Redefining Chiari Type I Malformation through Genetically, Radiologically, and Clinically-Derived Endophenotypes that are Predictive of Long-Term Neurological Outcome

通过遗传、放射学和临床衍生的可预测长期神经系统结果的内表型重新定义 Chiari I 型畸形

• 批准号: 10629124
• 负责人: David Delmar Limbrick
• 金额: $ 18.69万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10629124
• 关键词: Affect; Aftercare; Area; Biological; Brain; Brain Stem; Cerebellar tonsil; Cerebrospinal Fluid; Characteristics; Chiari Malformation Type 1; Classification; Clinical; Clinical Management; Clinical/Radiologic; Code; Complex; Consensus; Data; Data Set; Derivation procedure; Development; Diagnosis; Dimensions; Disease; Disease Progression; Etiology; Expert Opinion; Feedback; Foundations; Genetic; Genetic Risk; Genomics; Headache; Heterogeneity; Image; Imaging Techniques; Individual; Machine Learning; Measures; Methods; Modeling; Morphology; Neurological outcome; Operative Surgical Procedures; Outcome; Outcome Measure; Pathogenesis; Pathology; Patient Outcomes Assessments; Patient-Focused Outcomes; Patients; Phenotype; Population; Postoperative Complications; Practice Management; Precision therapeutics; Process; Quality of life; Radiology Specialty; Recommendation; Reproducibility; Research; Rest; Role; Scheme; Spinal Cord; Structure; Surgical complication; Symptoms; Syringomyelia; Techniques; Testing; Tonsil; Universities; Variant; Vertebral column; Washington; brain overgrowth; clinical center; clinical practice; clinically relevant; comorbidity; disease heterogeneity; disease natural history; endophenotype; foramen magnum; genetic signature; genomic signature; improved; insight; malformation; neurosurgery; novel; outcome prediction; patient oriented; patient subsets; personalized medicine; predictive modeling; radiological imaging; skeletal; statistical and machine learning; surgery outcome; treatment response; treatment strategy; unsupervised learning

PROJECT SUMMARY Project 4: Redefining CM Using Multidimensional Endophenotypes Predictive of Long-Term Outcome Chiari type 1 malformation (CM) is a common and potentially debilitating disease typically defined by caudal displacement of the cerebellar tonsils below the foramen magnum. While radiographic CM may be found in 1% or more of the population, this population is extremely heterogeneous. Patients with classically defined CM may be clinically asymptomatic or present with severe symptoms such as debilitating headaches or signs of brainstem or spinal cord malfunction. Furthermore, patients with similar clinical presentations may have distinct genetic profiles and comorbid diagnoses that suggest differing etiologies contributing to superficially similar disease. Increasing recognition of this heterogeneity has emphasized the need for a data-driven approach to reclassifying traditionally-defined “CM.” Furthermore, advances in contemporary methods in imaging, genomics, and patient-centered clinical measures have substantially expanded opportunities for phenotyping complex diseases, such as CM. Leveraging Washington University’s unique strengths in these areas, the overall objective of Project 4 is to derive clinically relevant, multidimensional endophenotypes within traditionally- defined “CM” to inform clinical management and optimize long-term patient outcomes. In particular, we expect these multidimensional endophenotypes will both aid in outcome prediction and also provide new biological insights regarding disease pathogenesis, thereby supporting personalized treatment strategies. We intend to pursue this objective through three specific aims. In Aim 1, we will apply well-established unsupervised and semi- supervised clustering methods to multidimensional clinical and radiological data to derive novel clusters in a large, multicenter dataset. We will then externally validate those multidimensional endophenotypes in three external, multicenter datasets. In Aim 2 we will compare differences in disease presentation across clusters and also use state-of-the-art genetics and advanced imaging techniques to obtain new insights into biological differences underlying CM heterogeneity and pathogenesis. In Aim 3 we will examine the association between these clusters and important CM outcomes (e.g., change in quality of life, postoperative complications). We will then use prediction modeling to examine how both cluster identity and other characteristics impact these outcomes. Finally, we will use a Modified Delphi Approach to create a novel treatment framework based on this Project’s findings along with structured feedback from experts in the research and clinical management of CM. Taken together, this Project’s results will offer a fundamentally new data-driven approach for classifying CM. We expect these findings will have an immediate impact on clinical management practices and will guide future research in this field.

项目摘要 项目4：使用多维内表型重新定义CM，可预测长期结果 Chiari 1型畸形（CM）是一种常见且可能使人衰弱的疾病，通常由尾骨定义 小脑扁桃体的位移下方的孔。虽然可以发现1％的射线照相CM 或更多人口，该人群极为异质。经典定义CM的患者可能 在临床上或出现严重症状，例如使标题或脑干的迹象 或脊髓故障。此外，具有相似临床表现的患者可能具有不同的遗传 概况和合并症诊断，表明有助于超类似疾病的分化病因。 对这种异质性的越来越认识到了对数据驱动方法的需求 重新分类传统定义的“ CM”。此外，当代成像方法的进步， 基因组学和以患者为中心的临床指标具有大幅扩大的表型机会 复杂疾病，例如商业。利用华盛顿大学在这些领域的独特优势，总体 项目4的目的是在传统上得出临床相关的多维内表型 定义“ CM”，以告知临床管理并优化长期患者结果。特别是，我们期望 这些多维的内表型将有助于结果预测，还提供了新的生物学 有关疾病发病机理的见解，从而支持个性化治疗策略。我们打算 通过三个特定目标来追求这一目标。在AIM 1中，我们将采用完善的无监督和半 对多维临床和放射学数据的监督聚类方法，以得出新的簇 大型，多中心数据集。然后，我们将在三个中验证这些多维内表型 外部，多中心数据集。在AIM 2中，我们将比较跨簇疾病表现的差异， 还要使用最先进的遗传学和先进的成像技术来获得对生物学的新见解 商业异质性和发病机理的差异。在AIM 3中，我们将研究 这些集群和重要的CM结果（例如，生活质量的变化，术后并发症）。我们将 然后使用预测建模来检查群集身份和其他特征如何影响这些 结果。最后，我们将使用修改后的Delphi方法基于此创建一个新颖的治疗框架 项目的发现以及商业研究和临床管理专家的结构化反馈。 综上所述，该项目的结果将提供一种从根本上提供新的数据驱动方法来分类CM。我们 希望这些发现将对临床管理实践产生直接影响，并将指导未来 该领域的研究。