Genome-wide and Ordered-Subset linkage analyses provide support for autism loci on 17q and 19p with evidence of phenotypic and interlocus genetic correlates

Abstract

Background: Autism is a neurobehavioral spectrum of phenotypes characterized by deficits in the development of language and social relationships and patterns of repetitive, rigid and compulsive behaviors. Twin and family studies point to a significant genetic etiology, and several groups have performed genomic linkage screens to identify susceptibility loci.

Methods: We performed a genome-wide linkage screen in 158 combined Tufts, Vanderbilt and AGRE (Autism Genetics Research Exchange) multiplex autism families using parametric and nonparametric methods with a categorical autism diagnosis to identify loci of main effect. Hypothesizing interdependence of genetic risk factors prompted us to perform exploratory studies applying the Ordered-Subset Analysis (OSA) approach using LOD scores as the trait covariate for ranking families. We employed OSA to test for interlocus correlations between loci with LOD scores > or =1.5, and empirically determined significance of linkage in optimal OSA subsets using permutation testing. Exploring phenotypic correlates as the basis for linkage increases involved comparison of mean scores for quantitative trait-based subsets of autism between optimal subsets and the remaining families.

Results: A genome-wide screen for autism loci identified the best evidence for linkage to 17q11.2 and 19p13, with maximum multipoint heterogeneity LOD scores of 2.9 and 2.6, respectively. Suggestive linkage (LOD scores > or =1.5) at other loci included 3p, 6q, 7q, 12p, and 16p. OSA revealed positive correlations of linkage between the 19p locus and 17q, between 19p and 6q, and between 7q and 5p. While potential phenotypic correlates for these findings were not identified for the chromosome 7/5 combination, differences indicating more rapid achievement of "developmental milestones" was apparent in the chromosome 19 OSA-defined subsets for 17q and 6q. OSA was used to test the hypothesis that 19p linkage involved more rapid achievement of these milestones and it revealed significantly increased LOD* scores at 19p13.

Conclusions: Our results further support 19p13 as harboring an autism susceptibility locus, confirm other linkage findings at 17q11.2, and demonstrate the need to analyze more discreet trait-based subsets of complex phenotypes to improve ability to detect genetic effects.

Figure 1

Genome-wide nonparametric linkage analysis in 158 multiplex families for autism loci. Individual plots show allele-sharing LOD* scores calculated for autosomes using Allegro and MLOD scores for the X chromosome calculated using ASPEX.

Figure 2

Multipoint linkage analysis under all models for chromosomes 17 (A) and 19 (B). Multipoint parametric HLOD plots for both dominant (blue) and recessive (red) models, and nonparametric allele-sharing LOD* values (black) are displayed across the respective chromosomes. OSA analysis using ascending "developmental milestones" factor scores to order families is shown for chromosome 19, for which a 92-family optimal subset was identified and used to calculate allele-sharing LOD* scores (dashed black line).

Figure 3

OSA using family-specific LOD scores as the ranking covariate. Families were ordered based on descending LOD scores at peak linkage for 19p13 and allele-sharing LOD scores calculated in the optimal subset for (A) chromosome 17 or (B) chromosome 6. Families were also ranked based on descending LOD scores at peak linkage on chromosome 7q (C), and LOD scores calculated for chromosome 5. Solid lines reflect multipoint LOD scores corresponding to the entire dataset for the chromosome being analyzed, while dashed lines represent analysis of the optimal subset (above the dataset division in all cases) identified from OSA; these were 52 families for chromosome 17, 30 for chromosome 6 and 41 families for chromosome 7.