Genes expressed in blood link osteoarthritis with apoptotic pathways

Ramos, Yolande F M; Bos, Steffan D.; Lakenberg, Nico; Böhringer, Stefan; Hollander, Wouter den; Kloppenburg, Margreet; Slagboom, P. Eline; Meulenbelt, Ingrid

doi:10.1136/annrheumdis-2013-203405

Cited by 64 publications

(73 citation statements)

References 35 publications

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“…These genes are primarily involved in eight functions, including transport, transmembrane receptor, cytokine, ion channel, transcription regulator, enzymes and growth factors. Compared with the 89 differentially expressed genes of OA identified by Ramos et al (12), BIRC3, IL-1β, NFKBIA, EGR1 and CXCL8 are identified as common differentially expressed genes (Table II).…”

Section: Resultsmentioning

confidence: 99%

“…A number of studies have analyzed the differentially expressed genes of peripheral blood to identify marker genes for early diagnosis of diseases including cancer, coronary disease and OA (8)(9)(10)(11)(12). With regard to KBD, in prior studies differentially expressed genes in cartilage and peripheral blood have been screened using microarrays (1,7,13).…”

Section: Introductionmentioning

confidence: 99%

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Comparative analysis of signaling pathways in peripheral blood from patients with Kashin-Beck disease and osteoarthritis

Ning

Wang

et al. 2016

Experimental and Therapeutic Medicine

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Abstract. The aim of the present study was to investigate the early diagnostic biomarkers of Kashin-Beck disease (KBD), and to compare the common signaling pathways of peripheral mononuclear cells between patients with KBD and those with osteoarthritis (OA). A total of 20 and 12 peripheral blood samples were separately collected from KBD patients and normal control subjects, respectively, in an endemic area according to the diagnosis criteria. Total RNAs were extracted and gene expression levels were determined using an Agilent whole genome expression microarrays. The gene expression data of OA were obtained from GEO published database. Significant different pathways between KBD and OA were analyzed using Ingenuity Pathway Analysis software. A total of 82 differentially expressed genes, 51 significant different signaling pathways and five significant biological functions were identified in KBD patient samples, while 89, 50 and five significantly different genes, pathways and functions were identified in OA. Nine common significant pathways and five common differentially expressed genes were identified between the KBD and OA. Nine common significant pathways and five common differentially expressed genes were found between the two diseases. The present results suggest that there are similarities in vascular microcirculation, immunoreactions and cell apoptosis between KBD and OA, which may contribute to the early diagnosis and pathogenetic study of KBD.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparative analysis of signaling pathways in peripheral blood from patients with Kashin-Beck disease and osteoarthritis

Ning

Wang

et al. 2016

Experimental and Therapeutic Medicine

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“…The lipid-associated cellular processes were enriched by the SM-dominant down-regulated cluster (C8). Because OA is not a systemic inflammatory disease, in contrast to RA, inflammatory gene signatures in peripheral blood mononuclear cells of OA patients are not significantly different from those of healthy individuals (16,17). We tried to validate differential expression of the selected 12 genes from FLS-and SM-dominant up-regulated clusters (C5 and C7) in independent RA-FLS and -SM samples obtained from different RA and OA patients and healthy controls using quantitative real-time PCR assays.…”

Section: Molecular Signatures Defining Invasive Potential Of Ra-flss Andmentioning

confidence: 99%

Identification of key regulators for the migration and invasion of rheumatoid synoviocytes through a systems approach

You

Yoo²,

Choi³

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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Rheumatoid synoviocytes, which consist of fibroblast-like synoviocytes (FLSs) and synovial macrophages (SMs), are crucial for the progression of rheumatoid arthritis (RA). Particularly, FLSs of RA patients (RA-FLSs) exhibit invasive characteristics reminiscent of cancer cells, destroying cartilage and bone. RA-FLSs and SMs originate differently from mesenchymal and myeloid cells, respectively, but share many pathologic functions. However, the molecular signatures and biological networks representing the distinct and shared features of the two cell types are unknown. We performed global transcriptome profiling of FLSs and SMs obtained from RA and osteoarthritis patients. By comparing the transcriptomes, we identified distinct molecular signatures and cellular processes defining invasiveness of RA-FLSs and proinflammatory properties of RA-SMs, respectively. Interestingly, under the interleukin-1β (IL-1β)–stimulated condition, the RA-FLSs newly acquired proinflammatory signature dominant in RA-SMs without losing invasive properties. We next reconstructed a network model that delineates the shared, RA-FLS–dominant (invasive), and RA-SM–dominant (inflammatory) processes. From the network model, we selected 13 genes, including periostin, osteoblast-specific factor (POSTN) and twist basic helix–loop–helix transcription factor 1 (TWIST1), as key regulator candidates responsible for FLS invasiveness. Of note, POSTN and TWIST1 expressions were elevated in independent RA-FLSs and further instigated by IL-1β. Functional assays demonstrated the requirement of POSTN and TWIST1 for migration and invasion of RA-FLSs stimulated with IL-1β. Together, our systems approach to rheumatoid synovitis provides a basis for identifying key regulators responsible for pathological features of RA-FLSs and -SMs, demonstrating how a certain type of cells acquires functional redundancy under chronic inflammatory conditions.

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“…The intersection of this set with the set of 17 variables in Table 1 is empty, although one of the nine variables, 41799, which corresponds to the gene H3F3B, is identified in ref. 6 as being highly differentially expressed between cases and controls. The discrepancy is attributable to the fact that many of the representations detailed define separating hyperplanes, achieving arbitrarily good fit for arbitrarily large regression coefficients.…”

Section: Illustration Of Methodsmentioning

confidence: 97%

“…In a study of osteoarthritis, a set of 106 patients clinically and radiographically diagnosed with primary symptomatic osteoarthritis at multiple joint sites were selected for gene expression analysis alongside 33 healthy controls (6). Samples from each patient were subjected to transcriptional profiling using microarrays containing probes for over 48,800 genes.…”

Section: Illustration Of Methodsmentioning

confidence: 99%

Large numbers of explanatory variables, a semi-descriptive analysis

Cox¹,

Battey

2017

Proc. Natl. Acad. Sci. U.S.A.

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3. The formal probabilistic behavior of the procedure in this paper under idealized conditions will be discussed in a separate paper. This paper adopts a different, less formal, and more exploratory approach in which judgment is needed at various stages. In this the conclusion is typically that a number of different simple models fit essentially equally well and that any choice between them requires additional information, for example new or different data or subject-matter knowledge. That is, informal choices are needed at various points in the analysis. Although the choices could be reformulated into a wholly automatic procedure this has not been done here.The combinatorial arrangements used in the method are essentially partially balanced incomplete block designs (4), in particular so-called cubic and square lattices, first developed in the context of plant breeding trials involving a very large number of varieties from which a small number are to be chosen for detailed study and agricultural use.

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Genes expressed in blood link osteoarthritis with apoptotic pathways

Cited by 64 publications

References 35 publications

Comparative analysis of signaling pathways in peripheral blood from patients with Kashin-Beck disease and osteoarthritis

Comparative analysis of signaling pathways in peripheral blood from patients with Kashin-Beck disease and osteoarthritis

Identification of key regulators for the migration and invasion of rheumatoid synoviocytes through a systems approach

Large numbers of explanatory variables, a semi-descriptive analysis

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