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Construction of a TF-miRNA-gene feed-forward loop network predicts biomarkers and potential drugs for myasthenia gravis.

ABSTRACT: Myasthenia gravis (MG) is an autoimmune disease and the most common type of neuromuscular disease. Genes and miRNAs associated with MG have been widely studied; however, the molecular mechanisms of transcription factors (TFs) and the relationship among them remain unclear. A TF-miRNA-gene network (TMGN) of MG was constructed by extracting six regulatory pairs (TF-miRNA, miRNA-gene, TF-gene, miRNA-TF, gene-gene and miRNA-miRNA). Then, 3/4/5-node regulatory motifs were detected in the TMGN. Then, the motifs with the highest Z-score, occurring as 3/4/5-node composite feed-forward loops (FFLs), were selected as statistically significant motifs. By merging these motifs together, we constructed a 3/4/5-node composite FFL motif-specific subnetwork (CFMSN). Then, pathway and GO enrichment analyses were performed to further elucidate the mechanism of MG. In addition, the genes, TFs and miRNAs in the CFMSN were also utilized to identify potential drugs. Five related genes, 3 TFs and 13 miRNAs, were extracted from the CFMSN. As the most important TF in the CFMSN, MYC was inferred to play a critical role in MG. Pathway enrichment analysis showed that the genes and miRNAs in the CFMSN were mainly enriched in pathways related to cancer and infections. Furthermore, 21 drugs were identified through the CFMSN, of which estradiol, estramustine, raloxifene and tamoxifen have the potential to be novel drugs to treat MG. The present study provides MG-related TFs by constructing the CFMSN for further experimental studies and provides a novel perspective for new biomarkers and potential drugs for MG.

SUBMITTER: Bo C

PROVIDER: S-EPMC7843995 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Construction of a TF-miRNA-gene feed-forward loop network predicts biomarkers and potential drugs for myasthenia gravis.

Bo Chunrui C Zhang Huixue H Cao Yuze Y Lu Xiaoyu X Zhang Cong C Li Shuang S Kong Xiaotong X Zhang Xiaoming X Bai Ming M Tian Kuo K Saitgareeva Aigul A Lyaysan Gaysina G Wang Jianjian J Ning Shangwei S Wang Lihua L

Scientific reports 20210128 1

Myasthenia gravis (MG) is an autoimmune disease and the most common type of neuromuscular disease. Genes and miRNAs associated with MG have been widely studied; however, the molecular mechanisms of transcription factors (TFs) and the relationship among them remain unclear. A TF-miRNA-gene network (TMGN) of MG was constructed by extracting six regulatory pairs (TF-miRNA, miRNA-gene, TF-gene, miRNA-TF, gene-gene and miRNA-miRNA). Then, 3/4/5-node regulatory motifs were detected in the TMGN. Then, ...[more]

PMID: 33510225

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Project description:Myasthenia gravis (MG) is an autoimmune disease affecting the neuromuscular junction, whose clinical hallmark is muscle weakness and early fatigability. Azathioprine (AZA) is commonly used in Myasthenia Gravis therapy. AZA is a purine antagonist, which inhibits the cell cycle in the resting and DNA synthesis phases. It is usually used as an immunosuppressant to block T- and B-cell proliferation. AZA, bioconverted to 6-mercaptopurine by glutathione S-transferase (GST), can be metabolized either through the hypoxanthine phosphoribosyl transferase pathway to active 6-thioguanine nucleotides (6-TGN) or through the thiopurine S-methyltransferase (TPMT) pathway to inactive methyl-thiopurine metabolites. The incorporation of active 6-TGNs into DNA, causing breaks in DNA strands resulting in interference with RNA production and thereby protein synthesis, is responsible for the drug effect. The response to AZA is determined by which metabolic pathway is being favored. While balanced use of both HPRT and TPMT pathways results in responsiveness to AZA, hyperactivity of TPMT skews the balance towards the TPMT pathway and results in unresponsiveness to AZA with no pharmacological effect. In contrast, low TPMT activity skews the balance towards the HPRT pathway, resulting in increasing side-effects due to the accumulation of 6-TGNs. Current treatments for MG therapy are often inadequate because less than 40% of patients achieve complete remission with available drugs. This reflects the lack of drugs acting on target sites for which there is strong evidence of pathogenicity and the inability to identify responder patients. No criteria for responsiveness are available, exposing patients to unpredictable failures and unpredictable side effects. These individuals are at particular risk for adverse drug reaction (ADRs) or therapeutic failure. Genetic profiling with the Affymetrix drug metabolizing enzymes and transports genotyping array offers the ability to determine 1,931 variants and 225 genes involved in drug metabolism and disposition. Accordingly, the study of well-known drug-metabolizing genes can be involved in the specific metabolic pathway of a drug, which is more likely to define genotype-phenotype association and thereby genotype profiles relevant to drug response that can be applied as predictive biomarkers for pharmacological treatment.

Project description:Ischemic stroke (IS) accounts for the leading cause of disability and mortality in China. Increasing researchers are studying the effects of neuroprotective agents on IS. However, the molecular mechanisms of feed-forward loops (FFLs) associated with neuroprotection in the pathogenesis of IS need to be further studied. A protein-protein interaction (PPI) network of IS immune genes was constructed to decipher the characters and excavate 3 hub genes (PI3K, IL6, and TNF) of immunity. Then, we identified two hub clusters of IS immune genes, and the cytokine-cytokine receptor interaction pathway was discovered on the pathway enrichment results of both clusters. Combined with GO enrichment analysis, the cytokines participate in the inflammatory response in the extracellular space of IS patients. Next, a transcription factor (TF)-miRNA-immune gene network (TMIGN) was established by extracting four regulatory pairs (TF-miRNA, TF-gene, miRNA-gene, and miRNA-TF). Then, we detected 3-node regulatory motif types in the TMIGN network. According to the criteria we set for defining 3-node motifs, the motif with the highest Z-score (3-node composite FFL) was picked as the statistically evident motif, which was merged to construct an immune-associated composite FFL motif-specific sub-network (IA-CFMSN), which contained 21 3-node FFLs composed of 13 miRNAs, 4 TFs, 9 immune genes, and 1 TF& immune gene, among which TP53 and VEGFA were prominent TF and immune gene, respectively. In addition, the immune genes in IA-CFMSN were used for identifying associated pathways and drugs to further clarify the immune regulation mechanism and neuroprotection after IS. As a result, 5 immune genes targeted by 20 drugs were identified and the Angiotensin II Receptor Blockers (ARBs) target AGTR1 was found to be a neuroprotective drug for IS. In the present study, the construction of IA-CFMSN provides IS immune-associated FFLs for further experimental studies, providing new prospects for the discovery of new biomarkers and potential drugs for IS.

Dataset Information

Construction of a TF-miRNA-gene feed-forward loop network predicts biomarkers and potential drugs for myasthenia gravis.

Publications

Construction of a TF-miRNA-gene feed-forward loop network predicts biomarkers and potential drugs for myasthenia gravis.

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