Development of analytical methods for detecting biomarkers in biological matrices to explore the mechanism of neurodegenerative disorders.

开发用于检测生物基质中生物标志物的分析方法，以探索神经退行性疾病的机制。

• 批准号: 2758414
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2758414
• 关键词: Development; analytical; methods; detecting; biomarkers

The number of people affected by cognitive impairment has been gradually increasing. Moreover, the predictions show that this trend is likely to continue in the upcoming years and the currently available pharmacotherapies do not represent a sufficient solution. Furthermore, an early and accurate diagnosis of a specific disease is not possible, as the diagnostic methods are costly, highly invasive, and not available at most clinics. Similarly, the onset of several neurodegenerations is often gradual and inconspicuous, further impeding early diagnosis. The project aims to develop a low-cost and rapid analytical method for an effective diagnosis of various neurological disorders. Such a setup would be far easier to use in a clinical setting and would enable more frequent monitoring of the patient. This could allow not only an early and reliable diagnosis but also monitoring the disease progression and even assessing the patient`s responsiveness to different therapies. Furthermore, the developed method could be used as a screening tool to search for new biomarkers or to recruit suitable patients for clinical trials for novel therapies. The methods applied in the project will combine Nuclear Magnetic Resonance (NMR) analysis of blood with advanced multivariate statistical techniques. The initial study will use biobanked blood samples (from the OPTIMA and VITACOG trials which are already available in Oxford and ethical approval for this project has been granted) to search for Alzheimer`s disease (AD)-specific blood biomarkers. The subsequent use of mathematical algorithms will allow combining these markers into metabolite constellations leading to the formation of a panel of diagnostically-crucial biomarkers. The primary objective of this initial study will be to identify novel diagnostic biomarkers of AD and to determine if these biomarkers can allow diagnosis at the earliest stages of the disease. Similarly, the panel aims to enable monitoring of the disease progression as well as the efficacy of the administered pharmacotherapy. Subsequently, the available biological samples will be used for the development of protocols for multi-omics analysis, including primarily the mass spectroscopic metabolomics, glycomics, and lipidomics experiments. These measurements will allow evaluation of whether a multi-omics approach improves the developed diagnostic models. Furthermore, this novel multi-omics approach should enable elucidation of the related metabolic pathways and potentially explain the role of some prominent biomarkers in the onset and/or development of a specific cognitive impairment. The initial results from the AD cohort will be then translated into a new sample databank with the aim of assembling diagnostic biomarker panels not only for AD but also for other neurodegenerative disorders such as vascular dementia or multiple sclerosis. In the long-term, the method will be validated and importantly, the academic findings will be translated to an established clinical NMR platform (AXINON) resulting in a 'prototype' test. This part of the project will be conducted in collaboration with Oxford University's long-standing industrial partner Numares AG. The proposed research falls squarely within the analytical science and clinical technologies EPSRC research areas. In particular, the development of a novel biochemical test able to provide personalised diagnostic, prognostic, and disease activity information in patients with different neurological disorders is in ideal alignment with the EPSRC's health care technologies' priority theme of optimising treatment through effective diagnosis and patient-specific prediction.

受认知障碍影响的人数一直在逐渐增加。此外，预测表明，这一趋势很可能在未来几年继续下去，目前可用的药物疗法并不代表足够的解决方案。此外，对特定疾病的早期准确诊断是不可能的，因为诊断方法成本高、侵入性强，而且大多数诊所都没有这种方法。同样，几种神经退行性变的发病通常是渐进的和不明显的，进一步阻碍了早期诊断。该项目旨在开发一种低成本和快速的分析方法，以有效诊断各种神经疾病。这样的设置将更容易在临床环境中使用，并将能够更频繁地监视患者。这不仅可以进行早期可靠的诊断，还可以监测病情进展，甚至评估患者对不同疗法的反应。此外，开发的方法可用作筛选工具，以寻找新的生物标志物或招募合适的患者进行新疗法的临床试验。该项目应用的方法将结合血液的核磁共振分析和先进的多变量统计技术。最初的研究将使用生物库血液样本(来自牛津大学已经提供的Optima和VITACOG试验，该项目已获得伦理批准)来搜索阿尔茨海默病(AD)特异性血液生物标记物。随后数学算法的使用将允许将这些标记物组合成代谢物星座，从而形成一组对诊断至关重要的生物标记物。这项初步研究的主要目标将是识别AD的新诊断生物标记物，并确定这些生物标记物是否可以在疾病的早期阶段进行诊断。同样，该小组的目标是能够监测疾病的进展以及所用药物治疗的疗效。随后，可用的生物样本将用于开发多组学分析的方案，主要包括质谱代谢组学、糖组学和脂类组学实验。这些测量将允许评估多组学方法是否改善了已开发的诊断模型。此外，这种新的多组学方法应该能够阐明相关的代谢途径，并潜在地解释一些重要的生物标记物在特定认知障碍的发生和/或发展中的作用。AD队列的初步结果将被转换到一个新的样本数据库中，目的是不仅为AD，而且为其他神经退行性疾病，如血管性痴呆或多发性硬化症，组装诊断生物标志物小组。从长远来看，该方法将得到验证，重要的是，学术成果将被转化为一个已建立的临床核磁共振平台(AXINON)，从而进行一项“原型”测试。该项目的这一部分将与牛津大学的长期工业合作伙伴努马雷斯股份公司合作进行。拟议的研究正好属于分析科学和临床技术EPSRC的研究领域。特别是，开发一种能够为不同神经疾病患者提供个性化诊断、预后和疾病活动信息的新型生化测试，与EPSRC的医疗保健技术通过有效诊断和患者特定预测优化治疗的优先主题是理想的一致。