Developmental trajectories as autism phenotypes

Early developmental milestone clusters of autistic children based on electronic health records

Autistic children vary in symptoms, co-morbidities, and response to interventions. This study aimed to identify clusters of autistic children with a distinct pattern of attaining early developmental milestones (EDMs). The clustering of 5836 autistic children was based on the attainment of 43 gross motor, fine motor, language, and social developmental milestones during the first 3 years of life as recorded in baby wellness visits. K-means cluster analysis detected four EDM clusters: mild (n = 1686); moderate (n = 1691); severe (n = 2265); and global (n = 194). The most prominent cluster differences were in the language domain. The global cluster showed earlier and greater developmental delay across domains, unique early gross motor delays, and more were born preterm via cesarean section. The severe cluster had poor language development prominently in the second year of life, and later fine motor delays. Moderate cluster had mainly language delays in the third year of life. The mild cluster mostly passed milestones. EDM clusters differed demographically, with higher socioeconomic status in mild cluster and lowest in global cluster. However, the severe cluster had more immigrant and non-Jewish mothers followed by the moderate cluster. The rates of parental concerns and provider developmental referrals were significantly higher in the global, followed by the severe, moderate, and mild EDM clusters. Autistic children's language and motor delay in the first 3 years can be grouped by common magnitude and onset profiles as distinct groups that may link to specific etiologies (like prematurity or genetics) and specific intervention programs. Early autism screening should be tailored to these different developmental profiles.

The Association Between Autism Symptomatology and Adaptive Functioning Over Six Months: Findings from the Pilot Phase of the PARC Study

PURPOSE

In the context of developmental trajectories, the association between adaptive functioning and core autism symptomatology remains unclear. The current study examines the associations of adaptive behavior with autism symptom sub-domains and with different facets of symptom expression.

METHODS

Participants include 36 children with a recent diagnosis of autism (33 males; mean age = 56.4 months; SD = 9 months). Families were recruited in the context of the Pediatric Autism Research Cohort (PARC) project. Parents filled out questionnaires at two time points, six months apart, regarding their child's autism symptoms and adaptive functioning. The longitudinal relationship between adaptive functioning and autism symptoms was investigated using Mixed Linear Model analyses: one assessing the relationship between general symptom levels and adaptive functioning, and another examining the associations between symptom frequency and impact with adaptive functioning. We conducted Pearson correlation tests at both time points to assess the associations between symptom sub-domains and adaptive functioning.

RESULTS

Findings showed that higher autism symptoms associated with lower adaptive behavior skills, and that this association remained stable over time. Autism impact scores did not significantly relate to adaptive skills, as opposed to frequency scores. Associations between adaptive functioning and autism symptom sub-domains strengthened over time.

CONCLUSION

These findings suggest that adaptive functioning is associated with parent-report autism symptomatology, and that this association changes and, on average, becomes stronger over time. Findings may indicate that frequency and impact of symptoms have differential roles in the development of adaptive skills and are worthy of further exploration.

Differences in regional brain structure in toddlers with autism are related to future language outcomes

Language and social symptoms improve with age in some autistic toddlers, but not in others, and such outcome differences are not clearly predictable from clinical scores alone. Here we aim to identify early-age brain alterations in autism that are prognostic of future language ability. Leveraging 372 longitudinal structural MRI scans from 166 autistic toddlers and 109 typical toddlers and controlling for brain size, we find that, compared to typical toddlers, autistic toddlers show differentially larger or thicker temporal and fusiform regions; smaller or thinner inferior frontal lobe and midline structures; larger callosal subregion volume; and smaller cerebellum. Most differences are replicated in an independent cohort of 75 toddlers. These brain alterations improve accuracy for predicting language outcome at 6-month follow-up beyond intake clinical and demographic variables. Temporal, fusiform, and inferior frontal alterations are related to autism symptom severity and cognitive impairments at early intake ages. Among autistic toddlers, brain alterations in social, language and face processing areas enhance the prediction of the child's future language ability.

Profiles of minimally verbal autistic children: Illuminating the neglected end of the spectrum

Heterogeneity among individuals on the autism spectrum is widely acknowledged as a barrier to develop effective interventions. Overcoming this challenge requires characterization of individual differences, especially for children that are minimally verbal and often excluded from research studies. Most studies that describe autistic subgroups identify a single minimally verbal verbal group based on a single identifying measure (e.g., ADOS module one or single item indicating absence of phrase speech). Determining personalized courses of intervention requires a more detailed understanding since a single intervention will not be effective for all who are minimally verbal. The present study identified comprehensive profiles of cognitive, language, and social communication skills within a large, diverse, group of minimally verbal children with autism. The analysis combined baseline data from two studies to yield a sample of 344 participants, who were 3 to 8 years old at the time of study onset, with 60% who identified as having a race/ethnicity other than White. Via latent profile analysis (LPA), a three-group model was identified as best fit to the data. Profile identification was dependent on a participant's combination of cognitive, expressive, and social communication characteristics, rather than a single domain. One group (n = 206) had global delays, while the other two groups (n = 95 and n = 43) had variable strengths in cognition and communication. Findings suggest that low-frequency/minimally verbal communicators with autism have heterogeneous characteristics that can be systematically organized.

Trajectories of adaptive functioning from early childhood to adolescence in autism: Identifying turning points and key correlates of chronogeneity

Background

Previous research has demonstrated heterogeneous adaptive outcomes across the autism spectrum; however, the current literature remains limited in elucidating turning points and associated factors for longitudinal variability (chronogeneity). To address these empirical gaps, we aimed to provide a finer-grained characterization of trajectories of adaptive functioning from early childhood to adolescence in autism.

Methods

Our sample (N = 406) was drawn from an inception cohort of children diagnosed Autistic at ages 2-5. Adaptive functioning was assessed with Vineland Adaptive Behavior Scales (VABS, 2nd Edition) across 6 visits from the time of diagnosis by age 18. Parallel-process latent growth curve modeling were used to estimate domain-level VABS trajectories, followed by latent class growth analysis to identify trajectory subgroups. Child characteristics at diagnosis, family demographics, and participation outcomes at adolescence were compared across subgroups.

Results

Piecewise latent growth models best described VABS trajectories with two turning points identified at around ages 5-6 and 9-10, respectively reflecting transitions into school age and early adolescence. We parsed four VABS trajectory subgroups that vary by level of functioning and change rate for certain domains and periods. Around 16% of the sample exhibited overall adequate functioning (standard score >85) with notable early growth and social adaptation during adolescence. About 21% showed low adaptive functioning (standard score ≤70), with decreasing slopes by age 6 followed by improvements in communication and daily-living skills by age 10. The other two subgroups (63% in total) were characterized by adaptive functioning between low and adequate levels, with relatively stable trajectories entering school age. These subgroups differed most in their cognitive ability at diagnosis, household income, and social participation in adolescence.

Conclusions

We identified key individual and family characteristics and time windows associated with distinct adaptive functioning trajectories, which have important implications for providing timely and tailored supports to Autistic people across developmental stages.

Evaluation of the Psychometric Properties of the Social Communication Questionnaire in Rural Kenya

Children can be reliably diagnosed with autism as early as 3 years of age, and early interventions are initiated. There is often a significant gap between the age of onset of symptoms (2-3 years) and diagnosis (8-10 years) in Africa. We conducted a study to validate the Social Communication Questionnaire (SCQ) as a screening instrument in a rural setting in Kenya. The study was conducted along the Kenyan Coast. Study participants included 172 children with a neurodevelopmental disorder (NDD) diagnosis (84 of which were autism) and 112 controls. Internal consistency was evaluated through the use of Cronbach's alpha, confirmatory factor analysis (CFA) with maximum likelihood procedure to assess the conceptual model for the SCQ. Additionally, the sensitivity and specificity of cut-off scores using ROC analysis and item difficulties and discrimination quality using an IRT framework were also assessed. Factor analysis revealed an adequate fitting model for the three-factor DSM-IV-TR (root mean squared error of approximation (RMSEA) = 0.050; Comparative Fit Index (CFI) = 0.974; Tucker-Lewis Index (TLI) = 0.973) and two-factor DSM-5 factor structure (RMSEA = 0.050; CFI = 0.972; TLI = 0.974). The reliability coefficient alphas for the whole group for all items (Cronbach's α = 0.90) and all three domains (Cronbach's α = 0.68-0.84) were acceptable to excellent. The recommended cut-off score of 15 yielded 72% sensitivity and 100% specificity in the ASD group compared to the typically developing group. We provide early evidence of the adequate factor structure and good internal consistency of the SCQ. We also note that the recommended cut-off yielded sufficient predictive validity.

Interleukin-23 levels in umbilical cord blood are associated with neurodevelopmental trajectories in infancy

Our previous study, which aimed to understand the early neurodevelopmental trajectories of children with and without neurodevelopmental disorders, identified five classes of early neurodevelopmental trajectories, categorized as high normal, normal, low normal, delayed, and markedly delayed. This investigation involved measurement using the Mullen Scale of Early Learning in a representative sample of Japanese infants followed up from the age of 0 to 2 years (Nishimura et al., 2016). In the present study, we investigated the potential association between cytokine concentrations in umbilical cord serum with any of the five classes of neurodevelopmental trajectories previously assigned, as follows: high normal (N = 85, 13.0%), normal (N = 322, 49.1%), low normal (N = 137, 20.9%), delayed (N = 87, 13.3%), and markedly delayed (N = 25, 3.8%) in infancy. Decreased interleukin (IL)-23 levels in the cord blood were associated with the markedly delayed class, independent of potential confounders (odds ratio, 0.44; 95%confidence interval: 0.26-0.73). Furthermore, IL-23 levels decreased as the developmental trajectory became more delayed, demonstrating that IL-23 plays an important role in development, and is useful for predicting the developmental trajectory at birth.

Promoting emotional and behavioral interventions in ASD treatment: Evidence from EPIGRAM, A naturalistic, prospective and longitudinal study

BACKGROUND

Prognostic factors from naturalistic treatment studies of children with Autism Spectrum Disorder (ASD) remain largely unknown. We aimed to identify baseline and treatment-related prognostic predictors at 1-year follow-up after Integrative Care Practices (ICPs).

METHODS

Eighty-nine preschool children with severe ASD were given ICP combining nine therapeutic workshops based on children's needs. Participants were assessed at baseline and during 12 months follow-up with the Psycho-educational Profile-3-R, Children Autism Rating Scale, Parental Global Impression, and the Autistic Behaviors Scale. We assessed prognostic predictors using multivariable regression models and explored treatment ingredients influencing outcome using Classification and Regression Trees (CART).

RESULTS

Multivariable models showed that being a child from first generation immigrant parents predicted increased maladaptive behaviors, whereas play activities had an opposite effect; severity of ASD symptoms and impaired cognitive functions predicted worse autism severity at follow-up; and lower play activities predicted worse parent impression. Regarding treatment effects, more emotion/behavioral interventions predicted better outcomes, and more communication interventions predicted lower autism severity, whereas more education and cognitive interventions had an opposite effect. CART confirmed that more hours of intervention in the emotion/behavioral domain helped classifying cases with better outcomes. More parental support was associated with decreased maladaptive behaviors. Sensorimotor and education interventions also significantly contributed to classifying cases according to outcomes but defined subgroups with opposite prognosis.

CONCLUSION

Children who exhibited the best prognosis following ICPs had less autism severity, better cognition, and non-immigrant parents at baseline. Emotion/behavior interventions appeared key across all outcomes and should be promoted.

Intellectual development in young children with autism spectrum disorders: A longitudinal study

Intelligence profiles in autism have been characterized by great variability. The questions of how autistic children's intelligence changes over time, and what factors influence these changes deserve study as part of efforts to document child autism profiles, but also because the relationship between intellectual functioning and children's background characteristics is poorly understood, particularly in a longitudinal context. A total of 39 autistic children and 39 age-matched neurotypical children (5-9 years old) completed two IQ assessments at preschool age and up to 4 years later. Repeated-measures analyses assessed longitudinal changes in the children's verbal (VIQ), performance (PIQ), and full-scale IQ (FSIQ) at group level. We further sought to identify clusters with distinct profiles in each group by adopting an unsupervised K-means clustering approach, and detect possible between-subgroup differences in terms of children's socioeconomic status and autism severity. The largest cluster in the autistic group was composed of children whose PIQ significantly dropped at follow-up, while the second largest cluster improved in all quotients; the smallest cluster, wherein children had more highly educated mothers than the rest of the clusters, was characterized by large improvement in VIQ. For the neurotypical children, there was a two-cluster division; the majority of them improved in the three quotients, while very few dropped in PIQ at follow-up. The relation between socioeconomic status and IQ changes was significant for both groups. The findings demonstrate both the complexity of intelligence changes in autism and the need to view this complexity through the lens of the children's socioeconomic diversity.

Trajectory research in children with an autism diagnosis: A scoping review

LAY ABSTRACT

The types of outcomes studied in children on the autism spectrum include clinical characteristics, such as social functioning, communication, language, or autism symptoms. Research that measures these outcomes at multiple timepoints is useful to improve our understanding of what to expect as children develop. In trajectory studies, researchers assess outcomes at three or more timepoints. This method has advantages over two-timepoint studies because it allows researchers to describe changes in the speed of development, such as accelerations, plateaus, or slowdowns. We identified and reviewed 103 published trajectory studies in children (to age 18 years) with an autism diagnosis. Importantly, we did not include studies of treatments or their effects, nor did we summarize the results of studies. Instead, this review summarizes the characteristics of the available published research, including the methods used, the many different outcomes that have been studied over time and the ages over which they have been studied. This summary may be of interest to autistic people and caregivers (parents) who want to know about the existence of research that provides answers about what to expect during an autistic child's development. We have recommended that future trajectory research efforts try to make up for the lack of studies from low- and middle-income countries; that more attention is given to the following outcomes that are meaningful to caregivers and autistic people; and to try to fill in the age gaps where more outcome-specific data are needed.

Impact of the Great Recession on Adults With Autism and Their Mothers

Autistic individuals and their families are at risk for poor outcomes in employment and mental health and may be vulnerable to long-term effects of broader societal conditions. The aim of the current longitudinal study was to understand the impact of the Great Recession of 2007-2009 on autistic individuals and their mothers (N = 392). Hierarchical linear modeling (HLM) results indicated that problem behavior of autistic adults increased in the years following the recession. The rate at which autistic individuals moved away and lived separately from their mothers also slowed during the recession. Mothers experienced significantly higher levels of depressive symptoms postrecession, compared to prerecession. In many other respects, the autistic individuals and their mothers did not experience negative outcomes, suggesting resilience and a strong safety net. These included the physical health and vocational/employment status of the autistic adults and their mothers. Results point to specific areas of vulnerability of autistic individuals and their mothers during the economic downturn, as well as a broad pattern of resilience in these families.

The Developmental Autism Early Screening (DAES): A Novel Test for Screening Autism Spectrum Disorder

This study was undertaken to set a novel developmental screening test for autism spectrum disorder (ASD) using the Griffiths Scales of Child Development (Griffith III) (Green et al., 2016; Stroud et al., 2016), in order to intercept the early atypical developmental patterns indicating ASD risk in the first 3 years of age. An observational and interactive ASD screener, the Developmental Autism Early Screening (DAES), was developed by detecting Griffiths III items differentiating toddlers with ASD risk from those with global developmental delay (DD) or neurotypical development. The DAES was validated with ASD-specific diagnostic instruments (ADOS-2) and the cut-off score based on sensitivity, specificity and positive predictive value that best differentiates between ASD and non-ASD children was identified. We enrolled a total sample of 297 subjects, including children at risk for ASD or DD and neurotypical children. At a cut-off score of 12.5, the DAES had a sensitivity of 93%, specificity of 98.4%, positive predictive value of 96.3% and negative predictive value of 96.9% for identifying children at risk for ASD from non-ASD participants (DD/neurotypical children). The DAES total score correlated significantly with the ADOS-2 calibrated severity scores (CSS) (R = 0.53, p < 0.001). Three ASD risk ranges were identified according to DAES total and ADOS-2 CSS: Little-to-no risk (CSS: 1-3, DAES: 1-7); Mild-to-moderate risk (CSS: 4-5, DAES: 8-14); Moderate-to-severe risk (CSS: 6-10, DAES ≥ 15). The DAES provides a direct approach based on developmental profiles to stratify risk for ASD in early childhood ensuring at risk children the most appropriate diagnostic procedures and targeted intervention.

Autism through midlife: trajectories of symptoms, behavioral functioning, and health

BACKGROUND

This study describes change in autism symptoms, behavioral functioning, and health measured prospectively over 22 years. Most studies tracking developmental trajectories have focused on autism during childhood, although adulthood is the longest stage of the life course. A robust understanding of how autistic people change through midlife and into older age has yet to be obtained.

METHODS

Using an accelerated longitudinal design with 9 waves of data, developmental trajectories were estimated from adolescence through midlife and into early old age in a community-based cohort (n = 406). The overall aim was to determine whether there were age-related increases or decreases, whether the change was linear or curvilinear, and whether these trajectories differed between those who have ID and those who have average or above-average intellectual functioning. Subsequently, the slopes of the trajectories were evaluated to determine if they differed depending on age when the study began, with the goal of identifying possible cohort effects.

RESULTS

There were significant trajectories of age-related change for all but one of the measures, although different measures manifested different patterns. Most autism symptoms improved through adulthood, while health worsened. An inverted U-shaped curve best described change for repetitive behavior symptoms, activities of daily living, maladaptive behaviors, and social interaction. For these measures, improved functioning was evident from adolescence until midlife. Then change leveled off, with worsening functioning from later midlife into early older age. Additionally, differences between autistic individuals with and without ID were evident. Although those who have ID had poorer levels of functioning, there were some indications that those without ID had accelerating challenges in their aging years that were not evident in those with ID - increases in medications for physical health problems and worsening repetitive behaviors.

CONCLUSIONS

Meeting the needs of the increasingly large population of autistic adults in midlife and old age requires a nuanced understanding of life course trajectories across the long stretch of adulthood and across multiple domains. Given the heterogeneity of autism, it will be important not to generalize across sub-groups, for example those who are minimally verbal and those who have above-average intellectual functioning.

Why it is so challenging to perform economic evaluations of interventions in autism and what to do about it

Economic evaluation is used to determine the optimal provision of services and programs under budget constraints and to inform public and private payer funding decisions. To maximize value-for-money in the design and delivery of programs and services for persons with autism spectrum disorder (ASD), it's essential to generate high-quality economic evidence to inform budget allocation. There is a paucity however, of economic evaluations of interventions for ASD. This is due in part to challenges in conducting economic evaluations in this population and the lack of guidance on suitable approaches. These challenges are related to the inherent heterogeneity of the autistic population; establishing short- and long-term effectiveness; measurement of costs and the availability of valid instruments for collecting economic data; the appropriateness of outcomes for use in economic evaluation; and achieving statistical power. This commentary addresses a lack of awareness and needed guidance on these issues by discussing the challenges and providing recommendations for how economic evaluations in ASD could be improved to generate high-quality evidence for program funding decision-making.

A convergent structure-function substrate of cognitive imbalances in autism

BACKGROUND

Autism spectrum disorder (ASD) is a common neurodevelopmental diagnosis showing substantial phenotypic heterogeneity. A leading example can be found in verbal and nonverbal cognitive skills, which vary from elevated to impaired compared with neurotypical individuals. Moreover, deficits in verbal profiles often coexist with normal or superior performance in the nonverbal domain.

METHODS

To study brain substrates underlying cognitive imbalance in ASD, we capitalized categorical and dimensional IQ profiling as well as multimodal neuroimaging.

RESULTS

IQ analyses revealed a marked verbal to nonverbal IQ imbalance in ASD across 2 datasets (Dataset-1: 155 ASD, 151 controls; Dataset-2: 270 ASD, 490 controls). Neuroimaging analysis in Dataset-1 revealed a structure-function substrate of cognitive imbalance, characterized by atypical cortical thickening and altered functional integration of language networks alongside sensory and higher cognitive areas.

CONCLUSION

Although verbal and nonverbal intelligence have been considered as specifiers unrelated to autism diagnosis, our results indicate that intelligence disparities are accentuated in ASD and reflected by a consistent structure-function substrate affecting multiple brain networks. Our findings motivate the incorporation of cognitive imbalances in future autism research, which may help to parse the phenotypic heterogeneity and inform intervention-oriented subtyping in ASD.

Does the severity of autism symptoms change over time? A review of the evidence, impacts, and gaps in current knowledge

Studies evaluating change in autism symptom severity across the lifespan have yielded inconsistent results, making it difficult to assess the prevalence of meaningful change in autism symptom severity, and what characterizes it. Better understanding the ways in which autism symptoms change over time is crucial, with important implications for intervention. Synthesizing information across past studies, autism symptom severity change (especially decreases) appears common, though stability of symptoms is also frequent. Symptom severity change is characterized by variability in patterns of change between different individuals (between-person), variability in change within a person's trajectory across time (within-person), and variability in change patterns across symptom domains (i.e., social-communication, restricted/repetitive behaviors). Variability in severity change is likely impacted by differences in person-level characteristics (e.g., sex, IQ, sociodemographic factors) as well as developmental processes across time. Numerous methodological issues may impact our ability to understand how common change in symptom severity is, including varying measurement tools, analytic approaches, and change patterns between symptom domains across time. Potential implications of better understanding and characterizing symptom severity change include incorporation of severity change patterns and predictors of change into research on biomarkers, and consideration of such predictors as moderators or mediators of change in clinical practice.

Language, Social, and Face Regions Are Affected in Toddlers with Autism and Predictive of Language Outcome

Identifying prognostic early brain alterations is crucial for autism spectrum disorder (ASD). Leveraging structural MRI data from 166 ASD and 109 typical developing (TD) toddlers and controlling for brain size, we found that, compared to TD, ASD toddlers showed larger or thicker lateral temporal regions; smaller or thinner frontal lobe and midline structures; larger callosal subregion volume; and smaller cerebellum. Most of these differences were replicated in an independent cohort of 38 ASD and 37 TD toddlers. Moreover, the identified brain alterations were related to ASD symptom severity and cognitive impairments at intake, and, remarkably, they improved the accuracy for predicting later language outcome beyond intake clinical and demographic variables. In summary, brain regions involved in language, social, and face processing were altered in ASD toddlers. These early-age brain alterations may be the result of dysregulation in multiple neural processes and stages and are promising prognostic biomarkers for future language ability.

A genetics-first approach to understanding autism and schizophrenia spectrum disorders: the 22q11.2 deletion syndrome

Recently, increasing numbers of rare pathogenic genetic variants have been identified that are associated with variably elevated risks of a range of neurodevelopmental outcomes, notably including Autism Spectrum Disorders (ASD), Schizophrenia Spectrum Disorders (SSD), and Intellectual Disability (ID). This review is organized along three main questions: First, how can we unify the exclusively descriptive basis of our current psychiatric diagnostic classification system with the recognition of an identifiable, highly penetrant genetic risk factor in an increasing proportion of patients with ASD or SSD? Second, what can be learned from studies of individuals with ASD or SSD who share a common genetic basis? And third, what accounts for the observed variable penetrance and pleiotropy of neuropsychiatric phenotypes in individuals with the same pathogenic variant? In this review, we focus on findings of clinical and preclinical studies of the 22q11.2 deletion syndrome (22q11DS). This particular variant is not only one of the most common among the increasing list of known rare pathogenic variants, but also one that benefits from a relatively long research history. Consequently, 22q11DS is an appealing model as it allows us to: (1) elucidate specific genotype-phenotype associations, (2) prospectively study behaviorally defined classifications, such as ASD or SSD, in the context of a known, well-characterized genetic basis, and (3) elucidate mechanisms underpinning variable penetrance and pleiotropy, phenomena with far-reaching ramifications for research and clinical practice. We discuss how findings from animal and in vitro studies relate to observations in human studies and can help elucidate factors, including genetic, environmental, and stochastic, that impact the expression of neuropsychiatric phenotypes in 22q11DS, and how this may inform mechanisms underlying neurodevelopmental expression in the general population. We conclude with research priorities for the field, which may pave the way for novel therapeutics.

Continuity of trajectories of autism symptom severity from infancy to childhood

BACKGROUND

Behavioral symptom trajectories are informative of the development of young children at increased likelihood for autism spectrum disorder (ASD).

METHODS

Developmental trajectories of early signs were examined in a cohort of siblings of children diagnosed with ASD (n = 502) from 6 to 18 months using the Autism Observation Scale for Infants (AOSI), and from 18 months to 5-7 years using the Autism Diagnostic Observation Schedule (ADOS). Diagnostic outcomes for ASD at age 3 confirmed diagnosis for 137 children. We further analyzed the conditional probability of a switch from a trajectory measured with the AOSI to a trajectory measured with the ADOS as well as predictors from age 6 months.

RESULTS

We derived three early trajectories of behavioral signs ("Low," "Intermediate," and "Increasing") from 6 to 18 months using the AOSI. We then derived three similar, distinct trajectories for the evolution of symptom severity between 18 and 60-84 months of age (Low, Intermediate, Increasing) using the ADOS. Globally, the Low trajectory included children showing fewer ASD signs or symptoms and the Increasing trajectory included children showing more severe symptoms. We also found that most children in the Low AOSI trajectory stayed in the corresponding ADOS trajectory, whereas children in an Increasing AOSI trajectory tended to transition to an Intermediate or Increasing ADOS trajectory. Developmental measures taken at 6 months (early signs of ASD, Fine Motor, and Visual Reception skills) were predictive of trajectory membership.

CONCLUSIONS

Results confirm substantial heterogeneity in the early emergence of ASD signs in children at increased likelihood for ASD. Moreover, we showed that the way those early behavioral signs emerge in infants is predictive of later symptomatology. Results yield clear clinical implications, supporting the need to repeatedly assess infants at increased likelihood for ASD as this can be highly indicative of their later development and behavior.

Disentangling global and domain-level adaptive behavior trajectories among children with autism spectrum disorder

BACKGROUND

Heterogeneity in adaptive behavior abilities among people with autism spectrum disorder (ASD) is expressed not only as uneven levels of impairment across domains, but also in the developmental trajectories of adaptive skills. We studied the question of whether, after accounting for global adaptive behavior development, we find evidence of heterogeneity in the trajectories of specific domains of adaptive behavior.

METHODS

A sample of 504 children with ASD was obtained by combining data from two independent natural history studies conducted in North America. We used a factor of curves model to explain growth between 36 and 138 months in Vineland Adaptive Behavior Scales, Second Edition (VABS) age equivalents as a function of domain-specific and global growth processes.

RESULTS

The domain-specific trajectories in all three domains (Communication, Daily Living Skills, and Socialization) reflected impairment relative to age expectations as well as slower-than-expected growth with age, and the parameters of these trajectories were moderately-to-strongly correlated across domains. The global adaptive behavior trajectory had an initial (36-41 months of age) developmental level of about 22 age-equivalent months, and eventually slowed after initially increasing by about 6 months each year. The global trajectory accounted for the majority of variance in the domain-level processes; however, additional variance remained (14%-38%) in the domain-level intercepts, slopes, and quadratic processes.

CONCLUSIONS

These results extend existing theoretical and empirical support for the hierarchical structure of adaptive behavior to include its development over time in clinical samples of children with ASD. A latent global trajectory may be sufficient to describe the growth of adaptive behavior in children with ASD; however, the remaining domain-specific variability after accounting for global adaptive behavior development allows for the possibility that differential effects of intervention on specific domains may be possible and detectable.

Brain white matter microstructure abnormalities in children with optimal outcome from autism: a four-year follow-up study

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder, with only a small proportion of people obtaining optimal outcomes. We do not know if children with ASD exhibit abnormalities in the white matter (WM) microstructure or if this pattern would predict ASD prognosis in a longitudinal study. 182 children with ASD were recruited for MRI and clinical assessment; 111 completed a four-year follow-up visit (30 with optimal outcomes, ASD-; 81 with persistent diagnosis, ASD+). Additionally, 72 typically developing controls (TDC) were recruited. The microstructural integrity of WM fiber tracts was revealed using tract-based spatial statistics (TBSS) and probabilistic tractography analyses. We examined the neuroimaging abnormality associated with ASD and its relationship to ASD with optimal outcome. The ASD+ and TDC groups were propensity score matched to the ASD- group in terms of age, gender, and IQ. TBSS indicated that children with ASD exhibited abnormalities in the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), and extending to the anterior thalamic radiation (ATR) and cingulum; whereas the ASD+ group showed more severe abnormalities than the ASD- group. Probabilistic tractography analysis revealed that ASD+ group exhibited lower Fractional Anisotropy (FA) of the left superior thalamic radiation (STR L) than ASD- group, and that FA value of the STR L was a significant predictor of optimal outcome (EX(B), 6.25; 95% CI 2.50-15.63; p < 0.001). Children with ASD showed significant variations in SLF_L and STR_L, and STR_L was a predictor of 'ASD with optimal outcome'. Our findings may aid in comprehension of the mechanisms of 'ASD with optimal outcome'.

Longitudinal Stability of Intellectual Functioning in Autism Spectrum Disorder: From Age 3 Through Mid-adulthood

Intelligence (IQ) scores are used in educational and vocational planning for individuals with autism spectrum disorder (ASD) yet little is known about the stability of IQ throughout development. We examined longitudinal age-related IQ stability in 119 individuals with ASD (3-36 years of age at first visit) and 128 typically developing controls. Intelligence measures were collected over a 20-year period. In ASD, Full Scale (FSIQ) and Verbal (VIQ) Intelligence started lower in childhood and increased at a greater rate with age relative to the control group. By early adulthood, VIQ and working memory stabilized, whereas nonverbal and perceptual scores continued to change. Our results suggest that in individuals with ASD, IQ estimates may be dynamic in childhood and young adulthood.

Machine learning for autism spectrum disorder diagnosis using structural magnetic resonance imaging: Promising but challenging

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects approximately 1% of the population and causes significant burdens. ASD's pathogenesis remains elusive; hence, diagnosis is based on a constellation of behaviors. Structural magnetic resonance imaging (sMRI) studies have shown several abnormalities in volumetric and geometric features of the autistic brain. However, inconsistent findings prevented most contributions from being translated into clinical practice. Establishing reliable biomarkers for ASD using sMRI is crucial for the correct diagnosis and treatment. In recent years, machine learning (ML) and specifically deep learning (DL) have quickly extended to almost every sector, notably in disease diagnosis. Thus, this has led to a shift and improvement in ASD diagnostic methods, fulfilling most clinical diagnostic requirements. However, ASD discovery remains difficult. This review examines the ML-based ASD diagnosis literature over the past 5 years. A literature-based taxonomy of the research landscape has been mapped, and the major aspects of this topic have been covered. First, we provide an overview of ML's general classification pipeline and the features of sMRI. Next, representative studies are highlighted and discussed in detail with respect to methods, and biomarkers. Finally, we highlight many common challenges and make recommendations for future directions. In short, the limited sample size was the main obstacle; Thus, comprehensive data sets and rigorous methods are necessary to check the generalizability of the results. ML technologies are expected to advance significantly in the coming years, contributing to the diagnosis of ASD and helping clinicians soon.

Intensive behavioural interventions based on applied behaviour analysis (ABA) for young children with autism: A cost-effectiveness analysis

Background

The economic and social costs of autism are significant. This study evaluates the cost-effectiveness of early intensive Applied Behaviour Analysis (ABA)-based interventions for autistic pre-school children in the UK.

Methods

A de novo economic analysis was developed in Microsoft Excel comparing early intensive ABA-based interventions compared with treatment as usual (TAU). The analysis used 15.5-year time horizon, with costs and benefits discounted a 3.5%. The model structure was based on cohort structure to capture changes in adaptive behaviour and cognitive ability over time. The analysis was informed by an individual patient data (IPD) meta-analysis of available evidence.

Results

Adopting a public sector perspective, early intensive ABA-based therapies were associated with greater incremental costs and greater benefits. When pessimistic assumptions were made regarding the long-term effects of treatment incremental costs were £46,103 and incremental quality-adjusted life years (QALYs) were 0.24, resulting in an incremental cost-effectiveness ratio (ICER) of £189,122 per quality-adjusted life year (QALY). When optimistic assumptions were made about long-term effects, incremental costs were £39,233 with incremental benefits of 0.84 QALYs. The resulting ICER was £46,768 per QALY. Scenario analyses emphasised the importance of assumptions made regarding adult outcomes and type of school attended, both of which significantly affect the results of the analysis.

Conclusions

The results of this economic analysis suggest that early intensive ABA-based interventions are unlikely to represent value for money, based on a £20,000 to £30,000 per QALY threshold typically adopted to inform UK healthcare funding decisions. However, important gaps in the available evidence, limit the strength of the conclusions that can be drawn from the presented analysis. Further research, focusing on the trajectory of autistic children following intervention is likely to be highly beneficial to resolving some of these uncertainties.

Epigenetic profiling of social communication trajectories and co-occurring mental health problems: a prospective, methylome-wide association study

While previous studies suggest that both genetic and environmental factors play an important role in the development of autism-related traits, little is known about potential biological mechanisms underlying these associations. Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC), we examined prospective associations between DNA methylation (DNAm: n_birth = 804, n_{age 7} = 877) and trajectories of social communication deficits at age 8-17 years. Methylomic variation at three loci across the genome (false discovery rate = 0.048) differentiated children following high (n = 80) versus low (n = 724) trajectories of social communication deficits. This differential DNAm was specific to the neonatal period and not observed at 7 years of age. Associations between DNAm and trajectory membership remained robust after controlling for co-occurring mental health problems (i.e., hyperactivity/inattention, conduct problems). The three loci identified at birth were not replicated in the Generation R Study. However, to the best of our knowledge, ALSPAC is the only study to date that is prospective enough to examine DNAm in relation to longitudinal trajectories of social communication deficits from childhood to adolescence. Although the present findings might point to potentially novel sites that differentiate between a high versus low trajectory of social communication deficits, the results should be considered tentative until further replicated.

Sensory processing and adaptive behavior in Phelan-McDermid syndrome: a cross-sectional study

Phelan-McDermid syndrome (PMS) is a genetic disorder caused by a mutation or deletion of the SHANK3 gene (chromosome 22q13.3), characterized by different sensory processing anomalies. The objective of this study is to expand and provide a detailed definition of the sensory profile of patients with PMS. The secondary objective was to examine the relationship between sensory patterns and adaptive behavior. A cross-sectional study was carried out among 51 Spanish patients with a confirmed genetic diagnosis of PMS. All the participants' parents completed the Short Sensory Profile-Spanish (SSP-S) and the Adaptive Behavior Assessment System II (ABAS-II). Correlational, multiple regression and hierarchical cluster analyses were performed. An atypical sensory profile was identified in almost 75% of PMS patients. Definite differences were found among scores; nonetheless, sub-threshold values were observed in tactile sensitivity, underresponsive/seeks sensation, auditory filtering, and low energy/weak sensory categories. Conceptual, social, and practical domains, as well as the General Adaptive Composite (GAC) of the ABAS-II showed extremely low scores (i.e., <70). Significant correlations were found (p<0.005) between SSP-S scores and the conceptual, social, practical, and GAC index of the ABAS-II, whereby higher SSP-S scores were associated with better skills and higher adaptive performance. The cluster analysis indicated that the group with the largest mutation size (7.23 Mb) showed the greatest sensory processing difficulties and very low adaptive skills.

CONCLUSIONS

Patients with PMS show an atypical sensory profile, which correlates with limitations in general adaptive behaviors.

WHAT IS KNOWN

• PMS sensory processing difficulties were associated with a pattern of underresponsive/seeks sensation, low energy/weak, and tactile hyporeactivity. • Sensory processing difficulties have been associated with limitations in the development of appropriate adaptive communication and interaction behaviors.

WHAT IS NEW

• Sensory definite differences associated with tactile hyperreactivity, as well as significant effects of underresponsiveness/seeks sensation and auditory filtering categories on the adaptive abilities were found in SHANK3deletion patients. • Cluster analysis suggests that smaller mutation sizes were related to better sensory processing and higher adaptive skills, while patients with larger deletion sizes have greater adaptive difficulties and worse sensory processing skills.

Sex- and age-related differences in autistic behaviours in children with neurofibromatosis type 1

This study investigated sex and age differences in autistic behaviours in children with neurofibromatosis type 1 (NF1) who scored within the clinical range on the Social Responsiveness Scale - Second Edition (T score ≥ 60). Thirty-four males and 28 females (3-16 years) were assessed with the Autism Diagnostic Observation Schedule - Second Edition and Autism Diagnostic Interview - Revised. Across both measures, males exhibited greater social communication deficits relative to females. Age-related abatement of social communication difficulties was observed for males but not females. Conversely, no sex differences were found for restricted/repetitive behaviours, which were stable over time for both males and females. The findings are discussed within the context of broader neurodevelopmental considerations that are common in NF1.

Relations of Restricted and Repetitive Behaviors to Social Skills in Toddlers with Autism

We examined the relations of restricted and repetitive behaviors (RRB; insistence on sameness, repetitive sensory-motor, self-injurious behavior) to social skills overall and aspects that comprise social skills as measured by the VABS-II (coping skills, play/leisure time, interpersonal relationships) in 24- (n = 63) and 36-month old (n = 35), high-familial-risk toddlers with ASD. Hierarchical linear regression results indicated that repetitive sensory-motor was the best predictor of social skills overall. Secondary results indicated that all three RRB subtypes were associated with each subdomain of social skills; however, repetitive sensory-motor was the strongest and most consistent among these effects. While our results suggests a general negative relation of subtypes of RRB to aspects of adaptive social function, repetitive sensory-motor behaviors may be of particular relevance to the development of social skills during toddlerhood.

Population heterogeneity in clinical cohorts affects the predictive accuracy of brain imaging

Brain imaging research enjoys increasing adoption of supervised machine learning for single-participant disease classification. Yet, the success of these algorithms likely depends on population diversity, including demographic differences and other factors that may be outside of primary scientific interest. Here, we capitalize on propensity scores as a composite confound index to quantify diversity due to major sources of population variation. We delineate the impact of population heterogeneity on the predictive accuracy and pattern stability in 2 separate clinical cohorts: the Autism Brain Imaging Data Exchange (ABIDE, n = 297) and the Healthy Brain Network (HBN, n = 551). Across various analysis scenarios, our results uncover the extent to which cross-validated prediction performances are interlocked with diversity. The instability of extracted brain patterns attributable to diversity is located preferentially in regions part of the default mode network. Collectively, our findings highlight the limitations of prevailing deconfounding practices in mitigating the full consequences of population diversity.

Interindividual Differences in Cortical Thickness and Their Genomic Underpinnings in Autism Spectrum Disorder

OBJECTIVE

Autism spectrum disorder (ASD) is accompanied by highly individualized neuroanatomical deviations that potentially map onto distinct genotypes and clinical phenotypes. This study aimed to link differences in brain anatomy to specific biological pathways to pave the way toward targeted therapeutic interventions.

METHODS

The authors examined neurodevelopmental differences in cortical thickness and their genomic underpinnings in a large and clinically diverse sample of 360 individuals with ASD and 279 typically developing control subjects (ages 6-30 years) within the EU-AIMS Longitudinal European Autism Project (LEAP). The authors also examined neurodevelopmental differences and their potential pathophysiological mechanisms between clinical ASD subgroups that differed in the severity and pattern of sensory features.

RESULTS

In addition to significant between-group differences in "core" ASD brain regions (i.e., fronto-temporal and cingulate regions), individuals with ASD manifested as neuroanatomical outliers within the neurotypical cortical thickness range in a wider neural system, which was enriched for genes known to be implicated in ASD on the genetic and/or transcriptomic level. Within these regions, the individuals' total (i.e., accumulated) degree of neuroanatomical atypicality was significantly correlated with higher polygenic scores for ASD and other psychiatric conditions, and it scaled with measures of symptom severity. Differences in cortical thickness deviations were also associated with distinct sensory subgroups, especially in brain regions expressing genes involved in excitatory rather than inhibitory neurotransmission.

CONCLUSIONS

The study findings corroborate the link between macroscopic differences in brain anatomy and the molecular mechanisms underpinning heterogeneity in ASD, and provide future targets for stratification and subtyping.

Diagnostic Stability and Phenotypic Differences Among School-Age Children Diagnosed With ASD Before Age 2

Given the importance of early detection, it is critical to understand the non-linearity in manifestation of ASD before age 24 months, when ASD symptoms are beginning to consolidate, through the age of 36 months when stability of ASD diagnosis is reportedly high into school-age when increased demands may challenge previously successful compensatory processes and permit first ASD detection. We employed a prospective, longitudinal design focused on children with an older sibling with ASD (n = 210) who received diagnostic evaluations at mean ages of 15.4 months (Time 1), 36.6 months (Time 2), and 5.7 years (Time 3) to examine: (1) diagnostic stability, (2) developmental trajectories associated with different patterns of ASD vs. non-ASD classifications, and (3) predictors of classification group over time. Clinical best estimate (CBE) diagnosis of ASD or non-ASD was made at each time point. Linear mixed-effects models were implemented to examine differences in developmental trajectories of stable and dynamic diagnostic groups. Multinomial logistic regression analyses were used to examine predictors of the likelihood of belonging to each CBE diagnostic classification group. Results revealed that sensitivity and stability of an ASD diagnosis significantly increased from Time 1 (sensitivity: 52%; stability: 63%) to Time 2 (sensitivity: 86%; stability: 68%). Different developmental trajectories of autism symptom severity and non-verbal and verbal IQ were observed across groups, with differences first observed at Time 1 and becoming more pronounced through Time 3. Presence of restricted and repetitive behaviors as well as limitations in initiation of joint attention and expressive language skills differentially predicted the likelihood of belonging to the different CBE diagnostic classification groups. Results suggest that ASD symptoms may emerge or attenuate over time, with some children meeting diagnosis at follow-up, and other children no longer meeting diagnostic criteria. From a systems perspective, diagnostic non-linearity may be viewed as a dynamic developmental process, where emergent properties arising from various biological, genetic, and experiential factors interact, culminating in phenotypic phenomena that change over time. Clinical implications include extending universal ASD and social communication screening into school-age, supporting families' understanding of diagnostic shifts, and ensuring unbiased diagnostic decision-making when following children with ASD.

Adults with Autism: Changes in Understanding Since DSM-111

Over the past four decades there have been significant advances in our understanding of autism, yet services for autistic adults continue to lag far behind those for children, and prospects for employment and independent living remain poor. Adult outcomes also vary widely and while cognitive and language abilities are important prognostic indicators, the influence of social, emotional, familial and many other factors remains uncertain. For this special issue marking the 40th anniversary of DSM-III, the present paper describes the changing perspectives of autism in adulthood that have occurred over this period, explores individual and wider environmental factors related to outcome, and suggests ways in which services need to be changed to improve the future for adults living with autism.

Can stratification biomarkers address the heterogeneity of autism spectrum disorder?

The search for biomarkers for autism spectrum disorder (henceforth autism) has received a lot of attention due to their potential clinical relevance. The clinical and aetiological heterogeneity of autism suggests the presence of subgroups. The lack of identification of a valid diagnostic biomarker for autism, and the inconsistencies seen in studies assessing differences between autism and typically developing control groups, may be partially explained by the vast heterogeneity observed in autism. The focus now is to better understand the clinical and biological heterogeneity and identify stratification biomarkers, which are measures that describe subgroups of individuals with shared biology. Using stratification approaches to assess treatment within pre-defined subgroups could clarify who may benefit from different treatments and therapies, and ultimately lead to more effective individualised treatment plans.

Autism spectrum disorder in older adults with intellectual disability: a scoping review

INTRODUCTION

Ireland has an ageing population of persons with intellectual disability (ID), autism spectrum disorder (ASD) and both (ID/ASD). Despite this, little is known about the prevalence of ASD and its effect on functional outcomes, psychiatric comorbidity or diagnostic issues in an older population with ID. This article reviews the literature on older adults with ID/ASD and identifies opportunities for future research in this population.

METHOD

The authors searched the Medline, Pubmed, Embase, CINAHL and PsychInfo databases using the search terms using key words: (older adults) AND (ID OR mental retardation OR learning disability) AND (autism OR ASD). After excluding articles for relevance, a scoping review was carried out on the results retrieved.

RESULTS

Of the 1227 articles retrieved from the literature on ID and autism/ASD in older adults, 85 articles were relevant to an adult population with ID/ASD. The data were collated and are presented covering domains of diagnosis, prevalence, psychiatric comorbidities and functional outcomes.

CONCLUSIONS

Despite increased prevalence in childhood ASD in the last 20 years, there is a lack of research regarding adults, especially older adults, with ASD, up to half of whom will have some level of ID. The existing literature suggests that older adults with ID/ASD may have reduced functional independence, increased psychiatric comorbidity and psychotropic prescribing and more behavioural presentations than the older population generally or those with ID only. There is a need for longitudinal data to be collected on this ageing population so that care and management needs can be met in the future.

Age of walking and intellectual ability in autism spectrum disorder and other neurodevelopmental disorders: a population-based study

BACKGROUND

Delayed walking is common in intellectual disability (ID) but may be less common when ID occurs with autism spectrum disorder (ASD). Previous studies examining this were limited by reliance on clinical samples and exclusion of children with severe motor deficits.

OBJECTIVE

To examine in a population-based sample if age of walking is differentially related to intellectual ability in children with ASD versus other neurodevelopmental disorders (NDD).

METHODS

Participants were from the nested Autism Birth Cohort Study of the Norwegian Mother, Father and Child Cohort Study (MoBa). Cox proportional hazards regression assessed if diagnosis (ASD n = 212 vs. NDD n = 354), continuous nonverbal IQ, and their interaction, were associated with continuous age of walking.

RESULTS

The relationship between nonverbal IQ and age of walking was stronger for NDD than for ASD (Group × nonverbal IQ interaction, χ²  = 13.93, p = .0002). This interaction was characterized by a 21% decrease in the likelihood of walking onset at any given time during the observation period per 10-point decrease in nonverbal IQ (hazard ratio = 0.79, 95% CI: 0.78-0.85) in the NDD group compared to 8% (hazard ratio = 0.92, 95% CI: 0.86-0.98) in the ASD group.

CONCLUSIONS

The finding that age of walking is less strongly related to low intellectual ability in children with ASD than in children without other NDDs supports the hypothesis that ID in ASD may result from heterogeneous developmental pathways. Late walking may be a useful stratification variable in etiological research focused on ASD and other NDDs.

Patterns of Continuity and Change in the Psychosocial Outcomes of Young Autistic People: a Mixed-Methods Study

Long-term longitudinal studies have consistently demonstrated that the outcomes of autistic individuals are highly variable. Yet, these studies have typically focused on aspects of functioning deemed to be critical by non-autistic researchers, rather than autistic people themselves. Here, we uniquely examined the long-term psychosocial outcomes of a group of young autistic people (n = 27; M age = 17 years; 10 months; 2 female) followed from childhood using a combination of approaches, including (1) the standard, normative approach, which examined changes in diagnostic outcomes, autistic features and adaptive functioning over a 9-year period and (2) a qualitative approach, which involved semi-structured interviews to understand young people's own subjective experiences of their current functioning. On average, there was no significant change in young people's diagnostic outcomes and autistic features over the 9-year period, although there was much variability at the individual level. There was far less variability, however, in young people's everyday functioning, with marked declines over the same period. While these often-substantial everyday challenges aligned well with young people's subjective reports, there was no straightforward one-to-one mapping between self-reported experiences of being autistic and standard measures of severity. These findings call for concerted efforts to understand autistic outcomes through the mixing of quantitative and qualitative reports and for sustained and targeted interventions during adolescence in those areas that matter most to young people themselves.

A white paper on a neurodevelopmental framework for drug discovery in autism and other neurodevelopmental disorders

In the last decade there has been a revolution in terms of genetic findings in neurodevelopmental disorders (NDDs), with many discoveries critical for understanding their aetiology and pathophysiology. Clinical trials in single-gene disorders such as fragile X syndrome highlight the challenges of investigating new drug targets in NDDs. Incorporating a developmental perspective into the process of drug development for NDDs could help to overcome some of the current difficulties in identifying and testing new treatments. This paper provides a summary of the proceedings of the 'New Frontiers Meeting' on neurodevelopmental disorders organised by the European College of Neuropsychopharmacology in conjunction with the Innovative Medicines Initiative-sponsored AIMS-2-TRIALS consortium. It brought together experts in developmental genetics, autism, NDDs, and clinical trials from academia and industry, regulators, patient and family associations, and other stakeholders. The meeting sought to provide a platform for focused communication on scientific insights, challenges, and methodologies that might be applicable to the development of CNS treatments from a neurodevelopmental perspective. Multidisciplinary translational consortia to develop basic and clinical research in parallel could be pivotal to advance knowledge in the field. Although implementation of clinical trials for NDDs in paediatric populations is widely acknowledged as essential, safety concerns should guide each aspect of their design. Industry and academia should join forces to improve knowledge of the biology of brain development, identify the optimal timing of interventions, and translate these findings into new drugs, allowing for the needs of users and families, with support from regulatory agencies.

The Effect of Comorbid Attention-Deficit/Hyperactivity Disorder Symptoms on Face Memory in Children with Autism Spectrum Disorder: Insights from Transdiagnostic Profiles

Face memory impairments are common but heterogeneous in autism spectrum disorder (ASD), which may be influenced by co-occurrence with attention-deficit/hyperactivity disorder (ADHD). Here, we aimed to investigate the phenotype change of face memory in children with ASD comorbid ADHD symptoms, and discuss the potential role of executive function (EF). Ninety-eight children were analyzed in the present study, including ASD- (ASD-only, n = 24), ADHD (n = 23), ASD+ (with ADHD symptoms, n = 23) and neurotypical controls (NTC, n = 28). All participants completed two tests: face encoding and retrieving task and Wisconsin Card Sorting Test (WCST) for measuring face memory and EF, respectively. Results revealed that: compared with the NTC group, children with ASD- exhibited lower accuracy in both face encoding and retrieving, and participants with ASD+ showed lower accuracy only in the retrieving, whereas no differences were found among participants with ADHD. Moreover, in the ASD+ group, face encoding performance was correlated with response perseverative errors (RPE) and failure to maintain sets (FMS) of WCST; significantly, there were no group differences between ASD+ and NTC in these two indices. The transdiagnostic profiles indicated that comorbid ADHD symptoms could modulate the face encoding deficiency of ASD, which may be partially compensated by EF. Shared and distinct intervention strategies to improve social cognition are recommended for children undergoing treatment for each condition.

Brain imaging-based machine learning in autism spectrum disorder: methods and applications

Autism spectrum disorder (ASD) is a neurodevelopmental condition with early childhood onset and high heterogeneity. As the pathogenesis is still elusive, ASD diagnosis is comprised of a constellation of behavioral symptoms. Non-invasive brain imaging techniques, such as magnetic resonance imaging (MRI), provide a valuable objective measurement of the brain. Many efforts have been devoted to developing imaging-based diagnostic tools for ASD based on machine learning (ML) technologies. In this survey, we review recent advances that utilize machine learning approaches to classify individuals with and without ASD. First, we provide a brief overview of neuroimaging-based ASD classification studies, including the analysis of publications and general classification pipeline. Next, representative studies are highlighted and discussed in detail regarding different imaging modalities, methods and sample sizes. Finally, we highlight several common challenges and provide recommendations on future directions. In summary, identifying discriminative biomarkers for ASD diagnosis is challenging, and further establishing more comprehensive datasets and dissecting the individual and group heterogeneity will be critical to achieve better ADS diagnosis performance. Machine learning methods will continue to be developed and are poised to help advance the field in this regard.

Unsupervised Machine Learning for Identifying Challenging Behavior Profiles to Explore Cluster-Based Treatment Efficacy in Children With Autism Spectrum Disorder: Retrospective Data Analysis Study

Background

Challenging behaviors are prevalent among individuals with autism spectrum disorder; however, research exploring the impact of challenging behaviors on treatment response is lacking.

Objective

The purpose of this study was to identify types of autism spectrum disorder based on engagement in different challenging behaviors and evaluate differences in treatment response between groups.

Methods

Retrospective data on challenging behaviors and treatment progress for 854 children with autism spectrum disorder were analyzed. Participants were clustered based on 8 observed challenging behaviors using k means, and multiple linear regression was performed to test interactions between skill mastery and treatment hours, cluster assignment, and gender.

Results

Seven clusters were identified, which demonstrated a single dominant challenging behavior. For some clusters, significant differences in treatment response were found. Specifically, a cluster characterized by low levels of stereotypy was found to have significantly higher levels of skill mastery than clusters characterized by self-injurious behavior and aggression (P<.003).

Conclusions

These findings have implications on the treatment of individuals with autism spectrum disorder. Self-injurious behavior and aggression were prevalent among participants with the worst treatment response, thus interventions targeting these challenging behaviors may be worth prioritizing. Furthermore, the use of unsupervised machine learning models to identify types of autism spectrum disorder shows promise.

Early differences in auditory processing relate to Autism Spectrum Disorder traits in infants with Neurofibromatosis Type I

BACKGROUND

Sensory modulation difficulties are common in children with conditions such as Autism Spectrum Disorder (ASD) and could contribute to other social and non-social symptoms. Positing a causal role for sensory processing differences requires observing atypical sensory reactivity prior to the emergence of other symptoms, which can be achieved through prospective studies.

METHODS

In this longitudinal study, we examined auditory repetition suppression and change detection at 5 and 10 months in infants with and without Neurofibromatosis Type 1 (NF1), a condition associated with higher likelihood of developing ASD.

RESULTS

In typically developing infants, suppression to vowel repetition and enhanced responses to vowel/pitch change decreased with age over posterior regions, becoming more frontally specific; age-related change was diminished in the NF1 group. Whilst both groups detected changes in vowel and pitch, the NF1 group were largely slower to show a differentiated neural response. Auditory responses did not relate to later language, but were related to later ASD traits.

CONCLUSIONS

These findings represent the first demonstration of atypical brain responses to sounds in infants with NF1 and suggest they may relate to the likelihood of later ASD.

Imbalanced social-communicative and restricted repetitive behavior subtypes of autism spectrum disorder exhibit different neural circuitry

Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97-99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.

Bayonet-shaped language development in autism with regression: a retrospective study

Background

Language delay is one of the major referral criteria for an autism evaluation. Once an autism spectrum diagnosis is established, the language prognosis is among the main parental concerns. Early language regression (ELR) is observed by 10–50% of parents but its relevance to late language level and socio-communicative ability is uncertain. This study aimed to establish the predictive value of ELR on the progression of language development and socio-communicative outcomes to guide clinicians in addressing parents’ concerns at the time of diagnosis.

Methods

We used socio-communicative, language, and cognitive data of 2,047 autism spectrum participants from the Simons Simplex Collection, aged 4–18 years (mean = 9 years; SD = 3.6). Cox proportional hazard and logistic regression models were used to evaluate the effect of ELR on language milestones and the probability of using complex and flexible language, as defined by the choice of ADOS module at enrollment. Linear models were then used to evaluate the relationship of ELR and non-verbal IQ with socio-communicative and language levels.

Results

ELR is associated with earlier language milestones but delayed attainment of fluent, complex, and flexible language. However, this language outcome can be expected for almost all autistic children without intellectual disability at 18 years of age. It is mostly influenced by non-verbal IQ, not ELR. The language and socio-communicative level of participants with flexible language, as measured by the Vineland and ADOS socio-communicative subscales, was not affected by ELR.

Limitations

This study is based on a relatively coarse measure of ultimate language level and relies on retrospective reporting of early language milestones and ELR. It does not prospectively document the age at which language catches up, the relationship between ELR and other behavioral areas of regression, nor the effects of intervention.

Conclusions

For autistic individuals with ELR and a normal level of non-verbal intelligence, language development follows a “bayonet shape” trajectory: early first words followed by regression, a plateau with limited progress, and then language catch up.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-021-00444-8.

Needs assessment in unmet healthcare and family support services: A survey of caregivers of children and youth with autism spectrum disorder in Delaware

The study aimed to collect data from families of children and youth with Autism Spectrum Disorder (ASD) in the state of Delaware, USA to understand their ongoing needs and challenges in accessing child healthcare and family support services. We analyzed responses from 263 caregivers of children and youth with ASD from 3 to 24 years using a statewide needs assessment survey. Over 50% caregivers indicated having unmet needs relative to both child/youth healthcare services and family support services. Between 24 and 38% caregivers expressed unmet needs for healthcare services such as social skills training, speech-language therapy, behavioral intervention, and occupational therapy for their child and 20-24% expressed needs for family support services such as respite care, parent/sibling support groups, counseling, and babysitting support. Additionally, number of prior early interventions received, limitations in accessing healthcare services, and unmet needs for family support services significantly predicted child/youth unmet healthcare needs. Greater ASD severity and difficulties accessing child/youth healthcare services predicted participant's functional dependence on caregivers for activities of daily living. Together, these findings call for designing holistic, family-centered interventions that address needs of both children and youth with ASD and their families. LAY SUMMARY: A statewide needs assessment survey of caregivers of children and youth with ASD revealed that 50% responders had unmet needs relative to both child/youth healthcare services and family support services. Number of prior services received, limitations in accessing healthcare, and unmet needs for family support are linked to child/youth unmet healthcare needs. Severity of autism and difficulties accessing child/youth healthcare are associated with participant's functional dependence. Together, these findings call for placing the family at the heart of the service system in ASD.

Which Factors Influence Teacher Report of Adaptive Functioning in Autistic Children?

A wealth of parent-report research shows adaptive functioning difficulties in autistic children, with parent-report influenced by a number of child factors. Adaptive functioning in autistic children is known to vary across settings; however, no research has yet explored factors influencing education professional-report. This study investigated the rate and profile of impairment, and child factors influencing education professional-reported adaptive skills in 248 autistic children. Twelve children were < 3 years (min age for available normative data on the adaptive function measure), so were removed from the analyses. Results replicated parent-literature; adaptive skills were negatively associated with age and informant-reported autism severity, and positively associated with nonverbal ability and expressive language. Adaptive functioning is important for real-world outcomes, e.g. educational attainment, independence, and support needs. Improving our understanding of adaptive functioning in the education context may support opportunities for shared learning and enhance personalised support .

Cognitive, Language, and Behavioral Outcomes in Children With Autism Spectrum Disorders Exposed to Early Comprehensive Treatment Models: A Meta-Analysis and Meta-Regression

Background: Early comprehensive treatment models (CTMs) have been developed as effective treatments for children with autism spectrum disorder (ASD). Numerous studies have suggested that CTMs can improve short-term outcomes, but little is known about precise outcome information in childhood. The current meta-analysis reviewed studies reporting broader outcomes in children with ASD who had ever participated in a CTM and examined the predictors of developmental gains. Methods: We searched eight databases up to June 13, 2019, for relevant trials and natural experiments. Longitudinal studies were selected if they investigated the outcomes of CTMs. Two meta-analyses were undertaken to provide a summary estimate of change in treatment outcomes and to evaluate the effect of CTMs; one used the standardized mean change between the pretest and posttest, and the other was a classical meta-analysis. Stratified and random-effects meta-regression analyses were performed to search for outcome differences among studies. Results: Eighteen intervention studies (involving 495 children with ASD) met all the inclusion criteria: 12 used early intensive behavioral intervention (EIBI), and two used the Early Start Denver Model (ESDM). Outcomes were categorized into three parts: cognitive, language and behavioral (e.g., adaptive functioning and symptomatology). Overall, most children with ASD who had ever participated in an early CTM made gains in many areas of functioning, especially in terms of symptom- and language-related outcomes. Stratified analyses indicated that the ESDM displayed the largest effect on IQ improvement (ES = 1.37, 95% CI: 0.95 to 1.80), while EIBI was more effective for symptom reduction (ES = -1.27, 95% CI: -1.96 to -0.58). Further, meta-regression suggested that interventions with parent involvement, higher intensity, and longer treatment hours yielded greater improvements in IQ and social adaptive functioning, respectively. Conclusion: The results demonstrate a positive association between CTMs and better prognosis in childhood, especially regarding symptoms, and language. However, most extant research involves small, non-randomized studies, preventing definitive conclusions from being drawn. Clearly, the outcomes of children with ASD are still far from normal, especially with respect to adaptive functioning, and the four mediating variables pertaining to treatment elements can affect their gains, including approach, implementer, intensity, and total treatment hours. Systematic Review Registration: [www.crd.york.ac.uk/PROSPERO], identifier [CRD42019146859].

Association between neighbourhood socioeconomic status and developmental vulnerability of kindergarten children with Autism Spectrum Disorder: A population level study

There is limited knowledge about the relationship between neighbourhood socioeconomic status (SES) and development of kindergarten children with ASD. The primary objective of this study was to determine the association between neighbourhood SES and developmental vulnerability of kindergarten children with ASD while controlling for family SES across 10 provinces and territories in Canada. This study used data from a population level database of child development in kindergarten, collected with the Early Development Instrument (EDI). The EDI covers five broad domains of developmental health: physical health and well-being, social competence, emotional maturity, language and cognitive development, and communication skills and general knowledge. Neighbourhood SES was assessed with an SES index created using 10 variables from the 2011 Canadian Census and 2010 Taxfiler data. Family SES was assessed using 4 variables from the 2016 Canadian Census. Descriptive statistics and regression-based models were used in this study. Multilevel binary logistic regression analyses were used to examine the association between neighbourhood SES and child developmental vulnerability (yes/no), at the individual level, while controlling for family SES, demographic characteristics, and neighbourhood clustering. The association between neighbourhood SES and child developmental vulnerability at the individual level, while controlling for family SES and demographic characteristics was examined with binary single level logistic regression analyses. Multivariable linear regression analyses were used to examine the association between neighbourhood SES and developmental vulnerability at the neighbourhood level (% of kindergarten children with ASD demonstrating developmental vulnerability in a neighbourhood). In Ontario, British Columbia, Manitoba, and Newfoundland and Labrador, higher neighbourhood SES was associated with lower likelihood of developmental vulnerability. In Nova Scotia, higher neighbourhood SES was associated with higher likelihood of vulnerability in the social competence and communication skills and general knowledge domains. These findings emphasize the importance of addressing neighbourhood deprivation to support the development of children with ASD. Additionally, the inconsistency highlights the importance of examining the mechanisms through which neighbourhood SES impacts development of these children on a provincial basis.