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Sequential depletion of human serum for the search of osteoarthritis biomarkers.

ABSTRACT: UNLABELLED: BACKGROUND:The field of biomarker discovery, development and application has been the subject of intense interest and activity, especially with the recent emergence of new technologies, such as proteomics-based approaches. In proteomics, search for biomarkers in biological fluids such as human serum is a challenging issue, mainly due to the high dynamic range of proteins present in these types of samples. Methods for reducing the content of most highly abundant proteins have been developed, including immunodepletion or protein equalization. In this work, we report for the first time the combination of a chemical sequential depletion method based in two protein precipitations with acetonitrile and DTT, with a subsequent two-dimensional difference in-gel electrophoresis (2D-DIGE) analysis for the search of osteoarthritis (OA) biomarkers in human serum. The depletion method proposed is non-expensive, of easy implementation and allows fast sample throughput. RESULTS:Following this workflow, we have compared sample pools of human serum obtained from 20 OA patients and 20 healthy controls. The DIGE study led to the identification of 16 protein forms (corresponding to 14 different proteins) that were significantly (p?

SUBMITTER: Fernandez-Costa C

PROVIDER: S-EPMC3515479 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Sequential depletion of human serum for the search of osteoarthritis biomarkers.

Fernández-Costa Carolina C Calamia Valentina V Fernández-Puente Patricia P Capelo-Martínez José-Luis JL Ruiz-Romero Cristina C Blanco Francisco J FJ

Proteome science 20120912 1

<h4>Unlabelled</h4><h4>Background</h4>The field of biomarker discovery, development and application has been the subject of intense interest and activity, especially with the recent emergence of new technologies, such as proteomics-based approaches. In proteomics, search for biomarkers in biological fluids such as human serum is a challenging issue, mainly due to the high dynamic range of proteins present in these types of samples. Methods for reducing the content of most highly abundant protein ...[more]

PMID: 22971006

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Project description:BackgroundOsteoarthritis (OA) is a slowly developing and debilitating disease, and there are no validated specific biomarkers for its early detection. To improve therapeutic approaches, identification of specific molecules/biomarkers enabling early determination of this disease is needed. This study aimed at identifying, with the use of proteomics/mass spectrometry, novel OA-specific serum biomarkers. As obesity is a major risk factor for OA, we discriminated obesity-regulated proteins to target only OA-specific proteins as biomarkers.MethodsSerum from the Osteoarthritis Initiative cohort was used and divided into 3 groups: controls (n=8), OA-obese (n=10) and OA-non-obese (n=10). Proteins were identified and quantified from the liquid chromatography-tandem mass spectrometry analyses using MaxQuant software. Statistical analysis used the Limma test followed by the Benjamini-Hochberg method. To compare the proteomic profiles, the multivariate unsupervised principal component analysis (PCA) followed by the pairwise comparison was used. To select the most predictive/discriminative features, the supervised linear classification model sparse partial least squares regression discriminant analysis (sPLS-DA) was employed. Validation of three differential proteins was performed with protein-specific assays using plasma from a cohort derived from the Newfoundland Osteoarthritis.ResultsIn total, 509 proteins were identified, and 279 proteins were quantified. PCA-pairwise differential comparisons between the 3 groups revealed that 8 proteins were differentially regulated between the OA-obese and/or OA-non-obese with controls. Further experiments using the sPLS-DA revealed two components discriminating OA from controls (component 1, 9 proteins), and OA-obese from OA-non-obese (component 2, 23 proteins). Proteins from component 2 were considered related to obesity. In component 1, compared to controls, 7 proteins were significantly upregulated by both OA groups and 2 by the OA-obese. Among upregulated proteins from both OA groups, some of them alone would not be a suitable choice as specific OA biomarkers due to their rather non-specific role or their strong link to other pathological conditions. Altogether, data revealed that the protein CRTAC1 appears to be a strong OA biomarker candidate. Other potential new biomarker candidates are the proteins FBN1, VDBP, and possibly SERPINF1. Validation experiments revealed statistical differences between controls and OA for FBN1 (p=0.044) and VDPB (p=0.022), and a trend for SERPINF1 (p=0.064).ConclusionOur study suggests that 4 proteins, CRTAC1, FBN1, VDBP, and possibly SERPINF1, warrant further investigation as potential new biomarker candidates for the whole OA population.

Project description:BackgroundOsteoarthritis (OA) is a debilitating chronic multijoint disease of global proportions. OA presence and severity is usually documented by x-ray imaging but whole body imaging is impractical due to radiation exposure, time and cost. Systemic (serum or urine) biomarkers offer a potential alternative method of quantifying total body burden of disease but no OA-related biomarker has ever been stringently qualified to determine the feasibility of this approach. The goal of this study was to evaluate the ability of three OA-related biomarkers to predict various forms or subspecies of OA and total body burden of disease.Methodology/principal findingsFemale participants (461) with clinical hand OA underwent radiography of hands, hips, knees and lumbar spine; x-rays were comprehensively scored for OA features of osteophyte and joint space narrowing. Three OA-related biomarkers, serum hyaluronan (sHA), cartilage oligomeric matrix protein (sCOMP), and urinary C-telopeptide of type II collagen (uCTX2), were measured by ELISA. sHA, sCOMP and uCTX2 correlated positively with total osteophyte burden in models accounting for demographics (age, weight, height): R(2) = 0.60, R(2) = 0.47, R(2) = 0.51 (all p<10(-6)); sCOMP correlated negatively with total joint space narrowing burden: R(2) = 0.69 (p<10(-6)). Biomarkers and demographics predicted 35-38% of variance in total burden of OA (total joint space narrowing or osteophyte). Joint size did not determine the contribution to the systemic biomarker concentration. Biomarker correlation with disease in the lumbar spine resembled that in the rest of the skeleton.Conclusions/significanceWe have suspected that the correlation of systemic biomarkers with disease has been hampered by the inability to fully phenotype the burden of OA in a patient. These results confirm the hypothesis, revealed upon adequate patient phenotyping, that systemic joint tissue concentrations of several biomarkers can be quantitative indicators of specific subspecies of OA and of total body burden of disease.

Project description:BACKGROUND: Osteoarthritis (OA) is the most common degenerative joint disease, of which the pathogenesis is inadequately understood. Hypertrophy-like changes have been observed as part of the progression of OA. The aim of the study was to develop and characterize a novel biomarker of chondrocytes hypertrophy and investigate how this marker was associated with cartilage degradation and inflammation in patients with various degrees of OA. METHODS: A competitive ELISA, C-Col10, applying a well-characterized monoclonal antibody was developed as a biomarker of chondrocyte hypertrophy through measurement of type X collagen (ColX). The levels of C-Col10, C2M (matrix metalloproteinase-derived fragments of type II collagen) and hsCRP (high sensitive C-reactive protein) were quantified by ELISAs in serum of 271 OA patients stratified by Kellgren-Lawrence (KL) score 0-4. Associations between serum levels of the three biomarkers (log transformed) were analyzed by Pearson's correlation and differences in C-Col10 levels between patients with high and low levels of inflammation measured by hsCRP were analyzed by ANOVA. RESULTS: We developed a C-Col10 assay measuring the C-terminus of ColX. We found significantly higher levels of ColX in patients with KL score 2 compared to patients with no radiographic evidence of OA (KL0) (p = 0.04). Levels of ColX were significantly elevated in OA patients with above normal hsCRP levels (p < 0.0001), as well as significantly correlated with levels of C2M (r = 0.55, p < 0.0001), which suggested that chondrocyte hypertrophy was associated with inflammation and cartilage degradation. There was no correlation between C2M and hsCRP. Age and BMI adjustment didn't change the results. Immuno-staining revealed that ColX was predominately located around the hypertrophic chondrocytes and the clustered chondrocytes indicating that C-Col10 measures may be linked to cartilage hypertrophic changes. CONCLUSIONS: We developed a novel assay, C-Col10, for measurement of chondrocyte hypertrophy and found its levels significantly elevated in OA patients with KL score of 2, and also in OA patients with above normal hsCRP levels. Concentration of C-Col10 strongly correlated with levels of C2M, a marker of cartilage destruction. The data suggest that chondrocyte hypertrophy and subsequent collagen X fragmentation seem to be increased in a subset of patients with inflammatory OA.

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Sequential depletion of human serum for the search of osteoarthritis biomarkers.

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Sequential depletion of human serum for the search of osteoarthritis biomarkers.

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