Heritability Estimation of Cognitive Phenotypes in the ABCD Study^® Using Mixed Models

Area of Science:

• Behavioral Genetics
• Developmental Neuroscience
• Quantitative Genetics

Background:

• Traditional twin and family studies partition phenotypic variance into additive genetic (A), common environment (C), and unique environment (E) effects.
• The Adolescent Brain Cognitive Development (ABCD) Study provides a large dataset for investigating genetic and environmental influences on development.

Purpose of the Study:

• To apply the ACE Model and its extensions to the ABCD Study data.
• To utilize the Fast Efficient Mixed Effects Analysis (FEMA) package for analyzing genetic and environmental variance components.
• To assess heritability and environmental contributions to traits in a large, diverse sample.

Main Methods:

• Application of the ACE Model using the FEMA package on the ABCD Study cohort.
• Analysis of a twin sub-sample (n=924) for initial heritability estimates.
• Integration of SNP-derived genetic relatedness for the full ABCD Study sample (n=9,742) to refine parameter estimates.

Main Results:

• Heritability estimates for height (0.86) and cognition (0.00-0.61) were consistent with prior research.
• Incorporating SNP-derived genetic relatedness narrowed confidence intervals for all parameter estimates.
• The FEMA package's sparse clustering method effectively handled diverse genetic relatedness within families.

Conclusions:

• The ACE Model, implemented with FEMA, is effective for dissecting genetic and environmental influences in large, complex datasets like the ABCD Study.
• SNP-derived relatedness improves the precision of heritability and environmental effect estimates.
• This approach advances our understanding of the etiology of developmental traits.