- 作者：Sabine Spijker ; Jeroen S. Van Zanten ; Simone De Jong ; Brenda W.J.H. Penninx ; Richard van Dyck ; Frans G. Zitman ; Jan H. Smit ; Bauke Ylstra ; August B. Smit ; Witte J.G. Hoogendijk
- 关键词：Biomarker ; genomics ; LPS challenge ; major depressive disorder ; microarray ; real-time quantitative polymerase chain reaction
- 刊名：Biological Psychiatry
- 出版年：2010
- 出版时间：15 July 2010
- 年：2010
- 卷：68
- 期：2
- 页码：179-186
- 全文大小：743 K
Background
Major depressive disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available.Methods
We used a classifier approach on blood gene expression profiles of a unique set of unmedicated subjects (MDD patients and control subjects) to select genes with expression predictive for disease status. To reveal blood gene expression changes related to major depressive disorder-disease, we applied a powerful ex vivo stimulus to the blood: incubation with lipopolysaccharide (LPS; 10 ng/mL blood).
Results
Based on LPS-stimulated blood gene expression using whole-genome microarrays (primary cohort; 21 MDD patients, 21 healthy control subjects), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated using an independent quantitative polymerase chain reaction method (primary cohort, p = .007). The difference between depressive patients and control subjects was confirmed (p = .019) in a replication cohort of 13 MDD patients and 14 control subjects. The MDD signature score comprised expression levels of seven genes could discriminate depressive patients from control subjects with sensitivity of 76.9 % and specificity of 71.8 % .
Conclusions
We have shown for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of major depressive disorder.