Trial reportBMC musculoskeletal disorders2017
Gene expression profiling in patients with polymyalgia rheumatica before and after symptom-abolishing glucocorticoid treatment.
Trial report in BMC musculoskeletal disorders, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 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
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Comprehensive multi-cohort transcriptional meta-analysis of muscle diseases identifies a signature of disease severity.Scientific reports · 2022Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe pathophysiology, including the impact of gene expression, of polymyalgia rheumatica (PMR) remains elusive. We profiled the gene expression in muscle tissue in PMR patients before and after glucocorticoid treatment.
methodsGene expression was measured using Affymetrix Human Genome U133 Plus 2.0 arrays in muscle biopsies from 8 glucocorticoid-naive patients with PMR and 10 controls before and after prednisolone-treatment for 14 days. For 14 genes, quantitative real-time PCR (qRT-PCR, n = 9 in both groups) was used to validate the microarray findings and to further investigate the expression of genes of particular interest.
resultsPrednisolone normalized erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) in PMR patients. A total of 165 putatively clinically relevant, differentially expressed genes were identified (cut-off: fold difference > ±1.2, difference of mean > 30, and p < 0.05); of these, 78 genes differed between patients and controls before treatment, 131 genes responded to treatment in a given direction only in patients, and 44 fulfilled both these criteria. In 43 of the 44 genes, treatment counteracted the initial difference. Functional clustering identified themes of biological function, including regulation of protein biosynthesis, and regulation of transcription and of extracellular matrix processes. Overall, qRT-PCR confirmed the microarray findings: Microarray-detected group differences were confirmed for 9 genes in 17 of 18 comparisons (same magnitude and direction of change); lack of group differences in microarray testing was confirmed for 5 genes in 8 of 10 comparisons. Before treatment, using qRT-PCR, expression of interleukin 6 (IL-6) was found to be 4-fold higher in patients (p < 0.05).
conclusionsThis study identifies genes in muscle, the expression of which may impact the pathophysiology of PMR. Moreover, the study adds further evidence of the importance of IL-6 in the disease. Follow-up studies are needed to establish the exact pathophysiological relevance of the identified genes. The study was retrospectively listed on the ISRCTN registry with study ID ISRCTN69503018 and date of registration the 26th of July 2017.
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.