The Nervous System Disease NcRNAome Atlas (NSDNA) (http://www.bio-bigdata.net/nsdna/) is a manually curated database that provides comprehensive experimentally supported associations about nervous system diseases (NSDs) and noncoding RNAs (ncRNAs). NSDs represent a common group of disorders, some of which are characterized by high morbidity and disabilities. The pathogenesis of NSDs at the molecular level remains poorly understood. ncRNAs are a large family of functionally important RNA molecules. Increasing evidence shows that diverse ncRNAs play a critical role in various NSDs. Mining and summarizing NSD–ncRNA association data can help researchers discover useful information. Hence, we developed an NSDNA database that documents 24 713 associations between 142 NSDs and 8593 ncRNAs in 11 species, curated from more than 1300 articles. This database provides a user-friendly interface for browsing and searching and allows for data downloading flexibility. In addition, NSDNA offers a submission page for researchers to submit novel NSD–ncRNA associations. It represents an extremely useful and valuable resource for researchers who seek to understand the functions and molecular mechanisms of ncRNA involved in NSDs.

Myasthenia gravis (MG) is a cell‐dependent autoimmune disease commonly associated with thymic pathology. Metastasis‐associated lung adenocarcinoma transcript 1 (MALAT‐1) has been associated with gene regulation and alternative splicing. It has shown relationship with proliferation, apoptosis, migration, and invasion. In this study, we found that MALAT‐1 expression was downregulated in MG. The level of the miR‐338‐3p was increased in peripheral blood mononuclear cells from MG patients compared with those from control subjects. MALAT‐1 competed for binding to miR‐338‐3p with male‐specific lethal 2 (MSL2) in luciferase reporter assays. We confirmed the MALAT‐1‐miR‐338‐3p‐MSL2 interaction network in MG in vitro. Thus, MALAT‐1 directly induced MSL2 expression in MG by acting as a competing endogenous RNA for miR‐338‐3p, suggesting that it may serve as a therapeutic target for MG treatment.

Myasthenia gravis (MG) is an autoimmune disorder resulting from antibodies against the proteins at the neuromuscular junction. Emerging evidence indicates that long non-coding RNAs (lncRNAs), acting as competing endogenous RNAs (ceRNAs), are involved in various diseases. However, the regulatory mechanisms of ceRNAs underlying MG remain largely unknown. In this study, we constructed a lncRNA-mediated ceRNA network involved in MG using a multi-step computational strategy. Functional annotation analysis suggests that these lncRNAs may play crucial roles in the immunological mechanism underlying MG. Importantly, through manual literature mining, we found that lncRNA SNHG16 (small nucleolar RNA host gene 16), acting as a ceRNA, plays important roles in the immune processes. Further experiments showed that SNHG16 expression was upregulated in peripheral blood mononuclear cells (PBMCs) from MG patients compared to healthy controls. Luciferase reporter assays confirmed that SNHG16 is a target of the microRNA (miRNA) let-7c-5p. Subsequent experiments indicated that SNHG16 regulates the expression of the key MG gene interleukin (IL)-10 by sponging let-7c-5p in a ceRNA manner. Furthermore, functional assays showed that SNHG16 inhibits Jurkat cell apoptosis and promotes cell proliferation by sponging let-7c-5p. Our study will contribute to a deeper understanding of the regulatory mechanism of MG and will potentially provide new therapeutic targets for MG patients.

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.

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