Abstract
Gene expression in peripheral blood has the potential to inform on pathophysiological mechanisms and has emerged as a viable avenue for the identification of biomarkers. Here, we aimed to identify gene expression candidate genes and to explore the potential for a composite gene expression measure as a diagnostic and state biomarker in bipolar disorder. First, messenger RNA levels of 19 candidate genes were assessed in peripheral blood mononuclear cells of 37 rapid cycling bipolar disorder patients in different affective states (depression, mania and euthymia) during a 6-12-month period and in 40 age- and gender-matched healthy control subjects. Second, a composite gene expression measure was constructed in the first half study sample and independently validated in the second half of the sample. We found downregulation of POLG and OGG1 expression in bipolar disorder patients compared with healthy control subjects. In patients with bipolar disorder, upregulation of NDUFV2 was observed in a depressed state compared with a euthymic state. The composite gene expression measure for discrimination between patients and healthy control subjects on the basis of 19 genes generated an area under the receiver-operating characteristic curve of 0.81 (P < 0.0001) in sample 1, which was replicated with a value of 0.73 (P < 0.0001) in sample 2, corresponding with a moderately accurate test. The present findings of altered POLG, OGG1 and NDUFV2 expression point to disturbances within mitochondrial function and DNA repair mechanisms in bipolar disorder. Further, a composite gene expression measure could hold promise as a potential diagnostic biomarker.
Original language | English |
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Article number | e614 |
Journal | Translational Psychiatry |
Volume | 5 |
Pages (from-to) | 1-10 |
Number of pages | 10 |
ISSN | 2158-3188 |
DOIs | |
Publication status | Published - 4 Aug 2015 |
Keywords
- Adult
- Biomarkers
- Bipolar Disorder
- Case-Control Studies
- DNA Glycosylases
- DNA-Directed DNA Polymerase
- Female
- Humans
- Male
- NADH Dehydrogenase
- Proteomics
- RNA, Messenger
- Real-Time Polymerase Chain Reaction
- Transcriptome