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Cerebrospinal fluid biomarkers for major depression confirm relevance of associated pathophysiology
Authors:Ditzen Claudia  Tang Ning  Jastorff Archana M  Teplytska Larysa  Yassouridis Alexander  Maccarrone Giuseppina  Uhr Manfred  Bronisch Thomas  Miller Christine A  Holsboer Florian  Turck Christoph W
Affiliation:Max Planck Institute of Psychiatry, Munich, Germany. ditzen@mpipsykl.mpg.de
Abstract:Individual characteristics of pathophysiology and course of depressive episodes are at present not considered in diagnostics. There are no biological markers available that can assist in categorizing subtypes of depression and detecting molecular variances related to disease-causing mechanisms between depressed patients. Identification of such differences is important to create patient subgroups, which will benefit from medications that specifically target the pathophysiology underlying their clinical condition. To detect characteristic biological markers for major depression, we analyzed the cerebrospinal fluid (CSF) proteome of depressed vs control persons, using two-dimensional polyacrylamide gel electrophoresis and time-of-flight (TOF) mass spectrometry peptide profiling. Proteins of interest were identified by matrix-assisted laser desorption ionization TOF mass spectrometry (MALDI-TOF-MS). Validation of protein markers was performed by immunoblotting. We found 11 proteins and 144 peptide features that differed significantly between CSF from depressed patients and controls. In addition, we detected differences in the phosphorylation pattern of several CSF proteins. A subset of the differentially expressed proteins implicated in brain metabolism or central nervous system disease was validated by immunoblotting. The identified proteins are involved in neuroprotection and neuronal development, sleep regulation, and amyloid plaque deposition in the aging brain. This is one of the first hypothesis-free studies that identify characteristic protein expression differences in CSF of depressed patients. Proteomic approaches represent a powerful tool for the identification of disease markers for subgroups of patients with major depression.
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