You are here
Integrative analysis of clinical and epigenetic biomarkers of mortality.
Wednesday,2022-07-20 21:10 America/Los_Angeles — ecterry
| Title | Integrative analysis of clinical and epigenetic biomarkers of mortality. |
| Publication Type | Journal Article |
| Year of Publication | 2022 |
| Authors | Huan, T, Nguyen, S, Colicino, E, Ochoa-Rosales, C, W Hill, D, Brody, JA, Soerensen, M, Zhang, Y, Baldassari, A, Elhadad, MAhmed, Toshiko, T, Zheng, Y, Domingo-Relloso, A, Lee, DHeon, Ma, J, Yao, C, Liu, C, Hwang, S-J, Joehanes, R, Fornage, M, Bressler, J, van Meurs, JBJ, Debrabant, B, Mengel-From, J, Hjelmborg, J, Christensen, K, Vokonas, P, Schwartz, J, Gahrib, SA, Sotoodehnia, N, Sitlani, CM, Kunze, S, Gieger, C, Peters, A, Waldenberger, M, Deary, IJ, Ferrucci, L, Qu, Y, Greenland, P, Lloyd-Jones, DM, Hou, L, Bandinelli, S, Voortman, T, Hermann, B, Baccarelli, A, Whitsel, E, Pankow, JS, Levy, D |
| Journal | Aging Cell |
| Volume | 21 |
| Issue | 6 |
| Pagination | e13608 |
| Date Published | 2022 Jun |
| ISSN | 1474-9726 |
| Keywords | Biomarkers, Cardiovascular Diseases, DNA Methylation, Epigenesis, Genetic, Epigenomics, Humans, Male, Neoplasms |
| Abstract | <p>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 , 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 = 4.1 × 10 ) and negatively associated with longevity (Beta = -1.9, P = 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.</p> |
| DOI | 10.1111/acel.13608 |
| Alternate Journal | Aging Cell |
| PubMed ID | 35546478 |
| PubMed Central ID | PMC9197414 |
| Grant List | U01HL080295 / HL / NHLBI NIH HHS / United States R01HL116747 / HL / NHLBI NIH HHS / United States N01HC85081 / HL / NHLBI NIH HHS / United States DK063491 / DK / NIDDK NIH HHS / United States N01HC85082 / HL / NHLBI NIH HHS / United States UL1 TR000124 / TR / NCATS NIH HHS / United States P30 DK063491 / DK / NIDDK NIH HHS / United States UL1TR000124 / TR / NCATS NIH HHS / United States R01AG023629 / AG / NIA NIH HHS / United States R01HL103612 / HL / NHLBI NIH HHS / United States U01HL130114 / HL / NHLBI NIH HHS / United States HHSN268201800001C / HL / NHLBI NIH HHS / United States N01HC85083 / HL / NHLBI NIH HHS / United States R01HL092111 / HL / NHLBI NIH HHS / United States HHSN268201500001C / HL / NHLBI NIH HHS / United States R01HL120393 / HL / NHLBI NIH HHS / United States U01 HL130114 / HL / NHLBI NIH HHS / United States R01HL111089 / HL / NHLBI NIH HHS / United States N01-HC-25195 / NH / NIH HHS / United States N01HC55222 / HL / NHLBI NIH HHS / United States HHSN268201200036C / HL / NHLBI NIH HHS / United States K08HL116640 / HL / NHLBI NIH HHS / United States HHSN268201500001I / NH / NIH HHS / United States HHSN268201500001I / HL / NHLBI NIH HHS / United States R01HL105756 / HL / NHLBI NIH HHS / United States HHSN268200800007C / HL / NHLBI NIH HHS / United States R01HL087652 / HL / NHLBI NIH HHS / United States N01HC85080 / HL / NHLBI NIH HHS / United States R01 AG023629 / AG / NIA NIH HHS / United States N01HC85086 / HL / NHLBI NIH HHS / United States N01HC85079 / HL / NHLBI NIH HHS / United States |
ePub date:
22/05