Diabetic Neuropathy Biomarkers: Mendelian Randomization and Bioinformatics Analysis

A 25.5 KB Excel file containing results from a study identifying plasma proteins and genes causally linked to diabetic neuropathy. The analysis by Jiannan Li, last updated April 27, 2026, integrated Mendelian randomization of 4,907 proteins with a gene expression dataset (GSE148061) from 106 individuals and validation via machine learning and animal models. It identifies HSPB1, KRT14, and SFN as potential diagnostic biomarkers.

Use Cases

• Validating candidate biomarkers for diabetic neuropathy based on the identified plasma proteins and genes.
• Conducting functional enrichment analysis based on pathways like Wnt Signaling and MAPK Cascade mentioned in the results.
• Training diagnostic models using the LASSO and Random Forest-identified key genes (HSPB1, KRT14, SFN).
• Performing colocalization analysis to support causal inference from Mendelian randomization findings.

Strengths

• Results are derived from Mendelian randomization analysis of 4,907 plasma proteins.
• Validation utilized a gene expression dataset (GSE148061) containing 53 patients and 53 healthy donors.
• Findings were further validated using two machine learning algorithms and a mouse model.

Limitations

• Row count and column-level documentation are absent; field semantics must be inferred after download.
• The dataset is very small at 25.5 KB, indicating limited scope, likely containing summary results rather than raw data.
• Last updated 2026-04-27 04:14:49; freshness should be verified as the date is in the future.

Provenance

Source

figshare, author Jiannan Li

Collection Method

Analysis integrated Mendelian randomization using GWAS data, differential gene analysis of GEO dataset GSE148061, and machine learning validation.

Freshness

Last updated 2026-04-27 04:14:49