Cited by 36Spaceflight effects on biologyEpigenetics and DNA MethylationGenetics, Aging, and Longevity in Model Organisms

A Longitudinal Epigenetic Aging and Leukocyte Analysis of Simulated Space Travel: The Mars-500 Mission

Open access
Nwanaji-Enwerem, Jamaji C., Nwanaji-Enwerem, Uzoji, Van Der Laan, Lars, Galazka, Jonathan M., Redeker, Nancy S., Cardenas, Andres·2020·Cell Reports

Abstract

Astronauts undertaking long-duration space missions may be vulnerable to unique stressors that can impact human aging. Nevertheless, few studies have examined the relationship of mission duration with DNA-methylation-based biomarkers of aging in astronauts. Using data from the six participants of the Mars-500 mission, a high-fidelity 520-day ground simulation experiment, we tested relationships of mission duration with five longitudinally measured blood DNA-methylation-based metrics: DNAmGrimAge, DNAmPhenoAge, DNA-methylation-based estimator of telomere length (DNAmTL), mitotic divisions (epigenetic mitotic clock [epiTOC2]), and pace of aging (PoA). We provide evidence that, relative to baseline, mission duration was associated with significant decreases in epigenetic aging. However, only decreases in DNAmPhenoAge remained significant 7 days post-mission. We also observed significant changes in estimated proportions of plasmablasts, CD4T, CD8 naive, and natural killer (NK) cells. Only decreases in NK cells remained significant post-mission. If confirmed more broadly, these findings contribute insights to improve the understanding of the biological aging implications for individuals experiencing long-duration space travel.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.celrep.2020.108406

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Increase of ROS production due to exposure to space radiation and microgravity could be associated with premature aging and loss of biological fitness in astronauts.

    “The increase of ROS production due to the exposure to space radiation and microgravity could be associated with premature aging and loss of biological fitness in astronauts191,192.”

    From Key points for the development of antioxidant cocktails to prevent cellular stress and damage caused by reactive oxygen species (ROS) during manned space missions (2021) · cites this paper as [192]

    The Introduction identifies microgravity and cosmic radiation as spaceflight stressors that can affect aging. But the cited paper does not link those exposures to increased ROS production or loss of biological fitness; the Discussion notes that the Mars-500 simulation did not replicate either exposure and reports decreased epigenetic aging during the mission. No page numbers were provided in our copy. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 31

  1. Acelajado MC, Calhoun DA, and Oparil S (2013). Pathogenesis of Hypertension In Hypertension: A Companion to Braunwald’s Heart Disease, Chapter 2, Second Edition, Black HR and Elliott WJ, eds. (Philadelphia: W.B. Saunders), pp. 12– 26.
  2. Arpón A, Milagro FI, Santos JL, García-Granero M, Riezu-Boj J-I, and Martínez JA (2019). Interaction Among Sex, Aging, and Epigenetic Processes Concerning Visceral Fat, Insulin Resistance, and Dyslipidaemia. Front. Endocrinol. (Lausanne) 10, 496. 31379754 PMC6653993
  3. Belsky DW, Caspi A, Arseneault L, Baccarelli A, Corcoran DL, Gao X, Hannon E, Harrington HL, Rasmussen LJ, Houts R, (2020). Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm. eLife 9, e54870. 32367804 PMC7282814
  4. Bi J, and Wang X (2020). Molecular Regulation of NK Cell Maturation. Front. Immunol 11, 1945. 32849653 PMC7431948
  5. Bigley AB, Agha NH, Baker FL, Spielmann G, Kunz HE, Mylabathula PL, Rooney BV, Laughlin MS, Mehta SK, Pierson DL, (2019). NK cell function is impaired during long-duration spaceflight. J Appl Physiol (1985) 126, 842– 853. 30382809
  6. Cuttitta F, and Martínez A (2013). Adrenomedullin In Handbook of Biologically Active Peptides, Chapter 66, Second Edition, Kastin AJ, ed. (Boston: Academic Press), pp. 489– 493.
  7. Demontis GC, Germani MM, Caiani EG, Barravecchia I, Passino C, and Angeloni D (2017). Human Pathophysiological Adaptations to the Space Environment. Front. Physiol 8, 547. 28824446 PMC5539130
  8. Fortin J-P, Labbe A, Lemire M, Zanke BW, Hudson TJ, Fertig EJ, Greenwood CM, and Hansen KD (2014). Functional normalization of 450k methylation array data improves replication in large cancer studies. Genome Biol 15, 503. 25599564 PMC4283580
  9. Garrett-Bakelman FE, Darshi M, Green SJ, Gur RC, Lin L, Macias BR, McKenna MJ, Meydan C, Mishra T, Nasrini J, (2019). The NASA Twins Study: A multidimensional analysis of a year-long human spaceflight. Science 364, eaau8650. 30975860 PMC7580864
  10. Giovanetti A, Tortolici F, and Rufini S (2020). Why Do the Cosmic Rays Induce Aging? Front. Physiol 11, 955. 32903447 PMC7434975
  11. Horvath S (2013). DNA methylation age of human tissues and cell types. Genome Biol 14, R115. 24138928 PMC4015143
  12. Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, Wiencke JK, and Kelsey KT (2012). DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 13, 86. 22568884 PMC3532182
  13. Jones A, Pruessner JC, McMillan MR, Jones RW, Kowalik GT, Steeden JA, Williams B, Taylor AM, and Muthurangu V (2016). Physiological adaptations to chronic stress in healthy humans - why might the sexes have evolved different energy utilisation strategies? J. Physiol 594, 4297– 4307. 27027401 PMC4967762
  14. Kehler DS, Theou O, and Rockwood K (2019). Bed rest and accelerated aging in relation to the musculoskeletal and cardiovascular systems and frailty biomarkers: A review. Exp. Gerontol 124, 110643. 31255732
  15. Levine ME, Lu AT, Quach A, Chen BH, Assimes TL, Bandinelli S, Hou L, Baccarelli AA, Stewart JD, Li Y, (2018). An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY) 10, 573– 591. 29676998 PMC5940111
  16. Li Q, Mei Q, Huyan T, Xie L, Che S, Yang H, Zhang M, and Huang Q (2013). Effects of simulated microgravity on primary human NK cells. Astrobiology 13, 703– 714. 23919749 PMC3746215
  17. Liang F, Lv K, Wang Y, Yuan Y, Lu L, Feng Q, Jing X, Wang H, Liu C, Rayner S, (2019). Personalized Epigenome Remodeling Under Biochemical and Psychological Changes During Long-Term Isolation Environment. Front. Physiol 10, 932. 31417412 PMC6684777
  18. Lu AT, Seeboth A, Tsai P-C, Sun D, Quach A, Reiner AP, Kooperberg C, Ferrucci L, Hou L, Baccarelli AA, (2019a). DNA methylation-based estimator of telomere length. Aging (Albany NY) 11, 5895– 5923. 31422385 PMC6738410
  19. Lu AT, Quach A, Wilson JG, Reiner AP, Aviv A, Raj K, Hou L, Baccarelli AA, Li Y, Stewart JD, (2019b). DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY) 11, 303– 327. 30669119 PMC6366976
  20. Lulkiewicz M, Bajsert J, Kopczynski P, Barczak W, and Rubis B (2020). Telomere length: how the length makes a difference. Mol. Biol. Rep 47, 7181– 7188. 32876842 PMC7561533
  21. Mohler SR (1985). Age and space flight. Aviat. Space Environ. Med 56, 714– 717. 4026755
  22. Moore LD, Le T, and Fan G (2013). DNA methylation and its basic function. Neuropsychopharmacology 38, 23– 38. 22781841 PMC3521964
  23. Patel R, Zhang L, Desai A, Hoenerhoff MJ, Kennedy LH, Radivoyevitch T, Ban Y, Chen XS, Gerson SL, and Welford SM (2019). Mlh1 deficiency increases the risk of hematopoietic malignancy after simulated space radiation exposure. Leukemia 33, 1135– 1147. 30275527 PMC6443507
  24. Pinheiro J, Bates D, DebRoy S, and Sarkar D; R Core Team (2020). {nlme}: Linear and Nonlinear Mixed Effects Models. R Package Version 3, pp. 1– 117.
  25. Rao R, and Androulakis IP (2019). Allostatic adaptation and personalized physiological trade-offs in the circadian regulation of the HPA axis: A mathematical modeling approach. Sci. Rep 9, 11212. 31371802 PMC6671996
  26. Rezwan FI, Imboden M, Amaral AFS, Wielscher M, Jeong A, Triebner K, Real FG, Jarvelin M-R, Jarvis D, Probst-Hensch NM, and Holloway JW (2020). Association of adult lung function with accelerated biological aging. Aging (Albany NY) 12, 518– 542. 31926111 PMC6977706
  27. Tanskanen J, and Anttila T (2016). A Prospective Study of Social Isolation, Loneliness, and Mortality in Finland. Am. J. Public Health 106, 2042– 2048. 27631736 PMC5055788
  28. Teschendorff AE (2020). A comparison of epigenetic mitotic-like clocks for cancer risk prediction. Genome Med 12, 56. 32580750 PMC7315560
  29. Turner KJ, Vasu V, and Griffin DK (2019). Telomere Biology and Human Phenotype. Cells 8, 73. PMC6356320 30669451
  30. Vetter VM, Meyer A, Karbasiyan M, Steinhagen-Thiessen E, Hopfenmüller W, and Demuth I (2019). Epigenetic Clock and Relative Telomere Length Represent Largely Different Aspects of Aging in the Berlin Aging Study II (BASE-II). J. Gerontol. A Biol. Sci. Med. Sci 74, 27– 32. 30137208
  31. Welsh J, Bevelacqua JJ, Keshavarz M, Mortazavi SAR, and Mortazavi SMJ (2019). Is Telomere Length a Biomarker of Adaptive Response in Space? Curious Findings from NASA and Residents of High Background Radiation Areas. J. Biomed. Phys. Eng 9, 381– 388. 31341884 PMC6613149

Cited by

Sorted by citations

Authors
Nwanaji-Enwerem, J. C., Nwanaji-Enwerem, U., Van Der Laan, L., Galazka, J. M., Redeker, N. S., & Cardenas, A.
Affiliations
  • Yale University (US)
  • Ames Research Center (US)
Venue
Cell Reports
Publisher
Elsevier BV
Published
2020-12
Volume
33
Issue
10
Pages
108406
ISSN
2211-1247 (ISSN-L)
OpenAlex
W3107836811
Cited by
36
References
6
Citations by year
2026: 5 · 2025: 2 · 2024: 8 · 2023: 3 · 2022: 8 · 2021: 10
FWCI
3.16
Type
journal article
Language
en
Open access
Locations
  • Cell Reports (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion, cc-by-nc-nd)
  • eScholarship (California Digital Library) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
Funders
National Institutes of Health
Topics
  • Health Sciences › Medicine › Physiology › Spaceflight effects on biology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
Keywords
epigenetic aging, DNA methylation, simulated spaceflight, long-duration spaceflight, astronauts, pace of aging, leukocyte composition, natural killer cells, CD4+ T cells, naive CD8+ T cells, plasmablasts, mission duration
MeSH terms
Adult, Aging, Humans, Leukocyte Count, Leukocytes, Longitudinal Studies, Male, Space Flight, Time Factors, Weightlessness, Astronauts, DNA Methylation, Epigenesis, Genetic, Epigenomics

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review