Trajectories of Symptom Severity in Children with Autism: Variability and Turning Points through the Transition to School.
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ABSTRACT:
SUBMITTER: Georgiades S
PROVIDER: S-EPMC8732828 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveThis study examined variability in autism symptom trajectories in toddlers referred for possible autism spectrum disorder (ASD) who had frequent observations from 14 to 36 months of age.MethodIn total, 912 observations of the Autism Diagnostic Observation Schedule (ADOS) were obtained from 149 children (103 with ASD) followed from 14 to 36 months of age. As a follow-up to a previous analysis of ADOS algorithm scores, a different analytic approach (Proc Traj) was implemented to identify several courses of symptom trajectories using ADOS Calibrated Severity Scores in a larger sample. Proc Traj is a statistical method that clusters individuals into separate groups based on different growth trajectories. Changes in symptom severity based on individual ADOS items also were examined.ResultsTrajectory analysis of overall symptom severity identified 4 clusters (non-spectrum ∼25%; worsening ∼27%; moderately-improving ∼25%; severe-persistent ∼23%). Trajectory clusters varied significantly in the proportions of confirmatory ASD diagnosis, level of baseline and final verbal and nonverbal abilities, and symptom severity. For the moderately-improving group, social communication improved, whereas restricted and repetitive behaviors were stable over time. Language and verbal and nonverbal communication improved for many children, but several social affect and restricted and repetitive behavior symptoms remained stable or worsened.ConclusionSignificant variability in symptom trajectories was observed among toddlers referred for possible ASD. Changes in social and restricted and repetitive behavior domain scores did not always co-occur. Similarly, item-level trajectories did not always align with trajectories of overall severity scores. These findings highlight the importance of monitoring individual symptoms within broader symptom domains when conducting repeated assessments for young children with suspected ASD.
| S-EPMC6636833 | biostudies-literature
Project description:Autism spectrum disorder (ASD) is characterized by social impairments and repetitive behaviors, and affects 1 in 68 US children. Despite ASD's societal impact, its disease mechanisms remain poorly understood. Recent preclinical ASD biomarker discovery research has implicated the neuropeptides oxytocin (OXT) and arginine vasopressin (AVP), and their receptors, OXTR and AVPR1A, in animal models. Efforts to translate these findings to individuals with ASD have typically involved evaluating single neuropeptide measures as biomarkers of ASD and/or behavioral functioning. Given that ASD is a heterogeneous disorder, and unidimensional ASD biomarker studies have been challenging to reproduce, here we employed a multidimensional neuropeptide biomarker analysis to more powerfully interrogate disease status and symptom severity in a well characterized child cohort comprised of ASD patients and neurotypical controls. These blood-based neuropeptide measures, considered as a whole, correctly predicted disease status for 57 out of 68 (i.e., 84%) participants. Further analysis revealed that a composite measure of OXTR and AVPR1A gene expression was the key driver of group classification, and that children with ASD had lower neuropeptide receptor mRNA levels compared to controls. Lower neuropeptide receptor mRNA levels also predicted greater symptom severity for core ASD features (i.e., social impairments and stereotyped behaviors), but were unrelated to intellectual impairment, an associated feature of ASD. Findings from this research highlight the value of assessing multiple related biological measures, and their relative contributions, in the same study, and suggest that low blood neuropeptide receptor availability may be a promising biomarker of disease presence and symptom severity in ASD.
| S-EPMC5878709 | biostudies-literature
Project description:Autism spectrum disorder (ASD) affects 1 in 88 children and is characterized by a complex phenotype, including social, communicative, and sensorimotor deficits. Autism spectrum disorder has been linked with atypical connectivity across multiple brain systems, yet the nature of these differences in young children with the disorder is not well understood.To examine connectivity of large-scale brain networks and determine whether specific networks can distinguish children with ASD from typically developing (TD) children and predict symptom severity in children with ASD.Case-control study performed at Stanford University School of Medicine of 20 children 7 to 12 years old with ASD and 20 age-, sex-, and IQ-matched TD children.Between-group differences in intrinsic functional connectivity of large-scale brain networks, performance of a classifier built to discriminate children with ASD from TD children based on specific brain networks, and correlations between brain networks and core symptoms of ASD.We observed stronger functional connectivity within several large-scale brain networks in children with ASD compared with TD children. This hyperconnectivity in ASD encompassed salience, default mode, frontotemporal, motor, and visual networks. This hyperconnectivity result was replicated in an independent cohort obtained from publicly available databases. Using maps of each individual's salience network, children with ASD could be discriminated from TD children with a classification accuracy of 78%, with 75% sensitivity and 80% specificity. The salience network showed the highest classification accuracy among all networks examined, and the blood oxygen-level dependent signal in this network predicted restricted and repetitive behavior scores. The classifier discriminated ASD from TD in the independent sample with 83% accuracy, 67% sensitivity, and 100% specificity.Salience network hyperconnectivity may be a distinguishing feature in children with ASD. Quantification of brain network connectivity is a step toward developing biomarkers for objectively identifying children with ASD.
| S-EPMC3951904 | biostudies-literature
Project description:BACKGROUND:A significant minority of children with autism spectrum disorder (ASD) are considered 'minimally verbal' due to language development stagnating at a few words. Recent developments allow for the severity of ASD symptoms to be examined using Autism Diagnostic Observation Schedule (ADOS) Social Affect (SA) and Restricted and Repetitive Behaviors (RRB) domain severity scores. The aim of the current study was to explore language outcomes in a cohort of minimally verbal children with autism evaluated through the preschool years and determine if and how ASD symptom severity in core domains predicts the development of spoken language by age 5. METHODS:The sample consisted of 70 children with autism aged 1-5 years at the first evaluation who were examined at least 1 year later, during their fifth year of age. The ADOS overall level of language item was used to categorize children as minimally verbal or having phrase speech, and the Mullen Scales of Early Learning was used as a continuous measure of expressive language. RESULTS:At Time 1, 65% (n = 47) of children in the sample were minimally verbal and by Time 2, 36% (n = 17 of 47) of them had developed phrase speech. While the Time 1 ADOS calibrated severity scores did not predict whether or not a child remained minimally verbal at Time 2, change in the SA calibrated severity score (but not RRB) was predictive of the continuous measure of expressive language. However, change in SA severity no longer predicted continuous expressive language when nonverbal cognitive ability was added to the model. CONCLUSIONS:Findings indicate that the severity of SA symptoms has some relationship with continuous language outcome, but not categorical. However, the omnipresent influence of nonverbal cognitive ability was confirmed in the current study, as the addition of it to the model rendered null the predictive utility of SA severity.
| S-EPMC4581593 | biostudies-literature
Project description:ObjectiveConverging evidence indicates that brain abnormalities in autism spectrum disorders (ASDs) involve atypical network connectivity. Given the central role of social deficits in the ASD phenotype, this investigation examined functional connectivity of the amygdala-a brain structure critically involved in processing of social information-in children and adolescents with ASDs, as well as age-dependent changes and links with clinical symptoms.MethodResting-state functional magnetic resonance imaging (rs-fMRI) data from 55 participants with ASDs and 50 typically developing (TD) controls, aged 7 to 17 years, were included. Groups were matched for age, gender, IQ, and head motion. Functional connectivity MRI (fcMRI) analysis was applied to examine intrinsic functional connectivity (iFC) of the amygdala, including cross-sectional tests of age-related changes.ResultsDirect between-group comparisons revealed reduced functional connectivity between bilateral amygdalae and left inferior occipital cortex, accompanied by greater connectivity between right amygdala and right sensorimotor cortex in the ASD group. This atypical pattern of amygdala connectivity was associated with decreased symptom severity and better overall functioning, as specifically seen in an ASD subgroup with the most atypical amygdala iFC but the least impaired social functioning. Age-related strengthening of amygdala-prefrontal connectivity, as observed in the TD group, was not detected in children with ASDs.ConclusionFindings support aberrant network sculpting in ASDs, specifically atypical integration between amygdala and primary sensorimotor circuits. Paradoxical links between atypical iFC and behavioral measures suggest that abnormal amygdala functional connections may be compensatory in some individuals with ASDs.
| S-EPMC6230473 | biostudies-literature
Project description:ObjectiveThe objectives of this study were to model growth in anxiety and depressive symptoms from late school age through young adulthood in individuals with autism spectrum disorder (ASD) and controls with developmental delay (DD), and to assess relationships among internalizing growth patterns, participant characteristics, baseline predictors, and distal outcomes.MethodData were collected between ages 6 and 24 years in 165 participants (n = 109 with ASD; n = 56 with nonspectrum DD), most of whom received diagnostic evaluations in both childhood and early adulthood. Questionnaires were collected approximately every 3 to 6 months between ages 9 and 24 years. Parent-rated Child Behavior Checklist (CBCL), Adult Behavior Checklist (ABCL), and Developmental Behaviour Checklist anxiety- and depression-related subscale distributions were modeled with mixed-effects Poisson models, covarying diagnosis, age, verbal IQ (VIQ), gender, and significant 2- and 3-way interactions.ResultsAnxiety was positively associated with VIQ, and controlling for VIQ, both anxiety and depressive symptoms were greater in ASD than nonspectrum participants. Female gender predicted greater increases over time in anxiety and depressive symptoms for both diagnostic groups. Lower maternal education was associated with increasing internalizing symptoms in a subset of less verbal individuals with ASD. In exploratory post hoc analyses, internalizing symptoms were associated with poorer emotional regulation in school age, and with lower life satisfaction and greater social difficulties in early adulthood.ConclusionFindings support previous claims that individuals with ASD are at particular risk for affect- and anxiety-specific problems. Although symptom levels in females increase at a faster rate throughout adolescence, males with ASD appear to have elevated levels of depressive symptoms in school age that are maintained into young adulthood.
| S-EPMC4407021 | biostudies-literature
Project description:Autism spectrum disorders (ASDs) are complex, pervasive, and heterogeneous neurodevelopmental conditions with varying trajectories, significant male bias and largely unknown etiology. However, an understanding of the biological mechanisms driving pathophysiology is evolving. Immune system aberrations, as identified through cytokine profiles, are believed to have a role in ASD. Altered cytokine levels may facilitate identification of ASD subtypes as well as provide biological markers of response to effective treatments. Research exploring the relationship between cytokine profiles and ASD symptoms is, however, in its infancy. The objective of this study was to explore relationships between cytokine levels and the severity of ASD and other clinical traits.Multiplex assay techniques were used to measure levels of 27 cytokines in plasma samples from a cohort of 144 children diagnosed with ASD.Overall, results showed a significant negative association between platelet-derived growth factor (PDGF)-BB, and the severity of ASD symptoms. Furthermore, a significant interaction with sex suggested a different immune profile for females compared to males. ASD symptom severity was negatively associated with levels of 4 cytokines, IL-1?, IL-8, MIP-1?, and VEGF, in females, but not in males.Results of the present study suggest that an altered cytokine response or profile is associated with the severity of ASD-related symptoms, with sex a potential modifier of this relationship. Further research in larger populations which recognizes the importance of sex comparisons and longitudinal assessments are now required to extend and further describe the role of the immune system in ASD.
| S-EPMC5712192 | biostudies-literature
Project description:Atypical brain function in attention-deficit/hyperactivity disorder (ADHD) has been identified using both task-activation and functional connectivity fMRI approaches. Recent work highlights the potential for another measure derived from functional neuroimaging data, brain signal variability, to reveal insights into clinical conditions. Higher brain signal variability has previously been linked with optimal behavioral performance. At present, little is known regarding the relationship between resting-state brain signal variability and ADHD symptom severity. The current study examined the relationship between a measure of moment-to-moment brain signal variability called mean-square successive difference (MSSD) and ADHD symptomatology in a group of children (7-12 years old) with (n = 40) and without (n = 30) a formal diagnosis of ADHD. A categorical analysis comparing subjects with and without a clinical diagnosis of ADHD showed no differences in MSSD between groups. A dimensional analysis revealed a positive relationship between MSSD and overall ADHD symptom severity and inattention across children with and without an ADHD diagnosis. Specifically, this positive relationship was found in medial prefrontal areas comprising the default mode network. These results demonstrate a link between intrinsic brain signal variability and ADHD symptom severity that cuts across diagnostic categories, and point to a locus of dysfunction consistent with previous neuroimaging literature.
| S-EPMC5857584 | biostudies-literature
Project description:This study reports on the initial validation of the Autism Symptom Interview (ASI), School-Age, a brief (15-20 min) phone interview derived from questions from the Autism Diagnostic Interview-Revised (ADI-R). The ASI, School-Age was administered by interviewers with minimal training to parents of children ages 5 to 12 who had all been previously identified with (or referred for assessment of) ASD or another neurodevelopmental disorder. Children then underwent a comprehensive assessment to determine a best-estimate clinical diagnosis of ASD (n?=?159) or non-ASD (e.g. language disorder, intellectual disability, ADHD; n?=?130). Clinicians who conducted the assessments were blind to ASI results. ROC analyses compared ASI scores to clinical diagnosis. Due to the small number of participants with non-ASD diagnoses who were classified as nonverbal (i.e. not yet using phrases on a daily basis), it was not possible to assess sensitivity and specificity of the nonverbal algorithm in this sample. The verbal algorithm yielded a sensitivity of 0.87 (95% CI?=?0.81-0.92) and a specificity of 0.62 (95% CI?=?0.53-0.70). When used in conjunction with the Autism Diagnostic Observation Schedule (ADOS), sensitivity and specificity were 0.82 (95% CI?=?0.74-0.88) and 0.92 (95% CI?=?0.86-0.96), respectively. Internal consistency and test-retest reliability were both excellent. Particularly for verbal school age children, the ASI may serve as a useful tool to more quickly ascertain or classify children with ASD for research or clinical triaging purposes. Additional data collection is underway to determine the utility of the ASI in children who are younger and/or nonverbal. Autism Res 2017, 10: 78-88. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
| S-EPMC5149113 | biostudies-literature
Project description:Motor challenges are commonly reported in autism spectrum disorder (ASD). Yet, there is substantial heterogeneity in motor ability within ASD, and it is unknown what behavioral characteristics best explain individual differences in motor ability in ASD and related conditions. This observational study examined motor ability as a function of sensory features, attention deficit/hyperactivity symptoms, ASD symptoms, and IQ in 110 children with ASD, typical development, or an intermediate behavioral profile. While motor challenges were more prevalent in the ASD group compared to other groups, sensory symptom severity and IQ across all individuals best predicted motor performance above-and-beyond group status. Therefore, motor challenges may be best characterized by individual variation in sensory features and cognitive abilities rather than diagnostic group.
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