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Daily Sepsis Research Analysis

3 papers

Multi-omic analyses advanced sepsis endotyping and mechanistic understanding: a JCI study linked inflammatory phenotypes in ARDS/sepsis to four mortality-associated molecular signatures centered on mitochondrial dysfunction, validated in an independent sepsis cohort. Complementary work identified mitophagy-related biomarkers and molecular subtypes with functional validation of NUP93, while a real-world study showed blood mNGS substantially increases pathogen detection and guides therapy in hemat

Summary

Multi-omic analyses advanced sepsis endotyping and mechanistic understanding: a JCI study linked inflammatory phenotypes in ARDS/sepsis to four mortality-associated molecular signatures centered on mitochondrial dysfunction, validated in an independent sepsis cohort. Complementary work identified mitophagy-related biomarkers and molecular subtypes with functional validation of NUP93, while a real-world study showed blood mNGS substantially increases pathogen detection and guides therapy in hematologic malignancy patients with sepsis after antibiotics.

Research Themes

  • Mitochondria-centric biology and endotypes in sepsis/ARDS
  • Mitophagy-related biomarkers and molecular subtyping
  • Metagenomic next-generation sequencing to guide therapy in immunocompromised sepsis

Selected Articles

1. Longitudinal multi-omic signatures of ARDS and sepsis inflammatory phenotypes identify pathways associated with mortality.

84Level IIICohortThe Journal of clinical investigation · 2025PMID: 41329523

Integrating plasma metabolomics and whole-blood transcriptomics from 160 ARDS patients stratified by inflammatory phenotype, the authors defined four mortality-associated molecular signatures that largely converged on mitochondrial dysfunction. These longitudinal signatures persisted to Day 2 and were validated in an independent critically ill sepsis cohort, revealing phenotype-specific and phenotype-independent pathways that may inform precision therapies.

Impact: This paradigm-advancing, validated multi-omic work links clinical inflammatory phenotypes to mechanistic, mortality-associated pathways centered on mitochondrial dysfunction, directly informing endotype-driven interventions in sepsis/ARDS.

Clinical Implications: Supports endotype-based risk stratification and prioritizes mitochondrial bioenergetics, fatty acid oxidation, interferon signaling, and redox pathways as therapeutic targets; enables longitudinal biomarker panels for early prognosis.

Key Findings

  • Four mortality-associated molecular signatures were identified, including innate immune activation with glycolysis, hepatic/immune dysfunction with impaired fatty acid β-oxidation, interferon suppression with altered mitochondrial respiration, and redox/proliferation pathways.
  • Signatures persisted from Day 0 to Day 2 and were validated in an independent critically ill sepsis cohort (EARLI).
  • Within-phenotype analyses revealed distinct mortality-associated pathways, indicating both phenotype-specific and phenotype-independent biology centered on mitochondrial dysfunction.

Methodological Strengths

  • Prospective trial-derived cohort with random selection by high phenotype probability and longitudinal sampling (Day 0, Day 2).
  • Integrated untargeted metabolomics and transcriptomics with external validation (EARLI) using advanced multi-modal factor analysis (MEFISTO).

Limitations

  • Secondary analysis of trial biospecimens with modest sample size (n=160) may limit generalizability.
  • Causal inference is limited; therapeutic targets require interventional validation.

Future Directions: Prospective, multi-center validation of signature-based risk models and interventional trials targeting mitochondrial bioenergetics, fatty acid oxidation, and interferon/redox pathways in endotype-enriched populations.

2. Integrated multi-omics of mitophagy-related molecular subtype characterization and biomarker identification in sepsis.

70.5Level VCohortScientific reports · 2025PMID: 41326582

Integrative analyses identified four mitophagy-associated gene biomarkers (RPL18, PRPF8, NUP93, CUL1) with excellent diagnostic performance and defined sepsis molecular subtypes with distinct immune landscapes. Functional experiments showed NUP93 overexpression rescues LPS-induced mitophagy impairment by restoring PINK1 and LC3B, linking biomarkers to mechanism.

Impact: Bridges computational endotyping with bench validation to position mitophagy as a diagnostic and therapeutic axis in sepsis, offering actionable biomarker candidates and a stratification framework.

Clinical Implications: Proposes a high-AUC diagnostic panel and mitophagy-informed subtypes that could guide precision diagnostics and selection of candidates for mitophagy-targeted therapies.

Key Findings

  • Machine learning identified four MAG biomarkers (RPL18, PRPF8, NUP93, CUL1) with individual AUCs 0.957–0.975 and a nomogram AUC of 0.990.
  • Consensus clustering based on MAG stratified sepsis into molecular subtypes with distinct immune landscapes and pathways.
  • NUP93 overexpression restored PINK1 and LC3B levels in LPS-stimulated macrophages, rescuing mitophagy impairment in vitro.

Methodological Strengths

  • Integration of bulk and single-cell transcriptomics with WGCNA, ssGSEA, ESTIMATE, and consensus clustering.
  • Functional validation linking biomarker (NUP93) to mitophagy rescue in LPS-stimulated macrophages.

Limitations

  • Predominantly in silico, retrospective dataset integration without prospective clinical validation.
  • Functional assays limited to in vitro macrophage models; no in vivo validation or clinical assay readiness.

Future Directions: Prospective, multi-center validation of biomarker panels and subtypes, development of rapid assays, and preclinical/in vivo testing of mitophagy-targeted interventions.

3. Application of metagenomic next-generation sequencing technology in hematologic malignancy patients with sepsis following antibiotic use.

66Level IIICohortBMC infectious diseases · 2025PMID: 41327021

In 119 hematologic malignancy patients with sepsis unresponsive to ≥3 days of antibiotics, blood mNGS detected pathogens far more frequently than culture (89.36% vs 25.53%) and prompted antimicrobial regimen changes in 39.49% of cases; antitumor therapy–related granulocytopenia was a risk factor for polymicrobial infection.

Impact: Demonstrates real-world utility of blood mNGS to guide therapy in immunocompromised sepsis where cultures underperform post-antibiotics, highlighting both clinical impact and interpretive challenges.

Clinical Implications: Supports incorporating blood mNGS to augment pathogen detection and tailor antimicrobials in complex, culture-negative or polymicrobial sepsis, with stewardship frameworks to manage specificity and contamination concerns.

Key Findings

  • mNGS positivity for bacteria/fungi was 89.36% versus 25.53% for blood culture.
  • Therapeutic modifications based on mNGS occurred in 39.49% of patients.
  • Agreement with culture was low (kappa −0.202), with reported sensitivity 58.33% and specificity 0% relative to reference used.
  • Granulocytopenia from antitumor therapy was a high-risk factor for polymicrobial infections.

Methodological Strengths

  • Head-to-head comparison of simultaneous blood mNGS and culture in a high-risk, clinically relevant population.
  • Actionability assessed via documented antimicrobial regimen changes.

Limitations

  • Single-center design with no definitive gold standard and very low agreement with culture complicates performance interpretation.
  • Potential contamination/background signals and lack of outcome-adjusted utility (e.g., mortality/LOS) limit conclusions.

Future Directions: Establish composite clinical/microbiologic adjudication standards, define quantitative thresholds for actionability, integrate host-response markers, and test mNGS-guided care pathways in randomized trials.