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Distinguishing bipolar from unipolar depression: the importance of clinical symptoms and illness features

  • A. K. Leonpacher (a1), D. Liebers (a1), M. Pirooznia (a1), D. Jancic (a2), D. F. MacKinnon (a1), F. M. Mondimore (a1), B. Schweizer (a1), J. B. Potash (a2), P. P. Zandi (a1) (a3), NIMH Genetics Initiative Bipolar Disorder Consortium, GenRED Consortium and F. S. Goes (a1)...
Abstract
Background

Distinguishing bipolar disorder (BP) from major depressive disorder (MDD) has important relevance for prognosis and treatment. Prior studies have identified clinical features that differ between these two diseases but have been limited by heterogeneity and lack of replication. We sought to identify depression-related features that distinguish BP from MDD in large samples with replication.

Method

Using a large, opportunistically ascertained collection of subjects with BP and MDD we selected 34 depression-related clinical features to test across the diagnostic categories in an initial discovery dataset consisting of 1228 subjects (386 BPI, 158 BPII and 684 MDD). Features significantly associated with BP were tested in an independent sample of 1000 BPI cases and 1000 MDD cases for classifying ability in receiver operating characteristic (ROC) analysis.

Results

Seven clinical features showed significant association with BPI compared with MDD: delusions, psychomotor retardation, incapacitation, greater number of mixed symptoms, greater number of episodes, shorter episode length, and a history of experiencing a high after depression treatment. ROC analyses of a model including these seven factors showed significant evidence for discrimination between BPI and MDD in an independent dataset (area under the curve = 0.83). Only two features (number of mixed symptoms, and feeling high after an antidepressant) showed an association with BPII versus MDD.

Conclusions

Our study suggests that clinical features distinguishing depression in BPI versus MDD have important classification potential for clinical practice, and should also be incorporated as ‘baseline’ features in the evaluation of novel diagnostic biomarkers.

Copyright
Corresponding author
* Address for correspondence: F. S. Goes, M.D., Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Meyer 4-119A, 600 N. Wolfe Street, Baltimore, MD 21287, USA. (Email: fgoes1@jhmi.edu)
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