Cross-Ancestry GWAS Results for Gestational Diabetes Mellitus

A 56.8 KB Excel file presents results from a meta-analysis of genome-wide association studies for gestational diabetes mellitus. The analysis integrated data from British, Finnish, and Chinese populations to identify novel genetic loci and pathways. The dataset was authored by Wendi Zhao and last updated in April 2026.

Use Cases

• Prioritizing candidate genes (ELL2, ATRAID) for functional validation based on multi-ancestry GWAS signals.
• Investigating cross-population genetic correlations for gestational diabetes using the Popcorn method mentioned in the description.
• Conducting pathway enrichment analysis based on the three identified biological pathways (regulation of hexokinase activity, insulin, and protein).
• Fine-mapping ancestry-specific genetic signals using the SuSiEx approach referenced in the study methods.

Strengths

• Results are derived from a multi-ancestry meta-analysis integrating British, Finnish, and Chinese GWAS data.
• The study employed a multi-pronged functional annotation approach including FUMA, eQTL mapping, and proteomic data integration.
• The dataset is openly available under a CC-BY-4.0 license.

Limitations

• Row count and specific column-level documentation are unknown, requiring manual inspection after download.
• The dataset's small size (56.8 KB) suggests it contains summary-level results, not individual-level genetic data.
• Data may reflect the geographic and methodological biases inherent to the source GWAS studies from figshare.

Provenance

Source

figshare, authored by Wendi Zhao.

Collection Method

Meta-analysis of GWAS datasets, with functional annotation and pathway enrichment analyses.

Time Range

null

Freshness

Last updated 2026-04-23 04:21:34; freshness should be verified.

Geography

Data sourced from British, Finnish, and Chinese populations.