A Glimpse at the Future of Preventative Treatment for Aging
At some point, the various measures of biological age currently under development and assessment will coalesce into some form of consensus measurement, largely agreed upon, the objections to its use minimal and circumstantial. At that point, a great deal of effort will go into assessing established and new interventions that might decrease or slow the progression of that consensus measure of biological age. It will likely take some decades for the back and forth of real time validation of interventions to treat aging to progress thereafter, but things will certainly become a great deal more heated once the research community agrees on how to best measure biological age. Meanwhile, anyone can propose a measure and demonstrate that some interventions affect it, but as of now it remains unlikely that any great number of other people will agree that this is the right, useful, or in any way proven measure of aging.
Clinical healthy aging recommendations are disease-centric and reactive rather than focusing on holistic, organismal aging. In contrast, biological age (BA) estimation informs risk stratification by predicting all-cause mortality, however current BA clocks are not connected to underlying aging mechanisms, making it difficult to intervene clinically.
To generate actionable BA clocks, we developed and validated a principal component (PC)-based clinical aging clock (PCAge) that identifies signatures (PCs) associated with healthy and unhealthy aging trajectories. We observed that by intervening in PC-specific space, angiotensin-converting-enzyme inhibitors (ACE-Is) or angiotensin receptor blockers (ARBs) normalize several modifiable clinical parameters, involved in renal and cardiac function as well as inflammation. Proactive treatment with ACE-I/ARBs appeared to significantly reduce future mortality risk and prevented BA acceleration.
Finally, we developed a reduced BA clock (PC_mAge), based directly on PCAge, which has equivalent predictive power, but is optimized for immediate application in clinical practice. Our geroscience approach points to mechanisms associated with BA providing targets for preventative medicine to modulate biological processes that drive the shift from healthy functioning toward aging and the eventual manifestations of age-related diseases.
An aging score will probably need to be a combination of things.
1. Epigenetic Clock(s), Imagine a clock for every organ and/or sub-structure of the organ (a clock for a cell type in a certain organ, or a clock that measures the aging of a kidney duct rather than the whole kidney)
2. AI will can measure your age through photos ( photos taken in a controlled environment/ controlled lighting, ensemble averaging over 100s of photos)
3. Functional scores, (how physical active are you and why are you active)
4. Elastography ( Ultra-Sound/MRI imaging) + AI. ( How dense are you bones, how tight is the dermis around your face, how elastic are you valves)
5. Basic Measurements, blood sugar, blood pressure, Lipid panel etc.
6. Single cell Transcriptomics and/or Proteomics
Some of these items could be passively tested every day, other items maybe tested once a decade.
really still decades away? With all this AI and quantum computers and 40 - 50 year old tech billionaires?
Matt is right. This is why we also need more fundamental research and a new approach to a "theory of aging". Fedischev's lab toward that with concepts like tBA (thermodynamic Biological Age) and dFI (dynamic Frailty Index) might be a path, inspired by physics. In physics you can control what you measure.