Dataset Information

Plasma non-targeted peptidomics discovers potential biomarkers for major depressive disorder

ABSTRACT: Purpose There are great demands for identifying markers of major depressive disorder (MDD), which is a common mental illness with a prevalence of approximately 6%. Finding potential markers to aid MDD diagnosis is in high demand. Experimental design In this study, combination of the salt-out assisted liquid-liquid extraction (SALLE) pretreatment method and a nontargeted peptidomics approach based on nano-LC-Orbitrap/MS is primarily employed to discover the candidate peptide biomarkers from the plasma of 238 subjects. Results A large number of peptides are enriched and identified from the plasma samples, of which 42 peptides show significant differences between MDD patients and controls by univariate statistical analysis. A diagnostic model combined four peptide markers (P1, P9, P17, P29) is established by binary logistic regression analysis, yielding an overall prediction accuracy of 91.7% and 82.2% in the discovery and validation sets, respectively. Conclusions and clinical relevance In conclusion, the good performance of diagnostic model in both discovery and validation sets demonstrates the robustness of peptide markers panel. It is very valuable for quantification the absolute content of four peptides and further verification.

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

SUBMITTER: yi wang

LAB HEAD: Yi Wang

PROVIDER: PXD023009 | Pride | 2023-04-13

REPOSITORIES: Pride

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Publications

Plasma nontargeted peptidomics discovers potential biomarkers for major depressive disorder.

Wang Yi Y Liu Xinxin X Liu Dan D Cheng Mengchun M Zhao Nan N He Meixi M Zhang Xiaozhe X

Proteomics. Clinical applications 20210812 6

<h4>Purpose</h4>There are great demands for identifying biomarkers of major depressive disorder (MDD), a common mental illness with a prevalence of approximately 6%. Finding potential biomarkers to aid MDD diagnosis is in high demand.<h4>Experimental design</h4>In this study, a combination of pretreatment methods named salt-out assisted liquid-liquid extraction (SALLE) and nontargeted peptidomics based on nano-LC-Orbitrap/MS was primarily employed to discover the candidate peptide markers from t ...[more]

PMID: 34329527

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Project description:Major depressive disorder (MDD) is the psychiatric disorder with the highest prevalence in the world. Pharmacological antidepressant treatment (AD), such as selective serotonin reuptake inhibitors [SSRI, i.e. fluoxetine (Flx)] is the first line of treatment for MDD. Despite its efficacy, lack of AD response occurs in numerous patients characterizing Difficult-to-treat Depression. ElectroConvulsive Therapy (ECT) is a highly effective treatment inducing rapid improvement in depressive symptoms and high remission rates of ~50–63% in patients with pharmaco-resistant depression. Nevertheless, the need to develop reliable treatment response predictors to guide personalized AD strategies and supplement clinical observation is becoming a pressing clinical objective. Here, we propose to establish a proteomic peripheral biomarkers signature of ECT response in an anxio/depressive animal model of non-response to AD. Using an emotionality score based on the analysis complementary behavioral tests of anxiety/depression (Elevated Plus Maze, Novelty Suppressed Feeding, Splash Test), we showed that a 4-week corticosterone treatment (35 μg/ml, Cort model) in C57BL/6JRj male mice induced an anxiety/depressive-like behavior. A 28-days chronic fluoxetine treatment (Flx, 18 mg/kg/day) reduced corticosterone-induced increase in emotional behavior. A 50% decrease in emotionality score threshold before and after Flx, was used to separate Flx-responding mice (Flx-R, n=18), or Flx non-responder mice (Flx-NR, n=7). Then, Flx-NR mice received 7 sessions of electroconvulsive seizure (ECS, equivalent to ECT in humans) and blood was collected before and after ECS treatment. Chronic ECS normalized the elevated emotionality observed in Flx-NR mice. Then, proteins were extracted from peripheral blood mononuclear cells (PBMCs) and isolated for proteomic analysis using a high-resolution MS Orbitrap. The proteomic analysis revealed a signature of 33 peripheral proteins associated with response to ECS (7 down- and 26 upregulated). These proteins were previously associated with mental disorders and involved in regulating pathways which participate to the depressive disorder etiology. remark for sample name : ECTR=Flx-NR-ES, C=cort/Veh, CFNR= Flx-NR

Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.

Dataset Information

Plasma non-targeted peptidomics discovers potential biomarkers for major depressive disorder

Publications

Plasma nontargeted peptidomics discovers potential biomarkers for major depressive disorder.

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