DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function

  1. Matías García, Pamela Raquel ORCID logo
  2. Ward-Caviness, Cavin K.
  3. Raffield, Laura ORCID logo
  4. Gao, Xu ORCID logo
  5. Zhang, Yan ORCID logo
  6. Wilson, Rory
  7. Gào, Xīn
  8. Nano, Jana
  9. Bostom, Andrew
  10. Colicino, Elena
  11. Correa, Adolfo
  12. Coull, Brent
  13. Eaton, Charles
  14. Hou, Lifang
  15. Just, Allan C.
  16. Kunze, Sonja
  17. Lange, Leslie
  18. Lange, Ethan
  19. Lin, Xihong
  20. Liu, Simin
  21. Nwanaji-Enwerem, Jamaji C.
  22. Reiner, Alex
  23. Shen, Jincheng
  24. Schöttker, Ben
  25. Vokonas, Pantel
  26. Zheng, Yinan
  27. Young, Bessie
  28. Schwartz, Joel
  29. Horvath, Steve
  30. Lu, Ake
  31. Whitsel, Eric A.
  32. Koenig, Wolfgang
  33. Adamski, Jerzy ORCID logo
  34. Winkelmann, Juliane
  35. Brenner, Hermann ORCID logo
  36. Baccarelli, Andrea A.
  37. Gieger, Christian
  38. Peters, Annette
  39. Franceschini, Nora ORCID logo
  40. Waldenberger, Melanie ORCID logo

Download
s13148-021-01082-w.pdf 1,85MB
WeightNameValue
1000 Titel
  • DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function
1000 Autor/in
  1. Matías García, Pamela Raquel |
  2. Ward-Caviness, Cavin K. |
  3. Raffield, Laura |
  4. Gao, Xu |
  5. Zhang, Yan |
  6. Wilson, Rory |
  7. Gào, Xīn |
  8. Nano, Jana |
  9. Bostom, Andrew |
  10. Colicino, Elena |
  11. Correa, Adolfo |
  12. Coull, Brent |
  13. Eaton, Charles |
  14. Hou, Lifang |
  15. Just, Allan C. |
  16. Kunze, Sonja |
  17. Lange, Leslie |
  18. Lange, Ethan |
  19. Lin, Xihong |
  20. Liu, Simin |
  21. Nwanaji-Enwerem, Jamaji C. |
  22. Reiner, Alex |
  23. Shen, Jincheng |
  24. Schöttker, Ben |
  25. Vokonas, Pantel |
  26. Zheng, Yinan |
  27. Young, Bessie |
  28. Schwartz, Joel |
  29. Horvath, Steve |
  30. Lu, Ake |
  31. Whitsel, Eric A. |
  32. Koenig, Wolfgang |
  33. Adamski, Jerzy |
  34. Winkelmann, Juliane |
  35. Brenner, Hermann |
  36. Baccarelli, Andrea A. |
  37. Gieger, Christian |
  38. Peters, Annette |
  39. Franceschini, Nora |
  40. Waldenberger, Melanie |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-06-02
1000 Erschienen in
1000 Quellenangabe
  • 13(1):121
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s13148-021-01082-w |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170969/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Background!#!The difference between an individual's chronological and DNA methylation predicted age (DNAmAge), termed DNAmAge acceleration (DNAmAA), can capture life-long environmental exposures and age-related physiological changes reflected in methylation status. Several studies have linked DNAmAA to morbidity and mortality, yet its relationship with kidney function has not been assessed. We evaluated the associations between seven DNAm aging and lifespan predictors (as well as GrimAge components) and five kidney traits (estimated glomerular filtration rate [eGFR], urine albumin-to-creatinine ratio [uACR], serum urate, microalbuminuria and chronic kidney disease [CKD]) in up to 9688 European, African American and Hispanic/Latino individuals from seven population-based studies.!##!Results!#!We identified 23 significant associations in our large trans-ethnic meta-analysis (p < 1.43E-03 and consistent direction of effect across studies). Age acceleration measured by the Extrinsic and PhenoAge estimators, as well as Zhang's 10-CpG epigenetic mortality risk score (MRS), were associated with all parameters of poor kidney health (lower eGFR, prevalent CKD, higher uACR, microalbuminuria and higher serum urate). Six of these associations were independently observed in European and African American populations. MRS in particular was consistently associated with eGFR (β =  - 0.12, 95% CI = [- 0.16, - 0.08] change in log-transformed eGFR per unit increase in MRS, p = 4.39E-08), prevalent CKD (odds ratio (OR) = 1.78 [1.47, 2.16], p = 2.71E-09) and higher serum urate levels (β = 0.12 [0.07, 0.16], p = 2.08E-06). The 'first-generation' clocks (Hannum, Horvath) and GrimAge showed different patterns of association with the kidney traits. Three of the DNAm-estimated components of GrimAge, namely adrenomedullin, plasminogen-activation inhibition 1 and pack years, were positively associated with higher uACR, serum urate and microalbuminuria.!##!Conclusion!#!DNAmAge acceleration and DNAm mortality predictors estimated in whole blood were associated with multiple kidney traits, including eGFR and CKD, in this multi-ethnic study. Epigenetic biomarkers which reflect the systemic effects of age-related mechanisms such as immunosenescence, inflammaging and oxidative stress may have important mechanistic or prognostic roles in kidney disease. Our study highlights new findings linking kidney disease to biological aging, and opportunities warranting future investigation into DNA methylation biomarkers for prognostic or risk stratification in kidney disease.
1000 Sacherschließung
lokal Aging, Premature/epidemiology [MeSH]
lokal DNA Methylation/genetics [MeSH]
lokal DNA Methylation/physiology [MeSH]
lokal Female [MeSH]
lokal Glomerular filtration rate
lokal Aged [MeSH]
lokal Mortality/trends [MeSH]
lokal Humans [MeSH]
lokal UACR
lokal Aging and Development Epigenetics
lokal Middle Aged [MeSH]
lokal Epigenetic age acceleration
lokal Aging
lokal Kidney function
lokal Male [MeSH]
lokal Serum urate
lokal Renal Insufficiency/blood [MeSH]
lokal Research
lokal Renal Insufficiency/mortality [MeSH]
lokal Aging, Premature/mortality [MeSH]
lokal Renal Insufficiency/etiology [MeSH]
lokal DNAm age
lokal Aging, Premature/genetics [MeSH]
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-3906-5405|https://frl.publisso.de/adhoc/uri/V2FyZC1DYXZpbmVzcywgQ2F2aW4gSy4=|https://orcid.org/0000-0002-7892-193X|https://orcid.org/0000-0001-6506-6084|https://orcid.org/0000-0001-9913-6490|https://frl.publisso.de/adhoc/uri/V2lsc29uLCBSb3J5|https://frl.publisso.de/adhoc/uri/R8OgbywgWMSrbg==|https://frl.publisso.de/adhoc/uri/TmFubywgSmFuYQ==|https://frl.publisso.de/adhoc/uri/Qm9zdG9tLCBBbmRyZXc=|https://frl.publisso.de/adhoc/uri/Q29saWNpbm8sIEVsZW5h|https://frl.publisso.de/adhoc/uri/Q29ycmVhLCBBZG9sZm8=|https://frl.publisso.de/adhoc/uri/Q291bGwsIEJyZW50|https://frl.publisso.de/adhoc/uri/RWF0b24sIENoYXJsZXM=|https://frl.publisso.de/adhoc/uri/SG91LCBMaWZhbmc=|https://frl.publisso.de/adhoc/uri/SnVzdCwgQWxsYW4gQy4=|https://frl.publisso.de/adhoc/uri/S3VuemUsIFNvbmph|https://frl.publisso.de/adhoc/uri/TGFuZ2UsIExlc2xpZQ==|https://frl.publisso.de/adhoc/uri/TGFuZ2UsIEV0aGFu|https://frl.publisso.de/adhoc/uri/TGluLCBYaWhvbmc=|https://frl.publisso.de/adhoc/uri/TGl1LCBTaW1pbg==|https://frl.publisso.de/adhoc/uri/TndhbmFqaS1FbndlcmVtLCBKYW1hamkgQy4=|https://frl.publisso.de/adhoc/uri/UmVpbmVyLCBBbGV4|https://frl.publisso.de/adhoc/uri/U2hlbiwgSmluY2hlbmc=|https://frl.publisso.de/adhoc/uri/U2Now7Z0dGtlciwgQmVu|https://frl.publisso.de/adhoc/uri/Vm9rb25hcywgUGFudGVs|https://frl.publisso.de/adhoc/uri/WmhlbmcsIFlpbmFu|https://frl.publisso.de/adhoc/uri/WW91bmcsIEJlc3NpZQ==|https://frl.publisso.de/adhoc/uri/U2Nod2FydHosIEpvZWw=|https://frl.publisso.de/adhoc/uri/SG9ydmF0aCwgU3RldmU=|https://frl.publisso.de/adhoc/uri/THUsIEFrZQ==|https://frl.publisso.de/adhoc/uri/V2hpdHNlbCwgRXJpYyBBLg==|https://frl.publisso.de/adhoc/uri/S29lbmlnLCBXb2xmZ2FuZw==|https://orcid.org/0000-0001-9259-0199|https://frl.publisso.de/adhoc/uri/V2lua2VsbWFubiwgSnVsaWFuZQ==|https://orcid.org/0000-0002-6129-1572|https://frl.publisso.de/adhoc/uri/QmFjY2FyZWxsaSwgQW5kcmVhIEEu|https://frl.publisso.de/adhoc/uri/R2llZ2VyLCBDaHJpc3RpYW4=|https://frl.publisso.de/adhoc/uri/UGV0ZXJzLCBBbm5ldHRl|https://orcid.org/0000-0001-9755-2175|https://orcid.org/0000-0003-0583-5093
1000 Hinweis
  • DeepGreen-ID: 4dc9fe3753134342bb127c7d344bb167 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
1000 Label
1000 Dateien
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6463999.rdf
1000 Erstellt am 2023-11-15T23:26:28.914+0100
1000 Erstellt von 322
1000 beschreibt frl:6463999
1000 Zuletzt bearbeitet 2023-11-30T22:47:47.697+0100
1000 Objekt bearb. Thu Nov 30 22:47:47 CET 2023
1000 Vgl. frl:6463999
1000 Oai Id
  1. oai:frl.publisso.de:frl:6463999 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

View source