3D genomic capture of regulatory immuno-genetic profiles in COVID-19 patients for prognosis of severe COVID disease outcome

Abstract

Human infection with the SARS-CoV-2 virus leads to coronavirus disease (COVID-19). A striking characteristic of COVID-19 infection in humans is the highly variable host response and the diverse clinical outcomes, ranging from clinically asymptomatic to severe immune reactions leading to hospitalization and death. Here we used a 3D genomic approach to analyse blood samples at the time of COVID diagnosis, from a global cohort of 80 COVID-19 patients, with different degrees of clinical disease outcomes. Using 3D whole genome EpiSwitch® arrays to generate over 1 million data points per patient, we identified a distinct and measurable set of differences in genomic organization at immune-related loci that demonstrated prognostic power at baseline to stratify patients with mild forms of illness and those with severe forms that required hospitalization and intensive care unit (ICU) support. Further analysis revealed both well established and new COVID-related dysregulated pathways and loci, including innate and adaptive immunity; ACE2; olfactory, Gβψ, Ca2+ and nitric oxide (NO) signalling; prostaglandin E2 (PGE2), the acute inflammatory cytokine CCL3, and the T-cell derived chemotactic cytokine CCL5. We identified potential therapeutic agents for mitigation of severe disease outcome, with several already being tested independently, including mTOR inhibitors (rapamycin and tacrolimus) and general immunosuppressants (dexamethasone and hydrocortisone). Machine learning algorithms based on established EpiSwitch® methodology further identified a subset of 3D genomic changes that could be used as prognostic molecular biomarker leads for the development of a COVID-19 disease severity test.

Development and validation of blood-based prognostic biomarkers for severity of COVID disease outcome using EpiSwitch 3D genomic regulatory immuno-genetic profiling

“…EpiSwitch ® 3C libraries, with chromosome conformation analytes converted to sequence based tags, were prepared from frozen whole blood samples using EpiSwitch ® protocols following the manufacturer's instructions (Oxford BioDynamics Plc) [15]. All samples were processed under biological containment level CL2+.…”

“…The top array-derived markers identified in our previous study were interrogated using OBD's proprietary primer design software package to identify genomic positions suitable for a hydrolysis probe based real time PCR (RT-PCR) assay [15]. Briefly, the top array-derived markers associated with prognostic potential to differentiate between mild and severe COVID disease outcomes were filtered on fold change and adjusted p value.…”

“…As SARS-CoV-2 variants can spread faster than the original strain and some variants may be resistant to the neutralizing antibodies produced by individuals after vaccination, the risk of a widespread disease resurgence and the continued societal burdens of an extended pandemic are real[39][40][41].While many molecular tests have been developed to detect the presence of the SARS-CoV-2 virus, a reduced to practice molecular test with high prognostic accuracy for severe outcomes following a SARS-CoV-2 infection represents an unmet healthcare need. Here we extended on a previously published study and describe the validation of a blood-based biomarkers for the prediction of severe symptoms of COVID-19 disease, which can place individuals in the intensive care support[15]. We identified a set of six biomarkers associated with systemic immune-genetic dysregulation, that when processed and measured by qPCR on human blood samples provided an accurate predictive readout on likely COVID-19 disease severity.…”

“…Recently, we reported on the use of EpiSwitch®, a chromosome conformation capture (3C) methodology that has been reduced to practice for the discovery of blood-based 3D genomic biomarkers and patient stratification in a variety of immune-related diseases, to identify prognostic profiles that could serve as a potential blood-based molecular classifier for the prediction of COVID-19 disease severity [15][16][17][18][19][20][21][22]. Specifically, we used EpiSwitch Explorer 3D whole genome arrays to identify changes at immune-related loci in blood samples from a multi-national cohort of COVID-19 patients.…”

“…The proteins encoded at the locations of the 3D genomic marker leads were involved in biological pathways with direct relevance to immune system function including T-cell signalling, macrophage-stimulating protein (MSP)-RON signalling, and calcium signalling [15]. The aim of this study was an extension of our previous work, using the established EpiSwitch platform to translate the array-derived 3D genomic biomarkers into a qPCR-based testing format, refine and reduce the biomarker panel, build a classification model and perform validation on independent COVID-19 patient cohorts.…”