Autologous chondrocyte implantation-derived synovial fluids display distinct responder and non-responder proteomic profiles

Hulme, Charlotte; Wilson, E. Lynette; Peffers, Mandy J.; Roberts, Sally; Simpson, Deborah M.; Richardson, James B.; Gallacher, Peter; Wright, Karina

doi:10.1186/s13075-017-1336-7

Cited by 19 publications

(36 citation statements)

References 53 publications

(71 reference statements)

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“…Genes that had a fold change (FC) ≥ ± 1.3 between cells cultured in 25 mM compared to 5 mM glucose were identified for further analyses. Similar fold change cut-offs are commonly used for such network and pathway analysis approaches 24 , 25 . Partial least square discriminant analysis (PLS-DA) was applied using the MixOmics R-package 26 , 27 and used to compare the fold changes of the selected genes to the unselected genes.…”

Section: Methodsmentioning

confidence: 99%

Identification of the functional pathways altered by placental cell exposure to high glucose: lessons from the transcript and metabolite interactome

Hulme

Stevens

Dunn

et al. 2018

Sci Rep

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The specific consequences of hyperglycaemia on placental metabolism and function are incompletely understood but likely contribute to poor pregnancy outcomes associated with diabetes mellitus (DM). This study aimed to identify the functional biochemical pathways perturbed by placental exposure to high glucose levels through integrative analysis of the trophoblast transcriptome and metabolome. The human trophoblast cell line, BeWo, was cultured in 5 or 25 mM glucose, as a model of the placenta in DM. Transcriptomic analysis using microarrays, demonstrated 5632 differentially expressed gene transcripts (≥± 1.3 fold change (FC)) following exposure to high glucose. These genes were used to generate interactome models of transcript response using BioGRID (non-inferred network: 2500 nodes (genes) and 10541 protein-protein interactions). Ultra performance-liquid chromatography-mass spectrometry (MS) and gas chromatography-MS analysis of intracellular extracts and culture medium were used to assess the response of metabolite profiles to high glucose concentration. The interactions of altered genes and metabolites were assessed using the MetScape interactome database, resulting in an integrated model of systemic transcriptome (2969 genes) and metabolome (41 metabolites) response within placental cells exposed to high glucose. The functional pathways which demonstrated significant change in response to high glucose included fatty acid β-oxidation, phospholipid metabolism and phosphatidylinositol phosphate signalling.

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Section: Methodsmentioning

confidence: 99%

Identification of the functional pathways altered by placental cell exposure to high glucose: lessons from the transcript and metabolite interactome

Hulme

Stevens

Dunn

et al. 2018

Sci Rep

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“…Encouraged by these findings, recent studies have focused on the identification of new markers, more specifically addressing early diagnosis, and the development of new targets for disease modifying drugs . Furthermore, biomarkers may also be a means to predict disease progression and optimize individual treatments …”

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confidence: 99%

“…5,[11][12][13] Furthermore, biomarkers may also be a means to predict disease progression and optimize individual treatments. 14,15 Abbreviations: ASPN, asporin; AUGN, augurin; Col, collagen; pN Col III, N-propeptide collagen type III; CILP1, cartilage intermediate layer protein 1; CILP2, cartilage intermediate layer protein 2; CHAD, chondroadherin; COMP, cartilage oligomeric matrix protein; CHADL, chondroadherin link protein; CSPG2, versican core protein; COBA2, collagen alpha-2 (XI) chain; DERM, dermatopontin; ECM, extracellular martix; FMOD, fibromodulin; Fx, fracture; FINC, fibronectin; GAGs, glycosaminoglycans; HPLN, hyaluronan and PG link protein; HTRA1, serine protease HTRA1; LC, liquid chromatography; LUM, lumican; MS, mass spectrometry; MRM, multiple reaction monitoring; MATN1, matrilin-1; MATN3, matrilin-3; MIME, mimecan; MGP, matrix Gla protein; OA, osteoarthritis; OMD, osteomodulin; OSTP, osteopontin; PGs, proteoglycans; PGCA, aggrecan core protein; PGS1, biglycan; PGS2, decorin; PRG4, lubricin; PRELP, prolargin; PGBM, basement membrane specific heparin sulfate PG core protein; TSP1, thrombospondin-1; TSP4, thrombospondin-4; SLRPs, small leucine rich repeat proteoglycans; TENA, tenascin-C; TENX, tenascin-X; TGF-b, Transforming growth factor-beta Patrik The aim of this study was to explore candidate proteins in early events of osteoarthritic cartilage which may predict development of OA. We used targeted proteomics and liquid chromatography coupled with mass spectrometry LC-MS.…”

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confidence: 99%

Targeted proteomics of hip articular cartilage in OA and fracture patients

Hosseininia

Önnerfjord

Dahlberg

2019

Journal Orthopaedic Research

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Osteoarthritis (OA) is a common chronic disease, causing joint pain and reduced physical function. OA progresses slowly over a period of several years; to avoid an exacerbation of symptoms, it is critical to able to diagnose the disease as early as possible. The identification of disease‐specific biomarkers may enable such an early diagnosis. The aim of this study was to investigate potential biomarkers of cartilage metabolism in OA using a targeted multiplex approach by single reaction monitoring. Intact looking cartilage of femoral heads from patients with OA (n = 9) or femoral neck fractures (n = 12) was examined. Variations and relative quantifications of 35 selected extracellular matrix (ECM) proteins were analyzed using nano‐LC coupled to tandem mass spectrometry. Our study showed statistically significantly increased levels of asporin (ASPN), mimecan (MIME), matrilin‐3 (MATN3), cartilage intermediate layer protein 2 (CILP‐2), collagen VI, collagen II, and collagen III N‐propeptide in OA cartilage compared with non‐OA cartilage. The other proteins in the protein panel did not appear to be different between the two groups. In conclusion, we identified a number of cartilage matrix proteins which may represent early molecular changes in the OA process and may have potential to predict the development of OA. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res

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“…Among the proteins that were differentially expressed with a fold change larger than 2 have previously been reported to have a connection to osteoarthritis disease progression ( Fig 4) 13, [26][27][28][29][30][31] 35 . In this study, all these three proteins were decreased in the synovial fluid of both early and late-stage OA in comparison to the controls.…”

Section: Discussionmentioning

confidence: 95%

Proteomics profiling of human synovial fluid suggests global increased protein interplay in early-osteoarthritis (OA) and lost in late-stage OA

Ali

Turkiewicz

Hughes

et al. 2020

Preprint

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The underlying molecular mechanisms in osteoarthritis (OA) development are largely unknown. This study explores the proteome and the pairwise interplay of proteins on a global level in synovial fluid from patients with late-stage knee OA (arthroplasty), early knee OA (arthroscopy due to degenerative meniscal tear) and from controls without knee OA. Synovial fluid samples were analyzed using state-of-the-art mass spectrometry with data-independent acquisition. The differential expression of the proteins detected was clustered and evaluated with data mining strategies and a multilevel model. Group-specific slopes of associations were estimated between expressions of each pair of identified proteins to assess the co-expression (i.e. interplay) between the proteins in each group. The differential expression revealed more proteins to be increased in early-OA vs controls than late-stage OA vs controls. For most of these proteins, the fold changes between late-stage OA vs controls and early-stage OA vs controls were remarkably similar suggesting potential involvement in the OA process. Further, for the first time, this study illustrated distinct patterns in protein co-expression suggesting that the global interplay between the protein machinery is increased in early-OA and lost in late-stage OA. Further efforts should probably focus on earlier stages of the disease than previously considered.

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Autologous chondrocyte implantation-derived synovial fluids display distinct responder and non-responder proteomic profiles

Cited by 19 publications

References 53 publications

Identification of the functional pathways altered by placental cell exposure to high glucose: lessons from the transcript and metabolite interactome

Identification of the functional pathways altered by placental cell exposure to high glucose: lessons from the transcript and metabolite interactome

Targeted proteomics of hip articular cartilage in OA and fracture patients

Proteomics profiling of human synovial fluid suggests global increased protein interplay in early-osteoarthritis (OA) and lost in late-stage OA

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