ReviewGlycoconjugate journal2016
A case for protein-level and site-level specificity in glycoproteomic studies of disease.
Review in Glycoconjugate journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Linkage Memory in Underivatized Protonated Carbohydrates.Journal of the American Society for Mass Spectrometry · 2021Article
- Article
- Parallel Determination of Polypeptide and Oligosaccharide Connectivities by Energy-Resolved Collison-Induced Dissociation of Protonated O-Glycopeptides Derived from Nonspecific Proteolysis.Journal of the American Society for Mass Spectrometry · 2020Article
- Mass Spectrometry Approaches to Glycomic and Glycoproteomic Analyses.Chemical reviews · 2018Review
- Precursor ion survival energies of protonated N-glycopeptides and their weak dependencies on high mannose N-glycan composition in collision-induced dissociation.The Analyst · 2018Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abnormal glycosylation of proteins is known to be either resultant or causative of a variety of diseases. This makes glycoproteins appealing targets as potential biomarkers and focal points of molecular studies on the development and progression of human ailment. To date, a majority of efforts in disease glycoproteomics have tended to center on either determining the concentration of a given glycoprotein, or on profiling the total population of glycans released from a mixture of glycoproteins. While these approaches have demonstrated some diagnostic potential, they are inherently insensitive to the fine molecular detail which distinguishes unique and possibly disease relevant glycoforms of specific proteins. As a consequence, such analyses can be of limited sensitivity, specificity, and accuracy because they do not comprehensively consider the glycosylation status of any particular glycoprotein, or of any particular glycosylation site. Therefore, significant opportunities exist to improve glycoproteomic inquiry into disease by engaging in these studies at the level of individual glycoproteins and their exact loci of glycosylation. In this concise review, the rationale for glycoprotein and glycosylation site specificity is developed in the context of human disease glycoproteomics with an emphasis on N-glycosylation. Recent examples highlighting disease-related perturbations in glycosylation will be presented, including those involving alterations in the overall glycosylation of a specific protein, alterations in the occupancy of a given glycosylation site, and alterations in the compositional heterogeneity of glycans occurring at a given glycosylation site. Each will be discussed with particular emphasis on how protein-specific and site-specific approaches can contribute to improved discrimination between glycoproteomes and glycoproteins associated with healthy and unhealthy states.
Indexed as
Identifiers
27007620What OpenQuestion holds
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.