Biomarkers Of Insulin Resistance Research Articles

Adipose Tissue-Derived Extracellular Vesicles as Agents of Metabolic Regulation and Potential Biomarkers of Insulin Resistance

Adipose Tissue-Derived Extracellular Vesicles as Agents of Metabolic Regulation and Potential Biomarkers of Insulin Resistance

TG/HDL-C Ratio for Predicting Insulin Resistance in Obese Children from Beijing, China.

International studies have found that the blood triglycerides to highdensity lipoproteins (TG/HDL-C) ratio predicted insulin resistance in children with overweight and obesity. However, there is a lack of such reports on children from China. The objective of this study is to explore the ability of the TG/HDL-C ratio as a blood biomarker for insulin resistance (IR) in obese children in Beijing. We evaluated 262 children with obesity from our paediatric outpatient clinic in a cross-sectional study. Detailed medical histories of all children were ascertained, as were clinical examination and laboratory test results, including blood lipids, fasting glucose, insulin, and glycated haemoglobin. We divided them into age groups of 6-9 and 10-13.5 years and then into IR and non-IR groups based on the homeostatic model assessment for IR (HOMA-IR). Analysis was accomplished with SPSS software (version 22.0). The TG/HDL-C ratio was higher in children with IR in the 6-9 and 10-13.5-year age groups (p < 0.001). Univariate and multivariate analyses displayed that the TG/HDL-C ratio and HOMA-IR were correlated in the 6-9 and 10-13.5-year-old groups (p < 0.05). In the 6-9-yearold group, IR identified by a TG/HDL-C ratio ≥ 0.645 had a sensitivity, specificity, and an area under the curve (AUC) of 79.1%, 60.9%, and 0.734, respectively. In the 10-13.5-year-old group, IR identified by a TG/HDL-C ratio ≥ 0.725 had a sensitivity, specificity, and an AUC of 79.4%, 62.9%, and 0.724, respectively. We showed the application of the TG/HDL-C ratio to predict insulin resistance in obese children in Beijing with different diagnostic thresholds based on age (6-9-year-old group with TG/HDL-C ≥ 0.645; 10-13.5-year-old group with TG/HDL-C ≥ 0.725), which were lower compared with the diagnostic threshold for insulin resistance in children reported in other countries.

MiRNA-122 as a biomarker for insulin resistance and risk of cardiovascular diseases in obese children

BackgroundObesity in children is a major worldwide concern that has several negative health consequences in both the short and long term. The objective of this study was to evaluate the expression level of microRNA-122 in obese Egyptian children and investigate its potential associations with insulin resistance and cardiovascular diseases. MethodsThe study included 70 obese and 30 age-matched normal-weight control children. Anthropometric measurements, systolic, and diastolic blood pressures were assessed, and quantitative real-time polymerase chain reaction was used to determine the expression of circulating microRNA-122. Pancreatic beta cell function (HOMA2-%B), insulin resistance (HOMA2-IR), and insulin sensitivity (HOMA2-%S) was assessed by the homeostasis model assessment version 2 (HOMA2). McAuley index and single-point insulin sensitivity estimator (SPISE) was used to further evaluate insulin sensitivity. Levels of serum biochemical parameters were measured. ResultsThe obese group showed significantly higher levels of microRNA-122, fasting blood glucose, triglycerides, total cholesterol, LDL, VLDL, non-HDL cholesterol, cardiac risk ratios, atherogenic coefficient, atherosclerotic index, insulin levels, HOMA2-%B, and HOMA2-IR compared to the control group. In obese children, microRNA-122 exhibited a significant negative correlation with HDL while a significant positive correlation with the cardiac risk ratio 1 and the atherogenic coefficient. MicroRNA-122 had predictive ability for insulin resistance and cardiovascular diseases risk in obese children. However, a significant decrease in HDL levels, HOMA2-%S, McAuley, and SPISE insulin sensitivity indices was found in obese children. ConclusionsModifications in blood levels of microRNA-122 in obese children may indicate a possible role in the etiology of childhood obesity and its associated consequences. As a result, it could function as a preliminary biomarker and potential indicator of further metabolic diseases.

Novel Proteome Targets Marking Insulin Resistance in Metabolic Syndrome.

In order to better understand which metabolic differences are related to insulin resistance in metabolic syndrome (MetSyn), we used hyperinsulinemic-euglycemic (HE) clamps in individuals with MetSyn and related peripheral insulin resistance to circulating biomarkers. In this cross-sectional study, HE-clamps were performed in treatment-naive men (n = 97) with MetSyn. Subjects were defined as insulin-resistant based on the rate of disappearance (Rd). Machine learning models and conventional statistics were used to identify biomarkers of insulin resistance. Findings were replicated in a cohort with n = 282 obese men and women with (n = 156) and without (n = 126) MetSyn. In addition to this, the relation between biomarkers and adipose tissue was assessed by nuclear magnetic resonance imaging. Peripheral insulin resistance is marked by changes in proteins related to inflammatory processes such as IL-1 and TNF-receptor and superfamily members. These proteins can distinguish between insulin-resistant and insulin-sensitive individuals (AUC = 0.72 ± 0.10) with MetSyn. These proteins were also associated with IFG, liver fat (rho 0.36, p = 1.79 × 10-9) and visceral adipose tissue (rho = 0.35, p = 6.80 × 10-9). Interestingly, these proteins had the strongest association in the MetSyn subgroup compared to individuals without MetSyn. MetSyn associated with insulin resistance is characterized by protein changes related to body fat content, insulin signaling and pro-inflammatory processes. These findings provide novel targets for intervention studies and should be the focus of future in vitro and in vivo studies.

Association between triglyceride-glucose index and risk of endometriosis in US population: results from the national health and nutrition examination survey (1999-2006).

The association of the triglyceride-glucose (TyG) index, a promising novel biomarker for insulin resistance, with the risk of endometriosis has not been investigated to date. This nationwide study aimed to explore the association between the TyG index and the endometriosis risk. Data were obtained from the National Health and Nutrition Examination Survey (1999-2006). Female participants who provided complete data on the TyG index and endometriosis were enrolled in the analysis. Multivariate logistic regression analyses were utilized to assess the association of the TyG index with endometriosis, adjusted by multiple potential confounders. Meanwhile, in-depth subgroup analyses were conducted. A total of 1,590 eligible participants were included, among whom 135 (8.5%) women were diagnosed with endometriosis. The fully adjusted multivariate logistic model showed TyG index was significantly associated with the endometriosis risk (odds ratio [OR]Q4 versus Q1 2.04, 95% confidence interval [CI]: 1.15-3.62; P for trend=0.013). In subgroup analyses, the significantly positive association between TyG index and the risk of endometriosis was also found in parous women (ORQ4 versus Q1 2.18, 95% CI: 1.20-3.96), women without diabetes (OR Q4 versus Q1 2.12, 95% CI: 1.19-3.79), women who smoke currently (OR Q4 versus Q1 3.93, 95% CI: 1.33-11.58), women who drink currently (OR Q4 versus Q1 2.54, 95% CI: 1.27-5.07), and in women who use oral contraceptives (OR Q4 versus Q1 1.91, 95% CI: 1.04-3.51). Additionally, significantly increasing trends in the odds of endometriosis across the quartiles of the TyG index were observed in the above-mentioned subgroups (all P for trend<0.05). This population-based study found that a higher TyG index, representing an increased level of insulin resistance, was associated with a higher risk of endometriosis among the US population. Our findings suggested TyG index might be a promising tool for the risk assessment of endometriosis. Prospective studies are warranted to further verify these findings.

Associations of sedentary behavior and screen time with biomarkers of inflammation and insulin resistance.

Sedentary behavior (SB) has been linked to risk factors of cardiometabolic disease, with inconsistent findings reported in the literature. We aimed to assess the associations of SB with multiple biomarkers of inflammation and insulin resistance in adults. Domain-specific SB, sitting time and moderate-to-vigorous physical activity (MVPA) were measured in 78 adults (mean ± SD 52.0 ± 10.8 y). Body fat percentage (BF%) was assessed using multi-frequency bioelectrical impedance. A blood draw assessed glucose, insulin, C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), leptin, and adiponectin. Adiponectin-leptin ratio (ALR), homeostasis model assessment of insulin resistance (HOMA-IR) and beta-cell function (HOMA-β) were calculated. Multivariable linear regression analyses, controlling for age, sex, MVPA, and BF%, were used to assess associations. After adjustment for age, sex and MVPA, total SB (7.5 ± 2.5h/day) was positively associated with leptin, insulin, HOMA-IR, HOMA-β (Standardized Beta (β) range 0.21-0.32) and negatively associated with ALR (β = -0.24, p < 0.05 for all). Similarly, total sitting time (7.2 ± 2.9h/day) was associated with TNF-α (β = 0.22) and ALR (β = -0.26). These associations were attenuated to non-significance after adjustment for BF%. Leisure screen time was detrimentally associated with IL-6 (β = 0.24), leptin (β = 0.21), insulin (β = 0.37), HOMA-IR (β = 0.37), and HOMA-β (β = 0.34), independent of age, sex and MVPA (p < 0.05 for all). Only the associations with insulin (β = 0.26), HOMA-IR (β = 0.26), and HOMA-β (β = 0.23) remained significant after further controlling BF% (p < 0.05). Self-reported SB is associated with biomarkers of inflammation and insulin resistance, independent of MVPA, and in some cases BF%.

ELUCIDATE Trial: A Single-Center Randomized Controlled Study.

Dapagliflozin, a sodium-glucose cotransporter 2 inhibitor, is an epochal oral antidiabetic drug that improves cardiorenal outcomes. However, the effect of early dapagliflozin intervention on left ventricular (LV) remodeling in patients with type 2 diabetes free from cardiovascular disease remains unclear. The ELUCIDATE trial was a prospective, open-label, randomized, active-controlled study that enrolled 76 patients with asymptomatic type 2 diabetes with LV ejection fraction ≥50%, randomized to the dapagliflozin 10 mg/day add-on or standard-of-care group. Speckle-tracking echocardiography-based measurements of the cardiac global longitudinal strain were performed at baseline and 24 weeks after treatment initiation. Patients who received dapagliflozin had a greater reduction in LV dimension (1.68 mm [95% CI, 0.53-2.84]; P=0.005), LV end-systolic volume (5.51 mL [95% CI, 0.86-10.17]; P=0.021), and LV mass index (4.25 g/m2.7 [95% CI, 2.42-6.09]; P<0.0001) compared with standard of care in absolute mean differences. Dapagliflozin add-on therapy led to a significant LV global longitudinal strain increment (0.74% [95% CI, 1.00-0.49]; P<0.0001) and improved LV systolic and early diastolic strain rates (0.27/s [95% CI, 0.17-0.60]; and 0.11/s [95% CI, 0.06-0.16], respectively; both P<0.0001) but not in global circumferential strain. No significant changes were found in insulin resistance, NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels, or other biomarkers at 6 months after the dapagliflozin administration. Dapagliflozin add-on therapy could lead to more favorable cardiac remodeling accompanied by enhanced cardiac mechanical function among patients with asymptomatic type 2 diabetes. Our findings provide evidence of the efficacy of dapagliflozin use for the primary prevention of diabetic cardiomyopathy. URL: https://www.clinicaltrials.gov; Unique identifier: NCT03871621.

Combined serum CTRP7 and CTRP15 levels as a novel biomarker for insulin resistance and type 2 diabetes mellitus

AimsThis study aimed to examine the alterations in the serum CTRP7 and CTRP15 concentrations in patients newly diagnosed with type 2 diabetes mellitus (T2DM) and to assess the diagnostic potential of the log10 (CTRP7+CTRP15) for insulin resistance (IR) and T2DM. MethodsSerum CTRP7, CTRP15, and adiponectin levels were measured using an enzyme-linked immunosorbent assay (ELISA). Bioinformatics analysis was conducted to investigate CTRP7 and CTRP15-related genes and metabolic signaling pathways. ResultsLog10 (CTRP7+CTRP15) levels were notably elevated in the impaired glucose tolerance (IGT) and T2DM cohorts compared with those in the normal control (NGT) cohort. Log10(CTRP7+CTRP15) exhibited positive correlations with HOMA-IR, area under the glucose curve (AUCg), HbA1c%, triglyceride (TG), visceral adiposity index (VAI), body mass index (BMI), and free fatty acid (FFA), levels but negative correlations with adiponectin. Multivariate stepwise regression analysis revealed that HOMA-IR, BMI, HbA1c and FFA levels were independent factors affecting the log10 (CTRP7+CTRP15). Logistic regression analysis revealed that log10 (CTRP7+CTRP15) was independently associated with T2DM and significantly associated with increased risk. Receiver operating characteristic (ROC) curve analysis indicated that the predictive value of log10 (CTRP7+CTRP15) for T2DM and IR was superior to that of CTRP7 or CTRP15 alone. Intervention studies demonstrated that insulin, FFAs and acute exercise contribute to the elevation of serum CTRP7 levels, while hyperglycemia inhibited CTRP7 secretion. Short-term changes in blood glucose, insulin, FFA and acute exercise had minimal effects on serum CTRP15 levels. Bioinformatics analysis revealed that CTRP7 and CTRP15 interact with multiple metabolism-related genes and are enriched in glucose and lipid metabolism-related pathways. ConclusionLog10 (CTRP7+CTRP15) may serve as a valuable diagnostic marker for the management of metabolic-related diseases, particularly T2DM and IR.

First-Trimester Triglyceride-Glucose Index and Triglyceride/High-Density Lipoprotein Cholesterol are Predictors of Gestational Diabetes Mellitus Among the Four Surrogate Biomarkers of Insulin Resistance.

This study seeks to assess the potential of early pregnancy Triglyceride Glucose Index (TyG), triglyceride to High-Density Lipoprotein Cholesterol ratio (TG/HDL-c), Low-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol ratio (LDL-C/HDL-C), and Total Cholesterol to High-Density Lipoprotein Cholesterol ratio (TC/HDL-C) in predicting Gestational Diabetes Mellitus (GDM). A total of 1073 adults singleton pregnant women were enrolled from June 2017 to September 2019. Complete anthropometric data and lipid profiles were measured in the first trimester (before 12 weeks gestation) and a 75g oral glucose tolerance test (OGTT) at 24-28 weeks was performed. Based on OGTT results, participants were categorised into Normal Glucose Tolerance (NGT) group (n=872) and GDM group (n=201). General data, laboratory test results, and surrogate insulin resistance indicators such as TyG index, TG/HDL-C, LDL-C/HDL-C, and TC/HDL-C were documented and compared. To compare differences between the two groups, t-test was used, Spearman correlation analysis and linear regression analysis were performed to establish associations between these indicators and insulin resistance in GDM. Receiver Operating Characteristic (ROC) curves were generated to compare the thresholds of these indicators for predicting GDM during pregnancy and to quantify overall diagnostic accuracy. Individuals with GDM had higher TyG, TG/HDL-C, and LDL-C/HDL-C levels (P < 0.001), but with no significant difference observed in TC/HDL-C. All four ratios were positively correlated with Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), yet only TyG emerged as an independent risk factor for HOMA-IR. The Area under the Curve (AUC) of TyG index (0.692) was comparable to that of HOMA-IR (0.703). The cut-off points for TyG index, TG/HDL-C, and HOMA-IR in predicting GDM were 7.088, 0.831, and 1.8, respectively. HOMA-IR exhibited the highest sensitivity (79.1%), while TyG index (64.3%) and TG/HDL-C ratio (64.3%) demonstrated better specificity compared to HOMA-IR (56.3%). LDL-C/HDL-C and TC/HDL-C offered no discernible predictive advantage. Early pregnancy TyG index and TG/HDL-C can aid in identifying pregnant women at risk for GDM, potentially facilitating early and effective intervention to improve prognosis. TyG index exhibited superior predictive capability compared to TG/HDL-C.

Metabolic health tracking using Ultrahuman M1 continuous glucose monitoring platform in non- and pre-diabetic Indians: a multi-armed observational study

Continuous glucose monitoring (CGM) device adoption in non- and pre-diabetics for preventive healthcare has uncovered a paucity of benchmarking data on glycemic control and insulin resistance for the high-risk Indian/South Asian demographic. Furthermore, the correlational efficacy between digital applications-derived health scores and glycemic indices lacks clear supportive evidence. In this study, we acquired glycemic variability (GV) using the Ultrahuman (UH) M1 CGM, and activity metrics via the Fitbit wearable for Indians/South Asians with normal glucose control (non-diabetics) and those with pre-diabetes (N = 53 non-diabetics, 52 pre-diabetics) for 14 days. We examined whether CGM metrics could differentiate between the two groups, assessed the relationship of the UH metabolic score (MetSc) with clinical biomarkers of dysglycemia (OGTT, HbA1c) and insulin resistance (HOMA-IR); and tested which GV metrics maximally correlated with inflammation (Hs-CRP), stress (cortisol), sleep, step count and heart rate. We found significant inter-group differences for mean glucose levels, restricted time in range (70–110 mg/dL), and GV-by-SD, all of which improved across days. Inflammation was strongly linked with specific GV metrics in pre-diabetics, while sleep and activity correlated modestly in non-diabetics. Finally, MetSc displayed strong inverse relationships with insulin resistance and dysglycemia markers. These findings present initial guidance GV data of non- and pre-diabetic Indians and indicate that digitally-derived metabolic scores can positively influence glucose management.

The Triglycerides and Glucose Index Is an Independent Risk Factor for Acute Respiratory Distress Syndrome in Patients with COVID-19.

Introduction: Although it has been observed that the triglycerides and glucose (TyG) index, a biomarker of insulin resistance, is associated with severity and morbidity by COVID-19, evidence is still scarce. Therefore, the objective of this study was to determine whether the TyG index is associated with both the degree of severity and mortality by acute respiratory distress syndrome (ARDS) in patients with COVID-19. Methods: Men and women aged 20 years or more with diagnosis of COVID-19 were included in a case-control study. Exclusion criteria were pregnancy, cancer, autoimmune diseases, autoimmune treatment, and incomplete data. Patients with severe COVID-19 ARDS were allocated into the case group, and those with mild or moderate COVID-19 ARDS in the control group. COVID-19 was defined by a positive reverse transcriptase-polymerase chain reaction test for SARS-CoV-2, and ARDS was defined according to the Berlin criteria. Results: A total of 206 patients were included and allocated into the case (n = 103) and control (n = 103) groups. The logistic regression analysis adjusted by age, sex, and body mass index showed that the TyG index is significantly associated with moderate [odds ratio (OR) = 6.0; 95% confidence interval (CI): 1.1-30.6] and severe (OR = 9.5; 95% CI: 2.4-37.5) COVID-19 ARDS, and death (OR = 10.1; 95% CI: 2.2-46.5). Conclusion: The results of our study show a significant and independent association of the TyG index with ARDS and mortality in patients with COVID-19.

Zinc Transporter ZnT1 mRNA Expression Is Negatively Associated with Leptin Serum Concentrations but Is not Associated with Insulin Resistance or Inflammatory Markers in Visceral Adipose Tissue.

The aim of this study was to evaluate the relationship between biomarkers of chronic inflammation, insulin resistance, and zinc transporter ZnT1 expression in human visceral adipose tissue. Visceral adipose tissue obtained from 47 adults undergoing laparoscopic surgery for cholecystectomy was used to analyze ZnT1 mRNA expression by RT-qPCR. ZnT1 mRNA levels were compared between subjects with normal weight, overweight, and obesity. A significantly lower ZnT1 expression was observed in overweight and obesity compared with normal-weight subjects (p = 0.0016). Moreover, subjects with normal weight had significantly higher serum zinc concentration (97.7 ± 13.1mg/L) than subjects with overweight (87.0 ± 12.8mg/L) and obesity (83.1 ± 6.6mg/L) (p = 0.002). Pearson test showed a positive correlation between serum zinc concentrations and ZnT1 mRNA expression in visceral adipose tissue (r = 0.323; p = 0.031) and a negative correlation with body mass index (r = - 0.358; p = 0.013). A linear regression model was used to analyze the associations between ZnT1 mRNA expression and serum zinc levels, insulin resistance (HOMA2-IR), serum adipokines (leptin and adiponectin), and serum inflammation biomarkers (tumor necrosis factor alpha, interleukin-6, and C-reactive protein). Interestingly, leptin concentrations were negatively associated with ZnT1 mRNA expression (p = 0.012); however, no significant associations were found for the rest of the analyzed variables. Future research is needed to analyze the causality of negative association between ZntT1 expression in visceral adipose tissue and leptin.

Associations of inflammatory and metabolic biomarkers with incident erosive hand osteoarthritis in the osteoarthritis initiative cohort

Erosive hand osteoarthritis (eHOA) is a subtype of hand osteoarthritis (OA) that develops in finger joints with pre-existing OA and is differentiated by clinical characteristics (hand pain/disability, inflammation, and erosions) that suggest inflammatory or metabolic processes. This was a longitudinal nested case-cohort design among Osteoarthritis Initiative participants who had hand radiographs at baseline and 48-months, and biospecimens collected at baseline. We classified incident radiographic eHOA in individuals with ≥1 joint with Kellgren-Lawrence ≥2 and a central erosion present at 48-months but not at baseline. We used a random representative sample (n=1282) for comparison. We measured serum biomarkers of inflammation, insulin resistance and dysglycemia, and adipokines using immunoassays and enzymatic colorimetric procedures, blinded to case status. Eighty-six participants developed incident radiographic eHOA. In the multivariate analyses adjusted for age, gender, race, smoking, and body mass index, and after adjustment for multiple analyses, incident radiographic eHOA was associated with elevated levels of interleukin-7 (risk ratio (RR) per SD=1.30 [95% confidence interval (CI) 1.09, 1.55] p trend 0.01). This exploratory study suggests an association of elevated interleukin-7, an inflammatory cytokine, with incident eHOA, while other cytokines or biomarkers of metabolic inflammation were not associated. Interleukin-7 may mediate inflammation and tissue damage in susceptible osteoarthritic finger joints and participate in erosive progression.

C-peptide in diabetes: A player in a dual hormone disorder?

C-peptide, a byproduct of insulin synthesis believed to be biologically inert, is emerging as a multifunctional molecule. C-peptide serves an anti-inflammatory and anti-atherogenic role in type 1 diabetes mellitus (T1DM) and early T2DM. C-peptide protects endothelial cells by activating AMP-activated protein kinase α, thus suppressing the activity of NAD(P)H oxidase activity and reducing reactive oxygen species (ROS) generation. It also prevents apoptosis by regulating hyperglycemia-induced p53 upregulation and mitochondrial adaptor p66shc overactivation, as well as reducing caspase-3 activity and promoting expression of B-cell lymphoma-2. Additionally, C-peptide suppresses platelet-derived growth factor (PDGF)-beta receptor and p44/p42 mitogen-activated protein (MAP) kinase phosphorylation to inhibit vascular smooth muscle cells (VSMC) proliferation. It also diminishes leukocyte adhesion by virtue of its capacity to abolish nuclear factor kappa B (NF-kB) signaling, a major pro-inflammatory cascade. Consequently, it is envisaged that supplementation of C-peptide in T1DM might ameliorate or even prevent end-organ damage. In marked contrast, C-peptide increases monocyte recruitment and migration through phosphoinositide 3-kinase (PI-3 kinase)-mediated pathways, induces lipid accumulation via peroxisome proliferator-activated receptor γ upregulation, and stimulates VSMC proliferation and CD4+ lymphocyte migration through Src-kinase and PI-3K dependent pathways. Thus, it promotes atherosclerosis and microvascular damage in late T2DM. Indeed, C-peptide is now contemplated as a potential biomarker for insulin resistance in T2DM and linked to increased coronary artery disease risk. This shift in the understanding of the pathophysiology of diabetes from being a single hormone deficiency to a dual hormone disorder warrants a careful consideration of the role of C-peptide as a unique molecule with promising diagnostic, prognostic, and therapeutic applications.

Fibre-rich Foods to Treat Obesity and Prevent Colon Cancer trial study protocol: a randomised clinical trial of fibre-rich legumes targeting the gut microbiome, metabolome and gut transit time of overweight and obese patients with a history of noncancerous adenomatous polyps

IntroductionRecently published studies support the beneficial effects of consuming fibre-rich legumes, such as cooked dry beans, to improve metabolic health and reduce cancer risk. In participants with overweight/obesity and a...

Metabolic and endocrine changes induced by cinnamon in women with polycystic ovarian syndrome: A pilot study.

Most polycystic ovary syndrome (PCOS) patients have metabolic abnormalities in which insulin resistance (IR) plays a pivotal role. Cinnamon is a herbal medicine with insulinotropic properties. This pilot study aimed to evaluate the effects of cinnamon on ovarian volume, androgenic profile, and metabolic and anthropometric parameters in women with PCOS. A single-center, double-blind, randomized, placebo-controlled trial was carried out on 39 overweight / obese women with PCOS. For six months, subjects in the cinnamon (500 mg) (n=19) and placebo (n=20) groups were given three capsules daily. Before and after the intervention, the variables were assessed. The data was analyzed using the GraphPad Prism software. After the intervention, the two intervention and control groups had significant differences in abdominal subcutaneous fat and ovarian volume, but they did not differ significantly in terms of body mass index (BMI). Also, after the intervention, no significant difference was observed between the two groups in terms of lipid profile and the concentration of androgenic biomarkers of insulin resistance. Cinnamon supplementation improves ovarian volume and subcutaneous abdominal fat but has no effect on anthropometric parameters, lipid profile, insulin resistance, or androgen hormones.

Interplay of adiponectin and resistin in type 2 diabetes: Implications for insulin resistance and atherosclerosis

Aim: The study aims to investigate the association between type 2 diabetes and adipokines, particularly resistin and adiponectin, in insulin resistance. It also explores the potential of the resistin to adiponectin ratio as an indicator for these conditions Methods: This research involved 198 participants, including 100 patients with type 2 diabetes and 98 controls. It focused on measuring various biochemical parameters like HbA1c, fasting plasma glucose, lipid profiles (low-density lipoprotein, oxidized low-density lipoprotein, triglyceride, total cholesterol), and adipokines (resistin and adiponectin). The study utilized the Homeostasis Model Assessment of Insulin Resistance and Triglyceride-Glucose index to evaluate insulin resistance. Results: Type 2 diabetic patients exhibited higher levels of HbA1c, fasting plasma glucose, lipid profiles, and resistin, but lower adiponectin levels compared to controls. Adiponectin showed a negative correlation with insulin resistance, while resistin demonstrated a positive correlation. Both adipokines significantly related to atherogenic markers, with adiponectin offering protection against atherosclerosis and resistin augmenting it. Conclusion: The findings underscore the complex roles of resistin and adiponectin in the pathophysiology of type 2 diabetes, insulin resistance. The resistin to adiponectin ratio could be a useful biomarker for insulin resistance. These insights suggest potential therapeutic strategies for treating diabetes and preventing its complications.

A combined analysis of TyG index, SII index, and SIRI index: positive association with CHD risk and coronary atherosclerosis severity in patients with NAFLD.

Insulin resistance(IR) and inflammation have been regarded as common potential mechanisms in coronary heart disease (CHD) and non-alcoholic fatty liver disease (NAFLD). Triglyceride-glucose (TyG) index is a novel biomarker of insulin resistance, System immune-inflammation index(SII) and Systemic inflammation response index(SIRI) are novel biomarkers of inflammation, these biomarkers have not been studied in CHD with NAFLD patients. This study investigated the correlation between the TyG index, SII index, and SIRI index and CHD risk among NAFLD patients. This cross-sectional study included 407 patients with NAFLD in the Department of Cardiology, The Second Hospital of Shanxi Medical University. Of these, 250 patients with CHD were enrolled in the NAFLD+CHD group and 157 patients without CHD were enrolled as NAFLD control. To balance covariates between groups, 144 patients were selected from each group in a 1:1 ratio based on propensity score matching (PSM). Potential influences were screened using Lasso regression analysis. Univariate and multivariate logistic regression analyses and the Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to assess independent risk and protective factors for CHD. Construction of nomogram using independent risk factors screened by machine learning. The receiver operating characteristic(ROC) curve was used to assess the ability of these independent risk factors to predict coronary heart disease. The relationship between the Gensini score and independent risk factors was reflected using the Sankey diagram. The LASSO logistic regression analysis and Logistic regression analyses suggest that TyG index (OR, 2.193; 95% CI, 1.242-3.873; P = 0.007), SII index (OR, 1.002; 95% CI, 1.001-29 1.003; P <0.001), and SIRI index (OR,1.483;95%CI,1.058-2.079,P=0.022) are independent risk factors for CHD. At the same time, Neutrophils, TG, and LDL-C were also found to be independent risk factors in patients, HDL-C was a protective factor for CHD in patients with NAFLD. Further analysis using three machine learning algorithms found these independent risk factors to have good predictive value for disease diagnosis, SII index shows the highest predictive value. ROC curve analysis demonstrated that combining the SII index, SIRI index, and TyG index can improve the diagnostic ability of non-alcoholic liver cirrhosis patients with CHD.ROC curve analysis showed that the combined analysis of these independent risk factors improved the predictive value of CHD(AUC: 0.751; 95% CI: 0.704-0.798; P <0.001). TyG index, SII index, and SIRI index are all independent risk factors for CHD in patients with NAFLD and are strongly associated with prediction and the severity of CHD.

Relationship between triglyceride-glucose index baselines and trajectories with incident cardiovascular diseases in the elderly population

BackgroundThe triglyceride-glucose (TyG) index is regarded as a sophisticated surrogate biomarker for insulin resistance, offering a refined means for evaluating cardiovascular diseases (CVDs). However, prospective cohort studies have not simultaneously conducted baseline and multi-timepoint trajectory assessments of the TyG index in relation to CVDs and their subtypes in elderly participants.MethodsAfter excluding data deficiencies and conditions that could influence the research outcomes, this study ultimately incorporated a cohort of 20,185 participants, with data chronicles extending from 2016 to 2022. The TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. Latent Class Trajectory Model (LCTM) was used to assess the change trends of the TyG index over multiple time points. Utilizing the Cox proportional-hazards models, we assessed the relationship between the baseline quartiles of the TyG index and various trajectories with CVDs and subtypes.ResultsDuring the mean follow-up time of 4.25 years, 11,099 patients experienced new CVDs in the elderly population. After stratifying by baseline TyG quartiles, the higher TyG level was associated with an increased risk of CVDs; the aHR and 95% CI for the highest quartile group were 1.28 (1.19–1.39). Five trajectory patterns were identified by the LCTM model. The low gradual increase group as the reference, the medium stable group, and the high gradual increase group exhibited an elevated risk of CVDs onset, aHR and 95%CIs were 1.17 (1.10–1.25) and 1.25 (1.15–1.35). Similar results were observed between the trajectories of the TyG index with subtypes of CVDs.ConclusionParticipants with high levels of baseline TyG index and medium stable or high gradual increase trajectories were associated with an elevated risk of developing CVDs in elderly populations.

Association between the triglyceride glucose index and low skeletal muscle mass: a cross-sectional study

ObjectivesTriglyceride glucose (TyG) represents a consistent surrogate biomarker and index of insulin resistance (IR), IR has also been linked to skeletal muscle mass loss (SMM-L). Here, we evaluated the association...