N-Glycosylation Patterns in Human Kidney Tissues with Minor Glomerular Abnormalities

672 upregulated and 573 downregulated intact N-glycopeptides were quantified in trace renal biopsy samples from 27 patients with minor glomerular abnormalities. This dataset compares these glycopeptides against 24 distant non-neoplastic tissue samples using a pressure cycling technology-based quantitative glycoproteomics workflow. The data was published by Yingying Ling in March 2026.

Use Cases

• Classify tissue as MGA or DNT based on abundances of 1245 quantified intact N-glycopeptides.
• Identify glycoproteins associated with the PI3K-Akt signaling pathway from the 24 found with elevated IGP abundances.
• Analyze distinct N-glycosylation patterns among IgG subclasses and complement-related markers to distinguish disease states.
• Validate glycoproteomic workflows for trace-tissue analysis using the provided fold-change and p-value metrics for each IGP.

Strengths

• Quantifies 1245 significantly altered intact N-glycopeptides (672 upregulated, 573 downregulated) with defined statistical thresholds (FC >1.5 or <0.67, p < 0.05).
• Compares 27 patient-derived MGA tissue samples against 24 control distant non-neoplastic tissue samples.

Limitations

• Dataset is small in file size (65.7 KB), indicating limited raw data or highly summarized results.
• Sample size is limited to 51 total tissue samples, which may constrain statistical power for subgroup analyses.
• Specific column names and raw peptide-level data are not provided in the description, limiting reproducibility of certain analyses.

Provenance

Source

figshare, authored by Yingling Ling.

Collection Method

Data generated via a laboratory-developed pressure cycling technology-based quantitative glycoproteomics workflow integrated with high-resolution mass spectrometry.

Freshness

Last updated March 2026.

Geography

Human kidney tissues; specific geographic origin not stated.