TY - JOUR
T1 - Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population
AU - Hwang, Gyujoon
AU - Wen, Junhao
AU - Sotardi, Susan
AU - Brodkin, Edward S
AU - Chand, Ganesh B
AU - Dwyer, Dominic B
AU - Erus, Guray
AU - Doshi, Jimit
AU - Singhal, Pankhuri
AU - Srinivasan, Dhivya
AU - Varol, Erdem
AU - Sotiras, Aristeidis
AU - Dazzan, Paola
AU - Kahn, Rene S
AU - Schnack, Hugo G
AU - Zanetti, Marcus V
AU - Meisenzahl, Eva
AU - Busatto, Geraldo F
AU - Crespo-Facorro, Benedicto
AU - Pantelis, Christos
AU - Wood, Stephen J
AU - Zhuo, Chuanjun
AU - Shinohara, Russell T
AU - Shou, Haochang
AU - Fan, Yong
AU - Di Martino, Adriana
AU - Koutsouleris, Nikolaos
AU - Gur, Raquel E
AU - Gur, Ruben C
AU - Satterthwaite, Theodore D
AU - Wolf, Daniel H
AU - Davatzikos, Christos
N1 - Funding Information:
Conflict of Interest Disclosures: Drs Brodkin, Shou, Di Martino, and Davatzikos reported grants from National Institutes of Health during the conduct of the study. Dr Sotiras reported personal fees from BrightFocus Foundation for serving as grant reviewer and equity from TheraPanacea outside the submitted work. Dr Dazzan reported personal fees from Lundbeck and Janssen outside the submitted work. Dr Kahn reported personal fees from Alkermes, Otsuka, and Sunovion outside the submitted work. Dr Crespo-Facorro reported grants from the Ministry of Economy and Competitiveness and the European Fund for Regional Development, Federación Española de Enfermedades Raras ISCIII, Fundacion Marques de Valdecilla, SENY Fundatio Research, and Instituto de Salud Carlos III and honoraria for lectures or advisory boards from Rovi, Janssen, Otsuka, Lundbeck, and Angelini outside the submitted work. Dr Wood reported personal fees from Biogen outside the submitted work. Dr Zhuo reported grants from National Natural Science Foundation of China during the conduct of the study. Dr Shinohara reported personal fees from Octave Biosciences and the American Medical Association outside the submitted work. No other disclosures were reported.
Funding Information:
Funding/Support: This study was supported by the National Institutes of Health (grants R01MH112070 and R01MH123550).
Publisher Copyright:
© 2023 American Medical Association. All rights reserved.
PY - 2023/5/3
Y1 - 2023/5/3
N2 - Importance: Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment. Objective: To assess distinct neuroanatomical dimensions of ASD using novel semisupervised machine learning methods and to test whether the dimensions can serve as endophenotypes also in non-ASD populations. Design, Setting, and Participants: This cross-sectional study used imaging data from the publicly available Autism Brain Imaging Data Exchange (ABIDE) repositories as the discovery cohort. The ABIDE sample included individuals diagnosed with ASD aged between 16 and 64 years and age- and sex-match typically developing individuals. Validation cohorts included individuals with schizophrenia from the Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging (PHENOM) consortium and individuals from the UK Biobank to represent the general population. The multisite discovery cohort included 16 internationally distributed imaging sites. Analyses were performed between March 2021 and March 2022. Main Outcomes and Measures: The trained semisupervised heterogeneity through discriminative analysis models were tested for reproducibility using extensive cross-validations. It was then applied to individuals from the PHENOM and the UK Biobank. It was hypothesized that neuroanatomical dimensions of ASD would display distinct clinical and genetic profiles and would be prominent also in non-ASD populations. Results: Heterogeneity through discriminative analysis models trained on T1-weighted brain magnetic resonance images of 307 individuals with ASD (mean [SD] age, 25.4 [9.8] years; 273 [88.9%] male) and 362 typically developing control individuals (mean [SD] age, 25.8 [8.9] years; 309 [85.4%] male) revealed that a 3-dimensional scheme was optimal to capture the ASD neuroanatomy. The first dimension (A1: aginglike) was associated with smaller brain volume, lower cognitive function, and aging-related genetic variants (FOXO3; Z = 4.65; P = 1.62 × 10-6). The second dimension (A2: schizophrenialike) was characterized by enlarged subcortical volumes, antipsychotic medication use (Cohen d = 0.65; false discovery rate-adjusted P =.048), partially overlapping genetic, neuroanatomical characteristics to schizophrenia (n = 307), and significant genetic heritability estimates in the general population (n = 14786; mean [SD] h2, 0.71 [0.04]; P < 1 × 10-4). The third dimension (A3: typical ASD) was distinguished by enlarged cortical volumes, high nonverbal cognitive performance, and biological pathways implicating brain development and abnormal apoptosis (mean [SD] β, 0.83 [0.02]; P = 4.22 × 10-6). Conclusions and Relevance: This cross-sectional study discovered 3-dimensional endophenotypic representation that may elucidate the heterogeneous neurobiological underpinnings of ASD to support precision diagnostics. The significant correspondence between A2 and schizophrenia indicates a possibility of identifying common biological mechanisms across the 2 mental health diagnoses..
AB - Importance: Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment. Objective: To assess distinct neuroanatomical dimensions of ASD using novel semisupervised machine learning methods and to test whether the dimensions can serve as endophenotypes also in non-ASD populations. Design, Setting, and Participants: This cross-sectional study used imaging data from the publicly available Autism Brain Imaging Data Exchange (ABIDE) repositories as the discovery cohort. The ABIDE sample included individuals diagnosed with ASD aged between 16 and 64 years and age- and sex-match typically developing individuals. Validation cohorts included individuals with schizophrenia from the Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging (PHENOM) consortium and individuals from the UK Biobank to represent the general population. The multisite discovery cohort included 16 internationally distributed imaging sites. Analyses were performed between March 2021 and March 2022. Main Outcomes and Measures: The trained semisupervised heterogeneity through discriminative analysis models were tested for reproducibility using extensive cross-validations. It was then applied to individuals from the PHENOM and the UK Biobank. It was hypothesized that neuroanatomical dimensions of ASD would display distinct clinical and genetic profiles and would be prominent also in non-ASD populations. Results: Heterogeneity through discriminative analysis models trained on T1-weighted brain magnetic resonance images of 307 individuals with ASD (mean [SD] age, 25.4 [9.8] years; 273 [88.9%] male) and 362 typically developing control individuals (mean [SD] age, 25.8 [8.9] years; 309 [85.4%] male) revealed that a 3-dimensional scheme was optimal to capture the ASD neuroanatomy. The first dimension (A1: aginglike) was associated with smaller brain volume, lower cognitive function, and aging-related genetic variants (FOXO3; Z = 4.65; P = 1.62 × 10-6). The second dimension (A2: schizophrenialike) was characterized by enlarged subcortical volumes, antipsychotic medication use (Cohen d = 0.65; false discovery rate-adjusted P =.048), partially overlapping genetic, neuroanatomical characteristics to schizophrenia (n = 307), and significant genetic heritability estimates in the general population (n = 14786; mean [SD] h2, 0.71 [0.04]; P < 1 × 10-4). The third dimension (A3: typical ASD) was distinguished by enlarged cortical volumes, high nonverbal cognitive performance, and biological pathways implicating brain development and abnormal apoptosis (mean [SD] β, 0.83 [0.02]; P = 4.22 × 10-6). Conclusions and Relevance: This cross-sectional study discovered 3-dimensional endophenotypic representation that may elucidate the heterogeneous neurobiological underpinnings of ASD to support precision diagnostics. The significant correspondence between A2 and schizophrenia indicates a possibility of identifying common biological mechanisms across the 2 mental health diagnoses..
KW - Adolescent
KW - Adult
KW - Autism Spectrum Disorder/diagnostic imaging
KW - Brain
KW - Cross-Sectional Studies
KW - Endophenotypes
KW - Female
KW - Humans
KW - Magnetic Resonance Imaging/methods
KW - Male
KW - Middle Aged
KW - Neuroanatomy
KW - Reproducibility of Results
KW - Schizophrenia/diagnostic imaging
KW - Young Adult
UR - http://www.scopus.com/inward/record.url?scp=85159060372&partnerID=8YFLogxK
U2 - 10.1001/jamapsychiatry.2023.0409
DO - 10.1001/jamapsychiatry.2023.0409
M3 - Article
C2 - 37017948
SN - 2168-622X
VL - 80
SP - 498
EP - 507
JO - JAMA Psychiatry
JF - JAMA Psychiatry
IS - 5
ER -