Urinary Metal Levels, Cognitive Test Performance, and Dementia in the Multi-Ethnic Study of Atherosclerosis
Bibliographic record
Abstract
Importance: Metals are established neurotoxicants, but evidence of their association with cognitive performance at low chronic exposure levels is limited. Objective: To investigate the association of urinary metal levels, individually and as a mixture, with cognitive tests and dementia diagnosis, including effect modification by apolipoprotein ε4 allele (APOE4). Design, Setting, and Participants: The multicenter prospective cohort Multi-Ethnic Study of Atherosclerosis (MESA) was started from July 2000 to August 2002, with follow-up through 2018. A total of 6303 MESA participants were included. Data analysis was performed from October 12, 2023, to June 13, 2024. Exposure: Urine samples were collected at baseline (2000-2002), and arsenic, cadmium, cobalt, copper, lead, manganese, tungsten, uranium, and zinc levels were measured in 2020-2022. Main Outcomes and Measures: Digit Symbol Coding (DSC) (n = 3819) (possible score range, 0-133), Cognitive Abilities Screening Instrument (CASI) (n = 3918) (possible score range, 0-100), and Digit Span (DS) (n = 4176) (possible score range, 0-30) cognitive tests were administered in 2010-2012; higher scores of each test indicate increasing levels of positive response. Results: A total of 6303 participants were followed up for dementia diagnosis through 2018. The median age at baseline was 60 (IQR, 53-70) years, and 3303 participants (52.4%) were female. The median cognitive scores were 51 (IQR, 38-64) for DSC, 90 (IQR, 84-95) for CASI, and 15 (IQR, 12-18) for DS. There were 559 cases of dementia through the follow-up period. Inverse associations with DSC were identified: mean differences in z scores per IQR increase in metal levels were -0.03 (95% CI, -0.07 to 0.00) for arsenic, -0.05 (95% CI, -0.09 to -0.004) for cobalt, -0.05 (95% CI, -0.07 to -0.02) for copper, -0.04 (95% CI, -0.08 to -0.001) for uranium, and -0.03 (95% CI, -0.06 to -0.01) for zinc. Among 1058 APOE4 carriers, manganese was also inversely associated with DSC. The joint mean difference of DSC comparing percentile 95th with the 25th of the 9-metal mixture was -0.30 (95% CI, -0.47 to -0.14) for APOE4 carriers and -0.10 (95% CI, -0.19 to -0.01) for noncarriers. Arsenic, cadmium, cobalt, copper, tungsten, uranium, and zinc were individually associated with dementia, with hazard ratios per IQR of metal ranging from 1.15 (95% CI, 1.03-1.29) for tungsten to 1.46 (95% CI, 1.06-2.02) for uranium. The joint hazard ratio of dementia comparing percentiles 95th with the 25th of the 9-metal mixture was 1.71 (95% CI, 1.24-3.89), with no significant difference by APOE4 status. Conclusions and Relevance: In this study, participants with higher concentrations of metals in their urine, compared with those with lower concentrations, had worse performance on cognitive tests and greater likelihood of developing dementia. The findings of this multicenter multiethnic cohort study might inform screening and potential interventions for prevention of dementia based on individuals' metal exposure levels and genetic profiles.
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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 | 0.000 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".