Characterising the biology of neurofilament light protein as a translational biomarker for Huntington's disease

亨廷顿病（HD）是一种致命的神经退行性疾病，其特征在于大量严重的运动、认知和精神症状。它是由亨廷顿蛋白基因中的CAG重复序列扩展的遗传引起的1。症状通常在30至50岁之间出现，在发病前数十年发生潜在的病理变化2。这些标志物已与后来的认知，运动和功能标志物一起用于开发HD综合分期系统（HD-ISS），这是一个用于临床试验和研究的突变亨廷顿蛋白（mHTT）基因载体的框架3。虽然目前没有可用的疾病修饰疗法，但开发管道中存在许多潜在的候选药物。然而，这些潜在治疗的成功可能受到缺乏生物学工具的限制，无法在短时间内灵敏地测量临床获益。在临床表现之前，HD的疾病进展仅通过基底节尾状核和壳核内脑萎缩的MRI测量来标记3。由于脑萎缩的缓慢速率、在疾病的最早阶段脑损失的假定不可逆性质以及罕见疾病（如HD）的试验样本量较小，因此准确测量潜在治疗疗效具有挑战性。此外，萎缩被认为是在分子水平上的病理变化之前4。验证一个可访问的，敏感的分子生物标志物将被证明是非常有用的，无论是作为一种手段，丰富的HD-ISS，以增加粒度的早期预显阶段，并作为一个潜在的替代终点，为未来的疾病修改临床试验。神经丝光（NfL）已成为一个有前途的候选人，它作为神经元损伤的指标，可在CSF和血液中测量，并与HD 5的多个临床严重程度评分显着相关。此外，CSF中的NfL水平已被证明在脊髓性肌萎缩症儿童的神经保护性治疗中降低，从而提供了一个衡量神经退行性变的持续速度的指标6。我的博士项目旨在探索NfL作为亨廷顿病的翻译生物标志物。这一目标将通过两个并行的办法来实现：利用观察性研究数据和计算方法研究NfL作为mHTT携带者的预后生物标志物，同时研究NfL作为诱导多能干细胞（iPSC）衍生的HD细胞模型的有效性和安全性生物标志物的活力。在计算水平，将合并和协调来自多项观察性研究的现有数据，在根据HD-ISS框架3进行分类之前。这将产生迄今为止最大的NfL HD数据集，允许在疾病的整个进展过程中映射NfL变异，代表不同的年龄和CAG重复长度。然后将进行回顾性分析，以研究NfL作为HD预后生物标志物的潜力，并对其未来在临床试验中作为替代终点的潜在用途产生重大影响。该项目将建立在我与Lauren Byrne博士的第三次轮换期间获得的技能基础上，在此期间，我学会了在Stata中编码，以回顾性分析mHTT携带者队列中的血浆NfL水平。我将开发我在这个旋转期间写的代码，同时也学习MATLAB开发一个新的协调协议NfL测量跨studies.In并行，NfL动力学将在体外研究，以评估其作为安全生物标志物和药物疗效的测量在HD细胞模型的潜力.将使用2D iPSC衍生的纹状体细胞培养物和3D皮质-纹状体类器官，其中将收集细胞和培养基，并且随后将从培养基中分离细胞外囊泡（EV）。2D模型将利用中等多刺神经元（MSN）和皮质神经元（MSNs）。

Huntington's disease (HD) is a fatal neurodegenerative disorder characterized by a multitude of severe motor, cognitive, and psychiatric symptoms. It is caused by the inheritance of an expanded CAG repeat in the huntingtin gene1. Symptoms typically manifest between the ages of 30 and 50 years old, with underlying pathological changes occurring decades prior to onset2. These landmarks have been utilized alongside later cognitive, motor and functional markers to develop the HD Integrated Staging System (HD-ISS), a framework for characterising mutant huntingtin (mHTT) gene carriers for clinical trials and research purposes3.Whilst there are currently no disease-modifying therapies available, numerous potential drug candidates exist within the developmental pipeline. However, the success of these potential treatments may be limited by the absence of biological tools to sensitively measure clinical benefit across short time periods. Prior to clinical manifestation, disease progression in HD is marked solely by MRI measurements of brain atrophy within the caudate and putamen of the basal ganglia3. Accurate measurement of potential therapeutic efficacy is challenging due to the slow rate of brain atrophy, the posited irreversible nature of brain loss in the earliest phases of the disease, and the small trial sample size in rare diseases such as HD. Moreover, atrophy is thought to be preceded by pathological changes at the molecular level4. The validation of an accessible, sensitive molecular biomarker would prove extremely useful both as a means of enriching the HD-ISS to add granularity to the early premanifest stages, and as a potential surrogate endpoint for future disease modifying clinical trials. Neurofilament light (NfL) has emerged as a promising candidate for this; it serves as an indicator of neuronal damage, measurable in both CSF and blood, and is significantly correlated with multiple clinical severity scores in HD5. Moreover, NfL levels in CSF have been shown to decrease in response to neuroprotective treatment in children with spinal muscular atrophy, thus providing a measure of the ongoing rate of neurodegeneration6.My PhD project seeks to explore NfL as a translational biomarker for Huntington's disease. This aim will be pursued through two concurrent approaches: utilizing observational study data and computational methods to investigate NfL as a prognostic biomarker in mHTT carriers, whilst simultaneously investigating NfL's viability as both an efficacy and safety biomarker in induced pluripotent stem cell (iPSC) derived cell models of HD.At the computational level, existing data from multiple observational studies will be combined and harmonised, before being categorised according to the HD-ISS framework3. This will generate the largest NfL HD dataset to date, allowing NfL variations to be mapped throughout the progression of the disease, representative of diverse ages and CAG repeat lengths. Retrospective analyses will then be performed to investigate NfL's potential as a prognostic biomarker in HD, with significant implications for its potential future use as a surrogate endpoint in clinical trials. The project will build upon the skills I acquired during my third rotation with Dr Lauren Byrne, in which I learnt to code in Stata to retrospectively analyse plasma NfL levels within a cohort of mHTT carriers. I will develop the code I wrote during this rotation whilst also learning MATLAB to develop a novel harmonization protocol for NfL measurements across studies.In parallel, NfL dynamics will be investigated in vitro to assess its potential as both a safety biomarker and measure of drug efficacy in cell models of HD. Both 2D iPSC derived striatal cell cultures and 3D cortico-striatal organoids will be utilized, where cells and media will be collected, and extracellular vesicles (EVs) will be subsequently isolated from the media. The 2D models will utilize medium spiny neurons (MSNs) and cortical