Common Variant Burden Contributes to the Familial Aggregation of Quantitative Autistic Traits

Panel Presentation
Saturday, May 4, 2019: 10:55 AM
Room: 517B (Palais des congres de Montreal)
J. N. Constantino1, R. E. Wagner2, W. Howells3, M. Panther1, J. Lowe4 and D. Geschwind5, (1)Washington University School of Medicine, St. Louis, MO, (2)Child and Adolescent Psychiatry, Washington University School of Medicine, St. Louis, MO, (3)Psychiatry, Washington University School of Medicine, St. Louis, MO, (4)Semel Institute, University of California, Los Angeles, Los Angeles, CA, (5)University of California, Los Angeles, Los Angeles, CA
Background: Both rare and common genetic variation act additively to contribute to autism spectrum disorder (ASD) risk in simplex and multiplex families. Quantitative autistic traits (QAT) aggregate in families affected by multiplex ASD, but no study to date has examined the extent to which common variants contribute to ASD risk in a familial multiplex sample encompassing the entire range of QAT. Critically, large epidemiological studies have demonstrated that family members of affected individuals exhibit subclinical QAT. Further, evidence from both twin and genomic studies suggests a genetic correlation between ASD and QAT in the general population.

Objectives: The goal of this study was to employ ASD polygenic risk scores (PRS) to predict the full range of phenotypic variance comprehensively characterizing QAT and establish common variant burden in a familial sample.

Methods: In a sample of clinically-ascertained subjects (N=634) from multiplex families in the Autism Genetic Resource Exchange, including individuals with and without ASD diagnosis, we calculated the amount of variance in QAT predicted by ASD-PRS, derived from the Psychiatric Genomics Consortium (PGC) ASD Genome Wide Association Study (GWAS) (N=10,610).

Results: The ASD-PRS explained 6.8% of the phenotypic variance in our sample. Across all subjects, the estimated correlation of the ASD-PRS with QAT was r=0.24 (p=1.17e-09). In females (N=232), the correlation was r=0.31 (p<.0001); and in males (N=402), the correlation was r=0.19 (p=0.0003). Further, we found a significant interaction of sex with ASD-PRS (p<.05). In the PGC-ASD sample, genetic complex trait analysis (GCTA) revealed the SNP heritability (which by definition measures only common, additive variation) of ASD to be 17%, setting an upper limit on how much variance a PRS can explain. Thus, it is notable that these PRS results capture 40% of the possible phenotypic variance. Similar analyses using summary statistics from the recently expanded 2018 iPSYCH-PGC ASD GWAS are underway and will be presented.

Conclusions: These results demonstrate a significant contribution of common polygenic variation to the familial aggregation of QAT. PRS enrichment in families was observed in both males and females, but this polygenic burden was significantly higher in females. Since multiplex families are preferentially selected for clinically-ascertained males, de novo mutations disrupting the relationship between PRS and phenotype may be more prevalent in males in this sample. Further, PRS derived from the largest ASD-GWAS to date, the Danish iPSYCH-PGC collaboration (N=46,350), explained 2.45% of variance in ASD diagnosis in a case-control sample; an estimate which, at 6.8%, our estimate nearly triples. To further contextualize these results, two previous studies attempting to employ ASD-PRS to predict subcomponents of QATs explained only .13% and .54% of the phenotypic variance. While it is possible that due to the multiplex nature of our sample, our subjects were enriched for common variant burden, a recent study demonstrated that the degree of over-transmission of ASD-PRS did not differ between simplex subjects and PGC-ASD probands. These results speak to the critical importance of employing QAT measurement in efforts to elucidate the genetic architecture of ASD.