TY - JOUR
T1 - The Link Between Autism and Sex-Related Neuroanatomy, and Associated Cognition and Gene Expression
AU - Floris, Dorothea L
AU - Peng, Han
AU - Warrier, Varun
AU - Lombardo, Michael V
AU - Pretzsch, Charlotte M
AU - Moreau, Clara
AU - Tsompanidis, Alex
AU - Gong, Weikang
AU - Mennes, Maarten
AU - Llera, Alberto
AU - van Rooij, Daan
AU - Oldehinkel, Marianne
AU - Forde, Natalie J
AU - Charman, Tony
AU - Tillmann, Julian
AU - Banaschewski, Tobias
AU - Moessnang, Carolin
AU - Durston, Sarah
AU - Holt, Rosemary J
AU - Ecker, Christine
AU - Dell'Acqua, Flavio
AU - Loth, Eva
AU - Bourgeron, Thomas
AU - Murphy, Declan G M
AU - Marquand, Andre F
AU - Lai, Meng-Chuan
AU - Buitelaar, Jan K
AU - Baron-Cohen, Simon
AU - Beckmann, Christian F
N1 - Publisher Copyright:
© 2023 American Psychiatric Association. All rights reserved.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Objective: The male preponderance in prevalence of autism more predictive of autistic males (ABIDE: Cohen’s d50.48; is among the most pronounced sex ratios across neuroLEAP: Cohen’s d51.34). Features positively predictive of developmental conditions. The authors sought to elucidate neurotypical females were on average significantly less the relationship between autism and typical sex-differential predictive of autistic females (ABIDE: Cohen’s d51.25; neuroanatomy, cognition, and related gene expression. LEAP: Cohen’s d51.29). These differences in sex prediction accuracy in autism were not observed in individuals Methods: Using a novel deep learning framework trained to with ADHD. In autistic females, the male-shifted neuropredict biological sex based on T1-weighted structural brain phenotype was further associated with poorer social images, the authors compared sex prediction model perforsensitivity and emotional face processing while also asmance across neurotypical and autistic males and females. sociated with gene expression patterns of midgestational Multiple large-scale data sets comprising T1-weighted MRI cell types. data were employed at four stages of the analysis pipeline: 1) pretraining, with the UK Biobank sample (.10,000 individuals); Conclusions: The results demonstrate an increased re-2) transfer learning and validation, with the ABIDE data sets semblance in both autistic male and female individuals’ (1,412 individuals, 5–56 years of age); 3) test and discovery, with neuroanatomy with male-characteristic patterns associated the EU-AIMS/AIMS-2-TRIALS LEAP data set (681 individuals, with typically sex-differential social cognitive features and 6–30 years of age); and 4) specificity, with the NeuroIMAGE related gene expression patterns. The findings hold promise and ADHD200 data sets (887 individuals, 7–26 years of age). for future research aimed at refining the quest for biological mechanisms underpinning the etiology of autism. Results: Across both ABIDE and LEAP, features positively predictive of neurotypical males were on average significantly Am J Psychiatry 2023; 180:50–64; doi: 10.1176/appi.ajp.20220194
AB - Objective: The male preponderance in prevalence of autism more predictive of autistic males (ABIDE: Cohen’s d50.48; is among the most pronounced sex ratios across neuroLEAP: Cohen’s d51.34). Features positively predictive of developmental conditions. The authors sought to elucidate neurotypical females were on average significantly less the relationship between autism and typical sex-differential predictive of autistic females (ABIDE: Cohen’s d51.25; neuroanatomy, cognition, and related gene expression. LEAP: Cohen’s d51.29). These differences in sex prediction accuracy in autism were not observed in individuals Methods: Using a novel deep learning framework trained to with ADHD. In autistic females, the male-shifted neuropredict biological sex based on T1-weighted structural brain phenotype was further associated with poorer social images, the authors compared sex prediction model perforsensitivity and emotional face processing while also asmance across neurotypical and autistic males and females. sociated with gene expression patterns of midgestational Multiple large-scale data sets comprising T1-weighted MRI cell types. data were employed at four stages of the analysis pipeline: 1) pretraining, with the UK Biobank sample (.10,000 individuals); Conclusions: The results demonstrate an increased re-2) transfer learning and validation, with the ABIDE data sets semblance in both autistic male and female individuals’ (1,412 individuals, 5–56 years of age); 3) test and discovery, with neuroanatomy with male-characteristic patterns associated the EU-AIMS/AIMS-2-TRIALS LEAP data set (681 individuals, with typically sex-differential social cognitive features and 6–30 years of age); and 4) specificity, with the NeuroIMAGE related gene expression patterns. The findings hold promise and ADHD200 data sets (887 individuals, 7–26 years of age). for future research aimed at refining the quest for biological mechanisms underpinning the etiology of autism. Results: Across both ABIDE and LEAP, features positively predictive of neurotypical males were on average significantly Am J Psychiatry 2023; 180:50–64; doi: 10.1176/appi.ajp.20220194
KW - Autism Spectrum Disorder
KW - Brain Imaging Techniques
KW - Gender Differences
KW - Machine Learning
KW - Neuroanatomy
KW - Neurodevelopmental Disorders
UR - http://www.scopus.com/inward/record.url?scp=85145344406&partnerID=8YFLogxK
U2 - 10.1176/appi.ajp.20220194
DO - 10.1176/appi.ajp.20220194
M3 - Article
C2 - 36415971
SN - 0002-953X
VL - 180
SP - 50
EP - 64
JO - American Journal of Psychiatry
JF - American Journal of Psychiatry
IS - 1
ER -