Download Autism Spectrum Disorders - The Role of Genetics in Diagnosis, Trtmt - S. Deutsch, et al., (Intech, 2011) WW PDF

TitleAutism Spectrum Disorders - The Role of Genetics in Diagnosis, Trtmt - S. Deutsch, et al., (Intech, 2011) WW
TagsMedical
LanguageEnglish
File Size3.3 MB
Total Pages210
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

logo1.eps


AUTISM SPECTRUM
DISORDERS: THE ROLE OF

GENETICS IN DIAGNOSIS
AND TREATMENT


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
Non Commercial Share Alike Attribution 3.0 license, which permits to copy,
distribute, transmit, and adapt the work in any medium, so long as the original
work is properly cited. After this work has been published by InTech, authors
have the right to republish it, in whole or part, in any publication of which they
are the author, and to make other personal use of the work. Any republication,
referencing or personal use of the work must explicitly identify the original source.

Statements and opinions expressed in the chapters are these of the individual contributors
and not necessarily those of the editors or publisher. No responsibility is accepted
for the accuracy of information contained in the published articles. The publisher
assumes no responsibility for any damage or injury to persons or property arising out
of the use of any materials, instructions, methods or ideas contained in the book.

Publishing Process Manager Ivana Lorkovic
Technical Editor Teodora Smiljanic
Cover Designer Jan Hyrat
Image Copyright A pyro Design, 2010. Used under license from Shutterstock.com

First published July, 2011
Printed in Croatia

A free online edition of this book is available at www.intechopen.com
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



93

(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.

Page 106

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



94

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

Page 209

Genetic Counseling in Autistic Phenotypes



197

Nissenkorn, A.; Gak, E.; Vecsler, M.; Reznik, H.; Menascu, S. & Ben Zeev, B. (2010).Epilepsy
in RettSyndrome -The experience of a National Rett Center. Epilepsia, Vol.51, No.7,
pp. 1252-1258.

Orsmond, G.I.; Kuo, H.Y. & Seltzer, M.M. (2009). Siblings of Individuals with an Autism
Spectrum Disorder: Sibling Relationships and Wellbeing in Adolescence and
Adulthood.Autism, Vol.13, No.1, pp. 59-80.

Orsmond, G.I. & Seltzer, M.M. (2009). Adolescent Siblings of Individuals with an Autism
Spectrum Disorder: Testing a Diathesis-Stress Model of Sibling Well-Being. J
Autism Dev Disord, Vol.39, No.7, pp. 1053-1065.

Pearson, D.A.; Loveland, K.A.; Lachar, D.; Lane, D.M.; Reddoch, S.L.; Mansour, R. &
Cleveland, L.A. (2006).A Comparison of Behavioral and Emocional in Children and
Adolescents With Autistic Disorder and PDD-NOS. Child Neuropsychol, Vol.12,
No.4-5, pp. 321-333.

Peters, K.F. & Petrill, S.A. (2011).Development of a Scale to Assess the Background, Needs,
and Expectations of Genetic Counseling Clients. Am J Med Genet A. Feb 23. doi:
10.1002/ajmg.a.33610. [Epub ahead of print]

Ratajczak, H.V. (2011). Theoretical Aspects of Autism: Causes - a Review. J Immunotoxicol,
Vol.8, No.1, pp. 68-79.

Schmidt, G.L.; Kimel, L.K.; Winterrowd, E.; Pennington, B.F.; Hepburn, S.L. & Rojas, D.C.
(2008). Impairments in Phonological Processing and Nonverbal Intellectual
Function in Parents of Children With Autism. J Clin Exp Neuropsychol, Vol.30, No.5,
pp. 557-567.

Selkirk, C.G.; McCarthy Veach, P.; Lian, F.; Schimmenti, L. & LeRoy, B.S. (2009). Parents'
Perceptions of Autism Spectrum Disorder Etiology and Recurrence Risk and Effects
of their Perceptions on Family Planning: Recommendations for Genetic Counselors.
J Genet Couns, Vol.18, No.5, pp. 507-519.

Shen, Y.; Dies, K.A.; Holm, I.A.; Bridgemohan, C.; Sobeih, M.M.; Caronna, E.B. Miller, K.J.;
Frazier, J.A.; Silverstein, I.; Picker, J.; Weissman, L.; Raffalli, P.; Jeste, S.; Demmer,
L.A.; Peters, H.K.; Brewster, S.J.; Kowalczyk, S.J.; Rosen-Sheidley, B.; McGowan, C.;
Duda, A.W. 3rd; Lincoln, S.A.; Lowe, K.R.; Schonwald, A.; Robbins, M.; Hisama, F.;
Wolff, R.; Becker, R.; Nasir, R.; Urion, D.K.; Milunsky, J.M.; Rappaport, L.; Gusella,
J.F.; Walsh, C.A.; Wu, B.L. & Miller, D.T. Autism Consortium Clinical
Genetics/DNA Diagnostics Collaboration. (2010). Clinical Genetic Testing for
Patients With Autism Spectrum Disorders. Pediatrics, Vol.125, No.4, pp. e727-735.

Smith, L.E.; Greenberg, J.S.; Seltzer, M.M. & Hong, J. (2008). Symptoms and Behavior Problems
of Adolescents and Adults With Autism: Effects of Mother-Child Relationship
Quality, Warmth, and Praise. Am J Ment Retard, Vol.113, No.5, pp. 387-402.

Smith, L.O. & Elder, J.H. (2010). Siblings and Family Environments of Persons With Autism
SpectrumDisorder: a Review of the Literature. J Child Adolesc Psychiatr Nurs, Vol.23,
No.3, pp. 189-195.

Snow, A.V. & Lecavalier, L. (2011). Comparing Autism, PDD-NOS, and Other
Developmental Disabilities on Parent-Reported Behavior Problems: Little Evidence
for ASD Subtype Validity. J Autism Dev Disord, Vol.41, No.3, pp. 302-310.

Sykes, N.H. & Lamb, J.A. (2007). Autism: the Quest for the Genes. Expert Rev Mol Med, Vol.9,
No.24. pp. 1-15.

Page 210

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



198

Temudo, T.; Santos, M.; Ramos, E.; Dias, K.; Vieira, J.P.; Moreira, A.; Calado, E.; Carrilho, I.;
Oliveira, G.; Levy, A.; Barbot, C.; Fonseca, M.; Cabral, A.; Cabral, P.; Monteiro, J.;
Borges, L.; Gomes, R.; Mira, G.; Pereira, S.A.; Santos, M.; Fernandes, A.; Epplen,
J.T.; Sequeiros, J. & Maciel, P. (2011). Rett syndrome With and Without Detected
MECP2 Mutations: An Attempt to Redefine Phenotypes. Brain Dev, Vol.33, No.1,
pp. 69-76.

Tuchman, R.; Cuccaro, M. & Alessandri, M. (2010). Autism and Epilepsy: Historical
Perspective. Brain Dev, Vol.32, No.9, pp. 709-718.

Vorstman, J.A.; Staal, W.G.; van Daalen, E.; van Engeland, H.; Hochstenbach, P.F. & Franke,
L. (2006). Identification of Novel Autism Candidate Regions Through Analysis of
Reported Cytogenetic Abnormalities Associated With Autism. Mol Psychiatry,
Vol.11, No.1, pp. 18-28.

Wachtel, K. & Carter, A.S. (2008).Reaction to Diagnosis and Parenting Styles Among
Mothers of Young Children with ASDs. Autism, Vol.12, No.5, pp. 575-594.

Wassink, T.H.; Losh, M.; Piven, J.; Sheffield, V.C.; Ashley, E.; Westin, E.R. & Patil, S.R.
(2007). Systematic for Subtelomeric Anomalies in a Clinical Sample of Autism. J
Autism Dev Disord,Vol.37, No.4, pp. 703-708.

Weil, J. (2000). Psychosocial Genetic Counseling. Oxford, ISBN 978-019-512066-0, New York,
USA.

WHO.World Health Organization (1998). Proposed International Guidelines on Ethical Issues in
Medical Genetics and Genetic Services: Report of WHO Meeting on Ethical Issues in
Medical Genetics. World Health Organization, Geneva.

WHO (2010). Community Genetics Services: Report of WHO Consultation on Community Genetics
in Low- and Middle-Income Countries. World Health Organization, Geneva.

Witwer, A.N. & Lecavalier, L. (2008). Examining the Validity of Autism Spectrum Disorder
Subtypes. J Autism Dev Disord, Vol.38, No.9, pp. 1611-1624.

Wood, J.J.; Drahota, A.; Sze, K.; Van Dyke, M.; Decker, K.; Fujii, C.; Bahng, C.; Renno, P.;
Hwang, W.C. & Spiker, M. (2009). Brief Report: Effects of Cognitive Behavioral
Therapy on Parent-Reported Autism Symptoms in School-Age Children With
High-Functioning Autism.J Autism Dev Disord, Vol.39, No.11, pp. 1608-1612.

Woodgate, R.L.; Ateah, C. &Secco, L. (2008). Living in a World of Our Own: the Experience
of Parents Who Have a Child With Autism. Qual Health Res, Vol.18, No.8, pp. 1075-
1083.

Zhang, X.; Lv, C.C.; Tian, J.; Miao, R.J.; Xi, W.; Hertz-Picciotto, I. & Qi, L. (2010). Prenatal
and Perinatal Risk Factors for Autism in China. J Autism Dev Disor, Vol.40, No.11,
pp. 1311-21.

Zahir, F.R. & Brown, C.J. (2011). Epigenetic Impacts on Neurodevelopment:
Pathophysiological Mechanisms and Genetic Modes of Action. Pediatr Res, Feb 2.
[Epub ahead of print]

Similer Documents