Table 3_Identification of biomarkers in diabetic neuropathy: a Mendelian randomization and

A 9.4 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 bioinformatics on a GEO dataset (GSE148061) with 53 patients and 53 healthy donors. It identifies HSPB1, KRT14, and SFN as potential diagnostic biomarkers.

Use Cases

• Validate potential diagnostic biomarkers for diabetic neuropathy based on the identified HSPB1, KRT14, and SFN genes.
• Perform functional enrichment analysis on key genes based on pathways like the Wnt Signaling Pathway mentioned in the results.
• Replicate Mendelian randomization or machine learning (LASSO/Random Forest) analyses using the provided protein association data.
• Cross-reference identified plasma proteins with other genomic datasets for diabetic complications.

Strengths

• Analysis is based on a specific, high-throughput sequencing dataset (GSE148061) containing 106 samples (53 patients, 53 controls).
• Employs multiple analytical methods: Mendelian randomization on 4,907 proteins, two machine learning algorithms (LASSO and RF), and validation via animal models.
• Results pinpoint three specific genes (HSPB1, KRT14, SFN) with validated expression changes, offering concrete targets.

Limitations

• Row count and column-level documentation are unknown, which limits suitability assessment and requires manual inspection after download.
• The dataset is very small (9.4 KB), suggesting it contains summary results rather than raw experimental data.
• Freshness should be verified as the last update date is in the future (2026-04-27).

Provenance

Source

figshare, author Jiannan Li

Collection Method

Mendelian randomization using GWAS data and bioinformatics analysis of a GEO dataset (GSE148061).

Freshness

Last updated 2026-04-27 04:14:48