Follow-up Linkage and Association Analyses of a Nonverbal Motor Speech Phenotype Identified in the AGRE Data Set

Background: Using behavioral and genetic information from the Autism Genetics Resource Exchange (AGRE) data set we developed phenotypes and investigated linkage and association for individuals with and without Autism Spectrum Disorders (ASD) who exhibit expressive language behaviors consistent with a motor speech disorder. Speech and language variables from Autism Diagnostic Interview-Revised (ADI-R) were used to develop a motor speech phenotype associated with non-verbal or unintelligible verbal behaviors (NVMSD:ALL) and a related phenotype restricted to individuals  who were non-verbal or unintelligible  but without significant comprehension difficulties (NVMSD:C). We previously identified several linkage peaks using the PPL framework to assess the strength of evidence for or against trait-marker linkage and linkage disequilibrium across the genome using Affymetrix 5.0 genotype data. As evidence for linkage disequilibrium was limited, Ingenuity Pathway Analysis (IPA) was then utilized to identify potential genes for further investigation.

 Objectives:  In this presentation, we fine mapped our genes of interest and used the PPL framework to assess evidence for association.  We also present the addition of 88 new families from the AGRE data set to the NVMSD:ALL phenotype for  sequential updating of our initial linkage analysis.

Methods: 1) Tag SNPs were selected from our genes of interest and were genotyped using an Oligonucleotide Ligation Assay.  Genotype information was analyzed for association using an extension of the PPL that detects linkage disequilibrium.  2) The SNPstream assay was used to genotype 450 SNPs from our linkage regions in the additional NVMSD:ALL family members.  Genotype information was checked for missingness, Mendelian inconsistencies, unlikely double recombination events, and departures from Hardy-Weinberg Equilibrium.  The initial PPL analysis was sequentially updated to include evidence for or against linkage in our extended sample.

Results:  Overall, evidence for linkage disequilibrium was limited in our candidate genes of interest, with the highest signals in TRPV2 (8%) and LMX1A (7%).  The sequential update of our linkage analysis increased evidence for linkage in the following regions: 1q24.2, 3q25.31, 4q22.3, 5p12, and 17q22 while evidence for linkage decreased in regions 5q33.1, 17p12, and 17q11.2.

Conclusions: The additional 88 families from AGRE added power to our PPL analysis with increasing evidence for linkage in several regions.  Even though there was a decrease in linkage evidence in a few regions and evidence for linkage disequilibrium was limited, the replication and strengthening of our previous findings   support   our continued investigation of this phenotype as playing an important role for reducing genetic heterogeneity in autism samples.