Using Supercentenarian Data to Estimate Future Increases in Maximum Human Life Span
In today's research materials, scientists attempt to model future increases in maximum human longevity based on past data for supercentenarians, people aged 110 and older. This is an interesting exercise, but I think that all of the results have to be taken with a sizable grain of salt. Firstly, the data for extreme human outliers in longevity isn't great. A lot of it is of poor quality, and the portions that are well maintained do not include a sizable number of people. There are few survivors to such exceptional ages, which makes it hard to call any analysis of that data truly robust. This is a problem that afflicts all similar work on survival and longevity in the oldest individuals.
Secondly, and more importantly, extrapolating past trends in human longevity will tell us next to nothing about what will happen in the years ahead. Past trends in human life expectancy in late life are near entirely incidental, as none of the widely available approaches to treating age-related disease actually target the underlying causes of aging in any meaningful way. That is changing. There is now a longevity industry working on numerous forms of therapy that will slow or reverse the cell and tissue damage that causes aging. The use of senolytics to clear senescent cells will become widespread in the years to come. The old people of the 2030s will have a greatly reduced chronic inflammation and disruption of tissue function in comparison to those of today or past decades. That sort of night and day difference isn't accounted for by extrapolation of trends.
How long can a person live? The 21st century may see a record-breaker
The number of people who live past the age of 100 has been on the rise for decades, up to nearly half a million people worldwide. There are, however, far fewer "supercentenarians," people who live to age 110 or even longer. Such extreme longevity likely will continue to rise slowly by the end of this century, and estimates show that a lifespan of 125 years, or even 130 years, is possible. With ongoing research into aging, the prospects of future medical and scientific discoveries and the relatively small number of people to have verifiably reached age 110 or older, experts have debated the possible limits to what is referred to as the maximum reported age at death. While some scientists argue that disease and basic cell deterioration lead to a natural limit on human lifespan, others maintain there is no cap, as evidenced by record-breaking supercentenarians.
To calculate the probability of living past 110 - and to what age - researchers turned to the most recent iteration of the International Database on Longevity. That database tracks supercentenarians from 10 European countries, plus Canada, Japan and the United States. Using a Bayesian approach to estimate probability, the team created projections for the maximum reported age at death in all 13 countries from 2020 through 2100. Among their findings: there is near 100% probability that the current record of maximum reported age at death of 122 years will be broken; the probability remains strong of a person living longer, to 124 years old (99% probability) and even to 127 years old (68% probability); an even longer lifespan is possible but much less likely, with a 13% probability of someone living to age 130; it is "extremely unlikely" that someone would live to 135 in this century.
Probabilistic forecasting of maximum human lifespan by 2100 using Bayesian population projections
We use the exponential survival model for supercentenarians (people over age 110) but extend the forecasting window, quantify population uncertainty using Bayesian population projections, and incorporate the most recent data from the International Database on Longevity (IDL) to obtain unconditional estimates of the distribution of maximum reported age at death (MRAD) this century in a fully Bayesian analysis. Based on this analysis, there is a greater than 99% probability that the current MRAD of 122 will be broken by 2100. We estimate the probabilities that a person lives to at least age 126, 128, or 130 this century, as 89%, 44%, and 13%, respectively.
https://www.quantamagazine.org/social-mitochondria-whispering-between-cells-influence-health-20210706/
interesting article about work of an aging researcher about "social" Mitochondria.
I agree. Future widespread application of senolytics and epigenetic reprogramming to the elderly should have sizable impacts on the ability of the oldest in good health to live longer. It is interesting that the malady that at present actually ends the lives of the super-centigenerians seems to be amyloid buildup. That may go away in the oldest individuals who have received senolytics and epigenetic reprogramming.
But if not, the FDA has just given questionable approval to Aduhelm, a drug that suppresses amyloid buildup (but probably won't work for full blown Alzheimers). Maybe Aduhelm should be given off-label to super-centigenerians who do NOT show any symptoms of Alzheimers.
@John G Cramer
Maybe iron chelation would help amyloid. Perhaps some of the benefit of rapamycin is from the chelation that comes with its use.
"The accumulation of neurofibrillary tangles (NFTs), which is composed of abnormally hyperphosphorylated tau aggregates, is the classic neuropathology associated with cognitive dysfunction in tauopathies such as Alzheimer's disease (AD). However, there is an emerging theory suggesting that dysregulation in cerebral iron may contribute to NFT formation. Iron is speculated to bind to tau and induce conformational changes of the protein, potentially leading to subsequent aggregation and cognitive decline. Deferiprone (DFP) is a clinically available iron chelator, which has demonstrated potential therapeutic advantages of chelating iron in neurodegenerative disorders, and is currently in clinical trials for AD. However, its effect on tau pathology remains unclear. Here, we report the effects of short-term DFP treatment (4 weeks, 100 mg/kg/daily, via oral gavage) in a mixed-gender cohort of the rTg(tauP301L)4510 mouse model of tauopathy. Our results revealed that DFP improved Y-maze and open field performance, accompanied by a 28% decrease in brain iron levels,"
https://pubmed.ncbi.nlm.nih.gov/33410108/
When do you think we will be able to cure all types of cancer?
@Alex
You asked about general cancer cures.
Essentially all cancer cells attempt to express the proteins p16 and p53, while healthy cell do not. That fact can be used. I am a minor investor in OncoSenX (https://www.oncosenx.com/), a biotech startup that is testing a liposome/plasmid treatment that, when a p16 or p53 transcription factor docks on the plasmid to initiate RNA transcription for expressing the proteins, it instead transcribes the RNA for a "suicide protein" that kills the cell.
So far the testing of this treatment has been done only on cancer-bearing mice, but the results were excellent. The hyper-expensive cost of human testing and the draconian FDA rules stand in the way of testing this as a general cure for human cancer. However, fund-raising has been successful, and human trials are about to begin.
If I had cancer of any kind, I would try to get some of this stuff in my arm.
@John G. Cramer
Thank you very much! The solution of OncoSensX is very interesting, I hope it will produce the expected results!
Nice thing about the regulations and barriers is that everyone has to face them. And it is priced into the cost of the drugs, including the risks and return on capital.
And say they get to market with the drug, it would be 10-15 years before a competitor got through the same regulations and barriers, if the competitors started work that day.
@John G: One of the reasons regulatory is such a minefield is simply this:
Our models suck.
If our models were predictive of clinical outcomes, regulatory barriers would fall away.
If the semiconductor industry (my original profession) had to deal with utterly miserable models the way biotech does right now, we'd still be using 386-based PCs and lugging around suitcase phones.
We urgently need *predictive* preclinical models, and the need is amplified for longevity therapeutics in which the clinical indication is in the future.
I'm hopeful that 3D-printed and organoid models will help, but some of the best models for aging research could come from unusable organ donor tissues. Sadly, there's plenty of aged tissue available from people dying of aging every day.
Cheers,
Robert