S
Stephen V. Faraone
Researcher at State University of New York Upstate Medical University
Publications - 1470
Citations - 155368
Stephen V. Faraone is an academic researcher from State University of New York Upstate Medical University. The author has contributed to research in topics: Attention deficit hyperactivity disorder & Bipolar disorder. The author has an hindex of 188, co-authored 1427 publications receiving 140298 citations. Previous affiliations of Stephen V. Faraone include University of Bergen & National Institute for Health Research.
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Journal ArticleDOI
Impact of low birth weight on attention-deficit hyperactivity disorder.
TL;DR: It is found that low birth weight (LBW) is an independent risk factor for ADHD, and children with LBW make up a relatively small proportion of children with ADHD.
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Does attention-deficit hyperactivity disorder impact the developmental course of drug and alcohol abuse and dependence?
TL;DR: In this paper, the authors examined the effects of ADHD on the transitions from substance abuse to dependence and between different classes of agents of abuse and found that ADHD was associated with a twofold increased risk for PSUD.
Journal ArticleDOI
Diagnosing Adult Attention Deficit Hyperactivity Disorder: Are Late Onset and Subthreshold Diagnoses Valid?
Stephen V. Faraone,Joseph Biederman,Thomas J. Spencer,Eric Mick,Kate Murray,Carter R. Petty,Joel J. Adamson,Michael C. Monuteaux +7 more
TL;DR: The data about the clinical features of probands and the pattern of transmission of ADHD among relatives found little evidence for the validity of subthreshold ADHD among such subjects, who reported a lifetime history of some symptoms that never met DSM-IV's threshold for diagnosis.
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In vivo neuroreceptor imaging in attention-deficit/hyperactivity disorder: a focus on the dopamine transporter.
Thomas J. Spencer,Joseph Biederman,Bertha K. Madras,Stephen V. Faraone,Darin D. Dougherty,Ali A. Bonab,Alan J. Fischman +6 more
TL;DR: Although there is fair agreement regarding the presence and direction of abnormal DAT binding, there remains disagreement as to the magnitude of the finding and the importance of many potentially confounding variables, including clinical characteristics and imaging methodology.
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New models of collaboration in genome-wide association studies: the Genetic Association Information Network
Teri A. Manolio,Laura Lyman Rodriguez,Lisa D. Brooks,Gonçalo R. Abecasis,Dennis G. Ballinger,Mark J. Daly,Peter Donnelly,Stephen V. Faraone,Kelly A. Frazer,Stacey Gabriel,Pablo V. Gejman,Alan E. Guttmacher,Emily L. Harris,Thomas R. Insel,John R. Kelsoe,Eric S. Lander,Norma McCowin,Matthew D. Mailman,Matthew D. Mailman,Elizabeth G. Nabel,James Ostell,Elizabeth W. Pugh,Stephen T. Sherry,Patrick F. Sullivan,John F. Thompson,James H. Warram,David Wholley,Patrice M. Milos,Francis S. Collins +28 more
TL;DR: GAIN has used new approaches for project selection, data deposition and distribution, collaborative analysis, publication and protection from premature intellectual property claims that demonstrate a new commitment to shared scientific knowledge that should facilitate rapid advances in understanding the genetics of complex diseases.