Pre-Existing and Pragmatically-Derived Immunohematologic Phenotypes Predict All-Cause and COVID-19-Specific Mortality: A 'Population Immunology' Approach (preprint)

Background: Dysregulation of immunohematologic function (IHF) promotes cardiovascular disease and impairs protective responses to cancer and infection. A pragmatic method to identify those as risk due to IHF could improve the precision of preventive interventions and provide insight into the heterogeneity of immunologic capacity. We developed and validated a method to distill complete blood cell count data into distinct IHF profiles of prognostic relevance. Methods: We adapted latent profile analysis methods to simultaneously identify distinct groups of patients with respect to 10 immunohematologic indicators and regress time to all-cause mortality on this latent IHF profile. The model was developed using data from 30274 National Health and Nutrition Examination Survey participants and externally validated in 49851 outpatients in the Veterans Heath Administration (VHA) system and 44142 SARS-CoV-2 positive VHA patients.Findings: Ten distinct IHF profiles were identified. Profile 1, with relative mild pan-leukopenia in absence of red cell abnormalities, was associated with the best long term survival in each setting. Profiles 8-10, featuring anemia/anisocytosis especially in the setting of lymphopenia (Profiles 9-10) were associated with adjusted hazard ratio (HR) estimates of 1.76-2.62 for mortality across the three cohorts, compared to Profile 1. Profiles 6-7, featuring relative neutrophilia, were less common but also independently associated with mortality risk, especially after COVID-19 infection (Profile 7 HR [95% CI]: 2.51 [1.63 – 3.86]). The magnitude of adjusted risk conveyed by IHF profiles was greater than individual clinical risk factors (i.e., smoking, diabetes) or prevalent co-morbidities.Interpretation: Distinct immunohematologic endotypes can be identified during routine blood panels which project to mortality risk on par with a decade of life, additive to demographic and clinical factors. Applications that consider immunohematologic dysfunction may improve prevention of common fatal diseases, including COVID-19.Funding Information:This study was funded in part by The National Institute on Aging (R01AG055480; Dalton and Perzynski), the National Cancer Institute (U01CA260513; Zidar and Chan), and the United States Veteran Administration (COVID19-8900-05; Zidar). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Department of Veteran Affairs or the National Institutes of Health.Declaration of Interests: No conflict of interest exists between any of the authors and the contents of this paper.Ethics Approval Statement: The study was approved by the Institutional Review Board of the Louis Stokes Cleveland VAMC.

SARS-CoV-2 Receptors are Expressed on Human Platelets and the Effect of Aspirin on Clinical Outcomes in COVID-19 Patients (preprint)

Coronavirus disease-2019 (COVID-19) caused by SARS-CoV-2 is an ongoing viral pandemic marked by increased risk of thrombotic events. However, the role of platelets in the elevated observed thrombotic risk in COVID-19 and utility of anti-platelet agents in attenuating thrombosis is unknown. We aimed to determine if human platelets express the known SARS-CoV-2 receptor-protease axis on their cell surface and assess whether the anti-platelet effect of aspirin may mitigate risk of myocardial infarction (MI), cerebrovascular accident (CVA), and venous thromboembolism (VTE) in COVID-19. Expression of ACE2 and TMPRSS2 on human platelets were detected by immunoblotting and confirmed by confocal microscopy. We evaluated 22,072 symptomatic patients tested for COVID-19. Propensity-matched analyses were performed to determine if treatment with aspirin or non-steroidal anti-inflammatory drugs (NSAIDs) affected thrombotic outcomes in COVID-19. Neither aspirin nor NSAIDs affected mortality in COVID-19. However, both aspirin and NSAID therapies were associated with increased risk of the combined thrombotic endpoint of (MI), (CVA), and (VTE). Thus, while platelets clearly express ACE2-TMPRSS2 receptor-protease axis for SARS-CoV-2 infection, aspirin does not prevent thrombosis and death in COVID-19. The mechanisms of thrombosis in COVID-19, therefore, appears distinct and the role of platelets as direct mediators of SARS-CoV-2-mediated thrombosis warrants further investigation.

Impact of the COVID-19 pandemic on healthcare workers risk of infection and outcomes in a large, integrated health system. (preprint)

Background: Understanding the impact of the COVID-19 pandemic on healthcare workers (HCW) is crucial. Objective: Utilizing a health system COVID-19 research registry, we assessed HCW risk for COVID-19 infection, hospitalization and intensive care unit (ICU) admission. Design: Retrospective cohort study with overlap propensity score weighting. Participants: Individuals tested for SARS-CoV-2 infection in a large academic healthcare system (N=72,909) from March 8-June 9 2020 stratified by HCW and patient-facing status. Main Measures: SARS-CoV-2 test result, hospitalization, and ICU admission for COVID-19 infection. Key Results: Of 72,909 individuals tested, 9.0% (551) of 6,145 HCW tested positive for SARS-CoV-2 compared to 6.5% (4353) of 66,764 non-HCW. The HCW were younger than non-HCW (median age 39.7 vs. 57.5, p<0.001) with more females (proportion of males 21.5 vs. 44.9%, p<0.001), higher reporting of COVID-19 exposure (72 vs. 17 %, p<0.001) and fewer comorbidities. However, the overlap propensity score weighted proportions were 8.9 vs. 7.7 for HCW vs. non-HCW having a positive test with weighted odds ratio (OR) 1.17, 95% confidence interval (CI) 0.99-1.38. Among those testing positive, weighted proportions for hospitalization were 7.4 vs.15.9 for HCW vs. non-HCW with OR of 0.42 (CI 0.26-0.66) and for ICU admission: 2.2 vs.4.5 for HCW vs. non-HCW with OR of 0.48 (CI 0.20 -1.04). Those HCW identified as patient-facing compared to not had increased odds of a positive SARS-CoV-2 test (OR 1.60, CI 1.08-2.39, proportions 8.6 vs. 5.5), but no statistically significant increase in hospitalization (OR 0.88, CI 0.20-3.66, proportions 10.2 vs. 11.4) and ICU admission (OR 0.34, CI 0.01-3.97, proportions 1.8 vs. 5.2). Conclusions: : In a large healthcare system, HCW had similar odds for testing SARS-CoV-2 positive, but lower odds of hospitalization compared to non-HCW. Patient-facing HCW had higher odds of a positive test. These results are key to understanding HCW risk mitigation during the COVID-19 pandemic.