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Identification of potential prognostic markers for knee osteoarthritis by serum proteomic analysis.

ABSTRACT: BACKGROUND:As osteoarthritis (OA) is a highly heterogeneous disease in terms of progression, establishment of prognostic biomarkers would be highly beneficial for treatment. The present study was performed to identify novel biomarkers capable of predicting the progression of knee OA. METHODS:A total of 69 plasma samples (OA patients undergoing radiographic progression, n = 25; nonprogression, n = 33; healthy donors, n = 11) were analyzed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), and ion peaks of interest were identified by liquid chromatography and matrix-assisted laser desorption/ionization (MALDI)-TOF MS. The identities of these proteins were further validated by immunoprecipitation combined with SELDI-TOF MS analysis. RESULTS:SELDI-TOF MS analysis indicated that the intensities of 3 ion peaks differed significantly between progressors and nonprogressors. Subsequent analyses indicated that these peaks corresponded to apolipoprotein C-I, C-III, and an N-terminal truncated form of transthyretin, respectively. The identities of these proteins were confirmed by the loss of ion peaks in SELDI-TOF MS spectra by immunoprecipitation using specific antibodies for the respective proteins. CONCLUSIONS:Three potential biomarkers were identified whose serum levels differed significantly between OA progressors and nonprogressors. These biomarkers are expected to be prognostic biomarkers for knee OA and to facilitate the development of novel disease-modifying treatments for OA.

SUBMITTER: Takinami Y

PROVIDER: S-EPMC3735238 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Identification of potential prognostic markers for knee osteoarthritis by serum proteomic analysis.

Takinami Yoshihiko Y Yoshimatsu Shinya S Uchiumi Takaoki T Toyosaki-Maeda Tomoko T Morita Atsushi A Ishihara Takeshi T Yamane Shoji S Fukuda Isao I Okamoto Hiroyuki H Numata Yoshito Y Fukui Naoshi N

Biomarker insights 20130729

<h4>Background</h4>As osteoarthritis (OA) is a highly heterogeneous disease in terms of progression, establishment of prognostic biomarkers would be highly beneficial for treatment. The present study was performed to identify novel biomarkers capable of predicting the progression of knee OA.<h4>Methods</h4>A total of 69 plasma samples (OA patients undergoing radiographic progression, n = 25; nonprogression, n = 33; healthy donors, n = 11) were analyzed by surface-enhanced laser desorption/ioniza ...[more]

PMID: 23935359

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Project description:BackgroundWe investigated the potential of proteomic fingerprinting with mass spectrometric serum profiling, coupled with pattern recognition methods, to identify biomarkers that could improve diagnosis of tuberculosis.MethodsWe obtained serum proteomic profiles from patients with active tuberculosis and controls by surface-enhanced laser desorption ionisation time of flight mass spectrometry. A supervised machine-learning approach based on the support vector machine (SVM) was used to obtain a classifier that distinguished between the groups in two independent test sets. We used k-fold cross validation and random sampling of the SVM classifier to assess the classifier further. Relevant mass peaks were selected by correlational analysis and assessed with SVM. We tested the diagnostic potential of candidate biomarkers, identified by peptide mass fingerprinting, by conventional immunoassays and SVM classifiers trained on these data.FindingsOur SVM classifier discriminated the proteomic profile of patients with active tuberculosis from that of controls with overlapping clinical features. Diagnostic accuracy was 94% (sensitivity 93.5%, specificity 94.9%) for patients with tuberculosis and was unaffected by HIV status. A classifier trained on the 20 most informative peaks achieved diagnostic accuracy of 90%. From these peaks, two peptides (serum amyloid A protein and transthyretin) were identified and quantitated by immunoassay. Because these peptides reflect inflammatory states, we also quantitated neopterin and C reactive protein. Application of an SVM classifier using combinations of these values gave diagnostic accuracies of up to 84% for tuberculosis. Validation on a second, prospectively collected testing set gave similar accuracies using the whole proteomic signature and the 20 selected peaks. Using combinations of the four biomarkers, we achieved diagnostic accuracies of up to 78%.InterpretationThe potential biomarkers for tuberculosis that we identified through proteomic fingerprinting and pattern recognition have a plausible biological connection with the disease and could be used to develop new diagnostic tests.

Project description:High tibial osteotomy (HTO) is a well-established treatment for medial compartmental knee osteoarthritis. Several microRNAs (miRNAs) are involved in osteoarthritis progression and are useful as osteoarthritis-related biomarkers. In this prospective study, we investigated differentially expressed microRNAs in the synovial fluid (SF) before and after HTO in patients with medial compartmental knee osteoarthritis to identify microRNAs that can be used as prognostic biomarkers. We used miRNA-PCR arrays to screen for miRNAs in SF samples obtained preoperatively and 6 months postoperatively from 6 patients with medial compartmental knee osteoarthritis who were treated with medial open wedge HTO. Differentially expressed miRNAs identified in the profiling stage were validated by real-time quantitative PCR in 22 other patients who had also been treated with HTO. All patients radiographically corresponded to Kellgren-Lawrence grade II or III with medial compartmental osteoarthritis. These patients were clinically assessed using a visual analogue scale and Western Ontario McMaster Universities scores. Mechanical axis changes were measured on standing anteroposterior radiographs of the lower limbs assessed preoperatively and at 6 months postoperatively. Among 84 miRNAs known to be involved in the inflammatory process, 14 were expressed in all SF specimens and 3 (miR-30a-5p, miR-29a-3p, and miR-30c-5p) were differentially expressed in the profiling stage. These 3 miRNAs, as well as 4 other miRNAs (miR-378a-5p, miR-140-3p, miR-23a-3p, miR-27b-3p), are related to osteoarthritis progression. These results were validated in the SF from 22 patients. Clinical and radiological outcomes improved after HTO in all patients, and only 2 miRNAs (miR-30c-5p and miR-23a-3p) were significantly differentially expressed between preoperative and postoperative 6-month SF samples (p = 0.006 and 0.007, respectively). Of these two miRNAs, miR-30c-5p correlated with postoperative pain relief. This study provides potential prognostic miRNAs after HTO and further investigations should be considered to determine clinical implications of these miRNAs.

Project description:BackgroundA previous systematic review on prognostic factors for knee osteoarthritis (OA) progression showed associations for generalized OA and hyaluronic acid levels. Knee pain, radiographic severity, sex, quadriceps strength, knee injury, and regular sport activities were not associated. It has been a decade since the literature search of that review and many studies have been performed since then investigating prognostic factors for radiographic knee OA progression.Questions/purposesThe purpose of this study is to provide an updated systematic review of available evidence regarding prognostic factors for radiographic knee OA progression.MethodsWe searched for observational studies in MEDLINE and EMBASE. Key words were: knee, osteoarthritis (or arthritis, or arthrosis, or degenerative joint disease), progression (or prognosis, or precipitate, or predictive), and case-control (or cohort, or longitudinal, or follow-up). Studies fulfilling the inclusion criteria were assessed for methodologic quality according to established criteria for reviews on prognostic factors in musculoskeletal disorders. Data were extracted and results were pooled if possible or summarized according to a best-evidence synthesis. A total of 1912 additional articles were identified; 43 met our inclusion criteria. The previous review contained 36 articles, thus providing a new total of 79 articles. Seventy-two of the included articles were scored high quality, the remaining seven were low quality.ResultsThe pooled odds ratio (OR) of two determinants showed associations with knee OA progression: baseline knee pain (OR, 2.38 [95% CI, 1.74-3.27) and Heberden nodes (OR, 2.66 [95% CI, 1.46-8.84]). Our best-evidence synthesis showed strong evidence that varus alignment, serum hyaluronic acid, and tumor necrosis factor-α are associated with knee OA progression. There is strong evidence that sex, former knee injury, quadriceps strength, smoking, running, and regular performance of sports are not associated with knee OA progression. Evidence for the majority of determined associations, however, was limited, conflicting, or inconclusive.ConclusionsBaseline knee pain, presence of Heberden nodes, varus alignment, and high levels of serum markers hyaluronic acid and tumor necrosis factor-α predict knee OA progression. Sex, knee injury, and quadriceps strength, among others, did not predict knee OA progression. Large variation remains in definitions of knee OA and knee OA progression. Clinical studies should use more consistent definitions of these factors to facilitate data pooling by future meta-analyses.

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Identification of potential prognostic markers for knee osteoarthritis by serum proteomic analysis.

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Identification of potential prognostic markers for knee osteoarthritis by serum proteomic analysis.

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