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Evaluating the role of IL-17A as an orchestrator of peripheral-central cross talk in depressive symptoms

Evaluating the role of IL-17A as an orchestrator of peripheral-central cross talk in depressive symptoms
评估 IL-17A 作为抑郁症状中外周-中枢串扰协调者的作用
批准号:
MR/Z503988/1
负责人:
Jonathan Cavanagh
金额:
$203.16万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2024
资助国家:
英国
项目状态:
未结题
起止时间:
2024 至 --

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中文摘要
翻译
摘要以一种可以向普通受众宣传的方式,用简单的语言描述这项研究。这将向公众开放,申请者有责任确保内容适合出版。不超过4000个字符,包括空格和回车。大约30%-40%的免疫介导性炎症性疾病(IMID)患者,如银屑病,经历过抑郁。这些都会对临床结果、生活质量和治疗依从性产生负面影响。越来越多的证据表明,外周炎症可能是抑郁症的原因之一。具体地说,a)刺激外周炎症会导致缓解性复发的抑郁症状,b)与这种抑郁相关的神经连接异常与外周炎症有关,c)针对特定外周炎症成分(细胞因子)的生物治疗可以改善抑郁症状。在这种情况下,IL-23/IL-17细胞因子轴是其病理的中心,这一途径的抑制剂的成功应用证明了这一点。此外,在临床前和临床研究中,这个轴最近也被牵连到抑郁症的神经生物学中。我们的目标是揭示IMIDs背景下抑郁的潜在机制,该研究是通过一项有针对性的免疫干预研究,在人类免疫疾病中精巧特异的治疗性免疫拦截的背景下,使用最先进的成像技术检查大脑电路。我们将检验抑郁症与IL-17A介导的脑神经化学(谷氨酸)变化有关的假设。这反过来又会导致大脑奖赏和情绪中心区域的电生理、功能和结构的失调。我们将使用高场强(7T)磁共振波谱(MRS)以最高的可用精度测量大脑谷氨酸,并使用磁共振成像(MRI)将大脑功能和连接(MRI)的测量与神经放电(EEG)的测量融合在一起,这将使我们能够以最佳的时间和空间分辨率水平测量大脑网络。这些成像和电生理终点将在基线和6周时在50名PSD患者中进行测量,随机1:1接受抗IL17A抗体(Seckinumab)或安慰剂治疗。我们预测,抗IL17A治疗将与减少大脑谷氨酸表达和改善特定的EEG/MRI指标有关,我们认为这些指标是抑郁症状的机械标志。通过这样做,我们期望更广泛地了解对抑郁症的生物学理解,以期为这一重大的社会优先事项产生迫切需要的新的药物靶点。
英文摘要
SummaryDescribe the research in simple terms in a way that could be publicised to a general audience. This will be made publicly available and Applicants are responsible for ensuring that the content is suitable for publication. No more than, 4000 characters including spaces and returns.Approximately 30-40% of patients with immune-mediated inflammatory diseases (IMIDs), such as Psoriatic disease, experience depression. These negatively affect clinical outcomes, quality of life and treatment adherence. There is accumulating evidence that peripheral inflammation may contribute to the origins of depression. In particular, a) stimulation of the peripheral inflammation results in remitting-relapsing depressive symptoms b) abnormal neural connectivity linked to this depression is correlated with peripheral inflammation and c) biologic therapies targeting specific peripheral inflammation components (cytokines) improve depressive symptoms.In this proposal, Psoriatic disease (PsD) will be our IMID exemplar. In this condition, the IL-23/IL-17 cytokine axis is central to its pathology, as proven by successful application of inhibitors to this pathway. Moreover, this axis has also recently been implicated in the neurobiology of depression in both preclinical and clinical studies. We aim to uncover the mechanisms that underlie depression in the context of IMIDs, delivered by a focused immune intervention study examining brain circuitry using state of the art imaging in the context of exquisitely specific therapeutic immune interception in human immune disease. We will test the hypotheses that depression is associated with changes in brain neurochemistry (glutamate) mediated by IL-17A. This in turn drives dysregulation in electrophysiology, function, and structure of brain regions central to reward and emotion. We will use high field strength (7T) magnetic resonance spectroscopy (MRS) to measure brain glutamate with the greatest available precision and magnetic resonance imaging (MRI) to fuse measures of brain function and connections (MRI) with measures of nerve firing (EEG) that will allow us to measure brain networks at optimal levels of resolution in time and space. These imaging and electrophysiological endpoints will be measured at baseline and 6 weeks in 50 PsD patients, randomised 1:1 to treatment with anti-IL17A antibody(secukinumab) or placebo. We predict that anti-IL17A treatment will be associated with reduced brain glutamate expression and amelioration of specific EEG/MRI measures which we consider mechanistic markers of depressive symptoms. In doing so we expect to inform the biological understanding of depression more generally with view to generating urgently needed novel drug targets for this major societal priority.
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Experimental medicine approach linking brain and peripheral immune mechanisms mediating sickness behaviours in people with rheumatoid arthritis
  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 负责人:
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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  • 负责人:
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