Insulin-related biomarkers to predict the risk of metabolic syndrome

Association between neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, and C-reactive protein levels and metabolic status in patients with a bipolar disorder

OBJECTIVES

Neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and C-Reactive Protein (CRP) are markers of inflammation that are elevated in bipolar disorder (BD) and are also related to a higher risk of metabolic syndrome (MetS). This study aimed at investigating for the first time the association between NLR, PLR, and CRP and the metabolic status in BD.

METHODS

We assessed the association between biomarkers and the metabolic status: number of metabolic risk factors, presence of MetS, insulin sensitivity (Quantitative Insulin Sensitivity Check Index, QUICKI) and insulin resistance (Homeostatic Model Assessment for Insulin Resistance, HOMA-IR index), in a sample of 219 outpatients with BD.

RESULTS

25.9% of the sample met the criteria for MetS. High levels of CRP were found in 12% of the sample. Older age, low PLR, high NLR, and high CRP levels significantly predicted a higher number of MetS risk factors (p < 0.001). Older age and low PLR were associated with a greater likelihood of developing MetS (p = 0.007).

CONCLUSIONS

Although further studies are needed to replicate and validate these findings, inflammatory biomarkers as CRP, PLR and NLR could be useful tools to identify patients with a BD at risk for a metabolic adverse outcome.

Association of Serum Uric Acid with cardio-metabolic risk factors and metabolic syndrome in seafarers working on tankers

BACKGROUND

There is still controversy over the clinical interpretation of the association between metabolic syndrome (MetS) and serum uric acid (SUA) levels. Therefore, the aim of this study was to investigate the association of SUA levels with MetS and other cardio-metabolic risk factors (CMRF) in seafarers working on tankers.

METHODS

This cross-sectional study was conducted in 2015 and included 234 male seafarers working on tankers. The participants were divided into three groups based on the tertiles of SUA. The report from of the National Committee of Obesity was used to define the MetS. The relationship between SUA, CMRF and MetS adjusted for age, educational level, job history, shift work, smoking and BMI was assessed by logistic regression analysis.

RESULTS

The subjects were aged 36.0 ± 10.3 years (mean ± SD). A notable upward trend was observed in mean weight, body mass index (BMI), triglyceride (TG), total cholesterol (TC), low density lipoprotein (LDL) and very low-density lipoprotein (VLDL) as tertiles of SUA increased (P < 0.001). In all models of the logistic regression analyses, the odds ratio (OR) of high TG for participants in the 3rd tertile of SUA was four times higher than that for participants in the 1st tertile of SUA (P < 0.001). The odds ratio of high TC and the SUA levels increased, so that the odds ratio of high TC for participants in the 2nd tertile was 2.47 (95% CI: 1.10-5.53) (P < 0.05) as compared with that for participants in the 1st tertile. Significant association was observed between MetS and the levels of SUA; 6.10 (95% CI: 1.77-20.94) (P < 0.05).

CONCLUSIONS

Findings revealed that SUA levels were associated with MetS, high TG and high TC. Therefore, it is recommended that clinical attention should be given to symptoms related to elevated SUA - being one of the most important remediable risk factors for MetS - in the annual medical examinations of seafarers.

Are plasma 25-hydroxyvitamin D and retinol levels and one-carbon metabolism related to metabolic syndrome in patients with a severe mental disorder?

There is a scarcity of studies assessing the influence of biomarkers in metabolic syndrome in psychiatric patients. Our aim was to correlate serum or plasma levels of 25-hydroxyvitamin D (25-OH-VD), retinol, vitamin B12 (VB12), folate and homocysteine (Hcy), with the metabolic status, in a sample of 289 outpatients with Schizophrenia or Bipolar Disorder. Logistic regression and multiple linear regressions were performed to assess the ability of biomarkers to predict the presence of MetS, the number of risk factors for MetS, and insulin resistance indexes (HOMA and QUICKI). Regarding the association between biomarkers and the QUICKI index, the model explained 6.8% of the variance, with folate and 25-OH-VD levels contributing significantly to the model. The model predicting the number of MetS risk factors was significant and explained 21.7% of the variance, being 25-OH-VD and retinol the statistically significant factors. As for the impact of biomarkers on MetS, the model was statistically significant, being 25-OH-VD and retinol levels the significant factors.  We report for the first time an association between MetS and both low 25-OH-VD and high retinol concentrations. Inflammation-related biomarkers may help identify patients with a high risk of MetS who might benefit from healthy lifestyle counselling and early intervention.

Visceral fat reference values derived from healthy European men and women aged 20-30 years using GE Healthcare dual-energy x-ray absorptiometry

Dual energy X-ray absorptiometry (DXA) is an established technique used in clinical and research settings to evaluate total and regional fat. Additionally, recently developed software allow to quantify visceral adipose tissue (VAT). Currently, there are no reference values available for GE Healthcare DXA systems for VAT. The aim of this study was to develop reference values for VAT in healthy European adults aged 20–30 years using a GE Healthcare Prodigy densitometer along with the dedicated CoreScan application. We also assessed the associations of VAT with traditional cardiometabolic risk factors. In 421 participants (207 men; 214 women), we performed DXA whole-body scans and calculated total body fat (BF) and VAT (in gender-specific percentiles). We also measured blood pressure and fasting glucose, insulin, and blood lipids. Males, in comparison with females, had 2-fold greater VAT both in units of mass (542 ± 451 g; 95% CI: 479.6‒605.1 g vs. 258 ± 226 g; 95% CI: 226.9‒288.6 g) and volume (570 ± 468 cm³; 95% CI: 505.1‒635.2 cm³ vs. 273 ± 237 cm³; 95% CI: 240.6‒305.3 cm³). They also had significantly higher the VAT/BF ratio. VAT showed a stronger positive correlation than BF with blood pressure, triglycerides, LDL-cholesterol, glucose, insulin, and homeostasis model assessment-insulin resistance index and a stronger negative correlation with HDL-cholesterol. Among these variables, VAT had the highest area under the curve for triglycerides ≥150 mg/dL (0.727 in males and 0.712 in females). In conclusion, we provide reference values for VAT obtained from healthy adults using the GE Healthcare DXA. These values may be useful in the diagnosis of visceral obesity, for identifying subjects with high obesity-related risks, in epidemiological studies, as a target for therapies, and in physically trained individuals. In both genders, VAT was associated with traditional cardiometabolic risk factors, particularly hypertriglyceridemia.

Differences in physical activity domains, guideline adherence, and weight history between metabolically healthy and metabolically abnormal obese adults: a cross-sectional study

BACKGROUND

Despite the accepted health consequences of obesity, emerging research suggests that a significant segment of adults with obesity are metabolically healthy (MHO). To date, MHO individuals have been shown to have higher levels of physical activity (PA), but little is known about the importance of PA domains or the influence of weight history compared to their metabolically abnormal (MAO) counterpart.

OBJECTIVE

To evaluate the relationship between PA domains, PA guideline adherence, and weight history on MHO.

METHODS

Pooled cycles of the National Health and Nutritional Examination Survey (NHANES) 1999-2006 (≥20 y; BMI ≥ 30 kg/m(2); N = 2,753) and harmonized criteria for metabolic syndrome (MetS) were used. Participants were categorized as "inactive" (no reported PA), "somewhat active" (>0 to < 500 metabolic equivalent (MET) min/week), and "active" (PA guideline adherence, ≥ 500 MET min/week) according to each domain of PA (total, recreational, transportation and household). Logistic and multinomial regressions were modelled for MHO and analyses were adjusted for age, sex, education, ethnicity, income, smoking and alcohol intake.

RESULTS

Compared to MAO, MHO participants were younger, had lower BMI, and were more likely to be classified as active according to their total and recreational PA level. Based on total PA levels, individuals who were active had a 70% greater likelihood of having the MHO phenotype (OR = 1.70, 95% CI: 1.19-2.43); however, once stratified by age (20-44 y; 45-59 y; and; ≥60 y), the association remained significant only amongst those aged 45-59 y. Although moderate and vigorous PA were inconsistently related to MHO following adjustment for covariates, losing ≥30 kg in the last 10 y and not gaining ≥10 kg since age 25 y were significant predictors of MHO phenotype for all PA domains, even if adherence to the PA guidelines were not met.

CONCLUSION

Although PA is associated with MHO, the beneficial effects of PA may be moderated by longer-term changes in weight. Longitudinal analysis of physical activity and weight change trajectories are necessary to isolate the contribution of duration of obesity, PA behaviours, and longer-term outcomes amongst MHO individuals.