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Overlaps between autism and language impairment: phenomimicry or shared etiology?

Bishop DV - Behav. Genet. (2010)

Bottom Line: Traditionally, autistic spectrum disorder (ASD) and specific language impairment (SLI) are regarded as distinct conditions with separate etiologies.Yet these disorders co-occur at above chance levels, suggesting shared etiology.A modified simulation involving G x G interactions obtained levels of comorbidity and rates of impairment in relatives more consistent with observed values.

View Article: PubMed Central - PubMed

Affiliation: Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK. dorothy.bishop@psy.ox.ac.uk

ABSTRACT
Traditionally, autistic spectrum disorder (ASD) and specific language impairment (SLI) are regarded as distinct conditions with separate etiologies. Yet these disorders co-occur at above chance levels, suggesting shared etiology. Simulations, however, show that additive pleiotropic genes cannot account for observed rates of language impairment in relatives, which are higher for probands with SLI than for those with ASD + language impairment. An alternative account is in terms of 'phenomimicry', i.e., language impairment in comorbid cases may be a consequence of ASD risk factors, and different from that seen in SLI. However, this cannot explain why molecular genetic studies have found a common risk genotype for ASD and SLI. This paper explores whether nonadditive genetic influences could account for both family and molecular findings. A modified simulation involving G x G interactions obtained levels of comorbidity and rates of impairment in relatives more consistent with observed values. The simulations further suggest that the shape of distributions of phenotypic trait scores for different genotypes may provide evidence of whether a gene is involved in epistasis.

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Related in: MedlinePlus

Traditional model of specific language impairment (SLI) and autism spectrum disorder (ASD) as separate disorders with distinct etiologies. Both disorders are conceptualised as spectrum disorders, with disorder identified when a continuous underlying causal trait falls below a threshold
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Fig1: Traditional model of specific language impairment (SLI) and autism spectrum disorder (ASD) as separate disorders with distinct etiologies. Both disorders are conceptualised as spectrum disorders, with disorder identified when a continuous underlying causal trait falls below a threshold

Mentions: A model of the etiology of SLI and autism is shown in Fig. 1. This is based on the original approach to complex multifactorial disorders proposed by Falconer (1965), and subsequently developed to contrast different models of comorbidity by Neale and Kendler (1995). The model assumes that underlying a categorical diagnosis is a normally distributed liability continuum. Figure 1 differs from the traditional models by having disorder result when the value on the continuum falls below a threshold, whereas Falconer treated liability as a positive risk variable with disorder resulting from a high value. The reason for this change is to make the model more compatible with conceptualisations of developmental disorders, where disorder is typically recognised when a score on a normally distributed ability is unusually low. In effect, we work with negative liability, but this affects only the graphical depiction of the model, and has no computational consequences. In the classic Falconer model, liability is a theoretical construct, not directly observed, but inferred from the frequencies of disorders in probands and their relatives. Nevertheless, it should be possible to identify measures that are correlated with the causal trait, which will be termed ‘liability markers’ for disorder. These could be indices of neurological or cognitive function. The construct of liability marker overlaps with the notion of endophenotype (Gottesman and Gould 2003), but is more general because it is not restricted to genetically determined traits. An additional point to note is that although the model specifies a single causal trait, risk factors are not unitary: on the contrary, they can be partitioned into genetic and environmental risks, with the latter subdivided into those shared between relatives and those specific to the individual. For each type of risk, there are many influences, each of small impact, whose combined effect gives rise to the continuous distribution on the relevant causal trait.Fig. 1


Overlaps between autism and language impairment: phenomimicry or shared etiology?

Bishop DV - Behav. Genet. (2010)

Traditional model of specific language impairment (SLI) and autism spectrum disorder (ASD) as separate disorders with distinct etiologies. Both disorders are conceptualised as spectrum disorders, with disorder identified when a continuous underlying causal trait falls below a threshold
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2921070&req=5

Fig1: Traditional model of specific language impairment (SLI) and autism spectrum disorder (ASD) as separate disorders with distinct etiologies. Both disorders are conceptualised as spectrum disorders, with disorder identified when a continuous underlying causal trait falls below a threshold
Mentions: A model of the etiology of SLI and autism is shown in Fig. 1. This is based on the original approach to complex multifactorial disorders proposed by Falconer (1965), and subsequently developed to contrast different models of comorbidity by Neale and Kendler (1995). The model assumes that underlying a categorical diagnosis is a normally distributed liability continuum. Figure 1 differs from the traditional models by having disorder result when the value on the continuum falls below a threshold, whereas Falconer treated liability as a positive risk variable with disorder resulting from a high value. The reason for this change is to make the model more compatible with conceptualisations of developmental disorders, where disorder is typically recognised when a score on a normally distributed ability is unusually low. In effect, we work with negative liability, but this affects only the graphical depiction of the model, and has no computational consequences. In the classic Falconer model, liability is a theoretical construct, not directly observed, but inferred from the frequencies of disorders in probands and their relatives. Nevertheless, it should be possible to identify measures that are correlated with the causal trait, which will be termed ‘liability markers’ for disorder. These could be indices of neurological or cognitive function. The construct of liability marker overlaps with the notion of endophenotype (Gottesman and Gould 2003), but is more general because it is not restricted to genetically determined traits. An additional point to note is that although the model specifies a single causal trait, risk factors are not unitary: on the contrary, they can be partitioned into genetic and environmental risks, with the latter subdivided into those shared between relatives and those specific to the individual. For each type of risk, there are many influences, each of small impact, whose combined effect gives rise to the continuous distribution on the relevant causal trait.Fig. 1

Bottom Line: Traditionally, autistic spectrum disorder (ASD) and specific language impairment (SLI) are regarded as distinct conditions with separate etiologies.Yet these disorders co-occur at above chance levels, suggesting shared etiology.A modified simulation involving G x G interactions obtained levels of comorbidity and rates of impairment in relatives more consistent with observed values.

View Article: PubMed Central - PubMed

Affiliation: Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK. dorothy.bishop@psy.ox.ac.uk

ABSTRACT
Traditionally, autistic spectrum disorder (ASD) and specific language impairment (SLI) are regarded as distinct conditions with separate etiologies. Yet these disorders co-occur at above chance levels, suggesting shared etiology. Simulations, however, show that additive pleiotropic genes cannot account for observed rates of language impairment in relatives, which are higher for probands with SLI than for those with ASD + language impairment. An alternative account is in terms of 'phenomimicry', i.e., language impairment in comorbid cases may be a consequence of ASD risk factors, and different from that seen in SLI. However, this cannot explain why molecular genetic studies have found a common risk genotype for ASD and SLI. This paper explores whether nonadditive genetic influences could account for both family and molecular findings. A modified simulation involving G x G interactions obtained levels of comorbidity and rates of impairment in relatives more consistent with observed values. The simulations further suggest that the shape of distributions of phenotypic trait scores for different genotypes may provide evidence of whether a gene is involved in epistasis.

Show MeSH
Related in: MedlinePlus