Evidence map›Paper›PMID 29106475›Full record

ReviewAmerican journal of epidemiology2017

Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Large-Scale Epidemiology: A Primer on -Omic Technologies.

Peter Würtz, Antti J Kangas, Pasi Soininen, Debbie A Lawlor, George Davey Smith, Mika Ala-Korpela

Abstract readReview
In one paragraph

Review in American journal of epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 377 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
377citing 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

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

  1. Pooled it
  2. Trial
  3. Trial
  4. Effects of aged black garlic (ABG10+Frontiers in nutrition · 2026
    Trial
  5. Trial
  6. Trial
  7. Trial
  8. Article
  9. Article
  10. Article
  11. Impact of matched samples on domain harmonization in cross-cohort NMR metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Associations of plasma HDL subclasses with incident dementia risk in older adults.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Risk factors of clonal hematopoiesis of indeterminate potential.Clinical medicine (London, England) · 2026
    Article

317 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

6 authors.

Peter Würtz
Antti J Kangas
Pasi Soininen
Debbie A Lawlor
George Davey Smith
Mika Ala-Korpela

Funding

Medical Research Council MC_UU_12013/1Medical Research Council MC_UU_12013/5Wellcome Trust
6 · The paper itself

Abstract

Detailed metabolic profiling in large-scale epidemiologic studies has uncovered novel biomarkers for cardiometabolic diseases and clarified the molecular associations of established risk factors. A quantitative metabolomics platform based on nuclear magnetic resonance spectroscopy has found widespread use, already profiling over 400,000 blood samples. Over 200 metabolic measures are quantified per sample; in addition to many biomarkers routinely used in epidemiology, the method simultaneously provides fine-grained lipoprotein subclass profiling and quantification of circulating fatty acids, amino acids, gluconeogenesis-related metabolites, and many other molecules from multiple metabolic pathways. Here we focus on applications of magnetic resonance metabolomics for quantifying circulating biomarkers in large-scale epidemiology. We highlight the molecular characterization of risk factors, use of Mendelian randomization, and the key issues of study design and analyses of metabolic profiling for epidemiology. We also detail how integration of metabolic profiling data with genetics can enhance drug development. We discuss why quantitative metabolic profiling is becoming widespread in epidemiology and biobanking. Although large-scale applications of metabolic profiling are still novel, it seems likely that comprehensive biomarker data will contribute to etiologic understanding of various diseases and abilities to predict disease risks, with the potential to translate into multiple clinical settings.

Indexed as

Genome-Wide Association StudyBiomarkersCardiovascular DiseasesCause of DeathEpidemiologic MethodsHumansMagnetic Resonance SpectroscopyMendelian Randomization AnalysisMetabolomicsRisk AssessmentBiomarkersamino acidsbiomarkersdrug developmentfatty acidsMendelian randomizationmetabolomicsnuclear magnetic resonanceserum

Identifiers

PMID29106475
PMCPMC5860146

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.