI: 0.50, 0.98) and 0.60 (95% CI: 0.42, 0.86) for the third tertile of sirtfoods intake compared with the first tertile. This association was nonlinear, and sirtfoods consumption of more than five servings per week did not result in a lower risk of MACE. In addition, there was a significant interaction between age (P-interaction < 0.001) and sirtfoods intake in relation to MACE occurrence. When assessing sirtfood components, compared with the lowest intake, the highest amount of soy (HR: 0.74, 95% CI: 0.56, 0.99) and parsley (HR: 0.62, 95% CI: 0.47, 0.83) intake was related to a lower risk of MACE.

Conclusion: Our results indicated an inverse association between a higher amount of sirtfood intake and a lower risk of MACE incidents. This association was nonlinear, and having more than five servings of sirtfood per week did not reduce the risk of MACE any further.