Here are some of the very biggest questions in aging science as I see it:
- What is aging? How do you measure aging on shorter timescales than death?
- What drives aging? How? Is the epigenome the primary driver?
- What slows aging? How? Which of the various possible interventions work? What combinations of these interventions is optimal?
- What reverses aging? How? Does cellular reprogramming reverse aging?
- What should humans do to live longer and healthier? How personalized do interventions need to be? How do I know if I'm doing the right things for my aging?
- How can we develop a simpler model of aging to answer the above questions? While the particulars are different, almost every organism ages. Mammals are so large and complex, and we still don't understand many fundamentals. Could we start with C. elegans with ~1,000 somatic cells vs. ~37 trillion cells for humans?
What data could illuminate our understanding of these fundamental questions?
Here is a data pipeline that would be very interesting:
- Start with a tiny, well-understood organism like C. elegans.
- Do whole organism epigenomics, spatial transcriptomics, genomics and imaging across the full lifespan. Maybe 10-100 unique time points so you can see changes over time? This is a tremendous amount of data.
- Identify spatio-temporal aging patterns.
- Create a "biological clock" based on all this data.
- Pick candidates for "drivers" of aging, e.g. epigenomic remodeling, and then intervene/perturb to return towards "youthful" state.
- Elucidate drivers of aging and methods for slowing and reversing aging.
- Once this works, expand to larger and larger organisms.
I'm sure others have considered this kind of approach. Why aren't we doing it today?