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Genome-wide linkage using the Social Responsiveness Scale in Utah autism pedigrees.

Coon H, Villalobos ME, Robison RJ, Camp NJ, Cannon DS, Allen-Brady K, Miller JS, McMahon WM - Mol Autism (2010)

Bottom Line: When analysed as a quantitative trait, results replicated a peak found in an independent sample using quantitative SRS scores on chromosome 11p15.1-p15.4 (HLOD = 2.77).The SRS linkage peaks reported here substantially overlap with peaks found in our previous affected-only genome scan of clinical diagnosis.These results suggest the SRS is a robust and useful phenotype measure for genetic linkage studies of ASD.

View Article: PubMed Central - HTML - PubMed

Affiliation: Utah Autism Research Project, Department of Psychiatry and Division of Genetic Epidemiology, University of Utah, 650 Komas Drive, Suite 206, Salt Lake City, UT 84108, USA. hilary.coon@hsc.utah.edu.

ABSTRACT

Background: Autism Spectrum Disorders (ASD) are phenotypically heterogeneous, characterized by impairments in the development of communication and social behaviour and the presence of repetitive behaviour and restricted interests. Dissecting the genetic complexity of ASD may require phenotypic data reflecting more detail than is offered by a categorical clinical diagnosis. Such data are available from the Social Responsiveness Scale (SRS) which is a continuous, quantitative measure of social ability giving scores that range from significant impairment to above average ability.

Methods: We present genome-wide results for 64 multiplex and extended families ranging from two to nine generations. SRS scores were available from 518 genotyped pedigree subjects, including affected and unaffected relatives. Genotypes from the Illumina 6 k single nucleotide polymorphism panel were provided by the Center for Inherited Disease Research. Quantitative and qualitative analyses were done using MCLINK, a software package that uses Markov chain Monte Carlo (MCMC) methods to perform multilocus linkage analysis on large extended pedigrees.

Results: When analysed as a qualitative trait, linkage occurred in the same locations as in our previous affected-only genome scan of these families, with findings on chromosomes 7q31.1-q32.3 [heterogeneity logarithm of the odds (HLOD) = 2.91], 15q13.3 (HLOD = 3.64), and 13q12.3 (HLOD = 2.23). Additional positive qualitative results were seen on chromosomes 6 and 10 in regions that may be of interest for other neuropsychiatric disorders. When analysed as a quantitative trait, results replicated a peak found in an independent sample using quantitative SRS scores on chromosome 11p15.1-p15.4 (HLOD = 2.77). Additional positive quantitative results were seen on chromosomes 7, 9, and 19.

Conclusions: The SRS linkage peaks reported here substantially overlap with peaks found in our previous affected-only genome scan of clinical diagnosis. In addition, we replicated a previous SRS peak in an independent sample. These results suggest the SRS is a robust and useful phenotype measure for genetic linkage studies of ASD. Finally, analyses of SRS scores revealed linkage peaks overlapping with evidence from other studies of neuropsychiatric diseases. The information available from the SRS itself may, therefore, reveal locations for autism susceptibility genes that would not otherwise be detected.

No MeSH data available.


Related in: MedlinePlus

Genome scan results of quantitative Social Responsiveness Scale (SRS) scores using MCLINK. The nonparametric analysis (a) does not assume a genetic model, and scores were converted to logarithm of odds (LOD) scores for ease of comparison. The parametric analysis (b), assumes the penetrance vector for an individual is based on their observed trait value and three specified trait distributions for the three genotypes at the disease locus (no risk allele, one risk allele, two risk alleles). These trait distributions are assumed to map onto the SRS score cutoffs (unaffected, spectrum, and affected). The penetrance vector for an individual is the relative probabilities of the trait being observed from the three distributions.
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Figure 3: Genome scan results of quantitative Social Responsiveness Scale (SRS) scores using MCLINK. The nonparametric analysis (a) does not assume a genetic model, and scores were converted to logarithm of odds (LOD) scores for ease of comparison. The parametric analysis (b), assumes the penetrance vector for an individual is based on their observed trait value and three specified trait distributions for the three genotypes at the disease locus (no risk allele, one risk allele, two risk alleles). These trait distributions are assumed to map onto the SRS score cutoffs (unaffected, spectrum, and affected). The penetrance vector for an individual is the relative probabilities of the trait being observed from the three distributions.

Mentions: The genome-wide analyses of the data are summarized in Table 3 and in Figures 2 and 3. Note that MCLINK does not provide NPL scores for the X chromosome. Qualitative analyses show substantial overlap with our previous affected-only genome-wide study of these same families [32], in addition to revealing new positive results. We also saw positive findings from our analysis of the quantitative SRS data and replicated the chromosome 11 SRS finding reported by Duvall et al. [20].


Genome-wide linkage using the Social Responsiveness Scale in Utah autism pedigrees.

Coon H, Villalobos ME, Robison RJ, Camp NJ, Cannon DS, Allen-Brady K, Miller JS, McMahon WM - Mol Autism (2010)

Genome scan results of quantitative Social Responsiveness Scale (SRS) scores using MCLINK. The nonparametric analysis (a) does not assume a genetic model, and scores were converted to logarithm of odds (LOD) scores for ease of comparison. The parametric analysis (b), assumes the penetrance vector for an individual is based on their observed trait value and three specified trait distributions for the three genotypes at the disease locus (no risk allele, one risk allele, two risk alleles). These trait distributions are assumed to map onto the SRS score cutoffs (unaffected, spectrum, and affected). The penetrance vector for an individual is the relative probabilities of the trait being observed from the three distributions.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2913945&req=5

Figure 3: Genome scan results of quantitative Social Responsiveness Scale (SRS) scores using MCLINK. The nonparametric analysis (a) does not assume a genetic model, and scores were converted to logarithm of odds (LOD) scores for ease of comparison. The parametric analysis (b), assumes the penetrance vector for an individual is based on their observed trait value and three specified trait distributions for the three genotypes at the disease locus (no risk allele, one risk allele, two risk alleles). These trait distributions are assumed to map onto the SRS score cutoffs (unaffected, spectrum, and affected). The penetrance vector for an individual is the relative probabilities of the trait being observed from the three distributions.
Mentions: The genome-wide analyses of the data are summarized in Table 3 and in Figures 2 and 3. Note that MCLINK does not provide NPL scores for the X chromosome. Qualitative analyses show substantial overlap with our previous affected-only genome-wide study of these same families [32], in addition to revealing new positive results. We also saw positive findings from our analysis of the quantitative SRS data and replicated the chromosome 11 SRS finding reported by Duvall et al. [20].

Bottom Line: When analysed as a quantitative trait, results replicated a peak found in an independent sample using quantitative SRS scores on chromosome 11p15.1-p15.4 (HLOD = 2.77).The SRS linkage peaks reported here substantially overlap with peaks found in our previous affected-only genome scan of clinical diagnosis.These results suggest the SRS is a robust and useful phenotype measure for genetic linkage studies of ASD.

View Article: PubMed Central - HTML - PubMed

Affiliation: Utah Autism Research Project, Department of Psychiatry and Division of Genetic Epidemiology, University of Utah, 650 Komas Drive, Suite 206, Salt Lake City, UT 84108, USA. hilary.coon@hsc.utah.edu.

ABSTRACT

Background: Autism Spectrum Disorders (ASD) are phenotypically heterogeneous, characterized by impairments in the development of communication and social behaviour and the presence of repetitive behaviour and restricted interests. Dissecting the genetic complexity of ASD may require phenotypic data reflecting more detail than is offered by a categorical clinical diagnosis. Such data are available from the Social Responsiveness Scale (SRS) which is a continuous, quantitative measure of social ability giving scores that range from significant impairment to above average ability.

Methods: We present genome-wide results for 64 multiplex and extended families ranging from two to nine generations. SRS scores were available from 518 genotyped pedigree subjects, including affected and unaffected relatives. Genotypes from the Illumina 6 k single nucleotide polymorphism panel were provided by the Center for Inherited Disease Research. Quantitative and qualitative analyses were done using MCLINK, a software package that uses Markov chain Monte Carlo (MCMC) methods to perform multilocus linkage analysis on large extended pedigrees.

Results: When analysed as a qualitative trait, linkage occurred in the same locations as in our previous affected-only genome scan of these families, with findings on chromosomes 7q31.1-q32.3 [heterogeneity logarithm of the odds (HLOD) = 2.91], 15q13.3 (HLOD = 3.64), and 13q12.3 (HLOD = 2.23). Additional positive qualitative results were seen on chromosomes 6 and 10 in regions that may be of interest for other neuropsychiatric disorders. When analysed as a quantitative trait, results replicated a peak found in an independent sample using quantitative SRS scores on chromosome 11p15.1-p15.4 (HLOD = 2.77). Additional positive quantitative results were seen on chromosomes 7, 9, and 19.

Conclusions: The SRS linkage peaks reported here substantially overlap with peaks found in our previous affected-only genome scan of clinical diagnosis. In addition, we replicated a previous SRS peak in an independent sample. These results suggest the SRS is a robust and useful phenotype measure for genetic linkage studies of ASD. Finally, analyses of SRS scores revealed linkage peaks overlapping with evidence from other studies of neuropsychiatric diseases. The information available from the SRS itself may, therefore, reveal locations for autism susceptibility genes that would not otherwise be detected.

No MeSH data available.


Related in: MedlinePlus