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All K, Chawarska K, Macari SL. Early executive functioning predicts externalizing problems in neurodiverse preschoolers. Autism Res 2024. [PMID: 38476104 DOI: 10.1002/aur.3109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 01/31/2024] [Indexed: 03/14/2024]
Abstract
Children with autism spectrum disorder (ASD) often exhibit externalizing problems, which have been linked with increased anxiety and depression, peer rejection, and parental stress. Identification of early predictors of externalizing behaviors in autism will facilitate identification of vulnerable children and implementation of early preventative interventions. There is ample evidence that executive functioning, social functioning, and temperament are predictive of later externalizing problems in general populations, but less is known about these relations in ASD and other neurodiverse populations, particularly in the early preschool years. To address this gap, we assessed the relations between executive functioning, social functioning, and temperament at age 3 and externalizing problems at age 5 in a sample of neurodiverse children with ASD and other neurodevelopmental disorders and delays. Analyses revealed that severity of early executive functioning impairment predicted increased externalizing problems. Severity of social autism symptoms moderated this relationship such that the effect of executive functioning on externalizing problems decreased as autism symptoms increased. These findings suggest that executive functioning is an important target for identifying and developing interventions for vulnerable children and underscore the necessity of considering severity of autism symptoms when researching the development of externalizing problems in children with neurodevelopmental disorders.
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Affiliation(s)
- Katherine All
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Katarzyna Chawarska
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Suzanne L Macari
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
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2
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Vernetti A, Butler M, Banarjee C, Boxberger A, All K, Macari S, Chawarska K. Face-to-face live eye-tracking in toddlers with autism: Feasibility and impact of familiarity and face covering. Autism Res 2023. [PMID: 38009948 DOI: 10.1002/aur.3060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 10/31/2023] [Indexed: 11/29/2023]
Abstract
Studies utilizing eye-tracking methods have potential to promptly capture real-world dynamics of one of the core areas of vulnerability in autism spectrum disorders (ASD), selective social attention. So far, no studies have successfully reported utilizing the method to examine social attention in toddlers with neurodevelopmental vulnerabilities in real world and challenging settings such as an interactive face-to-face. This study examined the feasibility and validity of live eye-tracking method in response to live interaction occurring in several contexts in toddlers with and without ASD. Forty-seven toddlers with ASD, with atypical development (ATYP), or typically developing (TD), underwent a 30-s live eye-tracking procedure during a face-to-face interaction with a masked stranger using child-directed-speech (16 ASD, 14 ATYP, 17 TD; Mage = 23.44 months, SD = 6.02). Out of this group of toddlers, 29 (10 ASD, 8 ATYP, 11 TD, Mage = 21.97 months, SD = 5.76) underwent the same procedure with one of their maskless parent. Task completion rate, calibration accuracy, and affective response (feasibility measures) as well as attention to the task and the social partner (validity measures) were examined. Task completion rate and calibration accuracy were excellent. Despite the challenging context of face-to-face interaction, the toddlers exhibited a neutral affect, and high attention to the task and the speaker. As anticipated, toddlers with ASD looked less at the social partner compared with control groups. However, attention was comparable between the Stranger and Parent conditions, indicating that the effect was consistent regardless of presence of face covering or the familiarity of the interactive partner. The study demonstrates the high feasibility and validity of a live eye-tracking task involving face-to-face interaction in neurodiverse toddlers with social vulnerabilities. The effect of diminished attention to social partners in toddlers with autism is robust and present when interacting with an unfamiliar person and parent. The results suggest that a brief live eye-tracking method constitutes a promising ecologically valid candidate biomarker and potential intervention outcome in autism.
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Affiliation(s)
- Angelina Vernetti
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Maureen Butler
- Child Study Center, Northwestern University, Chicago, Illinois, USA
| | - Chitra Banarjee
- Child Study Center, University of Central Florida, Orlando, Florida, USA
| | - Alexandra Boxberger
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Katherine All
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Suzanne Macari
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Katarzyna Chawarska
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
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3
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Shic F, Barney EC, Naples AJ, Dommer KJ, Chang SA, Li B, McAllister T, Atyabi A, Wang Q, Bernier R, Dawson G, Dziura J, Faja S, Jeste SS, Murias M, Johnson SP, Sabatos-DeVito M, Helleman G, Senturk D, Sugar CA, Webb SJ, McPartland JC, Chawarska K. The Selective Social Attention task in children with autism spectrum disorder: Results from the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) feasibility study. Autism Res 2023; 16:2150-2159. [PMID: 37749934 PMCID: PMC11003770 DOI: 10.1002/aur.3026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 08/25/2023] [Indexed: 09/27/2023]
Abstract
The Selective Social Attention (SSA) task is a brief eye-tracking task involving experimental conditions varying along socio-communicative axes. Traditionally the SSA has been used to probe socially-specific attentional patterns in infants and toddlers who develop autism spectrum disorder (ASD). This current work extends these findings to preschool and school-age children. Children 4- to 12-years-old with ASD (N = 23) and a typically-developing comparison group (TD; N = 25) completed the SSA task as well as standardized clinical assessments. Linear mixed models examined group and condition effects on two outcome variables: percent of time spent looking at the scene relative to scene presentation time (%Valid), and percent of time looking at the face relative to time spent looking at the scene (%Face). Age and IQ were included as covariates. Outcome variables' relationships to clinical data were assessed via correlation analysis. The ASD group, compared to the TD group, looked less at the scene and focused less on the actress' face during the most socially-engaging experimental conditions. Additionally, within the ASD group, %Face negatively correlated with SRS total T-scores with a particularly strong negative correlation with the Autistic Mannerism subscale T-score. These results highlight the extensibility of the SSA to older children with ASD, including replication of between-group differences previously seen in infants and toddlers, as well as its ability to capture meaningful clinical variation within the autism spectrum across a wide developmental span inclusive of preschool and school-aged children. The properties suggest that the SSA may have broad potential as a biomarker for ASD.
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Affiliation(s)
- Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Seattle, Washington, USA
- Department of General Pediatrics, University of Washington School of Medicine, Seattle, Washington, USA
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Erin C. Barney
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Seattle, Washington, USA
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Adam J. Naples
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Kelsey J. Dommer
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Seattle, Washington, USA
| | - Shou An Chang
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Beibin Li
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Seattle, Washington, USA
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, Washington, USA
| | - Takumi McAllister
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Adham Atyabi
- Department of General Pediatrics, University of Washington School of Medicine, Seattle, Washington, USA
- Department of Computer Science, University of Colorado - Colorado Springs, Colorado Springs, Colorado, USA
| | - Quan Wang
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
- Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an, China
| | - Raphael Bernier
- Department of Psychiatry & Behavioral Science, University of Washington School of Medicine, Seattle, Washington, USA
| | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina, USA
| | - James Dziura
- Emergency Medicine, Yale University, New Haven, Connecticut, USA
| | - Susan Faja
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
- Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts, USA
| | - Shafali Spurling Jeste
- Department of Psychiatry & Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California, USA
- Department of Neurology, Keck School of Medicine of USC, Los Angeles, California, USA
- Division of Neurology, Children’s Hospital Los Angeles, Los Angeles, California, USA
| | - Michael Murias
- Department of Medical Social Sciences, Northwestern University, Evanston, Illinois, USA
| | - Scott P. Johnson
- Department of Psychology, University of California Los Angeles, Los Angeles, California, USA
| | - Maura Sabatos-DeVito
- Duke Center for Autism and Brain Development, Duke University, Durham, North Carolina, USA
| | - Gerhard Helleman
- Department of Psychiatry & Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California, USA
- Department of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Damla Senturk
- Department of Biostatistics, University of California Los Angeles, Los Angeles, California, USA
| | - Catherine A. Sugar
- Department of Biostatistics, University of California Los Angeles, Los Angeles, California, USA
| | - Sara Jane Webb
- Department of General Pediatrics, University of Washington School of Medicine, Seattle, Washington, USA
- Department of Psychiatry & Behavioral Science, University of Washington School of Medicine, Seattle, Washington, USA
| | - James C. McPartland
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Katarzyna Chawarska
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
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Jourdon A, Wu F, Mariani J, Capauto D, Norton S, Tomasini L, Amiri A, Suvakov M, Schreiner JD, Jang Y, Panda A, Nguyen CK, Cummings EM, Han G, Powell K, Szekely A, McPartland JC, Pelphrey K, Chawarska K, Ventola P, Abyzov A, Vaccarino FM. Author Correction: Modeling idiopathic autism in forebrain organoids reveals an imbalance of excitatory cortical neuron subtypes during early neurogenesis. Nat Neurosci 2023; 26:2035. [PMID: 37674007 DOI: 10.1038/s41593-023-01447-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Affiliation(s)
- Alexandre Jourdon
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Feinan Wu
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Jessica Mariani
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Davide Capauto
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Scott Norton
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Livia Tomasini
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Anahita Amiri
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Milovan Suvakov
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Jeremy D Schreiner
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Yeongjun Jang
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Arijit Panda
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Cindy Khanh Nguyen
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Elise M Cummings
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Gloria Han
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Kelly Powell
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Anna Szekely
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - James C McPartland
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Kevin Pelphrey
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
- Brain Institute, Department of Neurology, University of Virginia School of Medicine, Charlottesville, VA, USA
| | | | - Pamela Ventola
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Alexej Abyzov
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
| | - Flora M Vaccarino
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA.
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA.
- Kavli Institute for Neuroscience, Yale University, New Haven, CT, USA.
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5
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Jourdon A, Wu F, Mariani J, Capauto D, Norton S, Tomasini L, Amiri A, Suvakov M, Schreiner JD, Jang Y, Panda A, Nguyen CK, Cummings EM, Han G, Powell K, Szekely A, McPartland JC, Pelphrey K, Chawarska K, Ventola P, Abyzov A, Vaccarino FM. Modeling idiopathic autism in forebrain organoids reveals an imbalance of excitatory cortical neuron subtypes during early neurogenesis. Nat Neurosci 2023; 26:1505-1515. [PMID: 37563294 PMCID: PMC10573709 DOI: 10.1038/s41593-023-01399-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 06/30/2023] [Indexed: 08/12/2023]
Abstract
Idiopathic autism spectrum disorder (ASD) is highly heterogeneous, and it remains unclear how convergent biological processes in affected individuals may give rise to symptoms. Here, using cortical organoids and single-cell transcriptomics, we modeled alterations in the forebrain development between boys with idiopathic ASD and their unaffected fathers in 13 families. Transcriptomic changes suggest that ASD pathogenesis in macrocephalic and normocephalic probands involves an opposite disruption of the balance between excitatory neurons of the dorsal cortical plate and other lineages such as early-generated neurons from the putative preplate. The imbalance stemmed from divergent expression of transcription factors driving cell fate during early cortical development. While we did not find genomic variants in probands that explained the observed transcriptomic alterations, a significant overlap between altered transcripts and reported ASD risk genes affected by rare variants suggests a degree of gene convergence between rare forms of ASD and the developmental transcriptome in idiopathic ASD.
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Affiliation(s)
- Alexandre Jourdon
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Feinan Wu
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Jessica Mariani
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Davide Capauto
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Scott Norton
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Livia Tomasini
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Anahita Amiri
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Milovan Suvakov
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Jeremy D Schreiner
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Yeongjun Jang
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Arijit Panda
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Cindy Khanh Nguyen
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Elise M Cummings
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Gloria Han
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Kelly Powell
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Anna Szekely
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - James C McPartland
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Kevin Pelphrey
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
- Brain Institute, Department of Neurology, University of Virginia School of Medicine, Charlottesville, VA, USA
| | | | - Pamela Ventola
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Alexej Abyzov
- Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
| | - Flora M Vaccarino
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA.
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA.
- Kavli Institute for Neuroscience, Yale University, New Haven, CT, USA.
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6
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Horien C, Greene AS, Shen X, Fortes D, Brennan-Wydra E, Banarjee C, Foster R, Donthireddy V, Butler M, Powell K, Vernetti A, Mandino F, O’Connor D, Lake EMR, McPartland JC, Volkmar FR, Chun M, Chawarska K, Rosenberg MD, Scheinost D, Constable RT. A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth. Cereb Cortex 2023; 33:6320-6334. [PMID: 36573438 PMCID: PMC10183743 DOI: 10.1093/cercor/bhac506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 09/15/2022] [Accepted: 09/16/2022] [Indexed: 12/29/2022] Open
Abstract
Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings in healthcare settings. Nevertheless, it remains unclear if it is possible to build dimensional predictive models of attentional state in a sample that includes participants with neurodiverse conditions. Here, we use 5 datasets to identify and validate functional connectome-based markers of attention. In dataset 1, we use connectome-based predictive modeling and observe successful prediction of performance on an in-scan sustained attention task in a sample of youth, including participants with a neurodiverse condition. The predictions are not driven by confounds, such as head motion. In dataset 2, we find that the attention network model defined in dataset 1 generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets 3-5, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attentional state in youth and support the further development of predictive dimensional models of other clinically relevant phenotypes.
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Affiliation(s)
- Corey Horien
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, United States
- MD-PhD Program, Yale School of Medicine, New Haven, CT, United States
| | - Abigail S Greene
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, United States
- MD-PhD Program, Yale School of Medicine, New Haven, CT, United States
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - Diogo Fortes
- Yale Child Study Center, New Haven, CT, United States
| | | | | | - Rachel Foster
- Yale Child Study Center, New Haven, CT, United States
| | | | | | - Kelly Powell
- Yale Child Study Center, New Haven, CT, United States
| | | | - Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - David O’Connor
- Department of Biomedical Engineering, Yale University, New Haven, CT, United States
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - James C McPartland
- Yale Child Study Center, New Haven, CT, United States
- Department of Psychology, Yale University, New Haven, CT, United States
| | - Fred R Volkmar
- Yale Child Study Center, New Haven, CT, United States
- Department of Psychology, Yale University, New Haven, CT, United States
| | - Marvin Chun
- Department of Psychology, Yale University, New Haven, CT, United States
| | - Katarzyna Chawarska
- Yale Child Study Center, New Haven, CT, United States
- Department of Statistics and Data Science, Yale University, New Haven, CT, United States
- Department of Pediatrics, Yale School of Medicine, New Haven, CT, United States
| | - Monica D Rosenberg
- Department of Psychology, University of Chicago, Chicago, IL, United States
- Neuroscience Institute, University of Chicago, Chicago, IL, United States
| | - Dustin Scheinost
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, United States
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
- Yale Child Study Center, New Haven, CT, United States
- Department of Statistics and Data Science, Yale University, New Haven, CT, United States
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, United States
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, United States
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7
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Faja S, Sabatos-DeVito M, Sridhar A, Kuhn JL, Nikolaeva JI, Sugar CA, Webb SJ, Bernier RA, Sikich L, Hellemann G, Senturk D, Naples AJ, Shic F, Levin AR, Seow HA, Dziura JD, Jeste SS, Chawarska K, Nelson CA, Dawson G, McPartland JC. Evaluation of clinical assessments of social abilities for use in autism clinical trials by the autism biomarkers consortium for clinical trials. Autism Res 2023; 16:981-996. [PMID: 36929131 PMCID: PMC10192100 DOI: 10.1002/aur.2905] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 02/11/2023] [Indexed: 03/18/2023]
Abstract
Clinical trials in autism spectrum disorder (ASD) often rely on clinician rating scales and parent surveys to measure autism-related features and social behaviors. To aid in the selection of these assessments for future clinical trials, the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) directly compared eight common instruments with respect to acquisition rates, sensitivity to group differences, equivalence across demographic sub-groups, convergent validity, and stability over a 6-week period. The sample included 280 children diagnosed with ASD (65 girls) and 119 neurotypical children (36 girls) aged from 6 to 11 years. Full scale IQ for ASD ranged from 60 to 150 and for neurotypical ranged from 86 to 150. Instruments measured clinician global assessment and autism-related behaviors, social communication abilities, adaptive function, and social withdrawal behavior. For each instrument, we examined only the scales that measured social or communication functioning. Data acquisition rates were at least 97.5% at T1 and 95.7% at T2. All scales distinguished diagnostic groups. Some scales significantly differed by participant and/or family demographic characteristics. Within the ASD group, most clinical instruments exhibited weak (≥ |0.1|) to moderate (≥ |0.4|) intercorrelations. Short-term stability was moderate (ICC: 0.5-0.75) to excellent (ICC: >0.9) within the ASD group. Variations in the degree of stability may inform viability for different contexts of use, such as identifying clinical subgroups for trials versus serving as a modifiable clinical outcome. All instruments were evaluated in terms of their advantages and potential concerns for use in clinical trials.
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Affiliation(s)
- Susan Faja
- Department of Pediatrics, Harvard Medical School. Boston MA. USA
- Boston Children’s Hospital. Boston MA. USA
| | - Maura Sabatos-DeVito
- Duke Center for Autism and Brain Development, Duke University. Durham NC. USA
- Department of Psychiatry & Behavioral Sciences, Duke University. Durham NC. USA
| | | | - Jocelyn L. Kuhn
- Department of Pediatrics, Boston University School of Medicine. Boston MA. USA
| | - Julia I. Nikolaeva
- Department of Communication Sciences and Disorders, Northwestern University. Evanston IL. USA
| | - Catherine A. Sugar
- Department of Biostatistics, University of California Los Angeles. Los Angeles CA. USA
- Department of Psychiatry & Biobehavioral Sciences, University of California Los Angeles. Los Angeles CA. USA
| | - Sara Jane Webb
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute. Seattle WA. USA
- Department of Psychiatry & Behavioral Science, University of Washington School of Medicine. Seattle WA. USA
| | - Raphael A. Bernier
- Department of Psychiatry & Behavioral Science, University of Washington School of Medicine. Seattle WA. USA
| | - Linmarie Sikich
- Department of Psychiatry & Behavioral Sciences, Duke University. Durham NC. USA
| | - Gerhard Hellemann
- Department of Biostatistics, University of Alabama at Birmingham. Birmingham AB. USA
| | - Damla Senturk
- Department of Biostatistics, University of California Los Angeles. Los Angeles CA. USA
| | - Adam J. Naples
- Yale Child Study Center, Yale University. New Haven CT. USA
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute. Seattle WA. USA
- Department of General Pediatrics, University of Washington School of Medicine. Seattle WA. USA
| | - April R. Levin
- Department of Neurology, Boston Children’s Hospital. Boston MA. USA
- Harvard Medical School. Boston MA. USA
| | - Helen A. Seow
- Yale Center for Clinical Investigation, Yale University. New Haven CT. USA
| | - James D. Dziura
- Department of Emergency Medicine, Yale University. New Haven CT. USA
| | - Shafali S. Jeste
- Department of Pediatrics and Neurology, Children’s Hospital, Los Angeles. Los Angeles CA. USA
- USC Keck School of Medicine. Los Angeles CA. USA
| | | | - Charles A. Nelson
- Department of Pediatrics, Harvard Medical School. Boston MA. USA
- Boston Children’s Hospital. Boston MA. USA
- Graduate School of Education, Harvard University. Boston MA. USA
| | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University. Durham NC. USA
- Department of Psychiatry & Behavioral Sciences, Duke University. Durham NC. USA
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8
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Shurtz L, Schwartz C, DiStefano C, McPartland JC, Levin AR, Dawson G, Kleinhans NM, Faja S, Webb SJ, Shic F, Naples AJ, Seow H, Bernier RA, Chawarska K, Sugar CA, Dziura J, Senturk D, Santhosh M, Jeste SS. Concomitant medication use in children with autism spectrum disorder: Data from the Autism Biomarkers Consortium for Clinical Trials. Autism 2023; 27:952-966. [PMID: 36086805 PMCID: PMC9995606 DOI: 10.1177/13623613221121425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
LAY ABSTRACT Children with autism spectrum disorder are prescribed a variety of medications that affect the central nervous system (psychotropic medications) to address behavior and mood. In clinical trials, individuals taking concomitant psychotropic medications often are excluded to maintain homogeneity of the sample and prevent contamination of biomarkers or clinical endpoints. However, this choice may significantly diminish the clinical representativeness of the sample. In a recent multisite study designed to identify biomarkers and behavioral endpoints for clinical trials (the Autism Biomarkers Consortium for Clinical Trials), school-age children with autism spectrum disorder were enrolled without excluding for medications, thus providing a unique opportunity to examine characteristics of psychotropic medication use in a research cohort and to guide future decisions on medication-related inclusion criteria. The aims of the current analysis were (1) to quantify the frequency and type of psychotropic medications reported in school-age children enrolled in the ABC-CT and (2) to examine behavioral features of children with autism spectrum disorder based on medication classes. Of the 280 children with autism spectrum disorder in the cohort, 42.5% were taking psychotropic medications, with polypharmacy in half of these children. The most commonly reported psychotropic medications included melatonin, stimulants, selective serotonin reuptake inhibitors, alpha agonists, and antipsychotics. Descriptive analysis showed that children taking antipsychotics displayed a trend toward greater overall impairment. Our findings suggest that exclusion of children taking concomitant psychotropic medications in trials could limit the clinical representativeness of the study population, perhaps even excluding children who may most benefit from new treatment options.
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Affiliation(s)
| | | | | | | | - April R Levin
- Boston Children’s Hospital, USA
- Harvard University, USA
| | | | | | - Susan Faja
- Boston Children’s Hospital, USA
- Harvard University, USA
| | - Sara J Webb
- University of Washington, USA
- Seattle Children’s Research Institute, USA
| | - Frederick Shic
- University of Washington, USA
- Seattle Children’s Research Institute, USA
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Webb SJ, Naples AJ, Levin AR, Hellemann G, Borland H, Benton J, Carlos C, McAllister T, Santhosh M, Seow H, Atyabi A, Bernier R, Chawarska K, Dawson G, Dziura J, Faja S, Jeste S, Murias M, Nelson CA, Sabatos-DeVito M, Senturk D, Shic F, Sugar CA, McPartland JC. The Autism Biomarkers Consortium for Clinical Trials: Initial Evaluation of a Battery of Candidate EEG Biomarkers. Am J Psychiatry 2023; 180:41-49. [PMID: 36000217 PMCID: PMC10027395 DOI: 10.1176/appi.ajp.21050485] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Numerous candidate EEG biomarkers have been put forward for use in clinical research on autism spectrum disorder (ASD), but biomarker development has been hindered by limited attention to the psychometric properties of derived variables, inconsistent results across small studies, and variable methodology. The authors evaluated the basic psychometric properties of a battery of EEG assays for their potential suitability as biomarkers in clinical trials. METHODS This was a large, multisite, naturalistic study in 6- to 11-year-old children who either had an ASD diagnosis (N=280) or were typically developing (N=119). The authors evaluated an EEG battery composed of well-studied assays of resting-state activity, face perception (faces task), biological motion perception, and visual evoked potentials (VEPs). Biomarker psychometrics were evaluated in terms of acquisition rates, construct performance, and 6-week stability. Preliminary evaluation of use was explored through group discrimination and phenotypic correlations. RESULTS Three assays (resting state, faces task, and VEP) show promise in terms of acquisition rates and construct performance. Six-week stability values in the ASD group were moderate (intraclass correlations ≥0.66) for the faces task latency of the P1 and N170, the VEP amplitude of N1 and P1, and resting alpha power. Group discrimination and phenotype correlations were primarily observed for the faces task P1 and N170. CONCLUSIONS In the context of a large-scale, rigorous evaluation of candidate EEG biomarkers for use in ASD clinical trials, neural response to faces emerged as a promising biomarker for continued evaluation. Resting-state activity and VEP yielded mixed results. The study's biological motion perception assay failed to display construct performance. The results provide information about EEG biomarker performance that is relevant for the next stage of biomarker development efforts focused on context of use.
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Affiliation(s)
- Sara Jane Webb
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Adam J Naples
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - April R Levin
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Gerhard Hellemann
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Heather Borland
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Jessica Benton
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Carter Carlos
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Takumi McAllister
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Megha Santhosh
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Helen Seow
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Adham Atyabi
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Raphael Bernier
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Katarzyna Chawarska
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Geraldine Dawson
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - James Dziura
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Susan Faja
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Shafali Jeste
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Michael Murias
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Charles A Nelson
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Maura Sabatos-DeVito
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Damla Senturk
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Frederick Shic
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - Catherine A Sugar
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
| | - James C McPartland
- Center for Child Health, Behavior, and Development and Seattle Children's Research Institute, Seattle (Webb, Borland, Benton, Santhosh, Shic); Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle (Webb, Bernier); Yale Child Study Center (Naples, Carlos, McAllister, Chawarska, McPartland), Yale Center for Clinical Investigation (Seow), and Department of Emergency Medicine (Dziura), Yale University, New Haven, Conn.; Department of Neurology, Boston Children's Hospital, Boston (Levin); Department of Neurology, Harvard Medical School, Boston (Levin); Department of Psychiatry and Biobehavioral Sciences (Hellemann, Jeste, Senturk, Sugar) and Department of Biostatistics (Senturk, Sugar), University of California Los Angeles, Los Angeles; Department of Computer Science, University of Colorado, Colorado Springs (Atyabi); Duke Center for Autism and Brain Development (Dawson, Sabatos-DeVito) and Department of Psychiatry and Behavioral Sciences (Dawson), Duke University, Durham, N.C.; Department of Pediatrics, Harvard University, Boston (Faja, Nelson); Division of Developmental Medicine, Boston Children's Hospital, Boston (Faja, Nelson); Department of Medical Social Sciences, Northwestern University, Chicago (Murias); Graduate School of Education, Harvard University, Boston (Nelson); Department of Pediatrics, University of Washington, Seattle (Shic)
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10
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Chawarska K, Lewkowicz D, Feiner H, Macari S, Vernetti A. Attention to audiovisual speech does not facilitate language acquisition in infants with familial history of autism. J Child Psychol Psychiatry 2022; 63:1466-1476. [PMID: 35244219 DOI: 10.1111/jcpp.13595] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 01/10/2022] [Accepted: 01/21/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND Due to familial liability, siblings of children with ASD exhibit elevated risk for language delays. The processes contributing to language delays in this population remain unclear. METHODS Considering well-established links between attention to dynamic audiovisual cues inherent in a speaker's face and speech processing, we investigated if attention to a speaker's face and mouth differs in 12-month-old infants at high familial risk for ASD but without ASD diagnosis (hr-sib; n = 91) and in infants at low familial risk (lr-sib; n = 62) for ASD and whether attention at 12 months predicts language outcomes at 18 months. RESULTS At 12 months, hr-sib and lr-sib infants did not differ in attention to face (p = .14), mouth preference (p = .30), or in receptive and expressive language scores (p = .36, p = .33). At 18 months, the hr-sib infants had lower receptive (p = .01) but not expressive (p = .84) language scores than the lr-sib infants. In the lr-sib infants, greater attention to the face (p = .022) and a mouth preference (p = .025) contributed to better language outcomes at 18 months. In the hr-sib infants, neither attention to the face nor a mouth preference was associated with language outcomes at 18 months. CONCLUSIONS Unlike low-risk infants, high-risk infants do not appear to benefit from audiovisual prosodic and speech cues in the service of language acquisition despite intact attention to these cues. We propose that impaired processing of audiovisual cues may constitute the link between genetic risk factors and poor language outcomes observed across the autism risk spectrum and may represent a promising endophenotype in autism.
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Affiliation(s)
- Katarzyna Chawarska
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
- Haskins Laboratories, New Haven, CT, USA
| | - David Lewkowicz
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
- Haskins Laboratories, New Haven, CT, USA
| | - Hannah Feiner
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Suzanne Macari
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Angelina Vernetti
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
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11
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Horien C, Floris DL, Greene AS, Noble S, Rolison M, Tejavibulya L, O'Connor D, McPartland JC, Scheinost D, Chawarska K, Lake EMR, Constable RT. Functional Connectome-Based Predictive Modeling in Autism. Biol Psychiatry 2022; 92:626-642. [PMID: 35690495 PMCID: PMC10948028 DOI: 10.1016/j.biopsych.2022.04.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 04/14/2022] [Accepted: 04/17/2022] [Indexed: 01/08/2023]
Abstract
Autism is a heterogeneous neurodevelopmental condition, and functional magnetic resonance imaging-based studies have helped advance our understanding of its effects on brain network activity. We review how predictive modeling, using measures of functional connectivity and symptoms, has helped reveal key insights into this condition. We discuss how different prediction frameworks can further our understanding of the brain-based features that underlie complex autism symptomatology and consider how predictive models may be used in clinical settings. Throughout, we highlight aspects of study interpretation, such as data decay and sampling biases, that require consideration within the context of this condition. We close by suggesting exciting future directions for predictive modeling in autism.
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Affiliation(s)
- Corey Horien
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; MD-PhD Program, Yale School of Medicine, New Haven, Connecticut.
| | - Dorothea L Floris
- Methods of Plasticity Research, Department of Psychology, University of Zürich, Zurich, Switzerland; Donders Center for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Abigail S Greene
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; MD-PhD Program, Yale School of Medicine, New Haven, Connecticut
| | - Stephanie Noble
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Max Rolison
- Yale Child Study Center, New Haven, Connecticut
| | - Link Tejavibulya
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut
| | - David O'Connor
- Department of Biomedical Engineering, Yale University, New Haven, Connecticut
| | - James C McPartland
- Department of Psychology, Yale University, New Haven, Connecticut; Yale Child Study Center, New Haven, Connecticut
| | - Dustin Scheinost
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Department of Biomedical Engineering, Yale University, New Haven, Connecticut; Department of Statistics and Data Science, Yale University, New Haven, Connecticut; Yale Child Study Center, New Haven, Connecticut
| | - Katarzyna Chawarska
- Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut; Department of Statistics and Data Science, Yale University, New Haven, Connecticut; Yale Child Study Center, New Haven, Connecticut
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, Connecticut; Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Department of Biomedical Engineering, Yale University, New Haven, Connecticut.
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12
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Scheinost D, Chang J, Lacadie C, Brennan-Wydra E, Foster R, Boxberger A, Macari S, Vernetti A, Constable RT, Ment LR, Chawarska K. Hypoconnectivity between anterior insula and amygdala associates with future vulnerabilities in social development in a neurodiverse sample of neonates. Sci Rep 2022; 12:16230. [PMID: 36171268 PMCID: PMC9517994 DOI: 10.1038/s41598-022-20617-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 09/15/2022] [Indexed: 11/25/2022] Open
Abstract
Altered resting state functional connectivity (FC) involving the anterior insula (aINS), a key node in the salience network, has been reported consistently in autism. Here we examined, for the first time, FC between the aINS and the whole brain in a sample of full-term, postmenstrual age (PMA) matched neonates (mean 44.0 weeks, SD = 1.5) who due to family history have high likelihood (HL) for developing autism (n = 12) and in controls (n = 41) without family history of autism (low likelihood, LL). Behaviors associated with autism were evaluated between 12 and 18 months (M = 17.3 months, SD = 2.5) in a subsample (25/53) of participants using the First Year Inventory (FYI). Compared to LL controls, HL neonates showed hypoconnectivity between left aINS and left amygdala. Lower connectivity between the two nodes was associated with higher FYI risk scores in the social domain (r(25) = -0.561, p = .003) and this association remained robust when maternal mental health factors were considered. Considering that a subsample of LL participants (n = 14/41) underwent brain imaging during the fetal period at PMA 31 and 34 weeks, in an exploratory analysis, we evaluated prospectively development of the LaINS-Lamy connectivity and found that the two areas strongly coactivate throughout the third trimester of pregnancy. The study identifies left lateralized anterior insula-amygdala connectivity as a potential target of further investigation into neural circuitry that enhances likelihood of future onset of social behaviors associated with autism during neonatal and potentially prenatal periods.
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Affiliation(s)
- Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT, 06520, USA
- Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Joseph Chang
- Department of Statistics and Data Science, Yale University, New Haven, CT, 06520, USA
| | - Cheryl Lacadie
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA
| | | | - Rachel Foster
- Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA
| | | | - Suzanne Macari
- Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Angelina Vernetti
- Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA
| | - R Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Laura R Ment
- Department of Pediatrics, Yale School of Medicine, New Haven, CT, 06510, USA
- Department of Neurology, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Katarzyna Chawarska
- Department of Statistics and Data Science, Yale University, New Haven, CT, 06520, USA.
- Department of Pediatrics, Yale School of Medicine, New Haven, CT, 06510, USA.
- Yale Child Study Center, Yale School of Medicine, 300 George Street, Suite 900, New Haven, CT, 06510, USA.
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13
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Scheinost D, Chang J, Lacadie C, Brennan-Wydra E, Constable RT, Chawarska K, Ment LR. Functional connectivity for the language network in the developing brain: 30 weeks of gestation to 30 months of age. Cereb Cortex 2022; 32:3289-3301. [PMID: 34875024 PMCID: PMC9340393 DOI: 10.1093/cercor/bhab415] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 09/20/2021] [Accepted: 10/12/2021] [Indexed: 11/14/2022] Open
Abstract
Although the neural scaffolding for language is putatively present before birth, the maturation of functional connections among the key nodes of the language network, Broca's and Wernicke's areas, is less known. We leveraged longitudinal and cross-sectional data from three sites collected through six studies to track the development of functional circuits between Broca's and Wernicke's areas from 30 weeks of gestation through 30 months of age in 127 unique participants. Using resting-state fMRI data, functional connectivity was calculated as the correlation between fMRI time courses from pairs of regions, defined as Broca's and Wernicke's in both hemispheres. The primary analysis evaluated 23 individuals longitudinally imaged from 30 weeks postmenstrual age (fetal) through the first postnatal month (neonatal). A secondary analysis in 127 individuals extended these curves into older infants and toddlers. These data demonstrated significant growth of interhemispheric connections including left Broca's and its homolog and left Wernicke's and its homolog from 30 weeks of gestation through the first postnatal month. In contrast, intrahemispheric connections did not show significant increases across this period. These data represent an important baseline for language systems in the developing brain against which to compare those neurobehavioral disorders with the potential fetal onset of disease.
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Affiliation(s)
- Dustin Scheinost
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
- Department of Statistics & Data Science, Yale University, New Haven, CT 06520, USA
- Child Study Center, Yale School of Medicine, New Haven, CT 06510, USA
| | - Joseph Chang
- Department of Statistics & Data Science, Yale University, New Haven, CT 06520, USA
| | - Cheryl Lacadie
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA
| | | | - R Todd Constable
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT 06510, USA
| | - Katarzyna Chawarska
- Department of Statistics & Data Science, Yale University, New Haven, CT 06520, USA
- Child Study Center, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Pediatrics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Laura R Ment
- Department of Pediatrics, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Neurology, Yale School of Medicine, New Haven, CT 06510, USA
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14
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Powell K, Macari S, Brennan-Wydra E, Feiner H, Butler M, Goncalves Fortes D, Boxberger A, Torres-Viso M, Morgan C, Lyons M, Chawarska K. Elevated symptoms of executive dysfunction predict lower adaptive functioning in 3-year-olds with autism spectrum disorder. Autism Res 2022; 15:1336-1347. [PMID: 35388596 PMCID: PMC9253075 DOI: 10.1002/aur.2715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 03/14/2022] [Accepted: 03/21/2022] [Indexed: 11/06/2022]
Abstract
Executive functioning (EF) deficits co-occur frequently with autism spectrum disorder (ASD) and have a long-term detrimental impact on quality of life of children and their families. Timely identification of risk for EF vulnerabilities may hasten access to early intervention and alleviate their long-term consequences. This study examines (1) if EF deficits are elevated in toddlers with ASD compared to nonautistic siblings of children with ASD, typically developing (TYP) toddlers, and toddlers with atypical developmental presentation; and (2) if EF deficits have a detrimental effect on adaptive functioning in ASD. Participants were recruited between September 2014 and October 2019 and included 73 toddlers with ASD, 33 nonautistic siblings of children with ASD, 35 toddlers with atypical development, and 28 TYP toddlers matched on chronological age (M = 39.01 months, SD = 3.11). EF deficits were measured using the BRIEF-P; adaptive skills were measured using the VABS-II. Whenever appropriate, analyses were controlled for MSEL verbal and nonverbal developmental quotient, ADOS-2 autism severity scores, and sex. Analyses revealed that toddlers with ASD exhibited elevated BRIEF-P scores across all domains compared to each of the three comparison groups. Higher BRIEF-P scores were associated with lower adaptive social, communication, and daily living skills while controlling for symptom severity, verbal and nonverbal functioning, and sex. In conclusion, marked vulnerabilities in EF are already present in 3-year-old toddlers with ASD and are predictive of the level of adaptive functioning in ASD. EF vulnerabilities in toddlers should be targeted for intervention to improve long-term outcomes in ASD. LAY SUMMARY: Many children with autism experience vulnerabilities in executive functioning (EF), which may include challenges with inhibition, working memory, cognitive flexibility, and planning. The study shows that these vulnerabilities can already be detected at age three and that their presence is linked with lower social, communication, and daily living skills. Screening children with ASD for EF challenges and helping those who have difficulties may improve their long-term outcomes.
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Affiliation(s)
- Kelly Powell
- Yale University School of Medicine, Yale Child Study Center, New Haven, Connecticut, USA
| | - Suzanne Macari
- Yale University School of Medicine, Yale Child Study Center, New Haven, Connecticut, USA
| | - Emma Brennan-Wydra
- Yale University School of Medicine, Yale Child Study Center, New Haven, Connecticut, USA
| | - Hannah Feiner
- Yale University School of Medicine, Yale Child Study Center, New Haven, Connecticut, USA
| | - Maureen Butler
- Yale University School of Medicine, Yale Child Study Center, New Haven, Connecticut, USA
| | - Diogo Goncalves Fortes
- Yale University School of Medicine, Yale Child Study Center, New Haven, Connecticut, USA
| | - Alexandra Boxberger
- Yale University School of Medicine, Yale Child Study Center, New Haven, Connecticut, USA
| | - Mariana Torres-Viso
- Yale University School of Medicine, Yale Child Study Center, New Haven, Connecticut, USA
| | - Chelsea Morgan
- Yale University School of Medicine, Yale Child Study Center, New Haven, Connecticut, USA
| | - Megan Lyons
- Yale University School of Medicine, Yale Child Study Center, New Haven, Connecticut, USA
| | - Katarzyna Chawarska
- Yale University School of Medicine, Yale Child Study Center, New Haven, Connecticut, USA
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15
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Pecukonis M, Young GS, Brian J, Charman T, Chawarska K, Elsabbagh M, Iverson JM, Jeste S, Landa R, Messinger DS, Schwichtenberg A, Webb SJ, Zwaigenbaum L, Tager-Flusberg H. Early predictors of language skills at 3 years of age vary based on diagnostic outcome: A baby siblings research consortium study. Autism Res 2022; 15:1324-1335. [PMID: 35652157 PMCID: PMC9253079 DOI: 10.1002/aur.2760] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 05/11/2022] [Indexed: 11/08/2022]
Abstract
While previous work has identified the early predictors of language skills in infants at elevated familial risk (ER) and low familial risk (LR) for autism spectrum disorder (ASD), no studies to date have explored whether these predictors vary based on diagnostic outcome of ASD or no ASD. The present study used a large, multisite dataset to examine associations between a set of commonly studied predictor variables (infant gesture abilities, fine motor skills, nonverbal cognition, and maternal education level), measured at 12 months, and language skills, measured at 3 years, across three diagnostic outcome groups-infants with ASD ("ASD"), ER infants without ASD ("ER-no ASD"), and LR infants without ASD ("LR-no ASD"). Findings revealed that the predictors of language skills differed across groups, as gesture abilities were positively associated with language skills in the ER-no ASD group but negatively associated with language skills in the ASD group. Furthermore, maternal education level was positively associated with language skills in the ASD and LR-no ASD groups only. Variability in these early predictors may help explain why language skills are heterogeneous across the autism spectrum, and, with further study, may help clinicians identify those in need of additional and/or specialized intervention services that support language development. LAY SUMMARY: The present study identified predictors of language skills in infants with and without autism spectrum disorder (ASD). Maternal education level and 12-month gesture abilities predicted 3-year language skills in infants with ASD. Measuring these predictors early in life may help identify infants and families in need of additional and/or specialized intervention services that support language development.
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Affiliation(s)
| | - Gregory S. Young
- Department of Psychiatry and Behavioral Sciences, University of California Davis
| | | | - Tony Charman
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London
| | | | | | | | - Shafali Jeste
- Department of Pediatrics, Department of Neurology, Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles
| | - Rebecca Landa
- Center for Autism and Related Disorders, Kennedy Krieger Institute
| | | | | | - Sara Jane Webb
- Psychiatry and Behavioral Sciences, University of Washington
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16
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Sridhar A, Kuhn J, Faja S, Sabatos-DeVito M, Nikolaeva JI, Dawson G, Nelson CA, Webb SJ, Bernier R, Jeste S, Chawarska K, Sugar CA, Shic F, Naples A, Dziura J, McPartland JC. Patterns of Intervention Utilization Among School-Aged Children with Autism Spectrum Disorder: Findings from a Multi-Site Research Consortium. Res Autism Spectr Disord 2022; 94. [PMID: 35444715 PMCID: PMC9015686 DOI: 10.1016/j.rasd.2022.101950] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
When designing and interpreting results from clinical trials evaluating treatments for children on the autism spectrum, a complicating factor is that most children receive a range of concurrent treatments. Thus, it is important to better understand the types and hours of interventions that participants typically receive as part of standard of care, as well as to understand the child, family, and geographic factors that are associated with different patterns of service utilization. In this multi-site study, we interviewed 280 caregivers of 6-to-11-year-old school-aged children on the autism spectrum about the types and amounts of interventions their children received in the prior 6 weeks. Reported interventions were coded as "evidence-based practice" or "other interventions," reflecting the level of empirical support. Results indicated that children received a variety of interventions with varying levels of empirical evidence and a wide range of hours (0 to 79.3 hours/week). Children with higher autism symptom levels, living in particular states, and who identified as non-Hispanic received more evidence-based intervention hours. Higher parental education level related to more hours of other interventions. Children who were younger, had lower cognitive ability, and with higher autism symptom levels received a greater variety of interventions overall. Thus, based on our findings, it would seem prudent when designing clinical trials to take into consideration a variety of factors including autism symptom levels, age, cognitive ability, ethnicity, parent education and geographic location. Future research should continue to investigate the ethnic, racial, and socioeconomic influences on school-aged intervention services.
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Affiliation(s)
- Aksheya Sridhar
- Boston Children's Hospital/Harvard Medical School, Boston, MA, USA
| | | | - Susan Faja
- Boston Children's Hospital/Harvard Medical School, Boston, MA, USA
| | - Maura Sabatos-DeVito
- Department of Psychiatry and Behavioral Sciences, Duke Center for Autism and Brain Development, Duke University, Durham, NC, USA
| | | | - Geraldine Dawson
- Department of Psychiatry and Behavioral Sciences, Duke Center for Autism and Brain Development, Duke University, Durham, NC, USA
| | - Charles A Nelson
- Boston Children's Hospital/Harvard Medical School, Boston, MA, USA
| | - Sara J Webb
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington School of Medicine, Seattle WA, USA
| | - Raphael Bernier
- Department of Pediatrics, University of Washington School of Medicine, Seattle WA, USA
| | | | | | | | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington School of Medicine, Seattle WA, USA
| | | | - James Dziura
- Yale Center for Analytical Sciences, New Haven, CT USA
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17
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Rolison M, Lacadie C, Chawarska K, Spann M, Scheinost D. Atypical Intrinsic Hemispheric Interaction Associated with Autism Spectrum Disorder Is Present within the First Year of Life. Cereb Cortex 2022; 32:1212-1222. [PMID: 34424949 PMCID: PMC8924430 DOI: 10.1093/cercor/bhab284] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/19/2021] [Accepted: 07/20/2021] [Indexed: 11/13/2022] Open
Abstract
Autism spectrum disorder (ASD) is characterized by atypical connectivity lateralization of functional networks. However, previous studies have not directly investigated if differences in specialization between ASD and typically developing (TD) peers are present in infancy, leaving the timing of onset of these differences relatively unknown. We studied the hemispheric asymmetries of connectivity in children with ASD and infants later meeting the diagnostic criteria for ASD. Analyses were performed in 733 children with ASD and TD peers and in 71 infants at high risk (HR) or normal risk (NR) for ASD, with data collected at 1 month and 9 months of age. Comparing children with ASD (n = 301) to TDs (n = 432), four regions demonstrated group differences in connectivity: posterior cingulate cortex (PCC), posterior superior temporal gyrus, extrastriate cortex, and anterior prefrontal cortex. At 1 month, none of these regions exhibited group differences between ASD (n = 10), HR-nonASD (n = 15), or NR (n = 18) infants. However, by 9 months, the PCC and extrastriate exhibited atypical connectivity in ASD (n = 11) and HR-nonASD infants (n = 24) compared to NR infants (n = 22). Connectivity did not correlate with symptoms in either sample. Our results demonstrate that differences in network asymmetries associated with ASD risk are observable prior to the age of a reliable clinical diagnosis.
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Affiliation(s)
- Max Rolison
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, USA
- Child Study Center, Yale School of Medicine, New Haven, CT 06519, USA
| | - Cheryl Lacadie
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, USA
| | - Katarzyna Chawarska
- Child Study Center, Yale School of Medicine, New Haven, CT 06519, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06510, USA
- Department of Pediatrics, Yale School of Medicine, New Haven, CT 06511, USA
| | - Marisa Spann
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, USA
- Child Study Center, Yale School of Medicine, New Haven, CT 06519, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT 06511, USA
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18
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Schjølberg S, Shic F, Volkmar FR, Nordahl-Hansen A, Stenberg N, Torske T, Larsen K, Riley K, Sukhodolsky DG, Leckman JF, Chawarska K, Øien RA. What are we optimizing for in autism screening? Examination of algorithmic changes in the M-CHAT. Autism Res 2022; 15:296-304. [PMID: 34837355 PMCID: PMC8821132 DOI: 10.1002/aur.2643] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 11/02/2021] [Accepted: 11/16/2021] [Indexed: 02/03/2023]
Abstract
The present study objectives were to examine the performance of the new M-CHAT-R algorithm to the original M-CHAT algorithm. The main purpose was to examine if the algorithmic changes increase identification of children later diagnosed with ASD, and to examine if there is a trade-off when changing algorithms. We included 54,463 screened cases from the Norwegian Mother and Child Cohort Study. Children were screened using the 23 items of the M-CHAT at 18 months. Further, the performance of the M-CHAT-R algorithm was compared to the M-CHAT algorithm on the 23-items. In total, 337 individuals were later diagnosed with ASD. Using M-CHAT-R algorithm decreased the number of correctly identified ASD children by 12 compared to M-CHAT, with no children with ASD screening negative on the M-CHAT criteria subsequently screening positive utilizing the M-CHAT-R algorithm. A nonparametric McNemar's test determined a statistically significant difference in identifying ASD utilizing the M-CHAT-R algorithm. The present study examined the application of 20-item MCHAT-R scoring criterion to the 23-item MCHAT. We found that this resulted in decreased sensitivity and increased specificity for identifying children with ASD, which is a trade-off that needs further investigation in terms of cost-effectiveness. However, further research is needed to optimize screening for ASD in the early developmental period to increase identification of false negatives.
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Affiliation(s)
- Synnve Schjølberg
- a: Norwegian Institute of Public Health, University of Washington School of Medicine
| | - Frederick Shic
- b: Seattle Children’s Research Institute, University of Washington School of Medicine
| | - Fred R. Volkmar
- c: Yale Child Study Center, The Arctic University of Norway,d: Southern Connecticut University, The Arctic University of Norway
| | | | - Nina Stenberg
- f: Oslo University Hospital, The Arctic University of Norway
| | - Tonje Torske
- g: Vestre Viken Hospital:, The Arctic University of Norway
| | | | - Katherine Riley
- b: Seattle Children’s Research Institute, University of Washington School of Medicine
| | | | | | | | - Roald A. Øien
- c: Yale Child Study Center, The Arctic University of Norway,h: UiT – The Arctic University of Norway,Corresponding author tel: +4793099994, PB 6070, 9037 Tromsoe, Norway
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19
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Webb SJ, Emerman I, Sugar C, Senturk D, Naples AJ, Faja S, Benton J, Borland H, Carlos C, Levin AR, McAllister T, Santhosh M, Bernier RA, Chawarska K, Dawson G, Dziura J, Jeste S, Kleinhans N, Murias M, Sabatos-DeVito M, Shic F, McPartland JC. Identifying Age Based Maturation in the ERP Response to Faces in Children With Autism: Implications for Developing Biomarkers for Use in Clinical Trials. Front Psychiatry 2022; 13:841236. [PMID: 35615454 PMCID: PMC9126041 DOI: 10.3389/fpsyt.2022.841236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 03/21/2022] [Indexed: 01/27/2023] Open
Abstract
Recent proposals have suggested the potential for neural biomarkers to improve clinical trial processes in neurodevelopmental conditions; however, few efforts have identified whether chronological age-based adjustments will be necessary (as used in standardized behavioral assessments). Event-related potentials (ERPs) demonstrate early differences in the processing of faces vs. objects in the visual processing system by 4 years of age and age-based improvement (decreases in latency) through adolescence. Additionally, face processing has been proposed to be related to social skills as well as autistic social-communication traits. While previous reports suggest delayed latency in individuals with autism spectrum disorder (ASD), extensive individual and age based heterogeneity exists. In this report, we utilize a sample of 252 children with ASD and 118 children with typical development (TD), to assess the N170 and P100 ERP component latencies (N170L and P100L, respectively), to upright faces, the face specificity effect (difference between face and object processing), and the inversion effect (difference between face upright and inverted processing) in relation to age. First, linear mixed models (LMMs) were fitted with fixed effect of age at testing and random effect of participant, using all available data points to characterize general age-based development in the TD and ASD groups. Second, LMM models using only the TD group were used to calculate age-based residuals in both groups. The purpose of residualization was to assess how much variation in ASD participants could be accounted for by chronological age-related changes. Our data demonstrate that the N170L and P100L responses to upright faces appeared to follow a roughly linear relationship with age. In the ASD group, the distribution of the age-adjusted residual values suggest that ASD participants were more likely to demonstrate slower latencies than would be expected for a TD child of the same age, similar to what has been identified using unadjusted values. Lastly, using age-adjusted values for stratification, we found that children who demonstrated slowed age-adjusted N170L had lower verbal and non-verbal IQ and worse face memory. These data suggest that age must be considered in assessing the N170L and P100L response to upright faces as well, and these adjusted values may be used to stratify children within the autism spectrum.
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Affiliation(s)
- Sara Jane Webb
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States.,Department of Psychiatry & Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
| | - Iris Emerman
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States
| | - Catherine Sugar
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Statistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Damla Senturk
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Statistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Adam J Naples
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - Susan Faja
- Harvard Medical School, Harvard University, Boston, MA, United States.,Department of Neurology, Boston Children's Hospital, Boston, MA, United States
| | - Jessica Benton
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States
| | - Heather Borland
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States
| | - Carter Carlos
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - April R Levin
- Harvard Medical School, Harvard University, Boston, MA, United States.,Department of Neurology, Boston Children's Hospital, Boston, MA, United States
| | - Takumi McAllister
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - Megha Santhosh
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States
| | - Raphael A Bernier
- Department of Psychiatry & Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
| | | | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States.,Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC, United States
| | - James Dziura
- Yale Center for Clinical Investigation, Yale University, New Haven, CT, United States
| | - Shafali Jeste
- Department of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Neurology, Children's Hospital of Los Angeles, Los Angeles, CA, United States
| | - Natalia Kleinhans
- Center on Human Development and Disabilities, University of Washington, Seattle, WA, United States.,Department of Radiology, University of Washington School of Medicine, Seattle, WA, United States
| | - Michael Murias
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States.,Medical Social Sciences, Northwestern University, Chicago, IL, United States
| | - Maura Sabatos-DeVito
- Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC, United States
| | - Frederick Shic
- Center on Child Health, Behavior, & Development, Seattle Children's Research Institute, Seattle, WA, United States.,Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, United States
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20
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Macari S, Chen X, Brunissen L, Yhang E, Brennan-Wydra E, Vernetti A, Volkmar F, Chang J, Chawarska K. Puppets facilitate attention to social cues in children with ASD. Autism Res 2021; 14:1975-1985. [PMID: 34350712 PMCID: PMC8434944 DOI: 10.1002/aur.2552] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 04/09/2021] [Accepted: 05/18/2021] [Indexed: 11/06/2022]
Abstract
Diminished visual attention to faces of social partners represents one of the early characteristics of autism spectrum disorder (ASD). Here we examine if the introduction of puppets as social partners alters attention to speakers' faces in young children with ASD and typically developing (TD) controls. Children with ASD (N = 37; Mage = 49.44 months) and TD (N = 27; Mage = 40.66 months) viewed a video depicting a puppet and a human engaged in a conversation. Dwell time on these faces was analyzed as a function of group and speaker's identity. Unlike TD controls, the ASD group exhibited limited visual attention to and chance-level visual preference for the human speaker. However, attention to and preference for the puppet speaker's face was greater than chance and comparable across the two groups. While there was a strong association between low human speaker preference and high autism severity, no association with autism severity was found for puppet speaker preference. Unlike humans, expressive and verbal puppets attracted the attention of children with ASD at levels comparable to that of TD controls. Considering that puppets can engage in reciprocal interactions and deliver simplified, salient social-communicative cues, they may facilitate therapeutic efforts in children with ASD. LAY SUMMARY: While studies have shown support for therapeutic uses of robots with children with autism, other similar agents such as puppets remain to be explored. When shown a video of a conversation between a puppet and a person, young children with ASD paid as much attention to the puppet's face as typically-developing (TD) children. Since puppets can engage in back-and-forth interactions and model social interactions and communication, they may play a promising role in therapeutic efforts for young children with ASD.
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Affiliation(s)
- Suzanne Macari
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Xinyuan Chen
- Department of Statistics and Data Science, Yale University, New Haven, Connecticut, USA
| | - Ludivine Brunissen
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Eukyung Yhang
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Emma Brennan-Wydra
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Angelina Vernetti
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Fred Volkmar
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Joseph Chang
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Statistics and Data Science, Yale University, New Haven, Connecticut, USA
| | - Katarzyna Chawarska
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
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21
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Xiao J, Gao Y, Yu Y, Toft G, Zhang Y, Luo J, Xia Y, Chawarska K, Olsen J, Li J, Liew Z. Associations of parental birth characteristics with autism spectrum disorder (ASD) risk in their offspring: a population-based multigenerational cohort study in Denmark. Int J Epidemiol 2021; 50:485-495. [PMID: 33411909 DOI: 10.1093/ije/dyaa246] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/06/2020] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Fetal exposure risk factors are associated with increased autism spectrum disorder (ASD) risk. New hypotheses regarding multigenerational risk for ASD have been proposed, but epidemiological evidence is largely lacking. We evaluated whether parental birth characteristics, including preterm birth and low birthweight, were associated with ASD risk in offspring. METHODS We conducted a nationwide register-based cohort study that included 230 174 mother-child and 157 926 father-child pairs in Denmark. Logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals (CI) for offspring ASD according to parental preterm (<37 weeks) and low birthweight (<2500 g) status, with or without adjustment for certain grandmaternal sociodemographic factors. Mediation analyses were performed for selected parental and offspring health-related factors. RESULTS Offspring of mothers or fathers with adverse birth characteristics had about 31-43% higher risk for ASD (maternal preterm birth, OR = 1.31, 95% CI= 1.12, 1.55; maternal low birthweight, OR = 1.35, 95% CI: 1.17,1.57; paternal preterm birth, OR = 1.43, 95% CI = 1.18, 1.73; paternal low birthweight, OR = 1.38, 95% CI= 1.13, 1.70). Parents born very preterm (<32 weeks) marked a nearly 2-fold increase in ASD risk in their children. These associations were slightly attenuated upon adjustment for grandmaternal sociodemographic factors. Mediation analyses suggested that parental social-mental and offspring perinatal factors might explain a small magnitude of the total effect observed, especially for maternal birth characteristic associations. CONCLUSIONS Offspring of parents born with adverse characteristics had an elevated risk for ASD. Transmission of ASD risk through maternal and paternal factors should be considered in future research on ASD aetiology.
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Affiliation(s)
- Jingyuan Xiao
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.,Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | - Yu Gao
- Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, Yale School of Public Health, New Haven, CT, USA.,Department of Environmental Health, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yongfu Yu
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
| | - Gunnar Toft
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
| | - Yawei Zhang
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.,Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | - Jiajun Luo
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.,Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | - Yuntian Xia
- Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | | | - Jørn Olsen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
| | - Jiong Li
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
| | - Zeyan Liew
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.,Yale Center for Perinatal, Pediatric, and Environmental Epidemiology, Yale School of Public Health, New Haven, CT, USA
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22
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Stenberg N, Schjølberg S, Shic F, Volkmar F, Øyen AS, Bresnahan M, Svendsen BK, von Tetzchner S, Thronæs NT, Macari S, Cicchetti DV, Chawarska K, Suren P, Øien RA. Functional Outcomes of Children Identified Early in the Developmental Period as at Risk for ASD Utilizing the The Norwegian Mother, Father and Child Cohort Study (MoBa). J Autism Dev Disord 2021; 51:922-932. [PMID: 32424708 PMCID: PMC7954713 DOI: 10.1007/s10803-020-04539-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Early identification of autism spectrum disorder (ASD) is regarded as crucial for swift access to early intervention and, subsequently, better outcomes later in life. However, current instruments miss large proportions of children who later go on to be diagnosed with ASD, raising a question of what these instruments measure. The present study utilized data from the Norwegian Mother, Father, and Child Cohort Study and the Autism Birth Cohort study to explore the subsequent developmental and diagnostic characteristics of children raising developmental concern on the six-critical discriminative item criterion of the M-CHAT (DFA6) at 18 months of age (N = 834). The DFA6 identified 28.8% of children diagnosed with ASD (N = 163), but 4.4% with language disorder (N = 188) and 81.3% with intellectual disability (N = 32) without ASD. Scoring in the «at-risk» range was associated with lower IQ, impaired functional language, and greater severity of autism symptoms whether children had ASD or not.
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Affiliation(s)
| | | | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Fred Volkmar
- School of Medicine, Child Study Center, Yale University, New Haven, USA
| | - Anne-Siri Øyen
- Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Hospital, Oslo, Norway
| | | | | | | | - Nina Torheim Thronæs
- Department of Education, UiT - The Arctic University of Norway, PB 6050, 9037, Tromsø, Norway
| | - Suzanne Macari
- School of Medicine, Child Study Center, Yale University, New Haven, USA
| | | | | | - Pål Suren
- Norwegian Institute of Public Health, Oslo, Norway
| | - Roald A Øien
- Department of Education, UiT - The Arctic University of Norway, PB 6050, 9037, Tromsø, Norway.
- School of Medicine, Child Study Center, Yale University, New Haven, USA.
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23
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Macari S, Milgramm A, Reed J, Shic F, Powell KK, Macris D, Chawarska K. Context-Specific Dyadic Attention Vulnerabilities During the First Year in Infants Later Developing Autism Spectrum Disorder. J Am Acad Child Adolesc Psychiatry 2021; 60:166-175. [PMID: 32061926 PMCID: PMC9524139 DOI: 10.1016/j.jaac.2019.12.012] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 12/18/2019] [Accepted: 02/07/2020] [Indexed: 12/27/2022]
Abstract
OBJECTIVE Although some eye-tracking studies demonstrate atypical attention to faces by 6 months of age in autism spectrum disorder (ASD), behavioral studies in early infancy return largely negative results. We examined the effects of context and diagnosis on attention to faces during face-to-face live interactions in infants at high familial risk (HR) and low familial risk (LR) for ASD. METHOD Participants were 6-, 9-, and 12-month-old siblings of children with ASD who were later determined to have ASD (n = 21), other developmental challenges (HR-C; n = 74), or typical development (TD) (HR-TD; n = 32), and low-risk, typically developing controls (LR-TD; n = 49). Infants were administered the social orienting probes task, consisting of five conditions: dyadic bid, song, peek-a-boo, tickle, and toy play. Attention to an unfamiliar examiner's face was coded by blinded raters from video recordings. RESULTS At all ages, the ASD group spent less time looking at the examiner's face than the HR-C, HR-TD, and LR-TD groups during the Dyadic Bid and Tickle conditions (all p <.05), but not during the Song, Peek-a-Boo, or Toy Play conditions (all p >.23). Lower attention to faces during Dyadic Bid and Tickle conditions was significantly correlated with higher severity of autism symptoms at 18 months. CONCLUSION During the prodromal stages of the disorder, infants with ASD exhibited subtle impairments in attention to faces of interactive partners during interactions involving eye contact and child-directed speech (with and without physical contact), but not in contexts involving singing, familiar anticipatory games, or toy play. Considering the convergence with eye-tracking findings on limited attention to faces in infants later diagnosed with ASD, reduced attention to faces of interactive partners in specific contexts may constitute a promising candidate behavioral marker of ASD in infancy.
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Affiliation(s)
- Suzanne Macari
- Yale Child Study Center, Yale School of Medicine, New Haven, Connecticut.
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24
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Horien C, Fontenelle S, Joseph K, Powell N, Nutor C, Fortes D, Butler M, Powell K, Macris D, Lee K, Greene AS, McPartland JC, Volkmar FR, Scheinost D, Chawarska K, Constable RT. Low-motion fMRI data can be obtained in pediatric participants undergoing a 60-minute scan protocol. Sci Rep 2020; 10:21855. [PMID: 33318557 PMCID: PMC7736342 DOI: 10.1038/s41598-020-78885-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 12/01/2020] [Indexed: 01/21/2023] Open
Abstract
Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult task, as participants tend to move while being scanned. Head motion represents a significant confound in fMRI connectivity analyses. One approach to limit motion has been to use shorter MRI protocols, though this reduces the reliability of results. Hence, there is a need to implement methods to achieve high-quality, low-motion data while not sacrificing data quantity. Here we show that by using a mock scan protocol prior to a scan, in conjunction with other in-scan steps (weighted blanket and incentive system), it is possible to achieve low-motion fMRI data in pediatric participants (age range: 7-17 years old) undergoing a 60 min MRI session. We also observe that motion is low during the MRI protocol in a separate replication group of participants, including some with autism spectrum disorder. Collectively, the results indicate it is possible to conduct long scan protocols in difficult-to-scan populations and still achieve high-quality data, thus potentially allowing more reliable fMRI findings.
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Affiliation(s)
- Corey Horien
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA.
- MD-PhD Program, Yale School of Medicine, New Haven, CT, USA.
- Magnetic Resonance Research Center, 300 Cedar St, PO Box 208043, New Haven, CT, 06520-8043, USA.
| | | | | | | | | | | | | | | | | | - Kangjoo Lee
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Abigail S Greene
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA
- MD-PhD Program, Yale School of Medicine, New Haven, CT, USA
| | - James C McPartland
- Yale Child Study Center, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Fred R Volkmar
- Yale Child Study Center, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Dustin Scheinost
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA
- Yale Child Study Center, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT, USA
| | - Katarzyna Chawarska
- Yale Child Study Center, New Haven, CT, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT, USA
- Department of Pediatrics, Yale School of Medicine, New Haven, CT, USA
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
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25
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Macari SL, Vernetti A, Chawarska K. Attend Less, Fear More: Elevated Distress to Social Threat in Toddlers With Autism Spectrum Disorder. Autism Res 2020; 14:1025-1036. [PMID: 33283976 DOI: 10.1002/aur.2448] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 11/01/2020] [Accepted: 11/21/2020] [Indexed: 01/10/2023]
Abstract
Differential emotional reactivity to social and nonsocial stimuli has been hypothesized but rarely examined empirically in ASD despite its potential importance for development of social motivation, cognition, and comorbid psychopathology. This study examined emotional reactivity, regulation, and attention to social and nonsocial threat in toddlers with ASD (n = 42, Mage : 22 months) and typically developing (TD) toddlers (n = 22, Mage : 23 months), and their mutual associations with autism symptom severity. Participants were exposed to social (stranger), nonsocial (mechanical objects), and ambiguous (masks) threats, and their intensity of distress (iDistress), attention to threat (Attention), and presence of emotion regulation (ER) strategies were measured. Autism symptom severity was quantified using the Autism Diagnostic Observation Schedule-2. In response to social threat, toddlers with ASD exhibited elevated iDistress (P < 0.038) but lower Attention (P < 0.002) and a wider variety of ER strategies (P < 0.040) compared to TD controls, though their ER strategies were less likely to be social. However, nonsocial and ambiguous threat elicited lower iDistress in ASD than in TD toddlers (P = 0.012 and P = 0.034, respectively), but comparable Attention and ER strategy use. Autism severity was not associated with iDistress. The study demonstrates elevated emotional salience but diminished attentional salience of social threat in ASD. A failure to attend adequately to social threats may restrict opportunities to appraise their threat value and engender often observed in ASD negative emotional responses to novel social situations. Early atypical emotional reactivity may independently contribute to the shaping of complex autism phenotypes and may be linked with later emerging affective and behavioral symptoms. LAY SUMMARY: Compared to typically developing toddlers, toddlers with ASD show diminished attention yet enhanced distress in response to social threat. Poor attention to potential social threat may limit opportunities to assess its threat value and thus contribute to often observed negative emotional responses to novel social situations. Identifying the precursors of atypical emotional reactivity in infancy and its links with later psychopathology will inform about novel treatment targets and mechanisms of change in the early stages of ASD. Autism Res 2021, 14: 1025-1036. © 2020 International Society for Autism Research, Wiley Periodicals, LLC.
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Affiliation(s)
- Suzanne L Macari
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, 06511, USA
| | - Angelina Vernetti
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, 06511, USA
| | - Katarzyna Chawarska
- Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, 06511, USA
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Brunissen L, Rapoport E, Chawarska K, Adesman A. Sex Differences in Gender-Diverse Expressions and Identities among Youth with Autism Spectrum Disorder. Autism Res 2020; 14:143-155. [PMID: 33283980 DOI: 10.1002/aur.2441] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 11/03/2020] [Accepted: 11/11/2020] [Indexed: 11/09/2022]
Abstract
A growing body of evidence supports a potential link between autism spectrum disorder (ASD) and gender dysphoria, yet few studies have looked at sex differences in the co-occurrence of gender diversity and ASD. The aim of this study was to characterize sex differences in gender-diverse expressions and identities, as well as gender-related concerns, in youth with ASD. Parents of youth with ASD ages 6-21 (n = 163) completed an online questionnaire about their child's gender expression and identity. Sex-typed behaviors during childhood were measured using the Gender Identity Questionnaire (GIQ). Semi-partial Kendall correlations and chi-square tests were used to compare gender non-conformity, gender-diverse identities, and gender-related concerns between sexes. Sex-based differences in mean GIQ score and individual GIQ items were evaluated using a linear regression and semi-partial Kendall correlations, respectively. All regressions and correlations controlled for child age. Parents of girls were more likely to report child appearances and mannerisms that were less concordant with their child's birth sex. Based on parent-report, girls had lower mean GIQ scores, indicating greater cross-gendered/fewer same-gendered behaviors in childhood. Lastly, parents of girls with ASD were more likely to report that their daughters experienced anxiety due to gender-related concerns and discomfort during puberty than parents of boys. These findings suggest that girls with ASD seem more likely have gender-diverse preferences, mannerisms, and appearances that fall outside of traditional gender norms. Gender-related concerns appear to be a source of real distress in girls with ASD, highlighting the need for individualized support, especially during puberty. LAY SUMMARY: Despite evidence of a potential link between autism and gender diversity, few studies have explored differences in gender identity/expression between boys and girls with autism. Based on parent responses, we found that girls with autism are more likely than boys to have appearances and mannerisms, as well as behaviors during childhood, that fall outside of the traditional gender role. The unique profile of girls with autism and their elevated distress over gender-related concerns call for individualized support during adolescence.
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Affiliation(s)
- Ludivine Brunissen
- Division of Developmental and Behavioral Pediatrics, Steven and Alexandra Cohen Children's Medical Center of New York, Lake Success, NY, USA
| | - Eli Rapoport
- Division of Developmental and Behavioral Pediatrics, Steven and Alexandra Cohen Children's Medical Center of New York, Lake Success, NY, USA
| | | | - Andrew Adesman
- Division of Developmental and Behavioral Pediatrics, Steven and Alexandra Cohen Children's Medical Center of New York, Lake Success, NY, USA.,Department of Pediatrics, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
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27
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Vernetti A, Shic F, Boccanfuso L, Macari S, Kane-Grade F, Milgramm A, Hilton E, Heymann P, Goodwin MS, Chawarska K. Atypical Emotional Electrodermal Activity in Toddlers with Autism Spectrum Disorder. Autism Res 2020; 13:1476-1488. [PMID: 32896980 PMCID: PMC10081486 DOI: 10.1002/aur.2374] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 07/19/2020] [Accepted: 07/23/2020] [Indexed: 01/22/2023]
Abstract
Past studies in autism spectrum disorder (ASD) indicate atypical peripheral physiological arousal. However, the conditions under which these atypicalities arise and their link with behavioral emotional expressions and core ASD symptoms remain uncertain. Given the importance of physiological arousal in affective, learning, and cognitive processes, the current study examined changes in skin conductance level (ΔSCL) in 41 toddlers with ASD (mean age: 22.7 months, SD: 2.9) and 32 age-matched toddlers with typical development (TD) (mean age: 21.6 months, SD: 3.6) in response to probes designed to induce anger, joy, and fear emotions. The magnitude of ΔSCL was comparable during anger (P = 0.206, d = 0.30) and joy (P = 0.996, d = 0.01) conditions, but significantly lower during the fear condition (P = 0.001, d = 0.83) in toddlers with ASD compared to TD peers. In the combined samples, ΔSCL positively correlated with intensity of behavioral emotional expressivity during the anger (r[71] = 0.36, P = 0.002) and fear (r[68] = 0.32, P = 0.007) conditions, but not in the joy (r[69] = -0.15, P = 0.226) condition. Finally, ΔSCL did not associate with autism symptom severity in any emotion-eliciting condition in the ASD group. Toddlers with ASD displayed attenuated ΔSCL to situations aimed at eliciting fear, which may forecast the emergence of highly prevalent internalizing and externalizing problems in this population. The study putatively identifies ΔSCL as a dimension not associated with severity of autism but with behavioral responses in negatively emotionally challenging events and provides support for the feasibility, validity, and incipient utility of examining ΔSCL in response to emotional challenges in very young children. LAY SUMMARY: Physiological arousal was measured in toddlers with autism exposed to frustrating, pleasant, and threatening tasks. Compared to typically developing peers, toddlers with autism showed comparable arousal responses to frustrating and pleasant events, but lower responses to threatening events. Importantly, physiological arousal and behavioral expressions were aligned during frustrating and threatening events, inviting exploration of physiological arousal to measure responses to emotional challenges. Furthermore, this study advances the understanding of precursors to emotional and behavioral problems common in older children with autism. Autism Res 2020, 13: 1476-1488. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.
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Affiliation(s)
- Angelina Vernetti
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Frederick Shic
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA.,Seattle Children's Research Institute, Seattle, Washington, USA.,Division of General Pediatrics, University of Washington School of Medicine, Seattle, Washington, USA
| | | | - Suzanne Macari
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Finola Kane-Grade
- Division of Developmental Medicine, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Anna Milgramm
- Center for Autism and Related Disabilities, University at Albany, SUNY, New York City, New York, USA
| | - Emily Hilton
- Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Perrine Heymann
- Early Childhood Behavior Lab, Florida International University, Miami, Florida, USA
| | - Matthew S Goodwin
- Department of Health Sciences, Bouvé College of Health Sciences, Northeastern University, Boston, Massachusetts, USA
| | - Katarzyna Chawarska
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
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Abstract
Importance Enhanced selective attention toward nonsocial objects and impaired attention to social stimuli constitute key clinical features of autism spectrum disorder (ASD). Yet, the mechanisms associated with atypical selective attention in ASD are poorly understood, which limits the development of more effective interventions. In typically developing individuals, selective attention to social and nonsocial stimuli is associated with the informational value of the stimuli, which is typically learned over the course of repeated interactions with the stimuli. Objective To examine value learning (VL) of social and nonsocial stimuli and its association with selective attention in preschoolers with and without ASD. Design, Setting, and Participants This case-control study compared children with ASD vs children with developmental delay (DD) and children with typical development (TD) recruited between March 3, 2017, and June 13, 2018, at a university-based research laboratory. Participants were preschoolers with ASD, DD, or TD. Main Outcomes and Measures Procedure consisted of an eye-tracking gaze-contingent VL task involving social (faces) and nonsocial (fractals) stimuli and consisting of baseline, training, and choice test phases. Outcome measures were preferential attention to stimuli reinforced (high value) vs not reinforced (low value) during training. The hypotheses were stated before data collection. Results Included were 115 preschoolers with ASD (n = 48; mean [SD] age, 38.30 [15.55] months; 37 [77%] boys), DD (n = 31; mean [SD] age, 45.73 [19.49] months; 19 [61%] boys), or TD (n = 36; mean [SD] age, 36.53 [12.39] months; 22 [61%] boys). The groups did not differ in sex distribution; participants with ASD or TD had similar chronological age; and participants with ASD or DD had similar verbal IQ and nonverbal IQ. After training, the ASD group showed preference for the high-value nonsocial stimuli (mean proportion, 0.61 [95% CI, 0.56-0.65]; P < .001) but not for the high-value social stimuli (mean proportion, 0.51 [95% CI, 0.46-0.56]; P = .58). In contrast, the DD and TD groups demonstrated preference for the high-value social stimuli (DD mean proportion, 0.59 [95% CI, 0.54-0.64]; P = .001 and TD mean proportion, 0.57 [95% CI, 0.53-0.61]; P = .002) but not for the high-value nonsocial stimuli (DD mean proportion, 0.52 [95% CI, 0.44-0.59]; P = .64 and TD mean proportion, 0.50 [95% CI, 0.44-0.57]; P = .91). Controlling for age and nonverbal IQ, autism severity was positively correlated with enhanced learning in the nonsocial domain (r = 0.22; P = .03) and with poorer learning in the social domain (r = -0.26; P = .01). Conclusions and Relevance Increased attention to objects in preschoolers with ASD may be associated with enhanced VL in the nonsocial domain. When paired with poor VL in the social domain, enhanced value-driven attention to objects may play a formative role in the emergence of autism symptoms by altering attentional priorities and thus learning opportunities in affected children.
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Affiliation(s)
- Quan Wang
- Child Study Center, Yale School of Medicine, New Haven, Connecticut
- Key Laboratory of Spectral Imaging Technology, Key Laboratory of Biomedical Spectroscopy of Xi’an, Xi’an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences
| | - Joseph Chang
- Child Study Center, Yale School of Medicine, New Haven, Connecticut
- Department of Statistics and Data Science, Yale University, New Haven, Connecticut
| | - Katarzyna Chawarska
- Child Study Center, Yale School of Medicine, New Haven, Connecticut
- Department of Statistics and Data Science, Yale University, New Haven, Connecticut
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29
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Levin AR, Naples AJ, Scheffler AW, Webb SJ, Shic F, Sugar CA, Murias M, Bernier RA, Chawarska K, Dawson G, Faja S, Jeste S, Nelson CA, McPartland JC, Şentürk D. Day-to-Day Test-Retest Reliability of EEG Profiles in Children With Autism Spectrum Disorder and Typical Development. Front Integr Neurosci 2020; 14:21. [PMID: 32425762 PMCID: PMC7204836 DOI: 10.3389/fnint.2020.00021] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 03/23/2020] [Indexed: 01/11/2023] Open
Abstract
Biomarker development is currently a high priority in neurodevelopmental disorder research. For many types of biomarkers (particularly biomarkers of diagnosis), reliability over short periods is critically important. In the field of autism spectrum disorder (ASD), resting electroencephalography (EEG) power spectral densities (PSD) are well-studied for their potential as biomarkers. Classically, such data have been decomposed into pre-specified frequency bands (e.g., delta, theta, alpha, beta, and gamma). Recent technical advances, such as the Fitting Oscillations and One-Over-F (FOOOF) algorithm, allow for targeted characterization of the features that naturally emerge within an EEG PSD, permitting a more detailed characterization of the frequency band-agnostic shape of each individual's EEG PSD. Here, using two resting EEGs collected a median of 6 days apart from 22 children with ASD and 25 typically developing (TD) controls during the Feasibility Visit of the Autism Biomarkers Consortium for Clinical Trials, we estimate test-retest reliability based on the characterization of the PSD shape in two ways: (1) Using the FOOOF algorithm we estimate six parameters (offset, slope, number of peaks, and amplitude, center frequency and bandwidth of the largest alpha peak) that characterize the shape of the EEG PSD; and (2) using nonparametric functional data analyses, we decompose the shape of the EEG PSD into a reduced set of basis functions that characterize individual power spectrum shapes. We show that individuals exhibit idiosyncratic PSD signatures that are stable over recording sessions using both characterizations. Our data show that EEG activity from a brief 2-min recording provides an efficient window into characterizing brain activity at the single-subject level with desirable psychometric characteristics that persist across different analytical decomposition methods. This is a necessary step towards analytical validation of biomarkers based on the EEG PSD and provides insights into parameters of the PSD that offer short-term reliability (and thus promise as potential biomarkers of trait or diagnosis) vs. those that are more variable over the short term (and thus may index state or other rapidly dynamic measures of brain function). Future research should address the longer-term stability of the PSD, for purposes such as monitoring development or response to treatment.
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Affiliation(s)
- April R. Levin
- Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Adam J. Naples
- Child Study Center, School of Medicine, Yale University, New Haven, CT, United States
| | - Aaron Wolfe Scheffler
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
| | - Sara J. Webb
- Center for Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | - Frederick Shic
- Center for Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Catherine A. Sugar
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Michael Murias
- Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, United States
| | - Raphael A. Bernier
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | - Katarzyna Chawarska
- Child Study Center, School of Medicine, Yale University, New Haven, CT, United States
| | - Geraldine Dawson
- Duke Institute for Brain Sciences, Duke University, Durham, NC, United States
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
| | - Susan Faja
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Shafali Jeste
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Charles A. Nelson
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - James C. McPartland
- Child Study Center, School of Medicine, Yale University, New Haven, CT, United States
| | - Damla Şentürk
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
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McPartland JC, Bernier RA, Jeste SS, Dawson G, Nelson CA, Chawarska K, Earl R, Faja S, Johnson SP, Sikich L, Brandt CA, Dziura JD, Rozenblit L, Hellemann G, Levin AR, Murias M, Naples AJ, Platt ML, Sabatos-DeVito M, Shic F, Senturk D, Sugar CA, Webb SJ. The Autism Biomarkers Consortium for Clinical Trials (ABC-CT): Scientific Context, Study Design, and Progress Toward Biomarker Qualification. Front Integr Neurosci 2020; 14:16. [PMID: 32346363 PMCID: PMC7173348 DOI: 10.3389/fnint.2020.00016] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 03/10/2020] [Indexed: 12/19/2022] Open
Abstract
Clinical research in neurodevelopmental disorders remains reliant upon clinician and caregiver measures. Limitations of these approaches indicate a need for objective, quantitative, and reliable biomarkers to advance clinical research. Extant research suggests the potential utility of multiple candidate biomarkers; however, effective application of these markers in trials requires additional understanding of replicability, individual differences, and intra-individual stability over time. The Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is a multi-site study designed to investigate a battery of electrophysiological (EEG) and eye-tracking (ET) indices as candidate biomarkers for autism spectrum disorder (ASD). The study complements published biomarker research through: inclusion of large, deeply phenotyped cohorts of children with ASD and typical development; a longitudinal design; a focus on well-evidenced candidate biomarkers harmonized with an independent sample; high levels of clinical, regulatory, technical, and statistical rigor; adoption of a governance structure incorporating diverse expertise in the ASD biomarker discovery and qualification process; prioritization of open science, including creation of a repository containing biomarker, clinical, and genetic data; and use of economical and scalable technologies that are applicable in developmental populations and those with special needs. The ABC-CT approach has yielded encouraging results, with one measure accepted into the FDA’s Biomarker Qualification Program to date. Through these advances, the ABC-CT and other biomarker studies in progress hold promise to deliver novel tools to improve clinical trials research in ASD.
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Affiliation(s)
| | - Raphael A Bernier
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle Children's Hospital, Seattle, WA, United States.,Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
| | - Shafali S Jeste
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Charles A Nelson
- Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Harvard University, Boston, MA, United States
| | | | - Rachel Earl
- Center on Human Development and Disability, University of Washington, Seattle, WA, United States
| | - Susan Faja
- Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Harvard University, Boston, MA, United States
| | - Scott P Johnson
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Linmarie Sikich
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | | | | | | | - Gerhard Hellemann
- University of California, Los Angeles, Los Angeles, CA, United States
| | - April R Levin
- Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Harvard University, Boston, MA, United States
| | | | - Adam J Naples
- Yale Child Study Center, New Haven, CT, United States
| | | | - Maura Sabatos-DeVito
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle Children's Hospital, Seattle, WA, United States.,Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, United States
| | - Damla Senturk
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Catherine A Sugar
- University of California, Los Angeles, Los Angeles, CA, United States
| | - Sara J Webb
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle Children's Hospital, Seattle, WA, United States.,Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
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Shic F, Wang Q, Macari SL, Chawarska K. The role of limited salience of speech in selective attention to faces in toddlers with autism spectrum disorders. J Child Psychol Psychiatry 2020; 61:459-469. [PMID: 31471912 PMCID: PMC7048639 DOI: 10.1111/jcpp.13118] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/15/2019] [Indexed: 12/31/2022]
Abstract
BACKGROUND Impaired attention to faces of interactive partners is a marker for autism spectrum disorder (ASD) in early childhood. However, it is unclear whether children with ASD avoid faces or find them less salient and whether the phenomenon is linked with the presence of eye contact or speech. METHODS We investigated the impacts of speech (SP) and direct gaze (DG) on attention to faces in 22-month-old toddlers with ASD (n = 50) and typically developing controls (TD, n = 47) using the Selective Social Attention 2.0 (SSA 2.0) task. The task consisted of four conditions where the presence (+) and absence (-) of DG and SP were systematically manipulated. The severity of autism symptoms, and verbal and nonverbal skills were characterized concurrently with eye tracking at 22.4 (SD = 3.2) months and prospectively at 39.8 (SD = 4.3) months. RESULTS Toddlers with ASD looked less than TD toddlers at face and mouth regions only when the actress was speaking (direct gaze absence with speech, DG-SP+: d = 0.99, p < .001 for face, d = 0.98, p < .001 for mouth regions; direct gaze present with speech, DG+SP+, d = 1.47, p < .001 for face, d = 1.01, p < .001 for mouth regions). Toddlers with ASD looked less at the eye region only when both gaze and speech cues were present (d = 0.46, p = .03). Salience of the combined DG and SP cues was associated concurrently and prospectively with the severity of autism symptoms, and the association remained significant after controlling for verbal and nonverbal levels. CONCLUSIONS The study links poor attention to faces with limited salience of audiovisual speech and provides no support for the face avoidance hypothesis in the early stages of ASD. These results are consequential for research on early discriminant and predictive biomarkers as well as identification of novel treatment targets.
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Affiliation(s)
- Frederick Shic
- Yale School of Medicine, Child Study Center; 40 Temple St Ste 7D; New Haven, CT 06510
- Seattle Children’s Research Institute, Center for Child Health, Behavior and Development; 2001 8 Ave Ste 400; Seattle, WA 98121
- Univeristy of Washington School of Medicine, Department of Pediatrics; 2001 8 Ave Ste 400; Seattle, WA 98121
| | - Quan Wang
- Yale School of Medicine, Child Study Center; 40 Temple St Ste 7D; New Haven, CT 06510
| | - Suzanne L. Macari
- Yale School of Medicine, Child Study Center; 40 Temple St Ste 7D; New Haven, CT 06510
| | - Katarzyna Chawarska
- Yale School of Medicine, Child Study Center; 40 Temple St Ste 7D; New Haven, CT 06510
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32
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Webb SJ, Shic F, Murias M, Sugar CA, Naples AJ, Barney E, Borland H, Hellemann G, Johnson S, Kim M, Levin AR, Sabatos-DeVito M, Santhosh M, Senturk D, Dziura J, Bernier RA, Chawarska K, Dawson G, Faja S, Jeste S, McPartland J. Biomarker Acquisition and Quality Control for Multi-Site Studies: The Autism Biomarkers Consortium for Clinical Trials. Front Integr Neurosci 2020; 13:71. [PMID: 32116579 PMCID: PMC7020808 DOI: 10.3389/fnint.2019.00071] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 11/28/2019] [Indexed: 12/31/2022] Open
Abstract
The objective of the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is to evaluate a set of lab-based behavioral video tracking (VT), electroencephalography (EEG), and eye tracking (ET) measures for use in clinical trials with children with autism spectrum disorder (ASD). Within the larger organizational structure of the ABC-CT, the Data Acquisition and Analytic Core (DAAC) oversees the standardization of VT, EEG, and ET data acquisition, data processing, and data analysis. This includes designing and documenting data acquisition and analytic protocols and manuals; facilitating site training in acquisition; data acquisition quality control (QC); derivation and validation of dependent variables (DVs); and analytic deliverables including preparation of data for submission to the National Database for Autism Research (NDAR). To oversee consistent application of scientific standards and methodological rigor for data acquisition, processing, and analytics, we developed standard operating procedures that reflect the logistical needs of multi-site research, and the need for well-articulated, transparent processes that can be implemented in future clinical trials. This report details the methodology of the ABC-CT related to acquisition and QC in our Feasibility and Main Study phases. Based on our acquisition metrics from a preplanned interim analysis, we report high levels of acquisition success utilizing VT, EEG, and ET experiments in a relatively large sample of children with ASD and typical development (TD), with data acquired across multiple sites and use of a manualized training and acquisition protocol.
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Affiliation(s)
- Sara Jane Webb
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
| | - Frederick Shic
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, United States
| | - Michael Murias
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Catherine A. Sugar
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Statistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Adam J. Naples
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - Erin Barney
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Heather Borland
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Gerhard Hellemann
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Scott Johnson
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Minah Kim
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - April R. Levin
- Department of Neurology, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Harvard University, Boston, MA, United States
| | - Maura Sabatos-DeVito
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Megha Santhosh
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Damla Senturk
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Statistics, University of California, Los Angeles, Los Angeles, CA, United States
| | - James Dziura
- Yale Child Study Center, Yale University, New Haven, CT, United States
| | - Raphael A. Bernier
- Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, United States
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
- Center on Human Development and Disability, University of Washington, Seattle, WA, United States
| | | | - Geraldine Dawson
- Duke Center for Autism and Brain Development, Duke University, Durham, NC, United States
| | - Susan Faja
- Harvard Medical School, Harvard University, Boston, MA, United States
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, United States
| | - Shafali Jeste
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, United States
| | - James McPartland
- Yale Child Study Center, Yale University, New Haven, CT, United States
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33
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McDonald NM, Senturk D, Scheffler A, Brian JA, Carver LJ, Charman T, Chawarska K, Curtin S, Hertz-Piccioto I, Jones EJH, Klin A, Landa R, Messinger DS, Ozonoff S, Stone WL, Tager-Flusberg H, Webb SJ, Young G, Zwaigenbaum L, Jeste SS. Developmental Trajectories of Infants With Multiplex Family Risk for Autism: A Baby Siblings Research Consortium Study. JAMA Neurol 2020; 77:73-81. [PMID: 31589284 PMCID: PMC6784852 DOI: 10.1001/jamaneurol.2019.3341] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Accepted: 08/18/2019] [Indexed: 01/01/2023]
Abstract
Importance Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with different genetic etiologies. Prospective examination of familial-risk infants informs understanding of developmental trajectories preceding ASD diagnosis, potentially improving early detection. Objective To compare outcomes and trajectories associated with varying familial risk for ASD across the first 3 years of life. Design, Setting, and Participants This longitudinal, prospective cohort study used data from 11 sites in the Baby Siblings Research Consortium database. Data were collected between 2003 and 2015. Infants who were younger siblings of children with ASD were followed up for 3 years. Analyses were conducted in April 2018. Of the initial 1008 infants from the database, 573 were removed owing to missing necessary data, diagnostic discrepancies, or only having 1 older sibling. Exposures Number of siblings with ASD. Main Outcomes and Measures Outcomes included ASD symptoms, cognitive abilities, and adaptive skills. Diagnosis (ASD or no ASD) was given at 36-month outcome. The no-ASD group was classified as atypical (developmental delays and/or social-communication concerns) or typical for some analyses. Generalized linear mixed models examined developmental trajectories by ASD outcome and familial-risk group. Results In the 435 analyzed participants (age range at outcome, 32-43 months; 246 male [57%]), 355 (82%) were from single-incidence families (1 sibling with ASD and ≥1 sibling without ASD) and 80 (18%) were from multiplex families (≥2 siblings with ASD). There were no significant group differences in major demographics. Children from multiplex families were more likely than those from single-incidence families to be classified as having ASD (29 of 80 [36%] vs 57 of 355 [16%]; 95% CI, 9%-31%; P < .001) and less likely as typical (26 of 80 [33%] vs 201 of 355 [57%]; 95% CI, -36% to -13%; P < .001), with similar rates of atypical classifications (25 of 80 [31%] vs 97 of 355 [27%]; 95% CI, -7% to 15%; P = .49). There were no differences in ASD symptoms between multiplex and single-incidence groups after controlling for ASD outcome (95% CI, -0.02 to 0.20; P = .18). During infancy, differences in cognitive and adaptive abilities were observed based on ASD outcome in the single-incidence group only. At 36 months, the multiplex/no-ASD group had lower cognitive abilities than the single-incidence/no-ASD group (95% CI, -11.89 to -2.20; P = .02), and the multiplex group had lower adaptive abilities than individuals in the single-incidence group after controlling for ASD outcome (95% CI, -9.01 to -1.48; P = .02). Conclusions and Relevance Infants with a multiplex family history of ASD should be monitored early and often and referred for early intervention at the first sign of concern. Direct examination of genetic contributions to neurodevelopmental phenotypes in infants with familial risk for ASD is needed.
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Affiliation(s)
- Nicole M. McDonald
- Semel Institute for Neuroscience & Human Behavior, University of California, Los Angeles, Los Angeles
| | - Damla Senturk
- Department of Biostatistics, University of California, Los Angeles, Los Angeles
| | - Aaron Scheffler
- Department of Biostatistics, University of California, Los Angeles, Los Angeles
- now with Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco
| | - Jessica A. Brian
- Holland Bloorview Kids Rehabilitation Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Leslie J. Carver
- Department of Psychology, University of California, San Diego, La Jolla
| | - Tony Charman
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Katarzyna Chawarska
- Child Study Center, Yale University School of Medicine, New Haven, Connecticut
| | - Suzanne Curtin
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
| | - Irva Hertz-Piccioto
- MIND Institute, Department of Public Health Sciences, University of California, Davis, Davis
| | - Emily J. H. Jones
- Centre for Brain & Cognitive Development, Birkbeck, University of London, London, United Kingdom
| | - Ami Klin
- Marcus Autism Center, Emory University School of Medicine and Children’s Healthcare of Atlanta, Atlanta, Georgia
| | - Rebecca Landa
- Center for Autism and Related Disorders, Kennedy Krieger Institute, Baltimore, Maryland
| | - Daniel S. Messinger
- Department of Psychology, University of Miami, Coral Gables, Florida
- Department of Pediatrics, University of Miami, Coral Gables, Florida
- Department of Electrical & Computer Engineering, University of Miami, Coral Gables, Florida
- Department of Music Engineering, University of Miami, Coral Gables, Florida
| | - Sally Ozonoff
- MIND Institute, Department of Psychiatry and Behavioral Sciences, University of California, Davis, Sacramento
| | - Wendy L. Stone
- Department of Psychology, University of Washington, Seattle
| | - Helen Tager-Flusberg
- Department of Psychology & Brain Sciences, Boston University, Boston, Massachusetts
| | - Sara Jane Webb
- Psychiatry and Behavioral Sciences, University of Washington, Seattle
| | - Gregory Young
- MIND Institute, Department of Psychiatry and Behavioral Sciences, University of California, Davis, Sacramento
| | - Lonnie Zwaigenbaum
- Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada
- Department of Psychiatry, University of Alberta, Edmonton, Alberta, Canada
| | - Shafali S. Jeste
- Semel Institute for Neuroscience & Human Behavior, University of California, Los Angeles, Los Angeles
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Wang Q, Wall CA, Barney EC, Bradshaw JL, Macari SL, Chawarska K, Shic F. Promoting social attention in 3-year-olds with ASD through gaze-contingent eye tracking. Autism Res 2020; 13:61-73. [PMID: 31468735 PMCID: PMC7256927 DOI: 10.1002/aur.2199] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Revised: 06/11/2019] [Accepted: 07/21/2019] [Indexed: 12/15/2022]
Abstract
Young children with autism spectrum disorder (ASD) look less toward faces compared to their non-ASD peers, limiting access to social learning. Currently, no technologies directly target these core social attention difficulties. This study examines the feasibility of automated gaze modification training for improving attention to faces in 3-year-olds with ASD. Using free-viewing data from typically developing (TD) controls (n = 41), we implemented gaze-contingent adaptive cueing to redirect children with ASD toward normative looking patterns during viewing of videos of an actress. Children with ASD were randomly assigned to either (a) an adaptive Cue condition (Cue, n = 16) or (b) a No-Cue condition (No-Cue, n = 19). Performance was examined at baseline, during training, and post-training, and contrasted with TD controls (n = 23). Proportion of time looking at the screen (%Screen) and at actresses' faces (%Face) was analyzed. At Pre-Training, Cue and No-Cue groups did not differ in %Face (P > 0.1). At Post-Training, the Cue group had higher %Face than the No-Cue group (P = 0.015). In the No-Cue group %Face decreased Pre- to Post-Training; no decline was observed in the Cue group. These results suggest gaze-contingent training effectively mitigated decreases of attention toward the face of onscreen social characters in ASD. Additionally, larger training effects were observed in children with lower nonverbal ability, suggesting a gaze-contingent approach may be particularly relevant for children with greater cognitive impairment. This work represents development toward new social attention therapeutic systems that could augment current behavioral interventions. Autism Res 2020, 13: 61-73. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: In this study, we leverage a new technology that combines eye tracking and automatic computer programs to help very young children with ASD look at social information in a more prototypical way. In a randomized controlled trial, we show that the use of this technology prevents the diminishing attention toward social information normally seen in children with ASD over the course of a single experimental session. This work represents development toward new social attention therapeutic systems that could augment current behavioral interventions.
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Affiliation(s)
- Quan Wang
- Child Study Center, School of Medicine, Yale University, New Haven, Connecticut
| | - Carla A Wall
- Department of School Psychology, University of South Carolina, Columbia, South Carolina
| | - Erin C Barney
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, Washington
| | - Jessica L Bradshaw
- Department of Psychology, University of South Carolina, Columbia, South Carolina
| | - Suzanne L Macari
- Child Study Center, School of Medicine, Yale University, New Haven, Connecticut
| | - Katarzyna Chawarska
- Child Study Center, School of Medicine, Yale University, New Haven, Connecticut
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, Washington
- Department of Pediatrics, University of Washington, Seattle, Washington
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35
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Sabatos-DeVito M, Murias M, Dawson G, Howell T, Yuan A, Marsan S, Bernier RA, Brandt CA, Chawarska K, Dzuira JD, Faja S, Jeste SS, Naples A, Nelson CA, Shic F, Sugar CA, Webb SJ, McPartland JC. Methodological considerations in the use of Noldus EthoVision XT video tracking of children with autism in multi-site studies. Biol Psychol 2019; 146:107712. [PMID: 31163191 PMCID: PMC7334026 DOI: 10.1016/j.biopsycho.2019.05.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 04/02/2019] [Accepted: 05/31/2019] [Indexed: 11/19/2022]
Abstract
Animal models of autism spectrum disorders (ASD) contribute to understanding of the role of genetics and the biological mechanisms underlying behavioral phenotypes and inform the development of potential treatments. Translational biomarkers are needed that can both validate these models and facilitate behavioral testing paradigms for ASD in humans. Automated video tracking of movement patterns and positions recorded from overhead cameras is routinely applied in behavioral paradigms designed to elicit core behavioral manifestations of ASD in rodent models. In humans, laboratory-based observations are a common semi-naturalistic context for assessing a variety of behaviors relevant to ASD such as social engagement, play, and attention. We present information learned and suggest guidelines for designing, recording, acquiring, and evaluating video tracking data of human movement patterns based on our experience in a multi-site video tracking study of children with ASD in the context of a parent-child, laboratory-based play interaction.
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Affiliation(s)
- Maura Sabatos-DeVito
- Department of Psychiatry and Behavioral Sciences, Duke Center for Autism and Brain Development, Duke University Medical Center, Durham, NC, USA.
| | - Michael Murias
- Duke Institute for Brain Sciences, Duke University Medical Center, Durham, NC, USA
| | - Geraldine Dawson
- Department of Psychiatry and Behavioral Sciences, Duke Center for Autism and Brain Development, Duke University Medical Center, Durham, NC, USA
| | - Toni Howell
- Department of Psychiatry and Behavioral Sciences, Duke Center for Autism and Brain Development, Duke University Medical Center, Durham, NC, USA
| | - Andrew Yuan
- Department of Psychiatry and Behavioral Sciences, Duke Center for Autism and Brain Development, Duke University Medical Center, Durham, NC, USA
| | - Samuel Marsan
- Department of Psychiatry and Behavioral Sciences, Duke Center for Autism and Brain Development, Duke University Medical Center, Durham, NC, USA
| | - Raphael A Bernier
- Department of Psychiatry, University of Washington, Seattle, WA, USA
| | | | | | - James D Dzuira
- Department of Emergency Medicine, Yale Center for Analytical Sciences, Yale University, CT, USA
| | - Susan Faja
- Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Shafali S Jeste
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, USA
| | - Adam Naples
- Yale University School of Medicine, Child Study Center, New Haven, CT, USA
| | - Charles A Nelson
- Boston Children's Hospital and Harvard Medical School, Boston, MA, USA; Harvard Graduate School of Education, Boston, MA, USA
| | - Frederick Shic
- University of Washington and Seattle Children's Research Institute Center for Child Behavior, Health, and Development, Seattle, WA, USA
| | - Catherine A Sugar
- Departments of Biostatistics, Statistics and Psychiatry, University of California, Los Angeles, CA, USA
| | - Sara J Webb
- University of Washington and Seattle Children's Research Institute Center for Child Behavior, Health, and Development, Seattle, WA, USA
| | - James C McPartland
- Yale University School of Medicine, Child Study Center, New Haven, CT, USA.
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36
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Macari SL, Wu GC, Powell KK, Fontenelle S, Macris DM, Chawarska K. Do Parents and Clinicians Agree on Ratings of Autism-Related Behaviors at 12 Months of Age? A Study of Infants at High and Low Risk for ASD. J Autism Dev Disord 2019; 48:1069-1080. [PMID: 29181689 DOI: 10.1007/s10803-017-3410-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Given the emphasis on early screening for ASD, it is crucial to examine the concordance between parent report and clinician observation of autism-related behaviors. Similar items were compared from the First Year Inventory (Baranek et al. First-Year Inventory (FYI) 2.0. University of North Carolina, Chapel Hill, 2003), a parent screener for ASD, and the ADOS-2 Toddler Module (Lord et al. 2013), a standardized ASD diagnostic tool. Measures were administered concurrently to 12-month-olds at high and low risk for ASD. Results suggest that clinicians and parents rated behaviors similarly. In addition, both informants rated high-risk infants as more impaired in several social-communication behaviors. Furthermore, the format of questions impacted agreement across observers. These findings have implications for the development of a new generation of screening instruments for ASD.
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Affiliation(s)
- Suzanne L Macari
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA.
| | - Grace C Wu
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
- Stanford University, Stanford, CA, USA
| | - Kelly K Powell
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Scuddy Fontenelle
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Deanna M Macris
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
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37
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Iverson JM, Shic F, Wall CA, Chawarska K, Curtin S, Estes A, Gardner JM, Hutman T, Landa RJ, Levin AR, Libertus K, Messinger DS, Nelson CA, Ozonoff S, Sacrey LAR, Sheperd K, Stone WL, Tager-Flusberg HB, Wolff JJ, Yirmiya N, Young GS. Early motor abilities in infants at heightened versus low risk for ASD: A Baby Siblings Research Consortium (BSRC) study. J Abnorm Psychol 2019; 128:69-80. [PMID: 30628809 DOI: 10.1037/abn0000390] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Research has identified early appearing differences in gross and fine motor abilities in infants at heightened risk (HR) for autism spectrum disorder (ASD) because they are the younger siblings of children with ASD, and it suggests that such differences may be especially apparent among those HR infants themselves eventually diagnosed with ASD. The present study examined overall and item-level performance on the gross (GM) and fine motor (FM) subscales of the Mullen Scales of Early Learning (MSEL) administered at 6 months to a large, geographically diverse sample of HR infants with varying developmental outcomes (ASD, elevated ADOS without ASD, low ADOS without ASD) and to infants with low ASD risk (low risk [LR]). We also explored whether motor abilities assessed at 6 months predicted ASD symptom severity at 36 months. FM (but not GM) performance distinguished all 3 HR groups from LR infants with the weakest performance observed in the HR-Elevated ADOS children, who exhibited multiple differences from both LR and other HR infants in both gross and fine motor skills. Finally, 6-month FM (but not GM) scores significant predicted 36-month ADOS severity scores in the HR group; but no evidence was found of specific early appearing motor signs associated with a later ASD diagnosis. Vulnerabilities in infants' fine and gross motor skills may have significant consequences for later development not only in the motor domain but in other domains. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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Affiliation(s)
| | | | - Carla A Wall
- Department of Psychology, University of South Carolina
| | | | | | - Annette Estes
- Department of Speech & Hearing Sciences, University of Washington
| | | | - Ted Hutman
- Department of Psychiatry, University of California, Los Angeles
| | | | | | | | | | - Charles A Nelson
- Boston Children's Hospital and Graduate School of Education, Harvard University
| | | | | | | | | | | | - Jason J Wolff
- Department of Educational Psychology, University of Minnesota
| | - Nurit Yirmiya
- Psychology Department, Hebrew University of Jerusalem
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38
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Macari S, DiNicola L, Kane-Grade F, Prince E, Vernetti A, Powell K, Fontenelle S, Chawarska K. Emotional Expressivity in Toddlers With Autism Spectrum Disorder. J Am Acad Child Adolesc Psychiatry 2018; 57:828-836.e2. [PMID: 30392624 PMCID: PMC6844292 DOI: 10.1016/j.jaac.2018.07.872] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 06/23/2018] [Accepted: 07/06/2018] [Indexed: 12/28/2022]
Abstract
OBJECTIVE There is a prevailing notion that children with autism spectrum disorder (ASD) exhibit intense negative and attenuated positive emotions, although the empirical evidence regarding their emotional expressiveness (EE) is limited. Given the importance of emotions in shaping social and cognitive development, we examined intensity and valence of EE and links between EE and autism severity and parent-reported temperament in ASD. METHOD Toddlers (aged 21.2 months) with ASD (n = 43), developmental delay (DD, n = 16), and typical development (TD, n = 40) underwent standardized probes designed to induce anger, joy, and fear. Intensity of EE through facial and vocal channels were coded offline. Autism severity and temperament were quantified using the Autism Diagnostic Observation Schedule-2 (ADOS-2) and Early Childhood Behavior Questionnaire (ECBQ). RESULTS The ASD group exhibited less intense fear compared to both the DD and TD groups, more intense anger than DD but not TD, with no differences in joy intensity. All groups showed similar levels of incongruous negative EE. Intensity of fear and anger were not associated with severity of autism symptoms, but lower intensity of joy was related to greater autism severity. Expressed fear and joy were associated with temperament. CONCLUSION The study provides no support for a negative emotionality bias in ASD. Instead, toddlers with ASD display a muted response to threat and an accentuated response to goal blockage, whereas the ability to express positive emotions appears intact. Negative emotionality and social disability dimensions are independent. The study demonstrates the complexity of EE in ASD and motivates investigations into underlying mechanisms as well as its role in shaping complex phenotypes of affected children.
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Øien RA, Schjølberg S, Volkmar FR, Shic F, Cicchetti DV, Nordahl-Hansen A, Stenberg N, Hornig M, Havdahl A, Øyen AS, Ventola P, Susser ES, Eisemann MR, Chawarska K. Clinical Features of Children With Autism Who Passed 18-Month Screening. Pediatrics 2018; 141:e20173596. [PMID: 29784756 DOI: 10.1542/peds.2017-3596] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/05/2018] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVES We compared sex-stratified developmental and temperamental profiles at 18 months in children screening negative for autism spectrum disorder (ASD) on the Modified Checklist for Autism in Toddlers (M-CHAT) but later receiving diagnoses of ASD (false-negative group) versus those without later ASD diagnoses (true-negative group). METHODS We included 68 197 screen-negative cases from the Norwegian Mother and Child Cohort Study (49.1% girls). Children were screened by using the 6 critical items of the M-CHAT at 18 months. Groups were compared on domains of the Ages and Stages Questionnaire and the Emotionality Activity Sociability Temperament Survey. RESULTS Despite passing M-CHAT screening at 18 months, children in the false-negative group exhibited delays in social, communication, and motor skills compared with the true-negative group. Differences were more pronounced in girls. However, with regard to shyness, boys in the false-negative group were rated as more shy than their true-negative counterparts, but girls in the false-negative group were rated as less shy than their counterparts in the true-negative group. CONCLUSIONS This is the first study to reveal that children who pass M-CHAT screening at 18 months and are later diagnosed with ASD exhibit delays in core social and communication areas as well as fine motor skills at 18 months. Differences appeared to be more pronounced in girls. With these findings, we underscore the need to enhance the understanding of early markers of ASD in boys and girls, as well as factors affecting parental report on early delays and abnormalities, to improve the sensitivity of screening instruments.
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Affiliation(s)
- Roald A Øien
- Department of Psychology, University of Tromsø - The Arctic University of Norway, Tromsø, Norway;
- Child Study Center, School of Medicine, Yale University, New Haven, Connecticut
| | - Synnve Schjølberg
- Division of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Fred R Volkmar
- Child Study Center, School of Medicine, Yale University, New Haven, Connecticut
| | - Frederick Shic
- Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, Washington
- Department of Pediatrics, School of Medicine, University of Washington, Seattle, Washington
| | - Domenic V Cicchetti
- Child Study Center, School of Medicine, Yale University, New Haven, Connecticut
| | | | - Nina Stenberg
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Mady Hornig
- Department of Epidemiology, and
- Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, New York
| | - Alexandra Havdahl
- Division of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Anne-Siri Øyen
- Division of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Hospital, Oslo, Norway; and
| | - Pamela Ventola
- Child Study Center, School of Medicine, Yale University, New Haven, Connecticut
| | - Ezra S Susser
- Department of Epidemiology, and
- New York State Psychiatric Institute, New York, New York
| | - Martin R Eisemann
- Department of Psychology, University of Tromsø - The Arctic University of Norway, Tromsø, Norway
| | - Katarzyna Chawarska
- Child Study Center, School of Medicine, Yale University, New Haven, Connecticut
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40
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Wang Q, DiNicola L, Heymann P, Hampson M, Chawarska K. Impaired Value Learning for Faces in Preschoolers With Autism Spectrum Disorder. J Am Acad Child Adolesc Psychiatry 2018; 57:33-40. [PMID: 29301667 PMCID: PMC5757250 DOI: 10.1016/j.jaac.2017.10.014] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 09/06/2017] [Accepted: 10/31/2017] [Indexed: 11/26/2022]
Abstract
OBJECTIVE One of the common findings in autism spectrum disorder (ASD) is limited selective attention toward social objects, such as faces. Evidence from both human and nonhuman primate studies suggests that selection of objects for processing is guided by the appraisal of object values. We hypothesized that impairments in selective attention in ASD may reflect a disruption of a system supporting learning about object values in the social domain. METHOD We examined value learning in social (faces) and nonsocial (fractals) domains in preschoolers with ASD (n = 25) and typically developing (TD) controls (n = 28), using a novel value learning task implemented on a gaze-contingent eye-tracking platform consisting of value learning and a selective attention choice test. RESULTS Children with ASD performed more poorly than TD controls on the social value learning task, but both groups performed similarly on the nonsocial task. Within-group comparisons indicated that value learning in TD children was enhanced on the social compared to the nonsocial task, but no such enhancement was seen in children with ASD. Performance in the social and nonsocial conditions was correlated in the ASD but not in the TD group. CONCLUSION The study provides support for a domain-specific impairment in value learning for faces in ASD, and suggests that, in ASD, value learning in social and nonsocial domains may rely on a shared mechanism. These findings have implications both for models of selective social attention deficits in autism and for identification of novel treatment targets.
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Affiliation(s)
- Quan Wang
- Yale School of Medicine, Child Study Center, New Haven, CT
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41
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Abstract
BACKGROUND Although temperament has been recognized as an important contributor to childhood psychopathology, its role in emergent autism spectrum phenotypes is not well understood. This study examined whether toddlers with autism spectrum disorder (ASD) display temperamental vulnerabilities compared to toddlers with other developmental challenges, whether these characteristics are distinct from core autism symptoms, if they are stable over time, and if they contribute to social outcomes in preschool. METHODS Parents of 165 toddlers with ASD, 58 nonverbal ability- and chronological age- (CA) matched developmentally delayed (DD) toddlers, and 92 CA-matched typically developing (TD) toddlers completed the Toddler Behavior Assessment Questionnaire-Supplemental (TBAQ-S) at 26 months (SD = 6; Time 1). TBAQ-S data were also available for a subset of toddlers with ASD (n = 126) at 43 months (SD = 9; Time 2). RESULTS Compared to the DD and TD groups, toddlers with ASD exhibited vulnerabilities within the Effortful Control domain as well as the Surgency domain. They also displayed greater Negative Emotionality compared to TD peers. In the ASD group, temperamental characteristics were not concurrently related to autism severity or developmental level and individual differences were highly stable over time. Changes in Perceptual Sensitivity, Inhibitory Control, and Low-Intensity Pleasure from age 2 to 3.5 uniquely predicted autism symptom severity and adaptive social skill level at Time 2. CONCLUSIONS Temperamental vulnerabilities in toddlers with ASD are stable over time and involve attentional and behavioral control as well as affective reactivity. They contribute uniquely to social outcomes in preschool and are likely to signal risk for developing later maladaptive attentional, affective, and behavioral symptoms. Considering biologically based dimensions may shed light on noncore facets of the early ASD phenotype that are potentially relevant to the emergence of comorbid conditions later in childhood.
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Affiliation(s)
- Suzanne L Macari
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Judah Koller
- School of Education, Hebrew University of Jerusalem, Jerusalem, Israel
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42
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Øien RA, Hart L, Schjølberg S, Wall CA, Kim ES, Nordahl-Hansen A, Eisemann MR, Chawarska K, Volkmar FR, Shic F. Parent-Endorsed Sex Differences in Toddlers with and Without ASD: Utilizing the M-CHAT. J Autism Dev Disord 2017; 47:126-134. [PMID: 27757737 PMCID: PMC5222910 DOI: 10.1007/s10803-016-2945-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Sex differences in typical development can provide context for understanding ASD. Baron-Cohen (Trends Cogn Sci 6(6):248-254, 2002) suggested ASD could be considered an extreme expression of normal male, compared to female, phenotypic profiles. In this paper, sex-specific M-CHAT scores from N = 53,728 18-month-old toddlers, including n = 185 (32 females) with ASD, were examined. Results suggest a nuanced view of the "extreme male brain theory of autism". At an item level, almost every male versus female disadvantage in the broader population was consistent with M-CHAT vulnerabilities in ASD. However, controlling for total M-CHAT failures, this male disadvantage was more equivocal and many classically ASD-associated features were found more common in non-ASD. Within ASD, females showed relative strengths in joint attention, but impairments in imitation.
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Affiliation(s)
- Roald A Øien
- Department of Psychology, UiT - The Arctic University of Norway, PB 6050, N-9037, Tromsø, Norway.
- Child Study Center, Yale School of Medicine, Yale University, New Haven, CT, USA.
| | - Logan Hart
- Department of Psychology, UiT - The Arctic University of Norway, PB 6050, N-9037, Tromsø, Norway
- Child Study Center, Yale School of Medicine, Yale University, New Haven, CT, USA
| | | | - Carla A Wall
- Child Study Center, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Elizabeth S Kim
- Center for Autism Research, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Martin R Eisemann
- Department of Psychology, UiT - The Arctic University of Norway, PB 6050, N-9037, Tromsø, Norway
| | - Katarzyna Chawarska
- Child Study Center, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Fred R Volkmar
- Child Study Center, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Frederick Shic
- Child Study Center, Yale School of Medicine, Yale University, New Haven, CT, USA
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43
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Kim SH, Joseph RM, Frazier JA, O’Shea TM, Chawarska K, Allred EN, Leviton A, Kuban KK. Predictive Validity of the Modified Checklist for Autism in Toddlers (M-CHAT) Born Very Preterm. J Pediatr 2016; 178:101-107.e2. [PMID: 27592094 PMCID: PMC5165696 DOI: 10.1016/j.jpeds.2016.07.052] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Revised: 06/14/2016] [Accepted: 07/29/2016] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To examine the predictive validity of the Modified Checklist for Autism in Toddlers (M-CHAT) administered at age 24 months for autism spectrum disorder (ASD) diagnosed at 10 years of age in a US cohort of 827 extremely low gestational age newborns (ELGANs) followed from birth. STUDY DESIGN We examined the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the M-CHAT in predicting an ASD diagnosis at age 10 years based on gold standard diagnostic instruments. We then assessed how these predictive parameters were affected by sensorimotor and cognitive impairments, socioeconomic status (SES), and emotional/behavioral dysregulation at age 2 years. RESULTS Using standard criteria, the M-CHAT had a sensitivity of 52%, a specificity of 84%, a PPV of 20%, and an NPV of 96%. False-positive and false-negative rates were high among children with hearing and vision impairments. High false-positive rates also were associated with lower SES, motor and cognitive impairments, and emotional/behavioral dysregulation at age 2 years. CONCLUSIONS Among extremely preterm children with ASD, almost one-half were not correctly screened by the M-CHAT at age 2 years. Sensorimotor and cognitive impairments, SES, and emotional/behavioral dysregulation contributed significantly to M-CHAT misclassifications. Clinicians are advised to consider these factors when screening very preterm toddlers for ASD.
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Affiliation(s)
- So Hyun Kim
- Department of Psychiatry, Weill Cornell Medicine, New York, NY.
| | - Robert M. Joseph
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Jean A. Frazier
- Department of Psychiatry and Pediatrics, University of Massachusetts Memorial Health Care and University of Massachusetts Medical School, Boston, MA, USA
| | - Thomas M. O’Shea
- Department of Pediatrics, University of North Carolina, Chapel Hill NC, USA
| | - Katarzyna Chawarska
- Yale Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Elizabeth N Allred
- Boston Children’s Hospital, Boston, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Alan Leviton
- Boston Children’s Hospital, Boston, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Karl K. Kuban
- Department of Pediatrics, Boston Medical Center, Boston, MA, USA
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44
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Charman T, Young GS, Brian J, Carter A, Carver LJ, Chawarska K, Curtin S, Dobkins K, Elsabbagh M, Georgiades S, Hertz-Picciotto I, Hutman T, Iverson JM, Jones EJ, Landa R, Macari S, Messinger DS, Nelson CA, Ozonoff S, Saulnier C, Stone WL, Tager-Flusberg H, Webb SJ, Yirmiya N, Zwaigenbaum L. Non-ASD outcomes at 36 months in siblings at familial risk for autism spectrum disorder (ASD): A baby siblings research consortium (BSRC) study. Autism Res 2016; 10:169-178. [PMID: 27417857 DOI: 10.1002/aur.1669] [Citation(s) in RCA: 93] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2015] [Revised: 04/23/2016] [Accepted: 06/13/2016] [Indexed: 11/06/2022]
Abstract
We characterized developmental outcomes of a large sample of siblings at familial high-risk of autism spectrum disorder (ASD), who themselves did not have ASD (n = 859), and low-risk controls with no family history of ASD (n = 473). We report outcomes at age 3 years using the Mullen Scales of Early Learning, the Autism Diagnostic Observation Schedule (ADOS), the Autism Diagnostic Interview-Revised (ADI-R) and adaptive functioning on the Vineland Adaptive Behavior Scales. Around 11% of high-risk siblings had mild-to-moderate levels of developmental delay, a rate higher than the low-risk controls. The groups did not differ in the proportion of toddlers with mild-to-moderate language delay. Thirty percent of high-risk siblings had elevated scores on the ADOS, double the rate seen in the low-risk controls. High-risk siblings also had higher parent reported levels of ASD symptoms on the ADI-R and lower adaptive functioning on the Vineland. Males were more likely to show higher levels of ASD symptoms and lower levels of developmental ability and adaptive behavior than females across most measures but not mild-to-moderate language delay. Lower maternal education was associated with lower developmental and adaptive behavior outcomes. These findings are evidence for early emerging characteristics related to the "broader autism phenotype" (BAP) previously described in older family members of individuals with ASD. There is a need for ongoing clinical monitoring of high-risk siblings who do not have an ASD by age 3 years, as well as continued follow-up into school age to determine their developmental and behavioral outcomes. Autism Res 2017, 10: 169-178. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Rebecca Landa
- Kennedy Krieger Institute and John Hopkins School of Medicine
| | | | | | - Charles A Nelson
- Harvard Medical School.,Harvard Graduate School of Education.,Boston Children's Hospital
| | | | | | | | | | - Sara Jane Webb
- Emory University School of Medicine.,Seattle Children's Research Institute
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45
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Messinger DS, Young GS, Webb SJ, Ozonoff S, Bryson SE, Carter A, Carver L, Charman T, Chawarska K, Curtin S, Dobkins K, Hertz-Picciotto I, Hutman T, Iverson JM, Landa R, Nelson CA, Stone WL, Tager-Flusberg H, Zwaigenbaum L. Commentary: sex difference differences? A reply to Constantino. Mol Autism 2016; 7:31. [PMID: 27358719 PMCID: PMC4926305 DOI: 10.1186/s13229-016-0093-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 06/06/2016] [Indexed: 11/10/2022] Open
Abstract
Messinger et al. found a 3.18 odds ratio of male to female ASD recurrence in 1241 prospectively followed high-risk (HR) siblings. Among high-risk siblings (with and without ASD), as well as among 583 low-risk controls, girls exhibited higher performance on the Mullen Scales of Early Learning, as well as lower restricted and repetitive behavior severity scores on the Autism Diagnostic Observation Schedule (ADOS) than boys. That is, female-favoring sex differences in developmental performance and autism traits were evident among low-risk and non-ASD high-risk children, as well as those with ASD. Constantino (Mol Autism) suggests that sex differences in categorical ASD outcomes in Messinger et al. should be understood as a female protective effect. We are receptive to Constantino’s (Mol Autism) suggestion, and propose that quantitative sex differences in autism-related features are keys to understanding this female protective effect.
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Affiliation(s)
| | | | - Sara Jane Webb
- Seattle Children's Research Institute, Seattle, USA ; University of Washington, Seattle, USA
| | | | - Susan E Bryson
- Izaak Walton Killam Health Centre, Halifax, Canada ; Dalhousie University, Halifax, Canada
| | - Alice Carter
- University of Massachusetts, Boston, Boston, USA
| | | | | | | | | | | | | | - Ted Hutman
- University of California, Los Angeles, Los Angeles, USA
| | | | - Rebecca Landa
- Kennedy Krieger Institute, Baltimore, USA ; John Hopkins School of Medicine, Baltimore, USA
| | - Charles A Nelson
- Harvard Medical School, Boston, USA ; Harvard Graduate School of Education, Cambridge, USA ; Boston Children's Hospital, Boston, USA
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46
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Chawarska K, Macari S, Powell K, DiNicola L, Shic F. Enhanced Social Attention in Female Infant Siblings at Risk for Autism. J Am Acad Child Adolesc Psychiatry 2016; 55:188-95.e1. [PMID: 26903252 PMCID: PMC5812780 DOI: 10.1016/j.jaac.2015.11.016] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Revised: 11/24/2015] [Accepted: 12/10/2015] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Sexual dimorphism in autism spectrum disorders (ASD) is a well-recognized but poorly understood phenomenon. Females are four times less likely to be diagnosed with ASD than males and, when diagnosed, are more likely to exhibit comorbid anxiety symptoms. One of the key phenotypic features of ASD is atypical attention to socially relevant stimuli. Eye-tracking studies indicate atypical patterns of spontaneous social orienting during the prodromal and early syndromic stages of ASD. However, there have been no studies evaluating sex differences in early social orienting and their potential contribution to later outcomes. METHOD We examined sex differences in social orienting in 6-, 9-, and 12-month-old infants at high genetic risk for ASD (n = 101) and in low-risk controls (n = 61), focusing on neurobehavioral measures of function across a spectrum of autism risk. RESULTS Results suggest that, between 6 and 12 months of age, a period highly consequential for the development of nonverbal social engagement competencies, high-risk females show enhanced attention to social targets, including faces, compared to both high-risk males and low-risk males and females. Greater attention to social targets in high-risk infants was associated with less severe social impairments at 2 years. CONCLUSION The results suggest an alternative expression of autism risk in females, which manifests in infancy as increased attention toward socially relevant stimuli. This increased attention may serve as a female protective factor against ASD by providing increased access to social experiences in early development.
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47
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Abstract
This study examined the latent structure of spontaneous social attention in 11- to 26-month-olds with autism spectrum disorder (ASD, n = 90) and typically developing (n = 79) controls. Application of the joint and individual variance explained decomposition technique revealed that attention was driven by a condition-independent tuning into the dynamic social scenes construct and context-specific constructs capturing selection of the most relevant social features for processing. Gaze behavior in ASD is characterized by a limited tuning into the social scenes and by a selection of atypical targets for processing. While the former may be due to early disruption of the reward circuitry leading to limited appreciation of the behavioral relevance of social information, the latter may represent secondary deficits reflecting limited knowledge about social partners.
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48
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Kim SH, Macari S, Koller J, Chawarska K. Examining the phenotypic heterogeneity of early autism spectrum disorder: subtypes and short-term outcomes. J Child Psychol Psychiatry 2016; 57:93-102. [PMID: 26264996 PMCID: PMC6852790 DOI: 10.1111/jcpp.12448] [Citation(s) in RCA: 105] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/01/2015] [Indexed: 12/18/2022]
Abstract
BACKGROUND Phenotypic heterogeneity among toddlers presenting with ASD symptoms complicates diagnostic considerations and limits our ability to predict long-term outcomes. To address this concern, we sought to identify more homogeneous subgroups within ASD based on toddlers' clinical profiles in the second year of life, evaluating diagnostic stability and clinical outcomes within the subgroups 1-2 years later. METHODS One hundred toddlers referred for suspected ASD underwent comprehensive assessments at 22 months (SD = 3) and 37 months (SD = 4). At 22 months, they were clustered based on symptom severity, developmental skills, and adaptive functioning. Diagnostic stability and clinical outcomes were evaluated within the clusters. RESULTS Four clusters characterized by distinct clinical profiles at the time of the first diagnosis were identified. Diagnostic stability was excellent in 3 out of 4 clusters (93%-100%) and was lowest in the initially least affected cluster (85%). Autism symptom severity was stable, except for one group where it increased over time (16% of the sample). A large proportion of toddlers showed significant improvements in verbal and communication skills. Only a small group (17%) exhibited very low levels of functioning and limited gains over time. CONCLUSIONS Diagnostic stability and developmental progression from the second to third year of life in toddlers with ASD vary depending on their initial early profiles of relative strengths and deficits. Although a small minority of toddlers with more complex clinical presentations may not retain their diagnoses by the age of three, most children continue to exhibit symptoms of autism. Despite limited improvements in symptom severity, many children show significant gains in verbal functioning. Only a small proportion of children (17%) exhibit very limited gains despite intensive intervention. These findings support continued efforts to examine determinants of developmental trajectories including factors mediating and moderating response to treatment.
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Affiliation(s)
- So Hyun Kim
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Suzanne Macari
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | - Judah Koller
- School of Education, Hebrew University of Jerusalem, Jerusalem, Israel
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49
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Ozonoff S, Young GS, Landa RJ, Brian J, Bryson S, Charman T, Chawarska K, Macari SL, Messinger D, Stone WL, Zwaigenbaum L, Iosif AM. Diagnostic stability in young children at risk for autism spectrum disorder: a baby siblings research consortium study. J Child Psychol Psychiatry 2015; 56:988-98. [PMID: 25921776 PMCID: PMC4532646 DOI: 10.1111/jcpp.12421] [Citation(s) in RCA: 222] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/25/2015] [Indexed: 11/27/2022]
Abstract
BACKGROUND The diagnosis of autism spectrum disorder (ASD) made before age 3 has been found to be remarkably stable in clinic- and community-ascertained samples. The stability of an ASD diagnosis in prospectively ascertained samples of infants at risk for ASD due to familial factors has not yet been studied, however. The American Academy of Pediatrics recommends intensive surveillance and screening for this high-risk group, which may afford earlier identification. Therefore, it is critical to understand the stability of an ASD diagnosis made before age 3 in young children at familial risk. METHODS Data were pooled across seven sites of the Baby Siblings Research Consortium. Evaluations of 418 later-born siblings of children with ASD were conducted at 18, 24, and 36 months of age and a clinical diagnosis of ASD or Not ASD was made at each age. RESULTS The stability of an ASD diagnosis at 18 months was 93% and at 24 months was 82%. There were relatively few children diagnosed with ASD at 18 or 24 months whose diagnosis was not confirmed at 36 months. There were, however, many children with ASD outcomes at 36 months who had not yet been diagnosed at 18 months (63%) or 24 months (41%). CONCLUSIONS The stability of an ASD diagnosis in this familial-risk sample was high at both 18 and 24 months of age and comparable with previous data from clinic- and community-ascertained samples. However, almost half of the children with ASD outcomes were not identified as being on the spectrum at 24 months and did not receive an ASD diagnosis until 36 months. Thus, longitudinal follow-up is critical for children with early signs of social-communication difficulties, even if they do not meet diagnostic criteria at initial assessment. A public health implication of these data is that screening for ASD may need to be repeated multiple times in the first years of life. These data also suggest that there is a period of early development in which ASD features unfold and emerge but have not yet reached levels supportive of a diagnosis.
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Affiliation(s)
- Sally Ozonoff
- University of California Davis, MIND Institute, Sacramento, CA, USA
| | - Gregory S. Young
- University of California Davis, MIND Institute, Sacramento, CA, USA
| | | | - Jessica Brian
- Child Development Centre, University of Toronto, Ontario, Canada
| | - Susan Bryson
- Department of Pediatrics, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, UK
| | | | - Suzanne L. Macari
- Child Study Center, Yale University School of Medicine, New Haven, CT, USA
| | | | - Wendy L. Stone
- University of Washington Autism Center, Center on Human Development and Disability, Seattle, WA, USA
| | | | - Ana-Maria Iosif
- University of California Davis, MIND Institute, Sacramento, CA, USA
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50
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Messinger DS, Young GS, Webb SJ, Ozonoff S, Bryson SE, Carter A, Carver L, Charman T, Chawarska K, Curtin S, Dobkins K, Hertz-Picciotto I, Hutman T, Iverson JM, Landa R, Nelson CA, Stone WL, Tager-Flusberg H, Zwaigenbaum L. Early sex differences are not autism-specific: A Baby Siblings Research Consortium (BSRC) study. Mol Autism 2015; 6:32. [PMID: 26045943 PMCID: PMC4455973 DOI: 10.1186/s13229-015-0027-y] [Citation(s) in RCA: 130] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2015] [Accepted: 05/13/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The increased male prevalence of autism spectrum disorder (ASD) may be mirrored by the early emergence of sex differences in ASD symptoms and cognitive functioning. The female protective effect hypothesis posits that ASD recurrence and symptoms will be higher among relatives of female probands. This study examined sex differences and sex of proband differences in ASD outcome and in the development of ASD symptoms and cognitive functioning among the high-risk younger siblings of ASD probands and low-risk children. METHODS Prior to 18 months of age, 1824 infants (1241 high-risk siblings, 583 low-risk) from 15 sites were recruited. Hierarchical generalized linear model (HGLM) analyses of younger sibling and proband sex differences in ASD recurrence among high-risk siblings were followed by HGLM analyses of sex differences and group differences (high-risk ASD, high-risk non-ASD, and low-risk) on the Mullen Scales of Early Learning (MSEL) subscales (Expressive and Receptive Language, Fine Motor, and Visual Reception) at 18, 24, and 36 months and Autism Diagnostic Observation Schedule (ADOS) domain scores (social affect (SA) and restricted and repetitive behaviors (RRB)) at 24 and 36 months. RESULTS Of 1241 high-risk siblings, 252 had ASD outcomes. Male recurrence was 26.7 % and female recurrence 10.3 %, with a 3.18 odds ratio. The HR-ASD group had lower MSEL subscale scores and higher RRB and SA scores than the HR non-ASD group, which had lower MSEL subscale scores and higher RRB scores than the LR group. Regardless of group, males obtained lower MSEL subscale scores, and higher ADOS RRB scores, than females. There were, however, no significant interactions between sex and group on either the MSEL or ADOS. Proband sex did not affect ASD outcome, MSEL subscale, or ADOS domain scores. CONCLUSIONS A 3.2:1 male:female odds ratio emerged among a large sample of prospectively followed high-risk siblings. Sex differences in cognitive performance and repetitive behaviors were apparent not only in high-risk children with ASD, but also in high-risk children without ASD and in low-risk children. Sex differences in young children with ASD do not appear to be ASD-specific but instead reflect typically occurring sex differences seen in children without ASD. Results did not support a female protective effect hypothesis.
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Affiliation(s)
| | | | - Sara Jane Webb
- Seattle Children's Research Institute, Seattle, WA USA ; University of Washington, Seattle, WA USA
| | | | - Susan E Bryson
- Izaak Walton Killam Health Centre, Dalhousie University, Halifax, NS Canada
| | | | | | | | | | | | | | | | - Ted Hutman
- University of California, Los Angeles, CA USA
| | | | - Rebecca Landa
- Kennedy Krieger Institute and John Hopkins School of Medicine, Baltimore, MD USA
| | - Charles A Nelson
- Harvard Medical School, Boston, MA USA ; Harvard Graduate School of Education, Cambridge, UK ; Boston Children's Hospital, Boston, MA USA
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