Clock Catalogue

Browse and filter every aging clock available in pyaging. Filter by any categorical column — data type, species, platform, model type, unit, tissue, last author, journal, and more; search by name, author, or notes; sort any column; toggle between table and card views; and click a clock to expand its full details.

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Clock name	Data type	Species	Predicts	Unit	Tissue	Platform	Population	Model type	N features	Year	Citations	Citations date	Last author	Journal	DOI	Notes	Preprocess	Postprocess	Reference values	Verified
altumage	methylation	Homo sapiens	chronological age	years	multi-tissue (pan-tissue; 142 human datasets)	Illumina 27K/450K/EPIC	pan-age (all ages, human)	Neural network	20318	2022	145	2026-07-05	Ritambhara Singh	npj Aging	https://doi.org/10.1038/s41514-022-00085-y	Pan-tissue DNA-methylation age predictor built with a deep neural network spanning diverse human tissues, capturing nonlinear CpG interactions to estimate chronological age.	scale		True	By authors
bitage	transcriptomics	C elegans	biological age (transcriptomic age)	hours	whole adult C. elegans (bulk RNA-seq, whole-organism, not tissue-specific)	RNA-seq	adult C. elegans only (trained on ~1,020 adult RNA-seq samples); also shown applicable to human age prediction	Elastic net	576	2021	173	2026-07-05	Björn Schumacher	Aging Cell	https://doi.org/10.1111/acel.13320	Transcriptome-based aging clock for C. elegans that predicts biological age from binarized (on/off) gene-expression profiles using penalized elastic-net regression, achieving accuracy near the theoretical limit.	binarize			By authors
camilloh3k27ac	histone mark	Homo sapiens	chronological age	years	Multi-tissue (82 human tissue/cell types, ENCODE ChIP-seq biosamples, n=359 for H3K27ac)	ChIP-seq	Humans, multiple tissues/cell types, embryonic through 90+ years, ~equal sex split	PCA + elastic net	1275	2025	4	2026-07-05	Ritambhara Singh	Science Advances	https://doi.org/10.1126/sciadv.adk9373	Chronological-age predictor built with a deep neural network from genome-wide H3K27ac ChIP-seq signal, a mark of active enhancers and promoters, as part of a pan-tissue family of histone-mark aging clocks spanning human tissues and cell types.				By authors
camilloh3k27me3	histone mark	Homo sapiens	Chronological age	years	Multi-tissue (pan-tissue human tissues and cell types, ~82 tissues/biosamples; ENCODE ChIP-seq)	ChIP-seq	Pan-age humans (embryonic to elderly), pan-tissue	PCA + elastic net	922	2025	4	2026-07-05	Ritambhara Singh	Science Advances	https://doi.org/10.1126/sciadv.adk9373	Chronological-age predictor built with a deep neural network from genome-wide H3K27me3 ChIP-seq signal, a Polycomb-associated repressive mark, as part of a pan-tissue family of histone-mark aging clocks spanning human tissues and cell types.				By authors
camilloh3k36me3	histone mark	Homo sapiens	chronological age	years	multi-tissue (human tissues and cell lines; ENCODE H3K36me3 ChIP-seq)	ChIP-seq	humans; pan-tissue, broad age range	PCA + elastic net	870	2025	4	2026-07-05	Ritambhara Singh	Science Advances	https://doi.org/10.1126/sciadv.adk9373	Chronological-age predictor built with a deep neural network from genome-wide H3K36me3 ChIP-seq signal, a mark of transcribed gene bodies, as part of a pan-tissue family of histone-mark aging clocks spanning human tissues and cell types.				By authors
camilloh3k4me1	histone mark	Homo sapiens	Chronological age	years	Multi-tissue (ENCODE human tissues and cell types; H3K4me1 ChIP-seq data, part of a larger dataset of 1,814 human samples across 82 tissues/cell types for 7 histone marks)	ChIP-seq	Human, pan-tissue; ages spanning embryonic/fetal stages to 90+ years	PCA + elastic net	892	2025	4	2026-07-05	Ritambhara Singh	Science Advances	https://doi.org/10.1126/sciadv.adk9373	Chronological-age predictor built with a deep neural network from genome-wide H3K4me1 ChIP-seq signal, a mark of enhancers, as part of a pan-tissue family of histone-mark aging clocks spanning human tissues and cell types.				By authors
camilloh3k4me3	histone mark	Homo sapiens	chronological age	years	Multi-tissue (82 human tissue/cell types; ENCODE ChIP-seq samples, n=359)	ChIP-seq	Humans, pan-age (embryonic to 90+ years), ~equal male/female	PCA + elastic net	1240	2025	4	2026-07-05	Ritambhara Singh	Science Advances	https://doi.org/10.1126/sciadv.adk9373	Chronological-age predictor built with a deep neural network from genome-wide H3K4me3 ChIP-seq signal, a mark of active promoters, as part of a pan-tissue family of histone-mark aging clocks spanning human tissues and cell types.				By authors
camilloh3k9ac	histone mark	Homo sapiens	chronological age	years	Multi-tissue (human tissues and cell types; ENCODE ChIP-seq)	ChIP-seq	Pan-age humans (fetal/embryonic to elderly)	PCA + elastic net	102	2025	4	2026-07-05	Ritambhara Singh	Science Advances	https://doi.org/10.1126/sciadv.adk9373	Chronological-age predictor built with a deep neural network from genome-wide H3K9ac ChIP-seq signal, a mark of active promoters, as part of a pan-tissue family of histone-mark aging clocks spanning human tissues and cell types.				By authors
camilloh3k9me3	histone mark	Homo sapiens	Chronological age	years	Multi-tissue (pan-tissue human tissues and cell types, from ENCODE H3K9me3 ChIP-seq)	ChIP-seq	Humans, pan-tissue, wide age range (embryonic to 90+ years)	PCA + elastic net	341	2025	4	2026-07-05	Ritambhara Singh	Science Advances	https://doi.org/10.1126/sciadv.adk9373	Chronological age predictor built from H3K9me3 histone-mark ChIP-seq signal, using this heterochromatin-associated modification profiled across diverse human tissues and cell types to estimate age via regularized regression on gene-level features.				By authors
camillopanhistone	histone mark	Homo sapiens	chronological age	years	multi-tissue (82 distinct human tissues; also validated on primary cell types)	ChIP-seq	humans, pan-tissue, wide age range (embryonic to 90+ years)	PCA + elastic net	3739	2025	4	2026-07-05	Ritambhara Singh	Science Advances	https://doi.org/10.1126/sciadv.adk9373	Pan-tissue, pan-histone-mark age predictor that integrates ChIP-seq signal from multiple histone modifications across diverse human tissues, demonstrating that age is broadly encoded across the epigenome with accuracy comparable to DNA-methylation clocks.				By authors
cpgptgrimage3	methylation	Homo sapiens	mortality/time-to-death risk (GrimAge-style)	years	whole blood	Illumina 450K/EPIC	adults	Cox regression	24	2025	30	2026-07-05	Bo Wang	bioRxiv (Cold Spring Harbor Laboratory)	https://doi.org/10.1101/2024.10.24.619766	Mortality-risk predictor derived from a DNA-methylation foundation transformer, reconstructing a GrimAge-style Cox model of time-to-death from genome-wide methylation profiles and reporting strong methylation-based mortality prediction.	scale	cox_to_years		By authors
cpgptpcgrimage3	methylation	Homo sapiens	mortality/time-to-death risk (GrimAge3 biological age proxy)	years	whole blood	Illumina 450K/EPIC	adults	PCA + elastic net	31	2025	30	2026-07-05	Bo Wang	bioRxiv (Cold Spring Harbor Laboratory)	https://doi.org/10.1101/2024.10.24.619766	Principal-component version of the foundation-transformer GrimAge3 mortality predictor, applying the model to PC-denoised DNA-methylation inputs to yield a more reliable Cox-based estimate of mortality risk.	scale	cox_to_years		By authors
dunedinpace	methylation	Homo sapiens	pace of aging (rate of biological aging / multi-organ decline)	years	whole blood	Illumina 450K/EPIC	adults (validated ~18-95 years); trained on Dunedin 1972-73 birth cohort, blood drawn at age 45	Elastic net	20000	2022	967	2026-07-05	Terrie E Moffitt	eLife	https://doi.org/10.7554/eLife.73420	Whole-blood elastic-net biomarker of the pace of biological aging, trained to predict a longitudinal Pace-of-Aging measure derived from decline across 19 organ-system biomarkers in the Dunedin birth cohort; it is restricted to reliability-filtered CpGs to achieve high test-retest reliability.	quantile_normalization_with_gold_standard		True	By authors
han	methylation	Homo sapiens	chronological age	years	whole blood	Illumina 450K	pan-age (pediatric to elderly, ~1-101 years)	LASSO	65	2020	102	2026-07-05	Wolfgang Wagner	BMC Biology	https://doi.org/10.1186/s12915-020-00807-2	Blood chronological-age predictor built by penalized (elastic-net/Lasso) regression on a small set of age-associated CpGs selected for targeted, cost-effective assays such as pyrosequencing, droplet digital PCR, and bisulfite amplicon sequencing.		anti_log_linear		By authors
knight	methylation	Homo sapiens	gestational age at birth	weeks	Umbilical cord blood and neonatal blood spots	Illumina 27K/450K	fetal/newborn (gestational age at birth, ~24-44 weeks)	Elastic net	148	2016	312	2026-07-05	Alicia K. Smith	Genome biology	https://doi.org/10.1186/s13059-016-1068-z	Elastic-net clock estimating gestational age at birth from cord- and neonatal-blood DNA methylation at 148 CpGs.			True	By authors
leecontrol	methylation	Homo sapiens	gestational age	weeks	placenta (chorionic villi, control/uncomplicated pregnancies)	Illumina 450K/EPIC	fetal/newborn (gestational, ~5-42 weeks)	Elastic net	546	2019	170	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.102049	Placental epigenetic clock estimating gestational age from placental DNA methylation, built with elastic-net regression on roughly 546 CpGs trained on control (uncomplicated) pregnancies.				By authors
leerefinedrobust	methylation	Homo sapiens	gestational age	weeks	placenta (chorionic villi, fetal side)	Illumina 450K/EPIC	fetal/newborn (gestational); optimized for uncomplicated term pregnancies (GA >36 weeks)	Elastic net	395	2019	170	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.102049	Placental gestational-age clock built by elastic-net regression, refined on uncomplicated term pregnancies using a reduced subset (about 395) of the robust clock’s CpGs for improved precision in that subgroup.				By authors
leerobust	methylation	Homo sapiens	gestational age	weeks	placenta (fetal-side chorionic villi)	Illumina 450K/EPIC	fetal/placental, gestational age ~5-42 weeks (robust across complicated pregnancies)	Elastic net	558	2019	170	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.102049	Placental epigenetic clock estimating gestational age from placental DNA methylation via elastic-net regression on about 558 CpGs, trained across pregnancies including complications to be robust to varied clinical conditions.				By authors
pasta	transcriptomics	Homo sapiens	relative (biological) age-shift; also discriminates senescent vs stem-like/quiescent cell states	years	Multi-tissue human (healthy donors; mostly GTEx, plus GEO and Expression Atlas datasets); also mouse datasets used for validation	RNA-seq	Human (adult, healthy donors, pan-tissue) and mouse; generalizes across platforms and species	Elastic net	8113	2025	1	2026-07-05	Christian G. Riedel	bioRxiv (Cold Spring Harbor Laboratory)	https://doi.org/10.1101/2025.06.04.657785	Cross-platform transcriptomic aging clock that estimates relative cellular age from rank-transformed gene expression using a ridge-regularized age-shift classifier trained on same-tissue sample pairs decades apart. It generalizes across bulk and single-cell RNA-seq, microarray, and L1000 data and multiple species, and was used to screen chemical and genetic perturbations that accelerate or reverse cellular aging.	median_fill_and_rank_normalization	scale_and_shift	True	By authors
pastamouse	transcriptomics	Mus musculus	Relative age-shift (biological age difference between paired samples), not absolute chronological age	years	Multi-tissue (trained on paired samples from same tissue/study, human transcriptomic data across studies; mouse-ortholog variant applies same model to mouse tissues)	RNA-seq	Primarily human (pan-tissue, adult), with a mouse-ortholog adaptation (pastamouse) enabling application to mouse transcriptomic data	Ridge regression	1600	2025	1	2026-07-05	Christian G. Riedel	bioRxiv (Cold Spring Harbor Laboratory)	https://doi.org/10.1101/2025.06.04.657785	Mouse implementation of the age-shift transcriptomic clock, predicting relative cellular age from rank-transformed expression restricted to mouse one-to-one orthologs of the human age-associated genes.	median_fill_and_rank_normalization	scale_and_shift	True	By authors
pipekelasticnet	methylation	Homo sapiens	chronological age	years	multi-tissue (whole blood and other tissues)	Illumina 27K/450K/EPIC	pan-age adults (multi-tissue human)	Elastic net	239	2022	2	2026-07-05	István Csabai	Journal of Mathematical Chemistry	https://doi.org/10.1007/s10910-022-01381-4	Multi-tissue, multi-platform DNA-methylation predictor of chronological age that revises Horvath’s pan-tissue clock, fit with elastic-net regression on roughly 6,000 samples. This variant selects a fresh set of about 239 CpGs and extends accurate age estimation to Illumina EPIC array data.		anti_log_linear		By authors
pipekfilteredh	methylation	Homo sapiens	chronological age	years	multi-tissue (whole blood and other tissues, ~6,000 training samples)	Illumina 27K/450K/EPIC	pan-tissue humans, all ages (revises Horvath pan-tissue clock; anti-log-linear transform, adult age 20)	Elastic net	272	2022	2	2026-07-05	István Csabai	Journal of Mathematical Chemistry	https://doi.org/10.1007/s10910-022-01381-4	Multi-tissue, multi-platform DNA-methylation chronological-age clock revising Horvath’s pan-tissue predictor. The ‘filtered’ variant reuses the original Horvath CpG covariates (about 272 sites) with re-estimated coefficients, improving accuracy on EPIC arrays while remaining backward-compatible with datasets already processed by the original clock.		anti_log_linear		By authors
pipekretrainedh	methylation	Homo sapiens	chronological age (DNAm age)	years	multi-tissue (pan-tissue methylation, ~6,000 samples)	Illumina 27K/450K/EPIC	pan-age humans (children to elderly)	Elastic net	308	2022	2	2026-07-05	István Csabai	Journal of Mathematical Chemistry	https://doi.org/10.1007/s10910-022-01381-4	Multi-tissue, multi-platform DNA-methylation chronological-age clock revising Horvath’s pan-tissue predictor. The ‘retrained’ variant re-fits coefficients over the original Horvath CpG set (about 308 sites) on roughly 6,000 samples to extend accurate age prediction to Illumina EPIC array data.		anti_log_linear		By authors
reg	transcriptomics	Homo sapiens	Chronological age (baseline regression clock, vs. Pasta’s relative age-shift)	years	Multi-tissue (human; 17,212 healthy samples from GTEx, GEO, Expression Atlas)	RNA-seq	Healthy humans, broad adult age range (generalizes across tissues, platforms, and to mouse)	Ridge regression	8113	2025	1	2026-07-05	Christian G. Riedel	bioRxiv (Cold Spring Harbor Laboratory)	https://doi.org/10.1101/2025.06.04.657785	Transcriptomic aging clock (Pasta) that estimates relative biological age from gene-expression profiles using an age-shift learning strategy, generalizing across tissues, platforms (bulk and single-cell RNA-seq and microarray) and species. Its coefficients are enriched for p53 and DNA-damage-response pathways, and age scores track senescent and stem-like states.	median_fill_and_rank_normalization	add_constant	True	By authors
stemtoc	methylation	Homo sapiens	Total/relative mitotic age (cumulative stem-cell and progenitor cell divisions), as a cancer-risk proxy	proportion (0-1)	Multi-tissue: constructed from 86 fetal/neonatal samples across 13 tissue types (Illumina 450K) plus in vitro cell-line passage data (EPIC) and adult whole-blood cohorts for CpG validation…	Illumina 450K/EPIC	Pan-age: constructed from fetal/neonatal tissue and validated in adult whole blood and cell lines; applicable across normal and precancerous tissues	Mitotic model	371	2024	24	2026-07-05	Andrew E. Teschendorff	Nature Communications	https://doi.org/10.1038/s41467-024-48649-8	Pan-tissue mitotic counter that estimates cumulative stem-cell divisions (mitotic age) from progressive hypermethylation at a set of promoter/Polycomb-associated CpGs that are unmethylated in fetal tissue and gain methylation with cell division. Its mitotic-age proxy rises with tumor cell-of-origin fraction across cancer types, precancerous lesions, and normal tissues exposed to cancer risk factors.	0.95 quantile		True	By authors
stoch	methylation	Homo sapiens	chronological age	years	Sorted monocytes (MESA cohort); validated on whole blood and other sorted immune cells	Illumina 450K/EPIC	adults	Elastic net	353	2024	66	2026-07-05	Andrew E. Teschendorff	Nature Aging	https://doi.org/10.1038/s43587-024-00600-8	Stochastic counterpart of Horvath’s pan-tissue methylation clock, estimating age from a model in which age-associated CpGs accumulate methylation changes purely at random; used to show that roughly two-thirds to three-quarters of the original clock’s accuracy can be reproduced by stochastic drift alone.				By authors
stocp	methylation	Homo sapiens	PhenoAge (biological/phenotypic age) — stochastic simulation counterpart of Levine’s PhenoAge clock	years	sorted monocytes (MESA cohort), applied to whole blood	Illumina 450K	adults	Elastic net	513	2024	66	2026-07-05	Andrew E. Teschendorff	Nature Aging	https://doi.org/10.1038/s43587-024-00600-8	Stochastic counterpart of the PhenoAge phenotypic-age clock in whole blood, predicting age from randomly accumulating CpG methylation; a comparatively smaller share of PhenoAge’s accuracy is stochastically driven, implying a larger nonstochastic biological component.				By authors
stocz	methylation	Homo sapiens	chronological age	years	sorted monocytes (MESA, training/effect-size estimation); validated on sorted immune cells and whole blood	Illumina 450K	adults	Elastic net	514	2024	66	2026-07-05	Andrew E. Teschendorff	Nature Aging	https://doi.org/10.1038/s43587-024-00600-8	Stochastic counterpart of Zhang’s blood-based age clock, modeling CpG methylation as a purely random accumulation process; nearly all of the original clock’s chronological-age accuracy is recapitulated by this stochastic model.				By authors
thompson	methylation	Mus musculus	chronological age	months	multi-tissue (adipose, blood, kidney, liver, lung, muscle; plus cortex, heart, cerebellum, spleen)	Bisulfite sequencing	mice, postnatal to old age (full lifespan), multiple strains (C57BL/6, BALB/cByJ, dwarf/GHRKO models, Diversity Outbred, HMDP inbred strains)	Elastic net	582	2018	236	2026-07-05	Matteo Pellegrini	Aging	https://doi.org/10.18632/aging.101590	Multi-tissue DNA-methylation clock estimating chronological age across the full mouse lifespan, built with elastic-net regression on reduced-representation bisulfite sequencing data from roughly 1,200 samples spanning ten tissues and from post-natal to advanced-age mice. It tracks slowed epigenetic aging under caloric restriction and in long-lived dwarf mutants.				By authors
abec	methylation	Homo sapiens	chronological age	years	whole blood	Illumina EPIC	adults, 19-59 years (ABEC training set; related eABEC/cABEC clocks span 18-88 years)	Elastic net	1695	2020	21	2026-07-05	Jon Bohlin	BMC Genomics	https://doi.org/10.1186/s12864-020-07168-8	Whole-blood elastic-net clock (the Adult Blood-based EPIC Clock) that estimates chronological age from Illumina MethylationEPIC-array CpGs, trained on adult peripheral-blood DNA methylation spanning roughly two to six decades of age.				Not yet
adbahadosingh	methylation	Homo sapiens	late-onset Alzheimer’s disease status (case vs. control)	probability (0-1)	peripheral blood leukocytes (whole blood)	Illumina EPIC	elderly adults (late-onset AD, ~65+)	Neural network	4	2021	33	2026-07-05	Uppala Radhakrishna	PLoS ONE	https://doi.org/10.1371/journal.pone.0248375	Peripheral-blood leukocyte DNA-methylation classifier built with a deep neural network on EPIC-array CpGs that distinguishes late-onset Alzheimer’s disease cases from cognitively healthy controls, reaching near-perfect discrimination in a small case-control cohort.		sigmoid		Not yet
bocklandt	methylation	Homo sapiens	chronological age	years	saliva	Illumina 27K	adults (18-70 years)	LASSO	1	2011	1057	2026-07-05	Éric Vilain	PLoS ONE	https://doi.org/10.1371/journal.pone.0014821	One of the earliest epigenetic age predictors, estimating chronological age from saliva DNA methylation via linear regression on a small set of age-correlated CpGs (in EDARADD, TOM1L1, and NPTX2).				Not yet
bohlin	methylation	Homo sapiens	gestational age	weeks	cord blood (newborn)	Illumina 450K	newborns (fetal/gestational, at birth)	LASSO	251	2016	237	2026-07-05	Wenche Nystad	Genome biology	https://doi.org/10.1186/s13059-016-1063-4	Gestational-age predictor that estimates age in weeks from neonatal cord-blood DNA methylation, built with penalized regression over genome-wide differentially methylated regions.		days_to_weeks		Not yet
cabec	methylation	Homo sapiens	chronological age	years	whole blood	Illumina EPIC	adults (18-88 years)	Elastic net	1892	2020	21	2026-07-05	Jon Bohlin	BMC Genomics	https://doi.org/10.1186/s12864-020-07168-8	Whole-blood elastic-net clock (the common Adult Blood-based EPIC Clock) estimating chronological age, trained on EPIC-array DNA methylation but restricted to CpGs shared between the EPIC and 450K arrays for cross-platform compatibility.				Not yet
cellpopage	methylation	Homo sapiens	passage-based epigenetic age of a cell population in culture	cell passage number	adult primary human fibroblasts (mammary and dermal) in culture	Illumina EPIC	adult primary human cells in culture	Elastic net	2543	2024	6	2026-07-05	Ivana Bjedov	Genome Medicine	https://doi.org/10.1186/s13073-024-01349-w	DNA-methylation clock that tracks the passage-based, replicative age of cultured adult human primary cell populations from a compact set of CpGs, uniquely designed to detect deceleration of aging by candidate anti-aging compounds in vitro.				Not yet
compil6	methylation	Homo sapiens	serum interleukin-6 (IL-6) level (DNAm proxy)	score (arbitrary)	whole blood	Illumina 450K/EPIC	adults (trained in older adults, mean age ~70)	Elastic net	35	2021	55	2026-07-05	Riccardo E. Marioni	The Journals of Gerontology Series A	https://doi.org/10.1093/gerona/glab046	Blood DNA-methylation surrogate for circulating interleukin-6 built by elastic-net regression over 35 CpGs, providing a stable epigenetic proxy that captures chronic inflammatory burden better than a single serum measurement.				Not yet
corticalclock	methylation	Homo sapiens	chronological age	years	brain cortex (post-mortem human cortical tissue)	Illumina 450K/EPIC	humans, ages 1-108 years	Elastic net	347	2020	206	2026-07-05	Jonathan Mill	Brain	https://doi.org/10.1093/brain/awaa334	Human cortex-specific epigenetic age predictor trained by elastic-net regression on over a thousand post-mortem cortical samples, recalibrated to correct the systematic age underestimation that multi-tissue clocks show in brain tissue.		anti_log_linear	True	Not yet
ctsliver	methylation	Homo sapiens	chronological age (hepatocyte-specific)	years	liver (bulk liver tissue; 210 normal/healthy liver specimens)	Illumina EPIC	adults (18-75 years, mean ~47)	Reference-based deconvolution	90	2024	25	2026-07-05	Andrew E. Teschendorff	Aging	https://doi.org/10.18632/aging.206184	Liver cell-type-specific DNA-methylation age clock built with lasso regression on hepatocyte age-associated CpGs identified after reference-based cell-type deconvolution, detecting age acceleration in conditions such as NAFLD and obesity.				Not yet
cvdwesterman	methylation	Homo sapiens	incident cardiovascular disease (CVD) risk / time-to-event	score (arbitrary)	whole blood	Illumina 450K	adults (middle-aged/older; WHI, Framingham Offspring, Lothian Birth Cohorts)	Cox regression	235	2020	53	2026-07-05	José M. Ordovás	Journal of the American Heart Association	https://doi.org/10.1161/JAHA.119.015299	Blood DNA-methylation risk score for incident cardiovascular disease, trained as a cross-study ensemble of Cox proportional-hazards elastic-net models across multiple cohorts to predict CVD events independent of traditional risk factors.		sigmoid		Not yet
deconvolutebloodepicbcell	methylation	Homo sapiens	B cell proportion (cell-type fraction)	proportion (0-1)	whole blood (leukocyte reference)	Illumina EPIC	adults	Reference-based deconvolution	600	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based DNA-methylation deconvolution that estimates the proportion of B cells in whole blood from an EPIC-array leukocyte reference panel.	fill_with_reference_means		True	Not yet
deconvolutebloodepiccd4tcell	methylation	Homo sapiens	CD4+ T cell proportion	proportion (0-1)	whole blood (EPIC leukocyte reference panel)	Illumina EPIC	adults	Reference-based deconvolution	600	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based DNA-methylation deconvolution that estimates the proportion of CD4+ T cells in whole blood from an EPIC-array leukocyte reference panel.	fill_with_reference_means		True	Not yet
deconvolutebloodepiccd8tcell	methylation	Homo sapiens	CD8+ T cell proportion in blood	proportion (0-1)	whole blood (EPIC leukocyte reference panel)	Illumina EPIC	adults	Reference-based deconvolution	600	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based DNA-methylation deconvolution that estimates the proportion of CD8+ T cells in whole blood from an EPIC-array leukocyte reference panel.	fill_with_reference_means		True	Not yet
deconvolutebloodepicmonocyte	methylation	Homo sapiens	monocyte cell-type proportion in blood	proportion (0-1)	whole blood (leukocyte reference)	Illumina EPIC	adults	Reference-based deconvolution	600	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based DNA-methylation deconvolution that estimates the proportion of monocytes in whole blood from an EPIC-array leukocyte reference panel.	fill_with_reference_means		True	Not yet
deconvolutebloodepicneutrophil	methylation	Homo sapiens	neutrophil proportion (cell-type fraction)	proportion (0-1)	whole blood (purified-leukocyte EPIC reference)	Illumina EPIC	adults	Reference-based deconvolution	600	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based cell-type deconvolution that estimates the proportion of neutrophils in whole blood from methylation at cell-type-discriminating CpGs, using a purified-leukocyte EPIC reference panel. Reports a leukocyte composition fraction rather than an age value.	fill_with_reference_means		True	Not yet
deconvolutebloodepicnkcell	methylation	Homo sapiens	natural killer (NK) cell proportion	proportion (0-1)	whole blood (purified-leukocyte EPIC reference)	Illumina EPIC	adults (whole blood)	Reference-based deconvolution	600	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based cell-type deconvolution that estimates the proportion of natural killer (NK) cells in whole blood from methylation at cell-type-discriminating CpGs, using a purified-leukocyte EPIC reference panel. Reports a leukocyte composition fraction rather than an age value.	fill_with_reference_means		True	Not yet
depressionbarbu	methylation	Homo sapiens	major depressive disorder (MDD) status/risk	score (arbitrary)	whole blood	Illumina EPIC	adults (Generation Scotland cohort)	Elastic net	196	2021	93	2026-07-05	Andrew M. McIntosh	Molecular Psychiatry	https://doi.org/10.1038/s41380-020-0808-3	Blood methylation risk score for major depressive disorder built with penalised regression on genome-wide EPIC-array CpGs, trained on over 1,200 cases and 1,800 controls. Discriminates prevalent from incident MDD independently of polygenic risk, with a smoking-independent variant also derived.				Not yet
dnamfili	methylation	Homo sapiens	frailty risk (frailty index, prevalent and incident frailty)	score (arbitrary)	whole blood (peripheral blood)	Illumina 450K/EPIC	older adults, aged 50-75 years (ESTHER); validated in KORA-Age, age >=65	LASSO	20	2022	22	2026-07-05	Hermann Brenner	Nature Communications	https://doi.org/10.1038/s41467-022-32893-x	Blood epigenetic frailty risk score predicting a deficit-accumulation frailty index, derived by LASSO regression that selects 20 CpGs from frailty-associated methylation loci in a population-based older-adult cohort. Predicts both prevalent frailty and its incidence over up to five years of follow-up.				Not yet
dnamfitage	methylation	Homo sapiens	biological age incorporating physical fitness (composite of DNAmGrimAge and DNAm fitness biomarkers: gait speed, grip strength, VO2max)	years	whole blood	Illumina 450K	adults (validation ages ~21-100)	LASSO	630	2023	99	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204538	Composite biological-age indicator from blood DNA methylation that integrates methylation-based estimates of physical fitness (grip strength, gait speed, VO2max) with the GrimAge mortality estimator via a Klemera-Doubal framework, built separately for each sex. Its age acceleration is associated with mortality and coronary heart disease.			True	Not yet
dnamfitagegaitf	methylation	Homo sapiens	gait (walking) speed, female-specific	gait speed (m/s)	whole blood	Illumina 450K	adult females (validation ages ~21-100)	LASSO	53	2023	99	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204538	Blood DNA-methylation estimator of walking (gait) speed built with LASSO penalised regression, trained as a sex-specific model for females and used as a fitness component of DNAmFitAge.			True	Not yet
dnamfitagegaitm	methylation	Homo sapiens	gait (walking) speed, male-specific	gait speed (m/s)	whole blood	Illumina 450K	adult males, middle-aged to elderly	LASSO	59	2023	99	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204538	Blood DNA-methylation estimator of walking (gait) speed built with LASSO penalised regression, trained as a sex-specific model for males and used as a fitness component of DNAmFitAge.			True	Not yet
dnamfitagegripf	methylation	Homo sapiens	maximal handgrip strength (female-specific)	kilograms	whole blood	Illumina 450K	adult women (~21-100 years)	LASSO	91	2023	99	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204538	Blood DNA-methylation estimator of maximum handgrip strength built with LASSO penalised regression, trained as a sex-specific model for females and used as a fitness component of DNAmFitAge.			True	Not yet
dnamfitagegripm	methylation	Homo sapiens	maximum handgrip strength (males)	kilograms	whole blood	Illumina 450K	adult males (~21-100 years)	LASSO	93	2023	99	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204538	Blood DNA-methylation estimator of maximum handgrip strength built with LASSO penalised regression, trained as a sex-specific model for males and used as a fitness component of DNAmFitAge.			True	Not yet
dnamfitagevo2max	methylation	Homo sapiens	VO2max (maximal oxygen uptake / cardiorespiratory fitness)	kilograms	whole blood	Illumina 450K	adults (validation age ~21-100 years, both sexes)	LASSO	41	2023	99	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204538	Blood DNA-methylation estimator of maximal oxygen uptake (VO2max) built with LASSO penalised regression across both sexes, incorporating X-chromosome CpGs to capture sex differences, and used as a cardiorespiratory-fitness component of DNAmFitAge.			True	Not yet
dnamic	methylation	Homo sapiens	intrinsic capacity (IC) composite score (mobility, cognition, psychological, sensory, vitality)	score (arbitrary)	whole blood	Illumina EPIC	adults (20-102 years, INSPIRE-T cohort)	Elastic net	91	2025	34	2026-07-05	David Furman	Nature Aging	https://doi.org/10.1038/s43587-025-00883-5	Blood DNA-methylation clock for intrinsic capacity, trained with penalised regression against a clinical composite of the five WHO domains (cognition, locomotion, psychological well-being, sensory function and vitality) in a cohort spanning ages 20-102. Outperforms first- and second-generation clocks at predicting all-cause mortality and tracks immune and inflammatory decline.				Not yet
dnamphenoage	methylation	Homo sapiens	phenotypic age (mortality/healthspan risk composite)	years	whole blood	Illumina 27K/450K/EPIC	adults (21-100 years)	Elastic net	513	2018	3594	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632%2Faging.101414	Blood DNA-methylation clock trained by elastic-net regression on 513 CpGs to predict a phenotypic age composite derived from chronological age and nine clinical blood biomarkers. This second-generation predictor captures mortality and healthspan-related risk beyond chronological age.				Not yet
dnamstress	methylation	Homo sapiens	stress exposure (composite/cumulative stress score, “MS_stress”)	score (arbitrary)	whole blood	Illumina 450K/EPIC	adults (alcohol use disorder patients and controls, n=615; replicated in Generation Scotland and Grady Trauma Project cohorts)	Elastic net	211	2023	27	2026-07-05	Falk W. Lohoff	Biological Psychiatry	https://doi.org/10.1016/j.biopsych.2022.06.036	Blood methylation score of cumulative stress comprising 211 CpGs selected by penalised regression as a proxy for a composite of stress-related exposures. Associates with accelerated epigenetic aging, shortened methylation-based telomere length and cardiovascular disease.				Not yet
dnamtl	methylation	Homo sapiens	leukocyte telomere length	kilobases	whole blood (leukocytes)	Illumina 450K/EPIC	adults (22-93 years), multi-ancestry; generalizes to children	Elastic net	140	2019	461	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.102173	Estimator of leukocyte telomere length built with an elastic-net model over roughly 140 blood DNA-methylation CpGs; the resulting DNAmTL tracks chronological age and mortality more strongly than directly measured telomere length and largely reflects cumulative replicative history.				Not yet
downsyndrome	methylation	Homo sapiens	Down syndrome (trisomy 21) status vs euploid controls	score (arbitrary)	neonatal dried blood spots (newborn whole blood)	Illumina EPIC	newborns/neonates (pediatric)	Weighted average of CpGs	652	2021	62	2026-07-05	Adam J. de Smith	Nature Communications	https://doi.org/10.1038/s41467-021-21064-z	Blood DNA-methylation classifier that distinguishes individuals with Down syndrome (trisomy 21) from euploid controls using trisomy-associated differentially methylated CpGs identified from neonatal blood, with top signals at hematopoietic regulators such as RUNX1 and FLI1.				Not yet
dunedinpoam38	methylation	Homo sapiens	pace of aging (rate of biological aging)	years	whole blood	Illumina 450K/EPIC	adults (developed at age 38; validated ages 18-95)	Elastic net	46	2020	666	2026-07-05	Terrie E. Moffitt	eLife	https://doi.org/10.7554/eLife.54870	Whole-blood elastic-net estimator (46 CpGs) of the pace of biological aging, trained on a longitudinal Pace-of-Aging score computed from 18 organ-system biomarkers tracked to age 38 in the Dunedin cohort, quantifying how fast aging is proceeding rather than age attained.				Not yet
eabec	methylation	Homo sapiens	chronological age	years	whole blood	Illumina EPIC	adults (ages 18-88)	Elastic net	1791	2020	21	2026-07-05	Jon Bohlin	BMC Genomics	https://doi.org/10.1186/s12864-020-07168-8	Blood elastic-net estimator of chronological age optimized for the Illumina MethylationEPIC array, trained on a European-ancestry adult cohort spanning ages 18 to 88.				Not yet
encen100	methylation	Homo sapiens	chronological age	years	whole blood (majority, ~95%); some saliva/buccal	Illumina 450K/EPIC	centenarians (100-115 years); recommended for supercentenarians (110+)	Elastic net	198	2023	45	2026-07-05	Steve Horvath	GeroScience	https://doi.org/10.1007/s11357-023-00731-7	Blood elastic-net clock estimating chronological age whose training set includes centenarians (age 100+), calibrating age estimates at extreme old age; developed to validate claims of exceptional longevity and most useful for supercentenarians.				Not yet
encen40	methylation	Homo sapiens	chronological age	years	whole blood (predominantly; small amounts of saliva/buccal)	Illumina 450K/EPIC	adults aged 40 and older (40-115 years)	Elastic net	559	2023	45	2026-07-05	Steve Horvath	GeroScience	https://doi.org/10.1007/s11357-023-00731-7	Blood elastic-net clock estimating chronological age trained on individuals aged 40 and older (up to 115 years), one of a set of centenarian clocks developed to validate claims of exceptional longevity across blood, saliva, and buccal samples.				Not yet
ensembleagehumanmouse	methylation	Homo sapiens	chronological age (cross-species)	years	multi-tissue (mouse and human; blood and multiple organs)	Mammalian methylation array	pan-age, cross-species (human and mouse)	ensemble	2252	2025	3	2026-07-05	Steve Horvath	GeroScience	https://doi.org/10.1007/s11357-025-01808-1	Cross-species ensemble epigenetic clock that aggregates predictions from multiple penalized DNA-methylation models to robustly estimate age across both human and mouse samples, enabling translational comparison of aging and rejuvenation interventions.				Not yet
ensembleagestatic	methylation	Mus musculus	epigenetic age (biological age)	years	multi-tissue (mouse; diverse tissues across 200+ perturbation experiments, MethylGauge dataset)	Mammalian methylation array	mice (pan-tissue, across lifespan)	Elastic net	288	2025	3	2026-07-05	Steve Horvath	GeroScience	https://doi.org/10.1007/s11357-025-01808-1	Mouse ensemble epigenetic clock that combines multiple penalized DNA-methylation models into a single static age estimate spanning diverse tissues, designed for robust detection of pro-aging and rejuvenating interventions.				Not yet
ensembleagestatictop	methylation	Mus musculus	Recalibrated, intervention-responsive epigenetic (biological) age (an ensemble-optimized age estimate selected to maximize sensitivity to pro-aging/rejuvenating interventions; not raw chronological…	years	Multi-tissue mouse (MethylGauge perturbation dataset: 211 controlled perturbation experiments across blood, liver, brain, and other tissues)	Mammalian methylation array	mice (Mus musculus), across lifespan, wild-type and intervention/perturbed animals from 211 perturbation experiments	Elastic net	431	2025	3	2026-07-05	Steve Horvath	GeroScience	https://doi.org/10.1007/s11357-025-01808-1	Variant of the mouse EnsembleAge static clock restricted to its top-performing constituent models, aggregating multiple penalized DNA-methylation predictors for robust chronological-age estimation across tissues.				Not yet
epicga	methylation	Homo sapiens	gestational age	days	cord blood (umbilical cord blood at birth)	Illumina EPIC	newborns (fetal/newborn gestational age)	LASSO	176	2021	54	2026-07-05	Jon Bohlin	Clinical Epigenetics	https://doi.org/10.1186/s13148-021-01055-z	Elastic-net predictor of gestational age (in weeks) from neonatal blood-spot DNA methylation on the Illumina MethylationEPIC array, developed and evaluated including in newborns conceived by assisted reproductive technologies.		days_to_weeks		Not yet
epicmithyper	methylation	Homo sapiens	cumulative mitotic (cell-division) / proliferative history (epiCMIT hypermethylation component)	score (arbitrary)	B cells (normal B-cell subpopulations and neoplastic B-cell tumors spanning the B-cell lineage)	Illumina 450K/EPIC	pan-age; normal and neoplastic B cells across the human B-cell developmental lineage (pediatric to adult tumor cohorts)	Mitotic model	184	2020	104	2026-07-05	José I. Martı́n-Subero	Nature Cancer	https://doi.org/10.1038/s43018-020-00131-2	Hypermethylation-based component of the epiCMIT mitotic clock, approximating the cumulative proliferative (mitotic) history of normal and neoplastic B cells from methylation gains at Polycomb/H3K27me3-marked regions, with independent prognostic value in B-cell tumors.	mean		True	Not yet
epicmithypo	methylation	Homo sapiens	mitotic age / cumulative proliferative history (hypomethylation component)	score (arbitrary)	B cells / B-cell tumors (normal B-cell subpopulations and neoplasms: ALL, MCL, DLBCL, CLL, MM)	Illumina 450K/EPIC	B-cell tumor patients and normal B cells (human)	Mitotic model	1164	2020	104	2026-07-05	José I. Martı́n-Subero	Nature Cancer	https://doi.org/10.1038/s43018-020-00131-2	Hypomethylation-based component of the epiCMIT mitotic clock, tracking the cumulative mitotic history of B cells from progressive loss of DNA methylation in heterochromatin and serving as an independent prognostic marker in B-cell malignancies.	mean		True	Not yet
epitoc1	methylation	Homo sapiens	Mitotic (stem-cell division) age / cumulative stem-cell divisions in a tissue, correlated with cancer risk	score (arbitrary)	Whole blood (age-hypermethylation trained in blood); the 385 PCGT/PRC2-marked promoter CpGs were selected as constitutively unmethylated across 37 fetal tissue samples from 12 tissue types	Illumina 450K	Adults (pan-tissue applicability, including cancer/precancerous tissue)	Mitotic model	385	2016	357	2026-07-05	Andrew E. Teschendorff	Genome biology	https://doi.org/10.1186/s13059-016-1064-3	Epigenetic mitotic-like clock (“Epigenetic Timer of Cancer”) that approximates the cumulative number of stem-cell divisions in a tissue from age-associated hypermethylation at 385 Polycomb-group-target promoter CpGs that are unmethylated across fetal tissues. Its tick rate tracks estimated stem-cell division rates and is universally accelerated in cancer and pre-cancerous lesions.	mean		True	Not yet
epitoc2	methylation	Homo sapiens	mitotic age (cumulative stem-cell divisions)	cell divisions	whole blood (calibrated on 456/656 450K blood samples; CpGs selected as unmethylated across fetal tissues; applicable pan-tissue)	Illumina 450K/EPIC	adults (pan-tissue; healthy and pre-cancer/cancer samples)	dynamic DNAm transmission model	163	2020	155	2026-07-05	Andrew E. Teschendorff	Genome Medicine	https://doi.org/10.1186/s13073-020-00752-3	Epigenetic mitotic-like clock that directly estimates the lifetime cumulative number of stem-cell divisions in a tissue from cumulative hypermethylation at a subset of PRC2/Polycomb-target CpGs. Its intrinsic per-tissue division-rate estimates closely match experimentally derived rates and are accelerated in cancer, making it a mitotic-age and cancer-risk predictor.	nan_to_zero		True	Not yet
epitoc3	methylation	Homo sapiens	Mitotic age: total number of stem-cell divisions per stem cell (TNSC), and, when normalized by chronological age, the intrinsic stem-cell division rate (IR) of a tissue — used as a…	years	Whole blood (656 Hannum samples used for parameter calibration); validated across multiple normal adult tissue types and TCGA cancers; fetal/cord-blood samples used only to select…	Illumina 450K/EPIC	Adults, pan-tissue (parameters calibrated in adult whole blood, applied across normal adult tissues and cancers)	Mitotic model	170	2020	155	2026-07-05	Andrew E. Teschendorff	Genome Medicine	https://doi.org/10.1186/s13073-020-00752-3	Epigenetic mitotic-like clock estimating the cumulative number of stem-cell divisions in a tissue from hypermethylation at Polycomb/PRC2-target CpGs, a variant formulation of the EpiTOC2 mitotic-age estimator developed for cancer-risk prediction from tissue and blood methylation.	nan_to_zero		True	Not yet
garagnani	methylation	Homo sapiens	chronological age	years	whole blood	Illumina 450K	pan-age (cord blood/newborn to 99 years)	Linear regression	1	2012	500	2026-07-05	Claudio Franceschi	Aging Cell	https://doi.org/10.1111/acel.12005	Whole-blood single-locus epigenetic age marker based on methylation of the ELOVL2 gene CpG island, whose methylation increases progressively from early life and correlates strongly with chronological age (Spearman correlation ~0.92).				Not yet
gliasin	methylation	Homo sapiens	chronological age (glia-specific)	years	brain prefrontal cortex (bulk)	Illumina 450K	adults (18-97 years)	Elastic net	220	2024	25	2026-07-05	Andrew E. Teschendorff	Aging	https://doi.org/10.18632/aging.206184	Glia-specific DNA-methylation age clock for human brain (prefrontal cortex), built by estimating glial cell-type fractions, identifying glia-specific age-associated CpGs via cell-type deconvolution, and fitting an elastic-net model on cell-type-unadjusted (“semi-intrinsic”) methylation values; it shows pronounced epigenetic age acceleration in Alzheimer’s disease.				Not yet
grimage	methylation	Homo sapiens	mortality/time-to-death risk (lifespan & healthspan)	years	whole blood (peripheral blood leukocytes; Framingham Heart Study Offspring Cohort)	Illumina 450K/EPIC	adults (middle-aged to elderly, mean age ~66)	Cox regression	1032	2019	2610	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.101684	Blood DNA-methylation composite predictor of lifespan and healthspan, trained with Cox regression on DNAm surrogate estimators of seven plasma proteins (ADM, B2M, cystatin C, GDF-15, leptin, PAI-1, TIMP-1) and a DNAm estimator of smoking pack-years, and calibrated to units of years to strongly predict time-to-death.		cox_to_years	True	Not yet
grimage2	methylation	Homo sapiens	mortality/time-to-death risk (all-cause)	years	whole blood	Illumina 450K/EPIC	adults (training ages 40-92; applied to broader ages)	Cox regression	1032	2022	291	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204434	Updated blood DNA-methylation mortality predictor that augments the original surrogate panel with DNAm estimators of C-reactive protein and hemoglobin A1c, trained via Cox regression to predict lifespan and healthspan in units of years with improved association to age-related disease.		cox_to_years	True	Not yet
grimage2adm	methylation	Homo sapiens	mortality/time-to-death risk (calibrated to age)	years	whole blood	Illumina 450K	adults (trained age 40-92; applicable to ages 22+)	Cox regression	187	2022	291	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204434	Blood DNA-methylation surrogate estimator of plasma adrenomedullin (ADM), a peptide involved in cardiovascular and blood-pressure regulation, trained by penalized regression as a component biomarker of the GrimAge2 mortality clock.		cox_to_years	True	Not yet
grimage2b2m	methylation	Homo sapiens	plasma beta-2-microglobulin (B2M) protein level (DNAm surrogate biomarker, GrimAge2 component)	protein level (surrogate)	whole blood	Illumina 450K	adults (Framingham Heart Study, ~40-92 years)	Elastic net	92	2022	291	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204434	Blood DNA-methylation surrogate estimator of plasma beta-2-microglobulin (B2M), a marker of kidney function and immune activation, trained by penalized regression as a component biomarker of the GrimAge2 mortality clock.		cox_to_years	True	Not yet
grimage2cystatinc	methylation	Homo sapiens	DNAm surrogate for plasma cystatin C level (kidney function marker), used as a component of GrimAge2	protein level (surrogate)	whole blood	Illumina 450K	adults (Framingham Heart Study Offspring Cohort, ages 40-92 years)	Cox regression	88	2022	291	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204434	Blood DNA-methylation surrogate estimator of plasma cystatin C, a renal-function marker, trained by penalized regression as a component biomarker of the GrimAge2 mortality clock.		cox_to_years	True	Not yet
grimage2gdf15	methylation	Homo sapiens	plasma GDF15 (growth differentiation factor 15) protein level (surrogate biomarker component of GrimAge2)	protein level (surrogate)	whole blood (Framingham Offspring)	Illumina 450K	adults (aged ~40-92)	Elastic net	138	2022	291	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204434	Blood DNA-methylation surrogate estimator of plasma growth differentiation factor 15 (GDF-15), a marker of cellular stress and inflammation, trained by penalized regression as a component biomarker of the GrimAge2 mortality clock.		cox_to_years	True	Not yet
grimage2leptin	methylation	Homo sapiens	DNAm surrogate of plasma leptin (component biomarker of GrimAge2 mortality clock)	protein level (surrogate)	whole blood (Framingham Heart Study Offspring cohort)	Illumina 450K	adults (~40-92 years)	Elastic net	187	2022	291	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204434	Blood DNA-methylation surrogate estimator of plasma leptin, an adipokine regulating appetite and energy balance, trained by penalized regression as a component biomarker of the GrimAge2 mortality clock.		cox_to_years	True	Not yet
grimage2loga1c	methylation	Homo sapiens	DNAm surrogate of log HbA1c (glycated hemoglobin)	proportion (0-1)	whole blood	Illumina 450K/EPIC	adults (~40-92 years)	Elastic net	87	2022	291	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204434	Blood DNA-methylation surrogate estimator of log hemoglobin A1c, reflecting long-term blood-glucose exposure and diabetes risk, newly added and trained by penalized regression as a component biomarker of the GrimAge2 mortality clock.		cox_to_years	True	Not yet
grimage2logcrp	methylation	Homo sapiens	DNAm surrogate for log C-reactive protein (CRP)	log CRP (mg/L)	whole blood	Illumina 450K	adults (ages 40-92, Framingham)	Elastic net	132	2022	291	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204434	Blood DNA-methylation elastic-net surrogate estimating log-transformed C-reactive protein, an inflammation marker. It is one of the DNAm biomarker components of the mortality-predictive GrimAge version 2 composite.		cox_to_years	True	Not yet
grimage2packyrs	methylation	Homo sapiens	smoking pack-years (DNAm surrogate)	years	whole blood (Framingham Heart Study Offspring Cohort)	Illumina 450K	adults (aged 40-92 in training)	Elastic net	173	2022	291	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204434	Blood DNA-methylation elastic-net surrogate estimating lifetime smoking exposure in pack-years. It serves as a component of the mortality-predictive GrimAge version 2 composite.		cox_to_years	True	Not yet
grimage2pai1	methylation	Homo sapiens	DNAm surrogate of plasma PAI-1 (plasminogen activator inhibitor-1) protein	protein level (surrogate)	whole blood	Illumina 450K/EPIC	Adults (Framingham Heart Study Offspring), ages ~40-92	Elastic net	211	2022	291	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204434	Blood DNA-methylation elastic-net surrogate estimating plasma plasminogen activator inhibitor-1 (PAI-1), a marker linked to triglycerides and visceral adiposity. It is one of the DNAm biomarker components of the GrimAge version 2 mortality predictor.			True	Not yet
grimage2timp1	methylation	Homo sapiens	DNAm surrogate of plasma TIMP-1 (tissue inhibitor of metalloproteinases 1) protein level	protein level (surrogate)	whole blood	Illumina 450K	adults (aged 40-92, mean ~66)	Elastic net	43	2022	291	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632/aging.204434	Blood DNA-methylation elastic-net surrogate estimating plasma tissue inhibitor of metalloproteinases-1 (TIMP-1). It is one of the DNAm biomarker components of the mortality-predictive GrimAge version 2 composite.		cox_to_years	True	Not yet
hannum	methylation	Homo sapiens	chronological age	years	whole blood	Illumina 450K	adults (19-101 years)	Elastic net	71	2013	4501	2026-07-05	Kang Zhang	Molecular Cell	https://doi.org/10.1016/j.molcel.2012.10.016	Whole-blood elastic-net clock estimating chronological age from 71 CpGs, derived from genome-wide methylation profiles of several hundred adults.				Not yet
hep	methylation	Homo sapiens	chronological age	years	liver (hepatocyte-specific, trained on bulk liver tissue)	Illumina EPIC	adults (18-75 years)	LASSO	70	2024	25	2026-07-05	Andrew E. Teschendorff	Aging	https://doi.org/10.18632/aging.206184	Hepatocyte-specific DNA-methylation clock estimating chronological age within the hepatocyte compartment of liver tissue, built by LASSO regression on cell-type-specific age-associated CpGs identified through cell-type deconvolution. It detects age acceleration in liver pathologies such as NAFLD and obesity that bulk-tissue clocks miss.				Not yet
hepatoxu	methylation	Homo sapiens	hepatocellular carcinoma diagnosis (disease presence/status) and prognosis	probability (0-1)	plasma cell-free DNA (ctDNA); methylation markers derived from HCC tumor tissue vs normal blood leukocytes	Bisulfite sequencing	adults (HCC patients, n=1,098, and normal/at-risk controls, n=835)	Logistic regression	10	2017	884	2026-07-05	Kang Zhang	Nature Materials	https://doi.org/10.1038/nmat4997	Blood plasma circulating tumour-DNA methylation marker panel that discriminates hepatocellular carcinoma from healthy controls and predicts tumour burden, stage, and prognosis, developed as a non-invasive liquid-biopsy diagnostic and prognostic model.				Not yet
horvath2013	methylation	Homo sapiens	chronological age (DNAm age)	years	multi-tissue (51 human tissues/cell types)	Illumina 27K/450K	pan-age (newborns to ~101 years)	Elastic net	353	2013	7318	2026-07-05	Steve Horvath	Genome biology	https://doi.org/10.1186/gb-2013-14-10-r115	Pan-tissue DNA-methylation clock estimating chronological age from 353 CpGs using penalized regression, applicable across a broad range of human tissues and cell types.		anti_log_linear	True	Not yet
hrsinchphenoage	methylation	Homo sapiens	phenotypic (biological) age	years	whole blood	Illumina 450K/EPIC	adults	PCA + elastic net	959	2022	497	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-022-00248-2	Principal-component (PC) reconstruction of the PhenoAge biological-age clock that summarizes CpGs into principal components before penalized regression, greatly improving test-retest reliability while retaining the mortality- and morbidity-related phenotypic-age signal.				Not yet
hypoclock	methylation	Homo sapiens	Mitotic age (cumulative stem-cell divisions / mitotic history, via PMD hypomethylation)	score (arbitrary)	Multi-tissue (WGBS of normal human/mouse tissues and primary tumors)	Illumina 450K/EPIC	Human tissues, normal and cancer, spanning fetal to adult (mitotic, not chronological, age)	Mitotic model	678	2018	452	2026-07-05	Benjamin P. Berman	Nature Genetics	https://doi.org/10.1038/s41588-018-0073-4	Mitotic clock approximating cumulative stem-cell divisions from progressive hypomethylation at solo-WCGW CpGs located in late-replicating, partially methylated domains.	mean	one_minus	True	Not yet
intrinclock	methylation	Homo sapiens	chronological age	years	multi-tissue (majority whole blood; also saliva, brain, skin, skeletal muscle)	Illumina 450K/EPIC	pan-age (neonates to 81+ years)	Elastic net	380	2024	53	2026-07-05	Eric Verdin	Communications Biology	https://doi.org/10.1038/s42003-024-06609-4	Blood/multi-tissue elastic-net clock estimating chronological age from 381 CpGs, designed so that predicted age is unchanged across immune cell types, isolating cell-intrinsic aging from age-related shifts in immune cell composition.		anti_log_linear		Not yet
lin	methylation	Homo sapiens	chronological age (Δage indicative of mortality/life expectancy)	years	whole blood	Illumina 27K/450K	adults (age 19-101)	Linear regression	99	2016	256	2026-07-05	Wolfgang Wagner	Aging	https://doi.org/10.18632/aging.100908	Blood DNA-methylation age predictor built by penalized multivariate regression on 99 age-associated CpGs, where a higher predicted age relative to chronological age is associated with increased mortality risk and shorter life expectancy.				Not yet
mammalian1	methylation	multi	chronological age	years	multi-tissue (pan-mammalian, ~59 tissue types)	Mammalian methylation array	pan-mammalian (185 species, prenatal to ~139 years)	Elastic net	335	2023	390	2026-07-05	Steve Horvath	Nature Aging	https://doi.org/10.1038/s43587-023-00462-6	Pan-mammalian DNA-methylation clock estimating chronological age in years, built by elastic-net regression on conserved CpGs and applicable across diverse species and tissues with a single formula.		anti_logp2		Not yet
mammalian2	methylation	multi	relative age (age relative to species maximum lifespan)	proportion (0-1)	multi-tissue (59 tissue types across mammals)	Mammalian methylation array	pan-mammalian, pan-age (185 species, prenatal to ~139 years)	Elastic net	2572	2023	390	2026-07-05	Steve Horvath	Nature Aging	https://doi.org/10.1038/s43587-023-00462-6	Pan-mammalian clock estimating relative age as the ratio of age to species maximum lifespan (scaled 0-1) via elastic-net regression, enabling biologically meaningful age comparisons across species with very different lifespans.		mammalian2	True	Not yet
mammalian3	methylation	multi	Chronological age (log-linear transformed age, combining relative age and gestational time, back-transformed to age scale)	years	Multi-tissue (59 tissue types across 185 mammalian species; blood, skin, liver, brain, muscle, etc.)	Mammalian methylation array	pan-mammalian (multi-species, all ages/life stages, 185 species)	Elastic net	2467	2023	390	2026-07-05	Steve Horvath	Nature Aging	https://doi.org/10.1038/s43587-023-00462-6	Pan-mammalian clock estimating a log-linear transformed age via elastic-net regression, substituting species maximum lifespan with age at sexual maturity and gestation time to allow cross-species comparison.		mammalian3	True	Not yet
mammalianblood2	methylation	multi	relative age (ratio of chronological age to species maximum lifespan)	proportion (0-1)	blood (whole blood)	Mammalian methylation array	multi-species mammals (pan-mammalian, blood; prenatal to ~139 years across species)	Elastic net	2257	2023	390	2026-07-05	Steve Horvath	Nature Aging	https://doi.org/10.1038/s43587-023-00462-6	Blood-focused pan-mammalian clock estimating relative age (ratio of age to species maximum lifespan) from conserved CpGs by elastic-net regression.		mammalian2	True	Not yet
mammalianblood3	methylation	multi	chronological age (log-linear transformed / relative age formulation, Clock 3)	years	blood	Mammalian methylation array	multi-species mammals (eutherians), pan-age	Elastic net	2097	2023	390	2026-07-05	Steve Horvath	Nature Aging	https://doi.org/10.1038/s43587-023-00462-6	Blood-focused pan-mammalian clock estimating log-linear transformed age from conserved CpGs by elastic-net regression, incorporating species age at sexual maturity and gestation time.		mammalian3	True	Not yet
mammalianfemale	methylation	multi	sex (probability that the sample is female)	probability (0-1)	multi-tissue (pan-mammalian; ~15,000 samples across 348 mammalian species, 59 tissue types)	Mammalian methylation array	pan-mammalian (multiple mammalian species, all ages)	Elastic net	101	2023	5	2026-07-05	Steve Horvath	bioRxiv (Cold Spring Harbor Laboratory)	https://doi.org/10.1101/2023.11.02.565286	Pan-mammalian DNA-methylation classifier estimating the probability that a sample is from a female, derived from CpGs conserved across mammalian species.		sigmoid		Not yet
mammalianlifespan	methylation	multi	species maximum lifespan	years	multi-tissue (tissue-agnostic; blood, skin, liver, brain, etc. across mammals)	Mammalian methylation array	pan-mammalian, species-level (348 mammalian species, ~15,000 samples across ~25 taxonomic orders)	Elastic net	152	2023	5	2026-07-05	Steve Horvath	bioRxiv (Cold Spring Harbor Laboratory)	https://doi.org/10.1101/2023.11.02.565286	Pan-mammalian predictor of species maximum lifespan from DNA methylation, built as a tissue-aware multivariate predictor using species- and tissue-averaged methylation across hundreds of mammals.		anti_log	True	Not yet
mammalianskin2	methylation	multi	relative age (chronological age / species maximum lifespan)	proportion (0-1)	skin (pan-mammalian skin samples)	Mammalian methylation array	pan-mammalian (skin), all ages/species; prenatal to ~139 years	Elastic net	2240	2023	390	2026-07-05	Steve Horvath	Nature Aging	https://doi.org/10.1038/s43587-023-00462-6	Skin-focused pan-mammalian clock estimating relative age (ratio of age to species maximum lifespan) from conserved CpGs by elastic-net regression.		mammalian2	True	Not yet
mammalianskin3	methylation	multi	chronological age (via log-linear transform relative to species age at sexual maturity and gestation time; “Universal Clock 3”)	years	skin (multi-species mammalian)	Mammalian methylation array	pan-mammalian (185 species, skin tissue), all ages	Elastic net	2055	2023	390	2026-07-05	Steve Horvath	Nature Aging	https://doi.org/10.1038/s43587-023-00462-6	Skin-focused pan-mammalian clock estimating log-linear transformed age from conserved CpGs by elastic-net regression, incorporating species age at sexual maturity and gestation time.		mammalian3	True	Not yet
mayne	methylation	Homo sapiens	gestational age	weeks	placenta (healthy singleton pregnancies)	Illumina 27K/450K	fetal/gestational (placental samples across pregnancy)	Elastic net	62	2017	150	2026-07-05	Tina Bianco‐Miotto	Epigenomics	https://doi.org/10.2217/epi-2016-0103	Placental DNA-methylation estimator of gestational age built from 62 CpG sites using penalized regression across pooled human placenta array datasets. Placentas from early-onset preeclampsia pregnancies show accelerated aging, with predicted gestational age exceeding chronological gestational age.				Not yet
mccartneyalcohol	methylation	Homo sapiens	alcohol consumption	weeks	whole blood	Illumina 450K	adults (Generation Scotland cohort, n=5087)	Elastic net	450	2018	301	2026-07-05	Riccardo E. Marioni	Genome biology	https://doi.org/10.1186/s13059-018-1514-1	Blood DNA-methylation LASSO predictor of alcohol consumption, one of ten lifestyle and health scores trained on Illumina array data in the large Generation Scotland cohort and tested out-of-sample. Alcohol was among the scores associated with all-cause mortality.				Not yet
mccartneybmi	methylation	Homo sapiens	body mass index (BMI)	kilograms	whole blood	Illumina 450K	adults (Generation Scotland cohort, discovery; Lothian Birth Cohort 1936 replication)	LASSO	1109	2018	301	2026-07-05	Riccardo E. Marioni	Genome biology	https://doi.org/10.1186/s13059-018-1514-1	Blood DNA-methylation LASSO predictor of body mass index, one of ten modifiable lifestyle and health traits modeled from array methylation in the Generation Scotland cohort.		sigmoid		Not yet
mccartneybodyfat	methylation	Homo sapiens	body fat percentage	proportion (0-1)	whole blood	Illumina 450K/EPIC	adults (Generation Scotland/STRADL, aged 18-99 years, mean ~48.5)	LASSO	968	2018	301	2026-07-05	Riccardo E. Marioni	Genome biology	https://doi.org/10.1186/s13059-018-1514-1	Blood DNA-methylation LASSO predictor of body fat percentage, part of a panel of ten lifestyle and health scores trained on array methylation in the Generation Scotland cohort.		sigmoid		Not yet
mccartneyeducation	methylation	Homo sapiens	educational attainment	score (arbitrary)	whole blood	Illumina 450K	adults	Elastic net	373	2018	301	2026-07-05	Riccardo E. Marioni	Genome biology	https://doi.org/10.1186/s13059-018-1514-1	Blood DNA-methylation LASSO predictor of educational attainment, one of ten lifestyle and health scores trained on array methylation in the Generation Scotland cohort. Educational attainment was among the scores that predicted all-cause mortality.		sigmoid		Not yet
mccartneyhdlcholesterol	methylation	Homo sapiens	HDL cholesterol level	mmol/L	whole blood	Illumina 450K	adults (18-99 years)	Elastic net	737	2018	301	2026-07-05	Riccardo E. Marioni	Genome biology	https://doi.org/10.1186/s13059-018-1514-1	Blood DNA-methylation LASSO predictor of HDL cholesterol, one of ten modifiable lifestyle and health traits modeled from array methylation in the Generation Scotland cohort.		sigmoid		Not yet
mccartneyldlcholesterol	methylation	Homo sapiens	LDL (with remnant) cholesterol level	score (arbitrary)	whole blood	Illumina 450K	adults (Generation Scotland cohort)	Elastic net	233	2018	301	2026-07-05	Riccardo E. Marioni	Genome biology	https://doi.org/10.1186/s13059-018-1514-1	Blood DNA-methylation LASSO predictor of LDL with remnant cholesterol, one of ten modifiable lifestyle and health traits modeled from array methylation in the Generation Scotland cohort.		sigmoid		Not yet
mccartneysmoking	methylation	Homo sapiens	smoking exposure (pack-years)	years	whole blood	Illumina 450K/EPIC	adults (Generation Scotland, mean age ~49 years)	LASSO	233	2018	301	2026-07-05	Riccardo E. Marioni	Genome biology	https://doi.org/10.1186/s13059-018-1514-1	Blood DNA-methylation LASSO predictor of smoking exposure, one of ten lifestyle and health scores trained on array methylation in the Generation Scotland cohort. Smoking was among the scores associated with all-cause mortality.				Not yet
mccartneytotalcholesterol	methylation	Homo sapiens	total cholesterol level	mmol/L	whole blood	Illumina 450K/EPIC	adults (Generation Scotland/STRADL cohort, n=5087)	LASSO	204	2018	301	2026-07-05	Riccardo E. Marioni	Genome biology	https://doi.org/10.1186/s13059-018-1514-1	Blood DNA-methylation LASSO predictor of total cholesterol, one of ten modifiable lifestyle and health traits modeled from array methylation in the Generation Scotland cohort.		sigmoid		Not yet
mccartneytotalhdlratio	methylation	Homo sapiens	total:HDL cholesterol ratio	score (arbitrary)	whole blood	Illumina 450K/EPIC	adults (Generation Scotland cohort)	Elastic net	412	2018	301	2026-07-05	Riccardo E. Marioni	Genome biology	https://doi.org/10.1186/s13059-018-1514-1	Blood DNA-methylation LASSO predictor of the total-to-HDL cholesterol ratio, one of ten modifiable lifestyle and health traits modeled from array methylation in the Generation Scotland cohort.				Not yet
mccartneywhr	methylation	Homo sapiens	waist-to-hip ratio	score (arbitrary)	whole blood	Illumina 450K/EPIC	adults (Generation Scotland training cohort, mean age ~49; tested in Lothian Birth Cohort 1936, age ~70)	LASSO	226	2018	301	2026-07-05	Riccardo E. Marioni	Genome biology	https://doi.org/10.1186/s13059-018-1514-1	Blood DNA-methylation LASSO predictor of waist-to-hip ratio, one of ten lifestyle and health scores trained on array methylation in the Generation Scotland cohort. Waist-to-hip ratio was among the scores that predicted all-cause mortality.				Not yet
meer	methylation	Mus musculus	chronological age	days	multi-tissue (11 mouse tissues, e.g. liver, lung, brain cortex, heart, blood)	Bisulfite sequencing	mice, whole lifespan (1 week to 35 months; C57BL/6)	Elastic net	435	2018	203	2026-07-05	Vadim N. Gladyshev	eLife	https://doi.org/10.7554/eLife.40675	Multi-tissue mouse chronological age clock built by elastic-net regression on reduced-representation bisulfite sequencing, using 435 CpG sites across roughly a dozen tissues. It spans the entire mouse lifespan and is responsive to longevity interventions such as caloric restriction and growth-hormone-receptor knockout.				Not yet
neusin	methylation	Homo sapiens	chronological age	years	brain (prefrontal cortex, bulk tissue, neuron-specific CpGs)	Illumina 450K	adults (18-97 years)	Elastic net	672	2024	25	2026-07-05	Andrew E. Teschendorff	Aging	https://doi.org/10.18632/aging.206184	Neuron semi-intrinsic DNA-methylation clock estimating chronological age in prefrontal cortex, trained by elastic-net regression on neuron-specific age-associated CpGs identified through cell-type deconvolution but applied to unadjusted methylation values. It captures within-neuron aging and shows age acceleration in Alzheimer’s disease.				Not yet
ocampoatac1	atac	Homo sapiens	chronological age	years	PBMCs (peripheral blood mononuclear cells)	ATAC-seq	healthy adults, ages 20-74 years	Elastic net	80400	2023	49	2026-07-05	Alejandro Ocampo	GeroScience	https://doi.org/10.1007/s11357-023-00986-0	Human aging clock that estimates chronological age from ATAC-seq chromatin-accessibility profiles of peripheral blood mononuclear cells, using elastic-net regression over age-variable open-chromatin regions. This base version operates on raw accessibility without adjusting for shifts in blood cell-type composition.	tpm_norm_log1p			Not yet
ocampoatac2	atac	Homo sapiens	chronological age	years	whole blood (PBMCs)	ATAC-seq	adults (20-74 years)	Elastic net	80400	2023	49	2026-07-05	Alejandro Ocampo	GeroScience	https://doi.org/10.1007/s11357-023-00986-0	Variant of the PBMC chromatin-accessibility age clock that corrects for age-related changes in blood cell-type composition before elastic-net estimation of chronological age, yielding substantially tighter predictions than the uncorrected version.	tpm_norm_log1p			Not yet
pcdnamtl	methylation	Homo sapiens	DNA methylation-estimated leukocyte telomere length	kilobases	whole blood	Illumina 450K/EPIC	adults	PCA + elastic net	78464	2022	497	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-022-00248-2	Principal-component reconstruction of the DNA-methylation estimator of leukocyte telomere length, computed by applying PCA across CpGs followed by penalized regression to suppress single-CpG technical noise and improve test-retest reliability.			True	Not yet
pcgrimage	methylation	Homo sapiens	mortality/time-to-death risk	years	whole blood (originally trained on Framingham Heart Study; PC version retrained across multiple cohorts including FHS, HRS, InCHIANTI, SATSA)	Illumina 450K/EPIC	adults	PCA + elastic net	78466	2022	497	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-022-00248-2	Principal-component version of the GrimAge mortality predictor, combining DNA-methylation surrogates of plasma proteins and smoking pack-years to estimate time-to-death, retrained through PCA to bolster reliability for longitudinal tracking.			True	Not yet
pchannum	methylation	Homo sapiens	chronological age	years	whole blood	Illumina 450K/EPIC	adults	PCA + elastic net	78464	2022	497	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-022-00248-2	Principal-component version of the Hannum whole-blood clock, estimating chronological age from blood DNA methylation via PCA across CpGs followed by penalized regression to reduce technical noise from individual probes.			True	Not yet
pchorvath2013	methylation	Homo sapiens	chronological age	years	multi-tissue (pan-tissue)	Illumina 450K/EPIC	pan-age humans (fetal to elderly), multi-tissue	PCA + elastic net	78464	2022	497	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-022-00248-2	Principal-component reconstruction of the pan-tissue multi-tissue clock, predicting chronological age across diverse human tissues from DNA methylation with improved reliability through PCA-based feature aggregation.		anti_log_linear	True	Not yet
pcphenoage	methylation	Homo sapiens	phenotypic (biological) age; mortality/morbidity risk	years	whole blood	Illumina 450K/EPIC	adults	PCA + elastic net	78464	2022	497	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-022-00248-2	Principal-component version of the DNAm PhenoAge clock, estimating a mortality- and morbidity-associated phenotypic age from blood DNA methylation, retrained via PCA to reduce technical noise for more reliable longitudinal measurement.			True	Not yet
pcskinandblood	methylation	Homo sapiens	chronological age	years	skin and blood (multi-tissue)	Illumina 450K/EPIC	pan-age adults/all ages	PCA + elastic net	78464	2022	497	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-022-00248-2	Principal-component version of the skin-and-blood clock, predicting chronological age with particular accuracy in skin, blood, and fibroblasts, using PCA across CpGs to strengthen test-retest reliability.		anti_log_linear	True	Not yet
pedbe	methylation	Homo sapiens	chronological age	years	buccal epithelial cells (pediatric)	Illumina 450K	pediatric/children (0-20 years)	Elastic net	94	2019	292	2026-07-05	Michael S. Kobor	Proceedings of the National Academy of Sciences	https://doi.org/10.1073/pnas.1820843116	Pediatric buccal-cell DNA-methylation clock estimating chronological age in children from a small set of CpGs selected by elastic-net regression, trained on buccal-epithelial samples spanning gestation to early adulthood.		anti_log_linear		Not yet
petkovich	methylation	Mus musculus	chronological age	months	whole blood (mouse)	Bisulfite sequencing	mice (C57BL/6), ages 3-35 months	Elastic net	90	2017	441	2026-07-05	Vadim N. Gladyshev	Cell Metabolism	https://doi.org/10.1016/j.cmet.2017.03.016	Mouse blood DNA-methylation age clock built by regression on reduced-representation bisulfite-sequencing CpGs, estimating biological age and shown to be slowed by lifespan-extending interventions such as caloric restriction and dwarfism.		petkovich		Not yet
phenoage	blood chemistry	Homo sapiens	phenotypic age (mortality/healthspan risk), i.e., DNA methylation-based estimate of phenotypic age	years	whole blood	Illumina 450K	adults (NHANES III training cohort, ages 20+; validated across adult lifespan)	Cox regression	10	2018	3594	2026-07-05	Steve Horvath	Aging	https://doi.org/10.18632%2Faging.101414	Phenotypic age estimator computed from nine clinical blood-chemistry biomarkers together with chronological age through a parametric (Gompertz) mortality model, expressing all-cause mortality risk as an equivalent age in years.		mortality_to_phenoage		Not yet
prostatecancerkirby	methylation	Homo sapiens	prostate cancer diagnosis (malignant vs benign tissue)	probability (0-1)	prostate tissue (fresh-frozen malignant and benign-adjacent)	Illumina 450K	adult men (prostate cancer patients)	Logistic regression	3	2017	61	2026-07-05	R Myers	BMC Cancer	https://doi.org/10.1186/s12885-017-3252-2	Prostate-tissue DNA-methylation diagnostic classifier that distinguishes malignant prostate cancer from benign-adjacent tissue, built by logistic regression on genome-wide Illumina 450K methylation from 73 tumor and 63 benign-adjacent prostate samples. The differentially methylated signature was also examined as a predictor of disease progression.				Not yet
reedbmi	methylation	Homo sapiens	body mass index (BMI) - biomarker of extant/concurrent BMI	kilograms	whole blood (peripheral blood; umbilical cord blood at birth)	Illumina 450K	pan-age (birth, childhood ~7y, adolescence ~15-17y, pregnancy ~29y, middle age ~48y); ARIES/ALSPAC mother-child cohort	Weighted average of CpGs	135	2020	86	2026-07-05	Gibran Hemani	Clinical Epigenetics	https://doi.org/10.1186/s13148-020-00841-5	Blood DNA-methylation score for body mass index, computed as a weighted combination of CpGs drawn from published BMI epigenome-wide associations. It was evaluated across the life course from birth through adulthood in a longitudinal mother-child cohort to separate methylation that acts as a biomarker of current BMI from methylation that predicts future BMI.				Not yet
replitali	methylation	Homo sapiens	cumulative replicative/mitotic history (population doublings)	population doublings	primary human cells in culture (fetal/neonatal/adult skin fibroblasts, foreskin keratinocytes, vascular endothelial and smooth muscle cells)	Illumina EPIC	human primary cells in culture (relative measure of replicative history, not chronological age)	Elastic net	87	2022	86	2026-07-05	Peter W. Laird	Nature Communications	https://doi.org/10.1038/s41467-022-34268-8	Elastic-net mitotic clock (RepliTali, Replication Times Accumulated in Lifetime) that estimates the cumulative replicative history of primary human cells from progressive hypomethylation at PMD solo-WCGW CpGs in late-replicating, lamina-associated domains, trained against population doublings measured in cultured fibroblasts on EPIC arrays.				Not yet
replitalinorm	methylation	Homo sapiens	Mitotic age (normalized cumulative population doublings / replicative history)	population doublings	Cultured primary human cells (fibroblasts, keratinocytes, endothelial cells)	Illumina EPIC	Primary human cells (in vitro cultured, multiple donors/cell types)	Elastic net	218	2022	86	2026-07-05	Peter W. Laird	Nature Communications	https://doi.org/10.1038/s41467-022-34268-8	Normalized version of the RepliTali mitotic clock that predicts population doublings adjusted for each donor’s unknown in vivo replicative history (calibrated using the chronologically youngest fetal fibroblast line), tracking cumulative cell divisions through PMD solo-WCGW hypomethylation in primary human cells.				Not yet
retroelementagev1	methylation	Homo sapiens	chronological age	years	whole blood	Illumina EPIC	adults (ages 12-100 years)	Elastic net	1317	2024	26	2026-07-05	Michael J. Corley	Aging Cell	https://doi.org/10.1111/acel.14288	Blood DNA-methylation clock (‘Retro-age’) that predicts chronological age from the methylation states of retroelements, specifically human endogenous retroviruses and LINE elements, using an elastic-net model over roughly 10,900 retroelement-annotated CpGs. This version is built for Illumina EPIC v1.0 data and draws on CpGs largely non-overlapping with existing epigenetic clocks.				Not yet
retroelementagev2	methylation	Homo sapiens	chronological age	years	whole blood	Illumina EPIC	ages 12-100 years (adolescents to elderly)	Elastic net	1378	2024	26	2026-07-05	Michael J. Corley	Aging Cell	https://doi.org/10.1111/acel.14288	EPIC v2.0-compatible version of the ‘Retro-age’ clock, an elastic-net predictor of chronological age from blood DNA-methylation states of retroelements (human endogenous retroviruses and LINEs), capturing an aging signal distinct from first- and second-generation epigenetic clocks.				Not yet
senchronoage	methylation	Homo sapiens	chronological age (senescence-enriched age predictor)	years	whole blood (age-predictor training) with senescence/age/mortality-concordant CpGs selected using cultured human cell senescence datasets (fibroblasts, MSCs, epithelial cells)	Illumina 450K/EPIC	adults	Elastic net	187	2026	0	2026-07-05	Albert T Higgins-Chen	Aging Cell	https://doi.org/10.1111/acel.70430	Senescence-enriched DNA-methylation clock that estimates chronological age from a methylome subset prioritized for association with cellular senescence. It is one of a family of senescence-focused clocks whose age signal was not reversed by senolytic treatment in vitro, in mice, or in human trials.				Not yet
sencultureage	methylation	Homo sapiens	in vitro cellular senescence status (core senescence signal across senescence inducers, e.g. DNA damage/replicative/oncogene-induced senescence vs control)	score (arbitrary)	cultured human fibroblasts and mesenchymal stem/stromal cells (in vitro)	Illumina 450K/EPIC	in vitro cultured human cells (fibroblasts/MSCs)	Elastic net	142	2026	0	2026-07-05	Albert T Higgins-Chen	Aging Cell	https://doi.org/10.1111/acel.70430	Senescence-enriched DNA-methylation clock trained to quantify cellular senescence accumulated in cultured human cells, using CpGs identified by meta-analysis of replicative, DNA-damage and oncogene-induced senescence across fibroblast cell lines. Its senescence signal was not reduced by senolytic treatment.				Not yet
senmortalityage	methylation	Homo sapiens	mortality/time-to-death risk (senescence-enriched CpGs)	relative risk/hazard	whole blood (Framingham Heart Study)	Illumina 450K/EPIC	adults	Cox regression	91	2026	0	2026-07-05	Albert T Higgins-Chen	Aging Cell	https://doi.org/10.1111/acel.70430	Senescence-enriched DNA-methylation predictor of mortality risk, constructed from CpGs prioritized for their association with cellular senescence and with mortality. It belongs to a clock family that showed little CpG overlap between the senescence, chronological-age and mortality signals.				Not yet
skinandblood	methylation	Homo sapiens	chronological age	years	multi-tissue (skin fibroblasts, keratinocytes, buccal, blood, endothelial cells)	Illumina 450K/EPIC	pan-age (fetal to elderly)	Elastic net	391	2018	853	2026-07-05	Kenneth Raj	Aging	https://doi.org/10.18632/aging.101508	Multi-tissue DNA-methylation age predictor built by penalized (elastic-net) regression across skin, blood, buccal, saliva, and cultured fibroblasts/keratinocytes and endothelial cells. Designed to remain highly accurate in fibroblasts and cell-culture material, and applied to characterize accelerated epigenetic aging in Hutchinson-Gilford Progeria Syndrome.		anti_log_linear		Not yet
stemtocvitro	methylation	Homo sapiens	Mitotic (stem-cell/progenitor division) age	score (arbitrary)	In vitro proliferating cell lines (fibroblast, endothelial, smooth muscle) used to derive mitCpGs; final CpG selection calibrated against whole-blood age-hypermethylation cohorts; fetal/neonatal…	Illumina 450K/EPIC	Pan-age, pan-tissue; applicable to normal, precancerous and cancer tissues (adults, plus fetal/neonatal reference samples used in CpG selection)	Mitotic model	629	2024	24	2026-07-05	Andrew E. Teschendorff	Nature Communications	https://doi.org/10.1038/s41467-024-48649-8	Variant of the StemTOC mitotic counter whose CpGs are defined from cell-division (in vitro) experiments, tracking mitotic age via hypermethylation at sites that accumulate methylation with proliferation rather than merely with chronological time.	0.95 quantile		True	Not yet
stubbs	methylation	Mus musculus	chronological age	weeks	multi-tissue mouse (primarily liver, lung, heart, cortex from Babraham dataset; also muscle, cerebellum, spleen from additional datasets)	Bisulfite sequencing	mice (Mus musculus), newborn to ~41 weeks (whole lifespan)	Elastic net	17992	2017	430	2026-07-05	Wolf Reik	Genome biology	https://doi.org/10.1186/s13059-017-1203-5	Multi-tissue DNA-methylation age predictor for mouse, trained by penalized regression on reduced-representation bisulfite sequencing methylation across several mouse tissues to estimate chronological age.	quantile_normalization_and_scale_with_gold_standard	stubbs	True	Not yet
systemsage	methylation	Homo sapiens	mortality risk / system-specific aging deterioration (composite of 11 physiological-system aging scores, mortality-trained via Cox regression, output scaled to a chronological-age-like unit)	years	whole blood	Illumina 450K/EPIC	adults (primarily older adults, ~51-100 years; HRS and FHS cohorts)	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Composite biological-age measure derived from a single blood DNA-methylation assay that integrates eleven physiological-system-specific methylation clocks trained with supervised and unsupervised learning against clinical biomarkers, functional measures, and mortality. Summarizes overall multisystem aging and predicts mortality and age-related outcomes more precisely than single-value clocks.			True	Not yet
systemsageblood	methylation	Homo sapiens	Blood-system biological age (aging of the blood/hematological physiological system, one of 11 systems in the Systems Age framework)	years	whole blood (trained in HRS, validated/replicated in Framingham Heart Study)	Illumina EPIC	adults/older adults, ~51-100 years (HRS training cohort)	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Blood-system component of the Systems Age framework, a blood DNA-methylation clock quantifying aging of the hematological system relative to clinical and functional markers of that system.			True	Not yet
systemsagebrain	methylation	Homo sapiens	brain/nervous-system biological aging (brain-system age)	years	whole blood	Illumina 450K/EPIC	adults	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Brain-system component of the Systems Age framework, a blood DNA-methylation clock quantifying aging of the nervous/brain system by training against system-relevant clinical, functional, and mortality outcomes.			True	Not yet
systemsageheart	methylation	Homo sapiens	heart/cardiovascular-system biological age (aging of the heart system)	years	whole blood	Illumina 450K/EPIC	adults (middle-aged to elderly)	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Heart-system component of the Systems Age framework, a blood DNA-methylation clock quantifying cardiovascular-system aging against system-specific clinical biomarkers and outcomes.			True	Not yet
systemsagehormone	methylation	Homo sapiens	hormone/endocrine physiological system aging (system-specific biological age)	years	whole blood	Illumina 450K/EPIC	adults (trained in HRS and Framingham Heart Study cohorts)	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Hormone-system component of the Systems Age framework, a blood DNA-methylation clock quantifying aging of the endocrine/hormonal system from a single blood draw.			True	Not yet
systemsageimmune	methylation	Homo sapiens	immune-system biological age (immune aging; linked to immune clinical/functional markers and mortality)	years	whole blood	Illumina 450K/EPIC	adults	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Immune-system component of the Systems Age framework, a blood DNA-methylation clock quantifying immune-system aging against immune-relevant clinical and functional markers.			True	Not yet
systemsageinflammation	methylation	Homo sapiens	inflammatory-system biological age (system-specific aging)	years	whole blood	Illumina 450K/EPIC	adults (middle-aged to older adults)	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Blood DNA-methylation clock estimating the aging rate of the inflammatory system, one of 11 organ-system-specific ages in the Systems Age framework derived by linking methylation to system-relevant clinical biomarkers, functional measures and mortality risk. Together the systems ages resolve within-person aging heterogeneity from a single blood draw and reveal distinct multisystem aging subtypes.			True	Not yet
systemsagekidney	methylation	Homo sapiens	kidney physiological system biological age (aging/mortality risk)	years	whole blood	Illumina 450K/EPIC	adults (older adults)	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Blood DNA-methylation clock estimating the aging rate of the kidney/renal system, one of 11 organ-system-specific ages in the Systems Age framework derived by linking methylation to system-relevant clinical biomarkers, functional assessments and mortality risk. It captures system-level aging heterogeneity within a person from a single blood methylation test.			True	Not yet
systemsageliver	methylation	Homo sapiens	aging of the liver (hepatic) physiological system	years	whole blood	Illumina 450K/EPIC	adults	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Blood DNA-methylation clock estimating the aging rate of the hepatic (liver) system, one of 11 organ-system-specific ages in the Systems Age framework derived by linking methylation to system-relevant clinical biomarkers, functional measures and mortality risk. It resolves organ-specific aging heterogeneity from a single blood draw.			True	Not yet
systemsagelung	methylation	Homo sapiens	biological age (aging rate) of the lung/pulmonary system	years	whole blood	Illumina 450K/EPIC	adults (~51-100+ years)	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Blood DNA-methylation clock estimating the aging rate of the pulmonary (lung) system, one of 11 organ-system-specific ages in the Systems Age framework derived by linking methylation to system-relevant clinical biomarkers, functional assessments and mortality risk. It contributes to a composite multisystem aging profile computed from a single blood sample.			True	Not yet
systemsagemetabolic	methylation	Homo sapiens	biological aging of the metabolic physiological system (one of 11 system-specific ages)	years	whole blood	Illumina 450K/EPIC	adults, ~51-100 years (trained in HRS n=3,593 and FHS ~3,935, validated in additional cohorts)	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Blood DNA-methylation clock estimating the aging rate of the metabolic system, one of 11 organ-system-specific ages in the Systems Age framework derived by linking methylation to system-relevant clinical biomarkers, functional measures and mortality risk. It captures within-person metabolic aging heterogeneity from a single blood methylation assay.			True	Not yet
systemsagemusculoskeletal	methylation	Homo sapiens	musculoskeletal system biological age (system-specific mortality-associated aging rate)	years	whole blood	Illumina 450K/EPIC	adults (trained in adults over 50, ages 51-100)	PCA + elastic net	125175	2025	41	2026-07-05	Morgan E. Levine	Nature Aging	https://doi.org/10.1038/s43587-025-00958-3	Blood DNA-methylation clock estimating the aging rate of the musculoskeletal system, one of 11 organ-system-specific ages in the Systems Age framework derived by linking methylation to system-relevant clinical biomarkers, functional assessments and mortality risk. It resolves organ-level aging heterogeneity within an individual from a single blood draw.			True	Not yet
twelvecelldeconvolutebloodepicbas	methylation	Homo sapiens	basophil cell-type proportion (12-cell blood deconvolution)	proportion (0-1)	whole blood	Illumina EPIC	adults	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based cell-type deconvolution estimating the proportion of basophils from whole-blood EPIC DNA-methylation data using an extended 12-leukocyte-subtype reference validated against flow cytometry.	fill_with_reference_means		True	Not yet
twelvecelldeconvolutebloodepicbmem	methylation	Homo sapiens	memory B cell (Bmem) proportion	proportion (0-1)	whole blood	Illumina EPIC	adults	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based cell-type deconvolution estimating the proportion of memory B cells from whole-blood EPIC DNA-methylation data using an extended 12-leukocyte-subtype reference validated against flow cytometry.	fill_with_reference_means		True	Not yet
twelvecelldeconvolutebloodepicbnv	methylation	Homo sapiens	naive B cell proportion (cell-type deconvolution)	proportion (0-1)	whole blood	Illumina EPIC	adults (whole-blood samples)	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based cell-type deconvolution estimating the proportion of naive B cells from whole-blood EPIC DNA-methylation data using an extended 12-leukocyte-subtype reference validated against flow cytometry.	fill_with_reference_means		True	Not yet
twelvecelldeconvolutebloodepiccd4mem	methylation	Homo sapiens	proportion of memory CD4+ T cells (cell-type composition)	proportion (0-1)	whole blood (purified leukocyte-subtype reference)	Illumina EPIC	adults (human whole-blood samples)	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based cell-type deconvolution estimating the proportion of memory CD4+ T cells from whole-blood EPIC DNA-methylation data using an extended 12-leukocyte-subtype reference validated against flow cytometry.	fill_with_reference_means		True	Not yet
twelvecelldeconvolutebloodepiccd4nv	methylation	Homo sapiens	naive CD4+ T cell proportion (CD4nv, cell-type deconvolution)	proportion (0-1)	whole blood	Illumina EPIC	adults	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based cell-type deconvolution estimating the proportion of naive CD4+ T cells from whole-blood EPIC DNA-methylation data using an extended 12-leukocyte-subtype reference validated against flow cytometry.	fill_with_reference_means		True	Not yet
twelvecelldeconvolutebloodepiccd8mem	methylation	Homo sapiens	memory CD8+ T cell proportion	proportion (0-1)	whole blood (purified leukocyte subsets reference panel)	Illumina EPIC	adults	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Reference-based cell-type deconvolution estimating the proportion of memory CD8+ T cells from whole-blood EPIC DNA-methylation data using an extended 12-leukocyte-subtype reference validated against flow cytometry.	fill_with_reference_means		True	Not yet
twelvecelldeconvolutebloodepiccd8nv	methylation	Homo sapiens	naive CD8+ T-cell (CD8nv) proportion	proportion (0-1)	whole blood	Illumina EPIC	adults (whole blood)	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Cell-type deconvolution estimate of the naive CD8+ T-cell fraction in whole blood, inferred from EPIC-array DNA methylation against a twelve immune cell-type reference of leukocyte-specific CpGs rather than being an age predictor.	fill_with_reference_means		True	Not yet
twelvecelldeconvolutebloodepiceos	methylation	Homo sapiens	eosinophil cell-type proportion (immune cell fraction)	proportion (0-1)	whole blood	Illumina EPIC	adults (whole blood)	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Cell-type deconvolution estimate of the eosinophil fraction in whole blood, inferred from EPIC-array DNA methylation against a twelve immune cell-type reference of leukocyte-specific CpGs rather than being an age predictor.	fill_with_reference_means		True	Not yet
twelvecelldeconvolutebloodepicmono	methylation	Homo sapiens	monocyte cell-type proportion	proportion (0-1)	whole blood	Illumina EPIC	adults	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Cell-type deconvolution estimate of the monocyte fraction in whole blood, inferred from EPIC-array DNA methylation against a twelve immune cell-type reference of leukocyte-specific CpGs rather than being an age predictor.	fill_with_reference_means		True	Not yet
twelvecelldeconvolutebloodepicneu	methylation	Homo sapiens	neutrophil cell-type proportion (12-cell-type deconvolution)	proportion (0-1)	whole blood	Illumina EPIC	adults	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Cell-type deconvolution estimate of the neutrophil fraction in whole blood, inferred from EPIC-array DNA methylation against a twelve immune cell-type reference of leukocyte-specific CpGs rather than being an age predictor.	fill_with_reference_means		True	Not yet
twelvecelldeconvolutebloodepicnk	methylation	Homo sapiens	NK (natural killer) cell proportion	proportion (0-1)	whole blood	Illumina EPIC	adults	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Cell-type deconvolution estimate of the natural killer (NK) cell fraction in whole blood, inferred from EPIC-array DNA methylation against a twelve immune cell-type reference of leukocyte-specific CpGs rather than being an age predictor.	fill_with_reference_means		True	Not yet
twelvecelldeconvolutebloodepictreg	methylation	Homo sapiens	regulatory T-cell (Treg) proportion in blood	proportion (0-1)	whole blood	Illumina EPIC	adults (human blood samples; not age-specific)	Reference-based deconvolution	240	2024	13	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-025-00987-y	Cell-type deconvolution estimate of the regulatory T-cell (Treg) fraction in whole blood, inferred from EPIC-array DNA methylation against a twelve immune cell-type reference of leukocyte-specific CpGs rather than being an age predictor.	fill_with_reference_means		True	Not yet
vidalbralo	methylation	Homo sapiens	chronological age	years	whole blood	Illumina 27K/450K	adults (>20 years)	Bayesian regression	8	2016	145	2026-07-05	Antonio González	Frontiers in Genetics	https://doi.org/10.3389/fgene.2016.00126	Whole-blood epigenetic age estimator for adults built by stepwise multiple linear regression over eight CpG sites, designed to run as a single low-cost MS-SNuPE multiplex assay rather than a genome-wide methylation microarray.				Not yet
weidner	methylation	Homo sapiens	chronological age	years	whole blood	Illumina 27K	adults	Linear regression	3	2014	973	2026-07-05	Wolfgang Wagner	Genome biology	https://doi.org/10.1186/gb-2014-15-2-r24	Whole-blood chronological age predictor based on multivariate linear regression over just three age-associated CpG sites (in ITGA2B, ASPA and PDE4C), measurable by targeted bisulfite pyrosequencing.				Not yet
wu	methylation	Homo sapiens	chronological age	months	whole blood (peripheral blood leukocytes)	Illumina 27K/450K	pediatric/children (9-212 months, ~0-18 years)	Elastic net	111	2019	82	2026-07-05	Huiying Liang	Aging	https://doi.org/10.18632/aging.102399	Pediatric DNA-methylation age clock estimating chronological age (in months) from children’s whole-blood methylation, built by sure independence screening followed by elastic-net regression over 111 CpGs, with methylation aging signatures largely distinct from adult clocks.		anti_log_linear		Not yet
xchrom	methylation	Homo sapiens	sex / sex chromosome complement (and aneuploidy, e.g. Turner/Klinefelter syndrome)	score (arbitrary)	whole blood (generalizes across tissues)	Illumina 450K/EPIC	human, all ages (sex-independent of age)	PCA	453152	2021	38	2026-07-05	Leonard C. Schalkwyk	BMC Genomics	https://doi.org/10.1186/s12864-021-07675-2	X-chromosome component of a DNA-methylation sex classifier that scores X-linked methylation using principal components of sex-associated CpGs, reflecting X-chromosome dosage to infer sex and detect aneuploidies such as 45,X and 47,XXY.	sex_estimation_autosomal_zscore		True	Not yet
ychrom	methylation	Homo sapiens	sex / sex chromosome aneuploidy (Y-chromosome presence)	sex (categorical)	whole blood	Illumina 450K/EPIC	adults (training age 18; validation 28-98), age-independent	PCA-based classifier	453152	2021	38	2026-07-05	Leonard C. Schalkwyk	BMC Genomics	https://doi.org/10.1186/s12864-021-07675-2	Y-chromosome component of a DNA-methylation sex classifier that scores Y-linked methylation using principal components of sex-associated CpGs, indicating presence or absence of the Y chromosome and helping identify sex-chromosome aneuploidy.	sex_estimation_autosomal_zscore		True	Not yet
yingadaptage	methylation	Homo sapiens	adaptive/protective epigenetic age (captures beneficial, protective methylation changes accumulated with aging; higher AdaptAge acceleration associated with lower mortality risk, opposite of DamAge)	years	whole blood	Illumina 450K	adults (18-93 years, Generation Scotland cohort)	Elastic net	999	2024	183	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-023-00557-0	Causality-enriched DNA-methylation clock trained on CpGs identified by epigenome-wide Mendelian randomization as protective/adaptive to aging, capturing beneficial adaptive methylation changes; built by elastic-net regression on blood methylation and decreasing under age-related damage.				Not yet
yingcausage	methylation	Homo sapiens	chronological age (causality-enriched, causal CpGs; CausAge), with derived DamAge/AdaptAge tracking damaging vs adaptive methylation changes	years	whole blood	Illumina 450K	adults (aged 18-93 years, Generation Scotland cohort)	Elastic net	585	2024	183	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-023-00557-0	Causality-enriched DNA-methylation age clock built by elastic-net regression over 586 CpGs selected via epigenome-wide Mendelian randomization to be causally linked to aging-related traits, estimating biological age from blood methylation while separating causal from merely correlative signals.				Not yet
yingdamage	methylation	Homo sapiens	age-related damage (damaging DNA methylation changes prioritized by Mendelian randomization); DamAge acceleration is strongly associated with mortality risk	years	whole blood	Illumina 450K	adults (trained on ages 18-93)	Elastic net	1089	2024	183	2026-07-05	Vadim N. Gladyshev	Nature Aging	https://doi.org/10.1038/s43587-023-00557-0	Blood DNA-methylation clock (DamAge) that quantifies damaging, deleterious epigenetic changes using CpGs prioritized by epigenome-wide Mendelian randomization to be causally linked to aging traits. It tracks detrimental methylation changes and is strongly associated with all-cause mortality and other adverse outcomes, complementing the protective AdaptAge counterpart.				Not yet
zhangblup	methylation	Homo sapiens	chronological age	years	whole blood	Illumina 450K	adults	BLUP	319607	2019	519	2026-07-05	Peter M. Visscher	Genome Medicine	https://doi.org/10.1186/s13073-019-0667-1	Chronological-age predictor for blood and saliva built with Best Linear Unbiased Prediction over 319,607 CpGs. Trained on a large multi-tissue sample to achieve high-precision age estimates, at which point the age-acceleration residual loses its association with mortality.	scale_row		True	Not yet
zhangen	methylation	Homo sapiens	chronological age	years	whole blood (some saliva)	Illumina 450K/EPIC	humans, ages 2-104 years	Elastic net	514	2019	519	2026-07-05	Peter M. Visscher	Genome Medicine	https://doi.org/10.1186/s13073-019-0667-1	Chronological-age predictor for blood and saliva built with elastic-net regression on 514 CpGs. Trained across a wide age range on 450K and EPIC array data, sharing few probes with the Hannum or Horvath clocks.	scale_row		True	Not yet
zhangmortality	methylation	Homo sapiens	all-cause mortality risk	relative risk/hazard	whole blood (peripheral blood)	Illumina 450K	adults (general population, ~50-75 years)	Cox regression	10	2017	404	2026-07-05	Hermann Brenner	Nature Communications	https://doi.org/10.1038/ncomms14617	Peripheral-blood methylation risk score for all-cause mortality derived from 10 CpGs selected by LASSO Cox regression from epigenome-wide screening. The score stratifies mortality risk independently of chronological-age epigenetic clocks, with several CpGs also linked to smoking.				Not yet