Funded Projects

Chronic low back pain (cLBP) is recurrent and often nonresponsive to conservative treatments. Biomechanists, physical therapists, and surgeons each utilize a variety of tools and techniques to assess and interpret qualitative movement changes to understand potential mechanical and neurological sources of low back pain and as critical elements in their treatment paradigm. However, objectively characterizing and communicating this information is currently impossible, since clinically feasible (i.e., cost-effective, objective, and accurate) tools and quantitative benchmarks do not exist. This research addresses the challenge to improve cLBP outcomes through the use of unique, inexpensive, screen-printable, elastomer-based, nanocomposite, piezoresponsive sensors, which will be integrated into a SPInal Nanosensor Environment (SPINE) sense system to measure lumbar kinematics and provide an objective, quantitative platform for diagnosis, monitoring, and follow-up assessment of cLBP.

Knee osteoarthritis is one of the leading causes of disability worldwide, particularly among older adults. Despite multiple guidelines for care, most patients do not receive adequate treatment, and about 30% are prescribed long-term opioids. This award will be used to recruit and support an early career faculty member from a group underrepresented in biomedicine. This research, part of the Pain Management Effectiveness Research Network will evaluate conservative and more aggressive treatments for knee osteoarthritis and determine which individual-level factors contribute to treatment outcomes.

The University of California, San Francisco, as part of the Back Pain Consortium (BACPAC) Research Program, has established a Core Center for Patient-centric Mechanistic Phenotyping in Chronic Low Back Pain (REACH). The main goal of REACH is to define different subtypes (phenotypes) of chronic low back pain as well as to identify underlying pain mechanisms that can lead to effective, personalized treatments for patients across all population subgroups. To achieve this goal, REACH is, or will be, participating in several clinical trials, and it is imperative that the patients participating in these trials reflect the diversity of the U.S. population. Therefore, this project seeks to adapt methods that have successfully improved minority participation in other settings as well as to develop and deploy digital strategies that can promote recruitment and engagement of patients from marginalized populations.

Pain caused by degenerative joint diseases such as osteoarthritis (OA) is a major public health challenge that significantly affects quality of life for millions of Americans. There are no therapies available that offer pain relief and reverse the course of OA.  This project will use state-of-the-art technologies to create a neuronal connectivity and molecular map of the mouse knee joint, which will help identify molecular signatures that can be targeted for therapy. The research will include animals of different ages and of both sexes and test joint effects after exercise, in animals with OA, and after gene therapy that delivers an experimental OA medication directly to the joint.

This project's goal is to develop a completely noninvasive, precise, and durable treatment option for low back pain (LBP). Focused ultrasound (FUS) is a lower-risk, completely noninvasive modality that enables the delivery of spatially confined acoustic energy to a small tissue region (dorsal root ganglion [DRG]) under magnetic resonance (MR) imaging guidance to treat axial low back pain by neuromodulation. The central goal of this study is to demonstrate neuromodulation of the DRG with FUS to decrease nerve conduction; this treatment can be used to attenuate pain sensation. This exploratory study will demonstrate FUS neuromodulation of the DRG in pigs as assessed by somatosensory evoked potential and perform unique behavioral assessments indicative of supraspinal pain sensation, with the ultimate goal of translating this technology to patients with LBP. FUS could potentially replace current invasive or systemically detrimental treatment modalities.

Digital health interventions, such as virtual reality (VR) applications, have become available for the treatment and monitoring of numerous health conditions, including pain management. A current HEAL-funded study is evaluating the role of a therapeutic VR approach for chronic low back pain. However, racial and ethnic disparities exist in patient access and response to such VR applications, as well as in the incidence and reporting of pain. For example, non-Hispanic Blacks and Hispanics are more likely to report severe pain than non-Hispanic Whites, yet are less likely to have access to digital health information and interventions. To address these disparities, this project will develop a framework to advance diversity and inclusion in digital health trials and will seek to increase the proportion of non-Hispanic Black and Hispanic participants in the ongoing VR trial by tailoring recruitment materials and using novel artificial intelligence-driven cohort building tools.

This project will use a variety of technologies to create a comprehensive, 3D map of how sensory neurons activate knee joints in both mice and humans. The research will use imaging techniques and molecular approaches that measure gene expression. The findings will help create a comprehensive gene expression profile map of individual cells in the nerve fibers leading to the knee, as well as describe how nerve cells and joint cells interact at the most fundamental level. This research will generate a rich anatomical and molecular resource to understand the molecular basis of joint pain and guide the development of novel pain-relieving strategies.

 Quell Therapeutics uses the Optopatch platform for making all-optical electrophysiology measurements in neurons at a throughput sufficient for phenotypic screening. Using engineered optogenetic proteins, blue and red light can be used to stimulate and record neuronal activity, respectively. Custom microscopes enable electrophysiology recordings from 100’s of individual neurons in parallel with high sensitivity and temporal resolution, a capability currently not available with any other platform screening technology. Here, researchers combine the Optopatch platform with an in vitro model of chronic pain, where dorsal root ganglion (DRG) sensory neurons are bathed in a mixture of inflammatory mediators found in the joints of osteoarthritis patients. The neurons treated with the inflammatory mixture become hyperexcitable, mimicking the anticipated cellular pain response. Investigators calculate the functional phenotype of arthritis pain, which captures the difference in action potential shape and firing rate in response to diverse stimuli. The team will screen for small molecule compounds that reverse the pain phenotype while minimizing perturbation of neuronal behavior orthogonal to the pain phenotype, the in vitro “side effects.” The highest ranking compounds will be chemically optimized and their pharmacokinetic, drug metabolism, and in vivo efficacy will be characterized. The goal is to advance therapeutic discovery for pain, which may ultimately help relieve the US opioid crisis.

The goal of this proposal is to conduct a randomized controlled trial to evaluate the comparative effectiveness of conservative behavioral and nonopioid pharmacological treatments (Phase I) and, among nonresponders, the benefits of nonsurgical procedural interventions (Phase II). Aim 1 will evaluate the effectiveness of individual and combined online cognitive behavioral therapy (painTRAINER) and pharmacologic treatment (duloxetine) in improving pain and function for knee osteoarthritis (KOA) patients compared with standard of care. Aim 2 will determine if genicular nerve radiofrequency ablation or intra-articular injection of hyaluronic acid and steroid is more effective in improving outcomes than local anesthetic nerve block or standard of care and help establish the role of these interventional treatments in the overall management of pain in KOA patients. Aim 3 will test whether clinical and psychosocial phenotypes predict short- and long-term treatment response.

The HEAL-funded Sequenced-strategy for Improving Outcomes in People with Knee Osteoarthritis Pain (SKOAP) clinical trial evaluates behavioral, pharmacologic, and procedural interventions for patients with knee osteoarthritis pain. It is designed to mimic clinical care for these patients by first testing the effectiveness of conservative and nonsurgical interventions before considering surgical interventions. It is a large-scale clinical trial with a novel design that evaluates multidisciplinary treatments. Therefore, it offers a unique training opportunity for junior investigators from various disciplines who are interested in pain research and management. This mentoring award will allow a selected investigator to train junior investigators by providing protected, mentorship-focused time.

Inhibitors of the epigenetic enzymes histone deacetylases (HDACs) produce analgesic responses and are therefore therapeutic targets for pain. The research team recently resolved a PET imaging agent, [11C]Martinostat, that selectively binds to a subset of HDAC enzymes. A series of initial proof-of-concept clinical validation studies will be conducted to evaluate whether [11C]Martinostat PET is a sensitive biomarker to detect the typical (axial) chronic low back pain (cLBP). The research team will validate [11C]Martinostat PET’s ability to differentiate subtypes of pain by comparing axial cLBP and other cLBP patients with radiculopathy and longitudinally study subacute LBP patients (sLBP) to investigate whether there is a unique imaging signature that differentiates patients who develop cLBP and those who recover from low back pain. Using [11C]Martinostat to understand HDAC expression changes in chronic pain patients will validate an epigenetic drug target, refine patient selection based on HDAC expression, and facilitate proof of mechanism in developing novel analgesics.

Therapeutic virtual reality (VR) has emerged as a promising and evidence-based treatment modality for musculoskeletal pain, including chronic low back pain (cLBP). Users of VR wear a pair of goggles with a close-proximity stereoscopic screen that creates a sensation of being transported into lifelike, three-dimensional worlds. By stimulating the visual cortex while engaging other senses, VR modulates the user’s processing of nociceptive stimuli. Functional magnetic resonance imaging (fMRI) of the brain reveals that VR has similar effects on the sensory and insular cortex as opioids, and head-to-head trials show that VR achieves similar or greater analgesia as hydromorphone. Since there are few data regarding long-term efficacy and safety of VR in cLBP, this study will measure patient-reported outcomes, biometric outcomes, and opioid use in nonspecific cLBP patients under various experimental conditions using VR therapy.

This project will design and test optimized temporal patterns of stimulation to improve the efficacy of commercially available spinal cord stimulation (SCS) systems to treat chronic neuropathic pain. Researchers will build upon a validated biophysical model of the effects of SCS on sensory signal processing in neurons within the dorsal horn of the spinal cord to better understand how to improve the electrical stimulus patterns applied to the spinal cord. They will use sensitivity analyses to determine the robustness of stimulation patterns to variations in electrode positioning, selectivity of stimulation, and biophysical properties of the dorsal horn neural network. Researchers will demonstrate improvements from these new stimulus patterns by 1) measuring their effects on pain-related behavioral outcomes in a rat model of chronic neuropathic pain and by 2) quantifying the effects of optimized temporal patterns on spinal cord neuron activity. The outcome will be mechanistically derived and validated stimulus patterns that are significantly more efficacious than the phenomenologically derived standard of care patterns; these patterns could be implemented with either a software update or minor hardware modifications to existing SCS products.