Evidence map›Paper›PMID 33704614›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2021

NMR metabolomic profiles associated with long-term risk of prostate cancer.

Lucie Lécuyer, Agnès Victor Bala, Aicha Demidem, Adrien Rossary, Nadia Bouchemal, Mohamed Nawfal Triba, Pilar Galan, Serge Hercberg, Valentin Partula, Bernard Srour and 7 more

Abstract read
PubMed Publisher
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023
    Article
  9. Targeting Glutamine Metabolism in Prostate Cancer.Frontiers in bioscience (Elite edition) · 2023
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Potential of nuclear magnetic resonance metabolomics in the study of prostate cancer.Indian journal of urology : IJU : journal of the Urological Society of India
    Review
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

17 authors.

Lucie LécuyerInserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France.
Agnès Victor BalaChemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France.
Aicha DemidemINRAE, UMR 1019, Human Nutrition Unit (UNH), Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Clermont Auvergne University, CRNH Auvergne, 63000, Clermont-Ferrand, France.
Adrien RossaryINRAE, UMR 1019, Human Nutrition Unit (UNH), Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Clermont Auvergne University, CRNH Auvergne, 63000, Clermont-Ferrand, France.
Nadia BouchemalChemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France.
Mohamed Nawfal TribaChemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France.
Pilar GalanInserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France.
Serge HercbergInserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France.
Valentin PartulaInserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France.
Bernard SrourInserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France.
Paule Latino-MartelInserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France.
Emmanuelle Kesse-GuyotInserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France.
Nathalie Druesne-PecolloInserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France.
Marie-Paule VassonINRAE, UMR 1019, Human Nutrition Unit (UNH), Cellular Micro-Environment, Immunomodulation and Nutrition (ECREIN), Clermont Auvergne University, CRNH Auvergne, 63000, Clermont-Ferrand, France.
Mélanie Deschasaux-TanguyInserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France. m.deschasaux@eren.smbh.univ-paris13.fr.ORCID 0000-0002-3359-420X
Philippe SavarinChemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), Nanomédecine Biomarqueurs Détection (NBD), The National Center for Scientific Research (CNRS) 7244, Sorbonne Paris Nord University, 93017, Bobigny Cedex, France.
Mathilde TouvierInserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - University of Paris (CRESS), Sorbonne Paris Nord University, SMBH Paris 13, 74 rue Marcel Cachin, 93017, Bobigny Cedex, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionProstate cancer is a multifactorial disease whose aetiology is still not fully understood. Metabolomics, by measuring several hundred metabolites simultaneously, could enhance knowledge on the metabolic changes involved and the potential impact of external factors.

objectivesThe aim of the present study was to investigate whether pre-diagnostic plasma metabolomic profiles were associated with the risk of developing a prostate cancer within the following decade.

methodsA prospective nested case-control study was set up among the 5141 men participant of the SU.VI.MAX cohort, including 171 prostate cancer cases, diagnosed between 1994 and 2007, and 171 matched controls. Nuclear magnetic resonance (NMR) metabolomic profiles were established from baseline plasma samples using NOESY1D and CPMG sequences. Multivariable conditional logistic regression models were computed for each individual NMR signal and for metabolomic patterns derived using principal component analysis.

resultsMen with higher fasting plasma levels of valine (odds ratio (OR) = 1.37 [1.07-1.76], p = .01), glutamine (OR = 1.30 [1.00-1.70], p = .047), creatine (OR = 1.37 [1.04-1.80], p = .02), albumin lysyl (OR = 1.48 [1.12-1.95], p = .006 and OR = 1.51 [1.13-2.02], p = .005), tyrosine (OR = 1.40 [1.06-1.85], p = .02), phenylalanine (OR = 1.39 [1.08-1.79], p = .01), histidine (OR = 1.46 [1.12-1.88], p = .004), 3-methylhistidine (OR = 1.37 [1.05-1.80], p = .02) and lower plasma level of urea (OR = .70 [.54-.92], p = .009) had a higher risk of developing a prostate cancer during the 13 years of follow-up.

conclusionsThis exploratory study highlighted associations between baseline plasma metabolomic profiles and long-term risk of developing prostate cancer. If replicated in independent cohort studies, such signatures may improve the identification of men at risk for prostate cancer well before diagnosis and the understanding of this disease.

Indexed as

AdultBiomarkers, TumorCase-Control StudiesHumansLogistic ModelsMagnetic Resonance ImagingMagnetic Resonance SpectroscopyMaleMetabolomicsMiddle AgedProspective StudiesProstatic NeoplasmsBiomarkers, TumorMetabolomicsNuclear magnetic resonanceProspective studyProstate cancer risk

Identifiers

What OpenQuestion holds

Textmetadata
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.