DNA methylation biomarkers for cumulative lead exposures and cognitive impairment
Bibliographic record
Abstract
BACKGROUND: Recent evidence suggests that cumulative low-level lead exposure has adverse effects on cognitive function in the elderly. To date, the few studies that have measured bone lead exposure relied on K-X-ray fluorescence (KXRF), methods that are mostly unavailable in large community-based studies. Here, we employ a methylation-based estimation method for bone and blood lead in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. METHODS: Tibia, patella, and blood lead levels were estimated using blood DNA methylation (DNAm) biomarkers in 625 participants from the ADNI cohort. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Longitudinal analyses were conducted using linear mixed-effect regression models. Participants had different years of baseline (2010-2014) and follow-up visits (2014-2015). RESULTS: DNAm derived tibia and patella lead levels were negatively associated with MoCA scores throughout follow-up, while DNAm derived blood lead level was not associated with MoCA scores. On average, we observed lower MoCA scores with increasing DNAm tibia lead (per interquartile range (IQR): β = -0.23; 95% CI: -0.44, -0.03) and DNAm patella lead, albeit the latter was weaker (per IQR: β = -0.19; 95% CI: -0.41, 0.04). When stratifying by gender, women showed a stronger decrease in cognitive function with increasing DNAm tibia lead (per IQR β = -0.34; 95% CI: -0.65, -0.04) than men (per IQR β = -0.15; 95% CI: -0.42, 0.13). The estimated decrease in MoCA scores per DNAm tibia lead IQR increase was stronger among participants with one or two APOE4 alleles (per IQR β = -0.37; 95% CI: -0.74, -0.01) than those with zero alleles (per IQR β = -0.14; 95% CI: -0.38, 0.10). CONCLUSION: These findings strengthen the evidence that cumulative long-term lead exposure levels are associated with decreased cognitive function in the elderly, especially among women and carriers of one or two APOE4 alleles. These findings based on whole blood methylation data corroborate previous epidemiologic studies that used KXRF for measuring bone lead.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".