Monitoring disease pathophysiology longitudinally using multiparametric PET acquisitions: The McGill TRIAD cohort
Bibliographic record
Abstract
Abstract Background The Translational Biomarkers in Aging and Dementia (TRIAD) cohort aims at describing the biomarker trajectories and interactions between pathophysiological processes as drivers of dementia. While focusing on advanced personalized and preclinical dementia diagnosis, TRIAD’s main objectives include understanding the interactions between amyloid‐β and tau and their role in the progression of brain atrophy and cognitive decline; as well as the role of neuroinflammation, epigenetics and synaptic depletion as mediators of cognitive decline. Method Inclusion into the TRIAD cohort begins with a telephone screening ensuring the participant’s eligibility. Participants sign an ethically approved consent form where they agree to donate biofluids (blood, urine, saliva and cerebrospinal fluid) at the first on‐site visit. The second visit consists of an extensive neuropsychological battery, followed by PET and MRI visits. The PET scans completed are dependent on their diagnosis and the project in which they are enrolled. TRIAD cohort uses a variety of tracers in their different projects to detect the presence of different protein accumulation in the brain. These tracers include [18F]MK6240, [18F]AZD4694, [18F]AV1451, [18F]PI2620 and [18F]RO948, [11C]PBR28 or [18F]DPA, [18F]FEOBV [11C]MRT and [18F]SDM‐8. TRIAD participants complete intermediate telephone follow‐up calls at 6 and 18 months and return for follow‐up clinical and imagery visits 12 and 24 months after baseline, with a retention rate of 75%. Result Since 2017, the TRIAD registry has recruited 1,285 people and enrolled 576 participants. Enrolled in the TRIAD studies are individuals without cognitive impairment (n=345), with mild cognitive impairment (n=75), sporadic and autosomal‐dominant Alzheimer’s disease (n=90), atypical dementia (n=27) and individuals under evaluation (n=39). The TRIAD cohort currently banks 495 baseline blood collections and 108 follow‐up collections with 85 participants having completed 12‐month follow‐up scans and neuropsychological evaluation. Conclusion With a strong participant retention rate, TRIAD presents a striking opportunity to further understand the progression of Alzheimer’s disease with resources ready to uphold the use of affordable biomarkers, capable of diagnosing and measuring disease progression.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".