Aging-related cell type-specific pathophysiologic immune responses that exacerbate disease severity in aged COVID-19 patients (preprint)

Coronavirus Disease 2019 (COVID-19) is especially severe in aged patients, defined as 65 years or older, for reasons that are currently unknown. To investigate the underlying basis for this vulnerability, we performed multimodal data analyses on immunity, inflammation, and COVID-19 incidence and severity as a function of age. Our analysis leveraged age-specific COVID-19 mortality and laboratory testing from a large COVID-19 registry, along with epidemiological data of [~]3.4 million individuals, large-scale deep immune cell profiling data, and single-cell RNA-sequencing data from aged COVID-19 patients across diverse populations. To begin, we confirmed a significantly increased rate of severe outcomes in aged COVID-19 patients. Furthermore, we identified increased inflammatory markers (C-reactive protein, D-dimer, and neutrophil-lymphocyte ratio), viral entry factors in secretory cells, and TGF{beta}-mediated immune-epithelial cell interactions, as well as reduction in both naive CD8 T cells and expression of interferon antiviral defense genes (i.e., IFITM3 and TRIM22), along with strong TGF-beta mediated immune-epithelial cell interactions (i.e., secretory - T regulatory cells), in aged severe COVID-19 patients. Taken together, our findings point to immuno-inflammatory factors that could be targeted therapeutically to reduce morbidity and mortality in aged COVID-19 patients.

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.

Multimodal Single-Cell Omics Analysis of COVID-19 Sex Differences in Human Immune Systems (preprint)

Sex differences in the risk of SARS-CoV-2 infection have been controversial and the underlying mechanisms of COVID-19 sexual dimorphism remain understudied. Here we inspected sex differences in SARS-CoV-2 positivity, hospitalization, admission to the intensive care unit (ICU), sera immune profiling, and two single-cell RNA-sequencing (snRNA-seq) profiles from nasal tissues and peripheral blood mononuclear cells (PBMCs) of COVID-19 patients with varying degrees of disease severity. Our propensity score-matching observations revealed that male individuals have a 29% increased likelihood of SARS-CoV-2 positivity, with a hazard ration (HR) 1.32 (95% confidence interval [CI] 1.18-1.48) for hospitalization and HR 1.51 (95% CI 1.24-1.84) for admission to ICU. Sera from male patients at hospital admission had decreased lymphocyte count and elevated inflammatory markers (C-reactive protein, procalcitonin, and neutrophils). We found that SARS-CoV-2 entry factors, including ACE2, TMPRSS2, FURIN and NRP1, have elevated expression in nasal squamous cells from males with moderate and severe COVID-19. Cell-cell network proximity analysis suggests possible epithelium-immune cell interactions and immune vulnerability underlying a higher mortality in males with COVID-19. Monocyte-elevated expression of Toll like receptor 7 (TLR7) and Bruton tyrosine kinase (BTK) is associated with severe outcomes in males with COVID-19. These findings provide basis for understanding immune responses underlying sex differences, and designing sex-specific targeted treatments and patient care for COVID-19.

A Network Medicine Approach to Investigation and Population-based Validation of Disease Manifestations and Drug Repurposing for COVID-19 (preprint)

The global Coronavirus Disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to unprecedented social and economic consequences. The risk of morbidity and mortality due to COVID-19 increases dramatically in the presence of co-existing medical conditions while the underlying mechanisms remain unclear. Furthermore, there are no proven effective therapies for COVID-19. This study aims to identify SARS-CoV-2 pathogenesis, diseases manifestations, and COVID-19 therapies using network medicine methodologies along with clinical and multi-omics observations. We incorporate SARS-CoV-2 virus-host protein-protein interactions, transcriptomics, and proteomics into the human interactome. Network proximity measure revealed underlying pathogenesis for broad COVID-19-associated manifestations. Multi-modal analyses of single-cell RNA-sequencing data showed that co-expression of ACE2 and TMPRSS2 was elevated in absorptive enterocytes from the inflamed ileal tissues of Crohn's disease patients compared to uninflamed tissues, revealing shared pathobiology by COVID-19 and inflammatory bowel disease. Integrative analyses of metabolomics and transcriptomics (bulk and single-cell) data from asthma patients indicated that COVID-19 shared intermediate inflammatory endophenotypes with asthma (including IRAK3 and ADRB2 ). To prioritize potential treatment, we combined network-based prediction and propensity score (PS) matching observational study of 18,118 patients from a COVID-19 registry. We identified that melatonin (odds ratio (OR) = 0.36, 95% confidence interval (CI) 0.22-0.59) was associated with 64% reduced likelihood of a positive laboratory test result for SARS-CoV-2. Using PS-matching user active comparator design, melatonin was associated with 54% reduced likelihood of SARS-CoV-2 positive test result compared to angiotensin II receptor blockers or angiotensin-converting enzyme inhibitors (OR = 0.46, 95% CI 0.24-0.86).