ArticleAging cell2025
Healthy Aging Metabolomic and Proteomic Signatures Across Multiple Physiological Compartments.
Article in Aging cell, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Citrulline drives age-related lipid deposition for healthspan.Nature communications · 2026Article
- Point-of-care Diagnostic Framework for Fibromyalgia Using Integrated Vibrational Spectroscopy and Metabolomics.Research square · 2026Article
- Plasma Proteomic Profiling of Young and Older Adults Identifies Candidate Biomarkers of Biological Aging at the Intersection of Age and Disease.Aging cell · 2026Article
- Age-Related Neurovascular Dysfunction in the Retina and Potential Pathogenic Mechanisms.Investigative ophthalmology & visual science · 2026Review
- Receptor-Mitochondria Crosstalk in the Kynurenine Metabolic Pathway: Integrating Metabolomics and Clinical Mass Spectrometry.Antioxidants (Basel, Switzerland) · 2026Review
- Metabolic deficits and immune dysfunction in aging people living with HIV.Immunometabolism (Cobham, Surrey) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
The study of biomarkers in biofluids and tissues expanded our understanding of the biological processes that drive physiological and functional manifestations of aging. However, most of these studies were limited to examining one biological compartment, an approach that fails to recognize that aging pervasively affects the whole body. The simultaneous modeling of hundreds of metabolites and proteins across multiple compartments may provide a more detailed picture of healthy aging and point to differences between chronological and biological aging. Herein, we report proteomic analyses of plasma and urine collected in healthy men and women, age 22-92 years. Using these data, we developed a series of metabolomic and proteomic predictors of chronological age for plasma, urine, and skeletal muscle. We then defined a biological aging score, which measures the departure between an individual's predicted age and the expected predicted age for that individual based on the full cohort. We show that these predictors are significantly and independently related to clinical phenotypes important for aging, such as inflammation, iron deficiency anemia, muscle mass, and renal and hepatic functions. Despite a different set of selected biomarkers in each compartment, the different scores reflect a similar degree of deviation from healthy aging in single individuals, thus allowing identification of subjects with significant accelerated or decelerated biological aging.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.