Enrollment and Scientific Update for the Multisite SuperAging Research Initiative
Bibliographic record
Abstract
BACKGROUND: Established in 2021, the SuperAging Research Initiative is a multisite, longitudinal study focused on identifying resilience and resistance factors that promote successful cognitive aging. "SuperAgers" are defined as individuals age 80+ with episodic memory performance that is average or better for individuals 20-30 years younger. The SuperAging Research Initiative aims to advance knowledge of the neurobiology of brain aging, resilience, and resistance against "typical" age-related cognitive decline and pathologic declines seen in Alzheimer's disease and related disorders. The SuperAging Research Initiative is focused on increasing racial-ethnic, geographical, and educational diversity by enrolling 500+ participants across the United States and Canada. The mid-project recruitment and enrollment success, baseline participant characteristics, and initial study findings from the unique cohort are highlighted. METHOD: Participant enrollment and harmonized data collection is ongoing at five North American sites. The protocol includes behavioral, biological, environmental, genetic, and psychosocial characteristics that may contribute to successful cognitive aging. Two embedded Research Projects provide focused opportunities to extend the depth and breadth of science. Project 1 utilizes state-of-the-art wearable technology to obtain quantitative measurements of daily activity, and Project 2 uses transcriptomic, genetic, and protein profiling to examine immune and inflammatory system parameters. RESULT: Across sites, >280 participants (ages 80-101 with 6-20 years education) have enrolled in the harmonized protocol using community engaged research (CER) strategies. More than 12 states/provinces are represented. To date, approximately 20% participants identify with a historically underrepresented racial-ethnic group. Sites leveraging existing CER methodology have enrolled a higher percentage of racially diverse participants (30+%). The Project 1 protocol has shown strong feasibility (>90%), yielding high-quality data (>95% data recovery) for a fully remote sensor data collection protocol. Project 2 has begun initial analyses, and estimates to date suggest SuperAgers have similar Alzheimer's disease polygenic risk scores compared to their cognitively-average peers. CONCLUSION: The prospective, longitudinal study of SuperAgers is feasible and provides a unique opportunity to identify mechanisms conferring cognitive resilience and resistance against "typical" and pathologic age-related cognitive decline. Outcomes may identify novel modifiable factors that promote successful cognitive aging.
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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 | 0.205 | 0.228 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.015 | 0.019 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.061 | 0.042 |
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".