Open Access Research article

Biochemical markers of bone turnover and their association with bone marrow lesions

David J Hunter12*, Michael LaValley1, Jiang Li1, Doug C Bauer3, Michael Nevitt3, Jeroen DeGroot4, Robin Poole5, David Eyre6, Ali Guermazi1, Daniel Gale7, Saara Totterman7 and David T Felson1

Author Affiliations

1 Department of Epidemiology and Biostatistics, Boston University School of Medicine, Albany Street, Boston, Massachusetts 02118, USA

2 New England Baptist Hospital, Parker Hill Avenue, Boston, Massachusetts 02120, USA

3 University of California at San Francisco, Berry Street, San Francisco, California 94107, USA

4 TNO Quality of Life, Business Unit Biomedical Research, Zernikedreef 9, 2333 CK Leiden, The Netherlands

5 Joint Diseases Laboratory, McGill University, Cedar Avenue, Quebec, H3G 1A6, Canada

6 Department of Orthopaedics and Sports Medicine, University of Washington, NE Pacific Street, Seattle, Washington 98195, USA

7 Virtualscopics, Linden Oaks, Rochester, New York 14625, USA

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Arthritis Research & Therapy 2008, 10:R102  doi:10.1186/ar2494

Published: 29 August 2008



Our objective was to determine whether markers of bone resorption and formation could serve as markers for the presence of bone marrow lesions (BMLs).


We conducted an analysis of data from the Boston Osteoarthritis of the Knee Study (BOKS). Knee magnetic resonance images were scored for BMLs using a semiquantitative grading scheme. In addition, a subset of persons with BMLs underwent quantitative volume measurement of their BML, using a proprietary software method. Within the BOKS population, 80 people with BMLs and 80 without BMLs were selected for the purposes of this case-control study. Bone biomarkers assayed included type I collagen N-telopeptide (NTx) corrected for urinary creatinine, bone-specific alkaline phosphatase, and osteocalcin. The same methods were used and applied to a nested case-control sample from the Framingham study, in which BMD assessments allowed evaluation of this as a covariate. Logistic regression models were fit using BML as the outcome and biomarkers, age, sex, and body mass index as predictors. An receiver operating characteristic curve was generated for each model and the area under the curve assessed.


A total of 151 subjects from BOKS with knee OA were assessed. The mean (standard deviation) age was 67 (9) years and 60% were male. Sixty-nine per cent had maximum BML score above 0, and 48% had maximum BML score above 1. The only model that reached statistical significance used maximum score of BML above 0 as the outcome. Ln-NTx (Ln is the natural log) exhibited a significant association with BMLs, with the odds of a BML being present increasing by 1.4-fold (95% confidence interval = 1.0-fold to 2.0-fold) per 1 standard deviation increase in the LnNTx, and with a small partial R2 of 3.05. We also evaluated 144 participants in the Framingham Osteoarthritis Study, whose mean age was 68 years and body mass index was 29 kg/m2, and of whom 40% were male. Of these participants 55% had a maximum BML score above 0. The relationship between NTx and maximum score of BML above 0 revealed a significant association, with an odds ratio fo 1.7 (95% confidence interval = 1.1 to 2.7) after adjusting for age, sex, and body mass index.


Serum NTx was weakly associated with the presence of BMLs in both study samples. This relationship was not strong and we would not advocate the use of NTx as a marker of the presence of BMLs.