Epigenetic clocks & biological-age diagnostics

01Overview and value chain

Markers: [EC: In Vitro Diagnostic Regulation (IVDR) Class C | OECD: Genomics & bioinformatics | Regulator: FDA (US), EMA (EU), NMPA (China)]

Epigenetic clocks are machine-learning models that compute a person’s biological age from the methylation state of specific cytosine-guanine (CpG) dinucleotides scattered across the genome, exploiting the fact that DNA methylation drifts in a predictable, measurable pattern as cells age. A single Illumina Infinium MethylationEPIC BeadChip reads methylation intensity at more than 850,000 CpG sites simultaneously, and commercial reports now stack six or more clock algorithms — DunedinPACE, GrimAge 2.0, PhenoAge, OMICmAge and SymphonyAge among them — on top of the same array run. Consumer-facing tests range $229-799 per kit, turned around from a saliva swab or blood draw in two to four weeks. The sector spans four algorithm generations: first-generation clocks (Horvath, Hannum) trained to predict chronological age; second-generation clocks (PhenoAge, GrimAge) trained on clinical mortality and morbidity biomarkers instead; DunedinPACE, which measures the current pace of aging (e.g., 0.8 or 1.2 biological years per calendar year) rather than accumulated age; and emerging deep-learning clocks that fuse methylation with transcriptomic and proteomic layers.

The key directions of epigenetic-clock diagnostics are:

1. Multi-clock consumer panels: stacking several validated algorithms (DunedinPACE, GrimAge 2.0, PhenoAge, organ-specific ages) on one methylation-array run to give a single report several complementary age read-outs.
2. Pace-of-aging measurement: DunedinPACE-class algorithms trained on decades-long cohort studies to quantify the current rate of biological aging rather than an accumulated age number.
3. Alternative non-methylation biomarkers: glycan-based clocks that measure immunoglobulin G (IgG) glycosylation as a proxy for systemic inflammation and aging, avoiding the array/bisulfite pipeline entirely.
4. Geroprotector and intervention trials: using repeat epigenetic-age measurements as a primary or secondary endpoint to quantify whether a drug, therapeutic plasma exchange, or lifestyle change measurably slows or reverses biological aging.

Sectoral value chain

[Sample collection (blood/saliva)] ──> [DNA extraction] ──> [Bisulfite/enzymatic conversion]
                  │                                         │                                      │
       (Stabilizing buffer)                    (Enzymatic protein digestion)                (EM-seq or bisulfite chemistry)
                                                                                                   │
  [Clinical report (bio-age)] <── [AI clock modeling (GrimAge/DunedinPACE)] <─── [Methylation array scan]

Value chain levels

Cross-cutting technologies of the sector:

• Illumina Infinium MethylationEPIC BeadChip: the field’s reference array, reading methylation at over 850,000 CpG sites per sample via two-color fluorescent bead-based detection.
• Enzymatic methylation sequencing (EM-seq): an alternative to bisulfite conversion, which degrades up to 90% of input DNA; EM-seq uses sequential TET2 and APOBEC3A enzyme treatment to detect methylated cytosines while preserving DNA fragment length and structure.
• Elastic-net regression clocks: the DunedinPACE algorithm class, trained on the decades-long Dunedin Study cohort of about 1,000 participants followed from birth to age 45 across dozens of biomarkers, to quantify an individual’s current pace of aging.

02US

The United States leads global commercialization of biological-age testing and the integration of epigenetic clocks into clinical trials of geroprotective compounds.

Steve Horvath’s original clocks, TruDiagnostic’s DunedinPACE license, Tally Health’s cheek-swab platform, Elysium’s PhenoAge-based Index

• Origin of epigenetic clocks: UCLA human genetics professor Steve Horvath published the first multi-tissue epigenetic clock in 2013, showing biological age could be computed from methylation at 353 CpG sites; he now leads clock R&D at Altos Labs, alongside Yale-trained researcher Morgan Levine, who developed the second-generation PhenoAge algorithm before also joining Altos Labs.
• TruDiagnostic’s multi-clock platform: founded in 2020 and based in Lexington, KY, TruDiagnostic runs its TruAge COMPLETE and TruAge PACE reports off a single 900,000+ CpG methylation array, stacking DunedinPACE, GrimAge 2.0, PhenoAge, OMICmAge, SymphonyAge and 11 organ-specific age estimates in one $399-799 panel, positioning it as the largest commercial epigenetic-testing lab in the country.
• Tally Health’s cheek-swab CheekAge: founded in 2023 in New York and co-founded by longevity researcher David Sinclair, Tally Health runs a $229 cheek-swab test built on its proprietary CheekAge clock, publishing its methodology as a peer-reviewed scientific paper and pairing the age read-out with an AI-driven nutrition and supplement app.
• Elysium Health’s Index: founded in 2014 in New York, Elysium Health sells the $299 Index DNA-methylation test built on Morgan Levine and Steve Horvath’s 2018 DNAm PhenoAge algorithm, and separately markets a Senolytic Complex supplement, positioning the company across both the diagnostic and geroprotective-supplement sides of the longevity market.
• Buck Institute’s clock research: the Marin County, CA-based Buck Institute for Research on Aging published a new blood-based epigenetic clock in June 2025 focused on “intrinsic capacity” rather than raw age, and is running its BIG Study biobank to collect blood at scale for aging research; a May 2025 Aging Cell trial from the Institute found that therapeutic plasma exchange combined with IVIG reduced multi-omics biological age by 2.6 years on average.

03CN

China is building population-scale epigenetic reference data and integrating biological-age testing into premium health-checkup packages, while its diagnostics sector adapts methylation-based cancer and aging assays to a domestic population whose methylation patterns differ from Western-trained clocks.

Population-specific clock calibration, oncology-diagnostics methylation platforms, premium health-checkup integration

• Population-specific clock calibration: Chinese Academy of Sciences (CAS) institutes are building population-scale methylation reference datasets, since CpG methylation patterns carry ethnic and dietary variation that Western-trained clocks (built mostly on European and American cohorts) do not capture accurately.
• Methylation-based diagnostics platforms: domestic NGS diagnostics companies are extending DNA-methylation assays developed for early cancer detection toward biological-age and organ-aging scoring, reusing the same bisulfite/array infrastructure built for oncology screening.
• Premium health-checkup integration: private clinics in Beijing, Shanghai and Shenzhen are folding methylation-based biological-age scoring into annual premium health-checkup packages, the main commercial channel for the test in China today.

04EU

The European Union anchors its biological-age diagnostics sector in long-running population cohorts, an alternative glycan-based biomarker pioneered in the UK and Croatia, and strict IVDR/GDPR oversight of genetic test data.

Long-running aging cohorts, GlycanAge’s IgG-glycosylation clock, IVDR Class C classification

• Long-running population cohorts: European institutes coordinate decades-long longitudinal aging studies (such as Edinburgh’s Lothian Birth Cohorts), providing the deep genomic and epigenetic follow-up data used to train and validate new clock algorithms.
• GlycanAge’s glycan clock: London-headquartered GlycanAge, spun out of Croatian glycoscience research, markets a biological-age test based on immunoglobulin G (IgG) glycosylation rather than DNA methylation; a May 2026 study run jointly with Circulate Health analyzed roughly 20,000 individuals across 42 studies, establishing IgG glycans as an independent predictor of all-cause mortality and showing therapeutic plasma exchange can measurably reduce the glycan-based age score.
• IVDR Class C classification and GDPR: clinical deployment of biological-age tests in the EU falls under the In Vitro Diagnostic Regulation as a Class C genetic screening test, with storage and bioinformatic processing of the underlying genomic data separately bound by GDPR.

05Leading companies and research institutes

06Tech stack and innovations

The biological-age diagnostics stack pairs high-throughput molecular biology automation with cloud AI modeling:

1. Automated library prep on liquid-handling robots:
   • High-throughput DNA extraction and bisulfite/enzymatic conversion of up to 96 samples in parallel, with robotic liquid handlers dispensing reagents at 0.1 µL precision to eliminate cross-contamination between DNA samples.
2. Laser array scanning:
   • Illumina iScan-class scanners read EPIC BeadChips with dual high-intensity lasers, resolving methylated (one fluorescent channel) versus unmethylated (the other channel) cytosine signals across 850,000+ CpG sites per chip in minutes.
3. Cloud AI age-prediction models:
   • Regularized regression (ridge/lasso/elastic net) and deep neural networks trained on millions of CpG profiles compute age acceleration and pace-of-aging indices from the normalized beta-value array, generating a graphical predictive-risk report.

07Value chains and production pipelines

Industrial pipeline for a clinical epigenetic-age test (ISO 15189)

┌───────────────────────────┐      ┌───────────────────────────┐
│ 1. Saliva/blood collection │ ───> │ 2. Automated genomic DNA   │
│    in preservative tube    │      │    extraction              │
└───────────────────────────┘      └───────────────────────────┘
                                                 │
                                                 ▼
┌───────────────────────────┐      ┌───────────────────────────┐
│ 4. Array hybridization     │ <─── │ 3. Bisulfite/enzymatic     │
│    (Illumina EPIC BeadChip)│      │    conversion               │
└───────────────────────────┘      └───────────────────────────┘
              │
              ▼
┌───────────────────────────┐      ┌───────────────────────────┐
│ 5. Laser scan & beta-value │ ───> │ 6. AI clock scoring &      │
│    calculation              │      │    report generation       │
└───────────────────────────┘      └───────────────────────────┘

Stage 1: Sample collection and stabilization

A patient collects roughly 2 mL of saliva into a kit tube (e.g., a DNA Genotek Oragene-DNA collector); closing the cap punctures an internal membrane that releases a preservative buffer, lysing bacteria and inhibiting DNase enzymes so that genomic DNA in buccal cells stays stable at room temperature for up to five years during mail-in transport.

Stage 2: Automated genomic DNA extraction

The sample is logged by barcode and a 1 mL aliquot is dispensed by a robotic station into a 96-well plate. Proteinase K digestion at 50°C for one hour breaks down salivary proteins, and DNA is purified on silica-coated magnetic microbeads held by a magnet through alcohol wash steps, eluting at least 2 µg of DNA at an A260/A280 purity ratio of roughly 1.8.

Stage 3: Bisulfite or enzymatic methylation conversion

500 ng of genomic DNA undergoes bisulfite conversion (e.g., with a Zymo Research EZ DNA Methylation kit) or enzymatic methylation sequencing: a stepwise thermocycler profile denatures DNA at 95°C and sulfonates it at 50°C for up to three hours, converting unmethylated cytosines to uracil while leaving methylated cytosines (5-mC) intact; the converted single-stranded DNA is then purified and neutralized.

Stage 4: Array hybridization

The converted DNA undergoes whole-genome amplification for roughly 20 hours at 37°C, is enzymatically fragmented, precipitated, and resuspended in hybridization buffer, then loaded onto an Illumina Infinium MethylationEPIC BeadChip v2.0 and incubated in a hybridization chamber for about 20 hours at 48°C, allowing DNA fragments to hybridize to probe-bearing beads.

Stage 5: Single-base extension and laser scanning

The chip undergoes single-base extension with fluorescently labeled dideoxynucleotides, is stained, dried, and loaded into an Illumina iScan-class laser scanner, which reads fluorescence intensity across two channels (methylated versus unmethylated signal) and outputs high-density IDAT data files.

Stage 6: AI scoring and report generation

IDAT files are processed through a bioinformatics pipeline (commonly the R minfi package) for background normalization and noise filtering, computing a beta-value for each of 850,000+ CpG sites. The resulting beta-value vector is passed into GrimAge/DunedinPACE-class models, which compute biological age, the DunedinPACE pace-of-aging index, and disease-risk scores, generating an illustrated PDF report with longevity and geroprotector recommendations delivered to the patient’s portal.