ArticleMolecular brain2019
Peripheral blood metabolome predicts mood change-related activity in mouse model of bipolar disorder.
Article in Molecular brain, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Common and specific patterns of functional and structural brain alterations in schizophrenia and bipolar disorder: a multimodal voxel-based meta-analysis.Journal of psychiatry & neuroscience : JPNPooled it
- Allostatic and Circadian Drives in Patients with Bipolar Disorder in Depressive Episodes or with Post-Traumatic Stress Disorder Versus Healthy Controls: Neuroendocrine Comparison Through Cortisol and 6-Sulfatoxymelatonin Overnight Urine Excretion.International journal of molecular sciences · 2026Article
- Metabolomics and Self-Reported Depression, Anxiety, and Phobic Symptoms in the VA Normative Aging Study.Metabolites · 2023Article
- Acute and chronic effects of oral administration of a medium-chain fatty acid, capric acid, on locomotor activity and anxiety-like and depression-related behaviors in adult male C57BL/6J mice.Neuropsychopharmacology reports · 2022Article
- Metabolism navigates neural cell fate in development, aging and neurodegeneration.Disease models & mechanisms · 2021Review
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bipolar disorder is a major mental illness characterized by severe swings in mood and activity levels which occur with variable amplitude and frequency. Attempts have been made to identify mood states and biological features associated with mood changes to compensate for current clinical diagnosis, which is mainly based on patients' subjective reports. Here, we used infradian (a cycle > 24 h) cyclic locomotor activity in a mouse model useful for the study of bipolar disorder as a proxy for mood changes. We show that metabolome patterns in peripheral blood could retrospectively predict the locomotor activity levels. We longitudinally monitored locomotor activity in the home cage, and subsequently collected peripheral blood and performed metabolomic analyses. We then constructed cross-validated linear regression models based on blood metabolome patterns to predict locomotor activity levels of individual mice. Our analysis revealed a significant correlation between actual and predicted activity levels, indicative of successful predictions. Pathway analysis of metabolites used for successful predictions showed enrichment in mitochondria metabolism-related terms, such as "Warburg effect" and "citric acid cycle." In addition, we found that peripheral blood metabolome patterns predicted expression levels of genes implicated in bipolar disorder in the hippocampus, a brain region responsible for mood regulation, suggesting that the brain-periphery axis is related to mood-change-associated behaviors. Our results may serve as a basis for predicting individual mood states through blood metabolomics in bipolar disorder and other mood disorders and may provide potential insight into systemic metabolic activity in relation to mood changes.
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