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Autism Families (autism + family)

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Life Sciences	100%

Selected Abstracts

Power calculations for likelihood ratio tests for offspring genotype risks, maternal effects, and parent-of-origin (POO) effects in the presence of missing parental genotypes when unaffected siblings are available

GENETIC EPIDEMIOLOGY, Issue 1 2007
E. Rampersaud
Abstract Genotype-based likelihood-ratio tests (LRT) of association that examine maternal and parent-of-origin effects have been previously developed in the framework of log-linear and conditional logistic regression models. In the situation where parental genotypes are missing, the expectation-maximization (EM) algorithm has been incorporated in the log-linear approach to allow incomplete triads to contribute to the LRT. We present an extension to this model which we call the Combined_LRT that incorporates additional information from the genotypes of unaffected siblings to improve assignment of incompletely typed families to mating type categories, thereby improving inference of missing parental data. Using simulations involving a realistic array of family structures, we demonstrate the validity of the Combined_LRT under the null hypothesis of no association and provide power comparisons under varying levels of missing data and using sibling genotype data. We demonstrate the improved power of the Combined_LRT compared with the family-based association test (FBAT), another widely used association test. Lastly, we apply the Combined_LRT to a candidate gene analysis in Autism families, some of which have missing parental genotypes. We conclude that the proposed log-linear model will be an important tool for future candidate gene studies, for many complex diseases where unaffected siblings can often be ascertained and where epigenetic factors such as imprinting may play a role in disease etiology. Genet. Epidemiol. © 2006 Wiley-Liss, Inc. [source]

Evaluation of FOXP2 as an autism susceptibility gene

AMERICAN JOURNAL OF MEDICAL GENETICS, Issue 5 2002
Thomas H. Wassink
Abstract A mutation in the gene FOXP2 was recently identified as being responsible for a complicated speech and language phenotype in a single large extended pedigree. This gene is of interest to autism because it lies in one of the most consistently linked autism chromosomal regions of interest. We therefore tested this gene for its involvement in autism in a large sample of autism families. We completely sequenced the exon containing the mutation, screened the remaining coding sequence using SSCP technology, and identified and genotyped two novel intronic tetranucleotide repeat polymorphisms that were then analyzed for evidence of linkage and linkage disequilibrium (LD). We identified two families in which heterozygous deletions of a small number of glutamines in a long poly-glutamine stretch were found in one parent and the autistic probands; no other non-conservative coding sequence changes were identified. Linkage and LD analyses were performed in 75 affected sibling pair families and in two subgroups of this sample defined by the presence/absence of severe language impairment. One allele appeared to have an opposite pattern of transmission in the language based subgroups, but otherwise the linkage and LD analyses were negative. We conclude that FOXP2 is unlikely to contribute significantly to autism susceptibility. © 2002 Wiley-Liss, Inc. [source]

A Genome-wide Association Study of Autism Reveals a Common Novel Risk Locus at 5p14.1

ANNALS OF HUMAN GENETICS, Issue 3 2009
Deqiong Ma
Summary Although autism is one of the most heritable neuropsychiatric disorders, its underlying genetic architecture has largely eluded description. To comprehensively examine the hypothesis that common variation is important in autism, we performed a genome-wide association study (GWAS) using a discovery dataset of 438 autistic Caucasian families and the Illumina Human 1M beadchip. 96 single nucleotide polymorphisms (SNPs) demonstrated strong association with autism risk (p-value < 0.0001). The validation of the top 96 SNPs was performed using an independent dataset of 487 Caucasian autism families genotyped on the 550K Illumina BeadChip. A novel region on chromosome 5p14.1 showed significance in both the discovery and validation datasets. Joint analysis of all SNPs in this region identified 8 SNPs having improved p-values (3.24E-04 to 3.40E-06) than in either dataset alone. Our findings demonstrate that in addition to multiple rare variations, part of the complex genetic architecture of autism involves common variation. [source]

An Analysis Paradigm for Investigating Multi-locus Effects in Complex Disease: Examination of Three GABAA Receptor Subunit Genes on 15q11-q13 as Risk Factors for Autistic Disorder.

ANNALS OF HUMAN GENETICS, Issue 3 2006
A. E. Ashley-Koch
Summary Gene-gene interactions are likely involved in many complex genetic disorders and new statistical approaches for detecting such interactions are needed. We propose a multi-analytic paradigm, relying on convergence of evidence across multiple analysis tools. Our paradigm tests for main and interactive effects, through allele, genotype and haplotype association. We applied our paradigm to genotype data from three GABAA receptor subunit genes (GABRB3, GABRA5, and GABRG3) on chromosome 15 in 470 Caucasian autism families. Previously implicated in autism, we hypothesized these genes interact to contribute to risk. We detected no evidence of main effects by allelic (PDT, FBAT) or genotypic (genotype-PDT) association at individual markers. However, three two-marker haplotypes in GABRG3 were significant (HBAT). We detected no significant multi-locus associations using genotype-PDT analysis or the EMDR data reduction program. However, consistent with the haplotype findings, the best single locus EMDR model selected a GABRG3 marker. Further, the best pairwise genotype-PDT result involved GABRB3 and GABRG3, and all multi-locus EMDR models also selected GABRB3 and GABRG3 markers. GABA receptor subunit genes do not significantly interact to contribute to autism risk in our overall data set. However, the consistency of results across analyses suggests that we have defined a useful framework for evaluating gene-gene interactions. [source]