ArticleComputational and mathematical methods in medicine2022
Identification of Characteristic Genes in Whole Blood of Intervertebral Disc Degeneration Patients by Weighted Gene Coexpression Network Analysis (WGCNA).
Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Identification and Experimental Verification of Potential Immune Cell-Associated Gene Biomarkers in Human Intervertebral Disc Degeneration.Journal of pain research · 2025Article
- SERINC2-mediated serine metabolism promotes cervical cancer progression and drives T cell exhaustion.International journal of biological sciences · 2025Article
- Unveiling immune mechanisms and potential biomarkers in intervertebral disc degeneration through integrated analysis.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2025Article
- Bioinformatics Analysis and Identification of Ferroptosis-Related Hub Genes in Intervertebral Disc Degeneration.Biochemical genetics · 2024Article
- SSR1 and CKAP4 as potential biomarkers for intervertebral disc degeneration based on integrated bioinformatics analysis.JOR spine · 2024Article
- Identification and validation of ferroptosis-related biomarkers in intervertebral disc degeneration.Frontiers in cell and developmental biology · 2024Article
- Diagnostic model based on key autophagy-related genes in intervertebral disc degeneration.BMC musculoskeletal disorders · 2023Article
- The CEBPA-FGF21 regulatory network may participate in the T2DM-induced skeletal muscle atrophy by regulating the autophagy-lysosomal pathway.Acta diabetologica · 2023Article
- lncRNA UCA1 inhibits mitochondrial dysfunction of skeletal muscle in type 2 diabetes mellitus by sequestering miR-143-3p to release FGF21.Cell and tissue research · 2023Article
- Identification and Verification of Key MiRNAs Associated with Intervertebral Disc Degeneration.Combinatorial chemistry & high throughput screening · 2023Article
- Retracted: Identification of Characteristic Genes in Whole Blood of Intervertebral Disc Degeneration Patients by Weighted Gene Coexpression Network Analysis (WGCNA).Computational and mathematical methods in medicine · 2023Article
- Identification of a potential novel biomarker in intervertebral disk degeneration by bioinformatics analysis and experimental validation.Frontiers in immunology · 2023Article
- Whole-transcriptome sequencing identifies key differentially expressed circRNAs/lncRNAs/miRNAs/mRNAs and linked ceRNA networks in adult degenerative scoliosis.Frontiers in molecular neuroscience · 2023Article
- Identifification and validation of ferroptosis signatures and immune infifiltration characteristics associated with intervertebral disc degeneration.Frontiers in genetics · 2023Article
- Analysis of potential genetic biomarkers using machine learning methods and immune infiltration regulatory mechanisms underlying atrial fibrillation.BMC medical genomics · 2022Article
- Key LncRNAs Associated With Oxidative Stress Were Identified by GEO Database Data and Whole Blood Analysis of Intervertebral Disc Degeneration Patients.Frontiers in genetics · 2022Article
- Identification of SMIM1 and SEZ6L2 as Potential Biomarkers for Genes Associated with Intervertebral Disc Degeneration in Pyroptosis.Disease markers · 2022Article
Corrections and comments
- Retraction · 2023-11-01Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Intervertebral disc degeneration (IDD) is a major cause of lower back pain. However, to date, the molecular mechanism of the IDD remains unclear. Gene expression profiles and clinical traits were downloaded from the Gene Expression Omnibus (GEO) database. Firstly, weighted gene coexpression network analysis (WGCNA) was used to screen IDD-related genes. Moreover, least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine (SVM) algorithms were used to identify characteristic genes. Furthermore, we further investigated the immune landscape by the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm and the correlations between key characteristic genes and infiltrating immune cells. Finally, a competing endogenous RNA (ceRNA) network was established to show the regulatory mechanisms of characteristic genes. A total of 2458 genes were identified by WGCNA, and 48 of them were disordered. After overlapping the genes obtained by LASSO and SVM-RFE algorithms, genes including LINC01347, ASAP1-IT1, lnc-SEPT7L-1, B3GNT8, CHRNB3, CLEC4F, LOC102724000, SERINC2, and LOC102723649 were identified as characteristic genes of IDD. Moreover, differential analysis further identified ASAP1-IT1 and SERINC2 as key characteristic genes. Furthermore, we found that the expression of both ASAP1-IT1 and SERINC2 was related to the proportions of T cells gamma delta and Neutrophils. Finally, a ceRNA network was established to show the regulatory mechanisms of ASAP1-IT1 and SERINC2. In conclusion, the present study identified ASAP1-IT1 and SERINC2 as the key characteristic genes of IDD through integrative bioinformatic analyses, which may contribute to the diagnosis and treatment of IDD.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.