A Conserved BDNF, Glutamate- and GABA-Enriched Gene Module Related to Human Depression Identified by Coexpression Meta-Analysis and DNA Variant Genome-Wide Association Studies

• Published in: PloS one Vol. 9; no. 3; p. e90980
• Main Authors: Chang, Lun-Ching, Jamain, Stephane, Lin, Chien-Wei, Rujescu, Dan, Tseng, George C., Sibille, Etienne
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 07.03.2014; Public Library of Science (PLoS)
• Subjects: Aged; Analysis; Anopheles; Bioinformatics; Biology; Bipolar disorder; Brain; Brain - metabolism; Brain - physiopathology; Brain research; Brain-Derived Neurotrophic Factor - genetics; Brain-Derived Neurotrophic Factor - metabolism; Case-Control Studies; Cell Adhesion Molecules, Neuronal - genetics; Cell Adhesion Molecules, Neuronal - metabolism; Deoxyribonucleic acid; Depression (Mood disorder); Depressive Disorder, Major - genetics; Depressive Disorder, Major - metabolism; Depressive Disorder, Major - physiopathology; Disease; DNA; Epidemiology; Extracellular Matrix Proteins - genetics; Extracellular Matrix Proteins - metabolism; Female; GABA; Gene expression; Gene Expression Profiling; Gene Expression Regulation; Gene Regulatory Networks; Genes; Genetic aspects; Genetic Predisposition to Disease; Genetics; Genome, Human; Genome-wide association studies; Genome-Wide Association Study; Genomes; Genomics; Glutamate; Heterogeneity; Humans; Hypotheses; Male; Medical research; Medicine; Mental depression; Meta-analysis; Metabolic Networks and Pathways - genetics; Middle Aged; Multigene Family; Nerve Tissue Proteins - genetics; Nerve Tissue Proteins - metabolism; Nervous system diseases; Neurosciences; Noise control; Psychiatry; Receptors, Eph Family - genetics; Receptors, Eph Family - metabolism; Receptors, GABA - genetics; Receptors, GABA - metabolism; Receptors, Metabotropic Glutamate - genetics; Receptors, Metabotropic Glutamate - metabolism; Reelin Protein; Serine Endopeptidases - genetics; Serine Endopeptidases - metabolism; Single nucleotide polymorphisms; Studies; Transcriptome
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0090980

Large scale gene expression (transcriptome) analysis and genome-wide association studies (GWAS) for single nucleotide polymorphisms have generated a considerable amount of gene- and disease-related information, but heterogeneity and various sources of noise have limited the discovery of disease mechanisms. As systematic dataset integration is becoming essential, we developed methods and performed meta-clustering of gene coexpression links in 11 transcriptome studies from postmortem brains of human subjects with major depressive disorder (MDD) and non-psychiatric control subjects. We next sought enrichment in the top 50 meta-analyzed coexpression modules for genes otherwise identified by GWAS for various sets of disorders. One coexpression module of 88 genes was consistently and significantly associated with GWAS for MDD, other neuropsychiatric disorders and brain functions, and for medical illnesses with elevated clinical risk of depression, but not for other diseases. In support of the superior discriminative power of this novel approach, we observed no significant enrichment for GWAS-related genes in coexpression modules extracted from single studies or in meta-modules using gene expression data from non-psychiatric control subjects. Genes in the identified module encode proteins implicated in neuronal signaling and structure, including glutamate metabotropic receptors (GRM1, GRM7), GABA receptors (GABRA2, GABRA4), and neurotrophic and development-related proteins [BDNF, reelin (RELN), Ephrin receptors (EPHA3, EPHA5)]. These results are consistent with the current understanding of molecular mechanisms of MDD and provide a set of putative interacting molecular partners, potentially reflecting components of a functional module across cells and biological pathways that are synchronously recruited in MDD, other brain disorders and MDD-related illnesses. Collectively, this study demonstrates the importance of integrating transcriptome data, gene coexpression modules and GWAS results for providing novel and complementary approaches to investigate the molecular pathology of MDD and other complex brain disorders.