Specific Nutritional Biomarker Profiles in Mild Cognitive Impairment and Subjective Cognitive Decline Are Associated With Clinical Progression: The NUDAD Project
Bibliographic record
Abstract
OBJECTIVES: Nutritional insufficiencies have been associated with cognitive impairment. Understanding whether nutritional biomarker levels are associated with clinical progression could help to design dietary intervention trials. This longitudinal study examined a panel of nutritional biomarkers in relation to clinical progression in patients with subjective cognitive decline (SCD) or mild cognitive impairment (MCI). DESIGN, SETTING AND PARTICIPANTS: We included 299 patients without dementia (n = 149 SCD; age 61 ± 10 years, female 44%, n = 150 MCI; age 66 ± 8 years, female 38%). Median (interquartile range) follow-up was 3 (2-5) years. METHODS: We measured 28 nutritional biomarkers in blood and 5 in cerebrospinal fluid (CSF), associated with 3 Alzheimer's disease pathologic processes: vascular change (lipids), synaptic dysfunction (homocysteine-related metabolites), and oxidative stress (minerals and vitamins). Nutritional biomarker associations with clinical progression to MCI/dementia and cognitive decline based on the Mini-Mental State Examination score were evaluated using Cox proportional hazard models and linear mixed models. We used partial least squares Cox models (PLS-Cox) to examine nutritional biomarker profiles associated with clinical progression. RESULTS: vitamin D were associated with cognitive decline. PLS-Cox showed 1 profile for SCD, characterized by high betaine and folate and low zinc associated with clinical progression. In MCI, a profile with high theobromine and HDL and low triglycerides and a second profile with high plasma SAM and low cholesterol were associated with risk of dementia. CONCLUSION AND IMPLICATIONS: High HDL was most consistently associated with clinical progression. Moreover, different nutritional biomarker profiles for SCD and MCI showed promising associations with clinical progression. Future dietary (intervention) studies could use nutritional biomarker profiles to select patients, taking into account the disease stage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".