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Innovative Statistical Models for Development of First HuntingtonÃÂ¢ÃÂÃÂs Disease Progression Risk Assessment Tool

用于开发第一个亨廷顿病进展风险评估工具的创新统计模型

基本信息

批准号：
10172189
负责人：
Tanya Pamela Garcia
金额：
$ 18.19万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-01 至 2022-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10172189
关键词：
Innovative Statistical Models Development First

项目摘要

7. Project Summary/Abstract Huntington's disease (HD) is a progressive, neurodegenerative disorder that can be genetically diagnosed years before clinical symptoms onset. This presents groundbreaking opportunities to learn the overall, dynamic progression of HD which is critical to the timing of therapeutic interventions and design of eﬀective clinical trials. Despite advancements in this area, signiﬁcant gaps exist about the transitional period from premanifest to manifest HD, particularly how and when overt clinical symptoms and neurological deterioration develop. As part of the candidate's long-term goal to become an independent, lead expert biostatistician for neurodegenerative diseases, the overarching goal of this K01 is to acquire training in the disease-related background and quantitative analytical skills to develop innovative methods that target new discoveries of HD progression. The candidate, Dr. Tanya P. Garcia, is a Huntington's Disease Society of America (HDSA) Human Biology Project Fellow (2013-2015) and has assembled a team of outstanding mentors and collaborators who will provide training to acquire the skills she lacks for an independent, biostatistically-focused, neuroscience career. Her two primary mentors are Dr. Karen Marder and Dr. Raymond J. Carroll. Dr. Marder is the Sally Kerlin Professor of Neurology at Columbia University with over 300 publications in behavioral neurology, neuroepidemiology and neurodegenerative diseases including Huntington's, Alzheimer's, Parkinson's and HIV dementia. Dr. Carroll is Distinguished Professor of Statistics at Texas A&M University with over 400 publications and 5 books in multiple statistics areas, particularly in those needed for this proposal. To conduct high-level research that ﬁlls signiﬁcant gaps about HD progression knowledge, Dr. Garcia proposes in-depth training (i) To learn the latest developments and challenges in clinical and neurological understanding of HD to ﬁne-tune statistical methodology; (ii) To obtain proﬁciency in analysis of correlated, longitudinal, big data; and (iii) To develop programming expertise to make the proposed methods accessible to neuroscience investigators in user-friendly software. Training in these areas directly support Dr. Garcia's research aims which are (i) To improve prediction of HD motor-diagnosis by modeling the time-varying eﬀects of multiple clinical performance measures; (ii) To improve identiﬁcation of disease-relevant brain regions in relation to HD motor-diagnosis by modeling the spatial-temporal brain structure; and (iii) To develop the ﬁrst generation of a HD Progression Risk Assessment Tool (HD-PRAT). Expected research outcomes include models that support President Obama's Precision Medicine Initiative in that they adhere to “2P's” of the NIH New Strategic Vision of the “4P's” of Medicine: they will oﬀer promising ways to Predict the pattern and intensity of an individual's clinical and neurological changes over time; and increase the capacity to Personalize early intervention based on these learned predictions. Having the models available in user-friendly HD-PRAT is of high

7.项目总结/摘要亨廷顿氏病（HD）是一种进行性神经退行性疾病，可以在几年前进行基因诊断临床症状发作。这为了解HD的整体动态进展提供了开创性的机会这对治疗干预的时机和有效临床试验的设计至关重要。尽管取得了进步在这一领域，从预显到显显HD的过渡期存在重大差距，特别是如何和当出现明显的临床症状和神经系统恶化时作为候选人长期目标的一部分，成为神经退行性疾病的独立，领先的专家生物统计学家，本K 01的总体目标是获得疾病相关背景和定量分析技能方面的培训，以开发创新方法针对HD进展的新发现。候选人Tanya P. Garcia博士是一名亨廷顿病协会的成员美国（HDSA）人类生物学项目研究员（2013-2015），并组建了一个优秀的导师团队和合作者谁将提供培训，以获得她缺乏的技能，一个独立的，生物医学为重点，神经科学生涯她的两个主要导师是卡伦·马尔德博士和雷蒙德·J·卡罗尔博士。马德博士是哥伦比亚大学神经学教授萨莉·科林在行为神经学方面发表了300多篇论文，神经流行病学和神经退行性疾病，包括亨廷顿氏病、阿尔茨海默氏病、帕金森氏病和HIV痴呆。博士卡罗尔是杰出的统计学教授在得克萨斯州A&M大学与超过400出版物和5本书，多个统计领域，特别是本提案所需的领域。进行高水平的研究，关于HD进展知识的差距，加西亚博士建议进行深入的培训（i）了解最新的发展， HD的临床和神经学理解方面的挑战，以微调统计方法;（ii）为了获得专业知识，在相关的，纵向的，大数据的分析;和（iii）发展编程专业知识，使拟议的方法神经科学研究人员可以通过用户友好的软件访问。在这些领域的培训直接支持加西亚博士的研究目的是：（i）通过建模的时间变化的影响，以提高HD电机诊断的预测多个临床性能指标;（ii）改善与以下相关的疾病相关脑区域的识别：通过模拟时空大脑结构进行HD运动诊断;以及（iii）开发第一代 HD进展风险评估工具（HD-PRAT）。预期的研究成果包括支持总统的模型奥巴马的精准医学倡议，他们坚持“2 P的”国家卫生研究院新的战略愿景的“4P的”，医学：他们将提供更有前途的方法来预测个人的临床和神经系统疾病的模式和强度。随着时间的推移而变化;并根据这些学习到的预测增加个性化早期干预的能力。具有在用户友好的HD-PRAT中可用的模型具有高