Source-news-medical.net
Breakthrough in Predicting Biological Age
In a groundbreaking study published in Nature Medicine, researchers have introduced a novel proteomic age clock that leverages plasma proteins to estimate biological age and associated health risks. This innovative clock not only predicts age with high accuracy but also provides insights into the risk of major chronic diseases, multimorbidity, and mortality across a diverse range of populations. This development represents a significant advancement over traditional methods, which often rely on chronological age as a proxy for biological aging.
Significance and Methodology
The research highlights the limitations of chronological age as a measure of biological aging, noting that it may not always accurately reflect an individual’s health status. Unlike deoxyribonucleic acid methylation (DNAm) clocks previously used to assess biological age, the new proteomic clock offers a more direct evaluation of aging mechanisms by analyzing protein levels. The study, the first to validate a proteomic age clock across large and varied populations, uses comprehensive data from the United Kingdom Biobank (UKB), China Kadoorie Biobank (CKB), and FinnGen.
Researchers developed and validated the proteomic age clock using the Olink Explore 3072 platform, focusing on the expression levels of specific proteins to predict biological age. The clock’s predictive power was assessed through a comparison of chronological age and “ProtAgeGap,” a measure of the discrepancy between chronological and biological age. The study involved 51,408 participants from the three biobanks, with extensive proteomic data processed and analyzed to create a predictive model. The gradient-boosting model (LightGBM) proved superior in accuracy, identifying 20 key proteins (ProtAge20) crucial for age prediction.
Findings and Implications
The proteomic age clock revealed a strong correlation between ProtAgeGap and various health outcomes, including chronic diseases, mortality, and aging-related conditions. The study found that ProtAgeGap was a robust predictor of multimorbidity and overall mortality, with hazard ratios indicating increased risk associated with each year of ProtAgeGap. For example, ProtAgeGap was linked to higher risks of Alzheimer’s disease, chronic kidney disease, type 2 diabetes, and several cancers, including breast and lung cancer.
The study also highlighted the proteomic clock’s ability to capture new aging-related proteins and biomarkers, which are not fully covered by DNAm clocks. Proteins involved in immune response, hormone regulation, and neuronal development were particularly influential. Despite its strengths, the study acknowledges limitations, including the use of a single platform for protein analysis and the absence of direct comparisons with DNAm clocks.
Overall, this new proteomic age clock offers a promising tool for predicting biological aging and associated health risks, potentially transforming how we assess and address age-related diseases and health management.
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