NAD+ and Niacin Supplementation as Possible Treatments for Glaucoma and Age-Related Macular Degeneration: A Narrative Review
Bibliographic record
Abstract
Glaucoma and age-related macular degeneration (AMD) are progressive retinal diseases characterized by increased oxidative stress, inflammation, and mitochondrial dysfunction. This review investigates the potential therapeutic benefits of NAD+ and niacin supplementation in managing glaucoma and AMD. A literature search was conducted encompassing keywords such as "niacin", "NAD", "glaucoma", "AMD", and "therapeutics". NAD+ depletion is associated with increased oxidative stress and mitochondrial dysfunction in glaucoma and AMD. Niacin, a precursor to NAD+, has shown promise in replenishing NAD+ levels, improving choroidal blood flow, and reducing oxidative damage. Animal studies in glaucoma models indicate that nicotinamide (NAM) supplementation preserves RGC density and function. Large-scale population-based studies indicate an inverse correlation between niacin intake and glaucoma prevalence, suggesting a preventative role. Randomized controlled trials assessing niacin supplementation showed significant improvements in visual field sensitivity and inner retinal function, with a dose-dependent relationship. In AMD, nicotinamide supplementation may improve rod cell function and protect against oxidative stress-induced damage. Cross-sectional studies reveal that individuals with AMD have a lower dietary intake of niacin. Further studies suggest niacin's role in improving choroidal blood flow and dilating retinal arterioles, potentially mitigating ischemic damage and oxidative stress in AMD. Beyond current management strategies, NAD+ and niacin supplementation may offer novel therapeutic avenues for glaucoma and AMD. Further research is warranted to elucidate their efficacy and safety in clinical settings.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".