Human Genome Polymorphisms and Computational Intelligence Approach Revealed a Complex Genomic Signature for COVID-19 Severity in Brazilian Patients.

We present a genome polymorphisms/machine learning approach for severe COVID-19 prognosis. Ninety-six Brazilian severe COVID-19 patients and controls were genotyped for 296 innate immunity loci. Our model used a feature selection algorithm, namely recursive feature elimination coupled with a support vector machine, to find the optimal loci classification subset, followed by a support vector machine with the linear kernel (SVM-LK) to classify patients into the severe COVID-19 group. The best features that were selected by the SVM-RFE method included 12 SNPs in 12 genes: PD-L1, PD-L2, IL10RA, JAK2, STAT1, IFIT1, IFIH1, DC-SIGNR, IFNB1, IRAK4, IRF1, and IL10. During the COVID-19 prognosis step by SVM-LK, the metrics were: 85% accuracy, 80% sensitivity, and 90% specificity. In comparison, univariate analysis under the 12 selected SNPs showed some highlights for individual variant alleles that represented risk (PD-L1 and IFIT1) or protection (JAK2 and IFIH1). Variant genotypes carrying risk effects were represented by PD-L2 and IFIT1 genes. The proposed complex classification method can be used to identify individuals who are at a high risk of developing severe COVID-19 outcomes even in uninfected conditions, which is a disruptive concept in COVID-19 prognosis. Our results suggest that the genetic context is an important factor in the development of severe COVID-19.

Real-life evaluation of a rapid antigen test (DPP® SARS-CoV-2 antigen) for COVID-19 diagnosis of primary healthcare patients, in the context of the omicron-dominant wave in Brazil.

OBJECTIVES: We aimed to investigate the real-life performance of the rapid antigen test (RAT) in the context of a primary healthcare setting, including symptomatic and asymptomatic individuals that sought diagnostic during a Omicron infection wave. METHODS: We prospectively accessed the performance of the DPP® SARS-CoV-2 Antigen test in the context of an omicron-dominant real-life setting. We evaluated 347 unselected individuals (all-comers) from a public testing center in Brazil, performing the RAT diagnosis at point-of-care with fresh samples. The combinatory result from two distinct RT-qPCR methods was employed as reference and 13 samples with discordant PCR results were excluded. RESULTS: The assessment of the rapid test in 67 PCR-positive and 265 negative samples revealed an overall sensitivity of 80.5% (CI95% = 69.1 - 89.2%), specificity of 99.2% (CI95% = 97.3 - 99.1%) and positive/negative predictive values higher than 95%. However, we observed that the sensitivity was dependent on the viral load (sensitivity in Ct<31 = 93.7%, CI = 82.8 - 98.7%; Ct>31 = 47.4%, CI = 24.4 - 71.1%). The positive samples evaluated in the study were Omicron (BA.1/BA.1.1) by whole-genome sequencing (n=40) and multiplex RT-qPCR (n=17). CONCLUSIONS: Altogether, the data obtained from a real-life prospective cohort supports that the RAT sensitivity for Omicron remains high and underscores the reliability of the test for COVID-19 diagnosis in settings with high disease prevalence and limited PCR testing capability.

Unusual SARS-CoV-2 intrahost diversity reveals lineage superinfection.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has infected almost 200 million people worldwide by July 2021 and the pandemic has been characterized by infection waves of viral lineages showing distinct fitness profiles. The simultaneous infection of a single individual by two distinct SARS-CoV-2 lineages may impact COVID-19 disease progression and provides a window of opportunity for viral recombination and the emergence of new lineages with differential phenotype. Several hundred SARS-CoV-2 lineages are currently well phylogenetically defined, but two main factors have precluded major coinfection/codetection and recombination analysis thus far: (i) the low diversity of SARS-CoV-2 lineages during the first year of the pandemic, which limited the identification of lineage defining mutations necessary to distinguish coinfecting/recombining viral lineages; and the (ii) limited availability of raw sequencing data where abundance and distribution of intrasample/intrahost variability can be accessed. Here, we assembled a large sequencing dataset from Brazilian samples covering a period of 18 May 2020 to 30 April 2021 and probed it for unexpected patterns of high intrasample/intrahost variability. This approach enabled us to detect nine cases of SARS-CoV-2 coinfection with well characterized lineage-defining mutations, representing 0.61 % of all samples investigated. In addition, we matched these SARS-CoV-2 coinfections with spatio-temporal epidemiological data confirming its plausibility with the cocirculating lineages at the timeframe investigated. Our data suggests that coinfection with distinct SARS-CoV-2 lineages is a rare phenomenon, although it is certainly a lower bound estimate considering the difficulty to detect coinfections with very similar SARS-CoV-2 lineages and the low number of samples sequenced from the total number of infections.

A Sanger-based approach for scaling up screening of SARS-CoV-2 variants of interest and concern.

The global spread of new SARS-CoV-2 variants of concern underscore an urgent need of simple deployed molecular tools that can differentiate these lineages. Several tools and protocols have been shared since the beginning of the COVID-19 pandemic, but they need to be timely adapted to cope with SARS-CoV-2 evolution. Although whole-genome sequencing (WGS) of the virus genetic material has been widely used, it still presents practical difficulties such as high cost, shortage of available reagents in the global market, need of a specialized laboratorial infrastructure and well-trained staff. These limitations result in SARS-CoV-2 surveillance blackouts across several countries. Here we propose a rapid and accessible protocol based on Sanger sequencing of a single PCR fragment that is able to identify and discriminate all SARS-CoV-2 variants of concern (VOCs) identified so far, according to each characteristic mutational profile at the Spike-RBD region (K417N/T, E484K, N501Y, A570D). Twelve COVID-19 samples from Brazilian patients were evaluated for both WGS and Sanger sequencing: three P.2, two P.1, six B.1.1 and one B.1.1.117 lineage. All results from the Sanger sequencing method perfectly matched the mutational profile of VOCs and non-VOCs RBD's characterized by WGS. In summary, this approach allows a much broader network of laboratories to perform molecular surveillance of SARS-CoV-2 VOCs and report results within a shorter time frame, which is of utmost importance in the context of rapid public health decisions in a fast evolving worldwide pandemic.

Evolutionary Dynamics and Dissemination Pattern of the SARS-CoV-2 Lineage B.1.1.33 During the Early Pandemic Phase in Brazil.

A previous study demonstrates that most of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) Brazilian strains fell in three local clades that were introduced from Europe around late February 2020. Here we investigated in more detail the origin of the major and most widely disseminated SARS-CoV-2 Brazilian lineage B.1.1.33. We recovered 190 whole viral genomes collected from 13 Brazilian states from February 29 to April 31, 2020 and combined them with other B.1.1 genomes collected globally. Our genomic survey confirms that lineage B.1.1.33 is responsible for a variable fraction of the community viral transmissions in Brazilian states, ranging from 2% of all SARS-CoV-2 genomes from Pernambuco to 80% of those from Rio de Janeiro. We detected a moderate prevalence (5-18%) of lineage B.1.1.33 in some South American countries and a very low prevalence (<1%) in North America, Europe, and Oceania. Our study reveals that lineage B.1.1.33 evolved from an ancestral clade, here designated B.1.1.33-like, that carries one of the two B.1.1.33 synapomorphic mutations. The B.1.1.33-like lineage may have been introduced from Europe or arose in Brazil in early February 2020 and a few weeks later gave origin to the lineage B.1.1.33. These SARS-CoV-2 lineages probably circulated during February 2020 and reached all Brazilian regions and multiple countries around the world by mid-March, before the implementation of air travel restrictions in Brazil. Our phylodynamic analysis also indicates that public health interventions were partially effective to control the expansion of lineage B.1.1.33 in Rio de Janeiro because its median effective reproductive number (R e ) was drastically reduced by about 66% during March 2020, but failed to bring it to below one. Continuous genomic surveillance of lineage B.1.1.33 might provide valuable information about epidemic dynamics and the effectiveness of public health interventions in some Brazilian states.

Multiple Introductions Followed by Ongoing Community Spread of SARS-CoV-2 at One of the Largest Metropolitan Areas of Northeast Brazil.

Multiple epicenters of the SARS-CoV-2 pandemic have emerged since the first pneumonia cases in Wuhan, China, such as Italy, USA, and Brazil. Brazil is the third-most affected country worldwide, but genomic sequences of SARS-CoV-2 strains are mostly restricted to states from the Southeast region. Pernambuco state, located in the Northeast region, is the sixth most affected Brazilian state, but very few genomic sequences from the strains circulating in this region are available. We sequenced 101 strains of SARS-CoV-2 from patients presenting Covid-19 symptoms that reside in Pernambuco. Phylogenetic reconstructions revealed that all genomes belong to the B lineage and most of the samples (88%) were classified as lineage B.1.1. We detected multiple viral introductions from abroad (likely from Europe) as well as six local B.1.1 clades composed by Pernambuco only strains. Local clades comprise sequences from the capital city (Recife) and other country-side cities, corroborating the community spread between different municipalities of the state. These findings demonstrate that different from Southeastern Brazilian states where the epidemics were majorly driven by one dominant lineage (B.1.1.28 or B.1.1.33), the early epidemic phase at the Pernambuco state was driven by multiple B.1.1 lineages seeded through both national and international traveling.