Genetic Epidemiology, Translational Neurogenomics, Psychiatric Genetics and Statistical Genetics Laboratories investigate the pattern of disease in families, particularly identical and non-identical twins, to assess the relative importance of genes and environment in a variety of important health problems.
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PMID
31306407
TITLE
A gene co-expression network-based analysis of multiple brain tissues reveals novel genes and molecular pathways underlying major depression.
ABSTRACT
Major depression is a common and severe psychiatric disorder with a highly polygenic genetic architecture. Genome-wide association studies have successfully identified multiple independent genetic loci that harbour variants associated with major depression, but the exact causal genes and biological mechanisms are largely unknown. Tissue-specific network approaches may identify molecular mechanisms underlying major depression and provide a biological substrate for integrative analyses. We provide a framework for the identification of individual risk genes and gene co-expression networks using genome-wide association summary statistics and gene expression information across multiple human brain tissues and whole blood. We developed a novel gene-based method called eMAGMA that leverages tissue-specific eQTL information to identify 99 biologically plausible risk genes associated with major depression, of which 58 are novel. Among these novel associations is Complement Factor 4A (C4A), recently implicated in schizophrenia through its role in synaptic pruning during postnatal development. Major depression risk genes were enriched in gene co-expression modules in multiple brain tissues and the implicated gene modules contained genes involved in synaptic signalling, neuronal development, and cell transport pathways. Modules enriched with major depression signals were strongly preserved across brain tissues, but were weakly preserved in whole blood, highlighting the importance of using disease-relevant tissues in genetic studies of psychiatric traits. We identified tissue-specific genes and gene co-expression networks associated with major depression. Our novel analytical framework can be used to gain fundamental insights into the functioning of the nervous system in major depression and other brain-related traits.
DATE PUBLISHED
2019 07
HISTORY
PUBSTATUS PUBSTATUSDATE
received 2019/02/01
accepted 2019/06/12
revised 2019/07/25
pubmed 2019/07/16 06:00
medline 2019/12/18 06:00
entrez 2019/07/16 06:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
Gerring ZF Gerring Zachary F ZF Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
Gamazon ER Gamazon Eric R ER Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Derks EM Derks Eske M EM Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium
INVESTIGATORS
JOURNAL
VOLUME: 15
ISSUE: 7
TITLE: PLoS genetics
ISOABBREVIATION: PLoS Genet.
YEAR: 2019
MONTH: 07
DAY:
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Internet
ISSN: 1553-7404
ISSNTYPE: Electronic
MEDLINE JOURNAL
MEDLINETA: PLoS Genet
COUNTRY: United States
ISSNLINKING: 1553-7390
NLMUNIQUEID: 101239074
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Journal Article
COMMENTS AND CORRECTIONS
GRANTS
GRANTID AGENCY COUNTRY
U01 MH109536 NIMH NIH HHS United States
GENERAL NOTE
KEYWORDS
MESH HEADINGS
DESCRIPTORNAME QUALIFIERNAME
Brain Chemistry
Complement C4a genetics
Depressive Disorder, Major genetics
Gene Expression Profiling methods
Gene Expression Regulation methods
Gene Regulatory Networks methods
Genome-Wide Association Study methods
Humans methods
Organ Specificity methods
Quantitative Trait Loci methods
Sequence Analysis, RNA methods
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
REGISTRYNUMBER NAMEOFSUBSTANCE
80295-49-4 Complement C4a
OTHER ID's