Evidence map›Paper›PMID 34512391›Full record

ReviewFrontiers in physiology2021

Towards Building a Quantitative Proteomics Toolbox in Precision Medicine: A Mini-Review.

Alejandro Correa Rojo, Dries Heylen, Jan Aerts, Olivier Thas, Jef Hooyberghs, Gökhan Ertaylan, Dirk Valkenborg

Registry-linked trialAbstract readReview
In one paragraph

Review in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06208072 (The Predictive Role of Urinary Proteomics in Blood Pressure Response of Obese Hypertensive Treated With Irbesartan or Eplerenone.), which is not on this map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–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.

NCT06208072 naunknown statusnot on this mapstarted 2023, after this paper: background citation

The Predictive Role of Urinary Proteomics in Blood Pressure Response of Obese Hypertensive Treated With Irbesartan or Eplerenone.

TypeinterventionalSponsorHippocration General HospitalRan2023 to 2025Enrolled50ConditionsPrimary Hypertension, ObesityArmsIrbesartan 150mg, Eplerenone 25 mg
3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Physiological and Proteomic Responses of the TetraploidInternational journal of molecular sciences · 2024
    Article
  6. [Molecular pathological analysis through the ages].Pathologie (Heidelberg, Germany) · 2024
    Review
  7. Review
  8. Review
  9. Article
  10. Recent methodological advances towards single-cell proteomics.Proceedings of the Japan Academy. Series B, Physical and biological sciences · 2023
    Review
  11. Review
  12. Article
  13. 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

7 authors.

Alejandro Correa RojoData Science Institute, Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Hasselt University, Diepenbeek, Belgium.
Dries HeylenData Science Institute, Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Hasselt University, Diepenbeek, Belgium.
Jan AertsData Science Institute, Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Hasselt University, Diepenbeek, Belgium.
Olivier ThasData Science Institute, Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Hasselt University, Diepenbeek, Belgium.
Jef HooyberghsFlemish Institute for Technological Research (VITO), Mol, Belgium.
Gökhan ErtaylanFlemish Institute for Technological Research (VITO), Mol, Belgium.
Dirk ValkenborgData Science Institute, Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Hasselt University, Diepenbeek, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision medicine as a framework for disease diagnosis, treatment, and prevention at the molecular level has entered clinical practice. From the start, genetics has been an indispensable tool to understand and stratify the biology of chronic and complex diseases in precision medicine. However, with the advances in biomedical and omics technologies, quantitative proteomics is emerging as a powerful technology complementing genetics. Quantitative proteomics provide insight about the dynamic behaviour of proteins as they represent intermediate phenotypes. They provide direct biological insights into physiological patterns, while genetics accounting for baseline characteristics. Additionally, it opens a wide range of applications in clinical diagnostics, treatment stratification, and drug discovery. In this mini-review, we discuss the current status of quantitative proteomics in precision medicine including the available technologies and common methods to analyze quantitative proteomics data. Furthermore, we highlight the current challenges to put quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data with genomics data for future applications in precision medicine.

Indexed as

bioinformaticsbiomarker discoveryclinical diagnosticsprecision medicineprotein quantitative trait lociquantitative proteomicstargeted techniques

Identifiers

PMID34512391
PMCPMC8427610

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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.