A Data-Driven Approach in an Unbiased Sample Reveals Equivalent Sex Ratio of Autism Spectrum Disorder–Associated Impairment in Early Childhood

IBIS Network; Catherine A. Burrows

doi:10.1016/j.biopsych.2022.05.027

A Data-Driven Approach in an Unbiased Sample Reveals Equivalent Sex Ratio of Autism Spectrum Disorder–Associated Impairment in Early Childhood

IBIS Network, Catherine A. Burrows

Research output: Contribution to journal › Article › peer-review

31 Scopus citations

Abstract

Background: Sex differences in the prevalence of neurodevelopmental disorders are particularly evident in autism spectrum disorder (ASD). Heterogeneous symptom presentation and the potential of measurement bias hinder early ASD detection in females and may contribute to discrepant prevalence estimates. We examined trajectories of social communication (SC) and restricted and repetitive behaviors (RRBs) in a sample of infant siblings of children with ASD, adjusting for age- and sex-based measurement bias. We hypothesized that leveraging a prospective elevated familial likelihood sample, deriving data-driven behavioral constructs, and accounting for measurement bias would reveal less discrepant sex ratios than are typically seen in ASD. Methods: We conducted direct assessments of ASD symptoms at 6 to 9, 12 to 15, 24, and 36 to 60 months of age (total n_observations = 1254) with infant siblings of children with ASD (n = 377) and a lower ASD-familial-likelihood comparison group (n = 168; n_observations = 527). We established measurement invariance across age and sex for separate models of SC and RRB. We then conducted latent class growth mixture modeling with the longitudinal data and evaluated for sex differences in trajectory membership. Results: We identified 2 latent classes in the SC and RRB models with equal sex ratios in the high-concern cluster for both SC and RRB. Sex differences were also observed in the SC high-concern cluster, indicating that girls classified as having elevated social concerns demonstrated milder symptoms than boys in this group. Conclusions: This novel approach for characterizing ASD symptom progression highlights the utility of assessing and adjusting for sex-related measurement bias and identifying sex-specific patterns of symptom emergence.

Original language	English (US)
Pages (from-to)	654-662
Number of pages	9
Journal	Biological psychiatry
Volume	92
Issue number	8
DOIs	https://doi.org/10.1016/j.biopsych.2022.05.027
State	Published - Oct 2022

Bibliographical note

Funding Information:
This study was supported by grants from the National Institutes of Health (Grant Nos. R01-HD055741 [principal investigator, JPi], R01-MH118362-01 [principal investigators, JRP, JPi], R01-MH118362-02S1 [principal investigators, JRP, JPi], U54-HD079124 [principal investigator, JPi], P50-HD103573 [project ID 8084; principal investigator, JPi], U54-HD086984 [to RTS]), Autism Speaks (Grant No. 6020 [principal investigator, JPi]), and the Simons Foundation (Grant No. 140209 [to JPi]). This study was also supported by a U.S. National Institutes of Health ResearchCareer Development Award (Grant No. K12-HD055887 [to CAB]) and by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Research Career Development Award (Grant No. 3KL2TR002490-03S1 [to RLG]). The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. IBIS Network: The Infant Brain Imaging Study Network is a United States National Institutes of Health funded Autism Center of Excellence (ACE) project and consists of a consortium of 10 universities in the United States and Canada. Members and components of the IBIS Network include J. Piven (IBIS Network PI), Clinical Sites: Children's Hospital of Philadelphia: R.T. Schultz, J. Pandey, J. Parish-Morris, B. Tunç, W. Guthrie; University of Minnesota (UMN): J.T. Elison, J.J. Wolff; University of North Carolina (UNC): J. Piven, H.C. Hazlett, M.D. Shen, J.B. Girault, R Grzadzinski; University of Washington (UW): S.R. Dager, A.M. Estes, T.St. John, D. Shaw; Washington University School of Medicine in St Louis (WU): K.N. Botteron, R.C. McKinstry, J.N. Constantino, N. Marrus. Admin Core: WU: Alicia Rocca; UNC: J.C. Chappell. Behavior Core: UW: A.M. Estes, T.St. John; University of Alberta: L. Zwaigenbaum; UMN: J.T. Elison, J.J. Wolff, C. Burrows; University of Texas at Dallas: M.R. Swanson. MRI Core: UNC: M.A. Styner, M.D. Shen; New York University: G. Gerig; WU: J.R. Pruett, Jr. R.C. McKinstry; UMN: J.T. Elison; UW: S.R. Dager. Data Coordinating Center: Montreal Neurological Institute: A.C. Evans, L.C. MacIntyre, S. Torres-Gomez, S. Das (see Das et al.: The Montreal Neurological Institute data-sharing and processing ecosystem. Neuroimage 2016; 124:1188–1195). Statistical Analysis Core: UNC: K. Truong. Environmental Risk Core: Johns Hopkins University: H. Volk. Genetics Core: Johns Hopkins University: M.D. Fallin; UNC: M.D. Shen. We thank all the families and children who have participated in the IBIS study. The authors report no biomedical financial interests or potential conflicts of interest.

Funding Information:
This study was supported by grants from the National Institutes of Health (Grant Nos. R01-HD055741 [principal investigator, JPi], R01-MH118362-01 [principal investigators, JRP, JPi], R01-MH118362-02S1 [principal investigators, JRP, JPi], U54-HD079124 [principal investigator, JPi], P50-HD103573 [project ID 8084; principal investigator, JPi], U54-HD086984 [to RTS]), Autism Speaks (Grant No. 6020 [principal investigator, JPi]) , and the Simons Foundation (Grant No. 140209 [to JPi]). This study was also supported by a U.S. National Institutes of Health ResearchCareer Development Award (Grant No. K12-HD055887 [to CAB]) and by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Research Career Development Award (Grant No. 3KL2TR002490-03S1 [to RLG]).

Publisher Copyright:
© 2022 Society of Biological Psychiatry

Keywords

Autism spectrum disorder
Measurement invariance
Mixture modeling
Restricted and repetitive behaviors
Sex differences
Social communication
Prospective Studies
Humans
Child, Preschool
Infant
Male
Sex Characteristics
Sex Ratio
Female
Child
Autism Spectrum Disorder/diagnosis
Siblings

PubMed: MeSH publication types

Research Support, Non-U.S. Gov't
Journal Article
Research Support, N.I.H., Extramural

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10.1016/j.biopsych.2022.05.027

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@article{5be0add215344958be92409878a248b5,

title = "A Data-Driven Approach in an Unbiased Sample Reveals Equivalent Sex Ratio of Autism Spectrum Disorder–Associated Impairment in Early Childhood",

abstract = "Background: Sex differences in the prevalence of neurodevelopmental disorders are particularly evident in autism spectrum disorder (ASD). Heterogeneous symptom presentation and the potential of measurement bias hinder early ASD detection in females and may contribute to discrepant prevalence estimates. We examined trajectories of social communication (SC) and restricted and repetitive behaviors (RRBs) in a sample of infant siblings of children with ASD, adjusting for age- and sex-based measurement bias. We hypothesized that leveraging a prospective elevated familial likelihood sample, deriving data-driven behavioral constructs, and accounting for measurement bias would reveal less discrepant sex ratios than are typically seen in ASD. Methods: We conducted direct assessments of ASD symptoms at 6 to 9, 12 to 15, 24, and 36 to 60 months of age (total nobservations = 1254) with infant siblings of children with ASD (n = 377) and a lower ASD-familial-likelihood comparison group (n = 168; nobservations = 527). We established measurement invariance across age and sex for separate models of SC and RRB. We then conducted latent class growth mixture modeling with the longitudinal data and evaluated for sex differences in trajectory membership. Results: We identified 2 latent classes in the SC and RRB models with equal sex ratios in the high-concern cluster for both SC and RRB. Sex differences were also observed in the SC high-concern cluster, indicating that girls classified as having elevated social concerns demonstrated milder symptoms than boys in this group. Conclusions: This novel approach for characterizing ASD symptom progression highlights the utility of assessing and adjusting for sex-related measurement bias and identifying sex-specific patterns of symptom emergence.",

keywords = "Autism spectrum disorder, Measurement invariance, Mixture modeling, Restricted and repetitive behaviors, Sex differences, Social communication, Prospective Studies, Humans, Child, Preschool, Infant, Male, Sex Characteristics, Sex Ratio, Female, Child, Autism Spectrum Disorder/diagnosis, Siblings",

author = "{IBIS Network} and Burrows, {Catherine A.} and Grzadzinski, {Rebecca L.} and Kevin Donovan and Stallworthy, {Isabella C.} and Joshua Rutsohn and {St. John}, Tanya and Natasha Marrus and Julia Parish-Morris and Leigh MacIntyre and Jacqueline Hampton and Juhi Pandey and Shen, {Mark D.} and Botteron, {Kelly N.} and Estes, {Annette M.} and Dager, {Stephen R.} and Hazlett, {Heather C.} and Pruett, {John R.} and Schultz, {Robert T.} and Lonnie Zwaigenbaum and Truong, {Kinh N.} and Joseph Piven and Elison, {Jed T.}",

note = "Funding Information: This study was supported by grants from the National Institutes of Health (Grant Nos. R01-HD055741 [principal investigator, JPi], R01-MH118362-01 [principal investigators, JRP, JPi], R01-MH118362-02S1 [principal investigators, JRP, JPi], U54-HD079124 [principal investigator, JPi], P50-HD103573 [project ID 8084; principal investigator, JPi], U54-HD086984 [to RTS]), Autism Speaks (Grant No. 6020 [principal investigator, JPi]), and the Simons Foundation (Grant No. 140209 [to JPi]). This study was also supported by a U.S. National Institutes of Health ResearchCareer Development Award (Grant No. K12-HD055887 [to CAB]) and by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Research Career Development Award (Grant No. 3KL2TR002490-03S1 [to RLG]). The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. IBIS Network: The Infant Brain Imaging Study Network is a United States National Institutes of Health funded Autism Center of Excellence (ACE) project and consists of a consortium of 10 universities in the United States and Canada. Members and components of the IBIS Network include J. Piven (IBIS Network PI), Clinical Sites: Children's Hospital of Philadelphia: R.T. Schultz, J. Pandey, J. Parish-Morris, B. Tun{\c c}, W. Guthrie; University of Minnesota (UMN): J.T. Elison, J.J. Wolff; University of North Carolina (UNC): J. Piven, H.C. Hazlett, M.D. Shen, J.B. Girault, R Grzadzinski; University of Washington (UW): S.R. Dager, A.M. Estes, T.St. John, D. Shaw; Washington University School of Medicine in St Louis (WU): K.N. Botteron, R.C. McKinstry, J.N. Constantino, N. Marrus. Admin Core: WU: Alicia Rocca; UNC: J.C. Chappell. Behavior Core: UW: A.M. Estes, T.St. John; University of Alberta: L. Zwaigenbaum; UMN: J.T. Elison, J.J. Wolff, C. Burrows; University of Texas at Dallas: M.R. Swanson. MRI Core: UNC: M.A. Styner, M.D. Shen; New York University: G. Gerig; WU: J.R. Pruett, Jr. R.C. McKinstry; UMN: J.T. Elison; UW: S.R. Dager. Data Coordinating Center: Montreal Neurological Institute: A.C. Evans, L.C. MacIntyre, S. Torres-Gomez, S. Das (see Das et al.: The Montreal Neurological Institute data-sharing and processing ecosystem. Neuroimage 2016; 124:1188–1195). Statistical Analysis Core: UNC: K. Truong. Environmental Risk Core: Johns Hopkins University: H. Volk. Genetics Core: Johns Hopkins University: M.D. Fallin; UNC: M.D. Shen. We thank all the families and children who have participated in the IBIS study. The authors report no biomedical financial interests or potential conflicts of interest. Funding Information: This study was supported by grants from the National Institutes of Health (Grant Nos. R01-HD055741 [principal investigator, JPi], R01-MH118362-01 [principal investigators, JRP, JPi], R01-MH118362-02S1 [principal investigators, JRP, JPi], U54-HD079124 [principal investigator, JPi], P50-HD103573 [project ID 8084; principal investigator, JPi], U54-HD086984 [to RTS]), Autism Speaks (Grant No. 6020 [principal investigator, JPi]) , and the Simons Foundation (Grant No. 140209 [to JPi]). This study was also supported by a U.S. National Institutes of Health ResearchCareer Development Award (Grant No. K12-HD055887 [to CAB]) and by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Research Career Development Award (Grant No. 3KL2TR002490-03S1 [to RLG]). Publisher Copyright: {\textcopyright} 2022 Society of Biological Psychiatry",

year = "2022",

month = oct,

doi = "10.1016/j.biopsych.2022.05.027",

language = "English (US)",

volume = "92",

pages = "654--662",

journal = "Biological psychiatry",

issn = "0006-3223",

publisher = "Elsevier USA",

number = "8",

}

TY - JOUR

T1 - A Data-Driven Approach in an Unbiased Sample Reveals Equivalent Sex Ratio of Autism Spectrum Disorder–Associated Impairment in Early Childhood

AU - IBIS Network

AU - Burrows, Catherine A.

AU - Grzadzinski, Rebecca L.

AU - Donovan, Kevin

AU - Stallworthy, Isabella C.

AU - Rutsohn, Joshua

AU - St. John, Tanya

AU - Marrus, Natasha

AU - Parish-Morris, Julia

AU - MacIntyre, Leigh

AU - Hampton, Jacqueline

AU - Pandey, Juhi

AU - Shen, Mark D.

AU - Botteron, Kelly N.

AU - Estes, Annette M.

AU - Dager, Stephen R.

AU - Hazlett, Heather C.

AU - Pruett, John R.

AU - Schultz, Robert T.

AU - Zwaigenbaum, Lonnie

AU - Truong, Kinh N.

AU - Piven, Joseph

AU - Elison, Jed T.

N1 - Funding Information: This study was supported by grants from the National Institutes of Health (Grant Nos. R01-HD055741 [principal investigator, JPi], R01-MH118362-01 [principal investigators, JRP, JPi], R01-MH118362-02S1 [principal investigators, JRP, JPi], U54-HD079124 [principal investigator, JPi], P50-HD103573 [project ID 8084; principal investigator, JPi], U54-HD086984 [to RTS]), Autism Speaks (Grant No. 6020 [principal investigator, JPi]), and the Simons Foundation (Grant No. 140209 [to JPi]). This study was also supported by a U.S. National Institutes of Health ResearchCareer Development Award (Grant No. K12-HD055887 [to CAB]) and by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Research Career Development Award (Grant No. 3KL2TR002490-03S1 [to RLG]). The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. IBIS Network: The Infant Brain Imaging Study Network is a United States National Institutes of Health funded Autism Center of Excellence (ACE) project and consists of a consortium of 10 universities in the United States and Canada. Members and components of the IBIS Network include J. Piven (IBIS Network PI), Clinical Sites: Children's Hospital of Philadelphia: R.T. Schultz, J. Pandey, J. Parish-Morris, B. Tunç, W. Guthrie; University of Minnesota (UMN): J.T. Elison, J.J. Wolff; University of North Carolina (UNC): J. Piven, H.C. Hazlett, M.D. Shen, J.B. Girault, R Grzadzinski; University of Washington (UW): S.R. Dager, A.M. Estes, T.St. John, D. Shaw; Washington University School of Medicine in St Louis (WU): K.N. Botteron, R.C. McKinstry, J.N. Constantino, N. Marrus. Admin Core: WU: Alicia Rocca; UNC: J.C. Chappell. Behavior Core: UW: A.M. Estes, T.St. John; University of Alberta: L. Zwaigenbaum; UMN: J.T. Elison, J.J. Wolff, C. Burrows; University of Texas at Dallas: M.R. Swanson. MRI Core: UNC: M.A. Styner, M.D. Shen; New York University: G. Gerig; WU: J.R. Pruett, Jr. R.C. McKinstry; UMN: J.T. Elison; UW: S.R. Dager. Data Coordinating Center: Montreal Neurological Institute: A.C. Evans, L.C. MacIntyre, S. Torres-Gomez, S. Das (see Das et al.: The Montreal Neurological Institute data-sharing and processing ecosystem. Neuroimage 2016; 124:1188–1195). Statistical Analysis Core: UNC: K. Truong. Environmental Risk Core: Johns Hopkins University: H. Volk. Genetics Core: Johns Hopkins University: M.D. Fallin; UNC: M.D. Shen. We thank all the families and children who have participated in the IBIS study. The authors report no biomedical financial interests or potential conflicts of interest. Funding Information: This study was supported by grants from the National Institutes of Health (Grant Nos. R01-HD055741 [principal investigator, JPi], R01-MH118362-01 [principal investigators, JRP, JPi], R01-MH118362-02S1 [principal investigators, JRP, JPi], U54-HD079124 [principal investigator, JPi], P50-HD103573 [project ID 8084; principal investigator, JPi], U54-HD086984 [to RTS]), Autism Speaks (Grant No. 6020 [principal investigator, JPi]) , and the Simons Foundation (Grant No. 140209 [to JPi]). This study was also supported by a U.S. National Institutes of Health ResearchCareer Development Award (Grant No. K12-HD055887 [to CAB]) and by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Research Career Development Award (Grant No. 3KL2TR002490-03S1 [to RLG]). Publisher Copyright: © 2022 Society of Biological Psychiatry

PY - 2022/10

Y1 - 2022/10

N2 - Background: Sex differences in the prevalence of neurodevelopmental disorders are particularly evident in autism spectrum disorder (ASD). Heterogeneous symptom presentation and the potential of measurement bias hinder early ASD detection in females and may contribute to discrepant prevalence estimates. We examined trajectories of social communication (SC) and restricted and repetitive behaviors (RRBs) in a sample of infant siblings of children with ASD, adjusting for age- and sex-based measurement bias. We hypothesized that leveraging a prospective elevated familial likelihood sample, deriving data-driven behavioral constructs, and accounting for measurement bias would reveal less discrepant sex ratios than are typically seen in ASD. Methods: We conducted direct assessments of ASD symptoms at 6 to 9, 12 to 15, 24, and 36 to 60 months of age (total nobservations = 1254) with infant siblings of children with ASD (n = 377) and a lower ASD-familial-likelihood comparison group (n = 168; nobservations = 527). We established measurement invariance across age and sex for separate models of SC and RRB. We then conducted latent class growth mixture modeling with the longitudinal data and evaluated for sex differences in trajectory membership. Results: We identified 2 latent classes in the SC and RRB models with equal sex ratios in the high-concern cluster for both SC and RRB. Sex differences were also observed in the SC high-concern cluster, indicating that girls classified as having elevated social concerns demonstrated milder symptoms than boys in this group. Conclusions: This novel approach for characterizing ASD symptom progression highlights the utility of assessing and adjusting for sex-related measurement bias and identifying sex-specific patterns of symptom emergence.

AB - Background: Sex differences in the prevalence of neurodevelopmental disorders are particularly evident in autism spectrum disorder (ASD). Heterogeneous symptom presentation and the potential of measurement bias hinder early ASD detection in females and may contribute to discrepant prevalence estimates. We examined trajectories of social communication (SC) and restricted and repetitive behaviors (RRBs) in a sample of infant siblings of children with ASD, adjusting for age- and sex-based measurement bias. We hypothesized that leveraging a prospective elevated familial likelihood sample, deriving data-driven behavioral constructs, and accounting for measurement bias would reveal less discrepant sex ratios than are typically seen in ASD. Methods: We conducted direct assessments of ASD symptoms at 6 to 9, 12 to 15, 24, and 36 to 60 months of age (total nobservations = 1254) with infant siblings of children with ASD (n = 377) and a lower ASD-familial-likelihood comparison group (n = 168; nobservations = 527). We established measurement invariance across age and sex for separate models of SC and RRB. We then conducted latent class growth mixture modeling with the longitudinal data and evaluated for sex differences in trajectory membership. Results: We identified 2 latent classes in the SC and RRB models with equal sex ratios in the high-concern cluster for both SC and RRB. Sex differences were also observed in the SC high-concern cluster, indicating that girls classified as having elevated social concerns demonstrated milder symptoms than boys in this group. Conclusions: This novel approach for characterizing ASD symptom progression highlights the utility of assessing and adjusting for sex-related measurement bias and identifying sex-specific patterns of symptom emergence.

KW - Autism spectrum disorder

KW - Measurement invariance

KW - Mixture modeling

KW - Restricted and repetitive behaviors

KW - Sex differences

KW - Social communication

KW - Prospective Studies

KW - Humans

KW - Child, Preschool

KW - Infant

KW - Male

KW - Sex Characteristics

KW - Sex Ratio

KW - Female

KW - Child

KW - Autism Spectrum Disorder/diagnosis

KW - Siblings

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UR - http://www.scopus.com/inward/citedby.url?scp=85135841245&partnerID=8YFLogxK

U2 - 10.1016/j.biopsych.2022.05.027

DO - 10.1016/j.biopsych.2022.05.027

M3 - Article

C2 - 35965107

AN - SCOPUS:85135841245

SN - 0006-3223

VL - 92

SP - 654

EP - 662

JO - Biological psychiatry

JF - Biological psychiatry

IS - 8

ER -

A Data-Driven Approach in an Unbiased Sample Reveals Equivalent Sex Ratio of Autism Spectrum Disorder–Associated Impairment in Early Childhood

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