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Front. Psychiatry | doi: 10.3389/fpsyt.2018.00459

Lipidomics in major depressive disorder: a systematic review

 Andreas Walther1, 2*,  Carlo V. Cannistraci2, 3,  Kai Simons2, Mathias J. Gerl2, Claudio Duran2, 3,  Susanne Wehrli1, 2 and Clemens Kirschbaum1, 2
  • 1Biological Psychology, Technische Universität Dresden, Germany
  • 2Lipotype, Biotechnological Center TU Dresden, Technische Universität Dresden, Germany
  • 3Biomedical Cybernetics, Biotechnological Center TU Dresden, Technische Universität Dresden, Germany

Omic sciences coupled with novel computational approaches such as machine intelligence offer completely new approaches to major depressive disorder (MDD) research. The complexity of MDD’s pathophysiology is being integrated into studies examining MDD’s biology within the omic fields. Lipidomics, as a late-comer among other omic fields, is increasingly being recognized for its role in the development and progression of MDD. Combinatorial lipid-markers with high classification power are being developed in order to assist MDD diagnosis, while rodent models of depression reveal lipidome changes and thereby unveil novel treatment targets for depression. In this systematic review, we provide an overview of current breakthroughs and future trends in the field of lipidomics in MDD research and thereby paving the way for precision medicine in MDD.

Keywords: Major Depressive Disorder, Depression, Lipids, lipidomics, precision psychiatry, Computational Psychiatry, cortisol, Glucocorticoids, Inflammation

Received: 07 May 2018; Accepted: 04 Sep 2018.

Edited by:

Stefan Borgwardt, Universität Basel, Switzerland

Reviewed by:

Stefania Schiavone, University of Foggia, Italy
Jennifer C. Felger, Emory University, United States  

Copyright: © 2018 Walther, Cannistraci, Simons, Gerl, Duran, Wehrli and Kirschbaum. 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.

* Correspondence: Dr. Andreas Walther, Technische Universität Dresden, Biological Psychology, Zellescher Weg 19 / 206, Dresden, 01069, Dresden, Germany,