ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2022
A Metabolomic Aging Clock Using Human Cerebrospinal Fluid.
Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01720810 (Pacific Northwest Udall Center), which is not on this map. Cited by 36 papers.
What it found
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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.
Pacific Northwest Udall Center (PANUC) Clinical Core
Who cites it
36 citing papers in PubMed, 42 citations in OpenAlex.
- Metabolomic profiles impacted by brief mindfulness intervention with contributions to improved health.Scientific reports · 2025Trial
- Estimation of biological age and age-related outcomes with easily accessible parameters in Chinese.GeroScience · 2026Article
- Peripheral transcriptomic aging acceleration in major depressive disorder: the mediating role of insular cortex alterations.Psychological medicine · 2026Article
- Article
- Functional, molecular, and digital measurements of biological age.The Journal of clinical investigation · 2026Review
- The Evolving Landscape of Clinical Aging Clocks: From Epigenetic to Multi-Omics Integration.Aging cell · 2026Review
- Untargeted and Targeted Cerebrospinal Fluid Neurometabolomics via Chromatography-Mass Spectrometry-Based Methods.Molecules (Basel, Switzerland) · 2026Review
- Amino acid-based biological age clock and its implications for human health and aging.Nature communications · 2026Article
- Blood biomarkers and breed genetics of aging in pet dogs.bioRxiv : the preprint server for biology · 2026Article
- Histone modification clocks for robust cross-species biological age prediction and elucidating senescence regulation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Preksha Dhyana meditation modulates the serum metabolome in healthy and meditation-naïve participants.Frontiers in molecular biosciences · 2026Article
- Review
- Microvascular Health as a Key Determinant of Organismal Aging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Rationale and design of the Dog Aging Project precision cohort: a multi-omic resource for longitudinal research in geroscience.GeroScience · 2025Article
- DoliClock: a lipid-based aging clock reveals accelerated aging in neurological disorders.Aging · 2025Article
- Metabolism and metabolomics in senescence, aging, and age-related diseases: a multiscale perspective.Frontiers of medicine · 2025Review
- Plasma triacylglycerol length and saturation level mark healthy aging groups in humans.GeroScience · 2025Article
- Cerebrospinal fluid metabolomics, lipidomics and serine pathway dysfunction in myalgic encephalomyelitis/chronic fatigue syndroome (ME/CFS).Scientific reports · 2025Article
- Robust Metabolomic Age Prediction Based on a Wide Selection of Metabolites.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- A Novel Metabolomic Aging Clock Predicting Health Outcomes and Its Genetic and Modifiable Factors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
Corrections and comments
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Authors and funding
17 authors at 4 institutions in 1 country.
Funding
Abstract
Quantifying the physiology of aging is essential for improving our understanding of age-related disease and the heterogeneity of healthy aging. Recent studies have shown that, in regression models using "-omic" platforms to predict chronological age, residual variation in predicted age is correlated with health outcomes, and suggest that these "omic clocks" provide measures of biological age. This paper presents predictive models for age using metabolomic profiles of cerebrospinal fluid (CSF) from healthy human subjects and finds that metabolite and lipid data are generally able to predict chronological age within 10 years. We use these models to predict the age of a cohort of subjects with Alzheimer's and Parkinson's disease and find an increase in prediction error, potentially indicating that the relationship between the metabolome and chronological age differs with these diseases. However, evidence is not found to support the hypothesis that our models will consistently overpredict the age of these subjects. In our analysis of control subjects, we find the carnitine shuttle, sucrose, biopterin, vitamin E metabolism, tryptophan, and tyrosine to be the most associated with age. We showcase the potential usefulness of age prediction models in a small data set (n = 85) and discuss techniques for drift correction, missing data imputation, and regularized regression, which can be used to help mitigate the statistical challenges that commonly arise in this setting. To our knowledge, this work presents the first multivariate predictive metabolomic and lipidomic models for age using mass spectrometry analysis of CSF.
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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.