Single-Nucleus RNA-Seq of Human Adipose Tissue from Type 2 Diabetes Patients and Controls

13 scWAT biopsies from 6 patients with type 2 diabetes and 7 non-diabetic controls were profiled by single-nucleus RNA sequencing. The dataset, authored by Haibin Ji and last updated in May 2026, contains integrated transcriptomic data used to analyze adipocyte and immune cell states, differential expression, and intercellular communication. It supports the investigation of mitochondrial stress and defective waste clearance in adipose tissue inflammation.

Use Cases

• Identify stress-enriched adipocyte states based on upregulated mitophagy and vesicle trafficking signatures.
• Map intercellular communication between adipocytes and lipid-associated macrophages using inferred ligand-receptor interactions.
• Analyze immunometabolic module scores and pathway activity in specific macrophage subsets.
• Construct pseudotime trajectories to model the differentiation and functional states of lipid-associated macrophages.

Strengths

• Data is derived from 13 human subcutaneous white adipose tissue biopsies, providing a direct human tissue context.
• Analysis includes multiple advanced methods: snRNA-seq, COMPASS metabolic flux inference, CellChat ligand-receptor analysis, and pseudotime trajectory modeling.
• Dataset is openly available under a CC-BY-4.0 license, permitting reuse with attribution.

Limitations

• The dataset is small in file size (820.7 KB), suggesting it may contain processed results or summary statistics rather than raw sequencing data.
• Row count and column-level documentation are unknown, requiring manual inspection after download to understand the data structure.
• The sample size of 13 individuals may limit the statistical power for detecting subtle effects.

Provenance

Source

figshare, authored by Haibin Ji.

Collection Method

Single-nucleus RNA sequencing (snRNA-seq) of human subcutaneous white adipose tissue biopsies.

Freshness

Last updated 2026-05-04 08:38:49