Journal article
Data-Driven Phenotypic Categorization for Neurobiological Analyses: Beyond DSM-5 Labels
Nicholas T Van Dam, David O'Connor, Enitan T Marcelle, Erica J Ho, R Cameron Craddock, Russell H Tobe, Vilma Gabbay, James J Hudziak, F Xavier Castellanos, Bennett L Leventhal, Michael P Milham
BIOLOGICAL PSYCHIATRY | ELSEVIER SCIENCE INC | Published : 2017
Abstract
BACKGROUND: Data-driven approaches can capture behavioral and biological variation currently unaccounted for by contemporary diagnostic categories, thereby enhancing the ability of neurobiological studies to characterize brain-behavior relationships. METHODS: A community-ascertained sample of individuals (N = 347, 18-59 years of age) completed a battery of behavioral measures, psychiatric assessment, and resting-state functional magnetic resonance imaging in a cross-sectional design. Bootstrap-based exploratory factor analysis was applied to 49 phenotypic subscales from 10 measures. Hybrid hierarchical clustering was applied to resultant factor scores to identify nested groups. Adjacent grou..
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Awarded by National Institute of Mental Health
Awarded by Child Mind Institute
Awarded by NATIONAL INSTITUTE OF MENTAL HEALTH
Funding Acknowledgements
This study was supported by National Institute of Mental Health Grant Nos. R01MH094639 (to MPM), R01MH081218 (to FXC), R01MH083246 (to FXC), and R21MH084126, with additional funding for personnel and administrative support provided by a grant from the Child Mind Institute (1FDN2012-1 to MPM) and funds from the New York State Office of Mental Health, the Research Foundation for Mental Hygiene, the Brain Research Foundation, and the Stavros Niarchos Foundation. Additional funds were provided by gifts from Phyllis Green, Randolph Cowen, and Joseph P. Healey.