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Record W4403492491 · doi:10.1101/2024.10.15.618102

A protective role for the cerebellum in cognitive aging

2024· preprint· en· W4403492491 on OpenAlexaboutno aff
Federico d’Oleire Uquillas, Esra Sefik, Jakob Seidlitz, Jewel Merriman, Veronica Zhang, Rafael Romero-Garcia, Varun Warrier, Richard A. I. Bethlehem, Aaron Alexander‐Bloch, Jorge Sepulcre, Samuel S.‐H. Wang, Patrizia Vannini, Jesse Gomez

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCerebellumCognitionCognitive psychologyNeurosciencePsychologyCognitive aging

Abstract

fetched live from OpenAlex

Abstract Background Brain reserve — the brain’s resilience to age-related change or damage — provides protection against cognitive decline. The cerebellum is relatively unstudied as a contributor to brain reserve. This study investigates cerebellar brain reserve in the largest cohort to date. Methods We used data from the Human Connectome Project (n=708, 36-100yrs), UK Biobank (n=45,013, 44-81yrs), and ADNI (n=1,423, 56-95yrs). ADNI participants were cognitively normal or had a diagnosis of mild cognitive impairment or Alzheimer’s disease (AD) dementia. We examined associations between cerebellar tissue volume, age, Montreal Cognitive Assessment (MoCA) scores, global PET amyloid burden, and APOE genotype. Findings HCP-Aging data revealed heterogenous aging-associated changes in cerebellar volume, with the greatest effects in posterior hemispheric regions (crus I) (Bonferroni-corrected, p <0·05). MoCA scores were associated with higher tissue density in the cerebellum ( p <0·0001) to the same extent as neocortex, and MoCA scores coupled most strongly with posterior cerebellar cortex. Strikingly, greater volume in MoCA visuospatial-related cerebellar cortex protected against aging-related cognitive decline ( p =0·0001). We replicated tissue aging results in the UK Biobank with the greatest aging-related effects in posterior cerebellum ( p <0·0001), and an association of greater cerebellar volumes with less cognitive decline (Trails Making-B: p <0·00001; Digit Symbol Substitution: p =0·034). AD patients with low amyloid-beta burden (Aβ−) exhibited the strongest cerebellar association with MoCA (volume x group, Aβ− AD: p =0·0001). In Aβ− individuals, APOE ε4/ε4 carriers showed the greatest effect with MoCA (volume x APOE, ε4/ε4: p =0·017). Interpretation Our large-scale study demonstrates a potentially strong role for the cerebellum in mitigating cognitive decline. The persistence of this protection in APOE ε4/ε4 carriers reshapes our understanding of reserve and AD risk. Our findings open the cerebellum as a novel target for future clinical research on brain reserve in aging populations. Funding National Science Foundation, National Academies of Sciences, Engineering and Medicine, National Institutes of Health. Research in Context Evidence before this study We searched PubMed and GoogleScholar between August 12, 2023, and September 25, 2024 for articles irrespective of language or date of publication, relating to measures of cortical and cerebellar aging. Search terms included “cerebellum”, “cognitive aging”, “cerebellar reserve”, “Alzheimer’s disease”, “covariance”, “retrogenesis”, and “connectivity”. Prior research demonstrated that the cerebellum may play a role in cognitive function. Studies have shown that cerebellar development is spatially heterogenous, with posterior regions undergoing the most protracted change in structure and function. Brain reserve has been predominantly studied in the neocortex, with some studies suggesting the cerebellum may contribute to cognitive changes in diseases like Alzheimer’s disease (AD) dementia. Cerebellar volume differences between young and older adults have been noted, as well as between healthy adults and neurodegenerative conditions like Parkinson’s disease. However, the cerebellum’s contribution to cognitive reserve, particularly in healthy aging and individuals with a clinical diagnosis of mild cognitive impairment or AD dementia, had not been explored especially in large population-based datasets. Added value of this study To our knowledge, this study is the largest to date looking into how cerebellar structures contribute to cognitive outcomes in both healthy older adults, and those with mild cognitive impairment or AD dementia. We leverage three large neuroimaging datasets — HCP-Aging, UK Biobank, and ADNI — and demonstrate that cerebellar aging is spatially heterogeneous, with posterior regions showing the greatest age-related decline. We further establish a significant link between larger cerebellar volumes and better cognitive outcomes, suggesting that the cerebellum plays a role in cognitive resilience. Additionally, we identify how cerebellar structures predict cognitive performance and interact with amyloid-beta brain pathology and APOE genotype, particularly in those with low amyloid brain burden and those at greatest risk of AD such as in homozygous APOE e4 allele carriers. Implications of all the available evidence The aging of the global population raises the challenge of maintaining cognitive health in older age. Our research focuses on the cerebellum as a novel mediator of preserved cognitive function in old age and clinical dementia. Our findings have profound implications, given that individuals with robust cerebellar structures may be missed during cognitive and clinical screenings. Greater cerebellum volume seems to be most advantageous in those at higher risk for Alzheimer’s disease based on APOE4 status and those who have yet to accumulate substantial amyloid-beta brain pathology. Our study underscores the importance of the cerebellum as a novel brain reserve mechanism in aging populations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.030
GPT teacher head0.258
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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