Dataset Information

Identification of potential Mitogen-Activated Protein Kinase-related key genes and regulation networks in molecular subtypes of major depressive disorder.

ABSTRACT:

Background

Major depressive disorder (MDD) is a heterogeneous and prevalent mental disorder associated with increased morbidity, disability, and mortality. However, its underlying mechanisms remain unclear.

Materials and methods

All analyses were conducted based on integrated samples from the GEO database. Differential expression analysis, unsupervised consensus clustering analysis, enrichment analysis, and regulation network analysis were performed.

Results

Mitogen-activated protein kinase (MAPK) signaling pathway was identified as an associated pathway in the development of MDD. From transcriptional signatures, we classified the MDD patients into two subgroups using unsupervised clustering and revealed 13 differential expression genes between subgroups, which indicates the probably relative complications. We further illustrated potential molecular mechanisms of MDD, including dysregulation in the neurotrophin signaling pathway, peptidyl-serine phosphorylation, and endocrine resistance. Moreover, we identified hub genes, including MAPK8, TP53, and HRAS in the maintenance of MDD. Furthermore, we demonstrated that the axis of miRNAs-TFs-HRAS/TP53/MAPK8 may play a critical role in MDD.

Conclusion

Taken together, we demonstrated an overview of MAPK-related key genes in MDD, determined two molecular subtypes, and identified the key genes and core network that may contribute to the procession of MDD.

SUBMITTER: Chen Y

PROVIDER: S-EPMC9634261 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Identification of potential Mitogen-Activated Protein Kinase-related key genes and regulation networks in molecular subtypes of major depressive disorder.

Chen Youfang Y Zhou Feng F Lu Weicheng W Zeng Weian W Wang Xudong X Xie Jingdun J

Frontiers in psychiatry 20221021

<h4>Background</h4>Major depressive disorder (MDD) is a heterogeneous and prevalent mental disorder associated with increased morbidity, disability, and mortality. However, its underlying mechanisms remain unclear.<h4>Materials and methods</h4>All analyses were conducted based on integrated samples from the GEO database. Differential expression analysis, unsupervised consensus clustering analysis, enrichment analysis, and regulation network analysis were performed.<h4>Results</h4>Mitogen-activat ...[more]

PMID: 36339846

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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.

Project description:BackgroundAccording to current classification systems, patients with major depressive disorder (MDD) may have very different combinations of symptoms. This symptomatic diversity hinders the progress of research into the causal mechanisms and treatment allocation. Theoretically founded subtypes of depression such as atypical, psychotic, and melancholic depression have limited clinical applicability. Data-driven analyses of symptom dimensions or subtypes of depression are scarce. In this systematic review, we examine the evidence for the existence of data-driven symptomatic subtypes of depression.MethodsWe undertook a systematic literature search of MEDLINE, PsycINFO and Embase in May 2012. We included studies analyzing the depression criteria of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) of adults with MDD in latent variable analyses.ResultsIn total, 1176 articles were retrieved, of which 20 satisfied the inclusion criteria. These reports described a total of 34 latent variable analyses: 6 confirmatory factor analyses, 6 exploratory factor analyses, 12 principal component analyses, and 10 latent class analyses. The latent class techniques distinguished 2 to 5 classes, which mainly reflected subgroups with different overall severity: 62 of 71 significant differences on symptom level were congruent with a latent class solution reflecting severity. The latent class techniques did not consistently identify specific symptom clusters. Latent factor techniques mostly found a factor explaining the variance in the symptoms depressed mood and interest loss (11 of 13 analyses), often complemented by psychomotor retardation or fatigue (8 of 11 analyses). However, differences in found factors and classes were substantial.ConclusionsThe studies performed to date do not provide conclusive evidence for the existence of depressive symptom dimensions or symptomatic subtypes. The wide diversity of identified factors and classes might result either from the absence of patterns to be found, or from the theoretical and modeling choices preceding analysis.

Dataset Information

Identification of potential Mitogen-Activated Protein Kinase-related key genes and regulation networks in molecular subtypes of major depressive disorder.

Background

Materials and methods

Results

Conclusion

Publications

Identification of potential Mitogen-Activated Protein Kinase-related key genes and regulation networks in molecular subtypes of major depressive disorder.

Similar Datasets

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