Genotype Data and Derived Genetic Instruments of Adolescent Brain Cognitive Development Study® for Better Understanding of Human Brain Development

被引：0
作者：
Chun Chieh Fan
Robert Loughnan
Sylia Wilson
John K. Hewitt
机构：
[1] Laureate Institute for Brain Research,Center for Population Neuroscience and Genetics
[2] School of Medicine,Department of Radiology
[3] University of California,Center for Human Development
[4] San Diego,Institute of Child Development
[5] University of California,Institute for Behavioral Genetics
[6] San Diego,undefined
[7] Univeristy of Minnesota,undefined
[8] University of Colorado Boulder,undefined
来源：
Behavior Genetics | 2023年 / 53卷
关键词：
ABCD; Adolescent Brain Cognitive Development Study; Genetic; Genomic; Genotyping; Data release;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The data release of Adolescent Brain Cognitive Development® (ABCD) Study represents an extensive resource for investigating factors relating to child development and mental wellbeing. The genotype data of ABCD has been used extensively in the context of genetic analysis, including genome-wide association studies and polygenic score predictions. However, there are unique opportunities provided by ABCD genetic data that have not yet been fully tapped. The diverse genomic variability, the enriched relatedness among ABCD subsets, and the longitudinal design of the ABCD challenge researchers to perform novel analyses to gain deeper insight into human brain development. Genetic instruments derived from the ABCD genetic data, such as genetic principal components, can help to better control confounds beyond the context of genetic analyses. To facilitate the use genomic information in the ABCD for inference, we here detail the processing procedures, quality controls, general characteristics, and the corresponding resources in the ABCD genotype data of release 4.0.
引用
收藏
页码：159 / 168
页数：9
相关论文
共 70 条
[1]  
Abdellaoui A(2023)15 years of GWAS discovery: realizing the promise Am J Hum Genet 526 68-74
[2]  
Yengo L(2015)A global reference for human genetic variation Nature 32 55-66
[3]  
Verweij KJH(2018)Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: rationale and description Dev Cogn Neurosci 17 145-54
[4]  
Visscher PM(2016)Smokescreen: a targeted genotyping array for addiction research BMC Genomics 32 43-1205
[5]  
Auton A(2018)The adolescent brain cognitive development (ABCD) study: imaging acquisition across 21 sites Dev Cogn Neurosci 12 100-293
[6]  
Barch DM(2020)Genotype imputation and variability in polygenic risk score estimation Genome Med 63 1196-148
[7]  
Baurley JW(2022)Integrative analysis of genomic and exposomic influences on youth mental health J Child Psychol Psychiatr 39 276-1287
[8]  
Edlund CK(2015)Robust inference of population structure for ancestry prediction and correction of stratification in the presence of relatedness Genet Epidemiol 98 127-1992
[9]  
Pardamean CI(2016)Model-free estimation of recent genetic relatedness Am J Hum Genet 48 1284-393
[10]  
Conti DV(2016)Next-generation genotype imputation service and methods Nat Genet 239 118262-5348
1234567