MS-based metabolic profiling in serum for bipolar disorder

Bipolar disorder (BD) is a chronic psychiatric illness characterized by alternating episodes of mania and depression. Diagnostic challenges arise from the subjective nature of clinical assessments, often leading to delayed or inaccurate treatment. The identification of objective biomarkers specific to BD may improve diagnostic accuracy and enable early intervention. This study aimed to analyze serum metabolomic profiles of BD patients during euthymic and manic states to identify potential diagnostic and predictive biomarkers.

Serum samples were collected from 33 patients in the manic phase, 25 patients in the euthymic phase, and 40 healthy controls. Samples were analyzed using high-resolution liquid chromatography-mass spectrometry. Metabolite levels were determined semi-quantitatively. The identified metabolic features were analysed using univariate statistics, confounder-adjusted logistic regression, and multivariate and pathway enrichment approaches.

Comparisons between patients with BD and healthy controls revealed alterations primarily in lipid-related metabolites, including primary fatty acid amides, phosphatidylcholine derivatives, and acylcarnitines. Following adjustment, oleamide and 2-arachidonoylglycerol were found to be significantly associated with the euthymic state relative to the control group. In manic patients, several lipid metabolites exhibited consistent directional changes compared to the control group, although most of these associations did not survive multiple testing correction. Direct comparison between the manic and euthymic states identified a limited number of metabolites, suggesting metabolic differences related to the state.

This exploratory serum metabolomics study has identified subtle yet biologically plausible metabolic alterations associated with bipolar disorder and its mood states. The findings emphasise the importance of lipid metabolism and mitochondrial energy pathways in the pathophysiology of BD, while also highlighting the influence of mood state. Although the results are preliminary and require validation in larger, longitudinal cohorts that are preferably drug-naïve, they lay the groundwork for future targeted metabolomic studies aimed at clarifying state- and disease-related metabolic signatures in BD.