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Background
In recent decades, with the development of the global economy and the improvement of living standards, insulin resistance (IR) has become a common phenomenon. Current studies have shown that IR varies between races. Therefore, it is necessary to develop individual prediction models for each country. The purpose of this study was to develop a predictive model of IR applicable to the US population.
Method
In total, 11 cycles of data from the NHANES database were selected for this study. Of these, participants from 1999 to 2010 (n = 14931) were used to establish the model, and participants from 2011 to 2020 (n = 13,646) were used to validate the model. Univariate and multivariable logistic regression was used to analyze the factors associated with IR. Optimal subset regression was used to filter the best modeling variables. ROC curves, calibration curves, and decision curve analysis were used to determine the strengths and weaknesses of the model.
Results
After screening the variables by optimal subset regression, variables with covariance were excluded, and a total of seven factors (including HDL, LDL, ALB, GLB, GLU, BMI, and waist) were finally included to establish the prediction model. The AUCs were 0.851 and 0.857 in the training and validation sets, respectively, and the Brier value of the calibration curve was 0.153.
Conclusion
The optimal subset predictive model proposed in this study has a great performance in predicting IR, and the decision curve analysis shows that it has a high net clinical benefit, which can help clinicians and epidemiologists easily detect IR and take appropriate interventions as early as possible.
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Objective
Metformin has emerged as a safe and effective pharmacological alternative to insulin in gestational diabetes mellitus (GDM), being associated with lower maternal weight gain and hypoglycemia risk. Nevertheless, glycemic control is unaccomplished in a considerable proportion of women only treated with metformin. We aim to determine the metformin monotherapy failure rate in GDM and to identify predictors of its occurrence.
Design and methods
This was a retrospective multicenter study including pregnant women with GDM patients who started metformin as a first-line pharmacological treatment (n = 2891). A comparative analysis of clinical and analytical data between the group of women treated with metformin monotherapy and those needing combined therapy with insulin was performed.
Results
In 685 (23.7%) women with GDM, combined therapy to achieve adequate glycemic control was required. Higher pregestational BMI (OR 1.039; CI 95% 1.008–1.071; P-value = 0.013), higher fasting plasma glucose (PG) levels in oral glucose tolerance test (OGTT) (OR 1.047; CI 95% 1.028–1.066; P-value <0.001) and an earlier gestational age (GA) at metformin introduction (0.839; CI 95% 0.796–0.885, P-value < 0.001) were independent predictive factors for metformin monotherapy failure. The best predictive cutoff values were a fasting PG in OGTT ≥87 mg/dL and GA at metformin introduction ≤29 weeks.
Conclusions
In 685 (23.7%) women, combined therapy with insulin to reach glycemic control was required. Higher pre-gestational BMI, fasting PG levels in OGTT ≥87 mg/dL and introduction of metformin ≤29 weeks of GA were independent predictive factors for metformin monotherapy failure. The early recognition of these characteristics can contribute to the establishment of individualized therapeutic strategies and attain better metabolic control during pregnancy.
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Background
The aim of the study was to explore whether plasma stromal cell-derived factor 1 (SDF-1) levels are associated with the EZSCAN score and its derived indicators in patients with type 2 diabetes (T2D).
Methods
From July 2020 to December 2020, a total of 253 patients with T2D were consecutively recruited. Serum SDF-1 levels were measured by sandwich ELISA. EZSCAN test was applied to evaluate the sudomotor function of each patient, and based on the results, EZSCAN score, cardiac autonomic neuropathy risk score (CANRS) and cardiovascular risk score (CVDRS) were calculated by particular algorithms. In addition, other relevant clinical data were also collected.
Results
With increasing tertiles of serum SDF-1 levels, the CANRS and CVDRS significantly increased (both Pfor trend <0.001), while the EZSCAN score significantly decreased (Pfor trend <0.001). Moreover, serum SDF-1 levels were significantly and positively correlated with the CANRS and CVDRS (r = 0.496 and 0.510, respectively, both P < 0.001), and negatively correlated with the EZSCAN score (r = −0.391, P < 0.001). Furthermore, multivariate linear regression analyses were constructed, and after adjusting for other clinical covariates, serum SDF-1 levels were independently responsible for EZSCAN score (β = −0.273, t = −3.679, P < 0.001), CANRS (β = 0.334, t = 5.110, P < 0.001) and CVDRS (β = 0.191, t = 4.983, P = 0.003).
Conclusions
SDF-1 levels in serum were independently associated with the EZSCAN score and its derived indicators, such as CANRS and CVDRS in patients with T2D.
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Background
Polycystic ovary syndrome (PCOS) is considered a risk factor for the development of type 2 diabetes mellitus (T2DM). However, which is the most appropriate way to evaluate dysglycemia in women with PCOS and who are at increased risk are as yet unclear.
Aim of the study
To determine the prevalence of T2DM, impaired glucose tolerance (IGT), and impaired fasting glucose (IFG) in PCOS women and potential factors to identify those at risk.
Subjects and methods
The oral glucose tolerance test (OGTT), biochemical/hormonal profile, and ovarian ultrasound data from 1614 Caucasian women with PCOS and 362 controls were analyzed in this cross-sectional multicenter study. The data were categorized according to age and BMI.
Results
Dysglycemia (T2DM, IGT, and IFG according to World Health Organization criteria) was more frequent in the PCOS group compared to controls: 2.2% vs 0.8%, P = 0.04; 9.5% vs 7.4%, P = 0.038; 14.2% vs 9.1%, P = 0.002, respectively. OGTT was essential for T2DM diagnosis, since in 88% of them basal glucose values were inconclusive for diagnosis. The presence of either T2DM or IFG was irrespective of age (P = 0.54) and BMI (P = 0.32), although the latter was associated with IGT (P = 0.021). There was no impact of age and BMI status on the prevalence of T2DM or IFG. Regression analysis revealed a role for age, BMI, fat deposition, androgens, and insulin resistance for dysglycemia. However, none of the factors prevailed as a useful marker employed in clinical practice.
Conclusions
One-third of our cohort of PCOS women with either T2DM or IGT displayed normal fasting glucose values but without confirming any specific predictor for dysglycemic condition. Hence, the evaluation of glycemic status using OGTT in all women with PCOS is strongly supported.
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Objectives
To evaluate the effect of metformin in improving platelet dysfunction in women with gestational diabetes mellitus (GDM).
Patients and methods
A randomized controlled trial was conducted on pregnant women diagnosed with GDM. Singleton low-risk pregnancies meeting the inclusion criteria were randomly allocated at 27–31 weeks to receive metformin and placebo through the rest of pregnancy. Thirty-seven and 39 cases were recruited into the metformin group and the placebo group, respectively. MPVs, P-selectin, and 8-isoprostane levels were determined at the time of allocation and 6 weeks after treatment. Obstetric and neonatal outcomes were also assessed.
Results
Most baseline characteristics of the two groups were comparable. The levels of P-selectin after 6 weeks of treatment were significantly higher in the metformin group (68.9 ± 14.4 vs 60.6 ± 11.3; P-value = 0.006), indicating more platelet activation. All of the obstetric and neonatal outcomes were comparable except that birth weight was significantly lower in the metformin group (3018 ± 364 g vs 3204 ± 393 g; P-value = 0.037).
Conclusion
Metformin, in addition to diet and lifestyle modifications, does not improve or worsen oxidative stress and platelet dysfunction in women with GDM. Nevertheless, metformin significantly reduces fetal weight in women with GDM, theoretically preventing macrosomia.
Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Aarhus, Denmark
Danish Diabetes Academy, Odense University Hospital, Odense, Denmark
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Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Aarhus, Denmark
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Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Aarhus, Denmark
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Department of Biomedicine, Aarhus University, Aarhus, Denmark
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Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Aarhus, Denmark
Danish Diabetes Academy, Odense University Hospital, Odense, Denmark
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SGLT2 inhibition induces an insulin-independent reduction in plasma glucose causing increased lipolysis and subsequent lipid oxidation by energy-consuming tissues. However, it is unknown whether SGLT2 inhibition also affects lipid storage in adipose tissue. Therefore, we aimed to determine the effects of SGLT2 inhibition on lipid storage and lipolysis in adipose tissue. We performed a randomized, double-blinded, placebo-controlled crossover design of 4 weeks of empagliflozin 25 mg and placebo once-daily in 13 individuals with type 2 diabetes treated with metformin. Adipose tissue fatty acid uptake, lipolysis rate and clearance were measured by 11C-palmitate PET/CT. Adipose tissue glucose uptake was measured by 18F-FDG PET/CT. Protein and gene expression of pathways involved in lipid storage and lipolysis were measured in biopsies of abdominal s.c. adipose tissue. Subjects were weight stable, which allowed us to quantify the weight loss-independent effects of SGLT2 inhibition. We found that SGLT2 inhibition did not affect free fatty acids (FFA) uptake in abdominal s.c. adipose tissue but increased FFA uptake in visceral adipose tissue by 27% (P < 0.05). In addition, SGLT2 inhibition reduced GLUT4 protein (P = 0.03) and mRNA content (P = 0.01) in abdominal s.c. adipose tissue but without affecting glucose uptake. In addition, SGLT2 inhibition decreased the expression of genes involved in insulin signaling in adipose tissue. We conclude that SGLT2 inhibition reduces GLUT4 gene and protein expression in abdominal s.c. adipose tissue, which could indicate a rebalancing of substrate utilization away from glucose oxidation and lipid storage capacity through reduced glycerol formation.
Department of Anatomy, Shanxi Medical University, Taiyuan, China
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Elucidating the mechanisms of regulation of β-cell proliferation is key to understanding the pathogenesis of diabetes mellitus. Txnip is a tumor suppressor that is upregulated in diabetes and plays an important role in the regulation of insulin sensitivity; however, its potential effect on pancreatic β-cell proliferation remains unclear. Here, we evaluated the role of Txnip in pancreatic β-cell compensatory proliferation by subjecting WT and Txnip knockout (KO) mice to a high-fat diet (HFD). Our results demonstrate that Txnip deficiency improves glucose tolerance and increases insulin sensitivity in HFD-induced obesity. The antidiabetogenic effect of Txnip deficiency was accompanied by increased β-cell proliferation and enhanced β-cell mass expansion. Furthermore, Txnip deficiency modulated the expression of a set of transcription factors with key roles in β-cell proliferation and cell cycle regulation. Txnip KO in HFD mice also led to activated levels of p-PI3K, p-AKT, p-mTOR and p-GSK3β, suggesting that Txnip may act via PI3K/AKT signaling to suppress β-cell proliferation. Thus, our work provides a theoretical basis for Txnip as a new therapeutic target for the treatment of diabetes mellitus.
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Background
Obesity is a growing problem worldwide, and newer therapeutic strategies to combat it are urgently required. This study aimed to analyze the effect of diet and exercise interventions on energy balance in mice and elucidate the mechanism of the peroxisome proliferator-activated receptor-gamma co-activator-1-alpha-IRISIN-uncoupling protein-1 (PGC-1α-IRISIN-UCP-1) pathway in the beigeization of white adipose tissue.
Methods
Four-week-old male C57BL/6 mice were randomly divided into normal (NC) and high-fat diet (HFD) groups. After 10 weeks of HFD feeding, obese mice were randomly divided into obesity control (OC), obesity diet control (OD), obesity exercise (OE), and obesity diet control exercise (ODE) groups. Mice in OE and ODE performed moderate-load treadmill exercises: for OD and ODE, the diet constituted 70% of the food intake of the OC group for 8 weeks.
Results
Long-term HFD inhibits white adipose tissue beigeization by downregulating PGC-1α-IRISIN-UCP-1 in the adipose tissue and skeletal muscles. Eight weeks of exercise and dietary interventions alleviated obesity-induced skeletal muscle, and adipose tissue PGC-1α-IRISIN-UCP-1 pathway downregulation promoted white adipose tissue beigeization and reduced body adipose tissue. The effects of the combined intervention were better than those of single interventions.
Conclusions
Diet and exercise intervention after obesity and obesity itself may affect the beigeization of WAT by downregulating/upregulating the expression/secretion of skeletal muscle and adipose PGC-1α-IRISIN, thereby influencing the regulation of bodyweight. The effects of the combined intervention were better than those of single interventions.
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Background
Increased serum cystatin C (CysC) can predict the onset of type 2 diabetes (T2D). Meanwhile, impaired pancreatic α- and β-cell functions get involved in the pathophysiological processes of T2D. So this study was to explore the relationships between serum CysC levels and pancreatic α- and β-cell functions in T2D.
Methods
In this cross-sectional observational study, a total of 2634 patients with T2D were consecutively recruited. Each recruited patient received a serum CysC test and oral glucose tolerance test for synchronous detection of serum C-peptide and plasma glucagon. As components of pancreatic β-cell function, insulin secretion and sensitivity indices were evaluated by C-peptide area under the curve (AUC-CP) and C-peptide-substituted Matsuda’s index (Matsuda-CP), respectively. Fasting glucagon (F-GLA) and post-challenge glucagon calculated by glucagon area under the curve (AUC-GLA) were used to assess pancreatic α-cell function. These skewed indices and were further natural log-transformed (ln).
Results
With quartiles of serum CysC levels ascending, AUC-CP, F-GLA and AUC-GLA were increased, while Matsuda-CP was decreased (P for trend <0.001). Moreover, serum CysC levels were positively related to lnAUC-CP, lnF-GLA and lnAUC-GLA (r= 0.241, 0.131 and 0.208, respectively, P < 0.001), and inversely related to lnMatsuda-CP (r= –0.195, P < 0.001). Furthermore, after controlling for other relevant variables via multivariable linear regression analysis, serum CysC levels were identified to account for lnAUC-CP (β= 0.178, t= 10.518, P < 0.001), lnMatsuda-CP (β= –0.137, t= –7.118, P < 0.001), lnF-GLA (β= 0.049, t= 2.263, P = 0.024) and lnAUC-GLA (β= 0.121, t= 5.730, P < 0.001).
Conclusions
Increased serum CysC levels may be partly responsible for increased insulin secretion from β-cells, decreased systemic insulin sensitivity, and elevated fasting and postprandial glucagon secretion from α-cells in T2D.
Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Objective
The association between insulin therapy and the risk of biliary tract cancer (BTC) is uncertain. We aimed to assess this risk in type 2 diabetic patients.
Methods
Using electronic medical data from the Shanghai Hospital Link database, 202,557 patients with type 2 diabetes (164,997 insulin never-users and 37,560 insulin ever-users) were identified in this study between January 1, 2013, and December 31, 2016, with follow-up until December 31, 2019. By propensity score matching, an ever-user was matched with a never-user. Cox proportional hazards regression analysis was used to estimate risk ratios (HRs) and 95% CIs for three subtypes of BTC (intrahepatic cholangiocarcinoma (ICC), extrahepatic cholangiocarcinoma (ECC), and gallbladder cancer (GBC)).
Results
At a mean follow-up of 5.33 years, 143 cases of BTC were observed. The crude incidence rates (per 100,000 person-years) of ECC, ICC, and GBC in ever-users:never-users were 10.22:3.63, 2.04:2.04, and 8.17:6.01, respectively. Insulin therapy was associated with an increased risk of ECC (HR, 4.10; 95% CI, 1.54–10.92; P = 0.005) compared to patients who never used insulin. No statistically significant results were observed for insulin and ICC/GBC. Consistent results were also found in the original cohort.
Conclusions
The relationship between insulin therapy and BTC is type-specific. Further studies are warranted to provide evidence on the identification of ECC risk groups among type 2 diabetic patients.
