Bipolar disorder debilitates about 1% of the population. It typically causes extreme mood swings between high (manic) and low (depressed) phases.
Jakub Tomasik, Assistant Research Professor at the University of Cambridge, introduced his latest work, which demonstrates how combining metabolomic biomarkers from dried blood spots and digital questionnaire data can significantly improve the diagnosis of bipolar disorder compared to major depression. Currently, around 40% of bipolar cases are misdiagnosed as major depression due to some shared symptoms. Therefore, Tomasik’s work is crucial to addressing this significant issue and is particularly valuable in cases where symptoms alone are ambiguous.
The study used metabolomic and digital questionnaire data to create a robust signature of bipolar disorder. It identified a panel of 17 metabolomic biomarkers. Ceramide was the most significant in distinguishing bipolar disorder from major depression. The model achieved an AUROC of 0.71, which increased to 0.96 when combined with digital data. Tomasik explained that biomarker levels correlated most strongly with manic or hypomanic symptoms and psychiatric history.
Although the protein-based biomarkers did not provide useful diagnostic information, the metabolomic data showed strong and reproducible results, validated in a prospective cohort. The biomarker panel was particularly effective in identifying up to 30% more misdiagnosed bipolar patients, especially when symptom information was limited or uncertain.
Tomasik explained that plans are underway for a large-scale international clinical validation study with Psyomics and Biocrates to further test the combined biomarker and digital questionnaire approach. Another key advantage of this study was that it is minimally invasive and suitable for remote application, making it more user-friendly.