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Lipidomics in Major Depressive Disorder

期刊

FRONTIERS IN PSYCHIATRY
卷 9, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fpsyt.2018.00459

关键词

major depressive disorder; depression; lipidomics; machine learning; computational psychiatry; cortisol; inflammation; prostaglandin

资金

  1. German Research Foundation
  2. Open Access Publication Funds of the TU Dresden

向作者/读者索取更多资源

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 in psychiatric research because it has allowed the investigation of global lipid perturbations in patients suffering from MDD and indicated a crucial role of specific patterns of lipid alterations 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.

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