SynthesisScientific reports2022
Transcriptomics and network analysis highlight potential pathways in the pathogenesis of pterygium.
Synthesis in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 14 citations in OpenAlex.
- Genome-Wide Association Study of Pterygium Versus Pinguecula Identifies Loci Associated with Lesion-Type Divergence.Ophthalmology science · 2026Article
- Exploring the Role of tRNA-Derived Fragments in Pterygium: Molecular Insights into tsRNA-Mediated Fibroblast Regulation and Disease Progression.Current medicinal chemistry · 2026Article
- Insight into the shared pathogenic link between COVID-19 and pterygium: a systematic bioinformatics analysis with experimental validation.Hereditas · 2025Article
- Investigating immune cell infiltration and gene expression features in pterygium pathogenesis.Scientific reports · 2025Article
- RIPK3 and RIPK1 gene expression in pterygium: unveiling molecular insights into pathogenesis.Molecular biology reports · 2024Article
- Identification of biomarkers and immune microenvironment associated with pterygium through bioinformatics and machine learning.Frontiers in molecular biosciences · 2024Article
- Synergic Action of Insulin-like Growth Factor-2 and miRNA-483 in Pterygium Pathogenesis.International journal of molecular sciences · 2023Article
- Resveratrol inhibits TGF-β1-induced fibrotic effects in human pterygium fibroblasts.Environmental health and preventive medicine · 2023Article
- Expression profiling suggests the involvement of hormone-related, metabolic, and Wnt signaling pathways in pterygium progression.Frontiers in endocrinology · 2022Article
- Exploring the Genetic Role of Matrix Metalloproteinase-13 Variants in Pterygium Risk.In vivo (Athens, Greece)Article
- Unravelling the Contribution of Matrix Metalloproteinase-3 Genotype-Phenotype to Pterygium Risk.Cancer genomics & proteomicsArticle
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
Abstract
Pterygium is a common ocular surface condition frequently associated with irritative symptoms. The precise identity of its critical triggers as well as the hierarchical relationship between all the elements involved in the pathogenesis of this disease are not yet elucidated. Meta-analysis of gene expression studies represents a novel strategy capable of identifying key pathogenic mediators and therapeutic targets in complex diseases. Samples from nine patients were collected during surgery after photo documentation and clinical characterization of pterygia. Gene expression experiments were performed using Human Clariom D Assay gene chip. Differential gene expression analysis between active and atrophic pterygia was performed using limma package after adjusting variables by age. In addition, a meta-analysis was performed including recent gene expression studies available at the Gene Expression Omnibus public repository. Two databases including samples from adults with pterygium and controls fulfilled our inclusion criteria. Meta-analysis was performed using the Rank Production algorithm of the RankProd package. Gene set analysis was performed using ClueGO and the transcription factor regulatory network prediction was performed using appropriate bioinformatics tools. Finally, miRNA-mRNA regulatory network was reconstructed using up-regulated genes identified in the gene set analysis from the meta-analysis and their interacting miRNAs from the Brazilian cohort expression data. The meta-analysis identified 154 up-regulated and 58 down-regulated genes. A gene set analysis with the top up-regulated genes evidenced an overrepresentation of pathways associated with remodeling of extracellular matrix. Other pathways represented in the network included formation of cornified envelopes and unsaturated fatty acid metabolic processes. The miRNA-mRNA target prediction network, also reconstructed based on the set of up-regulated genes presented in the gene ontology and biological pathways network, showed that 17 target genes were negatively correlated with their interacting miRNAs from the Brazilian cohort expression data. Once again, the main identified cluster involved extracellular matrix remodeling mechanisms, while the second cluster involved formation of cornified envelope, establishment of skin barrier and unsaturated fatty acid metabolic process. Differential expression comparing active pterygium with atrophic pterygium using data generated from the Brazilian cohort identified differentially expressed genes between the two forms of presentation of this condition. Our results reveal differentially expressed genes not only in pterygium, but also in active pterygium when compared to the atrophic ones. New insights in relation to pterygium's pathophysiology are suggested.
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.