Dietary nitrate intake and association with markers of cardiometabolic risk in Iranian female adolescents.

Dietary nitrates are thought to confer several cardiometabolic health benefits, including improvements in blood pressure and the plasma lipid profile. However, existing data from Iran is conflicting and there is a dearth of literature focusing on non-adult populations. A total of 988 adolescent girls were recruited from schools in different areas of Mashhad and Sabzevar, Iran. Dietary nitrate intake was assessed using a food frequency questionnaire and participants were categorized into quartiles based on this. Differences in participant characteristics between quartiles were assessed using one-way ANOVA and associations between total nitrate intake, nitrate intake from vegetables and cardiometabolic risk markers (blood lipid profile, fasting blood glucose, systolic and diastolic blood pressure) were assessed using linear regression. Nitrate intake from vegetables was positively correlated with triglycerides, even after adjusting for several variables (ß = 0.086, 95% CI = 0.002-0.097; P = 0.043). Total nitrate intake was also significantly positively associated with serum triglycerides (ß = 0.097, 95% CI = 0.010-0.084; P = 0.012); however, this relationship disappeared after adjusting for several variables. Significant interaction effects were observed between total nitrate intake, nitrate intake from vegetables, and vitamin C upon triglycerides (P < 0.01). No significant relationships were found between total nitrate intake, nitrate intake from vegetables, and other cardiometabolic risk markers. Our findings suggest there may be neutral or possibly detrimental cardiovascular effects of dietary nitrate and/or vitamin C intake which are not in agreement with contemporary literature and warrant further investigation.

The association of appendicular lean mass and grip strength with low-density lipoprotein, very low-density lipoprotein, and high-density lipoprotein particle diameter: a Mendelian randomization study of the UK Biobank cohort.

Aims: Reduced muscle mass and reduced strength are frequently associated with both alterations in blood lipids and poorer cardiometabolic outcomes in epidemiological studies; however, a causal association cannot be determined from such observations. Two-sample Mendelian randomization (MR) was applied to assess the association of genetically determined appendicular lean mass (ALM) and handgrip strength (HGS) with serum lipid particle diameter. Methods and results: Mendelian randomization was implemented using summary-level data from the largest genome-wide association studies on ALM (n = 450 243), HGS (n = 223 315), and lipoprotein [low-density lipoprotein (LDL), very LDL (VLDL), and high-density lipoprotein (HDL)] particle diameters (n = 115 078). Inverse variance-weighted (IVW) method was used to calculate the causal estimates. Weighted median-based method, MR-Egger, and leave-one-out method were applied as sensitivity analysis. Greater ALM had a statistically significant positive effect on HDL particle diameter (MR-Egger: ß = 0.055, SE = 0.031, P = 0.081; IVW: ß = 0.068, SE = 0.014, P < 0.001) and a statistically significant negative effect on VLDL particle diameter (MR-Egger: ß = -0.114, SE = 0.039, P = 0.003; IVW: ß = -0.081, SE = 0.017, P < 0.001). Similarly, greater HGS had a statistically significant positive effect on HDL particle diameter (MR-Egger: ß = 0.433, SE = 0.184, P = 0.019; IVW: ß = 0.121, SE = 0.052, P = 0.021) and a statistically significant negative effect on VLDL particle diameter (MR-Egger: ß = -0.416, SE = 0.163, P = 0.011; IVW: ß = -0.122, SE = 0.046, P = 0.009). There was no statistically significant effect of either ALM or HGS on LDL particle diameter. Conclusion: There were potentially causal associations between both increasing ALM and HGS and increasing HDL particle size and decreasing VLDL particle size. These causal associations may offer possibilities for interventions aimed at improving cardiovascular disease risk profile.

Effects of Single Low-Carbohydrate, High-Fat Meal Consumption on Postprandial Lipemia and Markers of Endothelial Dysfunction: A Systematic Review of Current Evidence.

CONTEXT: Postprandial lipemia (PPL) is associated with increased risk of endothelial dysfunction (ED), a precursor of atherosclerotic cardiovascular disease (ASCVD). The effects of low-carbohydrate, high-fat (LCHF) diets on ASCVD risk are uncertain; therefore, gaining a greater understanding of LCHF meals on PPL may provide valuable insights. OBJECTIVE: The current systematic review investigated the effects of single LCHF meal consumption on PPL and markers of ED. DATA SOURCES: CINAHL Plus, PubMed, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL) were searched for key terms related to endothelial function, cardiovascular disease, glycemia, lipemia, and the postprandial state with no restriction on date. DATA EXTRACTION: Full-text articles were independently screened by 2 reviewers, of which 16 studies were eligible to be included in the current review. All trials reported a minimum analysis of postprandial triglycerides (PPTG) following consumption of an LCHF meal (<26% of energy as carbohydrate). Results were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. DATA ANALYSIS: Single-meal macronutrient composition was found to play a key role in determining postprandial lipid and lipoprotein responses up to 8 hours post-meal. Consumption of LCHF meals increased PPTG and may contribute to ED via reduced flow-mediated dilation and increased oxidative stress; however, energy and macronutrient composition varied considerably between studies. CONCLUSION: Consumption of an LCHF meal had a negative impact on PPL based on some, but not all, single-meal studies; therefore, the contribution of LCHF meals to cardiometabolic health outcomes remains unclear. Further research is needed on specific categories of LCHF diets to establish a causal relationship between postprandial modulation of lipids/lipoproteins and impaired vascular endothelial function. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. CRD 42023398774.

Proteomic Analyses in Diverse Populations Improved Risk Prediction and Identified New Drug Targets for Type 2 Diabetes.

OBJECTIVE: Integrated analyses of plasma proteomics and genetic data in prospective studies can help assess the causal relevance of proteins, improve risk prediction, and discover novel protein drug targets for type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: We measured plasma levels of 2,923 proteins using Olink Explore among ∼2,000 randomly selected participants from China Kadoorie Biobank (CKB) without prior diabetes at baseline. Cox regression assessed associations of individual protein with incident T2D (n = 92 cases). Proteomic-based risk models were developed with discrimination, calibration, reclassification assessed using area under the curve (AUC), calibration plots, and net reclassification index (NRI), respectively. Two-sample Mendelian randomization (MR) analyses using cis-protein quantitative trait loci identified in a genome-wide association study of CKB and UK Biobank for specific proteins were conducted to assess their causal relevance for T2D, along with colocalization analyses to examine shared causal variants between proteins and T2D. RESULTS: Overall, 33 proteins were significantly associated (false discovery rate <0.05) with risk of incident T2D, including IGFBP1, GHR, and amylase. The addition of these 33 proteins to a conventional risk prediction model improved AUC from 0.77 (0.73-0.82) to 0.88 (0.85-0.91) and NRI by 38%, with predicted risks well calibrated with observed risks. MR analyses provided support for the causal relevance for T2D of ENTR1, LPL, and PON3, with replication of ENTR1 and LPL in Europeans using different genetic instruments. Moreover, colocalization analyses showed strong evidence (pH4 > 0.6) of shared genetic variants of LPL and PON3 with T2D. CONCLUSIONS: Proteomic analyses in Chinese adults identified novel associations of multiple proteins with T2D with strong genetic evidence supporting their causal relevance and potential as novel drug targets for prevention and treatment of T2D.

Proteomic aging clock predicts mortality and risk of common age-related diseases in diverse populations.

Circulating plasma proteins play key roles in human health and can potentially be used to measure biological age, allowing risk prediction for age-related diseases, multimorbidity and mortality. Here we developed a proteomic age clock in the UK Biobank (n = 45,441) using a proteomic platform comprising 2,897 plasma proteins and explored its utility to predict major disease morbidity and mortality in diverse populations. We identified 204 proteins that accurately predict chronological age (Pearson r = 0.94) and found that proteomic aging was associated with the incidence of 18 major chronic diseases (including diseases of the heart, liver, kidney and lung, diabetes, neurodegeneration and cancer), as well as with multimorbidity and all-cause mortality risk. Proteomic aging was also associated with age-related measures of biological, physical and cognitive function, including telomere length, frailty index and reaction time. Proteins contributing most substantially to the proteomic age clock are involved in numerous biological functions, including extracellular matrix interactions, immune response and inflammation, hormone regulation and reproduction, neuronal structure and function and development and differentiation. In a validation study involving biobanks in China (n = 3,977) and Finland (n = 1,990), the proteomic age clock showed similar age prediction accuracy (Pearson r = 0.92 and r = 0.94, respectively) compared to its performance in the UK Biobank. Our results demonstrate that proteomic aging involves proteins spanning multiple functional categories and can be used to predict age-related functional status, multimorbidity and mortality risk across geographically and genetically diverse populations.