A Genetic Multi-Mutation Model of Autism Spectrum Disorder

Thursday, May 14, 2015: 5:30 PM-7:00 PM
Imperial Ballroom (Grand America Hotel)
I. Kramer1, A. R. Marvin2, P. H. Lipkin3, J. K. Law4 and P. A. Law5,6, (1)Physics Department, University of Maryland Baltimore Country, Baltimore, MD, (2)Medical Informatics, Kennedy Krieger Institute, Baltimore, MD, (3)Pediatrics/Neurology and Developmental Medicine, Kennedy Krieger Institute/Johns Hopkins School of Medicine, Baltimore, MD, (4)Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, (5)Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, (6)School of Medicine, Congo Protestant University, Kinshasa, Congo-Kinshasa
Background: The degree of genetic vs environmental determination as it relates to the cause(s) of autism is paramount to our understanding of the disorder. Until now, concordance of twin pairs has varied significantly in published literature. In this analysis we use a novel mathematical model for evaluating the genetic component for twins that takes into account the varied ages of twin sets in autism research. We present a method novel to autism research for evaluating autism concordance.

Objectives: To evaluate how well ASD concordance data fits a multi-mutation model.

Methods: The design of this study is cross-sectional. Data for this study was provided by parents of child with autism spectrum disorder through their online participation in the Interactive Autism Network (IAN) based in the United States. The IAN project is an online, voluntary research registry that collects data from families using a set of standardized psychometric instruments and questionnaires. To be included in this analysis, participants must be from twin sets in IAN with at least one twin affected by ASD and for all affected twins must have provided their zygosity and date of diagnosis. A total of 320 twin sets were included (60 identical and 260 fraternal).

Results: The multi-mutation genetic model fits ASD age-of-onset data from IAN very closely (R>0.99). For an ASD susceptible cohort of twins with the same age of 120 months (10.3 years), for example, the modeling predicts that  the monozygote concordance will reach 94% and the dizygotic concordance  will reach 19%. 

Conclusions: The multi-mutation model for autism fits the monozygotic twin data in the IAN data set very well suggesting that the vast majority of autism cases have a genetic susceptibility to acquire autism. Additional research should be performed on cohorts of twins that can be followed over time to see if the model concordance pattern over time is consistent with the actual experience of the discordant twins.

See more of: Genetics
See more of: Genetics