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Mol Neuropsychiatry. 2015 May;1(1):1-12.

Molecular and Genetic Characterization of Depression: Overlap with other Psychiatric Disorders and Aging.

Author information

1
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.
2
Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA.
3
Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA ; Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15261, USA.
4
Université Paris-Sud EA 3544, Faculté de Pharmacie, Châtenay-Malabry cedex F-92296, France.
5
Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA 15312, USA.
6
Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15312, USA.
7
Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15312, USA ; Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA 15312, USA.
8
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.

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.

KEYWORDS:

Depression; genetic association; medical illnesses; meta-analysis; transcriptome

PMID:
26213687
PMCID:
PMC4512183

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