Correlation of resistin with inflammatory and cardiometabolic markers in obese adolescents with and without metabolic syndrome.

OBJECTIVE: The link between plasma resistin and obesity-related cardiometabolic disorders in children remains debatable. This study assessed the relationships of plasma resistin with cardiovascular risk factors, pro-inflammatory markers and insulin resistance index (HOMA-IR) in obese (Ob) adolescents and obese adolescents with metabolic syndrome (Ob-MS) compared to healthy controls (CO). METHODS: 114 obese adolescents (60 Ob, age 13.6 ± 0.9 years, BMI 28.0 ± 2.2 kg/m(2), and 54 Ob-MS, age 13.8 ± 1.0 years, BMI 32.5 ± 4.8 kg/m(2)) and 37 CO (age 13.7 ± 0.8 years, BMI 22.8 ± 0.8 kg/m(2)) were studied. Anthropometrics, cardiac variables as well as fasting plasma concentrations of lipids, glucose, insulin, and adipocytokines (resistin, tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), C-reactive protein (CRP)) were measured. HOMA-IR was calculated, and the presence of MS was assessed. RESULTS: Plasma resistin was significantly higher in Ob-MS than in both Ob and CO and was correlated with anthropometric, cardiovascular, pro-inflammatory markers and several components of MS as was HOMA-IR in Ob and Ob-MS. With increasing the number of MS components, plasma resistin, pro-inflammatory markers, and HOMA-IR were also increased. Multiple regression models highlighted significant correlation between resistin and both HOMA-IR (r = 0.40, p < 0.05) and systolic blood pressure (r = 0.63, p < 0.01) in Ob-MS. CONCLUSION: These results support the hypothesis that there is an association between circulating resistin and childhood obesity-related inflammatory and cardiometabolic events.

Validation for quantification of immunoglobulins by Fourier transform infrared spectrometry.

BACKGROUND: The objective of this study was to develop a robust quantification method for simultaneously analyzing molecules in human plasma using the Fourier transform infrared (FT-IR) system with a partial least square (PLS) regression. METHODS: Plasma spectra were analyzed from 4000 to 500 cm(-1) (with 2.0 cm(-1) of resolution and 32 scans), and the molecule concentrations (IgA, IgG, IgM) were measured blindly by using a cross-validation model prepared by PLS analysis of data from 135 samples. RESULTS: There was a significant correlation between the FT-IR predicted concentration and the concentration obtained with the clinical reference method: R(2)=0.98 (IgA), R(2)=0.98 (IgG), and R(2)=0.97 (IgM). The root mean square error of prediction (RMSEP) was 0.05 g.L(-1) (IgA), 0.4 g.L(-1) (IgG), and 0.03 g.L(-1) (IgM). Variability of inter-experimenter reproducibility was less than 2%. The interchangeability of the two methods was studied by using the Bland-Altman method. CONCLUSIONS: Together with PLS analysis, FT-IR spectrometry appears to be an easy-to-use and accurate method to determine multianalyte concentrations in dried human plasma. It could be an alternative tool for rapidly quantifying many molecules after developing a specific predictive model.