We previously quantified frailty in aged mice with frailty index (FI) that used specialized equipment to measure health parameters. Here we developed a simplified, noninvasive method to quantify frailty through clinical assessment of C57BL/6J mice (5–28 months) and compared the relationship between FI scores and age in mice and humans. FIs calculated with the original performance-based eight-item FI increased from 0.06±0.01 at 5 months to 0.36±0.06 at 19 months and 0.38±0.04 at 28 months (n = 14). By contrast, the increase was graded with a 31-item clinical FI (0.02±0.005 at 5 months; 0.12±0.008 at 19 months; 0.33±0.02 at 28 months; n = 14). FI scores calculated from 70 self-report items from the first wave of the Survey of Health, Ageing and Retirement in Europe were plotted as function of age (n = 30,025 people). The exponential relationship between FI scores and age (normalized to 90% mortality) was similar in mice and humans for the clinical FI but not the eight-item FI. This noninvasive FI based on clinical measures can be used in longitudinal studies to quantify frailty in mice. Unlike the performance-based eight-item mouse FI, the clinical FI exhibits key features of the FI established for use in humans.

The changes that occur in the microbiome of aging individuals are unclear, especially in light of the imperfect correlation of frailty with age. Studies in older human subjects have reported subtle effects, but these results may be confounded by other variables that often change with age such as diet and place of residence. To test these associations in a more controlled model system, we examined the relationship between age, frailty, and the gut microbiome of female C57BL/6 J mice. The frailty index, which is based on the evaluation of 31 clinical signs of deterioration in mice, showed a near-perfect correlation with age. We observed a statistically significant relationship between age and the taxonomic composition of the corresponding microbiome. Consistent with previous human studies, the Rikenellaceae family, which includes the Alistipes genus, was the most significantly overrepresented taxon within middle-aged and older mice. The functional profile of the mouse gut microbiome also varied with host age and frailty. Bacterial-encoded functions that were underrepresented in older mice included cobalamin (B12) and biotin (B7) biosynthesis, and bacterial SOS genes associated with DNA repair. Conversely, creatine degradation, associated with muscle wasting, was overrepresented within the gut microbiomes of the older mice, as were bacterial-encoded β-glucuronidases, which can influence drug-induced epithelial cell toxicity. Older mice also showed an overabundance of monosaccharide utilization genes relative to di-, oligo-, and polysaccharide utilization genes, which may have a substantial impact on gut homeostasis. We have identified taxonomic and functional patterns that correlate with age and frailty in the mouse microbiome. Differences in functions related to host nutrition and drug pharmacology vary in an age-dependent manner, suggesting that the availability and timing of essential functions may differ significantly with age and frailty. Future work with larger cohorts of mice will aim to separate the effects of age and frailty, and other factors.

Although many common diseases occur mostly in old age, the impact of ageing itself on disease risk and expression often goes unevaluated. To consider the impact of ageing requires some useful means of measuring variability in health in animals of the same age. In humans, this variability has been quantified by counting age-related health deficits in a frailty index. Here we show the results of extending that approach to mice. Across the life course, many important features of deficit accumulation are present in both species. These include gradual rates of deficit accumulation (slope = 0.029 in humans; 0.036 in mice), a submaximal limit (0.54 in humans; 0.44 in mice), and a strong relationship to mortality (1.05 [1.04–1.05] in humans; 1.15 [1.12–1.18] in mice). Quantifying deficit accumulation in individual mice provides a powerful new tool that can facilitate translation of research on ageing, including in relation to disease.

Although bone marrow-derived mesenchymal stromal cells (MSCs) may be beneficial in treating heart disease, their ability to transdifferentiate into functional cardiomyocytes remains unclear. Here, bone marrow-derived MSCs from adult female transgenic mice expressing green fluorescent protein (GFP) under the control of the cardiac-specific α-myosin heavy chain promoter were cocultured with male rat embryonic cardiomyocytes (rCMs) for 5–15 days. After 5 days in coculture, 6.3% of MSCs became GFP+ and stained positively for the sarcomeric proteins troponin I and α-actinin. The mRNA expression for selected cardiac-specific genes (atrial natriuretic factor, Nkx2.5, and α-cardiac actin) in MSCs peaked after 5 days in coculture and declined thereafter. Despite clear evidence for the expression of cardiac genes, GFP+ MSCs did not generate action potentials or display ionic currents typical of cardiomyocytes, suggesting retention of a stromal cell phenotype. Detailed immunophenotyping of GFP+ MSCs demonstrated expression of all antigens used to characterize MSCs, as well as the acquisition of additional markers of cardiomyocytes with the phenotype CD45−-CD34+-CD73+-CD105+-CD90+-CD44+-SDF1+-CD134L+-collagen type IV+-vimentin+-troponin T+-troponin I+-α-actinin+-connexin 43+. Although cell fusion between rCMs and MSCs was detectable, the very low frequency (0.7%) could not account for the phenotype of the GFP+ MSCs. In conclusion, we have identified an MSC population displaying plasticity toward the cardiomyocyte lineage while retaining mesenchymal stromal cell properties, including a nonexcitable electrophysiological phenotype. The demonstration of an MSC population coexpressing cardiac and stromal cell markers may explain conflicting results in the literature and indicates the need to better understand the effects of MSCs on myocardial injury. Disclosure of potential conflicts of interest is found at the end of this article.

A number of clinical studies have reported that diabetes mellitus (DM) is an independent risk factor for Atrial fibrillation (AF). After adjustment for other known risk factors including age, sex, and cardiovascular risk factors, DM remains a significant if modest risk factor for development of AF. The mechanisms underlying the increased susceptibility to AF in DM are incompletely understood, but are thought to involve electrical, structural, and autonomic remodeling in the atria. Electrical remodeling in DM may involve alterations in gap junction function that affect atrial conduction velocity due to changes in expression or localization of connexins. Electrical remodeling can also occur due to changes in atrial action potential morphology in association with changes in ionic currents, such as sodium or potassium currents, that can affect conduction velocity or susceptibility to triggered activity. Structural remodeling in DM results in atrial fibrosis, which can alter conduction patterns and susceptibility to re-entry in the atria. In addition, increases in atrial adipose tissue, especially in Type II DM, can lead to disruptions in atrial conduction velocity or conduction patterns that may affect arrhythmogenesis. Whether the insulin resistance in type II DM activates unique intracellular signaling pathways independent of obesity requires further investigation. In addition, the relationship between incident AF and glycemic control requires further study.