Urinary Metal Levels, Cognitive Test Performance, and Dementia in the Multi-Ethnic Study of Atherosclerosis
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».