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

亨廷顿氏病（HD）是一种致命的神经退行性疾病，其特征是多种严重的运动、认知和精神症状。它是由亨廷顿蛋白基因中扩增的CAG重复序列遗传引起的。症状通常在30岁至50岁之间出现，潜在的病理改变在发病前几十年就发生了。这些标志与后来的认知、运动和功能标记一起用于开发HD综合分期系统（HD- iss），这是一种用于临床试验和研究目的的表征突变亨廷顿蛋白（mHTT）基因携带者的框架3。虽然目前没有可用的疾病修饰疗法，但许多潜在的候选药物存在于开发管道中。然而，这些潜在的治疗方法的成功可能会受到限制，因为缺乏生物工具来敏感地测量短时间内的临床益处。在临床表现之前，HD的疾病进展仅通过基底节区尾状核和壳核内脑萎缩的MRI测量来标记3。由于脑萎缩速度缓慢，在疾病的早期阶段假定脑损失的不可逆性，以及在罕见疾病（如HD）中试验样本量小，因此准确测量潜在的治疗效果具有挑战性。此外，萎缩被认为是在分子水平上的病理改变之前发生的。一种可获得的、敏感的分子生物标志物的验证将被证明是非常有用的，无论是作为一种丰富HD-ISS的手段，以增加早期预表现阶段的粒度，还是作为未来疾病修饰临床试验的潜在替代终点。神经丝光（NfL）已成为一种很有希望的候选方法；它可作为神经元损伤的指标，在脑脊液和血液中均可测量，并与HD5的多项临床严重程度评分显著相关。此外，脑脊液中NfL水平已被证明在脊髓性肌萎缩症儿童的神经保护治疗反应中降低，从而提供了持续神经变性率的测量方法6。我的博士项目旨在探索NfL作为亨廷顿病的转化生物标志物。这一目标将通过两种并行的方法来实现：利用观察性研究数据和计算方法来研究NfL作为mHTT携带者的预后生物标志物，同时研究NfL作为HD诱导多能干细胞（iPSC）衍生细胞模型的有效性和安全性生物标志物的可行性。在计算层面，来自多个观测研究的现有数据将被合并和协调，然后根据HD-ISS框架进行分类3。这将产生迄今为止最大的NfL HD数据集，允许在疾病进展过程中绘制NfL变异，代表不同年龄和CAG重复长度。然后将进行回顾性分析，以调查NfL作为HD预后生物标志物的潜力，这对其未来在临床试验中作为替代终点的潜在应用具有重要意义。该项目将建立在我与Lauren Byrne博士第三次轮转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。我将开发我在此轮换期间编写的代码，同时也学习MATLAB，以开发跨研究的NfL测量的新型协调协议。同时，将在体外研究NfL动力学，以评估其作为HD细胞模型的安全性生物标志物和药物疗效测量的潜力。将利用2D iPSC衍生纹状体细胞培养物和3D皮质纹状体类器官，收集细胞和培养基，随后从培养基中分离细胞外囊泡（ev）。二维模型将利用中棘神经元（msn）和皮质神经元

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