IntroductionA single center open label phase II randomised control trial was done to assess the pathogen and host-intrinsic factors influencing clinical and immunological benefits of passive immunization using convalescent plasma therapy (CPT), in addition to standard of care (SOC) therapy in severe COVID-19 patients, as compared to patients only on SOC therapy.MethodsConvalescent plasma was collected from patients recovered from COVID-19 following a screening protocol which also included measuring plasma anti SARS-CoV2 spike IgG content. Retrospectively, neutralizing antibody content was measured and proteome was characterized by LC-MS/MS for all convalescent plasma units that were transfused to patients. Severe COVID-19 patients with evidence for acute respiratory distress syndrome (ARDS) with PaO2/FiO2 ratio 100-300 (moderate ARDS) were recruited and randomised into two parallel arms of SOC and CPT, N=40 in each arm. Peripheral blood samples were collected on the day of enrolment (T1) followed by day3/4 (T2) and day 7 (T3). RT-PCR and sequencing was done for SARS-CoV2 RNA isolated from nasopharyngeal swabs collected at T1. A panel of cytokines and neutralizing antibody content were measured in plasma at all three timepoints. Patients were followed up for 30 days post-admission to assess the primary outcomes of all cause mortality and immunological correlates for clinical benefits.ResultsWhile across all age-groups no statistically significant clinical benefit was registered for patients in the CPT arm, significant immediate mitigation of hypoxia, reduction in hospital stay as well as survival benefit was recorded in severe COVID-19 patients with ARDS aged less than 67 years receiving convalescent plasma therapy. In addition to its neutralizing antibody content a prominent effect of convalescent plasma on attenuation of systemic cytokine levels possibly contributed to its benefits.ConclusionPrecise targeting of severe COVID-19 patients is necessary for reaping the clinical benefits of convalescent plasma therapy.Clinical trial registrationClinical Trial Registry of India No. CTRI/2020/05/025209

The COVID-19 pandemic originating in the Wuhan province of China in late 2019 has impacted global health, causing increased mortality among elderly patients and individuals with comorbid conditions. During the passage of the virus through affected populations, it has undergone mutations, some of which have recently been linked with increased viral load and prognostic complexities. Several of these variants are point mutations that are difficult to diagnose using the gold standard quantitative real-time PCR (qRT-PCR) method and necessitates widespread sequencing which is expensive, has long turn-around times, and requires high viral load for calling mutations accurately. Here, we repurpose the high specificity of Francisella novicida Cas9 (FnCas9) to identify mismatches in the target for developing a lateral flow assay that can be successfully adapted for the simultaneous detection of SARS-CoV2 infection as well as for detecting point mutations in the sequence of the virus obtained from patient samples. We report the detection of the S gene mutation N501Y (present across multiple variant lineages of SARS-CoV2) within an hour using lateral flow paper strip chemistry. The results were corroborated using deep sequencing on multiple wild type (n=37) and mutant (n=22) viral RNA samples with a sensitivity of 87% and specificity of 97%. The design principle can be rapidly adapted for other mutations (as shown also for E484K and T716I) highlighting the advantages of quick optimization and roll-out of CRISPR diagnostics (CRISPRDx) for disease surveillance even beyond COVID-19. This study was funded by Council for Scientific and Industrial Research, India.

A single center open label phase 2 randomised control trial (Clinical Trial Registry of India No. CTRI/2020/05/025209) was done to assess clinical and immunological benefits of passive immunization using convalescent plasma therapy. At the Infectious Diseases and Beleghata General Hospital in Kolkata, India, 80 patients hospitalized with severe COVID-19 disease and fulfilling the inclusion criteria (aged more than 18 years, with either mild ARDS having PaO2/FiO2 200–300 or moderate ARDS having PaO2/FiO2 100–200, not on mechanical ventilation) were recruited and randomized into either standard of care (SOC) arm (N = 40) or the convalescent plasma therapy (CPT) arm (N = 40). Primary outcomes were all-cause mortality by day 30 of enrolment and immunological correlates of response to therapy if any, for which plasma abundance of a large panel of cytokines was quantitated before and after intervention to assess the effect of CPT on the systemic hyper-inflammation encountered in these patients. The secondary outcomes were recovery from ARDS and time taken to negative viral RNA PCR as well as to report any adverse reaction to plasma therapy. Transfused convalescent plasma was characterized in terms of its neutralizing antibody content as well as proteome. The trial was completed and it was found that primary outcome of all-cause mortality was not significantly different among severe COVID-19 patients with ARDS randomized to two treatment arms (Mantel-Haenszel Hazard Ratio 0.6731, 95% confidence interval 0.3010-1.505, with a P value of 0.3424 on Mantel-Cox Log-rank test). No adverse effect was reported with CPT. In severe COVID-19 patients with mild or moderate ARDS no significant clinical benefit was registered in this clinical trial with convalescent plasma therapy in terms of prespecified outcomes.

Background: SARS-CoV-2 infection may not provide long lasting post-infection immunity. While hundreds of reinfections have reported only a few have been confirmed. Whole genome sequencing (WGS) of the viral isolates from the different episodes is mandatory to establish reinfection.Methods: Nasopharyngeal (NP), oropharyngeal (OP) and whole blood (WB) samples were collected from paired samples of four individuals who were suspected of SARS-CoV-2 reinfection based on distinct clinical episodes and RT-PCR tests. Details from their case record files and investigations were documented. RNA was extracted from the NP and OP samples and subjected to WGS, and the nucleotide and amino acid sequences were subjected to genome and protein-based functional annotation analyses. Serial serology was performed for Anti-N IgG, Anti- S1 RBD IgG, and sVNT (surrogate virus neutralizing test).Findings: Three patients were more symptomatic with lower Ct values and longer duration of illness. Seroconversion was detected soon after the second episode in three patients. WGS generated a genome coverage ranging from 80.07 to 99.7%. Phylogenetic analysis revealed sequences belonged to G, GR and “Other” clades. A total of 42mutations were identified in all the samples, consisting of 22 non-synonymous, 17 synonymous, two in upstream, and one in downstream regions of the SARS-CoV-2 genome. Comparative genomic and protein-based annotation analyses revealed differences in the presence and absence of specific mutations in the virus sequences from the two episodes in all four paired samples.Interpretation: Based on the criteria of genome variations identified by whole genome sequencing and supported by clinical presentation, molecular and serological tests, we were able to confirm reinfections in two patients, provide weak evidence of reinfection in the third patient and unable to rule out a prolonged infection in the fourth. This study emphasizes the importance of detailed analyses of clinical and serological information as well as the virus's genomic variations while assessing cases of SARS-CoV-2 reinfection.

The variability of clinical course and prognosis of COVID-19 highlights the necessity of patient sub-group risk stratification based on clinical data. In this study, clinical data from a cohort of Indian COVID-19 hospitalized patients is used to develop risk stratification and mortality prediction models. We analyzed a set of 70 clinical parameters including physiological and hematological for developing machine learning models to identify biomarkers. We also compared the Indian and Wuhan cohort, and analyzed the role of steroids. A bootstrap averaged ensemble of Bayesian networks was also learned to construct an explainable model for discovering actionable influences on mortality and days to outcome. We discovered blood parameters, diabetes, co-morbidity and SpO2 levels as important risk stratification features, whereas mortality prediction is dependent only on blood parameters. XGboost and logistic regression model yielded the best performance on risk stratification and mortality prediction, respectively (AUC score 0.83, AUC score 0.92). Blood coagulation parameters (ferritin, D-Dimer and INR), immune and inflammation parameters IL6, LDH and Neutrophil (%) are common features for both risk and mortality prediction. Compared with Wuhan patients, Indian patients with extreme blood parameters indicated higher survival rate. Analyses of medications suggest that a higher proportion of survivors and mild patients who were administered steroids had extreme neutrophil and lymphocyte percentages. The ensemble averaged Bayesian network structure revealed serum ferritin to be the most important predictor for mortality and Vitamin D to influence severity independent of days to outcome. The findings are important for effective triage during strains on healthcare infrastructure.

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COVID-19 is invariably a disease of diverse clinical manifestation, with multiple facets involved in modulating the progression and outcome. In this regard, we investigated the role of transcriptionally active microbial co-infections as possible modulators of disease pathology in hospital admitted SARS-CoV-2 infected patients.

Over 95% of the COVID-19 cases are mild-to-asymptomatic who contribute to disease transmission whereas most of the severe manifestations of the disease are observed in elderly and in patients with comorbidities and dysregulation of immune response has been implicated in severe clinical outcomes. However, it is unclear whether asymptomatic or mild infections are due to low viral load or lack of inflammation. We have measured the kinetics of SARS-CoV-2 viral load in the respiratory samples and serum markers of inflammation in hospitalized COVID-19 patients with mild symptoms. We observed a bi-phasic pattern of virus load which was eventually cleared in most patients at the time of discharge. Viral load in saliva samples from a subset of patients showed good correlation with nasopharyngeal samples. Serum interferon levels were downregulated during early stages of infection but peaked at later stages correlating with elevated levels of T-cell cytokines and other inflammatory mediators such as IL-6 and TNF-alpha which showed a bi-phasic pattern. The clinical recovery of patients correlated with decrease in viral load and increase in interferons and other cytokines which indicates an effective innate and adaptive immune function in mild infections. We further characterized one of the SARS-CoV-2 isolate by plaque purification and show that infection of lung epithelial cells (Calu-3) with this isolate led to cytopathic effect disrupting epithelial barrier function and tight junctions. Finally we showed that zinc was capable of inhibiting SARS-CoV-2 infection in this model suggesting a beneficial effect of zinc supplementation in COVID-19 infection.