Social, Cognitive, and Behavioral Influences on Early Life Aging in Autism

社会、认知和行为对自闭症早期衰老的影响

• 批准号: 10526243
• 负责人: Abigail H Dickinson
• 金额: $ 18.21万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-05 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10526243
• 关键词: Acceleration; Address; Adult; Adverse event; Affect; Age; Age-Years; Aging; Algorithms; American; Behavior; Behavioral; Biological; Biological Aging; Body mass index; Brain; Cardiovascular Diseases; Cell Aging; Characteristics; Child; Childhood; Chronic; Chronic Disease; Chronology; Clinical; Clinical Data; Clinical Management; Cognitive; Cognitive aging; DNA Methylation; Data; Deterioration; Development; Diabetes Mellitus; Dimensions; Disease; Early Diagnosis; Electroencephalography; Environmental Risk Factor; Epigenetic Process; Face; Foundational Skills; Foundations; Frequencies; Future; General Population; Goals; Health; Health Care Costs; Impaired cognition; Impairment; Individual; Individual Differences; Investigation; K-Series Research Career Programs; Life; Life Expectancy; Light; Link; Longevity; Longitudinal cohort; Machine Learning; Measurement; Measures; Mentors; Methodology; Methods; Modeling; Molecular; Morbidity - disease rate; National Institute of Mental Health; Nerve Degeneration; Neurodegenerative Disorders; Neurosciences; Older Population; Outcome; Participant; Pathway interactions; Pattern; Persons; Pharmaceutical Preparations; Phase; Phenotype; Physiological; Population; Predisposition; Prevention; Prevention strategy; Procedures; Process; Proxy; Public Health; Reporting; Research; Rest; Risk; Risk Factors; Saliva; Sampling; Schools; Sensory; Social isolation; Stress; Surrogate Markers; Symptoms; Techniques; Time; Training; United States; Variant; Vulnerable Populations; adult with autism spectrum disorder; adverse outcome; age related; aging brain; autism spectrum disorder; autistic; base; behavior influence; catalyst; clinically relevant; cognitive function; cohort; comorbidity; early childhood; emerging adult; environmental intervention; epigenetic marker; experience; functional decline; high risk; improved; improved outcome; indexing; individuals with autism spectrum disorder; innovation; insight; methylation pattern; middle age; mortality; multidisciplinary; neurophysiology; novel; patient population; preventive intervention; programs; prospective; protective factors; psychosocial stressors; relating to nervous system; resilience; restrictive repetitive behavior; risk minimization; sex; skills; social; social communication; young adult

ABSTRACT Autism spectrum disorder (ASD) is characterized by disabling social impairments and restrictive, repetitive behaviors that emerge in early childhood and persist throughout the lifespan, affecting 2.2% of adults in the United States. As they age, autistic adults face a range of adverse outcomes, including significantly higher rates of chronic disease, neurodegenerative conditions, and early mortality. My recent electroencephalography (EEG) findings further reveal altered trajectories of functional brain aging in ASD, in line with reports of excessive cognitive aging. However, the mechanisms underlying these age-related declines remain unknown, and by the time that age-related decline manifests behaviorally and cognitively crucial opportunities for risk prevention have already passed. New ‘epigenetic clock’ techniques index the progression of cellular aging processes based on DNA methylation (DNAm) patterns, providing proxy measures of biological age that predict later cognitive, health, functional declines, and mortality. I will explore if these sensitive measures of individual aging trajectories may help to identify autistic individuals at high risk of poor outcomes before patterns of brain activity or behavior begin to change, specifically asking: (1) Is biological risk for poor aging outcomes increased in autistic adults at midlife? (2) Are variations in epigenetic risk linked to brain aging markers? (3) Which clinical and environmental differences during childhood and early adulthood contribute to biological risk variations in this population? The proposed career development award will allow me to address these aims through new integrated methods. Facilitated by a multidisciplinary team of expert mentors (Dr. Lord, Dr. Carroll, Dr. Geschwind, and Dr. Senturk), I will build upon my existing expertise in developmental neuroscience and ASD to acquire new training in epigenetic and longitudinal lifespan methodologies. I will collect epigenetic and neural (EEG) aging measures from a unique and deeply phenotyped cohort of individuals with (N=118) and without ASD (N=39) who have been prospectively followed since age two and are currently 32-36 years old (The ‘Early Diagnosis Study; EDX). Biological age will be quantified from saliva-derived DNAm patterns using three different well-established epigenetic clock algorithms. Brain aging will be measured using EEG markers of peak frequency (7-13Hz), which captures characteristic age-related oscillatory slowing. Together, these studies will inform potential strategies to identify and address age-related risks in ASD from earlier in development. The proposed training goals will be the catalyst for a novel and innovative research program focused on lifespan changes in ASD across multiple levels of measurement and lay the foundation for a longitudinal R01 investigation of epigenetic, neural, and cognitive aging in the EDX cohort. This research program will address a crucial gap in our understanding of long-term lifespan influences in ASD and provide crucial opportunities to mitigate long-term personal and public health burdens in the rapidly growing population of older autistic adults.

摘要 自闭症谱系障碍（ASD）的特点是残疾的社会障碍和限制性，重复性， 在儿童早期出现并持续整个生命周期的行为，影响了2.2%的成年人， 美国的随着年龄的增长，自闭症成年人面临着一系列不利的结果， 慢性疾病、神经退行性疾病和早期死亡率。我最近的脑电图（EEG） 研究结果进一步揭示了ASD患者功能性大脑衰老的轨迹改变，与过度的 认知老化然而，这些与年龄相关的下降的机制仍然未知， 次 与年龄相关的衰退表现在行为和认知方面，风险预防的关键机会 已经过去了。新的“表观遗传时钟”技术根据以下因素对细胞衰老过程的进展进行索引： DNA甲基化（DNAm）模式，提供生物学年龄的替代指标，预测以后的认知，健康， 功能衰退和死亡率。我将探讨这些敏感的个人衰老轨迹的措施， 帮助在大脑活动或行为模式开始之前识别出处于不良结果高风险中的自闭症个体 改变，特别是问：（1）在中年自闭症成年人中，衰老结果不佳的生物风险是否增加？ (2)表观遗传风险的变化与大脑衰老标记有关吗？(3)临床和环境 儿童期和成年早期的差异会导致这一人群的生物风险变化吗？ 拟议的职业发展奖将使我能够通过新的综合方法实现这些目标。 在多学科专家导师团队（洛德博士、卡罗尔博士、格施温德博士和森图克博士）的协助下， 我将利用我在发育神经科学和自闭症谱系障碍方面的现有专业知识，获得新的培训， 表观遗传和纵向寿命方法。我将收集表观遗传和神经（脑电图）老化措施 从一个独特的和深入的表型队列的个人与（N=118）和没有ASD（N=39），谁有 从2岁开始前瞻性随访，目前为32-36岁（早期诊断研究; EDX）。 生物学年龄将使用三种不同的成熟的方法从唾液来源的DNAm模式定量。 表观遗传时钟算法将使用峰值频率（7- 13 Hz）的EEG标记来测量脑老化， 捕捉到了年龄相关的振荡减慢特征。总之，这些研究将为潜在的战略提供信息， 从早期发展中识别和解决ASD中与年龄相关的风险。 拟议的培训目标将成为一个新颖和创新的研究计划的催化剂，重点是寿命 ASD在多个测量水平上的变化，并为纵向R 01调查奠定基础 表观遗传、神经和认知老化的研究。这项研究计划将解决一个关键的差距， 我们对ASD的长期寿命影响的理解，并提供了重要的机会，以减轻长期 个人和公共卫生负担的快速增长的老年自闭症成年人的人口。