I found your study on microRNAs and pro-inflammatory cytokines as candidate biomarkers for male infertility highly insightful, particularly the integration of immunological and epigenetic markers. I am interested in applying a similar approach in my research on infertility biomarkers, and I have a few methodological questions regarding your experimental design and data interpretation.
1. The study uses RNU6B and GAPDH as housekeeping genes for miRNA and mRNA normalization, respectively. Given that miRNA expression can be context-dependent, was the stability of these reference genes validated across your sample groups? Would alternative normalization strategies (e.g., small nucleolar RNAs or geometric averaging of multiple reference genes) impact the robustness of your results?
2. The paper highlights that SNP variants in miR-425 and miR-429 reduce ΔG, leading to prolonged miRNA circulation. Were decay kinetics directly measured, or was this conclusion drawn solely from computational free-energy predictions? Including experimental confirmation, such as miRNA stability assays in serum, could further validate this hypothesis.
3. While statistical significance is reported for several parameters, details on multiple testing corrections (e.g., Bonferroni or FDR adjustments) are not mentioned. Given the large number of comparisons, how was the risk of false positives managed?
4. The results suggest that TNF-α and IL-1α levels negatively correlate with sperm motility and morphology. However, were confounding factors such as lifestyle, BMI, or oxidative stress markers considered? These factors could independently affect semen quality and cytokine levels, influencing the observed relationships.
As a researcher who read this paper, I would like to share my perspective on your comment:
1. The authors likely skipped reference gene validation because their priority was linking miRNAs to infertility, not optimizing normalization methods. Using standard genes (RNU6B/GAPDH) kept things simple and comparable to past studies.
2. They took a practical approach: “Do these miRNAs correlate with infertility?” not “How exactly do they persist longer?” The free-energy data hints at a mechanism, but proving it would need another study.
3. With only a few key biomarkers tested, fancy multiple-test corrections might’ve been overkill. The consistent results (e.g., miRNAs always higher in infertile men) suggest the findings hold water.
4. They smartly ruled out major diseases but ignored lifestyle factors, probably because those would’ve muddied their core question about immune/epigenetic links.
To the Authors:
Please correct me anywhere I explained mistakenly. Given that the paper is already published, any clarifications you can provide here would be invaluable for readers interpreting your work. Your insights on these points would help bridge the gap between methodology and interpretation!