Evidence map›Paper›PMID 22834969›Full record

ArticleAging cell2012

Human serum metabolic profiles are age dependent.

Zhonghao Yu, Guangju Zhai, Paula Singmann, Ying He, Tao Xu, Cornelia Prehn, Werner Römisch-Margl, Eva Lattka, Christian Gieger, Nicole Soranzo and 12 more

Abstract readMulticenter Study
In one paragraph

Article in Aging cell, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 199 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
199citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

199 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Co-expression network multivariate regression.Briefings in bioinformatics · 2026
    Article
  6. Review
  7. Metabolomics Data Analysis with TIGER.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  8. Article
  9. Phenotypic and metabonomics studies of FMOs in C. elegans and their roles in lifespan extension.Metabolomics : Official journal of the Metabolomic Society · 2025
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Mechanisms and markers of lung ageing in health and disease.European respiratory review : an official journal of the European Respiratory Society · 2025
    Review

139 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Zhonghao YuResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
Guangju Zhai
Paula Singmann
Ying He
Tao Xu
Cornelia Prehn
Werner Römisch-Margl
Eva Lattka
Christian Gieger
Nicole Soranzo
Joachim Heinrich
Marie Standl
Elisabeth Thiering
Kirstin Mittelstraß
Heinz-Erich Wichmann
Annette Peters
Karsten Suhre
Yixue Li
Jerzy Adamski
Tim D Spector
Thomas Illig
Rui Wang-Sattler

Funding

Wellcome Trust
6 · The paper itself

Abstract

Understanding the complexity of aging is of utmost importance. This can now be addressed by the novel and powerful approach of metabolomics. However, to date, only a few metabolic studies based on large samples are available. Here, we provide novel and specific information on age-related metabolite concentration changes in human homeostasis. We report results from two population-based studies: the KORA F4 study from Germany as a discovery cohort, with 1038 female and 1124 male participants (32-81 years), and the TwinsUK study as replication, with 724 female participants. Targeted metabolomics of fasting serum samples quantified 131 metabolites by FIA-MS/MS. Among these, 71/34 metabolites were significantly associated with age in women/men (BMI adjusted). We further identified a set of 13 independent metabolites in women (with P values ranging from 4.6 × 10(-04) to 7.8 × 10(-42) , α(corr) = 0.004). Eleven of these 13 metabolites were replicated in the TwinsUK study, including seven metabolite concentrations that increased with age (C0, C10:1, C12:1, C18:1, SM C16:1, SM C18:1, and PC aa C28:1), while histidine decreased. These results indicate that metabolic profiles are age dependent and might reflect different aging processes, such as incomplete mitochondrial fatty acid oxidation. The use of metabolomics will increase our understanding of aging networks and may lead to discoveries that help enhance healthy aging.

Indexed as

MetabolomicsAdultAgedAged, 80 and overAge FactorsAgingBiomarkersBody Mass IndexFatty AcidsFemaleFlow Injection AnalysisHumansMaleMetabolomeMiddle AgedMultivariate AnalysisBiomarkersFatty Acids

Identifiers

PMID22834969
PMCPMC3533791

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.