Back

Epigenetic predictors of maximum lifespan and other life history traits in mammals

Li, C. Z.; Haghani, A.; Robeck, T. R.; Villar, D.; Lu, A. T.; Zhang, J.; Faulkes, C. G.; Vu, H.; Ablaeva, J.; Adams, D. M.; Ardehali, R.; Arneson, A.; Baker, C. S.; Belov, K.; Blumstein, D. T.; Bors, E. K.; Breeze, C. E.; Brooke, R. T.; Brown, J. L.; Caulton, A.; Cavin, J. M.; Chatzistamou, I.; Chen, H.; Chiavellini, P.; Choi, O.-W.; Clarke, S.; DeYoung, J.; Emmons, C. K.; Emmrich, S.; Fei, Z.; Ferguson, S. H.; Finno, C. J.; Flower, J. E.; Gaillard, J.-M.; Garde, E.; Gladyshev, V. N.; Goya, R. G.; Hanson, M. B.; Haulena, M.; Herrick, K.; Hogan, A. N.; Hogg, C. J.; Hore, T. A.; Jasinska, A. J.;

2021-05-18 evolutionary biology
10.1101/2021.05.16.444078 bioRxiv
Show abstract

Maximum lifespan of a species is the oldest that individuals can survive, reflecting the genetic limit of longevity in an ideal environment. Here we report methylation-based models that accurately predict maximum lifespan (r=0.89), gestational time (r=0.96), and age at sexual maturity (r=0.87), using cytosine methylation patterns collected from over 12,000 samples derived from 192 mammalian species. Our epigenetic maximum lifespan predictor corroborated the extended lifespan in growth hormone receptor knockout mice and rapamycin treated mice. Across dog breeds, epigenetic maximum lifespan correlates positively with breed lifespan but negatively with breed size. Lifespan-related cytosines are located in transcriptional regulatory regions, such as bivalent chromatin promoters and polycomb-repressed regions, which were hypomethylated in long-lived species. The epigenetic estimators of maximum lifespan and other life history traits will be useful for characterizing understudied species and for identifying interventions that extend lifespan.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 4%
26.4%
Similar papers in this journal
2
Nature
○ 645 papers in training set
Top 2%
7.8%
Similar papers in this journal
3
Science Advances
● 1243 papers in training set
Top 3%
6.7%
Similar papers in this journal
4
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 6%
6.7%
Similar papers in this journal
5
Nature Ecology & Evolution
131 papers in training set
Top 0.3%
6.7%
50% of probability mass above
6
eLife
● 5828 papers in training set
Top 22%
5.4%
7
Science
● 477 papers in training set
Top 2%
4.3%
8
Genome Biology
○ 637 papers in training set
Top 3%
4.3%
9
Nature Aging
○ 60 papers in training set
Top 0.4%
4.0%
10
Communications Biology
○ 993 papers in training set
Top 5%
3.4%
11
iScience
○ 1154 papers in training set
Top 18%
1.7%
12
npj Aging
○ 22 papers in training set
Top 0.2%
1.7%
13
Scientific Reports
○ 3612 papers in training set
Top 58%
1.4%
14
Cell Genomics
○ 172 papers in training set
Top 3%
1.4%
15
Nature Methods
○ 385 papers in training set
Top 5%
1.1%
16
Nature Genetics
○ 286 papers in training set
Top 4%
1.1%
17
Current Biology
○ 665 papers in training set
Top 8%
1.1%
18
Cell Reports
○ 1498 papers in training set
Top 25%
1.0%
19
Genome Research
● 468 papers in training set
Top 5%
1.0%
20
Aging Cell
○ 165 papers in training set
Top 2%
0.8%
21
National Science Review
◐ 21 papers in training set
Top 0.3%
0.8%
22
Cell Metabolism
○ 57 papers in training set
Top 2%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.