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      A Novel Stratification Method in Linkage Studies to Address Inter- and Intra-Family Heterogeneity in Autism

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          Abstract

          Most genome linkage scans for autism spectrum disorders (ASDs) have failed to be replicated. Recently, a new ASD phenotypic sub-classification method was developed which employed cluster analyses of severity scores from the Autism Diagnostic Interview-Revised (ADI-R). Here, we performed linkage analysis for each of the four identified ADI-R stratified subgroups. Additional stratification was also applied to reduce intra-family heterogeneity and to investigate the impact of gender. For the purpose of replication, two independent sets of single nucleotide polymorphism markers for 392 families were used in our study. This deep subject stratification protocol resulted in 16 distinct group-specific datasets for linkage analysis. No locus reached significance for the combined non-stratified cohort. However, study-wide significant (P = 0.02) linkage scores were reached for chromosomes 22q11 (LOD = 4.43) and 13q21 (LOD = 4.37) for two subsets representing the most severely language impaired individuals with ASD. Notably, 13q21 has been previously linked to autism with language impairment, and 22q11 has been separately associated with either autism or language disorders. Linkage analysis on chromosome 5p15 for a combination of two stratified female-containing subgroups demonstrated suggestive linkage (LOD = 3.5), which replicates previous linkage result for female-containing pedigrees. A trend was also found for the association of previously reported 5p14-p15 SNPs in the same female-containing cohort. This study demonstrates a novel and effective method to address the heterogeneity in genetic studies of ASD. Moreover, the linkage results for the stratified subgroups provide evidence at the gene scan level for both inter- and intra-family heterogeneity as well as for gender-specific loci.

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          Most cited references35

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          Mapping autism risk loci using genetic linkage and chromosomal rearrangements.

          Autism spectrum disorders (ASDs) are common, heritable neurodevelopmental conditions. The genetic architecture of ASDs is complex, requiring large samples to overcome heterogeneity. Here we broaden coverage and sample size relative to other studies of ASDs by using Affymetrix 10K SNP arrays and 1,181 [corrected] families with at least two affected individuals, performing the largest linkage scan to date while also analyzing copy number variation in these families. Linkage and copy number variation analyses implicate chromosome 11p12-p13 and neurexins, respectively, among other candidate loci. Neurexins team with previously implicated neuroligins for glutamatergic synaptogenesis, highlighting glutamate-related genes as promising candidates for contributing to ASDs.
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            Common genetic variants on 5p14.1 associate with autism spectrum disorders.

            Autism spectrum disorders (ASDs) represent a group of childhood neurodevelopmental and neuropsychiatric disorders characterized by deficits in verbal communication, impairment of social interaction, and restricted and repetitive patterns of interests and behaviour. To identify common genetic risk factors underlying ASDs, here we present the results of genome-wide association studies on a cohort of 780 families (3,101 subjects) with affected children, and a second cohort of 1,204 affected subjects and 6,491 control subjects, all of whom were of European ancestry. Six single nucleotide polymorphisms between cadherin 10 (CDH10) and cadherin 9 (CDH9)-two genes encoding neuronal cell-adhesion molecules-revealed strong association signals, with the most significant SNP being rs4307059 (P = 3.4 x 10(-8), odds ratio = 1.19). These signals were replicated in two independent cohorts, with combined P values ranging from 7.4 x 10(-8) to 2.1 x 10(-10). Our results implicate neuronal cell-adhesion molecules in the pathogenesis of ASDs, and represent, to our knowledge, the first demonstration of genome-wide significant association of common variants with susceptibility to ASDs.
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              Linkage, association, and gene-expression analyses identify CNTNAP2 as an autism-susceptibility gene.

              Autism is a genetically complex neurodevelopmental syndrome in which language deficits are a core feature. We describe results from two complimentary approaches used to identify risk variants on chromosome 7 that likely contribute to the etiology of autism. A two-stage association study tested 2758 SNPs across a 10 Mb 7q35 language-related autism QTL in AGRE (Autism Genetic Resource Exchange) trios and found significant association with Contactin Associated Protein-Like 2 (CNTNAP2), a strong a priori candidate. Male-only containing families were identified as primarily responsible for this association signal, consistent with the strong male affection bias in ASD and other language-based disorders. Gene-expression analyses in developing human brain further identified CNTNAP2 as enriched in circuits important for language development. Together, these results provide convergent evidence for involvement of CNTNAP2, a Neurexin family member, in autism, and demonstrate a connection between genetic risk for autism and specific brain structures.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                26 June 2013
                : 8
                : 6
                : e67569
                Affiliations
                [1 ]Medical Genetics Research, Children’s Mercy Hospitals and Clinics and University of Missouri-Kansas City School of Medicine, Kansas City, Missouri, United States of America
                [2 ]McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
                [3 ]Department of Biochemistry and Molecular Medicine, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, United States of America
                Sanjay Gandhi Medical Institute, India
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: ZT VWH. Designed the stratification pipeline used in study: ZT. Performed the linkage and simulation analyses: ZT. Conducted cluster analysis and prepared linkage heat map: VWH. Performed TDT analysis and assisted with simulation: DEA. Obtained permission for use of AGRE pedigree information: ZT VWH. Obtained permission for use of SNP data in the Weiss et al 2009 paper: DEA. Linkage data analysis: ZT. Contributed in data analysis: VWH. Provided classification information for AGRE subjects: VWH. Provided MERLIN formatted SNP data and map files from the Weiss et al 2009 paper: DEA. Drafted the paper: ZT. Made suggestions and provided advice on the study, reviewed and edited the manuscript: ZT VWH DEA.

                Article
                PONE-D-13-05270
                10.1371/journal.pone.0067569
                3694043
                23840741
                ab3e418e-508e-4dce-be5d-7011c0fec275
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 28 January 2013
                : 20 May 2013
                Page count
                Pages: 8
                Funding
                This study was not directly supported by particular funds; however, the authors’ efforts have been partially supported by the followings: Children’s Mercy Hospital intramural fund to ZT and Autism Speaks (AS1991 to ZT), the Simons Foundation (SFARI 221192 to VWH), and a LIFE Foundation gift to VWH. DEA’s contribution was supported by grants from the Simons Foundation (SFARI 137603 to DEA.) and the National Institutes of Health (ACE Genetics Consortium, MH081754 and MH60007). The authors gratefully acknowledge the resources provided by the Autism Genetic Resource Exchange (AGRE) Consortium and the participating AGRE families. The Autism Genetic Resource Exchange is a program of Autism Speaks and is supported, in part, by grant 1U24MH081810 from the National Institute of Mental Health to Clara M. Lajonchere (PI). The funders had no a role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Computational Biology
                Genomics
                Genome Analysis Tools
                Genetics
                Genetics of Disease

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                Uncategorized

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