Siyi Tang1, Nanbo Sun2, Dorothea L Floris3, Xiuming Zhang4, Adriana Di Martino5, B T Thomas Yeo6. 1. Department of Electrical and Computer Engineering, Centre for Sleep and Cognition, Clinical Imaging Research Centre, N.1 Institute for Health, National University of Singapore, Singapore, Republic of Singapore; Department of Electrical Engineering, Stanford University, Stanford, California. 2. Department of Electrical and Computer Engineering, Centre for Sleep and Cognition, Clinical Imaging Research Centre, N.1 Institute for Health, National University of Singapore, Singapore, Republic of Singapore. 3. Donders Center for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands; Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands. 4. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts. 5. Autism and Social Cognition Center, Child Mind Institute, New York, New York. 6. Department of Electrical and Computer Engineering, Centre for Sleep and Cognition, Clinical Imaging Research Centre, N.1 Institute for Health, National University of Singapore, Singapore, Republic of Singapore; Centre for Cognitive Neuroscience, Duke-National University of Singapore Medical School, Singapore, Republic of Singapore; National University of Singapore Graduate School for Integrative Sciences and Engineering, Singapore, Republic of Singapore; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts. Electronic address: thomas.yeo@nus.edu.sg.
Abstract
BACKGROUND: Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide individuals with ASD into nonoverlapping (categorical) subgroups. However, continuous interindividual variation in ASD suggests that there is a need for a dimensional approach. METHODS: A Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of individuals with ASD into multiple abnormal RSFC patterns, i.e., categorical subtypes, henceforth referred to as "factors." Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 individuals with ASD (5.2-57 years of age) from two multisite repositories. Post hoc analyses associated factors with symptoms and demographics. RESULTS: Analyses yielded three factors with dissociable whole-brain hypo- and hyper-RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default mode network, but the directionality (hypo- or hyper-RSFC) differed across factors. Factor 1 was associated with core ASD symptoms. Factors 1 and 2 were associated with distinct comorbid symptoms. Older male participants preferentially expressed factor 3. Factors were robust across control analyses and were not associated with IQ or head motion. CONCLUSIONS: There exist at least three ASD factors with dissociable whole-brain RSFC patterns, behaviors, and demographics. Heterogeneous default mode network hypo- and hyper-RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms-a less appreciated domain of heterogeneity in ASD. These factors are coexpressed in individuals with ASD with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.
BACKGROUND: Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide individuals with ASD into nonoverlapping (categorical) subgroups. However, continuous interindividual variation in ASD suggests that there is a need for a dimensional approach. METHODS: A Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of individuals with ASD into multiple abnormal RSFC patterns, i.e., categorical subtypes, henceforth referred to as "factors." Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 individuals with ASD (5.2-57 years of age) from two multisite repositories. Post hoc analyses associated factors with symptoms and demographics. RESULTS: Analyses yielded three factors with dissociable whole-brain hypo- and hyper-RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default mode network, but the directionality (hypo- or hyper-RSFC) differed across factors. Factor 1 was associated with core ASD symptoms. Factors 1 and 2 were associated with distinct comorbid symptoms. Older male participants preferentially expressed factor 3. Factors were robust across control analyses and were not associated with IQ or head motion. CONCLUSIONS: There exist at least three ASD factors with dissociable whole-brain RSFC patterns, behaviors, and demographics. Heterogeneous default mode network hypo- and hyper-RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms-a less appreciated domain of heterogeneity in ASD. These factors are coexpressed in individuals with ASD with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.
Authors: Aki Nikolaidis; Charlotte Heleniak; Andrea Fields; Paul A Bloom; Michelle VanTieghem; Anna Vannucci; Nicolas L Camacho; Tricia Choy; Lisa Gibson; Chelsea Harmon; Syntia S Hadis; Ian J Douglas; Michael P Milham; Nim Tottenham Journal: Dev Psychopathol Date: 2022-03-22
Authors: Natasha Bertelsen; Isotta Landi; Richard A I Bethlehem; Jakob Seidlitz; Elena Maria Busuoli; Veronica Mandelli; Eleonora Satta; Stavros Trakoshis; Bonnie Auyeung; Prantik Kundu; Eva Loth; Guillaume Dumas; Sarah Baumeister; Christian F Beckmann; Sven Bölte; Thomas Bourgeron; Tony Charman; Sarah Durston; Christine Ecker; Rosemary J Holt; Mark H Johnson; Emily J H Jones; Luke Mason; Andreas Meyer-Lindenberg; Carolin Moessnang; Marianne Oldehinkel; Antonio M Persico; Julian Tillmann; Steve C R Williams; Will Spooren; Declan G M Murphy; Jan K Buitelaar; Simon Baron-Cohen; Meng-Chuan Lai; Michael V Lombardo Journal: Commun Biol Date: 2021-05-14