Enrollment and Scientific Progress of the Multisite SuperAging Research Initiative
Bibliographic record
Abstract
Abstract Background The SuperAging Research Initiative is a multisite consortium focused on identifying factors promoting extraordinary cognitive aging. The designation of SuperAger is reserved for individuals age 80+ who have episodic memory capacity that would be considered at least average for those 2‐3 decades younger. The presence of such outliers raises questions of fundamental importance to the neurobiology of brain aging, resilience, resistance, and avoidance of cognitive decline caused by Alzheimer’s disease. The original study of SuperAgers emerged at Northwestern and helped establish the phenotype. The SuperAging Research Initiative was established in 2021 and is focused on increasing minority representation and expanding deep phenotyping of this unique population. Methods Harmonized data collection has been initiated across the five sites including behavioral, health, biologic, genetic, environmental, socioeconomic, psychosocial, neuroanatomic, and neuropathologic factors. Here we summarize the initial recruitment progress and baseline characteristics of the current cohort. Results We will present the organizational structure, progress, and baseline characteristics of the cohort to date. The SuperAging Research Initiative includes three Cores (Administrative/Biostatistics, Clinical/Imaging, and Biospecimen/Neuropathology) and two Research Projects. Enrollment (target, n = 500) has commenced across four U.S. Sites located in Illinois, Wisconsin, Michigan, and Georgia, and a Canadian Site in Southwest Ontario, with a focus on enrollment of Black SuperAgers and Cognitively Average Elderly Controls with similar demographics. Project 1 uses state‐of‐the‐art wearable technology to obtain quantitative measurements of daily life including, sleep, physical activity, autonomic responsivity, and social engagement to determine whether SuperAgers have relatively preserved physiologic and behavioral ‘complexity’ compared to Controls. Project 2 focuses on transcriptomic, genetic, and protein profiling to examine central and peripheral immune and inflammatory system parameters of SuperAgers. Conclusions By identifying factors contributing to superior memory performance in old age, outcomes may help isolate modifiable factors that promote healthspan and perhaps also prevent age‐related brain diseases such as Alzheimer’s disease.
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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 | 0.022 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".