Understanding the Pathogenesis of Age-Related Knee Osteoarthritis

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URL: http://purl.stanford.edu/cp312hg2373

Abstract

Osteoarthritis (OA) is clinically characterized by the degeneration of articular cartilage and affects 27 million people in the United States alone. OA is an irreversible disease that can be particularly debilitating in load-bearing joints such as the knee, and costs the U.S. over $185 billion per year in insurer and out-of pocket expenditures.. However, available treatments address the symptoms rather than the disease itself. The challenge to find disease-modifying treatments arises from the fact that OA typically remains symptomatically silent until degeneration progresses to the stage where only symptomatic treatment is viable. Biological, structural, and mechanical factors change prior to clinical symptoms, but the identification and validation of potential early markers have been confounded by the interaction of these factors in vivo.

Age is the single strongest risk factor in the development of knee OA. It is clear that changes in cartilage biology reflect a decreased ability for the cartilage to withstand forces and avoid breakdown. It has been shown that certain features in knee mechanics during walking change as one ages and progresses through OA, but it is unclear whether these same features can be prospectively used as markers for disease initiation and progression. This dissertation aimed to identify whether there are detectable kinematic, kinetic, and biological features that might precede cartilage changes to allow for a more thorough understanding of the pathogenesis of age-related knee OA as well as provide the most convincing evidence to date for what features could possibly be altered in clinical interventions to slow the progression of the disease. More specifically, the work presented in this dissertation studied the following aims:

The first aim was to identify the kinematic and kinetic features in ambulatory mechanics that exist across all asymptomatic populations and walking speeds, and to assess whether walking speed, age, gender, and body mass index are associated differences in walking mechanics. As part of this study, 121 asymptomatic subjects were asked to walk at 3 selfselected speeds (slow, normal, fast) and a linear mixed effects model was used to identify whether walking speed, age, gender, and body mass index were associated with differences in 78 gait features. It was found that nearly every feature was associated with variations in walking speed, supporting the notion that walking speed must always be considered when studying gait. In addition, several knee features were also affected by variations in demographic measures, including age affecting sagittal knee features, body mass index affecting frontal knee kinematics and kinetics, and gender affecting frontal knee kinematics. These results support the analysis of sagittal plane features (knee flexion angle at heelstrike, peak knee flexion angle during midstance, and peak knee flexion moment during midstance) in the context of age-related OA. In addition, the broader results will aid in the design of future studies, as well as clarify how walking speed, age, gender, and body mass index may act as potential confounders in small populations or in populations with insucient demographic variations for thorough statistical analyses.

The second aim was to test whether kinematic and kinetic features in knee mechanics are able to predict the progression of knee osteoarthritis in a population initially with knee OA. Gait mechanics during normal speed walking was collected for 16 subjects with medial knee osteoarthritis at baseline. Magnetic resonance imaging (MRI) was used at baseline and 5- year follow-up to calculate mean cartilage thickness at both time points. Linear regressions were used to identify specific kinetic and kinematic features that are prospectively associated with 5-year cartilage thickness change. Specifically, it was found that the first peak knee adduction moment (KAM1) at baseline was related to femoral cartilage change and the peak knee flexion moment (KFM) at baseline was related to tibial cartilage change. In addition, baseline knee flexion angle at heel-strike (KFAhs), peak knee flexion angle at mid-stance (KFAms), and femoral position during heel-strike (FPhs) were significantly associated with medial femoral and medial tibial cartilage thinning at the 5 year follow-up. This study provided new insight into the tibiofemoral variations in cartilage changes associated with walking kinetics by showing that baseline features in gait were associated with longitudinal cartilage change and thus disease progression.

The third aim was to test whether kinematic, kinetic, and biologic features in knee mechanics are able to predict early cartilage change in an asymptomatic population that is at risk for developing knee OA due to their age. Gait mechanics and serum cartilage oligomeric matrix protein after a mechanical stimulus (mCOMP) were collected for 38 subjects with no history of knee pain; MRI was used to calculate cartilage thickness at baseline and 7-year follow-up. Multiple linear regression models were used to show that several gait features are prospectively associated with cartilage change in this at-risk population. It was shown that the knee flexion angle at heel-strike (KFAhs) was the only kinematic feature that was predictive of cartilage change. In addition, the peak knee extension moment (KEM) and first peak knee adduction moment (KAM1) were the kinetic features that were most strongly correlated with femoral cartilage change over time. Finally, the serum concentration of cartilage oligomeric matrix protein 5.5 hours after a mechanical stimulus (mCOMP at 5.5 hrs) predicted medial tibial anterior cartilage thickness change. These findings further support the hypothesis that knee OA is a disease that is heavily impacted by the location and magnitude of mechanical loads and that there is a great potential for mechanical and biological markers in assessing patients’ relative risk for cartilage change in knee OA.

The fourth aim was to assess whether kinematic, kinetic, and biologic features can be combined to further improve the prediction of cartilage thickness change in knee OA. A series of multiple linear regressions were used in the progression cohort (16 subjects) to show that the kinematic, kinetic, and biological markers are not redundant in predicting cartilage change. That is, markers from all three of these categories can be combined to improve the prediction of knee OA progression. In addition, it was shown that mechanical features defined in different anatomical planes can be used to improve the prediction of early cartilage change in the at-risk cohort (38 subjects), which allows for a more complete description of the loading regime at the knee that may contribute to knee OA.

The fifth aim was to assess the nature of time-based changes in gait in a population that is at increased risk for OA initiation. Gait mechanics for 41 subjects with no history of knee pain were collected at baseline and 7-year follow-up to analyze longitudinal changes in walking mechanics that occur as subjects age. Mixed effects linear regression models were used to reveal that subjects tend to decrease their adduction moments (KAM1, KAM2). This indicates that the difference in knee moments between subjects with different disease status is attributable to the process of aging and likely OA itself, as the changes in knee moments were also shown to be associated with cartilage change over the 7-year follow-up period. This shows that these gait changes are not only due to an aging process, but are indeed associated with a breakdown of tissues that occurs in OA. In addition, this study revealed that subject tended to flex their knees (KFAhs, KFAms) more as they age, even after adjusting for their reductions in walking speed over time. This is consistent with the risk for cartilage change in the two previous aims, indicating that the knee flexion angle may be the best target for gait interventions aimed at slowing age-related changes in cartilage thickness and potentially early OA.

In conclusion, this dissertation presents five studies over three cohorts that elucidate the pathomechanism of age-related knee OA. The work provides a rigorous basis to understand the potential confounding factors in gait analysis, identifies potential kinematic, kinetic, and biological markers for cartilage change in subjects with OA and ”at-risk” for OA initiation, tests the value of combining these markers in predicting cartilage change, and clarifies the nature of gait changes in the context of early OA. Together, the results presented in this dissertation revealed novel insights into the nature of age-related knee OA and offer great potential for the study and design of clinical interventions.

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