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 大约有5个唐氏综合症（DS）的人符合合并自闭症谱的标准 疾病（ASD），与普通人群相比，风险增加十倍。合并ASD与 延迟语言，行为挑战的增加，对看护人的需求增加，以及更高的成本 整个生命周期的医疗保健。精确医学的最新进展有可能实质上 改善DS和合并状况（例如ASD）的个体的长期结果。但是，是 需要实现这种潜力，可靠和有效的措施。目前几乎没有科学基础 DS中ASD症状的鉴定和测量。没有准确的测量，临床试验 DS无法正确应用ASD纳入标准，在必要时对同类进行分层或跟踪对治疗的反应。 因此，迫切需要进行临床试验，以进行可靠，有效的ASD筛查，诊断和 DS中的症状监测工具。为了满足这一需求，我们建议（1）评估心理测量学 DS中ASD症状度量的特征，（2）DS中ASD症状概况的特征 深度表型。表征ASD符号和DS中相关的发展功能将进一步信息 临床试验通过使它们能够通过合并ASD对同类人群进行分层，并监测整个治疗的反应 症状特征。这些目标与NIH的两个优先事项一致包括：（a）增加可能性 通过测试临床结果评估指标的临床试验成功，并（b）定义介绍 DS患者的同时发生条件的过程。为了提高效率，可推广性， 以及未来临床试验的包容性，拟议的研究将在线进行。为了实现这些目标， 我们将利用现有资源（NIH的DS-Connect; Emory University的DS360）进行大规模的大规模。 全国对患有DS的500 6至18岁儿童的ASD症状的全国研究。我们将检查可靠性，有效性， 以及三个著名护理人员报告的ASD筛查和症状测量的变异性。我们将 利用这些ASD措施的数据以及其他深层表型来表征 DS中ASD表型的异质性并确定症状特征。最后，我们提出了一个探索目标 在高ASD风险或低ASD风险的子样本（n = 25）中，以检查电信方法的可行性 收集直接的，基于绩效的ASD评估。该项目产生的数据将增强临床试验 通过在DS中提供ASD测量值来准备（a）屏幕ASD风险以识别治疗的候选人 （b）通过ASD符号曲线对队列进行分层，并监测这些概况中对治疗的反应。一次 经过验证，这些ASD措施将为以后的临床试验提供急需的资源 响应治疗的结果。可行性研究将确定电信评估的程度 用于基于DS的儿童基于绩效的ASD评估。获得的知识将为 在线进行临床试验的领域，在Covid-19大流行时代尤其重要。