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

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.针对单核苷酸多态性（single nucleotide polymorphisms）的大规模基因表达（转录组）分析与全基因组关联分析（GWAS）已产生了大量基因与疾病相关的信息，但异质性与多种噪声来源限制了疾病机制的发掘。随着系统性数据集整合愈发成为必要手段，我们开发了相关方法，并对11项来自重度抑郁症（MDD）患者与非精神疾病对照受试者的死后脑组织转录组研究中的基因共表达关联开展了元聚类（meta-clustering）分析。随后，我们针对经元分析得到的前50个共表达模块，检测其是否富集于各类疾病相关GWAS所鉴定的基因中。结果发现，包含88个基因的共表达模块始终与MDD、其他神经精神疾病及脑功能相关GWAS显著关联，同时也与临床抑郁风险升高的内科疾病相关，但与其他疾病无显著关联。为验证该新方法的优异判别能力，我们发现，从单组研究中提取的共表达模块、或使用非精神疾病对照受试者基因表达数据构建的元模块（meta-modules），均未出现GWAS相关基因的显著富集现象。该模块内的基因编码参与神经元信号传导与结构形成的蛋白质，包括代谢型谷氨酸受体（GRM1、GRM7）、γ-氨基丁酸（GABA）受体（GABRA2、GABRA4），以及神经营养与发育相关蛋白[脑源性神经营养因子（BDNF）、reelin（RELN）、Ephrin受体（EPHA3、EPHA5）]。上述结果与当前对MDD分子机制的认知相符，并提供了一组推定的相互作用分子伴侣，潜在反映了跨细胞与生物学通路的功能模块组分，这些组分在MDD、其他脑疾病及MDD相关疾病中被同步募集。综上，本研究证实了整合转录组数据、基因共表达模块与GWAS结果的重要性，为探究MDD及其他复杂脑疾病的分子病理提供了全新且互补的研究手段。