Commentary on “Complex causal association between immune cell phenotypes and bladder cancer: a Mendelian randomization and mediation study”

Dear Editor,

We read with great interest the article by Li et al^[1] entitled “Complex Causal Association Between Immune Cell Phenotypes And Bladder Cancer: A Mendelian Randomization and Mediation Study”. The authors conducted a comprehensive bidirectional Mendelian randomization (MR) analysis to explore the causal relationships between 731 immune cell phenotypes and bladder cancer (BCa), further employing mediation analysis to identify potential metabolic pathways. Their work represents a significant step forward in understanding the immunogenetic mechanisms underlying BCa pathogenesis. In accordance with the TITAN 2025 guidelines for AI transparency^[2], a generative AI-based language model was used solely to polish the language and had no bearing on the scientific content.

The study robustly applied MR methods, including inverse variance weighted, MR-Egger, and MR-PRESSO, to control for pleiotropy and reverse causation. The identification of 16 immunophenotypes significantly associated with BCa risk – particularly the strong signal for CD4+/CD8+ ratio – provides valuable insights into the immune microenvironment’s role in bladder carcinogenesis. The mediation analysis further highlights the potential role of metabolites such as ribitol, choline, and alanine in mediating immune-related carcinogenesis, suggesting novel mechanistic pathways worthy of experimental validation.

However, we would like to raise a few points for consideration:

1. Clinical interpretability of effect sizes: While the odds ratios (ORs) reported are statistically significant, many are very close to 1 (e.g. OR = 1.001). Although such effects are common in MR studies due to the scale of genetic instruments, their biological and clinical relevance may require further contextualization.

2. Population generalizability: The GWAS data for immune cells and metabolites are derived predominantly from European populations. Given known ethnic disparities in immune response and BCa incidence, it would be beneficial to discuss the limitations regarding generalizability to non-European populations.

3. Mediation analysis interpretation: The mediation analysis is intriguing but preliminary. Were multiple-testing corrections applied to the metabolite analyses? Additionally, the directionality and biological plausibility of these metabolite pathways could be further discussed in light of existing cancer metabolism literature.

4. Potential confounding by smoking: Smoking is a major risk factor for BCa and also influences immune profiles. While MR helps mitigate confounding, residual bias due to smoking-associated genetic variants cannot be entirely ruled out. Did the authors consider using smoking-related SNPs as covariates or in multivariable MR?

In conclusion, Li et al^[1] have delivered a methodologically rigorous and insightful study that enhances our understanding of the immune-BCa axis. Their findings open new avenues for immunotherapeutic strategies and biomarker development. We look forward to future studies validating these associations in independent cohorts and functional models.

Ethical approval

This letter is not applicable.

Consent

Not applicable.

Sources of funding

This work was supported by grants from the Chongqing Natural Science Foundation General Program (No. CSTB2024NSCQ-MSX1163), the China Postdoctoral Science Foundation (No. 2025MD774159), and the National Natural Science Foundation of China (No. 82372881).

Author contributions

All authors have edited the manuscript.

Conflicts of interest disclosure

The authors have no conflicts of interest to declare.

Research registration unique identifying number (UIN)

Not applicable.

Guarantor

Weiyang He.

Provenance and peer review

Not commissioned.

Data availability statement

The data that support the findings of this study are all included in this article.