Risk Factors for Development of Dementia in a Unique Six-Year Cohort Study. I. An Exploratory, Pilot Study of Involvement of the E4 Allele of Apolipoprotein E, Mutations of the Hemochromatosis-HFE Gene, Type 2 Diabetes, and Stroke
Bibliographic record
Abstract
Risk factors for dementia development are not well-defined. We evaluated several factors alone and in combination in a unique cohort of Caucasian volunteers over an approximately 6-year observation window using a nested case/control design. Factors included: apolipoprotein E (ApoE) gene variants (the E4 allele is the strongest confirmed genetic predisposing factor for Alzheimer's disease), the hemochromatosis-HFE gene mutations (H63D and C282Y), diabetes, and stroke. At study entry, subjects were ≥65 years of age (M ± SD = 73.0 ± 4.9), had an MMSE score ≥24, and no evidence of cerebrovascular disease or current depression. Genotyping was completed on 163 available DNA samples from three different groups at the study end: those who still had normal cognitive function; those who had developed dementia; and those with Mild Cognitive Impairment (MCI). Analyses were interpreted at the 95% confidence level without Bonferroni corrections. In the subgroup with dementia, all cases of diabetes were type 2 and present at study entry, whereas all strokes occurred during the study. The results highlight apparently synergistic interactions between genetic and medical risk factors for dementia development, gender differences in risk factors, and involvement of HFE mutations. Having E4 (i.e., either of E3/4 or E4/4), C282Y, H63D, diabetes, or stroke alone did not attain significance. Significant predisposing factors with post-hoc power ≥80% were: E4 homozygosity (E4/4)males+females, odds ratio (OR) = 56.0); E4+diabetes (males+females, OR = 13.7; E4+H63D+diabetes (females, OR = 52.0); E4+stroke (males, OR = 46.5). The importance of preventing diabetes and stroke to ward off dementia and the possible role of iron dysmetabolism in dementia are discussed.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".