Frontiers in Endocrinology最新文献

Aims: Previous studies on the association between vitamin E and blood pressure (BP) levels are controversial. Our study aimed to evaluate the association between blood vitamin E (alpha-tocopherol and gamma-tocopherol) levels and systolic and diastolic BP in an adult population with diabetes and without diabetes.

Methods: Our study data were obtained from a biomarker project of the Midlife in the United States (MIDUS) study. A total of 1068 subjects were included, and the associations between alpha-tocopherol and gamma-tocopherol levels and systolic and diastolic BP were further analyzed by smooth curve and multivariate linear regression analyses.

Results: Our smooth curve analysis showed an almost linear correlation between blood vitamin E (alpha-tocopherol and gamma-tocopherol) levels and systolic and diastolic BP. Furthermore, we found that blood gamma-tocopherol levels were positively and independently associated with systolic BP (B=0.427, 95% CI 0.067-0.787, P=0.020) and diastolic BP (B=0.289, 95% CI 0.072-0.507, P=0.009) when the data were adjusted for age, gender, body mass index (BMI), ever smoked cigarettes regularly, number of years of consuming alcohol and regular exercise or activity for 20 minutes or more at least 3 times/week. Consistently, blood alpha-tocopherol levels were also positively associated with systolic BP (B=0.150, 95% CI 0.064-0.235, P=0.001) and diastolic BP (B=0.056, 95% CI 0.004-0.107, P=0.035) after these variables were adjusted. However, these significant relationships exist only in subjects without diabetes, but not in subjects with diabetes.

Conclusions: We observed for the first time that blood vitamin E (alpha-tocopherol and gamma-tocopherol) levels were positively associated with systolic and diastolic BP in subjects without diabetes.

Background: The accurate diagnosis of thyroid nodules with indeterminate cytology, particularly in the atypia of undetermined significance (AUS) category, remains challenging. This study aims to predict the risk of malignancy in AUS nodules by comparing two machine learning (ML) and three conventional logistic regression (LR) models.

Methods: A retrospective study on 356 AUS nodules in 342 individuals from 6728 patients who underwent thyroid surgery in 2021. All the clinical, ultrasonographic, and molecular data were collected and randomly separated into training and validation cohorts at a ratio of 7: 3. ML (random forest and XGBoost) and LR (lasso regression, best subset selection, and backward stepwise regression) models were constructed and evaluated using area under the curve (AUC), calibration, and clinical utility metrics.

Results: Approximately 90% (321/356) of the AUS nodules were malignant, predominantly papillary thyroid carcinoma with 68.6% BRAF V600E mutations. The final LR prediction model based on backward stepwise regression exhibited superior discrimination with AUC values of 0.83 (95% CI: 0.73-0.92) and 0.80 (95% CI: 0.67-0.94) in training and validation, respectively. Well calibration, and clinical utility were also confirmed. The ML models showed moderate performance. A nomogram was developed on the final LR model.

Conclusions: The LR model developed using the backward stepwise regression, outperformed ML models in predicting malignancy in AUS thyroid nodules. The corresponding nomogram based on this model provides a valuable and practical tool for personalized risk assessment, potentially reducing unnecessary surgeries and enhancing clinical decision-making.

Tendons are fibrous connective tissues that transmit force from muscles to bones. Despite their ability to withstand various loads, tendons are susceptible to significant damage. The healing process of tendons and ligaments connected to bone surfaces after injury presents a clinical challenge due to the intricate structure, composition, cellular populations, and mechanics of the interface. Inflammation plays a pivotal role in tendon healing, creating an inflammatory microenvironment through cytokines and immune cells that aid in debris clearance, tendon cell proliferation, and collagen fiber formation. However, uncontrolled inflammation can lead to tissue damage, and adhesions, and impede proper tendon healing, culminating in scar tissue formation. Therefore, precise regulation of inflammation is crucial. This review offers insights into the impact of inflammation on tendon-bone healing and its underlying mechanisms. Understanding the inflammatory microenvironment, cellular interactions, and extracellular matrix dynamics is essential for promoting optimal healing of tendon-bone injuries. The roles of fibroblasts, inflammatory cytokines, chemokines, and growth factors in promoting healing, inhibiting scar formation, and facilitating tissue regeneration are discussed, highlighting the necessity of balancing the suppression of detrimental inflammatory responses with the promotion of beneficial aspects to enhance tendon healing outcomes. Additionally, the review explores the significant implications and translational potential of targeted inflammatory modulation therapies in refining strategies for tendon-bone healing treatments.

According to the Society of Critical Care Medicine, critical illness-related corticosteroid insufficiency (CIRCI) characterizes hypothalamic-adrenal axis insufficiency following acute medical conditions of various causes, i.e., sepsis, septic shock, acute respiratory distress syndrome, community-acquired pneumonia, and status after major surgical procedures. Due to highly variable etiology, understanding the pathomechanism and management of CIRCI assumes relevance for all centers providing intensive care. During CIRCI, multiple peripheral adaptations develop, and cortisol distribution volume increases due to hypothalamic-adrenal axis dysregulation, alterations in cortisol metabolism, and tissue resistance to corticosteroids. The proper diagnosis and treatment of CIRCI may be challenging in many cases. Although we have been acquainted with CIRCI since 2008, it remains a difficult condition with widely variable approaches among clinicians due to inconsistent high-quality study results determining the effect of corticosteroids on mortality. Corticosteroids are widely used in acutely ill patients, highlighting the necessity for reliable knowledge to support crucial clinicians' decisions in daily medical practice. In this review, we provide an overview of the clinical management of patients with CIRCI based on current recommendations and selected studies.

Background: Observational studies suggested a bidirectional relationship between severe autoimmune type 2 diabetes and focal epilepsy. However, it remains debated whether and in which direction a causal association exists. This genetics-based study aimed to explore the relationships of severe autoimmune type 2 diabetes (T2DM) and focal epilepsy outcomes with two sample Mendelian randomization (TSMR) method.

Methods: Genetic instruments were obtained from large-scale genome-wide meta-analysis of severe autoimmune T2DM (Ncase = 452, Ncontrol = 2,744), and focal epilepsy (Ncase = 929, Ncontrol = 212,532) of European ancestry. A series of analyses were performed to select eligible genetic instruments robustly associated with each of the traits using summary-level statistics. Inverse variance weighted was used for primary analysis, with alternative 11 MR methods. A scatter plot was utilized to illustrate the association between single nucleotide polymorphism (SNP) effects on the exposure and SNP effects on the outcome. The Wald ratio for individual SNPs and their cumulative effects was depicted using a forest plot. And diagnostics and sensitivity analyses were used to evaluate if the causal estimates are robust to violations of MR underlying assumptions, including pleiotropy, heterogeneity assessment, and leave-one-out analysis. Then the results were validated using CURATED database of DisGeNET platform.

Results: For forward analysis, genetic predisposition to severe autoimmune T2DM was associated with an increased risk of focal epilepsy (Inverse variance weighted (IVW) method: OR = 1.11, 95% CI = 1.03-1.18, p = 0.012). For reverse analysis, there was no enough instrument variables of focal epilepsy on severe autoimmune T2DM. Further, the interrelation between severe autoimmune T2DM and focal epilepsy was demonstrated via variant-disease association network analysis using the instrument SNPs.

Discussion: This MR study supports a causal link between severe autoimmune T2DM and focal epilepsy. More effort should be made to screen seizure in severe autoimmune T2DM, unravel its clinical implications, and explore its role as a putative modifiable risk factor.

Background: Few studies focus on the clinical, laboratory, radiological, and biological characteristics of bone and muscle of multiple vertebral fractures, which are associated with a more poor prognosis compared with single fracture.

Purpose: To compare the BMD, bone turnover, muscularity, fatty infiltration of muscle, and prevalence of co-morbidities in patients with single and multiple vertebral fractures.

Methods: We recruited 100 patients with single fracture (age 66.96 ± 8.24 years) and 100 with multiple fractures (age 69.90 ± 7.80 years); performed dual-energy X-ray absorptiometry of the femoral neck, hip, and lumbar vertebrae; and measured biochemical markers of bone turnover, muscularity, and fatty infiltration.

Results: Patients with multiple vertebral fractures had lower hip BMD (p=0.010) than those with single fractures, but there was no difference in femoral neck and lumbar vertebral BMD nor in muscularity. However, fatty infiltration, an indicator of muscle quality, was significantly higher in participants with multiple fractures (p=0.006). Diabetes was significantly more common in patients with multiple fractures (p=0.042). There were no significant differences in markers of bone turnover, and Seperman analyses showed no correlations of CTX-1 or tPINP with the BMD of the hip, femoral neck, or lumbar spine. However, high CTX-1 was associated with high tPINP (r=0.4805; p<0.0001), and marked fatty infiltration was associated with low hip, lumbar vertebral, and femoral neck BMD. Cox regression analyses showed that age (OR 1.057; 95% CI 1.016-1.101; p=0.006) and low hip BMD (OR 0.016; 95% CI, 0.000-0.549; p=0.022) were associated with a higher risk of multiple fractures.

Conclusion: Patients with multiple fractures tend to have lower hip BMD, a history of type 2 diabetes, and more substantial fatty infiltration of muscle than in those with single fractures. Age and hip BMD rather than lumbar vertebrae BMD were found to be independent risk factors for multiple vertebral compression fractures, implying that hip BMD may be a more sensitive predictor for multiple vertebral fractures. More improvements in hip BMD and focus on older persons may be useful means of preventing multiple fractures.

Background: Anoikis is intricately associated with the malignant progression of cancer. Thyroid cancer (THCA) is the most common endocrine tumor, metastasis is closely related to treatment response and prognosis of THCA. Hence, it is imperative to comprehensively identify predictive prognostic genes and novel molecular targets for effective THCA therapy.

Methods: Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were utilized to mine differentially expressed anoikis-related (DE-ARGs). Then, the prognostic genes were identified and a risk signature was constructed for THCA using univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) method. Furthermore, the associations between risk signature and immune infiltration, immunotherapy, as well as potential mechanisms of action were determined using multiple R packages and Wilcoxon test. Finally, Mendelian randomized (MR) analysis was conducted to investigate the causal relationship between the prognostic genes and THCA.

Results: In total, six prognostic genes (LRRC75A, METTL7B, ADRA1B, TPD52L1, TNFRSF10C, and CXCL8) related to anoikis were identified, and the corresponding risk signature were constructed to assess the survival time of THCA patients. Immunocorrelation analysis demonstrated the anoikis-relevant risk signature could be used to evaluate immunotherapy effects in THCA patients, and the infiltration of immune cells was correlated with the degree of risk in THCA patients. According to two-sample MR analysis, there was the significant causal relationship between CXCL8 and THCA (odds ratio [OR] > 1 & p< 0.05), and the increase of its gene expression would lead to an increased risk of THCA. Furthermore, real-time quantitative polymerase chain reaction (RT-qPCR) confirmed the upregulated expression patterns of these prognostic genes in THCA tissues.

Conclusion: In conclusion, we constructed the risk signature related to anoikis for THCA, which might have important clinical significance for improving the quality of life and treatment effect of THCA patients.

Purpose: Cancer often coexists with erectile dysfunction, yet the causal relationship between them remains unclear. This study aims to investigate the causal link between tumors and ED through Mendelian randomization.

Method: Data on 13 different cancers, including lung cancer, colorectal cancer, testicular cancer, lymphoma, esophageal cancer, pancreatic cancer, thyroid cancer, bladder cancer and brain cancer were collected from various databases. ED data, comprising 2,205 cases and 164,104 controls, were sourced from the FinnGen project. Primary methods for MR analysis included IVW, MR-Egger, weighted median, and weighted mode.

Results: IVW results revealed associations between colorectal cancer (OR=1.17;95% CI 1.02-1.13, p=0.0252), prostate cancer (OR=1.63;95% CI 1.52-1.75, p<0.001) and liver cancer (OR=0.93;95% CI 0.88 -0.99, p=0.012) with ED.

Conclusion: Mendelian randomization analysis supports that prostate cancer and colorectal cancer are associated with an increased risk of Erectile Dysfunction, whereas liver cancer is linked to a decreased risk of ED. No evidence suggests that ED contributes to an increased risk of prostate cancer.

[This corrects the article DOI: 10.3389/fendo.2024.1433930.].

Objective: This study aimed to investigate the relationship between bone metabolism markers, including serum klotho, fibroblast growth factor 23 (FGF23), 25(OH)D3, iPTH, calcium (Ca), and PHOS and the progression of diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). Additionally, the predictive value of these markers for DKD progression was evaluated.

Methods: This study involved 126 patients with T2DM between May 2021 and March 2023. DKD staging was assessed based on urinary protein excretion rates and estimated glomerular filtration rate (eGFR). The study evaluated serum concentrations of klotho, FGF23, 25(OH)D3, iPTH, Ca and PHOS across various stages and examined their relationships with clinical parameters. Receiver operating characteristic (ROC) curve analysis was utilized to determine the predictive accuracy of these bone metabolism markers for DKD. Multivariate linear and logistic regression analyses identified risk factors linked to DKD severity.

Results: Among the 126 participants, 30 had non-DKD with normal proteinuria, while 96 had DKD, categorized as 31 with stage III DKD (microproteinuria), 34 with stage IV DKD, and 31 with stage V DKD (massive proteinuria). With advancing DKD from stage III to V, levels of klotho, 25(OH)D3, and Ca decreased significantly, whereas FGF23, iPTH and PHOS levels increased markedly. Klotho is significantly positively correlated with eGFR (r = 0.285, P = 0.001.) and negative correlations with serum creatinine (Scr) and UACR (r = -0.255, P = 0.004; r = -0.260, P = 0.011). FGF23 was positively related to systolic blood pressure (SBP) (r = 0.224, P = 0.012), but negatively with eGFR (r = -0.294, P = 0.001). Additionally, 25(OH)D3 exhibited significant negative correlations with several adverse clinical biomarkers, and both iPTH, Ca and PHOS were strongly associated with DKD progression (P<0.05). ROC analysis showed high predictive accuracy for DKD using these bone metabolism markers, with a combined area under the curve (AUC) of 0.846. Multivariate logistic regression analysis reinforced the significance of these markers in DKD progression.

Conclusion: Bone metabolism markers, such as klotho, FGF23, 25(OH)D3, iPTH, Ca and PHOS are intricately linked to DKD progression and may function as valuable predictive biomarkers.