Blood Lead Levels, ALAD Gene Polymorphisms, and Mortality
Bibliographic record
Abstract
BACKGROUND: Previous analyses from the National Health and Nutrition Examination Survey (NHANES III) have found that elevated blood lead levels may be associated with cardiovascular mortality, cancer mortality, and all-cause mortality. The 5-aminolevulinic acid dehydratase (ALAD) G177C genetic polymorphism (rs 1800435) affects lead toxicokinetics and may alter the adverse effects of lead exposure. We examined whether the ALAD G177C single nucleotide polymorphism (SNP) affects the relationship between lead and mortality. METHODS: We analyzed a subset of 3349 genotyped NHANES III participants at least 40 years of age. Using Cox proportional hazards regression, we estimated the relative risk of all-cause, cardiovascular disease, and cancer mortality by ALAD genotype, and by blood lead levels (<5 μg/dL vs. ≥5 μg/dL). We also tested whether the ALAD genotype modified the relationship between blood lead level and mortality. RESULTS: The adjusted overall relative risk for participants with the variant ALAD genotype was decreased for all-cause mortality (hazards ratio = 0.68; [95% confidence interval = 0.50-0.93]) compared with persons having the common GG genotype. There was some suggestion that higher lead levels were associated with cancer mortality (1.48 [0.92-2.38]). We observed no convincing interaction effect between ALAD genotype and blood lead level on mortality risk. CONCLUSION: The ALAD genotype may be associated with decreased mortality from all causes and from cancer. This association does not seem to be affected by lead exposure.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".