ArticleBMC medical genomics2019
Analysis of gene expression profiles and protein-protein interaction networks in multiple tissues of systemic sclerosis.
Article in BMC medical genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 62 citations in OpenAlex.
- Drought-responsive genes in tomato: meta-analysis of gene expression using machine learning.Scientific reports · 2023Pooled it
- System level identification and multidimensional analysis of hub genes reveal complex regulatory networks underlying human iPSC differentiation into motor neurons.Biochemistry and biophysics reports · 2026Article
- Data-Driven Discovery of a Key Regulator Cyclin A2 as a Promising Therapeutic Target in Hormone-Sensitive Cancers.Molecular biotechnology · 2026Article
- Integrative cross-platform transcriptomic analysis coupled with machine learning identifies candidate biomarkers of abiotic stress resilience in Arabidopsis thaliana.BMC plant biology · 2026Article
- Machine learning, whole-transcriptome and integrative omics analysis reveals key regulatory networks governing human spermatogonial stem cells.Clinical and experimental medicine · 2026Article
- Decoding Multi-Omics Signatures in Lower-Grade Glioma Using Protein-Protein Interaction-Informed Graph Attention Networks and Ensemble Learning.Diagnostics (Basel, Switzerland) · 2025Article
- Unraveling the role of MAG, PTEN, and NOTCH1 in axonal regeneration: a network analysis and molecular dynamics study of siRNA/drugs/nanocarriers interactions.Journal of translational medicine · 2025Article
- Bioinformatics deciphers the thebaine biosynthesis pathway in opium poppy: Hub genes, network analysis, and miRNA regulation.Journal, genetic engineering & biotechnology · 2024Article
- Collagen-Heparin-FGF2-VEGF Scaffolds Induce a Regenerative Gene Expression Profile in a Fetal Sheep Wound Model.Tissue engineering and regenerative medicine · 2024Article
- Fibroblast-Specific Protein-Protein Interactions for Myocardial Fibrosis from MetaCore Network.Biomolecules · 2024Article
- Integrated ML-Based Strategy Identifies Drug Repurposing for Idiopathic Pulmonary Fibrosis.ACS omega · 2024Article
- CAP-RNAseq: an integrated pipeline for functional annotation and prioritization of co-expression clusters.Briefings in bioinformatics · 2024Article
- CCR8 as a Therapeutic Novel Target: Omics-Integrated Comprehensive Analysis for Systematically Prioritizing Indications.Biomedicines · 2023Article
- Multi-omics analysis reveals genes and metabolites involved inFrontiers in microbiology · 2023Article
- Electroacupuncture alleviates perioperative hypothalamus-pituitary-adrenal axis dysfunctionFrontiers in molecular neuroscience · 2023Article
- Alterations of the Primary Cilia Gene SPAG17 and SOX9 Locus Noncoding RNAs Identified by RNA-Sequencing Analysis in Patients With Systemic Sclerosis.Arthritis & rheumatology (Hoboken, N.J.) · 2023Article
- Transcriptional Changes in Bifidobacterium bifidum Involved in Synergistic Multispecies Biofilms.Microbial ecology · 2022Article
- Integrated Transcriptome Profiling Identifies Prognostic Hub Genes as Therapeutic Targets of Glioblastoma: Evidenced by Bioinformatics Analysis.ACS omega · 2022Article
- Integrated analysis of lncRNAs and mRNAs by RNA-Seq in secondary hair follicle development and cycling (anagen, catagen and telogen) of Jiangnan cashmere goat (Capra hircus).BMC veterinary research · 2022Article
- Presentation of potential genes and deleterious variants associated with non-syndromic hearing loss: a computational approach.Genomics & informatics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSystemic sclerosis (SSc), a multi-organ disorder, is characterized by vascular abnormalities, dysregulation of the immune system, and fibrosis. The mechanisms underlying tissue pathology in SSc have not been entirely understood. This study intended to investigate the common and tissue-specific pathways involved in different tissues of SSc patients.
methodsAn integrative gene expression analysis of ten independent microarray datasets of three tissues was conducted to identify differentially expressed genes (DEGs). DEGs were mapped to the search tool for retrieval of interacting genes (STRING) to acquire protein-protein interaction (PPI) networks. Then, functional clusters in PPI networks were determined. Enrichr, a gene list enrichment analysis tool, was utilized for the functional enrichment of clusters.
resultsA total of 12, 2, and 4 functional clusters from 619, 52, and 119 DEGs were determined in the lung, peripheral blood mononuclear cell (PBMC), and skin tissues, respectively. Analysis revealed that the tumor necrosis factor (TNF) signaling pathway was enriched significantly in the three investigated tissues as a common pathway. In addition, clusters associated with inflammation and immunity were common in the three investigated tissues. However, clusters related to the fibrosis process were common in lung and skin tissues.
conclusionsAnalysis indicated that there were common pathological clusters that contributed to the pathogenesis of SSc in different tissues. Moreover, it seems that the common pathways in distinct tissues stem from a diverse set of genes.
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.