Integrated Causal Inference and Kidney Transcriptomics Data for Diabetic Kidney Disease

A 16.0 KB document published on figshare by Mingliang Liu in April 2026. It contains integrated data from a study using Mendelian randomization, kidney transcriptomic stratification, and experimental validation to investigate the role of the ChREBP transcription factor in diabetic kidney disease. The study integrates genetic inference, network biology, and validation in mouse models and primary cells.

Use Cases

• Validate causal gene-disease relationships based on Mendelian randomization results mentioned in the description
• Analyze metabolic pathway activity based on MLXIPL-high/low stratification and GSEA/GSVA results
• Study gene regulatory networks in kidney disease based on the described network inference
• Correlate transcriptomic signatures with profibrotic and proliferative remodeling mentioned in the results

Strengths

• Data is integrated from multiple methodological approaches, including genetic inference, transcriptomics, and experimental validation.
• The study design includes a non-diabetic control stratum for urinary albumin-to-creatinine ratio analysis.
• Key findings were validated in db/db mice and primary proximal tubular epithelial cells.

Limitations

• The dataset is a 16.0 KB DOCX file, indicating a very limited scope likely focused on summary results rather than raw data.
• Row count and column-level documentation are absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Collection Method

Integrated from two-sample Mendelian randomization, kidney transcriptomics (GSE30529), network analyses, and experimental validation in db/db mice and primary cells.

Time Range

The study's temporal coverage is not explicitly stated in the input.

Freshness

Last updated 2026-04-15 05:42:59; freshness should be verified.

Geography

The study's spatial coverage is not explicitly stated in the input.