Background/Purpose: Obesity is an important risk factor for knee OA, not only due to effects of excess adipose tissue on joint loading, but also due to potential metabolic effects. It is not known if metabolic differences in people with OA might contribute to OA progression. The purpose of this study was to use a metabolomics approach to determine if a metabolic signature could distinguish overweight and obese adults with knee OA who exhibited radiographic progression during an 18 month exercise and/or weight loss intervention from those who did not progress.

Methods: Urine samples collected from 24 overweight or obese participants in the Intensive Diet and Exercise for Arthritis (IDEA) trial at baseline and at 18 months of follow-up were selected from two subgroups (n=12 each): a group that exhibited radiographic progression of knee OA and an age, race, sex, and BMI matched group who did not progress. Progression was defined as a decrease in medial joint space width of ≥ 0.7mm from baseline to 18 months (knees flexed at a 15° angle using a positioning device and the x-ray beam centered on the joint space).  Non-progressors were defined as individuals who had a decrease in joint space width of ≤0.35mm.

Morning second void urine samples were collected at baseline and 18 months. After centrifuging and addition of internal standards, ¹H NMR spectra were acquired using a 950 MHz NMR spectrometer for each study sample and for a quality control  sample prepared by pooling individual samples NMR data was processed by automated integration over the spectral window, and bins were normalized to the total intensity for each spectrum. Principal component analysis (PCA) and orthogonal partial least square discriminate analysis (OPLS-DA) were used to reduce the dimensionality and enable visualization of the separation of progressors and non-progressors. NMR bins that distinguished the study phenotypes were determined based on inspection of loadings plots and variable importance plots.  Bins that distinguished the study groups were   mapped to corresponding metabolites. 

Results: The median age of this IDEA subgroup was 67 yrs. (range 60-78) and median BMI was 31.2 kg/m² (range 27.0-40.4).  The mean minimum JSW change was -1.03 (SD=0.29, range -1.7 to -0.76)mm for progressors and 0.05 (SD=0.28 range -0.26 to +0.68)mm for non-progressors. After applying PCA, two outliers (non-progressors) with high levels of urine glucose were excluded.  Using OPLS-DA, five urinary metabolites were determined that separated the progressors from non-progressors.  At baseline, relatively higher levels of hippurate and glycolate and lower levels of lysine were identified in progressors.  At 18 month follow-up, relatively higher levels of hippurate, glycolate, and sarcosine and lower levels of lysine and choline characterized the progressor group.  

Conclusion: Metabolic differences were found for the first time to correlate with radiographic progression in overweight and obese adults with knee OA. These results merit further investigation in a larger sample set. Given that hippurate is a gut-flora derived metabolite, differences in the gut microbiome could be contributing to OA progression.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/metabolomics-for-the-identification-of-urinary-biomarkers-in-knee-osteoarthritis-progression/