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@ARTICLE{Gao:166141,
author = {X. Gao$^*$ and Y. Zhang$^*$ and D. Boakye$^*$ and X. Li$^*$
and J. Chang-Claude$^*$ and M. Hoffmeister$^*$ and H.
Brenner$^*$},
title = {{W}hole blood {DNA} methylation aging markers predict
colorectal cancer survival: a prospective cohort study.},
journal = {Clinical epigenetics},
volume = {12},
number = {1},
issn = {1868-7083},
address = {[S.l.]},
publisher = {BioMed Central},
reportid = {DKFZ-2020-02649},
pages = {184},
year = {2020},
abstract = {Blood DNA methylation-based aging algorithms predict
mortality in the general population. We investigated the
prognostic value of five established DNA methylation aging
algorithms for patients with colorectal cancer
(CRC).AgeAccelHorvath, AgeAccelHannum, DNAmMRscore,
AgeAccelPheno and AgeAccelGrim were constructed using whole
blood epi-genomic data from 2206 CRC patients. After a
median follow-up of 6.2 years, 1079 deaths were documented,
including 596 from CRC. Associations of the aging algorithms
with survival outcomes were evaluated using the Cox
regression and survival curves. Harrell's C-statistics were
computed to investigate predictive performance.Adjusted
hazard ratios $(95\%$ confidence intervals) of all-cause
mortality for patients in the third compared to the first
tertile were 1.66 (1.32, 2.09) for the DNAmMRscore, 1.35
(1.14, 1.59) for AgeAccelPheno and 1.65 (1.37, 2.00) for
AgeAccelGrim, even after adjustment for age, sex and stage.
AgeAccelHorvath and AgeAccelHannum were not associated with
all-cause or CRC-specific mortality. In stage-specific
analyses, associations were much stronger for patients with
early or intermediate stage cancers (stages I, II and III)
than for patients with metastatic (stage IV) cancers.
Associations were weaker and less often statistically
significant for CRC-specific mortality. Adding DNAmMRscore,
AgeAccelPheno or AgeAccelGrim to models including age, sex
and tumor stage improved predictive performance
moderately.DNAmMRscore, AgeAccelPheno and AgeAccelGrim could
serve as non-invasive CRC prognostic biomarkers independent
of other commonly used markers. Further research should aim
for tailoring and refining such algorithms for CRC patients
and to explore their value for enhanced prediction of
treatment success and treatment decisions.},
cin = {C070 / HD01 / C020 / C120},
ddc = {610},
cid = {I:(DE-He78)C070-20160331 / I:(DE-He78)HD01-20160331 /
I:(DE-He78)C020-20160331 / I:(DE-He78)C120-20160331},
pnm = {313 - Cancer risk factors and prevention (POF3-313)},
pid = {G:(DE-HGF)POF3-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:33256852},
doi = {10.1186/s13148-020-00977-4},
url = {https://inrepo02.dkfz.de/record/166141},
}