Identification of Potential Prognostic Markers for Knee Osteoarthritis by Serum Proteomic Analysis

Takinami, Yoshihiko; Yoshimatsu, Shinya; Uchiumi, Takaoki; Toyosaki-Maeda, Tomoko; Morita, Atsushi; Ishihara, Takeshi; Yamane, Shoji; Fukuda, Isao; Okamoto, Hiroyuki; Numata, Yoshito; Fukui, Naoshi

doi:10.4137/bmi.s11966

Cited by 25 publications

(22 citation statements)

References 34 publications

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“…Previous studies have suggested some biomarkers that can be utilized in the diagnosis, grading severity and, the prognosis of OA progression. Until now, despite intensive research, just a few biochemical factors, of which SF or serum levels reveal a correlation with the radiographic findings of OA patients, have been known . The biomarkers that have been specifically defined for OA can be related to bone, cartilage, and synovium metabolisms or systemic inflammation.…”

Section: Discussionmentioning

confidence: 99%

Association of UCMA levels in serum and synovial fluid with severity of knee osteoarthritis

et al. 2019

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Aim Osteoarthritis (OA) is one of the most common joint diseases causing physical disability in the aged population. OA pathogenesis is not fully known and yet there are no effective therapeutic options against OA. Upper Zone of Growth Plate and Cartilage Matrix Associated (UCMA) is a member of vitamin K‐dependent protein family, and is involved in inflammation, cardiovascular diseases, cancer, and OA. In the present study, our aim was to detect serum and synovial fluid (SF) levels of UCMA and to analyze their correlation with radiographic findings and symptomatic severity in OA patients as well as the correlation between oxidative stress levels and SF UCMA levels. Methods Forty OA patients with cartilage degeneration and 20 patients with other knee joint disorders (non‐OA control) were included in the present study. We used the Kellgren‐Lawrence (KL) classification and Western Ontario McMaster University Osteoarthritis Index (WOMAC) scores to assess radiographic grading and symptomatic severity of OA, respectively. UCMA levels were measured in SF and serum. And also oxidative stress markers were analyzed in SF. Results SF UCMA levels of OA patients were higher compared to those of the non‐OA control group and were positively correlated with radiographic finding and symptomatic severity of OA. However, there was no significant correlation between oxidative markers of SF and the KL grade, WOMAC scores, and SF UCMA levels in OA patients. Conclusion There is a close connection between UCMA SF levels and symptomatic and radiographic severities of knee OA. Therefore, UCMA can be a promising biomarker in the diagnosis and/or prognosis of OA disease.

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Section: Discussionmentioning

confidence: 99%

Association of UCMA levels in serum and synovial fluid with severity of knee osteoarthritis

et al. 2019

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“…By SELDI-MS, they compared serum from a large OA cohort to those of healthy individuals and OA patients and they identified four novel markers for OA, including V65 vitronectin fragment, C3f peptide, CTAP-III, and m/z 3762 protein. Another OA proteomic study in plasma was reported by Takinami et al (2013). This group applied SELDI-MS to plasma samples from progressive OA, non-progressive OA, and healthy individuals without OA.…”

Section: Proteomic Analysis Of Serum In Oamentioning

confidence: 97%

Biomarkers and proteomic analysis of osteoarthritis

2014

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Our friend and colleague, Dr. Dick Heinegård, contributed greatly to the understanding of joint tissue biochemistry, the discovery and validation of arthritis-related biomarkers and the establishment of methodology for proteomic studies in osteoarthritis (OA). To date, discovery of OA-related biomarkers has focused on cartilage, synovial fluid and serum. Methods, such as affinity depletion and hyaluronidase treatment have facilitated proteomics discovery research from these sources. Osteoarthritis usually involves multiple joints; this characteristic makes it easier to detect OA with a systemic biomarker but makes it hard to delineate abnormalities of individual affected joints. Although the abundance of cartilage proteins in urine may generally be lower than other tissue/sample sources, the protein composition of urine is much less complex and its collection is non-invasive thereby facilitating the development of patient friendly biomarkers. To date however, relatively few proteomics studies have been conducted in OA urine. Proteomics strategies have identified many proteins that may relate to pathological mechanisms of OA. Further targeted approaches to validate the role of these proteins in OA are needed. Herein we summarize recent proteomic studies related to joint tissues and the cohorts used; a clear understanding of the cohorts is important for this work as we expect that the decisive discoveries of OA-related biomarkers rely on comprehensive phenotyping of healthy non-OA and OA subjects. Besides the common phenotyping criteria that include, gender, age, and body mass index (BMI), it is essential to collect data on symptoms and signs of OA outside the index joints and to bolster this with objective imaging data whenever possible to gain the most precise appreciation of the total burden of disease. Proteomic studies on systemic biospecimens, such as serum and urine, rely on comprehensive phenotyping data to unravel the true meaning of the proteomic results.

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“…In a subsequent study specifically focused in OA, the same authors identified four differential MS peaks Effect of IL-1b QConCAT + LC-MS/MS 252 Reduction of TIMP1 secretion [42] Characterization of MMPs and ADAMTs cleavage LC-MS/MS 16 Profiles of proteolytic peptides [44] Wounded zones of OA versus unwounded versus HC iTRAQ + LC-MS/MS 401 OPG, POSTN [37] OA versus HC articular cartilage vesicles LC-MS/MS 1700 big-H3, DEL1, VTN, HTRA1 [38] Chondrocytes Effect of IL-1b or TNF-a Antibody array 79 IL-8, IL-6, OPG [40] Effect of IL-1b or OSM Proteomic study of osteoarthritis Review informahealthcare.com between OA, RA and controls [11]. The same approach recently enabled the identification of potential prognostic markers for knee OA [47]. Finally, other kind of high-throughput proteomic approaches that have been performed using plasma or serum are protein microarrays, such as antigen microarrays or nucleic acid programmable protein arrays for profiling the autoantibody repertoire of OA [48].…”

Section: Proteomic Analysis Of Secretomes From Joint Tissues and Cellsmentioning

confidence: 98%

“…Finally, a recent work described the identification of putative biomarkers of psoriatic arthritis in SF using OA samples as control group [57]. Progressive versus non progressive OA SELDI 300 peaks APOC-I, APOC-III, TTHY fragment [47] OA K/L I/II versus K/L IV versus HC iTRAQ + LC-MS/MS 349 26 differential proteins [8] OA versus RA versus HC autoAb profiling Antigen and NAPPA arrays 3840 antigens Anti-CHST14 auto-antibodies [48] Serum and synovial fluid OA versus HC UF + LC-MS/MS 40 COL2, PRG4, SAA, TUB, VIME, MGP [50] MB + MALDI-TOF 61 peaks Two peptide peaks [55] Early and late OA versus HC 1-DE + LC-MS/MS 135 18 altered in OA [51] DIGE + SRM 337 AFAM, CLUS, LUMI, PEDF, ALS [56] PsA versus early OA LC-MS/MS + SRM 12 proteins quantified by SRM Apart from serum or SF, no other MS-based studies have been carried out for OA biomarker discovery in alternative body fluids, with the exception of the development of an immunoaffinity-LC-MS/MS assay for the determination of a type II collagen neoepitope in urine [58,59]. Being a promising strategy for the accurate quantification of markers in biofluids, this approach was more recently applied for the analysis of endogenous aggrecan fragments in SF and urine [60].…”

Section: Proteomic Analysis Of Secretomes From Joint Tissues and Cellsmentioning

confidence: 99%

Lessons from the proteomic study of osteoarthritis

Ruiz-Romero

Fernández-Puente

Calamia

et al. 2015

Expert Review of Proteomics

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Osteoarthritis is the most common rheumatic pathology and one of the leading causes of disability worldwide. It is a very complex disease whose etiopathogenesis is not fully understood. Furthermore, there are serious limitations for its management, since it lacks specific and sensitive biomarkers for early diagnosis, prognosis and therapeutic monitoring. Proteomic approaches performed in the last few decades have contributed to the knowledge on the molecular mechanisms that participate in this pathology and they have also led to interesting panels of putative biomarker candidates. In the next few years, further efforts should be made for translating these findings into the clinical routines. It is expected that targeted proteomics strategies will be highly valuable for the verification and qualification of biomarkers of osteoarthritis.

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Identification of Potential Prognostic Markers for Knee Osteoarthritis by Serum Proteomic Analysis

Cited by 25 publications

References 34 publications

Association of UCMA levels in serum and synovial fluid with severity of knee osteoarthritis

Association of UCMA levels in serum and synovial fluid with severity of knee osteoarthritis

Biomarkers and proteomic analysis of osteoarthritis

Lessons from the proteomic study of osteoarthritis

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