Novel subtypes of severe COVID-19 respiratory failure based on biological heterogeneity: a secondary analysis of a randomized controlled trial.

BACKGROUND: Despite evidence associating inflammatory biomarkers with worse outcomes in hospitalized adults with COVID-19, trials of immunomodulatory therapies have met with mixed results, likely due in part to biological heterogeneity of participants. Latent class analysis (LCA) of clinical and protein biomarker data has identified two subtypes of non-COVID acute respiratory distress syndrome (ARDS) with different clinical outcomes and treatment responses. We studied biological heterogeneity and clinical outcomes in a multi-institutional platform randomized controlled trial of adults with severe COVID-19 hypoxemic respiratory failure (I-SPY COVID). METHODS: Clinical and plasma protein biomarker data were analyzed from 400 trial participants enrolled from September 2020 until October 2021 with severe COVID-19 requiring ≥ 6 L/min supplemental oxygen. Seventeen hypothesis-directed protein biomarkers were measured at enrollment using multiplex Luminex panels or single analyte enzyme linked immunoassay methods (ELISA). Biomarkers and clinical variables were used to test for latent subtypes and longitudinal biomarker changes by subtype were explored. A validated parsimonious model using interleukin-8, bicarbonate, and protein C was used for comparison with non-COVID hyper- and hypo-inflammatory ARDS subtypes. RESULTS: Average participant age was 60 ± 14 years; 67% were male, and 28-day mortality was 25%. At trial enrollment, 85% of participants required high flow oxygen or non-invasive ventilation, and 97% were receiving dexamethasone. Several biomarkers of inflammation (IL-6, IL-8, IL-10, sTNFR-1, TREM-1), epithelial injury (sRAGE), and endothelial injury (Ang-1, thrombomodulin) were associated with 28- and 60-day mortality. Two latent subtypes were identified. Subtype 2 (27% of participants) was characterized by persistent derangements in biomarkers of inflammation, endothelial and epithelial injury, and disordered coagulation and had twice the mortality rate compared with Subtype 1. Only one person was classified as hyper-inflammatory using the previously validated non-COVID ARDS model. CONCLUSIONS: We discovered evidence of two novel biological subtypes of severe COVID-19 with significantly different clinical outcomes. These subtypes differed from previously established hyper- and hypo-inflammatory non-COVID subtypes of ARDS. Biological heterogeneity may explain inconsistent findings from trials of hospitalized patients with COVID-19 and guide treatment approaches.

The Plasma Lipidomic Landscape in Patients with Sepsis due to Community-acquired Pneumonia.

Rationale: The plasma lipidome has the potential to reflect many facets of the host status during severe infection. Previous work is limited to specific lipid groups or was focused on lipids as prognosticators.Objectives: To map the plasma lipidome during sepsis due to community-acquired pneumonia (CAP) and determine the disease specificity and associations with clinical features.Methods: We analyzed 1,833 lipid species across 33 classes in 169 patients admitted to the ICU with sepsis due to CAP, 51 noninfected ICU patients, and 48 outpatient controls. In a paired analysis, we reanalyzed patients still in the ICU 4 days after admission (n = 82).Measurements and Main Results: A total of 58% of plasma lipids were significantly lower in patients with CAP-attributable sepsis compared with outpatient controls (6% higher, 36% not different). We found strong lipid class-specific associations with disease severity, validated across two external cohorts, and inflammatory biomarkers, in which triacylglycerols, cholesterol esters, and lysophospholipids exhibited the strongest associations. A total of 36% of lipids increased over time, and stratification by survival revealed diverging lipid recovery, which was confirmed in an external cohort; specifically, a 10% increase in cholesterol ester levels was related to a lower odds ratio (0.84; P = 0.006) for 30-day mortality (absolute mortality, 18 of 82). Comparison with noninfected ICU patients delineated a substantial common illness response (57.5%) and a distinct lipidomic signal for patients with CAP-attributable sepsis (37%).Conclusions: Patients with sepsis due to CAP exhibit a time-dependent and partially disease-specific shift in their plasma lipidome that correlates with disease severity and systemic inflammation and is associated with higher mortality.

Plasma metabolic profiling implicates dysregulated lipid metabolism and glycolytic shift in hyperinflammatory ARDS.

Using latent class analysis (LCA) of clinical and protein biomarkers, researchers have identified two phenotypes of the acute respiratory distress syndrome (ARDS) with divergent clinical trajectories and treatment responses. We investigated whether plasma metabolites differed among patients with LCA-derived hyperinflammatory and hypoinflammatory ARDS, and we tested the prognostic utility of adding metabolic clusters to LCA phenotypes. We analyzed data from 93 patients with ARDS and sepsis enrolled in a multicenter prospective cohort of critically ill patients, comparing 970 metabolites between the two LCA-derived phenotypes. In all, 188 metabolites were differentially abundant between the two LCA-derived phenotypes. After adjusting for age, sex, confounding medications, and comorbid liver and kidney disease, 82 metabolites remained significantly different. Patients with hyperinflammatory ARDS had reduced circulating lipids but high levels of pyruvate, lactate, and malate. Metabolic cluster and LCA-derived phenotypes were each significantly and independently associated with survival. Patients with hyperinflammatory ARDS may be experiencing a glycolytic shift leading to dysregulated lipid metabolism. Metabolic profiling offers prognostic information beyond what is captured by LCA phenotypes alone. Deeper biological profiling may identify key differences in pathogenesis among patients with ARDS and may lead to novel targeted therapies.