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TitleAutism Spectrum Disorders - The Role of Genetics in Diagnosis, Trtmt - S. Deutsch, et al., (Intech, 2011) WW
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Table of Contents
                            00_preface_ Autism Spectrum Disorders The Role of Genetics in Diagnosis and Treatment
00a_Early Recognition and Diagnosis
01_Early Detection of Autism Spectrum Disorders
01a_Nosology and Diagnostic Criteria:
What Makes Sense and Can Genetics Help?
02_Pervasive Developmental
Disorder- not Otherwise Specified:
Specifying and Differentiating
03_Autism and Genetic Syndromes
03a_Genetics and Pathophysiology
of Autism Spectrum Disorders
04_The Genetics of Autism Spectrum Disorders
05_Genetic Heterogeneity of Autism
Spectrum Disorders
06_The Genetic Basis of Phenotypic Diversity:
Autism as an Extreme Tail of
a Complex Dimensional Trait
07_A New Genetic Mechanism for Autism
08_Common Genetic Etiologies and Biological
Pathways Shared Between Autism Spectrum
Disorders and Intellectual Disabilities
08a_Treatment and Genetic Counseling
09_Microgenetic Approach to
Therapy of Girls with ASD
10_Genetic Counseling in Autistic Phenotypes
Document Text Contents
Page 1




Edited by Stephen I. Deutsch

and Maria R. Urbano

Page 2

Autism Spectrum Disorders: The Role of Genetics in Diagnosis and Treatment
Edited by Stephen I. Deutsch and Maria R. Urbano

Published by InTech
Janeza Trdine 9, 51000 Rijeka, Croatia

Copyright © 2011 InTech
All chapters are Open Access articles distributed under the Creative Commons
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of the use of any materials, instructions, methods or ideas contained in the book.

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Image Copyright A pyro Design, 2010. Used under license from

First published July, 2011
Printed in Croatia

A free online edition of this book is available at
Additional hard copies can be obtained from [email protected]

Autism Spectrum Disorders: The Role of Genetics in Diagnosis and Treatment, Edited by
Stephen I. Deutsch and Maria R. Urbano
p. cm.
ISBN 978-953-307-495-5

Page 105

The Genetic Basis of Phenotypic Diversity:
Autism as an ExtremeTail of a Complex Dimensional Trait


(transcript traits), protein, metabolite, and functional levels. It has been suggested that less
heritability of metabolite traits than transcript traits is associated with the difference in the
quantity of biological noise between the genetic determinants and the trait (Rowe et al.,
2008). The more steps that are involved between genotype and the trait level, the more
biological noise may reside in the process. Such biological noise originates from inter-locus
interactions and gene-environment interactions, and the inter-locus interactions may have
an important role in the biological noise. Additive and/or non-additive inter-locus
interactions with other loci are available in a variety of processes including cis-, trans-, and
inter-cellular interactions (Figure 1). The presence of gene-environment-gene circuits may
make it difficult to distinguish inter-locus interactions from gene-environment interactions
in the biological noise (Ijichi et al., 2011). In these interactions, an intergenerational change in
the number or property of factors (environment and/or other related loci) in the regulatory
circuit may easily individualize the balance of each hierarchical trajectory (coding RNA,
non-coding RNA, translation, autocrine, paracrine, and endocrine levels) and individually
determine the developmental outcomes. The net non-additive effects of the biological noise
are metaphorically interpreted as hub-and-spoke structures of regulatory networks among
polymorphic loci (Benfey & Mitchell-Olds, 2008).

Fig. 1. Cellular and molecular interactions of biological noise in regulatory networks around a
gene locus (A). Additive and/or non-additive phenomena can be involved in each interaction
(Ijichi et al., 2011). In this explanation, an arrow represents the net contribution between loci
and the gene-environment relationship. The locus A can interact with other loci in association
with coding RNA and/or non-coding RNA level in cis-acting manner (①, ②) and trans-acting
manner (③, ④). The cis-acting interactions are involved in genetic imprinting. After
translation, interactions can be mediated through autocrine, paracrine, and endocrine
mechanisms (⑤, ⑥). Gene-environment interactions can modify penetrance of the outcomes
affected by the locus A. The network constituents can change the sensitivity to environmental
influences (⑦), that can provide gene-environment-gene circuits. In the monomorphic loci
theory, the gene A can be monomorphic and the link between monomorphic A and the A-
associated polymorphic noise is usually invisible in the context of traditional genetics.

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Autism Spectrum Disorders: The Role of Genetics in Diagnosis and Treatment


5. Quantitative domains and genetic factors
The distributional shift of a bell-shaped curve and the change in the curve shape illustrates
the mean value change and the variance alteration of the quantitative dimension,
respectively (Gibson, 2009). These changes can affect the proportion of individuals with
autism to those without as determined by a liability threshold. The biased male to female
ratio (3-4 to 1) in ASD is plausibly interpreted as a distributional shift of the quantitative
bell-shaped curve as a gender gap. In the hyper-systemizing theory, the male systemizing
mechanism is set at a slightly higher level than in females (Baron-Cohen, 2004). In an
imprinted-X liability threshold model, actions of some X-linked genes, which are expressed
only from paternal X-chromosome, are suggested to be associated with the male
predisposition to ASD (Skuse, 2000). The gender is a bimorphic genetic variation and there
is a gender gap in sensitivity or vulnerability to environmental factors (Constantino & Todd,
2003). The relationship between a bell-shaped quantitative distribution and the genetic
factors underlying the complex phenotype still remains to be elucidated.

5.1 Polygenic liability model
The traditional concept of polygenic liability supposes a normal distribution of frequencies
of susceptibility variant alleles (Gibson, 2009). The manner of the allele contribution is
additive, and each allele contribution usually results in a positive or negative effect on the
phenotype in the carrier individual and the quantitative population dimension results from
such additive allele contributions. To explain the smooth normal distribution, an
environmental variance of each allele contribution is addressed in this model.
In a genetic model, oligogenicity with epistasis, the contributing genes are likely to be
common ones in the population (Folstein & Rosen-Sheidley, 2001). There is no evidence that
the genetic causative processes affecting the autistic extreme are different from those
contributing the autistic dimension including individuals without autism (Ronald et al.,
2006a). If the presence of epistasis, pleiotropy, and gene-environment interactions are all
supposed, the polymorphic genetic underpinning is referred to as QTLs (Plomin et al., 1994,
2009; Plomin & Kosslyn, 2001). However, it is also the fact that the delay and difficulty in
detecting the causal variant alleles at QTLs is common to all idiopathic quantitative traits
including ASD, physical and physiological characteristics, and personalities (de Geus et al.,
2001; Fullerton, 2006; Palmert & Hirschhorn, 2003; Willis-Owen & Flint, 2006).
If the genetic factors for a tail of the bell-shaped curve are different from those for the
majority and have extremity-specific properties including serious involvement of coding
gene segments (Mitchison, 2000), the variant alleles should be more detectable. Because the
genetic contribution in ASD is the biggest in human complex traits and the environmental
influence on ASD is quite minimal as described above, the difficulty in finding the universal
genetic marker for ASD warrants the necessity of a paradigm shift.

5.2 Additive and non-additive interactions between mono- and poly-morphic loci
It has been emphasized that the three behavioral domains of ASD modestly correlate to each
other and the set of genes for each domain may be partly different (Dworzynski et al., 2007;
Happé et al., 2006; Ronald et al., 2005, 2006a, 2006b). The speculated modest genetic overlap
among autistic domains may be indistinguishable from that among human complex
phenotypes including ASD, bipolar disorder, and schizophrenia (Rzhetsky et al., 2007),
suggesting that the autistic domains and these psychiatric conditions might share the same

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Genetic Counseling in Autistic Phenotypes


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