Evidence map›Paper›PMID 37184129›Full record

Observational studyAging cell2023

Unraveling the metabolic underpinnings of frailty using multicohort observational and Mendelian randomization analyses.

Jonathan K L Mak, Laura Kananen, Chenxi Qin, Ralf Kuja-Halkola, Bowen Tang, Jake Lin, Yunzhang Wang, Tuija Jääskeläinen, Seppo Koskinen, Yi Lu and 3 more

Abstract readObservational Study
In one paragraph

Observational study in Aging cell, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

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

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. A seven-year longitudinal study of the Alzheimer's disease blood metabolome.medRxiv : the preprint server for health sciences · 2025
    Article
  8. Metabolomics-based identification and validation of the creatine precursor guanidinoacetic acid for frailty in older adults.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Temporal Dynamics of Epigenetic Aging and Frailty From Midlife to Old Age.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024
    Article
  17. Review
  18. Article
  19. Observational
  20. Observational
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

13 authors.

Jonathan K L MakDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0003-4454-8580
Laura KananenDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0003-3742-8927
Chenxi QinDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Ralf Kuja-HalkolaDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Bowen TangDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Jake LinDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Yunzhang WangDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Tuija JääskeläinenFinnish Institute for Health and Welfare, Helsinki, Finland.
Seppo KoskinenFinnish Institute for Health and Welfare, Helsinki, Finland.
Yi LuDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Patrik K E MagnussonDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Sara HäggDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0002-2452-1500
Juulia JylhäväDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying metabolic biomarkers of frailty, an age-related state of physiological decline, is important for understanding its metabolic underpinnings and developing preventive strategies. Here, we systematically examined 168 nuclear magnetic resonance-based metabolomic biomarkers and 32 clinical biomarkers for their associations with frailty. In up to 90,573 UK Biobank participants, we identified 59 biomarkers robustly and independently associated with the frailty index (FI). Of these, 34 associations were replicated in the Swedish TwinGene study (n = 11,025) and the Finnish Health 2000 Survey (n = 6073). Using two-sample Mendelian randomization, we showed that the genetically predicted level of glycoprotein acetyls, an inflammatory marker, was statistically significantly associated with an increased FI (β per SD increase = 0.37%, 95% confidence interval: 0.12-0.61). Creatinine and several lipoprotein lipids were also associated with increased FI, yet their effects were mostly driven by kidney and cardiometabolic diseases, respectively. Our findings provide new insights into the causal effects of metabolites on frailty and highlight the role of chronic inflammation underlying frailty development.

Indexed as

FrailtyMendelian Randomization AnalysisBiomarkersGenome-Wide Association StudyHumansMagnetic Resonance SpectroscopyMetabolomicsPolymorphism, Single NucleotideBiomarkersbiomarkersfrailtyMendelian randomizationmetabolomicstwins

Identifiers

PMID37184129
PMCPMC10410014

What OpenQuestion holds

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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.