Nicotinamide as Potential Biomarker for Alzheimer’s Disease: A Translational Study Based on Metabolomics
Bibliographic record
Abstract
Abstract Background: The metabolic routes altered in Alzheimer's disease (AD) brain are poorly understood. As the metabolic pathways are evolutionarily conserved, the metabolic profiles carried out in animal models of AD could be directly translated into human studies Methods: We performed untargeted 1 H-NMR metabolomics in hippocampus of McGill-R-Thy1-APP transgenic (Tg) rats, a model of AD-like cerebral amyloidosis. Three groups of 9 month-old rats were tested: hemizygous Tg+/-, displaying mild amyloid pathology characterized by intraneuronal amyloid β (iAβ) accumulation; homozygous Tg+/+, showing iAβ, senile plaques and neuroinflammation, and wild-type (WT). The translational potential of these findings was assessed in plasma of participants in the German longitudinal study on Aging, Cognition and Dementia (AgeCoDe), by targeted GC-EI/MS. Results : Eighteen metabolites were detected, three of them showed significant differences among genotypes, but only two were specifically assigned to a known molecule: nicotinamide adenine dinucleotide (NAD) and nicotinamide (Nam). Only Tg+/+ rats showed significantly decreased levels of total-NAD, NADH and NAD+ as compared to WT, and a significant increase in NAD+/NADH ratio, suggesting an alteration of the redox state, alongside the reduction of all forms of NAD. Transcript levels of NAD-consuming and NAD-synthesis enzymes were increased in both transgenic genotypes. Next, Nam and NAD were evaluated at the peripheral level in rat plasma, where NAD/H was undetectable, Nam levels were unchanged among genotypes, but Trigonelline (a metabolic product of Nam) was reduced in Tg+/+. While trigonelline was undetected, Nam was significantly reduced in AD demented patients respect to cognitively normal participants (controls). This finding in Nam was replicated in a second independent case-control sample drawn from the same AgeCoDe. Next, the predictive value of Nam on disease progression was analyzed. Herein, reduction of Nam levels was observed in AgeCoDe participants who progressed to AD dementia ~1 year after blood collection, whereas Nam level were not reduced in those who converted afterwards. Conclusions: This preclinical study suggests that dysregulation of NAD/Nam depends on cerebral amyloid burden, and support the hypothesis that changes observed in the hippocampus may be detected in plasma. Furthermore, the findings in AgeCoDe points toward the potential use of Nam as plasma biomarker for AD.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".