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Background Asthma is a common respiratory disease caused by genetic and environmental factors, but the contribution of insulin use to the risk of asthma remains unclear. This study aimed to investigate the association between insulin use and asthma in a large population-based cohort, and further explore their causal relationship by Mendelian randomization (MR) analysis. Methods An epidemiological study including 85,887 participants from the National Health and Nutrition Examination Survey (NHANES) 2001-2018 was performed to evaluate the association between insulin use and asthma. Based on the inverse-variance weighted approach, MR analysis were conducted to estimate the causal effect of insulin use on asthma from the UKB and FinnGen datasets, respectively. Results In the NHANES cohort, we found that insulin use was associated with an increased risk of asthma [odd ratio (OR) 1.38; 95% CI 1.16-1.64; p < 0.001]. For the MR analysis, we found a causal relationship between insulin use and a higher risk of asthma in both Finn (OR 1.10; p < 0.001) and UK Biobank cohorts (OR 1.18; p < 0.001). Meanwhile, there was no causal association between diabetes and asthma. After multivariable adjustment for diabetes in UKB cohort, the insulin use remained significantly associated with an increased risk of asthma (OR 1.17, p < 0.001). Conclusions An association between insulin use and an increased risk of asthma was found via the real-world data from the NHANES. In addition, the current study identified a causal effect and provided a genetic evidence of insulin use and asthma. More studies are needed to elucidate the mechanisms underlying the association between insulin use and asthma., Author(s): Zikai Lin [sup.1] [sup.2], Junfeng Huang [sup.1], Shuojia Xie [sup.1] [sup.2], Ziwen Zheng [sup.1], Kailun Tang [sup.1] [sup.3] [sup.4], Shiyue Li [sup.1], Ruchong Chen [sup.1] [sup.3] Author Affiliations: (1) [...]

Background: Because stomach adenocarcinoma (STAD) has a poor prognosis, it is necessary to explore new prognostic genes to stratify patients to guide existing individualized treatments., Methods: Survival and clinical information, RNA-seq data and mutation data of STAD were acquired from The Cancer Genome Atlas (TCGA) database. Fifty-one nicotinamide adenine dinucleotide (NAD + ) metabolism-related genes (NMRGs) were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases. Differentially expressed NMRGs (DE-NMRGs) between STAD and normal samples were screened, and consistent clustering analysis of STAD patients was performed based on the DE-NMRGs. Survival analysis, Gene Set Enrichment Analysis (GSEA), mutation frequency analysis, immune microenvironment analysis and drug prediction were performed among different clusters. Additionally, the differentially expressed genes (DEGs) among different clusters were selected, and the intersections of DEGs and DE-NMRGs were selected as the prognostic genes. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was performed on a human gastric mucosa epithelial cell line and cancer cell line to verify the expression of the prognostic genes., Results: A total of 27 DE-NMRGs and two clusters were selected. There was a difference in survival between clusters 1 and 2. Furthermore, 18 DE-NMRGs were significantly different between clusters 1 and 2. The different Gene Ontology (GO) biological processes and KEGG pathways between clusters 1 and 2 were mainly enriched in cyclic nucleotide mediated signaling, synaptic signaling and hedgehog signaling pathway, etc. The somatic mutation frequencies were different between the two clusters, and TTN was the highest mutated gene in the patients of the clusters 1 and 2. Additionally, eight immune cells, immune score, stromal score, and estimate score were different between clusters 1 and 2. The patients in cluster 2 were sensitive to CTLA4 inhibitor treatment. Furthermore, the top five drugs (AP.24534, BX.795, Midostaurin, WO2009093927 and CCT007093) were significantly higher in cluster 1 than in cluster 2. Finally, three genes (AOX1, NNMT and PTGIS) were acquired as prognostic, and their expressions were consistent with the results of bioinformatics analysis., Conclusions: Three prognostic genes related to NAD + metabolism in STAD were screened out, which provides a theoretical basis and reference value for future treatment and prognosis of STAD., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-22-1092/coif). The authors have no conflicts of interest to declare., (2022 Journal of Gastrointestinal Oncology. All rights reserved.)