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: 10221025
• 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/10221025
• 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; Pluripotent Stem Cells; 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; 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.

最近，基于DNA的治疗取得了巨大的进步，这一点可以从新出现的潜力的增加中得到证明。 治疗如基因置换和反义寡核苷酸以改变剪接或下调额外的 等位基因这些疗法有望治疗许多IDD;然而，必须解决主要挑战， 实现成功的临床试验。这种疗法的安全性是最重要的，因为许多基因 对剂量敏感。因此，必须确定对目标参与敏感的成果衡量标准， 能够检测过度治疗和功能获得表型向功能丧失表型的非预期转化 表型，反之亦然。在这里，我们关注MECP 2-（Rett vs. MECP 2 Duplication）、RAI 1-（Smith-Magenis vs. Potocki-Lupski综合征）和SHANK 3-（麦-麦二氏与SHANK 3复制）相关疾病 作为由这些剂量依赖性基因的改变引起的IDDs的测试案例。我们建议确定 分子和神经回路介质/这些基因的剂量改变的效应，无论是外周和 集中地，开发复合生物标志物，这些生物标志物在每个个体的 特殊疾病阶段。为了实现这一目标，我们利用贝勒大学的既定患者队列， 医学 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 建立人诱导神经元（iN）的患者特异性分子特征， 以及诱导性多能干细胞和血液。在目标2中，我们将 建立瞬时疾病阶段的患者特异性自主神经和感觉神经回路特征 和严重性使用新的前脉冲抑制范例，瞳孔测量，和诱发电位。这些签名 将从同一受试者中获得两次，间隔8-12个月，以评估稳定性。我们将整合 这些来自每个受试者的密集的多模态数据集，以生成复合生物标志物， 代表在特定时间对基因剂量水平的个性化反应。相比于常规 人口研究-并在精准医学的精神-这一分析框架依赖于完整的， 来自每个参与者的不同数据集，因为个人层面的安全至关重要，以避免导致 非预期的表型。该项目之所以成为可能，是因为有能力获得创新服务， 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的治疗的使用， 治疗许多单基因疾病，并可以帮助告知许多疾病是基因剂量- 依赖。患者特异性细胞系、分子和电路数据将可用于科学研究。 社区永久，将补充自然史研究，并将告知未来的临床试验。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 将有可能为评估、安全给药和 加速多基因剂量依赖性IDDs的临床试验。