Communicable and non-communicable co-morbidities and the presentation of COVID-19 in an African setting of high HIV-1 and tuberculosis prevalence (preprint)

Objectives To describe the presentation and outcome of SARS-CoV2 infection in an African setting of high non-communicable co-morbidity and also HIV-1 and tuberculosis prevalence. Design Case control analysis with cases stratified by HIV-1 and tuberculosis status. Setting A single-centre observational case-control study of adults admitted to a South African hospital with proven SARS-CoV-2 infection or alternative diagnosis. Participants 104 adults with RT-PCR-proven SARS-CoV2 infection of which 55 (52.9%) were male and 31 (29.8%) HIV-1 co-infected. 40 adults (35.7% male, 30.9% HIV-1 co-infected) admitted during the same period with no RT-PCR or serological evidence of SARS-CoV2 infection and assigned alternative diagnoses. Additional in vitro data from prior studies of 72 healthy controls and 118 HIV-1 uninfected and infected persons participants enrolled to a prior study with either immune evidence of tuberculosis sensitization but no symptoms or microbiologically confirmed pulmonary tuberculosis. Results Two or more co-morbidities were present in 57.7% of 104 RT-PCR proven COVID-19 presentations, the commonest being hypertension (48%), type 2 diabetes mellitus (39%), obesity (31%) but also HIV-1 (30%) and active tuberculosis (14%). Amongst patients dually infected by tuberculosis and SARS-CoV-2, clinical features could be dominated by either SARS-CoV-2 or tuberculosis: lymphopenia was exacerbated, and some markers of inflammation (D-dimer and ferritin) elevated in singly SARS-CoV-2 infected patients were even further elevated (p less than 0.05). HIV-1 and SARS-CoV2 co-infection resulted in lower absolute number and proportion of CD4 lymphocytes, with those in the lowest peripheral CD4 percentage strata exhibiting absent or lower antibody responses against SARS-CoV2. Death occurred in 30/104 (29%) of all COVID-19 patients and in 6/15 (40%) of patients with coincident SARS-CoV-2 and tuberculosis. Conclusions In this South African setting, HIV-1 and tuberculosis are common co-morbidities in patients presenting with COVID-19. In environments in which tuberculosis is common, SARS-CoV-2 and tuberculosis may co-exist with clinical presentation being typical of either disease. Clinical suspicion of exacerbation of co-existent tuberculosis accompanying SARS-CoV-2 should be high.

Adaptive immunity to SARS-CoV-2 in cancer patients: The CAPTURE study (preprint)

There is a pressing need to characterise the nature, extent and duration of immune response to SARS-CoV-2 in cancer patients and inform risk-reduction strategies and preserve cancer outcomes. CAPTURE is a prospective, longitudinal cohort study of cancer patients and healthcare workers (HCWs) integrating longitudinal immune profiling and clinical annotation. We evaluated 529 blood samples and 1051 oronasopharyngeal swabs from 144 cancer patients and 73 HCWs and correlated with >200 clinical variables. In patients with solid cancers and HCWs, S1-reactive and neutralising antibodies to SARS-CoV-2 were detectable five months post-infection. SARS-CoV-2-specific T-cell responses were detected, and CD4+ T-cell responses correlated with S1 antibody levels. Patients with haematological malignancies had impaired but partially compensated immune responses. Overall, cancer stage, disease status, and therapies did not correlate with immune responses. These findings have implications for understanding individual risks and potential effectiveness of SARS-CoV-2 vaccination in the cancer population.

Analysis of 46,046 SARS-CoV-2 whole-genomes leveraging principal component analysis (PCA) (preprint)

Since the beginning of the global SARS-CoV-2 pandemic, there have been a number of efforts to understand the mutations and clusters of genetic lines of the SARS-CoV-2 virus. Until now, phylogenetic analysis methods have been used for this purpose. Here we show that Principal Component Analysis (PCA), which is widely used in population genetics, can not only help us to understand existing findings about the mutation processes of the virus, but can also provide even deeper insights into these processes while being less sensitive to sequencing gaps. Here we describe a comprehensive analysis of a 46,046 SARS-CoV-2 genome sequence dataset downloaded from the GISAID database in June of this year. SummaryPCA provides deep insights into the analysis of large data sets of SARS-CoV-2 genomes, revealing virus lineages that have thus far been unnoticed.

Rapid, simplified whole blood-based multiparameter assay to quantify and phenotype SARS-CoV-2 specific T cells (preprint)

Rapid tests to evaluate SARS-CoV-2-specific T cell responses are urgently needed to decipher protective immunity and aid monitoring vaccine-induced immunity. Using a rapid whole blood assay requiring minimal amount of blood, we measured qualitatively and quantitatively SARS-CoV-2-specific CD4 T cell responses in 31 healthcare workers, using flow cytometry. 100% of COVID-19 convalescent participants displayed a detectable SARS-CoV-2-specific CD4 T cell response. SARS-CoV-2-responding cells were also detected in 40.9% of participants with no COVID-19-associated symptoms or who tested PCR negative. Phenotypic assessment indicated that, in COVID-19 convalescent participants, SARS-CoV-2 CD4 responses displayed an early differentiated memory phenotype with limited capacity to produce IFN{gamma}. Conversely, in participants with no reported symptoms, SARS-CoV-2 CD4 responses were enriched in late differentiated cells, co-expressing IFN{gamma} and TNF and also Granzyme B. This proof of concept study presents a scalable alternative to PBMC-based assays to enumerate and phenotype SARS-CoV-2-responding T cells, thus representing a practical tool to monitor adaptive immunity in vaccine trials. SummaryIn this proof of concept study, we show that SARS-CoV-2 T cell responses are easily detectable using a rapid whole blood assay requiring minimal blood volume. Such assay could represent a suitable tool to monitor adaptive immunity in vaccine trials.