Table 5_Identification of biomarkers in diabetic neuropathy: a Mendelian randomization and

A 17.0 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 in April 2026, employed Mendelian randomization on GWAS data for 4,907 proteins and validated findings using machine learning and a mouse model. The dataset likely contains the identified biomarkers and associated analysis results.

Use Cases

• Validate potential diagnostic biomarkers for diabetic neuropathy based on the identified HSPB1, KRT14, and SFN genes.
• Investigate protein-mediated pathogenesis pathways in diabetic neuropathy based on the seven identified plasma proteins.
• Perform functional enrichment analysis on key genes based on the described Wnt Signaling Pathway and MAPK Cascade associations.
• Benchmark machine learning algorithms for biomarker selection based on the described use of LASSO and Random Forest methods.

Strengths

• Analysis is based on Mendelian randomization of GWAS data for 4,907 plasma proteins.
• Findings were validated through multiple methods including Bayesian colocalization, two machine learning algorithms, and an animal model.
• Dataset is shared under a permissive CC-BY-4.0 license.

Limitations

• Row count and column-level documentation are unknown, which limits suitability assessment.
• The dataset is very small at 17.0 KB, indicating limited raw data scope.
• Freshness should be verified as the last update is dated in the future (2026-04-27).

Provenance

Source

figshare, author Jiannan Li

Collection Method

Results from Mendelian randomization, bioinformatics analysis of GEO dataset GSE148061, and experimental validation.

Freshness

Last updated 2026-04-27 04:14:50