Utility of Bulk T-Cell Receptor Repertoire Sequencing Analysis in Understanding Immune Responses to COVID-19.

Measuring immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 19 (COVID-19), can rely on antibodies, reactive T cells and other factors, with T-cell-mediated responses appearing to have greater sensitivity and longevity. Because each T cell carries an essentially unique nucleic acid sequence for its T-cell receptor (TCR), we can interrogate sequence data derived from DNA or RNA to assess aspects of the immune response. This review deals with the utility of bulk, rather than single-cell, sequencing of TCR repertoires, considering the importance of study design, in terms of cohort selection, laboratory methods and analysis. The advances in understanding SARS-CoV-2 immunity that have resulted from bulk TCR repertoire sequencing are also be discussed. The complexity of sequencing data obtained by bulk repertoire sequencing makes analysis challenging, but simple descriptive analyses, clonal analysis, searches for specific sequences associated with immune responses to SARS-CoV-2, motif-based analyses, and machine learning approaches have all been applied. TCR repertoire sequencing has demonstrated early expansion followed by contraction of SARS-CoV-2-specific clonotypes, during active infection. Maintenance of TCR repertoire diversity, including the maintenance of diversity of anti-SARS-CoV-2 response, predicts a favourable outcome. TCR repertoire narrowing in severe COVID-19 is most likely a consequence of COVID-19-associated lymphopenia. It has been possible to follow clonotypic sequences longitudinally, which has been particularly valuable for clonotypes known to be associated with SARS-CoV-2 peptide/MHC tetramer binding or with SARS-CoV-2 peptide-induced cytokine responses. Closely related clonotypes to these previously identified sequences have been shown to respond with similar kinetics during infection. A possible superantigen-like effect of the SARS-CoV-2 spike protein has been identified, by means of observing V-segment skewing in patients with severe COVID-19, together with structural modelling. Such a superantigen-like activity, which is apparently absent from other coronaviruses, may be the basis of multisystem inflammatory syndrome and cytokine storms in COVID-19. Bulk TCR repertoire sequencing has proven to be a useful and cost-effective approach to understanding interactions between SARS-CoV-2 and the human host, with the potential to inform the design of therapeutics and vaccines, as well as to provide invaluable pathogenetic and epidemiological insights.

High Prevalence of Pre-Existing Liver Abnormalities Identified Via Autopsies in COVID-19: Identification of a New Silent Risk Factor?

A high prevalence of hepatic pathology (in 17 of 19 cases) was reported in post-mortem (PM) examinations of COVID-19 patients, undertaken between March 2020 and February 2021 by a single autopsy pathologist in two English Coronial jurisdictions. The patients in our cohort demonstrated high levels of recognised COVID-19 risk factors, including hypertension (8/16, 50%), type 2 diabetes mellitus (8/16, 50%) and evidence of arteriopathy 6/16 (38%). Hepatic abnormalities included steatosis (12/19; 63%), moderate to severe venous congestion (5/19; 26%) and cirrhosis (4/19; 21%). A subsequent literature review indicated a significantly increased prevalence of steatosis (49%), venous congestion (34%) and cirrhosis (9.3%) in COVID-19 PM cases, compared with a pre-pandemic PM cohort (33%, 16%, and 2.6%, respectively), likely reflecting an increased mortality risk in SARS-CoV-2 infection for patients with pre-existing liver disease. To corroborate this observation, we retrospectively analysed the admission liver function test (LFT) results of 276 consecutive, anonymised COVID-19 hospital patients in our centre, for whom outcome data were available. Of these patients, 236 (85.5%) had significantly reduced albumin levels at the time of admission to hospital, which was likely indicative of pre-existing chronic liver or renal disease. There was a strong correlation between patient outcome (length of hospital admission or death) and abnormal albumin at the time of hospital admission (p = 0.000012). We discuss potential mechanisms by which our observations of hepatic dysfunction are linked to a risk of COVID-19 mortality, speculating on the importance of recently identified anti-interferon antibodies.

Use of machine learning to identify a T cell response to SARS-CoV-2.

The identification of SARS-CoV-2-specific T cell receptor (TCR) sequences is critical for understanding T cell responses to SARS-CoV-2. Accordingly, we reanalyze publicly available data from SARS-CoV-2-recovered patients who had low-severity disease (n = 17) and SARS-CoV-2 infection-naive (control) individuals (n = 39). Applying a machine learning approach to TCR beta (TRB) repertoire data, we can classify patient/control samples with a training sensitivity, specificity, and accuracy of 88.2%, 100%, and 96.4% and a testing sensitivity, specificity, and accuracy of 82.4%, 97.4%, and 92.9%, respectively. Interestingly, the same machine learning approach cannot separate SARS-CoV-2 recovered from SARS-CoV-2 infection-naive individual samples on the basis of B cell receptor (immunoglobulin heavy chain; IGH) repertoire data, suggesting that the T cell response to SARS-CoV-2 may be more stereotyped and longer lived. Following validation in larger cohorts, our method may be useful in detecting protective immunity acquired through natural infection or in determining the longevity of vaccine-induced immunity.