Breath biomarkers of insulin resistance in pre-diabetic Hispanic adolescents with obesity

AbstractInsulin resistance (IR) affects a quarter of the world’s adult population and is a major factor in the pathogenesis of cardio-metabolic disease. In this pilot study, we implemented a non-invasive breathomics approach, combined with random forest machine learning, to investigate metabolic markers from obese pre-diabetic Hispanic adolescents as indicators of abnormal metabolic regulation. Using the ReCIVA breathalyzer device for breath collection, we have identified a signature of 10 breath metabolites (breath-IR model), which correlates with Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) (R = 0.95, p < 0.001). A strong correlation was also observed between the breath-IR model and the blood glycemic profile (fasting insulin R = 0.91, p < 0.001 and fasting glucose R = 0.80, p < 0.001). Among tentatively identified metabolites, limonene, undecane, and 2,7-dimethyl-undecane, significantly cluster individuals based on HOMA-IR (p = 0.003, p = 0.002, and p < 0.001, respectively). Our breath-IR model differentiates between adolescents with and without IR with an AUC-ROC curve of 0.87, after cross-validation. Identification of a breath signature indicative of IR shows utility of exhaled breath metabolomics for assessing systemic metabolic dysregulation. A simple and non-invasive breath-based test has potential as a diagnostic tool for monitoring IR progression, allowing for earlier detection of IR and implementation of early interventions to prevent onset of type 2 diabetes mellitus.

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Breath biomarkers of insulin resistance in pre-diabetic Hispanic adolescents with obesity

10.1101/2021.06.23.21259399 ◽

2021 ◽

Author(s):

Mohammad S Khan ◽

Suzanna Cuda ◽

Genesio M Karere ◽

Laura A Cox ◽

Andrew C Bishop

Keyword(s):

Insulin Resistance ◽

Metabolic Regulation ◽

Adult Population ◽

Characteristic Curve ◽

Exhaled Breath ◽

Model Assessment ◽

Hispanic Adolescents ◽

Metabolic Markers ◽

Non Invasive ◽

Homeostatic Model Assessment

ABSTRACT Background: Insulin Resistance (IR) affects a quarter of the world's adult population and is a major factor in the pathogenesis of cardio-metabolic disease. Non-invasive sampling of exhaled breath contains metabolic markers indicative of underlying systemic metabolic abnormality. Method: In this pilot study, we implemented a non-invasive breathomics approach, combined with random forest machine learning, to investigate metabolic markers from pre-diabetic Hispanic adolescents with obesity as indicators of abnormal metabolic regulation. Findings: Exhaled breath collection using the ReCIVA breathalyzer is feasible in an adolescent population. We have identified a signature of breath metabolites (breath-IR model) which correlates with Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) (R = 0.95, p <0.001). A strong correlation was also observed between the breath-IR model and the blood glycemic profile (fasting insulin R=0.91, p <0.001 and fasting glucose R=0.80, p <0.001). Among tentatively identified metabolites, limonene, undecane, and 2,7-dimethyl-undecane, significantly cluster individuals based on HOMA-IR (p =0.003, p =0.002, and p<0.001, respectively). Our breath-IR model differentiates between adolescents with and without IR with an area under the receiver operating characteristic curve of 0.87, after cross-validation. Interpretation: Identification of a breath metabolite signature indicative of IR in prediabetic Hispanic adolescents with obesity provides evidence of the utility of exhaled breath metabolomics for assessing systemic metabolic dysregulation. A simple and non-invasive breath-based test has utility as a diagnostic tool for monitoring IR progression, potentially allowing for earlier detection of IR and implementation of early interventions to prevent onset of type 2 diabetes mellitus.

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Sex differences in the link between blood cobalt concentrations and insulin resistance in adults without diabetes

Environmental Health and Preventive Medicine ◽

10.1186/s12199-021-00966-w ◽

2021 ◽

Vol 26 (1) ◽

Author(s):

Yong Chen ◽

Haobin Huang ◽

Xiaowei He ◽

Weiwei Duan ◽

Xuming Mo

Keyword(s):

Insulin Resistance ◽

Linear Regression ◽

Linear Models ◽

Fasting Glucose ◽

Adult Population ◽

Linear Regression Analysis ◽

Cobalt Concentration ◽

Model Assessment ◽

Homeostatic Model Assessment ◽

Cobalt Exposure

Abstract Background Little is known about the effects of environmental cobalt exposure on insulin resistance (IR) in the general adult population. We investigated the association between cobalt concentration and IR. Methods A total of 1281 subjects aged more than 20 years with complete blood cobalt data were identified from the National Health and Nutrition Examination Survey (NHANES) 2015–2016 cycle. Blood cobalt levels were analyzed for their association with IR among all populations and subgroups by sex. Regression coefficients and 95% confidence intervals (CIs) of blood cobalt concentrations in association with fasting glucose, insulin and homeostatic model assessment of insulin resistance (HOMA-IR) were estimated using multivariate linear regression after adjusting for age, sex, ethnicity, alcohol consumption, body mass index, education level, and household income. A multivariate generalized linear regression analysis was further carried out to explore the association between cobalt exposure and IR. Results A negative association between blood cobalt concentration (coefficient = − 0.125, 95% CI − 0.234, − 0.015; P = 0.026) and HOMA-IR in female adults in the age- and sex-adjusted model was observed. However, no associations with HOMA-IR, fasting glucose, or insulin were found in the overall population. In the generalized linear models, participants with the lowest cobalt levels had a 2.74% (95% CI 0.04%, 5.50%) increase in HOMA-IR (P for trend = 0.031) compared with subjects with the highest cobalt levels. Restricted cubic spline regression suggested that a non-linear relationship may exist between blood cobalt and HOMA-IR. Conclusions These results provide epidemiological evidence that low levels of blood cobalt are negatively associated with HOMA-IR in female adults.

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Association of Serum Levels of Zinc, Copper, and Iron with Risk of Metabolic Syndrome

Nutrients ◽

10.3390/nu13020548 ◽

2021 ◽

Vol 13 (2) ◽

pp. 548

Author(s):

Chia-Wen Lu ◽

Yi-Chen Lee ◽

Chia-Sheng Kuo ◽

Chien-Hsieh Chiang ◽

Hao-Hsiang Chang ◽

...

Keyword(s):

Insulin Resistance ◽

Metabolic Syndrome ◽

Linear Models ◽

Serum Zinc ◽

Serum Levels ◽

Least Square ◽

Model Assessment ◽

Serum Concentrations ◽

Metabolic Factors ◽

Homeostatic Model Assessment

The association between serum concentrations of zinc, copper, or iron and the risk of metabolic syndrome are inconclusive. Therefore, we conduct a case-control study to explore the relationship between serum levels of zinc, copper, or iron and metabolic syndrome as well as each metabolic factor and insulin resistance. We enrolled 1165 adults, aged ≥ 40 (65.8 ± 10) years in a hospital-based population to compare the serum levels of zinc, copper, and iron between subjects with and without metabolic syndrome by using multivariate logistic regression analyses. The least square means were computed by general linear models to compare serum concentrations of zinc, copper, and iron in relation to the number of metabolic factors. The mean serum concentrations of zinc, copper, and iron were 941.91 ± 333.63 μg/L, 1043.45 ± 306.36 μg/L, and 1246.83 ± 538.13 μg/L, respectively. The odds ratios (ORs) of metabolic syndrome for the highest versus the lowest quartile were 5.83 (95% CI: 3.35–10.12; p for trend < 0.001) for zinc, 2.02 (95% CI: 1.25–3.25; p for trend: 0.013) for copper, and 2.11 (95% CI: 1.24–3.62; p for trend: 0.021) for iron after adjusting for age, sex, personal habits, body mass index, and homeostatic model assessment insulin resistance. Additionally, the serum zinc, copper, and iron concentrations increased as the number of metabolic factors rose (p for trend < 0.001). This was the first study to clearly demonstrate that higher serum levels of zinc, copper, and iron were associated with the risk of metabolic syndrome and the number of metabolic factors independent of BMI and insulin resistance.

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Metabolic syndrome and insulin resistance in pre-pubertal children with psoriasis

European Journal of Pediatrics ◽

10.1007/s00431-020-03924-w ◽

2021 ◽

Author(s):

Francesca Caroppo ◽

Alfonso Galderisi ◽

Laura Ventura ◽

Anna Belloni Fortina

Keyword(s):

Metabolic Disease ◽

Insulin Resistance ◽

Metabolic Syndrome ◽

Model Assessment ◽

Limited Data ◽

Single Center ◽

Increased Risk ◽

High Prevalence ◽

Homeostatic Model Assessment ◽

Homeostatic Model

AbstractPsoriasis in adults is associated with an increased risk of metabolic disease. Various cardiometabolic comorbidities have been reported in childhood psoriasis, but only a few studies have analyzed the prevalence of metabolic syndrome. We performed a single-center prospective study investigating the prevalence of metabolic syndrome and insulin resistance in children with psoriasis. The prevalence of metabolic syndrome was evaluated in 60 pre-pubertal children with psoriasis (age: 3–10 years), accordingly to recently established criteria for the diagnosis of metabolic syndrome in children. Insulin resistance was considered altered when the homeostatic model assessment (HOMA-IR) for insulin resistance was ≥ 90th sex- and age-specific percentile and HOMA 2-IR was > 1.8. Eighteen (30%) children with psoriasis were found to have metabolic syndrome. Sixteen (27%) children were found to have insulin resistance.Conclusion: Our data underline the importance of assessing metabolic syndrome not only in adults and adolescents but also in young children with psoriasis. What is Known:• Psoriasis in adults is strongly associated with metabolic disease and insulin resistance.• Very limited data are available on the prevalence of metabolic syndrome and insulin resistance in pre-pubertal children with psoriasis. What is New:• This study reports that in pre-pubertal children with psoriasis, there is a high prevalence of metabolic syndrome and insulin resistance.• In children with psoriasis metabolic syndrome risk factors should be assessed.

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P1279INSULIN RESISTANCE IN HEMODIALYSIS PATIENS

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfaa142.p1279 ◽

2020 ◽

Vol 35 (Supplement_3) ◽

Author(s):

Pavel Filinyuk ◽

Aleksander Rumyantsev

Keyword(s):

Insulin Resistance ◽

Systemic Inflammation ◽

Clinical Manifestations ◽

Biological Response ◽

Fold Increase ◽

Atherogenic Dyslipidemia ◽

Model Assessment ◽

Peripheral Tissues ◽

Reactive Protein ◽

Homeostatic Model Assessment

Abstract Background and Aims insulin resistance (IR) is a decrease in the biological response of sensitive tissues to insulin. IR is known as an adverse risk factor in cardiovascular disease, which largely determines the prognosis of patients receiving hemodialysis (HD). But this issue is not well understood. For the screening of IR, special indices have been developed that characterize the sensitivity of tissues to insulin. The aim of the study was to compare the methods of screening for IR in patients receiving HD in relation to the markers of systemic inflammation and atherogenic dyslipidemia (AtD). Method 124 patients receiving HD for 75.4 ± 44.5 months were examined including 66 men and 58 women aged 57.6 ± 13.6 years. For IR screening, the Homeostatic Model Assessment-1 and 2 indices (HOMA-1 and HOMA-2), the Quantitative Insulin Sensitivity Check Index (QUICKI) and triglycerides / glucose (Tri/G) were used. Patients were examined in accordance with the recommendations of KDIGO. Data analysis was carried out using “STATISTICA 10.0”. Results fasting insulin levels were elevated in 19% of patients. But, the calculated indices were consistent with the idea that IR is much more common. So, the IR index in the HOMA -1 model was increased in 47%, in the HOMA -2 model - in 33%, in the QUICKI model - in 36%, the TriH indicator - in 91%. The sensitivity of peripheral tissues in the HOMA-1 and HOMA-2 models was equally reduced by 35-40%. The results of the correlation analysis between indicators of IR and plasma concentration of C-reactive protein and lipid profile are presented in table 1. Informativeness of IR indicators depending on the presence of obesity is presented in table 2 We were also interested in whether insulin resistance affects the development of clinical manifestations of atherosclerosis, cardiac arrhythmias, and heart failure. An analysis of this relationship did not reveal. Only the IR index in the HOMA-1 model with a value of more than 2.7 units was associated with a 4.5-fold increase in the risk of developing clinical manifestations of atherosclerotic lesions (χ2 = 4.582 p = 0.032). Statistically significant it was only in men. Given our data, perhaps IR is one of the reasons for the higher morbidity and mortality of men at HD. Conclusion a comparison of IR models allows us to distinguish HOMA-2 as the most accurate index. The highest correlation with systemic inflammation and AtD was in the HOMA-1 and HOMA-2 indices.

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The Relationship between Insulin Resistance and the Cardiovascular Biomarker Growth Differentiation Factor-15 in Obese Patients

Clinical Chemistry ◽

10.1373/clinchem.2010.153726 ◽

2011 ◽

Vol 57 (2) ◽

pp. 309-316 ◽

Cited By ~ 73

Author(s):

Greisa Vila ◽

Michaela Riedl ◽

Christian Anderwald ◽

Michael Resl ◽

Ammon Handisurya ◽

...

Keyword(s):

Insulin Resistance ◽

Gastric Bypass ◽

Insulin Sensitivity ◽

Oral Glucose ◽

Model Assessment ◽

Obese Patients ◽

Growth Differentiation Factor 15 ◽

Homeostatic Model Assessment ◽

Homeostatic Model ◽

The Relationship

BACKGROUND Growth differentiation factor-15 (GDF-15) is a stress-responsive cytokine linked to obesity comorbidities such as cardiovascular disease, inflammation, and cancer. GDF-15 also has adipokine properties and recently emerged as a prognostic biomarker for cardiovascular events. METHODS We evaluated the relationship of plasma GDF-15 concentrations with parameters of obesity, inflammation, and glucose and lipid metabolism in a cohort of 118 morbidly obese patients [mean (SD) age 37.2 (12) years, 89 females, 29 males] and 30 age- and sex-matched healthy lean individuals. All study participants underwent a 75-g oral glucose tolerance test; 28 patients were studied before and 1 year after Roux-en-Y gastric bypass surgery. RESULTS Obese individuals displayed increased plasma GDF-15 concentrations (P < 0.001), with highest concentrations observed in patients with type 2 diabetes. GDF-15 was positively correlated with age, waist-to-height ratio, mean arterial blood pressure, triglycerides, creatinine, glucose, insulin, C-peptide, hemoglobin A1c, and homeostatic model assessment insulin resistance index and negatively correlated with oral glucose insulin sensitivity. Age, homeostatic model assessment index, oral glucose insulin sensitivity, and creatinine were independent predictors of GDF-15 concentrations. Roux-en-Y gastric bypass led to a significant reduction in weight, leptin, insulin, and insulin resistance, but further increased GDF-15 concentrations (P < 0.001). CONCLUSIONS The associations between circulating GDF-15 concentrations and age, insulin resistance, and creatinine might account for the additional cardiovascular predictive information of GDF-15 compared to traditional risk factors. Nevertheless, GDF-15 changes following bariatric surgery suggest an indirect relationship between GDF-15 and insulin resistance. The clinical utility of GDF-15 as a biomarker might be limited until the pathways directly controlling GDF-15 concentrations are better understood.

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