Mapping Divergent Subfield‐Specific Hippocampal Degeneration in Mild Cognitive Impairment Continuum: Volumetric, Cognitive, and Genetic Predictors of Accelerated Hippocampal Biological Aging
Bibliographic record
Abstract
OBJECTIVE: To investigate hippocampal subfield atrophy and biological aging across the mild cognitive impairment (MCI) continuum, we used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). METHODS: A cohort of 49 participants, categorized as cognitively normal (CN, n = 16), early MCI (EMCI, n = 16), or late MCI (LMCI, n = 17), underwent comprehensive neuroimaging, neuropsychological, and genetic assessments. High-resolution 3D T1-weighted MRI scans were processed using the volBrain platform and hippocampal subfield segmentation (HIPS) pipeline to quantify hippocampal subfield volumes and estimate biological age. Statistical analyses, including ANCOVA and stepwise regression, were employed to evaluate group differences and identify predictors of hippocampal biological age. RESULTS: The results revealed significant volumetric reductions in LMCI, particularly within the CA1, CA4/dentate gyrus (DG), and stratum radiatum/lacunosum/moleculare (SRLM) subfields, with pronounced lateralized effects. Clinical and demographic covariates attenuated group differences in biological age, but volumetric adjustments highlighted a significant distinction between EMCI and LMCI, with EMCI exhibiting a higher biological age. Cognitive performance, as measured by the Montreal Cognitive Assessment (MoCA), emerged as a consistent predictor of biological age, while APOE ε4 carrier status was significantly elevated in LMCI patients. Regression analyses identified divergent contributions of CA2/3 (positively associated) and CA4/DG (negatively associated) volumes to biological age, underscoring the subfield-specific pathophysiological mechanisms. Asymmetry indices, although variably expressed across groups, offered limited predictive utility, with CA2/3 and CA4/DG asymmetries modestly influencing biological age. CONCLUSION: These findings support the integration of subfield-specific hippocampal volumetry and cognitive assessments in early diagnostic frameworks while highlighting the need for longitudinal studies to elucidate causal pathways linking subfield atrophy, biological aging, and cognitive decline.
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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 | 0.000 |
| 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 | 0.000 | 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".