Linkage analysis of IQ discrepancy in autism: an attempt to replicate. A. Q. Nato1, N. H. Chapman1, H. K. Sohi1, R. A. Bernier2, J. M. Viskochil3, H. Coon3, E. M. Wijsman1,4,5 1) Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA; 2) Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA; 3) Department of Psychiatry, University of Utah, Salt Lake City, UT, USA; 4) Department of Biostatistics, University of Washington, Seattle, WA, USA; 5) Department of Genome Sciences, University of Washington, Seattle, WA, USA.
In individuals with autism spectrum disorders, performance IQ (PIQ) is often greater than verbal IQ (VIQ). Linkage analysis of IQ discrepancy (PIQ-VIQ) in University of Washington (UW) nuclear families identified several genomic regions with evidence of linkage, including the strongest evidence on chromosomes (chr) 10p12 and 17 [Hum Genet 2011:129,59-70]. These signals were not apparent when analyses were rerun without IQ data on parents, and attempts to replicate these signals in datasets without parental IQ data (AGRE and AGP) were unsuccessful. Here, we attempt to replicate these two linkage signals in large multi-generational families from Utah (UT), where IQ data are available on multiple generations.
A total of 1,532 individuals were available in 67 UT families, ranging from 4 to 177 people. 631 subjects are typed for 6,044 SNPs, and 509 of these subjects have IQ data. In the UW dataset, Wechsler PIQ was measured by block design and object assembly subscales, while VIQ was measured by vocabulary and comprehension subscales. A diversity of IQ measures were present in the UT families, so we chose single subtests to represent PIQ and VIQ, with an effort to stay as close as possible to original UW measures. For PIQ, we used block design from Wechsler tests and pattern construction from DAS tests (BD). For VIQ, we used vocabulary from Wechsler tests and naming vocabulary or word definition from DAS tests (VOC). Analysis of this revised definition of IQ discrepancy (BD-VOC) in the UW families showed the regions of interest on chr 10 and 17.
We estimated multipoint IBD sharing in the UT families with Markov chain Monte Carlo (MCMC) methods due to the large size of the pedigrees. We used PBAP to select a subpanel of markers to maximize information while using informative markers in linkage equilibrium that were spaced sufficiently for the MCMC methods. We performed variance components linkage analyses in SOLAR, using models allowing for additive effects with and without dominance in both the major gene and polygenic components. Using SNPs selected from the 6k panel, we found a moderate lod score (~0.75) on chr 10p12, in addition to a larger lod score 20 cM away. The chr 17 signal did not replicate. Analyses with more genotyped individuals, using SNPs from a 750k chip, are underway.
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