Kinematic and dynamic gait compensations resulting from knee instability in a rat model of osteoarthritis

Samuel B Adams,Brian A Mata,Lori A Setton,Janet L Huebner,Virginia B Kraus,Daniel O Schmitt,Kyle D Allen,Mostafa A Gabr

doi:10.1186/ar3801

Abstract

IntroductionOsteoarthritis (OA) results in pain and disability; however, preclinical OA models often focus on joint-level changes. Gait analysis is one method used to evaluate both preclinical OA models and OA patients. The objective of this study is to describe spatiotemporal and ground reaction force changes in a rat medial meniscus transection (MMT) model of knee OA and to compare these gait measures with assays of weight bearing and tactile allodynia.MethodsSixteen rats were used in the study. The medial collateral ligament (MCL) was transected in twelve Lewis rats (male, 200 to 250 g); in six rats, the medial meniscus was transected, and the remaining six rats served as sham controls. The remaining four rats served as naïve controls. Gait, weight-bearing as measured by an incapacitance meter, and tactile allodynia were assessed on postoperative days 9 to 24. On day 28, knee joints were collected for histology. Cytokine concentrations in the serum were assessed with a 10-plex cytokine panel.ResultsWeight bearing was not affected by sham or MMT surgery; however, the MMT group had decreased mechanical paw-withdrawal thresholds in the operated limb relative to the contralateral limb (P = 0.017). The gait of the MMT group became increasingly asymmetric from postoperative days 9 to 24 (P = 0.020); moreover, MMT animals tended to spend more time on their contralateral limb than their operated limb while walking (P < 0.1). Ground reaction forces confirmed temporal shifts in symmetry and stance time, as the MMT group had lower vertical and propulsive ground reaction forces in their operated limb relative to the contralateral limb, naïve, and sham controls (P < 0.05). Levels of interleukin 6 in the MMT group tended to be higher than naïve controls (P = 0.072). Histology confirmed increased cartilage damage in the MMT group, consistent with OA initiation. Post hoc analysis revealed that gait symmetry, stance time imbalance, peak propulsive force, and serum interleukin 6 concentrations had significant correlations to the severity of cartilage lesion formation.ConclusionThese data indicate significant gait compensations were present in the MMT group relative to medial collateral ligament (MCL) injury (sham) alone and naïve controls. Moreover, these data suggest that gait compensations are likely driven by meniscal instability and/or cartilage damage, and not by MCL injury alone.

Highlights

Osteoarthritis (OA) results in pain and disability; preclinical OA models often focus on jointlevel changes
Weight and weight distribution During the experiment, weight increased in all animals; the weight of medial meniscus transection (MMT) rats increased more slowly than that of medial collateral ligament (MCL) sham or naïve animals (Figure 2, left; P = 0.011, P = 0.003, respectively)
Spatiotemporal gait characteristics Gait became progressively asymmetric in the MMT group with time (Figure 4, left)

Summary

Introduction

Osteoarthritis (OA) results in pain and disability; preclinical OA models often focus on jointlevel changes. Increased sensitivity to non-noxious mechanical stimuli, a condition known as tactile allodynia, has been observed in the OA-affected limb of preclinical OA models [11,12]. These behavioral assays are useful, a more complete behavioral analysis of rodent OA models would provide a clearer picture of the relationships between disease parameters and disease sequelae. Similar tools exist to assess rodent gait characteristics [18,19,20,21,22,23,24,25]; spatiotemporal evaluations of gait patterns (stance time balance and gait symmetry) and dynamic assessments of three-component group reaction force can be evaluated in both the preclinical OA model and the OA patient. A better understanding of gait compensations in combination with biologic markers of disease in rodent OA models will allow a better understanding of how disease parameters associate with disease sequelae

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