Integrated Causal Inference and Transcriptomics Data for Diabetic Kidney Disease Research

A 17.5 KB research document from figshare, last updated on 2026-04-15. The dataset, authored by Mingliang Liu, integrates Mendelian randomization, kidney transcriptomic stratification, network analyses, and experimental validation to investigate the role of the transcription factor ChREBP (MLXIPL) in diabetic kidney disease.

Use Cases

• Conducting genetic causal inference based on Mendelian randomization using cis-eQTL instruments for MLXIPL.
• Performing pathway enrichment analysis (GSEA/GSVA) on kidney transcriptomic data stratified by MLXIPL expression.
• Validating transcriptomic findings in experimental models like db/db mice and primary proximal tubular epithelial cells.
• Building network models of metabolic interaction and regulatory landscapes centered on MLXIPL/ChREBP.

Strengths

• Integrates multiple analytical methods (Mendelian randomization, transcriptomics, network analysis, experimental validation).
• Includes validation in non-diabetic individuals and experimental models (db/db mice, PTECs).
• Released under a permissive CC-BY-4.0 license.
• Author and last update date (2026-04-15) are explicitly provided.

Limitations

• The dataset is a 17.5 KB DOCX file, indicating a limited scope focused on research findings rather than raw data.
• Column-level documentation and sample data are unavailable, requiring manual inspection after download.
• Row count and specific data formats for underlying analyses are unknown.

Provenance

Source

figshare, author Mingliang Liu.

Collection Method

Integrated analysis of genetic data, kidney transcriptomics (GSE30529), and experimental validation.

Time Range

The research document was last updated in 2026; the temporal coverage of the underlying data is not specified.

Freshness

Last updated 2026-04-15 05:43:03.

Geography

Spatial coverage is not specified.