Daily Sepsis Research Analysis
Analyzed 41 papers and selected 3 impactful papers.
Summary
Two mechanistic studies illuminate immunometabolic control points in sepsis—d-amino acids suppress macrophage IL-1β via gasdermin D acetylation, and CHAC1 deficiency reshapes the gut metabolome to elevate indole-3-carboxylic acid that reprograms macrophage metabolism via AHR. Clinically, an externally validated BAR-based nomogram enables early prediction of septic shock in acute pancreatitis with sepsis, supporting actionable ICU risk stratification.
Research Themes
- Immunometabolic regulation of inflammatory cell death in sepsis
- Microbiome–metabolite–immune crosstalk as therapeutic leverage
- Early risk prediction tools for septic shock in high-risk ICU populations
Selected Articles
1. d-amino acids restrain macrophage IL-1β release through gasdermin D acetylation.
This study uncovers that d-amino acids suppress macrophage IL-1β release by inducing GSDMD K146 acetylation, thereby blocking pore-forming oligomerization. d-Amino acids activate mitochondrial PDH to boost acetyl-CoA, and either d-Ala/d-Glu supplementation or myeloid DDO deletion ameliorates LPS-induced sepsis in mice.
Impact: It identifies a previously unrecognized acetylation-dependent checkpoint of GSDMD-mediated pyroptosis, linking d-amino acid metabolism to inflammasome effector control and improving survival in preclinical sepsis models.
Clinical Implications: Highlights a druggable immunometabolic node—enhancing GSDMD acetylation to restrain IL-1β release—suggesting adjunctive strategies (e.g., targeted d-amino acid therapy or DDO/DAAO modulation) to mitigate macrophage-driven inflammation in sepsis.
Key Findings
- Inflammatory macrophages downregulate DAAO/DDO via NF-κB; inhibition increases intracellular d-amino acids and suppresses IL-1β release.
- d-Amino acids induce GSDMD K146 acetylation, preventing GSDMD oligomerization and pore formation.
- d-Amino acids directly enhance mitochondrial PDH activity to increase acetyl-CoA for acetylation.
- d-Ala/d-Glu supplementation or myeloid-specific DDO deletion attenuates LPS-induced sepsis in mice.
Methodological Strengths
- Multi-level mechanistic validation from enzyme biochemistry to macrophage function and in vivo sepsis models.
- Genetic (myeloid DDO deletion) and metabolic (PDH activation, acetylation site mapping) triangulation of causality.
Limitations
- Primary reliance on LPS-induced sepsis; generalizability to polymicrobial sepsis remains to be tested.
- Human translational data (dose, safety, pharmacokinetics of d-amino acids) are not provided.
Future Directions: Validate in polymicrobial sepsis (e.g., CLP), assess human macrophage ex vivo responses, and develop pharmacologic strategies to modulate GSDMD acetylation safely in early-phase trials.
d-amino acids have been detected in various tissues; however, whether d-amino acids shape immune cell (e.g., macrophages) function remains undefined. Here, we demonstrated that inflammatory macrophages decrease mRNA expression of d-amino acid oxidase (DAAO) and d-aspartate oxidase (DDO) through nuclear factor κB (NF-κB) signaling. Notably, inhibition of DAAO or DDO increases the concentration of intracellular d-amino acids, consequently suppressing IL-1β release. Mechanistically, d-amino acids inhibit the formation of gasdermin D (GSDMD) oligomer via GSDMD-K146 acetylation. d-amino acids directly bind and increase the enzyme activity of mitochondrial pyruvate dehydrogenase (PDH), resulting in acetyl-coenzyme A production for acetylation. Consistently, d-Ala/d-Glu supplementation or myeloid-specific deletion of DDO attenuates lipopolysaccharides (LPS)-induced sepsis in mice. Collectively, our study reveals a mechanism involving acetylation mediated by d-amino acids in regulation of macrophage function, providing a potential therapeutic strategy for treating macrophage-associated inflammatory diseases.
2. Chac1 deficiency confers sepsis resistance by enriching gut microbiota-derived indole-3-carboxylic acid to drive macrophage metabolic shifts.
CHAC1 is elevated in human and murine sepsis. Genetic Chac1 deficiency confers resistance to sepsis by enriching gut microbiota-derived indole-3-carboxylic acid (ICA), which activates macrophage AHR and shifts metabolism from glycolysis to oxidative phosphorylation, thereby reducing inflammation and organ injury.
Impact: Defines a gut microbiota–metabolite–immune axis (CHAC1–ICA–AHR) that mechanistically links host redox enzymes to macrophage immunometabolism and sepsis outcomes, nominating ICA as a therapeutic candidate and CHAC1 as a biomarker.
Clinical Implications: Suggests metabolite-based interventions (e.g., ICA supplementation or AHR-targeted modulation) and CHAC1 measurement for risk stratification; translational steps include safety, dose-finding, and interaction with antibiotics and nutrition.
Key Findings
- Serum CHAC1 is elevated in septic patients and mice and correlates with disease severity.
- Chac1 deficiency protects against sepsis-induced multiorgan injury in a gut microbiota-dependent manner.
- Chac1 deficiency enriches indole-3-carboxylic acid (ICA), which activates macrophage AHR to shift metabolism from glycolysis to oxidative phosphorylation, reducing inflammation.
- The CHAC1–microbiota–ICA–AHR–macrophage axis is proposed as a therapeutic and prognostic framework.
Methodological Strengths
- Combines human observational correlation with mechanistic mouse and metabolite rescue experiments.
- Demonstrates microbiota dependency and identifies ICA–AHR signaling as a causal pathway.
Limitations
- Preclinical study without interventional human trials; generalizability across diverse human microbiomes is uncertain.
- Potential pleiotropic effects of CHAC1 and AHR modulation require careful toxicity and off-target evaluation.
Future Directions: Quantify ICA pharmacokinetics/pharmacodynamics, test adjunctive ICA in polymicrobial sepsis models and ex vivo human macrophages, and evaluate CHAC1 as a prognostic biomarker in prospective cohorts.
INTRODUCTION: Sepsis is a life-threatening dysregulated host response to infection, lacks effective therapies. ChaC glutathione-specific γ-glutamylcyclotransferase 1 (CHAC1) is elevated in sepsis and correlates with severity, but its functional role in the pathogenesis of sepsis-induced organ damage is unclear. OBJECTIVES: We aimed to define the contribution of CHAC1 to sepsis-induced organ injury and elucidate the underlying mechanisms involving gut microbiota-derived metabolites and host immunity. METHODS: Chac1 RESULTS: Serum CHAC1 was elevated in septic patients and mice, correlating with disease severity. Chac1 deficiency protected against sepsis-induced multi-organ injury, an effect that was gut microbiota-dependent. Chac1 CONCLUSION: Chac1 deficiency confers sepsis resistance by enriching protective gut microbiota and elevating ICA, which acts as a major downstream effector. ICA activates the AHR in macrophages, driving a metabolic shift from glycolysis to oxidative phosphorylation that dampens inflammation and organ injury. This CHAC1-microbiota-ICA-AHR-macrophage axis identifies ICA as a promising therapeutic candidate and CHAC1 as a potential prognostic biomarker for sepsis.
3. A BAR-based nomogram for predicting septic shock in patients with acute pancreatitis complicated by sepsis: development and external validation.
Using MIMIC-IV and an independent hospital cohort, a nine-variable nomogram centered on BAR predicted progression to septic shock in pancreatitis-associated sepsis with AUCs of 0.777–0.832. Calibration and decision curve analyses support clinical utility, and net reclassification improved over BUN alone.
Impact: Provides a pragmatic, externally validated bedside risk tool leveraging readily available labs, enabling earlier escalation or monitoring in a high-risk subgroup where shock carries high mortality.
Clinical Implications: Supports early ICU risk stratification for septic shock in acute pancreatitis complicated by sepsis, informing triage, monitoring intensity, and timely vasopressor readiness or transfer.
Key Findings
- A nine-variable nomogram featuring BAR achieved AUCs of 0.777 (training), 0.707 (internal validation), and 0.832 (external validation).
- Calibration and decision curve analyses indicated good agreement and net clinical benefit across thresholds.
- BAR-based modeling significantly improved risk reclassification over BUN alone (external cohort NRI = 0.247, P = 0.042).
Methodological Strengths
- External validation with consistent performance and comprehensive assessment (discrimination, calibration, decision curves).
- Transparent variable selection via LASSO and multivariable modeling using early ICU data.
Limitations
- Retrospective design with potential residual confounding and center-specific practices.
- Moderate discrimination in internal validation; generalizability beyond cohorts studied remains to be tested.
Future Directions: Prospective multicenter validation, integration into EHR decision support with impact evaluation on time-to-vasopressor, ICU LOS, and mortality, and adaptation to broader sepsis populations.
BACKGROUND: Septic shock is a common and life-threatening complication in patients with acute pancreatitis complicated by sepsis, yet rapid and accurate tools for early risk prediction remain limited in clinical practice. This study aimed to develop and externally validate a nomogram incorporating the blood urea nitrogen-to-albumin ratio (BAR) to predict the risk of progression to septic shock in this high-risk population. METHODS: In this retrospective multi-cohort study, a total of 541 patients with acute pancreatitis complicated by sepsis were identified from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and randomly divided into a training set (n = 379) and an internal validation set (n = 162) at a 7:3 ratio. An independent cohort of 295 patients from the Second Hospital of Hebei Medical University was used for external validation. Candidate variables collected within the first 24 hours of intensive care unit admission were screened using least absolute shrinkage and selection operator (LASSO) regression. A multivariable logistic regression model was constructed and visualized as a nomogram. Model performance was assessed using discrimination, calibration, and decision curve analysis. RESULTS: Nine variables were selected to construct the nomogram, with BAR emerging as a key predictor. The model demonstrated good discriminatory performance, with areas under the receiver operating characteristic curve of 0.777 in the training cohort, 0.707 in the internal validation cohort, and 0.832 in the external validation cohort. Calibration curves showed good agreement between predicted and observed risks, and decision curve analysis indicated favorable clinical utility across a wide range of threshold probabilities. Net reclassification improvement analysis in the external validation cohort demonstrated that the BAR-based model significantly improved risk classification compared with the model including blood urea nitrogen alone (NRI = 0.247, 95% CI 0.008-0.486, P = 0.042). CONCLUSIONS: We developed and externally validated a BAR-based nomogram for early and individualized prediction of septic shock in patients with acute pancreatitis complicated by sepsis. This clinically interpretable tool may facilitate early risk stratification and support timely clinical decision-making in the intensive care setting.