Evidence map›Paper›PMID 33565652›Full record

ReviewMass spectrometry reviews2022

Quantitative clinical glycomics strategies: A guide for selecting the best analysis approach.

Milani W Patabandige, Leah D Pfeifer, Hanna T Nguyen, Heather Desaire

Open access · greenAbstract readReview
In one paragraph

Review in Mass spectrometry reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.6field-weighted citation impact, top 16% of its field
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

15 citing papers in PubMed, 27 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. The Role of Clinical Glyco(proteo)mics in Precision Medicine.Molecular & cellular proteomics : MCP · 2023
    Article
  9. Article
  10. Review
  11. Article
  12. Comparison of denaturing agent effects in enzymaticTurkish journal of chemistry · 2022
    Article
  13. Article
  14. The Hitchhiker's guide to glycoproteomics.Biochemical Society transactions · 2021
    Review
  15. 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

4 authors at 1 institution in 1 country.

Milani W PatabandigeDepartment of Chemistry, Ralph N. Adams Institute for Bioanalytical Chemistry, University of Kansas, Lawrence, Kanas, USA.
Leah D PfeiferDepartment of Chemistry, Ralph N. Adams Institute for Bioanalytical Chemistry, University of Kansas, Lawrence, Kanas, USA.
Hanna T NguyenDepartment of Chemistry, Ralph N. Adams Institute for Bioanalytical Chemistry, University of Kansas, Lawrence, Kanas, USA.
Heather DesaireDepartment of Chemistry, Ralph N. Adams Institute for Bioanalytical Chemistry, University of Kansas, Lawrence, Kanas, USA.
University of Kansas · US

Funding

Mass Spectrometry Measurements for Complex PTMsR35GM130354 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI DESAIRE, HEATHER R · 2019 to 2023
$1.9M
NIGMS NIH HHS R35 GM130354
6 · The paper itself

Abstract

Glycans introduce complexity to the proteins to which they are attached. These modifications vary during the progression of many diseases; thus, they serve as potential biomarkers for disease diagnosis and prognosis. The immense structural diversity of glycans makes glycosylation analysis and quantitation difficult. Fortunately, recent advances in analytical techniques provide the opportunity to quantify even low-abundant glycopeptides and glycans derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Understanding the strengths and weaknesses of different quantitative glycomics analysis methods is important for selecting the best strategy to analyze glycosylation changes in any given set of clinical samples. To provide guidance towards selecting the proper approach, we discuss four widely used quantitative glycomics analysis platforms, including fluorescence-based analysis of released N-linked glycans and three different varieties of MS-based analysis: liquid chromatography (LC)-mass spectrometry (MS) analysis of glycopeptides, matrix-assisted laser desorption ionization-time of flight MS, and LC-ESI-MS analysis of released N-linked glycans. These methods' strengths and weaknesses are compared, particularly associated with the figures of merit that are important for clinical biomarker studies, including: the initial sample requirements, the methods' throughput, sample preparation time, the number of species identified, the methods' utility for isomer separation and structural characterization, method-related challenges associated with quantitation, repeatability, the expertise required, and the cost for each analysis. This review, therefore, provides unique guidance to researchers who endeavor to undertake a clinical glycomics analysis by offering insights on the available analysis technologies.

Indexed as

GlycomicsPolysaccharidesChromatography, LiquidGlycopeptidesMass SpectrometrySpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationGlycopeptidesPolysaccharides

Identifiers

PMID33565652
PMCPMC8601598
OpenAlexW3128606470

What OpenQuestion holds

Textmetadata
LicenceTDM
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.