Comments on “TREM1 deficiency attenuates LPS-induced sepsis-associated acute kidney injury by modulating macrophage polarization”

Dear Editor, We read with great interest the article by Xu et al, titled “TREM1 Deficiency Attenuates LPS-induced Sepsis-associated Acute Kidney Injury by Modulating Macrophage Polarization”, published in International Journal of Surgery (DOI: 10.1097/JS9.000000000003836)[1]. The study elucidates a novel mechanism by which TREM1 deficiency reprograms macrophage polarization via the PI3K/AKT and STAT6 signaling pathways. This work provides valuable insights into the immunopathogenesis of SA-AKI and highlights a potential therapeutic target. We believe there are several aspects worth discussing that could further strengthen these insightful findings, thereby enhancing the mechanistic depth and translational significance of the study. In line with the TITAN 2025 guideline for AI transparency[2], we note that a generative AI language model was used solely for language polishing and did not influence the scientific content or interpretation presented here. Translational disconnect and clinical correlation regarding sTREM1 The clinically relevant finding of elevated urinary sTREM1 in patients was not pursued in the animal model, which only measured serum levels. Validating urinary sTREM1 in mice is crucial to link the knockout phenotype to local renal pathology. Furthermore, given the proposed diagnostic value, it would be compelling to analyze whether urinary sTREM1 levels correlate with established severity indices (e.g., APACHE II scores) or AKI stages (KDIGO criteria) in the patient cohort, rather than simply comparing them to healthy controls[3]. Statistical rigor and verification gaps in omics data The conclusion of decreased renal Ifn-γ (Fig. 3A) appears heavily influenced by an extreme outlier in the WT + LPS group, necessitating re-analysis or outlier exclusion justification. More importantly, the transcriptional analysis (Fig. 4E and Fig. S1) relies on direct comparison of FPKM values. Standard practice requires differential expression tools capable of modeling biological variability (e.g., DESeq2 or edgeR). Specifically, it is unclear whether the identification of differentially expressed genes included correction for multiple hypothesis testing [e.g., False Discovery Rate (FDR) adjustment] to avoid false positives. Validation of key mechanistic targets by an independent method such as qPCR is strongly recommended. Need for functional validation beyond correlation The study provides direct biochemical evidence that TREM1 deficiency activates the PI3K/AKT and STAT6 signaling pathways. However, correlation does not imply causation. To establish that the activation of these specific pathways is functionally required for the observed M2 polarization and renal protection, rescue experiments are necessary. For instance, treating Trem1–/– macrophages with specific inhibitors of the PI3K/AKT or STAT6 pathways should be performed to test if it reverses the protective pro-M2 phenotype. Overinterpretation of macrophage polarization based on a simplified model The in vitro polarization assay, utilizing singular cytokine stimuli (LPS or IL-4), constitutes a reductionist model that fails to recapitulate the complex signaling milieu macrophages encounter in vivo during sepsis[4]. Therefore, extrapolating the observed increase in renal CD206+ cells in Trem1–/– mice under systemic LPS challenge as evidence of a straightforward shift toward a canonical IL-4-dependent M2 phenotype is potentially misleading. This population likely represents a disease-specific, alternatively activated state shaped by concurrent signals, the definition of which requires a multidimensional immunophenotypic analysis beyond a single marker. Inconclusive evidence for macrophage specificity A critical limitation is the attribution of the protective phenotype solely to macrophages using a whole-body Trem1 knockout model. Notably, the authors explicitly state in the manuscript that the “macrophage adoptive transfer experiment” failed to show significant differences in key kidney injury markers (e.g., Kim-1), attributing this solely to “small sample size.” This admission fundamentally weakens the central conclusion that TREM1-deficient macrophages are the primary drivers of protection, as the current data do not support it. Neutrophils, which abundantly express TREM1, are also key players in SA-AKI. To substantiate the claim of macrophage specificity, the authors must either provide a statistically powered adoptive transfer experiment or, ideally, utilize a myeloid-specific (e.g., Lyz2-Cre) or macrophage-specific conditional knockout model[5]. In summary, the study by Xu et al presents a compelling conceptual advance that opens important avenues for translation. The discussion points we raise concerning clinical correlation, data robustness, mechanistic causality, and cellular specificity represent key considerations as this work moves forward. Addressing these aspects could further solidify the framework for targeting TREM1 in SA-AKI. We commend the authors for their insightful contribution to the field.