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

MICA: Partnership for Assessment and Investigation of Neuropathic Pain: Studies Tracking Outcomes, Risks and Mechanisms (PAINSTORM).
MICA:神经病理性疼痛评估和调查伙伴关系:跟踪结果、风险和机制的研究 (PAINSTORM)。
批准号:
MR/W002388/1
负责人:
David Bennett
金额:
$461.28万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --

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中文摘要
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英文摘要
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.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
Classification of Painful or Painless Diabetic Peripheral Neuropathy and Identification of the Most Powerful Predictors Using Machine Learning Models in Large Cross-Sectional Cohorts
在大横截面队列中使用机器学习模型对疼痛或无痛糖尿病周围神经病变进行分类并识别最强大的预测因子
DOI: 10.21203/rs.3.rs-1074596/v1
发表时间: 2021
期刊:
影响因子: --
作者: [Baskozos G]
通讯作者: Baskozos G
DOI: 10.1186/s12911-022-01890-x
发表时间: 2022-05-29
期刊: BMC MEDICAL INFORMATICS AND DECISION MAKING
影响因子: 3.5
作者: [Baskozos, Georgios, Themistocleous, Andreas C., Hebert, Harry L., Pascal, Mathilde M., V, John, Jishi, Callaghan, Brian C., Laycock, Helen, Granovsky, Yelena, Crombez, Geert, Yarnitsky, David, Rice, Andrew S. C., Smith, Blair H., Bennett, David L. H.]
通讯作者: Bennett, David L. H.
The epidemiology of neuropathic pain: an analysis of prevalence and associated factors in UK Biobank
神经性疼痛的流行病学:英国生物银行的患病率和相关因素分析
DOI: 10.1101/2022.07.26.22278063
发表时间: 2022
期刊:
影响因子: --
作者: [Baskozos G]
通讯作者: Baskozos G
DOI: 10.1097/pr9.0000000000001115
发表时间: 2023-12
期刊: Pain reports
影响因子: 4.8
作者: []
通讯作者:
8
    Defining the primary afferent circuitry that drives neuropathic pain
    • 批准号:
      MR/T020113/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $268.27万
    • 财政年份:
      2020
    • 负责人:
      David Bennett
    • 依托单位:
    Using human IPSC derived nociceptors as a cellular model to investigate and therapeutically target Nav1.7
    • 批准号:
      BB/S006788/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $45.12万
    • 财政年份:
      2019
    • 负责人:
      David Bennett
    • 依托单位:
    The role of CASPR2 in regulating sensory neuronal excitability and chronic pain
    • 批准号:
      MR/M02394X/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $44.02万
    • 财政年份:
      2015
    • 负责人:
      David Bennett
    • 依托单位:
    Cold and Possibly Unbound Planets from Wide-Field Microlensing Surveys
    • 批准号:
      1211875
    • 项目类别:
      Standard Grant
    • 资助金额:
      $36.63万
    • 财政年份:
      2012
    • 负责人:
      David Bennett
    • 依托单位:
    海外基金