Dataset Information

MK4MDD: a multi-level knowledge base and analysis platform for major depressive disorder.

ABSTRACT:

Background

Major depressive disorder (MDD) is a complex neuropsychiatric syndrome with high heterogeneity. There are different levels of biological components that underlie MDD and interact with each other. To uncover the disease mechanism, large numbers of studies at different levels have been conducted. There is a growing need to integrate data from multiple levels of research into a database to provide a systematic review of current research results. The cross level integration will also help bridge gaps of different research levels for further understanding on MDD. So far, there has been no such effort for MDD.

Descriptions

We offer researchers a Multi-level Knowledge base for MDD (MK4MDD) to study the interesting interplay of components in the pathophysiological cascade of MDD from genetic variations to diagnostic syndrome. MK4MDD contains 2,341 components and 5,206 relationships between components based on reported experimental results obtained by diligent literature reading with manual curation. All components were well classified with careful curation and supplementary annotation. The powerful search and visualization tools make all data in MK4MDD form a cross-linked network to be applied to a broad range of both basic and applied research.

Conclusions

MK4MDD aims to provide researchers with a central knowledge base and analysis platform for MDD etiological and pathophysiological mechanisms research. MK4MDD is freely available at http://mdd.psych.ac.cn.

SUBMITTER: Guo L

PROVIDER: S-EPMC3465288 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Publications

MK4MDD: a multi-level knowledge base and analysis platform for major depressive disorder.

Guo Liyuan L Zhang Weina W Chang Suhua S Zhang Liuyan L Ott Jurg J Wang Jing J

PloS one 20121005 10

<h4>Background</h4>Major depressive disorder (MDD) is a complex neuropsychiatric syndrome with high heterogeneity. There are different levels of biological components that underlie MDD and interact with each other. To uncover the disease mechanism, large numbers of studies at different levels have been conducted. There is a growing need to integrate data from multiple levels of research into a database to provide a systematic review of current research results. The cross level integration will a ...[more]

PMID: 23071556

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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:Background: Major depressive disorder (MDD) is an affective disorder that is harmful to both physical and mental health. Abnormal self-knowledge, which refers to abnormal judgments about oneself, is a core symptom of depression. However, little research has summarized how and why patients with MDD differ from healthy individuals in terms of self-knowledge. Objective: To gain a better understanding of MDD, we reviewed previous studies that focused on the behavioral and neurological changes of self-knowledge in this illness. Main Findings: On the behavioral level, depressed individuals exhibited negative self-knowledge in an explicit way, while more heterogeneous patterns were reported in implicit results. On the neurological level, depressed individuals, as compared with non-depressed controls, showed abnormal self-referential processing in both early perception and higher cognitive processing phases during the Self-Referential Encoding Task. Furthermore, fMRI studies have reported aberrant activity in the medial prefrontal cortex area for negative self-related items in depression. These results revealed several behavioral features and brain mechanisms underlying abnormal self-knowledge in depression. Future Studies: The neural mechanism of implicit self-knowledge in MDD remains unclear. Future research should examine the importance of others' attitudes on the self-concept of individuals with MDD, and whether abnormal self-views may be modified through cognitive or pharmacological approaches. In addition, differences in abnormal self-knowledge due to genetic variation between depressed and non-depressed populations remain unconfirmed. Importantly, it remains unknown whether abnormal self-knowledge could be used as a specific marker to distinguish healthy individuals from those with MDD. Conclusion: This review extends our understanding of the relationship between self-knowledge and depression by indicating several abnormalities among individuals with MDD and those who are at risk for this illness.

Dataset Information

MK4MDD: a multi-level knowledge base and analysis platform for major depressive disorder.

Background

Descriptions

Conclusions

Publications

MK4MDD: a multi-level knowledge base and analysis platform for major depressive disorder.

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