title: Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example.
abstract: Resting-state functional Magnetic Resonance Imaging (R-fMRI) holds the promise to reveal functional biomarkers of neuropsychiatric disorders. However, extracting such biomarkers is challenging for complex multi-faceted neuropathologies, such as autism spectrum disorders. Large multi-site datasets increase sample sizes to compensate for this complexity, at the cost of uncontrolled heterogeneity. This heterogeneity raises new challenges, akin to those face in realistic diagnostic applications. Here, we demonstrate the feasibility of inter-site classification of neuropsychiatric status, with an application to the Autism Brain Imaging Data Exchange (ABIDE) database, a large (N=871) multi-site autism dataset. For this purpose, we investigate pipelines that extract the most predictive biomarkers from the data. These R-fMRI pipelines build participant-specific connectomes from functionally-defined brain areas. Connectomes are then compared across participants to learn patterns of connectivity that differentiate typical controls from individuals with autism. We predict this neuropsychiatric status for participants from the same acquisition sites or different, unseen, ones. Good choices of methods for the various steps of the pipeline lead to 67% prediction accuracy on the full ABIDE data, which is significantly better than previously reported results. We perform extensive validation on multiple subsets of the data defined by different inclusion criteria. These enables detailed analysis of the factors contributing to successful connectome-based prediction. First, prediction accuracy improves as we include more subjects, up to the maximum amount of subjects available. Second, the definition of functional brain areas is of paramount importance for biomarker discovery: brain areas extracted from large R-fMRI datasets outperform reference atlases in the classification tasks.
authors.affiliation: Parietal Team, Saclay-INRIA le-de-France,Saclay,France; CEA, Neurospin bât 145, 91191 Gif-Sur-Yvette, France. Electronic address: abraham.alexandre@gmail.com.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Abraham
authors.affiliation: Center for the Developing Brain, Child Mind Institute, New York, USA; Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
authors.forename: Michael P
authors.initials: MP
authors.lastname: Milham
authors.affiliation: The Child Study Center at NYU Langone Medical Center, New York, USA.
authors.forename: Adriana
authors.initials: A
authors.lastname: Di Martino
authors.affiliation: Center for the Developing Brain, Child Mind Institute, New York, USA; Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
authors.forename: R Cameron
authors.initials: RC
authors.lastname: Craddock
authors.affiliation: Stony Brook University, NY 11794, USA; Ecole Centrale, 92290 Châtenay Malabry, France.
authors.forename: Dimitris
authors.initials: D
authors.lastname: Samaras
authors.affiliation: Parietal Team, Saclay-INRIA le-de-France,Saclay,France; CEA, Neurospin bât 145, 91191 Gif-Sur-Yvette, France.
authors.forename: Bertrand
authors.initials: B
authors.lastname: Thirion
authors.affiliation: Parietal Team, Saclay-INRIA le-de-France,Saclay,France; CEA, Neurospin bât 145, 91191 Gif-Sur-Yvette, France.
authors.forename: Gael
authors.initials: G
authors.lastname: Varoquaux
mesh_terms: D000293:Adolescent; D000328:Adult; D000067877:Autism Spectrum Disorder / Q000000981:diagnostic imaging*; D015415:Biomarkers; D002540:Cerebral Cortex / Q000000981:diagnostic imaging / Q000503:physiopathology*; D002648:Child; D063132:Connectome / Q000379:methods* / Q000592:standards; D066264:Datasets as Topic / Q000592:standards; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000592:standards; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000592:standards; D015337:Multicenter Studies as Topic / Q000379:methods* / Q000592:standards; D015203:Reproducibility of Results
chemical_list: D015415:Biomarkers
keywords: Autism spectrum disorders; Biomarkers; Connectome; Data heterogeneity; Data pipelines; Resting-state fMRI