Somewhere in the long human effort to read the body's signs, a study of nearly seventeen and a half thousand Europeans has asked whether the proteins circulating in blood can reveal how old a person truly is, beyond the years on their birth certificate. Drawn from Spain, Italy, Britain, Germany and the Netherlands, and followed for up to twenty-eight years, these adults suggest that the gap between biological and calendar age carries quiet information about illness and death. The findings echo what people have long intuited: that smoking, drinking and stillness leave marks that run deeper than
Blood Protein Clocks Flag Accelerated Aging and Higher Risk of Death and Chronic Disease
Somewhere in the long human effort to read the body's signs, a study of nearly seventeen and a half thousand Europeans has asked whether the proteins circulating in blood can reveal how old a person truly is, beyond the years on their birth certificate. Drawn from Spain, Italy, Britain, Germany and the Netherlands, and followed for up to twenty-eight years, these adults suggest that the gap between biological and calendar age carries quiet information about illness and death. The findings echo what people have long intuited: that smoking, drinking and stillness leave marks that run deeper than appearance. Yet the work remains an observation rather than a verdict, and whether these molecular clocks will earn a place beside familiar risk factors awaits testing in wider populations.
Researchers gathered blood plasma from 17,473 adults aged 35 to 75 across five European countries, all enrolled in the large EPIC study of cancer and nutrition. They read the proteins in each sample to estimate how old the body was, then compared that figure with each person's actual age. Followed for as long as 28 years, the participants offered a long view of how the gap between the two numbers related to what came next.
The team combined five existing protein-based aging clocks into one overall measure, and also calculated age for individual organs. Disease cases were drawn from registries, hospital records and death data. After accounting for body weight, smoking, drinking, diet, activity and education, a clear pattern emerged: faster aging was linked to inactivity, alcohol and smoking, but not to body mass or diet quality.
The overall clock tracked with a wide range of outcomes, including heart disease, stroke, dementia and several cancers, and it predicted death from any cause about as well as established risk factors did. Combined with those factors, it sharpened predictions further. The organ-specific clocks were most telling for their own organs, linking kidney aging to kidney cancer and lung aging to lung cancer. Sensitivity checks, including a replication in the British Whitehall II cohort, produced broadly similar results, though some cancer associations weakened.
The authors are careful about what this means. The study is observational and cannot prove cause. Before protein clocks could sit alongside smoking and inactivity in everyday risk assessment, they would need testing in more diverse populations, genetic analysis and trials in primary care.
Researchers drew blood plasma from 17,473 adults across five European countries, then read the proteins in it to estimate how old their bodies really were. The adults were between 35 and 75 and came from Spain, Italy, the United Kingdom, Germany, and the Netherlands. All were part of the European Prospective Investigation into Cancer and Nutrition, known as EPIC, and they were followed for as long as 28 years. The results, published in Nature Aging, suggest that the gap between a person's protein-based age and their calendar age carries real information about who will get sick and who will die.
The team used the SomaScan proteomic platform to analyze the samples. They took five existing proteomic clocks, named for Tanaka, Lehallier, Wang, Oh, and Sathyan, and averaged their age estimates and age gaps into a single measure called the Global clock. They also calculated organ-specific aging. Disease cases were identified through disease registries, care and drug registers, hospitalization records, and mortality data, and were classified with ICD-10 codes.
The statistical models adjusted for body mass index, smoking status, alcohol intake, a healthy diet score, physical activity, and educational attainment. The researchers then repeated the work in participants of the British Whitehall II cohort. They also ran sensitivity analyses limited to never-smokers and to events occurring after the first two or five years of follow-up.
On lifestyle, faster aging on the Global clock was associated with physical inactivity, alcohol intake, and smoking. Body mass index and diet quality showed no association with the Global age gap, and the links varied from one individual clock to another.
On health outcomes, a more advanced biological age relative to chronological age was tied to higher risk of cardiovascular disease, dementia, and cancers of the oral cavity, pharynx, larynx, esophagus, liver, lung, and kidney. The Global clock had a hazard ratio of 1.4 for death from any cause. Each additional year of age gap was linked to a higher mortality risk, with estimates ranging from 5.0% to 13%. For coronary heart disease and stroke the ratios were 1.3 to 1.4, and for dementia 1.2. Among cancers, the Global clock gave ratios of 1.6 for liver, 1.5 for upper aero-digestive tract, and 1.3 each for lung and kidney.
The organ-specific clocks were most telling for the organs they measured. Kidney biological age was linked most strongly to kidney cancer, at 1.6. Lung aging and intestinal aging each carried a ratio of 1.4 for lung cancer and stomach cancer, respectively. The sensitivity analyses gave largely similar results, though the kidney and lung cancer associations weakened.
The Global clock predicted death from any cause about as well as established risk factors do. Combining the clock with those risk factors predicted mortality better than the risk factors alone. The authors suggest that, if added to routine investigations, protein profiles could one day help clinicians stratify risk and judge prognosis, and could point to the molecular pathways connecting aging to chronic disease.
The study is observational, so it cannot establish causality. The authors say validation is needed in more diverse populations, alongside genetic analyses and primary-care trials. Only then could proteome-based aging measures sit next to alcohol, smoking, and inactivity in risk assessment protocols.
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