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SP0122 Biomechanical Joint Homeostasis: Mechanisms in Health, Aging and Oa
  1. T.P. Andriacchi
  1. Mechanical Engineering, Stanford University, Stanford, California, United States


This presentation will approach the analysis of OA by considering that the maintenance of healthy cartilage homeostasis as well as cartilage breakdown is dependent on the balance of mechanical, biological and structural components acting as an integrated system.

The Systems Model The conceptual basis of the systems model [1] can be illustrated (Fig. 1a) as an overall system that depends on the integrated behavior of mechanical, biological and structural (components) subsystems where each subsystem has an indeterminate level of complexity as follows: Thus healthy homeostasis is maintained when each of the subsystems operates in normal ranges (Fig. 1b).

Aging: An illustration of the Systems Model The risk of knee OA increases substantially above the age of 45 [3]. However, not all older subjects develop knee OA. Applying the model in Figure 1 helps to understand potential reasons for individual variations in the development of clinical symptoms of knee OA. Specifically, the aging-OA scenario described above can be placed in concrete terms by reducing the abstract subsystems to specific measures. It will be shown that neuromuscular changes with aging can cause specific kinematic changes in an older population that can lead to cartilage changes similar to OA. However, potential morphological variations in the organization of cartilage as well as biological variations can be mitigated or exacerbate the risk of developing OA during aging.

Stimulus-Response Model While logical, the in vivo system model described above introduces a level of complexity that cannot be addressed by deterministic methods. One method to address this level of complexity can be described as a stimulus-response model [4] where a known stimulus is applied and the response of the system or subsystems is measured as a means of assessing the characteristics of the system. Using this approach the state of health (homeostasis) of cartilage can be assessed by introducing a stimulus to the in vivo system and assessing the response of the subsystems as potential surrogate markers for cartilage health and the ultimate risk of progressing to clinical OA (Fig. 1c).

Stimulus-Response Example: Enhancing Biomarker Sensitivity An example of the application of the stimulus-response model was illustrated in a recent study [5] where a mechanical stimulus (30 minute walk) was introduced to provoke a short-term biological response in patients with early knee OA. Specifically, changes in serum concentrations of cartilage oligomeric matrix protein (COMP) levels were assessed before and after the mechanical stimulus and found that COMP level changes relative to resting concentrations after the walking stimulus predicted the amount of cartilage thinning at 5-year follow-up.

Conclusions 1. Cartilage health (homeostasis) is dependent on the complex interaction of mechanical, biological and structural components.

2. An aberration in one of the components can initiate conditions that lead to cartilage breakdown before symptoms are present that can be considered preclinical OA (Pre OA).

3. The rate of progression to clinical OA will depend on the state of the other subsystem components as illustrated with the aging example.

4. The conditions associated with Pre OA offer the greatest opportunity for prevention or reducing the rate of progressing to Clinical OA and detecting conditions associated with Pre OA should be a priority.

5. Applying a stimulus-response model can be a useful method of dealing with the overall complexity of OA and can enhance the potential for detecting treatment response as well as the risk of progressing to clinical OA.


  1. Andriacchi, et al, Framework for the in vivo Pathomechanics of Osteoarthritis at the Knee, In: Annals of Biomechanical Engineering, vol. 32, No. 3, 447-457, March 2004.

  2. Chu CR et al,: Early diagnosis to enable early treatment of pre-osteoarthritis, Chu et al. Arthritis Research & Therapy,14:212, 2012.

  3. Felson DT et al. The Prevalence of Knee Osteoarthritis in the Elderly, Arthritis and Rheumatism, Vol. 30, No. 8 (1987).

  4. Andriacchi T. Osteoarthritis: Probing knee OA as a system responding to a stimulus, Nature Reviews Rheumatology, 8(7): 371-372, 2012.

  5. Erhart-Hledik J, et al, relationship between mechanically-induced changes in serum cartilage oligomeric matrix protein (COMP) changes in cartilage thickness after 5 years, Osteoarthritis and Cartilage, 20(11): 1309-15, 2012.

Disclosure of Interest T. Andriacchi Grant/Research support from: NIH and VA, Conflict with: Stanford University

DOI 10.1136/annrheumdis-2014-eular.6164

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