Quantitative Glycoproteomics Patterns in Human Kidney Tissues

Yingying Ling's dataset contains quantitative glycoproteomics data comparing intact N-glycopeptides (IGPs) between 24 distant non-neoplastic kidney tissues and 27 renal biopsy samples from patients with minor glomerular abnormalities (MGA). It identifies 672 upregulated and 573 downregulated IGPs in MGA tissues based on fold-change and p-value thresholds. The data was published on figshare in March 2026.

Use Cases

• Identify upregulated IGPs (FC > 1.5, p < 0.05) as potential biomarkers for minor glomerular abnormalities.
• Analyze distinct N-glycosylation patterns among IgG subclasses to differentiate MGA from healthy tissue.
• Investigate the 24 glycoproteins associated with the PI3K-Akt signaling pathway for mechanistic insights into MGA pathogenesis.
• Validate pressure cycling technology-based glycoproteomics workflows for trace-tissue analysis using the provided IGP quantification data.

Strengths

• Quantifies 1,245 total differentially regulated IGPs (672 upregulated, 573 downregulated).
• Compares samples from two distinct cohorts: 24 control tissues and 27 MGA patient biopsies.

Limitations

• Dataset is very small at 11.6 KB, indicating limited raw data or summary-level results only.
• Specific sample-level data, raw spectra, or columnar peptide/protein measurements are not visible in the provided description.

Provenance

Source

figshare, author Yingying Ling.

Collection Method

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 unknown.