Serum fatty acid chain length associates with prevalent symptomatic end-stage osteoarthritis, independent of BMI.

Higher body mass index (BMI) is associated with osteoarthritis (OA) in both weight-bearing and non-weight-bearing joints, suggesting a link between OA and poor metabolic health beyond mechanical loading. This risk may be influenced by systemic factors accompanying BMI. Fluctuations in concentrations of metabolites may mark or even contribute to development of OA. This study explores the association of metabolites with radiographic knee/hip OA prevalence and progression. A 1H-NMR-metabolomics assay was performed on plasma samples of 1564 cases for prevalent OA and 2,125 controls collected from the Rotterdam Study, CHECK, GARP/NORREF and LUMC-arthroplasty cohorts. OA prevalence and 5 to 10 year progression was assessed by means of Kellgren-Lawrence (KL) score and the OARSI-atlas. End-stage knee/hip OA (TJA) was defined as indication for arthroplasty surgery. Controls did not have OA at baseline or follow-up. Principal component analysis of 227 metabolites demonstrated 23 factors, of which 19 remained interpretable after quality-control. Associations of factor scores with OA definitions were investigated with logistic regression. Fatty acids chain length (FALen), which was included in two factors which associated with TJA, was individually associated with both overall OA as well as TJA. Increased Fatty Acid chain Length is associated with OA.

Osteoarthritis year in review 2018: biomarkers (biochemical markers).

OBJECTIVE: The aim of this narrative review is to summarize important findings from biochemical marker studies relevant to osteoarthritis (OA) in the context of new discoveries and clinical and scientific need. DESIGN: We conducted a systematic search of electronic medical databases (Embase, Medline, Web of Science, Cochrane central) between 01-03-2017 and 31-03-2018. The search was restricted to human studies, English language and full text available publications while reviews were excluded. Only papers describing protein based biomarkers measured in human body fluids (blood, urine and synovial fluid (SF)) were included. Of the 992 papers, 86 were reviewed here, with inclusion primarily based on relevance to OA biochemical markers. RESULTS: This review highlights a selection of studies based on their quality and perceived importance to the field mainly including those that1 evaluate prognostic value of biomarkers for OA progression (i.e., biomarkers reflecting change in composition of joint tissues and biomarkers of inflammation)2, help in assessment of intervention efficacy, and3 are innovative and uncover new candidate biomarkers, or use new approaches in biomarker discovery. CONCLUSIONS: Key findings and implications for possible clinical utility of biochemical markers are summarized and discussed. Given the paucity of robust biomarkers within the field, and the heterogeneity of the condition, enormous works are needed for development and validation of novel and clinically applicable biomarkers to reduce the impact of this highly prevalent and debilitating condition.

Development of a prediction model for future risk of radiographic hip osteoarthritis.

OBJECTIVE: To develop and validate a prognostic model for incident radiologic hip osteoarthritis (HOA) and determine the value of previously identified predictive factors. DESIGN: We first validated previously reported predictive factors for HOA by performing univariate and multivariate analyses for all predictors in three large prospective cohorts (total sample size of 4548 with 653 incident cases). The prognostic model was developed in 2327 individuals followed for 10 years from the Rotterdam Study-I (RS-I) cohort. External validation of the model was tested on discrimination in two other cohorts: RS-II (n = 1435) and the Cohort Hip and Cohort Knee (CHECK) study (n = 786). RESULTS: From the total number of 28 previously reported predictive factors, we were able to replicate 13 factors, while 15 factors were not significantly predictive in a meta-analysis of the three cohorts. The basic model including the demographic, questionnaire, and clinical examination variables (area under the receiver-operating characteristic curve (AUC) = 0.67) or genetic markers (AUC = 0.55) or urinary C-terminal cross-linked telopeptide of type II collagen (uCTX-II) levels (AUC = 0.67) alone were poor predictors of HOA in all cohorts. Imaging factors showed the highest predictive value for the development of HOA (AUC = 0.74). Addition of imaging variables to the basic model led to substantial improvement in the discriminative ability of the model (AUC = 0.78) compared with uCTX-II (AUC = 0.74) or genetic markers (AUC = 0.68). Applying external validation, similar results were observed in the RS-II and the CHECK cohort. CONCLUSIONS: The developed prediction model included demographic, a limited number of questionnaire, and imaging risk factors seems promising for prediction of HOA.