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

• 批准号: 10427281
• 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
• 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/10427281
• 关键词: 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 of activation protein; Medicine; Memory; Mendelian disorder; Methodology; 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; Readiness; Recording of previous events; Research; Research Project Grants; Safety; Sensory; Services; Severities; Single Nucleotide Polymorphism; Spinal Muscular Atrophy; Stimulus; Sum; Symptoms; Syndrome; Testing; Time; Treatment Efficacy; Treatment-related toxicity; Visual; Work; base; biomarker signature; clinical phenotype; clinical trial readiness; cognitive function; cohort; college; design; 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; somatosensory; tool; transcriptome; transcriptome sequencing; transcriptomics

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的治疗最近取得了巨大的进步，新兴潜力的增加证明了这一点。 改变剪接或下调额外基因的治疗方法，如基因替换和反义寡核苷酸 等位基因。这些疗法有望治疗许多IDDS；然而，必须应对重大挑战 取得临床试验成功。这种疗法的安全性是至关重要的，因为许多基因 对剂量敏感。因此，至关重要的是确定对目标接触敏感的成果衡量标准和 能够检测到过度治疗和功能增益表型向功能丧失的意外转换 表型，反之亦然。在这里，我们重点介绍MECP2-(Rett与MECP2复制)、RAI1-(Smith-Magenis 与Potocki-Lupski综合征)和SHANK3-(Phelan-Mcdermidvs.SHANK3重复)相关疾病 作为IDDS的测试案例，这些IDDS是由这些剂量依赖基因的改变引起的。我们建议确定 这些基因剂量变化的分子和神经回路介体/效应物，外周和 集中地，开发复合生物标记物，以响应每个个体在其 特定的疾病阶段。为了实现这一目标，我们充分利用了贝勒医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有着广泛的历史。在目标1中，我们将 建立来源于两种成纤维细胞的人诱导神经元(INS)的患者特异性分子特征 和可诱导的多能干细胞，以及血液，利用代谢组学和转录组学。在目标2中，我们将 建立短暂疾病阶段患者特有的自主神经和感觉神经回路特征 使用新的脉冲前抑制范式、瞳孔测量和诱发电位来评估严重程度。这些签名 将从同一受试者身上获得两次，相隔8-12个月，以评估稳定性。然后我们将整合 这些来自每个受试者的密集多模式数据集以生成准确的复合生物标志物 表示对特定时间的基因剂量水平的个性化反应。与传统的 人口研究--本着精确医学的精神--这一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是最重要的，以避免导致 意外的表型。该项目之所以有可能，是因为能够从 所有的核心。我们开发的策略将提供一个模板，以促进基于DNA的治疗在 治疗许多单基因疾病，并可能有助于了解许多疾病是基因剂量- 依附的。特定于患者的细胞系、分子和电路数据将供科学研究人员使用 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。最后， 检查神经回路的新方法和多层次的综合数据分析方法 将潜在地提供变革性工具和分析算法，用于评估、安全剂量和 加速多基因剂量依赖性IDDS的临床试验。