Back

Counting Cells by Age Tells Us About How, and Why, and When, We Grow, and Become Old and Ill

Citi, L.; Su, J.; Huang, L.; Michaelson, J. S.

2023-01-07 geriatric medicine
10.1101/2023.01.05.23284244 medRxiv
Show abstract

Growth and aging are fundamental features of animal life. The march from fertilization to oblivion comes in enormous variety: days and hundreds of cells for nematodes, decades and trillions of cells for humans.1-4 Since Verhulst (18385) proposed the Logistic Equation - exponential growth with a countervailing linear decline in rate - biologists have searched for ever better density-dependent growth equations,6-12 none of which accurately capture the relationship between size and time for real animals.13-15 Furthermore, while growth and aging run in parallel, whether the relationship is causal has yet to be determined. Similarly unknown has been the reason behind the exponential Force of Mortality, described by Gompertz in 1825 for all-cause mortality16 and reported by Levin et al. in 2020 for COVID-19.17 Here we report that examination in units of numbers of cells, N, Cellular Phylodynamic Analysis,6 reveals that growth, lifespan, and mortality, are linked to the reduction in the fraction of cells dividing, occurring by a simple expression, the Universal Mitotic Fraction Equation. Lifespan is correlated with an age when fewer than one-in-a-thousand cells are dividing, quantifying the long-appreciated mechanism of aging, the failure of cells to be rejuvenated by dilution with new materials made and DNA repaired at mitosis.29-31 These observations provide practical mathematical tools for comprehending and managing the challenges of growth and aging, for such tasks as deciphering COVID-19 lethality and its amelioration by vaccination.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
npj Aging
22 papers in training set
Top 0.1%
18.8%
2
Scientific Reports
3612 papers in training set
Top 4%
10.8%
3
Aging Cell
165 papers in training set
Top 0.5%
8.0%
4
eLife
5828 papers in training set
Top 23%
5.2%
5
Aging
75 papers in training set
Top 0.3%
4.9%
6
Journal of Theoretical Biology
162 papers in training set
Top 0.7%
4.4%
50% of probability mass above
7
Frontiers in Public Health
148 papers in training set
Top 2%
2.7%
8
PNAS Nexus
159 papers in training set
Top 0.4%
2.7%
9
PLOS ONE
5266 papers in training set
Top 41%
2.7%
10
Biology Methods and Protocols
61 papers in training set
Top 0.4%
2.7%
11
Journal of the American Geriatrics Society
12 papers in training set
Top 0.1%
2.4%
12
Cancers
213 papers in training set
Top 2%
2.4%
13
GeroScience
109 papers in training set
Top 1%
1.9%
14
Journal of The Royal Society Interface
235 papers in training set
Top 2%
1.9%
15
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 27%
1.8%
16
Nature Medicine
125 papers in training set
Top 2%
1.7%
17
Advanced Science
286 papers in training set
Top 6%
1.4%
18
iScience
1154 papers in training set
Top 24%
1.1%
19
Frontiers in Physiology
106 papers in training set
Top 2%
1.1%
20
The Journals of Gerontology: Series A
29 papers in training set
Top 0.4%
1.1%
21
PLOS Computational Biology
1863 papers in training set
Top 17%
1.1%
22
Nature Communications
5641 papers in training set
Top 56%
0.9%
23
Canadian Medical Association Journal
15 papers in training set
Top 0.2%
0.6%
24
Experimental Gerontology
12 papers in training set
Top 0.4%
0.6%