TL;DR
Get health and wellness essentials delivered free with Prime
- Fast, free delivery on millions of items
- Prime Video, Amazon Music and more included
- Member-only deals all year
Researchers analyzed blood metabolite data from 18,476 people aged 1 to 96 and developed measures associated with chronic disease and mortality risk. The measures added modest risk-discrimination value beyond several existing assessments; the observational study does not show that changing diet or lifestyle causes biological aging to slow.
Researchers used blood metabolite profiles from 18,476 people aged 1 to 96 to develop measures linked to biological aging, chronic disease and mortality risk, according to a study published in Science Translational Medicine. The findings suggest that blood chemistry may add information to health-risk assessments beyond chronological age, though the study does not establish that the measures can predict an individual’s future or that lifestyle changes directly alter aging.
The study drew on plasma samples from participants in the Shanghai Pudong Cohort, recruited across six centers. Researchers developed a metabolomic age model using 5,252 healthy participants, tested it in a separate healthy group of 5,456, and examined a disease cohort of 7,768 people. The average ages in the healthy and disease groups were 55 and 68, respectively.
For healthy participants, the team calculated metabolomic age acceleration, or how far a person’s metabolite-based age estimate differed from their actual age. For participants with existing conditions, it created a separate age-deviation measure based on mortality risk relative to what would be expected for a person’s age. A panel of 56 metabolites retained most of the age-predictive information found across 232 metabolite features.
Higher metabolomic age acceleration was associated with greater risk of developing conditions including diabetes, hypertension and fatty liver disease, as well as higher risk of death from any cause. Both measures modestly improved the ability to distinguish people at higher and lower mortality risk beyond frailty assessments, cardiovascular health scores and routine blood biomarkers. Researchers also tested their ensemble approach using data from other sources, including UK Biobank proteomic data, U.S. health-survey biomarkers and gut microbiome data.
How Blood Measures Could Add Risk Information
Chronological age is a simple measure, but people of the same age can have different health profiles. The study’s measures aim to capture some of that variation by looking at metabolites circulating in blood and relating them to health outcomes. If validated, such approaches could help researchers or clinicians identify groups whose risk may not be well represented by age alone.
The reported improvement in risk discrimination was modest, and the findings do not show that a metabolomic score should replace established clinical assessments. The potential relevance is in adding another source of information, particularly for population-level risk assessment, rather than offering a stand-alone diagnosis or an individual forecast.
As an affiliate, we earn on qualifying purchases.
Study Design and Follow-Up
Baseline assessments began in 2019. Researchers reassessed chronic disease status in 2023 and tracked deaths through January 2025. In 2023, 3,745 participants in the healthy cohort and 4,658 in the disease cohort completed repeat surveys and updated assessments; 1,500 also had repeat metabolomic profiling.
Questionnaires gathered information on diet, lifestyle, sleep, mental health and family medical history where available. The analysis linked higher metabolomic age acceleration with factors including smoking exposure, shift work and parental history of premature cardiovascular disease. It also found associations with greater consumption of some foods and lower values associated with mixed grains and exercise. These are observational associations, not evidence that any one exposure or food caused the changes.
“The findings highlight the potential of plasma metabolomic profiling for future population-level risk assessment and improved risk stratification.”
— The study authors, as summarized by News-Medical
As an affiliate, we earn on qualifying purchases.
Limits of the Aging Measures
The findings do not show that the blood-based measures can diagnose disease, determine how long an individual will live or establish why a person’s metabolite profile differs from age expectations. The reported risk-discrimination gains were modest, and the source report does not provide enough detail to judge their usefulness in routine clinical care.
Because diet and lifestyle findings came from observational data, they cannot establish cause and effect. It is also unclear from the report whether the measures perform equally well in populations outside the Shanghai cohort. The researchers’ tests using UK and U.S. datasets involved different types of biological data and do not, by themselves, establish broad clinical validation of the plasma measures.
As an affiliate, we earn on qualifying purchases.
Further Validation Before Clinical Use
The study’s results support further testing of metabolomic aging measures in independent populations and in settings where researchers can assess whether they improve decisions or health outcomes. The source report does not identify a planned clinical rollout or a timeline for additional studies.
For now, the measures are research tools. Any future use would need to clarify how reliably they work across populations, how scores should be interpreted, and whether acting on them benefits patients beyond existing risk assessments.
As an affiliate, we earn on qualifying purchases.
Key Questions
What does metabolomic age mean?
It is an estimate based on patterns of small molecules, called metabolites, measured in blood. In this study, metabolomic age acceleration described how far that estimate differed from a participant’s chronological age.
Did the study prove that diet or exercise changes biological aging?
No. The researchers found associations between some lifestyle factors and metabolomic measures, but the observational design does not establish that those factors caused changes in biological aging.
Can this blood measure predict an individual’s lifespan?
The study linked its measures with mortality risk across groups, but it does not establish that the results can predict an individual’s lifespan. The reported improvement in distinguishing higher- and lower-risk participants was modest.
Could the measure replace routine health checks?
The study does not support replacing established assessments. Its measures modestly added to risk discrimination beyond several existing measures, and further validation would be needed before any clinical role is clear.
Source: rss
Cold & flu season Picks
humidifiers
As an affiliate, we earn on qualifying purchases.
