title: Functional connectivity magnetic resonance imaging classification of autism.
abstract: Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear whether functional connectivity is sufficiently robust to be used as a diagnostic or prognostic metric in individual patients with autism. We obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the entire grey matter (26.4 million connections) in a well-characterized set of 40 male adolescents and young adults with autism and 40 age-, sex- and IQ-matched typically developing subjects. A single resting state blood oxygen level-dependent scan of 8 min was used for the classification in each subject. A leave-one-out classifier successfully distinguished autism from control subjects with 83% sensitivity and 75% specificity for a total accuracy of 79% (P = 1.1 × 10(-7)). In subjects <20 years of age, the classifier performed at 89% accuracy (P = 5.4 × 10(-7)). In a replication dataset consisting of 21 individuals from six families with both affected and unaffected siblings, the classifier performed at 71% accuracy (91% accuracy for subjects <20 years of age). Classification scores in subjects with autism were significantly correlated with the Social Responsiveness Scale (P = 0.05), verbal IQ (P = 0.02) and the Autism Diagnostic Observation Schedule-Generic's combined social and communication subscores (P = 0.05). An analysis of informative connections demonstrated that region of interest pairs with strongest correlation values were most abnormal in autism. Negatively correlated region of interest pairs showed higher correlation in autism (less anticorrelation), possibly representing weaker inhibitory connections, particularly for long connections (Euclidean distance >10 cm). Brain regions showing greatest differences included regions of the default mode network, superior parietal lobule, fusiform gyrus and anterior insula. Overall, classification accuracy was better for younger subjects, with differences between autism and control subjects diminishing after 19 years of age. Classification scores of unaffected siblings of individuals with autism were more similar to those of the control subjects than to those of the subjects with autism. These findings indicate feasibility of a functional connectivity magnetic resonance imaging diagnostic assay for autism.
authors: Department of Neuroradiology, University of Utah, 1A71 School of Medicine, Salt Lake City, UT 84132, USA. andersonjeffs@gmail.com
authors: Jeffrey S
authors: JS
authors: Anderson
authors: Jared A
authors: JA
authors: Nielsen
authors: Alyson L
authors: AL
authors: Froehlich
authors: Molly B
authors: MB
authors: DuBray
authors: T Jason
authors: TJ
authors: Druzgal
authors: Annahir N
authors: AN
authors: Cariello
authors: Jason R
authors: JR
authors: Cooperrider
authors: Brandon A
authors: BA
authors: Zielinski
authors: Caitlin
authors: C
authors: Ravichandran
authors: P Thomas
authors: PT
authors: Fletcher
authors: Andrew L
authors: AL
authors: Alexander
authors: Erin D
authors: ED
authors: Bigler
authors: Nicholas
authors: N
authors: Lange
authors: Janet E
authors: JE
authors: Lainhart
mesh_terms: D000293:Adolescent; D001321:Autistic Disorder / Q000145:classification* / Q000175:diagnosis / Q000503:physiopathology; D001921:Brain / Q000503:physiopathology*; D001931:Brain Mapping; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D009434:Neural Pathways / Q000503:physiopathology; D012680:Sensitivity and Specificity; D055815:Young Adult