Microarray analysis reveals an inflammatory transcriptomic signature in peripheral blood for sciatica

Wang, Yi; Dai, Guogang; Jiang, Ling; Liao, Shichuan; Xia, Jiao

doi:10.1186/s12883-021-02078-y

Cited by 24 publications

(20 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The training cohort GSE150408 containing 17 healthy controls and 42 sciatica patients was acquired from the Gene Expression Omnibus (GEO) database ( http://www.ncbi.nlm.nih.gov/geo ) ( Wang et al, 2021a ). Immune-related genes (IRGs) were downloaded from the ImmPort database ( https://immport.niaid.nih.gov ) ( Huang et al, 2020 ).…”

Section: Methodsmentioning

confidence: 99%

“…The sciatic nerve is generally visualized using magnetic resonance imaging (MRI) ( Ailianou et al, 2012 ). Spinal sciatica is mainly caused by single-level lumbar disc herniation at the L4/5 or L5/S1 level ( Wang et al, 2021a ). Current treatment methods for sciatica mainly include conservative treatment, exercise, manual therapy, and surgery ( Jensen et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

“…Individuals with sciatica present inflammatory and immune characteristics that may be detected in peripheral blood ( Wang et al, 2021a ). In our study, we screened for differentially expressed immune-related genes (DEIRGs) between healthy controls and sciatica patients using the “limma” package and verified our results in clinical specimens by RT-qPCR analysis.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Identification of Immune-Related Biomarkers for Sciatica in Peripheral Blood

et al. 2021

View full text Add to dashboard Cite

Objective: Sciatica pertains to neuropathic pain that has been associated with inflammatory response. We aimed to identify significant immune-related biomarkers for sciatica in peripheral blood.Methods: We utilized the GSE150408 expression profiling data from the Gene Expression Omnibus (GEO) database as the training dataset and extracted immune-related genes for further analysis. Differentially expressed immune-related genes (DEIRGs) between healthy controls and patients with sciatica were selected using the “limma” package and verified in clinical specimens by quantitative reverse transcription PCR (RT-qPCR). A diagnostic immune-related gene signature was established using the training model and random forest (RF), generalized linear model (GLM), and support vector machine (SVM) models. Sciatica patient subtypes were identified using the consensus clustering method.Results: Thirteen significant DEIRGs were acquired, of which five (CRP, EREG, FAM19A4, RLN1, and WFIKKN1) were selected to establish a diagnostic immune-related gene signature according to the most appropriate training model, namely, the RF model. A clinical application nomogram model was established based on the expression level of the five DEIRGs. The sciatica patients were divided into two subtypes (C1 and C2) according to the consensus clustering method.Conclusions: Our research established a diagnostic five immune-related gene signature to discriminate sciatica and identified two sciatica subtypes, which may be beneficial to the clinical diagnosis and treatment of sciatica.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of Immune-Related Biomarkers for Sciatica in Peripheral Blood

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In short, the predictive model was constructed with reference to previous studies (49)(50)(51)(52)(53). With CHRM1, NR3C1, ADRB2, and OPRD1 as dependent variables and the presence or absence of IS as the dependent variable, the "pacman" package of R software was used to build random forest (RF) and support vector machine (SVM) models.…”

Section: Building Predictive Modelsmentioning

confidence: 99%

Eucommia ulmoides Oliver-Tribulus terrestris L. Drug Pair Regulates Ferroptosis by Mediating the Neurovascular-Related Ligand-Receptor Interaction Pathway- A Potential Drug Pair for Treatment Hypertension and Prevention Ischemic Stroke

Zhang

Yang

et al. 2022

Front. Neurol.

View full text Add to dashboard Cite

BackgroundIn this study, we used the network pharmacology approach to explore the potential disease targets of the Eucommia ulmoides Oliver (EUO)-Tribulus terrestris L. (TT) drug pair in the treatment of hypertension-associated neurovascular lesions and IS via the ferroptosis pathway.MethodsWe used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform to search for the key active compounds and targets of the drug pair. Based on the GeneCards database, the relevant targets for the drug pair were obtained. Then, we performed the molecular docking of the screened core active ingredients and proteins using the DAVID database and the R AutoDock Vina software. Based on the GSE22255 dataset, these screened target proteins were used to build random forest (RF) and support vector machine (SVM) models. Finally, a new IS nomogram prediction model was constructed and evaluated.ResultsThere were 36 active compounds in the EUO-TT drug pair. CHRM1, NR3C1, ADRB2, and OPRD1 proteins of the neuroactive ligand-receptor interaction pathway interacted with the proteins related to the ferroptosis pathway. Molecular docking experiments identified 12 active ingredients of the drug pair that may tightly bind to those target proteins. We constructed a visual IS nomogram prediction model using four genes (CHRM1, NR3C1, ADRB2, and OPRD1). The calibration curve, DCA, and clinical impact curves all indicated that the nomogram model is clinically applicable and diagnostically capable. CHRM1, NR3C1, ADRB2, and OPRD1, the target genes of the four effective components of the EUO-TT drug pair, were considered as risk markers for IS.ConclusionsThe active ingredients of EUO-TT drug pair may act on proteins associated with the neuroactive ligand-receptor interaction pathway to regulate ferroptosis in vascular neurons cells, ultimately affecting the onset and progression of hypertension.

show abstract

“…In addition, GSE124272 [ 15 ] with 8 IDD samples and 8 control samples were used as validation dataset (the platform was Agilent-072363 SurePrint G3 Human GE v3 8x60K Microarray 039494). The GSE150408 [ 16 ] dataset from the Agilent-072363 SurePrint G3 Human GE v3 8x60K Microarray 039494 platform was also incorporated as an additional external validation set. The expression profile data of 17 IDD samples and 17 control samples were extracted.…”

Section: Rna Expression Profilementioning

confidence: 99%

Systematic analysis of Long non-coding RNAs reveals diagnostic biomarkers and potential therapeutic drugs for intervertebral disc degeneration

Zhan

Wang

et al. 2021

Bioengineered

View full text Add to dashboard Cite

Long non-coding RNAs (lncRNAs) are related to a variety of human diseases. However, little is known about the role of lncRNA in intervertebral disc degeneration (IDD). LncRNA expression profile of human IDD were downloaded from Gene Expression Omnibus (GEO) database. Potential biomarkers and therapeutic drugs for IDD were analyzed by weighted gene co-expression network analysis (WGCNA), R software package Limma, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We identified 1455 differentially expressed genes and 423 differentially expressed lncRNAs. Twenty-six co-expression modules were obtained, among them, the tan, brown, and turquoise modules were most closely related to IDD. The turquoise module contained a large number of differential expressed lncRNAs and genes, these genes were mainly enriched in the MAPK signaling pathway, TGF-beta signaling pathway. Furthermore, we obtained 11,857 LmiRM-Degenerated, these lncRNAs and genes showed higher differential expression multiples and higher expression correlation. After constructing a disease-gene interaction network, 25 disease-specific genes and 9 disease-specific lncRNAs were identified. Combined with the drug-target gene interaction network, three drugs, namely, Calcium citrate, Calcium Phosphate, and Calcium phosphate dihydrate, which may have curative effects on IDD, were determined. Finally, a genetic diagnosis model and lncRNA diagnosis model with 100% diagnostic performance in both the training data set and the validation data set were established based on these genes and lncRNA. This study provided new diagnostic features for IDD and could help design personalized treatment of IDD.

show abstract

Microarray analysis reveals an inflammatory transcriptomic signature in peripheral blood for sciatica

Cited by 24 publications

References 42 publications

Identification of Immune-Related Biomarkers for Sciatica in Peripheral Blood

Identification of Immune-Related Biomarkers for Sciatica in Peripheral Blood

Eucommia ulmoides Oliver-Tribulus terrestris L. Drug Pair Regulates Ferroptosis by Mediating the Neurovascular-Related Ligand-Receptor Interaction Pathway- A Potential Drug Pair for Treatment Hypertension and Prevention Ischemic Stroke

Systematic analysis of Long non-coding RNAs reveals diagnostic biomarkers and potential therapeutic drugs for intervertebral disc degeneration

Contact Info

Product

Resources

About