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

基本信息

批准号：
10676874
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
项目类别：
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/10676874
关键词：
Acceleration Address Adult Adverse event Affect Age Age Years Aging Algorithms American Anxiety 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 Communication DNA Methylation Data Deterioration Development Diabetes Mellitus Dimensions Disease Disparity 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 Link Longevity Longitudinal cohort Machine Learning Malignant Neoplasms Measurement Measures Mental Depression 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 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 neural neurophysiology novel patient population preventive intervention programs promote resilience prospective protective factors psychosocial stressors repetitive behavior resilience factor risk minimization risk mitigation sex skills social young adult

项目摘要

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.

抽象的自闭症谱系障碍 (ASD) 的特点是社交障碍和限制性、重复性行为出现在幼儿期并持续终生的行为，影响了 2.2% 的成年人随着年龄的增长，自闭症成年人面临一系列不良后果，包括显着更高的发病率。我最近的脑电图（EEG）。研究结果进一步揭示了自闭症谱系障碍患者大脑功能老化的轨迹改变，这与过度使用的报告一致。然而，这些与年龄相关的衰退背后的机制仍然未知。那个时间与年龄相关的衰退在行为和认知上表现出预防风险的重要机会新的“表观遗传时钟”技术根据细胞衰老过程的进展进行索引。 DNA 甲基化 (DNAm) 模式，提供生物年龄的代理测量，预测以后的认知、健康、我将探讨这些个人衰老轨迹的敏感指标是否可以预测。帮助在大脑活动或行为模式开始之前识别出具有不良结果高风险的自闭症患者改变，特别询问：（1）中年自闭症成年人不良衰老结果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志物有关吗？ (3) 哪些临床和环境因素？儿童期和成年早期的差异会导致该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来实现这些目标。在多学科专家导师团队（Lord 博士、Carroll 博士、Geschwind 博士和 Senturk 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，接受新的培训我将收集表观遗传和神经（EEG）衰老测量方法。来自一个独特且深度表型的队列，该队列由患有自闭症谱系障碍 (ASD) 的个体 (N=118) 和不患有自闭症谱系障碍 (N=39) 的个体组成从两岁起就开始进行前瞻性随访，目前年龄为 32-36 岁（“早期诊断研究”；EDX）。生物年龄将使用三种不同的成熟方法根据唾液衍生的 DNAm 模式进行量化表观遗传时钟算法将使用峰值频率（7-13Hz）的脑电图标记来测量大脑老化。这些研究共同捕捉了与年龄相关的振荡减慢的特征，将为潜在的策略提供信息。从发展早期识别并解决自闭症谱系障碍中与年龄相关的风险。拟议的培训目标将成为关注寿命的新颖和创新研究计划的催化剂 ASD 跨多个测量级别的变化，为纵向 R01 调查奠定基础该研究项目将解决 EDX 队列中的表观遗传、神经和认知衰老问题。我们了解自闭症谱系障碍的长期寿命影响，并为减轻长期影响提供了重要的机会快速增长的老年自闭症成年人口的个人和公共健康负担。