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Purpose <p>We used Mendelian randomization (MR) analyses to examine the potential causal effects of type 2 diabetes and glycemic traits on bladder cancer risk.</p> Methods <p>Two-sample MR analyses were conducted using summary data from genome-wide association studies (GWAS). Exposures included type 2 diabetes, fasting glucose, glycosylated hemoglobin (HbA1c), fasting insulin, and proinsulin levels, with bladder cancer as the outcome. Four methods—inverse variance weighted, MR-Egger, weighted median, and weighted mode—were used to assess the causal effects. Sensitivity analyses were conducted to ensure that the results were robust.</p> Results <p>In the inverse variance weighted model, a weak positive effect was detected between genetically predicted HbA1c and bladder cancer (OR = 1.003, 95% CI = 1.0001 to 1.0052, <i>P</i> = 0.043). Other MR methods produced results with the same trend, although not all were statistically significant. However, there was no evidence to support the effect of type 2 diabetes, fasting insulin, or proinsulin levels on bladder cancer. No significant heterogeneity or pleiotropy was detected.</p> Conclusion <p>Mendelian randomization analysis indicated a mild promoting effect of increased HbA1c levels on bladder cancer risk. Further studies with larger sample sizes are needed to confirm this hypothesis.</p>

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A mendelian randomization study on the association between type 2 diabetes and the risk of bladder cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月2日

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  • Yuan He,
  • Yu Chen,
  • Chang Gao

摘要

Purpose

We used Mendelian randomization (MR) analyses to examine the potential causal effects of type 2 diabetes and glycemic traits on bladder cancer risk.

Methods

Two-sample MR analyses were conducted using summary data from genome-wide association studies (GWAS). Exposures included type 2 diabetes, fasting glucose, glycosylated hemoglobin (HbA1c), fasting insulin, and proinsulin levels, with bladder cancer as the outcome. Four methods—inverse variance weighted, MR-Egger, weighted median, and weighted mode—were used to assess the causal effects. Sensitivity analyses were conducted to ensure that the results were robust.

Results

In the inverse variance weighted model, a weak positive effect was detected between genetically predicted HbA1c and bladder cancer (OR = 1.003, 95% CI = 1.0001 to 1.0052, P = 0.043). Other MR methods produced results with the same trend, although not all were statistically significant. However, there was no evidence to support the effect of type 2 diabetes, fasting insulin, or proinsulin levels on bladder cancer. No significant heterogeneity or pleiotropy was detected.

Conclusion

Mendelian randomization analysis indicated a mild promoting effect of increased HbA1c levels on bladder cancer risk. Further studies with larger sample sizes are needed to confirm this hypothesis.