Archaeogenomic distinctiveness of the Isthmo-Colombian area.

The recently enriched genomic history of Indigenous groups in the Americas is still meager concerning continental Central America. Here, we report ten pre-Hispanic (plus two early colonial) genomes and 84 genome-wide profiles from seven groups presently living in Panama. Our analyses reveal that pre-Hispanic demographic events contributed to the extensive genetic structure currently seen in the area, which is also characterized by a distinctive Isthmo-Colombian Indigenous component. This component drives these populations on a specific variability axis and derives from the local admixture of different ancestries of northern North American origin(s). Two of these ancestries were differentially associated to Pleistocene Indigenous groups that also moved into South America, leaving heterogenous genetic footprints. An additional Pleistocene ancestry was brought by a still unsampled population of the Isthmus (UPopI) that remained restricted to the Isthmian area, expanded locally during the early Holocene, and left genomic traces up to the present day.

GUANIN: An all-in-one GUi-driven Analyzer for NanoString Interactive Normalization.

SUMMARY: Most tools for normalizing NanoString gene expression data, apart from the default NanoString nCounter software, are R packages that focus on technical normalization and lack configurable parameters. However, content normalization is the most sensitive, experiment-specific, and relevant step to preprocess NanoString data. Currently this step requires the use of multiple tools and a deep understanding of data management by the researcher. We present GUANIN, a comprehensive normalization tool that integrates both new and well-established methods, offering a wide variety of options to introduce, filter, choose, and evaluate reference genes for content normalization. GUANIN allows the introduction of genes from and endogenous subset as reference genes, addressing housekeeping-related selection problems. It performs a specific and straightforward normalization approach for each experiment, using a wide variety of parameters with suggested default values. GUANIN provides a large number of informative output files that enable the iterative refinement of the normalization process. In terms of normalization, GUANIN matches or outperforms other available methods. Importantly, it allows researchers to interact comprehensively with the preprocessing process without programming knowledge, thanks to its easy-to-use Graphical User Interface (GUI). AVAILABILITY AND IMPLEMENTATION: GUANIN can be installed with pip install guanin and it is available at https://pypi.org/project/guanin/. Source code, documentation and case studies are available at https://github.com/julimontoto/guanin under the GPLv3 license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative.

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Superspreading in the emergence of COVID-19 variants.

Superspreading and variants of concern (VOC) of the human pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are the main catalyzers of the coronavirus disease 2019 (COVID-19) pandemic. However, measuring their individual impact is challenging. By examining the largest database of SARS-CoV-2 genomes The Global Initiative on Sharing Avian Influenza Data [GISAID; n >1.2 million high-quality (HQ) sequences], we present evidence suggesting that superspreading has had a key role in the epidemiological predominance of VOC. There are clear signatures in the database compatible with large superspreading events (SSEs) coinciding chronologically with the worst epidemiological scenarios triggered by VOC. The data suggest that, without the randomness effect of the genetic drift facilitated by superspreading, new VOC of SARS-CoV-2 would have had more limited chance of success.

Mapping genome variation of SARS-CoV-2 worldwide highlights the impact of COVID-19 super-spreaders.

The human pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the major pandemic of the twenty-first century. We analyzed more than 4700 SARS-CoV-2 genomes and associated metadata retrieved from public repositories. SARS-CoV-2 sequences have a high sequence identity (>99.9%), which drops to >96% when compared to bat coronavirus genome. We built a mutation-annotated reference SARS-CoV-2 phylogeny with two main macro-haplogroups, A and B, both of Asian origin, and more than 160 sub-branches representing virus strains of variable geographical origins worldwide, revealing a rather uniform mutation occurrence along branches that could have implications for diagnostics and the design of future vaccines. Identification of the root of SARS-CoV-2 genomes is not without problems, owing to conflicting interpretations derived from either using the bat coronavirus genomes as an outgroup or relying on the sampling chronology of the SARS-CoV-2 genomes and TMRCA estimates; however, the overall scenario favors haplogroup A as the ancestral node. Phylogenetic analysis indicates a TMRCA for SARS-CoV-2 genomes dating to November 12, 2019, thus matching epidemiological records. Sub-haplogroup A2 most likely originated in Europe from an Asian ancestor and gave rise to subclade A2a, which represents the major non-Asian outbreak, especially in Africa and Europe. Multiple founder effect episodes, most likely associated with super-spreader hosts, might explain COVID-19 pandemic to a large extent.

COVID-19 vaccine effectiveness in children by age groups. A population-based study in Galicia, Spain.

BACKGROUND: Studies on vaccine effectiveness (VE) against COVID-19 in the pediatric population are outgoing. We aimed to quantify VE against SARS-CoV-2 in two pediatric age groups, 5-11 and 12-17-year-old, while considering vaccine type, SARS-CoV-2 variant, and duration of protection. METHODS: A population-based test-negative control study was undertaken in Galicia, Spain. Children 5-11-year-old received the Comirnaty® (Pfizer, US) vaccine, while those aged 12-17-year-old received the Comirnaty® (Pfizer, US) or SpikeVax® (ModernaTX, Inc) vaccine. Participants were categorized into unvaccinated (0 doses or one dose with <14 days since vaccination), partially vaccinated (only one dose with ≥14 days, or two doses with <14 days after the second dose administration), and fully vaccinated (two doses with ≥14 days after the second injection). Adjusted odds ratios (OR) and their 95% confidence intervals (CI) were estimated using multiple logistic regression models. VE was calculated as (1-OR) * 100. Stratified and sensitivity analyses were performed. RESULTS: In the fully vaccinated 5-11-year-old children, VE against the Omicron variant was 44.1% (95% CI: 38.2%-49.4%). In the fully vaccinated 12-17-year-old individuals, VE was 83.4% (95% CI: 81.2%-85.3%) against Delta and 74.8% (95% CI: 58.5%-84.9%) against Omicron. Comirnaty® and SpikeVax® vaccines showed a similar magnitude of VE against Delta [Comirnaty® VE: 81.9% (95% CI: 79.3%-84.1%) and SpikeVax® VE: 85.3% (95% CI: 81.9%-88.1%)]. Comirnaty® (Pfizer, US; VE: 79.7%; 95% CI: 50.7%-92.4%) showed a slightly higher magnitude of protection against Omicron than SpikeVax® (ModernaTX, Inc), yet with an overlapping CI (VE: 74.3%; 95% CI: 56.6%-84.9%). VE was maintained in all age subgroups in both pediatric populations, but it declined over time. CONCLUSIONS: In Galicia, mRNA VE was moderate against SARS-CoV-2 infections in the 5-11-year-old populations, but high in older children. VE declined over time, suggesting a potential need for booster dose schedules.

CovidPhy: A tool for phylogeographic analysis of SARS-CoV-2 variation.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the coronavirus disease 2019 (COVID-19) pandemic. SARS-CoV-2 genomes have been sequenced massively and worldwide and are now available in different public genome repositories. There is much interest in generating bioinformatic tools capable to analyze and interpret SARS-CoV-2 variation. We have designed CovidPhy (http://covidphy.eu), a web interface that can process SARS-CoV-2 genome sequences in plain fasta text format or provided through identity codes from the Global Initiative on Sharing Avian Influenza Data (GISAID) or GenBank. CovidPhy aggregates information available on the large GISAID database (>1.49 M genomes). Sequences are first aligned against the reference sequence and the interface provides different sources of information, including automatic classification of genomes into a pre-computed phylogeny and phylogeographic information, haplogroup/lineage frequencies, and sequencing variation, indicating also if the genome contains known variants of concern (VOC). Additionally, CovidPhy allows searching for variants and haplotypes introduced by the user and includes a list of genomes that are good candidates for being responsible for large outbreaks worldwide, most likely mediated by important superspreading events, indicating their possible geographic epicenters and their relative impact as recorded in the GISAID database.

A multi-tissue study of immune gene expression profiling highlights the key role of the nasal epithelium in COVID-19 severity.

Coronavirus Disease-19 (COVID-19) symptoms range from mild to severe illness; the cause for this differential response to infection remains unknown. Unravelling the immune mechanisms acting at different levels of the colonization process might be key to understand these differences. We carried out a multi-tissue (nasal, buccal and blood; n = 156) gene expression analysis of immune-related genes from patients affected by different COVID-19 severities, and healthy controls through the nCounter technology. Mild and asymptomatic cases showed a powerful innate antiviral response in nasal epithelium, characterized by activation of interferon (IFN) pathway and downstream cascades, successfully controlling the infection at local level. In contrast, weak macrophage/monocyte driven innate antiviral response and lack of IFN signalling activity were present in severe cases. Consequently, oral mucosa from severe patients showed signals of viral activity, cell arresting and viral dissemination to the lower respiratory tract, which ultimately could explain the exacerbated innate immune response and impaired adaptative immune responses observed at systemic level. Results from saliva transcriptome suggest that the buccal cavity might play a key role in SARS-CoV-2 infection and dissemination in patients with worse prognosis. Co-expression network analysis adds further support to these findings, by detecting modules specifically correlated with severity involved in the abovementioned biological routes; this analysis also provides new candidate genes that might be tested as biomarkers in future studies. We also found tissue specific severity-related signatures mainly represented by genes involved in the innate immune system and cytokine/chemokine signalling. Local immune response could be key to determine the course of the systemic response and thus COVID-19 severity. Our findings provide a framework to investigate severity host gene biomarkers and pathways that might be relevant to diagnosis, prognosis, and therapy.

Effectiveness of COVID-19 vaccine booster in the general population and in subjects with comorbidities. A population-based study in Spain.

BACKGROUND: Research on the effectiveness of COVID-19 booster-based vaccine schedule is ongoing and real-world data on vaccine effectiveness (VE) in comorbid patients are limited. We aimed to estimate booster dose VE against SARS-CoV-2 infection and COVID-19 severity in the general population and in comorbid patients. METHOD: A retrospective test-negative control study was undertaken in Galicia-Spain (December 2020-November 2021). VE and 95% confidence interval (CI) were estimated using multivariate logistic regression models. RESULTS: 1,512,415 (94.13%) negative and 94,334 (5.87%) positive SARS-CoV-2 test results were included. A booster dose of COVID-19 vaccine is associated with substantially higher protection against SARS-CoV-2 infection than vaccination without a booster [VEboosted = 87% (95%CI: 83%; 89%); VEnon-boosted = 66% (95%CI: 65%; 67%)]. The high VE was observed in all ages, but was more pronounced in subjects older than 65 years. VE against COVID-19 severity was analyzed in a mixed population of boosted and non-boosted individuals and considerable protection was obtained [VE: hospitalization = 72% (95%CI: 68%; 75%); intensive care unit administration = 83% (95%CI: 78%; 88%), in-hospital mortality = 66% (95%CI: 53%; 75%)]. Boosted comorbid patients are more protected against SARS-CoV-2 infection than those who were non-boosted. This was observed in a wide range of major diseases including cancer (81% versus 54%), chronic obstructive pulmonary disease (84% versus 61%), diabetes (84% versus 65%), hypertension (82% versus 65%) and obesity (91% versus 67%), among others. CONCLUSIONS: A booster dose of COVID-19 vaccine increases the protection against SARS-CoV-2 infection and COVID-19 severity in the general population and in comorbid patients.

A Timeframe for SARS-CoV-2 Genomes: A Proof of Concept for Postmortem Interval Estimations.

Establishing the timeframe when a particular virus was circulating in a population could be useful in several areas of biomedical research, including microbiology and legal medicine. Using simulations, we demonstrate that the circulation timeframe of an unknown SARS-CoV-2 genome in a population (hereafter, estimated time of a queried genome [QG]; tE-QG) can be easily predicted using a phylogenetic model based on a robust reference genome database of the virus, and information on their sampling dates. We evaluate several phylogeny-based approaches, including modeling evolutionary (substitution) rates of the SARS-CoV-2 genome (~10-3 substitutions/nucleotide/year) and the mutational (substitutions) differences separating the QGs from the reference genomes (RGs) in the database. Owing to the mutational characteristics of the virus, the present Viral Molecular Clock Dating (VMCD) method covers timeframes going backwards from about a month in the past. The method has very low errors associated to the tE-QG estimates and narrow intervals of tE-QG, both ranging from a few days to a few weeks regardless of the mathematical model used. The SARS-CoV-2 model represents a proof of concept that can be extrapolated to any other microorganism, provided that a robust genome sequence database is available. Besides obvious applications in epidemiology and microbiology investigations, there are several contexts in forensic casework where estimating tE-QG could be useful, including estimation of the postmortem intervals (PMI) and the dating of samples stored in hospital settings.

Phylogeography of Sub-Saharan Mitochondrial Lineages Outside Africa Highlights the Roles of the Holocene Climate Changes and the Atlantic Slave Trade.

Despite the importance of ancient DNA for understanding human prehistoric dispersals, poor survival means that data remain sparse for many areas in the tropics, including in Africa. In such instances, analysis of contemporary genomes remains invaluable. One promising approach is founder analysis, which identifies and dates migration events in non-recombining systems. However, it has yet to be fully exploited as its application remains controversial. Here, we test the approach by evaluating the age of sub-Saharan mitogenome lineages sampled outside Africa. The analysis confirms that such lineages in the Americas date to recent centuries-the time of the Atlantic slave trade-thereby validating the approach. By contrast, in North Africa, Southwestern Asia and Europe, roughly half of the dispersal signal dates to the early Holocene, during the "greening" of the Sahara. We elaborate these results by showing that the main source regions for the two main dispersal episodes are distinct. For the recent dispersal, the major source was West Africa, but with two exceptions: South America, where the fraction from Southern Africa was greater, and Southwest Asia, where Eastern Africa was the primary source. These observations show the potential of founder analysis as both a supplement and complement to ancient DNA studies.

The peopling of South America and the trans-Andean gene flow of the first settlers.

Genetic and archaeological data indicate that the initial Paleoindian settlers of South America followed two entry routes separated by the Andes and the Amazon rainforest. The interactions between these paths and their impact on the peopling of South America remain unclear. Analysis of genetic variation in the Peruvian Andes and regions located south of the Amazon River might provide clues on this issue. We analyzed mitochondrial DNA variation at different Andean locations and >360,000 autosomal SNPs from 28 Native American ethnic groups to evaluate different trans-Andean demographic scenarios. Our data reveal that the Peruvian Altiplano was an important enclave for early Paleoindian expansions and point to a genetic continuity in the Andes until recent times, which was only marginally affected by gene flow from the Amazonian lowlands. Genomic variation shows a good fit with the archaeological evidence, indicating that the genetic interactions between the descendants of the settlers that followed the Pacific and Atlantic routes were extremely limited.

Origins and genetic legacies of the Caribbean Taino.

The Caribbean was one of the last parts of the Americas to be settled by humans, but how and when the islands were first occupied remains a matter of debate. Ancient DNA can help answering these questions, but the work has been hampered by poor DNA preservation. We report the genome sequence of a 1,000-year-old Lucayan Taino individual recovered from the site of Preacher's Cave in the Bahamas. We sequenced her genome to 12.4-fold coverage and show that she is genetically most closely related to present-day Arawakan speakers from northern South America, suggesting that the ancestors of the Lucayans originated there. Further, we find no evidence for recent inbreeding or isolation in the ancient genome, suggesting that the Lucayans had a relatively large effective population size. Finally, we show that the native American components in some present-day Caribbean genomes are closely related to the ancient Taino, demonstrating an element of continuity between precontact populations and present-day Latino populations in the Caribbean.

Identification of a Minimal 3-Transcript Signature to Differentiate Viral from Bacterial Infection from Best Genome-Wide Host RNA Biomarkers: A Multi-Cohort Analysis.

The fight against the spread of antibiotic resistance is one of the most important challenges facing health systems worldwide. Given the limitations of current diagnostic methods, the development of fast and accurate tests for the diagnosis of viral and bacterial infections would improve patient management and treatment, as well as contribute to reducing antibiotic misuse in clinical settings. In this scenario, analysis of host transcriptomics constitutes a promising target to develop new diagnostic tests based on the host-specific response to infections. We carried out a multi-cohort meta-analysis of blood transcriptomic data available in public databases, including 11 different studies and 1209 samples from virus- (n = 695) and bacteria- (n = 514) infected patients. We applied a Parallel Regularized Regression Model Search (PReMS) on a set of previously reported genes that distinguished viral from bacterial infection to find a minimum gene expression bio-signature. This strategy allowed us to detect three genes, namely BAFT, ISG15 and DNMT1, that clearly differentiate groups of infection with high accuracy (training set: area under the curve (AUC) 0.86 (sensitivity: 0.81; specificity: 0.87); testing set: AUC 0.87 (sensitivity: 0.82; specificity: 0.86)). BAFT and ISG15 are involved in processes related to immune response, while DNMT1 is related to the preservation of methylation patterns, and its expression is modulated by pathogen infections. We successfully tested this three-transcript signature in the 11 independent studies, demonstrating its high performance under different scenarios. The main advantage of this three-gene signature is the low number of genes needed to differentiate both groups of patient categories.

Respiratory Syncytial Virus Consortium in Europe (RESCEU) Birth Cohort Study: Defining the Burden of Infant Respiratory Syncytial Virus Disease in Europe.

BACKGROUND: Respiratory syncytial virus (RSV) causes significant morbidity and mortality in infants worldwide. Although prematurity and cardiopulmonary disease are risk factors for severe disease, the majority of infants hospitalized with RSV are previously healthy. Various vaccines and therapeutics are under development and expected to be available in the near future. To inform the use of these new vaccines and therapeutics, it is necessary to determine the burden of RSV disease in Europe. We will prospectively follow-up a birth cohort to obtain incidence data on RSV acute respiratory tract infection (ARTI). METHODS: Multicenter prospective study of a birth cohort consisting of 10 000 healthy infants, recruited during 3 consecutive years. RSV associated hospitalization in the first year of life will be determined by questionnaires and hospital chart reviews. A nested cohort of 1000 infants will be actively followed. In case of ARTI, a respiratory sample will be collected for RSV molecular diagnosis. RESULTS: The primary outcome is the incidence rate of RSV-associated hospitalization in the first year of life. In the active cohort the primary outcome is RSV associated ARTI and MA-ARTI. CONCLUSIONS: We will provide key information to fill the gaps in knowledge about the burden of RSV disease in healthy infants. CLINICAL TRIALS REGISTRATION: NCT03627572.

Low Sensitivity of BinaxNOW RSV in Infants.

BACKGROUND: Respiratory syncytial virus (RSV) is a major cause of hospitalization in infants. Early detection of RSV can optimize clinical management and minimize use of antibiotics. BinaxNOW RSV (BN) is a rapid antigen detection test that is widely used. We aimed to validate the sensitivity of BN in hospitalized and nonhospitalized infants against the gold standard of molecular diagnosis. METHODS: We evaluated the performance of BN in infants with acute respiratory tract infections with different degrees of disease severity. Diagnostic accuracy of BN test results were compared with molecular diagnosis as reference standard. RESULTS: One hundred sixty-two respiratory samples from 148 children from October 2017 to February 2019 were studied. Sixty-six (40.7%) samples tested positive for RSV (30 hospitalizations, 31 medically attended episodes not requiring hospitalization, and 5 nonmedically attended episodes). Five of these samples tested positive with BN, leading to an overall sensitivity of BN of 7.6% (95% confidence interval [CI], 3.3%-16.5%) and a specificity of 100% (95% CI, 96.2%-100%). Sensitivity was low in all subgroups. CONCLUSIONS: We found a low sensitivity of BN for point-of-care detection of RSV infection. BinaxNOW RSV should be used and interpreted with caution.

A Meta-Analysis of Multiple Whole Blood Gene Expression Data Unveils a Diagnostic Host-Response Transcript Signature for Respiratory Syncytial Virus.

Respiratory syncytial virus (RSV) is one of the major causes of acute lower respiratory tract infection worldwide. The absence of a commercial vaccine and the limited success of current therapeutic strategies against RSV make further research necessary. We used a multi-cohort analysis approach to investigate host transcriptomic biomarkers and shed further light on the molecular mechanism underlying RSV-host interactions. We meta-analyzed seven transcriptome microarray studies from the public Gene Expression Omnibus (GEO) repository containing a total of 922 samples, including RSV, healthy controls, coronaviruses, enteroviruses, influenzas, rhinoviruses, and coinfections, from both adult and pediatric patients. We identified > 1500 genes differentially expressed when comparing the transcriptomes of RSV-infected patients against healthy controls. Functional enrichment analysis showed several pathways significantly altered, including immunologic response mediated by RSV infection, pattern recognition receptors, cell cycle, and olfactory signaling. In addition, we identified a minimal 17-transcript host signature specific for RSV infection by comparing transcriptomic profiles against other respiratory viruses. These multi-genic signatures might help to investigate future drug targets against RSV infection.

RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans.

There is a growing interest in unraveling gene expression mechanisms leading to viral host invasion and infection progression. Current findings reveal that long non-coding RNAs (lncRNAs) are implicated in the regulation of the immune system by influencing gene expression through a wide range of mechanisms. By mining whole-transcriptome shotgun sequencing (RNA-seq) data using machine learning approaches, we detected two lncRNAs (ENSG00000254680 and ENSG00000273149) that are downregulated in a wide range of viral infections and different cell types, including blood monocluclear cells, umbilical vein endothelial cells, and dermal fibroblasts. The efficiency of these two lncRNAs was positively validated in different viral phenotypic scenarios. These two lncRNAs showed a strong downregulation in virus-infected patients when compared to healthy control transcriptomes, indicating that these biomarkers are promising targets for infection diagnosis. To the best of our knowledge, this is the very first study using host lncRNAs biomarkers for the diagnosis of human viral infections.

The Paleo-Indian Entry into South America According to Mitogenomes.

Recent and compelling archaeological evidence attests to human presence ∼14.5 ka at multiple sites in South America and a very early exploitation of extreme high-altitude Andean environments. Considering that, according to genetic evidence, human entry into North America from Beringia most likely occurred ∼16 ka, these archeological findings would imply an extremely rapid spread along the double continent. To shed light on this issue from a genetic perspective, we first completely sequenced 217 novel modern mitogenomes of Native American ancestry from the northwestern area of South America (Ecuador and Peru); we then evaluated them phylogenetically together with other available mitogenomes (430 samples, both modern and ancient) from the same geographic area and, finally, with all closely related mitogenomes from the entire double continent. We detected a large number (N = 48) of novel subhaplogroups, often branching into further subclades, belonging to two classes: those that arose in South America early after its peopling and those that instead originated in North or Central America and reached South America with the first settlers. Coalescence age estimates for these subhaplogroups provide time boundaries indicating that early Paleo-Indians probably moved from North America to the area corresponding to modern Ecuador and Peru over the short time frame of ∼1.5 ka comprised between 16.0 and 14.6 ka.