PT - JOURNAL ARTICLE AU - Morgan E. Levine AU - Ake T. Lu AU - Austin Quach AU - Brian H. Chen AU - Themistocles L. Assimes AU - Stefania Bandinelli AU - Lifang Hou AU - Andrea A. Baccarelli AU - James D. Stewart AU - Yun Li AU - Eric A. Whitsel AU - James G Wilson AU - Alex P Reiner AU - Abraham Aviv AU - Kurt Lohman AU - Yongmei Liu AU - Luigi Ferrucci AU - Steve Horvath TI - An epigenetic biomarker of aging for lifespan and healthspan AID - 10.1101/276162 DP - 2018 Jan 01 TA - bioRxiv PG - 276162 4099 - http://biorxiv.org/content/early/2018/03/05/276162.short 4100 - http://biorxiv.org/content/early/2018/03/05/276162.full AB - 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 a 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 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.