Our gastrointestinal system functions to digest and absorb ingested food, but it is also home to trillions of microbes that change across time, nutrition, lifestyle, and disease conditions. Largely commensals, these microbes are gaining prominence with regards to how they collectively affect the function of important metabolic organs, from the adipose tissues to the endocrine pancreas to the skeletal muscle. Muscle, as the biggest utilizer of ingested glucose and an important reservoir of body proteins, is intricately linked with homeostasis, and with important anabolic and catabolic functions, respectively. Herein, we provide a brief overview of how gut microbiota may influence muscle health and how various microbes may in turn be altered during certain muscle disease states. Specifically, we discuss recent experimental and clinical evidence in support for a role of gut-muscle crosstalk and include suggested underpinning molecular mechanisms that facilitate this crosstalk in health and diseased conditions. We end with a brief perspective on how exercise and pharmacological interventions may interface with the gut-muscle axis to improve muscle mass and function.
Introduction: The focus on intrinsic capacity (IC) could help clinicians to design interventions to improve the health of the older population. This review aims to map the current state of the art in the field of multi-domain interventions based on the IC framework, to allow health professionals in identifying personalized clinical interventions, oriented to empower the older people with a holistic and positive approach.
Methods: A systematic review of the literature was conducted in July 2021 analyzing manuscripts and articles of the last 10.5 years from PubMed, Scopus, Embase, Google Scholar and Elsevier databases. A total of 12 papers were included.
Results: The majority of successful interventions are based on a goal setting approach where the older people are involved in the definition of the strategy to follow to remain active and independent. None of the study have used the IC as a framework to design a clinical intervention.
Conclusion: To the best of our knowledge, no other reviews are reported in the literature regarding the IC. Our study offers several research directions, which may take the existing debates to the next level.
Introduction: This study aims to develop and validate an integrative intrinsic capacity (IC) scoring system, to investigate its associations with a wide spectrum of biomarkers and to explore the predictive value of the integrative IC score on 4-year mortality among community dwelling people aged 50 years and older.
Methods: We included 839 adults aged ≥50 years from the Social Environment and Biomarkers of Aging Study (SEBAS) and randomly divided them into derivation and validation cohorts to develop the IC scoring system. The multivariate logistic regression model was used to weight each subdomain (locomotion, sensory, vitality, psychological, and cognition) of IC according to its association with impairments in instrumental activities of daily living (IADL) and to construct the integrative IC score. Age-related biomarkers and genetic markers were compared between IC groups by ordinal logistic regression. A Cox proportional hazard model was used to examine the association between IC and mortality, and subgroup analysis was used to assess the robustness of the results among participants aged 60 years and older.
Results: A 12-score IC scoring system (AUROC = 0.83; Hosmer–Lemeshow goodness-of-fit test p = 0.17) was developed, and higher scores indicated better intrinsic capacity. High interleukin (IL)-6, high E-selectin, low serum albumin and low folate were significantly associated with low IC in the whole sample. However, high IL-6, low serum albumin, low folate, high allostatic load, and APOE ε4 genotype were significantly associated with low IC in those aged 60 years old and older. Compared to the high IC group, the low IC group was significantly associated with all-cause mortality (HR: 2.50, 95% CI: 1.22–5.11, p = 0.01 for all participants; HR 2.19, 95% CI 1.03–4.64, p = 0.04 for participants aged 60 years and older).
Conclusions: The conceptually proposed IC can be easily transformed into a scoring system considering different weights of individual subdomains, which not only predicts mortality but also suggests different pathophysiologies across the life course of aging (inflammation, nutrition, stress, and ApoE4 genotype). An intervention study is needed using the composite IC score to promote healthy aging and determine the underlying pathophysiology.