Ghada A. Soliman

Background/Objectives: It is estimated that one in three adults in the US has one or more risk factors for cardiovascular–kidney–metabolic (CKM) syndrome. The American Heart Association (AHA) has warned that the interaction between obesity, Type 2 diabetes (T2D), chronic kidney disease (CKD), and cardiovascular disease (CVD) leads to a multistage CKM syndrome with elevated mortality. This narrative review describes the newly coined terms CKM health and CKM syndrome, introduced by the AHA Presidential Advisory in 2023. Methods: In this narrative review, we will discuss the epidemiology and development of CKM syndrome, CKM stages, and the possible impact of precision nutrition on CKM and evaluate what is currently known about the role of nutrient metabolism in the physiological state and pathogenesis of CKM. Results: Since the AHA defined CKM syndrome in 2023, several studies have analyzed NHANES data to identify the correlations between CKM stages and adverse health outcomes. Studies also found that correlations between dietary intake and diet patterns may contribute to the protection against progression through various stages of CKM. However, experimental research and clinical studies are still lagging. Although the liver plays an integral role in nutrient metabolism, energy homeostasis, protein synthesis, nutrient storage, antibody production, and detoxifying compounds, it has not been included in the definition of CKM. Conclusions: Integrated body systems contribute to the development and progression of CKM. Precision nutrition and dietary patterns may play a role in the management of CKM and related comorbidities. Further research is warranted to address the role of precision nutrition in the prevention, early detection, and intervention in CKM syndrome as part of a comprehensive approach. It would be worth considering including metabolic dysfunction-associated liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) within the CKM framework.

Background/Objectives: Legacy media are those that existed prior to the advent of the internet. Legacy media have a focus on the needs of specific readership populations. Because of this focus, they remain a trusted source of information for many people. During the COVID-19 pandemic, these media addressed readers’ needs for recipes for home food preparation. Methods: To evaluate the accuracy of the recipe descriptions and to compare these to their estimated nutritional value, we examined 182 recipes extracted from 942 food- and nutrition-related articles in a sample of magazines collected from January to December 2020. Because herbs and spices enhance the palatability of foods, are associated with healthier diet patterns, and provide phytochemicals which may have health benefits, we also examined the inclusion of these in the recipes when comparing their nutritional value. Results: Nutrient comparisons across these groups showed that recipes identified as healthy were the highest in vitamin C, fiber, and potassium and the lowest in cholesterol (p < 0.01). Cocktails were about half the calories per serving as all other recipes, and they were substantially lower in all the nutrients evaluated (p < 0.01) except for sugars (p = NS). An increase in seasonings was associated with higher levels of vitamin A, vitamin C, calcium, potassium, iron, and fiber (p < 0.001). Recipes with added seasonings were also lower in sugar (p < 0.05). Conclusions: Overall, these results support the hypothesis that recipes in legacy media identified as healthy, as well as those that contained more herbs and spices, were more likely to correspond to healthy diet guidelines.

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) reduce bodyweight and blood glucose. Extensive evidence from randomized controlled trials has indicated that GLP-1RAs have benefits well beyond weight loss and glucose control, extending from reductions in cardiovascular mortality to reductions in prostate cancer risk. Notably, some benefits of GLP-1RAs for the cardiovascular–kidney–metabolic (CKM) system arise before weight loss occurs for reasons that are not entirely clear but are key to patient care and drug development. Here, we hypothesize that GLP-1RAs act by inducing calorie restriction and by activating adenosine monophosphate-activated protein kinase (AMPK), which not only provides an explanation for the unique effectiveness of GLP-1RAs but also indicates a common mechanism shared by effective CKM therapies, including salicylates, metformin, statins, healthy diet, and physical activity. Whether AMPK activation is obligatory for effective CKM therapies should be considered. As such, we propose a mechanism of action for GLP-1RAs and explain how it provides an overarching framework for identifying means of preventing and treating cardiovascular, kidney, metabolic and related diseases, as well as informing the complementary question as to the components of a healthy lifestyle.

Objectives: We have previously shown that inhibition of the mTORC1 nutrient-sensing complex by rapamycin and mTORC1/mTORC2 inhibition by either Torin-2 or RapaLink-1 have differential effects on the global untargeted metabolomics in in vivo and in vitro cell culture models. Methods: In this study, we leveraged the mummichog Python algorithm to analyze the high-dimension untargeted metabolomics data to model the biochemical pathways and metabolic networks and predict their functional activity. We used pancreatic beta-cell culture (Beta TC6) and incubated the cells with either Rapalink-1, Rapamycin or the vehicle control for 24 h. Cells were harvested and flush-frozen in liquid nitrogen. Cells were extracted in ethanol, and the supernatant was collected. The untargeted metabolomics was performed using the high-resolution mass spectrometry LC-MS/MS HILIC peak detection of ESI-positive and -negative polarity modes. The data were collected using Bruker’s maXis-II ESI-Q-q-TOF coupled to Dionex Ultimate-3000 U(H)PLC system using Sequant ZIC-HILIC 150 × 2.1 mm column (Bruker, Hamburg, Germany). We compared the high-resolution untargeted precision metabolomics (LC-MS/MS) between groups using positive and negative polarity modes to capture both hydrophilic and hydrophobic metabolites. We employed the XCMS plus bioinformatics platform to link mTOR-regulated metabolites to the predicted biological pathways. Statistical significance (p < 0.001) was assessed by ANOVA and Ranked order data by Whitney-Cox followed by ad hoc unpaired t-test. Results: The cluster heatmap deconvolution and cloud plot analysis show the differential pattern of metabolites between Rapamycin and Rapalink-treated pancreatic beta cell lines. Mapping the downstream metabolites data onto predictive metabolic pathways and activity networks revealed that the top pathways affected included the pentose phosphate pathway, dopamine and ubiquinol degradation pathways in the ESI-positive polarity mode, and creatine synthesis/glycine degradation and nicotine degradation pathways in the ESI negative polarity mode. Conclusions: The high-resolution untargeted metabolomics can be leveraged as a proxy of the internal exposome yielding high-dimensional data that provide mechanistic insights into metabolic and signaling pathways, and the underlying biology. This approach will have beneficial applications of the internal exposome in determining the optimal precision nutrition pathways for personalized medicine.

A queueing theory based model of mTOR complexes impact on Akt-mediated cell response to insulin is presented in this paper. The model includes several aspects including the effect of insulin on the transport of glucose from the blood into the adipocytes with the participation of GLUT4, and the role of the GAPDH enzyme as a regulator of mTORC1 activity. A genetic algorithm was used to optimize the model parameters. It can be observed that mTORC1 activity is related to the amount of GLUT4 involved in glucose transport. The results show the relationship between the amount of GAPDH in the cell and mTORC1 activity. Moreover, obtained results suggest that mTORC1 inhibitors may be an effective agent in the fight against type 2 diabetes. However, these results are based on theoretical knowledge and appropriate experimental tests should be performed before making firm conclusions.

Intermittent fasting (IF), time-restricted eating (TRE) and fasting-mimicking diets (FMD) are gaining popularity as weight loss programs. As such, the timing and frequency of meals have been recognized as essential contributors to improving cardiometabolic health and a role as adjuvant therapy in cancer. Randomized controlled trials suggested that the weight loss associated with IF is due to a reduced energy intake due to time restriction. Although the supervised TRE clinical trials documented the dietary caloric intake, many free-living studies focused on the timing of meals without a complete characterization of the dietary intake, caloric density, or macronutrient composition. It is possible that both caloric-restriction diets and time-restriction protocols could work synergistically or additively to improve metabolic health outcomes. Like personalized medicine, achieving precision nutrition mandates the provision of the right nutrients to the right patient at the right time. To accomplish this goal, future studies need to evaluate the benefits of IF and TRE. Randomized controlled trials were conducted in different populations, ethnic groups, ages, geographic distribution, physical activity levels, body composition and in patients with obesity, diabetes, and cardiovascular diseases. Also, it is crucial to analyze the dietary composition and caloric density as related to circadian rhythm and timing of meals. It is conceivable that IF and TRE may contribute to precision nutrition strategies to achieve optimal health. However, more research is needed to evaluate IF and TRE effects on health outcomes and any side effects.

Esophageal cancer is an aggressive, often deadly disease globally that represents a significant health problem in Tanzania. The WHO reported 604,100 new esophageal cancer cases worldwide during 2020 and 544,076 deaths (Sung, 2021; World Health Organization, 2020). In Eastern Africa, 16,137 cases and 15,188 deaths were related to this disease in 2020. Esophageal cancer is associated with various etiologic risk factors, and access to the disease treatment is a major barrier to survival. This study examined associations between the prevalence of four geographically stratified, population-level, etiologic risk factors (tobacco use, unprotected water use, solid fuel source use, and poverty), as well as two access-to-care predictors (persons per hospital and distance from residence to where esophageal cancer treatment occurs). Regional- and coarser-scale zonal incidence rates were calculated for 2006 through 2016 and evaluated for geographic differences in relation to risk factors and access to care predictors using Poisson regression. Differences in the geographic distribution of esophageal cancer were observed. Distance from the region of residence to the treatment center (Ocean Road Cancer Institute) was statistically associated with the geographic pattern of esophageal cancer incidence. Further research into etiologic risk factors, dietary practices, and nutrition is needed to better understand the associations with esophageal cancer in Tanzania and other parts of Eastern Africa.

Background: Pancreatic beta cells regulate bioenergetics efficiency and secret insulin in response to glucose and nutrient availability. The mechanistic Target of Rapamycin (mTOR) network orchestrates pancreatic progenitor cell growth and metabolism by nucleating two complexes, mTORC1 and mTORC2. Objective: To determine the impact of mTORC1/mTORC2 inhibition on amino acid metabolism in mouse pancreatic beta cells (Beta-TC-6 cells, ATCC-CRL-11506) using high-resolution metabolomics (HRM) and live-mitochondrial functions. Methods: Pancreatic beta TC-6 cells were incubated for 24 h with either: RapaLink-1 (RL); Torin-2 (T); rapamycin (R); metformin (M); a combination of RapaLink-1 and metformin (RLM); Torin-2 and metformin (TM); compared to the control. We applied high-resolution mass spectrometry (HRMS) LC-MS/MS untargeted metabolomics to compare the twenty natural amino acid profiles to the control. In addition, we quantified the bioenergetics dynamics and cellular metabolism by live-cell imaging and the MitoStress Test XF24 (Agilent, Seahorse). The real-time, live-cell approach simultaneously measures the oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) to determine cellular respiration and metabolism. Statistical significance was assessed using ANOVA on Ranks and post-hoc Welch t-Tests. Results: RapaLink-1, Torin-2, and rapamycin decreased L-aspartate levels compared to the control (p = 0.006). Metformin alone did not affect L-aspartate levels. However, L-asparagine levels decreased with all treatment groups compared to the control (p = 0.03). On the contrary, L-glutamate and glycine levels were reduced only by mTORC1/mTORC2 inhibitors RapaLink-1 and Torin-2, but not by rapamycin or metformin. The metabolic activity network model predicted that L-aspartate and AMP interact within the same activity network. Live-cell bioenergetics revealed that ATP production was significantly reduced in RapaLink-1 (122.23 ± 33.19), Torin-2 (72.37 ± 17.33) treated cells, compared to rapamycin (250.45 ± 9.41) and the vehicle control (274.23 ± 38.17), p < 0.01. However, non-mitochondrial oxygen consumption was not statistically different between RapaLink-1 (67.17 ± 3.52), Torin-2 (55.93 ± 8.76), or rapamycin (80.01 ± 4.36, p = 0.006). Conclusions: Dual mTORC1/mTORC2 inhibition by RapaLink-1 and Torin-2 differentially altered the amino acid profile and decreased mitochondrial respiration compared to rapamycin treatment which only blocks the FRB domain on mTOR. Third-generation mTOR inhibitors may alter the mitochondrial dynamics and reveal a bioenergetics profile that could be targeted to reduce mitochondrial stress.

Type 2 diabetes (T2D) is a prevalent chronic disease associated with several comorbidities. This study investigated whether the risk of T2D varied with genetically predicted insulin (INS), insulin receptor (INS-R), or insulin-like growth factor 1 receptor (IGF-1R) using genetic variants in a Mendelian randomization (MR) study. A 2-sample MR study was conducted using summary statistics from 2 genome-wide association studies (GWASs). Genetic predictors of the exposures (INS, INS-R, and IGF-1R) were obtained from a publicly available proteomics GWAS of the INTERVAL randomized controlled trial of blood donation in the United Kingdom. For T2D, the study leveraged the DIAbetes Meta-ANalysis of Trans-Ethnic association studies (DIAMANTE) consortium. The estimated associations of INS, INS-R, and IGF-1R proteins with T2D were based on independent single nucleotide polymorphisms (SNPs) strongly (P < 5 × 10^–6) predicting each exposure. These SNPs were applied to publicly available genetic associations with T2D from the DIAMANTE case (n = 74,124) and control (n = 824,006) study of people of European descent. SNP-specific Wald estimates were meta-analyzed using inverse variance weighting with multiplicative random effects. Sensitivity analysis was conducted using the weighted median (WM) and MR-Egger. INS-R (based on 13 SNPs) was associated with a lower risk of T2D (OR: 0.95 per effect size; 95% CI: 0.92, 0.98; P = 0.001), with similar estimates from the WM and MR-Egger. Insulin (8 SNPs) and IGF-1R (10 SNPs) were not associated with T2D. However, 1 of the SNPs for INS-R was from the ABO blood group gene. This study is consistent with a causally protective association of the INS-R with T2D. INS-R in RBCs regulates glycolysis and thus may affect their functionality and integrity. However, a pleiotropic effect via the blood group ABO gene cannot be excluded. The INS-R may be a target for intervention by repurposing existing therapeutics or otherwise to reduce the risk of T2D.

The mammalian Target of Rapamycin complex 1 (mTORC1) nutrient-sensing pathway is a central regulator of cell growth and metabolism and is dysregulated in diabetes. The eukaryotic translation initiation factor 4E (EIF-4E) protein, a key regulator of gene translation and protein function, is controlled by mTORC1 and EIF-4E Binding Proteins (EIF4EBPs). Both EIF4EBPs and ribosomal protein S6K kinase (RP-S6K) are downstream effectors regulated by mTORC1 but converge to regulate two independent pathways. We investigated whether the risk of type 2 diabetes varied with genetically predicted EIF-4E, EIF-4A, EIF-4G, EIF4EBP, and RP-S6K circulating levels using Mendelian Randomization. We estimated the causal role of EIF-4F complex, EIF4EBP, and S6K in the circulation on type 2 diabetes, based on independent single nucleotide polymorphisms strongly associated (p = 5 × 10^–6) with EIF-4E (16 SNPs), EIF-4A (11 SNPs), EIF-4G (6 SNPs), EIF4EBP2 (12 SNPs), and RP-S6K (16 SNPs). The exposure data were obtained from the INTERVAL study. We applied these SNPs for each exposure to publically available genetic associations with diabetes from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) case (n = 26,676) and control (n = 132,532) study (mean age 57.4 years). We meta-analyzed SNP-specific Wald-estimates using inverse variance weighting with multiplicative random effects and conducted sensitivity analysis. Mendelian Randomization (MR-Base) R package was used in the analysis. The PhenoScanner curated database was used to identify disease associations with SNP gene variants. EIF-4E is associated with a lowered risk of type 2 diabetes with an odds ratio (OR) 0.94, 95% confidence interval (0.88, 0.99, p = 0.03) with similar estimates from the weighted median and MR-Egger. Similarly, EIF-4A was associated with lower risk of type 2 diabetes with odds ratio (OR) 0.90, 95% confidence interval (0.85, 0.97, p = 0.0003). Sensitivity analysis using MR-Egger and weighed median analysis does not indicate that there is a pleiotropic effect. This unbiased Mendelian Randomization estimate is consistent with a protective causal association of EIF-4E and EIF-4A on type 2 diabetes. EIF-4E and EIF-4A may be targeted for intervention by repurposing existing therapeutics to reduce the risk of type 2 diabetes.