CoChat
Sign Up
Cited by 21

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Effect of metformin on the epigenetic age of peripheral blood in patients with diabetes mellitus

Li, Man, Bao, Litao, Zhu, Ping, Wang, Shuxia·2022·Frontiers in Genetics
DOI 10.3389/fgene.2022.955835PMC PMC9548538
Open this paper in CoChat — free account

Abstract

Background: Metformin has been proven to have an antiaging effect. However, studies on how metformin affects global epigenetic regulation and its effect on the epigenetic clock in diabetes mellitus (DM) patients are limited. This study aims to investigate the impact of metformin on the epigenetic age in subjects with type 2 DM. Results: We collected the peripheral blood of the metformin group and the no-metformin group of the 32 DM patients. Three previously established epigenetic clocks (Hannum, Horvath, and DNAmPhenoAge) were used to estimate the epigenetic age acceleration of the two groups. We defined biological age acceleration for each group by comparing the estimated biological age with the chronological age. Results were presented as follows: 1) all three epigenetic clocks were strongly correlated with chronological age. 2) We found a strong association between metformin intake and slower epigenetic aging by Horvath’s clock and Hannum’s clock. Conclusions: Here, we found an association between metformin intake and slower epigenetic aging.

Overview

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 · 10.3389/fgene.2022.955835

Cites

13 of 13 references verified0 citation errors · 0 not checkable

Statistics

Figures

FIGURE 1 Correlation between epigenetic age and chronological age.
FIGURE 1 Correlation between epigenetic age and chronological age.CC BY · PubMed Central
FIGURE 2 Epigenetic Age Acceleration of the two groups by the three epigenetic clocks.
FIGURE 2 Epigenetic Age Acceleration of the two groups by the three epigenetic clocks.CC BY · PubMed Central
FIGURE 3 Adjusted hazard ratios [and 95% confidence intervals (CI)] for the epigenetic age acceleration.
FIGURE 3 Adjusted hazard ratios [and 95% confidence intervals (CI)] for the epigenetic age acceleration.CC BY · PubMed Central

Verification

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?

Self-check

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

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

Citations

Cites

Show all 13 references

Research works printed but not linked: 40

  1. Admasu, 2018, Drug synergy slows aging and improves healthspan through IGF and SREBP lipid signaling, Dev. Cell., 47, 67, 10.1016/j.devcel.2018.09.001 · DOI
  2. Banerjee, 2016, Metformin mediated reversal of epithelial to mesenchymal transition is triggered by epigenetic changes in E-cadherin promoter, J. Mol. Med., 94, 1397, 10.1007/s00109-016-1455-7 · DOI
  3. Bell, 2012, Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population, PLoS Genet., 8, e1002629, 10.1371/journal.pgen.1002629 · DOI
  4. Benayoun, 2015, Epigenetic regulation of ageing: Linking environmental inputs to genomic stability, Nat. Rev. Mol. Cell. Biol., 16, 593, 10.1038/nrm4048 · DOI · Paper page
  5. Cabreiro, 2013, Metformin retards aging in C. elegans by altering microbial folate and methionine metabolism, Cell., 153, 228, 10.1016/j.cell.2013.02.035 · DOI · Paper page
  6. Daniel, 2018, T cell epigenetic remodeling and accelerated epigenetic aging are linked to long-term immune alterations in childhood cancer survivors, Clin. Epigenetics, 10, 138, 10.1186/s13148-018-0561-5 · DOI
  7. Dhahbi, 2005, Identification of potential caloric restriction mimetics by microarray profiling, Physiol. Genomics, 23, 343, 10.1152/physiolgenomics.00069.2005 · DOI · Paper page
  8. Dziewulska, 2020, SCD1 regulates the AMPK/SIRT1 pathway and histone acetylation through changes in adenine nucleotide metabolism in skeletal muscle, J. Cell. Physiol., 235, 1129, 10.1002/jcp.29026 · DOI
  9. El Khoury, 2019, Systematic underestimation of the epigenetic clock and age acceleration in older subjects, Genome Biol., 20, 283, 10.1186/s13059-019-1810-4 · DOI
  10. Elbere, 2018, Significantly altered peripheral blood cell DNA methylation profile as a result of immediate effect of metformin use in healthy individuals, Clin. Epigenetics, 10, 156, 10.1186/s13148-018-0593-x · DOI
  11. Forslund, 2015, Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota, Nature, 528, 262, 10.1038/nature15766 · DOI · Paper page
  12. García-Calzón, 2017, Diabetes medication associates with DNA methylation of metformin transporter genes in the human liver, Clin. Epigenetics, 9, 102, 10.1186/s13148-017-0400-0 · DOI
  13. Gibson, 2019, A meta-analysis of genome-wide association studies of epigenetic age acceleration, PLoS Genet., 15, e1008104, 10.1371/journal.pgen.1008104 · DOI
  14. Gwinn, 2008, AMPK phosphorylation of raptor mediates a metabolic checkpoint, Mol. Cell., 30, 214, 10.1016/j.molcel.2008.03.003 · DOI · Paper page
  15. Hannum, 2013, Genome-wide methylation profiles reveal quantitative views of human aging rates, Mol. Cell., 49, 359, 10.1016/j.molcel.2012.10.016 · DOI · Paper page
  16. Horvath, 2013, DNA methylation age of human tissues and cell types, Genome Biol., 14, R115, 10.1186/gb-2013-14-10-r115 · DOI · Paper page
  17. Horvath, 2015, Accelerated epigenetic aging in Down syndrome, Aging Cell., 14, 491, 10.1111/acel.12325 · DOI
  18. Inoki, 2003, TSC2 mediates cellular energy response to control cell growth and survival, Cell., 115, 577, 10.1016/s0092-8674(03)00929-2 · DOI · Paper page
  19. Inzucchi, 2002, Oral antihyperglycemic therapy for type 2 diabetes: Scientific review, JAMA, 287, 360, 10.1001/jama.287.3.360 · DOI
  20. Jylhävä, 2017, Biological age predictors, EBioMedicine, 21, 29, 10.1016/j.ebiom.2017.03.046 · DOI · Paper page
  21. Karnewar, 2018, Metformin regulates mitochondrial biogenesis and senescence through AMPK mediated H3K79 methylation: Relevance in age-associated vascular dysfunction, Biochim. Biophys. Acta. Mol. Basis Dis., 1864, 1115, 10.1016/j.bbadis.2018.01.018 · DOI · Paper page
  22. Kresovich, 2019, Methylation-based biological age and breast cancer risk, J. Natl. Cancer Inst., 111, 1051, 10.1093/jnci/djz020 · DOI
  23. Lee, 2016, Forensic DNA methylation profiling from evidence material for investigative leads, BMB Rep., 49, 359, 10.5483/bmbrep.2016.49.7.070 · DOI
  24. Levine, 2018, An epigenetic biomarker of aging for lifespan and healthspan, Aging, 10, 573, 10.18632/aging.101414 · DOI · Paper page
  25. Madeo, 2019, Caloric restriction mimetics against age-associated disease: Targets, mechanisms, and therapeutic potential, Cell. Metab., 29, 592, 10.1016/j.cmet.2019.01.018 · DOI · Paper page
  26. Maegawa, 2010, Widespread and tissue specific age-related DNA methylation changes in mice, Genome Res., 20, 332, 10.1101/gr.096826.109 · DOI · Paper page
  27. Marioni, 2015, DNA methylation age of blood predicts all-cause mortality in later life, Genome Biol., 16, 25, 10.1186/s13059-015-0584-6 · DOI · Paper page
  28. Marioni, 2015, The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936, Int. J. Epidemiol., 44, 1388, 10.1093/ije/dyu277 · DOI
  29. Na, 2013, Mechanism of metformin: Inhibition of DNA damage and proliferative activity in Drosophila midgut stem cell, Mech. Ageing Dev., 134, 381, 10.1016/j.mad.2013.07.003 · DOI
  30. Nguyen, 2019, Metformin inhibits lithocholic acid-induced interleukin 8 upregulation in colorectal cancer cells by suppressing ROS production and NF-kB activity, Sci. Rep., 9, 2003, 10.1038/s41598-019-38778-2 · DOI
  31. Nwanaji-Enwerem, 2018, Multi-tissue DNA methylation age: Molecular relationships and perspectives for advancing biomarker utility, Ageing Res. Rev., 45, 15, 10.1016/j.arr.2018.04.005 · DOI
  32. Ong, 2018, Role of Sirtuin1-p53 regulatory axis in aging, cancer and cellular reprogramming, Ageing Res. Rev., 43, 64, 10.1016/j.arr.2018.02.004 · DOI
  33. Pernicova, 2014, Metformin-mode of action and clinical implications for diabetes and cancer, Nat. Rev. Endocrinol., 10, 143, 10.1038/nrendo.2013.256 · DOI
  34. Rakyan, 2010, Human aging-associated DNA hypermethylation occurs preferentially at bivalent chromatin domains, Genome Res., 20, 434, 10.1101/gr.103101.109 · DOI
  35. Sae-Lee, 2018, Dietary intervention modifies DNA methylation age assessed by the epigenetic clock, Mol. Nutr. Food Res., 62, e1800092, 10.1002/mnfr.201800092 · DOI · Paper page
  36. Vazirpanah, 2019, mTOR inhibition by metformin impacts monosodium urate crystal-induced inflammation and cell death in gout: a prelude to a new add-on therapy?, Ann. Rheum. Dis., 78, 663, 10.1136/annrheumdis-2018-214656 · DOI
  37. Wagner, 2017, Epigenetic aging clocks in mice and men, Genome Biol., 18, 107, 10.1186/s13059-017-1245-8 · DOI
  38. Yang, 2020, The influence of metformin on IGF-1 levels in humans: A systematic review and meta-analysis, Pharmacol. Res., 151, 104588, 10.1016/j.phrs.2019.104588 · DOI · Paper page
  39. Zhang, 2016, Metformin improves defective hematopoiesis and delays tumor formation in Fanconi anemia mice, Blood, 128, 2774, 10.1182/blood-2015-11-683490 · DOI
  40. Zhong, 2017, Metformin alters DNA methylation genome-wide via the H19/SAHH axis, Oncogene, 36, 2345, 10.1038/onc.2016.391 · DOI · Paper page

Cited by

Sorted by citations

Metadata

Authors
Li, M., Bao, L., Zhu, P., & Wang, S.
Venue
Frontiers in Genetics
Publisher
Frontiers Media SA
Published
2022-09-26
Volume
13
ISSN
1664-8021
DOI
10.3389/fgene.2022.955835
PMC
PMC9548538
Cited by
21
References
13
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
National Key Research and Development Program of China

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