Are remitted affective disorders and familial risk of affective disorders associated with metabolic syndrome, inflammation and oxidative stress? – a monozygotic twin study
Bibliographic record
Abstract
BACKGROUND: Metabolic syndrome (MetS) is associated with reduced life expectancy in patients with affective disorders, however, whether MetS also plays a role before the onset of affective disorder is unknown. We aimed to investigate whether MetS, inflammatory markers or oxidative stress act as risk factors for affective disorders, and whether MetS is associated with increased inflammation and oxidative stress. METHODS: We conducted a high-risk study including 204 monozygotic (MZ) twins with unipolar or bipolar disorder in remission or partial remission (affected), their unaffected co-twins (high-risk) and twins with no personal or family history of affective disorder (low-risk). Metabolic Syndrome was ascertained according to the International Diabetes Federation (IDF) criteria. Inflammatory markers and markers of oxidative stress were analyzed from fasting blood and urine samples, respectively. RESULTS: The affected and the high-risk group had a significantly higher prevalence of MetS compared to the low-risk group (20% v. 15% v. 2.5%, p = 0.0006), even after adjusting for sex, age, smoking and alcohol consumption. No differences in inflammatory and oxidative markers were seen between the three groups. Further, MetS was associated with alterations in inflammatory markers, and oxidative stress was modestly correlated with inflammation. CONCLUSION: Metabolic syndrome is associated with low-grade inflammation and may act as a risk factor and a trait marker for affective disorders. If confirmed in longitudinal studies, this suggests the importance of early intervention and preventive approaches targeted towards unhealthy lifestyle factors that may contribute to later psychopathology.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".