Variants of concern responsible for SARS-CoV-2 vaccine breakthrough infections from India.

Emerging reports of SARS-CoV-2 breakthrough infections entail methodical genomic surveillance for determining the efficacy of vaccines. This study elaborates genomic analysis of isolates from breakthrough infections following vaccination with AZD1222/Covishield and BBV152/Covaxin. Variants of concern B.1.617.2 and B.1.1.7 responsible for cases surge in April-May 2021 in Delhi, were the predominant lineages among breakthrough infections.

Spatio-temporal dynamics of intra-host variability in SARS-CoV-2 genomes.

During the course of the COVID-19 pandemic, large-scale genome sequencing of SARS-CoV-2 has been useful in tracking its spread and in identifying variants of concern (VOC). Viral and host factors could contribute to variability within a host that can be captured in next-generation sequencing reads as intra-host single nucleotide variations (iSNVs). Analysing 1347 samples collected till June 2020, we recorded 16 410 iSNV sites throughout the SARS-CoV-2 genome. We found ∼42% of the iSNV sites to be reported as SNVs by 30 September 2020 in consensus sequences submitted to GISAID, which increased to ∼80% by 30th June 2021. Following this, analysis of another set of 1774 samples sequenced in India between November 2020 and May 2021 revealed that majority of the Delta (B.1.617.2) and Kappa (B.1.617.1) lineage-defining variations appeared as iSNVs before getting fixed in the population. Besides, mutations in RdRp as well as RNA-editing by APOBEC and ADAR deaminases seem to contribute to the differential prevalence of iSNVs in hosts. We also observe hyper-variability at functionally critical residues in Spike protein that could alter the antigenicity and may contribute to immune escape. Thus, tracking and functional annotation of iSNVs in ongoing genome surveillance programs could be important for early identification of potential variants of concern and actionable interventions.

X-Linked Agammaglobulinemia and COVID-19: Two Case Reports and Review of Literature.

Introduction: The Centers for Disease Control and Prevention (CDC) has listed primary immunodeficiency disorders as being predisposed to severe coronavirus disease 2019 (COVID-19). However, patients affected with X-linked agammaglobulinemia (XLA) have shown contrary results. In this study, we present 2 boys in late adolescence from south India with XLA who were infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as well as a review of cases reported in the literature. Case Presentation: Two patients with XLA had been diagnosed late and were started on regular immunoglobulin prophylaxis only during adolescence. Both of them had developed bronchiectasis, an irreversible suppurative lung disease. However, both patients made an uneventful recovery without the need for artificial ventilation or convalescent plasma. Conclusion: Successful outcomes of patients with XLA and COVID-19, except for delayed recovery, from our experience and from global reports are intriguing and the role of B cell depletion is being studied as well. Further research and clinical experience are necessary to fully elucidate the reasons for these observations.

An optimized, amplicon-based approach for sequencing of SARS-CoV-2 from patient samples using COVIDSeq assay on Illumina MiSeq sequencing platforms.

Sequencing of SARS-CoV-2 genomes is crucial for understanding the genetic epidemiology of the COVID-19 pandemic. It is also critical for understanding the evolution of the virus and also for the rapid development of diagnostic tools. The present protocol is a modification of the Illumina COVIDSeq test. We describe an amplicon-based next-generation sequencing approach with short turnaround time, adapted for bench-top sequencers like MiSeq, iSeq, and MiniSeq. For complete details on the use and execution of this protocol, please refer to Bhoyar et al. (2021).

Clinical Spectrum of Neurological Manifestations in Pediatric COVID-19 Illness: A Case Series.

We describe a cohort of three patients with variable neurological presentations by SARS-COV-2 infection. It includes one case each of acute cerebellitis, acute encephalomyelitis and arterial ischemic stroke. To the best of our knowledge, we report the first pediatric case of acute cerebellitis due to SARS-CoV-2 infection. All critically ill patients were treated with methylprednisolone pulse therapy and dexamethasone. Patient with acute cerebellitis in addition required intravenous immunoglobulin infusion. All the patients responded to the treatment with complete neurological recovery.

Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes.

Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug-gene (pharmacogenetic), drug-drug and drug-drug-gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug-drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians.

Initial Insights Into the Genetic Epidemiology of SARS-CoV-2 Isolates From Kerala Suggest Local Spread From Limited Introductions.

Coronavirus disease 2019 (COVID-19) rapidly spread from a city in China to almost every country in the world, affecting millions of individuals. The rapid increase in the COVID-19 cases in the state of Kerala in India has necessitated the understanding of SARS-CoV-2 genetic epidemiology. We sequenced 200 samples from patients in Kerala using COVIDSeq protocol amplicon-based sequencing. The analysis identified 166 high-quality single-nucleotide variants encompassing four novel variants and 89 new variants in the Indian isolated SARS-CoV-2. Phylogenetic and haplotype analysis revealed that the virus was dominated by three distinct introductions followed by local spread suggesting recent outbreaks and that it belongs to the A2a clade. Further analysis of the functional variants revealed that two variants in the S gene associated with increased infectivity and five variants mapped in primer binding sites affect the efficacy of RT-PCR. To the best of our knowledge, this is the first and most comprehensive report of SARS-CoV-2 genetic epidemiology from Kerala.

Six artificial intelligence paradigms for tissue characterisation and classification of non-COVID-19 pneumonia against COVID-19 pneumonia in computed tomography lungs.

BACKGROUND: COVID-19 pandemic has currently no vaccines. Thus, the only feasible solution for prevention relies on the detection of COVID-19-positive cases through quick and accurate testing. Since artificial intelligence (AI) offers the powerful mechanism to automatically extract the tissue features and characterise the disease, we therefore hypothesise that AI-based strategies can provide quick detection and classification, especially for radiological computed tomography (CT) lung scans. METHODOLOGY: Six models, two traditional machine learning (ML)-based (k-NN and RF), two transfer learning (TL)-based (VGG19 and InceptionV3), and the last two were our custom-designed deep learning (DL) models (CNN and iCNN), were developed for classification between COVID pneumonia (CoP) and non-COVID pneumonia (NCoP). K10 cross-validation (90% training: 10% testing) protocol on an Italian cohort of 100 CoP and 30 NCoP patients was used for performance evaluation and bispectrum analysis for CT lung characterisation. RESULTS: Using K10 protocol, our results showed the accuracy in the order of DL > TL > ML, ranging the six accuracies for k-NN, RF, VGG19, IV3, CNN, iCNN as 74.58 ± 2.44%, 96.84 ± 2.6, 94.84 ± 2.85%, 99.53 ± 0.75%, 99.53 ± 1.05%, and 99.69 ± 0.66%, respectively. The corresponding AUCs were 0.74, 0.94, 0.96, 0.99, 0.99, and 0.99 (p-values < 0.0001), respectively. Our Bispectrum-based characterisation system suggested CoP can be separated against NCoP using AI models. COVID risk severity stratification also showed a high correlation of 0.7270 (p < 0.0001) with clinical scores such as ground-glass opacities (GGO), further validating our AI models. CONCLUSIONS: We prove our hypothesis by demonstrating that all the six AI models successfully classified CoP against NCoP due to the strong presence of contrasting features such as ground-glass opacities (GGO), consolidations, and pleural effusion in CoP patients. Further, our online system takes < 2 s for inference.

Analysis of the potential impact of genomic variants in global SARS-CoV-2 genomes on molecular diagnostic assays.

An epidemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus diseases (C0VID-19) initially reported in Wuhan, China has rapidly emerged into a global pandemic affecting millions of people worldwide. Molecular detection of SARS-CoV-2 using reverse transcription polymerase chain reaction (RT-PCR) forms the mainstay in screening, diagnosis and epidemiology of the disease. Since the virus evolves by accumulating base substitutions, mutations in the viral genome could possibly affect the accuracy of RT-PCR-based detection assays. The recent availability of genomes of SARS-CoV-2 isolates motivated us to assess the presence and potential impact of variations in target sites of the oligonucleotide primers and probes used in molecular diagnosis. We catalogued a total of 132 primer or probe sequences from literature and data available in the public domain. Our analysis revealed that a total of 5862 unique genetic variants mapped to at least one of the 132 primer or probe binding sites in the genome. A total of 29 unique variants were present in ≥ 1% of genomes from at least one of the continents (Asia, Africa, Australia, Europe, North America, and South America) that mapped to 36 unique primers or probes binding sites. Similarly, a total of 27 primer or probe binding sites had cumulative variants frequency of ≥ 1% in the global SARS-CoV-2 genomes. These included primers or probes sites which are used worldwide for molecular diagnosis as well as approved by national and international agencies. We also found 286 SARS-CoV-2 genomic regions with low variability at a continuous stretch of ≥ 20bps that could be potentially used for primer designing. This highlights the need for sequencing genomes of emerging pathogens to enable evidence-based policies for development and approval of diagnostics.

Admission Hyperglycemia in Non-diabetics Predicts Mortality and Disease Severity in COVID-19: a Pooled Analysis and Meta-summary of Literature.

In the latter part of 2019, a cluster of unexplained pneumonia cases were reported in Wuhan, China. In less than a year, SARS-CoV-2 has infected over 27 million people and claimed more than 800,000 deaths worldwide. Diabetes is a highly prevalent chronic metabolic disease, and recent reports have suggested a possible existence of COVID-19 related new-onset diabetes. Hyperglycemia induces an inflammatory state in the body, which coupled with coronavirus associated immune response is a possible explanation for clinical worsening of patients. We present a summary and pooled analysis of available evidence to ascertain the relationship between hyperglycemia in undiagnosed diabetics and outcomes of COVID-19 disease. Our results showed that hyperglycemia in non-diabetics was associated with higher risk of severe/critical illness (OR 1.837 (95% CI 1.368-2.465, P < 0.001) and mortality (2.822, 95% CI 1.587-5.019, P < 0.001) compared with those with normal values of blood glucose. The management of hyperglycemia in COVID-19 poses significant challenges in clinical practice, and the need to develop strategies for optimal glucose control in these patients cannot be overlooked.