ArticleJournal of molecular histology2026
Integrative analysis of single-cell and bulk RNA sequencing data using machine learning identifies PTGDS as a key subsynovial fibroblast gene in osteoarthritis.
Article in Journal of molecular histology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Synovial lesions significantly contribute to osteoarthritis (OA) pathogenesis; nonetheless, the specific roles played by synovial cells in OA progression remain inadequately understood. The current study combined single-cell RNA sequencing (scRNA-seq) data with bulk RNA sequencing to investigate the functional involvement of subsynovial fibroblasts (SSF) within the synovial microenvironment of OA. An ensemble machine learning (ML) approach consisting of 113 algorithmic combinations identified four key genes associated with SSF. Pathway analysis indicated that SSF exhibited increased angiogenesis-related pathways and decreased inflammatory response pathways. Consensus clustering classified OA patients into two molecular subtypes (C1 and C2). Immune infiltration analysis identified PTGDS and SCG2 as immune-associated genes differentiating these subgroups. Mendelian randomization (MR) analysis indicated a potential causal relationship between elevated PTGDS expression and OA risk. To validate the biological significance of PTGDS in SSF, a knee OA (KOA) rat model was established. Histopathological analyses using Masson staining (MASSO) and hematoxylin-eosin (HE) staining revealed significant morphological alterations in cartilage and synovial tissues. Additionally, immunohistochemistry (IHC), western blotting (WB), and quantitative real-time PCR (RT-qPCR) demonstrated increased expression of PTGDS and SSF markers (WISP2 and THY1) at both protein and mRNA levels in the KOA group. Crucially, double immunofluorescence (IF) staining provided clear histological evidence that PTGDS is predominantly expressed in SSF rather than in synovial intimal fibroblasts (SIF), thus linking this molecular signature explicitly to a distinct synovial cell subset. This integrative strategy combining transcriptomic analysis with histological validation presents a valuable approach for elucidating OA pathogenesis and identifying novel therapeutic targets.
Indexed as
Identifiers
41951989What 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.