Evaluating ASD Symptomatology in Children with Down Syndrome

评估唐氏综合症儿童的 ASD 症状

• 批准号: 10294431
• 负责人: Marie Moore Channell
• 金额: $ 44.08万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-09 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10294431
• 关键词: 18 year old; Address; Area; Behavior; Behavioral; Biometry; COVID-19 pandemic; Caregivers; Characteristics; Child; Clinical; Clinical Trials; Complex; Conduct Clinical Trials; Data; Data Collection; Development; Diagnostic; Down Syndrome; Epidemiology; Evaluation; Family; Feasibility Studies; Future; General Population; Genetic; Health Care Costs; Heterogeneity; Individual; Intellectual functioning disability; Intervention; Knowledge; Language; Language Delays; Longevity; Measurement; Measures; Methods; Monitor; Outcome; Participant; Performance; Phenotype; Population; Positioning Attribute; Psychometrics; Questionnaires; Relative Risks; Reporting; Research; Resources; Risk; Sampling; Symptoms; Testing; United States National Institutes of Health; Universities; autism spectrum disorder; base; behavioral phenotyping; clinical outcome assessment; clinical practice; clinical trial readiness; cohort; comorbidity; disorder risk; executive function; improved; inclusion criteria; individualized medicine; inter-individual variation; neurodevelopment; performance based measurement; precision medicine; recruit; screening; social; social communication; sound; success; symptomatology; tool; treatment response

PROJECT SUMMARY/ABSTRACT Approximately 1 in 5 individuals with Down syndrome (DS) meet criteria for comorbid autism spectrum disorder (ASD), a tenfold increase in risk compared to the general population. Comorbid ASD is associated with delayed language, increased behavioral challenges, greater demands on caregivers, and higher costs of healthcare across the lifespan. Recent advances in precision medicine have the potential to substantially improve long-term outcomes among individuals with DS and comorbid conditions such as ASD. However, for this potential to be realized, reliable and valid measures are required. There is currently little scientific basis for the identification and measurement of ASD symptoms in DS. Without accurate measurement, clinical trials in DS cannot properly apply ASD inclusion criteria, stratify cohorts where necessary, or track response to treatment. Consequently, there is an urgent need for clinical trials to have reliable, valid ASD screening, diagnostic, and symptom monitoring tools in DS. To address this need, we propose to (1) evaluate the psychometric characteristics of ASD symptom measures in DS, and (2) characterize ASD symptom profiles in DS through deep phenotyping. Characterizing ASD symptoms and related developmental features in DS will further inform clinical trials by enabling them to stratify cohorts by comorbid ASD and monitor response to treatment across symptom profiles. These aims align with two priorities of the NIH INCLUDE Project: (a) increase the likelihood of clinical trial success through testing of clinical outcome assessment measures, and (b) define the presentation and course of co-occurring conditions in individuals with DS. In an effort to improve the efficiency, generalizability, and inclusiveness of future clinical trials, the proposed study will be conducted online. To accomplish these aims, we will leverage existing resources (NIH’s DS-Connect; Emory University’s DS360) to conduct a large-scale, nationwide study of ASD symptoms in 500 6- to 18-year-olds with DS. We will examine the reliability, validity, and variability of three well-known caregiver report-based ASD screening and symptom measures. We will leverage data from these ASD measures, along with additional deep phenotyping, to characterize the heterogeneity of the ASD phenotype in DS and identify symptom profiles. Finally, we propose an exploratory aim among a subsample (n = 25) at high or low ASD risk to examine the feasibility of tele-assessment methods for gathering direct, performance-based ASD evaluations. Data generated from this project will enhance clinical trial readiness by providing ASD measures in DS that can (a) screen for ASD risk to identify candidates for treatment and (b) stratify cohorts by ASD symptom profiles and monitor response to treatment across these profiles. Once validated, these ASD measures will provide a much-needed resource for future clinical trials to document outcomes in response to treatment. The feasibility study will determine the extent to which tele-assessments can be used for performance-based ASD evaluations in children with DS. The knowledge gained will prepare the field for conducting clinical trials online, particularly important in the era of the COVID-19 pandemic.

项目摘要/摘要 大约五分之一的唐氏综合征(DS)患者符合共病自闭症谱系的标准 自闭症(ASD)，与普通人群相比，风险增加了十倍。合并房间隔缺陷症与 语言延迟，行为挑战增加，对照顾者的要求更高，以及 贯穿整个生命周期的医疗保健。精准医学的最新进展有可能大幅提高 改善患有DS和ASD等共病的患者的长期结果。然而，对于 要实现这一潜力，需要采取可靠和有效的措施。目前几乎没有科学依据来证明 DS患者房间隔缺损症状的识别和测量。如果没有准确的测量，临床试验将 DS不能正确应用ASD纳入标准，在必要时对队列进行分层，或跟踪治疗反应。 因此，迫切需要临床试验进行可靠、有效的ASD筛查、诊断和治疗。 DS中的症状监测工具。为了满足这一需要，我们建议(1)评估心理测量学 DS中ASD症状测量的特点，以及(2)DS中ASD症状的特征 深入的表型。对DS的ASD症状和相关发育特征的特征将进一步了解 临床试验，使他们能够通过合并ASD对队列进行分层，并监测治疗的反应 症状特征。这些目标与NIH项目的两个优先事项一致，包括：(A)增加 通过临床结果评估措施的测试来评估临床试验的成功，以及(B)定义介绍 以及DS患者的共生病程。为了提高效率、通用性， 和未来临床试验的包容性，拟议的研究将在网上进行。为了实现这些目标， 我们将利用现有资源(NIH的DS-Connect；埃默里大学的DS-360)进行大规模、 全国范围内对500名6-18岁DS儿童ASD症状的研究。我们将检验其信度、效度、 以及三种基于照顾者报告的ASD筛查和症状测量的可变性。我们会 利用来自这些ASD测量的数据，以及其他深入的表型分析，来表征 DS患者ASD表型的异质性，并确定症状特征。最后，我们提出了探索性的目标。 在ASD风险高或低的亚样本(n=25)中，检查远程评估方法的可行性 收集直接的、基于绩效的ASD评估。该项目产生的数据将加强临床试验 通过在DS中提供ASD措施来做好准备，这些措施可以(A)筛查ASD风险，以确定候选治疗对象 以及(B)根据ASD症状特征对队列进行分层，并监测这些特征对治疗的反应。一次 经过验证，这些ASD措施将为未来的临床试验提供急需的资源来记录 对治疗的反应结果。可行性研究将确定远程评估可以在多大程度上 用于对患有DS的儿童进行基于成绩的ASD评估。所获得的知识将为 在线进行临床试验的领域，在新冠肺炎大流行的时代尤为重要。