Asthma and lung cancer are both significant public health concerns worldwide. Previous observational studies have indicated a potential link between asthma and an increased risk of lung cancer, whereas the causal relationship remains uncertain. We aimed to investigate the potential causal relationship between asthma and lung cancer risk utilizing Mendelian randomization (MR) design.The present study employed a two-sample MR analysis utilizing summary statistics from genome-wide association studies (GWAS) with European descent of asthma and lung cancer. The MR analysis was performed using inverse variance weighting (IVW), supplemented with MR-Egger regression and weighted median method to investigate the potential causality between asthma and lung cancer. Furthermore, Sensitivity analyses were also conducted to ensure the reliability of the findings. The MR analysis showed that genetically predicted asthma had suggestive causal association with the elevated risk of lung cancer [odds ratio (OR), 1.05 (95%Cl,1.01-1.09), P = 0.01]. The consistent direction of effects observed in the three methods further supported this finding. In addition, sensitivity analyses demonstrated the reliability of the results. This study provided potential evidence supporting a causal association between asthma and lung cancer. These findings highlighted the importance of early detection and prevention strategies for lung cancer in individuals with asthma. Further research was needed to elucidate the underlying mechanisms linking asthma and lung cancer.
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http://dx.doi.org/10.1038/s41598-024-74883-7 | DOI Listing |
J Breath Res
January 2025
School of Medicine and Pharmacy, Ocean University of China, 5 Yushan Rd, Qingdao, Shandong, 266003, CHINA.
Lung cancer is one of the most common malignancy in the world, and early detection of lung cancer remains a challenge. The exhaled breath condensate (EBC) from lung and trachea can be collected totally noninvasively. In this study, our aim is to identify differential metabolites between non-small cell lung cancer (NSCLC) and control EBC samples and discriminate NSCLC group from control group by orthogonal projections to latent structures-discriminant analysis (OPLS-DA) models.
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January 2025
School of Public Health, Capital Medical University, Beijing, 100069, P. R. China.
Substantial epidemiological evidence suggests a significant correlation between particulate matter 2.5 (PM) and lung cancer. However, the mechanism underlying this association needs to be further elucidated.
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January 2025
Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, 211166, P. R. China.
A previous study classifies solid tumors based on collagen deposition and immune infiltration abundance, identifying a refractory subtype termed armored & cold tumors, characterized by elevated collagen deposition and diminished immune infiltration. Beyond its impact on immune infiltration, collagen deposition also influences tumor angiogenesis. This study systematically analyzes the association between immuno-collagenic subtypes and angiogenesis across diverse cancer types.
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January 2025
Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 2112 Cyprus.
Breath analysis is increasingly recognized as a powerful noninvasive diagnostic technique, and a plethora of exhaled volatile biomarkers have been associated with various diseases. However, traditional analytical methodologies are not amenable to high-throughput diagnostic applications at the point of need. An optical spectroscopic technique, surface-enhanced Raman spectroscopy (SERS), mostly used in the research setting for liquid sample analysis, has recently been applied to breath-based diagnostics.
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January 2025
Research Institute of the, McGill University Health Centre, Montreal, QC, Canada.
The increasing shift from cannabis smoking to cannabis vaping is largely driven by the perception that vaping to form an aerosol represents a safer alternative to smoking and is a form of consumption appealing to youth. Herein, we compared the chemical composition and receptor-mediated activity of cannabis smoke extract (CaSE) to cannabis vaping extract (CaVE) along with the biological response in human bronchial epithelial cells. Chemical analysis using HPLC and GC/MS revealed that cannabis vaping aerosol contained fewer toxicants than smoke; CaSE and CaVE contained teratogens, carcinogens, and respiratory toxicants.
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