A systematic review and meta-analysis of lipid metabolomic signatures of Major Depressive Disorder
Bibliographic record
Abstract
The aim of this meta-analysis was to provide a comprehensive synthesis of the evidence examining biomarker signatures in MDD patients including lipids, lipid regulatory proteins (LRP), and polyunsaturated fatty acid (PUFA) as compared to healthy individuals. We performed meta-analyses and meta-regression of the studies comparing lipid, LRP, and PUFA levels between MDD patients and healthy individuals by searching Embase, Ovid Medline, Scopus, PsycINFO, PubMed, and Cochrane databases. Search was performed in these databases up to September 2019 and 29 studies were included. Levels of lipid parameter triglyceride (TG) (SMD 0.55, 95% CI 0.30-0.80, p < 0.0001) were higher while total cholesterol (TC) (SMD = -0.46, 95%CI -0.93 to -0.001, p = 0.04) and very low-density lipoprotein (VLDL) (SMD = -0.46, 95%CI -0.71 to -0.20, p = 0.02) were lower in MDD patients than controls. Subgroup analysis for age showed that the levels of high-density lipoprotein (HDL) were lower in ≥40-year age group (SMD = -0.38, 95%CI -0.70 to -0.06, p = 0.01) and levels of TC was lower in MDD patients in studies from Asian countries (SMD = -0.74, 95%CI -1.37 to -0.10, p = 0.02). TG levels were found to be high all subgroups in MDD patients than controls. A negative association between TC levels and use of lipid lowering medications and a positive association between smoking and LDL levels was found using meta-regression analysis. This study will be useful for physicians when considering the assessment of lipidand LRP profiles in MDD patients to reduce the cardiovascular morbidity and mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.018 | 0.007 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".