Some proteins in the blood change in characteristic ways with age and physical decline, and that change can be measured. Numerous research groups have put forward various proposed biomarkers of biological age that are based on the proteomic analysis of blood samples. The work here is an illustrative example, focused specifically on frailty in old age. While frailty is regularly measured via tests of physical function, as the researchers note, it is a complicated state that involves not just physical weakness, but also chronic inflammation, immune dysfunction, cognitive decline, and other components. Having a more rigorous measure will assist in the development of rejuvenation therapies capable of reversing frailty, and work continues towards achievement of that goal.

Frailty is a late life phenotype, which is associated with low physiologic reserve and increased vulnerability to adverse outcomes such as disability, hospitalization, and death. Frailty is a multidimensional construct and involves several components, including physical, psychological, cognitive, and social domains. The complexity of this clinical syndrome has made it difficult to elucidate its biology. Although both genetic and proteomic approaches have been applied, previous studies have been inconclusive regarding the biology of frailty. To date, no large-scale proteomic study has been carried out in regard to frailty. An additional challenge is to distinguish the biological antecedents of frailty from aging. Since frailty is strongly associated with chronological age, both may share a common biological signature.

To elucidate the proteomic signature associated with frailty, 4265 proteins were measured in plasma of older adults, of which 55 were positively associated and 88 were negatively associated with frailty. The proteins most strongly associated with frailty were fatty acid-binding proteins, including FABP and FABPA, leptin, and ANTR2. Pathway analysis with the top 143 frailty-associated proteins revealed enrichment for proteins in pathways related to lipid metabolism, musculoskeletal development and function, cell-to-cell signaling and interaction, cellular assembly, and organization. A frailty prediction model utilizing 110 proteins demonstrated a correlation between predicted frailty and observed frailty. Predicted frailty was also more strongly correlated with chronological age than observed frailty.