ArticleNature communications2017
Network inference from glycoproteomics data reveals new reactions in the IgG glycosylation pathway.
Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 42 papers.
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Who cites it
42 citing papers in PubMed.
- Large glycomics datasets as a tool to understand the function of glycans.Nature chemical biology · 2026Review
- Glycoproteomic and genetic analysis of N-glycosylation of complement component C3 reveals immune pathway regulation.Genome biology · 2026Article
- Immunoglobulin G Subclass-Specific Glycosylation Changes in Rheumatoid Arthritis.International journal of molecular sciences · 2025Article
- Immune and inflammatory resolution pathways through multi-omics using the AI-based Network Integration.Research square · 2025Article
- Serum Disease-Specific IgG Fc Glycosylation as Potential Biomarkers for Nonproliferative and Proliferative Diabetic Retinopathy Using Mass Spectrometry.Molecular & cellular proteomics : MCP · 2025Article
- Site-specific immunoglobulin G N-glycosylation is associated with gastric cancer progression.BMC cancer · 2025Article
- The role of antibody glycosylation in autoimmune and alloimmune kidney diseases.Nature reviews. Nephrology · 2024Review
- The genetics and epidemiology of N- and O-immunoglobulin A glycomics.Genome medicine · 2024Article
- Deciphering disease through glycan codes: leveraging lectin microarrays for clinical insights.Acta biochimica et biophysica Sinica · 2024Review
- Expanding N-glycopeptide identifications by modeling fragmentation, elution, and glycome connectivity.Nature communications · 2024Article
- Article
- Accelerating Bayesian inference of dependency between mixed-type biological traits.PLoS computational biology · 2023Article
- Article
- Leveraging IgG N-glycosylation to infer the causality between T2D and hypertension.Diabetology & metabolic syndrome · 2023Article
- CHOGlycoNET: Comprehensive glycosylation reaction network for CHO cells.Metabolic engineering · 2023Article
- Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.Molecular medicine (Cambridge, Mass.) · 2023Article
- Article
- GeneNetTools: tests for Gaussian graphical models with shrinkage.Bioinformatics (Oxford, England) · 2022Article
- High-Throughput Glycomic Methods.Chemical reviews · 2022Review
- Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.PLoS pathogens · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
31 authors.
Funding
Abstract
Immunoglobulin G (IgG) is a major effector molecule of the human immune response, and aberrations in IgG glycosylation are linked to various diseases. However, the molecular mechanisms underlying protein glycosylation are still poorly understood. We present a data-driven approach to infer reactions in the IgG glycosylation pathway using large-scale mass-spectrometry measurements. Gaussian graphical models are used to construct association networks from four cohorts. We find that glycan pairs with high partial correlations represent enzymatic reactions in the known glycosylation pathway, and then predict new biochemical reactions using a rule-based approach. Validation is performed using data from a GWAS and results from three in vitro experiments. We show that one predicted reaction is enzymatically feasible and that one rejected reaction does not occur in vitro. Moreover, in contrast to previous knowledge, enzymes involved in our predictions colocalize in the Golgi of two cell lines, further confirming the in silico predictions.
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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.