Anoikis-related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironment.

Clear cell renal cell carcinoma (ccRCC) is one of the most common primary malignancies of the urinary tract, highly heterogeneous, and increasing in incidence worldwide. Anoikis is a specific type of programmed cell death in which solid tumor cells or normal epithelial cells that do not have metastatic properties lose adhesion to the extracellular matrix or undergo inappropriate cell adhesion-induced apoptosis. Anoikis is thought to play a critical role in tumorigenesis, maintenance, and treatment, according to an increasing amount of research. However, there is still some uncertainty regarding the general impact of anoikis-related genes (ARGs) on the prognostic importance, tumor microenvironment characteristics, and treatment reaction of ccRCC patients. For this study, we used The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus datasets to access the RNA sequencing results and clinical information from ccRCC patients. 29 ARGs related to survival were found using differential analysis and univariate Cox regression analysis. The samples were then divided into two clusters that had different immune traits via unsupervised cluster analysis using 29 prognosis-associated differently expressed ARGs. Then, to build an ARGs signature, 7 genes (PLAU, EDA2R, AFP, PLG, TUBB3, APOBEC3G, and MALAT1) were found using Least Absolute Shrinkage and Selection Operator regression analysis. The new ARGs signature demonstrated outstanding prognostic capability for ccRCC patients' overall survival. In conclusion, for ccRCC patients, we created an ARGs signature that strongly connects to immunological traits and therapy response. Clinicians may find this ARGs signature helpful in developing more individualized and detailed treatment strategies for ccRCC patients.

Physical Activity, Sedentary Behavior, and Osteoarthritis: A Two-Sample Mendelian Randomization Analysis.

Background: Sedentary behavior and physical activity are still ambiguous in their effects on osteoarthritis. We aimed to evaluate the effects of physical activity and sedentary behavior on osteoarthritis to provide a reference for the prevention of osteoarthritis. Methods: This study was conducted in Changchun, China in 2022. We used two-sample Mendelian randomization with the SNP as an instrumental variable to investigate the effect of physical activity and sedentary behavior on osteoarthritis. In addition, a two-step Mendelian randomization method was used to test whether mediating factors (BMI, smoking, Apolipoprotein B) were involved in mediating the effects of exposure factors on osteoarthritis. Results: TV watching was causally related to knee osteoarthritis and spine osteoarthritis, and they were positively correlated (knee osteoarthritis: OR=1.162,95 %CI: 1.027-1.315, P=0.017; spine osteoarthritis: OR=1.208,95 %CI: 1.033-1.413, P=0.018). BMI played a mediating role in the process of TV watching with knee osteoarthritis and spine osteoarthritis. ((The proportion of BMI mediating effect: knee osteoarthritis: 47.1% (95% CI: 36.7%~63.2%); spine osteoarthritis: 29.5% (95% CI: 19.3%~40.8%)). The proportion of Smoking mediating effect in the process of TV watching with spine osteoarthritis was 16.1% (95% CI: 3.7% ~ 31.6%). Conclusion: TV watching is a potential risk factor for osteoarthritis and plays a role through modifiable factors such as BMI and smoking, therefore, interventions on these factors have the potential to reduce the burden of osteoarthritis caused by longer TV watching times.

Effects of blood pressure and antihypertensive drugs on osteoarthritis: a mendelian randomized study.

BACKGROUND: Previous studies have suggested that antihypertensive drugs may play a role in the treatment of osteoarthritis, but these studies may be limited by confounding factors and lead to biased results. Therefore, we conducted a Mendelian randomization study to investigate the effects of blood pressure and antihypertensive drugs on osteoarthritis. METHODS: We used published large-scale genome-wide association data and applied univariate and multivariate Mendelian randomization methods. The main analysis model was inverse variance weighting, and the reliability of the results was tested using MR-Egger intercept analysis, Cochran's Q test, and leave-one-out analysis. We comprehensively evaluated the relationship between systolic blood pressure, diastolic blood pressure, 12 antihypertensive drugs, and osteoarthritis. We also conducted verification in the independent queue of UK Biobank and built a simple linear regression model to obtain an independent comparison. RESULTS: We found no evidence that systolic and diastolic blood pressure significantly affected osteoarthritis. However, among antihypertensive drugs, we observed a significant positive correlation between potassium-preserving diuretics and aldosterone antagonists and all osteoarthritis (OR: 0.560, 95% CI 0.406-0.772, P = 0.0004). Sensitivity analysis showed no horizontal pleiotropy or heterogeneity, and the leave-one-out analysis demonstrated the reliability of the results. This result was replicated with nominally statistical significance in the validation cohort and exhibited significant correlation in the linear regression analysis. CONCLUSIONS: Our study suggested that controlling the protein targets of potassium-sparing diuretics and aldosterone antagonists may have beneficial results for osteoarthritis. These findings provide valuable medication strategies for the control of hypertension in patients with osteoarthritis.

Analysis of cuproptosis-related genes in Ulcerative colitis and immunological characterization based on machine learning.

Cuproptosis is a novel form of cell death, mediated by protein lipid acylation and highly associated with mitochondrial metabolism, which is regulated in the cell. Ulcerative colitis (UC) is a chronic inflammatory bowel disease that recurs frequently, and its incidence is increasing worldwide every year. Currently, a growing number of studies have shown that cuproptosis-related genes (CRGs) play a crucial role in the development and progression of a variety of tumors. However, the regulatory role of CRGs in UC has not been fully elucidated. Firstly, we identified differentially expressed genes in UC, Likewise, CRGs expression profiles and immunological profiles were evaluated. Using 75 UC samples, we typed UC based on the expression profiles of CRGs, followed by correlative immune cell infiltration analysis. Using the weighted gene co-expression network analysis (WGCNA) methodology, the cluster's differentially expressed genes (DEGs) were produced. Then, the performances of extreme gradient boosting models (XGB), support vector machine models (SVM), random forest models (RF), and generalized linear models (GLM) were constructed and predicted. Finally, the effectiveness of the best machine learning model was evaluated using five external datasets, receiver operating characteristic curve (ROC), the area under the curve of ROC (AUC), a calibration curve, a nomogram, and a decision curve analysis (DCA). A total of 13 CRGs were identified as significantly different in UC and control samples. Two subtypes were identified in UC based on CRGs expression profiles. Immune cell infiltration analysis of subtypes showed significant differences between immune cells of different subtypes. WGCNA results showed a total of 8 modules with significant differences between subtypes, with the turquoise module being the most specific. The machine learning results showed satisfactory performance of the XGB model (AUC = 0.981). Finally, the construction of the final 5-gene-based XGB model, validated by the calibration curve, nomogram, decision curve analysis, and five external datasets (GSE11223: AUC = 0.987; GSE38713: AUC = 0.815; GSE53306: AUC = 0.946; GSE94648: AUC = 0.809; GSE87466: AUC = 0.981), also proved to predict subtypes of UC with accuracy. Our research presents a trustworthy model that can predict the likelihood of developing UC and methodically outlines the complex relationship between CRGs and UC.

Visceral adipose tissue and osteoarthritis, a two-sample Mendelian randomized study.

Background: The relationship between visceral adipose tissue and osteoarthritis is not clear. The purpose of our study was to explore the relationship between visceral adipose tissue and osteoarthritis. Methods: We used a two-sample Mendelian randomization method to select single-nucleotide polymorphisms (SNPs) significantly associated with visceral adipose tissue as instrumental variables to explore the relationship between visceral adipose tissue and all osteoarthritis, hand osteoarthritis, hip osteoarthritis, knee osteoarthritis, and spine osteoarthritis. The reliability of the results was tested using sensitivity analysis. Results: Our findings indicated that visceral adipose tissue was associated with all osteoarthritis, hip osteoarthritis, knee osteoarthritis, and spine osteoarthritis (all osteoarthritis: OR = 1.399, 95% CI: 1.335-1.467, p = 7.95e-44; hip osteoarthritis: OR = 1.399, 95% CI: 1.284-1.524, p = 1.41e-14; knee osteoarthritis: OR = 1.794, 95% CI: 1.662-1.937, p = 1.33e-50; and spine osteoarthritis: OR = 1.445, 95% CI: 1.314-1.589, p = 2.89e-14). Sensitivity analysis demonstrated the reliability of these results. Conclusion: Our study suggests that genetically predicted visceral adipose tissue is associated with osteoarthritis. Reducing the accumulation of visceral adipose tissue could potentially have an impact on the incidence of osteoarthritis.

Prevalence and Distribution of Osteopenia in Chinese Population: A System Review and Meta-Analysis.

Background: The number of patients with osteoporosis ranks first in the world in China and as a precursor state of osteoporosis, the number and incidence of osteopenia are much higher than that of osteoporosis. This meta-analysis was conducted to evaluate the incidence and distribution of osteopenia in adults in mainland of China over 10 years to provides reference for the early prevention of osteoporosis and policymaking. Methods: Relevant data were extracted from the databases including CNKI, Wanfang, VIP, Web of Science, PubMed, EMBASE, and Medline about the surveys on osteoporosis and bone loss from 2010 to 2021 by searching. The random effects model was adopted for Meta-analysis, and the funnel plot was used to test publication bias. Results: Forty-seven literatures were included in this study, covering 27 provinces and 38 regions in the mainland of China, with the study of 135,688 cases, showing that the prevalence of osteopenia in adults in the past decade was 28.3%(95% CI 24-33%), aged 40∼60 yr old, reaching the highest level. The incidence of osteopenia in males was higher than that in females (P<0.05), without significant difference in south and north China. Conclusion: There is a large population with osteopenia in China, especially middle-aged population, both men and women should pay attention to osteopenia to delay its further progression.