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Washington AM, Mercer AH, Burrows CA, Dager SR, Elison JT, Estes AM, Grzadzinski R, Lee C, Piven J, Pruett JR, Shen MD, Wilfond B, Wolff J, Zwaigenbaum L, MacDuffie KE. Parent attitudes towards predictive testing for autism in the first year of life. J Neurodev Disord 2024; 16:47. [PMID: 39154179 PMCID: PMC11330042 DOI: 10.1186/s11689-024-09561-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Accepted: 07/17/2024] [Indexed: 08/19/2024] Open
Abstract
BACKGROUND Emerging biomarker technologies (e.g., MRI, EEG, digital phenotyping, eye-tracking) have potential to move the identification of autism into the first year of life. We investigated the perspectives of parents about the anticipated utility and impact of predicting later autism diagnosis from a biomarker-based test in infancy. METHODS Parents of infants were interviewed to ascertain receptiveness and perspectives on early (6-12 months) prediction of autism using emerging biomarker technologies. One group had experience parenting an older autistic child (n=30), and the other had no prior autism parenting experience (n=25). Parent responses were analyzed using inductive qualitative coding methods. RESULTS Almost all parents in both groups were interested in predictive testing for autism, with some stating they would seek testing only if concerned about their infant's development. The primary anticipated advantage of testing was to enable access to earlier intervention. Parents also described the anticipated emotions they would feel in response to test results, actions they might take upon learning their infant was likely to develop autism, attitudes towards predicting a child's future support needs, and the potential impacts of inaccurate prediction. CONCLUSION In qualitative interviews, parents of infants with and without prior autism experience shared their anticipated motivations and concerns about predictive testing for autism in the first year of life. The primary reported motivators for testing-to have more time to prepare and intervene early-could be constrained by familial resources and service availability. Implications for ethical communication of results, equitable early intervention, and future research are discussed.
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Affiliation(s)
| | | | | | | | | | | | | | - Chimei Lee
- University of Minnesota, Minneapolis, MN, USA
| | - Joseph Piven
- University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - John R Pruett
- Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Mark D Shen
- University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Benjamin Wilfond
- University of Washington, Seattle, WA, USA
- Seattle Children's Research Institute, M/S JMB-6, PO Box 5371, Seattle, WA, 98145, USA
| | - Jason Wolff
- University of Minnesota, Minneapolis, MN, USA
| | | | - Katherine E MacDuffie
- University of Washington, Seattle, WA, USA.
- Seattle Children's Research Institute, M/S JMB-6, PO Box 5371, Seattle, WA, 98145, USA.
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2
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Pye K, Jackson H, Iacono T, Shiell A. Economic Evaluation of Early Interventions for Autistic Children: A Scoping Review. J Autism Dev Disord 2024; 54:1691-1711. [PMID: 36914827 DOI: 10.1007/s10803-023-05938-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/16/2023] [Indexed: 03/16/2023]
Abstract
Many autistic children access some form of early intervention, but little is known about the value for money of different programs. We completed a scoping review of full economic evaluations of early interventions for autistic children and/or their families. We identified nine studies and reviewed their methods and quality. Most studies involved behavioral interventions. Two were trial-based, and the others used various modelling methods. Clinical measures were often used to infer dependency levels and quality-adjusted life-years. No family-based or negative outcomes were included. Authors acknowledged uncertain treatment effects. We conclude that economic evaluations in this field are sparse, methods vary, and quality is sometimes poor. Economic research is needed alongside longer-term clinical trials, and outcome measurement in this population requires further exploration.
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Affiliation(s)
- Katherine Pye
- School of Health and Social Development, Deakin University, Geelong, Australia.
| | - Hannah Jackson
- Monash Centre for Health Research and Implementation, Monash University, Melbourne, Australia
| | - Teresa Iacono
- La Trobe Rural Health School, La Trobe University, Bendigo, Australia
| | - Alan Shiell
- School of Psychology and Public Health, La Trobe University, Melbourne, Australia
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3
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Ayoub MJ, Keegan L, Tager-Flusberg H, Gill SV. Neuroimaging Techniques as Descriptive and Diagnostic Tools for Infants at Risk for Autism Spectrum Disorder: A Systematic Review. Brain Sci 2022; 12:602. [PMID: 35624989 PMCID: PMC9139416 DOI: 10.3390/brainsci12050602] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 04/26/2022] [Accepted: 04/27/2022] [Indexed: 02/04/2023] Open
Abstract
Autism Spectrum Disorder (ASD) has traditionally been evaluated and diagnosed via behavioral assessments. However, increasing research suggests that neuroimaging as early as infancy can reliably identify structural and functional differences between autistic and non-autistic brains. The current review provides a systematic overview of imaging approaches used to identify differences between infants at familial risk and without risk and predictive biomarkers. Two primary themes emerged after reviewing the literature: (1) neuroimaging methods can be used to describe structural and functional differences between infants at risk and infants not at risk for ASD (descriptive), and (2) neuroimaging approaches can be used to predict ASD diagnosis among high-risk infants and developmental outcomes beyond infancy (predicting later diagnosis). Combined, the articles highlighted that several neuroimaging studies have identified a variety of neuroanatomical and neurological differences between infants at high and low risk for ASD, and among those who later receive an ASD diagnosis. Incorporating neuroimaging into ASD evaluations alongside traditional behavioral assessments can provide individuals with earlier diagnosis and earlier access to supportive resources.
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Affiliation(s)
- Maria J. Ayoub
- College of Health and Rehabilitation Sciences: Sargent College, Boston University, 635 Commonwealth Avenue, Boston, MA 02215, USA; (M.J.A.); (L.K.)
| | - Laura Keegan
- College of Health and Rehabilitation Sciences: Sargent College, Boston University, 635 Commonwealth Avenue, Boston, MA 02215, USA; (M.J.A.); (L.K.)
| | - Helen Tager-Flusberg
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA;
| | - Simone V. Gill
- College of Health and Rehabilitation Sciences: Sargent College, Boston University, 635 Commonwealth Avenue, Boston, MA 02215, USA; (M.J.A.); (L.K.)
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Grzadzinski R, Amso D, Landa R, Watson L, Guralnick M, Zwaigenbaum L, Deák G, Estes A, Brian J, Bath K, Elison J, Abbeduto L, Wolff J, Piven J. Pre-symptomatic intervention for autism spectrum disorder (ASD): defining a research agenda. J Neurodev Disord 2021; 13:49. [PMID: 34654371 PMCID: PMC8520312 DOI: 10.1186/s11689-021-09393-y] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 09/16/2021] [Indexed: 12/26/2022] Open
Abstract
Autism spectrum disorder (ASD) impacts an individual's ability to socialize, communicate, and interact with, and adapt to, the environment. Over the last two decades, research has focused on early identification of ASD with significant progress being made in understanding the early behavioral and biological markers that precede a diagnosis, providing a catalyst for pre-symptomatic identification and intervention. Evidence from preclinical trials suggest that intervention prior to the onset of ASD symptoms may yield more improved developmental outcomes, and clinical studies suggest that the earlier intervention is administered, the better the outcomes. This article brings together a multidisciplinary group of experts to develop a conceptual framework for behavioral intervention, during the pre-symptomatic period prior to the consolidation of symptoms into diagnosis, in infants at very-high-likelihood for developing ASD (VHL-ASD). The overarching goals of this paper are to promote the development of new intervention approaches, empirical research, and policy efforts aimed at VHL-ASD infants during the pre-symptomatic period (i.e., prior to the consolidation of the defining features of ASD).
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Affiliation(s)
- Rebecca Grzadzinski
- Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC, USA.
- Program for Early Autism Research Leadership and Service (PEARLS), University of North Carolina, Chapel Hill, NC, USA.
| | - Dima Amso
- Department of Psychology, Columbia University, New York, NY, USA
| | - Rebecca Landa
- Center for Autism and Related Disorders, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Linda Watson
- Program for Early Autism Research Leadership and Service (PEARLS), University of North Carolina, Chapel Hill, NC, USA
- Division of Speech and Hearing Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - Michael Guralnick
- Center on Human Development and Disability, University of Washington, Seattle, WA, USA
| | | | - Gedeon Deák
- Department of Cognitive Science, University of California, San Diego, San Diego, CA, USA
| | - Annette Estes
- Department of Speech and Hearing Sciences, University of Washington Autism Center, University of Washington, Seattle, WA, USA
| | - Jessica Brian
- Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
- Department of Paediatrics, University of Toronto, Toronto, Canada
| | - Kevin Bath
- Department of Neuroscience, Brown University, Providence, RI, USA
| | - Jed Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Leonard Abbeduto
- University of California, Davis, MIND Institute, University of California, Davis, Sacramento, CA, USA
| | - Jason Wolff
- Department of Educational Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC, USA
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5
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Tunç B, Pandey J, John TS, Meera SS, Maldarelli JE, Zwaigenbaum L, Hazlett HC, Dager SR, Botteron KN, Girault JB, McKinstry RC, Verma R, Elison JT, Pruett JR, Piven J, Estes AM, Schultz RT. Diagnostic shifts in autism spectrum disorder can be linked to the fuzzy nature of the diagnostic boundary: a data-driven approach. J Child Psychol Psychiatry 2021; 62:1236-1245. [PMID: 33826159 PMCID: PMC8601115 DOI: 10.1111/jcpp.13406] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/06/2021] [Indexed: 01/14/2023]
Abstract
BACKGROUND Diagnostic shifts at early ages may provide invaluable insights into the nature of separation between autism spectrum disorder (ASD) and typical development. Recent conceptualizations of ASD suggest the condition is only fuzzily separated from non-ASD, with intermediate cases between the two. These intermediate cases may shift along a transition region over time, leading to apparent instability of diagnosis. METHODS We used a cohort of children with high ASD risk, by virtue of having an older sibling with ASD, assessed at 24 months (N = 212) and 36 months (N = 191). We applied machine learning to empirically characterize the classification boundary between ASD and non-ASD, using variables quantifying developmental and adaptive skills. We computed the distance of children to the classification boundary. RESULTS Children who switched diagnostic labels from 24 to 36 months, in both directions, (dynamic group) had intermediate phenotypic profiles. They were closer to the classification boundary compared to children who had stable diagnoses, both at 24 months (Cohen's d = .52) and at 36 months (d = .75). The magnitude of change in distance between the two time points was similar for the dynamic and stable groups (Cohen's d = .06), and diagnostic shifts were not associated with a large change. At the individual level, a few children in the dynamic group showed substantial change. CONCLUSIONS Our results suggested that a diagnostic shift was largely due to a slight movement within a transition region between ASD and non-ASD. This fact highlights the need for more vigilant surveillance and intervention strategies. Young children with intermediate phenotypes may have an increased susceptibility to gain or lose their diagnosis at later ages, calling attention to the inherently dynamic nature of early ASD diagnoses.
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Affiliation(s)
- Birkan Tunç
- Center for Autism Research, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Biomedical and Health Informatics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.,Correspondence to: Birkan Tunç, PhD,
| | - Juhi Pandey
- Center for Autism Research, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tanya St. John
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
| | - Shoba S. Meera
- Department of Speech Pathology and Audiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Jennifer E. Maldarelli
- Center for Autism Research, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Lonnie Zwaigenbaum
- Department of Pediatrics, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Heather C. Hazlett
- The Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, , NC 27599, USA
| | - Stephen R. Dager
- Department of Radiology and Bioengineering, University of Washington, Seattle, WA 98195, USA
| | - Kelly N. Botteron
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jessica B. Girault
- The Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, , NC 27599, USA
| | - Robert C. McKinstry
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Ragini Verma
- DiCIPHR (Diffusion and Connectomics in Precision Healthcare Research) Lab, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jed T. Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN 55455, USA
| | - John R. Pruett
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Joseph Piven
- The Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, , NC 27599, USA
| | - Annette M. Estes
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA.,Department of Psychology, University of Washington, Seattle, WA 98195, USA
| | - Robert T. Schultz
- Center for Autism Research, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Biomedical and Health Informatics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.,Department of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104, USA
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Emerging Evidence for Putative Neural Networks and Antecedents of Pediatric Anxiety in the Fetal, Neonatal, and Infant Periods. Biol Psychiatry 2021; 89:672-680. [PMID: 33518264 PMCID: PMC8087150 DOI: 10.1016/j.biopsych.2020.11.020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 11/12/2020] [Accepted: 11/22/2020] [Indexed: 12/20/2022]
Abstract
Anxiety disorders are the most prevalent psychiatric disorders in youth and are associated with profound individual impairment and public health costs. Research shows that clinically significant anxiety symptoms manifest in preschool-aged children, and correlates of anxiety symptoms are observable in infancy. Yet, predicting who is at risk for developing anxiety remains an enduring challenge. Predictive biomarkers of anxiety are needed before school age when anxiety symptoms typically consolidate into diagnostic profiles. Increasing evidence indicates that early neural measures implicated in anxiety and anxious temperament may be incorporated with traditional measures of behavioral risk (i.e., behavioral inhibition) to provide more robust classification of pediatric anxiety problems. This review examines the phenomenology of anxiety disorders in early life, highlighting developmental research that interrogates the putative neurocircuitry of pediatric anxiety. First, we discuss enduring challenges in identifying and predicting risk for pediatric anxiety. Second, we summarize emerging evidence for putative neural antecedents and networks underlying risk for pediatric anxiety in the fetal, neonatal, and infant periods that represent novel potential avenues for risk identification and prediction. We focus on evidence examining the importance of early amygdala and extended amygdala circuitry development to the emergence of anxiety. Finally, we discuss the utility of integrating developmental psychopathology and neuroscience to facilitate future research and clinical work.
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7
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Swanson MR. The role of caregiver speech in supporting language development in infants and toddlers with autism spectrum disorder. Dev Psychopathol 2020; 32:1230-1239. [PMID: 32893764 PMCID: PMC7872436 DOI: 10.1017/s0954579420000838] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Parents play an essential role in supporting child development by providing a safe home, proper nutrition, and rich educational opportunities. In this article we focus on the role of caregiver speech in supporting development of young children with autism spectrum disorder (ASD). We review studies from typically developing children and children with autism showing that rich and responsive caregiver speech supports language development. Autism intervention studies that target caregiver speech are reviewed as are recent scientific advances from studies of typical development. The strengths and weakness of different techniques for collecting language data from caregivers and children are reviewed, and natural language samples are recommended as best practice for language research in autism. We conclude that caregivers play a powerful role in shaping their children's development and encourage researchers to adapt parent-mediated intervention studies to acknowledge individual differences in parents by using a personalized medicine approach.
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Affiliation(s)
- Meghan R Swanson
- School of Behavioral and Brain Sciences, University of Texas at Dallas, TX, USA
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