gms | German Medical Science

German Congress of Orthopedic and Trauma Surgery (DKOU 2017)

24.10. - 27.10.2017, Berlin

Dynamic mathematical model of OA progression

Meeting Abstract

  • presenting/speaker Vikram Sunkara - Konrad Zuse Institute Berlin, FU Berlin, Berlin, Germany
  • Tobias Haase - Charitè Universitätmedizin Berlin, Klinik für Unfall- und Wiederherstellungschirurgie, Labor für Unfallchirurgie, Berlin, Germany
  • Benjamin Kohl - Charitè Universitätmedizin Berlin, Klinik für Unfall- und Wiederherstellungschirurgie, Labor für Unfallchirurgie, Berlin, Germany
  • Carola Meier - Charitè Universitätmedizin Berlin, Klinik für Unfall- und Wiederherstellungschirurgie, Labor für Unfallchirurgie, Berlin, Germany
  • Patricia Bußmann - Charitè Universitätmedizin Berlin, Klinik für Unfall- und Wiederherstellungschirurgie, Labor für Unfallchirurgie, Berlin, Germany
  • Max von Kleist - Konrad Zuse Institute Berlin, FU Berlin, Berlin, Germany
  • Wolfgang Ertel - Charitè Universitätmedizin Berlin, Klinik für Unfall- und Wiederherstellungschirurgie, Labor für Unfallchirurgie, Berlin, Germany
  • Jessica Becker - Charitè Universitätmedizin Berlin, Klinik für Unfall- und Wiederherstellungschirurgie, Labor für Unfallchirurgie, Berlin, Germany

Deutscher Kongress für Orthopädie und Unfallchirurgie (DKOU 2017). Berlin, 24.-27.10.2017. Düsseldorf: German Medical Science GMS Publishing House; 2017. DocPO29-700

doi: 10.3205/17dkou879, urn:nbn:de:0183-17dkou8793

Published: October 23, 2017

© 2017 Sunkara et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.


Outline

Text

Objectives: Currently there is a lack of translation of typically univariate preclinical findings into effective therapies in osteoarthritis (OA). OA-associated factors form usually only parts of a complex regulatory network driving the progression of OA and there is a limiting understanding of how different OA-associated factors are dynamically interrelated. Mathematical modelling is becoming a standard tool to summarise and integrate the dynamical interplay of causal factors/hypothesis in disease progression. Our aim is to develop a mathematical model of the multifactorial processes involved in OA progression with the help of a standardised preclinical mouse model. The goal is to improve the understanding of dynamics of OA progression.

Methods: OA was surgically induced in C57Bl/6 mice by transection of the medial collateral ligament and the medial meniscus (MCL-MM). In sham mice, skin and underlying tissue were cut to visualise the medial collateral ligament without transection. Mice were sacrificed at different time points between 2 and 8 weeks post injury and OA progression was analysed. Using computer vision and automated segmentation we produced time resolved quantitative immunohistochemistry to establish and parametrise our mathematical model.

Results and Conclusion: Surgical destabilisation of the knee joint induced progressive degeneration of cartilage with first structural changes becoming visible as early as 2 week post injury. We observe that the cartilage height in OA mice decreases at 8µm per week and 3µm per week for sham mice. We observe a linear trend in cartilage degradation. On the contrary, we observe two drops in chondrocyte populations, one early until week 2 (a 20% decrease), then a later drop after week 6 (a 20% further decrease).

Using our mathematical model, two phases of OA progression become visible. We suggest that the first drop in chondrocytes decreases extra cellular matrix synthesis, creating an imbalance, which initiates cartilage erosion. The progressive degradation presumably leads to altered biomechanics which in return induces further reduction in chondrocytes. In principle, if we observe similar progression in a variant of OA in humans, our mathematical model, with extensions, could be used to stratify patients in terms of their OA stage, guiding clinical intervention (Figure 1 [Fig. 1]).