Blood Tests of Ageing Face Off: Brain Scans and Epigenetic Clocks Beat Organ Clocks at Predicting Death

What makes one 73-year-old thrive while another of the same age declines rapidly? A landmark study of Scottish older adults has now put the most fashionable ageing biomarkers through a head-to-head contest, and the results are reshaping how scientists think about measuring biological age. Researchers followed 861 members of the Lothian Birth Cohort 1936 for an average of 16 years, recording 444 deaths, and compared 23 different ageing measures for their power to forecast who would die. Their verdict: the much-hyped proteomic organ clocks, which estimate the biological age of individual organs from blood proteins, do predict mortality, but they are outperformed by an epigenetic clock, brain scans, lung function tests and simple cognitive assessments.

The study, published in Aging Cell, is among the first to benchmark eleven proteomic organ clocks against molecular, imaging, cognitive and physical biomarkers within a single population. The organ clocks were originally developed by mapping thousands of plasma proteins to their tissues of origin and training mathematical models to predict chronological age for organs including the brain, heart, liver, kidney, immune system and arteries. When the researchers applied these clocks to the Scottish cohort, they found substantial heterogeneity: organs within the same person appeared to age at strikingly different rates, and the organ age gaps were only mildly correlated with one another, with a mean pairwise correlation of 0.32. Extreme ageing, defined as an organ age gap exceeding two standard deviations from the population mean, most commonly affected just a single organ rather than several at once.

Despite this biological richness, the organ clocks delivered only modest prognostic power. Each standard deviation of accelerated organ ageing corresponded to a 16 to 43 percent higher mortality hazard over the follow-up period. The strongest effects emerged for the liver, with a hazard ratio of 1.43, followed by the immune system at 1.42 and the heart at 1.38. The proteomic brain age gap, at a hazard ratio of 1.31, performed almost identically to a brain age gap derived from magnetic resonance imaging, which scored 1.30. These findings replicate the original organ clock study, which reported a 17 to 53 percent mortality increase per standard deviation in a separate American cohort, confirming that the approach generalises across populations.

Yet several other biomarkers left the organ clocks behind. The clear champion was GrimAge2, a second-generation epigenetic clock that estimates biological age from DNA methylation patterns in blood. A single standard deviation of GrimAge2 acceleration conferred a 62 percent higher mortality hazard, the largest effect of any biomarker tested. Close behind came structural brain measures: smaller total brain volume raised mortality risk by 52 percent per standard deviation, and smaller grey matter volume by 44 percent. Reduced lung function also proved formidable, with a one-second forced expiratory volume deficit carrying a 51 percent higher hazard, and poorer general cognitive function adding 46 percent. All of these surpassed every proteomic organ clock in effect size.

The researchers then asked which biomarkers carried independent information when all were considered simultaneously. In a multivariable Cox model including 21 ageing measures among the 460 participants with complete data, only four survived: total brain volume, white matter hyperintensity volume, general cognitive function and walking time. GrimAge2, despite its stellar univariable performance, lost significance, not because it lacks biological relevance but because much of its prognostic signal overlaps with correlated measures. Together, the four independent biomarkers explained roughly 19 percent of the variance in mortality risk, while all 21 biomarkers combined raised that figure only to 23 percent, suggesting diminishing returns from adding further measures.

The variance decomposition was equally revealing. Chronological age and sex accounted for just 2 percent of mortality risk, with lifestyle factors adding 4 percent. GrimAge2 contributed a further 6 percent, proteomic organ clocks 8 percent and physical function measures 9 percent. Brain-related measures, combining neuroimaging and cognition, accounted for around 16 percent, roughly double any other single domain. For the authors, this underscores that brain health, encompassing atrophy, cerebrovascular damage and cognitive capacity, is a particularly powerful window on survival in old age, likely because the brain regulates essential physiological functions and because atrophy captures neurodegenerative processes long before clinical diagnosis.

Beyond benchmarking clocks, the team mined the full plasma proteome for mortality signals. Using the SomaScan 11K platform, which quantifies nearly 10,000 protein targets from a small plasma sample, they identified 368 proteins significantly associated with all-cause mortality after adjustment for age and sex. The strongest positive associations belonged to GDF15, a stress- and inflammation-induced cytokine, with a hazard ratio of 1.56, followed by WFDC2 at 1.47 and TIMP1 at 1.45. Notably, GDF15 ranked as the second strongest mortality predictor overall, behind only GrimAge2, and three of the nine proteins whose DNA methylation surrogates are built into GrimAge2 appeared among the top twenty. On the protective side, higher circulating levels of neuropeptide S, BAGE3 and ABCC6 each corresponded to roughly 41 to 42 percent lower mortality risk per standard deviation.

Gene set enrichment analysis revealed a striking functional dichotomy among these proteins. Those whose higher levels predicted death were overwhelmingly enriched for immune processes, including antimicrobial humoral immune responses, chemokine and cytokine activity, and interleukin-4 and interleukin-13 signalling, painting a picture of inflammaging and immunosenescence, the chronic low-grade inflammation and immune decline that characterise ageing. Proteins associated with survival, by contrast, were enriched for genomic integrity: nucleosome assembly, regulation of the G2/M cell cycle transition, damaged DNA binding and ribosome biogenesis. Among the protective candidates were Sirtuin-2 and Caspase-2, both involved in DNA damage response and tumour suppression, with higher levels linked to 18 and 32 percent lower mortality risk respectively. An elastic net penalised regression across all 9,703 protein targets distilled the signal to just 37 proteins, with GDF15 carrying the largest positive coefficient and strong concordance with the univariate results.

The study has limitations the authors acknowledge. The cohort consists of relatively healthy, ethnically homogeneous Scots born in 1936, so validation in more diverse populations is needed. The analyses relied on single baseline measurements rather than longitudinal trajectories, examined all-cause rather than cause-specific mortality, and depended on one proteomics platform. The findings are observational and cannot establish causality. Still, the practical implications are considerable: simple, inexpensive measures such as walking speed, lung function and cognition rival or exceed costly molecular assays, while integrative biomarkers trained directly on mortality outcomes, like GrimAge2, currently offer the strongest single-molecule performance. Whether organ clocks add value for cause-specific mortality, such as distinguishing cardiac from neurological deaths, remains an open question.

What emerges is a clear message for the booming biological-ageing industry: no single number captures how fast someone is ageing. Organs age at their own pace, blood proteins tell one story, brain scans another, and the most informative forecast comes from combining complementary measures across modalities. As the world’s population over 60 doubles to a projected 2.1 billion by 2050, choosing the right combination of biomarkers could determine who benefits from early intervention, and the new results suggest that protecting the brain, preserving lung capacity and taming chronic inflammation may matter more than any single molecular clock.

Subject of Research: Multimodal ageing biomarkers and plasma proteomic signatures associated with all-cause mortality in older adults

Article Title: Multimodal Ageing Biomarkers and Plasma Proteomic Signatures Associated With All‐Cause Mortality

Article References: Pyrgioti, M., Eguiagaray, I. M., Redmond, P., Corley, J., Bastin, M. E., Hernández, M. V., Russ, T. C., Wardlaw, J. M., Hannon, E., Deary, I. J., Walker, K. A., Tucker‐Drob, E. M., Cox, S. R., Marioni, R. E., & Harris, S. E. (2026). Multimodal Ageing Biomarkers and Plasma Proteomic Signatures Associated With All‐Cause Mortality. Aging Cell, 25(10), Article e70747. https://doi.org/10.1111/acel.70747

Image Credits: AI Generated

DOI: 10.1111/acel.70747

Keywords: biological age, proteomic organ clocks, epigenetic clock, GrimAge2, all-cause mortality, plasma proteomics, GDF15, brain atrophy, cognitive function, lung function, immunosenescence, Lothian Birth Cohort 1936