Integrated Causal Inference and Kidney Transcriptomics Data for Diabetic Kidney Disease

Mingliang Liu published a research document on figshare in April 2026. The 18.1 KB DOCX file integrates two-sample Mendelian randomization, kidney transcriptomic stratification, network analyses, and experimental validation to identify ChREBP (MLXIPL) as a driver of maladaptive metabolic remodeling in diabetic kidney disease.

Use Cases

• Validate causal gene-disease relationships based on Mendelian randomization analysis described in the study.
• Analyze metabolic pathway activity in diabetic kidney disease based on MLXIPL-high/low stratification and GSEA/GSVA results.
• Study the regulatory network of ChREBP in renal injury based on the integrated network biology and experimental validation.
• Investigate the link between glucose-responsive transcription factors and lipogenic targets like Acly and Acaca in proximal tubular epithelial cells.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• Research integrates multiple methodologies: Mendelian randomization, transcriptomics, network analysis, and experimental validation.
• Last updated on 2026-04-15, indicating recent availability.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is a 18.1 KB DOCX file, suggesting limited scope and likely containing textual results rather than raw data.

Provenance

Source

figshare, author Mingliang Liu.

Collection Method

Integrated analysis of genetic inference, kidney transcriptomics, network biology, and experimental validation.

Time Range

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Freshness

Last updated 2026-04-15 05:43:05; freshness should be verified.

Geography

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