Project 1: Identifying and optimizing monogenetic risk prediction for autism in newborns

项目 1：识别和优化新生儿自闭症单基因风险预测

• 批准号: 10698081
• 负责人: Wendy K Chung
• 金额: $ 40.05万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-06 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10698081
• 关键词: Architecture; Behavior; Behavior Therapy; Behavioral; Brain; Categories; Consent; Data; Development; Diagnostic; Disease; Doctor of Philosophy; Down Syndrome; Early Intervention; Education; Evaluation; Family; Family member; Foundations; Genes; Genetic; Genetic Models; Genetic Risk; Genomics; Goals; Heritability; Individual; Infant; Inherited; Intellectual functioning disability; Knowledge; Lead; Life; Methods; Neonatal Screening; New York City; Newborn Infant; Outcome; Parents; Pilot Projects; Population; Predisposition; Quality of life; Recording of previous events; Research; Risk; Risk Factors; Self-Injurious Behavior; Symptoms; Variant; autism spectrum disorder; cohort; comparison group; de novo mutation; exome sequencing; family burden; genetic disorder diagnosis; genetic testing; genetic variant; genome sequencing; genomic data; high risk; improved; improved outcome; individuals with autism spectrum disorder; neurobehavioral; neurogenetics; novel; polygenic risk score; population based; prospective; rare variant; risk prediction; risk variant; tool

PROJECT SUMMARY The heritability of autism has been estimated to be > 80%; therefore, genetics should be a powerful tool to predict risk of autism. Newborn screening using genomic sequencing is a platform that can deliver genetic diagnoses before autism symptoms emerge – providing the opportunity for early intervention which improves autism outcomes. Independent of this proposal, we are conducting a pilot study (GUARDIAN) of genome sequencing as a new platform for traditional newborn screening in a diverse New York City population. In GUARDIAN, parents will have the option to receive results for at least 100 monogenic conditions for which the genetic variants are highly penetrant for some impact on the brain and behavior, and on average ~20% of individuals with the risk variant have autism. The individuals with monogenic conditions and autism often have challenges with self-injurious behavior, have poorer adaptation, are less independent, and have associated lower quality of life and greater family burden. It is unclear what factors determine which of the individuals with the monogenic risk factor will develop autism (including other rare or common inherited genetic variants or other factors) and whether it is possible to predict, among infants with these risk variants, who will develop autism and perhaps benefit from behavioral interventions. The key to accurately predicting risk with genetics is to identify all risk genes and variants and precisely estimate their effect size. Inherited, rare, moderate-risk variants, and common variants of individually small effect are a major contributor to autism risk in aggregation, but the majority of these genes or variants have not been identified. As the genomic data increase in autism cohorts including SPARK, there will be substantially improved power to more completely understand the genomic architecture and identify new genes and variants and quantify the autism risk for these variants. In Project 1, we propose to identify the PROGRESS Cohort: newborns at high risk for autism in a diverse New York City population. We will screen a large (~100,000) population-based cohort of newborns in GUARDIAN and identify an unbiased group of infants with monogenic susceptibility to highly penetrant neurogenetic conditions that increase the risk of autism (IGR, N=400) and return these genetic results to parents within 6 weeks of life. Of these infants identified in GUARDIAN, 240 will be consented for Projects 2 and 3. We will identify a comparison group of 120 infants without monogenic risk (non-IGR). Using large autism cohorts we will identify additional genes and genetic variants that confer risk of autism and test genetic models including high, moderate, and low risk genetic variants and family history to develop a composite genomic risk score and apply it in our PROGRESS cohort of newborns at identified genetic risk (IGR) of autism. The prospective assessment of neurobehavioral development of this cohort (Project 3) will provide infant neurodevelopmental trajectories that will be combined with the composite genomic risk score to generate an integrated autism risk score (Projects 1 and 3).

项目总结