Muscle Transcriptomic Circuits Linked to Periarticular Physiology in End-Stage Osteoarthritis.
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA845210 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR19537851_1.fastq.gz | Fastqsanger.gz | |||
| SRR19537851_2.fastq.gz | Fastqsanger.gz | |||
| SRR19537852_1.fastq.gz | Fastqsanger.gz | |||
| SRR19537852_2.fastq.gz | Fastqsanger.gz | |||
| SRR19537853_1.fastq.gz | Fastqsanger.gz |
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Project description:Osteoarthritis is characterized by degeneration of cartilage and bone in the synovial joints. Recent findings suggest that inflammation may play a role in osteoarthritis, with synovitis being associated with the clinical symptoms of osteoarthritis. Furthermore, we have found that levels of inflammatory complement components are abnormally high in the synovial fluid of individuals with osteoarthritis. To determine whether synovial membranes could be a source of complement and other inflammatory molecules in osteoarthritic joints, we characterized the expression of genes in synovial membranes from patients with early-stage or end-stage osteoarthritis. Samples of synovial membrane were obtained from the suprapatellar pouch of patients with osteoarthritis who were treated at the Hospital for Special Surgery. Specifically, samples were from 10 patients with early-stage knee osteoarthritis who were undergoing arthroscopic procedures for degenerative meniscal tears (with documented cartilage degeneration but no full-thickness cartilage loss, Kellgren Lawrence score </=2), and from 9 patients with end-stage knee osteoarthritis ( diffuse full thickness cartilage erosion) who were undergoing total knee joint replacement. Raw data from microarray analysis of healthy synovial membranes, which were run on the same platform and array as our osteoarthritic samples, were downloaded from the NCBI Gene Expression Omnibus (accession number GSE12021) and used for comparison. The 19 new Samples of this Series were analyzed (RMA) together with 7 previously submitted healthy individual Samples (GSM175810, GSM175812, GSM176290, GSM176291, GSM176292, GSM176268, GSM176269). The complete RMA data are provided as a supplementary file on the Series record. The GSE12021 reanalyzed data are also provided as a supplementary file on the Series record. GSE32317_12genes.txt includes data from figure 1 of the paper.
2011-11-01 | E-GEOD-32317 | biostudies-arrayexpress
Project description:Synovial biopsies were obtained from osteoarthritis (OA) synovium to find genes upregulated during OA. The genes upregulated during OA can be used to identify disease characteristic genes. 10 microarrays of end-stage OA synovial biopsies were compared to 7 microarrays of synovial biopsies from individuals without a joint disease. Genes with >1.2-fold upregulation and P<0.05 in OA VS HC were selected from the analysis.
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Project description:ObjectiveThis study constructs a risk score for patients' progression to end-stage knee osteoarthritis (OA) within 4 years.DesignThe Osteoarthritis Initiative (OAI) was a longitudinal study of the onset and progression of knee OA. Using a recent definition of end-stage knee OA, we implement interval-censored survival forests to select predictors of this endpoint. We fit an interval-censored Cox model for time to end-stage knee OA, using the selected predictors. The risk score is the Cox model's fitted linear combination of the nine selected baseline structural and symptomatic knee OA variables.ResultsWe fit our models on a training set of 2,701 patients, and we evaluate on an independent test set of 1,436 patients. On the test sample, we observe a concordance index of 0.86 between risk score and time to end-stage, AUC of 0.87 for predicting end-stage within 24, 36, and 48 months, and positive predictive values that increase with the risk score. This risk stratification algorithm could enrich clinical trial patient enrollment. By enrolling test sample patients with scores above a threshold, a trial could have included 91% of test set patients who reach end-stage within 4 years while only enrolling 45% of the test sample.ConclusionUsing statistical methods, we construct and validate an interpretable risk score for time to end-stage knee OA. This score can help disease-modifying OA treatment developers to select candidates with the highest risk of fast-progressing knee OA.
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