Bilingualism is associated with lower cognitive decline and with lower levels of AD biomarkers in a cognitively unaffected cohort
Bibliographic record
Abstract
Abstract Background Speaking two or more languages has been shown to contribute to cognitive reserve and to delay the onset of Alzheimer’s disease (AD). However, little is known about the effect of bilingualism on the progression of AD biomarkers. In this study, we intended to investigate the effect of bilingualism on cognitive scores and on AD biomarkers in a cohort of cognitively unaffected individuals. Method We analyzed data from participants of the PREVENT‐AD cohort. This cohort comprises cognitively normal participants over the age of 55 who have a first degree relative with AD. Cognition was assessed with the RBANS scale, Tau burden was measured with [18F]‐AV1451 PET, and CSF biomarkers were measured with Innotest’s enzyme‐linked immunosorbent assay kit (Fujirebio, Ghent, Belgium). Analyses were performed comparing participants who speak one, two or three languages and comparing participants who speak one or more than one language. Result A total of 327 participants were included, with 89 that speak one language, 195 that speak two languages, and 43 that speak three languages. We found that participants who speak more than one language have significantly higher attention scores (p=0.041) (Fig. 1a) and total RBANS scores (p=0.021) (Fig 1b) than participants who speak only one language. Participants who speak two languages have a lower tau burden in the entorhinal cortex than participants who speak one language (p=0.047) (Fig. 2). For total Tau, participants who speak more than one language have lower CSF levels than participants who speak one language. This difference increases over time and becomes statistically significant on follow up visits 36 months (p=0.049) and 48 months (p= 0.031) (Fig 3a). Participants who speak more than one language have lower CSF levels of phospho‐Tau (p= 0.017) (Fig 3b), and neurofilament light (p=0.041)(Fig 3c) compared to participants who speak one language. Conclusion Our results show that bilingualism is associated not only with less cognitive decline, but also with lower levels of AD biomarkers in pre‐symptomatic AD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".