Characterizing genetic pathways unique to autism spectrum disorder at multiple levels of biological analysis

• Published in: Molecular autism Vol. 15; no. 1; pp. 46 - 11
• Main Authors: Schaffer, Lukas S, Breunig, Sophie, Lawrence, Jeremy M, Foote, Isabelle F, Grotzinger, Andrew D
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 15-10-2024; BioMed Central; BMC
• Subjects: Analysis; Attention Deficit Disorder with Hyperactivity - genetics; Attention-deficit/hyperactivity disorder; Autism; Autism spectrum disorder; Autism Spectrum Disorder - genetics; Child; Comorbidity; Female; Gene expression; Genes; Genetic aspects; Genetic Predisposition to Disease; Genetic research; Genome-Wide Association Study; Genomic SEM; Genomics; Humans; Latent Class Analysis; Liability (Law); Male; Medical research; Medicine, Experimental; Multivariate genomics; Neurodevelopmental disorders; Pervasive developmental disorders; Phenotype; Physiological aspects; Polymorphism, Single Nucleotide; Transcriptome; United States; Comorbidity; Multivariate genomics; Genomic SEM; Attention-deficit/hyperactivity disorder; Neurodevelopmental disorders; Autism spectrum disorder; Psychiatric genetics
• ISSN: 2040-2392; 2040-2392
• DOI: 10.1186/s13229-024-00624-2

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by atypical patterns of social functioning and repetitive/restricted behaviors. ASD commonly co-occurs with ADHD and, despite their clinical distinctiveness, the two share considerable genetic overlap. Given their shared genetic liability, it is unclear which genetic pathways increase the likelihood of ASD independently of ADHD.
We applied Genomic Structural Equation Modeling (SEM) to GWAS summary statistics for ASD and childhood-diagnosed ADHD, decomposing the genetic variance for ASD into that which is unique to ASD (uASD) and that which is shared with ADHD. We computed genetic correlations between uASD and 83 external traits to estimate genetic overlap between uASD and other clinically relevant phenotypes. We went on to apply Stratified Genomic SEM to identify classes of genes enriched for uASD. Finally, we implemented Transcriptome-Wide SEM (T-SEM) to explore patterns of gene-expression associated with uASD.
We observed positive genetic correlations between uASD and several external traits, most notably those relating to cognitive/educational outcomes and internalizing psychiatric traits. Stratified Genomic SEM showed that heritability for uASD was significantly enriched in genes involved in evolutionarily conserved processes, as well as for a histone mark in the germinal matrix. T-SEM revealed 83 unique genes with expression associated with uASD, 34 of which were novel with respect to univariate analyses. These genes were overrepresented in skin-related pathologies.
Our study was limited by summary statistics derived exclusively from individuals of European ancestry. Additionally, using data based on a general ASD diagnosis limits our ability to understand genetic factors contributing to the pronounced clinical heterogeneity in ASD.
Our findings delineate the unique genetic underpinnings of ASD that are independent of ADHD at the genome-wide, functional, and gene expression level of analysis. In addition, we identify novel associations previously masked by their diametric effects on ADHD. Collectively, these results provide insight into the processes that make ASD biologically unique.