Impaired ATF3 signaling involves SNAP25 in SOD1 mutant ALS patients

Yazar, Volkan; Kühlwein, Julia K.; Knehr, Antje; Grozdanov, Veselin; Ekici, Arif B.; Ludolph, Albert C.; Danzer, Karin M

doi:10.1038/s41598-023-38684-8

Cited by 6 publications

(2 citation statements)

References 69 publications

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“…Altered expression of MAP1B [557], EGFR (epidermal growth factor receptor) [554], SREBF1 [769] and CREB1 [770] promotes Parkinson’s disease. MAP1B [637], EGFR (epidermal growth factor receptor) [636], NEDD4L [632], hsa-mir-21-5p [771], ATF3 [772] and SREBF1 [773] were significantly altered in patients with amyotrophic lateral sclerosis. A previous study reported that the EGFR (epidermal growth factor receptor) [658], hsa-mir-21-5p [762] and SREBF1 [774] biomarkers were associated with the dementia.…”

Section: Discussionmentioning

confidence: 99%

Identification of key genes and signaling pathway in the pathogenesis of Huntington's disease via bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2024

Preprint

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Huntington's disease (HD) is the primary cause of progressive motor deficits, psychiatric symptoms, and cognitive impairment. The exact molecular mechanisms of HD pathogenesis are largely unknown. This investigation aims to identify the hub genes, miRNA and TFs in HD and explore their potential molecular regulatory network. Next generation sequencing (NGS) dataset (GSE105041) was extracted from the Gene Expression Omnibus (GEO) database. An integrated bioinformatics pipeline including identification of differentially expressed genes (DEGs), Gene ontology and REACTOME pathway enrichment analysis, protein-protein interaction (PPI) network and module analysis, miRNA-hub gene regulatory network analysis and TF-hub gene regulatory network analysis, and receiver operating characteristic curve (ROC) analysis were applied to identify hub genes, miRNA and TFs, and key drivers of HD pathogenesis. We identified 958 DEGs in the discovery phase, consisting of 479 up regulated genes and 479 down regulated genes. GO and REACTOME enrichment analyses of the 479 up regulated genes and 479 down regulated genes showed that they were mainly involved in multicellular organismal process, developmental process, signaling by GPCR and MHC class II antigen presentation. Further analysis of the PPI network using Cytoscape and PEWCC plugins identified 10 hub genes, including LRRK2, MTUS2, HOXA1, IL7R, ERBB3, EGFR, TEX101, WDR76, NEDD4L and COMT. Possible target miRNAs and TFs, including hsa-mir-1292-5p, hsa-mir-4521, ESRRB and SREBF1, were predicted by constructing a miRNA-hub gene regulatory network analysis and TF-hub gene regulatory network. This investigation used bioinformatics methods to explore the molecular pathogenesis of HD, and identified potential molecular markers. These molecular markers might provide novel ideas and methods for the early diagnosis, treatment, and monitoring of HD.

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Section: Discussionmentioning

confidence: 99%

Identification of key genes and signaling pathway in the pathogenesis of Huntington's disease via bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2024

Preprint

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“…PNPLA3 [174], ACTN2 [175], MMP15 [176], SVEP1 [177], CPB2 [178], DYSF (dysferlin) [179], ADAMTSL2 [180], NINJ2 [181], LRP2 [106], PHLDA3 [182], LIPC (lipase C, hepatic type) [183], CARNS1 [184], PRODH (proline dehydrogenase 1) [185], TRPV6 [186], CNDP1 [187], DHCR7 [188], KCNE5 [189] SAA1 [190], ADSS1 [191], ACADS (acyl-CoA dehydrogenase short chain) [192], ADAP1 [193], KLK10 [194], HCN2 [195], F11 [196], RNASE1 [197], GNLY (granulysin) [198], EVA1A [199], CIRBP (cold inducible RNA binding protein) [200], EDIL3 [201], NOXA1 [202], ANGPTL2 [203], CYP2A6 [204] and CTNNA3 [205] might be associated with cardiovascular diseases progression. The abnormal expression of CCL18 [206], EOMES (eomesodermin) [207], GZMA (granzyme A) [208], HLA-DRB5 [209], GPNMB (glycoprotein nmb) [210], PRPH (peripherin) [211], HGF (hepatocyte growth factor) [212], TTR (transthyretin) [213], VEGFA (vascular endothelial growth factor A) [214], CHI3L1 [215], AATK (apoptosis associated tyrosine kinase) [216], SREBF1 [217], OLIG2 [218], ATF3 [219], NGFR (nerve growth factor receptor) [220], ADAMTS4 [221], LMNA (lamin A/C) [222], MT3 [223], DAO (D-amino acid oxidase) [224], AATK (apoptosis associated tyrosine kinase) [216] and LGALS3BP [225] might be related to the progression of amyotrophic lateral sclerosis. SLAMF7 [226], GPR174 [227], FCRL3 [228], SLAMF6 [229], EOMES (eomesodermin) [230], CCR4 [231], CCR2 [232], CD48 [233], CD3E [234], CCL26 [235], CCL4 [236], SLAMF1 [237], CD24 [238], IKZF3 [239], CD2 […”

Section: Discussionmentioning

confidence: 99%

Identification of candidate biomarkers and pathways associated with multiple sclerosis using bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2023

Preprint

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Multiple sclerosis (MS) is the main reason for disability caused by autoimmunity. However, effective biomarkers for MS have not been identified. This study explored the molecular mechanisms and potential therapeutic targets for MS occurrence and progression using bioinformatics and next generation sequencing (NGS) data analysis. NGS data GSE138614, including patients with MS and 25 normal control samples, were obtained from Gene Expression Omnibus (GEO) database Differentially expressed genes (DEGs) were filtered and subjected to gene ontology (GO) and pathway enrichment analyses. Protein–protein interaction (PPI) network and module analyses were performed based on the DEGs. MiRNA-hub gene regulatory network and TF-hub gene regulatory network analysis were built by Cytoscape to predict the underlying microRNAs (miRNAs) and transcription factors (TFs) associated with hub genes. We also validated the identified hub genes via receiver operating characteristic (ROC) curve analysis. A total of 959 DEGs (479 up regulated genes and 480 down regulated genes) were detected. The GO terms and pathways of DEGs involve immune system process, developmental process, immune system and regulation of cholesterol biosynthesis by SREBP (SREBF). The network analysis revealed that hub genes include LCK, PYHIN1, SLAMF1, DOK2, TAB2, CFTR, RHOB, LMNA, EGLN3 and ERBB3 might be involved in the development of MS. The present investigation illustrates a characteristic gene profile in MS, which might contribute to the interpretation of the progression of MS and provide novel biomarkers and therapeutic targets for MS.

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Clinical characterization of common pathogenic variants of SOD1-ALS in Germany

Wiesenfarth,

Forouhideh-Wiesenfarth,

Elmas

et al. 2024

J Neurol

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Pathogenic variants in the Cu/Zn superoxide dismutase (SOD1) gene can be detected in approximately 2% of sporadic and 11% of familial amyotrophic lateral sclerosis (ALS) patients in Europe. We analyzed the clinical phenotypes of 83 SOD1-ALS patients focusing on patients carrying the most frequent (likely) pathogenic variants (R116G, D91A, L145F) in Germany. Moreover, we describe the effect of tofersen treatment on ten patients carrying these variants. R116G patients showed the most aggressive course of disease with a median survival of 22.0 months compared to 198.0 months in D91A and 87.0 months in L145F patients (HR 7.71, 95% CI 2.89–20.58 vs. D91A; p < 0.001 and HR 4.25, 95% CI 1.55–11.67 vs. L145F; p = 0.02). Moreover, R116G patients had the fastest median ALSFRS-R progression rate with 0.12 (IQR 0.07–0.20) points lost per month. Median diagnostic delay was 10.0 months (IQR 5.5–11.5) and therefore shorter compared to 57.5 months (IQR 14.0–83.0) in D91A (p < 0.001) and 21.5 months (IQR 5.8–38.8) in L145F (p = 0.21) carriers. As opposed to D91A carriers (50.0%), 96.2% of R116G (p < 0.001) and 100.0% of L145F (p = 0.04) patients reported a positive family history. During tofersen treatment, all patients showed a reduction of neurofilament light chain (NfL) serum levels, independent of the SOD1 variant. Patients with SOD1-ALS carrying R116G, D91A, or L145F variants show commonalities, but also differences in their clinical phenotype, including a faster progression rate with shorter survival in R116G, and a comparatively benign disease course in D91A carriers.

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Impaired ATF3 signaling involves SNAP25 in SOD1 mutant ALS patients

Cited by 6 publications

References 69 publications

Identification of key genes and signaling pathway in the pathogenesis of Huntington's disease via bioinformatics and next generation sequencing data analysis

Identification of key genes and signaling pathway in the pathogenesis of Huntington's disease via bioinformatics and next generation sequencing data analysis

Identification of candidate biomarkers and pathways associated with multiple sclerosis using bioinformatics and next generation sequencing data analysis

Clinical characterization of common pathogenic variants of SOD1-ALS in Germany

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