Mendelian Randomization Meta-Analysis of Type 2 Diabetes and 17 Cancer Types
by Wei Wu·Updated 1mo ago
1.2 MB1files
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Description
Wei Wu's systematic review and meta-analysis synthesizes evidence from 131 Mendelian randomization studies on the causal relationship between type 2 diabetes mellitus and 17 site-specific cancers. The work, published on figshare in April 2026, includes data from 44 articles identified through searches of Scopus, PubMed, and other major databases up to June 2025. Pooled results show significant positive associations for pancreatic and endometrial cancer and negative associations for gastric cancer, melanoma, and esophageal cancer.
Use Cases
Validate causal inference models for diabetes and cancer based on pooled Mendelian randomization odds ratios.
Assess tissue-specific cancer risk profiles associated with type 2 diabetes based on the reported meta-analysis results.
Inform the design of future genetic epidemiology studies based on the systematic review of 44 included articles.
Benchmark observational study findings against genetic evidence for diabetes-cancer links described in the review.
Strengths
Includes a meta-analysis of 131 Mendelian randomization studies from 42 articles, providing quantitative pooled estimates.
Reports specific odds ratios and confidence intervals for significant associations with five cancer types.
Registered with PROSPERO (CRD420251066404), indicating a predefined protocol.
Systematically searched six major databases (Scopus, PubMed, Cochrane, Web of Science, Embase, Ovid MEDLINE).
Limitations
The dataset is a 1.2 MB DOCX file; the underlying tabular meta-analysis data may not be directly machine-readable.
Row count and column-level documentation for the extracted study data are unknown.
Freshness should be verified; the last update was 2026-04-15, but the literature search cutoff was June 2025.
Provenance
Source
Wei Wu via figshare.
Collection Method
Systematic review and meta-analysis of published Mendelian randomization studies.
Time Range
Literature published up to June 2025.
Freshness
Last updated 2026-04-15 04:37:03; literature search up to June 2025.
Geography
Global (studies from international databases).
Primary data format is a DOCX document; users may need to extract tables or numerical results manually for computational analysis.