Single nucleotide variants in the CCL2, OAS1 and DPP9 genes and their association with the severity of COVID-19 in an Ecuadorian population.

COVID-19 has a broad clinical spectrum, ranging from asymptomatic-mild form to severe phenotype. The severity of COVID-19 is a complex trait influenced by various genetic and environmental factors. Ethnic differences have been observed in relation to COVID-19 severity during the pandemic. It is currently unknown whether genetic variations may contribute to the increased risk of severity observed in Latin-American individuals The aim of this study is to investigate the potential correlation between gene variants at CCL2, OAS1, and DPP9 genes and the severity of COVID-19 in a population from Quito, Ecuador. This observational case-control study was conducted at the Carrera de Biologia from the Universidad Central del Ecuador and the Hospital Quito Sur of the Instituto Ecuatoriano de Seguridad Social (Quito-SUR-IESS), Quito, Ecuador. Genotyping for gene variants at rs1024611 (A>G), rs10774671 (A>G), and rs10406145 (G>C) of CCL2, OAS1, and DPP9 genes was performed on 100 COVID-19 patients (43 with severe form and 57 asymptomatic-mild) using RFLP-PCR. The genotype distribution of all SNVs throughout the entire sample of 100 individuals showed Hardy Weinberg equilibrium (P=0.53, 0.35, and 0.4 for CCL2, OAS1, and DPP9, respectively). The HWE test did not find any statistically significant difference in genotype distribution between the study and control groups for any of the three SNVs. The multivariable logistic regression analysis showed that individuals with the GG of the CCL2 rs1024611 gene variant had an increased association with the severe COVID-19 phenotype in a recessive model (P = 0.0003, OR = 6.43, 95% CI 2.19-18.89) and for the OAS1 rs10774671 gene variant, the log-additive model showed a significant association with the severe phenotype of COVID-19 (P=0.0084, OR=3.85, 95% CI 1.33-11.12). Analysis of haplotype frequencies revealed that the coexistence of GAG at CCL2, OAS1, and DPP9 variants, respectively, in the same individual increased the presence of the severe COVID-19 phenotype (OR=2.273, 95% CI: 1.271-4.068, P=0.005305). The findings of the current study suggests that the ethnic background affects the allele and genotype frequencies of genes associated with the severity of COVID-19. The experience with COVID-19 has provided an opportunity to identify an ethnicity-based approach to recognize genetically high-risk individuals in different populations for emerging diseases.

An assessment of alterations to human sperm methylation patterns in coronavirus disease 2019 infected and healthy control males.

OBJECTIVE: To determine whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection affects male reproductive health, considering the many potential factors that contribute to declines in male fertility on a semiglobal scale. DESIGN: In total, 64 human semen samples-32 treatment and 32 control-were laboratory processed and bioinformatically analyzed to assess differences in DNA methylation patterns. Implementing multiple bioinformatic tools, the analyses conducted will elicit between-group differences with respect to epigenetic age, epigenetic instability, semiglobal, and regional methylation, in addition to methylation patterns as a function of time since infection. SETTING: University hospital. PATIENTS: The study cohort of 64 individuals was drawn from a larger population of 94 volunteer participants recruited at the Human Reproduction Center at the Clinical Hospital of the Ribeirao Preto Medical School-University of São Paulo between June 2021 and January 2022 as well as in accordance with the ethical guidelines established by the Declaration of Helsinki. INTERVENTION: Exposure to SARS-CoV-2. MAIN OUTCOME MEASURE(S): Effects on male reproductive health were reported as differences in DNA methylation measured using an array. Mean ß values at key regulatory loci for human spermatocytes were analyzed and compared between groups. Further analysis of ß values using epigenetic age, instability, semiglobal, and regional methylation tools provided an analysis with substantial breadth and depth. RESULTS: In all analyses, there were no differences between groups. Considering these results, it can be inferred that infection with SARS-CoV-2 does not alter the epigenome of human spermatocytes in significant and/or persistent ways. Tangentially, these data also suggest that human male reproductive health is minimally altered by the virus, or that it is altered in a way that is independent of epigenetic programming. CONCLUSION: Infection with SARS-CoV-2 has been reportedly associated with alterations in male fertility. This study asserts that such alterations do not have an epigenetic basis but are likely a result of concomitant symptomatology, i.e., fever and inflammation. Across the multiple bioinformatic analyses conducted, the results of this test did not detect any differences in DNA methylation patterns between coronavirus disease 2019 and noncoronavirus disease semen donor groups.

Uncovering associations between pre-existing conditions and COVID-19 Severity: A polygenic risk score approach across three large biobanks.

OBJECTIVE: To overcome the limitations associated with the collection and curation of COVID-19 outcome data in biobanks, this study proposes the use of polygenic risk scores (PRS) as reliable proxies of COVID-19 severity across three large biobanks: the Michigan Genomics Initiative (MGI), UK Biobank (UKB), and NIH All of Us. The goal is to identify associations between pre-existing conditions and COVID-19 severity. METHODS: Drawing on a sample of more than 500,000 individuals from the three biobanks, we conducted a phenome-wide association study (PheWAS) to identify associations between a PRS for COVID-19 severity, derived from a genome-wide association study on COVID-19 hospitalization, and clinical pre-existing, pre-pandemic phenotypes. We performed cohort-specific PRS PheWAS and a subsequent fixed-effects meta-analysis. RESULTS: The current study uncovered 23 pre-existing conditions significantly associated with the COVID-19 severity PRS in cohort-specific analyses, of which 21 were observed in the UKB cohort and two in the MGI cohort. The meta-analysis yielded 27 significant phenotypes predominantly related to obesity, metabolic disorders, and cardiovascular conditions. After adjusting for body mass index, several clinical phenotypes, such as hypercholesterolemia and gastrointestinal disorders, remained associated with an increased risk of hospitalization following COVID-19 infection. CONCLUSION: By employing PRS as a proxy for COVID-19 severity, we corroborated known risk factors and identified novel associations between pre-existing clinical phenotypes and COVID-19 severity. Our study highlights the potential value of using PRS when actual outcome data may be limited or inadequate for robust analyses.

Assessment of positive selection across SARS-CoV-2 variants via maximum likelihood.

Study of the genome of the SARS-CoV-2 virus, particularly with regard to understanding evolution of the virus, is crucial for managing the COVID-19 pandemic. To this end, we sample viral genomes from the GISAID repository and use several of the maximum likelihood approaches implemented in PAML, a collection of open source programs for phylogenetic analyses of DNA and protein sequences, to assess evidence for positive selection in the protein-coding regions of the SARS-CoV-2 genome. Across all major variants identified by June 2021, we find limited evidence for positive selection. In particular, we identify positive selection in a small proportion of sites (5-15%) in the protein-coding region of the spike protein across variants. Most other variants did not show a strong signal for positive selection overall, though there were indications of positive selection in the Delta and Kappa variants for the nucleocapsid protein. We additionally use a forward selection procedure to fit a model that allows branch-specific estimates of selection along a phylogeny relating the variants, and find that there is variation in the selective pressure across variants for the spike protein. Our results highlight the utility of computational approaches for identifying genomic regions under selection.

Reconstruction of Viral Variants via Monte Carlo Clustering.

Identifying viral variants through clustering is essential for understanding the composition and structure of viral populations within and between hosts, which play a crucial role in disease progression and epidemic spread. This article proposes and validates novel Monte Carlo (MC) methods for clustering aligned viral sequences by minimizing either entropy or Hamming distance from consensuses. We validate these methods on four benchmarks: two SARS-CoV-2 interhost data sets and two HIV intrahost data sets. A parallelized version of our tool is scalable to very large data sets. We show that both entropy and Hamming distance-based MC clusterings discern the meaningful information from sequencing data. The proposed clustering methods consistently converge to similar clusterings across different runs. Finally, we show that MC clustering improves reconstruction of intrahost viral population from sequencing data.

A weapon to fight against pervasive Omicron: systematic actions transiting to pre-COVID normal.

The Coronavirus Disease-2019 (COVID-19) pandemic is not just a health crisis but also a social crisis. Confronted with the resurgence of variants with massive infections, the triggered activities from personal needs may promote the spread, which should be considered in risk management. Meanwhile, it is important to ensure that the policy responses on citizen life to a lower level. In the face of Omicron mutations, we need to sum up the control experience accumulated, adapting strategies in the dynamic coevolution process while balancing life resumption and pandemic control, to meet challenges of future crises. We collected 46 cases occurring between 2021 and 2022, mainly from China, but also including five relevant cases from other countries around the world. Based on case studies, we combine micro-view individual needs/behaviors with macro-view management measures linking Maslow's hierarchy of needs with the transmission chain of Omicron clusters. The proposed loophole chain could help identify both individual and management loopholes in the spread of the virus. The systematic actions that were taken have effectively combated these ubiquitous vulnerabilities at lower costs and lesser time. In the dynamic coevolution process, the Chinese government has made effective and more socially acceptable prevention policies while meeting the divergent needs of the entire society at the minimum costs. Systematic actions do help maintain the balance between individuals' satisfaction and pandemic containment. This implies that risk management policies should reasonably consider individual needs and improve the cooperation of various stakeholders with targeted flexible measures, securing both public health and life resumption.

Assessment of thermal and temporal stability of SARS-CoV-2 samples using real-time qRT-PCR.

BACKGROUND: As per the guidelines of the Indian Council of Medical Research, nasopharyngeal and oropharyngeal swabs in viral transport medium (VTM) are to be stored at 4 °C for less than 5 days and for more than 5 days at -70 °C. Samples are not transported or stored as per prescribed conditions because of the limitations, resulting in an apprehensive diagnosis. The aim of the study was to test the stability of the SARS-CoV-2 sample stored in VTM at different temperatures. METHODS: In this study, the stability of 21 positive and 9 negative samples for SARS-CoV-2 was evaluated in commercial VTM at different temperatures (-80 °C, -20 °C, 4 °C, and 25 to 30 °C). Stability was checked for up to 50 days in the above storage conditions at different intervals. PathoDetect™ and Hi-PCR® kits were used for the detection of the four genes of SARS-CoV-2. The Cycle Threshold (Ct) value for determining the positivity of samples for PathoDetect™ was < 40 and for Hi-PCR® was < 38. RESULTS: The SARS-CoV-2 confirmatory genes (RdRp and E genes) and the internal housekeeping gene remained detectable even on the 50th day of the study. The Ct of the RdRp and E genes were found to increase with storage duration, but all positive samples remained positive till the end of the study, or the Ct value remained below the cut-off level. The negative samples gave consistent results until the end of the study. When the differences in Ct values were compared between the days in a set of experiments, they were not significantly different except in a few samples. CONCLUSION: The SARS-CoV-2 genetic materials in commercial VTM were stable at room temperature to -80 °C for 50 days.

Identification of Key Genes Related to Immune Cells in Patients with COVID-19 Via Integrated Bioinformatics-Based Analysis.

COVID-19 has spread all over the world which poses a serious threat to social economic development and public health. Despite enormous progress has been made in the prevention and treatment of COVID-19, the specific mechanism and biomarker related to disease severity or prognosis have not been clarified yet. Our study intended to further explore the diagnostic markers of COVID-19 and their relationship with serum immunology by bioinformatics analysis. The datasets about COVID-19 were downloaded from the Gene Expression Omnibus (GEO) dataset. The differentially expressed genes (DEGs) were selected via the limma package. Then, weighted gene co-expression network analysis (WGCNA) was conducted to identify the critical module associated with the clinic status. The intersection DEGs were processed for further enrichment analysis. The final diagnostic genes for COVID-19 were selected and verified through special bioinformatics algorithms. There were significant DEGs between the normal and COVID-19 patients. These genes were mainly enriched in cell cycle, complement and coagulation cascade, extracellular matrix (ECM) receptor interaction, and the P53 signaling pathway. As much as 357 common intersected DEGs were selected in the end. These DEGs were enriched in organelle fission, mitotic cell cycle phase transition, DNA helicase activity, cell cycle, cellular senescence, and P53 signaling pathway. Our study also identified CDC25A, PDCD6, and YWAHE were potential diagnostic markers of COVID-19 with the AUC (area under curve), 0.958 (95% CI 0.920-0.988), 0.941(95% CI 0.892-0.980), and 0.929 (95% CI 0.880-0.971). Moreover, CDC25A, PDCD6, and YWAHE were correlated with plasma cells, macrophages M0, T cells CD4 memory resting, T cells CD8, dendritic cells, and NK cells. Our study discovered that CDC25A, PDCD6, and YWAHE can be used as diagnostic markers for COVID-19. Moreover, these biomarkers were also closely associated with immune cell infiltration, which plays a pivotal role in the diagnosis and progression of COVID-19.

TEMPO: A transformer-based mutation prediction framework for SARS-CoV-2 evolution.

The widespread of SARS-CoV-2 presents a significant threat to human society, as well as public health and economic development. Extensive efforts have been undertaken to battle against the pandemic, whereas effective approaches such as vaccination would be weakened by the continuous mutations, leading to considerable attention being attracted to the mutation prediction. However, most previous studies lack attention to phylogenetics. In this paper, we propose a novel and effective model TEMPO for predicting the mutation of SARS-CoV-2 evolution. Specifically, we design a phylogenetic tree-based sampling method to generate sequence evolution data. Then, a transformer-based model is presented for the site mutation prediction after learning the high-level representation of these sequence data. We conduct experiments to verify the effectiveness of TEMPO, leveraging a large-scale SARS-CoV- 2 dataset. Experimental results show that TEMPO is effective for mutation prediction of SARS- CoV-2 evolution and outperforms several state-of-the-art baseline methods. We further perform mutation prediction experiments of other infectious viruses, to explore the feasibility and robustness of TEMPO, and experimental results verify its superiority. The codes and datasets are freely available at https://github.com/ZJUDataIntelligence/TEMPO.

A bias of Asparagine to Lysine mutations in SARS-CoV-2 outside the receptor binding domain affects protein flexibility.

Introduction: COVID-19 pandemic has been threatening public health and economic development worldwide for over two years. Compared with the original SARS-CoV-2 strain reported in 2019, the Omicron variant (B.1.1.529.1) is more transmissible. This variant has 34 mutations in its Spike protein, 15 of which are present in the Receptor Binding Domain (RBD), facilitating viral internalization via binding to the angiotensin-converting enzyme 2 (ACE2) receptor on endothelial cells as well as promoting increased immune evasion capacity. Methods: Herein we compared SARS-CoV-2 proteins (including ORF3a, ORF7, ORF8, Nucleoprotein (N), membrane protein (M) and Spike (S) proteins) from multiple ancestral strains. We included the currently designated original Variant of Concern (VOC) Omicron, its subsequent emerged variants BA.1, BA2, BA3, BA.4, BA.5, the two currently emerging variants BQ.1 and BBX.1, and compared these with the previously circulating VOCs Alpha, Beta, Gamma, and Delta, to better understand the nature and potential impact of Omicron specific mutations. Results: Only in Omicron and its subvariants, a bias toward an Asparagine to Lysine (N to K) mutation was evident within the Spike protein, including regions outside the RBD domain, while none of the regions outside the Spike protein domain were characterized by this mutational bias. Computational structural analysis revealed that three of these specific mutations located in the central core region, contribute to a preference for the alteration of conformations of the Spike protein. Several mutations in the RBD which have circulated across most Omicron subvariants were also analysed, and these showed more potential for immune escape. Conclusion: This study emphasizes the importance of understanding how specific N to K mutations outside of the RBD region affect SARS-CoV-2 conformational changes and the need for neutralizing antibodies for Omicron to target a subset of conformationally dependent B cell epitopes.

RASCL: Rapid Assessment of Selection in CLades through molecular sequence analysis.

An important unmet need revealed by the COVID-19 pandemic is the near-real-time identification of potentially fitness-altering mutations within rapidly growing SARS-CoV-2 lineages. Although powerful molecular sequence analysis methods are available to detect and characterize patterns of natural selection within modestly sized gene-sequence datasets, the computational complexity of these methods and their sensitivity to sequencing errors render them effectively inapplicable in large-scale genomic surveillance contexts. Motivated by the need to analyze new lineage evolution in near-real time using large numbers of genomes, we developed the Rapid Assessment of Selection within CLades (RASCL) pipeline. RASCL applies state of the art phylogenetic comparative methods to evaluate selective processes acting at individual codon sites and across whole genes. RASCL is scalable and produces automatically updated regular lineage-specific selection analysis reports: even for lineages that include tens or hundreds of thousands of sampled genome sequences. Key to this performance is (i) generation of automatically subsampled high quality datasets of gene/ORF sequences drawn from a selected "query" viral lineage; (ii) contextualization of these query sequences in codon alignments that include high-quality "background" sequences representative of global SARS-CoV-2 diversity; and (iii) the extensive parallelization of a suite of computationally intensive selection analysis tests. Within hours of being deployed to analyze a novel rapidly growing lineage of interest, RASCL will begin yielding JavaScript Object Notation (JSON)-formatted reports that can be either imported into third-party analysis software or explored in standard web-browsers using the premade RASCL interactive data visualization dashboard. By enabling the rapid detection of genome sites evolving under different selective regimes, RASCL is well-suited for near-real-time monitoring of the population-level selective processes that will likely underlie the emergence of future variants of concern in measurably evolving pathogens with extensive genomic surveillance.

Assessment of mutations on RBD in the Spike protein of SARS-CoV-2 Alpha, Delta and Omicron variants.

The severe acute respiratory syndrome (SARS) coronavirus 2 (CoV-2) variant Omicron spread more rapid than the other variants of SARS-CoV-2 virus. Mutations on the Spike (S) protein receptor-binding domain (RBD) are critical for the antibody resistance and infectivity of the SARS-CoV-2 variants. In this study, we have used accelerated molecular dynamics (aMD) simulations and free energy calculations to present a systematic analysis of the affinity and conformational dynamics along with the interactions that drive the binding between Spike protein RBD and human angiotensin-converting enzyme 2 (ACE2) receptor. We evaluate the impacts of the key mutation that occur in the RBDs Omicron and other variants in the binding with the human ACE2 receptor. The results show that S protein Omicron has stronger binding to the ACE2 than other variants. The evaluation of the decomposition energy per residue shows the mutations N440K, T478K, Q493R and Q498R observed in Spike protein of SARS-CoV-2 provided a stabilization effect for the interaction between the SARS-CoV-2 RBD and ACE2. Overall, the results demonstrate that faster spreading of SARS-CoV-2 Omicron may be correlated with binding affinity of S protein RBD to ACE2 and mutations of uncharged residues to positively charged residues such as Lys and Arg in key positions in the RBD.

External quality assessment of COVID-19 real time reverse transcription PCR laboratories in India.

Sudden emergence and rapid spread of COVID-19 created an inevitable need for expansion of the COVID-19 laboratory testing network across the world. The strategy to test-track-treat was advocated for quick detection and containment of the disease. Being the second most populous country in the world, India was challenged to make COVID-19 testing available and accessible in all parts of the country. The molecular laboratory testing network was augmented expeditiously, and number of laboratories was increased from one in January 2020 to 2951 till mid-September, 2021. This rapid expansion warranted the need to have inbuilt systems of quality control/ quality assurance. In addition to the ongoing inter-laboratory quality control (ILQC), India implemented an External Quality Assurance Program (EQAP) with assistance from World Health Organization (WHO) and Royal College of Pathologists, Australasia. Out of the 953 open system rRTPCR laboratories in both public and private sector who participated in the first round of EQAP, 891(93.4%) laboratories obtained a passing score of > = 80%. The satisfactory performance of Indian COVID-19 testing laboratories has boosted the confidence of the public and policy makers in the quality of testing. ILQC and EQAP need to continue to ensure adherence of the testing laboratories to the desired quality standards.

Assessment of Interleukin-13(rs20541) Genomic Polymorphism in Patients with Acute Respiratory Distress Syndrome in Relation to COVID19 Infection.

Elevated Interleukin-13 (IL-13) may play an important role in the pathophysiology of COVID-19, yet, the attenuated response did not notice across all severe cases. Susceptibility to asthma in specific populations is associated with several SNPs of multifunctional cytokines, such as IL-13, IL-31 and IL-33. This prospective case-control study is designed to investigate the extent of genetic susceptibility in subsets of Iraqi patients with COVID-19 by targeting the variants of interleukin IL-13rs20541 polymorphism in relation to disease susceptibility and severity of clinical presentation. One hundred samples were obtained from the throat, nasopharyngeal and nasal swabs enrolled in this study. Eighty samples of the throat, nasopharyngeal and nasal localization swabs were obtained from patients with acute respiratory distress syndrome (ARDS) (both COVID-19 and non-COVID19 patients), while other 20 nasopharyngeal swabs were included as a healthy control group (AHC). Detection of IL-13rs20541 polymorphism was done by ARMS technique. The frequencies of GG- genotype in ARDS- patients with COVID-19, non-COVID19-, and AHC groups were respectively 14%, 12% and 3%, where, and as compared to the control group, showed a significant increase in COVID-19 patients. The AA- genotype in patients with COVID-19 group, non- COVID-19 group and healthy control group documented the frequency of 9%, 7%, and 14%, respectively, where the frequency decreased in the patient's groups as compared to the AHC group. Finally, and among the studied groups, an increase of AG- genotype (as rate OR=1.89) was documented compared to genotype GG and A-. Genetic polymorphisms in the IL-13rs20541 gene might influence its functions in patients with SARS-associated respiratory tract infection and thus might involve the pathogenicity of patients with COVID-19.

High sensitivity-low cost detection of SARS-CoV-2 by two steps end point RT-PCR with agarose gel electrophoresis visualization.

More than one year since Coronavirus disease 2019 (COVID-19) pandemic outbreak, the gold standard technique for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection is still the RT-qPCR. This is a limitation to increase testing capacities, particularly at developing countries, as expensive reagents and equipment are required. We developed a two steps end point RT-PCR reaction with SARS-CoV-2 Nucleocapsid (N) gene and Ribonuclease P (RNase P) specific primers where viral amplicons were verified by agarose gel electrophoresis. We carried out a clinical performance and analytical sensitivity evaluation for this two-steps end point RT-PCR method with 242 nasopharyngeal samples using the CDC RT-qPCR protocol as a gold standard technique. With a specificity of 95.8%, a sensitivity of 95.1%, and a limit of detection of 20 viral RNA copies/uL, this two steps end point RT-PCR assay is an affordable and reliable method for SARS-CoV-2 detection. This protocol would allow to extend COVID-19 diagnosis to basic molecular biology laboratories with a potential positive impact in surveillance programs at developing countries.

UnCovid: A versatile, low-cost, and open-source protocol for SARS-CoV-2 RNA detection.

Here, we describe a detailed step-by-step protocol to detect SARS-CoV-2 RNA using RT-PCR-mediated amplification and CRISPR/Cas-based visualization. The optimized assay uses basic molecular biology equipment such as conventional thermocyclers and transilluminators for qualitative detection. Alternatively, a fluorescence plate reader can be used for quantitative measurements. The protocol detects two regions of the SARS-CoV-2 genome in addition to the human RNaseP sample control. Aiming to reach remote regions, this work was developed to use the portable molecular workstation from BentoLab. For complete details on the use and execution of this protocol, please refer to Alcántara et al., 2021.

Immunological assessment of SARS-CoV-2 infection in pregnancy from diagnosis to delivery: A multicentre prospective study.

BACKGROUND: Background Population-based data on SARS-CoV-2 infection in pregnancy and assessment of passive immunity to the neonate, is lacking. We profiled the maternal and fetal response using a combination of viral RNA from naso-pharyngeal swabs and serological assessment of antibodies against SARS-CoV-2. METHODS: This multicentre prospective observational study was conducted between March 24th and August 31st 2020. Two independent cohorts were established, a symptomatic SARS-CoV-2 cohort and a cohort of asymptomatic pregnant women attending two of the largest maternity hospitals in Europe. Symptomatic women were invited to provide a serum sample to assess antibody responses. Asymptomatic pregnant women provided a nasopharyngeal swab and serum sample. RT-PCR for viral RNA was performed using the Cobas SARS-CoV-2 6800 platform (Roche). Umbilical cord bloods were obtained at delivery. Maternal and fetal serological response was measured using both the Elecsys® Anti-SARS-CoV-2 immunoassay (Roche), Abbott SARS-CoV-2 IgG Assay and the IgM Architect assay. Informed written consent was obtained from all participants. RESULTS: Ten of twenty three symptomatic women had SARS-CoV-2 RNA detected on nasopharyngeal swabs. Five (5/23, 21.7%) demonstrated serological evidence of anti-SARS-CoV-2 IgG antibodies and seven (30.4%, 7/23) were positive for IgM antibodies. In the asymptomatic cohort, the prevalence of SARS-CoV-2 infection in RNA was 0.16% (1/608). IgG SARS-CoV-2 antibodies were detected in 1·67% (10/598, 95% CI 0·8%-3·1%) and IgM in 3·51% (21/598, 95% CI 2·3-5·5%). Nine women had repeat testing post the baseline test. Four (4/9, 44%) remained IgM positive and one remained IgG positive. 3 IgG anti-SARS-CoV-2 antibodies were detectable in cord bloods from babies born to five seropositive women who delivered during the study. The mean gestation at serological test was 34 weeks. The mean time between maternal serologic positivity and detection in umbilical cord samples was 28 days. CONCLUSION: Using two independent serological assays, we present a comprehensive illustration of the antibody response to SARS-CoV-2 in pregnancy, and show a low prevalence of asymptomatic SARS-CoV2. Transplacental migration of anti-SARS-CoV-2 antibodies was identified in cord blood of women who demonstrated antenatal anti-SARS-CoV-2 antibodies, raising the possibility of passive immunity.

Excess mortality from COVID and non-COVID causes in minority populations.

The 2020 US mortality totaled 2.8 million after early March, which is 17.3% higher than age-population-weighted mortality over the same time interval in 2017 to 2019, for a total excess death count of 413,592. We use data on weekly death counts by cause, as well as life tables, to quantify excess mortality and life years lost from both COVID-19 and non-COVID-19 causes by race/ethnicity, age, and gender/sex. Excess mortality from non-COVID-19 causes is substantial and much more heavily concentrated among males and minorities, especially Black, non-Hispanic males, than COVID-19 deaths. Thirty-four percent of the excess life years lost for males is from non-COVID-19 causes. While minorities represent 36% of COVID-19 deaths, they represent 70% of non-COVID-19 related excess deaths and 58% of non-COVID-19 excess life years lost. Black, non-Hispanic males represent only 6.9% of the population, but they are responsible for 8.9% of COVID-19 deaths and 28% of 2020 excess deaths from non-COVID-19 causes. For this group, nearly half of the excess life years lost in 2020 are due to non-COVID-19 causes.

Anti-SARS-CoV-2 Strategies and the Potential Role of miRNA in the Assessment of COVID-19 Morbidity, Recurrence, and Therapy.

Recently, we have experienced a serious pandemic. Despite significant technological advances in molecular technologies, it is very challenging to slow down the infection spread. It appeared that due to globalization, SARS-CoV-2 spread easily and adapted to new environments or geographical or weather zones. Additionally, new variants are emerging that show different infection potential and clinical outcomes. On the other hand, we have some experience with other pandemics and some solutions in virus elimination that could be adapted. This is of high importance since, as the latest reports demonstrate, vaccine technology might not follow the new, mutated virus outbreaks. Thus, identification of novel strategies and markers or diagnostic methods is highly necessary. For this reason, we present some of the latest views on SARS-CoV-2/COVID-19 therapeutic strategies and raise a solution based on miRNA. We believe that in the face of the rapidly increasing global situation and based on analogical studies of other viruses, the possibility of using the biological potential of miRNA technology is very promising. It could be used as a promising diagnostic and prognostic factor, as well as a therapeutic target and tool.