Post-traumatic osteoarthritis: from mouse models to clinical trials

Nat Rev Rheumatol. 2013 Aug;9(8):485-97. doi: 10.1038/nrrheum.2013.72. Epub 2013 May 21.

Abstract

Osteoarthritis (OA), the most common of all arthropathies, is a leading cause of disability and has a large (and growing) worldwide socioeconomic cost. Despite its burgeoning importance, translation of disease-modifying OA therapies from the laboratory into clinical practice has slowed. Differences between the OA models studied preclinically and the disease evaluated in human clinical trials contribute to this failure. Most animal models of OA induce disease through surgical or mechanical disruption of joint biomechanics in young individuals rather than the spontaneous development of age-associated disease. This instability-induced joint disease in animals best models the arthritis that develops in humans after an injurious event, known as post-traumatic OA (PTOA). Studies in genetically modified mice suggest that PTOA has a distinct molecular pathophysiology compared with that of spontaneous OA, which might explain the poor translation from preclinical to clinical OA therapeutic trials. This Review summarizes the latest data on potential molecular targets for PTOA prevention and modification derived from studies in genetically modified mice, and describes their validation in preclinical therapeutic trials. This article focuses on how these findings might best be translated to humans, and identifies the potential challenges to successful implementation of clinical trials of disease-modifying drugs for PTOA.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Animals
  • Antirheumatic Agents / therapeutic use
  • Biomarkers / metabolism
  • Disease Models, Animal*
  • Genetic Engineering
  • Humans
  • Mice
  • Osteoarthritis / drug therapy
  • Osteoarthritis / etiology*
  • Osteoarthritis / metabolism
  • Translational Medical Research*
  • Wounds and Injuries / complications*

Substances

  • Antirheumatic Agents
  • Biomarkers