ABSTRACT
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. Interestingly, several of these variants are point mutations that are difficult to diagnose using the gold standard quantitative real-time PCR (qPCR) method. This necessitates widespread sequencing which is expensive, has long turn-around times, and requires high viral load for calling mutations accurately. In this study, we show that the high specificity of Francisella novicida Cas9 (FnCas9) to point mismatches 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 mutation N501Y (earlier shown to be present in the British N501Y.V1, South African N501Y.V2, and Brazilian N501Y.V3 variants of SARS-CoV2) within an hour using paper strip chemistry. The results were corroborated using deep sequencing. Our design principle can be rapidly adapted for other mutations, highlighting the advantages of quick optimization and roll-out of CRISPR diagnostics (CRISPRDx) for disease surveillance even beyond COVID-19.
ABSTRACT
The clinical course of coronavirus disease 2019 (COVID-19) infection is highly variable with the vast majority recovering uneventfully but a small fraction progressing to severe disease and death. Appropriate and timely supportive care can reduce mortality and it is critical to evolve better patient risk stratification based on simple clinical data, so as to perform effective triage during strains on the healthcare infrastructure. This study presents risk stratification and mortality prediction models based on usual clinical data from 544 COVID-19 patients from New Delhi, India using machine learning methods. An XGboost classifier yielded the best performance on risk stratification (F1 score of 0.81). A logistic regression model yielded the best performance on mortality prediction (F1 score of 0.71). Significant biomarkers for predicting risk and mortality were identified. Examination of the data in comparison to a similar dataset with a Wuhan cohort of 375 patients was undertaken to understand the much lower mortality rates in India and the possible reasons thereof. The comparison indicated higher survival rate in the Delhi cohort even when patients had similar parameters as the Wuhan patients who died. Steroid administration was very frequent in Delhi patients, especially in surviving patients whose biomarkers indicated severe disease. This study helps in identifying the high-risk patient population and suggests treatment protocols that may be useful in countries with high mortality rates.
ABSTRACT
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
ABSTRACT
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- 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. IMPORTANCEA majority of COVID-19 patients are asymptomatic or exhibit mild symptoms despite high viral loads suggesting a key role for the acute phase innate immune response in limiting the damage and clearing the virus. Therefore, it is important to understand the early phase response to SARS-CoV-2 infection in such patients to devise strategies for clinical management of the disease. Our study shows the kinetics of immune mediators in the serum samples collected from hospitalized COVID-19 patients with mild symptoms. We further characterize a virus isolate from one of these patients and demonstrate its effect on epithelial barrier functions and show that zinc was capable of inhibiting SARS-CoV-2 infection under these conditions. Our results suggest a key role for the innate immune responses in the early phase of infection in mitigating clinical symptoms, clearing the virus and recovery from illness and suggest an antiviral role for zinc in COVID-19 infection.
