Clinical trial readiness biomarkers for gene dosage-dependent disorders

基因剂量依赖性疾病的临床试验准备生物标志物

基本信息

批准号：
10675478
负责人：
MIRJANA MALETIC-SAVATIC
金额：
$ 20.06万
依托单位：
BAYLOR COLLEGE OF MEDICINE
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：
2020-07-22 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10675478
关键词：
Acceleration Address Algorithms Alleles Antisense Oligonucleotide Therapy Antisense Oligonucleotides Attention Auditory Evoked Potentials Bioinformatics Biological Biological Markers Biosensor Blinking Blood Brain Cell Line Cells Clinical Clinical Trials Cognition Communities Complement Complementary DNA Complex Copy Number Polymorphism DNA Data Data Analyses Data Set Development Developmental Gene Disease Dose Enrollment Evoked Potentials Fibroblasts Foundations Future Gene Dosage Gene Expression Gene Mutation Genes Genetic Goals Human Impairment Individual Intellectual and Developmental Disabilities Research Centers Intellectual functioning disability Learning Machine Learning Mass Spectrum Analysis Measurement Measures Mediator Medicine Memory Mendelian disorder Methodology Methyl-CpG-Binding Protein 2 Molecular Molecular Profiling Mus Mutation Natural History Neurologic Neurons Outcome Measure Participant Pathology Patients Perception Peripheral Phenotype Physiological Population Study Potocki-Lupski syndrome Proteins Pupil RNA Splicing Recording of previous events Research Research Project Grants Safety Sensory Services Severities Single Nucleotide Polymorphism Somatosensory Evoked Potentials Spinal Muscular Atrophy Stimulus Symptoms Syndrome Testing Time Titrations Treatment Efficacy Treatment-related toxicity Visual evoked cortical potential Work biomarker identification biomarker panel biomarker signature candidate identification clinic ready clinical phenotype clinical trial readiness cognitive function cohort college design diverse data dosage gain of function gene replacement improved individual patient induced pluripotent stem cell innovation insight interest loss of function metabolome metabolomics molecular marker mouse model multimodal data neural circuit new technology next generation novel overexpression overtreatment precision medicine prepulse inhibition response social skills tool transcriptome transcriptome sequencing transcriptomics

项目摘要

DNA-based therapy has made tremendous advances recently, as evident by the increase in emerging potential therapies such as gene replacement and antisense oligonucleotides to alter splicing or downregulate an extra allele. These therapies hold the promise to treat many IDDs; however, major challenges must be addressed to achieve successful clinical trials. Safety of such therapies is of the utmost importance since many of the genes are dosage sensitive. It is therefore critical to identify outcome measures sensitive to target engagement and able to detect overtreatment and unintended conversion of gain-of-function phenotypes into a loss-of-function phenotypes, and vice versa. Here, we focus on MECP2- (Rett vs. MECP2 Duplication), RAI1- (Smith-Magenis vs. Potocki-Lupski syndrome) and SHANK3- (Phelan-McDermid vs. SHANK3 Duplication) associated disorders as test cases of IDDs that are caused by alterations of these dosage-dependent genes. We propose to identify molecular and neurocircuitry mediators/effectors of dosage alterations of these genes, both peripherally and centrally, to develop composite biomarkers that are responsive to gene dosage in each individual at their particular disease stage. Toward this goal, we capitalize on the established patient cohorts at Baylor College of Medicine, which has an extensive history in studying these disorders and their genetics. In Aim 1, we will establish patient-specific molecular signatures of human induced neurons (iNs), derived from both fibroblasts and inducible pluripotent stem cells, and blood, using metabolomics and transcriptomics. In Aim 2, we will establish patient-specific autonomic and sensory neurocircuitry signatures of the momentary disease stage and severity using novel pre-pulse inhibition paradigm, pupillometry, and evoked potentials. These signatures will be obtained twice from the same subject, 8-12 months apart, to assess stability. We will then integrate these dense multimodal datasets from each subject to generate a composite biomarker that accurately represents personalized response to the gene dosage level at that particular time. In contrast to conventional population studies – and in the spirit of precision medicine – this analysis framework relies on complete and diverse datasets from each participant because safety at the individual level is paramount to avoid causing unintended phenotypes. This project is possible because of the ability to access the innovative services from all the cores. The strategies we develop will provide a template to advance the use of DNA-based therapy for treatment of many monogenic disorders and could help inform many disorders that are gene dosage- dependent. The patient-specific cell lines, molecular, and circuit data will be available for the scientific community in perpetuity, will complement natural history studies, and will inform future clinical trials. Lastly, the new methodologies for examining neurocircuitry and the integrative data analysis approaches at multiple levels will potentially provide transformative tools and analytical algorithms for assessment, safe dosing, and accelerated clinical trials for multiple gene dosage-dependent IDDs.

基于 DNA 的疗法最近取得了巨大进展，新兴潜力的增加就证明了这一点基因替代和反义寡核苷酸等疗法可改变剪接或下调额外的剪接这些疗法有望治疗许多 IDD；但是，必须解决重大挑战。此类疗法的安全性至关重要，因为许多基因都与此相关。因此，确定对目标参与和敏感的结果测量至关重要。能够检测过度治疗和功能获得表型无意中转变为功能丧失表型，反之亦然。在这里，我们重点关注 MECP2-（Rett 与 MECP2 重复）、RAI1-（Smith-Magenis）。与 Potocki-Lupski 综合征）和 SHANK3-（Phelan-McDermid 与 SHANK3 重复）相关疾病作为由这些剂量依赖性基因改变引起的 IDD 的测试案例，我们建议鉴定。分子和神经回路介质/影响这些基因改变的剂量，无论是外周还是集中开发对每个个体的基因剂量做出反应的复合生物标志物为了实现这一目标，我们利用贝勒学院现有的患者队列。医学，其中在研究这些疾病及其遗传学方面拥有丰富的历史。在目标 1 中，我们将。建立源自两种成纤维细胞的人类诱导神经元 (iN) 的患者特异性分子特征在目标 2 中，我们将使用代谢组学和转录组学来研究诱导多能干细胞和血液。建立患者特定的瞬时疾病阶段的自主神经和感觉神经回路特征使用新颖的预脉冲抑制范例、瞳孔测量和诱发电位来确定严重程度。将从同一受试者获得两次，间隔 8-12 个月，以评估稳定性，然后我们将进行整合。这些来自每个受试者的密集多模式数据集可生成准确的复合生物标记物代表在特定时间对基因剂量水平的个性化反应，与传统的反应相反。人口研究——本着精准医学的精神——这个分析框架依赖于完整和来自每个参与者的不同数据集，因为个人层面的安全对于避免造成意想不到的表型这个项目是可能的，因为能够获得来自的创新服务。我们开发的所有策略将为推进基于 DNA 的疗法的使用提供模板。治疗许多单基因疾病，并有助于了解许多基因剂量相关的疾病患者特定的细胞系、分子和电路数据将可供科学研究使用。永久社区，将补充自然历史研究，并将为未来的临床试验提供信息。检查神经回路的新方法和多层次的综合数据分析方法将有可能提供用于评估、安全剂量和治疗的变革性工具和分析算法加速多基因剂量依赖性 IDD 的临床试验。