@article{bb9083b1aa414e9cbf9f27d0a78ad488,
title = "A morphometric signature of depressive symptoms in unmedicated patients with mood disorders",
abstract = "Objective: A growing literature indicates that unipolar depression and bipolar depression are associated with alterations in grey matter volume. However, it is unclear to what degree these patterns of morphometric change reflect symptom dimensions. Here, we aimed to predict depressive symptoms and hypomanic symptoms based on patterns of grey matter volume using machine learning. Method: We used machine learning methods combined with voxel-based morphometry to predict depressive and self-reported hypomanic symptoms from grey matter volume in a sample of 47 individuals with unmedicated unipolar and bipolar depression. Results: We were able to predict depressive severity from grey matter volume in the anteroventral bilateral insula in both unipolar depression and bipolar depression. Self-reported hypomanic symptoms did not predict grey matter loss with a significant degree of accuracy. Discussion: The results of this study suggest that patterns of grey matter volume alteration in the insula are associated with depressive symptom severity across unipolar and bipolar depression. Studies using other modalities and exploring other brain regions with a larger sample are warranted to identify other systems that may be associated with depressive and hypomanic symptoms across affective disorders.",
keywords = "DARTEL, MRI, Machine learning, VBM, bipolar disorder, depression, magnetic resonance imaging",
author = "T. Wise and L. Marwood and Perkins, {A. M.} and A. Herane-Vives and Williams, {S. C.R.} and Young, {A. H.} and Cleare, {A. J.} and D. Arnone",
note = "Funding Information: This research was funded by Academy of Medical Sciences grant AMS-SGCL8 to DA, a National Institute of Health Research (NIHR) PhD studentship to TW supervised by AJC and DA, a Medical Research Council (MRC) / IoPPN Excellence PhD studentship to LM, supervised by AJC and AMP and departmental funds generated by AJC and SCRW. DA, AJC, AMP, SCRW, TW and AHY have received support from the NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. TW receives funding support from the Wellcome Trust. AHV was supported by a Chilean Bicentennial Fund Scholarship from the Bicentennial Fund for Human Capital Development (Becas Chile) and by the Psychiatric Research Trust. This study represents independent research part funded by the NIHR/Wellcome Trust, King's Clinical Research Facility and the NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. The views expressed are those of the author(s) and not necessarily those of the NHS, NIHR, MRC, The Academy of Medical Sciences Mental Health Research Network (MHRN) or the Department of Health. AHV was supported by a Chilean Bicentennial Fund Scholarship from the Bicentennial Fund for Human Capital Development (Becas Chile) and by the Psychiatric Research Trust. The authors would like to thank the staff of the NIHR/Wellcome Trust Clinical Research Facility at King's College Hospital, the Centre for Neuroimaging Science at King's College London and Dean Broadhurst, and Michael Kelly of the MHRN for their support in the conduct of the study. We thank all participants of this study for their support. The funders had no role in design and conduct of the study, collection, management, analysis, data interpretation, preparation, review, approval of the manuscript and decision to submit for publication. Publisher Copyright: {\textcopyright} 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd",
year = "2018",
month = jul,
doi = "10.1111/acps.12887",
language = "English",
volume = "138",
pages = "73--82",
journal = "Acta Psychiatrica Scandinavica",
issn = "0001-690X",
publisher = "Wiley-Blackwell",
number = "1",
}