Title: Development of a robust T cell assay to retrospectively diagnose SARS-CoV-2 infection and T cell cytokine release assay as diagnostic and monitoring assay in Long COVID patients
Funder: Department of Health and Social Care

Abstract: In the UK, 4.38 million people have been infected with SARS-CoV-2 and ~ 95% are non-hospitalised cases. At least 20% of the non-hospitalised cases will likely go on to have Long COVID. As many as 30% of patients don t have detectable antibodies especially those that had asymptomatic and mild COVID infection. Mounting evidence shows that SARS-CoV-2 memory T cell responses are detected >6 months after infection. Our hypothesis is that we can utilise T cell assays to develop a diagnostic assay to retrospectively diagnose infection with SARS-CoV-2 and determine immune biomarker/s to monitor Long COVID. Co-applicant (NS) set up a clinic in May 2020, at Addenbrooke s hospital, specifically for non-hospitalised Long COVID patients. Participants (85 patients) are being enrolled into the Cambridge NIHR COVID BioResource, blood samples for sera and PBMC are being collected and BioBanked. From our pilot study, results show that IL-2 responses specific to N and M peptides are indicative of past SARS-CoV-2 infection. We are also able to distinguish infection specific response from vaccination, by measuring Spike, M and N, which will become increasingly important. Measurement of IFN-&gamma; has also proved of use as we have started to identify a spontaneous production of IFN-&gamma; associated with Long COVID patients. In the proposed application study participants will continue to be recruited from our clinic and followed up every 3 months for up to 18 months; a) to confirm that the measurement of N and M specific T cell IL-2 production is a robust assay for the retrospective diagnosis of SARS-CoV-2 infection and b) utilise spontaneous IFN-&gamma; production (as monitoring biomarker for Long COVID patients). We will then adapt the approach to a simpler whole blood peptide stimulation assay with IFN-&gamma; and IL-2 ELISA readouts that would be high throughput and easier to implement as clinical diagnostic assay.

Lay abstract: The current COVID-19 pandemic caused by coronavirus (SARS-CoV-2), has already infected close to 150 million people with over 3 million deaths worldwide. Unfortunately, a significant proportion of people continue to experience distressing and life altering symptoms several months after the initial illness. People with persistent symptoms are currently classified as having Long COVID. Diagnosis of Long COVID is hampered especially in the group of non-hospitalised patients as the majority had asymptomatic to mild infection hence less likely to have generated antibodies against coronavirus and antibody tests miss a significant proportion of patients (~30%). We therefore propose to develop a COVID diagnostic assay that is based on detecting the aspect of the body s immune response (T cell response) that is triggered in this case in response to coronavirus and is most likely to be detected several months to years following infection. The diagnostic assay will be used in clinical setting. This research proposal was birthed in consultation with patients suffering from Long COVID since the initial wave. We set up a Long COVID clinic for non-hospitalised patients in May 2020 at Addenbrooke s, to provide better clinical care and enroll patients into the Cambridge COVID NIHR BioResource. The enrolled patients had bloods taken and we have preliminary results that show our study s feasibility and we want to scale this to an assay that will be able to process high volumes of samples with quick turnaround of results. We will continue to enroll patients and follow them up every 3 months for up to 18 months. We will disseminate our research findings to the public and patients via bulletins to GPs, patient information leaflets generated by the Addenbrooke s media and communications department and to the scientific and medical community via local medical grand rounds, publications in high impact scientific journals and departmental meetings.

Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: INFECTION