#AI Reads Urine# Healthy Aging Metabolomic and Proteomic Signatures Across Multiple Physiological Compartments

Plasma and urine samples were collected from 101 healthy participants (aged 22 - 92 years) at baseline and 65 at 2 - year follow - up from the GESTALT study. Participants had to meet strict inclusion criteria, such as being free of major diseases, having no chronic medication use (except one antihypertensive drug), and having a BMI less than 30kg/m2. The Olink Explore 1536 platform based on Proximity Extension Assay (PEA) was used to measure proteins in plasma and urine. This technology can detect up to 1536 proteins in 90 samples simultaneously with a small sample volume.

Plasma Proteome Associated With Age: 475 plasma proteins were age - associated at baseline. Top age - associated proteins were related to inflammation, cellular senescence, extracellular matrix (ECM), and mitochondrial function. For example, GDF15, a senescence - associated protein, was highly age - associated. STRING enrichment analysis confirmed the involvement of inflammation - related pathways.

Urine Proteome Associated With Age: 113 urine proteins were age - associated at baseline. Many age - associated proteins in urine were related to inflammation and ECM, indicating a decline in kidney function with age. For example, LIF was over - represented, while its receptor LIFR was under - represented.

The use of Olink's proximity extension assay (PEA), a targeted proteomics approach, indeed raises concerns about selection bias potentially influencing the identification results in blood and urine samples. The pre - selected proteins in Olink analysis are chosen based on specific research interests, existing knowledge, or the availability of probes.

In contrast, untargeted proteomics offers a more comprehensive and exploratory approach:

Discovery of Novel Proteins: Untargeted proteomics can identify a vast number of proteins without prior assumptions. This allows for the discovery of new proteins that may be associated with aging in blood and urine. These novel proteins could potentially represent new biomarkers or key players in aging - related biological processes that were previously unknown. For example, it might uncover proteins involved in unique metabolic pathways or cell - cell communication mechanisms that are altered during aging.

Unbiased View of the Proteome: It provides an unbiased view of the entire proteome present in the sample. Instead of focusing on specific proteins, untargeted methods capture a wide range of proteins, including those from different functional categories, cellular compartments, and biological pathways. This comprehensive view can reveal complex relationships and interactions within the proteome that may not be apparent in targeted analysis. It could show how proteins from seemingly unrelated pathways are interconnected during the aging process in blood and urine.

The study found significant age - related alterations in ECM across compartments. The developed metabolomic and proteomic molecular signatures correlated with clinical parameters, suggesting they can capture accelerated aging. Future research should focus on larger cohorts and exploring the causal relationships between identified biomarkers and aging - related phenotypes.

Aging Cell. 2025 Feb 14:e70014. doi: 10.1111/acel.70014.

Youhe Gao

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