There are numerous methods to construct a measure of biological age, with machine learning playing a key role in determining algorithmic combinations of measured values that correlate with age. Researchers suggest using protein aggregate levels as the basis for building a biological clock, as proteins tend to aggregate more with advancing age, particularly IDPs which are prone to forming amyloids. This aggregation could serve as an indicator of cell health and disease risk. While challenges remain, further research on IDP dynamics could lead to advancements in measuring biological aging processes.
As we age, our bodies undergo changes in DNA and proteins, leading to a decline in body function and increased risk of age-related diseases. Specifically, proteins can misfold and aggregate, forming amyloids, with intrinsically disordered proteins (IDPs) being particularly susceptible. Accumulation of these aggregates in long-lived cells can contribute to diseases like Alzheimer’s. Researchers propose using IDP aggregation as a biological clock for measuring health and age, although diagnostic tests are still in development. Continued research on IDP dynamics is crucial for advancements in this field.
“In practice, we are still far from having a routine diagnostic test, but understanding the mechanisms of IDP aggregation is key. Our goal is to encourage research on protein aggregates to better measure biological aging processes. With further research on IDP dynamics and technological advancements, we are hopeful for progress in reading a protein aggregation clock.”
