PMID- 27870505
OWN - NLM
STAT- MEDLINE
DCOM- 20171003
LR  - 20181202
IS  - 1399-5618 (Electronic)
IS  - 1398-5647 (Linking)
VI  - 18
IP  - 7
DP  - 2016 Nov
TI  - Distinguishing medication-free subjects with unipolar disorder from subjects with 
      bipolar disorder: state matters.
PG  - 612-623
LID - 10.1111/bdi.12446 [doi]
AB  - OBJECTIVES: Recent studies have indicated that pattern recognition techniques of 
      functional magnetic resonance imaging (fMRI) data for individual classification 
      may be valuable for distinguishing between major depressive disorder (MDD) and 
      bipolar disorder (BD). Importantly, medication may have affected previous 
      classification results as subjects with MDD and BD use different classes of 
      medication. Furthermore, almost all studies have investigated only depressed 
      subjects. Therefore, we focused on medication-free subjects. We additionally 
      investigated whether classification would be mood state independent by including 
      depressed and remitted subjects alike. METHODS: We applied Gaussian process 
      classifiers to investigate the discriminatory power of structural MRI (gray 
      matter volumes of emotion regulation areas) and resting-state fMRI (resting-state 
      networks implicated in mood disorders: default mode network [DMN], salience 
      network [SN], and lateralized frontoparietal networks [FPNs]) in depressed (n=42) 
      and remitted (n=49) medication-free subjects with MDD and BD. RESULTS: Depressed 
      subjects with MDD and BD could be classified based on the gray matter volumes of 
      emotion regulation areas as well as DMN functional connectivity with 69.1% 
      prediction accuracy. Prediction accuracy using the FPNs and SN did not exceed 
      chance level. It was not possible to discriminate between remitted subjects with 
      MDD and BD. CONCLUSIONS: For the first time, we showed that medication-free 
      subjects with MDD and BD can be differentiated based on structural MRI as well as 
      resting-state functional connectivity. Importantly, the results indicated that 
      research concerning diagnostic neuroimaging tools distinguishing between MDD and 
      BD should consider mood state as only depressed subjects with MDD and BD could be 
      correctly classified. Future studies, in larger samples are needed to investigate 
      whether the results can be generalized to medication-naive or first-episode 
      subjects.
CI  - (c) 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
FAU - Rive, Maria M
AU  - Rive MM
AD  - Program for Mood Disorders, Department of Psychiatry, Academic Medical Center, 
      University of Amsterdam, Amsterdam, the Netherlands.
FAU - Redlich, Ronny
AU  - Redlich R
AD  - Department of Psychiatry, University of Munster, Munster, Germany.
FAU - Schmaal, Lianne
AU  - Schmaal L
AD  - Department of Psychiatry and Neuroscience, Campus Amsterdam, VU University 
      Medical Center, Amsterdam, the Netherlands.
FAU - Marquand, Andre F
AU  - Marquand AF
AD  - Donders Institute for Brain, Cognition and Behaviour, Radboud University, 
      Nijmegen, the Netherlands.
FAU - Dannlowski, Udo
AU  - Dannlowski U
AD  - Department of Psychiatry, University of Munster, Munster, Germany.
FAU - Grotegerd, Dominik
AU  - Grotegerd D
AD  - Department of Psychiatry, University of Munster, Munster, Germany.
FAU - Veltman, Dick J
AU  - Veltman DJ
AD  - Department of Psychiatry, VU University Medical Center, Amsterdam, the 
      Netherlands.
FAU - Schene, Aart H
AU  - Schene AH
AD  - Program for Mood Disorders, Department of Psychiatry, Academic Medical Center, 
      University of Amsterdam, Amsterdam, the Netherlands.
AD  - Donders Institute for Brain, Cognition and Behaviour, Radboud University, 
      Nijmegen, the Netherlands.
AD  - Department of Psychiatry, Radboud University Medical Center, Nijmegen, the 
      Netherlands.
FAU - Ruhe, Henricus G
AU  - Ruhe HG
AD  - Program for Mood Disorders, Department of Psychiatry, Academic Medical Center, 
      University of Amsterdam, Amsterdam, the Netherlands.
AD  - Department of Psychiatry, Mood and Anxiety Disorders, University of Groningen, 
      University Medical Center Groningen, Groningen, the Netherlands.
LA  - eng
PT  - Journal Article
DEP - 20161105
PL  - Denmark
TA  - Bipolar Disord
JT  - Bipolar disorders
JID - 100883596
SB  - IM
MH  - Adult
MH  - Bipolar Disorder/*diagnosis/physiopathology/psychology
MH  - Depressive Disorder, Major/*diagnosis/physiopathology/psychology
MH  - Diagnosis, Differential
MH  - Female
MH  - Gray Matter/pathology
MH  - Humans
MH  - Magnetic Resonance Imaging/methods
MH  - Male
MH  - Middle Aged
MH  - Nerve Net/physiopathology
MH  - Organ Size
OTO - NOTNLM
OT  - fMRI
OT  - bipolar disorder
OT  - diagnosis
OT  - machine learning
OT  - major depressive disorder
OT  - mood state
EDAT- 2016/11/22 06:00
MHDA- 2017/10/04 06:00
CRDT- 2016/11/22 06:00
PHST- 2016/05/18 00:00 [received]
PHST- 2016/10/01 00:00 [accepted]
PHST- 2016/11/22 06:00 [entrez]
PHST- 2016/11/22 06:00 [pubmed]
PHST- 2017/10/04 06:00 [medline]
AID - 10.1111/bdi.12446 [doi]
PST - ppublish
SO  - Bipolar Disord. 2016 Nov;18(7):612-623. doi: 10.1111/bdi.12446. Epub 2016 Nov 5.