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Background: Lung Adenocarcinoma (LUAD) is the leading cause of death from lung cancer. Cuproptosis is the latest discovered way of programmed cell death, and Cuproptosis-Related Gene (CRG) is associated with the risk of LUAD. At present, there are few research of LUAD and Cuproptosis focuses on Long non-coding RNA (LncRNA). As genomics advances, LncRNA emerges as a potential target for understanding tumor progression and prognosis, offering prospects for biological targeted therapy. Therefore, this study provides new biomarkers and therapeutic targets for LUAD from the perspective of LncRNA. Methods: Gene expression, clinical outcome and gene mutation data of LUAD patients were downloaded from TCGA database. Spearman correlation was used to analyze the correlation between LncRNA and CRG. Univariate Cox, multivariate Cox and LASSO Cox regression analysis were used to construct a prognostic model of Cuproptosis-LncRNAs. GO and KEGG enrichment and immune function analysis were performed on differentially expressed genes between different risk groups. Then, immune escape analysis was performed on LUAD patients with different TIDE score. Finally, drug sensitivity analysis was performed on these differentially expressed genes. Results: A total of 2244 Cuproptosis-LncRNAs were found. Through the application of univariate Cox regression analysis, multivariate Cox regression analysis, and LASSO Cox regression analysis, a prognostic model was developed, integrating 15 Cuproptosis-LncRNAs to assess the risk of mortality. Following that, the model underwent assessment through risk score analysis, Kaplan-Meier survival analysis, risk distribution, and evaluation of survival outcomes. The results revealed an AUC value of 0.755 for the model, surpassing the AUC of other clinical pathological features. The results of KEGG analysis showed that the differentially expressed genes in different model groups were mainly involved in Amoebiasis, Fat digestion and absorption, and other signaling pathways. The results of TMB showed that the prognostic model of TMB combined with risk score could well evaluate the prognosis of patients. The TIDE scores did not exhibit a notable distinction between the two risk models. Analysis of drug sensitivity revealed that individuals in the low-risk category demonstrated greater responsiveness to 5-Fluorouracil, Axitinib, Bexarotene, and other drugs compared to those in the high-risk group. Conclusion: Our research offers a valuable reference for predicting the prognosis of LUAD, contributing to a better understanding of the future elucidation of the process and mechanism of Cuproptosis-LncRNAs in LUAD. [ABSTRACT FROM AUTHOR]

Background: Prior research has established a strong link between cerebral aneurysm (CA) occurrence and inflammation. Tea intake (TI) has been found to have anti-inflammatory properties through multiple mechanisms, potentially lowering CA incidence. This study aims to employ Mendelian Randomization (MR) methodology to explore the genetic causality between TI and CA. Methods: We collected Genome-wide association study (GWAS) data for CA, TI, Green tea intake (GTI), Herbal tea intake (HTI), and Rooibos tea intake (RTI). The MR analysis employed the TwoSampleMR package and utilized the inverse variance-weighted (IVW) method. Results: The findings suggest no genetic causal relationship between TI and CA (IVW: OR = 1.10, 95% CI: 0.59--2.05, P = 0.772). Similarly, there is no genetic causal association between GTI and CA (IVW: OR = 1.07, 95% CI: 0.91--1.26, P = 0.388), HTI and CA (IVW: OR = 1.00, 95% CI: 0.89--1.13, P = 0.943), or RTI and CA (IVW: OR = 1.02, 95% CI: 0.96--1.09, P = 0.472). Conclusion: There is no genetic causal relationship between TI and CA, and the different types of tea do not change this result. Further MR analysis is needed to investigate whether there is a potential genetic causal association between the quantity of TI and CA. [ABSTRACT FROM AUTHOR]