Metabolic syndrome and related disorders最新文献

With the change in lifestyle of people, there has been a considerable increase in diabetes, which brings with it certain follow-up pathological conditions, which lead to a substantial medical burden. Identifying biomarkers that aid in screening, diagnosis, and prognosis of diabetes and its associated pathologies would help better patient management and facilitate a personalized treatment approach for prevention and treatment. With the advancement in techniques and technologies, metabolomics has emerged as an omics approach capable of large-scale high throughput data analysis and identifying and quantifying metabolites that provide an insight into the underlying mechanism of the disease and its progression. Diabetes and metabolomics keywords were searched in correspondence with the assigned keywords, including kidney, cardiovascular diseases and critical illness from PubMed and Scopus, from its inception to Dec 2023. The relevant studies from this search were extracted and included in the study. This review is focused on the biomarkers identified in diabetes, diabetic kidney disease, diabetes-related development of CVD, and its role in critical illness.

Introduction: Chronic kidney disease (CKD) is associated with metabolic disorders. However, the evidence for the causality of circulating metabolites to promote or prevent CKD is still lacking. Methods: The two-sample Mendelian randomization (MR) analysis was conducted to evaluate the latent causal relationship between the genetically proxied 486 blood metabolites and CKD. Genome-wide association study (GWAS) data for exposures were derived from 7824 European GWAS on metabolite levels, which have been extensively utilized in the medical field to elucidate the mechanisms underlying disease onset and progression. The random inverse variance weighted (IVW) is the primary analysis for causality analysis while MR-Egger and weighted median as complementary analyses. For the further identification of metabolites, reverse MR and linkage disequilibrium score regression were performed for further evaluation. The drug target for N-acetylornithine was subsequently supplemented into the analysis, with MR and colocalization analysis being utilized. Key metabolic pathways were identified via MetaboAnalyst 4.0 (https://www.metaboanalyst.ca/) online website. Results: N-acetylornithine was identified as a reliable metabolite that increases the susceptibility to estimated glomerular filtration rate (eGFR) decrease (β = 0.047; 95% confidence interval: -0.068 to -0.026; P_IVW = 1.5E-5). The "glyoxylate and dicarboxylate metabolism" pathway showed significant relevance to CKD development (P = 6E-4), whereas the "glycine, serine, and threonine metabolism" pathway was also recognized as associated with CKD by general practitioners (P = 7E-4). Colocalization analysis revealed a robust genetic link between N-acetylornithine and both CKD and eGFR, with 85.1% and 99.4% colocalization rates, respectively. IVW-MR analysis substantiated these findings with a significant positive association for CKD (odds ratio = 1.43, P = 4.7E-5) and a negative correlation with eGFR (b = -0.04, P = 1.13E-31). Conclusions: MR was utilized to explore the potential causal links between 61 genetic serum metabolites and CKD. N-acetylornithine and NAT8 were further explored as a potential therapeutic target for CKD treatment.

Aims: Exercise interventions positively affect numerous cardiometabolic risk factors. To better evaluate the health effects of exercise training, it may be more appropriate to evaluate risk factors together. The Metabolic Syndrome Severity Score (MetSSS) is a composite score representing cardiometabolic risk. Purpose: To evaluate the relationships between physical activity, neuromuscular fitness, exercise capacity, and the MetSSS in a heterogenous sample of people with complex chronic disease. Material and Methods: Fifty-three people with kidney or liver disease and at least one feature of the metabolic syndrome (MetS) were included. Pearson correlations were conducted between physical activity, neuromuscular fitness, exercise capacity, and the MetSSS. Linear regressions were performed for multi-level categorical variables. Independent variables with an association with MetSSS (P ≤ 0.2) were included in a multiple regression analysis. Results: The 6-minute walk test (6MWT) distance was inversely and independently associated with MetSSS [standardized beta coefficient (β) = -0.31, P = 0.04]. No relationship was found between MetSSS and physical activity or neuromuscular fitness. Mean 6MWT in the highest tertile was 550 m (range: 505-620 m) and 346 m (range: 233-408 m) in the lowest. The analysis showed a medium-large between-group effect for the difference in MetSSS for the lowest and highest tertile of 6MWT [Eta squared (η²) = 0.16, P = 0.01]. Conclusions: Exercise capacity was inversely and independently associated with MetSSS in people with complex chronic disease. Clinical trials with exercise interventions are needed to further investigate if improvements in exercise capacity result in clinically significant changes in the MetSSS.

Background: The interaction between COVID-19 infection, hyperglycemia, and insulin resistance (IR) may lead to poor outcome. Methods: This prospective study included 100 adult participants without diabetes attending Alexandria Fever Hospital with confirmed COVID-19 infections. They were classified into four groups according to disease severity using World Health Organization (WHO) criteria. Demographic and clinical parameters were collected. Laboratory investigations were obtained. Another follow-up fasting plasma glucose (FPG) value was measured after 3 months in cured patients. Results: Admission FPG, follow-up FPG, lipid profile, markers of IR, and inflammation were significantly higher in severe and critical cases than in mild and moderate cases with increasing values with increased severity. Furthermore, these parameters were significantly higher in died cases compared with cured cases. Admission FPG, TyG index, and homeostatic model assessment (HOMA)-IR showed significant positive correlations with follow-up FPG. Admission FPG was the only independent mortality predictor in multivariate analysis (P = 0.027) with 1.7-folds increased mortality risk with each 10 mg/dL increments. Values exceeding 117 mg/dL, 2.2, and 6.33 for admission FPG, HOMA-IR, and Fasting Insulin Resistance Index, respectively, were able to predict mortality in the studied sample. Conclusions: These results will help in identifying patients at high risk of severe infection and death at admission and take early actions to improve outcome.

Introduction: Effective management of dyslipidemias is crucial for reducing morbidity and mortality among patients after acute coronary syndrome (ACS). Sex differences in dyslipidemia management after premature ACS in Israeli patients have not been extensively studied. This study aimed to investigate potential disparities between men and women in managing dyslipidemia, considering current guidelines. Methods: This retrospective cohort study examined patients who were 55 years old or younger and admitted to Meir Medical Center for ACS from January 2018 to February 2019. The study aimed to evaluate the use of lipid-lowering therapy (LLT), measure the achievement of target low-density lipoprotein cholesterol (LDL-C) levels, and analyze the occurrence of major adverse cardiovascular and cerebrovascular events (MACCE) in both male and female patients. Results: The study included a total of 687 participants, of which 23.3% were identified as females. Upon discharge, ∼80% of the patients were prescribed high-intensity statins. After 1 year, it was observed that females had higher levels of LDL-C and lower rates of achieving target LDL-C levels (<70 and 55 mg/dL) as compared with males (45% vs. 54.6% and 30% vs. 42.2%, respectively). The use of non-statin LLT at the 1-year mark was minimal in both groups. Finally, it was found that the occurrence of MACCE was similar between males and females. Conclusion: Sex disparities in dyslipidemia management after a premature ACS were apparent, with females having higher LDL-C levels and lower rates of target achievement. Intervention is necessary to address these disparities and encourage greater use of non-statin LLT.

Introduction: Obesity (OB), type 2 diabetes mellitus (T2D), and hypertension (HTN) are health issues in Mexico linked to unhealthy behaviors. This study investigates the relationship between behavior change indicators and metabolic control in Mexican adults with OB, T2D, and HTN. Methods: We used data from the 2016 National Health and Nutrition Survey Midway (ENSANUT MC-2016), representing ∼59.5 million Mexican adults aged 20-59 with these conditions. We assessed behavior change indicators, including stages of change, self-efficacy, and perceptions of benefits and barriers. In addition, we conducted descriptive analyses and used statistical tests, such as Pearson's chi-squared test and logistic regression models, adjusted for multiple variables. Results: We found that adults in the action and maintenance stages of physical activity (PA) were four times more likely to have adequate HTN control than those in the precontemplation stage. Self-efficacy for PA was related to better control in T2D and HTN. Self-efficacy for reducing the consumption of sugary beverages was positively associated with control in OB and T2D. No significant association was observed with self-efficacy for consuming fruits and vegetables. Conclusion: Behavior-change indicators are significantly linked to metabolic control in adults with HTN. These results support the importance of these indicators in managing chronic diseases such as HTN and their potential use in public health strategies.

Background: Altering the dietary patterns can potentially decrease the likelihood of metabolic syndrome and circadian syndrome (CircS), but it remains unclear which types of flavonoid compounds are responsible for these effects, particularly among nationally representative populations. Thus, we conducted a cross-sectional study to investigate the impact of flavonoid intake on CircS. Methods: The study included 9212 noninstitutionalized adults from two survey cycles (2007-2008 and 2009-2010) of the National Health and Nutrition Examination Survey (NHANES). Data on six dietary flavonoids were collected through a 24-hr dietary recall, including isoflavones, anthocyanidins, flavan-3-ols, flavanones, flavones, and flavonols. All statistical analyses were weighted to account for the complex survey sampling design to generate nationally representative estimates. Multivariable logistic regression and propensity score matching (PSM) were performed to control for potential confounders and assess the association between the six flavonoids and risk of short sleep. Results: After adjusting for all covariates, only individuals with high intake of total flavanones exhibited a 28% [odds ratio (OR) = 0.72, 95% confidence interval (CI) = 0.64-0.83, P < 0.001] decrease in the risk of CircS. The results obtained through PSM were consistent with this finding (OR = 0.70, 95% CI = 0.61-0.80, P < 0.001). Total flavanone intake displayed a linear dose-response relationship with the likelihood of CircS (P for interaction = 0.448). Conclusions: Our findings suggest that high dietary intakes of flavanones have beneficial effects on reducing the risk of CircS.

Background and Aim: There is limited evidence to support the relationship between dietary patterns and metabolic phenotypes. Therefore, this study aimed to assess the association of dietary patterns with metabolic phenotypes among a large sample of Iranian industrial employees. Methods: This cross-sectional study was conducted among 3,063 employees of Esfahan Steel Company, Iran. Using exploratory factor analysis, major dietary patterns were obtained from a validated short form of food frequency questionnaire. The metabolic phenotypes were defined according to Adult Treatment Panel III guidelines. The independent-sample t-test, one-way analysis of variance, χ² test, and multivariable logistic regression were applied to analyze data. Results: Three major dietary patterns were identified by factor analysis: the Western dietary pattern, the healthy dietary pattern, and the traditional dietary pattern. After controlling for potential confounders, subjects in the highest tertile of Western dietary pattern score had a higher odds ratio (OR) for metabolically healthy obese (MHO; OR 1.58, 95% confidence interval [CI]: 1.29-1.94), metabolically unhealthy normal weight (OR 1.93, 95% CI 1.08-3.45), and metabolically unhealthy obese (MUHO) phenotypes (OR 2.87, 95% CI 2.05-4.03) than those in the lowest tertile. Also, higher adherence to traditional dietary pattern was positively associated with a higher risk of MHO (OR 1.91, 95% CI 1.56-2.34) and MUHO phenotypes (OR 2.33, 95% CI 1.69-3.22) in the final model. Conclusion: There were significant associations between dietary patterns and metabolic phenotypes, suggesting the necessity of nutritional interventions in industrial employees to improve metabolic phenotype, health outcomes, and, therefore, job productivity in the workforce population.

Purpose: To determine whether high-sensitivity C-reactive protein (hsCRP) is associated with incident Metabolic Syndrome (MetS) among U.S. Hispanic/Latino adults. Patients and Methods: The Hispanic Community Health Study/Study of Latinos is a longitudinal observational cohort assessing cardiovascular health among diverse U.S. Hispanic/Latino adults. hsCRP was measured at visit 1 (2008-2011) and classified as low, moderate, or high, based on the Centers for Disease Control and Prevention and American Heart Association (CDC/AHA) guidelines. All MetS components [abdominal obesity, triglycerides, high-density lipoprotein (HDL) cholesterol, blood pressure, and fasting glucose] were measured at visit 1 and visit 2 (2014-2017). MetS was defined as the presence of three or more components based on the 2005 definition from the modified Third Report of the National Cholesterol Education Program Adult Treatment Panel (modified NCEP ATP III). Participants free of MetS at visit 1 and with complete data on hsCRP and all MetS components were included (n = 6121 participants). We used Poisson regression analysis to determine whether hsCRP was associated with incident MetS after adjusting for demographic, behavioral, and clinical factors. All analyses accounted for the complex survey design of the study. Results: In fully adjusted models, moderate versus low hsCRP was associated with a 33% increased risk of MetS [incidence rate ratio (IRR): 1.33, 95% confidence interval (CI): 1.10-1.61], while high versus low hsCRP was associated with a 89% increased risk of MetS (IRR: 1.89, 95% CI: 1.58-2.25). Conclusions: Greater levels of hsCRP were associated with new onset of MetS in a diverse sample of U.S. Hispanic/Latino adults. Results suggest that hsCRP may be an independent risk factor for MetS.

Purpose: The type 2 diabetes (T2D) burden is disproportionately concentrated in low- and middle-income economies, particularly among rural populations. The purpose of the systematic review was to evaluate the inclusion of rurality and social determinants of health (SDOH) in documents for T2D primary prevention. Methods: This systematic review is reported following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. We searched 19 databases, from 2017-2023, for documents on rurality and T2D primary prevention. Furthermore, we searched online for documents from the 216 World Bank economies, categorized by high, upper-middle, lower-middle, and low income status. We extracted data on rurality and the ten World Health Organization SDOH. Two authors independently screened documents and extracted data. Findings: Based on 3318 documents (19 databases and online search), we selected 15 documents for data extraction. The 15 documents applied to 32 economies; 12 of 15 documents were from nongovernment sources, none was from low-income economies, and 10 of 15 documents did not define or describe rurality. Among the SDOH, income and social protection (SDOH 1) and social inclusion and nondiscrimination (SDOH 8) were mentioned in documents for 25 of 29 high-income economies, while food insecurity (SDOH 5) and housing, basic amenities, and the environment (SDOH 6) were mentioned in documents for 1 of 2 lower-middle-income economies. For U.S. documents, none of the authors was from institutions in noncore (most rural) counties. Conclusions: Overall, documents on T2D primary prevention had sparse inclusion of rurality and SDOH, with additional disparity based on economic status. Inclusion of rurality and/or SDOH may improve T2D primary prevention in rural populations.