Abstract / Description of output
DNA methylation (DNAm) has been reported to be associated with many diseases and with mortality. We hypothesized that the integration of DNAm with clinical risk factors would improve mortality prediction. We performed an epigenome-wide association study of whole blood DNAm in relation to mortality in 15 cohorts (n = 15,013). During a mean follow-up of 10 years, there were 4314 deaths from all causes including 1235 cardiovascular disease (CVD) deaths and 868 cancer deaths. Ancestry-stratified meta-analysis of all-cause mortality identified 163 CpGs in European ancestry (EA) and 17 in African ancestry (AA) participants at p < 1 × 10 -7 , of which 41 (EA) and 16 (AA) were also associated with CVD death, and 15 (EA) and 9 (AA) with cancer death. We built DNAm-based prediction models for all-cause mortality that predicted mortality risk after adjusting for clinical risk factors. The mortality prediction model trained by integrating DNAm with clinical risk factors showed an improvement in prediction of cancer death with 5% increase in the C-index in a replication cohort, compared with the model including clinical risk factors alone. Mendelian randomization identified 15 putatively causal CpGs in relation to longevity, CVD, or cancer risk. For example, cg06885782 (in KCNQ4) was positively associated with risk for prostate cancer (Beta = 1.2, P MR = 4.1 × 10 -4 ) and negatively associated with longevity (Beta = -1.9, P MR = 0.02). Pathway analysis revealed that genes associated with mortality-related CpGs are enriched for immune- and cancer-related pathways. We identified replicable DNAm signatures of mortality and demonstrated the potential utility of CpGs as informative biomarkers for prediction of mortality risk.
| Original language | English |
|---|---|
| Article number | e13608 |
| Journal | Aging Cell |
| Volume | 21 |
| Issue number | 6 |
| Early online date | 12 May 2022 |
| DOIs | |
| Publication status | Published - Jun 2022 |
Keywords / Materials (for Non-textual outputs)
- cancer
- cardiovascular disease
- DNA methylation
- machine learning
- mortality
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- HuanEtalAC2022IntegrativeAnalysisFinal published version, 2.93 MBLicence: Creative Commons: Attribution (CC-BY)
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In: Aging Cell, Vol. 21, No. 6, e13608, 06.2022.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Integrative analysis of clinical and epigenetic biomarkers of mortality
AU - Huan, Tianxiao
AU - Nguyen, Steve
AU - Colicino, Elena
AU - Ochoa-Rosales, Carolina
AU - Hill, W. David
AU - Brody, Jennifer A.
AU - Soerensen, Mette
AU - Zhang, Yan
AU - Baldassari, Antoine
AU - Elhadad, Mohamed Ahmed
AU - Toshiko, Tanaka
AU - Zheng, Yinan
AU - Domingo-Relloso, Arce
AU - Lee, Dong Heon
AU - Ma, Jiantao
AU - Yao, Chen
AU - Liu, Chunyu
AU - Hwang, Shih Jen
AU - Joehanes, Roby
AU - Fornage, Myriam
AU - Bressler, Jan
AU - van Meurs, Joyce B.J.
AU - Debrabant, Birgit
AU - Mengel-From, Jonas
AU - Hjelmborg, Jacob
AU - Christensen, Kaare
AU - Vokonas, Pantel
AU - Schwartz, Joel
AU - Gahrib, Sina A.
AU - Sotoodehnia, Nona
AU - Sitlani, Colleen M.
AU - Kunze, Sonja
AU - Gieger, Christian
AU - Peters, Annette
AU - Waldenberger, Melanie
AU - Deary, Ian J.
AU - Ferrucci, Luigi
AU - Qu, Yishu
AU - Greenland, Philip
AU - Lloyd-Jones, Donald M.
AU - Hou, Lifang
AU - Bandinelli, Stefania
AU - Voortman, Trudy
AU - Hermann, Brenner
AU - Baccarelli, Andrea
AU - Whitsel, Eric
AU - Pankow, James S.
AU - Levy, Daniel
N1 - Funding Information: The Framingham Heart Study is funded by National Institutes of Health contract N01-HC-25195 and HHSN268201500001I. The laboratory work for this investigation was funded by the Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health. The analytical component of this project was funded by the Division of Intramural Research, National Heart, Lung, and Blood Institute, and the Center for Information Technology, National Institutes of Health, Bethesda, MD. The Cardiovascular Health Study is supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants U01HL080295, U01HL130114, K08HL116640, R01HL087652, R01HL092111, R01HL103612, R01HL105756, R01HL103612, R01HL111089, R01HL116747 and R01HL120393 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through R01AG023629 from the National Institute on Aging (NIA), Merck Foundation/Society of Epidemiologic Research as well as Laughlin Family, Alpha Phi Foundation, and Locke Charitable Foundation. A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. Infrastructure for the CHARGE Consortium is supported in part by the National Heart, Lung, and Blood Institute grant R01HL105756. The DTR study was supported by The Danish Council for Independent Research—Medical Sciences (DFF-6110-00016), the European Union's Seventh Framework Programme (FP7/2007–2011) under grant Agreement No. 259679 and The Danish National Program for Research Infrastructure 2007 (09-063256). The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. Work in WHI was NIEHS-supported by R01-ES020836 (EAW; AB; LH). Phenotype collection in the Lothian Birth Cohort 1921 was supported by the UK’s Biotechnology and Biological Sciences Research Council (BBSRC), The Royal Society and The Chief Scientist Office of the Scottish Government. Phenotype collection in the Lothian Birth Cohort 1936 was supported by Age UK (The Disconnected Mind project). Methylation typing was supported by Centre for Cognitive Ageing and Cognitive Epidemiology (Pilot Fund award), Age UK, The Wellcome Trust Institutional Strategic Support Fund, The University of Edinburgh, and The University of Queensland. IJD is a member of the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), which is supported by funding from the BBSRC, the Medical Research Council (MRC), and the University of Edinburgh as part of the cross-council Lifelong Health and Wellbeing initiative (MR/K026992/1). W.D.H. is supported by a grant from Age UK (Disconnected Mind Project). The VA Normative Aging Study is sponsored by the CSP/ERIC program of the U.S. Department of Veterans Affairs and is a research component of the Massachusetts Veterans Education Research and Information Center (MAVERIC). The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under Contract nos. 75N92022D00001, 75N92022D00002, 75N92022D00003, 75N92022D00004, and 75N92022D00005. Funding was also supported by 5RC2HL102419 and R01NS087541. The authors thank the staff and participants of the ARIC study for their important contributions. J.M. is supported by a grant from NIH HL135075. W.D.H. is supported by a Career Development Award from the Medical Research Council (MRC) [MR/T030852/1] for the project titled “From genetic sequence to phenotypic consequence: genetic and environmental links between cognitive ability, socioeconomic position, and health.” The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. For a list of all the investigators who have contributed to WHI science, please visit: https://s3-us-west-2.amazonaws.com/www-whi-org/wp-content/uploads/WHI-Investigator-Long-List.pdf. Funding Information: The Framingham Heart Study is funded by National Institutes of Health contract N01‐HC‐25195 and HHSN268201500001I. The laboratory work for this investigation was funded by the Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health. The analytical component of this project was funded by the Division of Intramural Research, National Heart, Lung, and Blood Institute, and the Center for Information Technology, National Institutes of Health, Bethesda, MD. The Cardiovascular Health Study is supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants U01HL080295, U01HL130114, K08HL116640, R01HL087652, R01HL092111, R01HL103612, R01HL105756, R01HL103612, R01HL111089, R01HL116747 and R01HL120393 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through R01AG023629 from the National Institute on Aging (NIA), Merck Foundation/Society of Epidemiologic Research as well as Laughlin Family, Alpha Phi Foundation, and Locke Charitable Foundation. A full list of principal CHS investigators and institutions can be found at CHS‐NHLBI.org. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. Infrastructure for the CHARGE Consortium is supported in part by the National Heart, Lung, and Blood Institute grant R01HL105756. The study was supported by The Danish Council for Independent Research—Medical Sciences (DFF‐6110‐00016), the European Union's Seventh Framework Programme (FP7/2007–2011) under grant Agreement No. 259679 and The Danish National Program for Research Infrastructure 2007 (09‐063256). The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. Work in WHI was NIEHS‐supported by R01‐ES020836 (EAW; AB; LH). Phenotype collection in the Lothian Birth Cohort 1921 was supported by the UK’s Biotechnology and Biological Sciences Research Council (BBSRC), The Royal Society and The Chief Scientist Office of the Scottish Government. Phenotype collection in the Lothian Birth Cohort 1936 was supported by Age UK (The Disconnected Mind project). Methylation typing was supported by Centre for Cognitive Ageing and Cognitive Epidemiology (Pilot Fund award), Age UK, The Wellcome Trust Institutional Strategic Support Fund, The University of Edinburgh, and The University of Queensland. IJD is a member of the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), which is supported by funding from the BBSRC, the Medical Research Council (MRC), and the University of Edinburgh as part of the cross‐council Lifelong Health and Wellbeing initiative (MR/K026992/1). W.D.H. is supported by a grant from Age UK (Disconnected Mind Project). The VA Normative Aging Study is sponsored by the CSP/ERIC program of the U.S. Department of Veterans Affairs and is a research component of the Massachusetts Veterans Education Research and Information Center (MAVERIC). The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under Contract nos. 75N92022D00001, 75N92022D00002, 75N92022D00003, 75N92022D00004, and 75N92022D00005. Funding was also supported by 5RC2HL102419 and R01NS087541. The authors thank the staff and participants of the ARIC study for their important contributions. J.M. is supported by a grant from NIH HL135075. W.D.H. is supported by a Career Development Award from the Medical Research Council (MRC) [MR/T030852/1] for the project titled “From genetic sequence to phenotypic consequence: genetic and environmental links between cognitive ability, socioeconomic position, and health.” DTR © 2022 The Authors. Aging Cell published by Anatomical Society and John Wiley & Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
PY - 2022/6
Y1 - 2022/6
N2 - DNA methylation (DNAm) has been reported to be associated with many diseases and with mortality. We hypothesized that the integration of DNAm with clinical risk factors would improve mortality prediction. We performed an epigenome-wide association study of whole blood DNAm in relation to mortality in 15 cohorts (n = 15,013). During a mean follow-up of 10 years, there were 4314 deaths from all causes including 1235 cardiovascular disease (CVD) deaths and 868 cancer deaths. Ancestry-stratified meta-analysis of all-cause mortality identified 163 CpGs in European ancestry (EA) and 17 in African ancestry (AA) participants at p < 1 × 10 -7 , of which 41 (EA) and 16 (AA) were also associated with CVD death, and 15 (EA) and 9 (AA) with cancer death. We built DNAm-based prediction models for all-cause mortality that predicted mortality risk after adjusting for clinical risk factors. The mortality prediction model trained by integrating DNAm with clinical risk factors showed an improvement in prediction of cancer death with 5% increase in the C-index in a replication cohort, compared with the model including clinical risk factors alone. Mendelian randomization identified 15 putatively causal CpGs in relation to longevity, CVD, or cancer risk. For example, cg06885782 (in KCNQ4) was positively associated with risk for prostate cancer (Beta = 1.2, P MR = 4.1 × 10 -4 ) and negatively associated with longevity (Beta = -1.9, P MR = 0.02). Pathway analysis revealed that genes associated with mortality-related CpGs are enriched for immune- and cancer-related pathways. We identified replicable DNAm signatures of mortality and demonstrated the potential utility of CpGs as informative biomarkers for prediction of mortality risk.
AB - DNA methylation (DNAm) has been reported to be associated with many diseases and with mortality. We hypothesized that the integration of DNAm with clinical risk factors would improve mortality prediction. We performed an epigenome-wide association study of whole blood DNAm in relation to mortality in 15 cohorts (n = 15,013). During a mean follow-up of 10 years, there were 4314 deaths from all causes including 1235 cardiovascular disease (CVD) deaths and 868 cancer deaths. Ancestry-stratified meta-analysis of all-cause mortality identified 163 CpGs in European ancestry (EA) and 17 in African ancestry (AA) participants at p < 1 × 10 -7 , of which 41 (EA) and 16 (AA) were also associated with CVD death, and 15 (EA) and 9 (AA) with cancer death. We built DNAm-based prediction models for all-cause mortality that predicted mortality risk after adjusting for clinical risk factors. The mortality prediction model trained by integrating DNAm with clinical risk factors showed an improvement in prediction of cancer death with 5% increase in the C-index in a replication cohort, compared with the model including clinical risk factors alone. Mendelian randomization identified 15 putatively causal CpGs in relation to longevity, CVD, or cancer risk. For example, cg06885782 (in KCNQ4) was positively associated with risk for prostate cancer (Beta = 1.2, P MR = 4.1 × 10 -4 ) and negatively associated with longevity (Beta = -1.9, P MR = 0.02). Pathway analysis revealed that genes associated with mortality-related CpGs are enriched for immune- and cancer-related pathways. We identified replicable DNAm signatures of mortality and demonstrated the potential utility of CpGs as informative biomarkers for prediction of mortality risk.
KW - cancer
KW - cardiovascular disease
KW - DNA methylation
KW - machine learning
KW - mortality
U2 - 10.1111/acel.13608
DO - 10.1111/acel.13608
M3 - Article
C2 - 35546478
AN - SCOPUS:85130029475
SN - 1474-9718
VL - 21
JO - Aging Cell
JF - Aging Cell
IS - 6
M1 - e13608
ER -