Daily Sepsis Research Analysis
Three studies advance sepsis science across mechanisms and methods: (1) a Nature Communications study shows the mannose receptor Mrc1 (CD206) maintains the circulating proteome and links its dysfunction to inflammation, organ injury, and sepsis mortality; (2) a JCI Insight study identifies myocardial PDK4 as a driver of male-biased cardiac dysfunction in endotoxemia and a potential sex-specific target; (3) a PLoS One methods paper demonstrates that patient-centric graph neural networks using com
Summary
Three studies advance sepsis science across mechanisms and methods: (1) a Nature Communications study shows the mannose receptor Mrc1 (CD206) maintains the circulating proteome and links its dysfunction to inflammation, organ injury, and sepsis mortality; (2) a JCI Insight study identifies myocardial PDK4 as a driver of male-biased cardiac dysfunction in endotoxemia and a potential sex-specific target; (3) a PLoS One methods paper demonstrates that patient-centric graph neural networks using complete blood count time series markedly improve sepsis classification performance.
Research Themes
- Lectin receptor control of plasma proteome and links to sepsis pathobiology
- Sex-specific cardiac metabolism in sepsis via PDK4 and potential therapeutic modulation
- Graph neural networks leveraging CBC time series for sepsis detection
Selected Articles
1. Mrc1 (MMR, CD206) controls the blood proteome in reducing inflammation, age-associated organ dysfunction and mortality in sepsis.
Using a glycosidic linkage enrichment approach, the authors show that the endocytic mannose receptor Mrc1 (CD206) governs the abundance of over 200 circulating mannosylated proteins in mice. Mrc1 dysfunction aligns with pathways linked to inflammation, age-related organ dysfunction, and increased mortality in sepsis, suggesting a systems-level mechanism connecting lectin receptor biology to sepsis pathobiology.
Impact: This work uncovers a previously unappreciated role of Mrc1 in shaping the circulating proteome with direct relevance to sepsis outcomes, offering mechanistic insights and a potential axis for biomarker interpretation and therapeutic targeting.
Clinical Implications: While preclinical, the identification of an Mrc1-dependent control of mannosylated proteins suggests opportunities to refine sepsis biomarker panels (glycoprotein clearance context) and raises the prospect of modulating lectin receptor pathways to mitigate inflammation and organ failure.
Key Findings
- Mrc1 (CD206) absence leads to accumulation of over 200 endogenous mannosylated plasma proteins at steady state.
- Accumulated proteins map to inflammatory and organ dysfunction pathways that overlap with human sepsis.
- Circulating Mrc1 levels rise in sepsis proportionally to mannosylated protein accumulation, linking receptor status to proteome shifts.
Methodological Strengths
- Comprehensive glycoproteomic enrichment strategy to identify mannosylated ligands linked to Mrc1 function.
- Use of genetic models (Mrc1 deficiency) with systems-level pathway mapping to human sepsis signatures.
Limitations
- Findings are derived from murine models; direct human mechanistic validation is pending.
- Causal links to clinical outcomes in sepsis have not been tested in intervention studies.
Future Directions: Validate Mrc1-proteome relationships in human cohorts with sepsis, assess diagnostic/prognostic utility of mannosylated glycoprotein panels, and explore pharmacologic or biologic modulation of Mrc1 pathways.
Circulating blood proteins and enzymes are maintained within normal physiological and clinically relevant concentration ranges. Excursions from normality include diagnostic markers and causes of disease. Rapid and persistent changes in the levels and functions of circulating blood components can reflect the functions of multiple endocytic lectin receptors. The majority of non-albumin blood proteins are post-translationally modified with sialylated N-glycans bearing cryptic ligands of various endocytic lectin receptors. During time in circulation, these cryptic ligands are progressively unmasked thereby contributing to glycoprotein half-life and abundance. The relationships between distinct lectin receptors and their endogenous ligand repertoires are not easily established. Herein we apply a glycosidic linkage enrichment strategy to identify accumulating mannosylated plasma glycoproteins linked to the absence of the endocytic Mrc1 (MMR, CD206) mannose-binding lectin receptor. We find that Mrc1 controls the abundance of over two hundred circulating endogenous mannosylated proteins in healthy mice at steady state, including glycoproteins linked to inflammation, age-associated organ dysfunction, and elevated mortality in sepsis. Increased circulating Mrc1 levels previously ascribed to proteolysis during sepsis are proportional to mannosylated protein accumulation in the blood. Assignment of circulating mannosylated proteins to curated biological and pathogenic signaling pathways reveals significant overlap between Mrc1 dysfunction and human sepsis.
2. Myocardial pyruvate dehydrogenase kinase 4 drives sex-specific cardiac responses to endotoxemia.
In murine endotoxemia, myocardial PDK4 is upregulated and drives male-biased cardiac dysfunction through PDH inhibition and metabolic reprogramming; genetic PDK4 ablation is protective while overexpression worsens injury. Dichloroacetate improved cardiac function in males but not females, highlighting sex-specific therapeutic potential.
Impact: Defines PDK4 as a mechanistic driver of sex-specific cardiac injury in sepsis and demonstrates differential response to metabolic modulation, opening avenues for sex-tailored therapies.
Clinical Implications: Supports stratifying future sepsis cardioprotection trials by sex and evaluating PDH/PDK axis modulators (e.g., dichloroacetate) with sex-specific endpoints and biomarkers.
Key Findings
- LPS (5 mg/kg) upregulated myocardial PDK4 and induced cardiac dysfunction in male but not female mice.
- PDK4 overexpression worsened, and PDK4 knockout mitigated, metabolic shifts (reduced PDH activity/FAO, elevated lactate) and cardiac dysfunction.
- Dichloroacetate improved cardiac function during endotoxemia in males but not females, indicating sex-specific therapeutic response.
Methodological Strengths
- Combined genetic (cardiac-specific overexpression/knockout) and pharmacologic (DCA) interventions.
- Sex-stratified metabolic phenotyping including PDH activity, FAO, lactate, and mitochondrial integrity.
Limitations
- Endotoxemia model may not fully recapitulate polymicrobial sepsis.
- Translational relevance of DCA dosing and timing requires clinical investigation.
Future Directions: Test PDH/PDK modulators in sepsis models beyond endotoxemia, incorporate sex-specific endpoints in translational and early-phase clinical studies, and identify circulating biomarkers of myocardial PDK4 activity.
Males often experience worse cardiac outcomes than females in sepsis. This study identified pyruvate dehydrogenase kinase 4 (PDK4) as a key mediator of this disparity. PDK4 regulates glucose utilization by inhibiting pyruvate dehydrogenase (PDH) in mitochondria. In a mouse endotoxemia model, a sublethal dose of lipopolysaccharide (LPS, 5 mg/kg) significantly upregulated myocardial PDK4 and induced cardiac dysfunction in males but not females. Cardiac-specific PDK4 overexpression promoted this cardiac dysfunction in both sexes, whereas PDK4 knockout provided protection. In WT males, LPS reduced PDH activity and fatty acid oxidation (FAO) while increasing lactate levels, suggesting a shift toward glycolysis. These effects were exacerbated by PDK4 overexpression but attenuated by knockout. In females, metabolic changes were minimal, aside from reduced FAO in LPS-challenged females overexpressing PDK4. Additionally, a higher LPS dose (8 mg/kg) triggered cardiac dysfunction in females, accompanied by modest upregulation of PDK4, but without changes in PDH or lactate. Dichloroacetate (DCA), restraining PDK-mediated PDH inhibition, improved cardiac function in males but not females during endotoxemia. PDK4 overexpression also exacerbated cardiac mitochondrial damage, reduced mitophagy, and increased oxidative stress and inflammation during endotoxemia - effects that were prevented by PDK4 knockout. These findings suggest that PDK4 drives sex-specific cardiac responses in sepsis.
3. Edges are all you need: Potential of medical time series analysis on complete blood count data with graph neural networks.
Graph neural networks applied to CBC data can match or outperform strong baselines, but modeling temporal relationships by connecting a patient's serial samples yields a large performance gain (AUROC up to 0.9565) for sepsis classification. Feature importance and temporal slope differ across model classes, highlighting methodological implications.
Impact: Demonstrates a practical, generalizable paradigm—patient-centric temporal graphs—for leveraging routine lab time series to improve sepsis detection, with broad implications for CDSS design.
Clinical Implications: Encourages integrating temporal linkages of routine labs in predictive systems for early sepsis detection; next steps include external validation and prospective clinical impact evaluation.
Key Findings
- Similarity-graph GNNs achieved AUROC up to 0.8747, comparable to XGBoost and a neural network.
- Patient-centric temporal graphs incorporating time series boosted AUROC to 0.9565 for sepsis classification.
- Feature slope and importance differ substantially between GNNs and tree-based models, affecting interpretability and deployment.
Methodological Strengths
- Direct comparison of multiple GNN architectures against strong baselines with AUROC handling class imbalance.
- Innovative patient-centric temporal graph construction to encode intra-patient time series.
Limitations
- Retrospective modeling with unspecified cohort size; lack of external validation.
- Clinical utility and workflow integration not assessed prospectively.
Future Directions: Perform external validation across institutions, assess fairness and robustness, develop interpretable temporal explanations, and test prospective clinical impact within CDSS.
PURPOSE: Machine learning is a powerful tool to develop algorithms for clinical diagnosis. However, standard machine learning algorithms are not perfectly suited for clinical data since the data are interconnected and may contain time series. As shown for recommender systems and molecular property predictions, Graph Neural Networks (GNNs) may represent a powerful alternative to exploit the inherently graph-based properties of clinical data. The main goal of this study is to evaluate when GNNs represent a valuable alternative for analyzing large clinical data from the clinical routine on the example of Complete Blood Count Data. METHODS: In this study, we evaluated the performance and time consumption of several GNNs (e.g., Graph Attention Networks) on similarity graphs compared to simpler, state-of-the-art machine learning algorithms (e.g., XGBoost) on the classification of sepsis from blood count data as well as the importance and slope of each feature for the final classification. Additionally, we connected complete blood count samples of the same patient based on their measured time (patient-centric graphs) to incorporate time series information in the GNNs. As our main evaluation metric, we used the Area Under Receiver Operating Curve (AUROC) to have a threshold independent metric that can handle class imbalance. RESULTS AND CONCLUSION: Standard GNNs on evaluated similarity-graphs achieved an Area Under Receiver Operating Curve (AUROC) of up to 0.8747 comparable to the performance of ensemble-based machine learning algorithms and a neural network. However, our integration of time series information using patient-centric graphs with GNNs achieved a superior AUROC of up to 0.9565. Finally, we discovered that feature slope and importance highly differ between trained algorithms (e.g., XGBoost and GNN) on the same data basis.