Language deficits across PET-based Braak stages of tau accumulation in Alzheimer’s disease
Bibliographic record
Abstract
Abstract INTRODUCTION Widespread language complaints in the cognitively unimpaired (CU) may reflect Alzheimer’s Disease (AD) pathology and future objective impairments. METHODS 138 CU, 45 mild cognitive impairment and 28 dementia participants from the TRIAD cohort underwent 18 F-MK-6240 tau-PET and 18 F-AZD-4694 amyloid-PET. Word-finding complaints, confrontation naming, semantic and phonemic fluency and word-knowledge were evaluated. Covariance, direct and stepwise discriminant, and voxel-wise regression analyses were conducted. RESULTS Word-finding complaints appeared in early tau stages (Braak 1–2), followed by naming difficulties (Braak 3–4), and widespread language impairments in later stages (Braak 5–6). Complaints over forgetting the names of objects, naming, and APOE significantly improved classification of early AD pathology. In CU, complaints over forgetting names of objects were linked to left fusiform and inferior temporal gyri tau accumulation. DISCUSSION Language measures are useful in detecting and tracking AD-related pathophysiologies. Results encourage refinement of clinical tools for early detection and disease monitoring. Highlights Language decline parallels tau buildup across PET-based Braak stages of AD. Subjective anomia marks earliest tau-related language symptom (Braak 1–2). Objective naming deficits emerge in the middle tau spread stages (Braak 3–4). Advanced tau spread reflects significant and widespread language impairments. Word-finding complaints correlate with left fusiform and inferior temporal tau. Research in context Systematic review: The literature was reviewed using traditional sources. The core biological definition of Alzheimer’s disease (AD) has recently been linked to its defining cognitive clinical features of episodic memory impairments. Widespread subjective language complaints amongst cognitively unimpaired (CU) older adults and objective language impairments observed across the AD continuum suggests these measures and the further bridging of biological and clinical definitions of AD could play a critical, cost-effective role in disease detection and monitoring. Interpretation : Results extend to tau previous findings describing language changes in AD and related to amyloid status and grey-matter atrophy. They also establish the likely staging of language impairments across the biological AD continuum. Future directions: The manuscript contextualises the use of subjective word-finding complaints, alongside genetic risks to significantly enhance the prediction of underlying AD related pathology in CU. Languages measures used in clinical practice remain limited however and better test should be utilized and developed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".