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

Insulin 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.

The self-nanoemulsifying drug delivery system of Petiveria alliacea extract reduced the homeostatic model assessment-insulin resistance value, interleukin-6, and tumor necrosis factor-α level in diabetic rat models

Background and Aim: Metaflammation plays a significant role in the pathogenesis, development, and complication of diabetes mellitus (DM). This inflammation is associated with insulin resistance. Therefore, the inflammatory pathways have been targeted for pharmacological treatment. Petiveria alliacea can decrease blood glucose levels and has anti-inflammatory and antioxidant activities; however, there are still insufficient data regarding its efficacy for the treatment of DM. This study aimed to investigate the effect of the self-nanoemulsifying drug delivery system (SNEDDS) of P. alliacea leaf extract on the homeostatic model assessment (HOMA)-insulin resistance (IR) value and interleukin (IL)-6 and tumor necrosis factor-α (TNF-α) levels in a streptozotocin (STZ)-induced diabetic rat model. Materials and Methods: Thirty-five diabetic rat models were randomly divided into five groups. The first group received the SNEDDS of P. alliacea leaf extract at a dose of 50 mg/kg body weight (BW), the second group received it at a dose of 100 mg/kg BW, the third group received it at a dose of 200 mg/kg BW, the fourth group received 18 mg of metformin, and the fifth group only received the SNEDDS formula. The treatment was administered once a day, orally, for 14 days. On the 15th day after treatment, the rats were sacrificed to obtain blood samples for cardiac examination. The IL-6, TNF-α, and insulin levels in the serum were measured using the enzyme-linked immunosorbent assay method. The HOMA-IR value was calculated using a formula. Results: The mean IL-6 and TNF-α levels were low in the group that received the SNEDDS of P. alliacea leaf extract. There was no significant difference in the insulin level in all treatment and control groups. However, a significant difference in the HOMA-IR value was noted between the group that received the SNEDDS of P. alliacea leaf extract and metformin and the group that did not receive treatment (p<0.05). Conclusion: The SNEDDS of P. alliacea leaf extract reduced the HOMA-IR value and suppressed the TNF-α and IL-6 levels in the STZ-induced diabetic rat model.

Risk Assessment and Determination of Factors That Cause the Development of Hyperinsulinemia in School-Age Adolescents

Background and Objectives: Hyperinsulinemia and insulin resistance are not synonymous; if the risk of developing insulin resistance in adolescents is monitored, they do not necessarily have hyperinsulinemia. It is considered a condition of pre-diabetes and represents a condition of increased risk of developing DM (diabetes mellitus); it can exist for many years without people having the appropriate symptoms. This study aims to determine the risk of developing hyperinsulinemia at an early age in adolescents by examining which factors are crucial for its occurrence. Materials and Methods: The cross-sectional study lasting from 2019 to 2021 (2 years) was realized at the school children’s department in the Valjevo Health Center, which included a total of 822 respondents (392 male and 430 female) children and adolescents aged 12 to 17. All respondents underwent a regular, systematic examination scheduled for school children. BMI is a criterion according to which respondents are divided into three groups. Results: After summary analyzes of OGTT test respondents and calculated values of HOMA-IR (homeostatic model assessment for insulin resistance), the study showed that a large percentage of respondents, a total of 12.7%, are at risk for hyperinsulinemia. The research described in this paper aimed to use the most popular AI (artificial intelligence) model, ANN (artificial neural network), to show that 13.1% of adolescents are at risk, i.e., the risk is higher by 0.4%, which was shown by statistical tests as a significant difference. Conclusions: It is estimated that a model using three different ANN architectures, based on Taguchi’s orthogonal vector plans, gives more precise and accurate results with much less error. In addition to monitoring changes in each individual’s risk, the risk assessment of the entire monitored group is updated without having to analyze all data.

Evaluation of Antidiabetic Properties of the Leaves Extract of Ficus vallis-choudae Delile in a Model of Type 2 Diabetes Induced by High-Fat Diet and Streptozotocin

This work aimed to determine the phytochemical composition of the aqueous extract of leaves of Ficus vallis-choudae (AEFV) and to evaluate its antidiabetic properties on a model of type 2 diabetes induced by a high-fat diet (HFD) and a low dose of streptozotocin (STZ). The phytochemical analysis was carried out according to several methods using the standard of each bioactive compound. Type 2 diabetes was induced by feeding rats for 4 weeks with HFD lard followed by injection of a low dose of STZ (35 mg/kg). After induction, the rats were divided into groups and treated for 28 days with metformin (40 mg/kg) and the AEFV at doses of 110, 220, and 440 mg/kg. The results showed that the AEFV contains saponins, flavonoids, tannins, and total polyphenols. In addition, it dramatically reduced body mass, body mass index (BMI), atherogenic index (AI), coronary heart risk index (CRI), and abdominal fat and increased homeostatic model assessment of β-cell function (HOMA-β), high-density lipoprotein cholesterol (HDL-c) levels, and cardioprotective index (CI). The AEFV also lowered blood glucose levels, insulinemia, homeostatic model assessment of insulin resistance (HOMA-IR) index, and total cholesterol (TC), triglycerides (TG), low-density lipoproteins cholesterol (LDL-c), and very-low-density lipoproteins cholesterol (VLDL-c) levels. There was a decrease in alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activity and in urea and serum creatinine levels following the administration of AEFV. The AEFV caused increased superoxide dismutase (SOD) and catalase (CAT) activities, reduced glutathione (GSH) levels, and decreased malondialdehyde (MDA) levels in the liver, kidneys, and heart of rats. The AEFV has hypoglycemic, antioxidant, and cardioprotective properties, thus validating its use in traditional medicine for the treatment of type 2 diabetes and its complications.

Quantile-Dependent Heritability of Glucose, Insulin, Proinsulin, Insulin Resistance, and Glycated Hemoglobin

<b><i>Background:</i></b> “Quantile-dependent expressivity” is a dependence of genetic effects on whether the phenotype (e.g., insulin resistance) is high or low relative to its distribution. <b><i>Methods:</i></b> Quantile-specific offspring-parent regression slopes (β_OP) were estimated by quantile regression for fasting glucose concentrations in 6,453 offspring-parent pairs from the Framingham Heart Study. <b><i>Results:</i></b> Quantile-specific heritability (<i>h</i>²), estimated by 2β_OP/(1 + <i>r</i>_spouse), increased 0.0045 ± 0.0007 (<i>p</i> = 8.8 × 10⁻¹⁴) for each 1% increment in the fasting glucose distribution, that is, <i>h</i>² ± SE were 0.057 ± 0.021, 0.095 ± 0.024, 0.146 ± 0.019, 0.293 ± 0.038, and 0.456 ± 0.061 at the 10th, 25th, 50th, 75th, and 90th percentiles of the fasting glucose distribution, respectively. Significant increases in quantile-specific heritability were also suggested for fasting insulin (<i>p</i> = 1.2 × 10⁻⁶), homeostatic model assessment of insulin resistance (HOMA-IR, <i>p</i> = 5.3 × 10⁻⁵), insulin/glucose ratio (<i>p</i> = 3.9 × 10⁻⁵), proinsulin (<i>p</i> = 1.4 × 10⁻⁶), proinsulin/insulin ratio (<i>p</i> = 2.7 × 10⁻⁵), and glucose concentrations during a glucose tolerance test (<i>p</i> = 0.001), and their logarithmically transformed values. <b><i>Discussion/Conclusion:</i></b> These findings suggest alternative interpretations to precision medicine and gene-environment interactions, including alternative interpretation of reported synergisms between <i>ACE, ADRB3</i>, <i>PPAR-γ2</i>, and <i>TNF-α</i> polymorphisms and being born small for gestational age on adult insulin resistance (fetal origin theory), and gene-adiposity (<i>APOE, ENPP1, GCKR, IGF2BP2, IL-6, IRS-1, KIAA0280, LEPR, MFHAS1, RETN, TCF7L2</i>), gene-exercise (<i>INS</i>), gene-diet (<i>ACSL1</i>, <i>ELOVL6</i>, <i>IRS-1</i>, <i>PLIN</i>, <i>S100A9</i>), and gene-socioeconomic interactions.

Vitamin D Deficiency Is Inversely Associated with Homeostatic Model Assessment of Insulin Resistance

The study was conducted to comprehensively assess the association of the concentration of vitamin D in the blood and insulin resistance in non-diabetic subjects. The objective was to pool the results from all observational studies from the beginning of 1980 to August 2021. PubMed, Medline and Embase were systematically searched for the observational studies. Filters were used for more focused results. A total of 2248 articles were found after raw search which were narrowed down to 32 articles by the systematic selection of related articles. Homeostatic Model Assessment of Insulin Resistance (HOMAIR) was used as the measure of insulin resistance and correlation coefficient was used as a measure of the relationship between vitamin D levels and the insulin resistance. Risk of bias tables and summary plots were built using Revman software version 5.3 while Comprehensive meta-analysis version 3 was used for the construction of forest plot. The results showed an inverse association between the status of vitamin D and insulin resistance (r = −0.217; 95% CI = −0.161 to −0.272; p = 0.000). A supplement of vitamin D can help reduce the risk of insulin resistance; however further studies, like randomized controlled trials are needed to confirm the results.

Osteoglycin across the adult lifespan

Background Osteoglycin (OGN) is a proteoglycan released from bone and muscle, which has been associated with markers of metabolic health. However, it is not clear whether the levels of circulating OGN change throughout the adult lifespan or if they are associated with clinical metabolic markers or fitness. Methods 107 individuals (46 males and 61 females) aged 21-87 years were included in the study. Serum OGN levels, aerobic capacity (VO2peak), glucose and homeostatic model assessment for insulin resistance (HOMA-IR) were assessed. T-tests were used to compare participant characteristics between sexes. Regression analyses were performed to assess the relationship between OGN and age and OGN and fitness and metabolic markers. Results OGN displayed a non-linear, weak “U-shaped” relationship with age across both sexes. Males had higher levels of OGN than females across the lifespan (β=0.23, p=0.03). Age and sex explained 16% of the variance in OGN (adjusted R 2=0.16; p&lt;0.001). Higher OGN was associated with higher VO2peak (β=0.02, p=0.001); however, those aged &lt;50 showed a stronger positive relationship than those aged &gt;50. A higher OGN level was associated with a higher circulating glucose level (β=0.17, p&lt;0.01). No association was observed between OGN and HOMA-IR. Conclusions OGN was characterized by a U-shaped curve across the lifespan, which was similar between sexes. Those with a higher aerobic capacity or higher glucose concentration had higher OGN levels. Our data suggest an association between OGN and aerobic fitness and glucose regulation. Future studies should focus on exploring the potential of OGN as a biomarker for chronic disease.

Hypothalamic miR-1983 Targets Insulin Receptor β and the Insulin-mediated miR-1983 Increase Is Blocked by Metformin

MicroRNAs (miRNAs) expressed in the hypothalamus are capable of regulating energy balance and peripheral metabolism by inhibiting translation of target messenger RNAs (mRNAs). Hypothalamic insulin resistance is known to precede that in the periphery, thus a critical unanswered question is whether central insulin resistance creates a specific hypothalamic miRNA signature that can be identified and targeted. Here we show that miR-1983, a unique miRNA, is upregulated in vitro in 2 insulin-resistant immortalized hypothalamic neuronal neuropeptide Y-expressing models, and in vivo in hyperinsulinemic mice, with a concomitant decrease of insulin receptor β subunit protein, a target of miR-1983. Importantly, we demonstrate that miR-1983 is detectable in human blood serum and that its levels significantly correlate with blood insulin and the homeostatic model assessment of insulin resistance. Levels of miR-1983 are normalized with metformin exposure in mouse hypothalamic neuronal cell culture. Our findings provide evidence for miR-1983 as a unique biomarker of cellular insulin resistance, and a potential therapeutic target for prevention of human metabolic disease.