Identification and verification of immune-related genes for diagnosing the progression of atherosclerosis and metabolic syndrome.

BACKGROUND: Atherosclerosis and metabolic syndrome are the main causes of cardiovascular events, but their underlying mechanisms are not clear. In this study, we focused on identifying genes associated with diagnostic biomarkers and effective therapeutic targets associated with these two diseases. METHODS: Transcriptional data sets of atherosclerosis and metabolic syndrome were obtained from GEO database. The differentially expressed genes were analyzed by RStudio software, and the function-rich and protein-protein interactions of the common differentially expressed genes were analyzed.Furthermore, the hub gene was screened by Cytoscape software, and the immune infiltration of hub gens was analyzed. Finally, relevant clinical blood samples were collected for qRT-PCR verification of the three most important hub genes. RESULTS: A total of 1242 differential genes (778 up-regulated genes and 464 down-regulated genes) were screened from GSE28829 data set. A total of 1021 differential genes (492 up-regulated genes and 529 down-regulated genes) were screened from the data set GSE98895. Then 23 up-regulated genes and 11 down-regulated genes were screened by venn diagram. Functional enrichment analysis showed that cytokines and immune activation were involved in the occurrence and development of these two diseases. Through the construction of the Protein-Protein Interaction(PPI) network and Cytoscape software analysis, we finally screened 10 hub genes. The immune infiltration analysis was further improved. The results showed that the infiltration scores of 7 kinds of immune cells in GSE28829 were significantly different among groups (Wilcoxon Test < 0.05), while in GSE98895, the infiltration scores of 4 kinds of immune cells were significantly different between groups (Wilcoxon Test < 0.05). Spearman method was used to analyze the correlation between the expression of 10 key genes and 22 kinds of immune cell infiltration scores in two data sets. The results showed that there were 42 pairs of significant correlations between 10 genes and 22 kinds of immune cells in GSE28829 (|Cor| > 0.3 & P < 0.05). There were 41 pairs of significant correlations between 10 genes and 22 kinds of immune cells in GSE98895 (|Cor| > 0.3 & P < 0.05). Finally, our results identified 10 small molecules with the highest absolute enrichment value, and the three most significant key genes (CX3CR1, TLR5, IL32) were further verified in the data expression matrix and clinical blood samples. CONCLUSION: We have established a co-expression network between atherosclerotic progression and metabolic syndrome, and identified key genes between the two diseases. Through the method of bioinformatics, we finally obtained 10 hub genes in As and MS, and selected 3 of the most significant genes (CX3CR1, IL32, TLR5) for blood PCR verification. This may be helpful to provide new research ideas for the diagnosis and treatment of AS complicated with MS.

The discriminative ability of the triglyceride-glucose index to identify metabolic syndrome among adults of the northern Sri Lankan population.

BACKGROUND: The triglyceride-glucose index (TyG index) is a simple surrogate marker for Insulin Resistance (IR). However, the relationship between the TyG index and Metabolic Syndrome (MetS) remains unknown in the Northern Sri Lankan population. METHODS: This was a descriptive, cross-sectional study of adults aged between 18 and 65 years living in Jaffna, Sri Lanka. This study aimed to verify the discriminative ability of the TyG index to identify MetS using the International Diabetes Federation (IDF-2006) criteria and to determine the gender-specific TyG index cut-off values for better prediction of MetS in Northern Sri Lankan adults. TyG index was calculated as Ln[Triglycerides (TG) (mg/dl) × Fasting plasma glucose (FPG) (mg/dl)/2]. RESULTS: A total of 540 individuals were included in this study, with a mean age of 42.18 (± 13.89) years for males and 43.80 (± 12.56) years for females. The mean value of the TyG index in the total study population was 8.54 (± 0.53). Individuals in the higher quartiles of the TyG index had a significantly increased risk of MetS compared with those in the lowest quartile (p < 0.01). TyG index showed a stronger association with MetS than the FPG and all the conventional lipid components and the unadjusted odds ratio was 5.47. The area under the curve (AUC) of ROC revealed values of 0.914 (95% confidence interval (CI): 0.884, 0.944) for females, 0.881 (95% CI: 0.830, 0.932) for males and 0.897 (95% CI: 0.870, 0.924) for the total study population. TyG index had a stronger discriminative ability to identify MetS as per IDF criteria in the study population with a cut-off value of 8.60. The mean level of the TyG index significantly increased with the increasing number of MetS components. CONCLUSIONS: The mean value of the TyG index increased as the number of MetS components in the study population increased. Individuals with a higher TyG index had a significantly increased risk of having MetS compared with the lowest quartile of the TyG index. TyG index had a good discriminative ability to diagnose MetS as per IDF criteria among the northern Sri Lankan population.

The predictive capability of several anthropometric indices for identifying the risk of metabolic syndrome and its components among industrial workers.

Metabolic syndrome (MetS) is closely associated with adverse cardiometabolic outcomes. The objective of this study was to identify practical methods that could enable the effective identification of MetS based on anthropometric indices. The basis of our study involved retrospective database obtained from routine medical prophylactic examinations. This was a cross-sectional study on the health status of male workers employed in hazardous working conditions at industrial enterprises in the Ural region conducted in 2019. A total of 347 male workers employed under hazardous working conditions were investigated. The presence of MetS was established by a healthcare professional in accordance with the guidelines of the International Diabetes Federation (IDF). Simple linear regression was used to evaluate the associations between anthropometric indices and MetS incidence. Logistic regression was used to determine the odds ratios of MetS in relation to increases in anthropometric indices. ROC curves were calculated to compare the ability of each anthropometric index to predict MetS and to determine the diagnostic thresholds of the indicators considered. According to the IDF criteria, 36.3% of the workers had MetS. A direct relationship was found between the individual components of MetS and the anthropometric indices studied. The highest OR was shown by the Body Roundness Index (BRI) of 2.235 (95% CI 1.796-2.781). For different age quartiles, the optimal cut-off values for predicting MetS were as follows: BRI, 4.1-4.4 r.u.; body shape index (ABSI), 0.080-0.083 m11/6 kg-2/3; and lipid accumulation product (LAP), 49.7-70.5 cm mmol/l. The most significant associations with MetS were observed where the values were greater than these cut-off points (Se = 97.4%). The results of this study demonstrated the rapid use of new anthropometric indicators, which have shown good predictive ability and are quite easy to use.

Retrospective Cross-Sectional Study of the Relationship of Thyroid Volume and Function with Anthropometric Measurements, Body Composition Analysis Parameters, and the Diagnosis of Metabolic Syndrome in Euthyroid People Aged 18-65.

Background and Objectives: The thyroid is a key endocrine gland for the regulation of metabolic processes. A body composition analysis (BCA) is a valuable complement to the assessment of body mass index, which is derived only from body weight and height. This cross-sectional retrospective study aimed to investigate the relationships between thyroid volume (TV) and thyroid function parameters, anthropometric measurements, BCA parameters, and the presence of metabolic syndrome (MetS) in adults without clinically overt thyroid disease. Material and Methods: This study involved 45 people (females: 57.8%; MetS: 28.9%) hospitalized for planned diagnostics without signs of acute illness or a deterioration of their health and without thyroid disease, who underwent thyroid ultrasound scans, biochemical tests to assess their thyroid function, MetS assessments, anthropometric measurements, and BCAs using the bioelectrical impedance method. Results: The TV was significantly larger in people with MetS compared to people without MetS. The TV was significantly higher and the serum thyrotropin (TSH) concentration was significantly lower in overweight and obese people than in normal and underweight people. The free triiodothyronine (FT3) serum concentration and TV were correlated with waist circumference and some parameters of the BCA, and the FT3 concentration was also correlated with the body mass index, waist-hip ratio, and waist-height ratio. No significant correlations were found between the FT4 and TSH and the results of the anthropometric and BCA measurements. Conclusions: Even in a population of euthyroid patients without clinically overt thyroid disease, there were some significant relationships between the volume and function of the thyroid gland and the results of their anthropometric parameters, BCAs, and the presence of MetS features.

Superiority of the triglyceride glucose index over the homeostasis model in predicting metabolic syndrome based on NHANES data analysis.

The triglyceride-glucose (TyG) index is a simple and inexpensive new marker of insulin resistance that is being increasingly used for the clinical prediction of metabolic syndrome (MetS). Nevertheless, there are only a few comparative studies on its predictive capacity for MetS versus those using the traditional homeostasis model assessment (HOMA). We conducted a cross-sectional study using a database from the National Health and Nutrition Examination Survey (1999 March to 2020 pre-pandemic period). Using statistical methods, we compared the predictive abilities of the TyG index and HOMA (including HOMA of insulin resistance [HOMA-IR] and HOMA of beta-cell function [HOMA-ß]) for MetS. A total of 34,195 participants were enrolled and divided into the MetS group (23.1%) or no MetS group (76.9%) according to the International Diabetes Federation (IDF) diagnostic criteria. After applying weighted data, the baseline characteristics of the population were described. Following the exclusion of medication influences, the final count was 31,304 participants. Receiver operating characteristic curve analysis revealed that while distinguishing between MetS and no MetS, the TyG index had an area under the curve (AUC) of 0.827 (sensitivity = 71.9%, specificity = 80.5%), and the cutoff was 8.75, slightly outperforming HOMA-IR (AUC = 0.784) and HOMA-ß (AUC = 0.614) with a significance of P < 0.01. The prevalence of MetS in the total population calculated using the TyG index cutoff value was 30.9%, which was higher than that reported in the IDF diagnostic criteria. Weighted data analysis using univariate and multivariate logistic regression displayed an independent association between elevated TyG and HOMA-IR with the risk of MetS. Subgroup analysis further revealed differences in the predictive ability of the TyG index among adult populations across various genders and ethnicities, whereas such differences were not observed for children and adolescents. The TyG index is slightly better than HOMA in predicting MetS and may identify more patients with MetS; thus, its applications in a clinical setting can be appropriately increased.

Alanine aminotransferase predicts incident steatotic liver disease of metabolic etiology: Long life to the old biomarker!

Alanine aminotransferase (ALT) serum levels increase because of hepatocellular damage. Metabolic dysfunction-associated fatty liver disease (MAFLD), which identifies steatotic liver disease (SLD) associated with ≥ 2 metabolic abnormalities, has prominent sexual differences. The Metabolic Syndrome defines a cluster comprising abdominal obesity, altered glucose metabolism, dyslipidemia, and hypertension. Male sex, body mass index, glucose, lipids, ferritin, hypertension, and age independently predict ALT levels among blood donors. Over the last few decades, the reference range of ALT levels has been animatedly debated owing to attempts to update sex-specific reference ranges. With this backset, Chen et al have recently published a study which has two main findings. First, > 80% of individuals with MAFLD had normal ALT levels. Second, there was a linear increasing trend in the association between cumulative excess high-normal ALT levels and the rate of incident MAFLD. This study has biologically credible findings. However, it inaccurately considered sex differences in the MAFLD arena. Therefore, future studies on SLD owing to metabolic dysfunction should adopt locally determined and prospectively validated reference ranges of ALT and carefully consider sex differences in liver enzymes and MAFLD pathobiology.

Machine Learning-Assisted Analysis of Sublingual Microcirculatory Dysfunction for Early Cardiovascular Risk Evaluation and Cardiovascular-Kidney-Metabolic Syndrome Stage in Patients With Type 2 Diabetes Mellitus.

AIMS: To examine whether sublingual microcirculation can be used as an effective and noninvasive method for assessing cardiovascular, kidney, and metabolic risks in patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: This cross-sectional observational study enrolled 186 patients with T2DM. All patients were evaluated using the Framingham General Cardiovascular Risk Score (FGCRS) and cardiovascular-kidney-metabolic (CKM) syndrome stage. Side-stream dark-field microscopy was used for sublingual microcirculation, including total and perfused vessel density (TVD and PVD). Multiple machine-learning prediction models have been developed for CKM risk and stage assessment in T2DM patients. Receiver operating characteristic (ROC) curves were generated to determine cutoff points. RESULTS: Compared to patients with T2DM, diabetic patients with subclinical atherosclerosis (SA) had a greater CV risk, as measured by the FGCRS, accompanied by markedly decreased microcirculation perfusion. Microcirculatory parameters (TVD and PVD), including carotid intima-media thickness (IMT), brachial-ankle pulse wave velocity (ba-PWV), and FGCRS, were closely associated with SA incidence. Microcirculatory parameters, Index (DMSA screen), and cut-off points were used to screen for SA in patients with T2DM. Furthermore, a new set of four factors identified through machine learning showed optimal sensitivity and specificity for detecting CKM risk in patients with T2DM. Decreased microcirculatory perfusion served as a useful early marker for CKM syndrome risk stratification in patients with T2DM without SA. CONCLUSIONS: Sublingual microcirculatory dysfunction is closely correlated with the risk of SA and CKM risk in T2DM patients. Sublingual microcirculation could be a novel tool for assessing the CKM syndrome stage in patients with T2DM.

Risk of Cardiovascular Events Associated with Chronic Obstructive Pulmonary Disease and/or Metabolic Syndrome: A Large-Scale Nationwide Population-Based Cohort Study.

Purpose: Chronic obstructive pulmonary disease (COPD) and metabolic syndrome (MetS) are among the most prevalent conditions that might predispose individuals to life-threatening events. We aimed to examine their associations with cardiovascular (CV) events and mortality using a large-scale population dataset from the National Health Information Database in Korea. Patients and Methods: This population-based cohort study enrolled adults aged ≥40 years who had undergone more than two health examinations between 2009 and 2011. They were divided into four groups based on the presence of COPD and MetS. Analysis of the outcomes and CV events or deaths was performed from 2014 to 2019. We compared CV event incidence and mortality rates using a multivariate Cox proportional hazards model and Kaplan-Meier curves. Results: Totally, 5,101,810 individuals were included, among whom 3,738,458 (73.3%) had neither COPD nor MetS, 1,193,014 (23.4%) had only MetS, 125,976 (2.5%) had only COPD, and 44,362 (0.9%) had both. The risk of CV events was significantly higher in individuals with both COPD and MetS than in those with either COPD or MetS alone (HRs: 2.4 vs 1.6 and 1.8, respectively; all P <0.001). Similarly, among those with both COPD and MetS, all-cause and CV mortality risks were also elevated (HRs, 2.9 and 3.0, respectively) compared to the risks in those with either COPD (HRs, 2.6 and 2.1, respectively) or MetS (HRs, 1.7 and 2.1, respectively; all P <0.001). Conclusion: The comorbidity of MetS in patients with COPD increases the incidence of CV events and all-cause and cardiovascular mortality rates.

Evaluation of Fasting Glucose-Insulin-C-Peptide-Derived Metabolic Indices for Identifying Metabolic Syndrome in Young, Healthy Adults.

Metabolic syndrome (MetS) is a condition defined by a cluster of symptoms, including excessive adipose tissue, impaired glucose homeostasis, dyslipidemia, and high blood pressure (BP). We aimed to evaluate the correlation between the MetS criteria (IDF) and fasting glucose-insulin-C-peptide-derived indices in a cohort of 128 healthy young adults who were 20-35 years old at the time of this study. We measured fasting serum glucose, insulin, C-peptide (CP), HDL-cholesterol, triglycerides, and hsCRP; HOMA-IR INS, HOMA-IR CP1, HOMA-IR CP2, HOMA-BETA, HOMA-BETA CP, QUICKI, disposition index (DI), CP index (CPI), and 20/C-peptide*glucose. Significant correlations were found between BMI and all HOMA indices, QUICKI, and CPI; waist circumferences and HOMA-IR INS, HOMA-BETA, and QUICKI (for both sexes); glucose and HOMA-IR INS/CP1/CP2, HOMA-BETA CP, DI, and QUICKI; HDL-cholesterol and HOMA-IR INS, HOMA-BETA, and QUICKI for males and females only with QUICKI; triglycerides and HOMA-IR INS, HOMA-BETA, and QUICKI; systolic BP and HOMA-IR INS, HOMA-BETA; diastolic BP and DI. The cut-off values for HOMA-IR INS, HOMA-BETA, and QUICKI in the combined group (females + males) were 1.855, 82.250, 0.355; 2.115, 106.370, 0.345 for males; 1.805, 71.305, 0.355 for females. A stronger correlation was found between males' indices and hsCRP. In conclusion, CP-derived indices do not add significant information, and the male sex is more predisposed to MetS.

[Research progress in biosensors for adiponectin].

Adiponectin, a cytokine associated with adipose tissue, is a recently defined adipocytokine involved in insulin, glucose, and adipocyte metabolism. Reduced adiponectin levels can increase the risk of developing metabolic syndrome (MS). Adiponectin is considered an important target for the treatment of type 2 diabetes mellitus (T2DM) and MS due to its anti-atherosclerotic and insulin-sensitizing effects. Therefore, the accurate determination of adiponectin concentrations in human plasma is necessary for the management of both T2DM and MS. A variety of biosensors have been developed for the detection of biomarkers such as adiponectin. This paper reviews the applications of electrochemical sensors, surface-enhanced Raman scattering sensors, and microfluidic chip-based chemiluminescence sensors in the detection of adiponectin and the recent research progress in the sensors for the detection of adiponectin, aiming to provide a reference for the research and application of sensors for adiponectin in the medical field.

MetSCORE: a molecular metric to evaluate the risk of metabolic syndrome based on serum NMR metabolomics.

BACKGROUND: Metabolic syndrome (MetS) is a cluster of medical conditions and risk factors correlating with insulin resistance that increase the risk of developing cardiometabolic health problems. The specific criteria for diagnosing MetS vary among different medical organizations but are typically based on the evaluation of abdominal obesity, high blood pressure, hyperglycemia, and dyslipidemia. A unique, quantitative and independent estimation of the risk of MetS based only on quantitative biomarkers is highly desirable for the comparison between patients and to study the individual progression of the disease in a quantitative manner. METHODS: We used NMR-based metabolomics on a large cohort of donors (n = 21,323; 37.5% female) to investigate the diagnostic value of serum or serum combined with urine to estimate the MetS risk. Specifically, we have determined 41 circulating metabolites and 112 lipoprotein classes and subclasses in serum samples and this information has been integrated with metabolic profiles extracted from urine samples. RESULTS: We have developed MetSCORE, a metabolic model of MetS that combines serum lipoprotein and metabolite information. MetSCORE discriminate patients with MetS (independently identified using the WHO criterium) from general population, with an AUROC of 0.94 (95% CI 0.920-0.952, p < 0.001). MetSCORE is also able to discriminate the intermediate phenotypes, identifying the early risk of MetS in a quantitative way and ranking individuals according to their risk of undergoing MetS (for general population) or according to the severity of the syndrome (for MetS patients). CONCLUSIONS: We believe that MetSCORE may be an insightful tool for early intervention and lifestyle modifications, potentially preventing the aggravation of metabolic syndrome.

Metabolic score for insulin resistance (METS-IR) predicts all-cause and cardiovascular mortality in the general population: evidence from NHANES 2001-2018.

BACKGROUND: The prevalence of obesity-associated insulin resistance (IR) is increasing along with the increase in obesity rates. In this study, we compared the predictive utility of four alternative indexes of IR [triglyceride glucose index (TyG index), metabolic score for insulin resistance (METS-IR), the triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio and homeostatic model assessment of insulin resistance (HOMA-IR)] for all-cause mortality and cardiovascular mortality in the general population based on key variables screened by the Boruta algorithm. The aim was to find the best replacement index of IR. METHODS: In this study, 14,653 participants were screened from the National Health and Nutrition Examination Survey (2001-2018). And TyG index, METS-IR, TG/HDL-C and HOMA-IR were calculated separately for each participant according to the given formula. The predictive values of IR replacement indexes for all-cause mortality and cardiovascular mortality in the general population were assessed. RESULTS: Over a median follow-up period of 116 months, a total of 2085 (10.23%) all-cause deaths and 549 (2.61%) cardiovascular disease (CVD) related deaths were recorded. Multivariate Cox regression and restricted cubic splines analysis showed that among the four indexes, only METS-IR was significantly associated with both all-cause and CVD mortality, and both showed non-linear associations with an approximate "U-shape". Specifically, baseline METS-IR lower than the inflection point (41.33) was negatively associated with mortality [hazard ratio (HR) 0.972, 95% CI 0.950-0.997 for all-cause mortality]. In contrast, baseline METS-IR higher than the inflection point (41.33) was positively associated with mortality (HR 1.019, 95% CI 1.011-1.026 for all-cause mortality and HR 1.028, 95% CI 1.014-1.043 for CVD mortality). We further stratified the METS-IR and showed that significant associations between METS-IR levels and all-cause and cardiovascular mortality were predominantly present in the nonelderly population aged < 65 years. CONCLUSIONS: In conjunction with the results of the Boruta algorithm, METS-IR demonstrated a more significant association with all-cause and cardiovascular mortality in the U.S. population compared to the other three alternative IR indexes (TyG index, TG/HDL-C and HOMA-IR), particularly evident in individuals under 65 years old.

Adaptation of the Barriers, Attitudes, Confidence, and Knowledge Scale (M-BACK-Tr) into Turkish culture to assess the metabolic health of psychiatric professionals and investigation of Its psychometric characteristics.

AIM: The aim was to evaluate the validity and reliability of the "Barriers, Attitudes, Confidence, and Knowledge Scale for Assessing Metabolic Health" (M-Back-Tr) to determine the barriers, attitudes, confidence, and knowledge status of psychiatry professionals in the assessing of metabolic syndrome. METHODS: This methodological study was conducted with 304 psychiatric nurses who were working in public and private healthcare institutions between March and June 2023. Translation and back-translation were made into the Turkish language during the adaptation process and it was found that there was no semantic shift between the versions. While the validity of M-Back-Tr was tested with content validity, construct validity, and convergent validity, its internal reliability and Split-Half Test Reliability were examined for reliability. RESULTS: The structure of M-Back-Tr, which consists of 4 dimensions (i.e., Barriers, Attitudes, Confidence, Knowledge) and 16 items, was confirmed in Turkish culture. This structure can explain 73 % of the variance in the related concept. The minimum score that can be taken from each sub-dimension is 4 and the maximum is 20. The Cronbach α value of the sub-dimensions of the scale was found to be between 0.79 and 0.91. CONCLUSION: The study findings showed that the M-Back-Tr is a valid and reliable measurement tool that can be used in Turkish culture.

Diagnosis of metabolic syndrome in nursing professionals: An accuracy study.

Metabolic Syndrome (MetS) represents a group of cardiovascular risk factors. This article aims to evaluate the accuracy of the tools of MetS diagnosis in Nursing professionals from Primary Health Care (PHC) in Bahia, Brazil. A cross-sectional study with a random sample selected according to essential health information for the diagnostic of MetS. For MetS diagnostic, we used EGIR, NCEP-ATPIII, AACE, IDF, Barbosa et al. (2006), and IDF/AHA/NHLBI (defined as gold standard) definition. Sensitivity, specificity, predictive values, and likelihood ratio were estimated for each diagnostic tool and compared with the gold standard. Kappa statistic was used to determine the agreement between the diagnostic methods. One thousand one hundred and eleven nursing professionals were included in this study. Sensitivity varied from 15% to 95.1%, and specificity varied between 99.5% and 100%. IDF and Barbosa et al. (2006) definitions were more sensitive (95.1% and 92.8%, respectively), and EGIR, NCEP, ATP III, and IDF showed 100% specificity. IDF and Barbosa et al. (2006) use suitable metabolic syndrome identification and confirmation criteria. The highest agreement was found in the definition of the IDF, Barbosa et al. (2006) and the NCEP ATP III. Defining metabolic syndrome with a higher diagnostic accuracy could contribute to the screening and the early identification of nursing professionals with cardiovascular disease risk factors, which provide opportunities for appropriate prevention and treatment.

Metabolic syndrome parameters' variability and stroke incidence in hypertensive patients: evidence from a functional community cohort.

BACKGROUND: Stroke is a common complication of hypertension, but the predictive value of metabolic syndrome parameters' variability on stroke risk in individuals with hypertension remains unclear. Therefore, our objective was to investigate the relationship between metabolic syndrome parameters' variability and the risk of total stroke and its subtypes in hypertensive patients. METHODS: This prospective cohort study included 17,789 individuals with hypertension from the Kailuan study since 2006. Metabolic syndrome parameters, including waist circumference (WC), fasting blood glucose (FBG), systolic blood pressure (SBP), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG), were collected at three follow-up visits in the 2006, 2008, and 2010 surveys. We assess the variability utilizing the coefficient of variation (CV), standard deviation (SD), average real variation (ARV), and variability independent of the mean (VIM), with CV initially assessed. Participants were categorized based on the number of high-variability metabolic syndrome parameters (0, 1, 2, ≥ 3). Stroke cases were identified by reviewing medical records. The associations between variability in metabolic syndrome parameters and the risk of total stroke and its subtypes were analyzed using Cox proportional hazard regression models. RESULTS: During a median follow-up of 9.32 years, 1223 cases of stroke were recorded. Participants with ≥ 3 high-variability metabolic syndrome parameters had an increased risk of total stroke (HR: 1.29, 95%CI 1.09-1.52), as well as an increased risk of ischemic stroke (HR: 1.31, 95%CI 1.05-1.63) compared to those without high-variability parameters. The study also examined variability in each metabolic syndrome parameter, and significant associations with an increased risk of total stroke were observed for variability in SBP (HR: 1.24, 95%CI 1.05-1.46) and HDL-C (HR: 1.34, 95%CI 1.09-1.64). CONCLUSIONS: Long-term fluctuations in metabolic syndrome parameters significantly increase the risk of total stroke, especially ischemic stroke. Maintaining low variability in metabolic syndrome parameters could benefit health, and hypertensive individuals must be regularly monitored.

The role of small dense LDL-C/large buoyant LDL-C ratio as an independent risk factor in patients with type 2 diabetes mellitus and metabolic syndrome

Dyslipidemia plays a key role in metabolic syndrome (MS), intricately linked to type 2 diabetes mellitus (T2DM). This study aimed to investigate the differences in low-density lipoprotein cholesterol (LDL-C) subfraction levels between T2DM and T2DM with MS, and identify the risk factors associated with the disease. A total of 246 individuals diagnosed with T2DM, including 144 T2DM patients with MS, and 147 healthy subjects were recruited. All participants underwent a comprehensive clinical evaluation. Lipoprotein subfraction analysis was performed using the Lipoprint LDL system. Multivariate logistic regression analysis revealed that several lipid markers, including triglyceride (TG), LDL-C, large buoyant LDL-C (lbLDL-C), small dense LDL-C (sdLDL-C), LDLC2-5, and sdLDL-C/lbLDL-C ratio, were identified as independent risk factors for T2DM. Additionally, TG, sdLDL-C, LDLC-4, LDLC-5, and sdLDL-C/lbLDL-C ratio were found to be independent risk factors for T2DM with MS. Furthermore, the results of the receiver operating characteristic (ROC) curves demonstrated that sdLDL-C, LDLC-4, LDLC-3, and sdLDL-C/lbLDL-C ratio exhibited excellent predictive performance for the risk of T2DM (AUC > 0.9). The sdLDL-C/lbLDL-C ratio emerges as a shared independent risk factor for T2DM and MS complications. Furthermore, sdLDL-C/lbLDL-C ratio, along with LDL-4 and LDL-3, exhibits noteworthy predictive capabilities for T2DM.

Presence of metabolic syndrome markers in very low birth weight ex-premature infants during early adolescence.

OBJECTIVES: To investigate the association of growth patterns with overweight/obesity and markers of metabolic syndrome in ex-premature adolescents; to assess the relationship between the increase (1 SD) in Z-score weight at term and at 2 years with outcomes in adolescents with or without intrauterine growth restriction; and to evaluate the association between the Cook criteria and overweight/obesity according to body mass index. METHODS: Cohort, retrospective, analytical study. Population: adolescents born weighting<1,500 g. RESULTS: One hundred twenty-seven adolescents (11.3 years) were included. There is an association between the 1 SD increase in the percentile (Pc) of weight at 40 weeks and at 2 years in the population with adequate birth weight (PCA) with insulin levels, resistance, and sensitivity at 11 years. Catch-up at 2 years was associated with significantly higher proportion of HDL value<41 (18.75 vs. 5.36 %) OR 4.08 95% CI (1.04-16.05) p=0.031. Overweight/obesity was associated with waist circumference index>0.5, HDL<41, and with blood pressure greater than Pc 90 for sex and height. CONCLUSIONS: In preterm infants, a 1 SD increase in weight Z score at 40 weeks and 2 years was predictive of metabolic and cardiovascular disorders in adolescence.

Estimated pulse wave velocity as a forefront indicator of developing metabolic syndrome in Korean adults.

BACKGROUND/AIMS: The predictive value of the estimated pulse wave velocity (ePWV) for the development of metabolic syndrome has not yet been extensively explored. This study aimed to fill this gap by evaluating ePWV as a potential predictor of metabolic syndrome development in middle-aged Korean adults. METHODS: Using prospective data obtained from the Ansan-Ansung cohort database, participants without metabolic syndrome at baseline were studied. ePWV was calculated using specific equations based on age and blood pressure. The primary outcome was the incidence of metabolic syndrome during a median follow-up period of 187 months. RESULTS: Among the 6,186 participants, 2,726 (44.1%) developed metabolic syndrome during the follow-up period. ePWV methvalues were categorized into tertiles to assess their predictive value for the development of metabolic syndrome. An ePWV cut-off of 7.407 m/s was identified as a predictor of metabolic syndrome development, with a sensitivity of 0.743 and a specificity of 0.464. Participants exceeding this cut-off, especially those in the third tertile (8.77-14.63 m/s), had a notably higher risk of developing metabolic syndrome. Specifically, the third tertile exhibited a 52.8% cumulative incidence compared with 30.8% in the first tertile. After adjustments, those in the third tertile faced a 1.530-fold increased risk of metabolic syndrome (95% confidence interval, 1.330-1.761). CONCLUSION: ePWV is a significant predictor of the development of metabolic syndrome. This finding underscores the potential of ePWV as a cardiometabolic risk assessment tool and can thus provide useful information for primary prevention strategies.