Integrated Causal Inference and Transcriptomics Data on ChREBP in Diabetic Kidney Disease

Mingliang Liu published a 27.9 KB document on figshare in April 2026. The dataset describes an integrated study using Mendelian randomization, kidney transcriptomics, and experimental validation to investigate the role of the transcription factor ChREBP (MLXIPL) in diabetic kidney disease. It includes results from genetic inference, pathway analyses, and validation in mouse models and primary cells.

Use Cases

• Conducting Mendelian randomization analysis based on blood cis-eQTL instruments for MLXIPL.
• Performing gene set enrichment analysis (GSEA) based on MLXIPL expression stratification in kidney transcriptomic data.
• Investigating metabolic and profibrotic pathway activity using gene set variation analysis (GSVA).
• Building regulatory network models based on the described metabolic interaction landscape.
• Validating computational findings in experimental models like db/db mice and primary proximal tubular epithelial cells.

Strengths

• The study integrates multiple methodologies: Mendelian randomization, transcriptomics, network analysis, and experimental validation.
• Data is openly available under a CC-BY-4.0 license, permitting reuse with attribution.
• Analysis includes a non-diabetic stratum for urinary albumin-to-creatinine ratio (UACR) to support causal inference.

Limitations

• The dataset is a 27.9 KB DOCX file, suggesting limited raw data and a focus on summary results.
• Column-level documentation and sample data are unavailable, requiring manual inspection after download.
• Row count and the specific structure of any underlying data tables are unknown.

Provenance

Source

figshare, author Mingliang Liu.

Collection Method

Integrated analysis of public genetic and transcriptomic data (e.g., GSE30529) with experimental validation.

Time Range

The study likely uses data from the referenced public datasets (e.g., GSE30529), but the specific temporal coverage is not stated.

Freshness

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

Geography

Geographic coverage of the underlying human genetic and transcriptomic data is not specified.