BMC Medicine | |
Depression pathogenesis and treatment: what can we learn from blood mRNA expression? | |
Carmine M Pariante1  Patricia A Zunszain1  Annamaria Cattaneo1  Nilay Hepgul1  | |
[1] Sections of Perinatal Psychiatry & Stress, Psychiatry and Immunology, Department of Psychological Medicine, Institute of Psychiatry, King's College London, 125 Coldharbour Lane, London, SE5 9NU, UK | |
关键词: transcriptomics; peripheral blood; neuroplasticity; mRNA; microarray; inflammation; glucocorticoid receptor; gene expression; depression; | |
Others : 857204 DOI : 10.1186/1741-7015-11-28 |
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received in 2012-11-15, accepted in 2013-02-05, 发布年份 2013 | |
【 摘 要 】
Alterations in several biological systems, including the neuroendocrine and immune systems, have been consistently demonstrated in patients with major depressive disorder. These alterations have been predominantly studied using easily accessible systems such as blood and saliva. In recent years there has been an increasing body of evidence supporting the use of peripheral blood gene expression to investigate the pathogenesis of depression, and to identify relevant biomarkers. In this paper we review the current literature on gene expression alterations in depression, focusing in particular on three important and interlinked biological domains: inflammation, glucocorticoid receptor functionality and neuroplasticity. We also briefly review the few existing transcriptomics studies. Our review summarizes data showing that patients with major depressive disorder exhibit an altered pattern of expression in several genes belonging to these three biological domains when compared with healthy controls. In particular, we show evidence for a pattern of 'state-related' gene expression changes that are normalized either by remission or by antidepressant treatment. Taken together, these findings highlight the use of peripheral blood gene expression as a clinically relevant biomarker approach.
【 授权许可】
2013 Hepgul et al; licensee BioMed Central Ltd.
【 预 览 】
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20140723072043461.pdf | 517KB | download |
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