An epigenetic biomarker of aging for lifespan and healthspan

Abstract

43Identifying reliable biomarkers of aging is a major goal in geroscience. While the first generation 44 of epigenetic biomarkers of aging were developed using chronological age as a surrogate for 45 biological age, we hypothesized that incorporation of composite clinical measures of phenotypic 46 age that capture differences in lifespan and healthspan may identify novel CpGs and facilitate the 47 development of a more powerful epigenetic biomarker of aging. Using a innovative two-step 48 process, we develop a new epigenetic biomarker of aging, DNAm PhenoAge, that strongly 49 outperforms previous measures in regards to predictions for a variety of aging outcomes, including 50 all-cause mortality, cancers, healthspan, physical functioning, and Alzheimer's disease. While this 51 biomarker was developed using data from whole blood, it correlates strongly with age in every 52 tissue and cell tested. Based on an in-depth transcriptional analysis in sorted cells, we find that 53 increased epigenetic, relative to chronological age, is associated increased activation of pro-54 inflammatory and interferon pathways, and decreased activation of transcriptional/translational 55 machinery, DNA damage response, and mitochondrial signatures. Overall, this single epigenetic 56 biomarker of aging is able to capture risks for an array of diverse outcomes across multiple tissues 57 and cells, and provide insight into important pathways in aging. 58 Keywords: aging; life expectancy; biological age; epigenetic clock; DNA methylation 59 60 61 62 63 64 4 BACKGROUND 65One of the major goals of geroscience research is to define 'biomarkers of aging' [1, 2], which can 66 be thought of as individual-level measures of aging that capture between-person differences in the 67 timing of disease onset, functional decline, and death over the life course. While chronological age 68 is arguably the strongest risk factor for aging-related death and disease, it is important to 69 distinguish chronological time from biological aging. Individuals of the same chronological age 70 may exhibit greatly different susceptibilities to age-related diseases and death, which is likely 71 reflective of differences in their underlying biological aging processes. Such biomarkers of aging 72 will be crucial to enable evaluation of interventions aimed at promoting healthier aging, by 73 providing a measurable outcome, that unlike incidence of death and/or disease, does not require 74 extremely long follow-up observation. 75One potential biomarker that has gained significant interest in recent years is DNA methylation 76 (DNAm). Chronological time has been shown to elicit predictable hypo-and hyper-methylation 77 changes at many regions across the genome [3][4][5][6][7], and as a result, the first generation of DNAm 78 based biomarkers of aging were developed to predict chronological age [8][9][10][11][12][13]. The blood-based 79 algorithm by Hannum[10] and the multi-tissue algorithm by Horvath [14] produce age estimates 80 (DNAm age) that correlate with chronologica...

Reversal of epigenetic aging and immunosenescent trends in humans

“…The specific epigenetic “clocks” chosen for use in this study were those derived by Horvath (; DNAm age), Hannum et al (; DNAm age H), Levine et al (; DNAm PhenoAge), and Lu et al (; DNAm age G or “GrimAge”). The specific rationales for these choices are based on Horvath and Levine (), Marioni et al (), and Triche, Weisenberger, van den Berg, Laird, and Siegmund, () and are described in Appendix .…”

Immune epigenetic age in pregnancy and 1 year after birth: Associations with weight change

“…Phenotypic epigenetic age acceleration was calculated by Morgan Levine using R syntax as described elsewhere . PEAA is calculated from 513 CpG sites that were selected based on ability to predict both chronological age and phenotypic indicators of aging.…”

“…PEAA is calculated from 513 CpG sites that were selected based on ability to predict both chronological age and phenotypic indicators of aging. PEAA is associated with all‐cause mortality, cancers, physical function, and Alzheimer's disease …”

“…Finally, clinical or phenotypic‐derived epigenetic age indices are calculated using DNA methylation sites that are highly correlated with clinical risk factors or outcomes. Phenotypic epigenetic age acceleration (PEAA) was developed as an epigenetic biomarker of “phenotypic age,” defined by nine biological markers (albumin, creatinine, glucose, C‐reactive protein, lymphocyte percent, mean cell volume, red cell distribution, alkaline phosphatase, and white blood cell count) and chronological age . GrimAge was constructed as a composite marker calculated from epigenetic surrogate markers for 12 plasma proteins (adrenomedullin, β‐2‐microglobulin, CD56, ceruloplasmin, cystatin C, EGF fibulin‐like ECM protein 1, growth differentiation factor 15, leptin, myoglobin, plasminogen activator inhibitor 1, serum paraoxonase/arylesterase 1, and tissue inhibitor metalloproteinases 1) and smoking pack‐years, based on self‐reported smoking data, and is strongly predictive of death.…”

Prospects for incorporation of epigenetic biomarkers in human health and environmental risk assessment of chemicals

“…Their inheritance through successive generations can ultimately lead to the induction of micro‐evolutionary patterns in individual‐ and population‐level traits (Burggren, ; Jeremias et al ., ). Accordingly, epigenetics has become vital to understanding gene × environment interactions and researchers are increasingly interested in using epigenetic exposure‐associated changes as biological markers (Chan & Baylin, ; Lockwood, Su & Youssef, ; Whayne, ; Leygo et al ., ; Levine et al ., ).…”