Thanks for Per Andelius who has sent me this marvellous paper from Harvard University

It’s a forgotten truth that — more than oil, gold, or data — working-age adults are the most valuable resource of our time.

Scientists, nurses, thinkers, bakers, engineers and builders make up the backbone of our economies. The United States remains the world’s most powerful country, in great part, because it attracts the world’s most talented and productive people. It is also the third most populous country in the world, behind only India and China. And for as long as robots and artificial intelligence fail to take over our jobs and engineer a welcome era of abundance, the ceiling of the world’s economies will remain largely fixed to the health and number of their working-age adults.

The world is aging, and more births would be a partial solution to the emerging shortage of working-age adults worldwide. Yet they would be no silver bullet. In the short term, higher fertility rates worsen dependency ratios (newborns don’t work, and they temporarily remove their parents from the workforce); in the long term, they leave the sky-high socio-economic costs of aging unchanged. In a rational universe, healthy aging would be a top priority of governments, foundations, families, and investors worldwide. Yet many market failures and misaligned incentives stand in the way of private and public investments into extending healthy life.

The diseases of aging still begin to show up at nearly the same age as they did in 300 BC — and they follow a predictable trajectory throughout our lifespan.

Age is the primary risk factor for the diseases of aging. The median age of a cancer diagnosis is 66; the first heart attack, 65; and a dementia diagnosis, 83. Biological aging is also a neglected factor in global pandemics and even rare diseases like progeria or childhood cancers, where patients experience a form of accelerated aging. This explains why the value of investing in research on aging biology is high even compared to other excellent investments, since most severe conditions are downstream of biological aging. Eliminating all cancers, for instance, would add between 2 and 3 years to life expectancy. But since the median age of a cancer diagnosis is 66, the same patients would anyway soon be diagnosed with another manifestation of aging — like Parkinson’s, hypertension, severe illness from an otherwise mild infection, or a broken rib.

Scientific challenges help explain why we lack human-relevant results in aging biology. Yet they do not explain why, for instance, research on Alzheimer’s alone receives roughly 8 times more funding than research on the biology of aging, though we lack human-relevant results for safe Alzheimer’s drugs. Today, the United States spends a mere 0.54% of its National Institutes of Health research budget on the biology of aging. Due to a number of market failures and misaligned incentives, the vast majority of public and private funds go towards the treatment of late-stage conditions.

To start with, aging isn’t time.

Some species, like the Aldabra giant tortoise, are more likely to die the moment they are born than they are at age 90. Others, like the jellyfish Turritopsis Dohrnii, are often called “biologically immortal,” which means that without extrinsic mortality rates (e.g. predators or infectious diseases) they would not necessarily die. Mammals like the bowhead whale and fish like Greenland sharks routinely live for centuries without developing chronic illnesses like cancers or Alzheimer’s, while the health of naked-mole rats appears not to decline at all over time. Humans exhibit a similar ability for health maintenance until our twenties. Throughout our lives, our cells constantly undergo mutations and alterations. But as our natural capacity for repair begins to wane, damage begins to irreversibly accumulate. The same type of molecular damage that might have been easily tended to at a young age begins to build up during our thirties and forties. The diseases of aging — like cancers, heart diseases, dementias, and diabetes — most often appear after decades of misrepairs.

It’s well established that some hallmarks of aging can be accelerated by habits like smoking, or by events like pregnancy and infection. Less obvious is the fact that biological aging can be slowed down and reversed. Indeed, some hallmarks of aging are temporarily reversed every day with diet, mental health practices, and exercise. Yet there is a low ceiling to what can be achieved with lifestyle interventions for primates with our DNA. Just as two-hundred-year-old tortoises won’t suddenly start aging poorly after several days of little movement on the beach, or after binge-eating the carcasses of other tortoises (a habit they sometimes indulge in), humans can’t buy cancer-free, two-hundred-year lives by self-starving or walking at giant-tortoise speed.

Aging isn’t one thing, equally manifested in all species — and this explains why scientists  have such a hard time agreeing on just what it is.

We interviewed 102 scientists for this project. Some scientists understand aging as a “software design flaw”— a programmatic process that can be targeted epigenetically, by targeting gene expression rather than the genetic code itself. Others see it as a multifactorial set of processes whose causes demand more invasive solutions, like replacing tissues. Aging is a convenient word to describe the loss of function caused by a buildup in molecular damage over a species’ average lifespan. But different animals experience this loss differently (or not at all); different humans age at different paces (owing in part to different lifestyle choices, and in part to different genes); and different organs warrant different aging clocks. The ovaries, for instance, become geriatric some 40 years before the brain. For a discussion on why aging evolved in the first place, read the book, or peek here and here for two brief explanations.

What matters is that attempts at increasing health and lifespan have been successful in nearly every animal model studied so far. In a 1993 study, changing just one gene (daf-2, an insulin pathway humans share) in C. elegans worms doubled their lifespan. Changing one additional gene (rsks-1) resulted in a 500% lifespan increase, or the equivalent of a 400-year-old human in seemingly good health. In mammalian models, approaches like inhibiting mTOR activity or eliminating senescent cells often result in increased median survival rates. A short list of currently used therapeutics like rapamycin, metformin, GLP-1 agonists like Ozempic, and senolytics show signs of delaying multiple age-related diseases at once. Yet the risk-benefit profile of existing drugs remains unproven for most healthy humans, and the discovery of new and more effective drug targets should be prioritized.

You might think that in purely economic terms, human death is a net positive, since it mostly occurs to people dependent on costly social and medical care.

Yet the fact that over half of U.S. states recorded more deaths than births in 2022 can only be mourned. Healthy humans would impose fewer burdens on our medical and social systems. But even half-healthy humans are by far more productive (as well as happier and healthier) than dead ones; and more newborns are generally worth more to the economy, in the long run, than fewer.

The holy grail of aging science — and arguably of medicine — is to extend health at the same pace that it extends life. This would have substantial effects on the global economy, lowering the burden on caregivers, care receivers, and young populations who in part subsidize the medical and social care of older adults. Longer-lived and more productive humans would also lead to higher investments in human capital: more education, more spending, and more productive labor.

Economic growth is broadly driven by two factors: growth in the population, and growth in the amount each worker can produce within a given time. Labor productivity is the most direct way in which increases in healthspan impact the economy’s output. And in any century of recorded productivity so far, one pattern is clear: labor productivity rises in the first part of working life as experience and human capital accumulate, then declines later in life, as declines in physical and cognitive function overwhelm the increases in human capital. Improving the biology of aging implies slowing the rates of cognitive and physical decline later in life, which translates into slower decline in labor productivity.

People typically reach peak earnings as late as their experience has not been outpaced by cognitive decline.

This is shown by the graph below, which outlines how humans typically earn their highest income around age 55, followed by a steep decline caused primarily by the effects of biological aging. In the average lifetime, hourly earnings follow a near-perfect triangle shape, increasing as human capital goes up, then decreasing with age-related health decline. Improvements in the biology of aging are unique relative to other health investments in that they can extend one’s productive time at the apex of this triangle. This is what we mean when we discuss year shifts in productivity by age.

Higher fertility rates by age, by contrast, add to the number of triangles without meaningfully changing their shape. In other words, higher fertility by age creates more people without making existing ones more productive. But fertility rates would have little to do with biological aging if they did not also have the ability to at least marginally change the shape of the triangle – i.e., to increase productivity. In Future 2, we discuss how a better reproductive aging profile could lower the odds of disease and increase life expectancy.

Mortality rates by age can be counterintuitive. We all know that 60-year-olds are far likelier to die by any cause than 16-year-olds. What is counterintuitive is that life extension, even without a 1-1 improvement in healthspan, often increases GDP. The major way in which older adults become economically burdensome is through lower labor supply and increased medical and social costs. In our simulations, the underlying assumption is that older adults would be healthier and therefore more productive. This means that when discussing the biology of aging, shifts in mortality and productivity rates often go hand-in-hand. We assume no shifts in the age of retirement, and take into account only older adults who would voluntarily work past the age of 65, in good health. Interestingly, workers aged 65 and older are the fastest-growing labor group in the U.S. Today, many professionals (think physicians, teachers, politicians) refuse to retire despite their short cognitive healthspan. Others cannot afford to retire, and are forced to keep working even while suffering from age-related loss of function and dignity.