title: Molecular and Genetic Characterization of Depression: Overlap with other Psychiatric Disorders and Aging.
abstract: Genome-wide expression and genotyping technologies have uncovered the genetic bases of complex diseases at unprecedented rates; However despite its heavy burden and high prevalence, the molecular characterization of major depressive disorder (MDD) has lagged behind. Transcriptome studies report multiple brain disturbances but are limited by small sample sizes. Genome-wide association studies (GWAS) report weak results but suggest overlapping genetic risk with other neuropsychiatric disorders. We performed systematic molecular characterization of altered brain function in MDD, using meta-analysis of differential expression in eight gene array studies in three corticolimbic brain regions in 101 subjects. The identified "metaA-MDD" genes suggest altered neurotrophic support, brain plasticity and neuronal signaling in MDD. Notably, metaA-MDD genes display low connectivity and hubness in coexpression networks, and uniform genomic distribution, consistent with diffuse polygenic mechanisms. We next integrated these findings with results from over 1800 published GWAS and show that genetic variations nearby metaA-MDD genes predict greater risk for neuropsychiatric disorders and notably for age-related phenotypes, but not for other medical illnesses, including those frequently co-morbid with depression, or body characteristics. Collectively, the intersection of unbiased investigations of gene function (transcriptome) and structure (GWAS) provides novel leads to investigate molecular mechanisms of MDD and suggest common biological pathways between depression, other neuropsychiatric diseases, and brain aging.
authors.affiliation: Joint CMU-Pitt PhD program in Computational Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA ; Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA.
authors.forename: Ying
authors.initials: Y
authors.lastname: Ding
authors.affiliation: Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA.
authors.forename: Lun-Ching
authors.initials: LC
authors.lastname: Chang
authors.affiliation: Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA ; Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15261, USA.
authors.forename: Xingbin
authors.initials: X
authors.lastname: Wang
authors.affiliation: Université Paris-Sud EA 3544, Faculté de Pharmacie, Châtenay-Malabry cedex F-92296, France.
authors.forename: Jean-Philippe
authors.initials: JP
authors.lastname: Guilloux
authors.affiliation: Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA 15312, USA.
authors.forename: Jenna
authors.initials: J
authors.lastname: Parrish
authors.affiliation: Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA 15312, USA.
authors.forename: Hyunjung
authors.initials: H
authors.lastname: Oh
authors.affiliation: Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15312, USA.
authors.forename: Beverly J
authors.initials: BJ
authors.lastname: French
authors.affiliation: Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15312, USA ; Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA 15312, USA.
authors.forename: David A
authors.initials: DA
authors.lastname: Lewis
authors.affiliation: Joint CMU-Pitt PhD program in Computational Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA ; Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA.
authors.forename: George C
authors.initials: GC
authors.lastname: Tseng
authors.affiliation: Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15312, USA ; Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA 15312, USA ; Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Departments of Psychiatry, Pharmacology and Toxicology, University of Toronto, Toronto, CA.
authors.forename: Etienne
authors.initials: E
authors.lastname: Sibille
keywords: Depression; genetic association; medical illnesses; meta-analysis; transcriptome