Potential protein biomarkers for systemic lupus erythematosus determined by bioinformatics analysis

Kong, Jie; Li, Liuxia; Lu, Zhimin; Yan, Jiaxin; Ding, Jingzhong; Chen, Yanfeng; Wu, Yuanyuan; Chen, Xu; Shao, Hongbo; Wang, Jiehua; Da, Zhanyun

doi:10.1016/j.compbiolchem.2019.107135

Cited by 19 publications

(17 citation statements)

References 42 publications

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“…High levels of serum IFN together with overexpression of IFN-inducible genes have been found in individuals with SLE. The level of IFN correlated with the severity of the disease [ 12 ]. The role of type I IFN, paticularly IFN- α in the development and pathogenasis of SLE has been described [ 26 ].…”

Section: Discussionmentioning

confidence: 99%

“…Through these techniques, many new genes involved in complex human diseases such as cancer and autoimmune complications have also been discovered [ 6 , 7 ]. Several studies have identified disease-related genes and functional pathways by analyzing the expression profile between SLE and healthy controls [ 8 – 12 ]. However, in the majority of the studies, SLE patients have a history of exposure to anti-SLE drugs, a variable that can cause considerable transcriptional changes [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

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IFN-γ Mediates the Development of Systemic Lupus Erythematosus

Liu

Wang

et al. 2020

BioMed Research International

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Objective. Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that can affect all organs in the body. It is characterized by overexpression of antibodies against autoantigen. Although previous bioinformatics analyses have identified several genetic factors underlying SLE, they did not discriminate between naive and individuals exposed to anti-SLE drugs. Here, we evaluated specific genes and pathways in active and recently diagnosed SLE population. Methods. GSE46907 matrix downloaded from Gene Expression Omnibus (GEO) was analyzed using R, Metascape, STRING, and Cytoscape to identify differentially expressed genes (DEGs), enrichment pathways, protein-protein interaction (PPI), and hub genes between naive SLE individuals and healthy controls. Results. A total of 134 DEGs were identified, in which 29 were downregulated, whereas 105 were upregulated in active and newly diagnosed SLE cases. GO term analysis revealed that transcriptional induction of the DEGs was particularly enhanced in response to secretion of interferon-γ and interferon-α and regulation of cytokine production innate immune responses among others. KEGG pathway analysis showed that the expression of DEGs was particularly enhanced in interferon signaling, IFN antiviral responses by activated genes, class I major histocompatibility complex (MHC-I) mediated antigen processing and presentation, and amyloid fiber formation. STAT1, IRF7, MX1, OASL, ISG15, IFIT3, IFIH1, IFIT1, OAS2, and GBP1 were the top 10 DEGs. Conclusions. Our findings suggest that interferon-related gene expression and pathways are common features for SLE pathogenesis, and IFN-γ and IFN-γ-inducible GBP1 gene in naive SLE were emphasized. Together, the identified genes and cellular pathways have expanded our understanding on the mechanism underlying development of SLE. They have also opened a new frontier on potential biomarkers for diagnosis, biotherapy, and prognosis for SLE.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

IFN-γ Mediates the Development of Systemic Lupus Erythematosus

Liu

Wang

et al. 2020

BioMed Research International

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“…PPI networks are used to establish all protein coding genes into a massive biological network that serves an advance compassionate of the functional system of the proteome [ 25 ]. The HiPPIE interactome ( https://cbdm.uni-mainz.de/hippie/ ) [ 26 ] database furnish information regarding predicted and experimental interactions of proteins.…”

Section: Methodsmentioning

confidence: 99%

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Kolur¹,

Vastrad²,

Vastrad

et al. 2021

BMC Cardiovasc Disord

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Introduction Heart failure (HF) is a heterogeneous clinical syndrome and affects millions of people all over the world. HF occurs when the cardiac overload and injury, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental HF as well as to explore active drug molecules. Methods The expression profiling by high throughput sequencing of GSE141910 dataset was downloaded from the Gene Expression Omnibus (GEO) database, which contained 366 samples, including 200 heart failure samples and 166 non heart failure samples. The raw data was integrated to find differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. Gene ontology (GO) and REACTOME enrichment analyses were performed via ToppGene; protein–protein interaction (PPI) networks of the DEGs was constructed based on data from the HiPPIE interactome database; modules analysis was performed; target gene—miRNA regulatory network and target gene—TF regulatory network were constructed and analyzed; hub genes were validated; molecular docking studies was performed. Results A total of 881 DEGs, including 442 up regulated genes and 439 down regulated genes were observed. Most of the DEGs were significantly enriched in biological adhesion, extracellular matrix, signaling receptor binding, secretion, intrinsic component of plasma membrane, signaling receptor activity, extracellular matrix organization and neutrophil degranulation. The top hub genes ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 were identified from the PPI network. Module analysis revealed that HF was associated with adaptive immune system and neutrophil degranulation. The target genes, miRNAs and TFs were identified from the target gene—miRNA regulatory network and target gene—TF regulatory network. Furthermore, receiver operating characteristic (ROC) curve analysis and RT-PCR analysis revealed that ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 might serve as prognostic, diagnostic biomarkers and therapeutic target for HF. The predicted targets of these active molecules were then confirmed. Conclusion The current investigation identified a series of key genes and pathways that might be involved in the progression of HF, providing a new understanding of the underlying molecular mechanisms of HF.

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“…Hub genes in this module included IFI44L and ZIP10. IFI44L is reported to be associated with virus infection and immune activity, as well as the formation of microtubular structures [69][70][71]. This gene has not been verified to be closely related to early embryonic development; however, the PPI network predicts that IFI44L plays an essential role in this module, illustrating that IFI44L may be related to early immune response and the survival of embryos, and thus, contributes to the early development mechanisms.…”

Section: Grey Modulementioning

confidence: 98%

Deep Transcriptomic Analysis Reveals the Dynamic Developmental Progression during Early Development of Channel Catfish (Ictalurus punctatus)

Tian

et al. 2020

IJMS

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The transition from fertilized egg to larva in fish is accompanied with various biological processes. We selected seven early developmental stages in channel catfish, Ictalurus punctatus, for transcriptome analysis, and covered 22,635 genes with 590 million high-quality RNA-sequencing (seq) reads. Differential expression analysis between neighboring developmental timepoints revealed significantly enriched biological categories associated with growth, development and morphogenesis, which was most evident at 2 vs. 5 days post fertilization (dpf) and 5 vs. 6 dpf. A gene co-expression network was constructed using the Weighted Gene Co-expression Network Analysis (WGCNA) approach and four critical modules were identified. Among candidate hub genes, GDF10, FOXA2, HCEA and SYCE3 were involved in head formation, egg development and the transverse central element of synaptonemal complexes. CK1, OAZ2, DARS1 and UBE2V2 were mainly associated with regulation of cell cycle, growth, brain development, differentiation and proliferation of enterocytes. IFI44L and ZIP10 were critical for the regulation of immune activity and ion transport. Additionally, TCK1 and TGFB1 were related to phosphate transport and regulating cell proliferation. All these genes play vital roles in embryogenesis and regulation of early development. These results serve as a rich dataset for functional genomic studies. Our work reveals new insights of the underlying mechanisms in channel catfish early development.

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Potential protein biomarkers for systemic lupus erythematosus determined by bioinformatics analysis

Cited by 19 publications

References 42 publications

IFN-γ Mediates the Development of Systemic Lupus Erythematosus

IFN-γ Mediates the Development of Systemic Lupus Erythematosus

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Deep Transcriptomic Analysis Reveals the Dynamic Developmental Progression during Early Development of Channel Catfish (Ictalurus punctatus)

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