Identification of age-related protein waves in blood

New proteomic discoveries reveal a link between levels of certain proteins in human plasma and aging.

The field of aging-targeting therapeutics is rapidly evolving. The observation that blood transfusion from young mice to old ones can delay or even reverse aging has paved the way for a whole new chapter in the development of interventions for the management of aging and age-related disorders. However, which blood components exactly are responsible for these effects has yet to be determined [1].

Researchers from Stanford University have identified numerous proteins whose levels change in the blood of humans as we age. A new study measured approximately 3000 plasma proteins from 4263 individuals aged between 18 and 95. The research identified proteins whose levels oscillate in three distinct waves; in the fourth, seventh, and eighth decades of life. These findings are a big step forward in the identification of blood proteins that can slow down or reverse aging, and were published in Nature Medicine [2].

Smaller-scale studies have tried to address similar questions in the past. For example, a study conducted by researchers at the National Institute on Aging (NIA) has led to the identification of a 217-plasma protein signature associated with age. This signature included proteins involved in blood coagulation, chemokine and inflammatory pathways, axon guidance, peptidase activity and apoptosis [3].

There have also been commercialisation efforts around using blood plasma from young people in anti-aging products. For example, Alkahest who we interviewed recently, is a clinical-stage biopharmaceutical company that focuses on blood plasma-based therapies for the management of Alzheimer’s disease and other age-related disorders [4].

However, blood transfusion entails risks and is therefore strictly regulated. The identification and isolation of the blood proteins that are responsible for beneficial effects is an attractive development for those seeking to overcome these obstacles.

Several open questions arise from these studies. What age-related transitions occur in each wave, and what are the mechanisms controlling these transitions? Are these mechanisms the same, or do they differ depending on the particular wave? Where do these age-related oscillating proteins come from? And most importantly, how can we utilise these novel “proteomic aging clocks” to promote Longevity and healthy aging?
We’ll be addressing the answers to these questions in 2020.

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