Mood disturbances are associated with an activated inflammatory response system.
To identify a discriminating and coherent expression pattern of proinflammatory genes in monocytes of patients with bipolar disorder.
A quantitative polymerase chain reaction (Q-PCR) case-control gene expression study on purified monocytes of bipolar patients, the offspring of bipolar patients, and healthy control participants after having selected 22 discriminating inflammatory genes using whole genome analyses.
Academic research setting in the Netherlands.
Forty-two bipolar patients with 25 healthy controls, 54 offspring of a bipolar parent (13 had a mood disorder and 3 developed one during follow-up), and 70 healthy children underwent Q-PCR.
Main Outcome Measure
Inflammatory gene expression levels in monocytes.
We detected in the monocytes of bipolar patients a coherent mutually correlating set (signature) of 19 aberrantly expressed (P < .01) messenger RNAs of inflammatory (PDE4B, IL1B, IL6, TNF, TNFAIP3, PTGS2, and PTX3), trafficking (CCL2, CCL7, CCL20, CXCL2, CCR2, and CDC42), survival (BCL2A1 and EMP1), and mitogen-activated protein kinase pathway (MAPK6, DUSP2, NAB2, and ATF3) genes. Twenty-three of 42 bipolar patients (55%) had a positive signature test result vs 7 of 38 healthy controls (18%)
(positive test result: positivity for PDE4B, ie, a messenger RNA 1 SD higher than the mean level found in healthy controls, plus 25% of the other genes with similar positive findings).
Positive signature test results were also present in 11 of 13 offspring with a mood disorder (85%), 3 of 3 offspring developing a mood disorder (100%), and 17 of 38 euthymic offspring (45%) vs 13 of 70 healthy children (19%). Lithium carbonate and antipsychotic treatment downregulated the gene expression of most inflammatory genes.
The monocytes of a large proportion of bipolar patients and offspring of bipolar parents showed an inflammatory gene expression signature. This coherent set of genes opens new avenues for biomarker development with possibilities for disease prediction in individuals genetically at risk and for the subclassification of bipolar patients who could possibly benefit from anti-inflammatory treatment.