An epigenetic biomarker of aging for lifespan and healthspan

By M. Levine, A. Lu, Austin Quach, Brian H. Chen, Themistocles L. Assimes, Stefania Bandinelli, Lifang Hou, Andrea A. Baccarelli, J. Stewart, Yun Li and 8 more. bioRxiv, 2018

3,003 citations recorded by the source corpus.

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.

Subfields: Genetics, Molecular Biology, Pediatrics, Perinatology and Child Health

View Paper: https://www.semanticscholar.org/paper/8968b5bdbb86740f0f33a4515cf90cf62f7a506e

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Citations in the corpus

DNA methylation aging clocks: challenges and recommendations (2019, methodology): “The size of the circle is proportional to the entire genome space for each functional category (~10(genome size proportion)). e-h Direct overlap comparison for four DNA methylation clocks (Horvath clock, Hannum et al. clock, PhenoAge clock, epiTOC clock) as well as Illumina array CpGs (27k, 450k, EP”
Measuring biological age using omics data (2022, methodology): “The DNAm GrimAge clock shows consistently stronger associations with various measures of age-related dysfunction, including heart disease, frailty, and cognitive and physical decline, compared to other clocks 47,48,50,64–72 .”
DNA methylation GrimAge strongly predicts lifespan and healthspan (2019, methodology): “For example, Zhang et al (2017) combined mortality associated CpGs [21] into an overall mortality risk score, while Levine et al (2018) developed a lifespan predictor, DNAm PhenoAge, by regressing a phenotypic measure of mortality risk on CpGs [22].”
Measuring biological aging in humans: A quest (2019, background): “Among these three, a growing body of literature emphasizes the role of DNA methylation in aging and agerelated chronic diseases in humans (Gensous et al., 2017; Levine et al., 2018).”
A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: A cohort study (2018, methodology): “We calculated Phenotypic Age in accordance with the method described previously [12].”
A toolkit for quantification of biological age from blood chemistry and organ function test data: BioAge (2021, methodology): “In the kdm_nhanes function in BioAge package, the reference sample is NHANES III nonpregnant participants aged 30–75 years.”
Aging and aging-related diseases: from molecular mechanisms to interventions and treatments (2022, background): “This clock confirmed the intrinsic links between the epigenetic clock and some aging mechanisms, such as the activation of proinflammatory and interferon pathways, transcriptional and translational mechanisms, and the DNA damage response.(72) A growing number of studies have confirmed that aging-rel”
DunedinPACE, a DNA methylation biomarker of the pace of aging (2021, methodology): “We compared DunedinPACE with the epigenetic clocks proposed by Horvath, Hannum et al., Levine et al., and Lu et al. (Hannum et al., 2013; Horvath, 2013; Levine et al., 2018; Lu et al., 2019), with measurements of biological age derived from physiological data and with participants’ subjective percep”