Completed Brain & Nervous System Mental Health

MICA: Partnership for Assessment and Investigation of Neuropathic Pain: Studies Tracking Outcomes, Risks and Mechanisms (PAINSTORM).

In plain English

AI plain-English summary

One in twelve people live with neuropathic pain—nerve damage from diabetes, chemotherapy, or HIV—yet existing drugs help only a minority and often cause severe side effects. The PAINSTORM consortium will follow thousands of people at risk of developing this condition, tracking them over years to uncover why some become severely disabled while others with identical nerve damage do not. This matters because neuropathic pain research has been fragmented: pharmacologists study drugs, psychologists study mood, and clinicians treat symptoms in isolation. PAINSTORM will integrate genetic analysis, tissue biopsies, brain and spinal cord imaging, remote monitoring, and psychosocial assessments into a single, multidimensional dataset. The goal is to identify biomarkers that measure pain objectively—something that does not currently exist—and to pinpoint which personal, social, and biological factors determine who gets worse and who recovers. If successful, the project could transform how neuropathic pain is diagnosed and managed. Clinicians might one day use a blood test or a brain scan to match each patient to the therapy most likely to work, rather than cycling through drugs by trial and error. The consortium will also build a national biobank of tissue samples and patient data, making these resources freely available to other researchers worldwide.

View original technical description
This consortium brings together experts in Neuropathic pain (NeuP). NeuP affects 8% of the population and is caused by damage to the sensory nervous system (through conditions such as diabetes, chemotherapy and HIV). It is increasingly common as a consequence of the ageing population, increasing levels of diabetes and enhanced cancer survival. NeuP has a major negative impact on quality of life. Unfortunately current management options are inadequate as they are only effective in a small subgroup of patients. Additionally, whilst NeuP impact is multidimensional, most research and clinical management in this area is separate rather than being interdisciplinary. They over emphasise pharmacological approaches, often associated with side effects, rather than taking a more holistic approach addressing the complex social and psychological aspects of NeuP. To rectify this situation we need to understand the mechanisms driving NeuP in patients. In order to do so, PAINSTORM will use a broad range of approaches cutting across traditional disciplinary boundaries, to uncover the causes of NeuP and understand how they interact. This inter-disciplinary collaboration will include people living with NeuP (embedding patient and public involvement), scientists from diverse clinical and scientific backgrounds, and industry expertise to help translate the research into effective, multifaceted interventions. Our focus will be on studying people at risk of NeuP and following their progress over time. We will use a number of established cohorts, as well as recruiting new participants, and harmonise outcomes with national scale community studies. A key question is understanding why some people are severely impacted by NeuP whilst others with a similar pattern of nerve damage are not. Hence we will identify the personal characteristics (such as age, gender and ethnicity), environmental/social and clinical factors which determine NeuP risk. We will identify and validate novel genetic risk factors for NeuP. Tissue samples and patient-derived cells will be used to validate molecular pathways contributing to chronic NeuP and help develop blood biomarkers. These samples will be stored and made available to other researchers via a biobank. We will optimise measures to assess NeuP, including sensory profiling, application of remote monitoring and assessment of psychosocial factors to understand the impact of pain on daily activities (from self-care to work) and important conditions that are often associated with chronic pain such as depression, anxiety and poor sleep. We will use innovative technologies, including brain, spinal cord and nerve imaging and electrophysiology, to directly assess the factors that drive NeuP. We will integrate this multi-dimensional dataset to understand the interaction between risk and protective factors. We will develop biomarkers, as a means to measure pain and how it changes over time, which can be applied to clinical practice and drug trials. We aim to improve targeting of existing therapies, as well as identifying and prioritising novel treatment targets. We will engage key stakeholder groups including health professionals, people living with NeuP and industry at the outset and throughout PAINSTORM. Results will be widely disseminated through development of accessible databases, lay summaries, an accessible biobank and ongoing training of scientists and clinicians both within and external to our consortium to enhance impact. Our aim is that PAINSTORM should transform lives through our understanding and future interdisciplinary management of NeuP.

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Researchers

Andrew Rice (Co-Investigator)Annina Schmid (Co-Investigator)Blair Smith (Co-Investigator)David Bennett (Principal Investigator)Douglas Steele (Co-Investigator)Geert Crombez (Co-Investigator)Harry Lidstone Hebert (Co-Investigator)Irene Tracey (Co-Investigator)Kathryn Martin (Co-Investigator)Lesley Colvin (Co-Investigator)Whitney Scott (Co-Investigator)

Related Research

Grants with similar aims, by meaning.

Partnership for Assessment and Investigation of Neuropathic pain: Studies Tracking Outcomes, Risks and Mechanisms (PAINSTORM). Imperial College London Phenotyping
Neurotechnology for Chronic Pain
Consortium to Research Individual, Interpersonal, and Social influences in Pain (CRIISP)
DOLORisk: Understanding risk factors and determinants for neuropathic pain
Stratifying Chronic Pain Patients By Pathological Mechanism- A Multimodal Investigation Using Functional MRI, Psychometric And Clinical Assessment

Original classification

Research Grant

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