Genetic Risk for Attention-Deficit/Hyperactivity Disorder Predicts Cognitive Decline and Development of Alzheimer’s Disease Pathophysiology in Cognitively Unimpaired Older Adults
Bibliographic record
Abstract
Abstract Background Attention-Deficit/Hyperactivity Disorder (ADHD) persists in older age and is postulated to be a risk factor for cognitive impairment and Alzheimer’s Disease (AD). However, this notion relies exclusively on epidemiological associations, and no previous study has linked ADHD with a decline in cognitive performance in older adults or with AD progression. Therefore, this study aimed to determine whether genetic liability for ADHD, as measured by a well-validated ADHD polygenic risk score (ADHD-PRS), is associated with longitudinal cognitive decline and the development of AD pathophysiology in cognitively unimpaired (CU) older adults. Methods We calculated a weighted ADHD-PRS in 212 CU individuals without a clinical diagnosis of ADHD (55-90 years) using whole-genome information. These individuals had baseline amyloid-β (Aβ) positron emission tomography, as well as longitudinal cerebrospinal fluid (CSF) phosphorylated tau at threonine 181, structural magnetic resonance imaging, and cognitive assessments for up to 6 years. Linear mixed-effects models were used to test the association of ADHD-PRS with cognition and AD biomarkers. Outcomes Higher ADHD-PRS was associated with greater cognitive decline over 6 years. The combined effect between high ADHD-PRS and brain Aβ deposition on cognitive deterioration was more significant than each individually. Additionally, higher ADHD-PRS was associated with increased CSF p-tau 181 levels and frontoparietal atrophy in CU Aβ-positive individuals. Interpretation Our results suggest that genetic liability for ADHD is associated with cognitive deterioration and the development of AD pathophysiology in the CU elderly. These findings indicate that ADHD-PRS might inform the risk of developing cognitive decline in this population. Funding National Institute of Health and Brain & Behavioral Research Foundation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".