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Highlights
• A panel of 20 biomarkers was identified capable of differentiating BD patients from controls.
• Excellent discrimination between established BD patients and controls.
• Good to excellent discrimination between misdiagnosed BD patients and first onset MDD patients.
• Fair to good discrimination between pre-diagnostic BD patients and controls.
• Study demonstrates the potential utility of a protein biomarker panel as a diagnostic test for BD.
Abstract
Background: Bipolar disorder (BD) is a costly, devastating and life shortening mental disorder that is often misdiagnosed, especially on initial presentation. Misdiagnosis frequently results in ineffective treatment. We investigated the utility of a biomarker panel as a diagnostic test for BD.
Methods and findings: We performed a meta-analysis of eight case-control studies to define a diagnostic biomarker panel for BD. After validating the panel on established BD patients, we applied it to undiagnosed BD patients. We analysed 249 BD, 122 pre-diagnostic BD, 75 pre-diagnostic schizophrenia and 90 first onset major depression disorder (MDD) patients and 371 controls. The biomarker panel was identified using ten-fold cross-validation with lasso regression applied to the 87 analytes available across the meta-analysis studies.
We identified 20 protein analytes with excellent predictive performance [area under the curve (AUC) ⩾ 0.90]. Importantly, the panel had a good predictive performance (AUC 0.84) to differentiate 12 misdiagnosed BD patients from 90 first onset MDD patients, and a fair to good predictive performance (AUC 0.79) to differentiate between 110 pre-diagnostic BD patients and 184 controls. We also demonstrated the disease specificity of the panel.
Conclusions: An early and accurate diagnosis has the potential to delay or even prevent the onset of BD. This study demonstrates the potential utility of a biomarker panel as a diagnostic test for BD.
Highlights
• Inflammatory monocyte genes were used to stratify patients in a RCT with statins.
• One group (∼30% SSD patients) showed a distinct inflammatory monocyte signature.
• Within this “inflammatory” group, statins improved PANSS scores.
• Such changes were not observed for “inflammatory” patients receiving placebo.
• Depression scores in the “inflammatory” group improved during treatment as usual.
Abstract
Immune dysregulation has been reported in schizophrenia spectrum disorders (SSD). In the past decade, several trials using anti-inflammatory agents for treatment of SSD have been completed, with so far limited success. One such anti-inflammatory agent used is simvastatin. A recent, large-scale, randomized controlled trial with simvastatin augmentation failed to show improvement in the predefined primary outcome. However, baseline inflammatory profiles were not taken into account. Here we employed a data-driven clustering approach to investigate whether patients with an inflammatory monocyte gene signature respond better to add-on simvastatin treatment than those without such a signature, over a treatment period of 2 years. In 61 patients (60 randomized, 1:1 placebo:simvastatin) and healthy controls, a previously validated monocyte gene expression signature was assessed using quantitative polymerase chain reaction. Resulting delta cycle threshold values were used to identify patient clusters. Two major patient clusters with either up- or downregulated pro-inflammatory factors were detected. Linear mixed models showed a significant three-way interaction between the inflammatory cluster, treatment, and time for psychotic symptoms. Only patients treated with simvastatin who were in the inflammatory group, showed a consistent improvement: symptom severity gradually decreased after 3 months and reached significance after 12 and 24 months compared to baseline (p.adj<0.05). The effects were small, and overall between-group effects were not significant. Here, we show that patient stratification based on inflammatory gene expression might be useful to select appropriate treatment augmentation for patients with SSD, highlighting the need for precision medicine approaches. Our findings corroborate the results of the primary analyses, showing that in the overall group, simvastatin was not effective; however, at the individual level the treatment might make a difference.