Inflammatory Signatures in Older Persons with Physical Frailty and Sarcopenia

Experimental Gerontology
15 May, 2019 ,

Emanuele Marzetti et al used a multivariate statistical approach to explore the link between a large panel of inflammatory biomolecules and PF&S in older adults and explored gender-specific inflammatory patterns. They also included 100 non-sarcopenic, non-frail controls (non-PF&S) in this study. Higher levels of P-selectin, C-reactive protein (CRP), and interferon γ-induced protein 10 defined the inflammatory profile of people with PF&S. Higher levels of myeloperoxidase (MPO), interleukin (IL)-8, monocyte chemoattractant protein 1 (MCP-1), macrophage inflammatory protein 1-α, and platelet-derived growth factor (PDGF) BB characterized non-PF&S participants. A “core” inflammatory signature of PF&S was identified in this study by performing gender-specific partial least squares discriminant analysis. This signature consisted of higher levels of CRP and lower levels of MPO, IL8, MCP-1, and PDGF-BB, with peculiar patterns of links for men and women.

Source
Full content

Abstract

Background

The construct of physical frailty and sarcopenia (PF&S) identifies an age-related pre-disability condition defined by reduced physical performance and low muscle mass. Whether PF&S is characterized by perturbations of the cytokine network is presently unclear. Furthermore, the existence of gender-specific inflammatory profiles of PF&S is unknown. This study was designed to explore the association between a large panel of inflammatory biomolecules and PF&S in older adults through a multivariate statistical approach. Gender-specific inflammatory patterns were also explored.

Methods

One-hundred community-dwellers aged 70 years and older with PF&S and 100 non-sarcopenic, non-frail controls (nonPF&S) were enrolled. A panel of 30 circulating inflammatory biomarkers was assayed. Partial least squares discriminant analysis (PLS-DA) was employed to explore the relationship between inflammatory molecules and PF&S. Separate PLS-DA models were built for the whole sample and the two genders. Double cross-validation procedures were used to validate the predictive ability of PLS-DA models.

Results

The optimal complexity of the PLS-DA model built on the whole sample was found to be four latent variables. The proportion of correct classification was 75.6 ± 1.3% (82.3 ± 1.6% for enrollees with PF&S and 68.7 ± 2.5% for nonPF&S controls). The inflammatory profile of people with PF&S was defined by higher levels of P-selectin, C-reactive protein (CRP), and interferon γ-induced protein 10. NonPF&S participants were characterized by higher levels of myeloperoxidase (MPO), interleukin (IL) 8, monocyte chemoattractant protein 1 (MCP-1), macrophage inflammatory protein 1-α, platelet-derived growth factor (PDGF) BB. Gender-specific PLS-DA allowed identifying a “core” inflammatory signature of PF&S, composed by higher levels of CRP, and lower concentrations of MPO, IL8, MCP-1, and PDGF-BB, with peculiar patterns of relationships for men and women.

Conclusions

A core inflammatory profile was identified in people with PF&S with a gender-specific signature. The dissection of the PF&S “cytokinome” will provide novel insights into the role played by inflammation in the disabling cascade and allow designing personalized treatment strategies.