TY  - JOUR
A1  - Kittel-Schneider, Sarah
A1  - Hahn, Tim
A1  - Haenisch, Frieder
A1  - McNeill, Rhiannon
A1  - Reif, Andreas
A1  - Bahn, Sabine
T1  - Proteomic profiling as a diagnostic biomarker for discriminating between bipolar and unipolar depression
T2  - Frontiers in psychiatry
N2  - Introduction: Affective disorders are a major global burden, with approximately 15% of people worldwide suffering from some form of affective disorder. In patients experiencing their first depressive episode, in most cases it cannot be distinguished whether this is due to bipolar disorder (BD) or major depressive disorder (MDD). Valid fluid biomarkers able to discriminate between the two disorders in a clinical setting are not yet available.
Material and Methods: Seventy depressed patients suffering from BD (bipolar I and II subtypes) and 42 patients with major MDD were recruited and blood samples were taken for proteomic analyses after 8 h fasting. Proteomic profiles were analyzed using the Multiplex Immunoassay platform from Myriad Rules Based Medicine (Myriad RBM; Austin, Texas, USA). Human DiscoveryMAPTM was used to measure the concentration of various proteins, peptides, and small molecules. A multivariate predictive model was consequently constructed to differentiate between BD and MDD.
Results: Based on the various proteomic profiles, the algorithm could discriminate depressed BD patients from MDD patients with an accuracy of 67%.
Discussion: The results of this preliminary study suggest that future discrimination between bipolar and unipolar depression in a single case could be possible, using predictive biomarker models based on blood proteomic profiling.
KW  - affective disorder
KW  - bipolar disorder
KW  - major depression (MD)
KW  - major depressive disorder (MDD)
KW  - proteome
KW  - biomarker
KW  - blood
KW  - machine learning
Y1  - 2020
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/54473
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-544730
SN  - 1664-0640
N1  - Copyright © 2020 Kittel-Schneider, Hahn, Haenisch, McNeill, Reif and Bahn. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
VL  - 11
IS  - article 189
SP  - 1
EP  - 7
PB  - Frontiers Research Foundation
CY  - Lausanne
ER  -