Mitochondrial Biomarkers and Metabolic Syndrome in Bipolar Disorder
Bibliographic record
Abstract
Abstract Importance Examining translatable mitochondrial blood-based biological markers to identify its association with metabolic diseases in bipolar disorder. Objective To test whether mitochondrial metabolites, mainly lactate, and cell-free circulating mitochondrial DNA are associated with markers of metabolic syndrome in bipolar disorder, hypothesizing higher lactate but unchanged cell-free circulating mitochondrial DNA levels in bipolar disorder patients with metabolic syndrome. Design In a cohort study, primary testing from the FondaMental Advanced Centers of Expertise for bipolar disorder was conducted, including baseline plasma samples and blinded observers for all experimentation and analysis. Setting The FondaMental Foundation coordinate a multicenter, multidisciplinary French networks aiming at creation of cohorts to improve identification of homogeneous subgroups of psychiatric disorders toward personalized treatments. Participants The FACE-BD primary testing cohort includes 837 stable bipolar disorder patients. The I-GIVE validation cohort consists of 235 participants: stable and acute bipolar patients, non-psychiatric controls, and acute schizophrenia patients. Participants were randomly selected based on biosample availability. Exposures All patients underwent the standard primary care within their center. No intentional exposures were part of this study. Main Outcome and Measures The primary outcome modelled an association with lactate and metabolic syndrome in this population. Reflective a priori hypothesis. Results Multivariable regression analyses show lactate association with triglycerides (Est= 0.072(0.023), p = 0.0065,), fasting glucose (Est = 12(0.025), p= 0.000015) and systolic (Est= 0.003(0.0013), p= 0.031) and diastolic blood pressure (Est = 0.0095±0.0017, p= 1.3e-7). Significantly higher levels of lactate were associated with presence of metabolic syndrome (Est = 0.17±0.049, p=0.00061) after adjusting for potential confounding factors. Mitochondrial-targeted metabolomics identified distinct metabolite profiles in patients with lactate presence and metabolic syndrome, differing from those without lactate changes but with metabolic syndrome. Circulating cell-free mitochondrial DNA was not associated with metabolic syndrome. Conclusion & Relevance This thorough analysis mitochondrial biomarkers indicate the associations with lactate and metabolic syndrome, whereas circulating cell-free mitochondrial DNA is limited in the context of metabolic syndrome. This study is relevant to improve the identification and stratification of bipolar patients with metabolic syndrome and provide potential personalized-therapeutic opportunities. Key Points Question Can lactate, a mitochondrial metabolite, indicate metabolic syndrome in bipolar disorder? Finding In 837 stable bipolar disorder patients, we found high lactate levels significantly associated with metabolic syndrome, unlike circulating cell-free mitochondrial DNA. This pattern also appeared in acute bipolar and schizophrenia cases. Mitochondrial-targeted metabolomics distinguishes patients with high lactate and metabolic syndrome from those without lactate changes, but presence of metabolic syndrome. Meaning This research underscores lactate as a potential biomarker for identifying bipolar disorder patients with metabolic syndrome. It opens new avenues for personalized treatment strategies, leveraging mitochondrial metabolite profiling to improve patient stratification and therapeutic outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".