Development and validation of novel techniques to quantify chronic pain in dogs using osteoarthritis as a spontaneous pain model

Osteoarthritis (OA) is an incurable chronic disease affecting up to 20% of dogs over one year of age [1]. Currently the severity of associated chronic pain and efficacy of disease management is difficult to gauge. We propose to develop and validate novel techniques for measuring dogs' subjective experience of chronic pain. Chronic pain is under-investigated in companion animals and the development of measures of pain neurobiology and hyperalgesia has not been paired with investigations into animals' affective pain experiences. Existing animal pain models lack face validity and are too reliant on reflex tests or innate behaviours rather than outcome measures that require complex processing by cerebral cortical structures that likely participate in the conscious perception of pain. Further, most models have little fidelity with naturally occurring painful disease. Using OA as a naturally occurring disease in dogs that is similar to the human condition [2] provides a clinically relevant pain model that can be integrated into translational research to benefit both man and animal. New techniques that will be developed and validated include 1) Complex and detailed ethograms of normal and pain related behaviour using sophisticated video based behavioural algorithms that can detect subtle changes in posture and movement; 2) Application of novel 'cognitive bias' techniques to probe the relationship between chronic pain and affective state. In humans, affective state is related to 'biases' in cognition (e.g. negative states are related to increased threat detection and negative judgements of ambiguous stimuli). The same relationship appears to exist in animals [3]. We hypothesise that dogs experiencing greater pain will be in a more negative affective state and show greater defensive responses to both threatening and ambiguous stimuli. A population of client-owned dogs with different severities of chronic OA will be enrolled into the study as well as matched case controls. The novel behavioural measures of chronic pain will be evaluated against currently used validated measures of OA pain in dogs, such as force plate techniques and accelerometry. Using these new and existing measures, we will also investigate the effectiveness of non-steroidal anti-inflammatory drugs (NSAIDs) commonly used in OA treatment. NSAIDs differ in their selectivity for enzymes that catalyse the inflammatory mediators that result in pain. Different dosing strategies are also recommended. Objective comparison of drug efficacy and dosing strategies is impeded by a lack of sensitive and relevant measures for quantifying changes in chronic pain. Our study aims to provide such measures. We will also begin scoping investigations into the integrity of Diffuse Noxious Inhibitory Control (DNIC) in dogs with OA as a potential behavioural marker of NSAID analgesic efficacy. Altered DNIC has been proposed as a mechanism that may underlie chronic pain conditions. The development of techniques to measure the efficacy of DNIC in dogs with OA could provide a novel tool to assess the severity of chronic pain and the efficacy of analgesia. The student will be trained by Pfizer and Bristol University in behavioural techniques and pharmacotherapy associated with chronic OA. They will gain experience of field data collection and develop communication skills with a wide range of groups; academic, clinical, commercial, public. Pfizer manufacture NSAIDs for the management of OA in dogs. Project outcomes will allow the company to more effectively evaluate their products and facilitate the development of evidence based dosing regimens. We will apply methods and new knowledge from this project to other species and disease conditions, benefiting both clinical and fundamental pain research. [1] Johnston S (1997), Vet Clin NA, Small Anim Pract, 27, 699-723; [2] Clements et al. (2006), Arthritis Res Ther 8, R158; [3] Mendl et al (2009), Appl. Anim. Behav. Sci. 118, 161-181