Covid Sepsis Gene Expression Subphenotypes Manifest Differential Plasma Protein Signatures

INTRODUCTION: Transcriptome-derived sepsis subphenotypes, termed 'adaptive', 'inflammopathic' and 'coagulopathic', have been reliably identified in sepsis cohorts, however plasma proteomics in these groups have not been well characterized. We hypothesized that inflammatory and vascular injury markers would be elevated in the inflammopathic and coagulopathic groups compared to the adaptive group. METHOD(S): We prospectively enrolled and obtained blood from 130 inpatients with COVID19-related sepsis. Severity was classified by NIH ordinal scale. Gene expression analysis was performed by Nanostring nCounter (Inflammatix). Inflammatory proteins interleukin (IL)-6, IL8, IL10, IL1RA, IL1RL1, and IFNg and vascular markers ANGPT2, sICAM, vWF, ADAMTS13, and protein C were measured with OLINK proximity extension assay. Clinical variables were compared by chi-square and protein levels were compared using ANOVA with Bonferroni adjustment. RESULT(S): The transcriptomic classifier identified 32% (41) inflammopathic, 50% (65) adaptive and 18% (24) coagulopathic subjects. The inflammopathic group had more patients requiring mechanical ventilation (39% vs 9% vs 21%;p < 0.001) and higher 90-day mortality (32% vs 8% vs 13%, p = 0.016). Inflammatory cytokines IL8 and IL10 were significantly higher in inflammopathic compared to adaptive (p=0.038 and p=0.017 respectively), but not compared to coagulopathic (p>0.99 and p=0.24, respectively). Both the inflammopathic and coagulopathic groups expressed higher IL1RL1 and interferon-gamma compared to adaptive (IL1RL1;p< 0.001, p=0.002, IFNg;p=0.007, p=0.001). Plasma IL6 and IL1RA did not differ between groups, nor did many vascular proteins. The inflammopathic group expressed higher sICAM (p=0.049 vs adaptive) and lower ADAMTS13 compared to the adaptive group, and the coagulopathic group did not differ in its vascular protein expression. CONCLUSION(S): Transcriptomic subphenotypes are present in COVID-19 sepsis at similar proportions to non-COVID-19 sepsis. Inflammopathic subjects manifested higher severity of illness at admission, higher expression of inflammatory proteins and higher mortality. Markers of vascular injury did not distinguish the coagulopathic group. Integrating RNA and protein expression may offer new insights to host immune dysregulation during COVID sepsis.

Plasma resistin levels are associated with acute kidney injury in hospitalized COVID-19 patients

Rationale: Obesity is a strong risk factor for acute kidney injury (AKI) in patients with COVID-19, but underlying mechanisms are unknown. Resistin is an immunomodulatory adipokine with elevated circulating levels in obese outpatients that could contribute to inflammatory kidney injury. We hypothesized that plasma resistin levels would be associated with AKI and BMI, and correlated with the inflammatory markers IL6 and MCP1 in hospitalized COVID-19 patients. Methods: We conducted a prospective cohort study of 134 patients admitted to the Hospital of the University of Pennsylvania with a primary diagnosis of COVID-19. Plasma samples were collected within 48 hours of admission and analyzed using the Olink Proximity Extension Assay, with biomarker levels expressed using normalized protein expression (NPX) values relative to common pooled control plasma. We tested the association of each biomarker with AKI, defined by Kidney Disease Improving Global Outcomes creatinine and dialysis criteria, using the Wilcoxon rank-sum test as well as multivariable logistic regression to adjust for confounders. Spearman's rho and correlation coefficients were calculated for the correlation of biomarker levels with each other. We used causal mediation models to investigate effects of BMI on AKI mediated by plasma resistin. Results: Of 134 patients enrolled, 43 (32.1%) developed AKI: 25 with stage 1, 5 with stage 2, and 13 with stage 3. Plasma resistin levels ranged from 5.26-13.01 NPX units and were strongly associated with AKI: odds ratio 2.13 (95% CI 1.43-3.17) per NPX unit. This association was diminished but remained significant after adjustment for age and APACHE III score (OR 1.69 (1.09-2.63)). Body mass index was higher in patients with AKI than without (median 31.4 (IQR 27.1-37.6) kg/m2 v. 28.3 (25.1-34.9) kg/m2, respectively), but the difference was not statistically significant (p=0.082). There was no significant correlation of BMI with resistin levels (rho 0.05, p=0.562), and causal mediation models failed to detect significant mediation of BMI-AKI association through resistin. Plasma IL6 and MCP1 were associated with AKI (p=0.044 and p=0.003, respectively) and correlated with resistin levels (rho=0.32, p<0.001 and rho=0.40, p<0.001, respectively). Conclusion: In patients hospitalized with COVID-19, plasma levels of the adipokine resistin were strongly associated with the development of AKI, and correlated with circulating inflammatory markers IL6 and MCP1. We did not detect a mediation effect of the obesity-AKI association by plasma resistin but had limited sample size to adequately power this analysis.

Proteomic analysis of COVID-19 plasma reveals dysregulated trem-1, I-17, and tumor microenvironment pathways associated with disease severity

Rationale: To utilize high-dimensional proteomic data to identify dysregulated pathways that are associated with COVID-19 disease severity and suggest potential therapeutic targets. Methods: We enrolled 161 COVID-19 inpatients admitted at two tertiary care hospitals. Plasma samples collected within 48 hours of admission were analyzed with the Olink Proximity Extension Assay;713 unique proteins were assayed. The WHO COVID-19 ordinal severity scale at enrollment was dichotomized into moderate (levels 3-4) and severe (levels 5-7). Normalized protein expression (NPX) values were generated in relation to a common pooled control plasma on each plate. The association between NPX values and disease severity on admission was estimated with logistic regression (LR) after adjustment for age, sex, race, and select comorbidities. Ingenuity Pathway Analysis (IPA) was employed after application of the Benjamini-Hochberg procedure with a false discovery rate of 5% to all proteins for which the NPX difference was +/-0.8 between groups. Predictive models of disease severity on hospital day 7 using all proteins as potential features were fit using elastic net LR (ENLR) and gradient boosting (GBM). Performance was estimated on a held-out test set (40% of the data) with area under the receiveroperator characteristic curve (AUROC). Results: Of 161 subjects, 85 (53%) were classified as having severe COVID-19. A total of 552 proteins were differentially expressed (Figure 1), and 31 of these proteins met criteria for inclusion in pathway analysis. IPA identified the triggering receptor expressed on myeloid cells 1 (TREM-1) signaling pathway (4 members, p=3.8E-3), the tumor microenvironment (TME) pathway (5 members, p=4.1E-3), and the interleukin 17 (IL-17) signaling pathway (4 members, p=1.8E-2). Interleukin 1 receptor-like 1, a member of the TREM-1 pathway, was the protein most associated with disease severity (OR=3.18, p=1.82E-08). Tumor necrosis factor ligand superfamily member 11 (TNFSF11), a member of the IL-17 signaling pathway was the only factor whose enrichment was associated with less severe disease (OR=0.39, p=2.3E-05). ENLR and GBM predicted disease severity on day 7 with AUROC values of 0.908 (0.828, 0.968) and 0.882 (0.788, 0.957), respectively. Conclusion: We identified pathways differentially expressed between patients with severe and nonsevere COVID-19 associated with immune function and angiogenesis. Several agents currently being investigated to treat severe COVID-19 act on these dysregulated pathways, and future investigations could test whether these proteins act as enrichment markers or response indicators. Integrating protein expression with cellular immune phenotype may help explain COVID-19 pathophysiology.