Construction and analysis of the protein-protein interaction networks for schizophrenia, bipolar disorder, and major depression

Abstract

BackgroundSchizophrenia, bipolar disorder, and major depression are devastating mental diseases, each with distinctive yet overlapping epidemiologic characteristics. Microarray and proteomics data have revealed genes which expressed abnormally in patients. Several single nucleotide polymorphisms (SNPs) and mutations are associated with one or more of the three diseases. Nevertheless, there are few studies on the interactions among the disease-associated genes and proteins.ResultsThis study, for the first time, incorporated microarray and protein-protein interaction (PPI) databases to construct the PPI network of abnormally expressed genes in postmortem brain samples of schizophrenia, bipolar disorder, and major depression patients. The samples were collected from Brodmann area (BA) 10 of the prefrontal cortex. Abnormally expressed disease genes were selected by t-tests comparing the disease and control samples. These genes were involved in housekeeping functions (e.g. translation, transcription, energy conversion, and metabolism), in brain specific functions (e.g. signal transduction, neuron cell differentiation, and cytoskeleton), or in stress responses (e.g. heat shocks and biotic stress).The diseases were interconnected through several “switchboard”-like nodes in the PPI network or shared abnormally expressed genes. A “core” functional module which consisted of a tightly knitted sub-network of clique-5 and -4s was also observed. These cliques were formed by 12 genes highly expressed in both disease and control samples.ConclusionsSeveral previously unidentified disease marker genes and drug targets, such as SBNO2 (schizophrenia), SEC24C (bipolar disorder), and SRRT (major depression), were identified based on statistical and topological analyses of the PPI network. The shared or interconnecting marker genes may explain the shared symptoms of the studied diseases. Furthermore, the “switchboard” genes, such as APP, UBC, and YWHAZ, are proposed as potential targets for developing new treatments due to their functional and topological significance.

Innate immune response is differentially dysregulated between bipolar disease and schizophrenia

“…Lee et al analyzed BD and SZ separately in relation to controls revealing genes involved in housekeeping functions (translation, transcription, energy conversion, and metabolism), in brain specific functions (signal transduction, neuron cell differentiation, and cytoskeleton), and in stress responses (heat shocks and biotic stress) (Lee et al, 2011). A recent whole transcriptome analysis of post-mortem brain tissues identified differentially expressed genes between SZ and BD, compared to control subjects, many of the genes showing concordant expression level, also revealing the involvement of lysosomal function and regulation of actin cytoskeleton with both diseases (Zhao et al, 2014).…”

Epigenetic profiling of human brain differential DNA methylation networks in schizophrenia

“…The analyses of disease PPI networks, the underlying pathways and protein complexes may construct a backbone for developing potential treatment strategy of the disease. Topologically and functionally important genes on the PPI networks may be seen as potential drug targets [19]. …”

Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

“…Recently, the topological analyses have been applied to PPI networks by tools or algorithms such as modularity and centrality analyses by which the biological significance of proteins has been determined (Huang et al, 2013; Lee et al, 2011). Graph centrality measures like degree, betweenness and closeness centrality are very useful in the identification of nodes that are functionally crucial in the network by ranking the elements of the network (Hindumathi et al, 2014).…”