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Background: Clinically similar older adults demonstrate variable responses to health stressors, heterogeneity attributable to differences in physical resilience. However, molecular mechanisms underlying physical resilience are unknown. We previously derived a measure of physical resilience after hip fracture-the expected recovery differential (ERD)-that captures the difference between actual recovery and predicted recovery. Starting with biomarkers associated with physical performance, morbidity, mortality, and hip fracture, we evaluated associations with the ERD to identify biomarkers of physical resilience after hip fracture.Methods: In the Baltimore Hip Studies (N = 304) sera, we quantified biomarkers of inflammation (TNFR-I, TNFR-II, sVCAM-1, and IL-6), metabolic and mitochondrial function (non-esterified fatty acids, lactate, ketones, acylcarnitines, free amino acids, and IGF-1), and epigenetic dysregulation (circulating microRNAs). We used principal component analysis, canonical correlation, and least absolute shrinkage and selection operator regression (LASSO) to identify biomarker associations with better-than-expected recovery (greater ERD) after hip fracture.Results: Participants with greater ERD were more likely to be women and less disabled at baseline. The complete biomarker set explained 37% of the variance in ERD (p < .001) by canonical correlation. LASSO regression identified a biomarker subset that accounted for 27% of the total variance in the ERD and included a metabolic factor (aspartate/asparagine, C22, C5:1, lactate, glutamate/mine), TNFR-I, miR-376a-3p, and miR-16-5p.Conclusions: We identified a set of biomarkers that explained 27% of the variance in ERD-a measure of physical resilience after hip fracture. These ERD-associated biomarkers may be useful in predicting physical resilience in older adults facing hip fracture and other acute health stressors. [ABSTRACT FROM AUTHOR]

Background: Approaches for quantifying physical resilience in older adults have not been described.Methods: We apply two conceptual approaches to defining physical resilience to existing longitudinal data sets in which outcomes are measured after an acute physical stressor. A "recovery phenotype" approach uses statistical methods to describe how quickly and completely a patient recovers. Statistical methods using a recovery phenotype approach can consider multiple outcomes simultaneously in a composite score (eg, factor analysis and principal components analysis) or identify groups of patients with similar recovery trajectories across multiple outcomes (eg, latent class profile analysis). An "expected recovery differential" approach quantifies how patients' actual outcomes are compared to their predicted outcome based on a population-derived model and their individual clinical characteristics at the time of the stressor.Results: Application of the approaches identified different participants as being the most or least physically resilient. In the viral respiratory cohort (n = 186) weighted kappa for agreement across resilience quartiles was 0.37 (0.27-0.47). The expected recovery differential approach identified a group with more comorbidities and lower baseline function as highly resilient. In the hip fracture cohort (n = 541), comparison of the expected recovery differentials across 10 outcome measures within individuals provided preliminary support for the hypothesis that there is a latent resilience trait at the whole-person level.Conclusions: We posit that recovery phenotypes may be useful in clinical applications such as prediction models because they summarize the observed outcomes across multiple measures. Expected recovery differentials offer insight into mechanisms behind physical resilience not captured by age and other comorbidities. [ABSTRACT FROM AUTHOR]

Background. Advanced glycation endproducts are biologically active compounds that accumulate in disordered metabolism and normal aging. Carboxymethyl-lysine (CML), a ubiquitous human advanced glycation endproduct, has been associated with age-related conditions and mortality. Our objective was to ascertain the relationship between CML and geriatric outcomes (disability and frailty) in a large cohort of older men and women. Methods. In 1996–1997, serum CML was measured in 3,373 Cardiovascular Health Study participants (mean age 78.1 ± 4.8 years). Disability, defined as difficulty in any of six activities of daily living, was assessed every 6–12 months for 14 years. Frailty was defined according to five standard criteria at the 1996–1997 visit. Cox proportional hazard models estimated the relationship between CML and incident disability (N = 2,643). Logistic regression models estimated the relationship between CML and prevalent frailty. Results. Adjusting for multiple potential confounders, higher CML was associated with incident disability (hazard ratio per standard deviation [225 ng/mL] increase: 1.05, 95% CI 1.01–1.11). In men, odds of frailty increased with higher CML values (odds ratio = 1.30 per standard deviation, 95% CI 1.14–1.48), but the relationship was attenuated by adjustment for cognitive status, kidney function, and arthritis. CML was not associated with frailty in women. Conclusions. Higher serum CML levels in late life are associated with incident disability and prevalent frailty. Further work is needed to understand CML’s value as a risk stratifier, biomarker, or target for interventions that promote healthy aging. [ABSTRACT FROM PUBLISHER]