Dataset Information

An epigenetic biomarker of aging for lifespan and healthspan.

ABSTRACT: Identifying reliable biomarkers of aging is a major goal in geroscience. While the first generation of epigenetic biomarkers of aging were developed using chronological age as a surrogate for biological age, we hypothesized that incorporation of composite clinical measures of phenotypic age that capture differences in lifespan and healthspan may identify novel CpGs and facilitate the development of a more powerful epigenetic biomarker of aging. Using an innovative two-step process, we develop a new epigenetic biomarker of aging, DNAm PhenoAge, that strongly outperforms previous measures in regards to predictions for a variety of aging outcomes, including all-cause mortality, cancers, healthspan, physical functioning, and Alzheimer's disease. While this biomarker was developed using data from whole blood, it correlates strongly with age in every tissue and cell tested. Based on an in-depth transcriptional analysis in sorted cells, we find that increased epigenetic, relative to chronological age, is associated with increased activation of pro-inflammatory and interferon pathways, and decreased activation of transcriptional/translational machinery, DNA damage response, and mitochondrial signatures. Overall, this single epigenetic biomarker of aging is able to capture risks for an array of diverse outcomes across multiple tissues and cells, and provide insight into important pathways in aging.

SUBMITTER: Levine ME

PROVIDER: S-EPMC5940111 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An epigenetic biomarker of aging for lifespan and healthspan.

Levine Morgan E ME Lu Ake T AT Quach Austin A Chen Brian H BH Assimes Themistocles L TL Bandinelli Stefania S Hou Lifang L Baccarelli Andrea A AA Stewart James D JD Li Yun Y Whitsel Eric A EA Wilson James G JG Reiner Alex P AP Aviv Abraham A Lohman Kurt K Liu Yongmei Y Ferrucci Luigi L Horvath Steve S

Aging 20180401 4

Identifying reliable biomarkers of aging is a major goal in geroscience. While the first generation of epigenetic biomarkers of aging were developed using chronological age as a surrogate for biological age, we hypothesized that incorporation of composite clinical measures of phenotypic age that capture differences in lifespan and healthspan may identify novel CpGs and facilitate the development of a more powerful epigenetic biomarker of aging. Using an innovative two-step process, we develop a ...[more]

PMID: 29676998

Similar Datasets

Project description:BackgroundDNA methylation-based biological age (DNAm age) is an important biomarker for adult health. Studies in specific age ranges have found widely varying results about its genetic and environmental causes of variation. However, these studies are not able to provide a comprehensive view of the causes of variation over the lifespan.ResultsIn order to investigate the genetic and environmental causes of DNAm age variation across the lifespan, we pooled genome-wide DNA methylation data for 4217 people aged 0-92 years from 1871 families. DNAm age was calculated using the Horvath epigenetic clock. We estimated familial correlations in DNAm age for monozygotic (MZ) twin, dizygotic (DZ) twin, sibling, parent-offspring, and spouse pairs by cohabitation status. Genetic and environmental variance components models were fitted and compared. We found that twin pair correlations were - 0.12 to 0.18 around birth, not different from zero (all P > 0.29). For all pairs of relatives, their correlations increased with time spent living together (all P < 0.02) at different rates (MZ > DZ and siblings > parent-offspring; P < 0.001) and decreased with time spent living apart (P = 0.02) at similar rates. These correlation patterns were best explained by cohabitation-dependent shared environmental factors, the effects of which were 1.41 (95% confidence interval [CI] 1.16 to 1.66) times greater for MZ pairs than for DZ and sibling pairs, and the latter were 2.03 (95% CI 1.13 to 9.47) times greater than for parent-offspring pairs. Genetic factors explained 13% (95% CI - 10 to 35%) of variation (P = 0.27). Similar results were found for another two epigenetic clocks, suggesting that our observations are robust to how DNAm age is measured. In addition, results for the other clocks were consistent with there also being a role for prenatal environmental factors in determining their variation.ConclusionsVariation in DNAm age is mostly caused by environmental factors, including those shared to different extents by relatives while living together and whose effects persist into old age. The equal environment assumption of the classic twin study might not hold for epigenetic aging.

Dataset Information

An epigenetic biomarker of aging for lifespan and healthspan.

Publications

An epigenetic biomarker of aging for lifespan and healthspan.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets