Sampling the host response to SARS-CoV-2 in hospitals under siege

Charney, Alexander; Simons, Nicole W.; Mouskas, Konstantinos; Lepow, Lauren; Cheng, Esther; Bérichel, Jessica Le; Chang, Christie; Marvin, Robert; Valle, Diane Marie Del; Calorossi, Sharlene; Lansky, Alona; Walker, Laura; Patel, Manishkumar; Xie, Hui; Yi, Nancy; Yu, Alex W.; Kang, Gurpawan; Mendoza, Anthony; Liharska, Lora; Moya, Emily; Hartnett, Matthew; Hatem, Sandra; Wilkins, Lillian; Eaton, Melody; Jamal, Hajra; Tuballes, Kevin; Chen, Shuo; Tabachnikova, Alexandra; Chung, Jonathan H.; Harris, Jocelyn; Batchelor, Craig; Lacunza, Jose; Yishak, Mahlet; Argueta, Kimberly; Karekar, Neha; Lee, Brian; Kelly, Geoffrey; Geanon, Daniel; Handler, Diana; Leech, John; Stefanos, Hiyab; Dawson, Travis; Scott, Ieisha; Francoeur, Nancy; Johnson, Jessica; Vaid, Akhil; Glicksberg, Benjamin S.; Nadkarni, Girish N.; Schadt, Eric E.; Gelb, Bruce D.; Rahman, Adeeb; Sebra, Robert; Martin, Glenn; Agashe, Charuta; Agrawal, Priyal; Akyatan, Alara; Alesso-Carra, Kasey; Alibo, Eziwoma; Alvarez, Kelvin; Amabile, Angelo; Ascolillo, Steven; Bailey, Rasheed; Begani, Priya; Correra, Paloma Bravo; Brown, Stacey-Ann Whittaker; Buckup, Mark; Burka, Larissa; Cambron, Lena; Carrara, Gina; Chang, Serena M.; Chien, Jonathan; Chowdhury, Mashkura; Bozkus, Cansu Cimen; Comella, Phillip; Cosgrove, Dana; Cossarini, Francesca; Cotter, Liam; Dave, Arpit; Dayal, Bheesham; Dhainaut, Maxime; Dornfeld, Rebecca; Dul, Katie; Eber, Nissan; Elaiho, Cordelia; Fabris, Frank; Faith, Jeremiah J.; Falci, Dominique; Feng, Susie; Fennessy, Brian; Fernandes, Marie; Gangadharan, Sandeep; Grabowska, Joanna; Gyimesi, Gavin; Hamdani, Maha; Herbinet, Manon; Herrera, Elva; Hochman, Arielle; Hoffman, Gabriel E.; Hook, Jaime; Horta, Laila; Humblin, Étienne; Karim, Subha; Kim, Jessica; Lebovitch, Dannielle; Lee, Grace; Lee, Gyu Ho; Lee, Jacky; Leventhal, Mike; Lindblad, Katherine E.; Livanos, Alexandra E.; Machado, Rosalie; Mahmood, Zafar; Mar, Kelcey; Maskey, Shrisha; Matthews, Paul D.; Meckel, Katherine; Mehandru, Saurabh; Mercedes, Cynthia; Meyer, Dara; Mollaoglu, Gürkan; Morris, Sarah; Nie, Kai; Nisenholtz, Marjorie; Ofori-Amanfo, George; Onel, Kenan; Ounadjela, Merouane; Patel, Vishwendra; Pruitt, Cassandra; Rathi, Shivani; Redes, Jamie; Reyes-Torres, Ivan; Rodrigues, Alcina; Rodríguez, Alfonso; Roudko, Vladimir; Ruiz, Evelyn; Scalzo, Pearl; Silva, Pedro; Schanoski, Alessandra Soares; Straw, Meghan; Tabachnikova, Sasha; Teague, Collin; Upadhyaya, Bhaskar; Heide, Verena van der; Vaninov, Natalie; Wacker, Daniel; Walsh, Hadley; Wilk, C. Matthias; Wilson, Jessica; Wilson, Karen M.; Xue, Li; Yeboah, Naa-akomaah; Young, Sabina; Zaks, Nina; Zha, Renyuan; Marron, Thomas U.; Beckmann, Noam D.; Kim‐Schulze, Seunghee; Gnjatic, Sacha; Mérad, Miriam

doi:10.1038/s41591-020-1004-3

Cited by 29 publications

(24 citation statements)

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“…These advantages make this workflow particularly well‐suited to standardized large‐scale immune monitoring of COVID‐19 patients. We have integrated this workflow as part of a large centralized COVID‐19 sample collection and biobanking effort at the Mount Sinai Health System, in which the initial whole blood processing and staining was performed by a large team of volunteers with no prior CyTOF expertise 3 . Here we present data from a subset of this hospitalized cohort as a demonstration of the power of this assay in resolving changes in circulating immune cell frequency and phenotype associated with COVID‐19 disease status and severity.…”

Section: Resultsmentioning

confidence: 99%

A streamlined whole blood CyTOF workflow defines a circulating immune cell signature of COVID‐19

et al. 2021

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Mass cytometry (CyTOF) represents one of the most powerful tools in immune phenotyping, allowing high throughput quantification of over 40 parameters at single‐cell resolution. However, wide deployment of CyTOF‐based immune phenotyping studies are limited by complex experimental workflows and the need for specialized CyTOF equipment and technical expertise. Furthermore, differences in cell isolation and enrichment protocols, antibody reagent preparation, sample staining, and data acquisition protocols can all introduce technical variation that can confound integrative analyses of large data‐sets of samples processed across multiple labs. Here, we present a streamlined whole blood CyTOF workflow which addresses many of these sources of experimental variation and facilitates wider adoption of CyTOF immune monitoring across sites with limited technical expertise or sample‐processing resources or equipment. Our workflow utilizes commercially available reagents including the Fluidigm MaxPar Direct Immune Profiling Assay (MDIPA), a dry tube 30‐marker immunophenotyping panel, and SmartTube Proteomic Stabilizer, which allows for simple and reliable fixation and cryopreservation of whole blood samples. We validate a workflow that allows for streamlined staining of whole blood samples with minimal processing requirements or expertise at the site of sample collection, followed by shipment to a central CyTOF core facility for batched downstream processing and data acquisition. We apply this workflow to characterize 184 whole blood samples collected longitudinally from a cohort of 72 hospitalized COVID‐19 patients and healthy controls, highlighting dynamic disease‐associated changes in circulating immune cell frequency and phenotype.

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Section: Resultsmentioning

confidence: 99%

A streamlined whole blood CyTOF workflow defines a circulating immune cell signature of COVID‐19

et al. 2021

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“…Peripheral blood was collected at enrollment, day 5, and day 28 post enrollment. A subset of participants (n=80) returned for long-term follow-up visits 4,7, and 10 months post enrollment, with peripheral blood obtained.Sixty-one samples were obtained from hospitalized COVID-19 patients enrolled in the Mount SinaiHealth System (MSHS) collected by the Mount Sinai COVID-19 biobank22 . The median age was 65 years old with a range from 33 -98 years old.…”

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confidence: 99%

Structurally and functionally distinct early antibody responses predict COVID-19 disease trajectory and mRNA vaccine response

Chakraborty

González

Sievers

et al. 2021

Preprint

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Serologic markers that predict severe COVID-19 disease trajectories could enable early medical interventions and reduce morbidity and mortality. We found that distinct features of IgG Fab and Fc domain structures were present within three days of a positive test that predicted two separate disease trajectories in a prospective cohort of patients with COVID-19. One trajectory was defined by early production of neutralizing antibodies and led to mild disease. A distinct trajectory, characterized by an initial period of mild symptoms followed by rapid progression to more severe outcomes, was predicted by the absence of early neutralizing antibody responses with concomitant production of afucosylated IgGs. Elevated frequencies of monocytes expressing the receptor for afucosylated IgGs, FcγRIIIa (CD16a), were an additional antecedent in patients with the more severe outcomes. In mechanistic studies, afucosylated immune complexes in the lung triggered an inflammatory infiltrate and cytokine production that was dependent on CD16a. Finally, in healthy subjects, mRNA SARS-CoV-2 vaccination elicited neutralizing antibodies that were enriched for Fc fucosylation and sialylation and distinct from both infection-induced trajectories. These data show the importance of combined Fab and Fc domain functions in the antiviral response, define an early antibody signature in people who progressed to more severe COVID-19 outcomes and have implications for novel therapeutic strategies targeting FcγRIIIa pathways.

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“…For the Mount Sinai COVID-19 biobank 23 , electronic medical records (EMR) of all patients hospitalized in the previous 24 hours were screened daily to identify eligible patients (and controls) and to obtain bio-specimens with very broad inclusion criteria and very limited exclusion criteria. This study was approved by the Institutional Review Board (IRB) at the Icahn School of Medicine at Mount Sinai (20-0327).…”

Section: Methodsmentioning

confidence: 99%

IL10RB as a key regulator of COVID-19 host susceptibility and severity

Voloudakis

Hoffman

Venkatesh

et al. 2021

Preprint

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Background Recent efforts have identified genetic loci that are associated with coronavirus disease 2019 (COVID-19) infection rates and disease outcome severity. Translating these genetic findings into druggable genes and readily available compounds that reduce COVID-19 host susceptibility is a critical next step. Methods We integrate COVID-19 genetic susceptibility variants, multi-tissue genetically regulated gene expression (GReX) and perturbargen signatures to identify candidate genes and compounds that reverse the predicted gene expression dysregulation associated with COVID-19 susceptibility. The top candidate gene is validated by testing both its GReX and observed blood transcriptome association with COVID-19 severity, as well as by in vitro perturbation to quantify effects on viral load and molecular pathway dysregulation. We validate the in silico drug repositioning analysis by examining whether the top candidate compounds decrease COVID-19 incidence based on epidemiological evidence. Results We identify IL10RB as the top key regulator of COVID-19 host susceptibility. Predicted GReX up-regulation of IL10RB and higher IL10RB expression in COVID-19 patient blood is associated with worse COVID-19 outcomes. In vitro IL10RB overexpression is associated with increased viral load and activation of immune-related molecular pathways. Azathioprine and retinol are prioritized as candidate compounds to reduce the likelihood of testing positive for COVID-19. Conclusions We establish an integrative data-driven approach for gene target prioritization. We identify and validate IL10RB as a suitable molecular target for modulation of COVID-19 host susceptibility. Finally, we provide evidence for a few readily available medications that would warrant further investigation as drug repositioning candidates.

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Sampling the host response to SARS-CoV-2 in hospitals under siege

Cited by 29 publications

References 0 publications

A streamlined whole blood CyTOF workflow defines a circulating immune cell signature of COVID‐19

A streamlined whole blood CyTOF workflow defines a circulating immune cell signature of COVID‐19

Structurally and functionally distinct early antibody responses predict COVID-19 disease trajectory and mRNA vaccine response

IL10RB as a key regulator of COVID-19 host susceptibility and severity

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