Evidence map›Paper›PMID 41692986›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2026

Social and clinical frailty indices in aging mice: a comparative analysis of longitudinal and cross-sectional designs.

Maria Razzoli, Charles W Collinge, Monica Luciana, Alessandro Bartolomucci

Abstract readComparative Study
In one paragraph

Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. How human and animal frailty index studies can inform each other: a brief narrative review.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
    Review
  2. The association of frailty with age and lifespan in mice differs by strain and sex.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Maria RazzoliDepartment of Integrative Biology and Physiology, University of Minnesota, Minneapolis, United States.
Charles W CollingeDepartment of Psychology, University of Minnesota, Minneapolis, United States.ORCID 0009-0009-5757-8376
Monica LucianaDepartment of Psychology, University of Minnesota, Minneapolis, United States.
Alessandro BartolomucciDepartment of Integrative Biology and Physiology, University of Minnesota, Minneapolis, United States.ORCID 0000-0001-6439-8829

Funding

Mouse models for the influence of the social environment on health and agingR33AG078520 · NIA · UNIVERSITY OF MINNESOTA · PI Alessandro Bartolomucci · 2024 to 2026
$1.7M
Biotechnology and Molecular Genomics #18.4Biotechnology and Molecular Genomics #24.01National Institutes of Health/National Institute on Aging R61/R33 AG078520NIA NIH HHS R33 AG078520
6 · The paper itself

Abstract

Aging is a heterogeneous phenomenon provoked by biological processes that still need to be fully understood. Frailty is a relevant outcome of aging reflecting biological decline that can be quantified through indices measuring the accumulation of functional deficits. Age-related declines may occur across multiple domains of functioning, and longitudinal study designs may better characterize decline within aging individuals. Thus, it is imperative to characterize how frailty indices that capture different functional domains associate with one another over the natural lifespan and across study designs. Here, the clinical frailty index (CFI) and the mouse social frailty index (mSFI) were applied to male and female mice both longitudinally and cross-sectionally over the lifespan. An overall similar association with aging was apparent: within each cohort, both CFI and mSFI were strongly positively associated with age. The utility of the CFI and mSFI as age predictors within the longitudinal study was confirmed. Critically, a model developed within the longitudinal study based on CFI scores, mSFI scores, and sex was able to predict age better than alternative models using only one of the indices. This result suggests that the CFI and the mSFI capture intrinsically different elements of deficit accumulation with age. The same model also showed a good performance in predicting the age of mice in the cross-sectional study. Overall, these results demonstrate that the information captured by both frailty indices is relevant to aging, relationships between indices vary across study design, and both frailty domains are needed to produce better age predictions.

Indexed as

AgingFrailtyAnimalsCross-Sectional StudiesFemaleLongitudinal StudiesMaleMiceMice, Inbred C57BLAnimal modelBiomarkers of agingGeroscienceLinear mixed-effects models

Identifiers

PMID41692986
PMCPMC13200211

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.