Severity of the metabolic syndrome as a predictor of prediabetes and type 2 diabetes in first degree relatives of type 2 diabetic patients: A 15-year prospective cohort study

Trajectory patterns of metabolic syndrome severity score and risk of type 2 diabetes

BACKGROUND

The available evidence indicates that the severity of metabolic syndrome tends to worsen progressively over time. We assessed the trajectory of age and sex-specific continuous MetS severity score (cMetS-S) and its association with the development of diabetes during an 18-year follow-up.

METHODS

In a prospective population-based Tehran Lipid and Glucose Study, 3931 eligible participants free of diabetes, aged 20-60 years, were followed at three-year intervals. We examined the trajectories of cMetS-S over nine years using latent growth mixture modeling (LGMM) and subsequent risks of incident diabetes eight years later. The prospective association of identified trajectories with diabetes was examined using the Cox proportional hazard model adjusting for age, sex, education, and family history of diabetes, physical activity, obesity (BMI ≥ 30 kg/m2), antihypertensive and lipid-lowering medication, and baseline fasting plasma glucose in a stepwise manner.

RESULTS

Among 3931 participants, three cMetS-S trajectory groups of low (24.1%), medium (46.8%), and high (29.1%) were identified during the exposure period. Participants in the medium and high cMetS-S trajectory classes had HRs of 2.44 (95% CI: 1.56-3.81) and 6.81 (95% CI: 4.07-10.01) for future diabetes in fully adjusted models, respectively. Normoglycemic individuals within the high cMetS-S class had an over seven-fold increased risk of diabetes (HR: 7.12; 95% CI: 6.05-12.52).

CONCLUSION

Although most adults exhibit an unhealthy metabolic score, its severity usually remains stable throughout adulthood over ten years of follow-up. The severity score of metabolic syndrome has the potential to be utilized as a comprehensive and easily measurable indicator of cardiometabolic dysfunction. It can be employed in clinical settings to detect and track individuals at a heightened risk of developing T2DM, even if their glucose levels are normal.

Gut Microbiota and Serum Metabolites in Individuals with Class III Obesity Without Type 2 Diabetes Mellitus: Pilot Analysis

Background: Gut microbial composition seems to change in association with prediabetes. The purpose of this prospective cross-sectional study was to compare the composition of gut microbiota and energy metabolites between individuals with class III obesity but without type 2 diabetes mellitus (OB) and healthy normal weight controls. Methods: The subjects of this prospective cross-sectional study were participants recruited from a previous clinical trial (No: NCT02325804), with intervention focused on weight loss. We recruited 19 OB [mean age ± standard deviation (SD) was 35.4 ± 7.0 years, mean body mass index (BMI) ± SD was 48.8 ± 6.7 kg/m²] and 23 controls (mean age ± SD was 31.7 ± 14.8 years, mean BMI ± SD was 22.2 ± 1.7 kg/m²). Their fecal microbiota was categorized using specific primers targeting the V1-V3 region of 16S rDNA, whereas serum metabolites were characterized by nuclear magnetic resonance spectroscopy. Multivariate statistical analysis and Random Forest models were applied to discriminate predictors with the highest variable importance. Results: We observed a significantly lower microbial α-diversity (P = 0.001) and relative abundance of beneficial bacterium Akkermansia (P = 0.001) and the short-chain fatty acid-producing bacteria Eubacterium hallii (P = 0.019), Butyrivibrio (P = 0.024), Marvinbryantia (P = 0.010), and Coprococcus (P = 0.050) and a higher abundance of the pathogenic bacteria Bilophila (P = 0.018) and Fusobacterium (P = 0.022) in OB compared with controls. Notably, the Random Forest machine learning analysis identified energy metabolites (citrate and acetate), HOMA-IR, and insulin as important predictors capable of discriminating between OB and controls. Conclusions: Our results suggest that changes in gut microbiota and in serum acetate and citrate are additional promising biomarkers before progression to Type 2 diabetes. The non-invasive manipulation of gut microbiota composition in OB through a healthy lifestyle, thus, offers a new approach for managing class III obesity and associated disorders. ClinicalTrials.gov identifier: NCT02325804.

Prediabetes is more than a pre-disease: additional evidences supporting the importance of its early diagnosis and appropriate treatment

AIM

To identify Prediabetes (PreD) as early and serious diabetes step using clinical-biochemical characteristics in the population of the Primary Prevention Diabetes Buenos Aires (PPDBA) study.

METHODS

PPDBA Study evaluated benefits of adopting healthy lifestyles to prevent T2D. It recruited people 45-75 years of age with PreD (impaired fasting glycaemia [IFG], impaired glucose tolerance [IGT] or both, American Diabetes Association criteria), using an opportunistic approach. They completed a FINDRISC questionnaire, and those with a score ≥13 points were invited to participate. When they accepted, we performed an oral glucose tolerance test (OGTT) with a complete lipid profile and HbA1c while physicians completed a clinical history. We recruited 367 persons, and depending on OGTT results, the sample was divided into normals (NGT), PreD, or with diabetes (last one was excluded in our analysis). Data were statistically analyzed using parametric and nonparametric tests and logistic regression to identify parameters associated with PreD.

RESULTS

From the recruited (n = 367) 47.7% have NGT, 48.5% PreD and 3.8% unknown T2D (excluded). People with PreD were significantly older, with a higher percentage of overweight/obesity, BMI, and larger waist circumference than NGT. They also showed significantly higher fasting and 2 h post glucose load, HbA1c, and triglyceride levels. No significant differences were recorded in the blood pressure, lipid profile though both groups had abnormally high LDL-c values. They also had a larger percentage of TG/HDL-c ratios (insulin resistance indicator) (55% vs. 37.5%). Logistic regression analysis showed that PreD was significant associated with age, waist circumference, and triglyceride above target values.

CONCLUSION

Our findings showed that clinical and biochemical parameters were significantly different between people with PreD and those with NGT. This evidence supports the concept that PreD is a serious dysfunction, which should be early diagnosed and treated properly to prevent its transition to T2D and its complications.

The beneficial effect of a comprehensive diabetes care model on high-risk relatives accompanying patients with type 2 diabetes

AIMS

Assess the effect of a diabetes program on lifestyle, metabolic, and mental health parameters in relatives of patients with T2D, and correlate changes between relatives and patients.

METHODS

Relatives were included in a structured program for patients with T2D. They received individualized interventions or were asked to follow lifestyle modifications indicated to their patient with diabetes. Outcomes were change in BMI, fat loss, patients achieving LDL-c and triglycerides goals, exercise, and mental health indicators at three and twelve months.

RESULTS

We included 200 relatives. Obesity was present in 42 %, hypertension in 8.5 %, hypercholesterolemia in 29.5 %, and hypertriglyceridemia in 46 % of relatives. Relatives lost - 3.7 kg and - 3.0 kg of body fat at three months and one-year evaluations. At least 60 % achieved normal triglycerides and LDL-c, and 40 % exercised at least 150 min/week. Anxiety symptoms dropped from 37 % to 22 % (p = 0.001), and depressive symptoms from 22 % to 12.9 % (p = 0.01) at three months. Correlations were found between the changes in relatives and patients in weight at three months (r = 0.22, p = 0.001), one year (r = 0.3, p < 0.001), and the number of goals achieved at one year.

CONCLUSION

Relatives of patients with diabetes attending a multidisciplinary program for T2D benefit in metabolic, lifestyle, and mental health indicators.

Specific metabolic syndrome components predict cognition and social functioning in people with type 2 diabetes mellitus and severe mental disorders

OBJECTIVE

Obesity and metabolic diseases such as metabolic syndrome (MetS) are more prevalent in people with type 2 diabetes mellitus (T2DM), major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ). MetS components might be associated with neurocognitive and functional impairments in these individuals. The predictive and discriminatory validity of MetS and its components regarding those outcomes were assessed from prospective and transdiagnostic perspectives.

METHODS

Metabolic syndrome components and neurocognitive and social functioning were assessed in 165 subjects, including 30 with SZ, 42 with BD, 35 with MDD, 30 with T2DM, and 28 healthy controls (HCs). A posteriori, individuals were classified into two groups. The MetS group consisted of those who met at least three of the following criteria: abdominal obesity (AO), elevated triglycerides (TG), reduced high-density lipoprotein cholesterol (HDL), elevated blood pressure (BP), and elevated fasting glucose (FPG); the remaining participants comprised the No-MetS group. Mixed one-way analysis of covariance and linear and binary logistic regression analyses were performed.

RESULTS

Cognitive impairment was significantly greater in the MetS group (n = 82) than in the No-MetS group (n = 83), with small effect sizes (p < 0.05; η²p = 0.02 - 0.03). In both groups, the most robust associations between MetS components and neurocognitive and social functioning were observed with TG and FPG (p < 0.05). There was also evidence for a significant relationship between cognition and BP in the MetS group (p < 0.05). The combination of TG, FPG, elevated systolic BP and HDL best classified individuals with greater cognitive impairment (p < 0.001), and TG was the most accurate (p < 0.0001).

CONCLUSIONS

Specific MetS components are significantly associated with cognitive impairment across somatic and psychiatric disorders. Our findings provide further evidence on the summative effect of MetS components to predict cognition and social functioning and allow the identification of individuals with worse outcomes. Transdiagnostic, lifestyle-based therapeutic interventions targeted at that group hold the potential to improve health outcomes.