Frequency of insulin resistance in nondiabetic adult Bangladeshi individuals of different obesity phenotypes

The triglycerides and glucose index is more strongly associated with metabolically healthy obesity phenotype than the lipid and obesity indices

PURPOSE

The triglycerides and glucose (TyG) index is a reliable biomarker for estimating insulin resistance; however, evidence regarding the use of the TyG index in individuals with metabolically healthy obesity (MHO) is scarce. Thus, we examined the association between the TyG index and the MHO phenotype.

METHODS

Apparently healthy men and women aged 18 years or more with obesity (body mass index [BMI] ≥ 30 kg/m2) were allocated into the following groups: MHO and metabolically unhealthy obesity (MUO). The MHO phenotype was defined by obesity and the absence of the following metabolic disorders: elevated triglyceride concentrations, elevated glucose levels, elevated blood pressure, and low HDL-C. The MUO was defined by individuals with obesity and at least one of the aforementioned cardiovascular risk factors.

RESULTS

A total 827 individuals, 605 (73.1%) women and 222 (26.9%) men were enrolled and allocated into the MHO (n = 104) and MUO (n = 723) groups. The adjusted regression analysis by age, sex, BMI, and waist circumference showed that fasting glucose (OR = 0.90; 95% CI: 0.88-0.93), and triglycerides (OR = 0.97; 95% CI: 0.96-0.98), as well as the triglycerides/HDL-C (OR = 0.18; 95% CI: 0.13-0.26), lipid accumulation product (OR = 0.95; 95% CI: 0.93-0.96), visceral adipose index (OR = 0.38; 95% CI: 0.31-0.46), and TyG index (OR = 0.001; 95% CI: 0.000-0.004) are inversely associated with the MHO, while the HDL-C (OR = 1.10; 95% CI: 1.07-1.12) had a direct association.

CONCLUSIONS

Our results show that the TyG index is more strongly associated with the MHO phenotype than the lipid and obesity indices.

Correlation between insulin-based and C-peptide based homeostatic model assessment of insulin resistance in adults without diabetes in a sub-Saharan African setting: a cross-sectional study

OBJECTIVE

To assess the correlation between the insulin-based and C-peptide based HOMA-IR in the general population without diabetes in sub-Saharan Africa as well as to identify factors associated with IR.

RESULTS

This was a cross-sectional study in urban settings in Yaoundé, Cameroon. We included 84 people with a body mass index (BMI) ≥ 18.5 Kg/m² and without diabetes (females: 72.6%; mean age: 37 years). IR was assessed using the following formulae: HOMA-IR_INS = fasting insulin (mU/ml) x fasting plasma glucose (FPG) (mmol/L)/ 22.5; HOMA-IR_CP1 = fasting C-peptide (mU/ml) x FPG (mmol/L)/ 22.5; and HOMA-IR_CP2 = 1.5 + (FPG (mg/dl) x fasting C-peptide (ng/ml))/ 2800. Correlation (rho) between HOMA-IR_INS and C-peptide based HOMA-IR was investigated using the Spearman rank test. The median (25th -75th percentiles) HOMA-IR_INS, HOMA-IR_CP1, and HOMA-IR_CP2 were: 1.94 (1.36-3.50), 0.18 (0.11-0.27) and 9.91 (6.81-14.52), respectively. There was no correlation between the insulin-based and C-peptide-based HOMA-IR indices: rho = 0.043, p = 0.697. IR (HOMA-IR_INS ≥ 2.8) was associated with obesity: A BMI ≥ 30 Kg/m² (adjusted odds ratio (aOR): 16.9, 95% confidence intervals (CI): 3.1-92.5) and being a student (aOR: 8.9, 95%CI: 2.1-38.2) were associated with IR.

Metabolically obese phenotype and its dynamic change are associated with increased carotid intima-media thickness: Results from a cohort study

BACKGROUND AND AIMS

To examine associations between metabolically obese phenotypes or their changes and increased carotid intima-media thickness (CIMT).

METHODS AND RESULTS

This prospective cohort included 13,681 Chinese adults aged 20-80 years who completed follow-up health examination with carotid ultrasound and were divided according to metabolic and weight status: metabolically healthy and normal weight (MHNW); metabolically obese but normal weight (MONW); metabolically healthy but obese (MHO); metabolically abnormal and obese (MAO). Cox and logistic regression were used to evaluate the associations of the phenotypes or their changes with increased CIMT. During a mean follow-up of 33 months, 1927 participants developed increased CIMT. After adjusting for age, sex and potential biochemical confounders, MAO was significantly associated with increased CIMT (HR 1.22, 95% CI [1.07, 1.4]); the association remained significant in those 40 years or older. Compared with stable MHNW, increased CIMT risk was higher for stable MAO (OR 1.35 [1.16, 1.57]), transitional MAO from MONW (OR 1.44 [1.04, 1.97]), and transitional MHO from MHNW (OR 1.59 [1.10, 2.26]) in demographic adjusted models; only stable MAO remained significant in the multivariate adjusted model (OR 1.23 [1.05, 1.45]).

CONCLUSION

MAO significantly elevated the risk of increased CIMT. Stable MAO and obese transitions also promoted CIMT progression.

Changes in the Expression of Insulin Pathway, Neutrophil Elastase and Alpha 1 Antitrypsin Genes from Leukocytes of Young Individuals with Insulin Resistance

BACKGROUND

Chronic hyperinsulinemia is a hallmark of insulin resistance that affects a diversity of cells, including leukocytes modifying the expression of some genes involved in insulin signaling.

PURPOSE

The aim of this study was to evaluate how hyperinsulinemia affects the expression of genes involved in the proximal insulin signaling pathway in leukocytes from 45 young individuals grouped: normal weight with not insulin resistance (NIR), with insulin resistance (IR) and with obesity (OB-IR).

METHODS

qPCR was performed to analyze the expression of insulin receptor (INSR), insulin receptor substrate 1 and 2 (IRS-1 and IRS-2), neutrophil elastase (NE), alpha 1 antitrypsin (A1AT), glucose transporters 1, 3 and 4 (GLUT-1, GLUT-3 and GLUT-4) by the 2^-ΔCt method, and the correlation between the genes was determined by Spearman's test.

RESULTS

The mRNA expression analysis of all genes between NIR and IR individuals revealed no differences. However, when comparing NIR and IR individuals with OB-IR, an increase in NE and A1AT expression and a clear trend towards a decrease in IRS-2 expression was observed, whereas the comparison of IR and OB-IR showed a decrease in GLUT-3 expression. Overall, the correlation analysis showed that in the IR group there was a positive correlation only between NE with IRS-1 (r = 0.72, p = 0.003), while in the OB-IR group, there was a positive correlation between the NE and A1AT with INSR (r = 0.62, p = 0.01 and r = 0.74, p = 0.002, respectively) and with IRS-2 (r = 0.74, p = 0.002 and r = 0.76, p = 0.001, respectively).

CONCLUSION

These results suggest that hyperinsulinemia and obesity are associated with changes in the expression of genes in leukocytes involved in the insulin pathway that are related to NE and A1AT.

Sample Preparation Methods for Lipidomics Approaches Used in Studies of Obesity

Obesity is associated with alterations in the composition and amounts of lipids. Lipids have over 1.7 million representatives. Most lipid groups differ in composition, properties and chemical structure. These small molecules control various metabolic pathways, determine the metabolism of other compounds and are substrates for the syntheses of different derivatives. Recently, lipidomics has become an important branch of medical/clinical sciences similar to proteomics and genomics. Due to the much higher lipid accumulation in obese patients and many alterations in the compositions of various groups of lipids, the methods used for sample preparations for lipidomic studies of samples from obese subjects sometimes have to be modified. Appropriate sample preparation methods allow for the identification of a wide range of analytes by advanced analytical methods, including mass spectrometry. This is especially the case in studies with obese subjects, as the amounts of some lipids are much higher, others are present in trace amounts, and obese subjects have some specific alterations of the lipid profile. As a result, it is best to use a method previously tested on samples from obese subjects. However, most of these methods can be also used in healthy, nonobese subjects or patients with other dyslipidemias. This review is an overview of sample preparation methods for analysis as one of the major critical steps in the overall analytical procedure.