Proton Magnetic Resonance Spectroscopy of N-acetyl aspartate in First Depressive Episode and Chronic Major Depressive Disorder: a Systematic Review and Meta-Analysis.
Bibliographic record
Abstract
N-acetyl aspartate (NAA) is a neuronal integrity and functionality marker and its reduction has been demonstrated to indicate neuronal loss or damage. The role of NAA as a marker and/or pathogenetic factor in Major Depressive Disorder (MDD) is still unclear, since previous studies showed discordant results. In this work we aimed to conduct a meta-analysis of the studies that assessed brain levels of NAA in MDD using Proton Magnetic Resonance Spectroscopy (1H-MRS). Studies were retrieved from Scopus® and Web of Knowledge℠ databases using the search terms: n-acetylaspartate OR naa AND major depressive disorder OR mdd OR depression. The inclusion criteria were 1H-MRS studies that compared adult patients (> 18 years old) with a diagnosis of MDD - either First Episode of Depression (FED) or chronic MDD (cMDD) - to healthy controls. We excluded studies: a) recruiting patients with diagnosis other than MDD or whose MDD was secondary to drugs or general medical conditions; b) conducted in children and adolescents; b) using 1H-MRS to investigate brain levels of other cerebral metabolites, such as glutamate, glutamine, myo-inositol, choline, but not NAA. We analysed data separately by illness phase (FED or cMDD) and brain region. Hedges’ g was used as effect size measure. Effect sizes were pooled using a random-effect model. We sought sources of heterogeneity and bias by performing influence analyses with the leave-one-out method and the Graphic Display of Heterogeneity (GOSH) plot analysis. The impact of socio-demographic (i.e., age, % female), methodological (1H-MRS field strength and acquisition sequence, NAA quantification, CSF correction, time echo, time relaxation), and clinical (illness duration, depression symptom severity, antidepressant treatment) moderators was tested with subgroup analyses and meta-regressions for categorical and continuous moderators, respectively. We assessed publication bias by plotting funnel plots and p-curves. The quality of the included studies was evaluated with the Newcastle-Ottawa Quality Assessment Scale (NOS). The protocol for the present systematic review was registered in PROSPERO by ID number CRD 42020221050. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We identified 63 studies, which included a total of 1457 patients and 1184 healthy controls. Among FED patients, we found significantly lower NAA concentrations as compared to healthy controls in the thalamus (n = 1, Hedges’ g = -2.789, 95% CI -3.580 to -2.016) and frontal white matter (n = 1, Hedges’ g = -0.793, 95% CI -1.483 to -0.104). No significant differences were observed in the other analysed brain regions. However, results in FED are to be taken with caution because of the paucity of published data. Among cMDD patients, we found significantly lower NAA concentrations as compared to controls in the frontal lobe (n = 26, Hedges’ g = -0.330, 95% CI -0.598 to -0.062; p = 0.018), the occipital lobe (n = 4, Hedges’ g = -0.677, 95% CI -1.013 to -0.341; p = 0.007), the insula (n = 1, Hedges’ g = -2.949, 95% CI -4.093 to -1.805), the frontal white matter (n = 6, Hedges’ g = -0.471, 95% CI -0.891 to -0.052; p = 0.034), the periventricular white matter (n = 3, Hedges’ g = -0.478, 95% CI -0.938 to -0.018; p = 0.047) and the thalamus after removal of an influential study (n = 4, Hedges’ g = -0.673, 95% CI -1.108 to -0.238; p = 0.016). None of the moderators was found to significantly impact the results. In particular, there was no evidence that antidepressant treatment might modify NAA concentrations, although this should be properly investigated in longitudinal studies. Our findings indicate an association between an altered neuronal metabolism in these brain regions and the pathophysiology of MDD. . Future longitudinal studies are needed to better elucidate if NAA alterations are present in early stages of MDD, and if they can represent a useful biomarker of disease progression and/or therapy response predictor.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.026 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".