Published in Volume
119, Issue 4
(April 1, 2009)J Clin Invest.
Copyright © 2009, American Society for Clinical
The genetic and neurobiologic compass points toward common signaling
dysfunctions in autism spectrum disorders
Vanderbilt Kennedy Center for Research on Human Development and
Department of Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee,
Address correspondence to: Pat Levitt, Zilkha Neurogenetic Institute, Keck
School of Medicine of University of Southern California, 1501 San Pablo Street, Los
Angeles, California 90087, USA. Phone: (323) 442-1509; Fax: (323) 442-2145; E-mail:
Published April 1, 2009
Autism spectrum disorder (ASD) is a common neurodevelopmental disorder with high
heritability. Here, we discuss data supporting the view that there are at least two
distinct genetic etiologies for ASD: rare, private (de novo) single gene mutations
that may have a large effect in causing ASD; and inherited, common functional
variants of a combination of genes, each having a small to moderate effect in
increasing ASD risk. It also is possible that a combination of the two mechanisms may
occur in some individuals with ASD. We further discuss evidence from individuals with
a number of different neurodevelopmental syndromes, in which there is a high
prevalence of ASD, that some private mutations and common variants converge on
dysfunctional ERK and PI3K signaling, which negatively impacts neurodevelopmental
events regulated by some receptor tyrosine kinases.
Autism spectrum disorder (ASD) is a syndrome characterized by a triad of core deficits:
disturbances in social behavior, atypical verbal and nonverbal communication, and
restricted interests that can be accompanied by repetitive behavior. The clinical
diagnosis, which includes individuals with any one of a spectrum of neurodevelopmental
conditions (including autism, Rett syndrome, pervasive developmental
disorder–not otherwise specified, and Asperger syndrome), is made in 1 of every
150 individuals and is four times more prevalent in boys than girls (1). While ASD is among the most heritable psychiatric disorders defined
in the Diagnostic and statistical manual of mental disorders (4th edition)
(2), it is not a static or simple disorder with
fixed effects on a circumscribed age. Instead, equally fundamental facets of pathology
emerge at different points of maturation of the child. Moreover, the disorder does not
result in immutable social and cognitive deficits, but rather the core symptoms typically
change over time and to different degrees. Co-occurring medical conditions (sleep problems,
epilepsy, and gastrointestinal symptoms) and psychiatric disturbances (anxiety,
obsessive-compulsive disorder, and aggression) are common and can appear at different ages
in children on the spectrum.
Contemporary hypotheses of the causes of ASD often include experience-dependent processes
through which atypical gene-by-environment (G X E) interactions yield pathophysiology in
later emerging systems that underlie social and communication competencies. The later
emergence of symptoms is consistent with the concept that developmental differentiation,
whether at the cellular, circuit, or systems level, occurs from the bottom up; behavior
develops from basic sensory and perceptual systems that feed into higher integration
centers (3–5). Impairments in initial basic processes become expressed in ever more complex
systems, with the population heterogeneity of the clinical features of ASD expected to
increase from infancy to childhood and through adolescence. However, it is not clear
whether the factors that contribute to the developmental diversification and phenotypic
heterogeneity of ASD are related to a complex genetic etiology of ASD itself or whether
they also involve the interaction between ASD-specific and -nonspecific functional
Clinical researchers have noted the importance of addressing disorder heterogeneity in the
study of ASD (6–8). In this regard, the conundrum facing investigators is connecting the
well-defined, highly heritable nature of ASD with the striking differences in the initial
expression of core symptoms, progressive changes over time, and differential response to
interventions. Thus, a major goal of the current interdisciplinary research agenda is not
only to explain the etiologies of ASD but also to understand the syndrome-specific and
-nonspecific factors that influence variability in the relative risk of developing ASD, in
the developmental course of symptom presentation, in the responsiveness to treatment, and
in the co-occurrence of other medical dysfunctions (6, 8–11). This Review highlights the current understanding of ASD genetics,
key pathophysiological findings from behavior and imaging studies, and potential G X E
interactions that may be at the core of ASD expression. The Review ends with what we
believe to be a novel hypothesis that combines recent genetic findings to propose one
potential mechanism of heterogeneity in ASD.
Distinct genetic mechanisms can result in ASD
Based on studies in mono- and dizygotic twins (12, 13), the estimated heritability of
ASD is approximately 0.90. This far exceeds the estimated heritability of other common
polygenic diseases, including cancer, heart disease, schizophrenia, and depression. The
focus, therefore, on defining the underlying genetic etiology of ASD has escalated
dramatically during the current decade, in parallel with the rapid development of
affordable genomic methods that have facilitated the analysis of large populations and
entire genomes. Like other complex disorders, however, the most critical challenges of
the field lie in defining the heritability of risk for developing ASD that may be due to
G X E factors that alter the trajectory of brain development and the direct impact of de
novo or heritable gene variation on brain development. ASD is a spectrum of disorders,
in which there are differences in the degree of severity of the three core symptoms as
well as other co-occurring mental health and physical conditions. Thus, to emphasize the
functional importance of recognizing many different kinds of ASD, the term
“autisms” has been used (14). The behaviors that are disrupted in ASD are complex and develop through a
bottom-up assembly of simple to more complex brain circuits that control very basic
processes such as physiological homeostasis and more complex tasks such as being
motivated to pay attention to certain cues in the environment that regulate outward
social behavior and verbal and nonverbal communication. The heterogeneity of ASD is
entirely consistent with the concept that different genetic mechanisms may influence
brain circuit development at different levels of the hierarchy (5). The field thus is moving away from defining the ASD genes to
defining unique phenotypic features of stratified populations of children, adolescents,
and adults that may relate to specific genetic etiologies, such as increased risk due to
common allelic variations, rare mutations, or copy number variation (CNV) (Figure 1). Implicit in this view is that there will not be
identification of genetic risks that map one-to-one with behavioral dysfunction; that
is, while there are genetic variants that are enriched in populations with particular
dysfunctions, such as language, there are no genes that directly
regulate social behavior or language. Instead, genetic vulnerability resides in the
disruption of cellular processes, due to the disruption of proteins encoded by genes, in
specific brain circuits that may also be influenced by G X E mechanisms. Research
findings emerging from human genetic and animal studies suggest that disruption of a key
developmental process, synapse formation and stabilization (synaptogenesis), is a final
common path in ASD etiology. Different molecular mechanisms may contribute to increasing
ASD risk, including disturbances in the assembly of structural proteins needed to build
synapses, such as the neuroligins and neurexins, and dysfunctional cellular signaling
pathways that control synaptogenesis.
Current experimental approaches to determining genetic etiologies for ASD. These approaches include whole-genome analyses that identify disorder-related
sequences or CNVs in genes that exhibit preferential inheritance patterns or de
novo appearance in individuals with ASD. The current challenges include the
translation of these genetic findings to define the biological consequences of the
variations, to determine the influence on defined clinical phenotypes of ASD, and
eventually to design new intervention strategies.
Distinct patterns of heritability of risk alleles in ASD
As noted above, ASD is highly heritable, and current studies suggest that there are
multiple mechanisms through which different types of gene mutations increase risk of
developing the disorder (15–17). There are a number of considerations that are
key to successful genetic studies of ASD. First, because of the heterogeneity of the
disorder, it is necessary to analyze large numbers of individuals with ASD. Second, each
individual gene is likely to have very small effects on disease risk, but in combination
with other genes and/or G X E factors, an individual gene may encode a protein that
functions in a key cellular process, which, when disrupted, contributes to disease
pathophysiology. Third, disorder emergence through de novo genetic mutations or
heritability of gene-specific functional polymorphisms in the DNA sequence transmitted
from parent to child may underlie distinct but equivalently valid ASD etiologies.
Fourth, distinct genetic etiologies, together with different environmental factors, may
be part of ASD heterogeneity. Last, the nature of the core behavioral dimensions that
characterize ASD emerge through perturbation of developing brain circuits. Disruption at
distinct levels of the organizational and functional hierarchy relate to the
heterogeneity in social behavior and communication capabilities.
The aim of genetic studies of ASD should be to identify functional variants that
contribute to ASD risk. A thorough recent review provides a detailed listing of
up-to-date genetic findings (16). One approach
with great promise for the identification of candidate genes and pathways is analysis of
CNV (see The basics of CNVs) (18, 19). However, as with single gene
mutations and common variants, CNV analyses need to be interpreted with extreme caution
for a number of reasons. First, the presence of a de novo CNV in an individual with ASD
does not necessarily imply it is associated with increased risk of developing the
disorder. Further, CNVs typically are not fully penetrant, meaning that they may be
present in individuals who do not have an ASD. CNVs were first described in healthy
control individuals, with more than 11 CNVs per individual (20), indicating that having multiple CNVs is not pathologic. Only
formal genetic association analyses involving large sample sizes should be used to imply
a particular CNV is associated with disorder risk. Second, the presence of a CNV does
not necessarily imply functional disruption. Analyses of CNVs in the human adult
cerebral cortex indicate that more than 50% of mature neurons are aneuploid (21, 22), and
experiments in mice indicate that CNVs in cortical neurons may have little impact on
function (23). Further, germline deletion of both
copies of certain genes in experimental animals can result in mutants without a
detectable phenotype. This suggests that due to adaptive processes, gene dosage in the
form of CNV does not lead necessarily to dramatic functional changes in vivo. Third, CNV
in peripheral blood cells, the cells typically analyzed in humans, may not relate in a
one-to-one fashion to CNVs in neurons. Indeed, the number of CNVs in the human cerebral
cortex is approximately 7-fold higher than in peripheral blood cells (21), and thus, analysis of peripheral blood may
identify some, but not necessarily all, of the CNVs occurring in neurons that contribute
to ASD-related disturbances of brain architecture and circuitry. Fourth, de novo CNVs
are observed in 7%–10% of cases from simplex families (families with only
one child with ASD), 2%–3% of cases from multiplex families (families with
more than one child with ASD), and 1% of controls (24, 25). The de novo CNVs that occur in a
subset of individuals with ASD in multiplex families may influence the severity of the
disorder, rather than contributing directly to the expression of the disorder. Despite
these cautions, CNV analysis can be used to identify candidate genes that can be tested
further for functional effects that may contribute to ASD susceptibility (18, 19).
We are beginning to recognize that inheritance of rare or common functional alleles is
only one genetic mechanism that increases disorder risk. Private (de novo) functional
mutations also impart genetic risk. Analyses suggest that, at the genetic and behavioral
levels, multiplex families may be fundamentally different from simplex families (24, 26–29). Furthermore,
multiple genes or even multiple mutations of the same gene may be involved in the
etiology of the same clinically diagnosed disorder in different individuals. For
example, there are over 50 genes that carry mutations known to cause nonsyndromic
retinitis pigmentosa (30). Conversely, there are
more than 130 distinct catalogued mutations of the 7-dehydrocholesterol
reductase (DHCR7) gene in individuals with the monogenic
disorder Smith-Lemli-Opitz syndrome (31).
Heritable, high-risk mutations in breast cancer, such as those in the breast cancer 1,
early onset (BRCA1) gene, are balanced by more common variants in
multiple genes discovered through whole-genome association studies (WGASs). Given the
range of possibilities for disorder etiology, sample numbers are clearly important. For
example, WGASs have examined between 500,000 and 1,000,000 SNPs simultaneously in
thousands of patient samples for diabetes and coronary artery disease (18, 32–34). These diseases,
with arguably less complex pathophysiology than ASD, only recently have had the sample
power to generate statistically reliable data that reveal common SNPs with
disease-related heritability patterns in multiple genes. Similarly, rare functional
mutations in ASD candidate risk genes initially may seem to be overrepresented in the
clinical population compared with unrelated controls, but recent analysis demonstrates
that even these types of studies more accurately reflect clinical findings when larger
sample populations are assessed (35).
Syndromic disorders and rare mutations point the way
Although not understood from an etiological or pathophysiological perspective, it is now
clear that rare neurodevelopmental disorders (<1 in 10,000) are becoming
increasingly important to study in greater detail because of their relationship to ASD.
Higher penetrance of ASD diagnosis (far greater than the 0.75% observed in the general
population) is reported in children who have genetically diverse neurodevelopmental
syndromic disorders, including Angelman syndrome, Fragile X syndrome (FraX), Rett
syndrome, Smith-Lemli-Opitz syndrome, Timothy syndrome, neurofibromatosis, and tuberous
sclerosis. It is important to emphasize that each syndrome is characterized by
fundamentally different gene mutations, which presumably impart distinct molecular
pathophysiologies (Table 1). However, there are
few studies that examine closely the similarities and differences in phenotypic
characteristics between single gene (syndromic) and multigenic (idiopathic) ASD (36). The neurodevelopmental syndromic disorders
listed in Table 1 are characterized in part by
intellectual disability (ID; formally termed mental retardation). A large minority
(25%–40%) of individuals with ASD has ID, but ASD is not synonymous with ID.
A recent structural MRI study suggests that individuals with FraX, with or without ASD
diagnosis, are more closely related in the context of the size of brain structures than
those with idiopathic ASD (37). Microarray
analysis of lymphocytes from patients with FraX, chromosome 15q deletion, or idiopathic
ASD reveal unique patterns of gene expression that may serve as a signature for each
disorder, but with a potentially important small subset of overlapping changes in mRNA
expression (38). Moreover, detailed
neuropathological studies are lacking to compare these syndromes and idiopathic ASD.
Although there is likely to be diversity in the pathological targets in each syndrome,
there are suggestions of some commonalities. The triad of overlapping dysfunctions
(social behavior, communication, and repetitive behavior) across ASD and the syndromes,
together with the known brain neuropathology of some of the syndromes, suggests that
later neurodevelopmental events, such as synapse formation and maturation, dendritic
growth, and myelination, are probably most vulnerable. In addition to the evidence from
syndromic disorders, the focus on later events in this Review is supported by the
discovery of rare mutations in certain genes that regulate synaptogenesis. A substantial
focus has been on the adhesive and structural elements needed for synapse formation,
stability, and physiologic maturation. In ASD cases, rare mutations and CNVs have been
identified in genes encoding neuroligins, neurexins, contactin-associated protein-2
(CNTNAP2), and SH3 and multiple ankyrin repeat domains 3 (SHANK3). The disruptions are
likely to occur in shared forebrain and cerebral cortical circuits. Thus, while not
identical to idiopathic ASD, biological and behavioral analyses of syndromic disorders
and rare mutations provide a sound approach to discern potential overlapping molecular
and brain targets (Table 1).
Rare syndromic disorders with ASD co-occurrence
Intracellular kinase signaling in ASD-associated disorders
The potential contribution of defects in adhesion and structural proteins that build
synapses to the etiology of ASD has been the subject of many reviews of ASD (16, 17, 39–41). In this Review, we suggest that some neurodevelopmental syndromic disorders
and rare mutations point to an additional set of molecular targets. Thus, recognizing
that we are attempting to resolve a spectrum of disorders that will not have a single,
underlying etiology, findings from studies of certain syndromic disorders with high
penetrance of ASD converge on the ERK and PI3K intracellular signaling pathways that we
believe deserve increased scrutiny in all forms of ASD. ERK and PI3K activate mammalian
target of rapamycin (mTOR), which through other kinases will increase mRNA translation
to influence developmental functions as diverse as the cell cycle, cell survival,
differentiation, and motility. Receptor tyrosine kinases (RTKs) can signal through
either of these intracellular kinase pathways, with cell type and cellular milieu
defining the intracellular response (Figure 2).
Table 1 reports several syndromic disorders with
high penetrance of ASD that involve a primary disruption in signaling through these
pathways specifically and others that would disrupt RTK signaling, the primary membrane
receptor class that transduces signals through ERK and PI3K. The most convincing
connections between ERK/PI3K signaling disruption and ASD are evident in tuberous
sclerosis and neurofibromatosis type 1, in which different elements of the ERK/PI3K
pathway are disrupted genetically, leading to enhanced mTOR downstream activation
(Figure 2). In addition, ERK and PI3K signaling is
dependent in part on normal cholesterol biosynthesis, which is absent in
Smith-Lemli-Opitz syndrome. For example, Ras signaling, a key upstream mediator of ERK
activation, requires cholesterolization. Rare gene mutations of another element of the
PI3K signaling pathway, phosphatase and tensin homolog (PTEN),
are associated with high prevalence of ASD. Rett syndrome disrupts the X-linked methyl
CpG binding protein 2 (MECP2) gene, which encodes a protein
that binds to specific regulatory regions of certain genes (based on DNA methylation
patterns) that control gene transcription. Methylation status and/or MECP2 binding
directly regulates transcription of key genes involved in met
proto-oncogene–RTK signaling (MET RTK signaling; MET is also known as HGFR),
which our laboratory has implicated in ASD risk (see below). Those genes include those
encoding MET, the MET coreceptor CD44, the MET transcriptional
regulator SP1, and several proteins in the ERK/PI3K downstream signaling pathway (42).
The MET RTK signaling pathway and genes implicated in ASD risk. Intracellular signaling of MET and other RTKs occurs via the PI3K or ERK1/2
pathways. Rare mutations and CNVs (which are both designated by ‡) or
associated common alleles (which are designated by *) have been identified in
individuals with ASD in seven genes encoding proteins involved in these signaling
pathways. Of note, an association between common MET variants and ASD has been
reported for five independent family cohorts. PLAUR and SERPINE1 associations with
ASD have been determined in single, large family cohorts (>600 families).
Ras disruption in Smith-Lemli-Opitz syndrome is due to alterations in cholesterol
biosynthesis (which is designated by †). Also depicted are other
proteins that interact with the MET signaling pathway, such as semaphorins,
plexins, and other RTKs. MET can signal via the PI3K and the ERK pathway. RTKs,
including MET, are involved in key neurodevelopmental processes, including axon
guidance, synapse formation, and plasticity. Convergence of many different genetic
etiologies suggests that risk via ERK/PI3K signaling may be common in ASD. Risk,
severity of the pathophysiology (i.e., intellectual disability), and disorder
heterogeneity may relate to differences in genetic and epigenetic points of entry
to the pathways. Thus, the impact due to genetic risk, via regulators of ligand
availability or RTKs such as MET, may be less severe than the more severe clinical
impact (i.e., intellectual disability) from disruption downstream along the
intracellular signaling pathways. c-cbl, E3 ubiquitin-protein ligase c-Cbl; rheb,
Ras homolog enriched in brain; RSK, ribosomal S6 kinase; uPA, urokinase
The various neurodevelopmental syndromic disorders and rare mutations described thus far
along the ERK/PI3K pathways result in an increased state of activation of mTOR (Figure
2). Additional evidence for involvement of these
intracellular kinase pathways in ASD comes from recent treatment studies in genetically
engineered mice that exhibit behavioral and neuropathologic phenotypes that are common
in the human neurodevelopmental syndromic disorders. For example, systemic
administration of drugs that reduce mTOR activation, such as rapamycin, wortmannin, and
RAD001, can reverse behavioral and structural pathology in mice with
Pten (43), tuberous sclerosis 1
(Tsc1) (44, 45), and neurofibromin 1 (Nf1)
(46, 47) mutations, with no reported side effects.
ASD etiologies also are likely to include environmental factors that work together with
genetic risk to drive neurodevelopment systems over the threshold for disorder
expression (Figure 3). We therefore hypothesize
that different genetic routes to altered RTK function, by way of modulation of ERK/PI3K
signaling pathways, combine with environmental factors, such as biochemical stressors,
that also modulate these signaling pathways. The G X E interactions either modulate the
degree of dysfunction of the core clinical features of ASD or have an impact on
neurobiological circuits that are at greater risk for dysfunction, because genetic
vulnerability pushes the system closer to disorder threshold.
Contributions of the PI3K pathway to ASD risk threshold. The degree of genetic risk is indicated by shading, with darker color indicating
increased risk. The model presents common functional variants in the
MET, PLAUR, and SERPINE1 genes
that, along with other genetic risk alleles, contribute to risk of developing ASD.
Adaptive processes may prevent presentation of ASD, but additional environmental
factors or the presence of multiple risk alleles result in idiopathic (multiple
genes, each having a small effect) ASD. Mutations further down the PI3K pathway
result in syndromic disorders, with penetrance and phenotype severity determined
by a decreasing availability of adaptive processes.
Given that ERK/PI3K signaling is widely distributed throughout multiple organ systems,
where does disorder specificity arise? One way to think about the issue of specificity
is to recognize that signaling through ERK/PI3K is highly influenced by cell type and
timing of activation of the RTK signaling systems. For example, there is a potential
dichotomy in the molecular mechanisms of ASD and cancer that would involve different
genetic risk factors affecting ERK/PI3K signaling. Unequivocal evidence implicates
hyperactivated PI3K signaling in a number of malignant cancer types (48–50). In contrast, decreased PI3K activation may contribute in some instances to
ASD (26, 51, 52). We are unaware of any studies of
cancer frequencies in individuals with ASD. However, disruption of PI3K signaling also
has been implicated in other psychiatric disorders of neurodevelopmental origin, such as
schizophrenia (53, 54). An altered incidence of various cancers in individuals with
schizophrenia is debated (55, 56), but reduced cancer incidence is observed
consistently in parents and siblings of individuals with schizophrenia compared with the
general population (57–59). These data support the plausibility of a
genetic impact, through different mutations or common variants, that increases risk for
a neurodevelopmental disorder and decreases cancer risk, a hypothesis that can be tested
by epidemiological studies and complete sequencing of candidate genes to identify
mutations associated with specific disorders.
One testable facet of our hypothesis is that risk for more global neurodevelopmental
disruptions increases when the genetic hits are downstream from the
molecular components that are involved in initial RTK activation, which are the growth
factors or receptors themselves. Consistent with this, mutations in
NF1, AKT, TSC1, and
TSC2 typically result in widespread and severe clinical problems such
as mild to severe intellectual disabilities, seizure disorder, sensory-motor deficits,
and medical dysfunctions (Figure 3). The corollary
to this would be that mutations in upstream genes encoding RTKs or proteins
that regulate growth factor availability would place signaling through this pathway at
risk but require additional genetic and environmental insults to cause
neurodevelopmental disruption. Disruption of the development of specific brain circuits
would occur, because, unlike their intracellular mediators, upstream signaling elements
are not distributed uniformly. Rather, RTKs and growth factors may be concentrated in
developing circuits at key periods of development that mediate the maturation of
connections underlying specific functions. This hypothesis is consistent with the
identification of neuregulin 1 (the ligand for the RTK ERBB4) as a factor for
schizophrenia susceptibility (60) and the RTK MET
as a factor for ASD risk (26, 27, 52).
Although both ERBB4 and MET activate PI3K signaling, the differential timing and
patterns of expression of each of these RTKs in developing cerebral cortex (61) may account for the distinct neurodevelopmental
disruptions characteristic of each disorder. We have shown that MET is enriched in
neocortex, amygdala, septum, and cerebellum, regions implicated in ASD (62).
MET in PI3K signaling and ASD
Our own genetic and neuropathological studies of ASD have focused on one of the upstream
activators of both ERK and PI3K in various cell types, MET. Much is known about its role
in PI3K signaling. Specifically, HGF activation of MET causes phosphorylation of AKT
that can be blocked by the PI3K inhibitors LY294002 and wortmannin (63–65). Most relevant to the current discussion, MET activation of PI3K signaling
has been demonstrated in neuronal cells, resulting in neuroprotection of cerebellar
granule cells (63), cell motility in striatal
progenitor cells (66), and protection of cortical
neurons from hypoxia-induced insult (67).
It is again important to emphasize that the phenotypic heterogeneity of ASD makes it
unlikely that any individual gene will contribute to more than a subset of cases. This
creates a natural tension in the field that is attempting to translate genetic findings
into plausible biological models of ASD. Thus, there currently is legitimate skepticism
regarding any particular candidate gene (16,
17). However, both convergent neurobiological
and genetic evidence is emerging to suggest ASD vulnerability may lie, in part, in the
well-defined MET signaling pathway. Our initial decision to examine the RTK
MET gene as an ASD risk candidate was based on several factors,
including the location of the gene under a broad linkage peak on chromosome 7 that has
been replicated multiple times (68–72) as a region
carrying ASD risk genes, as well as a number of developmental neurobiology findings that
implicate MET signaling in forebrain circuit development. MET activation by HGF
modulates forebrain interneuron motility in vitro (73). Excitatory/inhibitory imbalance has been postulated to occur in ASD (74, 75).
Moreover, in mice gene targeting of the MET signaling pathway, through deletion of the
gene encoding plasminogen activator, urokinase receptor (Plaur), which controls levels
of HGF, results in reduced numbers of neocortical interneurons, spontaneous seizures
(which occur in 20%–30% of children with ASD), increased anxiety, and
reduced social interactions (76–78). Additionally, MET signaling participates in
autonomic nervous system and cerebellar development, immune function, and
gastrointestinal function and repair (79–84). Disruptions of
these neural and peripheral elements have been reported in ASD (85–90).
Candidate gene analyses often fail to generate replicable findings due to small effects
in a limited number of samples. In the case of the MET signaling cascade (Figure 2), however, the pathophysiologic and genetic evidence
of its contribution to ASD risk is now considerable. First, the expression of MET
protein is reduced by approximately 2-fold in the postmortem temporal neocortex of
individuals with ASD compared with age- and gender-matched controls (52). Second, several thousand samples have been
genotyped to reveal significant association of the MET promoter
rs1858830 C allele with ASD risk in a 204-family Italian cohort, a larger 539-family US
replication cohort (26), and a third, distinct
cohort of 101 US families (27). Third, the
ASD-associated MET promoter allele is functional in cell-based assays,
reducing dramatically the binding of the transcription factor SP1 to the
MET promoter and reducing transcription from the MET
promoter by approximately 2-fold (26). Fourth,
the rs38845 A allele in intron 1 of MET is associated with ASD risk in
a cohort of 335 International Molecular Genetic Study of Autism Consortium families
(91). The same research group replicated
association of this allele with ASD risk in an Italian case-control sample (91). Fifth, in addition to the SNP alleles that may
regulate MET transcription, 2 of 26 cases with ASD in which rare de
novo CNV losses were observed, had CNV losses of the chromosome 7 region, including the
MET gene (25). Sixth,
although not statistically significant, direct resequencing of the 21
MET exons in several hundred cases and controls identified functional
mutations that are more prevalent in the cases compared with controls (26). The mutations alter the juxtamembrane region of
MET, which regulates receptor activation (92).
Last, five other genes in the MET signaling pathway were examined in a large family
cohort. Two of the genes, PLAUR and serpin peptidase inhibitor, clade E
(nexin, plasminogen activator inhibitor type 1), member 1 (SERPINE1),
are associated with increased ASD risk (27), and
each mRNA exhibits altered expression in the postmortem cerebral cortex of individuals
with ASD compared with age- and gender-matched controls (52).
The genetic findings from our own studies and those gathered from analysis of defined
neurodevelopmental syndromic disorders implicate PI3K signal disruption in both
multigenic and syndromic ASD. The observation that de novo CNV is substantially more
common in simplex families than multiplex families (24, 25) suggests that private mutations,
along with other rare functional mutations, may contribute to ASD. In contrast,
association of the risk alleles in MET (26, 91) and the MET-regulating genes
PLAUR and SERPINE1 (27) is found only in multiplex families and is therefore linked to
multigenic, idiopathic ASD. Heritability of common risk alleles in multiplex families
also is reflected in behavioral profiles in parents of children with ASD. Thus, the
broader autism phenotype is found to a far greater extent in parents from multiplex
compared with simplex families (28, 29), suggesting that heritable, rather than de novo
mechanisms for ASD expression occur in multiplex families. Collectively, there seem to
be a number of different genetic etiologies that can contribute to altering MET
signaling in many individuals with ASD.
G X E interactions in ASD etiology
Beyond multiple genetic elements implicated in ASD risk, the MET/PI3K pathway also is
highly vulnerable to environmental perturbations. For example, increasing the redox
state of oligodendrocyte progenitor cells by brief exposure to lead or mercury activates
c-Cbl–regulated internalization and degradation of certain RTKs, including
MET, EGFR, and PDGFR (93). Not all RTKs are
affected by stressing cells through altering redox state. The reason for selective
vulnerability of MET and other RTKs is not known. Irrespective of the mechanism, the
cell stressor results in reduced signaling through ERK/PI3K. Benzo(a)pyrine (BaP), a
common chemical in vehicle exhaust, paper and wood processing, and trash incineration,
disrupts the binding of transcription factors such as SP1 to DNA targets (94, 95). This
is relevant to MET expression and perhaps ASD, because the normal level of binding of
SP1 is reduced by the ASD-associated rs1858830 C allele (25). A testable hypothesis would be to combine the MET risk
allele with exposure to BaP to examine how the double hit affects
expression levels. The findings from the studies involving cell stressors and toxic
chemicals suggest additional ways in which genetic risk due to regulatory alleles may
combine with environmental factors to shift a system closer to disease threshold (Figure
ASD heterogeneity needs to be considered more seriously in developing strategies to
investigate underlying biological etiologies. Within syndromic and multigenic ASDs,
functional profiles are diverse. Heterogeneity at the genetic level may be probed more
strategically by using much larger sample populations, as has been done for diabetes and
cardiovascular disease. Technology development will continue to facilitate the larger
scale association and deep sequencing studies that will generate new candidates and
validate current risk factors. We believe it is important not to lose sight of the
long-term challenge, which will be to translate the genetic risk of ASD into
biologically plausible mechanisms (Figure 1) that
can lead to earlier diagnosis and individualized treatments. Although a number of
signaling pathways are likely to be involved, the recent surge of convergent findings on
the MET and ERK/PI3K signaling pathways, together with the data implicating key
structural and adhesion proteins in synapse formation and maturation brings us closer to
defining one cellular process that may serve to help us identify new, credible
biomarkers and treatment targets.
Newschaffer, C.J., et al. 2007. The epidemiology of autism spectrum disorders. Annu. Rev. Public Health. 28:235-258.
American Psychiatric Association. 1994.Diagnostic and statistical
manual of mental disorders. 4th edition. American Psychiatric
Association. Washington, DC, USA. 886 pp.
Knudsen, E.I. 2004. Sensitive periods in the development of the brain and behavior. J. Cogn. Neurosci. 16:1412-1425.
Thatcher, R. 1994. Psychopathology of early frontal lobe damage: dependence on cycles of
development. Dev. Psychopathol. 6:565-596.
Hammock, E.A.D., Levitt, P. 2006. The discipline of neurobehavioral development: the emerging interface
of processes that build circuits and skills. Hum. Dev. 49:294-309.
Dawson, G., et al. 2002. Defining the broader phenotype of autism: genetic, brain, and
behavioral perspectives. Dev. Psychopathol. 14:581-611.
Beauchaine, T.P., Strassberg, Z., Kees, M.R., Drabick, D.A. 2002. Cognitive response repertoires to child noncompliance by mothers of
aggressive boys. J. Abnorm. Child Psychol. 30:89-101.
Piven, J. 2001. The broad autism phenotype: a complementary strategy for molecular
genetic studies of autism. Am. J. Med. Genet. 105:34-35.
Devlin, B., et al. 2005. Autism and the serotonin transporter: the long and short of it. Mol. Psychiatry. 10:1110-1116.
Rutter, M. 1996. Autism research: prospects and priorities. J. Autism Dev. Disord. 26:257-275.
Volkmar, F.R., Lord, C., Bailey, A., Schultz, R.T., Klin, A. 2004. Autism and pervasive developmental disorders. J. Child Psychol. Psychiatry. 45:135-170.
Bailey, A., et al. 1995. Autism as a strongly genetic disorder: evidence from a British twin
study. Psychol. Med. 25:63-77.
Steffenburg, S., et al. 1989. A twin study of autism in Denmark, Finland, Iceland, Norway and
Sweden. J. Child Psychol. Psychiatry. 30:405-416.
Geschwind, D.H., Levitt, P. 2007. Autism spectrum disorders: developmental disconnection syndromes. Curr. Opin. Neurobiol. 17:103-111.
Veenstra-Vanderweele, J., Christian, S.L., Cook (Jr.), E.H. 2004. Autism as a paradigmatic complex genetic disorder. Annu. Rev. Genomics Hum. Genet. 5:379-405.
Abrahams, B.S., Geschwind, D.H. 2008. Advances in autism genetics: on the threshold of a new neurobiology. Nat. Rev. Genet. 9:341-355.
O’Roak, B.J., State, M.W. 2008. Autism genetics: strategies, challenges, and opportunities. Autism Res. 1:4-17.
Craddock, N., O’Donovan, M.C., Owen, M.J. 2008. Genome-wide association studies in psychiatry: lessons from early
studies of non-psychiatric and psychiatric phenotypes. Mol. Psychiatry. 13:649-653.
Cook (Jr.), E.H., Scherer, S.W. 2008. Copy-number variations associated with neuropsychiatric conditions. Nature. 455:919-923.
Sebat, J., et al. 2004. Large-scale copy number polymorphism in the human genome. Science. 305:525-528.
Rehen, S.K., et al. 2005. Constitutional aneuploidy in the normal human brain. J. Neurosci. 25:2176-2180.
Kingsbury, M.A., Yung, Y.C., Peterson, S.E., Westra, J.W., Chun, J. 2006. Aneuploidy in the normal and diseased brain. Cell. Mol. Life Sci. 63:2626-2641.
Kingsbury, M.A., et al. 2005. Aneuploid neurons are functionally active and integrated into brain
circuitry. Proc. Natl. Acad. Sci. U. S. A. 102:6143-6147.
Sebat, J., et al. 2007. Strong association of de novo copy number mutations with autism. Science. 316:445-449.
Marshall, C.R., et al. 2008. Structural variation of chromosomes in autism spectrum disorder. Am. J. Hum. Genet. 82:477-488.
Campbell, D.B., et al. 2006. A genetic variant that disrupts MET transcription is associated with
autism. Proc. Natl. Acad. Sci. U. S. A. 103:16834-16839.
Campbell, D.B., Li, C., Sutcliffe, J.S., Persico, A.M., Levitt, P. 2008. Genetic evidence implicating multiple genes in the MET receptor
tyrosine kinase pathway in autism spectrum disorder. Autism Res. 1:159-168.
Losh, M., Sullivan, P.F., Trembath, D., Piven, J. 2008. Current developments in the genetics of autism: from phenome to
genome. J. Neuropathol. Exp. Neurol. 67:829-837.
Liu, X.Q., Paterson, A.D., Szatmari, P. 2008. Genome-wide linkage analyses of quantitative and categorical autism
subphenotypes. Biol. Psychiatry. 64:561-570.
Daiger, S.P., Bowne, S.J., Sullivan, L.S. 2007. Perspective on genes and mutations causing retinitis pigmentosa. Arch. Ophthalmol. 125:151-158.
Porter, F.D. 2008. Smith-Lemli-Opitz syndrome: pathogenesis, diagnosis and management. Eur. J. Hum. Genet. 16:535-541.
Todd, J.A., et al. 2007. Robust associations of four new chromosome regions from genome-wide
analyses of type 1 diabetes. Nat. Genet. 39:857-864.
Zeggini, E., et al. 2007. Replication of genome-wide association signals in UK samples reveals
risk loci for type 2 diabetes. Science. 316:1336-1341.
Samani, N.J., et al. 2007. Genomewide association analysis of coronary artery disease. N. Engl. J. Med. 357:443-453.
Bakkaloglu, B., et al. 2008. Molecular cytogenetic analysis and resequencing of contactin
associated protein-like 2 in autism spectrum disorders. Am. J. Hum. Genet. 82:165-173.
Kates, W.R., et al. 2007. Comparing phenotypes in patients with idiopathic autism to patients
with velocardiofacial syndrome (22q11 DS) with and without autism. Am. J. Med. Genet. A. 143A:2642-2650.
Gothelf, D., et al. 2008. Neuroanatomy of fragile X syndrome is associated with aberrant
behavior and the fragile X mental retardation protein (FMRP). Ann. Neurol. 63:40-51.
Nishimura, Y., et al. 2007. Genome-wide expression profiling of lymphoblastoid cell lines
distinguishes different forms of autism and reveals shared pathways. Hum. Mol. Genet. 16:1682-1698.
Persico, A., Bourgeron, T. 2006. Searching for ways out of the autism maze: genetic, epigenetic and
environmental clues. Trends Neurosci. 29:349-358.
Walsh, C.A., Morrow, E.M., Rubenstein, J.L.R. 2008. Autism and brain development. Cell. 135:396-400.
Zoghbi, H.Y. 2003. Postnatal neurodevelopmental disorders: meeting at the synapse? Science. 302:826-830.
Urdinguio, R.G., et al. 2008. Mecp2-null mice provide new neuronal targets for Rett syndrome. PLoS ONE. 3:e3669.
Kwon, C.H., Zhu, X., Zhang, J., Baker, S.J. 2003. mTor is required for hypertrophy of Pten-deficient neuronal soma in
vivo. Proc. Natl. Acad. Sci. U. S. A. 100:12923-12928.
Meikle, L., et al. 2008. Response of a neuronal model of tuberous sclerosis to mammalian target
of rapamycin (mTOR) inhibitors: effects on mTORC1 and Akt signaling lead to
improved survival and function. J. Neurosci. 28:5422-5432.
Ehninger, D., et al. 2008. Reversal of learning deficits in a Tsc2+/– mouse model of
tuberous sclerosis. Nat. Med. 14:843-848.
Costa, R.M., et al. 2002. Mechanism for the learning deficits in a mouse model of
neurofibromatosis type 1. Nature. 415:526-530.
Li, W., et al. 2005. The HMG-CoA reductase inhibitor lovastatin reverses the learning and
attention deficits in a mouse model of neurofibromatosis type 1. Curr. Biol. 15:1961-1967.
Network, T.C.G.A.R. 2008. Comprehensive genomic characterization defines human glioblastoma
genes and core pathways. Nature. 455:1061-1068.
Ding, L., et al. 2008. Somatic mutations affect key pathways in lung adenocarcinoma. Nature. 455:1069-1075.
Chalhoub, N., Baker, S.J. 2008. PTEN and the PI3-kinase pathway in cancer. Annu Rev Pathol.Online publication ahead of print. doi:
Serajee, F.J., Nabi, R., Zhong, H., Mahbubul Huq, A.H. 2003. Association of INPP1, PIK3CG, and TSC2 gene variants with autistic
disorder: implications for phosphatidylinositol signalling in autism. J. Med. Genet. 40:e119.
Campbell, D.B., et al. 2007. Disruption of cerebral cortex MET signaling in autism spectrum
disorder. Ann. Neurol. 62:243-250.
Harrison, P.J., Law, A.J. 2006. Neuregulin 1 and schizophrenia: genetics, gene expression, and
neurobiology. Biol. Psychiatry. 60:132-140.
Kanakry, C.G., Li, Z., Nakai, Y., Sei, Y., Weinberger, D.R. 2007. Neuregulin-1 regulates cell adhesion via an ErbB2/phosphoinositide-3
kinase/Akt-dependent pathway: potential implications for schizophrenia and cancer. PLoS ONE. 2:e1369.
Grinshpoon, A., et al. 2005. Cancer in schizophrenia: is the risk higher or lower? Schizophr. Res. 73:333-341.
Hippisley-Cox, J., Vinogradova, Y., Coupland, C., Parker, C. 2007. Risk of malignancy in patients with schizophrenia or bipolar disorder:
nested case-control study. Arch. Gen. Psychiatry. 64:1368-1376.
Lichtermann, D., Ekelund, J., Pukkala, E., Tanskanen, A., Lonnqvist, J. 2001. Incidence of cancer among persons with schizophrenia and their
relatives. Arch. Gen. Psychiatry. 58:573-578.
Levav, I., et al. 2007. Cancer risk among parents and siblings of patients with schizophrenia. Br. J. Psychiatry. 190:156-161.
Catts, V.S., Catts, S.V., O’Toole, B.I., Frost, A.D. 2008. Cancer incidence in patients with schizophrenia and their first-degree
relatives - a meta-analysis. Acta Psychiatr. Scand. 117:323-336.
Norton, N., et al. 2006. Evidence that interaction between neuregulin 1 and its receptor erbB4
increases susceptibility to schizophrenia. Am. J. Med. Genet. B Neuropsychiatr. Genet. 141B:96-101.
Fox, I.J., Kornblum, H.I. 2005. Developmental profile of ErbB receptors in murine central nervous
system: implications for functional interactions. J. Neurosci. Res. 79:584-597.
Judson, M.C., Bergman, M.Y., Campbell, D.B., Eagleson, K.L., Levitt, P. 2009. Dynamic gene and protein expression patterns of the autism-associated
c-Met receptor tyrosine kinase in the developing mouse forebrain. J. Comp. Neurol. 513:511-531.
Hossain, M.A., Russell, J.C., Gomez, R., Laterra, J. 2002. Neuroprotection by scatter factor/hepatocyte growth factor and FGF-1
in cerebellar granule neurons is phosphatidylinositol 3-kinase/akt-dependent and
MAPK/CREB-independent. J. Neurochem. 81:365-378.
Liu, Y., et al. 2007. Hepatocyte growth factor and c-Met expression in pericytes:
implications for atherosclerotic plaque development. J. Pathol. 212:12-19.
Roggia, C., Ukena, C., Bohm, M., Kilter, H. 2007. Hepatocyte growth factor (HGF) enhances cardiac commitment of
differentiating embryonic stem cells by activating PI3 kinase. Exp. Cell Res. 313:921-930.
Cacci, E., et al. 2003. Hepatocyte growth factor stimulates cell motility in cultures of the
striatal progenitor cells ST14A. J. Neurosci. Res. 74:760-768.
He, F., et al. 2008. HGF protects cultured cortical neurons against hypoxia/reoxygenation
induced cell injury via ERK1/2 and PI-3K/Akt pathways. Colloids Surf. B Biointerfaces. 61:290-297.
[No authors listed]. 1998. A full genome screen for autism with evidence for linkage to a region
on chromosome 7q. International Molecular Genetic Study of Autism Consortium. Hum. Mol. Genet. 7:571-578.
Philippe, A., et al. 1999. Genome-wide scan for autism susceptibility genes. Paris Autism
Research International Sibpair Study. Hum. Mol. Genet. 8:805-812.
International Molecular Genetic Study of Autism Consortium. 2001. A genomewide screen for autism: strong evidence for linkage to
chromosomes 2q, 7q, and 16p. Am. J. Hum. Genet. 69:570-581.
Lamb, J.A., et al. 2005. Analysis of IMGSAC autism susceptibility loci: evidence for sex
limited and parent of origin specific effects. J. Med. Genet. 42:132-137.
Schellenberg, G.D., et al. 2006. Evidence for multiple loci from a genome scan of autism kindreds. Mol. Psychiatry. 11:1049-1060.
Powell, E.M., Mars, W.M., Levitt, P. 2001. Hepatocyte growth factor/scatter factor is a motogen for interneurons
migrating from the ventral to dorsal telencephalon. Neuron. 30:79-89.
Levitt, P., Eagleson, K.L., Powell, E.M. 2004. Regulation of neocortical interneuron development and the implications
for neurodevelopmental disorders. Trends Neurosci. 27:400-406.
Rubenstein, J.L., Merzenich, M.M. 2003. Model of autism: increased ratio of excitation/inhibition in key
neural systems. Genes Brain Behav. 2:255-267.
Powell, E.M., et al. 2003. Genetic disruption of cortical interneuron development causes region-
and GABA cell type-specific deficits, epilepsy, and behavioral dysfunction. J. Neurosci. 23:622-631.
Levitt, P. 2005. Disruption of interneuron development. Epilepsia. 46(Suppl. 7):22-28.
Eagleson, K.L., Bonnin, A., Levitt, P. 2005. Region- and age-specific deficits in gamma-aminobutyric acidergic
neuron development in the telencephalon of the uPAR(–/–)
mouse. J. Comp. Neurol. 489:449-466.
Beilmann, M., et al. 1997. Neoexpression of the c-met/hepatocyte growth factor-scatter factor
receptor gene in activated monocytes. Blood. 90:4450-4458.
Ieraci, A., Forni, P.E., Ponzetto, C. 2002. Viable hypomorphic signaling mutant of the Met receptor reveals a role
for hepatocyte growth factor in postnatal cerebellar development. Proc. Natl. Acad. Sci. U. S. A. 99:15200-15205.
Arthur, L.G., Schwartz, M.Z., Kuenzler, K.A., Birbe, R. 2004. Hepatocyte growth factor treatment ameliorates diarrhea and bowel
inflammation in a rat model of inflammatory bowel disease. J. Pediatr. Surg. 39:139-143.
Okunishi, K., et al. 2005. A novel role of hepatocyte growth factor as an immune regulator
through suppressing dendritic cell function. J. Immunol. 175:4745-4753.
Ido, A., Numata, M., Kodama, M., Tsubouchi, H. 2005. Mucosal repair and growth factors: recombinant human hepatocyte growth
factor as an innovative therapy for inflammatory bowel disease. J. Gastroenterol. 40:925-931.
McCall-Culbreath, K.D., Li, Z., Zutter, M.M. 2008. Crosstalk between the alpha2beta1 integrin and c-met/HGF-R regulates
innate immunity. Blood. 111:3562-3570.
Jyonouchi, H., Geng, L., Ruby, A., Zimmerman-Bier, B. 2005. Dysregulated innate immune responses in young children with autism
spectrum disorders: their relationship to gastrointestinal symptoms and dietary
intervention. Neuropsychobiology. 51:77-85.
Valicenti-McDermott, M., et al. 2006. Frequency of gastrointestinal symptoms in children with autistic
spectrum disorders and association with family history of autoimmune disease. J. Dev. Behav. Pediatr. 27:S128-S136.
Hansen, R.L., et al. 2008. Regression in autism: prevalence and associated factors in the CHARGE
Study. Ambul. Pediatr. 8:25-31.
Xue, M., Brimacombe, M., Chaaban, J., Zimmerman-Bier, B., Wagner, G.C. 2008. Autism spectrum disorders: concurrent clinical disorders. J. Child Neurol. 23:6-13.
Garbett, K., et al. 2008. Immune transcriptome alterations in the temporal cortex of subjects
with autism. Neurobiol. Dis. 30:303-311.
Enstrom, A.M., et al. 2009. Altered gene expression and function of peripheral blood natural
killer cells in children with autism. Brain Behav. Immun. 23:124-133.
Sousa, I., et al. 2008. MET and autism susceptibility: family and
case-control studies. Eur. J. Hum. Genet. Online publication ahead of print. doi: 10.1038/ejhg.2008.215.
Ma, P.C., et al. 2003. c-MET mutational analysis in small cell lung cancer: novel
juxtamembrane domain mutations regulating cytoskeletal functions. Cancer Res. 63:6272-6281.
Li, Z., Dong, T., Proschel, C., Noble, M. 2007. Chemically diverse toxicants converge on Fyn and c-Cbl to disrupt
precursor cell function. PLoS Biol. 5:e35.
Hood, D.B., Nayyar, T., Ramesh, A., Greenwood, M., Inyang, F. 2000. Modulation in the developmental expression profile of Sp1 subsequent
to transplacental exposure of fetal rats to desorbed benzo[a]pyrene following
maternal inhalation. Inhal. Toxicol. 12:511-535.
Nayyar, T., Zawia, N.H., Hood, D.B. 2002. Transplacental effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin on the
temporal modulation of Sp1 DNA binding in the developing cerebral cortex and
cerebellum. Exp. Toxicol. Pathol. 53:461-468.
Peters, S.U., Beaudet, A.L., Madduri, N., Bacino, C.A. 2004. Autism in Angelman syndrome: implications for autism research. Clin. Genet. 66:530-536.
Veltman, M.W., Craig, E.E., Bolton, P.F. 2005. Autism spectrum disorders in Prader-Willi and Angelman syndromes: a
systematic review. Psychiatr. Genet. 15:243-254.
Bonati, M.T., et al. 2007. Evaluation of autism traits in Angelman syndrome: a resource to unfold
autism genes. Neurogenetics. 8:169-178.
Lowenthal, R., Paula, C.S., Schwartzman, J.S., Brunoni, D., Mercadante, M.T. 2007. Prevalence of pervasive developmental disorder in Down’s
syndrome. J. Autism Dev. Disord. 37:1394-1395.
Kent, L., Evans, J., Paul, M., Sharp, M. 1999. Comorbidity of autistic spectrum disorders in children with Down
syndrome. Dev. Med. Child Neurol. 41:153-158.
Garcia-Nonell, C., et al. 2008. Secondary medical diagnosis in fragile X syndrome with and without
autism spectrum disorder. Am. J. Med. Genet. A. 146A:1911-1916.
Clifford, S., et al. 2007. Autism spectrum phenotype in males and females with fragile X full
mutation and premutation. J. Autism Dev. Disord. 37:738-747.
Williams, P.G., Hersh, J.H. 1998. Brief report: the association of neurofibromatosis type 1 and autism. J. Autism Dev. Disord. 28:567-571.
Butler, M.G., et al. 2005. Subset of individuals with autism spectrum disorders and extreme
macrocephaly associated with germline PTEN tumour suppressor gene mutations. J. Med. Genet. 42:318-321.
Potocki, L., et al. 2007. Characterization of Potocki-Lupski syndrome (dup(17)(p11.2p11.2)) and
delineation of a dosage-sensitive critical interval that can convey an autism
phenotype. Am. J. Hum. Genet. 80:633-649.
Chahrour, M., Zoghbi, H.Y. 2007. The story of Rett syndrome: from clinic to neurobiology. Neuron. 56:422-437.
Ben Zeev Ghidoni, B. 2007. Rett syndrome. Child Adolesc. Psychiatr. Clin. N. Am. 16:723-743.
Tierney, E., et al. 2001. Behavior phenotype in the RSH/Smith-Lemli-Opitz syndrome. Am J. Med. Genet. 98:191-200.
Sikora, D.M., Pettit-Kekel, K., Penfield, J., Merkens, L.S., Steiner, R.D. 2006. The near universal presence of autism spectrum disorders in children
with Smith-Lemli-Opitz syndrome. Am J. Med. Genet. A. 140:1511-1518.
Splawski, I., et al. 2004. Ca(V)1.2 calcium channel dysfunction causes a multisystem disorder
including arrhythmia and autism. Cell. 119:19-31.
Smalley, S.L. 1998. Autism and tuberous sclerosis. J. Autism Dev. Disord. 28:407-414.
Jeste, S.S., Sahin, M., Bolton, P., Ploubidis, G.B., Humphrey, A. 2008. Characterization of autism in young children with tuberous sclerosis
complex. J. Child Neurol. 23:520-525.
Philippe, A., et al. 2008. Neurobehavioral profile and brain imaging study of the 22q13.3
deletion syndrome in childhood. Pediatrics. 122:e376-e382.