Billets de Michelle Dawson
Liens cités structurés
Dorothea L. Floris, Han Peng, Varun Warrier, Michael V. Lombardo, Charlotte M. Pretzsch, Clara Moreau, Alexandros Tsompanidis, Weikang Gong, et al. (2022). The link between autism and sex-specific neuroanatomy, and associated cognition and gene expression. openRxiv.
Résumé
ABSTRACT Objectives The male preponderance in autism spectrum conditions (ASC) prevalence is among the most pronounced sex ratios across different neurodevelopmental conditions. Here, we aimed to elucidate the relationship between autism and typical sex-differential neuroanatomy, cognition, and related gene expression. Methods Using a novel deep learning framework trained to predict biological sex, we compared sex prediction model performance across neurotypical and autistic males and females. Multiple large-scale datasets were employed at different stages of the analysis pipeline: a) Pre-training: the UK Biobank sample (>10.000 individuals); b) Transfer learning and validation: the ABIDE datasets (1,412 individuals, 5-56 years of age); c) Test and discovery: the EU-AIMS/AIMS-2-TRIALS LEAP dataset (681 individuals, 6-30 years of age) and d) Specificity: the Neuroimage and ADHD200 datasets (887 individuals, 7-26 years of age). Results Across both ABIDE and LEAP we showed that features positively predictive of neurotypical males were on average more predictive of autistic males (P =1.1e-23). Features positively predictive of neurotypical females were on average less predictive of autistic females (P =1.2e-22). These accuracy differences in autism were not observed in individuals with ADHD. In autistic females the male-shifted neurophenotype was further associated with poorer social sensitivity and emotional face processing while also with associated gene expression patterns of midgestational cell types. Conclusions Our results demonstrate a shift in both autistic male and female individuals’ neuroanatomy towards male-characteristic patterns associated with typically sex-differential, social cognitive features and related gene expression patterns. Findings hold promise for future research aimed at refining the quest for biological mechanisms underpinning the etiology of autism.
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