26210
Modifiers of Severity in Autism Spectrum Disorder

Poster Presentation
Friday, May 11, 2018: 5:30 PM-7:00 PM
Hall Grote Zaal (de Doelen ICC Rotterdam)
S. P. Smieszek, R. Igo and J. Haines, Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH
Background:

Autism Spectrum Disorder (ASD) comprises a complex of neurodevelopmental disorders primarily characterized by deficits in verbal communication, impaired social interaction and repetitive behaviors. The genetic architecture has proved to be complex and encompasses profound clinical heterogeneity, which poses challenges in understanding its pathophysiology.

Objectives:

There is accumulating evidence that ASD is caused by rare inherited or spontaneous genetic mutations, such as copy number changes and single nucleotide alterations. However, the genetic causes that have currently been found only in s small proportion of cases. We conducted a large scale association analysis of the MSSNG whole genome sequencing data to elucidate potential modifiers of ASD severity.

Methods:

Using the additive linear model method (PLINK) we have directly tested association between 6,198,166 SNPs (Quality Control: MAF > 0.05, HWE P < 1 × 10−6, Mendelian errors, removal of samples with dis-concordant sex status, twins, samples with unreported relatedness) and Vineland Adaptive Behavior Scale Scores.

Results:

Interestingly, the top variants direct us to a region (part of the biggest META-significant haplostretch of SNPs, n=132) containing multiple variants on chromosome 3 including a highly interesting nonsynonymous SNV rs11539148 within QARS (NM_001272073:c.A821G:p.N274S MAF=0.0391). Furthermore, to leverage the size of the data we conducted a pathway enrichment analysis of the set of highly significant results (P < 1 × 10−6) using PARIS and DAVID software. The most significant categories included brain development and structural component of myelin sheath pathways. Genes categorized a neurological, developmental and immune related constituted 65% of all the genes contributing in these pathways. We took variants from contributing genes from significantly over-represented categories to test how much variability in the VABS scores can be explained by the variants. The cumulative effect of the single top pathway enrichment alone on affection status is 2% (P = 6.34 × 10−6). Furthermore we inspected eQTLs for the region and reassuringly we detected lower expression across multiple data-sets, a result consistent with our hypothesis.

Conclusions:

We detect a region that may be a hallmark of severity in ASD. As genetic predisposition may be different for almost every ASD individual, understanding the common mechanisms for endo-phenotypes may help elucidate ASD causal mechanisms.

See more of: Genetics
See more of: Genetics