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Comprehending depression through proteomics

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Comprehendingdepressionthroughproteomics
DanielMartinsdeSouza
TheInternationalJournalofNeuropsychopharmacology/Volume15/Issue10/November2012,pp13731374
DOI:10.1017/S146114571200034X,Publishedonline:17April2012
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DanielMartinsdeSouza(2012).Comprehendingdepressionthroughproteomics.TheInternationalJournalof
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Comprehending depression through proteomics
Daniel Martins-de-Souza
Max Planck Institute of Psychiatry, Munich, Germany
Received 14 March 2012; Reviewed 14 March 2012; Revised 15 March 2012 ; Accepted 15 March 2012 ;
First published online 17 April 2012
Even being a severe neuropsychiatric disorder affect-
ing approximately 10 % of the population worldwide,
the molecular mechanisms underlying depression,
unipolar depression, clinical depression or major de-
pressive disorder (MDD) are still to be comprehended
(Fava & Kendler, 2000). One of the main challenges is
to understand how the multifactorial characteristics of
MDD – which come from genetic or metabolic predis-
position triggered by environmental factors – are con-
nected to each other. But in order to understand their
interaction, it is necessary to characterize each one of
these factors.
Key molecular components of MDD such as gen-
etics (Goltser-Dubner et al. 2010), gene expression
(Mehta et al. 2010) and a range of studies in preclinical
models (Muller & Holsboer, 2006) have been inves-
tigated. But one of the key components of the mol-
ecular basis of MDD – the proteome – has just started
to be characterized in human tissues. Proteome was
defined around 15 years ago as the total set of ex-
pressed proteins by a cell, tissue or organism at a given
time under a determined condition (Wilkins et al.
1996). This definition led to the science currently
known as proteomics that also included the study of
protein–protein interactions and post-translational
modifications. The identification of sets of differen-
tially expressed proteins or even the differential post-
translational modifications of proteins while studying
samples from MDD patients may lead to two main
outcomes: (1) revealing proteins, and consequently
metabolites and biochemical pathways which may
shed light on the comprehension of pathological
states; (2) revealing biomarker candidates with
potential for therapeutic applications (Martins-
de-Souza et al. 2010). Non-hypothesis-driven pro-
teomic applications offer different insights of MDD by
complementing those provided by the standard tar-
geted methodologies.
Regarding the molecular comprehension of MDD,
post-mortem dorsolateral prefrontal cortex from 24
MDD patients and 12 matched controls were analysed
using label-free proteomics. Distinct proteome finger-
prints between MDD and controls associated with
energy metabolism and synaptic function were ob-
served. Additionally, differential proteome profiles in
MDD with and without psychosis were assessed
showing a marked overlap to proteome changes seen
in schizophrenia brains (Martins-de-Souza et al.
2012a). Complementarily, a shotgun proteomics ap-
proach has been used also to identify differences in the
phosphorylation of brain proteins compared to con-
trols. The majority of phosphorylation differences
were associated with synaptic transmission and cellu-
lar architecture (Martins-de-Souza et al. 2012b). Other
studies in brain tissue from MDD patients were per-
formed previously using anterior cingulate cortex
(ACC) and frontal cortex (FC) (Beasley et al. 2006 ;
Johnston-Wilson et al. 2000). Both showed the altered
expression of carbonic anhydrase (CA2) and Aldolase
C (ALDOC), suggesting effects on energy metabolism.
Additionally, dihydropyrimidinase-related protein-2
(DPYSL2) was also found common to both studies,
but down-regulated in FC and up-regulated in ACC.
However, these studies focused on schizophrenia
using MDD samples as controls for specificity.
Considering the lack of biochemical markers for
MDD that could aid, for instance in patient stratifi-
cation, the proteome of the cerebrospinal fluid
(CSF) from 12 MDD patients and 12 controls were
evaluated recently (Ditzen et al. 2012). Using
traditional proteomic methodologies such as two-
dimensional gel electrophoresis followed by matrix-
assisted laser desorption ionization–time-of-flight–
mass spectrometry (MALDI-TOF-MS), 11 proteins
were observed as differentially expressed including
Address for correspondence : Dr D. Martins-de-Souza, Max Planck
Institute of Psychiatry, Proteomics and Biomarkers, Kraepelinstr.
2, D-80804 Munich, Germany.
Tel. :+49 89 30622 630 Fax :+49 89 30622 200
Email : martins@mpipsykl.mpg.de
See Xu et al. (2012). Comparative proteomic analysis of plasma
from major depressive patients : identification of proteins
associated with lipid metabolism and immunoregulation
(doi :S1461145712000302).
International Journal of Neuropsychopharmacology (2012), 15, 1373–1374. fCINP 2012
doi:10.1017/S146114571200034X
FOCUS
protein players in neuroprotection, neurodevelop-
ment and sleep regulation.
In their recent publication, Xu and colleagues pres-
ent a proteome analysis of the plasma from 21 first-
onset drug-naive MDD patients which were compared
to 21 controls using shotgun proteomics for protein
identification and isobaric tags for relative and absol-
ute quantitation (iTRAQ) for protein quantitation (Xu
et al. 2012). The study focuses on the understanding of
MDD as a systemic disorder, but also mentions the
biomarker potential of these candidates. By using this
proteomic hypothesis-free approach and a further
validation by Western blot and enzyme-linked im-
munoadsorbent assay (ELISA), Xu et al. identified 94
proteins and found nine of those differentially ex-
pressed in MDD patients. These are mostly involved
with lipid metabolism and the immune system and
authors suggest that these are processes that might be
involved in the early stages of MDD pathophysiology.
Proteomic studies mentioned here have indeed
provided understanding of the molecular aspects of
MDD, exploring not only the role of the proteins, but
also the role of biochemical pathways and related
metabolites. However, only the report from Ditzen
et al. (2012) in MDD CSF explored reasonably the dif-
ferentially expressed proteins as biomarkers candi-
dates for MDD. This aspect of proteomic studies is still
open to exploration in order to reveal proteins that can
be useful not only in diagnosis, but in patient stratifi-
cation in accordance with the different types of MDD
(i.e. atypical depression and psychotic depression),
prognosis, treatment monitoring and response, and
potential drug targets.
Acknowledgements
I sincerely thank all tissue donors and their families for
comprehending how important their consent is to
medical research and to the lives of patients. I also
thank Professor Chris W. Turck and his entire group at
the Max Planck Institute of Psychiatry as well as
Professor Peter Falkai and Dr Andrea Schmitt from
the University of Go
¨ttingen for their unconditional
support.
Statement of Interest
None.
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1374 D. Martins-de-Souza
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... In doing so, a more comprehensive understanding of the pathophysiology of depression could be established, along with the identification of a biomarker for clinical applications. 16 In this study, we compared the same patient' s proteome between the depression status before treatment and during the remission status after antidepressant treatment. Each patient's protein expression was individually analyzed to identify biomarker candidates with accurate diagnostic ability. ...
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Article
  • Jul 2012
Introduction Major depressive disorder (MDD) is estimated by the World Health Organization to be a leading cause for loss of disability-adjusted life years. In the USA, the 2001 National Comorbidity Survey showed overall lifetime prevalence estimates for MDD of 16.2% (Kessler et al., 2003). Over 50% of respondents with MDD received some type of treatment in the 12 months before their interview. However, only about one-fifth of patients received “adequate” treatment during that time, indicating that more efforts are required at improving access to and utilization of care. Even for patients who are treated, pharmacotherapy is not uniformly effective. Many episodes do not completely respond to initial antidepressant, response may be delayed for weeks or months, and residual symptoms may cause significant morbidity. In this paper, we review the evidence for first-line treatment of MDD, and strategies for patients with treatment-resistant depression. Methods For the purposes of this review, we searched MEDLINE and PsycINFO for controlled trials published in English between January 1981 and October 2010, in which adults with MDD were randomly assigned to receive medication, placebo, or active comparator drugs, and for all meta-analyses of pharmacotherapy for MDD. The number of published randomized placebo-controlled trials (RCTs) of antidepressants for the acute treatment of MDD is too vast to allow discussion of each study. In order to recommend first-line treatment for MDD, we examined meta-analyses of RCTs of antidepressant drugs for MDD as a statistical means of weighing the relative efficacy of antidepressants that have not been compared directly. Because placebo response rates in antidepressant trials tend to be high, many positive trials have small effect sizes, and meta-analysis of multiple trials may be used to determine whether drug–placebo differences are meaningful.
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From Proteins to Proteomes: Large Scale Protein Identification by Two-Dimensional Electrophoresis and Arnino Acid Analysis
Article
  • Jan 1996
Separation and identification of proteins by two-dimensional (2-D) electrophoresis can be used for protein-based gene expression analysis. In this report single protein spots, from polyvinylidene difluoride blots of micropreparative E. coli 2-D gels, were rapidly and economically identified by matching their amino acid composition, estimated pI and molecular weight against all E. coli entries in the SWISS-PROT database. Thirty proteins from an E. coli 2-D map were analyzed and identities assigned. Three of the proteins were unknown. By protein sequencing analysis, 20 of the 27 proteins were correctly identified. Importantly, correct identifications showed unambiguous "correct" score patterns. While incorrect protein identifications also showed distinctive score patterns, indicating that protein must be identified by other means. These techniques allow large-scale screening of the protein complement of simple organisms, or tissues in normal and disease states. The computer program described here is accessible via the World Wide Web at URL address (http://expasy.hcuge.ch/).
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Disease-specific alterations in frontal cortex brain proteins in schizophrenia, bipolar disorder, and major depressive disorder
Article
  • May 2000
  • MOL PSYCHIATR
Severe psychiatric disorders such as schizophrenia, bipolar disorder and major depressive disorder are brain diseases of unknown origin. No biological marker has been documented at the pathological, cellular, or molecular level, suggesting that a number of complex but subtle changes underlie these illnesses. We have used proteomic technology to survey postmortem tissue to identify changes linked to the various diseases. Proteomics uses two-dimensional gel electrophoresis and mass spectrometric sequencing of proteins to allow the comparison of subsets of expressed proteins among a large number of samples. This form of analysis was combined with a multivariate statistical model to study changes in protein levels in 89 frontal cortices obtained postmortem from individuals with schizophrenia, bipolar disorder, major depressive disorder, and non-psychiatric controls. We identified eight protein species that display disease-specific alterations in level in the frontal cortex. Six show decreases compared with the non-psychiatric controls for one or more diseases. Four of these are forms of glial fibrillary acidic protein (GFAP), one is dihydropyrimidinase-related protein 2, and the sixth is ubiquinone cytochrome c reductase core protein 1. Two spots, carbonic anhydrase 1 and fructose biphosphate aldolase C, show increase in one or more diseases compared to controls. Proteomic analysis may identify novel pathogenic mechanisms of human neuropsychiatric diseases.
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Beasley CL, Pennington K, Behan A, Wait R, Dunn MJ, Cotter D. Proteomic analysis of the anterior cingulate cortex in the major psychiatric disorders: evidence for disease-associated changes. Proteomics 6: 3414-3425
Article
  • Jun 2006
  • PROTEOMICS
Abnormalities of the anterior cingulate cortex have previously been described in schizophrenia, major depressive disorder and bipolar disorder. In this study 2-DE was performed followed by mass spectrometric sequencing to identify disease-specific protein changes within the anterior cingulate cortex in these psychiatric disorders. The 2-DE system comprised IPGs 4–7 and 6–9 in the first, IEF dimension and SDS-PAGE in the second dimension. Resultant protein spots were compared between control and disease groups. Statistical analysis indicated that 35 spots were differentially expressed in one or more groups. Proteins comprising 26 of these spots were identified by mass spectroscopy. These represented 19 distinct proteins; aconitate hydratase, malate dehydrogenase, fructose bisphosphate aldolase A, ATP synthase, succinyl CoA ketoacid transferase, carbonic anhydrase, α- and β-tubulin, dihydropyrimidinase-related protein-1 and -2, neuronal protein 25, trypsin precursor, glutamate dehydrogenase, glutamine synthetase, sorcin, vacuolar ATPase, creatine kinase, albumin and guanine nucleotide binding protein β subunit. All but three of these proteins have previously been associated with the major psychiatric disorders. These findings provide support for the view that cytoskeletal and mitochondrial dysfunction are important components of the neuropathology of the major psychiatric disorders.
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Genetics of Unipolar Major Depressive Disorder
Article
  • Jan 2010
  • ISR J PSYCHIATR REL
Major depressive disorder (MDD) is a heterogeneous, highly prevalent, and moderately heritable disorder. A complex and diverse genetic-environmental interplay converges to set apart a significant minority that is susceptible to MDD, from among those who experience shorter lived and less recurrent intensive and incapacitating forms of sadness. The major technological advances of deciphering the human genome reference sequence and its common gene variations are beginning to allow cost effective genetic studies of unprecedented scale, applying increasingly denser genome wide mapping to increasingly larger case control samples. This effort is now at the initial stages of unraveling the genetic architecture of several complex phenotypes. Despite a tardy beginning, MDD genetic research is maturing from modest scale candidate gene association studies to include family-based linkage studies, and will soon allow genome wide case control association studies. Replicated risk conferring gene variants discovered so far exert a modest effect size that appears to contribute to overt phenotype expression in the context of a highly intricate concert of interrelated epigenetic and epistatic modifiers. The unraveling of additional previously unimplicated MDD risk conferring genes, that will throw light on molecular mechanisms mediating such susceptibilities, is necessary for progressing beyond current generation monoamine modulating antidepressant drugs. The review outlines basic concepts and current progress briefly overviews major replicated gene findings that to date mostly stem from hypotheses driven candidates, and ends with a discussion of current directives, including sample size and phenotype considerations and advancement of systematic studies of the functional significance of implicated gene variants, beyond their current exploratory stage.
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