Multimodal Developmental Neurogenetics of Females with ASD

The term autism-spectrum disorders (ASD) exemplifies the tremendous heterogeneity in this developmental disorder at both the phenotypic and underlying genetic levels. It has repeatedly been observed that ASD disproportionately affects males (♂) relative to females (♀). Although many hypotheses attempt to explain this bias, no clear answers have emerged because of inconsistent and incomplete phenotyping and small sample sizes. We propose to leverage the interdisciplinary strengths and recruiting power of our network to study sex-specific differences by deep phenotyping and genotyping of ASD participants. We hypothesize that advanced network data analytic methods (Integrated Weighted Gene Co-Expression Network Analysis) can aid in understanding the tremendous heterogeneity in ASD by connecting different levels of phenotype with genetic variation. We will therefore combine multiple levels of biology and endophenotypes – SNVs, CNVs, behavioral metrics, and resting state imaging and electrophysiology measures – into one framework across affected and unaffected siblings and controls using an integrated network analysis, iWGCNA

 The specific aims of the study are as follows:

1) Identify sex differences in brain structure, function, connectivity, and temporal dynamics in ASD.

2) Characterize associations between DNA sequence and copy number variants and brain structure and function in ♀ASD and ♀TD versus ♂ASD and ♂TD.

3) Relate brain differences in structure, function, and temporal dynamics to heterogeneity in ASD behavior and genetics.