Abstract
Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97–99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.
Highlights
Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains
If the statistical norms are highly different between Discovery and Replication, the model learned from Discovery data will not generalize well to the labels in the Replication set and would produce poor out-of-sample prediction accuracy
In this work, we examined how autism SC-RRB balance subtypes are atypical at the level of macroscale neural circuitry measured with resting state fMRI (rsfMRI)
Summary
Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. Given that subtypes could exhibit different functional connectome phenotypes, we leverage the link between macroscale rsfMRI functional networks and transcriptomic mechanisms to better understand whether autismrelevant functional genomic mechanisms differentially affect such phenotypes To test these ideas, we developed a stratification approach that subtypes individuals based on the within-individual balance between SC versus RRB severity, as measured by ADI-R data from thousands of individuals (n = 2,628) obtained from the National Database for Autism Research (NDAR) (https://nda.nih.gov). In order to link functional connectome phenotypes to autism-associated genes, we utilize the Allen Institute Human Brain Atlas[22,23] to identify genes whose spatial expression pattern is highly similar to macroscale functional networks that differ amongst the SC-RRB subtypes These functional network-relevant gene lists are investigated for enrichment in a variety of autism-associated gene lists derived from evidence at genetic or transcriptomic levels. This approach will allow us to test whether autism-associated genes affect networks or differently across the SC-RRB balance subtypes
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