The causality between gut microbiota and non-Hodgkin lymphoma: a two-sample bidirectional Mendelian randomization study.

Background: Studies have indicated an association between gut microbiota (GM) and non-Hodgkin lymphoma (NHL). However, the causality between GM and NHL remains unclear. This study aims to investigate the causality between GM and NHL using Mendelian randomization (MR). Methods: Data on GM is sourced from the MiBioGen consortium, while data on NHL and its subtypes is sourced from the FinnGen consortium R10 version. Inverse variance weighted (IVW) was employed for the primary MR analysis method, with methods such as Bayesian weighted Mendelian randomisation (BWMR) as an adjunct. Sensitivity analyses were conducted using Cochran's Q test, MR-Egger regression, MR-PRESSO, and the "Leave-one-out" method. Results: The MR results showed that there is a causality between 27 GMs and NHL. Among them, 20 were negatively associated (OR < 1), and 7 were positively associated (OR > 1) with the corresponding diseases. All 27 MR results passed sensitivity tests, and there was no reverse causal association. Conclusion: By demonstrating a causal link between GM and NHL, this research offers novel ideas to prevent, monitor, and cure NHL later.

Construction of lncRNA-miRNA-mRNA regulatory network in severe asthmatic bronchial epithelial cells: A bioinformatics study.

Asthma is a chronic respiratory disease caused by environment-host interactions. Bronchial epithelial cells (BECs) are the first line of defense against environmental toxins. However, the mechanisms underlying the role of BECs in severe asthma (SA) are not yet fully understood. Long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) have been shown to play important roles in the regulation of gene expression in the pathogenesis of SA. In this study, bioinformatics was used for the first time to reveal the lncRNA-miRNA-mRNA regulatory network of BECs in SA. Five mRNA datasets of bronchial brushing samples from patients with SA and healthy controls (HC) were downloaded from the Gene Expression Omnibus (GEO) database. A combination of the Venn diagram and robust rank aggregation (RRA) method was used to identify core differentially expressed genes (DEGs). Protein-protein interaction (PPI) analysis of core DEGs was performed to screen hub genes. The miRDB, miRWalk, and ENCORI databases were used to predict the miRNA-mRNA relationships, and the ENCORI and starBase v2.0 databases were used to predict the upstream lncRNAs of the miRNA-mRNA relationships. Four core DEGs were identified: carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5), interleukin-1 receptor type 2 (IL1R2), trefoil factor 3 (TFF3), and vascular endothelial growth factor A (VEGFA). These 4 core DEGs indicated that SA was not significantly associated with sex. Enrichment analysis showed that the MAPK, Rap1, Ras, PI3K-Akt and Calcium signaling pathways may serve as the principal pathways of BECs in SA. A lncRNA-miRNA-mRNA regulatory network of the severe asthmatic bronchial epithelium was constructed. The top 10 competing endogenous RNAs (ceRNAs) were FGD5 antisense RNA 1 (FGD5-AS1), metastasis associated lung adenocarcinoma transcript 1 (MALAT1), X inactive specific transcript (XIST), HLA complex group 18 (HCG18), small nucleolar RNA host gene 16 (SNHG16), has-miR-20b-5p, has-miR-106a-5p, hsa-miR-106b-5p, has-miR-519d-3p and Fms related receptor tyrosine kinase 1 (FLT1). Our study revealed a potential mechanism for the lncRNA-miRNA-mRNA regulatory network in BECs in SA.

Research trends and hotspots of exosomes in respiratory diseases.

Currently, theoretical studies on exosomes in respiratory diseases have received much attention from many scholars and have made remarkable progress, which has inestimable value and potential in future clinical and scientific research. Unfortunately, no scholar has yet addressed this field's bibliometric analysis and summary. We aim to comprehensively and profoundly study and explore the present situation and highlights of exosome research at the stage of respiratory diseases and to provide meaningful insights for the future development of this field. The WOSCC literature was gathered for the study using bibliometrics, and the data were collected and analyzed using CiteSpace, VOSviewer, Microsoft Excel, and Endnote software. The publication language is "English," and the search strategy is TS = (exosome OR exosomes OR exosomal) AND TS = (respiratory OR lung). The search time is from the beginning of the WOS construction, and the deadline is July 11, 2022, at 22:00 hours. The literature types selected were dissertation, review paper, and online published paper. The analysis includes 2456 publications in 738 journals from 76 countries, 2716 institutions, and 14,568 authors. The field's annual publications have been rising, especially in recent years. China and the US lead research, and prominent universities, including Harvard Medical School, Shanghai Jiao Tong University, and Fudan University, are essential research institutes. Takahiro Ochiya, whose research focuses on exosomes and lung cancer, and Clotilde Théry, a pioneering exosome researcher, are the most cited authors in this field. The key terms include lung cancer, non-small cell lung cancer, mesenchymal stem cells, intercellular communication, exosomal miRNAs, and oncology. Cell biology, biochemistry & biotechnology, and oncology are related fields. The final summary of research hotspots is exosomes and lung cancer, mesenchymal stem cell-derived exosomes and lung inflammation, and miRNAs in exosomes as biomarkers for respiratory illnesses. The present research situation and relevant hotspots of the area were analyzed through bibliometric studies on exosomes in respiratory diseases. The research development in this field has a considerable upside, and the exosome's function in diagnosing, treating, monitoring, and prognosis of respiratory illnesses cannot be taken lightly. Moreover, we believe the research results will bring the gospel to many patients with clinical respiratory diseases shortly.

Causal relationship between gut microflora and dementia: a Mendelian randomization study.

Background: Numerous pertinent investigations have demonstrated a correlation between gut microflora (GM) and the occurrence of dementia. However, a causal connection between GM and dementia and its subtypes has not yet been clarified. Objective: To explore the causal association between GM and dementia, including its subtypes, a two-sample Mendelian randomization (TSMR) analysis was used. Methods: Our data comes from the Genome-Wide Association Study (GWAS). The principal approach employed for the Mendelian randomization study was the inverse-variance weighted method, supplemented by four methods: MR-Egger, weighted median, simple mode, and weighted mode. This was followed by Cochrane's Q test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out as sensitivity analysis validation. Results: Twenty-one GMs associated with any dementia, Alzheimer's disease, vascular dementia, Lewy body dementia, Parkinson's disease, and dementia under other disease classifications were derived from the analysis, and 21 passed sensitivity tests. Conclusion: We confirmed the causal relationship between GM and dementia and its subtypes, derived specific flora associated with increased or decreased risk of dementia, and provided new ideas for preventive, diagnostic, and therapeutic interventions for dementia mediated by gut microbiota.