MICA: Exploiting specialised pro-resolution molecule mediated analgesia to identify novel targets for the treatment of chronic pain

Osteoarthritis (OA) and diabetic neuropathy are often associated with chronic pain which, as highlighted by our PPIE representatives, hugely impacts upon daily life. Not everybody with these diseases experiences chronic pain, and understanding these differences may offer insight into new treatments. A family of natural molecules produced by the body (specialised pro-resolution molecules (SPMs)) have robust analgesic effects in animal models of pain, while healthy volunteers with lower levels of SPMs are more sensitive to pain. Crucially, we showed that people with OA who have lower levels of SPMs experience significantly more pain. The SPMs reduce pain by interfering with multiple signalling pathways, leading to strong analgesic effects. Although SPMs are quickly broken-down into inactive products, they have long-lasting effects - a process likely to be due to the modulation of molecules known to drive pain responses at the gene expression level. We have already identified gene pathways implicated in the effects of the SPMs on OA pain in people.
Aim: To identify the cellular and molecular processes that lead to the powerful and long-lasting analgesia produced by the SPMs and to use this information to identify new therapeutic approaches to improve the treatment of chronic pain.

Team: This new research is guided by our PPIE steering group, and is lead by a team which brings strength in chronic pain mechanisms, genetics of pain and experimental pain. The pharmaceutical company Eli Lilly brings expertise in analysing and integrating large-scale datasets to maximise the benefits of these valuable clinical datasets. The project also supports the career development of researcher co-investigator Dr P Gowler.

Experimental Plan: We will use in-house bioinformatic approaches to analyse our existing and newly acquired data to predict the specific molecules (known as microRNAs) which may regulate changes in gene expression associated with high versus low levels of SPMs and their relationships with chronic pain.
First we will collect blood from people with OA pain (and control non-OA group) to undertake a detailed analysis of microRNAs that are predicted to regulate the levels of genes associated with OA pain and levels of a specific stable molecule which is a precursor for many SPMs, known as 17-HDHA. Using existing computational tools we will identify the microRNAs associated with having high versus low levels of 17-HDHA and how this relates to the OA pain experienced. We will validate these findings in patients with a different type of chronic pain (diabetic neuropathic pain with and without pain) to identify commonality and differences between these two types of chronic pain, thus identifying targets that are specific to the diseases, and those shared between them. To focus on potential roles of these pathways in driving pain, computational analysis of existing microRNA datasets from joint tissue and synovial fluid already collected from people with OA (by our collaborator) will identify which microRNAs that we have identified are also present at the site of disease and the source of the pain.
Using experimental models and tools we will identify which of the clinically identified microRNAs are altered by 17-HDHA treatment in mice, supporting which pathways are likely candidates for novel therapeutics. Molecular tools specifically developed to manipulate the function of those microRNAs will be used to identify the miRNAs that mediate the effects of the 17-HDHA on excitatory sensory nerve activity that drives pain responses. This approach will prioritise the clinically identified microRNAs to those with the most potential for therapeutic development for people with chronic OA pain. The importance of this outcome was supported by our PPIE representatives, as people living with pain want the development of new treatments which reduce their existing pain and allows them to have a fuller and happier life experience.

Osteoarthritis (OA) is the leading cause of chronic pain. Specialised resolution molecules (SPMs) have robust analgesic effects in models of chronic pain, acting via microRNAs (miRNAs) to shut-down multiple pro-inflammatory signalling pathways to restore tissue homeostasis. Levels of the SPM precursor 17-HDHA are significantly associated with pain thresholds in healthy volunteers and levels of OA pain.
Aim: to identify the miRNAs critical to the analgesic effects of the SPMs to provide new strategies for OA pain treatment.
A clinical study will identify miRNAs associated with 17-HDHA levels and OA pain, with validation in people with diabetic neuropathy +/- pain. Bioinformatic analysis will categorise dataset commonality for the two conditions. Using a publicly available synovial fluid dataset we will focus on miRNAs both implicated in the effects of 17-HDHA and locally at the painful joint. The top 30 clinically relevant miRNAs will be mechanistically probed. Levels of 17-HDHA will be augmented in mice in the presence (and absence) of a clinically relevant model of OA pain behaviour, and blood levels of the top 30 clinically relevant miRNAs will be quantified to confirm which miRNAs are modified by 17-HDHA. Using microfluidic chambers for the culture of mouse sensory nerve axons we will quantify the effects of 17-HDHA on calcium (Ca2+) transients in cell bodies after axon terminals are stimulated with PGE2 plus capsaicin (to mimic hyperalgesia). The effects of manipulating (with inhibitors or mimics) 10-15 of the 17-HDHA modifiable miRNAs on evoked Ca2+responses (in the presence and absence of 17-HDHA) will confirm which miRNAs are essential for the inhibitory effects of 17-HDHA on sensory excitability.
The identification of the clinically and functionally relevant miRNAs that underpin SPM-mediated natural analgesia will provide crucial mechanistic understanding which will underpin the development of novel approaches for treating chronic OA pain.