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Updated: Jun 13, 2026

Frailty Assessment in an Aging Mouse Model
Published on: September 23, 2025
High frailty index scores predict mortality and changes in blood-based biomarkers in aging female mice
Elise S Bisset1, Shashi Gujar2,3,4, Kenneth Rockwood5
1Department of Pharmacology, Dalhousie University, Halifax, Nova Scotia, Canada.
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Variability in aging rates can be quantified with a frailty index (FI) based on the accumulation of clinically evident health deficits in aging mice. Deficit accumulation characteristics have been investigated in longitudinal studies of male but not female mice. We investigated frailty longitudinally in aging female C57BL/6N mice (n = 79; 6-29 months) and determined whether high frailty scores predicted mortality and abnormalities in blood-based biomarkers. Female mice exhibited a gradual rate of deficit accumulation (slope = 0.025) as previously observed in males. High FI scores (>0.20 at 18 months) predicted mortality during follow-up at 24 months and older (p = .015). The range of FI scores broadened with age, with a submaximal limit to frailty of 0.55, similar to values in males. Few correlations were significant between blood-based biomarkers and chronological age in female mice, with only urea (r = 0.39; p = .006) and creatinine (r = 0.35; p = .01) levels exhibiting positive correlations with age. By contrast, many biomarkers were closely graded by the degree of frailty in females. Urea (r = 0.46, p = .001), creatinine (r = 0.35; p = .01), and chloride (r = 0.49; p = .001) were all positively associated with FI scores whereas glucose (r = -0.63; p = .001), hematocrit (r = -0.53; p = .001), and hemoglobin (r = -0.45; p = .002) were negatively correlated. Interestingly, in a small cohort of aging male mice (n = 15; aged 13-27 months), no biomarkers significantly correlated with age, despite many being correlated with frailty. Characteristic features of deficit accumulation are present in female mice. High FI scores based on the accumulation of clinically evident health deficits forecast early mortality and predict abnormalities in blood-based biomarkers better than chronological age.
