Evaluating the causal effect of atherosclerosis on the risk of intervertebral disc degeneration.

Background: Intervertebral disc degeneration (IDD) and atherosclerosis are two common age-related conditions that can cause significant morbidity. While previous studies have suggested an association between the two conditions, the nature of this association remains unclear. Methods: We used Mendelian randomization (MR) to investigate the causal relationship between IDD and atherosclerosis. We identified genetic variants associated with IDD using summary statistics from a large genome-wide association study (GWAS). These variants were then used as instrumental variables to infer causal relationships with atherosclerosis in summary statistics from a separate GWAS. Results: Our MR analysis provided evidence for a causal relationship between IDD and atherosclerosis. We found that the genetic predisposition to atherosclerosis was associated with a higher risk of IDD (odds ratio [OR] = 3.55, 95% confidence interval [CI]: 1.07-11.74, p = 0.04). The IVW estimates were consistent with the observational findings and other robust MR methods. Sensitivity analyses suggested that our findings were robust to potential sources of bias. Conclusions: Our study provides evidence for a causal link between IDD and atherosclerosis, suggesting that interventions targeting atherosclerosis could have potential benefits for reducing the risk of IDD. Further research is needed to explore the underlying mechanisms that link these two conditions and to investigate potential therapeutic interventions.

Investigation of causal relationships between cortical structure and osteoporosis using two-sample Mendelian randomization.

The mutual interaction between bone characteristics and brain had been reported previously, yet whether the cortical structure has any relevance to osteoporosis is questionable. Therefore, we applied a two-sample bidirectional Mendelian randomization analysis to investigate this relationship. We utilized the bone mineral density measurements of femoral neck (n = 32,735) and lumbar spine (n = 28,498) and data on osteoporosis (7300 cases and 358,014 controls). The global surficial area and thickness and 34 specific functional regions of 51,665 patients were screened by magnetic resonance imaging. For the primary estimate, we utilized the inverse-variance weighted method. The Mendelian randomization-Egger intercept test, MR-PRESSO, Cochran's Q test, and "leave-one-out" sensitivity analysis were conducted to assess heterogeneity and pleiotropy. We observed suggestive associations between decreased thickness in the precentral region (OR = 0.034, P = 0.003) and increased chance of having osteoporosis. The results also revealed suggestive causality of decreased bone mineral density in femoral neck to declined total cortical surface area (ß = 1400.230 mm2, P = 0.003), as well as the vulnerability to osteoporosis and reduced thickness in the Parstriangularis region (ß = -0.006 mm, P = 0.002). Our study supports that the brain and skeleton exhibit bidirectional crosstalk, indicating the presence of a mutual brain-bone interaction.

Network Pharmacology Prediction: The Possible Mechanisms of Cinobufotalin against Osteosarcoma.

OBJECTIVE: To explore the active compounds and targets of cinobufotalin (huachansu) compared with the osteosarcoma genes to obtain the potential therapeutic targets and pharmacological mechanisms of action of cinobufotalin on osteosarcoma through network pharmacology. METHODS: The composition of cinobufotalin was searched by literature retrieval, and the target was selected from the CTD and TCMSP databases. The osteosarcoma genes, found from the GeneCards, OMIM, and other databases, were compared with the cinobufotalin targets to obtain potential therapeutic targets. The protein-protein interaction (PPI) network of potential therapeutic targets, constructed through the STRING database, was inputted into Cytoscape software to calculate the hub genes, using the NetworkAnalyzer. The hub genes were inputted into the Kaplan-Meier Plotter online database for exploring the survival curve. Functional enrichment analysis was identified using the DAVID database. RESULTS: 28 main active compounds of cinobufotalin were explored, including bufalin, adenosine, oleic acid, and cinobufagin. 128 potential therapeutic targets on osteosarcoma are confirmed among 184 therapeutic targets form cinobufotalin. The hub genes included TP53, ACTB, AKT1, MYC, CASP3, JUN, TNF, VEGFA, HSP90AA1, and STAT3. Among the hub genes, TP53, ACTB, MYC, TNF, VEGFA, and STAT3 affect the patient survival prognosis of sarcoma. Through function enrichment analysis, it is found that the main mechanisms of cinobufotalin on osteosarcoma include promoting sarcoma apoptosis, regulating the cell cycle, and inhibiting proliferation and differentiation. CONCLUSION: The possible mechanisms of cinobufotalin against osteosarcoma are preliminarily predicted through network pharmacology, and further experiments are needed to prove these predictions.