Lipidomics in Major Depressive Disorder - Walther, Andreas; Cannistraci, Carlo Vittorio; Simons, Kai; Durán, Claudio; Gerl, Mathias J.; Wehrli, Susanne; Kirschbaum, Clemens (Frontiers in Psychiatry, 2018)
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.