articole autism

Neural Pathways for Language in Autism: The Potential for Music-based Treatments
Catherine Y Wan; Gottfried Schlaug

Abstract and Introduction
Abstract Language deficits represent the core diagnostic characteristics of autism, and some of these individuals never develop functional speech. The language deficits in autism may be due to structural and functional abnormalities in certain language regions (e.g., frontal and temporal), or due to altered connectivity between these brain regions. In particular, a number of anatomical pathways that connect auditory and motor brain regions (e.g., the arcuate fasciculus, the uncinate fasciculus and the extreme capsule) may be altered in individuals with autism. These pathways may also provide targets for experimental treatments to facilitate communication skills in autism. We propose that music-based interventions (e.g., auditory± motor mapping training) would take advantage of the musical strengths of these children, and are likely to engage, and possibly strengthen, the connections between frontal and temporal regions bilaterally. Such treatments have important clinical potential in facilitating expressive language in nonverbal children with autism. Introduction Impairments in language and communication skills represent the core diagnostic features of autism or autism spectrum disorders.[1] The linguistic ability of individuals on the autism spectrum varies greatly. Up to 25% of individuals with autism spectrum disorders lack the ability to communicate with others using speech sounds.[101] Others have adequate linguistic knowledge coupled with abnormalities of nonliteral language, such as the comprehension of idioms,[2] and some individuals display impairments in the understanding of language in context.[3,4] At present, there appears to be no evidence-based intervention that consistently produces significant improvements in expressive language in individuals with autism.[5] Deficits in communication thus present a persistent and life-long challenge for individuals with autism and their families. To elucidate the language deficits in autism, researchers have used structural and functional imaging and neurophysiological techniques to examine potential abnormalities in classical language areas in the brain, such as the posterior inferior frontal gyrus (pIFG; i.e., Broca's region) and the posterior superior and middle temporal gyri (i.e., Wernicke's region). In this article, we review studies that have reported abnormalities in these key brain regions and the connections between them, and present a new experimental intervention that may provide an alternative medium to engage a network that might be abnormal, impaired or underdeveloped. It is inevitable that verbal individuals will be over-represented in this literature, so the work reviewed here may not be ideal for illuminating the mechanisms underlying the complete absence of speech, as is observed in some individuals with autism. We argue that interventions that engage the network of frontal and temporal brain regions bilaterally, such as

using alternative methods, may have important clinical potential, specifically in facilitating expressive language in otherwise nonverbal individuals, as well as in strengthening the underlying connections. Finally, we present a music-based intervention (termed auditory± motor mapping training) and provide a rationale of why it may serve as a viable therapeutic tool in assisting individuals with autism to develop speech.

Language Processing in Typically Developing Individuals
An investigation of language processing in autism requires an understanding of the core language regions and the underlying neural mechanisms in typically developing individuals. The two core regions of language consists of an anterior 'expressive' language region with a center in the left pIFG, which may serve as a coordinating center for motor planning and execution regions in the adjacent premotor and motor regions, and a posterior 'receptive' language region with a center in the left posterior superior temporal and middle temporal gyrus, which may have different subregions that deal with auditory feedback, matching of auditory perceptions to formed templates and a lexicon. Most of what we know about these brain regions, their interactions and their hemispheric laterality is derived from observations of patients with acquired brain lesions. Functional imaging studies have demonstrated that the cognitive processes that emphasize temporal features, such as speech perception, activate the left hemisphere more than the right hemisphere, whereas the opposite pattern of lateralization has been observed when the emphasis is on spectral or pitch information.[6,7] As a complement to these two classically defined language areas, it has been proposed that the putative human mirror neuron system (MNS) plays an important role in the acquisition of language. Originally discovered in area F5 of the macaque monkey, neurons in this region fire in response to both observed and performed actions.[8±10] A homolog area is believed to exist in the human brain with its hub in the inferior frontal gyrus, which overlaps with Broca's area. Other regions, such as the inferior parietal lobule and the superior temporal sulcus, are also believed to contain mirror neurons.[9±11] The shared representations of observed and executed actions in these neurons may serve as a foundation for our capacity to understand the experiences of other people, which is crucial for effective communication and social interactions. Accordingly, it has been hypothesized that an intact MNS might underlie normal language functions in humans,[12,13] and that language comprehension may be achieved through action understanding and mental simulations of sensory motor structures.[13±15] As illustrated below, components of the putative MNS are often abnormal in individuals with autism, which may account for some of their behavioral deficits, such as those related to language.[12,13]

Structural Abnormalities in Autism
Neuroimaging studies reported structural differences in language-related regions between individuals with autism and controls. A larger total brain volume has been consistently reported in children with autism,[16±19] with some studies showing that this overall volume difference may persist through to adulthood.[20,21] Abnormal asymmetry in frontal and temporal areas has been reported by a number of studies, although the direction of regional abnormalities is somewhat inconsistent. For example, a reversal of the usual left±right asymmetry (in typically developing individuals) has been found in the right inferior frontal gyrus, with larger volumes in the right hemisphere of individuals with autism.[22,23] By contrast, a smaller right volume in autism has also been

reported.[24] Using structural MRI, smaller volumes of the left planum temporale have been observed.[25,26] However, other research has reported a reduction in both hemispheres.[27] The inconsistent findings reported by these structural imaging studies may be attributable, in part, to the complexity of the disorder, which may have different etiologies, as well as intrinsic heterogeneity in linguistic abilities among individuals on the autism spectrum. In particular, individuals with Asperger's syndrome with no language delay should be separated from individuals with autism who display atypical language development. Indeed, McAlonan et al. found gray matter differences between these two groups;[28] children with autism had smaller gray matter volumes in posterior cingulate and precuneus regions compared with the Asperger's group. Therefore, this finding highlights the importance of language skills as a differentiating variable. A recent study compared a relatively homogenous group of participants (atypical language development with average IQ) with matched controls.[29] Increases in cortical thickness were found in the autism group in areas that are implicated in social cognition and communication, such as the inferior frontal gyrus, superior temporal sulcus, inferior parietal lobule and fusiform gyrus. Thus, it appears that structural abnormalities are apparent in brains of individuals with autism, particularly in areas that underlie core features such as communication problems of the disorder.

Aberrant Connectivity in Autism
To fully characterize the neural underpinnings of autism, it may be necessary to view it as a disorder of connections between brain regions rather than at the level of a single region. From this perspective, the language deficits in autism may be due to problems integrating a set of brain functions into a coherent concept even though the ability to execute individual functions may be relatively preserved. Indeed, it has been reported that some high-functioning children with autism have unusual strengths in processing single words, whereas their ability to process the meaning of complex sentences is significantly impaired.[30] Connectivity across brain regions can be examined using functional and structural imaging techniques. Functional connectivity examines the extent to which the activation levels within specified regions of interest are correlated with each other. Using functional MRI (fMRI), Just et al. compared the activation patterns between high-functioning individuals with autism and controls on a written sentence comprehension task.[31] The autism group demonstrated increased activation in Wernicke's area but decreased activation in Broca's area. Despite the enhanced activation in Wernicke's area, there was reduced functional connectivity (less correlation in activity) across the two areas in the autism group, supporting the idea that language functions may be poorly integrated in autism. In addition to functional connectivity, researchers have also investigated abnormalities in brain networks using a structural imaging method known as diffusion tensor imaging (DTI). DTI enables the delineation of white matter tract structure based on the degree of restriction to water diffusion and the direction of water diffusion (fractional anisotropy [FA]). Low FA implies less organized diffusion of water molecules along axons or in a certain direction, which reflects lower white matter integrity and possibly less efficient transmission of information. To date, only a handful of DTI studies in autism have been conducted, and low FA has been found in a number of key brain regions; the corpus callosum,[32] which is critical for interhemispheric communication; the white matter of the superior temporal gyrus and the temporal stem, which includes portions of the uncinate fasciculus and inferior occipitofrontal

fasciculus,[32] which are important for language and sound processing and comprehension; and the ventromedial prefrontal cortices, the anterior cingulated gyri and the temporoparietal junction,[33] which are critical for social cognitive processing. Recent research has also reported abnormality in the corpus callosum and frontal lobe tracts, such as the arcuate fasciculus, in children with autism.[34] In addition to abnormal long-range connectivity across brain regions, researchers suggested that there may be increased short-range connectivity in autism.[35,36] Post-mortem studies reported increased density of cortical mini-columns in brains of individuals with autism, suggesting a greater proportion of short range (as opposed to long-range) fibers.[36] Similarly, Herbert and colleagues[35] used a white matter parcellation technique and found increased radiate white matter in the autism group, which contains predominately short association fibers. Thus, these findings indicate abnormal microstructure of white matter in autism.

Language-related Anatomical Pathways
A number of tracts in the human brain are believed to be involved in language and speech processing, and possibly in the integration of auditory and motor functions. They are the arcuate fasciculus (AF), extreme capsule (EmC) and the uncinate fasciculus (UF). The tract that has received the most attention is the AF, which is a bundle of arched fibers that supposedly reciprocally connects the frontal motor coordinating and planning centers with the posterior temporal comprehension and auditory feedback regions. The AF may overlap with parts of the superior longitudinal fascicle.[37,38] Patients with isolated lesion of just the AF, known as conduction aphasics, have difficulty with aspects of language functions, such as poor word and phrase repetition and problems with naming, but relatively intact spontaneous speech and comprehension. The function of the AF can also be inferred from the structural asymmetry of the tracts across the two hemispheres, which may be either the cause or the consequence of hemispheric language specialization.[39] Indeed, a number of studies have reported left hemispheric dominance of the AF with a larger volume and a more elaborate connection pattern,[38,40,41] which is consistent with its hypothesized function of language processing. Although there is widespread support for the Broca±Wernicke connection of the AF, recent findings have also implicated the involvement of the precentral gyrus, the premotor and primary motor areas.[38,39] This has led to the suggestion that the AF connects the Broca's and Wernicke's area through a relay station located in the premotor and motor cortex,[42] which highlights the importance of this auditory-motor feedforward and feedback loop through the AF in coordinating and planning the motor actions of speech production, as well as the monitoring of speech production and language learning.[42] In particular, the connection between the postcentral gyrus and the inferior frontal gyrus may underlie imitation and programming of speech, which is important for language acquisition. This idea fits well with the clinical view that speech apraxia may underlie some of the deficits associated with conduction aphasia.[42] More importantly, the complete absence of speech in some individuals with autism, and the speech±motor planning difficulties of these individuals observed in our own laboratory,[43] highlights the possible involvement of the AF in accounting for the communication deficits in autism. Beyond the AF, recent research has implicated two other frontotemporal tracts, the UF and EmC, which may underlie language functions in humans. The UF is a hook-shaped fiber bundle that links the anterior temporal lobe to the orbitofrontal area, including the inferior

front l rus.[38] Some of its hypothesi ed functions include lexical retrieval semantic associations and naming of actions.[38] The EmC is a fi er bundle that interconnects the prefrontal cortex/inferior frontal cortex and the superior temporal gyrus extending into the inferior parietal lobule. The EmC has not been studied extensively; however, it is believed to play a role in language processing and possibly even auditory ±motor mapping owing to the [44] fiber's course connecting parts of both Broca's and Wernicke's areas. Given the connections between frontal and temporal regions, these anatomical pathways may serve to integrate sensory information with motor planning, preparation and action areas that is crucial for language representation and operations. Hickokand Poeppel proposed a dual stream framework in which phonological and semantic processing occurs in two separate ferior pathways.[45] The dorsal stream, which connects the temporal lobe with the in motor/premotor and pIFG via the AF, is responsible for the mapping of sound onto articulatory-based representations. By contrast, the ventral stream connects the temporal lobe with the anterior inferior frontal gyrus and the inferior/ventral prefron cortex via the UF tal and EmC tracts, and is involved in the mapping of sound onto meaning.
[34] The role of some of these anatomical pathways in autism has been recently investigated. Relative to the controls, individuals with autism had a greater number of long fibers in the right AF and UF. As illustrated in Figure 1 by our own data, the right AF and UF of a nonverbal boy (right with autism have more fibers and possibly a different microarchitecture than that of his age-matched control (left . We speculate that the reduced left±right asymmetries and microstructural abnormalities of anatomically identified tracts may be involved in the language deficits associated with autism. Similar structural problems have been observed in hippocampo-fusiform and amygdalo-fusiform tracts in their involvement in social and face cognition.[46]

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(Enlarge Image)

(l l) 8 l l i i ( i l). The right arcuate fasciculus ( ) and uncinate fasciculus (B) of the nonverbal boy is slighter larger than that of the age-matched control ( & ).

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Facili ate Auditory±Motor

How can the aberrant connections in autism be modified? It is well known that the human brain is capable of reorgani ation in response to environmental demands. Intensive training, in particular, has been shown to produce long -lasting functional and structural modifications in the brain. Music making and intensive musical training over long periods of timeprovide a particularly good opportunity for studying brain plasticity, as it is an intense, multisensory, motor experience that incorporates auditory feedback in improving sensorimotor skills. It has been demonstrated that children who engage in long -term instrumental practice have larger [47] corpus callosum, as well as frontal, temporal and motor areas,[48] relative to controls. Similarly, adult patients with Broca's aphasia who engage in an intensive course of music [49] based speech therapy showed increases in fiber number and volume of the AF, the frontaltemporal tract that may underlie the communication deficits in individuals with autism. These

structural changes are consistent with a large body of literature suggesting training-induced plasticity, such as in jugglers,[50,51] taxi drivers[52] and foreign language learners.[53] A recent study using DTI also showed structural changes following training with a complex visual± motor task.[54] Given the potential benefits of music making in producing plastic changes in the brain, it is conceivable that a music-based intervention can be used to engage and strengthen the connections between frontal and temporal regions that are abnormal in autism, thus potentially enabling affected individuals to develop their language skills. One such intervention is auditory±motor mapping training (AMMT),[43] which utilizes the musical strengths of individuals with autism, many of whom exhibit superior music perception abilities[55±57] and thoroughly enjoy music making (through singing and/or playing an instrument).[58±60] In addition, they tend to focus more on the perceptual (e.g., prosodic) information rather than the linguistic information of speech compared to typically developing individuals, which may contribute to their language and communication deficits.[61±65] Moreover, listening to music can evoke a great intensity of emotions in individuals with autism, who typically have difficulty processing emotions, a condition known as alexithymia.[66±68] The potential utility of music interventions in autism has been reported.[69,70] Musical stimuli have been shown to activate brain regions associated with the processing of emotions, such as the insular and cingulate cortex, hypothalamus, hippocampus, amygdala and prefrontal cortex,[71] thus further highlighting the therapeutic potential of musical activities in autism. Auditory±motor mapping training involves three main components: singing, motor activity and imitation. This training contains features of MIT,[72] but also uses a set of tuned drums to engage both hands in rhythmic motor activity and to facilitate auditory±motor mapping. Singing (more than speaking) is known to engage a bilateral reciprocal network between frontal and temporal regions, which contain some components of the putative MNS.[73,74] Critically, it has been proposed that a dysfunctional MNS underlies some of the language deficits in autism,[75] although some researchers have argued that the mirror neuron explanation may not account for all of the deficits in autism.[76] Motor activity (through playing an instrument) not only captures the child's interest, but also engages a sensorimotor network that controls orofacial and articulatory movements in speech.[77] The sound produced by the instrument may also facilitate the auditory±motor mapping that is critical for meaningful vocal communication.[78] Imitation through repetitive training facilitates learning and alters the responses in the MNS.[79] The potential utility of AMMT in ameliorating the language deficits in autism is reinforced by neuroimaging research showing overlapping responses to music and language stimuli.[74,80±83] In particular, fMRI studies have reported activation of the inferior frontal regions during music perception tasks,[80,84] active music tasks such as singing[74] and imagining playing an instrument.[85,86] Research has also shown that the dopaminergic system plays an important role in some aspects of language processing (e.g., grammar)[87] and that this system also mediates musical pleasure in individuals with autism.[88] Moreover, a common network appears to support the sensorimotor components for both speaking and singing,[74,86,89] and engaging in musical activities has been shown to improve verbal abilities in language-delayed children.[90]

Conclusion
Taken together, therapies that incorporate elements of music making (e.g., AMMT) may offer a viable approach to facilitate social skills and communication ± including expressive language ± in otherwise nonverbal individuals with autism. More importantly, as evidenced by the literature on training-induced plasticity, an intensive course of music-based or auditory-motor intervention, such as AMMT, may create a situation in which long-range connections between auditory and motor regions could be particularly engaged and possibly strengthened, such as those observed following intensive music training in children,[47] or melodic intonation therapy in aphasic patients.[49] Given the aberrant connectivity between frontal and temporal regions in autism, and the abnormalities within these two regions, the AF, the UF and the EmC may be some of the long-range tracts that serve as targets for experimental treatments to facilitate communication skills in autism.

Future Perspective
Over the past decade, research on autism has focused on its behavioral manifestations, neural underpinning, and more recently, possible candidate genes. Although the mechanisms underlying autism remain elusive, the considerable body of research conducted to date has laid a foundation for the development of new and innovative interventions. Theoretically grounded music-based interventions have been underutilized, which is unfortunate because music perception and music making is known to be a relative strength of individuals with autism. In particular, no study has systematically investigated the efficacy of a music-based intervention in facilitating speech output, and whether an intensive program can induce plastic changes in the brains of these individuals. On the basis of previous and current research, we hope that such specialized treatments for autism will be developed in the near future. Ultimately, such treatments should maximize the individual's potential for developing or relearning expressive language function and, thus, improve the quality of life for people with autism and their families.

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Advanced Parental Age and the Ris of Autism Spectrum Disorder
Maureen S. Durkin; Matthew J. Maenner; Craig J. Newschaffer; Li-Ching Lee; Christopher M. Cunniff; Julie L. Daniels; Russell S. Kirby; Lewis Leavitt; Lisa Miller; Walter Zahorodny; Laura A. Schieve

Abstract and Introduction
Abstract This study evaluated independent effects of maternal and paternal age on risk of autism spectrum disorder. A case-cohort design was implemented using data from 10 US study sites participating in the Centers for Disease Control and Prevention's Autism and Developmental Disabilities Monitoring Network. The 1994 birth cohort included 253,347 study-site births with complete parental age information. Cases included 1,251 children aged 8 years with complete parental age information from the same birth cohort and identified as having an autism spectrum disorder based on Diagnostic and Statistical Manual of Mental Disorders , Fourth Edition, Text Revision criteria. After adjustment for the other parent's age, birth order, maternal education, and other covariates, both maternal and paternal age were independently associated with autism (adjusted odds ratio for maternal age • 35 vs. 2529 years = 1.3, 95% confidence interval: 1.1, 1.6; adjusted odds ratio for paternal age • 40 years vs. 25-29 years = 1.4, 95% confidence interval: 1.1, 1.8). Firstborn offspring of 2 older parents were 3 times more likely to develop autism than were third- or later-born offspring of mothers aged 20-34 years and fathers aged <40 years (odds ratio 3.1, 95% confidence interval: 2.0, 4.7). The increase in autism risk with both maternal and paternal age has potential implications for public health planning and investigations of autism etiology. Introduction This paper examines the relation between parental age at delivery and the prevalence of autism spectrum disorder (ASD). The possibility that autism is more common in offspring of older parents has generated considerable interest.[1-6] Confirmation of such an association could have important public health implications in light of increasing trends in recent decades regarding both maternal and paternal age.[7] In addition, evidence of paternal and maternal age effects on autism risk may provide clues to the etiology of a class of neurodevelopmental disorder that is still poorly understood and thought to be complex and multifactoral. In evaluating the association between parental age and autism risk, it is important to account for other variables related to both parental age and autism or that may modify the association. Birth order is a potentially confounding factor because it is positively associated with parental age and has been reported in some studies to be associated with autism risk, with at least 3 studies reporting firstborn children to be at increased risk of autism.[1,2,4] The goal of this study was to determine, in a large, population-based cohort of US children, whether advancing maternal and paternal age each independently increase a child's risk of developing autism after controlling for the other parent's age, birth order, and other risk factors.

Materials and Methods

Study Design and Sample We implemented a population-based, case-cohort design in which the comparison group was a cohort of all livebirths in 1994 in 10 geographically defined study areas participating in the Centers for Disease Control and Prevention's Autism and Developmental Disabilities Monitoring Network.[8] The 10 areas are all sites with deidentified birth certificate information on parental age and other relevant variables included in the Network database and include sites in Alabama, Arizona, Arkansas, Colorado, Georgia, Maryland, Missouri, New Jersey, North Carolina, and Wisconsin. The cohort serving as the comparison group includes all livebirths to mothers residing in any 1 of the study areas in 1994, with complete information available from birth certificates on maternal and paternal age, birth order, and other variables. We used 2 data sources to construct the cohort: 1994 deidentified birth records for the Wisconsin study area provided by the Wisconsin Department of Health and Family Services and, for the remaining sites, the National Center for Health Statistics public use natality data files.[9] The public use file includes county of residence for births in densely populated counties, which enabled us to ascertain deidentified birth information for all births in most of the counties. We were unable to precisely obtain counts of births occurring in sparsely populated counties in which 13,043 (4.1%) of the study-area births occurred in 1994. For these counties, we obtained county-level aggregate information on the total number of births in 1994 and their distribution by variables such as maternal marital status, ethnicity, and age and selected a stratified random sample of deidentified birth records (equal in number and similar in distribution by maternal marital status, ethnicity, and age to all livebirths occurring in the respective counties in 1994) from sparsely populated counties of the state in which the study area was located. The full cohort included 326,785 livebirths, of which 73,438 (22.5%) were excluded because of missing paternal age. The cohort serving as the comparison group thus included the 253,347 livebirths with complete information on parental age and other key variables ( Table 1 ). The total number of children aged 8 years residing in the study areas in 2002 determined by the Autism and Developmental Disabilities Monitoring Network surveillance system to have an ASD was 2,142. Birth certificate information was available for 1,517 (70.8%) of these children, who were born in the same state as their state of residence in 2002. The remaining 29.2% of cases were excluded from this analysis because of missing birth certificate information. The case group for the present analysis was further restricted to the 1,251 children (58.4% of the total ASD case group) for whom information on both parents' age as well as birth order and gestational age was available. Our final sample was comparable to the total population of ASD cases regarding demographic factors and ASD case characteristics ( Table 1 ). Case Definition ASDs include behaviorally defined neurodevelopmental disorders diagnosed through clinical observation, and they encompass impairments in social, communicative, and behavioral development, often accompanied by abnormalities in intellectual functioning, learning, attention, and sensory processing. For this study, children with ASD included members of the birth cohort residing in the study area in 2002 who met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision criteria for autistic disorder; pervasive developmental disorders-not otherwise specified (PDD-NOS (http://www.cdc.gov/ncbddd/autism/overview_diagnostic_criteria.htm ), including atypical

autism); or Asperger's disorder[10] based on a comprehensive review of educational and clinical records by trained clinicians. Children were classified by clinician reviewers as having an ASD if they had either a documented previous classification of ASD (65%) or an evaluation record from an educational or medical setting indicating unusual behaviors consistent with ASD (35%). For children previously identified as having an ASD, case status was confirmed on the basis of evaluation records. For children without a documented ASD classification, data were abstracted on all relevant ASD and developmental behaviors from education or medical evaluations to determine whether behaviors described in the evaluations by clinical reviewers were consistent with the diagnostic criteria. Because case status was determined solely on the basis of information contained in evaluation records, and because Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision criteria are less well defined for PDD-NOS than for autistic disorder, the surveillance protocol for determining whether a child could be classified as having PDD-NOS required documentation of at least 1 behavior considered to be an ASD discriminator, such as being oblivious to others when there is a clear social opportunity or demonstrating atypical and persistent focus on sensory input.[11] Of the 1,251 ASD cases, 80.7% were determined to meet criteria for autistic disorder, while there was insufficient information for those remaining to distinguish between autistic disorder, Asperger's disorder, or PDD-NOS. Information from standardized intelligence tests was available for approximately 75% of the ASD cases. On the basis of this information, children with ASD were classified as having intellectual impairment (an IQ of < 70) versus normal intelligence. Further details regarding the 2002 Autism and Developmental Disabilities Monitoring Network sample and methodology have been reported previously.[8,11] Analytic Strategy and Statistical Methods Potential for confounding effects of birth order, gender, and other variables was evaluated by first examining unadjusted associations between each potential confounder and the independent variables of maternal and paternal age as well as the dependent variable, ASD case status. Variables were considered to be potentially confounding factors if they were associated with both parental age and ASD. Unadjusted odds ratios with confidence intervals were computed to evaluate the magnitude of these associations, and unconditional logistic regression models were fit to estimate adjusted odds ratios and 95% confidence intervals. Statistical significance was evaluated by using chi-square tests for categorical variables and analysis of variance for continuous variables. To enhance the comparability of our findings with those from other studies, we fit 2 types of models, 1 with parental ages categorized into 6 categories: < 20, 20-24, 25-29, 30-34, 35-39, • 40 years; and the other with parental age as a continuous variable with the odds ratio scaled to reflect a 10-year difference in age.[4] Although we found the association between parental age and autism risk to be similar across the 10 sites, to adjust for potential site-to-site variability we included site dummy variables in all multivariable models. To evaluate interaction or modifying effects of each covariate and of ASD subtypes on the associations between parental age and ASD, we performed stratified analyses. We also tested interaction terms for maternal age by paternal age and 2-way and 3-way interaction terms for each parent's age by the other covariates in the regression models, but we identified no significant interactions. SAS version 9.1.3 software (SAS Institute, Inc., Cary, North Carolina) was used for all statistical analyses.

This research involved secondary analysis of deidentified data and was approved by the University of Wisconsin Institutional Review Board.

Results
In unadjusted analyses, both mean maternal age and mean paternal age were significantly higher for ASD cases than for the birth cohort as a whole ( Table 2 ). Table 2 also shows that mean parental ages differed significantly in unadjusted analyses across categories of birth order, maternal education, ethnicity, multiple birth, gestational age, and birth weight for gestational age, but not for gender. With parental age 25-29 years as the reference group, the odds of developing ASD was significantly reduced for parental age < 20 years and increased for maternal age • 35 and paternal age • 40 years ( Table 3 , unadjusted odds ratios). We the refore used these age cutoffs (maternal age • 35, paternal age • 40 years) to classify each parent's age as "older" versus "younger." Other significant predictors of ASD in unadjusted analyses included low birth order, male gender, advanced maternal education, and preterm birth ( Table 3 ). Multivariable Analysis of Parental Ages Modeled as Categorical Variables After we adjusted for the other parent's age and other covariates, the increases in ASD risk associated with maternal age • 35 years and paternal age • 40 years (relative to age 25-29 years) were slightly reduced compared with the unadjusted analysis ( Table 3 ). In contrast, the results for birth order suggest that the decline in ASD risk associated with increasing birth order is somewhat stronger in the adjusted analysis than in the unadjusted analysis ( Table 3 ). In addition, the apparent increase in ASD risk associated with higher levels of maternal education in the unadjusted analysis is no longer evident in the adjusted model, suggesting that the apparent maternal education effect is due to its association with parental age ( Table 3 ). Parental Ages Modeled as Continuous Variables In unadjusted analyses, the risk of developing ASD increased significantly with each 10-year increase in both maternal age and paternal age. After adjustment for age of the other parent and other covariates, each 10-year increase in maternal age was associated with a 20% increase in ASD risk (odds ratio = 1.2, 95% confidence interval: 1.1, 1.4) while each 10-year increase in paternal age was associated with a 30% increase in ASD risk (odds ratio = 1.3, 95% confidence interval: 1.1, 1.5). Combined Effects of Parental Age and Birth Order The risk of ASD within each of 3 parental age categories (both parents "younger," 1 parent "older," and both parents "older") was highest among firstborn children and declined with increasing birth order ( Table 4 ). Considering the combined effects of parental age and birth order, we excluded from the analysis births to mothers aged < 20 years and found the lowest risk group to be third- or later-born offspring of mothers aged 20-34 years and fathers aged < 40 years. Compared with that for this group, the risk of ASD increased with both declining birth order and increasing number of older parents. The highest risk group included firstborn offspring of mothers aged • 35 years and fathers aged • 40 years, with a risk 3 times that of the reference group ( Table 4 ).

Discussion
Our findings are consistent with those recently reported from a large study of members of a California health maintenance organization[4] that found the risk of ASD to be positively and independently associated with both maternal and paternal age, with adjusted odds ratios nearly identical to those reported here. These findings contrast somewhat with 5 other recent epidemiologic studies that found only 1 or neither parent's age to be associated with ASD risk after controlling for the other parent's age.[2,3,12-14] The lack of consistency across studies could be due to limitations of sample size and of population representation of previous studies as well as other methodological differences, including autism case definitions and inclusion criteria and the ability to control for important variables. The present study included a large sample of children with sufficient information to enable evaluation of separate and combined effects of each parent's age as well as birth order and other variables. With more than 1,200 cases, it included over 50% more cases and thus more statistical power than any of the previous studies examining independent effects of maternal and paternal age on ASD risk. Another advantage of this study is the population-based nature and diversity of the cohort, allowing control for factors that may confound the association between parental age and ASD. Maternal education is 1 variable we considered to be a potentially confounding factor because it is associated with maternal age and has been observed to be related to ASD risk.[15] Our results, however, suggest that the association between advanced maternal education and ASD risk observed in unadjusted analysis may be spurious and due to confounding by parental age. The results of this study also demonstrate the importance of controlling for birth order in evaluating independent effects of parental age on ASD risk. Because birth order increases with parental age and, in this and other studies, has been found to be negatively associated with ASD risk, failure to control for birth order may mask a positive association between parental age and ASD risk. Two of the previous studies reporting an association between advancing maternal age and ASD[2,4] also had adjusted for birth order and, similar to the present study, found birth order to be negatively associated with ASD. An additional advantage of this study is its restriction to a single birth year, thereby controlling for temporal trends in recent decades in both ASD prevalence and parental ages at the birth of their children. This feature of the study allows estimation of the association between parental age and ASD risk independently of temporal trends in diagnostic practices or other factors. Public Health Implications The strength of the independent associations between maternal and paternal age and ASD risk, as indicated by the odds ratios in the range of 1.2-1.4 reported here, is modest. However, the observation that these effects are independent of each other and of low birth order raises the likelihood that the combined effects of parental age and birth order may have important public health implications. Mean maternal age in the United States has increased steadily since the 1970s, particularly for firstborn children, for whom mean maternal age at delivery increased by 3.8 years between 1970 and 2004.[16] In addition, the proportion of births to women aged • 35 years began increasing in the United States after 1980, when it was 5%; by 2004, it had increased to 14.2%.[17,18] During this same period, fertility rates for men aged

• 40 years also increased each year, while fertility among men age d < 30 years declined. [16] With the decline in average family size in recent decades, we would also expect the proportion of children who are firstborn to have increased. Similar trends are occurring in other developed countries.[7] The results of this study raise the question of whether some portion of the recent rise in ASD prevalence[19] may be linked to recent trends in parental age and family size. A furthe r question is whethe r a modest increase in prevalence associated with advancing parental age and low birth order may have contributed to a greater awareness of ASD and, in turn, increases in measured prevalence. The tendency for older parents of firstborn children to have higher levels of educational achievement and resources than other parents could further contribute to increased awareness and an expansion of the diagnosis of ASD. Potential Etiologic Implications of Parental Age Effects Because we observed independent effects of the age of each parent on ASD risk, the possible mechanisms for these effects could include a broad range of processes associated with either or both maternal and paternal age. The observed paternal age effect independent of maternal age could point to a causal role of gene mutations in male germ cells, because the probability or selection of these mutations increases as men age.[20,21] The independent effect of maternal age, on the other hand, may point to age -related chromosome changes, pregnancy complications, or environmental exposures during pregnancy. Independent effects of 1 or both parents' ages also could point to a role of accumulated environmental exposures that may have mutagenic effects on gametes or could result from a combination of mechanisms.[21,22] The association between advanced maternal and paternal age and ASD is also consistent with a potential role of infertility treatments or assisted reproductive technologies, the uses of which have increased in the past decade, especially by women and men of advanced reproductive age.[23] Numerous studies have found associations between these technologies and adverse pregnancy outcomes, including those due to epigenetic effects (24-27), although a recent review found no evidence of elevated rates of autism among children born after in vitro fertilization techniques.[28] Even though we have no information about exposure to these treatments in our cohort, the observation that firstborn children of older parents had the highest ASD risk is consistent with a possible infertility treatment effect because women who give birth after infertility treatment are more likely to be primiparous than those represented in the general birth cohort. However, the association between multiple birth and ASD in this study was weak and not statistically significant ( Table 3 , unadjusted odds ratio), whereas assisted reproduction technologies are strongly associated with multiple birth.[23] Another unmeasured factor in the present study potentially associated with both advanced parental age and ASD risk in offspring is psychopathology or behavioral traits of parents that may result in both delayed parenthood and genetic susceptibility to autism in offspring. [14] Birth-order Effects The observation in this and at least 2 previous studies[2,4] that the risk of developing ASD was highest for firstborn children and declined with increasing birth order is a pattern also observed for other childhood disorders, including type I diabetes and atopy, and is cited as support for the "hygiene hypothesis." According to this hypothesis, firstborn children are exposed to fewer infections from other children early in childhood and, because of delayed immunologic challenge, may be more likely to develop autoimmune responses including

those that may adversely affect neurodevelopment.[29] Another possible factor that could lead to the observed birth-order effect is exposure to potentially neurotoxic, fat-soluble chemicals accumulated in maternal tissue that have been passed to offspring transplacentally or through breast milk.[30] Because of accumulation over a lifetime, the load of such neurotoxins transmitted might be expected to be highest for firstborn children, particularly when combined with advanced maternal age. Another possible explanation for the observed birth order effect is "stoppage" or a tendency for parents of 1 child with ASD not to have subsequent children because of the demand s of parenting a child with a disability or concerns about genetic susceptibility,[31] thus increasing the likelihood in the cohort as a whole that a child with ASD will have a low birth order. Information available for the present study did not allow examination of these hypotheses. Another important limitation of this study is that the cohort available for analysis excludes births with missing paternal age information. Because this exclusion applied to both the ASD cases and the comparison group ( Table 1 ), we would not expect it to have resulted in biased estimates of the association between ASD and parental age. In a separate analysis, we examined the association between maternal age and ASD without adjusting for paternal age and including the full birth cohort, and we found the association between maternal age and ASD to be the same as that observed in the subcohort with paternal age. Another limitation is that the birth cohort comparison group includes about 1% of births of children who died postnatally in addition to an undetermined number who moved out of the study area between birth and the age of 8 years, whereas children who died postnatally and those moving out of the study area after birth are excluded from the case group. Because of this limitation, we could not estimate cumulative incidence of ASD. Nonetheless, this limitation is unlikely to have biased the estimated odds ratios reported in this study, particularly those adjusted for factors such as gestational age and birth weight for gestational age, which are strongly associated with postnatal mortality. Another possible explanation for the increase in ASD among offspring of older parents, but one we cannot evaluate with the data available, is that, compared with younger parents, older parents may be more aware of developmental abnormalities and better able to access diagnostic and special educational services. other limitations are that parity pertains to only mothers and does not take into account the number of previous births fathered by the fathers represented in the cohort, potential for residual confounding by factors not measured in the present study, possible misclassification of ASD case status, and missing information on paternal education.

Conclusion
The results of this study provide the most compelling evidence to date that ASD risk increases with both maternal and paternal age and decreases with birth order. Further research involving large, well-characterized birth cohorts followed longitudinally will be required to confirm these findings and adequately evaluate the range of alternative genetic and environmental hypotheses that this and other studies raise regarding parental age and birth-order effects on ASD risk. Smaller, focused studies may also be useful, such as Crow's idea to look for mutations responsible for complex disorders of unknown etiology and with parental age effects by studying affected families with older parents.[20]

References 1. Tsai LY, Stewart MA. Etiological implication of maternal age and birth order in infantile autism. J Autism Dev Disord. 1983;13(1):57-65. 2. Glasson EJ, Bower C, Petterson B, et al. Perinatal factors and the development of autism. Arch Gen Psychiatry. (2004;61(6):618-627. 3. Reichenberg A, Gross R, Weiser M, et al. Advancing paternal age and autism. Arch Gen Psychiatry. 2006;63(9):1026-1032. 4. Croen LA, Najjar DV, Fireman B, et al. Maternal and paternal age and risk of autism spectrum disorder. Arch Pediatr Adolesc Med. 2007;161(4):334-340. 5. Cantor RM, Yoon JL, Furr J, et al. Paternal age and autism are associated in a familybased sample. Mol Psychiatry. 2007;12(5):419-421. 6. Koyama T, Miyake Y, Kurita H. Parental age s at birth of children with pervasive developmental disorders are higher than those of children in the general population. Psychiatry Clin Neurosci. 2007;61(2):200-202. 7. Bray I, Gunnell D, Davey Smith G. Advanced paternal age : how old is too old? J Epidemiol Community Health. 2006;60(10):851-853. 8. Autism and Developmental Disabilities Monitoring Network Surveillance Year 2002 Principal Investigators; Centers for Disease Control and Prevention. 14 sites, United States, 2002. MMWR Surveill Summ. 2007;56(1):12-28. 9. National Center for Health Statistics, natality data, public-use data files. (http://www.cdc.gov/nchs/products/elec_prods/subject/natality.htm) (Accessed November 2007). 10. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR. Fourth Edition, Text Revision. Arlington, VA: American Psychiatric Association; 2000. 11. Rice CE, Baio JL, Van Naarden Braun K, et al. A public health collaboration for the surveillance of autism spectrum disorders. Paediatr Perinat Epidemiol. 2007;21(2):179-190. 12. Lauritsen MB, Pedersen CB, Mortensen PB. Effects of familial risk factors and place of birth on the risk of autism: a nationwide register-based study. J Child Psychol Psychiatry. 2005;46(9):963-971. 13. Maimburg RD, Vaeth M. Perinatal risk factors for infantile autism. Acta Psychiatr Scand. 2006;114(4):257-264. 14. Larsson HJ, Eaton WW, Madsen KM, et al. Risk factors for autism: perinatal factors, parental psychiatric history, and socioeconomic status. Am J Epidemiol. 2005;161(10):916-925. 15. Treffert DA. Epidemiology of infantile autism. Arch Gen Psychiatry. 1970;22(5):431438. 16. Martin JA, Hamilton BE, Sutton PD. Births: final data for 2004. Natl Vital Stat Rep. 2006;55(1):1-102. 17. Mathe ws TJ, Hamilton BE. Mean age of mother, 1970-2000. Natl Vital Stat Rep. 2002;51(1):1-14. 18. CDC. National Vital Statistics System. (http://www.cdc.gov/nchs/births.htm#Tabulated) (Accessed September 11, 2008). 19. Yeargin-Allsopp M, Rice C, Karapurkar T, et al. Prevalence of autism in a US metropolitan area. JAMA 2003;289(1):49-55. 20. Crow JF. The high spontaneous mutation rate: is it a health risk? Proc Natl Acad Sci U S A. 1997;94(16):8380-8386.

21. Crow JF. Age and sex effects on new mutation rates: an old problem with new complexities. J Radiat Res (Tokyo). 2006;47(suppl B):B75-B82. 22. Penrose LS. Parental age and mutation. Lancet. 1955;269(6885):312-313. 23. Wright VC, Chang J, Jeng G, et al. Assisted reproductive technology surveillance² United States, 2004. MMWR Surveill Summ. 2007;56(6):1-22. 24. Ombelet W, Martens G, De Sutter P, et al. Perinatal outcome of 12,021 singleton and 3108 twin births after non-IVF-assisted reproduction: a cohort study. Hum Reprod. 2006;21(4):1025-1032. 25. Schieve LA, Rasmussen SA, Reefhuis J. Risk of birth defects among children conceived with assisted reproductive technology: providing an epidemiologic context to the data. Fertil Steril. 2005;84(5):1320-1324. 26. DeBaun MR, Niemitz EL, Feinberg AP. Association of in vitro fertilization with Beckwith-Wiedemann syndrome and epigenetic alterations of LIT1 and H19. Am J Hum Genet. 2003;72(1):156-160. 27. Sato A, Otsu E, Negishi H, et al. Aberrant DNA methylation of imprinted loci in superovulated oocytes. Hum Reprod. 2007;22(1):26-35. 28. Newschaffer CJ, Croen LA, Daniels J, et al. The epidemiology of autism spectrum disorders. Annu Rev Public Health. 2007;28:235-258. 29. Rook GA. The hygiene hypothe sis and the increasing prevalence of chronic inflammatory disorders. Trans R Soc Trop Med Hyg. 2007;101(11):1072 -1074. 30. Iida T, Hirakawa H, Matsueda T, et al. Polychlorinated dibenzo-P-dioxins and related compounds in breast milk of Japanese primiparas and multiparas. Chemosphere. 1999;38(11):2461-2466. 31. Jones MB, Szatmari P. Stoppage rules and genetic studies of autism. J Autism Dev Disord. 1988;18(1):31-40.

Mental Health of Adults with Autism Spectrum Disorders and Intellectual Disability
Lisa Underwood; Jane McCarthy; Elias Tsakanikos

Abstract and Introduction
Abstract Purpose of review The literature has often suggested that individuals with intellectual disability who have an autism spectrum disorder (ASD) experience higher rates of mental health problems than those without ASD. This finding has been challenged in recent years and so the purpose of this article was to critically review relevant studies since March 2009. The review focuses on studies specifically about the mental health of adults with intellectual disability who have ASD. Recent findings Recent studies do not support the hypothesis that adults with intellectual disability and ASD are more vulnerable to psychiatric disorders than those without ASD. Factors found to be associated with poorer mental health include severity of intellectual disability, adaptive behaviour skills and social skills. Summary The evidence base on the mental health of adults with intellectual disability and ASD is small but rapidly increasing. Studies tend to have relatively small sample sizes and there remain difficulties in accurately assessing ASD and psychopathology in adults with intellectual disability. Introduction Autism spectrum disorders (ASDs) are neurodevelopmental conditions characterized by lifelong impairments in social interaction, communication and imagination.[1] Depending on diagnostic criteria and methodological instruments, the rate of ASD in those with intellectual disability has been reported to be between 8 and 20%.[2,3,4‡] In adults with intellectual disability who live in community settings, presence of ASD is the strongest predictor of hospital admission, psychotropic medication and problem behaviours.[5,6] Although presence of ASD in children and young adults increases the likelihood of mental health problems[7,8] it is less clear if this is also the case in adults with intellectual disability. Studies that employed clinical[9] and population-based[10] samples showed that the presence of ASD in adults does not increase the likelihood of mental-health problems.

The Evidence Base
Research with a specific focus on comorbid psychopathology in adults with intellectual disability and ASD has increased dramatically in recent years. Five years ago only one study, on rates of psychiatric disorder, had been published. [11] Between then and the current review period another five reports emerged.[9,10,12±14] The most recently published studies are described below. Table 1 [4‡,15‡,16‡,17‡] describes relevant reviews published since March 2009.

Assessment of Psychopathology

A review of measures for assessing psychopathology in people with ASD identified several tools for adults with intellectual disability.[15‡] The authors concluded that, as a number of instruments have been developed for people with intellectual disability and ASD, there is currently insufficient evidence on their accuracy and that tools need to be further developed and tested. The review looked at recent reports on the Autism Spectrum Disorders ± Comorbidity for Adults scale (ASD-CA;)[18‡] and the Psychopathology in Autism Checklist (PAC;).[19]

Prevalence and Patterns of Psychopathology
The prevalence of psychiatric disorder in people with ASD and intellectual disability was discussed in a review on the mental health needs of people with ASD.[16‡] The authors reported mixed results from the studies discussed and highlighted the difficulties in carrying out epidemiological studies, including referral bias (particularly in clinic-based samples), small sample sizes and problems differentiating between symptoms of psychiatric disorders and features of ASD. The authors point to a range of risk factors for psychiatric disorder including genetic factors, communication problems, loneliness and low self-esteem. Cooper and van der Speck[17‡‡] reviewed studies on the epidemiology of mental health problems in adults with intellectual disability. Their section on ASD covered three papers from 2008 with mixed results: a low rate of psychiatric disorder, a higher rate of schizophrenia than individuals without ASD and no difference in prevalence rates of mental ill health. The authors did not draw any conclusions on the epidemiology of mental ill health in adults with ASD and intellectual disability. A Canadian study looked at the clinical characteristics of adults with ASD and intellectual disability.[20‡] More than half of those with ASD also had a psychiatric disorder; 26.1% had a mood disorder, another 26.1% had a psychotic disorder and one person (4.3%) had a personality disorder. When rates of these disorders were compared with those in individuals without ASD, those with ASD were significantly less likely to have a psychotic disorder. There were no other statistically significant differences between the groups; however, this should be taken with caution given the very small sample sizes in some of the analyses. Furthermore, the study was unable to match the groups with intellectual disability on severity due to a lack of available information. A report on older adults with intellectual disability and ASD combined data from four UK studies of participants in staffed group homes.[21‡‡] Two analyses were carried out; firstly, participants with ASD were compared with all those without ASD, then a subsample of participants with ASD were compared with a matched sample without ASD on the basis of their level of adaptive skills. In the comparison of the unmatched groups there was no statistically significant difference in the rate of psychiatric disorder, which was 31.7% for people with ASD and 23.3% for those without ASD. The analysis of the matched groups found no statistically significant differences between the groups with and without ASD. The findings of the study are discussed with caution, given the way in which presence of ASD was defined in this study, with the authors suggesting that '«the presence of the triad of impairment typically observed in ASD is not associated with differential outcomes among older adults with an ID [intellectual disability].' Information on the severity of intellectual disability of the study's participants was not available. Therefore, it is unclear whether differences in psychopathology, behaviour problems and quality of life are associated with a stable characteristic such as level of intellectual disability or adaptive skills, which the authors suggest could be improved thus perhaps leading to better outcomes.

A study in the United States investigated the frequency of symptoms in adults with intellectual disability, ASD and diagnosed psychiatric disorder.[18‡] Psychopathology was assessed using the ASD-CA. Differences were found between those with intellectual disability only and those with intellectual disability and ASD. However, expected differences between those with intellectual disability and ASD and those with additional psychopathology were not found. A more recent study from the same research group employed the ASD-CA to look at rates of psychopathology in adults with combinations of intellectual disability, ASD and epilepsy.[22] A small number of individuals with ASD (N¼25, 4.4% of the sample) were included in a study of factors associated with mental disorders in adults with intellectual disability.[23‡] The presence of autism was associated with higher levels of psychosis, anxiety, problem behaviour and overall mental ill health. However, after controlling for age, sex, presence of autism and other factors, only severity of intellectual disability remained a statistically significant predictor of psychopathology. The relationship between intellectual disability and ASD was reviewed by Matson and Shoemaker.[4‡] A section on comorbid psychopathology looked at a number of studies published since 2006. Their finding of higher rates of psychopathology in those with intellectual disability and ASD was mainly supported by studies on children and adolescents. The authors call for more work on the development of tools for accurately assessing psychopathology in people with intellectual disability and ASD of all ages. A review of studies on psychosis, affective disorders and anxiety in ASD found a wide range in the rates of these disorders.[24] Anxiety disorders were most common (5±35% for generalized anxiety, 10±64% for phobias and 1±37% for OCD), followed by affective disorders (0±50%) and schizophrenia (0±6%). Aside from methodological issues, the authors found it difficult to tell whether studies included individuals with intellectual disability and ASD. In addition, for many studies comorbidity was not the primary aim.

Characteristics Associated with Psychopathology
The relationship between psychopathology and challenging behaviour in adults with intellectual disability and ASD was investigated in a large sample of patients from a specialist mental health service in the UK.[25‡‡] The 124 participants with intellectual disability and ASD were more likely to exhibit challenging behaviour than those without ASD (N¼562). In participants with challenging behaviour there were significant differences in psychopathology between those with and without ASD. Participants with ASD and challenging behaviour were less likely to have schizophrenia and less likely to have any additional psychiatric disorder. However, when level of intellectual disability, sex and age were controlled for presence of challenging behaviour was not associated with psychopathology; only the presence of ASD and severe intellectual disability predicted challenging behaviour. The authors concluded that, in adults with intellectual disability and ASD, challenging behaviour and mental health problems are independent conditions. This finding could have implications for the diagnosis of psychopathology ± which often relies on the assessment of behavioural symptoms ± and for the management of challenging behaviour in individuals with intellectual disability and ASD. A study on the relationship between psychopathology and social skills in adults with intellectual disability and ASD was carried out in the United States.[26‡‡] There were significant variations in the pattern of associations between individual psychopathology symptoms and social skills between those with and without ASD. Only the ASD group had

positive skills associated with psychopathology as well as negative social behaviours. Social skill items were a predictor of the severity of psychiatric symptoms for both groups. The relationship between adaptive behaviour skills, psychopathology and ASD was investigated in a study of adults with intellectual disability.[27‡] Half of the participants with intellectual disability and ASD had an additional mental health problem compared with only 13% of the participants with intellectual disability. Those with intellectual disability, ASD and a psychiatric disorder had the lowest level of adaptive skills, significantly lower than those with intellectual disability and ASD or intellectual disability alone. Presence of a psychiatric disorder appeared to have no effect on adaptive behaviour, and there did not seem to be any interactional effect between psychopathology and ASD. There were no differences between the groups with and without ASD on sex or severity of intellectual disability. This study found that a higher proportion of those without ASD were African±American than those with ASD. A study of adults with intellectual disability receiving psychiatric treatment from a specialist mental health service in the UK looked at the role of ethnic differences in clinical psychopathology.[28‡] Among the participants were 144 people with intellectual disability and ASD (constituting 19.1% of the total sample). A diagnosis of ASD was more likely in black participants than in white or other ethnic group participants. However, this may be accounted for by age differences between the groups studied and the authors state that there is 'a lack of substantial supporting evidence [for] an association between ethnicity and autistic spectrum disorders'.

Services and Intervention for Mental Health Problems
In June 2009, the National Audit Office published its report on services for adults with autism.[29‡] Although much of the report focused on people with 'high-functioning' autism, several of the recommendations were relevant to mental health services for people with intellectual disability and ASD. During 2009 the Autism Act became law in the UK in November.[30] The Government is required to publish mandatory guidance for health and social care services to support implementation of the Act by end of 2010. Knapp et al. [31‡‡] estimated that the economic cost of ASD in the UK is £27.7 billion a year. They carried out separate analyses for adults with and without intellectual disability, finding that annual costs for adults with intellectual disability are £16.9 billion. Several of the datasets used in the analyses for those with ASD and intellectual disability included participants with additional mental health problems. However the exact number of people with intellectual disability, ASD and mental health problems was not clear, separate analyses for those with and without mental health problems were not carried out and the study focused on service costs specifically attributable to ASD so it was not clear whether there was any variation in mental health service use. A survey of systematic reviews on psychosocial interventions for adults with intellectual disability and/or ASD with mental health problems found only three studies that met their inclusion criteria.[32] Unfortunately, neither the two reviews on psychotherapy nor the review on integrated care appeared to include studies on participants with ASD. It was not clear how many of the 123 excluded reviews, which covered housing support, social skills training and psychotherapy, included studies on people with ASD.

Additional Studies

Other potentially relevant studies published since March 2009 include those on psychiatric and psychosocial problems in adults with 'normal-intelligence' ASD;[33] psychiatric and psychosocial problems in young adults with autistic traits;[34] medication use among people with ASD (the majority of whom had intellectual disability);[35] psychiatric symptoms among high-functioning adolescents with ASD;[36] and challenging behaviour in adults with intellectual disability with and without ASD.[37] In addition to the studies reviewed above there have been a number of recent studies on children with ASD, some of which included participants with intellectual disability.[38±43] The primary studies included in this review vary in purpose, methodology and quality. Table 2 summarizes the issues which are important when judging the strength of studies and the extent to which they add to the evidence base.

Conclusion
At present there is no consensus on the best way to assess psychopathology in adults with ASD and intellectual disability. More population-based and clinic-based studies are needed before a clear picture of the prevalence, course and outcome of mental health problems in adults with intellectual disability and ASD can emerge. In addition to ensuring that presence of ASD is attributed accurately, studies should collect data on a broader range of measures including health, social functioning and service users' experience with mental health services. These recent findings show how important it is that studies match groups with and without ASD on age, sex and severity of intellectual disability. Investigating whether predictors of outcome are fixed or possibly subject to intervention (e.g. adaptive behaviour skills) would be a valuable addition to the evidence base. References 1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th edition. Washington, DC: American Psychiatric Association; 1994. 2. Bhaumik S, Tyrer F, McGrother C, Ganghadaran SK. Psychiatric service use and psychiatric disorders in adults with intellectual disability. J Intellect Disabil Res 2008; 52:986±995. 3. Cooper S-A, Smiley E, Morrison J, et al. Mental ill-health in adults with intellectual disabilities: prevalence and associated factors. Br J Psychiatry 2007; 190:27±35. 4. Matson JL, Shoemaker M. Intellectual disability and its relationship to autism spectrum disorders. Res Dev Disabil 2009; 30:1107±1114. ‡ This is an in-depth review covering the nosology and prevalence of ASD in people with intellectual disability. This report critiques recent research on adaptive behaviour, challenging behaviour and comorbid psychopathology. 5. Cowley A, Newton J, Sturmey P, et al. Psychiatric inpatient admissions of adults with intellectual disabilities: predictive factors. Am J Ment Retard 2005; 110:216±225. 6. Tsakanikos E, Costello H, Holt G, et al. Behaviour management problems as predictors of psychotropic medication and use of psychiatric services in adults with autism. J Autism Dev Disord 2007; 37:1080±1085. 7. Bradley EA, Summers JA,Wood HL, Bryson SE.Comparing rates of psychiatric and behaviour disorders in adolescents and young adults with severe intellectual disability with and without autism. J AutismDev Disord 2004; 34:151±161.

8. Brereton AV, Tonge BJ, Einfeld SL. Psychopathology in children and adolescents with autism compared to young people with intellectual disability. J Autism Dev Disord 2006; 36:863±870. 9. Tsakanikos E, Costello H, Holt G, et al. Psychopathology in adults with autism and intellectual disability. J Autism Dev Disord 2006; 36:1123±1129. 10. Melville CA, Cooper S-A, Morrison J, et al. The prevalence and incidence of mental ill-health in adults with autism and intellectual disabilities. J Autism Dev Disord 2008; 38:1676±1688. 11. Morgan CN, Roy M, Chance P. Psychiatric comorbidity and medication use in autism: a community survey. Psychiatric Bull 2003; 27:378±381. 12. Tsakanikos E, Sturmey P, Costello H, et al. Referral trends in mental health services for adults with intellectual disability and autism spectrum disorders. Autism 2007; 11:9±17. 13. La Malfa G, Lassi S, Salvini R, et al. The relationship between autism and psychiatric disorders in intellectually disabled adults. Res Autism Spectr Disord 2007; 1:218±228. 14. Matson JL, Boisjoli JA. Autism spectrum disorders in adults with intellectual disability and comorbid psychopathology: scale development and reliability of the ASD-CA. Res Autism Spectr Disord 2008; 2:276±287. 15. Underwood LA, McCarthy J, Tsakanikos, E. Assessment of co-morbid psychopathology. In: Matson JL, Sturmey P, editors. International handbook of autism and pervasive developmental disorders. New York: Springer (in press). ‡ Extensive critical review of the tools available to assess psychopathology in children and adolescents with ASD. Looks at issues of reliability and validity, as well as the evidence available for each measure. 16. Kannabiran M, McCarthy J. The mental health needs of people with autism spectrum disorders. Psychiatry 2009; 8:398±401. ‡ This is a comprehensive review focusing on issues of diagnosis and risk factors for psychopathology in people with ASD. Covers studies on those with additional intellectual disability. 17. Cooper S-A, van der Speck R. Epidemiology of mental ill health in adults with intellectual disabilities. Curr Opin Psychiatry 2009; 22:431±436. ‡‡ Useful critique of recent research, which highlights a number of important studies and suggests directions for future research. 18. LoVullo SV, Matson JL. Comorbid psychopathology in adults with autism spectrum disorders and intellectual disabilities. Res Dev Disabil 2009; 30:1288±1296. ‡ There is a great need for tools that can accurately assess psychopathology in adults with intellectual disability and ASD. This study reports on the development of such a measure and provides evidence on its psychometric properties. 19. Helvershou SB, Bakken TL, Martinsen H. The Psychopathology in Autism (PAC): a pilot study. Res Autism Spectr Disord 2009; 3:179±195. 20. Lunsky Y, Gracey C, Bradley E. Adults with autism spectrum disorders using psychiatric hospitals in Ontario: clinical profile and service needs. Res Autism Spectr Disord 2009; 3:1006±1013. ‡ One of the few studies specifically on the mental health service needs of adults with intellectual disability and ASD. Interesting differences in participants' clinical characteristics were also reported. 21. Totsika V, Felce D, Kerr M, Hastings RP. Behavior problems, psychiatric symptoms and quality of life for older adults with intellectual disability with and without autism. J Autism Dev Disord 2010. [Epub ahead of print] ‡‡ The first study to look at the experiences of older adults with intellectual disability

and ASD. With a large sample size, the analyses point to the effect of differences in adaptive skills on mental health outcomes. 22. Smith KRM, Matson JL. Psychopathology: differences among adults with intellectually disabled comorbid autism spectrum disorders and epilepsy. Res Dev Disabil 2010; 31:743±749. 23. Hove O, Havik OE. Developmental level and other factors associated with symptoms of mental disorders and problem behaviour in adults with intellectual disabilities living in the community. Soc Psychiat Epidemiol 2010; 45:105±113. ‡ This is an important attempt to explore the effect of the clinical characteristics of adults with intellectual disability on their mental health. This study includes separate analyses on a sub-sample of individuals with ASD. 24. Skokauskas N, Gallagher L. Psychosis, affective disorders and anxiety in autistic spectrum disorder: prevalence and nosological considerations. Psychopathology 2010; 43:8±16. 25. McCarthy J, Hemmings C, Kravariti E, et al. Challenging behaviour and co-morbid psychopathology in adults with intellectual disability and autism spectrum disorders. Res Dev Disabil 2010; 31:362±366. ‡‡ One of the largest studies specifically on the mental health of adults with intellectual disability and ASD. Adds valuable evidence on the (apparent lack of) association between psychopathology and challenging behaviour. 26. Matson JL, Dempsey T, Rivet TT. The interrelationships of psychopathology symptoms on social skills in adults with autism or PDD-NOS and intellectual disability. J Dev Phys Disabil 2009; 21:39±55. ‡‡ Significant study on adults with intellectual disability, ASD and mental health problems, which explores the association between symptom severity and social skills. The consideration of a wider range of factors than age, sex and severity of intellectual disability marks an important development in the evidence base. 27. Matson JL, Rivet TT, Fodstad JC, et al. Examination of adaptive behaviour differences in adults with autism spectrum disorders and intellectual disability. Res Dev Disabil 2009; 30:1317±1325. ‡ This large study on adults with intellectual disability, ASD and mental health problems provides additional evidence on the complex relationship between individuals' cognitive impairments, skills and symptoms of psychopathology. 28. Tsakanikos E, McCarthy J, Kravariti E, et al. The role of ethnicity in clinical psychopathology and care pathways of adults with intellectual disabilities. Res Dev Disabil 2010; 31:410±415. ‡ One of the very few studies to investigate the impact of ethnicity on mental health service users with intellectual disability. This report also includes analyses on those with ASD. 29. National Audit Office. Supporting people with autism through adulthood. London: National Audit Office; 2009. ‡ Government commissioned review of services for adults with ASD, which explored the impacts of providing specialized support for those with high-functioning ASD. The recommendations made by the report informed the Autism Bill, which was passed in November 2009. 30. Great Britain. Autism Act 2009. Chapter 15, London: The Stationery Office; 2009. 31. Knapp M, Romeo R, Beecham J. Economic cost of autism in the UK. Autism 2009; 13:317±336. ‡‡ This is the only study to estimate the number of people with ASD and intellectual

disability in the UK. This is the very important finding on the costs of autism in the UK and how they vary between groups. 32. Gustafsson C, Öjehagen A, Hansson L, et al. Effects of psychosocial interventions for people with intellectual disabilities and mental health problems: a survey of systematic reviews. Res Soc Work Pract 2009; 19:281± 290. 33. Hofvander B, Delorme R, Chaste P, et al. Psychiatric and psychosocial problems in adults with normal-intelligence autism spectrum disorders. BMC Psychiatry 2009; 9:35. 34. Kanne SM, Christ SE, Reiersen AM. Psychiatric symptoms and psychosocial difficulties in young adults with autistic traits. J Autism Dev Disord 2009; 39:827± 833. 35. Esbensen AJ, Greenberg JS, Seltzer MM, Aman MG. A longitudinal investigation of psychotropic and nonpsychotropic medication use among adolescents and adults with autism spectrum disorders. J Autism Dev Disord 2009; 39:1339±1349. 36. Hurtig T, Kuusikko S, Mattila ML, et al. Multiinformant reports of psychiatric symptoms among high-functioning adolescents with Asperger syndrome or autism. Autism 2009; 13:583±598. 37. Rojahn J, Wilkins J, Matson JL, Boisjoli J. A comparison of adults with intellectual disabilities with and without ASD on parallel measures of challenging behaviour: the behavior problems inventory-01 (BPI-01) and autism spectrum disorders-behavior problems for intellectually disabled adults (ASDBPA). J Appl Res Intellect Disabil 2009; 23:179±185. 38. MacNeil BM, Lopes VA, Minnes PM. Anxiety in children and adolescents with autism spectrum disorders. Res Autism Spectr Disord 2009; 3:1±21. 39. Kanne SM, Abbacchi AM, Constantino JN. Multiinformant ratings of psychiatric symptom severity in children with autism spectrum disorders: the importance of environmental context. J Autism Dev Disord 2009; 39:856± 864. 40. Matson JL, LoVullo SV, Rivet TT, Boisjoli JA. Validity of the autism spectrum disorder-comorbid for children (ASD-CC). Res Autism Spectr Disord 2009; 3:345± 357. 41. White SW, Oswald D, Ollendick T, Scahill L. Anxiety in children and adolescents with autism spectrum disorders. Clin Psychol Rev 2009; 29:216±229. 42. Matson JL, Hess JA, Boisjoli JA. Comorbid psychopathology in infants and toddlers with autism and pervasive developmental disorders-not otherwise specified (PDDNOS). Res Autism Spectr Disord 2010; 4:300±304. 43. Howlin P. Evaluating psychological treatments for children with autismspectrum disorders. Adv Psychiatr Treat 2010; 16:133±140. Additional references related to this topic can also be found in the Current World Literature section in this issue (pp. 482±483).