Background Several observational studies have found that idiopathic pulmonary fibrosis (IPF) is often accompanied by elevated circulating C-reactive protein (CRP) levels. However, the causal relationship between them remains to be determined. Therefore, our study aimed to explore the causal effect of circulating CRP levels on IPF risk by the two-sample Mendelian randomization (MR) analysis. Methods We analyzed the data from two genome-wide association studies (GWAS) of European ancestry, including circulating CRP levels (204,402 individuals) and IPF (1028 cases and 196,986 controls). We primarily used inverse variance weighted (IVW) to assess the causal effect of circulating CRP levels on IPF risk. MR-Egger regression and MR-PRESSO global test were used to determine pleiotropy. Heterogeneity was examined with Cochran's Q test. The leave-one-out analysis tested the robustness of the results. Results We obtained 54 SNPs as instrumental variables (IVs) for circulating CRP levels, and these IVs had no significant horizontal pleiotropy, heterogeneity, or bias. MR analysis revealed a causal effect between elevated circulating CRP levels and increased risk of IPF (ORIVW = 1.446, 95% CI 1.128–1.854, P = 0.004). Conclusions The present study indicated that elevated circulating CRP levels could increase the risk of developing IPF in people of European ancestry.

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Background Patients with lung adenocarcinoma (LUAD) may be more predisposed to coronavirus disease 2019 (COVID-19) and have a poorer prognosis. Currently, there is still a lack of effective anti-LUAD/COVID-19 drugs. Thus, this study aimed to screen for an effective anti-LUAD/COVID-19 drug and explore the potential mechanisms. Methods Firstly, we performed differentially expressed gene (DEG) analysis on LUAD transcriptome profiling data in The Cancer Genome Atlas (TCGA), where intersections with COVID-19-related genes were screened out. Then, we conducted Cox proportional hazards analyses on these LUAD/COVID-19 DEGs to construct a risk score. Next, LUAD/COVID-19 DEGs were uploaded on Connectivity Map to obtain drugs for anti-LUAD/COVID-19. Finally, we used network pharmacology, molecular docking, and molecular dynamics (MD) simulation to explore the drug’s therapeutic targets and potential mechanisms for anti-LUAD/COVID-19. Results We identified 230 LUAD/COVID-19 DEGs and constructed a risk score containing 7 genes (BTK, CCL20, FURIN, LDHA, TRPA1, ZIC5, and SDK1) that could classify LUAD patients into two risk groups. Then, we screened emetine as an effective drug for anti-LUAD/COVID-19. Network pharmacology analyses identified 6 potential targets (IL6, DPP4, MIF, PRF1, SERPING1, and SLC6A4) for emetine in anti-LUAD/COVID-19. Molecular docking and MD simulation analyses showed that emetine exhibited excellent binding capacities to DDP4 and the main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Conclusions This study found that emetine may inhibit the entry and replication of SARS-CoV-2 and enhance tumor immunity by bounding to DDP4 and Mpro.

Depression affects people with multiple adverse outcomes, and the side effects of antidepressants are troubling for depression sufferers. Aromatic drugs have been widely used to relieve symptoms of depression with fewer side effects. Ligustilide (LIG) is the main component of volatile oil in angelica sinensis, exhibiting an excellent anti-depressive effect. However, the mechanisms of the anti-depressive effect of LIG remain unclear. Therefore, this study aimed to explore the mechanisms of LIG exerting an anti-depressive effect. We obtained 12,969 depression-related genes and 204 LIG targets by a network pharmacology approach, which were intersected to get 150 LIG anti-depressive targets. Then, we identified core targets by MCODE, including MAPK3, EGF, MAPK14, CCND1, IL6, CASP3, IL2, MYC, TLR4, AKT1, ESR1, TP53, HIF1A, SRC, STAT3, AR, IL1B, and CREBBP. Functional enrichment analysis of core targets showed a significant association with PI3K/AKT and MAPK signaling pathways. Molecular docking showed strong affinities of LIG with AKT1, MAPK14, and ESR1. Finally, we validated the interactions between these proteins and LIG by molecular dynamics (MD) simulations. In conclusion, this study successfully predicted that LIG exerted an anti-depressive effect through multiple targets, including AKT1, MAPK14, and ESR1, and the pathways of PI3K/AKT and MAPK. The study provides a new strategy to explore the molecular mechanisms of LIG in treating depression.

BackgroundSmall-cell lung cancer (SCLC) usually presents as an extensive disease with a poor prognosis at the time of diagnosis. Exosomes are rich in biological information and have a powerful impact on tumor progression and metastasis. Therefore, this study aimed to screen for diagnostic markers of blood exosomes in SCLC patients and to build a prognostic model.MethodsWe identified blood exosome differentially expressed (DE) RNAs in the exoRBase cohort and identified feature RNAs by the LASSO, Random Forest, and SVM-REF three algorithms. Then, we identified DE genes (DEGs) between SCLC tissues and normal lung tissues in the GEO cohort and obtained exosome-associated DEGs (EDEGs) by intersection with exosomal DEmRNAs. Finally, we performed univariate Cox, LASSO, and multivariate Cox regression analyses on EDEGs to construct the model. We then compared the patients’ overall survival (OS) between the two risk groups and assessed the independent prognostic value of the model using receiver operating characteristic (ROC) curve analysis.ResultsWe identified 952 DEmRNAs, 210 DElncRNAs, and 190 DEcircRNAs in exosomes and identified 13 feature RNAs with good diagnostic value. Then, we obtained 274 EDEGs and constructed a risk model containing 7 genes (TBX21, ZFHX2, HIST2H2BE, LTBP1, SIAE, HIST1H2AL, and TSPAN9). Low-risk patients had a longer OS time than high-risk patients. The risk model can independently predict the prognosis of SCLC patients with the areas under the ROC curve (AUCs) of 0.820 at 1 year, 0.952 at 3 years, and 0.989 at 5 years.ConclusionsWe identified 13 valuable diagnostic markers in the exosomes of SCLC patients and constructed a new promising prognostic model for SCLC.