Predicting Treatment Response with Sensory Phenotyping in Post-Traumatic Neuropathic Pain

An improved conflict avoidance assay reveals modality-specific differences in pain hypersensitivity across sexes

ABSTRACT

Abnormal encoding of somatosensory modalities (ie, mechanical, cold, and heat) are a critical part of pathological pain states. Detailed phenotyping of patients' responses to these modalities have raised hopes that analgesic treatments could one day be tailored to a patient's phenotype. Such precise treatment would require a profound understanding of the underlying mechanisms of specific pain phenotypes at molecular, cellular, and circuitry levels. Although preclinical pain models have helped in that regard, the lack of a unified assay quantifying detailed mechanical, cold, and heat pain responses on the same scale precludes comparing how analgesic compounds act on different sensory phenotypes. The conflict avoidance assay is promising in that regard, but testing conditions require validation for its use with multiple modalities. In this study, we improve upon the conflict avoidance assay to provide a validated and detailed assessment of all 3 modalities within the same animal, in mice. We first optimized testing conditions to minimize the necessary amount of training and to reduce sex differences in performances. We then tested what range of stimuli produce dynamic stimulus-response relationships for different outcome measures in naive mice. We finally used this assay to show that nerve injury produces modality-specific sex differences in pain behavior. Our improved assay opens new avenues to study the basis of modality-specific abnormalities in pain behavior.

Neuropathic Pain and Spinal Cord Injury: Management, Phenotypes, and Biomarkers

Chronic neuropathic pain after a spinal cord injury (SCI) continues to be a complex condition that is difficult to manage due to multiple underlying pathophysiological mechanisms and the association with psychosocial factors. Determining the individual contribution of each of these factors is currently not a realistic goal; however, focusing on the primary mechanisms may be more feasible. One approach used to uncover underlying mechanisms includes phenotyping using pain symptoms and somatosensory function. However, this approach does not consider cognitive and psychosocial mechanisms that may also significantly contribute to the pain experience and impact treatment outcomes. Indeed, clinical experience supports that a combination of self-management, non-pharmacological, and pharmacological approaches is needed to optimally manage pain in this population. This article will provide a broad updated summary integrating the clinical aspects of SCI-related neuropathic pain, potential pain mechanisms, evidence-based treatment recommendations, neuropathic pain phenotypes and brain biomarkers, psychosocial factors, and progress regarding how defining neuropathic pain phenotypes and other surrogate measures in the neuropathic pain field may lead to targeted treatments for neuropathic pain after SCI.

Maximizing treatment efficacy through patient stratification in neuropathic pain trials

Treatment of neuropathic pain remains inadequate despite the elucidation of multiple pathophysiological mechanisms and the development of promising therapeutic compounds. The lack of success in translating knowledge into clinical practice has discouraged pharmaceutical companies from investing in pain medicine; however, new patient stratification approaches could help bridge the translation gap and develop individualized therapeutic approaches. As we highlight in this article, subgrouping of patients according to sensory profiles and other baseline characteristics could aid the prediction of treatment success. Furthermore, novel outcome measures have been developed for patients with neuropathic pain. The extent to which sensory profiles and outcome measures can be employed in routine clinical practice and clinical trials and across distinct neuropathic pain aetiologies is yet to be determined. Improvements in animal models, drawing on our knowledge of human pain, and robust public-private partnerships will be needed to pave the way to innovative and effective pain medicine in the future.