Dataset Information

High-resolution magic angle spinning NMR spectroscopy of human osteoarthritic cartilage.

ABSTRACT: Osteoarthritis (OA) is a degenerative disease of the joints and results in changes in the biochemical composition of cartilage. Previous studies have been undertaken that have used high-resolution NMR spectroscopy to study the biochemical composition of porcine, canine and bovine cartilage. In the present study, high-resolution magical angle spinning (HR-MAS) NMR spectroscopy at 11.7 T has been used to characterize metabolites and detect differences in the spectral signature of human knee articular cartilage from non-OA healthy cadaver knees and samples acquired from severe OA patients at the time of total knee replacement surgery. A statistically significant difference in the alanine (1.47 p.p.m.), N-acetyl (2.04 p.p.m.), choline (3.25 p.p.m.) and glycine (3.55 p.p.m.) metabolite levels was observed between healthy and OA specimens. The results of the present study indicate that a decrease in the intensity of N-acetyl resonance occurs in the later stages of OA. A positive correlation of the N-acetyl levels as measured by (1)H HR-MAS NMR spectroscopy with the total proteoglycan content in the same cartilage specimens as measured by the glycosaminoglycan (GAG) assay was observed. This indicates that N-acetyl can serve as an important bio-marker of OA disease progression. A decrease in the alanine concentration in OA may be attributed to the degradation of the collagen framework with disease progression and eventual loss of the degradation products that are transported from cartilage into the synovial cavity.

SUBMITTER: Shet K

PROVIDER: S-EPMC3299852 | biostudies-other | 2012 Apr

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:Osteoarthritis (OA) is a common multifactorial and heterogeneous degenerative joint disease, and biochemical changes in cartilage matrix occur during the early stages of OA before morphological changes occur. Thus, it is desired to measure regional biochemical changes in the joint. High-resolution magic angle spinning (HRMAS) NMR spectroscopy is a powerful method of observing cartilaginous biochemical changes ex vivo, including the concentrations of alanine and N-acetyl, which are markers of collagen and total proteoglycan content, respectively. Previous studies have observed significant changes in chondrocyte metabolism of OA cartilage via the altered gene expression profiles of ACAN, COL2A1 and MMP13, which encode aggrecan, type II collagen and matrix metalloproteinase 13 (a protein crucial in the degradation of type II collagen), respectively. Employing HRMAS, this study aimed to elucidate potential relationships between N-acetyl and/or alanine and ACAN, COL2A1 and/or MMP13 expression profiles in OA cartilage. Thirty samples from the condyles of five subjects undergoing total knee arthroplasty to treat OA were collected. HRMAS spectra were obtained at 11.7 T for each sample. RNA was subsequently extracted to determine gene expression profiles. A significant negative correlation between N-acetyl metabolite and ACAN gene expression levels was observed; this provides further evidence of N-acetyl as a biomarker of cartilage degeneration. The alanine doublet was distinguished in the spectra of 15 of the 30 specimens of this study. Alanine can only be detected with HRMAS NMR spectroscopy when the collagen framework has been degraded such that alanine is sufficiently mobile to form a distinguished peak in the spectrum. Thus, HRMAS NMR spectroscopy may provide unique localized measurements of collagenous degeneration in OA cartilage. The identification of imaging markers that could provide a link between OA pathology and chondrocyte metabolism will facilitate the development of more sensitive diagnostic techniques and will improve methods of monitoring treatment for patients suffering from OA.

Dataset Information

High-resolution magic angle spinning NMR spectroscopy of human osteoarthritic cartilage.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets