Emerging data support associations between depletion of the healthy gut microbiome and aging-related physiological decline and disease. In humans, fecal microbiota transplantation (FMT) has been used successfully to restore gut microbiome structure and function to treat C. difficile infections, but application to healthy aging has been scarcely investigated. The marmoset is an excellent model for evaluating microbiome-mediated changes with age and interventional treatments due to their relatively shorter lifespan and many social, behavioral, and physiological functions that mimic human aging. This review 1) provides an overview of the rationale for FMT to support healthy aging using the marmoset as a translational geroscience model, 2) summarizes prior use of FMT in marmosets, 3) outlines a protocol for studying FMT in aging marmosets, and 4) describes knowledge gaps and future research needs in this field.

Emerging data support associations between the depletion of the healthy gut microbiome and aging-related physiological decline and disease. In humans, fecal microbiota transplantation (FMT) has been used successfully to restore gut microbiome structure and function and to treat C. difficile infections, but its application to healthy aging has been scarcely investigated. The marmoset is an excellent model for evaluating microbiome-mediated changes with age and interventional treatments due to their relatively shorter lifespan and many social, behavioral, and physiological functions that mimic human aging. Prior work indicates that FMT is safe in marmosets and may successfully mediate gut microbiome function and host health. This narrative review (1) provides an overview of the rationale for FMT to support healthy aging using the marmoset as a translational geroscience model, (2) summarizes the prior use of FMT in marmosets, (3) outlines a protocol synthesized from prior literature for studying FMT in aging marmosets, and (4) describes limitations, knowledge gaps, and future research needs in this field.

Assessing body weight is common practice for monitoring health in common marmosets ( Callithrix jacchus ). Body composition analysis via quantitative magnetic resonance (QMR) is a more in-depth assessment allowing measurements of lean and fat mass, but it is expensive and remains unavailable to most. Alternatively, body condition scoring (BCS) is an instrument-free method for visually inspecting and palpating lean and fat tissue. Animals are rated for lean and fat mass abundance, using an ordinal scale with species-specific descriptions as reference. However, modified BCS systems developed for other species are being used, because no BCS system has been fully validated for marmosets. The accuracy of BCS in identifying marmosets with poor body condition or obesity remains unknown. We assessed an adapted BCS for marmosets (n=68, 2–16 years). Objectives were to 1) determine whether BCS predicts body weight and body composition, and 2) evaluate the performance of BCS as a screening test for low body condition and obesity in marmosets, in comparison to QMR body composition analysis. BCS predicted body weight and body composition ( F (15, 166)=7.51, Wilks’ Λ=0.240, p <0.001), and was better at predicting low lean mass and obesity, than at predicting low adiposity. Marmosets with low BCS had higher odds of low lean mass ( B =3.37, (95% CI, 0.95-5.78), OR=29.0, p =0.006). Marmosets with excessively high BCS had higher odds of obesity ( B =2.72, (95% CI, 1.07-4.38), OR=15.23, p =0.001). The accuracy of BCS suggests it can serve as an instrument-free method to screen for low body condition (79.4%-91.2%) and obesity (77.9%) in marmosets. Research highlights: We evaluated body condition scoring (BCS) as a screening tool for detecting low body condition and obesity in marmosets by comparing it to diagnoses based on quantitative magnetic resonance, the gold-standard method for body composition analysis. BCS was more accurate at detecting low lean mass and obesity than low adiposity, with marmosets having low BCS showing higher odds of low lean mass and those with excessively high BCS having higher odds of obesity. Results suggest that BCS can serve as an instrument-free method to screen for low body condition and obesity in marmosets, enabling early detection of health decline and guiding the need for further diagnostic testing and treatment.

The kidney collecting system develops from the ureteric bud (UB), which undergoes multiple rounds of iterative branching. This process is controlled by growth factors and requires the interaction between the extracellular matrix and β1-containing integrin receptors. Integrin affinity for its ligands is regulated by integrin-binding proteins including kindlins, which bind well-defined motifs within the β subunit cytoplasmic tail. We show that mice expressing β1 integrins with mutations that abrogate kindlin binding in the developing UB have mild medullary hypoplasia and a moderate branching defect. Collecting duct (CD) cells expressing the same mutations in the β1 subunit have moderate tubulogenesis, spreading and adhesion defects, but show intact growth factor-dependent signaling. In contrast, mice lacking kindlins in the UB are anephric due to a complete absence of UB budding. Kindlin-knockout CD cells are unable to spread, adhere or respond to growth factors, irrespective of whether the integrins are bound to a ligand. Thus, in addition to regulating integrin function, kindlins mediate crucial growth factor signaling required for initial UB formation.

Valid animal models are needed to evaluate how age related changes in kidney function influence healthspan. Aging marmosets frequently develop renal insufficiency with anemia and exhibit reductions in body mass and metabolic rate. However, it remains unclear which age related changes predict survival and which thresholds indicate increased mortality risk. We prospectively evaluated age, body composition, resting energy expenditure, hematology, and blood chemistry as predictors of 3 year survival in female and male marmosets (n = 66), 2 to 16 years of age. Objectives were to identify prognostic markers, define high risk thresholds, and to develop and test a composite risk factor scale for mortality screening in captivity. A 10 variable model showed the best predictive performance in multivariable Cox proportional hazards modeling, and was retained for further analysis (concordance = 0.881, p < 0.001). ROC curves using Youden Index and AUC identified high risk thresholds for predictors in the multivariable model, and threshold defined categories were evaluated by Kaplan Meier survival analysis. The 10 binary risk factors were combined into a composite scale scored from 0 to 10 and tested with Cox regression. The scale explained approximately 42% of variance in survival and each additional risk factor increased mortality risk 1.75 fold (95% CI: 1.43 to 2.14, p < 0.001). Marmosets with 7 or more risk factors exhibited a 19 month reduction in survival, and this high risk threshold predicted 3 year survival with 89.4% accuracy. Results support the scale as a screening tool for mortality risk and highlight the high prevalence of age associated renal disease and anemia in marmosets.

Objective: Characterize the effects of obesity on common marmoset glucose metabolism and develop predictive markers of glucose metabolism dysfunction. Methods: Body size, weight, lean mass, fat mass, %fat, resting energy expenditure (REE), and glycosylated hemoglobin (HbA1c) were measured on 51 adult marmosets. Physical activity was assessed using actimeter collars (n = 50). A body mass-per-length parameter (BML) was constructed. Animals were classified as without obesity or with obesity (%fat >10%) and by the age they obtained maximum weight (Maxwt). Correlation, MANOVA, and binary logistic regression were used to examine relationships between parameters; path analysis to explore directional relationships. Results: Body fat and BML were correlated (r = 0.565, p < 0.001). Both were correlated with HbA1c (r = 0.658; r = 0.764, p < 0.001). Activity was negatively correlated with %fat and REE (r = −0.437, p = 0.002; r = −0.473, p < 0.001). REE was correlated with %fat, BML, and HbA1c (r > 0.5, p < 0.001). Marmosets with obesity were more likely to have elevated HbA1c (>5.7%; odds ratio = 8.25, p = 0.003). BML above 3.4 g/mm predicted obesity (OR = 6.25 [95% CI 1.62–24.02], p = 0.008) and high HbA1c (OR = 29.47 [95% CI 6.21–139.72], p < 0.001). Early Maxwt predicted increased fat mass (F = −0.476, p = 0.015) and high %fat (F = −0.084, p = 0.014). Conclusion: Both %fat and BML were markers for high HbA1c. Early maximum adult weight predicts increased adiposity and risk of glucose dysfunction.