title: Diagnostic potential of structural neuroimaging for depression from a multi-ethnic community sample.
abstract: BACKGROUND
  At present, we do not have any biological tests which can contribute towards a diagnosis of depression. Neuroimaging measures have shown some potential as biomarkers for diagnosis. However, participants have generally been from the same ethnic background while the applicability of a biomarker would require replication in individuals of diverse ethnicities.
  
  
  OBJECTIVE
  We sought to examine the diagnostic potential of the structural neuroanatomy of depression in a sample of a wide ethnic diversity.
  
  
  METHODS
  Structural magnetic resonance imaging (MRI) scans were obtained from 23 patients with major depressive disorder in an acute depressive episode (mean age: 39.8 years) and 20 matched healthy volunteers (mean age: 38.8 years). Participants were of Asian, African and Caucasian ethnicity recruited from the general community.
  
  
  RESULTS
  Structural neuroanatomy combining white and grey matter distinguished patients from controls at the highest accuracy of 81% with the most stable pattern being at around 70%. A widespread network encompassing frontal, parietal, occipital and cerebellar regions contributed towards diagnostic classification.
  
  
  CONCLUSIONS
  These findings provide an important step in the development of potential neuroimaging-based tools for diagnosis as they demonstrate that the identification of depression is feasible within a multi-ethnic group from the community.
  
  
  BACKGROUND
  C.H.Y.F. has held recent research grants from Eli Lilly and Company and GlaxoSmithKline. L.M. is a former employee and stockholder of Eli Lilly and Company.
  © The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence.
authors.affiliation: PhD, Centre for Affective Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
authors.forename: Anjali
authors.initials: A
authors.lastname: Sankar
authors.affiliation: PhD, Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Pennsylvania, USA.
authors.forename: Tianhao
authors.initials: T
authors.lastname: Zhang
authors.affiliation: MS, Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Pennsylvania, USA.
authors.forename: Bilwaj
authors.initials: B
authors.lastname: Gaonkar
authors.affiliation: MS, Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Pennsylvania, USA.
authors.forename: Jimit
authors.initials: J
authors.lastname: Doshi
authors.affiliation: PhD, Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Pennsylvania, USA.
authors.forename: Guray
authors.initials: G
authors.lastname: Erus
authors.affiliation: MD, Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK.
authors.forename: Sergi G
authors.initials: SG
authors.lastname: Costafreda
authors.affiliation: MD, Department of Psychiatry, University of Texas Health Science Center, Houston, Texas, USA.
authors.forename: Lauren
authors.initials: L
authors.lastname: Marangell
authors.affiliation: PhD, Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Pennsylvania, USA.
authors.forename: Christos
authors.initials: C
authors.lastname: Davatzikos
authors.affiliation: MD, School of Psychology, University of East London, London, UK.
authors.forename: Cynthia H Y
authors.initials: CH
authors.lastname: Fu