The staging and pacing of neurodevelopmental change during adolescence exhibits observable individual differences, yet how much of this between- and within-subject variation is attributable to genetic factors is unknown. Current understanding of the genetic basis for brain structure and function measured by neuroimaging data is based on analyses of (mostly cross-sectional) adult samples. By obtaining results from a developmentally-critical period, i.e. adolescence, we will be able to determine whether the identified genetic components are time-invariant traits or time-sensitive developmental results. Our long-term goal is to determine the causal mechanisms underlying vulnerabilities to risky behavior and psychiatric disorders that emerge during adolescence. To achieve this goal, we aim to search for genetic factors associated with developmental variation measured by multi-modal neuroimaging data. We propose three approaches to perform unbiased genetic analyses of data from the Adolescent Brain Cognitive Development (ABCD) study: 1) Extract patterns of developmental changes across brain regions; 2) Identify associated genetic loci through integrated genome-wide association studies across derived developmental multi-modal imaging phenotypes; 3) Determine the relationship between genetic risk for psychiatric diseases and neurodevelopmental trajectories. We will pursue these aims utilizing a novel combination of methods from population genetics and neuroscience while innovatively tailoring the analytic strategies to avoid potential biases and spurious associations due to admixture and relatedness. The proposed research is significant because the identified genetic mechanisms will provide a potential basis for therapeutics and public health interventions, attending to the impact of the epidemiologically guided sampling of ABCD data. By sharing the tools we develop in this research program and the resulting genetic instruments, we will impact the field immediately, enabling researchers to more deeply investigate neurodevelopmental processes with ABCD data as well as with other accumulating datasets to which they have access.
Identifying genetic effects on complex traits is a critical step in the quest to establish causal mechanisms. Our research program focuses on identifying and quantifying the genetic basis of developmental differences in the human brain during adolescence, using unbiased approaches for identifying associated genes, determining genetic relationships, and profiling the impact of genetic predisposition for diseases in longitudinal Adolescent Brain Cognitive Development (ABCD) data. Our proposal utilizes innovative approaches to achieve the analytic goals and reduce the risks of spurious associations from admixed and related participants.
