International Journal of Endocrinology

Introduction. To investigate the effects of acupuncture on endogenous metabolites in the liver of type 2 diabetes mellitus (T2DM) with nonalcoholic fatty liver disease (NAFLD) mice-based metabolomics. Methods. Proton nuclear magnetic resonance (¹H-NMR) metabolomics combined with multivariate statistical analysis and univariate analysis were used to analyze the changes of endogenous metabolites in the liver of mice in each group and to provide new clinical ideas for acupuncture in the treatment of glycolipid metabolism disorders caused by T2DM and NAFLD. Results. After 4 weeks of continuous treatment, fasting blood glucose (FBG), insulin (INS), total cholesterol (TC), and triglyceride (TG) decreased significantly in mice in the acupuncture treatment group (ATG), and the content of liver glycogen increased significantly. Based on ¹H-NMR metabolomic analysis, a total of 47 metabolites were identified in the liver of T2DM with NAFLD mice, of which eight metabolites: UDP-N-acetylglucosamine, adenosine, glutamate, isoleucine, ATP, 3-hydroxybutyric acid, NADP⁺, and leucine were significantly altered by acupuncture treatment. Through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, it is found that acupuncture has an intervention effect on five metabolic pathways, mainly involving amino acid metabolism, energy metabolism, and oxidative stress. Conclusion. Our study shows that acupuncture can regulate the liver metabolism mode of T2DM in NAFLD mice. It can reduce blood glucose and lipid accumulation in the liver, and these findings provide a new idea and theoretical basis for acupuncture in the treatment of diseases related to glucose and lipid metabolism.

Objective. The growing evidence shows that parathyroid hormone (PTH) may affect glucose metabolism. However, the relationship between them is still controversial among diabetic patients. The current study aimed to investigate the relationship between PTH and glucose metabolism in the patients with newly diagnosed type 2 diabetes (T2D). Methods. A total of 532 participants, including 387 patients with newly diagnosed T2D and 145 healthy controls, were recruited in the present study. PTH and metabolic parameters were measured in all participants. Results. The PTH levels were significantly lower in the newly diagnosed T2D patients compared with the control group (35.10 (25.90, 47.20) vs. 47.15 (35.83, 58.65) pg/ml, ). The T2D patients with a higher glycated hemoglobin (HbA1c) tertile had lower PTH levels than the patients with a lower HbA1c tertile (32.90 (24.85, 41.40) vs. 37.50 (26.10, 54.55) pg/ml, ). Spearman correlation analysis showed that PTH was positively correlated with the body mass index (BMI), fasting insulin (FINS), homeostasis model assessment of β-cell function (HOMA-β), and homeostasis model assessment of insulin resistance (HOMA-IR) and negatively correlated with HbA1c, blood calcium (Ca), blood phosphorus (P), and 25-hydroxyvitamin D3 (25-OH-D3). Multiple linear regression analysis demonstrated that PTH was significantly associated with HbA1c (β = −1.475, ) and HOMA-β (β = 0.090, ) after adjusting for age, sex, BMI, season, 25-OH-D3, Ca, and P. Conclusion. PTH was negatively correlated with HbA1c in the newly diagnosed T2D patients. Our results suggested that the PTH level within the reference range is related to islet β-cell function and hyperglycemia.

Objective. To explore associations of combined exposure to metabolic/inflammatory indicators with thyroid nodules. Methods. We reviewed personal data for health screenings from 2020 to 2021. A propensity score matching method was used to match 931 adults recently diagnosed with thyroid nodules in a 1 : 4 ratio based on age and gender. Conditional logistic regression and Bayesian kernel machine regression (BKMR) were used to explore the associations of single metabolic/inflammatory indicators and the mixture with thyroid nodules, respectively. Results. In the adjusted models, five indicators (OR_{Q4 vs. Q1}: 1.30, 95% CI: 1.07–1.58 for fasting blood glucose; OR_{Q4 vs. Q1}: 1.30, 95% CI: 1.08–1.57 for systolic blood pressure; OR_{Q4 vs. Q1}: 1.26, 95% CI: 1.04–1.53 for diastolic blood pressure; OR_{Q4 vs. Q1}: 1.23, 95% CI: 1.02–1.48 for white blood cell; OR_{Q4 vs. Q1}: 1.28, 95% CI: 1.07–1.55 for neutrophil) were positively associated with the risk of thyroid nodules, while high-density lipoproteins (OR_{Q3 vs. Q1}: 0.75, 95% CI: 0.61–0.91) were negatively associated with the risk of thyroid nodules. Univariate exposure-response functions from BKMR models showed similar results. Moreover, the metabolic and inflammatory mixture exhibited a significant positive association with thyroid nodules in a dose-response pattern, with systolic blood pressure being the greatest contributor within the mixture (conditional posterior inclusion probability of 0.82). No interaction effects were found among the five indicators. These associations were more prominent in males, participants with higher age (≥40 years old), and individuals with abnormal body mass index status. Conclusions. Levels of the metabolic and inflammatory mixture have a linear dose-response relationship with the risk of developing thyroid nodules, with systolic blood pressure levels being the most important contributor.

Background. Diabetes mellitus (DM) presents a significant global health challenge with considerable cardiovascular implications. Coenzyme Q10 (CoQ10) has gained recognition for its potential as a natural antioxidant supplement in the management of diabetes and its associated cardiovascular complications. Aim. This comprehensive review systematically examines the scientific rationale underlying the therapeutic properties of CoQ10 in mitigating the impact of diabetes and its cardiovascular consequences. The analysis encompasses preclinical trials (in vitro and in vivo) and clinical studies evaluating the efficacy and mechanisms of action of CoQ10. Result & Discussion. Findings reveal that CoQ10, through its potent antioxidant and anti-inflammatory attributes, demonstrates significant potential in reducing oxidative stress, ameliorating lipid profiles, and regulating blood pressure, which are crucial aspects in managing diabetes-induced cardiovascular complications. CoQ10, chemically represented as C₅₉H₉₀O₄, was administered in capsule form for human studies at doses of 50, 100, 150, 200, and 300 mg per day and at concentrations of 10 and 20 μM in sterile powder for experimental investigations and 10 mg/kg in powder for mouse studies, according to the published research. Clinical trials corroborate these preclinical findings, demonstrating improved glycemic control, lipid profiles, and blood pressure in patients supplemented with CoQ10. Conclusion. In conclusion, CoQ10 emerges as a promising natural therapeutic intervention for the comprehensive management of diabetes and its associated cardiovascular complications. Its multifaceted impacts on the Nrf2/Keap1/ARE pathway, oxidative stress, and metabolic regulation highlight its potential as an adjunct in the treatment of diabetes and related cardiovascular disorders. However, further extensive clinical investigations are necessary to fully establish its therapeutic potential and assess potential synergistic effects with other compounds.

Background. Serum uric acid (SUA) and glycosylated hemoglobin (HbA1c) were closely related to the body’s metabolism. This study aimed to investigate the relationship between HbA1c and SUA in adults. Methods. This study selected 7293 participants aged ≥20 from 2011 to 2020 in the National Health and Nutrition Examination Survey (NHANES). The multivariate linear regression model was used to test the association between HbA1c and SUA. Subgroup analysis was performed according to age, gender, race, and body mass index (BMI). This study solved the relationship between HbA1c and SUA by fitting a smooth curve. Finally, the inflection point in the nonlinear relationship was calculated by the recursive algorithm, and the relationship between HbA1c and SUA on both sides of the inflection point was analyzed by the two-segment piecewise linear regression model. Results. All 7293 participants found a negative correlation between HbA1c and SUA by completely adjusting the model (β = −7.93 and 95% CI: −9.49–−6.37). In addition, when this study was stratified by gender, age, race, and BMI status, this negative correlation was still statistically significant. In the subgroup analysis, we found that the relationship between the two had different results due to gender differences. In men, HbA1c had a significant negative correlation with SUA. However, in women, the HbA1c value was positively correlated with SUA before 6.8%, and the HbA1c value was negatively correlated with SUA after 6.8%, which indicates that the relationship between HbA1c and SUA in women has changed in prediabetes and diabetes. Conclusion. This study shows that HbA1c is positively correlated with SUA in American adults before 7%. There is a negative correlation after the HbA1c value of 7%.

Background. Metformin is commonly prescribed to treat polycystic ovary syndrome (PCOS) patients, but in some cases, it may not be effective even at high doses or may cause intolerable side effects. Therefore, recent studies have examined the impact of combining metformin with other antidiabetic medications. Methods. A systematic search was performed in Scopus, PubMed, Web of Science, and Embase up to 30 June 2023. All interventional studies that assessed the efficacy of different antidiabetic agents were included. Results. Among the 3488 records found in the primary search, 16 papers were included. Our study showed that dipeptidyl peptidase-4 inhibitors (DPP4i) had the most significant impact on glycemic profile, while thiazolidinediones (TZDs) had the most influence on lipid levels. However, it was observed that patients taking only metformin experienced a greater increase in high-density lipoprotein cholesterol (HDL-C) levels. Glucagon-like peptide-1 receptor agonists (GLP1RAs) effectively modified various anthropometric measurements, such as weight, body mass index, waist circumference, and waist-to-hip ratio. The effects of different antidiabetic drugs on hormone levels were inconclusive, although testosterone levels were more affected by GLP1RA, sodium-glucose cotransporter-2 inhibitors (SGLT2i), and TZDs. None of the combined therapies showed a significant change in blood pressure. Conclusion. Since PCOS is a metabolic disorder, choosing the best combination of antidiabetic drugs in the clinical course of PCOS patients will be very important. Today, it seems that we need a new metabolic approach for better treatment of the metabolic aspects of these patients.