Towards a Data-Driven Approach to Screen for Autism Risk at 12 Months of Age

IBIS Network

doi:10.1016/j.jaac.2020.10.015

Towards a Data-Driven Approach to Screen for Autism Risk at 12 Months of Age

IBIS Network

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Abstract

Objective: This study aimed to develop a classifier for infants at 12 months of age based on a parent-report measure (the First Year Inventory 2.0 [FYI]), for the following reasons: (1) to classify infants at elevated risk, above and beyond that attributable to familial risk status for ASD; and (2) to serve as a starting point to refine an approach for risk estimation in population samples. Method: A total of 54 high−familial risk (HR) infants later diagnosed with ASD (HR-ASD), 183 HR infants not diagnosed with ASD at 24 months of age (HR-Neg), and 72 low-risk controls participated in the study. All infants contributed FYI data at 12 months of age and had a diagnostic assessment for ASD at age 24 months. A data-driven, cross-validated analytic approach was used to develop a classifier to determine screening accuracy (eg, sensitivity) of the FYI to classify HR-ASD and HR-Neg. Results: The newly developed FYI classifier had an estimated sensitivity of 0.71 (95% CI: 0.50, 0.91) and specificity of 0.72 (95% CI: 0.49, 0.91). Conclusion: This classifier demonstrates the potential to improve current screening for ASD risk at 12 months of age in infants already at elevated familial risk for ASD, increasing opportunities for detection of autism risk in infancy. Findings from this study highlight the utility of combining parent-report measures with machine learning approaches.

Original language	English (US)
Pages (from-to)	968-977
Number of pages	10
Journal	Journal of the American Academy of Child and Adolescent Psychiatry
Volume	60
Issue number	8
DOIs	https://doi.org/10.1016/j.jaac.2020.10.015
State	Published - Aug 2021

Bibliographical note

Funding Information:
Disclosure: Dr. Piven has received grant or research support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development , the US Department of Health and Human Services Administration on Intellectual and Developmental Disabilities, the National Institute of Mental Health , NIH , the National Institute of Neurological Disorders and Stroke , the National Institute of Environmental Health Sciences , and the Simons Foundation . He has served on the John Merck Fund Scientific Advisory Board. He is the Editor-in-Chief of the Journal of Neurodevelopmental Disorders. He is co-inventor of UNC file 16-0185, patent application PCT/US2017/040032, “Methods, Systems, and Computer Readable Media for Utilizing Functional Connectivity Brain Imaging for Diagnosis of a Neurobehavioral Disorder.” Drs. Meera, Wolff, Zwaigenbaum, Elison, Kinh, Shen, Estes, Hazlett, Watson, Baranek, Swanson, St. John, Burrows, Schultz, Dager, Botteron, Pandey and Mr. Donovan have reported no biomedical financial interests or potential conflicts of interest.

Funding Information:
This work was supported by grants through the National Institutes of Health (NIH; R01-HD055741 , PI Piven; U54HD079124 , PI Piven). Additional funding support has been provided from the Simons Foundation (SFARI; grant 140209, PI Piven). Dr. Meera was supported by the Fulbright-Nehru Post-Doctoral fellowship grant USIEF-2264/FNDPR/2017. The funders had no role in study design, data collection, analysis, data interpretation, or writing of the report.

Funding Information:
This work was supported by grants through the National Institutes of Health (NIH; R01-HD055741, PI Piven; U54HD079124, PI Piven). Additional funding support has been provided from the Simons Foundation (SFARI; grant 140209, PI Piven). Dr. Meera was supported by the Fulbright-Nehru Post-Doctoral fellowship grant USIEF-2264/FNDPR/2017. The funders had no role in study design, data collection, analysis, data interpretation, or writing of the report.Disclosure: Dr. Wolff has received grant or research support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Institute of Mental Health. Dr. Piven has received grant or research support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the US Department of Health and Human Services Administration on Intellectual and Developmental Disabilities, the National Institute of Mental Health, NIH, the National Institute of Neurological Disorders and Stroke, the National Institute of Environmental Health Sciences, and the Simons Foundation. He has served on the John Merck Fund Scientific Advisory Board. He is the Editor-in-Chief of the Journal of Neurodevelopmental Disorders. He is co-inventor of UNC file 16-0185, patent application PCT/US2017/040032, ?Methods, Systems, and Computer Readable Media for Utilizing Functional Connectivity Brain Imaging for Diagnosis of a Neurobehavioral Disorder.? Drs. Meera, Zwaigenbaum, Elison, Kinh, Shen, Estes, Hazlett, Watson, Baranek, Swanson, St. John, Burrows, Schultz, Dager, Botteron, Pandey and Mr. Donovan have reported no biomedical financial interests or potential conflicts of interest. Funding acquisition: Piven The Infant Brain Imaging Study (IBIS) Network is an NIH-funded Autism Center of Excellence project and consists of a consortium of 8 universities in the US and Canada. Clinical Sites: University of North Carolina: J. Piven (IBIS Network PI), H.C. Hazlett, C. Chappell; University of Washington: S. Dager, A. Estes, D. Shaw; Washington University: K. Botteron, R. McKinstry, J. Constantino, J. Pruett; Children's Hospital of Philadelphia: R. Schultz, J. Pandey, S. Paterson; University of Alberta: L. Zwaigenbaum; University of Minnesota: J. Elison, J. Wolff; Data Coordinating Center: Montreal Neurological Institute: A.C. Evans, D.L. Collins, G.B. Pike, V. Fonov, P. Kostopoulos, S. Das, L. MacIntyre; Image Processing Core: University of Utah: G. Gerig; University of North Carolina: M. Styner; Statistical Analysis Core: University of North Carolina: H. Gu.

Publisher Copyright:
© 2020 American Academy of Child and Adolescent Psychiatry

Keywords

autism spectrum disorder
first year
high-risk
parent report
screening

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@article{a01384e1f05a421ebdf37a91afe7c2c0,

title = "Towards a Data-Driven Approach to Screen for Autism Risk at 12 Months of Age",

abstract = "Objective: This study aimed to develop a classifier for infants at 12 months of age based on a parent-report measure (the First Year Inventory 2.0 [FYI]), for the following reasons: (1) to classify infants at elevated risk, above and beyond that attributable to familial risk status for ASD; and (2) to serve as a starting point to refine an approach for risk estimation in population samples. Method: A total of 54 high−familial risk (HR) infants later diagnosed with ASD (HR-ASD), 183 HR infants not diagnosed with ASD at 24 months of age (HR-Neg), and 72 low-risk controls participated in the study. All infants contributed FYI data at 12 months of age and had a diagnostic assessment for ASD at age 24 months. A data-driven, cross-validated analytic approach was used to develop a classifier to determine screening accuracy (eg, sensitivity) of the FYI to classify HR-ASD and HR-Neg. Results: The newly developed FYI classifier had an estimated sensitivity of 0.71 (95% CI: 0.50, 0.91) and specificity of 0.72 (95% CI: 0.49, 0.91). Conclusion: This classifier demonstrates the potential to improve current screening for ASD risk at 12 months of age in infants already at elevated familial risk for ASD, increasing opportunities for detection of autism risk in infancy. Findings from this study highlight the utility of combining parent-report measures with machine learning approaches.",

keywords = "autism spectrum disorder, first year, high-risk, parent report, screening",

author = "{IBIS Network} and Meera, {Shoba S.} and Kevin Donovan and Wolff, {Jason J.} and Lonnie Zwaigenbaum and Elison, {Jed T.} and Truong Kinh and Shen, {Mark D.} and Estes, {Annette M.} and Hazlett, {Heather C.} and Watson, {Linda R.} and Baranek, {Grace T.} and Swanson, {Meghan R.} and {St. John}, Tanya and Burrows, {Catherine A.} and Schultz, {Robert T.} and Dager, {Stephen R.} and Botteron, {Kelly N.} and Juhi Pandey and Joseph Piven",

note = "Funding Information: Disclosure: Dr. Piven has received grant or research support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development , the US Department of Health and Human Services Administration on Intellectual and Developmental Disabilities, the National Institute of Mental Health , NIH , the National Institute of Neurological Disorders and Stroke , the National Institute of Environmental Health Sciences , and the Simons Foundation . He has served on the John Merck Fund Scientific Advisory Board. He is the Editor-in-Chief of the Journal of Neurodevelopmental Disorders. He is co-inventor of UNC file 16-0185, patent application PCT/US2017/040032, “Methods, Systems, and Computer Readable Media for Utilizing Functional Connectivity Brain Imaging for Diagnosis of a Neurobehavioral Disorder.” Drs. Meera, Wolff, Zwaigenbaum, Elison, Kinh, Shen, Estes, Hazlett, Watson, Baranek, Swanson, St. John, Burrows, Schultz, Dager, Botteron, Pandey and Mr. Donovan have reported no biomedical financial interests or potential conflicts of interest. Funding Information: This work was supported by grants through the National Institutes of Health (NIH; R01-HD055741 , PI Piven; U54HD079124 , PI Piven). Additional funding support has been provided from the Simons Foundation (SFARI; grant 140209, PI Piven). Dr. Meera was supported by the Fulbright-Nehru Post-Doctoral fellowship grant USIEF-2264/FNDPR/2017. The funders had no role in study design, data collection, analysis, data interpretation, or writing of the report. Funding Information: This work was supported by grants through the National Institutes of Health (NIH; R01-HD055741, PI Piven; U54HD079124, PI Piven). Additional funding support has been provided from the Simons Foundation (SFARI; grant 140209, PI Piven). Dr. Meera was supported by the Fulbright-Nehru Post-Doctoral fellowship grant USIEF-2264/FNDPR/2017. The funders had no role in study design, data collection, analysis, data interpretation, or writing of the report.Disclosure: Dr. Wolff has received grant or research support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Institute of Mental Health. Dr. Piven has received grant or research support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the US Department of Health and Human Services Administration on Intellectual and Developmental Disabilities, the National Institute of Mental Health, NIH, the National Institute of Neurological Disorders and Stroke, the National Institute of Environmental Health Sciences, and the Simons Foundation. He has served on the John Merck Fund Scientific Advisory Board. He is the Editor-in-Chief of the Journal of Neurodevelopmental Disorders. He is co-inventor of UNC file 16-0185, patent application PCT/US2017/040032, ?Methods, Systems, and Computer Readable Media for Utilizing Functional Connectivity Brain Imaging for Diagnosis of a Neurobehavioral Disorder.? Drs. Meera, Zwaigenbaum, Elison, Kinh, Shen, Estes, Hazlett, Watson, Baranek, Swanson, St. John, Burrows, Schultz, Dager, Botteron, Pandey and Mr. Donovan have reported no biomedical financial interests or potential conflicts of interest. Funding acquisition: Piven The Infant Brain Imaging Study (IBIS) Network is an NIH-funded Autism Center of Excellence project and consists of a consortium of 8 universities in the US and Canada. Clinical Sites: University of North Carolina: J. Piven (IBIS Network PI), H.C. Hazlett, C. Chappell; University of Washington: S. Dager, A. Estes, D. Shaw; Washington University: K. Botteron, R. McKinstry, J. Constantino, J. Pruett; Children's Hospital of Philadelphia: R. Schultz, J. Pandey, S. Paterson; University of Alberta: L. Zwaigenbaum; University of Minnesota: J. Elison, J. Wolff; Data Coordinating Center: Montreal Neurological Institute: A.C. Evans, D.L. Collins, G.B. Pike, V. Fonov, P. Kostopoulos, S. Das, L. MacIntyre; Image Processing Core: University of Utah: G. Gerig; University of North Carolina: M. Styner; Statistical Analysis Core: University of North Carolina: H. Gu. Publisher Copyright: {\textcopyright} 2020 American Academy of Child and Adolescent Psychiatry",

year = "2021",

month = aug,

doi = "10.1016/j.jaac.2020.10.015",

language = "English (US)",

volume = "60",

pages = "968--977",

journal = "Journal of the American Academy of Child and Adolescent Psychiatry",

issn = "0890-8567",

publisher = "Elsevier Limited",

number = "8",

}

TY - JOUR

T1 - Towards a Data-Driven Approach to Screen for Autism Risk at 12 Months of Age

AU - IBIS Network

AU - Meera, Shoba S.

AU - Donovan, Kevin

AU - Wolff, Jason J.

AU - Zwaigenbaum, Lonnie

AU - Elison, Jed T.

AU - Kinh, Truong

AU - Shen, Mark D.

AU - Estes, Annette M.

AU - Hazlett, Heather C.

AU - Watson, Linda R.

AU - Baranek, Grace T.

AU - Swanson, Meghan R.

AU - St. John, Tanya

AU - Burrows, Catherine A.

AU - Schultz, Robert T.

AU - Dager, Stephen R.

AU - Botteron, Kelly N.

AU - Pandey, Juhi

AU - Piven, Joseph

N1 - Funding Information: Disclosure: Dr. Piven has received grant or research support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development , the US Department of Health and Human Services Administration on Intellectual and Developmental Disabilities, the National Institute of Mental Health , NIH , the National Institute of Neurological Disorders and Stroke , the National Institute of Environmental Health Sciences , and the Simons Foundation . He has served on the John Merck Fund Scientific Advisory Board. He is the Editor-in-Chief of the Journal of Neurodevelopmental Disorders. He is co-inventor of UNC file 16-0185, patent application PCT/US2017/040032, “Methods, Systems, and Computer Readable Media for Utilizing Functional Connectivity Brain Imaging for Diagnosis of a Neurobehavioral Disorder.” Drs. Meera, Wolff, Zwaigenbaum, Elison, Kinh, Shen, Estes, Hazlett, Watson, Baranek, Swanson, St. John, Burrows, Schultz, Dager, Botteron, Pandey and Mr. Donovan have reported no biomedical financial interests or potential conflicts of interest. Funding Information: This work was supported by grants through the National Institutes of Health (NIH; R01-HD055741 , PI Piven; U54HD079124 , PI Piven). Additional funding support has been provided from the Simons Foundation (SFARI; grant 140209, PI Piven). Dr. Meera was supported by the Fulbright-Nehru Post-Doctoral fellowship grant USIEF-2264/FNDPR/2017. The funders had no role in study design, data collection, analysis, data interpretation, or writing of the report. Funding Information: This work was supported by grants through the National Institutes of Health (NIH; R01-HD055741, PI Piven; U54HD079124, PI Piven). Additional funding support has been provided from the Simons Foundation (SFARI; grant 140209, PI Piven). Dr. Meera was supported by the Fulbright-Nehru Post-Doctoral fellowship grant USIEF-2264/FNDPR/2017. The funders had no role in study design, data collection, analysis, data interpretation, or writing of the report.Disclosure: Dr. Wolff has received grant or research support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Institute of Mental Health. Dr. Piven has received grant or research support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the US Department of Health and Human Services Administration on Intellectual and Developmental Disabilities, the National Institute of Mental Health, NIH, the National Institute of Neurological Disorders and Stroke, the National Institute of Environmental Health Sciences, and the Simons Foundation. He has served on the John Merck Fund Scientific Advisory Board. He is the Editor-in-Chief of the Journal of Neurodevelopmental Disorders. He is co-inventor of UNC file 16-0185, patent application PCT/US2017/040032, ?Methods, Systems, and Computer Readable Media for Utilizing Functional Connectivity Brain Imaging for Diagnosis of a Neurobehavioral Disorder.? Drs. Meera, Zwaigenbaum, Elison, Kinh, Shen, Estes, Hazlett, Watson, Baranek, Swanson, St. John, Burrows, Schultz, Dager, Botteron, Pandey and Mr. Donovan have reported no biomedical financial interests or potential conflicts of interest. Funding acquisition: Piven The Infant Brain Imaging Study (IBIS) Network is an NIH-funded Autism Center of Excellence project and consists of a consortium of 8 universities in the US and Canada. Clinical Sites: University of North Carolina: J. Piven (IBIS Network PI), H.C. Hazlett, C. Chappell; University of Washington: S. Dager, A. Estes, D. Shaw; Washington University: K. Botteron, R. McKinstry, J. Constantino, J. Pruett; Children's Hospital of Philadelphia: R. Schultz, J. Pandey, S. Paterson; University of Alberta: L. Zwaigenbaum; University of Minnesota: J. Elison, J. Wolff; Data Coordinating Center: Montreal Neurological Institute: A.C. Evans, D.L. Collins, G.B. Pike, V. Fonov, P. Kostopoulos, S. Das, L. MacIntyre; Image Processing Core: University of Utah: G. Gerig; University of North Carolina: M. Styner; Statistical Analysis Core: University of North Carolina: H. Gu. Publisher Copyright: © 2020 American Academy of Child and Adolescent Psychiatry

PY - 2021/8

Y1 - 2021/8

N2 - Objective: This study aimed to develop a classifier for infants at 12 months of age based on a parent-report measure (the First Year Inventory 2.0 [FYI]), for the following reasons: (1) to classify infants at elevated risk, above and beyond that attributable to familial risk status for ASD; and (2) to serve as a starting point to refine an approach for risk estimation in population samples. Method: A total of 54 high−familial risk (HR) infants later diagnosed with ASD (HR-ASD), 183 HR infants not diagnosed with ASD at 24 months of age (HR-Neg), and 72 low-risk controls participated in the study. All infants contributed FYI data at 12 months of age and had a diagnostic assessment for ASD at age 24 months. A data-driven, cross-validated analytic approach was used to develop a classifier to determine screening accuracy (eg, sensitivity) of the FYI to classify HR-ASD and HR-Neg. Results: The newly developed FYI classifier had an estimated sensitivity of 0.71 (95% CI: 0.50, 0.91) and specificity of 0.72 (95% CI: 0.49, 0.91). Conclusion: This classifier demonstrates the potential to improve current screening for ASD risk at 12 months of age in infants already at elevated familial risk for ASD, increasing opportunities for detection of autism risk in infancy. Findings from this study highlight the utility of combining parent-report measures with machine learning approaches.

AB - Objective: This study aimed to develop a classifier for infants at 12 months of age based on a parent-report measure (the First Year Inventory 2.0 [FYI]), for the following reasons: (1) to classify infants at elevated risk, above and beyond that attributable to familial risk status for ASD; and (2) to serve as a starting point to refine an approach for risk estimation in population samples. Method: A total of 54 high−familial risk (HR) infants later diagnosed with ASD (HR-ASD), 183 HR infants not diagnosed with ASD at 24 months of age (HR-Neg), and 72 low-risk controls participated in the study. All infants contributed FYI data at 12 months of age and had a diagnostic assessment for ASD at age 24 months. A data-driven, cross-validated analytic approach was used to develop a classifier to determine screening accuracy (eg, sensitivity) of the FYI to classify HR-ASD and HR-Neg. Results: The newly developed FYI classifier had an estimated sensitivity of 0.71 (95% CI: 0.50, 0.91) and specificity of 0.72 (95% CI: 0.49, 0.91). Conclusion: This classifier demonstrates the potential to improve current screening for ASD risk at 12 months of age in infants already at elevated familial risk for ASD, increasing opportunities for detection of autism risk in infancy. Findings from this study highlight the utility of combining parent-report measures with machine learning approaches.

KW - autism spectrum disorder

KW - first year

KW - high-risk

KW - parent report

KW - screening

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Towards a Data-Driven Approach to Screen for Autism Risk at 12 Months of Age

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