The Science Behind the GlycanAge Test: 30 Years of Research, 350+ Published Papers

Biological age testing built on glycans isn't a new idea rushed to market. It's the public-facing result of more than 30 years of glycan biomarker research and 350+ peer-reviewed papers examining how IgG glycosylation, the pattern of sugar molecules attached to antibodies, tracks immune function and chronic inflammation as people age. What began as academic research into a specific class of biomarkers has become one of the most extensively validated approaches to measuring biological age, and one increasingly used to test whether health interventions are actually changing the underlying biology.

For a closer look at how these sugar structures work and what they reveal about the immune system, see Glycans: The Sugars That Reveal Your Biological Age and Immune Health.

A chronology of discovery

"I've been in this field for nearly 30 years. What fascinated me from the start was the complexity of glycans — they're several orders of magnitude more complex than DNA or proteins, and wherever we looked, glycans were part of all biological processes."

— Prof. Gordan Lauc, Co-Founder and Chief Scientific Officer, GlycanAge; Professor of Biochemistry and Molecular Biology, University of Zagreb

The scientific foundation goes back to early population studies establishing that specific IgG glycan structures move with chronological age in a measurable, reproducible way. A landmark study published in The Journals of Gerontology modelled this relationship across four independent population cohorts, including the Orkney Complex Disease Study, Vis, Korcula and TwinsUK, and found the association held consistently across all of them rather than in a single dataset.

From there, glycan biomarker research expanded well beyond a single ageing model. A 2020 analysis of the EPIC-Potsdam cohort, covering more than 27,000 participants and published in Diabetes Care, used N-glycan profiling to help predict incident type 2 diabetes and cardiovascular disease years ahead of diagnosis. Subsequent research applied the same underlying biology to menopause and hormone replacement therapy, exercise, weight loss and chronic inflammatory conditions, with each study adding to a growing, cross-validated evidence base rather than standing alone.

This body of work has never been confined to a single lab. Academic collaborations with the University of Oxford, Harvard Medical School and the University of Edinburgh have extended glycan biomarker research into cardiovascular risk, immune ageing and population epidemiology, adding independent scrutiny that no single research group could provide alone. Cardiovascular findings co-authored with Harvard Medical School researchers, published in Circulation Research, extended the glycan-inflammation link specifically to heart disease risk, while epidemiological work from Edinburgh has situated glycan-based ageing alongside other major biological age measures.

Peer-review at scale

What separates glycan biomarker research from many newer biological age markers is scale. The evidence base spans more than 30 years, 350+ published, peer-reviewed papers, and over 300,000 glycan samples analysed to date, generating the kind of statistical power that single-cohort studies cannot match. The original GlycanAge index was built using a training-and-validation split across thousands of samples, then tested again on entirely separate populations to confirm the pattern wasn't a quirk of one dataset. More than €40 million in research and development grant funding has supported this work over the years, much of it channelled through independent academic collaborations rather than internal product development alone.

This matters for interpretation. A biomarker validated once, in one cohort, is a hypothesis. A biomarker that holds up across multiple independent populations, disease areas and intervention types, replicated over three decades, is closer to an established measurement tool, which is the bar glycan biomarker research has been held to from the outset.

The original population model illustrates why. Built on a training set and confirmed against a separate validation set, it explained a substantial share of the variation in chronological age, with a correlation between predicted and actual age strong enough to be considered clinically meaningful, and the pattern held when the same model was applied to three further, entirely independent cohorts. That kind of cross-population replication, rather than a single strong result, is what peer review at this scale is designed to test for. The underlying laboratory work has also been carried out under CLIA-certified conditions, the same quality standard applied to clinical diagnostic testing more broadly, adding a further layer of methodological accountability to the research.

Why glycans are a functional, not static, marker

Unlike DNA-based markers, which capture inherited, largely fixed information, IgG glycosylation is a functional marker: it reflects what is actually happening in the body's immune system, not what a person was born with. Glycosylation is the process by which glycans, chains of sugar molecules, attach to proteins such as IgG. As a person ages, or experiences disease, inflammation or lifestyle change, this pattern shifts in measurable, well-characterised ways.

"It did look to us that glycans were a useful marker of real biological age, as opposed to simply measuring what we could measure anyway from our calendars. There's a lot of prospect there, specifically in terms of prognostic tests for health arising out of glycans."

— Dr. Peter Joshi, Chief Scientist, Humanity Health; University of Edinburgh

That responsiveness is what peer-reviewed research points to when it describes IgG glycans as a predictive biomarker for biological age, providing considerably more insightful information than any single static marker, such as telomere length, which offers a narrower, less dynamic view. Because glycans move with biology rather than staying fixed at birth, research has been able to link specific glycosylation shifts to hormone therapy, weight change, exercise and chronic inflammatory disease, giving each study something to actually measure over time.

Glycan biomarker research also sits alongside, rather than replacing, epigenetic ageing clocks. First- and second-generation epigenetic clocks can vary by roughly 1.7 to 4 years at a population level depending on which clock is used, since DNA methylation-based measures are sensitive to model choice. IgG glycosylation is measured from a stable, well-characterised set of glycan structures, offering a more consistent readout that doesn't depend on which specific epigenetic model is used for comparison, a distinction that matters increasingly as more ageing clocks enter the research literature.

In work directly comparing the two approaches in the same cohort, one of the researchers involved described the difference in real terms:

"In Steve's original study, the median error was around four years, but in our study, testing an external data set, the median error was 1.7 years. In lay terms, for half of the individuals in our test population, we were able to predict their age to within 1.7 years."

— Prof. Riccardo Marioni, PhD, Chair of Molecular Epidemiology of Ageing, University of Edinburgh

IgG glycosylation is measured from a stable, well-characterised set of glycan structures, offering a readout that doesn't depend on which specific epigenetic model or generation of clock is used for comparison — a distinction that matters increasingly as more ageing clocks enter the research literature.

Where the science is heading

The direction of travel for glycan biomarker research points toward precision prevention. Early studies already show N-glycan profiles improving the accuracy of established risk scores for cardiometabolic disease, and ongoing research continues to extend glycan-based models into new disease areas, hormonal transitions and intervention tracking. As the evidence base grows past 350 published papers and hundreds of thousands of analysed samples, the case for glycans as a core biomarker in preventative medicine, one capable of showing whether an intervention is changing biology rather than simply relieving symptoms, continues to strengthen.

What started as a research question in population genetics laboratories has become a measurement tool with genuine clinical and public health relevance. The next decade of glycan biomarker research is likely to be defined less by proving that glycans track biological age, a case the literature has already made, and more by how that tool gets used in preventative medicine, from earlier detection of inflammatory risk to genuinely personalised, evidence-based interventions.

Ready to see where your own biology stands? Explore GlycanAge testing kits.

External sources

• Krištić J, Vučković F, Menni C, Klarić L, Keser T, Beceheli I, et al. Glycans are a novel biomarker of chronological and biological ages. J Gerontol A Biol Sci Med Sci. 2014;69(7):779–789. doi:10.1093/gerona/glt190. PMID: 24325898. PMC: https://pmc.ncbi.nlm.nih.gov/articles/PMC4049143/

• Wittenbecher C, Štambuk T, Kuxhaus O, Rudman N, Vučković F, Štambuk J, et al. Plasma N-glycans as emerging biomarkers of cardiometabolic risk: a prospective investigation in the EPIC-Potsdam cohort study. Diabetes Care. 2020;43(3):661–668. doi:10.2337/dc19-1507. PMID: 31915204. No PMC — https://pubmed.ncbi.nlm.nih.gov/31915204/

• Menni C, Keser T, Mangino M, Bell JT, Erte I, Akmačić I, et al. Glycosylation of immunoglobulin G: role of genetic and epigenetic influences. PLoS One. 2013;8(12):e82558. doi:10.1371/journal.pone.0082558. PMID: 24324808. PMC: https://pmc.ncbi.nlm.nih.gov/articles/PMC3855797/

• Hoshi RA, Plavša B, Liu Y, Trbojević-Akmačić I, Glynn RJ, Ridker PM, et al. N-Glycosylation profiles of immunoglobulin G and future cardiovascular events. Circ Res. 2024;134(5):e3–e14. doi:10.1161/CIRCRESAHA.123.323623. PMID: 38348651. PMC: https://pmc.ncbi.nlm.nih.gov/articles/PMC10923145/

• Macdonald-Dunlop E, Taba N, Klarić L, Frkatović A, Walker R, Hayward C, et al. A catalogue of omics biological ageing clocks reveals substantial commonality and universal parameters of complex biological ageing. Aging (Albany NY). 2022;14(2):623–659. doi:10.18632/aging.203847. PMID: 35073279. PMC: https://pmc.ncbi.nlm.nih.gov/articles/PMC8833109/