MK4MDD contains multi-level data surrounding the pathological cascade of MDD and highly integrated data connections by profound literature reading with manual curation, which allows researchers to acquire systematic knowledge for MDD from the database. MK4MDD emphasizes on the interplay of different levels of data across widely disparate disciplines, so that all data in MK4MDD form a cross-linked data network. MK4MDD provide powerful search and visualization tools to access both data and data connections for identification of novel targets and hypotheses. It is not only a knowledge resource, but also an analysis platform for interdisciplinary research to accelerate the pace of new discovery in psychotic mechanism.

1. Data Content

MK4MDD contains multi-level data, which were classified into 7 levels (genetic/epigenetic locus, protein and other molecule, cell and molecular pathway, neural system, cognition and behavior, symptoms and signs and environment) and 14 data types. Data of a certain data type in a research level is defined as ‘component’ and connection between two components of either the same research level or different levels is defined as ‘relationship’, which are all based on experimental results from literature. The statistics for data content in MK4MDD is shown in Data Statistics.

2. Literature search and data extraction

A search formula ("major depression"[Title/Abstract] OR "MDD"[Title/Abstract] OR "unipolar depression"[Title/Abstract] OR "unipolar depressive disorder"[Title/Abstract] OR "major depressive disorder"[Title/Abstract]) AND ("XXX"[Title/Abstract] OR "XXX"[Title/Abstract] OR …OR"XXX"[Title/Abstract]) was designed to search and collect publications from PubMed. The five aliases of MDD were gotten from Wikipedia and Medical Subheadings (MeSH) terms of MDD. Keywords in different research levels (represented as XXX in the search formula) were selected according to the following criteria.

1) Keywords targeting the first three research levels. Keywords were decided by taking reference of several published databases on psychiatric disorders, such as ADHDgene [1], AutDB [2], SZGene [3] and SZGR [4]. Keywords for epigenetic studies were decided follow the representative textbooks [5,6].

2) Keywords for neurobiological system. This kind of keywords covers neurotransmitter systems, neuroendocrine and immune systems. The selection was based on several psychiatric textbooks [7,8,9] and important reviews about MDD [10,11]. Because neurobiological systems often contain multi-cell and multi-molecule, search results of this kind of keywords also partly overlap with the results by keywords in 1).

3) Symptomatic keywords. This kind of keywords covers the ‘symptom’ and ‘cognition and behavior’ research levels, by following the diagnostic criteria for MDD in DSM-IV (diagnostic and statistical manual of mental disorders) [12]. It should be noted that the diagnosis about cognitive impairments of MDD in DSM-IV is described as ‘decreased ability to concentrate and think’, which is too general to describe the cognitive characteristics of MDD. So we set the data level ‘cognition and behavior’ to collect cognitive impairments and cognitive characteristics of MDD.

4) Methodological keywords. This kind of keywords corresponds to the data levels of ‘neural system’ and ‘cognition and behavior’. Major methods in neuroscience and cognitive science were included bead on several authoritative textbooks [13,14].

In conclusion, keywords were selected from different aspects by taking references of published database, paper and textbooks, so that they can cover all research levels on which MK4MDD is focusing. All keywords employed in PubMed search and their corresponding data levels are shown in Table 1.

3. Data integration and analysis

The data from literature were classified into seven research levels according to pathological cascade of MDD and data in different levels were integrated by relationships between components. The seven levels were further classified into 14 data types and detailed descriptions of data types and research levels are shown in Table 2.

Careful curation and annotation were made on each component, inlcuding:

  • 1) Standardization of component name according to common databases or knowledge, such as finding approved symbols for genes in HGNC, and approved names for proteins in UniProt.
  • 2) Detailed descriptions were provided for some types of data, such as diagrammatic presentation for neural system components and morphological and functional annotation for brain.

Supplementary annotations for components of SNPs, genes, proteins and pathways were made, including:

  • 1) functional annotation for SNPs (non-synonymous coding SNPs, or SNPs leading to gain or lost of stop codon);
  • 2) map SNPs to genes according to their chromosomal locations;
  • 3) annotate genes by using gene ontology (GO) and pathways from KEGG, BioCarta and Reactome;
  • 4) map genes to proteins by using UniProt database;
  • 5) identify interactions between genes by using HPRD database.

Hot components (defined as components with at least N studies, in which, the threshold N is different for different data type) were analyzed for each data type to provide reliable candidates for further research.

These annotation and analyses enriched the content of the database to provide new clues for understanding the genetic basis and molecular mechanism of MDD.


1. Zhang, L., Chang, S., Li, Z., Zhang, K., Du, Y., Ott, J. and Wang, J. (2012) ADHDgene: a genetic database for attention deficit hyperactivity disorder. Nucleic Acids Res, 40, D1003-1009.
2. Basu SN, Kollu R, Banerjee-Basu S (2009) AutDB: a gene reference resource for autism research. Nucleic Acids Res 37: D832-836.
3. Allen NC, Bagade S, McQueen MB, Ioannidis JP, Kavvoura FK, et al. (2008) Systematic meta-analyses and field synopsis of genetic association studies in schizophrenia: the SzGene database. Nat Genet 40: 827-834.
4. Jia P, Sun J, Guo AY, Zhao Z (2010) SZGR: a comprehensive schizophrenia gene resource. Mol Psychiatry 15: 453-462.
5. Allis CD, Jenuwein T, Reinberg D (2007) Epigenetics. Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press. x, 502 p. p.
6. Tollefsbol TO (2011) Handbook of Epigenetics: The New Molecular and Medical Genetics.: Academic Press 624 p.
7. Gelder MG, Mayou R, Geddes J (1999) Psychiatry. Oxford ; New York: Oxford University Press. 502 p. p.
8. Gelder MG (1996) Oxford textbook of psychiatry. Oxford ; New York: Oxford University Press. xi, 944 p. p.
9. Gelder M (2011) New Oxford textbook of psychiatry. New York, NY: Oxford University Press.
10. Krishnan V, Nestler EJ (2008) The molecular neurobiology of depression. Nature 455: 894-902.
11. Belmaker RH, Agam G (2008) Major depressive disorder. N Engl J Med 358: 55-68.
12. Association AP, DSM-IV. APATFo (2000) Diagnostic and statistical manual of mental disorders: DSM-IV-TR: American Psychiatric Publishing, Inc.
13. Gazzaniga MS, Ivry RB, Mangun GR (2009) Cognitive neuroscience : the biology of the mind. New York: W.W. Norton. xx, 666, 612, 622, 668, 623 p. p.
14. Senior C, Russell T, Gazzaniga MS (2006) Methods in mind. Cambridge, Mass.: MIT Press. ix, 382 p. p.