BMC Endocrine Disorders最新文献

Background: The role of dietary fat quality in promotion of cardiovascular diseases is studies before. However, the results are inconsistent. Recently, cholesterol to saturated fatty acid index (CSI) is suggested as a novel indicator of the atherogenicity and thrombogenicity potential of a diet. However, due to limited number of studies, in the current cross-sectional study, we aimed to evaluate the role of CSI in metabolic and inflammatory response among obese individuals.

Methods: In the current cross-sectional study 488 obese individuals aged 18-50 years old were involved in volunteer based invitation from outpatient obesity clinics. Subjects underwent anthropometric assays including weight, height, waist circumference (WC) and body composition and their fasting blood sample were obtained for biochemical assessments including blood sugar, serum lipids, hs-CRP and IL-6 concentrations by commercial kits. Physical activity was also assessed by short form of international physical activity questionnaire (IPAQ).

Results: According to our results, being at the top tetile of CSI was associated with higher anthropometric indices including weight, height, WC, FFM, and basal metabolic rate (BMR) compared with those at the lowest tertile (P < 0.05). Similarly, those at the highest category of CSI had significantly higher levels of serum glucose and hs-CRP both in crude and adjusted models in ANCOVA and in multinomial logistic regression models (P < 0.05).

Conclusion: In the current study, for the first time, we identified the possible triggering role of dietary cholesterol to saturated fat index in increasing serum glucose and hs-CRP levels. due to cross-sectional design of the current study, causal inference is impossible. Further studies will help for better scientific justification.

Objective: The relationship between thyrotropin (TSH), free triiodothyronine (FT3), free thyroxine (FT4) and diabetic kidney disease (DKD) is still controversial, and this study analyzed the correlation between TSH, FT3, FT4 and DKD in patients with type 2 diabetes mellitus (T2DM).

Methods: T2DM patients (1216) were divided into five groups based on serum TSH, FT3, and FT4 levels, differences in urinary albumin excretion rate (UACR), estimated glomerular filtration rate (eGFR) were compared. Binary logistic regression verified independent correlations among TSH, FT3, FT4 and UACR, eGFR. TSH and FT3 predictive values for DKD were analyzed using receiver operating characteristic (ROC) curves.

Results: The prevalence of albuminuria with decreased eGFR was higher in T2DM patients with subclinical hypothyroidism and overt hypothyroidism than that in patients with normal thyroid function. TSH positively correlated with UACR (r = 0.133, p < 0.001) and positively correlated with eGFR (r = -0.218, p < 0.001), FT3 negatively correlated with UACR (r = -0.260, p < 0.001) and positively correlated with eGFR (r = 0.324, p < 0.001). With the change from the lower normal level to the increased level of TSH and the change from the higher normal level to the reduced level of FT3, the prevalence of albuminuria gradually increased, the prevalence of decreased eGFR gradually increased in TSH groups and FT3 groups. After adjusting for age, BMI, duration of diabetes, TPOAb, TGAb, smoking, drinking, hypertension, the use of anti-diabetic medications (metformin, sodium-glucose cotransporter 2 inhibitors), HbA1c, CRP, TC, TG, LDL-C, and HDL-C, both TSH and FT3 correlated with increased UACR (TSH: OR 1.253, p = 0.001; FT3: OR 0.166, p < 0.001) and decreased eGFR (TSH: OR 1.245, p < 0.001, FT3: OR 0.579, p < 0.001), but this correlation of TSH with eGFR < 60 mL/min/1.73 m² was not found in male. The area under the ROC curve (AUC) for FT3 was greater than that for TSH (FT3: 0.64; TSH: 0.61).

Conclusions: Increased TSH and reduced FT3 levels were associated with DKD in T2DM patients, but in a sex-dependent manner. FT3 had a higher predictive value for DKD.

Objective: This Study aims to investigate the risk factors of hypoglycemia in neonates through meta-analysis.

Method: PubMed, Embase, Cochrane library, and Web of science databases were searched for case-control studies on risk factors for neonatal hypoglycemia. The search was done up to 1st October 2023 and Stata 15.0 was used for data analysis.

Results: A total of 12 published studies were included, including 991 neonates in the hypoglycemic group and 4388 neonates in the non-hypoglycemic group. Meta-analysis results suggested caesarean section [OR = 1.90 95%CI (1.23, 2.92)], small gestational age[OR = 2.88, 95%CI (1.59, 5.20)], gestational diabetes [OR = 1.65, 95%CI (1.11, 2.46)], gestational hypertension[OR = 2,79, 95%CI (1.78, 4.35)] and respiratory distress syndrome[OR = 5.33, 95%CI (2.22, 12.84)] were risk factors for neonatal hypoglycemia.

Conclusion: Based on the current study, we found that caesarean section, small gestational age, gestational diabetes, gestational hypertension, respiratory distress syndrome are risk factors for neonatal hypoglycemia.

Prospero registration number: CRD42023472974.

Purpose: This study aimed to preliminarily investigate the association and possible mechanisms between Helicobacter. pylori (H. pylori) infection and type 2 diabetes mellitus (T2DM) through data collection, statistical analysis, and bioinformatics analysis.

Methods: A retrospective cohort study, including a total of 4406 participants who attended annual health checkups at Xian GEM Flower Changqing Hospital, was conducted to explore the correlation between the incidence of T2DM and H. pylori infection. To uncover the potential mechanisms underlying the interaction between the two diseases, differentially expressed genes (DEGs) common to T2DM and H. pylori infection were identified using the GEO database and Venn diagrams. These DEGs were then analyzed through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) analysis.

Results: In total, 2053 participants were classified into the H. pylori-positive group and 2353 into the H. pylori-negative group. H. pylori infection was associated with a higher risk of T2DM occurrence (adjusted HR 1.59; 95% CI 1.17-2.15, P = 0.003). The average disease-free survival time was 34.81 months (95% CI 34.60-35.03 months) in the H. pylori positive group and 35.42 months (95% CI 35.28-35.56 months) in the H. pylori negative group. Multivariate analysis and subgroup analyses also showed that H. pylori infection increased the risk of developing T2DM. A total of 21 DEGs between T2DM and H. pylori infection were identified and enriched in 7 signaling pathways, indicating specific protein interactions.

Conclusions: The prevalence of T2DM was associated with H. pylori infection. T2DM and H. pylori infection may interact with each other through metabolic and immune pathways.

Background: Inadequate glycemic management in type 2 diabetes Mellitus patients is a serious public health issue and a key risk factor for progression as well as diabetes-related complications. The main therapeutic goal of preventing organ damage and other problems caused by diabetes is glycemic control. Knowing when to modify glycemic control in type 2 diabetes Mellitus is crucial for avoiding complications and early drug intensifications.

Methods: An institutional based retrospective follow-up study was undertaken among 514 eligible adult diabetes patients in Amhara region Comprehensive Specialized Hospitals, Northwest Ethiopia, from January 2017 to January 2022. Simple random sampling technique was used to select study participants. The Kaplan Meier curve was used to assess the survival status of categorical variables, and the log-rank test was used to compare them. The cox proportional hazard model was fitted to identify the predictors of time to first optimal glycemic control. Variables with a p-value < 0.05 were considered to be statistically significance at 95% confidence interval.

Results: A total of 514 patient records (227 males and 287 females) were reviewed in this study. The median time to first optimal glycemic control among the study population was 8.4 months IQR (7.6-9.7). The predictors that affect the time to first optimal glycemic control were age group ((AHR = 0.63, 95% CI = 0.463, 0.859 for 50-59 years), (AHR = 0.638, 95% CI = 0.471, 0.865 for 60-69 years), and (AHR = 0.480, 95% CI = 0.298, 0.774 for > = 70 years)), diabetes neuropathy (AHR = 0.629, 95% CI = 0.441,0.900), hypertension (AHR = 0.667, 95% CI = 0.524, 0.848), dyslipidemia (AHR = 0.561, 95% CI = 0.410, 0.768), and cardiovascular disease (AHR = 0.681, 95% CI = 0.494, 0.938).

Conclusion: The median time to initial optimal glycemic control in type 2 diabetes Mellitus patients in this study was short. Age between 50 and 59 years and 60-69, diabetes neuropathy, hypertension, dyslipidemia, and cardiovascular disease were predictor's of time to first glycemic control. Therefore, health care providers should pay extra attention for patients who are aged and who have complications or co-morbidities.

Background: Multiple clinician adjustable parameters impact upon glycemia in people with type 1 diabetes (T1D) using Medtronic Mini Med 780G (MM780G) AHCL. These include glucose targets, carbohydrate ratios (CR), and active insulin time (AIT). Algorithm-based decision support advising upon potential settings adjustments may enhance clinical decision-making.

Methods: Single-arm, two-phase exploratory study developing decision support to commence and sustain AHCL. Participants commenced investigational MM780G, then 8 weeks Phase 1-initial optimization tool evaluation, involving algorithm-based decision support with weekly AIT and CR recommendations. Clinicians approved or rejected CR and AIT recommendations based on perceived safety per protocol. Co-design resulted in a refined algorithm evaluated in a further identically configured Phase 2. Phase 2 participants also transitioned to commercial MM780G following "Quick Start" (algorithm-derived tool determining initial AHCL settings using daily insulin dose and weight). We assessed efficacy, safety, and acceptability of decision support using glycemic metrics, and the proportion of accepted CR and AIT settings per phase.

Results: Fifty three participants commenced Phase 1 (mean age 24.4; Hba1c 61.5mmol/7.7%). The proportion of CR and AIT accepted by clinicians increased between Phases 1 and 2 respectively: CR 89.2% vs. 98.6%, p < 0.01; AIT 95.2% vs. 99.3%, p < 0.01. Between Phases, mean glucose percentage time < 3.9mmol (< 70mg/dl) reduced (2.1% vs. 1.4%, p = 0.04); change in mean TIR 3.9-10mmol/L (70-180mg/dl) was not statistically significant: 72.9% ± 7.8 and 73.5% ± 8.6. Quick start resulted in stable TIR, and glycemic metrics compared to international guidelines.

Conclusion: The co-designed decision support tools were able to deliver safe and effective therapy. They can potentially reduce the burden of diabetes management related decision making for both health care practitioners and patients.

Trial registration: Prospectively registered with Australia/New Zealand Clinical Trials Registry(ANZCTR) on 30th March 2021 as study ACTRN12621000360819.

Background: Due to China's rapid urbanization, many farmers have relocated to urban resettlement regions. There is limited research on the glycemic control of Type 2 diabetes mellitus (T2DM) farmers in these areas. This study examined their blood glucose control and its determinants.

Methods: This study took place from March 2021 to January 2022 in a resettlement community in Yiwu, Zhejiang Province, China. In the first phase, a quantitative survey of 181 T2DM farmers was conducted using a questionnaire to gather demographic data, blood glucose control status, disease cognition levels, and treatment compliance. Inclusion criteria were migrant workers with ≥ 3 months of residence and local household registration and T2DM patients who met the diagnostic criteria of the Chinese guidelines. In the second phase, qualitative research involved face-to-face, semi-structured interviews with 15 patients with varying blood glucose control levels to analyze their experiences.

Results: The blood glucose control rate in this particular group was 27.62%, and the average disease cognition score was 2.5 ± 0.75. Many patients (67.96%) had inadequate treatment compliance, specifically in monitoring compliance (4.45 ± 1.92) and regular review compliance (3.58 ± 1.74).

Conclusion: There is a need for tailored programs to improve glycemic control among resettled farmers. Enhancing disease awareness and treatment compliance through targeted education and support is crucial. Further studies are needed to evaluate different treatment regimens' impact on glycemic control.

Clinical trial number: Not applicable.

Background: Type 2 diabetes mellitus, one of the most prevalent metabolic disorders worldwide, is closely linked with an enhanced risk of atherosclerosis. However, the molecular mechanism of this linkage is not still clear. Genetic variations in the mTOR gene may increase the susceptibility of individuals to these diseases.

Methods: One hundred nine diabetic patients and 375 healthy subjects participated in this study. mTOR Single Nucleotide Polymorphism (SNP) rs2295080 was determined using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP).

Results: Comparison of genotypic, allelic, and genotypic combination frequencies between cases and controls revealed no significant result. Nevertheless, the frequency of rs2295080 GT + TT genotype was significantly more in diabetic women with atherosclerosis compared with those without atherosclerosis (p = 0.047). Besides, the rs2295080 G allele was more frequently detected in diabetic women without atherosclerosis compared to those with atherosclerosis (p = 0.046).

Conclusion: The rs2295080 GT + TT genotype predisposes Iranian diabetic women to atherosclerosis, while the rs2295080 G allele protects them against atherosclerosis. However, additional experiments using larger sample sizes are needed to verify this result.

Background: Nonalcoholic fatty liver disease (NAFLD) shares common pathogenic mechanisms of type 2 diabetes mellitus (T2DM) with upregulated advanced glycation end products (AGEs). Here, we aim to investigate the effect of FPS-ZM1, an inhibitor for receptor for AGEs (RAGE), on lipid deposition in the liver of mice.

Methods: KK-Ay mice were used as models of T2DM with NAFLD, while C57BL/6j mice were controls. Additionally, KK-Ay mice were treated with DMSO (with a concentration of 1%), with or without FPS-ZM1 (3 mg/kg/day, i.p). Lipid deposition in hepatocytes was observed using oil red O stain. Levels of AGEs and RAGE were measured. Sterol regulatory element-binding protein-1c (SREBP-1c), as well as nuclear factor κB p65 (p65 nfκb) and mitogen-activated protein kinase p38 (p38 MAPK), were also detected.

Results: Lipid deposition is increased in the hepatocytes of KK-Ay mice compared to C57BL/6j mice. In addition, not only were the levels of AGEs elevated in plasma, but also the levels of RAGE in liver tissue. Although total SREBP-1c levels did not change in the liver of diabetic mice, mature SREBP-1c increased in KK-Ay mice with diabetes mellitus. Moreover, diabetic mice showed increased levels of phosphorylated-p65 nfκb (p-p65 nfκb) and phosphorylated-p38 MAPK (p-p38 MAPK). On the contrary, FPS-ZM1 decreased lipid deposition in liver cells, as well as mature SREBP-1c, p-p65 nfκb and p-p38 MAPK levels in liver tissue.

Conclusion: Generally, FPS-ZM1 may attenuate lipid deposition in hepatocytes of diabetic mice via SREBP-1c down-regulation. This may depend on the downregulation of p65 nfκb and p38 MAPK phosphorylation.

Background: Follistatin-like protein 1 (FSTL1) has been identified as a secreted glycoprotein that plays an important role in obesity. However, its role in children with metabolic-associated fatty liver disease (MAFLD) has not been investigated. This study aimed at characterizing the relationship between serum FSTL1 concentration and MAFLD in children with obesity.

Methods: A total of 121 subjects were recruited from the Second Affiliated Hospital of Xi'an Jiaotong University, including 45 obese children with MAFLD, 31 obese children without MAFLD, and 45 healthy controls. Anthropometric parameters, biochemical data were measured and circulating FSTL1 levels were detected by ELISA.

Results: The levels of FSTL1 in obese children with MAFLD were higher than that in obese children without MAFLD: 1.31 (0.35-2.29) ng/mL vs. 0.55 (0.36-1.38) ng/mL. Correlation analysis illustrated that FSTL1 was associated with nonesterified free fatty acid and leptin (r = 0.278, P < 0.05 and r = 0.572, P < 0.05, respectively). Binary logistic regression suggested that increased FSTL1 was a risk factor for MAFLD in children (OR = 1.105, 95% CI: 1.066-1.269, P < 0.05).

Conclusions: Serum FSTL1 concentrations increase in obese children with MAFLD and may have the potential to be a risk factor for MAFLD in children with obesity.