Risk Of Metabolic Syndrome Research Articles

The association between metabolic syndrome and lung cancer risk: a Mendelian randomization study

The association between metabolic syndrome and lung cancer risk: a Mendelian randomization study

Insulin resistance has closer correlation with the occurrence of metabolic dysfunction associated steatotic liver disease diagnosed by liver biopsy

ObjectiveTo explore any correlation between serum urate (SU) level or insulin resistance (IR) and metabolic dysfunction associated steatotic liver disease (MASLD) in patients with metabolic syndrome (MS).MethodsData from all MASLD patients, diagnosed by liver biopsy, were enrolled and divided into MASLD alone group and MASLD with MS group. They were subdivided into hyperuricemia group and normal SU group to find correlation between SU/IR and MASLD in patients with MS and independent risk factors for MASLD.ResultsData from 539 MASLD patients were analyzed. Body mass index (BMI) (p = 0.000), waist circumference (WC) (p = 0.004), and low-density lipoprotein (LDL) (p = 0.000) were dramatically higher in MASLD with MS group than those with MASLD alone; MASLD with MS patients had significantly more family history of diabetes (p = 0.000) and hypertension (p = 0.000) than patients with MASLD alone. Height (p = 0.000), weight (p = 0.000), BMI (p = 0.000) and WC (p = 0.001), and LDL (p = 0.007) were dramatically higher in hyperuricemia patients than those with normal SU. SU was inversely associated with age (p = 0.000) and high-density lipoprotein (HDL) (p = 0.003), and positively correlated with weight (p = 0.000), BMI (p = 0.000) and WC (p = 0.000), TG (p = 0.000), and LDL (p = 0.000). Logistic Regression analysis showed that age (p = 0.031), TG (p = 0.002), LDL (p = 0.010), HbA1c (p = 0.026), and family history of hypertension (p = 0.000) may be independent risk factors for MASLD in patient with MS.ConclusionInsulin resistance (IR) in MASLD patients with MS, but not higher SU levels, has closer correlation with the occurrence of MASLD in patients with family history of hypertension and diabetes having higher BMI, LDL, HbA1c.

The Role of Vitamin D3 Deficiency and Colonization of the Oral Mucosa by Candida Yeast-like Fungi in the Pathomechanism of Psoriasis

Psoriasis is a chronic inflammatory skin disease with complex pathogenesis and variable severity. Performed studies have indicated the impact of vitamin D3 deficiency on the pathogenesis of psoriasis and its severity. However, there is no clear evidence of the influence of the mucosal microbiome on the onset and progression of psoriasis. This review aims to present the current evidence on the role of vitamin D3 and colonization of the oral mucosa by Candida yeast-like fungi in the pathogenesis of psoriasis. Candida albicans is a common yeast that can colonize the skin and mucosal surfaces, particularly in individuals with weakened immune systems or compromised skin barriers. In psoriasis, the skin’s barrier function is disrupted, potentially making patients more susceptible to fungal infections such as Candida. Since patients with psoriasis are at increased risk of metabolic syndrome, they may experience the vicious circle effect in which chronic inflammation leads to obesity. Vitamin D3 deficiency is also associated with microbiological imbalance, which may promote excessive growth of Candida fungi. Under normal conditions, the intestinal and oral microflora support the immune system. Vitamin D3 deficiency, however, leads to disruption of this balance, which allows Candida to overgrow and develop infections.

Relationship of Body Fat Distribution and Anthropometric Status with Lipid Profiles in Ethnic Minang Adult Women

Background The prevalence of metabolic syndrome is increasing, and it is a risk factor for cardiovascular disease. One of the indicators of metabolic syndrome is dyslipidemia. Objective This study analyzes adult women's body fat distribution, anthropometric status, and lipid profiles. Methods This study used a cross-sectional design with simple random sampling. A total of 159 adult women aged 25-44 living in the Pesisir Selatan district participated in the study. Ethical approval was obtained, and the respondents were not taking cholesterol-lowering drugs. Body fat distribution, anthropometric status, and lipid profile data were assessed using standard procedures and compared with the categories recommended for Indonesian women. Results The average age of respondents was 36.6 years. 45.3% of the respondents suffered from dyslipidemia. Most of them were obese based on BMI and had central obesity based on WC. Additionally, 76% had an above-normal fat mass. Lipid profile data showed that some (45.3%) had high total cholesterol, 44% had high LDL, 8% had high TG, and a small proportion (15%) had low HDL levels. There was a significant relationship (p < 0.01) between body fat distribution and anthropometric status with lipid profiles, except for total cholesterol (p < 0.05). A negative correlation was found between body fat percentage, BMI, and WC with HDL, while a positive correlation existed between body fat percentage, BMI, and WC with TG and LDL levels. Conclusions Obesity is found to be higher, and dyslipidemia begins to occur in women at a younger age, increasing the risk of metabolic syndrome. Education and routine screening are necessary to prevent non-communicable diseases.

Abstract 4137770: Development of a User-Friendly Self-Screening Tool for Assessing Metabolic Syndrome Risk in young adults from economically challenged regions

Background: Metabolic syndrome is a cluster of conditions that increase the risk of heart disease and diabetes. Early identification and management are crucial, particularly in economically challenged regions where access to healthcare may be limited. Research Questions/Hypothesis: User-friendly self-report data accurately predict metabolic outcomes. Aims: To develop and validate nomograms for individualized estimation of metabolic syndrome risk. Methods: Data from 521 college students (60.1% aged 17-20 years; 68.7% female; 28.0% white) were collected in 2022/2023 from two Brazilian cities. These cities are located in the country's poorest states, with Gini indices of 0.56 and 0.43. The potential predictors include demographic and economic variables, school-related factors, behaviors, and body weight. Based on predictors for abdominal obesity identified through multilevel logistic regression, we created a nomogram model. We performed the Hosmer-Lemeshow test to assess model calibration and used a bootstrapping approach (B = 150) for internal validation. To evaluate external validity, we assessed metabolic syndrome in a subset of 375 students. The area under the receiver operating characteristic curve (AUROC), with a threshold of 0.70, was used to evaluate the model's discrimination accuracy. Results: We identified 114 (23.0%) college students who were abdominally obese. We found ten variables associated with the primary outcome: age, biological sex, physical education facilities, enrollment in sports competition (during elementary school); grade retention, preferred subject, physical education classes per week; enrollment in sports training (during secondary school); adherence of 24-hour movement behaviors and body weight. The proposed nomogram showed acceptable performance in the AUROC (0.94 [95% CI: 0.92-0.96). The calibration assessment indicated reasonable consistency of our model (p > 0.05). In the internal validation, we observed a decreased predictive capability (AUROC = 0.86). Conclusion: The 24h-MESYN risk score offers an effective self-screening tool for college students from diverse racial and ethnic backgrounds in economically challenged regions to assess their risk of developing metabolic syndrome.

Gestational Diabetes Mellitus: Unveiling Maternal Health Dynamics from Pregnancy Through Postpartum Perspectives

Gestational Diabetes Mellitus (GDM) is the most frequent pregnancy-related medical issue and presents significant risks to both maternal and foetal health, requiring monitoring and management during pregnancy. The prevalence of GDM has surged globally in recent years, mirroring the rise in diabetes and obesity rates. Estimated to affect from 5% to 25% of pregnancies, GDM impacts approximately 21 million live births annually, according to the International Diabetes Federation (IDF). However, consensus on diagnostic approaches remains elusive, with varying recommendations from international organizations, which makes the comparison between research complicated. Compounding concerns are the short-term and long-term complications stemming from GDM for mothers and offspring. Maternal outcomes include heightened cardiovascular risks and a notable 70% risk of developing Type 2 Diabetes Mellitus (T2DM) within a decade postpartum. Despite this, research into the metabolic profiles associated with a previous GDM predisposing women to T2D remains limited. While genetic biomarkers have been identified, indicating the multifaceted nature of GDM involving hormonal changes, insulin resistance, and impaired insulin secretion, there remains a dearth of exploration into the enduring health implications for both mothers and their children. Furthermore, offspring born to mothers with GDM have been shown to face an increased risk of obesity and metabolic syndrome during childhood and adolescence, with studies indicating a heightened risk ranging from 20% to 50%. This comprehensive review aims to critically assess the current landscape of Gestational Diabetes Mellitus (GDM) research, focusing on its prevalence, diagnostic challenges, and health impacts on mothers and offspring. By examining state-of-the-art knowledge and identifying key knowledge gaps in the scientific literature, this review aims to highlight the multifaceted factors that have hindered a deeper understanding of GDM and its long-term consequences. Ultimately, this scholarly exploration seeks to promote further investigation into this critical area, improving health outcomes for mothers and their children.

Abstract 4134873: Olezarsen for Hypertriglyceridemia in Patients at High Cardiovascular Risk - A Systematic Review and Meta Analysis

Background: Hypertriglyceridemia, a common lipid disorder linked to increased risks of cardiovascular diseases and metabolic syndrome, remains a global health challenge. Traditional treatments, though widely used, often have limited efficacy and adverse effects. Olezarsen, a novel antisense oligonucleotide, targets apolipoprotein C-III and shows promise in significantly reducing triglyceride levels. Aim: To conduct a meta-analysis comparing Olezarsen with placebo in patients with hypertriglyceridemia. Methods: We performed an extensive literature search of PubMed, EMBASE, and Cochrane Library databases up to May 2024 to identify studies comparing Olezarsen and placebo in patients with hypertriglyceridemia, irrespective of comorbid cardiovascular disease. Effect estimates were pooled using a random-effects model and reported as risk ratios (RR) for dichotomous outcomes and standard mean differences (SMD) for continuous outcomes, with 95% confidence intervals (CIs) for each. Results: Three randomized controlled trials (RCTs) with a total of 334 participants were included. Olezarsen significantly reduced triglyceride levels at 6 months (SMD: -1.69; 95% CI -2.22 to -1.17; P < 0.00001; Figure ) and 12 months (SMD: -1.64; 95% CI -2.22 to -1.07; P < 0.00001; Figure ). VLDL levels also decreased at 6 months (SMD: -1.95; 95% CI -2.38 to -1.51; P < 0.00001) and 12 months (SMD: -0.83; 95% CI -1.13 to -0.53; P < 0.00001). Lipid profile improvements included reductions in total cholesterol, non-HDL cholesterol, and apoB levels, with increases in HDL cholesterol and apoA-1. Adverse events were comparable between Olezarsen and placebo, although serious adverse events were significantly higher in the Olezarsen group (RR: 2.55; 95% CI 1.17 to 5.58; p = 0.02). Conclusion: Olezarsen demonstrates significant efficacy in reducing triglyceride and VLDL levels while improving overall lipid profiles in hypertriglyceridemia patients. Despite higher rates of serious adverse events, its overall safety profile remains acceptable.

Metabolic syndrome is associated with poorer outcomes in people with osteoarthritis participating in a rehabilitation program: an observational study

Purpose To determine the prevalence of metabolic syndrome and explore its association with clinical outcomes (pain, quality of life, and physical function) in adults participating in an education and exercise program (GLA:D®). Methods An observational study of adults with hip and/or knee osteoarthritis who participated in GLA:D® between 2019 and 2022. Metabolic syndrome status was determined through self-report. Differences in clinical outcomes among people with, at risk of (1–2 risk factors), or without metabolic syndrome were compared at baseline, 3-, and 12-months using linear mixed models (age, sex, and baseline outcomes as covariates). Results Of 6846 participants (aged 65(SD 9) years), 20% (n = 1337) had, and 68% (n = 4632) were at risk of metabolic syndrome. Adults with metabolic syndrome reported higher pain (0–100 VAS: 7.3, 95% CI 5.4–9.1), lower health-related quality of life (EQ5D 0–100, VAS: −8.6, 95% CI −10.2 to −7.0), and slower gait speed (−0.26 m/s, 95%CI -0.3 to −0.23) at baseline compared to those with no metabolic risk factors. Differences remained at 3- and 12-months for pain and quality of life. Conclusions Metabolic syndrome risk factors were common in adults with osteoarthritis. Clinical outcomes remain impaired in people with metabolic syndrome compared to those without after education and exercise, suggesting further intervention may be required.

Lipid Accumulation Product and Cardiometabolic Index as Effective Tools for the Identification of Athletes at Risk for Metabolic Syndrome

Introduction: Metabolic syndrome (MS) is a growing global public health concern that is associated with increased risk for cardiovascular events, even in athletes. The lipid accumulation product (LAP) index and cardiometabolic index (CMI) have been shown to be efficient markers of MS in the general population; its applicability in athletes has not been discussed yet. We aimed to assess the role of LAP and CMI in predicting MS in athletes. Methods: We retrospectively enrolled 793 Olympic athletes practicing different sporting disciplines (power, skill, endurance, and mixed), classified arbitrarily into no risk (NR), low risk (LR), high risk (HR), or MS if they had 0, 1, 2, or 3 criteria for MS, respectively. Evaluations included a calculation of the LAP index, CMI, anthropometric measurements, and clinical and laboratorial variables. Results: Among our population, only 0.8% reached the criteria for MS, 9.1% were at HR for MS, 37.8% were defined as LR, and 52.3% had NR. Significant differences in anthropometric parameters and the principal components of MS criteria (blood pressure, lipidic profile, glycemia) were reported predominantly in HR athletes and those with MS (p < 0.0001). LAP and CMI presented linearly increasing values from individuals with NR to those with MS (p < 0.0001). In addition, HR and MS athletes were classified as “likely MS” (9.8%) and LR and NR athletes as “unlikely MS” (90.2%). After adjusting for potential confounders, LAP ≥ 34.66 and CMI ≥ 0.776 emerged as independent predictors for MS in the overall cohort (Hazar Ratio (HR) 7.22 [3.75–13.89], p < 0.0001, and HR 5.37 [2.96–9.73], p < 0.0001, respectively). The ROC curve revealed that these cut-offs in the general population predict MS with an area under the curve (AUC) of 0.80 and 0.79, respectively, for LAP and CMI. However, gender-related cut-offs seem to be more precise in predicting MS (LAP ≥ 38.79 for male, LAP ≥ 14.16 for female, and CMI ≥ 0.881 for male and ≥0.965 for female). Conclusion: The ROC curve analyses of LAP and CMI showed good diagnostic accuracy in predicting MS among athletes, despite the low prevalence of MS in our sample. Thus, these indexes may be used to promote screening for primary prevention and early detection of athletes at risk for MS to establish an early prevention strategy. Larger prospective studies are necessary to validate their benefit in the general population.

Combined lifestyle factors and metabolic syndrome risk: a systematic review and meta-analysis.

The metabolic syndrome is a complex condition influenced by many factors including lifestyle. Recently, more and more studies explored the relationships between combined lifestyle factors (often measured as lifestyle scores/indices) and metabolic syndrome due to the co-occurrence of these factors. These scores/indices considered potential interactions among lifestyle factors, offering a more comprehensive understanding of their relationship with metabolic syndrome. However, no review/meta-analysis has been conducted to summarize existing evidence. Thus, this study aimed to synthesize the associations between lifestyle scores/indices and metabolic syndrome in cross-sectional and cohort studies. A literature search was performed in Embase and Medline. Multivariable-adjusted estimates were synthesized using random-effects models. In research where higher scores indicated better health, we used original estimates directly. In studies where higher scores denoted poorer health, we first calculated the coefficients and standard errors based on original estimates. Afterward, we reversed coefficients' directions and recalculated new estimates. Thus, the pooled estimates compared the healthiest with the least-healthy lifestyles (the highest vs. lowest scores/indices). Subgroup analyses were conducted based on study design, region, baseline time, baseline age, sex, health status, metabolic syndrome diagnosis, and lifestyles' number. Sensitivity analyses were performed by including only high-quality studies and employing leave-one-out analyses. Nineteen studies from 16 publications were included. Physical activity, diet, and smoking were the top three included lifestyle factors. Compared to participants with the least-healthy lifestyles, those with the healthiest lifestyles had a 43% lower metabolic syndrome risk (95% confidence interval = 0.41-0.73). In subgroup analyses, healthy lifestyle scores/indices were inversely associated with both metabolic syndrome prevalence in cross-sectional studies (Odds ratio = 0.62; 95% confidence interval = 0.51-0.73) and metabolic syndrome incidence in cohort studies (Odds ratio = 0.40; 95% confidence interval = 0.11-0.68). The inverse association was consistent in other subgroup and sensitivity analyses. Adherence to a healthy lifestyle pattern was beneficial to metabolic syndrome prevention.

Effect of resting heart rate on the risk of metabolic syndrome in adults: a dose-response meta-analysis.

Given the notable rise in the prevalence of metabolic syndrome (MS) in China, it is urgent to identify early screening indicators. Extensive dose-response meta-analyses have been conducted to investigate the association between resting heart rate (RHR) and MS, and additional relevant studies have been updated in the last five years. Therefore, this paper aims to update the results of previous meta-analyses. PubMed, Cochrane Library, Web of Science, and Embase databases were searched from the inception to 25th May 2023. Additional relevant references were manually screened. Quality assessment was performed independently by authors using the Newcastle-Ottawa Scale. Stata 15.0 software was applied for data analysis. A random-effects model was adopted to pool the effect size of hazard ratio (HR) and 95% confidence interval (CI). A restricted cubic spline function was utilized to assess dose-response relationships. The protocol was prospectively registered in PROSPERO (number CRD42023458979). 35 studies from 21 reports were included, with 433,365 adults and 84,354 events of MS and/or diabetes mellitus. The highest RHR tertile was positively associated with the risk of MS [HR = 1.80, 95% CI (1.60, 2.04)]. Dose-response analysis suggested a non-linear correlation between RHR and MS, with a 3.5% increase in risk per unit increase in RHR, at a RHR of 42.5. Both high RHR and its increasing rate are significantly associated with the risk of MS. Therefore, RHR might be a non-invasive and convenient community-based screening tool for the management and monitoring of MS.

Impact of sleep duration and dietary patterns on risk of metabolic syndrome in middle-aged and elderly adults: a cross-sectional study from a survey in Anhui, Eastern China

The aim of this study was to assess the sleep status of middle-aged and elderly adults in Bengbu City, Anhui Province, China, to identify the major dietary patterns, and to analyze the association of different sleep duration and dietary patterns with metabolic syndrome (MetS) and its related influencing factors, as well as to explore the predictive value of sleep duration and dietary patterns. A cross-sectional analysis was performed utilizing data collected from the Community-based Cardiovascular and Health Promotion Study 2019 (COCHPS 2019) conducted in Bengbu. The definition of MetS adhered to the criteria of Guidelines for the Prevention and Treatment of Dyslipidemia in Chinese Adults (2016 Revision). Dietary information was obtained using the Food Frequency Questionnaire (FFQ) to assess dietary intake over the past year. Principal component analysis (PCA) was performed to identify dominant dietary patterns. A logistic regression model was developed to analyze the associations among sleep duration, dietary patterns, and MetS, and a decision tree (DT) model was developed to compare factors affecting MetS and screen people at high risk for MetS. The prevalence of MetS was 13.4% among the 9132 middle-aged and elderly residents over 45 years of age included in COCHPS 2019. Participants were divided into short (< 6 h/d), normal (6–8 h/d), and long (> 8 h/d) groups based on their daily sleep duration. Three dietary patterns were identified by PCA, the fruit-milk pattern, the tubers-meat pattern, and the vegetable-cereal pattern. After adjusting for covariables, logistic regression analysis showed that long sleep duration was significantly negatively associated with MetS. The fruit-milk and vegetable-cereal patterns were negatively associated with MetS, whereas the tubers-meat pattern was positively correlated with MetS. The results of the DT model analysis showed that the vegetable-cereal pattern is the most important factor impacting MetS, followed by marital status, the tubers-meat pattern, the fruit-milk pattern, exercise, sleep duration, and gender. The DT model also screened out five types of MetS high-risk groups. The results of our study indicate that normal sleep duration and consumption of either a fruit-milk or vegetable-cereal diet may lower the likelihood of developing MetS in middle-aged and elderly adults.

Association between the oxidative balance score with metabolic syndrome traits in US adults

ObjectiveTo explore the association between the Oxidative Balance Score (OBS), which represents the balance of multiple oxidative stress-related dietary and lifestyle exposures, and the risk of metabolic syndrome (MetS).MethodsA population-based cross-sectional study design was adopted and 16,850 participants in NHANES database were included in the statistics analysis stage. The OBS was constructed by combining information from 20 a priori selected pro- and antioxidant factors. Weighted logistic regression and restricted cubic splines (RCS) were used to estimate the association between OBS and MetS.ResultsParticipants in the highest OBS quartile, indicating low oxidative stress (OS) levels, exhibited a significantly lower risk of MetS (odds Ratio [OR] = 0.55, 95% confidence Interval [CI]: 0.47–0.64) compared to the lowest quartile. Specifically, higher OBS was inversely associated with abdominal obesity (OR = 0.61, 95% CI: 0.54–0.69), hypertension (OR = 0.69, 95% CI: 0.58–0.83), elevated triglycerides (OR = 0.68, 95% CI: 0.57–0.82), low high-density lipoprotein cholesterol (HDL-C) levels (OR = 0.60, 95% CI: 0.50–0.70) and fasting blood glucose (FBG) levels (OR = 0.74, 95% CI: 0.62–0.88). The observed inverse association between OBS and hypertension or FBG levels appeared to primarily influenced by BMI. The association between dietary OBS intervals and elevated FBG levels was not statistically significant in men, whereas the risk was lower by 25% in women.ConclusionsA higher OBS, representing a balance of multiple oxidative stress-related dietary and lifestyle exposures, is associated with a lower risk of MetS. Therefore, adhering to an antioxidant diet and lifestyle may help prevent the occurrence of metabolic disorders.

Cardio-metabolic Disorders Affected by Genetic Polymorphisms Related to Premature Menopause.

Premature menopause (PM) is defined as the end of ovulation before the age of 40 years, a condition commonly referred to as primary ovarian insufficiency. It has been shown there is an association between early menopause and a high risk of cardiovascular disease. This study aimed to evaluate the effect of genetic polymorphisms related to premature menopause on cardio-metabolic disorders Objective: We aimed to investigate the single nucleotide polymorphisms associated with PM and the risk of cardio-metabolic disorders in the MASHAD cohort study. In this cross-sectional study, a total of 117 women with PM were recruited and compared with 183 healthy women. All participants were assessed for anthropometric indices and genotyped for eight selected polymorphisms within seven different genes. A significant difference was observed in physical activity level (PAL) between the groups. Individuals with rs4806660 CC genotype had a 3.63-fold increased risk of metabolic syndrome. Moreover, individuals with a TT genotype of the rs2303369 polymorphism had a 3.11-- fold increased risk of obesity. Our findings showed that genetic variations are risk factors related to cardio- metabolic disorders in women with premature menopause.

Association between neutrophil-percentage-to-albumin ratio (NPAR) and metabolic syndrome risk: insights from a large US population-based study

Metabolic syndrome (MetS) is a cluster of conditions that increase the risk of cardiovascular disease and diabetes. This study aimed to investigate the association between Neutrophil-Percentage-to-Albumin Ratio (NPAR) and MetS in a large, nationally representative US population. We analyzed data from 28,178 participants in the National Health and Nutrition Examination Survey (NHANES) 2005–2018. Logistic regression models were used to evaluate the association between NPAR and MetS. Restricted cubic spline (RCS) models were employed to assess the dose-response relationship. Mediation analyses were conducted to explore potential mediating effects of serum uric acid and triglyceride-glucose (TyG) index. After adjusting for confounders, participants in the highest NPAR quartile had a 14% higher risk of MetS compared to those in the lowest quartile (OR 1.14, 95%CI 1.03–1.27, P = 0.010). RCS models revealed a monotonic increasing trend between NPAR and MetS risk (P for overall association = 0.002). Mediation analyses showed that serum uric acid and TyG index mediated 14.93% and 29.45% of the total effect of NPAR on MetS, respectively. Subgroup analyses indicated that the positive association between NPAR and MetS was more pronounced in Mexican Americans, individuals aged 20–65 years, those with lower income, males, current smokers, and moderate drinkers. Higher NPAR is associated with increased risk of MetS in the US adult population. This association is partially mediated by serum uric acid and TyG index. These findings suggest that NPAR may serve as a novel biomarker for MetS risk assessment and provide insights into potential mechanisms linking inflammation and metabolic disorders.

Daily and Peak Monitor Independent Movement Summary (MIMS) Values Associated With Metabolic Syndrome: NHANES 2011-12 and 2013-14.

The U.S. National Health and Nutrition Examination Survey (NHANES) physical activity monitor datasets for 2011-12 and 2013-14 were released in late 2020. To date, there has been limited interpretation of these nationally representative wrist-worn accelerometer data (summarized and reported in Monitor Independent Movement Summary [MIMS] units) and their relationships with health-related outcomes. This study examined the associations between free-living DailyMIMS (volume), Peak 1MIMS and Peak 30MIMS (intensity), and risk of Metabolic Syndrome (MetS). Data from adults (N=3787; 18-80+ years) in the 2011-12 and 2013-14 NHANES cycles with health examination and accelerometry data were included. Accelerometer data were processed into Peak 1MIMS and Peak 30MIMS (MIMS/min), and DailyMIMS (MIMS/day). Design-based generalized linear and logistic regressions, and a sample-weighted decision tree, were used to examine associations between MIMS variables and MetS risk factors. Lower Peak 1MIMS, Peak 30MIMS, and DailyMIMS were observed for every one-unit increase in the number of risk factors -3.9 [95% CI: -4.3, -3.4] and -2.3 [-2.6, -2.1] MIMS/min, (-672.1 [-772.7, -571.5] MIMS/day, respectively, all p< 0.001). The Decision Tree classified individuals ≥ 46.5 years with a DailyMIMS ≥ 12 245 MIMS/day and a Peak 30MIMS < 45.1 MIMS/min as having MetS (≥ 3 risk factors). Individuals < 46.5 years with a Peak 1MIMS ≥ 62.9 MIMS/min were classified with 0 risk factors. Higher DailyMIMS and PeakMIMS were associated with an absence of MetS risk factors, with a progressive decline as the number of risk factors increased. These findings may be considered as preliminary benchmarks for DailyMIMS and PeakMIMS associated with cardiometabolic risk.

High-coverage targeted lipidomics revealed novel profile of serum lipid dysregulation in adult growth hormone deficiency.

Patients with adult growth hormone deficiency (AGHD) are at increased risk of metabolic syndrome. Despite extensive research efforts in recent decades, the lipid metabolism pattern of AGHD has yet to be thoroughly characterized. In this study, we used lipidomics analysis of fasting serum samples from 30 AGHD patients due to intracranial germ cell tumors (iGCTs) and 30 age-, gender-, and body mass index (BMI)-matched healthy controls to investigate the serum lipidomic pattern of AGHD patients due to iGCTs. We meticulously quantified 534 serum lipids from 29 classes using high-coverage targeted lipidomics technology in conjunction with a robust bioinformatics pipeline. Our results revealed an AGHD-specific dynamic change in serum lipidomic profile, manifested by higher overall levels of many lipid subclasses, including triacylglycerols (TAGs), diacylglycerols (DAGs), phosphatidylglycerols, phosphatidylethanolamines (PE), phosphatidylcholines (PC), phosphatidylinositols, ceramides, and bis(monoacylglycerol)phosphates than in healthy controls, and a distinct lowering level in alkyl PE (PE-O) and alkyl PC (PC-O). AGHD individuals with non-alcoholic fatty liver disease showed specific changes in higher TAG and DAG subclass levels. Alterations in lipid profiles may contribute to metabolic dysregulation in AGHD patients. TAGs, PCs, and PE-fatty acids positively correlated with BMI, fasting insulin, insulin resistance index, and adverse lipid parameters. In contrast, ether-linked PE-O, PC-O, and LysoPE-O showed a negative correlation. This study has significantly expanded the current understanding of lipid dysregulation in AGHD patients due to iGCT. These findings can potentially guide future research and the development of monitoring and intervention strategies.

Liver magnetic resonance imaging, non-alcoholic fatty liver disease and metabolic syndrome risk in pre-pubertal Mexican boys.

Rising global pediatric obesity rates, increase non-alcoholic fatty liver disease (NAFLD) and metabolic syndrome (MetS) prevalence, with MetS being a NAFLD risk factor. NAFLD can be asymptomatic, with liver function tests insensitive to mild disease, and liver biopsy, risking complications. Thus, we investigated multiparametric MRI (mpMRI) metrics of liver fat (proton density fat fraction, PDFF) and disease activity (fibro-inflammation; iron-corrected T1, cT1), in a Hispanic pre-pubertal pediatric cohort, with increased risk of NAFLD. Pre-pubertal boys (n = 81) of varying Body-Mass Index (BMI) were recruited in Mexico City. Most children (81%) had normal liver transaminase levels, 38% had high BMI, and 14% had ≥ 3 MetS risk factors. Applying mpMRI thresholds, 12%, 7% and 4% of the cohort had NAFLD, NASH and high-risk NASH respectively. Participants with ≥ 3 MetS risk factors had higher cT1 (834ms vs. 737ms, p = 0.004) and PDFF (8.7% vs. 2.2%, p < 0.001) compared to those without risk factors. Those with elevated cT1 tended to have high BMI and high insulin (p = 0.005), HOMA-IR (p = 0.005) and leptin (p < 0.001). The significant association of increased risk of MetS with abnormal mpMRI, particularly cT1, proposes the potential of using mpMRI for routine pediatric NAFLD screening of high-risk (high BMI, high MetS risk score) populations.

Metabolic Risk Factors and Survival in Patients with Glioblastoma.

Metabolic syndrome increases the risk of developing various systemic cancers. The prevalence of metabolic syndrome in newly diagnosed glioblastoma patients is unknown. Further, there have been contradictory reports about how metabolic syndrome affects clinical outcomes. Therefore, the purpose of this study is to test the hypothesis that metabolic syndrome is associated with an increased prevalence of glioblastoma and worsened survival outcomes. This retrospective cohort study examines seventy-three patients with isocitrate dehydrogenase (IDH)-wild-type glioblastoma as it provides a relatively homogeneous population to examine. Patient characteristics, vital signs, lab results, tumor molecular markers, and overall survival were analyzed. Patients with metabolic syndrome and individual risk factors were identified, and survival outcomes were examined. Our results demonstrate that there is a higher prevalence of metabolic syndrome in our cohort of patients with glioblastoma than in the general population (41% vs. 33%), though this effect is confounded by older age. We also demonstrate that after correction for confounding variables, metabolic syndrome is not significantly associated with overall survival (p = 0.1). When analyzing individual metabolic risk factors, we demonstrate that there is a significant association between the accumulation of metabolic risk factors and decreased survival (p = 0.03), and hyperglycemia emerges as a significant independent risk factor for decreased survival (p = 0.05). These results suggest that metabolic risk factors can affect survival in patients with glioblastoma, which can have significant implications for clinical practice. These findings need to be further explored through further clinical and mechanistic studies.

Meal timing and risk of metabolic syndrome in the prospective French NutriNet-Santé biobank

Abstract Background Circadian rhythm disruption has been associated with higher risks of cardiometabolic diseases and several cancers. Mistimed eating patterns can desynchronize circadian rhythms, and could therefore influence metabolic health. However, long-term associations between meal timing and the metabolic syndrome remain unclear. The aim of this study was to evaluate the prospective associations between meal timing and the risk of developing metabolic syndrome. Methods We used measured biological and clinical data from 16 353 adults (51 years ± 13.72) in the NutriNet-Santé biobank (2011-2014), and examined the associations between meal timing, assessed with repeated 24-hour dietary records during the first two years of follow-up (starting 2009), and the risk of metabolic syndrome, using modified Poisson regression models, adjusted for main confounders. Results At the end of follow-up (mean 2.1 years (SD = 1.2)), a later timing of the first meal of the day was associated with a moderately higher risk of metabolic syndrome (1,788 cases; RR per 1-hour delay = 1.05; 95% CI: 1.00-1.10). However, after adjusting for overall diet quality, this association was attenuated (RR: 1.04; 95% CI: 0.99-1.09). Overall, we found no evidence of an association between the occurrence of metabolic syndrome and the time of the last meal (RR: 0.99; 95% CI: 0.95-1.05), the number of eating occasions (RR: 1.00; 95% CI: 0.98 - 1.03), or night-time fasting duration (RR: 1.03; 95% CI: 0.99 1.07). Conclusions In this large prospective study, timing of the first meal showed modest associations with metabolic syndrome. Further investigations using a longer follow-up are needed to elucidate how meal timing influences metabolic health. Key messages • Beyond the nutritional quality of meals, meal timing, particularly time of first meal, may be an accessible prevention strategy for metabolic health. • More largescale prospective and intervention studies are needed to better understand the links between meal timing and metabolic health.