Table 2_Identification of biomarkers in diabetic neuropathy: a Mendelian randomization and

A 9.6 KB Excel file containing results from a study identifying plasma proteins causally linked to diabetic neuropathy. The analysis used Mendelian randomization on 4,907 proteins and validated findings with machine learning and a mouse model. The dataset was authored by Jiannan Li and last updated on 2026-04 27.

Use Cases

• Validate potential diagnostic biomarkers for diabetic neuropathy based on identified plasma proteins.
• Perform secondary analysis on gene enrichment pathways mentioned, such as the Wnt Signaling Pathway.
• Replicate or compare machine learning methods (LASSO and Random Forest) for biomarker selection.
• Investigate the causal role of specific genes (HSPB1, KRT14, SFN) in disease pathogenesis.

Strengths

• Results are derived from a multi-method study integrating Mendelian randomization, bioinformatics, and animal model validation.
• The analysis considered a large number of potential biomarkers, specifically 4,907 plasma proteins.
• The dataset is openly available under a CC-BY-4.0 license.

Limitations

• Row count and column-level documentation are unknown, requiring manual inspection after download.
• The dataset is very small (9.6 KB), indicating limited scope, likely containing summary results rather than raw data.
• Description metadata is limited; actual data quality and structure must be verified.

Provenance

Source

figshare

Collection Method

Results from a Mendelian randomization and bioinformatics analysis study.

Time Range

The study likely reflects data available up to its publication date, but the specific temporal coverage of the underlying GWAS and GEO data is not stated.

Freshness

Last updated 2026-04-27 04:14:48; freshness should be verified.

Geography

Geographic coverage of the underlying human and mouse model data is not specified.