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Study summary · Biological age, epigenetics & aging clocks

Can plasma protein levels be estimated using DNA methylation (DNAm) levels, and can these estimates be combined into a robust predictor of lifespan?

In one paragraph

Comprehensive Blood-Biomarker Testing — age-adjusted DNAm PAI-1 levels were associated with lifespan (P=5.4E-28), comorbidity count (P=7.3E-56), and type 2 diabetes (P=2.0E-26). No numeric effect size is reported for Comprehensive Blood-Biomarker Testing in the source abstract. Source: Aging 2019, PMID 30669119.

Source: Aging 2019, PMID 30669119 ↗ · Research map · How Magellan grades evidence · evidence confidence: low

Aging · 2019 · PMID 30669119 · DOI 10.18632/aging.101684

Plain-English summary written and published by Magellan Longevity · medical review by Gabriel Radu, DO (physiatrist, NPI 1376861765). We summarize what the paper reported — we did not run this study.

The takeaway

A new DNA methylation-based biomarker, DNAm GrimAge, accurately predicts lifespan and various age-related health conditions.

The question

Can plasma protein levels be estimated using DNA methylation (DNAm) levels, and can these estimates be combined into a robust predictor of lifespan?

What they tested

The study implicitly hypothesizes that DNAm levels can be used to estimate plasma protein levels, and that these estimates, along with other DNAm-based factors, can form a powerful predictor of lifespan and healthspan.

How they did it

The researchers developed seven DNAm-based estimators for plasma proteins, including plasminogen activator inhibitor 1 (PAI-1) and growth differentiation factor 15. These estimators, along with a DNAm-based estimator of smoking pack-years, were consolidated into a composite biomarker called DNAm GrimAge. They also created AgeAccelGrim by adjusting DNAm GrimAge for chronological age. The predictive ability of DNAm GrimAge and AgeAccelGrim was validated using large-scale data from thousands of individuals.

What they found

DNAm GrimAge strongly predicted time-to-death (P=2.0E-75), time-to-coronary heart disease (P=6.2E-24), and time-to-cancer (P=1.3E-12). It also showed a strong relationship with fatty liver/excess visceral fat from CT data and age-at-menopause (P=1.6E-12). AgeAccelGrim was significantly associated with comorbidity count (P=3.45E-17). Age-adjusted DNAm PAI-1 levels were associated with lifespan (P=5.4E-28), comorbidity count (P=7.3E-56), and type 2 diabetes (P=2.0E-26). These biomarkers also showed expected relationships with healthy diet and educational attainment.

What it means

DNAm GrimAge and its components are powerful epigenetic biomarkers that strongly predict lifespan and healthspan, outperforming existing epigenetic clocks. These biomarkers are expected to have applications in human anti-aging research.

Limitations

The abstract does not explicitly state any limitations of the study.

Where the published abstract does not list limitations, we say so rather than inventing them. Read the full paper on PubMed before drawing conclusions.

“GrimAge stands out among epigenetic clocks for predicting time-to-death”— from the published abstract, Aging 2019

The paper at a glance

TitleDNA methylation GrimAge strongly predicts lifespan and healthspan
JournalAging
Year2019
PMID30669119 ↗
DOI10.18632/aging.101684 ↗
TopicBiological age, epigenetics & aging clocks

Read the source: PubMed record (authors, abstract, full citation) ↗ · Publisher via doi.org ↗

Where Magellan uses this paper

This citation sits behind the evidence grade on the pages below. Grades are set from the research and are independent of affiliate commissions.

Comprehensive Blood-Biomarker Testing

Many of the strongest predictors of healthy aging (glucose control, inflammation, lipid and hormonal balance) are silent until measured. Regular biomarker tracking turns aging into a set of actionable numbers and lets interventions be tailored and monitored objectively.

Epigenetic Age (DNA-Methylation Clock) Testing

DNA-methylation clocks are among the strongest available predictors of lifespan and healthspan, and second-generation clocks predict mortality risk across many conditions. They provide an objective baseline and a way to measure whether longevity interventions are moving biological age in the right direction.

Molecules & mechanisms in this paper

Each of these is named in the paper’s own words above. Open the monograph for the full mechanism and its other citations.

Cite this page

These citations point at this summary. To cite the original paper with its full author list, use the PubMed record or doi.org.

APA
Magellan Longevity. (2026). Can plasma protein levels be estimated using DNA methylation (DNAm) levels, and can these estimates be combined into a robust predictor of lifespan? [Plain-English summary of Aging 2019, PMID 30669119, DOI 10.18632/aging.101684]. Magellan Longevity. https://magellanlongevity.com/study/x10.html
BibTeX
@misc{magellan_x10, title = {Can plasma protein levels be estimated using DNA methylation (DNAm) levels, and can these estimates be combined into a robust predictor of lifespan?}, author = {{Magellan Longevity}}, year = {2026}, howpublished = {\url{https://magellanlongevity.com/study/x10.html}}, note = {Plain-English summary of PubMed PMID 30669119; DOI 10.18632/aging.101684; Aging 2019. Reviewed by Gabriel Radu, DO}, urldate = {2026-08-11} }
Permalink
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How this summary was made. Every section above restates what the published abstract of PMID 30669119 reports — the question, the design, the numbers, the authors’ own conclusion and their stated limitations. We do not add claims the paper did not make, and we keep negative and no-effect findings in. Magellan’s evidence grades are set from research like this and never from affiliate commissions.

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Educational information, not medical advice. This is a plain-English summary of published research; it is not a treatment recommendation and nothing here is intended to diagnose, treat, cure, or prevent any disease. Individual studies can be wrong, and a single paper rarely settles a question. Talk to your physician before acting on any research, especially if you are pregnant, nursing, or taking medication.