Race and the insulin resistance syndrome

Association of serum total IgE and allergen-specific IgE with insulin resistance in adolescents: an analysis of the NHANES database

BACKGROUND

Recent studies have found that total immunoglobulin E (IgE) and allergen-specific IgE were associated with some metabolic diseases. However, the role of IgE in metabolism among adolescents is still unclear. Herein, this study aims to investigate the associations of serum total IgE and allergen-specific IgE with insulin resistance (IR) in adolescents, in order to provide some reference for the prevention and treatment of metabolic diseases in a young age.

METHODS

Data of 870 adolescents were extracted from the National Health and Nutrition Examination Survey (NHANES) database in 2005-2006 in this cross-sectional study. Weighted univariate and multivariate logistic regression analyses were utilized to screen covariates and explore the relationships of serum total IgE and allergen-specific IgE with IR. The evaluation indexes were odds ratios (ORs) and 95% confidence intervals (CIs). In addition, these relationships were also assessed in subgroups of allergy history, asthma history, and number of allergens.

RESULTS

Among eligible adolescents, 168 had IR. No significant association between serum total IgE level and IR was found. However, adolescents with higher level of allergen-specific IgE to rye grass [OR = 0.47, 95%CI: (0.25-0.91)], white oak [OR = 0.57, 95%CI: (0.37-0.88)], or peanut [OR = 0.38, 95%CI: (0.15-0.97)] seemed to have lower odds of IR, whereas those had higher level of shrimp-specific IgE [OR = 2.65, 95%CI: (1.21-5.84)] have increased odds of IR. In addition, these associations between allergen-specific IgE and IR were also discovered in adolescents who had allergy history or asthma history, or had different numbers of allergens.

CONCLUSION

Paying attention to different allergens in adolescents may be important in the early identification of IR among this high-risk population. The study results relatively provided some reference for further exploration on IR prevention.

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.

Adiposity and family history of type 2 diabetes in an admixed population of adolescents: Associations with insulin sensitivity, beta-cell function, and hepatic insulin extraction in BRAMS study

AIMS

Insulin resistance and beta-cell dysfunction manifest differently across racial/ethnic groups, and there is a lack of knowledge regarding the pathophysiology of type 2 diabetes mellitus (T2DM) for ethnically admixed adolescents. This study aimed to investigate the influence of adiposity and family history (FH) of T2DM on aspects of insulin sensitivity, beta-cell function, and hepatic insulin extraction in Brazilian adolescents.

METHODS

A total of 82 normoglycemic adolescents were assessed. The positive FH of T2DM was defined as the presence of at least one known family member with T2DM. The hyperglycemic clamp test consisted of a 120-min protocol. Insulin secretion and beta-cell function were obtained from C-peptide deconvolution. Analysis of covariance considered pubertal stage as a covariate.

RESULTS

Both lean and overweight/obese adolescents had similar glycemic profiles and disposition indexes. Overweight/obese adolescents had about 1/3 the insulin sensitivity of lean adolescents (1.1 ± 0.2 vs. 3.4 ± 0.3 mg·kg·min·pmol ∗ 1000), which was compensated by an increase around 2.5 times in basal (130 ± 7 vs. 52 ± 10 pmol·l·min) and total insulin secretion (130,091 ± 12,230 vs. 59,010 ± 17,522 pmol·l·min), and in the first and second phases of insulin secretion; respectively (p < 0.001). This increase was accompanied by a mean reduction in hepatic insulin extraction of 35%, and a 2.7-time increase in beta-cell glucose sensitivity (p < 0.05). The positive FH of T2DM was not associated with derangements in insulin sensitivity, beta-cell function, and hepatic insulin extraction.

CONCLUSIONS

In an admixed sample of adolescents, the hyperglycemic clamp test demonstrated that adiposity had a strong influence, and FH of T2DM had no direct influence, in different aspects of glucose metabolism.

Metabolic clustering of risk factors: evaluation of Triglyceride-glucose index (TyG index) for evaluation of insulin resistance

BACKGROUND

Metabolic syndrome over the years have structured definitions to classify an individual with the disease. Literature review suggests insulin résistance is hallmark of these metabolic clustering. While measuring insulin resistance directly or indirectly remains technically difficult in general practice, along with multiple stability issues for insulin, various indirect measures have been suggested by authorities. Fasting triglycerides-glucose (TyG) index is one such marker, which is recently been suggested as a useful diagnostic marker to predict metabolic syndrome. However, limited data is available on the subject with almost no literature from our region on the subject.

OBJECTIVE

1. To correlate TyG index with insulin resistance, anthropometric indices, small dense LDLc, HbA1c and nephropathy. 2. To evaluate TyG index as a marker to diagnose metabolic syndrome in comparison to other available markers.

DESIGN-CROSS-SECTIONAL ANALYSIS

Place and duration of study-From Jun-2016 to July-2017 at PSS HAFEEZ hospital Islamabad.

SUBJECTS AND METHODS

From a finally selected sample size of 227 male and female subjects we evaluated their anthropometric data, HbA1c, lipid profile including calculated sdLDLc, urine albumin creatinine raito(UACR) and insulin resistance (HOMAIR). TyG index was calculated using formula of Simental-Mendía LE et al. Aforementioned parameters were correlated with TyG index, differences between subjects with and without metabolic syndrome were calculated using Independent sample t-test. Finally ROC curve analysis was carried out to measure AUC for candidate parameters including TyG Index for comparison.

RESULTS

TyG index in comparison to other markers like fasting triglycerides, HOMAIR, HDLc and non-HDLc demonstrated higher positive linear correlation with BMI, atherogenic dyslipidemia (sdLDLc), nephropathy (UACR), HbA1c and insulin resistance. TyG index showed significant differences between various markers among subjects with and without metabolic syndrome as per IDF criteria. AUC (Area Under Curve) demonstrated highest AUC for TyG as [(0.764, 95% CI 0.700-0.828, p-value ≤ 0.001)] followed by fasting triglycerides [(0.724, 95% CI 0.656-0.791, p-value ≤ 0.001)], sdLDLc [(0.695, 95% CI 0.626-0.763, p-value ≤ 0.001)], fasting plasma glucose [(0.686, 95% CI 0.616-0.756, p-value ≤ 0.001)], Non-HDLc [(0.640, 95% CI 0.626-0.763, p-value ≤ 0.001)] and HOMAIR [(0.619, 95% CI 0.545-0.694, p-value ≤ 0.001)].

CONCLUSION

TyG index, having the highest AUC in comparison to fasting glucose, triglycerides, sdLDLc, non-HDLc and HOMAIR can act as better marker for diagnosing metabolic syndrome.

Association of treatment response with obesity and other metabolic risk factors in adults with depressive disorders: Results from a National Depression Cohort study in Korea (the CRESCEND study)

BACKGROUND

Available studies indicate that obesity may exert a moderational effect on antidepressant treatment response. The aim of this study was to investigate the relationship between treatment response and metabolic abnormalities amongst patients with depressive disorders in a large naturalistic clinical setting.

METHODS

A nationwide prospective study was conducted in 18 hospitals in South Korea; 541 depressive patients meeting DSM-IV criteria were recruited. After baseline evaluation, subjects received naturalistic clinician-determined antidepressant interventions. Assessment was performed at baseline and weeks 1, 2, 4, 8, 12, 24 and 52. Treatment response was defined as a ≥50% reduction from baseline on at least one evaluation point.

RESULTS

In univariate comparison, the patients who showed insufficient response to antidepressant therapy were more likely to be male, unmarried, unemployed, and obese. After adjusting for baseline variables, male sex (OR=1.82) and obesity (OR=1.55) remained as were significant variables. Stratification of the subjects into one of three groups, i.e. male, pre-menopausal female and post-menopausal female, revealed that males with concurrent metabolic problems, (i.e. the presence of one or more of hypertension, hyperglycemia, or hypercholesterolemia) had significantly higher risk for insufficient response (OR=2.32) and, after adjusting for baseline variables, obesity predicted insufficient response in post-menopausal female (OR=2.41).

CONCLUSIONS

The presence of metabolic abnormalities in patients with depressive disorders was associated with decreased treatment response to antidepressants. These results underscore the neurobiological relationship between obesity and the central nervous system, and provide empiric evidence supporting stratification of treatment response in depression.