Intersecting Genetics of Frailty and Cardiovascular Disease
Bibliographic record
Abstract
OBJECTIVES: To determine the genetic correlates of physical frailty and sarcopenia, focusing on single nucleotide polymorphisms (SNPs) in genome-wide association studies (GWAS), and to explore the genetic overlap of frailty with cardiovascular disease (CVD) and its risk factors. METHODS: PubMed was systematically searched for GWAS studies investigating the association between SNPs and objective measures of physical frailty or sarcopenia. SNPs were retained if they were associated with one of the phenotypes of interest by a p-value of 5.0x10-8 or less. RESULTS: Ten studies were included, with a total of 237 SNPs in 181 genes being associated with physical frailty or sarcopenia; as measured by handgrip strength or lean (muscle) mass. These genes were cross-referenced in the GWAS Catalog, and many of them were found to be associated with CVD or metabolic syndrome. CONCLUSIONS: Evidence from GWAS has shown that frailty is associated with common genetic polymorphisms. Many of these polymorphisms have been implicated in CVD, supporting the hypothesis of a shared pathophysiology between these entities. Future studies are eagerly anticipated to map out the mechanistic links and discover therapeutic targets and novel biomarkers for frailty.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".