RESUMO
While significant attention has been paid to the immunologic determinants of disease states associated with COVID-191,2, their contributions to post-acute sequelae of COVID-19 (PASC) remain less clear3-5. Due to the wide array of PASC presentations6, it is critical to understand if specific features of the disease are associated with discrete immune processes, and whether those processes may be therapeutically targeted. To this end, we performed wide immunologic and serological characterization of patients in the early recovery phase of COVID-19 across a breadth of symptomatic presentations. Using high-parameter proteomics screening and applied machine learning (ML), we identify clear signatures of immunologic activity between PASC patients and uncomplicated recovery, dominated by inflammatory cytokine signaling, neutrophil activity, and markers of cell death. Consistent with disease complexity, heterogeneity in plasma profiling reveals distinct PASC subsets with striking divergence in these ongoing inflammatory processes, here termed plasma quiescent (plaq) and inflammatory (infl) PASC. In addition to elevated inflammatory blood proteomics, inflPASC patients display positive clinical tests of acute inflammation including C-reactive protein and fibrinogen, increased B cell activity with extrafollicular involvement coupled with elevated targeting of viral nucleocapsid protein and clinical autoreactivity. Further, the unique plasma signatures of PASC patients allowed for the creation of refined models with high sensitivity and specificity for the positive identification of inflPASC with a streamlined assessment of 12 blood markers. Additionally, refined ML modeling highlights the unexpected significance of several markers of potential diagnostic or therapeutic use for PASC in general, including the peptide hormone, epiregulin. In all, this work identifies clear biological signatures of PASC with potential diagnostic and therapeutic potential and establishes clear disease subtypes that are both easily identifiable and highly relevant to ongoing efforts in both therapeutic targeting and epidemiological investigation of this highly complex disease.
RESUMO
ObjectivesTo determine clinical course and outcomes in rheumatic disease patients with coronavirus disease 2019 (COVID-19) and compare results to uninfected patients. MethodsWe conducted a case cohort study of autoimmune disease patients with COVID-19 (confirmed by severe acute respiratory syndrome coronavirus 2 PCR) from 02/01/2020 to 07/31/2020 and compared them in a 1:3 ratio with uninfected patients who were matched based on race, age, sex, and comorbidity index. Patient demographics, clinical course, and outcomes were compared among these patient groups. ResultsA total of 70 rheumatic disease patients with COVID-19 (mean age, 56.6 years; 64% African American) were identified. The 34 (49%) patients who were hospitalized used oral glucocorticoids more frequently (p<0.01). All 10 patients on anti-TNF medications were treated as outpatients (p<0.01). Those hospitalized with COVID-19 more often required ICU admission (17 (50%) vs 27 (26%), OR=2.78 (95% CI: 1.24 to 6.20)) and intubation (10 (29%) vs 6 (6%), OR=6.67 (95% CI: 2.20 to 20.16)) than uninfected patients. They also had higher mortality rates (6 (18%) vs 3 (3%), OR=7.21 (95% CI: 1.70 to 30.69)). Of the six COVID-19 patients who died, one was of African ancestry (p=0.03). ConclusionsRheumatic disease patients infected with COVID-19 were more likely to require ICU admission, ventilation, and died more frequently versus uninfected patients with autoimmune disease. Patients on anti-TNF medications were hospitalized less frequently while those on chronic glucocorticoids were hospitalized more frequently. These findings have important implications for medication choice in rheumatic disease patients during the ongoing spread of COVID-19.