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Record W4390194881 · doi:10.1002/alz.077136

A Polygenic Risk Score for Hand Grip Strength is Associated with Cognitive Function in Mid‐to‐Late Life Adults

2023· article· en· W4390194881 on OpenAlexaffabout
Rachel Bercovitch, Earvin S. Tio, Daniel Felsky

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsGrip strengthCognitionEffects of sleep deprivation on cognitive performancePhysical fitnessHand strengthPhysical strengthProxy (statistics)Cardiorespiratory fitnessSarcopeniaPsychologyGerontologyMedicinePhysical medicine and rehabilitationDemographyPhysical therapyInternal medicineStatistics

Abstract

fetched live from OpenAlex

Abstract Background Lower muscular fitness is a risk factor for Alzheimer’s disease (AD). Hand grip strength (HGS) specifically ‐ a proxy for muscular fitness ‐ is a heritable predictor of cognitive decline in aging adults. However, the genetic component of HGS has not yet been explored with respect to cognitive decline. Therefore, we examined the association between a polygenic risk score (PRS) for hand grip strength (HGS) and cognitive function in mid‐to‐late life individuals. Method We accessed data for 22,759 unrelated adults of European ancestry (ages 45‐86) from the Canadian Longitudinal Study on Aging (CLSA), calculating a PRS for HGS using the PRS‐CS‐Auto method and summary statistics from Willems et al., 2017. Linear models were used to test for PRS effects on baseline memory and executive function t‐scores, co‐varying for physical activity and other lifestyle and demographic factors. We also explored interactions with measured hand grip strength, physical activity level, sex, and age. Finally, we tested if our HGS‐PRS was able to significantly augment the predictive performance of a benchmark AD‐PRS, calculated using summary statistics from Bellenguez et al., 2022. Result A higher HGS‐PRS was associated with better global cognitive performance (p = 6.05e‐08). This effect remained significant after controlling for a full set of covariates, including cardiovascular fitness, physical activity, and lean muscle mass (p = 3.14e‐05). Interaction models revealed that age, sex, measured grip strength, and level of physical activity did not change the relationship between HGS‐PRS and cognition. Finally, when assessing whether the HGS‐PRS could augment the predictive performance of an established AD‐PRS, we found significant improvements to models of memory (p = .0035), executive function (p = 7.13e‐06), and global cognition (p = 3.07e‐06). While statistically significant, the additional variance explained in cognition was very small (improvement in R2∼0.1%). Conclusion Genetic predisposition for greater HGS is significantly associated with better cognitive performance in mid‐late life, regardless of sex, fitness, or levels of physical activity. It is therefore possible that direct mind‐muscle connections account for this observation, rather than indirect effects of active lifestyle. Further analyses on longitudinal cognitive outcomes and intermediate brain functional phenotypes are warranted.

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 score0.102
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.049
GPT teacher head0.312
Teacher spread0.263 · 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".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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