Chapter 192
The Path Forward — 4
It’s the era of digital biology. As Jensen Huang, CEO of Nvidia, put it: “For the first time in human history, biology has the opportunity to be engineering, not science.” I would say both. How we can engineer healthy aging—prevention of age-related diseases—is an outgrowth of accelerated life science output in recent years. The exponential growth we have seen with generative AI will be paralleled by the same in digital biology (fig. 13.2). Evolutionary Scale, formed by scientists from Meta, created a protein language model with 2.7 billion protein sequences, structure, and functions; we’re on the path to making biology programmable. The dizzying pace of innovations that span the gamut from genome editing, controlling our (tolerogenic) immune response, identifying critical biomarkers for tracking early cancer and neurodegenerative diseases, engineering cells, and delivering biologics via mRNA and nanoparticles is all taking hold at one time. Collectively, we are witnessing an incomparable time in life science.
The target to prevent or markedly delay age-related diseases that I find most intriguing, as will probably be obvious by now, is our immune system. There’s a pervasive belief that we’re either immunocompetent or immunocompromised. That’s wrong! We desperately need a way to systematically assess our immune system. By conducting an “immunome,” we will be able to predict a person’s response to infections, vulnerability to cancer or its spread, and propensity for developing cardiovascular and neurodegenerative diseases. Today, we do little to characterize a person’s immune system’s status beyond a conventional blood test. Although this tells us the number of white blood cells (neutrophils) and lymphocytes, it is grossly insufficient. Even the neutrophil to lymphocyte ratio has some negative prognostic information for lifespan when high, but we ignore that. A decade ago, we saw how our exposure to more than one thousand virus strains and timing could be accurately detected through antibodies from a drop of blood for the low cost of $25. That would tell us about our exposure to cytomegalovirus, a key exposure that tracks with older immunotypes, associated with an aging immune system. But this test is still not clinically available.
Figure 13.2. Exponential curves of transformative impact over time for generative AI and digital biology
What if we could periodically grade an individual’s immune system? One of the most provocative studies in this regard was published several years ago, tracking 135 healthy individuals over nine years, each year assessing a participant’s immune system for their immune cell profile (T, B, NK, and subtypes), gene expression, and cytokine production. One finding was the decline in CD8+ cytotoxic T cells with age, which was highly variable from one individual to another (fig. 13.3). The immunologic age clock from this study was superior to epigenetic clocks for predicting mortality.