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A study in Geromedicine identified 17 plasma proteins associated with all-cause mortality in older adults. Several proteins were also linked to biological-age measures across organs, and key associations were replicated in a second cohort. The findings are associations, not evidence that the proteins cause aging or can predict an individual’s lifespan.
Researchers have identified 17 plasma proteins associated with all-cause mortality among older adults, and found that several were also linked to biological-age measures across the body and individual organs. The study, published in Geromedicine, tested its key associations in a separate cohort, but does not show that the proteins cause aging or can predict an individual’s lifespan.
The team analyzed levels of 4,265 proteins in blood samples from 1,025 older adults in the LonGenity study. Participants were followed for an average of 8.05 years. Using statistical models for time-to-event outcomes, the researchers assessed whether protein levels were associated with death from any cause. They also examined links with chronic disease burden and proteome-derived measures of biological age for the whole body and specific organ systems.
Among the proteins associated with mortality, higher levels of ERBB1 and ANTXR2 were linked to lower mortality risk and younger biological-age measures across multiple organ systems. Higher levels of MIC-1/GDF15, HE4 and IGFBP-2, by contrast, were associated with higher mortality risk and older biological age across multiple systems. The report also described more specific findings: elevated MIC-1/GDF15 was associated with older organismal biological age, while ERBB1 was associated with younger liver biological age.
The researchers then evaluated their findings in 1,124 participants from the Baltimore Longitudinal Study of Aging. The report says key associations were independently replicated in this group. The study, titled “Exploring mortality-linked proteins: Understanding their association with biological aging, disease phenotypes, signaling pathways, and their implications for longevity,” was published open access in Geromedicine. Its authors include researchers from Albert Einstein College of Medicine, Stony Brook University, the National Institute on Aging, Stanford University School of Medicine, Kannur University and collaborating institutions.
How Protein Patterns May Track Aging
The results add evidence that blood proteins linked to mortality may also reflect differences in biological aging, a concept intended to capture how the body or its organs are aging rather than simply how many years a person has lived. That connection may help researchers investigate why people of similar chronological age can have different health, disease burdens and resilience.
Because the findings include associations in a discovery cohort and replication in another group, they offer candidates for further research into aging-related pathways and health outcomes. But they do not establish that changing these protein levels would reduce mortality, nor that measuring them can currently guide individual care. The work is a research finding, not a validated clinical test.
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Two Cohorts, One Protein Study
The study addresses a question in geroscience: whether measurable biological features can help explain variation in health among people of the same age. Chronological age counts elapsed time; biological-age measures attempt to reflect the condition or aging pace of the body, sometimes at the level of particular organs. In this research, those measures were derived from protein data rather than used as a direct measure of lifespan.
The analysis followed a discovery-and-validation approach. Researchers first identified mortality-associated proteins in the LonGenity cohort, then assessed key results in participants in the Baltimore Longitudinal Study of Aging. Such replication can show whether statistical relationships are also observed in a separate group, but it does not by itself explain why the relationships occur or establish their usefulness in clinical decisions.
What the Associations Cannot Show
The study establishes statistical associations, not cause and effect. It cannot determine whether the proteins contribute to aging or mortality, arise in response to other biological processes, or reflect factors not fully captured in the analysis. The source report does not provide enough detail here to assess the size of each association or how well the proteins predict outcomes for individuals.
It is also unclear whether these findings would apply in the same way to younger people or populations unlike the two older-adult cohorts. The researchers did not establish a clinical blood test, a personal lifespan estimate or a treatment based on the protein results. Further work is needed to test the biological mechanisms and determine whether any of the markers have practical value.
Testing the Findings Further
The study identifies proteins for further mechanistic and clinical investigation. Future research would need to examine how these proteins relate to aging pathways, whether the associations hold across more diverse groups, and whether they can improve prediction beyond existing health information. Studies would also need to determine whether the protein levels change over time and how such changes relate to later health outcomes.
No clinical follow-up or test was announced in the source report. For now, the results provide research leads rather than a new screening option or a basis for individual medical decisions.
Key Questions
What did the study find?
Researchers identified 17 plasma proteins associated with all-cause mortality in older adults. Several were also associated with biological-age measures across the body or specific organ systems.
Which proteins were linked to lower mortality risk?
Higher levels of ERBB1 and ANTXR2 were associated with lower mortality risk and younger biological-age measures across multiple organ systems. These are statistical associations, not proof that the proteins reduce risk.
Which proteins were linked to higher mortality risk?
Higher levels of MIC-1/GDF15, HE4 and IGFBP-2 were associated with higher mortality risk and older biological-age measures across multiple systems.
Can a blood test based on these findings predict how long someone will live?
No. The study did not establish a clinical test or show that the proteins can predict an individual’s lifespan or disease outcome.
Do the proteins cause biological aging?
The study does not show cause and effect. It found associations that require further research to explain their mechanisms and potential clinical relevance.
Source: news-medical.net
