? The?Journal?of?Clinical?Investigation http://www.jci.org Volume 119 Number 4 April 2009
The genetic and neurobiologic compass
points toward common signaling dysfunctions
in autism spectrum disorders
Pat Levitt and Daniel B. Campbell
Vanderbilt Kennedy Center for Research on Human Development and Department of Pharmacology,
Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Autism spectrum disorder (ASD) is a syndrome characterized by a
triad of core deficits: disturbances in social behavior, atypical ver-
bal 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 neurode-
velopmental conditions (including autism, Rett syndrome, perva-
sive developmental disorder–not otherwise specified, and Asperg-
er 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 differ-
ent 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 expe-
rience-dependent processes through which atypical gene-by-environ-
ment (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 sys-
tems level, occurs from the bottom up; behavior develops from basic
sensory and perceptual systems that feed into higher integration cen-
ters (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 features.
Clinical researchers have noted the importance of addressing dis-
order 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 syn-
drome-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 esti-
mated 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 facili-
tated 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 dif-
ferences in the degree of severity of the three core symptoms as well as
Conflict?of?interest: The authors have declared that no conflict of interest exists.
Nonstandard?abbreviations?used: ASD, autism spectrum disorder; CNV, copy num-
ber variation; G X E, gene by environment; MET, met proto-oncogene; mTOR, mam-
malian target of rapamycin; RTK, receptor tyrosine kinase.
Citation?for?this?article: J. Clin. Invest. 119:747–754 (2009). doi:10.1172/JCI37934.
748? The?Journal?of?Clinical?Investigation http://www.jci.org Volume 119 Number 4 April 2009
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 behav-
iors 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 cer-
tain 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 mecha-
nisms 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 popu-
lations of children, adolescents, and adults that may relate to specific
genetic etiologies, such as increased risk due to common allelic varia-
tions, 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 par-
ticular 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. Differ-
ent 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 dys-
functional cellular signaling pathways that control synaptogenesis.
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 dis-
ease pathophysiology. Third, disorder emergence through de novo
genetic mutations or heritability of gene-specific functional poly-
morphisms 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 function-
al 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 vari-
ants, 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 individ-
uals 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 for-
mal 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 distur-
bances 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
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.
? The?Journal?of?Clinical?Investigation http://www.jci.org Volume 119 Number 4 April 2009
(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 candi-
date 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 disor-
der risk. Private (de novo) functional mutations also impart genetic
risk. Analyses suggest that, at the genetic and behavioral levels, mul-
tiplex 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 clinical-
ly 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 dis-
tinct 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 clear-
ly 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 candi-
date 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 pathophysiologi-
cal perspective, it is now clear that rare neurodevelopmental disor-
ders (<1 in 10,000) are becoming increasingly important to study
in greater detail because of their relationship to ASD. Higher pen-
etrance 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 Angel-
man 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 neurodevel-
opmental syndromic disorders listed in Table 1 are characterized in
part by intellectual disability (ID; formally termed mental retarda-
tion). 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 diagno-
sis, are more closely related in the context of the size of brain struc-
tures 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 expres-
sion (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 overlap-
ping 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 matu-
ration, dendritic growth, and myelination, are probably most vul-
nerable. 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 matura-
tion. In ASD cases, rare mutations and CNVs have been identified
in genes encoding neuroligins, neurexins, contactin-associated pro-
tein-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 idiopath-
ic 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).
Intracellular kinase signaling in ASD-associated
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
The basics of CNVs
CNVs are deletions or duplications of segments of chromosomes. Thus, rather than the normal two copies of a genetic sequence,
CNVs are fewer or more copies of the particular sequence. CNVs are typically benign, either because no genes lie within the deleted
or duplicated chromosomal region or because there is functional compensation for the amount of gene product produced due to
the CNV. However, CNVs that are located in functionally important genes and disrupt regulatory or coding regions can contribute
to disease processes. Large CNVs that eliminate or duplicate several genes are more likely to be pathophysiological than small
CNVs that may miss important regulatory or coding regions of genes. CNVs may be inherited, arising in parental germ cells, or
arise spontaneously (de novo) in offspring germ or somatic cells. In somatic cells, the developmental timing of when de novo CNVs
arise (early versus late) may influence the degree of functional deficits.
750? The?Journal?of?Clinical?Investigation http://www.jci.org Volume 119 Number 4 April 2009
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 path-
ways 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 path-
ways, 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 geneti-
cally, leading to enhanced mTOR downstream activation (Figure 2).
In addition, ERK and PI3K signaling is dependent in part on nor-
mal 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 regula-
tory 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 sev-
eral proteins in the ERK/PI3K downstream signaling pathway (42).
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 disor-
ders. 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 path-
ways, 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.
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 signal-
ing 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 can-
cer 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 instanc-
es to ASD (26, 51, 52). We are unaware of any studies of cancer fre-
quencies 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 schizophre-
nia is debated (55, 56), but reduced cancer incidence is observed con-
sistently in parents and siblings of individuals with schizophrenia
compared with the general population (57–59). These data support
Rare syndromic disorders with ASD co-occurrence
Chromosome 21 triplication
PI3K signaling activity
PI3K signaling activity
Transcriptional regulation, including
MET, CD44, and SP1
Cholesterol biosynthesis; Ras-mediated
ERK signaling; PI3K signaling
ACo-diagnosis (4%) of narrowly-defined autistic disorder with neurofibromatosis type I; the co-occurrence of ASD is likely to be higher. Co-diagnosis of neu-
rodevelopmental disorders with neurofibromatosis type I is 70%. CACNA1C, calcium channel, voltage-dependent, L type, alpha 1C subunit; DHCR7, 7-dehy-
drocholesterol reductase; FMR1, fragile X mental retardation syndrome 1; MECP2, methyl CpG binding protein 2; NF1, neurofibromin 1; PDD-NOS, pervasive
developmental disorder–not otherwise specified; PTEN, phosphatase and tensin homolog; TSC1, tuberous sclerosis 1; UBE3A, ubiquitin protein ligase E3A.
? The?Journal?of?Clinical?Investigation http://www.jci.org Volume 119 Number 4 April 2009
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 sig-
naling 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 underly-
ing specific functions. This hypothesis is consistent with the identi-
fication 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 dis-
order. 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 phosphory-
lation of AKT that can be blocked by the PI3K inhibitors LY294002
and wortmannin (63–65). Most relevant to the current discus-
sion, 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 protec-
tion of cortical neurons from hypoxia-induced insult (67).
It is again important to emphasize that the phenotypic heterogene-
ity 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 skepti-
cism regarding any particular candidate gene (16, 17). However, both
convergent neurobiological and genetic evidence is emerging to sug-
gest ASD vulnerability may lie, in part, in the well-defined MET sig-
naling 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 develop-
ment. MET activation by HGF modulates forebrain interneuron
motility in vitro (73). Excitatory/inhibitory imbalance has been pos-
tulated 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 interneu-
rons, 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 sys-
tem and cerebellar development, immune function, and gastrointes-
tinal 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 find-
ings due to small effects in a limited number of samples. In the
case of the MET signaling cascade (Figure 2), however, the patho-
physiologic and genetic evidence of its contribution to ASD risk is
now considerable. First, the expression of MET protein is reduced
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 desig-
nated 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 fami-
lies). 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 neuro-
developmental processes, including axon guidance, synapse formation,
and plasticity. Convergence of many different genetic etiologies sug-
gests 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 regu-
lators 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 plasminogen activator.
752? The?Journal?of?Clinical?Investigation http://www.jci.org Volume 119 Number 4 April 2009
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 gen-
otyped 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 dra-
matically 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 resequenc-
ing 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 observa-
tion 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, associa-
tion of the risk alleles in MET (26, 91) and the MET-regu-
lating 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), sug-
gesting that heritable, rather than de novo mechanisms
for ASD expression occur in multiplex families. Collec-
tively, there seem to be a number of different genetic eti-
ologies 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 envi-
ronmental perturbations. For example, increasing the redox
state of oligodendrocyte progenitor cells by brief exposure
to lead or mercury activates c-Cbl–regulated internaliza-
tion 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 stress-
ors and toxic chemicals suggest additional ways in which genetic
risk due to regulatory alleles may combine with environmental fac-
tors to shift a system closer to disease threshold (Figure 3).
ASD heterogeneity needs to be considered more seriously in devel-
oping strategies to investigate underlying biological etiologies.
Within syndromic and multigenic ASDs, functional profiles are
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 develop-
ing 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.
? The?Journal?of?Clinical?Investigation http://www.jci.org Volume 119 Number 4 April 2009
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 struc-
tural 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.
Address correspondence to: Pat Levitt, Zilkha Neurogenetic Insti-
tute, 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: email@example.com.
Pat Levitt’s present address is: Zilkha Neurogenetic Institute,
Keck School of Medicine of University of Southern California, Los
Angeles, California, USA.
1. Newschaffer, C.J., et al. 2007. The epidemiology of
autism spectrum disorders. Annu. Rev. Public Health.
2. American Psychiatric Association. 1994. Diagnostic
and statistical manual of mental disorders. 4th edition.
American Psychiatric Association. Washington,
DC, USA. 886 pp.
3. Knudsen, E.I. 2004. Sensitive periods in the devel-
opment of the brain and behavior. J. Cogn. Neurosci.
4. Thatcher, R. 1994. Psychopathology of early frontal
lobe damage: dependence on cycles of development.
Dev. Psychopathol. 6:565–596.
5. Hammock, E.A.D., and Levitt, P. 2006. The disci-
pline of neurobehavioral development: the emerg-
ing interface of processes that build circuits and
skills. Hum. Dev. 49:294–309.
6. Dawson, G., et al. 2002. Defining the broader phe-
notype of autism: genetic, brain, and behavioral
perspectives. Dev. Psychopathol. 14:581–611.
7. Beauchaine, T.P., Strassberg, Z., Kees, M.R., and
Drabick, D.A. 2002. Cognitive response repertoires
to child noncompliance by mothers of aggressive
boys. J. Abnorm. Child Psychol. 30:89–101.
8. Piven, J. 2001. The broad autism phenotype: a com-
plementary strategy for molecular genetic studies
of autism. Am. J. Med. Genet. 105:34–35.
9. Devlin, B., et al. 2005. Autism and the serotonin
transporter: the long and short of it. Mol. Psychiatry.
10. Rutter, M. 1996. Autism research: prospects and
priorities. J. Autism Dev. Disord. 26:257–275.
11. Volkmar, F.R., Lord, C., Bailey, A., Schultz, R.T., and
Klin, A. 2004. Autism and pervasive developmental
disorders. J. Child Psychol. Psychiatry. 45:135–170.
12. Bailey, A., et al. 1995. Autism as a strongly genet-
ic disorder: evidence from a British twin study.
Psychol. Med. 25:63–77.
13. Steffenburg, S., et al. 1989. A twin study of autism
in Denmark, Finland, Iceland, Norway and Sweden.
J. Child Psychol. Psychiatry. 30:405–416.
14. Geschwind, D.H., and Levitt, P. 2007. Autism spec-
trum disorders: developmental disconnection syn-
dromes. Curr. Opin. Neurobiol. 17:103–111.
15. Veenstra-Vanderweele, J., Christian, S.L., and Cook,
E.H., Jr. 2004. Autism as a paradigmatic complex
genetic disorder. Annu. Rev. Genomics Hum. Genet.
16. Abrahams, B.S., and Geschwind, D.H. 2008.
Advances in autism genetics: on the threshold of a
new neurobiology. Nat. Rev. Genet. 9:341–355.
17. O’Roak, B.J., and State, M.W. 2008. Autism genet-
ics: strategies, challenges, and opportunities.
Autism Res. 1:4–17. doi:10.1002/aur.3.
18. Craddock, N., O’Donovan, M.C., and Owen, M.J.
2008. Genome-wide association studies in psy-
chiatry: lessons from early studies of non-psychi-
atric and psychiatric phenotypes. Mol. Psychiatry.
19. Cook, E.H., Jr., and Scherer, S.W. 2008. Copy-num-
ber variations associated with neuropsychiatric
conditions. Nature. 455:919–923.
20. Sebat, J., et al. 2004. Large-scale copy number
polymorphism in the human genome. Science.
21. Rehen, S.K., et al. 2005. Constitutional aneuploidy in
the normal human brain. J. Neurosci. 25:2176–2180.
22. Kingsbury, M.A., Yung, Y.C., Peterson, S.E., Westra,
J.W., and Chun, J. 2006. Aneuploidy in the normal
and diseased brain. Cell. Mol. Life Sci. 63:2626–2641.
23. Kingsbury, M.A., et al. 2005. Aneuploid neurons are
functionally active and integrated into brain cir-
cuitry. Proc. Natl. Acad. Sci. U. S. A. 102:6143–6147.
24. Sebat, J., et al. 2007. Strong association of de novo
copy number mutations with autism. Science.
25. Marshall, C.R., et al. 2008. Structural variation of
chromosomes in autism spectrum disorder. Am. J.
Hum. Genet. 82:477–488.
26. Campbell, D.B., et al. 2006. A genetic variant that dis-
rupts MET transcription is associated with autism.
Proc. Natl. Acad. Sci. U. S. A. 103:16834–16839.
27. Campbell, D.B., Li, C., Sutcliffe, J.S., Persico, A.M.,
and Levitt, P. 2008. Genetic evidence implicating
multiple genes in the MET receptor tyrosine kinase
pathway in autism spectrum disorder. Autism Res.
28. Losh, M., Sullivan, P.F., Trembath, D., and Piven,
J. 2008. Current developments in the genetics of
autism: from phenome to genome. J. Neuropathol.
Exp. Neurol. 67:829–837.
29. Liu, X.Q., Paterson, A.D., and Szatmari, P. 2008.
Genome-wide linkage analyses of quantitative and
categorical autism subphenotypes. Biol. Psychiatry.
30. Daiger, S.P., Bowne, S.J., and Sullivan, L.S. 2007.
Perspective on genes and mutations causing reti-
nitis pigmentosa. Arch. Ophthalmol. 125:151–158.
31. Porter, F.D. 2008. Smith-Lemli-Opitz syndrome:
pathogenesis, diagnosis and management. Eur. J.
Hum. Genet. 16:535–541.
32. Todd, J.A., et al. 2007. Robust associations of four
new chromosome regions from genome-wide anal-
yses of type 1 diabetes. Nat. Genet. 39:857–864.
33. 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.
34. Samani, N.J., et al. 2007. Genomewide association
analysis of coronary artery disease. N. Engl. J. Med.
35. 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.
36. Kates, W.R., et al. 2007. Comparing phenotypes in
patients with idiopathic autism to patients with velo-
cardiofacial syndrome (22q11 DS) with and without
autism. Am. J. Med. Genet. A. 143A:2642–2650.
37. 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.
38. 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.
39. Persico, A., and Bourgeron, T. 2006. Searching for
ways out of the autism maze: genetic, epigenetic and
environmental clues. Trends Neurosci. 29:349–358.
40. Walsh, C.A., Morrow, E.M., and Rubenstein,
J.L.R. 2008. Autism and brain development. Cell.
41. Zoghbi, H.Y. 2003. Postnatal neurodevelopmen-
tal disorders: meeting at the synapse? Science.
42. Urdinguio, R.G., et al. 2008. Mecp2-null mice pro-
vide new neuronal targets for Rett syndrome. PLoS
43. Kwon, C.H., Zhu, X., Zhang, J., and Baker, S.J. 2003.
mTor is required for hypertrophy of Pten-deficient
neuronal soma in vivo. Proc. Natl. Acad. Sci. U. S. A.
44. Meikle, L., et al. 2008. Response of a neuronal
model of tuberous sclerosis to mammalian tar-
get of rapamycin (mTOR) inhibitors: effects on
mTORC1 and Akt signaling lead to improved sur-
vival and function. J. Neurosci. 28:5422–5432.
45. Ehninger, D., et al. 2008. Reversal of learning defi-
cits in a Tsc2+/– mouse model of tuberous sclerosis.
Nat. Med. 14:843–848.
46. Costa, R.M., et al. 2002. Mechanism for the learn-
ing deficits in a mouse model of neurofibromato-
sis type 1. Nature. 415:526–530.
47. Li, W., et al. 2005. The HMG-CoA reductase inhibi-
tor lovastatin reverses the learning and attention
deficits in a mouse model of neurofibromatosis
type 1. Curr. Biol. 15:1961–1967.
48. Network, T.C.G.A.R. 2008. Comprehensive genom-
ic characterization defines human glioblastoma
genes and core pathways. Nature. 455:1061–1068.
49. Ding, L., et al. 2008. Somatic mutations affect
key pathways in lung adenocarcinoma. Nature.
50. Chalhoub, N., and Baker, S.J. 2008. PTEN and
the PI3-kinase pathway in cancer. Annu Rev Pathol.
Online publication ahead of print. doi:10.1146/
51. Serajee, F.J., Nabi, R., Zhong, H., and 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.
52. Campbell, D.B., et al. 2007. Disruption of cerebral
cortex MET signaling in autism spectrum disorder.
Ann. Neurol. 62:243–250.
53. Harrison, P.J., and Law, A.J. 2006. Neuregulin 1 and
schizophrenia: genetics, gene expression, and neu-
robiology. Biol. Psychiatry. 60:132–140.
54. Kanakry, C.G., Li, Z., Nakai, Y., Sei, Y., and Wein-
berger, 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.
55. Grinshpoon, A., et al. 2005. Cancer in schizo-
phrenia: is the risk higher or lower? Schizophr. Res.
review series Download full-text
754? The?Journal?of?Clinical?Investigation http://www.jci.org Volume 119 Number 4 April 2009
56. Hippisley-Cox, J., Vinogradova, Y., Coupland, C.,
and Parker, C. 2007. Risk of malignancy in patients
with schizophrenia or bipolar disorder: nested case-
control study. Arch. Gen. Psychiatry. 64:1368–1376.
57. Lichtermann, D., Ekelund, J., Pukkala, E., Tans-
kanen, A., and Lonnqvist, J. 2001. Incidence of can-
cer among persons with schizophrenia and their
relatives. Arch. Gen. Psychiatry. 58:573–578.
58. Levav, I., et al. 2007. Cancer risk among parents
and siblings of patients with schizophrenia. Br. J.
59. Catts, V.S., Catts, S.V., O’Toole, B.I., and Frost, A.D.
2008. Cancer incidence in patients with schizophre-
nia and their first-degree relatives - a meta-analysis.
Acta Psychiatr. Scand. 117:323–336.
60. Norton, N., et al. 2006. Evidence that interac-
tion between neuregulin 1 and its receptor erbB4
increases susceptibility to schizophrenia. Am. J.
Med. Genet. B Neuropsychiatr. Genet. 141B:96–101.
61. Fox, I.J., and Kornblum, H.I. 2005. Developmental
profile of ErbB receptors in murine central nervous
system: implications for functional interactions.
J. Neurosci. Res. 79:584–597.
62. Judson, M.C., Bergman, M.Y., Campbell, D.B.,
Eagleson, K.L., and Levitt, P. 2009. Dynamic gene
and protein expression patterns of the autism-asso-
ciated c-Met receptor tyrosine kinase in the develop-
ing mouse forebrain. J. Comp. Neurol. 513:511–531.
63. Hossain, M.A., Russell, J.C., Gomez, R., and Lat-
erra, 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.
64. Liu, Y., et al. 2007. Hepatocyte growth factor and
c-Met expression in pericytes: implications for athero-
sclerotic plaque development. J. Pathol. 212:12–19.
65. Roggia, C., Ukena, C., Bohm, M., and Kilter, H.
2007. Hepatocyte growth factor (HGF) enhances
cardiac commitment of differentiating embryonic
stem cells by activating PI3 kinase. Exp. Cell Res.
66. 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.
67. 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.
68. [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.
69. Philippe, A., et al. 1999. Genome-wide scan for
autism susceptibility genes. Paris Autism Research
International Sibpair Study. Hum. Mol. Genet.
70. 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.
71. 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.
72. Schellenberg, G.D., et al. 2006. Evidence for mul-
tiple loci from a genome scan of autism kindreds.
Mol. Psychiatry. 11:1049–1060.
73. Powell, E.M., Mars, W.M., and Levitt, P. 2001. Hepa-
tocyte growth factor/scatter factor is a motogen for
interneurons migrating from the ventral to dorsal
telencephalon. Neuron. 30:79–89.
74. Levitt, P., Eagleson, K.L., and Powell, E.M. 2004.
Regulation of neocortical interneuron develop-
ment and the implications for neurodevelopmen-
tal disorders. Trends Neurosci. 27:400–406.
75. Rubenstein, J.L., and Merzenich, M.M. 2003. Model
of autism: increased ratio of excitation/inhibition
in key neural systems. Genes Brain Behav. 2:255–267.
76. 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.
77. Levitt, P. 2005. Disruption of interneuron develop-
ment. Epilepsia. 46(Suppl. 7):22–28.
78. Eagleson, K.L., Bonnin, A., and Levitt, P. 2005. Region-
and age-specific deficits in gamma-aminobutyric aci-
dergic neuron development in the telencephalon of
the uPAR(–/–) mouse. J. Comp. Neurol. 489:449–466.
79. Beilmann, M., et al. 1997. Neoexpression of the c-met/
hepatocyte growth factor-scatter factor receptor
gene in activated monocytes. Blood. 90:4450–4458.
80. Ieraci, A., Forni, P.E., and Ponzetto, C. 2002. Viable
hypomorphic signaling mutant of the Met recep-
tor reveals a role for hepatocyte growth factor in
postnatal cerebellar development. Proc. Natl. Acad.
Sci. U. S. A. 99:15200–15205.
81. Arthur, L.G., Schwartz, M.Z., Kuenzler, K.A., and
Birbe, R. 2004. Hepatocyte growth factor treatment
ameliorates diarrhea and bowel inflammation in a
rat model of inflammatory bowel disease. J. Pediatr.
82. Okunishi, K., et al. 2005. A novel role of hepatocyte
growth factor as an immune regulator through
suppressing dendritic cell function. J. Immunol.
83. Ido, A., Numata, M., Kodama, M., and Tsubouchi,
H. 2005. Mucosal repair and growth factors: recom-
binant human hepatocyte growth factor as an
innovative therapy for inflammatory bowel disease.
J. Gastroenterol. 40:925–931.
84. McCall-Culbreath, K.D., Li, Z., and Zutter, M.M.
2008. Crosstalk between the alpha2beta1 integ-
rin and c-met/HGF-R regulates innate immunity.
85. Jyonouchi, H., Geng, L., Ruby, A., and Zimmerman-
Bier, B. 2005. Dysregulated innate immune respons-
es in young children with autism spectrum disor-
ders: their relationship to gastrointestinal symptoms
and dietary intervention. Neuropsychobiology.
86. Valicenti-McDermott, M., et al. 2006. Frequency of
gastrointestinal symptoms in children with autistic
spectrum disorders and association with family his-
tory of autoimmune disease. J. Dev. Behav. Pediatr.
87. Hansen, R.L., et al. 2008. Regression in autism:
prevalence and associated factors in the CHARGE
Study. Ambul. Pediatr. 8:25–31.
88. Xue, M., Brimacombe, M., Chaaban, J., Zimmer-
man-Bier, B., and Wagner, G.C. 2008. Autism
spectrum disorders: concurrent clinical disorders.
J. Child Neurol. 23:6–13.
89. Garbett, K., et al. 2008. Immune transcriptome
alterations in the temporal cortex of subjects with
autism. Neurobiol. Dis. 30:303–311.
90. Enstrom, A.M., et al. 2009. Altered gene expression
and function of peripheral blood natural killer
cells in children with autism. Brain Behav. Immun.
91. 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/
92. 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.
93. Li, Z., Dong, T., Proschel, C., and Noble, M. 2007.
Chemically diverse toxicants converge on Fyn and
c-Cbl to disrupt precursor cell function. PLoS Biol.
94. Hood, D.B., Nayyar, T., Ramesh, A., Greenwood,
M., and Inyang, F. 2000. Modulation in the devel-
opmental expression profile of Sp1 subsequent to
transplacental exposure of fetal rats to desorbed
benzo[a]pyrene following maternal inhalation.
Inhal. Toxicol. 12:511–535.
95. Nayyar, T., Zawia, N.H., and Hood, D.B. 2002.
Transplacental effects of 2,3,7,8-tetrachlorodiben-
zo-p-dioxin on the temporal modulation of Sp1
DNA binding in the developing cerebral cortex and
cerebellum. Exp. Toxicol. Pathol. 53:461–468.
96. Peters, S.U., Beaudet, A.L., Madduri, N., and Bacino,
C.A. 2004. Autism in Angelman syndrome: implica-
tions for autism research. Clin. Genet. 66:530–536.
97. Veltman, M.W., Craig, E.E., and Bolton, P.F. 2005.
Autism spectrum disorders in Prader-Willi and
Angelman syndromes: a systematic review. Psychi-
atr. Genet. 15:243–254.
98. Bonati, M.T., et al. 2007. Evaluation of autism
traits in Angelman syndrome: a resource to unfold
autism genes. Neurogenetics. 8:169–178.
99. Lowenthal, R., Paula, C.S., Schwartzman, J.S., Bruno-
ni, D., and Mercadante, M.T. 2007. Prevalence of per-
vasive developmental disorder in Down’s syndrome.
J. Autism Dev. Disord. 37:1394–1395.
100. Kent, L., Evans, J., Paul, M., and Sharp, M. 1999.
Comorbidity of autistic spectrum disorders in chil-
dren with Down syndrome. Dev. Med. Child Neurol.
101. Garcia-Nonell, C., et al. 2008. Secondary medical
diagnosis in fragile X syndrome with and without
autism spectrum disorder. Am. J. Med. Genet. A.
102. 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.
103. Williams, P.G., and Hersh, J.H. 1998. Brief report:
the association of neurofibromatosis type 1 and
autism. J. Autism Dev. Disord. 28:567–571.
104. Butler, M.G., et al. 2005. Subset of individuals with
autism spectrum disorders and extreme macroceph-
aly associated with germline PTEN tumour suppres-
sor gene mutations. J. Med. Genet. 42:318–321.
105. Potocki, L., et al. 2007. Characterization of Potocki-
Lupski syndrome (dup(17)(p11.2p11.2)) and delin-
eation of a dosage-sensitive critical interval that
can convey an autism phenotype. Am. J. Hum. Genet.
106. Chahrour, M., and Zoghbi, H.Y. 2007. The story
of Rett syndrome: from clinic to neurobiology.
107. Ben Zeev Ghidoni, B. 2007. Rett syndrome. Child
Adolesc. Psychiatr. Clin. N. Am. 16:723–743.
108. Tierney, E., et al. 2001. Behavior phenotype in the
RSH/Smith-Lemli-Opitz syndrome. Am J. Med.
109. Sikora, D.M., Pettit-Kekel, K., Penfield, J., Merkens,
L.S., and 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.
110. Splawski, I., et al. 2004. Ca(V)1.2 calcium channel
dysfunction causes a multisystem disorder includ-
ing arrhythmia and autism. Cell. 119:19–31.
111. Smalley, S.L. 1998. Autism and tuberous sclerosis.
J. Autism Dev. Disord. 28:407–414.
112. Jeste, S.S., Sahin, M., Bolton, P., Ploubidis, G.B., and
Humphrey, A. 2008. Characterization of autism in
young children with tuberous sclerosis complex.
J. Child Neurol. 23:520–525.
113. Philippe, A., et al. 2008. Neurobehavioral profile
and brain imaging study of the 22q13.3 deletion
syndrome in childhood. Pediatrics. 122:e376–e382.