TABLE OF CONTENTS
Autism on the Rise, Multidisciplinary
efforts aim at finding the biological basis for a complex disease
Developmental Disorders in Preschool Children
Chakrabarti, MD, MRCP; Eric Fombonne, MD, FRCPsych
285 No. 24, June 27, 2001
Context Prevalence rates of autism-spectrum disorders are
uncertain, and speculation that their incidence is increasing continues to cause
Objective To estimate the prevalence of pervasive
developmental disorders (PDDs) in a geographically defined population of
Design, Setting, and Participants Survey conducted July
1998 to June 1999 in Staffordshire, England. The area's 15 500 children
aged 2.5 to 6.5 years were screened for developmental problems. Children with
symptoms suggestive of a PDD were intensively assessed by a multidisciplinary
team, which conducted standardized diagnostic interviews and administered
Main Outcome Measure Prevalence estimates for subtypes of
Results A total of 97 children (79.4% male) were confirmed
to have a PDD. The prevalence of PDDs was estimated to be 62.6 (95% confidence
interval, 50.8-76.3) per 10 000 children. Prevalences were 16.8 per 10 000
for autistic disorder and 45.8 per 10 000 for other PDDs. The mean age at
diagnosis was 41 months, and 81% were originally referred by health visitors
(nurse specialists). Of the 97 children with a PDD, 25.8% had some degree of
mental retardation and 9.3% had an associated medical condition.
Conclusions Our results suggest that rates of PDD are
higher than previously reported. Methodological limitations in existing
epidemiological investigations preclude interpretation of recent high rates as
indicative of increased incidence of these disorders although this hypothesis
requires further rigorous testing. Attention is nevertheless drawn to the
important needs of a substantial minority of preschool children.
Autism is a severe developmental disorder involving deviance and often delay
in the development of language or communication skills; social interactions and
reciprocity; and imagination, play, and interests.1
Since the first epidemiological survey of autism was conducted in the mid 1960s
in England,2 more than 30 surveys have been
performed worldwide.3, 4
Rates of autism typically have been reported in the range of 4 to 6 per 10 000
although these figures increased in surveys conducted in the last 15 years.4,
5 These estimates do not account for a large group of
children falling short of strict diagnostic criteria for autism (pervasive
developmental disorders [PDDs]) and whose development poses similar assessment
and educational challenges.
Although the apparent increased prevalence of autism may reflect improved
detection and recognition of autism and its variants, it might also index a
secular change in the incidence of the disorder. The role of genetic factors in
the origin of autism does not favor such a hypothesis,6
however. Moreover, no survey has thus far concentrated specifically on preschool
children. Obtaining a reliable estimate in this age group is particularly
important since early intensive preschool education might improve the outcome in
Accordingly, the goals of this study were to estimate the prevalence of PDDs in
preschool children in a geographically defined population.
Site and Target Population
The study was conducted at the child development centers in Stafford, Cannock,
and Wightwick in the Midlands, England, and it received approval from the South
Staffordshire Health Authority local ethics committee. These child development
centers serve the entire preschool and early school population of one National
Health Service Trust. The survey was conducted from July 1998 to June 1999
although some initial clinical assessments were performed from 1994 onward. The
area is a mixture of urban, rural, and semi-industrial areas. There is a stable
population of indigenous British people with a small (1.4%), mostly Asian,
immigrant population. The total population living in the area covered by the
National Health Service Trust was 320 000 people in June 1998. The target
population included all children (N = 15 500) born between January 1, 1992,
and December 31, 1995, living within the target area on June 6, 1998.
Case Identification and Definition: 4 Stages
The national framework of Child Health Surveillance recommends the screening by
health professionals of all UK children at birth; at age 6 weeks; between ages 6
and 9 months, 18 and 24 months, and 3¼ and 3½ years. In the study population,
all the neonatal and 6-week screenings were performed by pediatricians or
general practitioners and the 7-month screening by health visitors, who are
nurse specialists experienced in working with children and families. Health
visitors or physicians performed the 18- to 24-month and 3¼- to 3½-year
screening. Screening was conducted in accordance with the guidelines of the
"Health for All Children" report,9 which
emphasizes continuity of care, making observations, checking history, eliciting
parental concerns, offering health advice and guidance, and moving away from
prescriptive tests. The primary care worker may also have had the opportunity to
listen to and discuss any concerns about the child's progress during the
immunization visits at 2, 3, 4, and 13 months. Besides health visitors, speech
and language therapists, pediatricians, general practitioners, and other
professionals contributed to the referral process, especially for children older
than 3 years. The study was coordinated through the child development centers
that processed all the referrals of preschool children.
The participating professionals underwent training sessions on early
identification of developmental problems and received written guidelines for
referral of children with developmental or behavioral problems. The guidance to
those making referrals for the initial screenings was left purposefully general
to include children with any likely serious developmental, behavioral, or
physical problems. This procedure also ensured maximal sensitivity for PDD case
finding. The guidelines for the initial screen were to refer all children with
more than mild or transient problems in one or more areas of development,
including personal-social, fine or gross motor, speech and language, play skills
and attention, concentration, and behavioral difficulties. Referrals were sought
as soon as any problem was identified, usually by the age of 2 to 2½ years or
Children referred at this initial stage underwent a second screening carried out
by a developmental pediatrician (S.C.) or by the child development team,
consisting of a pediatrician, a specialist health visitor, and speech and
language, physical, occupational, and play therapists. Parents or main
caretakers were involved in each stage of the screening. Any urgent referrals
were fast-tracked to the developmental pediatrician or a multidisciplinary team.
Children who failed the second screening were selected for a 2-week assessment
conducted by a multidisciplinary team. During these assessments, a play
therapist led a group of 4 children with their participating parents in 2-hour
sessions of structured activities as well as free play. A developmental
pediatrician (S.C.) took a detailed developmental history and conducted a
comprehensive medical and neurodevelopmental examination. Children were assessed
by a speech and language therapist, a pediatric physical therapist, an
occupational therapist, a dental nurse, a dietitian, and a nurse specialist
trained in behavioral intervention for children with PDDs and other learning
problems. Hearing was assessed by an audiological physician, and vision was
screened by an orthoptist. At the end of this assessment, a clinical diagnostic
formulation was made by the lead pediatrician.
All screening and evaluation steps undertaken at stages 1, 2, and 3 were part
of a normal screening procedure implemented by the local service. Permission for
extra data collection associated with research was sought either at the end of
stage 3 or shortly after entering stage 4. About 75% of parents provided written
informed consent. The rest provided oral informed consent.
Children strongly suspected of having a PDD diagnosis were further assessed with
standardized diagnostic measures and psychometric assessments. The Autism
Diagnostic Interview-Revised (ADI-R)10-12
is a semistructured diagnostic interview for use with caregivers of children
with a possible PDD diagnosis. The ADI-R was administered by the developmental
pediatrician (S.C.), who has been trained in its use. The ADI-R algorithm
generates scores for the areas of social interaction, communication (verbal and
nonverbal), repetitive behaviors, and age of recognition of first abnormalities
for which appropriate cutoff points are available. The ADI-R algorithm is
compatible with Diagnostic and Statistical Manual of Mental Disorders, Fourth
Edition (DSM-IV) diagnostic criteria. A total ADI-R score is obtained
by summing the scores in the 3 domains of developmental deviance.
Children diagnosed as having a PDD subsequently underwent a formal
psychometric assessment by a senior educational psychologist. All tests were
performed in 1999 and early 2000. The tests used were the Wechsler Preschool and
Primary Scale of Intelligence13 and the
Merrill-Palmer14 tests. Intellectual functioning
was estimated according to performances on the nonverbal scales of the Wechsler
Preschool and Primary Scale of Intelligence or with the quotient derived from
the Merrill-Palmer test. Mental retardation was defined according to
conventional levels of severity (ie, mild, 50-69; moderate, 35-49; severe,
20-34; and profound, <20).
The final diagnostic determination was derived from a review of all existing
data by the pediatrician who knew all children well. Diagnosis was made with DSM-IV
diagnostic criteria1 for PDD including autistic
disorder (AD), Asperger syndrome, Rett syndrome, childhood disintegrative
disorder, and pervasive developmental disorder-not otherwise specified (PDD-NOS).
All ADI-R interviews were videotaped or audiotaped. A subset of 38 ADI-R
videotapes was selected at random and blindly rated by 3 trained raters
(including E.F.). Interrater reliability for domain scores as measured by the
intraclass correlation coefficient15 was 0.82 for
social interactions, 0.87 for nonverbal communication, 0.85 for verbal
communication (based on a subset of 28 children with a sufficient language
level), 0.59 for repetitive behaviors, and 0.86 for the total ADI-R score.
Agreement on the proportion of subjects scoring higher than each of the
predetermined cutoffs was high for all domains (social interactions, 92.1%;
nonverbal communication, 90.0%; verbal communication, 85.7%; repetitive
behavior, 81.6%; and onset before age 3 years, 97.4%). Blinded raters were also
asked to provide an independent global diagnostic judgment about the presence or
absence of a PDD based on the parental interview. Independent raters confirmed
the presence of a PDD in all 38 children, yielding a 100% agreement with the
original pediatrician's diagnoses.
Following the 2-week assessment, systematic laboratory investigations were
performed, which included full blood cell count; plasma chemistry; serum
calcium, thyrotropin and thyroxine, and creatine kinase levels; plasma and urine
amino acid chromatogram; urine organic acids; chromosomes; fragile X testing;
and electroencephalogram. The skin of children with suggestive birthmarks was
examined with UV light to detect markers of tuberous sclerosis. In a small
number of cases, brain imaging using computed tomographic or magnetic resonance
imaging scans was performed on clinical suspicion of a possible neurological
Between-group comparisons for continuous variables were performed with both
nonparametric (Kruskal-Wallis) and parametric 1-way analyses of variance
followed by post hoc Scheffé pairwise comparisons. Because P values were
almost identical, the results of parametric analyses are subsequently presented.
2 tests were
used for categorical variables. Throughout, a conventional P value of .05
was retained as the level of statistical significance. Asymptotic 95% confidence
intervals (CIs) for prevalence estimates were obtained with STATA software
The details of case ascertainment in this investigation are summarized in Figure
1. Of the 576 children referred to a child development center for a stage 1
assessment, 103 children were clinically diagnosed as having PDD at the stage 3
assessment. Of these 103 children, 99 parents agreed to take part in the ADI-R
interview and 4 parents refused. One interview was deferred indefinitely for
external circumstances, and 98 interviews were finally carried out (95
videotaped, 3 audiotaped).
Developmental Disorders in Preschool Children (JAMA.
Of the 5 children who did not receive an ADI-R interview, a final PDD
diagnosis was subsequently confirmed by an independent educational psychologist
or child psychiatrist (2, AD; 3, PDD-NOS). Of the 98 children with ADI-R data, 6
children did not fulfill strict ADI-R diagnostic criteria for a PDD at stage 4.
Thus, at the completion of stage 4, 97 children were diagnosed as having PDD,
resulting in a prevalence estimate of 62.6 (95% CI, 50.8-76.3) per 10 000
children for all PDDs. Further analysis by PDD subtype led to the following
estimates: for 26 children with AD, the prevalence was 16.8 (95% CI, 11.0-24.6)
per 10 000; for 13 with Asperger syndrome, 8.4 (95% CI, 4.5-14.3) per 10 000;
for 1 girl with Rett syndrome, 0.6 (95% CI, 0.02-3.6) per 10 000; for 1 boy
with childhood disintegrative disorder, 0.6 (95% CI, 0.02-3.6) per 10 000;
and for 56 with PDD-NOS, 36.1 (95% CI, 27.3-46.9) per 10 000. For the 71
children with a PDD diagnosis other than AD, the prevalence was 45.8 (95% CI,
35.8-57.7) per 10 000 children.
ADI-R Mean Scores
The mean (SD) age of 92 children with available ADI data was 58.1 (13.0) months
at interview. Excluding the boy with childhood disintegrative disorder and the
girl with Rett syndrome, comparison of scores across the 3 remaining diagnostic
subgroups yielded significant differences in all domains except for the
repetitive behaviors domain (Table
1). Post hoc tests showed that children with AD had consistently higher
scores than the 2 other groups, which in turn did not differ from each other.
All children met the requirement of an onset before age 3 years.
Table 1. Mean Autism Diagnostic Interview-Revised (ADI-R)
Scores by Diagnostic Subgroup*
Referral Source and Age at Diagnosis
Thirty-four percent of the 97 referrals came from pediatricians, 32.9% from
speech and language therapists, 21.6% from health visitors, 5.1% from general
practitioners, and 6.2% from miscellaneous sources. However, a closer look at
referral patterns showed that most of the referrals to pediatricians and speech
therapists were initiated by health visitors; thus, taking these data in
combination, 79 (81%) of the 97 children were originally identified by the
health visitor as having a problem requiring further assessment. The average age
of children at referral was 35.7 months (range, 11-63 months), and the average
age at initial clinical diagnosis was 41 months (range, 21-78 months). Analyses
of variance were performed to test for differences in age at referral and age at
diagnosis in the 95 children with AD, Asperger syndrome, or PDD-NOS diagnoses. A
significant effect of diagnosis was found for age at referral (F2,92
= 11.3; P<.001). Pairwise comparisons showed that mean age at referral
for children with AD (30.0 months) was significantly lower than for children
with PDD-NOS (37.2 months; P = .03) or with Asperger syndrome (47.5
months; P<.001). Age at referral of children with PDD-NOS was also
significantly lower than in those children with Asperger syndrome (P =
.01). For age at diagnosis, a significant effect of diagnostic subgroup was also
found (F2,92 = 12.0; P<.001). Post hoc Scheffé tests
similarly indicated significantly lower mean age at diagnosis for children with
AD (34.6 months) vs children with PDD-NOS (43.1 months; P = .005) and
lower age at diagnosis for children with Asperger syndrome (51.8 months; P<.001),
whereas children with PDD-NOS had significantly lower mean age at diagnosis than
those with Asperger syndrome (P = .04).
The sample included 77 boys (79.4%) with no significant difference (22
= 0.33; P = .85) in the proportion of boys in the AD (76.9%), Asperger
syndrome (84.6%), and PDD-NOS (80.4%) groups. Of the 97 children, 29 (29.9%) had
no functional use of language defined as the daily spontaneous use of 3-word
phrases. The proportion of children without functional language was however
strongly associated with diagnostic subtype (AD, 69.2%; Asperger syndrome, 0%;
PDD-NOS, 16.1%; 22
= 30.6; P<.001).
Of the 97 children, 37 children underwent Merrill-Palmer testing and 56,
Wechsler Preschool and Primary Scale of Intelligence testing. Four children
could not be tested for practical reasons. Overall, 24 (25.8%) of 93 children
had some degree of mental retardation. The 2 children with childhood
disintegrative disorder and Rett syndrome scored in the moderate range of mental
retardation. However, patterns of cognitive functioning varied according to
2) and, combining together all levels of mental retardation, a significant
difference was found for the presence or absence of mental retardation between
the 3 PDD subtypes (22
= 40.6; P<.001), the AD group having more frequent and severe
cognitive delays than the Asperger syndrome and PDD-NOS groups.
Table 2. Intellectual Functioning by Diagnostic Subgroup*
In the sample, 5 children had a sibling with another PDD (including 1 twin
pair). Four of the sibling pairs were in the age range of this study and were
included in the prevalence pool. Of the sibling pairs, 3 sets were diagnosed
with both pairs having PDD-NOS, 1 set with AD and PDD-NOS, and 1 set with
Asperger syndrome and AD. Based on the total number of siblings across all 93
families (n = 220, including the 97 participating children), the sibling risk is
estimated at 3.94% (5/127) in this study.
Associated Medical Conditions
The results of medical investigations in this sample are summarized in Table
3. There was no case of deafness, blindness, or fragile X disorder, and only
1 child had tuberous sclerosis. Six of 8 children with an abnormal medical
result had mental retardation. Overall, the proportion of children with any
abnormal medical result was 9.3%.
Associated Medical Conditions in Children With Pervasive Developmental Disorder
Most other surveys5, 17
estimated the prevalence of children with PDD to be nearer to 20 per 10 000
children than the 62.6 per 10 000 prevalence in our study. This rate is,
however, consistent with the 57.9 and 67.4 per 10 000 estimates reported in
2 recent investigations.18, 19
These 3 surveys have all used intensive screening procedures, focused on
children younger than 10 years, and used modern standardized diagnostic measures
such as the ADI-R10-12 or the Autism Diagnostic
Observation Schedule-Generic.20 The somewhat lower
estimate of 26.1 per 10 000 (and 30.1 per 10 000 among children aged 5
to 9 years) obtained in another UK survey21
probably reflects methodological differences in an investigation that was
focusing primarily on common childhood psychiatric disorders. Thus, the latter
survey did not rely on screening procedures and diagnostic measures specific to
PDDs. It is worth noting that 4 UK surveys of children in the same age groups
conducted at the same time and in the same country showed a 6-fold variation in
prevalence rates, emphasizing how powerfully various methods used in a survey
affect prevalence estimates.4 The findings also
point to the probable lack of sensitivity of case finding procedures in earlier
surveys resulting in underestimation of rates. Therefore, the prevalence of PDDs
seems to be about 60 per 10 000 children, an estimate that draws attention
to the needs of a substantial minority of children.
Whether the higher prevalence rates reported recently arise from a secular
increase in the incidence of the disorder or merely reflect a broadening of the
concept of PDD together with improved detection and recognition cannot be
assessed from these data. Comparison of prevalence rates obtained from
cross-sectional surveys conducted at different times are confounded by changes
in diagnostic concepts and criteria, changes in the efficiency of case finding
procedures (as already shown above), and improved awareness in both the lay and
professional public about the autism-spectrum conditions.4
In 1 survey, comparison of rates between successive birth cohorts was performed
holding constant case definition and identification methods, and no evidence
could be produced of an increase over time.22
Reports of increased numbers of children with PDD by providers of educational
services have also been quoted as evidence of an epidemic of autism23,
24 although several analyses of these claims refuted
One factor accounting for increased rates lies in the decreasing age at
diagnosis, which occurred during the last 30 years.23, 25,
28 Assuming no change in the underlying incidence and a
steady prevalence pool, this trend could explain the increasing numbers of young
children seen in clinical settings and identified in surveys, particularly since
those surveys usually relied on service providers to detect known cases rather
than on systematic population screening.
In our survey, AD accounted for only 27% of the cases with these children
showing much greater cognitive and language impairments. By contrast, the
majority of cases was found at the mild end of the autistic spectrum, with the
PDD-NOS and Asperger syndrome groups accounting for 71.1% of the cases. High
proportions of PDDs were also found in recent surveys (46.8%18
and 40%19). Prior surveys focused on a narrow
definition, which led to the exclusion of these milder forms although it has
been recognized for some time that they represented a group as sizable if not
bigger than that of autism.5 The inclusion of these
milder variants certainly may account for a substantial part of the increase in
Children with a PDD thus present as a whole as less impaired than what has
been classically described. Although the average rate of mental retardation was
near 75% in previous autism surveys,5 this rate has
fallen to much lower figures of 40%18 and 55%19
in large epidemiological series of PDD and was 26% in this survey. Moreover,
there appears to be a downward trend for the rate of mental retardation within
the group narrowly defined as autism (ie, 50% in the Brick Township study among
3- to 10-year-olds19 and 25% among 3- to
5-year-olds in a Finnish survey29).
This shift has important implications for intervention since the majority of
these children will require education in mainstream schools with provision of
individual support. In addition, it is possible that very early intervention in
autism and PDD might be associated with a much better cognitive outcome in the
short term. Evidence of the beneficial impact of intensive educational programs
between the ages of 2 and 4 years has accumulated recently,7,
8 and the notion of a critical period for a maximal
effect of intensive educational interventions clearly requires further
examination. Parents recognize the first developmental abnormalities before the
second birthday in the majority of cases,30,
31 and one encouraging result from this survey was that
four fifths of PDD cases were identified at a very early age by trained health
visitors, indicating that early population screening programs could detect a
high proportion of children with PDDs before the age of 2 years. Instruments
with adequate levels of sensitivity and specificity are currently being
developed,18, 32, 33
which may make that goal attainable. Such screening must be supported with
appropriate assessment services combining special expertise in autism and
multidisciplinary skills,32 as was the case in our
Consistent with a major role of genetic factors in PDD,6,
34 identified medical abnormalities were found in less
than 10% of our sample. Moreover, the abnormalities reported in this sample
might not be causally implicated in the development of PDD and might have
occurred simply as random findings in a population submitted to intensive
medical work-up. Nevertheless, the rate of 10% for medical abnormalities of
potential etiological significance is consistent with prior findings deriving
from both clinical35, 36
and epidemiological surveys.3, 5
The rate of sibling recurrence obtained in this study is also consistent with
figures of 3% to 7% reported by other investigators,34
and although the absolute magnitude of the risk remains small, a comparison with
the population prevalence points toward a large increase in the risk of autism
or PDD in families with an already affected child.
Some limitations of this study must be mentioned. First, clinical assessment
of children was not performed with standardized diagnostic techniques although
such instruments were available for parental interviews and cognitive testing.
It is unlikely that this would affect the prevalence estimates obtained in this
study since experienced clinicians agreed 100% on the presence of a PDD in the
whole sample. Availability of these assessments might nevertheless have provided
a different breakdown of the diagnosis into various diagnostic subcategories.
Assessing young children with PDDs is a complex task and guidelines to draw the
line between high-functioning autism, Asperger syndrome, and PDD-NOS remain to
be firmly established. Second, there is a possibility that some children might
have been missed despite the intensive screening efforts used in the survey.
This might particularly apply to some cases of Asperger syndrome who are
sometimes not detected before school age and might have led to some
underestimation of the prevalence. Conversely, some children diagnosed as having
mild forms of PDD-NOS may turn out on follow-up assessments to have more
transient developmental problems. This might have produced an inflation of the
prevalence estimate. Whether these 2 problems might cancel each other remains to
be seen, but we are committed to reassess this sample at age 8 to 10 years to
address these issues and to obtain a more stable estimate.
Author Affiliations: Child Development Centre, Central Clinic, Stafford,
England (Dr Chakrabarti); and Department of Child & Adolescent Psychiatry,
MRC Child Psychiatry Unit, Institute of Psychiatry, King's College, London,
England (Dr Fombonne).
Corresponding Author and Reprints: Eric Fombonne, MD, FRCPsych, MRC Child
Psychiatry Unit, Institute of Psychiatry/King's College London, Denmark Hill,
London SE5 8AF, England (e-mail: firstname.lastname@example.org).
Author Contributions: Study concept and design, analysis and
interpretation of data, drafting of the manuscript, critical revision of the
manuscript for important intellectual content, and administrative, technical, or
material support: Chakrabarti, Fombonne.
Acquisition of data and obtained funding: Chakrabarti.
Statistical expertise and supervision: Fombonne.
Funding/Support: Funding for this study was provided by the First
Community Health Trust.
Acknowledgment: We are grateful to the First Community Trust board and
its executive directors for supporting this research. We especially thank the
parents and children in the research group without whose cooperation and help
this research would not have been possible. We also thank all the staff of the
child development centers for their support and Sally Williams, BSc, senior
educational psychologist of Staffordshire LEA, who conducted all the
psychometric assessments of the children. Frank Devine, RGN, RNM, behavior nurse
specialist, helped enormously by his meticulous observation and recording of the
children's behavior, as well as by providing support to the children's families.
We also thank Marianne Murin and Simon Wallace for taking part in the
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The Scientist 15:16, May 14, 2001
Autism on the Rise
efforts aim at finding the biological basis for a complex disease
By Laura DeFrancesco
The rate of autism is rising. The number of reported cases has increased
10-fold in the last few decades, from 1 in 2,500 in the 1970s to 1 in 250 in the
1990s. Researchers are looking everywhere for the reason--from drinking water to
the womb--with no clear-cut answer to date. In part, the increased incidence can
be attributed to a broader definition of autism, which now includes milder forms
of the disorder,1 as well as to better diagnostics and greater public
awareness.2 But scientists don't know if these reasons explain the
At a late-April conference entitled "Autism: Deciphering the
Puzzle," developmental biologists, geneticists, and neurobiologists
gathered to talk about this complex disease. While scientists attending the
conference at the California Institute of Technology could not explain the huge
jump in incidence, they did voice some hope: there is progress in understanding
the condition's biological basis, along with the development of experimental
models, and it could lead to better treatments.
A Neurologist's Nightmare
Described by one participant as "a neurologist's
nightmare," autism affects a cohort of complex behaviors, involving
impaired language development, the inability to interact socially, and
repetitive and restrictive behaviors. Generally, autism is diagnosed in children
aged 2 and older because the behaviors can't be observed at an earlier age. But
researchers are working on improving the tools for diagnosing autism,
particularly in young children. As with many neurological diseases, including
apraxia and fetal alcohol syndrome, early intervention improves the prognosis.
Patricia Rodier, professor of obstetrics and
gynecology at the University of Rochester, described an early intervention test
at the conference that is used with infants. Devised by Susan
Bryson of York University in Toronto, this test measures a child's
ability to shift focus from one stimulus to another. In the first part of the
test, one light is turned on, and then as a second light is turned on, the first
is shut off. All children will shift their focus from the first to the second
light. In the second part of the test, the first light is left on. Here, normal
children will disengage from the first to the second light, but autistic
children cannot make that shift. Rodier showed dramatic video footage of a
5-year-old autistic child attempting this task. A look of panic came across the
child's face, as he realized that he couldn't take his eyes off the first light.
In contrast, a severely retarded 6-month-old could refocus her gaze with no
The above image shows positive functional activity in the fusiform gyrus (FG)
and superior temporal sulcus (STS) in a group of normal subjects in response to
faces, in comparison to the lack of functional activity noted in these regions
in autistic patients (left image). The T value is a metric of the functional NMR
signal intensity in relation to the variance. Courtesy
One research tool that has eluded workers in this field is an experimental
animal model for autism, because the diagnosis relies on human terms such as eye
contact, facial expressions, and speech. Bryson's test may be just the ticket;
it provides a glimpse into the nervous system but doesn't require learning or
In the Mind's Eye
Many parents of autistic children suffer a heart-breaking burden: often,
their youngsters are not emotionally connected to them. A recent University of
Washington study, presented to the Society for Research in Child Development,
showed that autistic children don't respond to faces, which could explain the
emotional distance from their parents. Measuring brain activity with a net of
external electrodes, Geraldine Dawson, director of the
University of Washington Autism Center, found that the brains of autistic
children were electrophysiologically silent when shown pictures of their
mothers, while they did respond to other pictures, such as their favorite toys.
At the Caltech conference, Eric Courchesne,
professor of neurosciences at the University of California, San Diego, presented
live, deep-brain scans that back Dawson's work. Using imaging techniques,
Courchesne and co-workers showed that the fusiform gyrus, the part of the brain
involved with face recognition, is not active when autistic children are shown
pictures of faces. Instead, in autistic children, each child displays a
different electrophysiological pattern. Why there is decreased activity in the
fusiform gyrus is unknown, but Karen Pierce, the
principal investigator, offers several explanations. "One possibility is
that limited exposure to faces in patients with autism (perhaps due to innate
preference, biases of processing style, or learning) results in an
underdevelopment or maldevelopment of face-processing systems. Another reason is
that the neural substrates involved in face processing (e.g., fusiform gyrus or
amygdala) is abnormal in autism." She made her comments after the
Most everyone is familiar with the haunting pictures from the 1960s of
so-called thalidomide babies, who were born with deformed limbs after their
mothers took this sedative while pregnant. Overlooked in the early studies is
that many thalidomide children are autistic--missed, no doubt, because their
parents and doctors were dealing with the more obvious and dramatic limb
deformities. But in 1994, Swedish researchers reported the surprising finding
that thalidomide children had a high incidence of autism,3 and for
developmental biologist Rodier, this was helpful news, because the Swedish
researchers identified when, during their pregnancies, the women took the drug.
Armed with these results, Rodier is developing an animal model for the kinds
of brain abnormalities observed with autism, since she knows exactly when in the
developmental program she needs to intervene. And she has the environmental
agents to do it. Though thalidomide doesn't affect rodents in the same way as
humans, Rodier has found that valproic acid, a common anti-seizure drug known to
induce autism, causes brain damage in rodents, and precisely in the places
expected, based on what's known about this disease.
Meeting organizer Paul Patterson describes a
promising experimental system being developed in his lab at Caltech that is
based on studies linking prenatal infections and immune dysfunction with mental
illness. In developing a system that assesses how interactions between the
immune system and nervous system affect brain development, Patterson has
observed autistic-like behaviors in mice born to mothers exposed to influenza
during pregnancy using a battery of behavioral tests. In one experiment, mice
are dropped into a box. While normal mice move around the box, frequently
stretching to sniff the environment, mice born to infected mothers stay in the
corner, clinging to the wall and sniffing only occasionally. Using this test and
others, Patterson intends to pick apart the immune response to see what proteins
or factors might be involved in explaining the offspring's odd behavior.
The evidence for a genetic component to autism is overwhelming and
indisputable.4 Consider, for example, that the parents of an autistic
child are more likely to have a second autistic child, as opposed to those who
have unaffected children. In a normal family, the likelihood is 0.4 percent; if
there already is an autistic child, the odds grow to 2 to 3 percent. With
identical twins, if one is autistic, the likelihood that the second will have
some form of autism is a staggering 90 percent; with fraternal twins, the odds
shrink to 2 to 3 percent.
Strong sentiment exists, particularly among the parents of autistic children,
that environmental factors also are involved here. One popular theory links
immunizations, particularly measles, mumps, rubella (MMR), with the onset of
autism. Researchers at the Caltech meeting summarily dismissed this notion,
because scientific evidence, they say, does not exist. Several recent studies,
including an Institute of Medicine report issued April 23, did not show a
correlation between MMR immunization and autism.5 In a study
published last February in the British Medical Journal,6 there
was no abrupt increase in the incidence of autism after the MMR vaccine was
What about other environmental factors? Eric Hollander,
professor of psychiatry at the Mt. Sinai School of Medicine and Clinical
Director of the Seaver Autism Research Center in New York City, is looking at
several factors. Noting that an unusually large number of women at his clinic
had pitocin-induced labor, Hollander is currently conducting a survey of some
58,000 births recorded in a national perinatal database to look for a connection
between that drug and autism. Hollander also is investigating the possibility
that an infectious agent is involved. He has found that in autistic children, a
high expression level exists of a particular B-cell marker, D8/17, which is
associated with altered sensitivity to streptococcus A.
Though much research has been carried out, there is still no complete answer,
or answers, as to why more autistic children exist today. "Cautious folks
will say that it is really impossible to say for sure what the reason is at this
point," Patterson says. "Given the broadening of the diagnostic
criteria, the heightened recognition of the disorder by doctors, and the fact
that parents only get state funds to help with special education ... if the
child has a diagnosis of a severe disorder such as autism, we'll only be able to
tell if this is a true rise in incidence after the dust has settled."
Laura DeFrancesco can be contacted at email@example.com.
1. E. Fombonne, "The epidemiology of autism: a review," Psychological
Medicine, 29: 769-86, 2000.
2. C. Lord et al., "Autism spectrum disorders," Neuron
28(2): 355-63, 2001.
3. K. Strömland, K. et al., "Autism in thalidomide embryopathy: A
population study," Developmental Medicine and Child Neurology, 36:
4. A. Bailey, "Autism as a strongly genetic disorder: evidence from a
British twin study," Psychological Medicine, 25:63-77, 1995.
5. "Immunization Safety Review: Measles-Mumps-Rubella Vaccine and
Autism," Institute of Medicine, April 23, 2001.
6. J.A. Kaye et al., "Mumps, measles, and rubella vaccine and the
incidence of autism recorded by general practitioners; a time trend
analysis," British Medical Journal, 322:460-3, 2001.