In this post I want to remind the readers about one fascinating theory of aging which was one of the first which explained Hompertz law.
Leo Szilard, the inventor of nuclear chain reaction, created his own theory of aging. Given the impact of the first Leo's invention, the second seems to be also important. Below is AI summary of it:
“Here is Szilard's 1959 theory laid out as a chain of theses, from premise to prediction.
1.Aging has a single elementary cause. The whole phenomenon reduces to one kind of discrete, random event, which Szilard calls an "aging hit."
2.A hit destroys a whole chromosome. Each aging hit inactivates an entire chromosome of a somatic cell, switching off every gene that chromosome carries. (This is the target borrowed from radiation biology.)
3.Hits fall at a constant rate. They arrive steadily across the whole of life, driven by background radiation and other DNA-damaging agents, so genetic damage accumulates linearly with age.
4.Redundancy buffers the damage. Because we are diploid, every chromosome has a second copy, so a single hit is normally survivable: the homolog still works.
5.There are two routes to inactivation: hits and faults. Beyond the random somatic hits collected during life, an individual may inherit "faults," recessive defects already present in a chromosome from birth.
6.A cell dies only on the second strike. A cell becomes nonfunctional when both copies of an essential chromosome are gone, either from two hits, or from one hit on a chromosome whose homolog carried a fault.
7.Health depends on a threshold of surviving cells. The organism stays well as long as the functional fraction stays above a critical value, which Szilard placed somewhere between one third and one twelfth of all cells.
8.Linear damage produces nonlinear mortality. Because the threshold hides all accumulating damage until it is suddenly exhausted, death rates stay low and flat through midlife, then climb steeply in old age.
9.Lifespan is set by two numbers. The model makes lifespan a calculable function of the number of essential chromosomes (targets) and the inherited fault load, so a heavier fault load means a shorter life.
10.The theory yields concrete predictions. Inbreeding, which doubles recessive faults, should shorten life; radiation-induced life-shortening should scale inversely with the square root of a species' chromosome count; mice and humans should lose roughly the same fraction of life to the same dose; and one can compute a species' average and maximum lifespan from the parameters.
Later the theory was revised:
“The model revision is the 2009 paper by Zetterberg and colleagues in Genetics, written for the 50th anniversary of his hypothesis. They took the part everyone agreed was biologically impossible, the assumption that one hit wipes out a whole chromosome, and rebuilt the math around single essential genes instead, with diploidy giving you two copies of each gene rather than two copies of each chromosome. Then they fit the revised model to actual human mortality data (Swedish death statistics). The gene-based version reproduced the shape of the human mortality curve better than Szilard's original chromosome-based one. Their verdict was the careful kind: many newer findings cast doubt on the specific features of the model, but it was the first serious attempt to posit accumulated genetic damage as a cause of senescence, and parts of it remain relevant once reassessed. So at the model level, fixing the gene assumption keeps it alive as a curve-fitter.
The much stronger test came in 2022, when Cagan and colleagues at the Sanger Institute actually measured it. They used whole-genome sequencing of intestinal crypts from 16 mammalian species and found that the rate of somatic mutation inversely scales with lifespan. The striking part is the threshold echo: the per-year mutation rate varied enormously and showed a strong inverse relationship with lifespan, with no other life-history trait coming close, yet despite roughly 30-fold variation in lifespan and 40,000-fold in body mass, the somatic mutation burden at the end of life varied only about 3-fold. In other words, animals seem to die at roughly the same accumulated mutation load regardless of how fast they get there, which is almost exactly Szilard's picture of a fixed damage threshold you exhaust on your own schedule. The authors concluded cautiously that somatic mutation rates appear evolutionarily constrained and may be a contributing factor in ageing.
So the honest scorecard: his specific mechanism (whole-chromosome hits) is dead, but the gene-level and genome-level reworkings vindicate the spirit of it. Damage does pile up roughly linearly, there does seem to be a tolerable budget, and crossing it does track with death. Note the word though: "a contributing factor." That is the same ceiling every theory hits. Even with gorgeous modern genomics behind it, the somatic mutation idea earns a seat at the table, not the head of it, which is exactly what the equalization picture predicts.”
In this post I want to remind the readers about one fascinating theory of aging which was one of the first which explained Hompertz law.
Leo Szilard, the inventor of nuclear chain reaction, created his own theory of aging. Given the impact of the first Leo's invention, the second seems to be also important. Below is AI summary of it:
“Here is Szilard's 1959 theory laid out as a chain of theses, from premise to prediction.
1. Aging has a single elementary cause. The whole phenomenon reduces to one kind of discrete, random event, which Szilard calls an "aging hit."
2. A hit destroys a whole chromosome. Each aging hit inactivates an entire chromosome of a somatic cell, switching off every gene that chromosome carries. (This is the target borrowed from radiation biology.)
3. Hits fall at a constant rate. They arrive steadily across the whole of life, driven by background radiation and other DNA-damaging agents, so genetic damage accumulates linearly with age.
4. Redundancy buffers the damage. Because we are diploid, every chromosome has a second copy, so a single hit is normally survivable: the homolog still works.
5. There are two routes to inactivation: hits and faults. Beyond the random somatic hits collected during life, an individual may inherit "faults," recessive defects already present in a chromosome from birth.
6. A cell dies only on the second strike. A cell becomes nonfunctional when both copies of an essential chromosome are gone, either from two hits, or from one hit on a chromosome whose homolog carried a fault.
7. Health depends on a threshold of surviving cells. The organism stays well as long as the functional fraction stays above a critical value, which Szilard placed somewhere between one third and one twelfth of all cells.
8. Linear damage produces nonlinear mortality. Because the threshold hides all accumulating damage until it is suddenly exhausted, death rates stay low and flat through midlife, then climb steeply in old age.
9. Lifespan is set by two numbers. The model makes lifespan a calculable function of the number of essential chromosomes (targets) and the inherited fault load, so a heavier fault load means a shorter life.
10. The theory yields concrete predictions. Inbreeding, which doubles recessive faults, should shorten life; radiation-induced life-shortening should scale inversely with the square root of a species' chromosome count; mice and humans should lose roughly the same fraction of life to the same dose; and one can compute a species' average and maximum lifespan from the parameters.
Later the theory was revised:
“The model revision is the 2009 paper by Zetterberg and colleagues in Genetics, written for the 50th anniversary of his hypothesis. They took the part everyone agreed was biologically impossible, the assumption that one hit wipes out a whole chromosome, and rebuilt the math around single essential genes instead, with diploidy giving you two copies of each gene rather than two copies of each chromosome. Then they fit the revised model to actual human mortality data (Swedish death statistics). The gene-based version reproduced the shape of the human mortality curve better than Szilard's original chromosome-based one. Their verdict was the careful kind: many newer findings cast doubt on the specific features of the model, but it was the first serious attempt to posit accumulated genetic damage as a cause of senescence, and parts of it remain relevant once reassessed. So at the model level, fixing the gene assumption keeps it alive as a curve-fitter.
The much stronger test came in 2022, when Cagan and colleagues at the Sanger Institute actually measured it. They used whole-genome sequencing of intestinal crypts from 16 mammalian species and found that the rate of somatic mutation inversely scales with lifespan. The striking part is the threshold echo: the per-year mutation rate varied enormously and showed a strong inverse relationship with lifespan, with no other life-history trait coming close, yet despite roughly 30-fold variation in lifespan and 40,000-fold in body mass, the somatic mutation burden at the end of life varied only about 3-fold. In other words, animals seem to die at roughly the same accumulated mutation load regardless of how fast they get there, which is almost exactly Szilard's picture of a fixed damage threshold you exhaust on your own schedule. The authors concluded cautiously that somatic mutation rates appear evolutionarily constrained and may be a contributing factor in ageing.
So the honest scorecard: his specific mechanism (whole-chromosome hits) is dead, but the gene-level and genome-level reworkings vindicate the spirit of it. Damage does pile up roughly linearly, there does seem to be a tolerable budget, and crossing it does track with death. Note the word though: "a contributing factor." That is the same ceiling every theory hits. Even with gorgeous modern genomics behind it, the somatic mutation idea earns a seat at the table, not the head of it, which is exactly what the equalization picture predicts.”