000177561 001__ 177561
000177561 005__ 20240229133743.0
000177561 0247_ $$2doi$$a10.1016/j.ebiom.2021.103686
000177561 0247_ $$2pmid$$apmid:34808433
000177561 0247_ $$2altmetric$$aaltmetric:117402528
000177561 037__ $$aDKFZ-2021-02628
000177561 041__ $$aEnglish
000177561 082__ $$a610
000177561 1001_ $$0P:(DE-He78)70ce269695a19b94f3f8b0bca12ec49b$$aLi, Xiangwei$$b0$$eFirst author$$udkfz
000177561 245__ $$aComparative validation of three DNA methylation algorithms of ageing and a frailty index in relation to mortality: results from the ESTHER cohort study.
000177561 260__ $$aAmsterdam [u.a.]$$bElsevier$$c2021
000177561 3367_ $$2DRIVER$$aarticle
000177561 3367_ $$2DataCite$$aOutput Types/Journal article
000177561 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1637681339_25265
000177561 3367_ $$2BibTeX$$aARTICLE
000177561 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000177561 3367_ $$00$$2EndNote$$aJournal Article
000177561 500__ $$a#EA:C070#LA:C070#LA:C120
000177561 520__ $$aThree DNA methylation (DNAm) based algorithms, DNAm PhenoAge acceleration (AgeAccelPheno), DNAm GrimAge acceleration (AgeAccelGrim), and mortality risk score (MRscore), based on methylation in 513, 1030, and 10 CpGs, respectively, were established to predict health outcomes and mortality. We aimed to compare and validate the predictive ability of these scores and frailty in relation to mortality in a population-based cohort from Germany.DNA methylation in whole blood was measured by the Infinium Methylation EPIC BeadChip kit (EPIC, Illumina, San Diego, CA, USA) in two random subsets of the ESTHER cohort study (n = 741 and n = 1030). AgeAccelPheno, AgeAccelGrim, and a revised MRscore to adapt EPIC, the MRscore with 8 CpGs (MRscore-8CpGs), were calculated. Frailty was assessed by a frailty index (FI).During 17 years of follow-up, 458 deaths were observed. All DNAm algorithms and FI were positively correlated with each other. AgeAccelPheno, AgeAccelGrim, MRscore, and FI showed independent associations with all-cause mortality [hazard ratio (95% CI) per SD increase = 1·32 (1·19-1·46), 1·47 (1·32-1·64), 1·73 (1·49-2·01), and 1·31 (1·20-1·43), respectively]. Harrell's C-statistic was 0·710 for a model predicting mortality by age, sex, and leukocyte composition and increased to 0·759 in a model including MRscore-8CpGs and FI. The predictive performance was further improved (Harrell's C-statistic = 0·766) when additionally including AgeAccelPheno and AgeAccelGrim into the model.The combination of a DNA methylation score based on 8 CpGs only and an easy to ascertain frailty index may strongly enhance mortality prediction beyond age and sex.The ESTHER study was funded by grants from the Baden-Württemberg state Ministry of Science, Research and Arts (Stuttgart, Germany), the Federal Ministry of Education and Research (Berlin, Germany), the Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (Berlin, Germany), and the Saarland State Ministry of Health, Social Affairs, Women and the Family (Saarbrücken, Germany). The work of Xiangwei Li was supported by a grant from Fondazione Cariplo (Bando Ricerca Malattie invecchiamento, #2017-0653).
000177561 536__ $$0G:(DE-HGF)POF4-313$$a313 - Krebsrisikofaktoren und Prävention (POF4-313)$$cPOF4-313$$fPOF IV$$x0
000177561 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo01.inet.dkfz-heidelberg.de
000177561 650_7 $$2Other$$aDNA methylation
000177561 650_7 $$2Other$$aage acceleration
000177561 650_7 $$2Other$$aepigenetic clock
000177561 650_7 $$2Other$$afrailty
000177561 650_7 $$2Other$$amortality
000177561 7001_ $$0P:(DE-He78)6a8f87626cb610618a60d742677284cd$$aZhang, Yan$$b1
000177561 7001_ $$0P:(DE-He78)8218df9f6f41792399cd3a29b587e4e7$$aGào, Xīn$$b2$$udkfz
000177561 7001_ $$aHolleczek, Bernd$$b3
000177561 7001_ $$0P:(DE-He78)c67a12496b8aac150c0eef888d808d46$$aSchöttker, Ben$$b4$$udkfz
000177561 7001_ $$0P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aBrenner, Hermann$$b5$$eLast author$$udkfz
000177561 773__ $$0PERI:(DE-600)2799017-5$$a10.1016/j.ebiom.2021.103686$$gVol. 74, p. 103686 -$$p103686$$tEBioMedicine$$v74$$x2352-3964$$y2021
000177561 909CO $$ooai:inrepo02.dkfz.de:177561$$pVDB
000177561 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)70ce269695a19b94f3f8b0bca12ec49b$$aDeutsches Krebsforschungszentrum$$b0$$kDKFZ
000177561 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)6a8f87626cb610618a60d742677284cd$$aDeutsches Krebsforschungszentrum$$b1$$kDKFZ
000177561 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)8218df9f6f41792399cd3a29b587e4e7$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000177561 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)c67a12496b8aac150c0eef888d808d46$$aDeutsches Krebsforschungszentrum$$b4$$kDKFZ
000177561 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aDeutsches Krebsforschungszentrum$$b5$$kDKFZ
000177561 9131_ $$0G:(DE-HGF)POF4-313$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vKrebsrisikofaktoren und Prävention$$x0
000177561 9141_ $$y2021
000177561 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bEBIOMEDICINE : 2019$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Blind peer review$$d2021-02-03
000177561 915__ $$0LIC:(DE-HGF)CCBYNCNDNV$$2V:(DE-HGF)$$aCreative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND (No Version)$$bDOAJ$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bEBIOMEDICINE : 2019$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2021-02-03
000177561 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2021-02-03
000177561 9201_ $$0I:(DE-He78)C070-20160331$$kC070$$lC070 Klinische Epidemiologie und Alternf.$$x0
000177561 9201_ $$0I:(DE-He78)C120-20160331$$kC120$$lPräventive Onkologie$$x1
000177561 9201_ $$0I:(DE-He78)HD01-20160331$$kHD01$$lDKTK HD zentral$$x2
000177561 980__ $$ajournal
000177561 980__ $$aVDB
000177561 980__ $$aI:(DE-He78)C070-20160331
000177561 980__ $$aI:(DE-He78)C120-20160331
000177561 980__ $$aI:(DE-He78)HD01-20160331
000177561 980__ $$aUNRESTRICTED