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

Mingliang Liu's 2026 study integrates Mendelian randomization, kidney transcriptomics, and experimental validation to identify the transcription factor ChREBP (MLXIPL) as a driver of metabolic remodeling in diabetic kidney disease. The 16.3 KB document, shared under a CC-BY-4.0 license, details methods and results from genetic inference, network analyses, and validation in db/db mice and primary cells. This work provides a mechanistic rationale for targeting the MLXIPL/ChREBP axis to mitigate residual renal risk.

Use Cases

• Validate causal gene-disease hypotheses based on the described two-sample Mendelian randomization approach.
• Analyze metabolic pathway activity in diabetic kidney disease based on the MLXIPL-high/low stratification and GSEA/GSVA results.
• Study gene regulatory networks in renal injury based on the described network analyses positioning MLXIPL/ChREBP.
• Investigate lipogenic target gene expression (e.g., Acly, Acaca, Fasn, Srebf1) in high-glucose conditions based on the experimental validation.

Strengths

• The dataset is associated with a detailed, multi-method study integrating genetic inference, transcriptomics, and experimental validation.
• The document is licensed under CC-BY-4.0, permitting broad reuse with attribution.
• The study design addresses confounding from tissue remodeling and cellular compositional shifts in advanced disease.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The primary data file is a 16.3 KB DOCX document, which likely contains textual results rather than raw, structured data tables.

Provenance

Source

figshare, authored by Mingliang Liu.

Collection Method

Integrated analysis of two-sample Mendelian randomization, kidney transcriptomic data (GSE30529), network analyses, and experimental validation in db/db mice and primary proximal tubular epithelial cells.

Time Range

The study was last updated in April 2026; specific temporal coverage of the underlying data is not provided.

Freshness

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

Geography

Spatial coverage is not specified.