Home > Publications database > Ageing-related markers and risks of cancer and cardiovascular disease: a prospective study in the EPIC-Heidelberg cohort. > print |
001 | 178285 | ||
005 | 20240229133803.0 | ||
024 | 7 | _ | |a 10.1007/s10654-021-00828-3 |2 doi |
024 | 7 | _ | |a pmid:34935094 |2 pmid |
024 | 7 | _ | |a 0393-2990 |2 ISSN |
024 | 7 | _ | |a 1573-7284 |2 ISSN |
024 | 7 | _ | |a altmetric:119568633 |2 altmetric |
037 | _ | _ | |a DKFZ-2021-03232 |
041 | _ | _ | |a English |
082 | _ | _ | |a 610 |
100 | 1 | _ | |a Srour, Bernard |0 P:(DE-He78)0644671d309776d45e0fc705d1156cac |b 0 |e First author |u dkfz |
245 | _ | _ | |a Ageing-related markers and risks of cancer and cardiovascular disease: a prospective study in the EPIC-Heidelberg cohort. |
260 | _ | _ | |a Dordrecht [u.a.] |c 2022 |b Springer Science + Business Media B.V. |
336 | 7 | _ | |a article |2 DRIVER |
336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1643971855_5756 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a ARTICLE |2 BibTeX |
336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
500 | _ | _ | |a #EA:C020#LA:C020# / 37, pages 49–65 (2022) |
520 | _ | _ | |a Biological age is an important risk factor for chronic diseases. We examined the associations between five markers of unhealthy ageing; Growth Differentiation Factor-15 (GDF-15), N-terminal pro-brain natriuretic peptide (NT-proBNP), glycated hemoglobin A1c (HbA1C), C-Reactive Protein (CRP) and cystatin-C; with risks of cancer and cardiovascular disease (CVD). We used a case-cohort design embedded in the EPIC-Heidelberg cohort, including a subcohort of 3792 participants along with 4867 incident cases of cancer and CVD. Hazard ratios (HRs) were computed and the strongest associations were used to build weighted multi-marker combinations, and their associations with cancer and CVD risks were tested. After adjusting for common confounders, we observed direct associations of GDF-15 with lung cancer risk, NT-proBNP with breast, prostate and colorectal cancers, HbA1C with lung, colorectal, and breast cancer risks, and CRP with lung and colorectal cancer risks. An inverse association was observed for GDF-15 and prostate cancer risk. We also found direct associations of all 5 markers with myocardial infarction (MI) risk, and of GDF-15, NT-proBNP, CRP and cystatin-C with stroke risk. A combination of the independently-associated markers showed a moderately strong association with the risks of cancer and CVD (HRQ4-Q1 ranged from 1.78[1.36, 2.34] for breast cancer, when combining NT-proBNP and HbA1C, to 2.87[2.15, 3.83] for MI when combining NT-proBNP, HbA1C, CRP and cystatin-C). This analysis suggests that combinations of biomarkers related to unhealthy ageing show strong associations with cancer risk, and corroborates published evidence on CVD risk. If confirmed in other studies, using these biomarkers could be useful for the identification of individuals at higher risk of age-related diseases. |
536 | _ | _ | |a 313 - Krebsrisikofaktoren und Prävention (POF4-313) |0 G:(DE-HGF)POF4-313 |c POF4-313 |f POF IV |x 0 |
588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: inrepo01.inet.dkfz-heidelberg.de |
650 | _ | 7 | |a Ageing biomarkers |2 Other |
650 | _ | 7 | |a Cancer risk |2 Other |
650 | _ | 7 | |a Cardiovascular disease |2 Other |
650 | _ | 7 | |a Case-cohort |2 Other |
650 | _ | 7 | |a NT-proBNP |2 Other |
700 | 1 | _ | |a Kaaks, Rudolf |0 P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a |b 1 |u dkfz |
700 | 1 | _ | |a Johnson, Theron |0 P:(DE-He78)79ab945544e5bc017a2317b6146ed3aa |b 2 |u dkfz |
700 | 1 | _ | |a Hynes, Lucas Cory |0 P:(DE-He78)f55fe2dee9fdef0b4db17187de23a9bf |b 3 |u dkfz |
700 | 1 | _ | |a Kühn, Tilman |0 P:(DE-He78)0907a10ba1dc8f53f04907f54f6fdcfe |b 4 |
700 | 1 | _ | |a Katzke, Verena |0 P:(DE-He78)fb68a9386399d72d84f7f34cfc6048b4 |b 5 |e Last author |u dkfz |
773 | _ | _ | |a 10.1007/s10654-021-00828-3 |0 PERI:(DE-600)2004992-4 |p 49–65 |t European journal of epidemiology |v 37 |y 2022 |x 0393-2990 |
909 | C | O | |p VDB |o oai:inrepo02.dkfz.de:178285 |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 0 |6 P:(DE-He78)0644671d309776d45e0fc705d1156cac |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 1 |6 P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 2 |6 P:(DE-He78)79ab945544e5bc017a2317b6146ed3aa |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 3 |6 P:(DE-He78)f55fe2dee9fdef0b4db17187de23a9bf |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 4 |6 P:(DE-He78)0907a10ba1dc8f53f04907f54f6fdcfe |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 5 |6 P:(DE-He78)fb68a9386399d72d84f7f34cfc6048b4 |
913 | 1 | _ | |a DE-HGF |b Gesundheit |l Krebsforschung |1 G:(DE-HGF)POF4-310 |0 G:(DE-HGF)POF4-313 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-300 |4 G:(DE-HGF)POF |v Krebsrisikofaktoren und Prävention |x 0 |
914 | 1 | _ | |y 2021 |
915 | _ | _ | |a DEAL Springer |0 StatID:(DE-HGF)3002 |2 StatID |d 2021-01-28 |w ger |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2021-01-28 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2021-01-28 |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2021-01-28 |
915 | _ | _ | |a National-Konsortium |0 StatID:(DE-HGF)0430 |2 StatID |d 2022-11-17 |w ger |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2022-11-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2022-11-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2022-11-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2022-11-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2022-11-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |d 2022-11-17 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |d 2022-11-17 |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b EUR J EPIDEMIOL : 2021 |d 2022-11-17 |
915 | _ | _ | |a IF >= 10 |0 StatID:(DE-HGF)9910 |2 StatID |b EUR J EPIDEMIOL : 2021 |d 2022-11-17 |
920 | 1 | _ | |0 I:(DE-He78)C020-20160331 |k C020 |l C020 Epidemiologie von Krebs |x 0 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a I:(DE-He78)C020-20160331 |
980 | _ | _ | |a UNRESTRICTED |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|