EDEM2 is a diagnostic and prognostic biomarker and associated with immune infiltration in glioma: A comprehensive analysis

Genetic Influence of the Brain on Muscle Structure: A Mendelian Randomization Study of Sarcopenia

BACKGROUND

The association between brain and sarcopenia has not been clarified. We aim to investigate the causal association between brain structure, function, gene expression and sarcopenia-related traits.

METHODS

All participants were Europeans. GWAS data of Brain Imaging Data Structure (BIDs) was from the UK Biobank. Gene expression in 13 brain regions was acquired from the GTEx Consortium. The sarcopenia-related traits, including appendicular lean mass (ALM), whole body lean mass (WBLM), grip strength and sarcopenia diagnosed by the European Working Group on Sarcopenia in Older People (EWGSOP) or Foundation for the National Institutes of Health (FNIH), were from the IEU website. The inverse variance weighted (IVW), MR Egger, weighted median, weighted mode and Wald ratio methods were used for a two-sample Mendelian randomization (MR) analysis between brain structures and sarcopenia-related traits. The summary-data-based MR (SMR) was used to investigate brain genes causally influencing sarcopenia. We calculated the F-value, odds ratio with 95% CI and p-value. For the sensitivity analysis, the heterogeneity I2 statistic, Cochrane's Q test, Egger's intercept test, MR-PRESSO and the leave-one-out sensitivity test were used. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI), transcription factor interaction prediction and miRNA interaction prediction analysis were used to reveal potential signalling pathways and mechanisms.

RESULTS

We included 3144 imaging phenotypes from 8428 participants in BIDs data. One hundred forty-one BIDs were identified to causally influence ALM, 160 BIDs showed significant causal effect on the WBLM, and 86 BIDs showed significant causal effect on grip strength. There were 48 or 32 BIDs causally associated with sarcopenia diagnosed by the EWGSOP or FNIH criteria respectively. After FDR correction, there were 35 BIDs showing causal effect on the ALM, 28 BIDs showing causal effect on the WBLM and 7 BIDs showing causal effect on grip strength (p < 0.05). Twelve to forty-eight genes in different brain regions showed causal effect on all the five sarcopenia-related traits. MMP24-AS1, HLA-DRB6, HLA-DQA2, DDX42, BAG6, NUSAP1, LINC00940, NME1-NME2 and AS3MT in the amygdala region showed detrimental effect on all the five sarcopenia-related traits, whereas HLA-DRB1, HLA-DQB1-AS1 and C6ORF3 showed protective effect (p < 0.05). The gene enrichment analysis indicated these screened genes was mainly enriched in immune-related signalling.

CONCLUSION

We discovered the causal effect of BIDs and brain gene expression on sarcopenia. The positive genes were mainly enriched in immune-related signalling, suggesting an immune-based cross-organ regulation mechanism of brain-muscle axis.

Identification of Crucial Genes and Signaling Pathways in Alectinib-Resistant Lung Adenocarcinoma Using Bioinformatic Analysis

Alectinib, a second-generation anaplastic lymphoma kinase (ALK) inhibitor, has been shown to be effective for patients with ALK-positive non-small cell lung cancer (NSCLC). However, alectinib resistance is a serious problem worldwide. To the best of our knowledge, little information is available on its molecular mechanisms using the Gene Expression Omnibus (GEO) database. In this study, the differentially expressed genes (DEGs) were selected from the gene expression profile GSE73167 between parental and alectinib-resistant human lung adenocarcinoma (LUAD) cell samples. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) annotation enrichment analyses were conducted using Database for Annotation, Visualization and Integrated Discovery (DAVID). The construction of protein-protein interaction (PPI) network was performed to visualize DEGs. The hub genes were extracted based on the analysis of the PPI network using plug-in cytoHubba of Cytoscape software. The functional roles of the key genes were investigated using Gene Expression Profiling Interactive Analysis (GEPIA), University of Alabama at Birmingham Cancer (UALCAN), Gene Set Enrichment Analysis (GSEA), and Tumor Immune Estimation Resource (TIMER) analysis. The networks of kinase, miRNA, and transcription-factor targets of SFTPD were explored using LinkedOmics. The drug sensitivity analysis of SFTPD was analyzed using the RNAactDrug database. Results showed a total of 144 DEGs were identified. Five hub genes were extracted, including mucin 5B (MUC5B), surfactant protein D (SFTPD), deleted in malignant brain tumors 1 (DMBT1), surfactant protein A2 (SFTPA2), and trefoil factor 3 (TFF3). The survival analysis using GEPIA displayed that low expression of SFTPD had a significantly negative effect on the prognosis of patients with LUAD. GSEA revealed that low expression of SFTPD was positively correlated with the pathways associated with drug resistance, such as DNA replication, cell cycle, drug metabolism, and DNA damage repair, including mismatch repair (MMR), base excision repair (BER), homologous recombination (HR), and nucleotide excision repair (NER). The SFTPD expression was negatively correlated with the drug sensitivity of alectinib according to RNAactDrug database. The expression of SFTPD was further validated in parental H3122 cells and alectinib-resistant H3122 cells by quantitative reverse transcription PCR (RT-qPCR). In conclusion, our study found that the five hub genes, especially low expression of SFTPD, are closely related to alectinib resistance in patients with LUAD.