Causal relationship between Alzheimer's disease and cardiovascular disease: a bidirectional Mendelian randomization analysis.

Observational studies suggest that cardiovascular disease (CVD) increases the risk of developing Alzheimer's disease (AD). However, the causal relationship between the two is not clear. This study applied a two-sample bidirectional Mendelian randomization method to explore the causal relationship between CVD and AD. Genome-wide association study (GWAS) data from 46 datasets of European populations (21,982 cases of AD and 41,944 controls) were utilized to obtain genetic instrumental variables for AD. In addition, genetic instrumental variables for atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), coronary heart disease (CHD), angina pectoris (AP), and ischemic stroke (IS) (including large-artery atherosclerotic stroke [LAS] and cardioembolic stroke [CES]) were selected from GWAS data of European populations (P < 5E-8). The inverse variance weighting method was employed as the major Mendelian randomization analysis method. Genetically predicted AD odds ratios (OR) (1.06) (95% CI: 1.02-1.10, P = 0.003) were linked to higher AP analysis. A higher genetically predicted OR for CES (0.9) (95% CI 0.82-0.99, P = 0.02) was linked to a decreased AD risk. This Mendelian randomized study identified AD as a risk factor for AP. In addition, CES was related to a reduced incidence of AD. Therefore, these modifiable risk factors are crucial targets for preventing and treating AD.

Identification of critical genes and molecular pathways in COVID-19 myocarditis and constructing gene regulatory networks by bioinformatic analysis.

BACKGROUND: There is growing evidence of a strong relationship between COVID-19 and myocarditis. However, there are few bioinformatics-based analyses of critical genes and the mechanisms related to COVID-19 Myocarditis. This study aimed to identify critical genes related to COVID-19 Myocarditis by bioinformatic methods, explore the biological mechanisms and gene regulatory networks, and probe related drugs. METHODS: The gene expression data of GSE150392 and GSE167028 were obtained from the Gene Expression Omnibus (GEO), including cardiomyocytes derived from human induced pluripotent stem cells infected with SARS-CoV-2 in vitro and GSE150392 from patients with myocarditis infected with SARS-CoV-2 and the GSE167028 gene expression dataset. Differentially expressed genes (DEGs) (adjusted P-Value <0.01 and |Log2 Fold Change| ≥2) in GSE150392 were assessed by NetworkAnalyst 3.0. Meanwhile, significant modular genes in GSE167028 were identified by weighted gene correlation network analysis (WGCNA) and overlapped with DEGs to obtain common genes. Functional enrichment analyses were performed by using the "clusterProfiler" package in the R software, and protein-protein interaction (PPI) networks were constructed on the STRING website (https://cn.string-db.org/). Critical genes were identified by the CytoHubba plugin of Cytoscape by 5 algorithms. Transcription factor-gene (TF-gene) and Transcription factor-microRibonucleic acid (TF-miRNA) coregulatory networks construction were performed by NetworkAnalyst 3.0 and displayed in Cytoscape. Finally, Drug Signatures Database (DSigDB) was used to probe drugs associated with COVID-19 Myocarditis. RESULTS: Totally 850 DEGs (including 449 up-regulated and 401 down-regulated genes) and 159 significant genes in turquoise modules were identified from GSE150392 and GSE167028, respectively. Functional enrichment analysis indicated that common genes were mainly enriched in biological processes such as cell cycle and ubiquitin-protein hydrolysis. 6 genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) were identified as critical genes. TF-gene interactions and TF-miRNA coregulatory network were constructed successfully. A total of 10 drugs, (such as Etoposide, Methotrexate, Troglitazone, etc) were considered as target drugs for COVID-19 Myocarditis. CONCLUSIONS: Through bioinformatics method analysis, this study provides a new perspective to explore the pathogenesis, gene regulatory networks and provide drug compounds as a reference for COVID-19 Myocarditis. It is worth highlighting that critical genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) may be potential biomarkers and treatment targets of COVID-19 Myocarditis for future study.

Application of Cell-Free Protein Synthesis System for the Biosynthesis of l-Theanine.

l-Theanine, as an active component of the leaves of the tea plant, possesses many health benefits and broad applications. Chemical synthesis of l-theanine is possible; however, this method generates chiral compounds and needs further isolation of the pure l-isoform. Heterologous biosynthesis is an alternative strategy, but one main limitation is the toxicity of the substrate ethylamine on microbial host cells. In this study, we introduced a cell-free protein synthesis (CFPS) system for l-theanine production. The CFPS expressed l-theanine synthetase 2 from Camellia sinensis (CsTS2) could produce l-theanine at a concentration of 11.31 µM after 32 h of the synthesis reaction. In addition, three isozymes from microorganisms were expressed in CFPS for l-theanine biosynthesis. The γ-glutamylcysteine synthetase from Escherichia coli could produce l-theanine at the highest concentration of 302.96 µM after 24 h of reaction. Furthermore, CFPS was used to validate a hypothetical two-step l-theanine biosynthetic pathway consisting of the l-alanine decarboxylase from C. sinensis (CsAD) and multiple l-theanine synthases. Among them, the combination of CsAD and the l-glutamine synthetase from Pseudomonas taetrolens (PtGS) could synthesize l-theanine at the highest concentration of 13.42 µM. Then, we constructed an engineered E. coli strain overexpressed CsAD and PtGS to further confirm the l-theanine biosynthesis ability in living cells. This engineered E. coli strain could convert l-alanine and l-glutamate in the medium to l-theanine at a concentration of 3.82 mM after 72 h of fermentation. Taken together, these results demonstrated that the CFPS system can be used to produce the l-theanine through the two-step l-theanine biosynthesis pathway, indicating the potential application of CFPS for the biosynthesis of other active compounds.