Application of a High-Resolution Melt Assay for Monitoring SARS-CoV-2 Variants in Burkina Faso and Kenya (preprint)

The rapid emergence and global dissemination of SARS-CoV-2 highlighted a need for robust, adaptable surveillance systems. However, financial and infrastructure requirements for whole genome sequencing (WGS) mean most surveillance data have come from higher-resource geographies, despite unprecedented investment in sequencing in low-middle income countries (LMICs) throughout the SARS-CoV-2 pandemic. Consequently, the molecular epidemiology of SARS-CoV-2 in some LMICs is limited, and there is a need for more cost-accessible technologies to help close data gaps for surveillance of SARS-CoV-2 variants. To address this, we have developed two high-resolution melt curve (HRM) assays that target key variant-defining mutations in the SARS-CoV-2 genome, which give unique signature profiles that define different SARS-CoV-2 variants of concern (VOCs). Extracted RNA from SARS-CoV-2 positive samples collected from 205 participants (112 in Burkina Faso, 93 in Kenya) on the day of enrolment in the MALCOV study (Malaria as a Risk Factor for COVID-19) between February 2021 and February 2022 were analysed using our optimised HRM assays and compared to Next Generation Sequencing (NGS) on Oxford Nanopore MinION . With NGS as a reference, two HRM assays, HRM-VOC-1 and HRM-VOC-2, demonstrated sensitivity/specificity of 100%/99.29% and 92.86/99.39%, respectively, for detecting Alpha, 90.08%/100% and 92.31%/100% for Delta and 93.75%/100% and 100%/99.38% for Omicron. The assays described here provide a lower-cost approach (<$1 per sample) to conducting molecular epidemiology, capable of high-throughput testing. We successfully scaled up the HRM-VOC-2 assay to screen a total of 506 samples from which we were able to show the replacement of Alpha with the introduction of Delta and the replacement of Delta by the Omicron variant in this community in Kisumu, Kenya. These assays are readily adaptable and can focus on local epidemiological surveillance questions or be updated quickly to accommodate the emergence of a novel variant or adapt to novel and emerging pathogens.

Molecular epidemiology of invasive Group A Streptococcal infections before and after the COVID-19 pandemic in Switzerland (preprint)

Group A Streptococcus (GAS, aka Streptococcus pyogenes) poses a significant public health concern, causing a diverse spectrum of infections with high mortality rates. Following the COVID-19 pandemic, a resurgence of invasive GAS (iGAS) infections has been documented, necessitating efficient outbreak detection methods. Whole genome sequencing (WGS) serves as the gold standard for GAS molecular typing, albeit constrained by time and costs. This study aimed to characterize the postpandemic increased prevalence of iGAS on the molecular epidemiological level in order to assess whether new, more virulent variants have emerged, as well as to assess the performance of the rapid and cost-effective Fourier-transform infrared (FTIR) spectroscopy as an alternative to WGS for detecting and characterizing GAS transmission routes. A total of 66 iGAS strains isolated from nine Swiss hospitals during the COVID-19 post-pandemic increased GAS prevalence were evaluated and compared to 15 strains collected before and 12 during the COVID-19 pandemic. FT-IR measurements and WGS were conducted for network analysis. Demographic, clinical, and epidemiological data were collected. Skin and soft tissue infection was the most common diagnosis, followed by primary bacteremia and pneumonia. Viral co-infections were found in 25% of cases and were significantly associated with more severe disease requiring intensive care unit admission. WGS analysis did not reveal emerging GAS genetic distinct variants after the COVID-19 pandemic, indicating the absence of a pandemic-induced shift. FT-IR spectroscopy exhibited limitations in differentiating genetically distant GAS strains, yielding poor overlap with WGS-derived clusters. The emm1/ST28 gebotype was predominant in our cohort and was associated with five of the seven deaths recorded, in accordance with the molecular epidemiological data before the pandemic. Additionally, no notable shift in antibiotic susceptibility patterns was observed. Our data suggest that mainly non-pathogen related factors contributed to the recent increased prevalence of iGAS.

Genomic Surveillance of a Canadian Airport Wastewater Samples Allows Early Detection of Emerging SARS-CoV-2 Lineages (preprint)

The SARS-CoV-2 pandemic has shown that wastewater (WW) surveillance is an effective means of tracking the emergence of viral lineages in communities, arriving by many routes including via transportation hubs. In Ontario, numerous municipal WWTPs participate in WW surveillance of infectious disease targets such as SARS-CoV-2 by qPCR and whole genome sequencing (WGS). The Greater Toronto Airports Authority (GTAA), operator of Toronto Pearson International Airport (Toronto Pearson), has been participating in WW surveillance since January 2022. As a major international airport in Canada and the largest national hub, this airport is an ideal location for tracking globally emerging SARS-CoV-2 variants of concern (VOCs). In this study, WW collected from Toronto Pearson’s two terminals and pooled aircraft sewage was processed for WGS using a tiled-amplicon approach targeting the SARS-CoV-2 virus. Data generated was analyzed to monitor trends SARS-CoV-2 lineage frequencies. Initial detections of emerging lineages were compared between Toronto Pearson WW samples, municipal WW samples collected from the surrounding regions, and Ontario clinical data as published by Public Health Ontario. Results enabled the early detection of VOCs and individual mutations emerging in Ontario. On average, emergence of novel lineages at the airport ahead of clinical detections was 1–4 weeks, and up to 16 weeks. This project illustrates the efficacy of WW surveillance at transitory transportation hubs and sets an example that could be applied to other viruses as part of a pandemic preparedness strategy and to provide monitoring on a mass scale.

Developing molecular surveillance of SARS-CoV-2 in the Czech Republic (2021–2022) (preprint)

Molecular surveillance was widely used during the COVID-19 pandemic to rapidly detect emerging variants and monitor the transmission of SARS-CoV-2 within communities. In 2021, the Czech COVID-19 Genomics Consortium (COG-CZ) was set up to coordinate a new SARS-CoV-2 molecular surveillance network. In the Czech Republic, molecular surveillance employed whole genome sequencing (WGS) and variant discrimination polymerase chain reaction (VD-PCR) on samples collected through passive, active and sentinel surveillance. All WGS data was uploaded to GISAID and the PANGO lineages used by GISAID were compared to the main variants determined by VD-PCR. To assess the effectiveness and reliability of the gathered data in adapting pandemic responses, the capabilities and turnaround times of the molecular surveillance methods are evaluated.VD-PCR enabled accurate detection of changes in major variant dominance within 48 h of sample collection during the Delta/Omicron transition. WGS detected novel mutations and infection clusters, including several genetic lineages and clades of the virus, some of which were unique to the Czech Republic, such as AY.20.1. Molecular surveillance informed the implementation of public health measures and contributed to reduced cases and mortality, however further areas for improvement have been identified for monitoring and managing future pandemics.

Rhinovirus infection of airway epithelial cells uncovers the non-ciliated subset as a likely driver of genetic susceptibility to childhood-onset asthma (preprint)

Asthma is a complex disease caused by genetic and environmental factors. Epidemiological studies have shown that in children, wheezing during rhinovirus infection (a cause of the common cold) is associated with asthma development during childhood. This has led scientists to hypothesize there could be a causal relationship between rhinovirus infection and asthma or that RV-induced wheezing identifies individuals at increased risk for asthma development. However, not all children who wheeze when they have a cold develop asthma. Genome-wide association studies (GWAS) have identified hundreds of genetic variants contributing to asthma susceptibility, with the vast majority of likely causal variants being non-coding. Integrative analyses with transcriptomic and epigenomic datasets have indicated that T cells drive asthma risk, which has been supported by mouse studies. However, the datasets ascertained in these integrative analyses lack airway epithelial cells. Furthermore, large-scale transcriptomic T cell studies have not identified the regulatory effects of most non-coding risk variants in asthma GWAS, indicating there could be additional cell types harboring these 'missing regulatory effects'. Given that airway epithelial cells are the first line of defense against rhinovirus, we hypothesized they could be mediators of genetic susceptibility to asthma. Here we integrate GWAS data with transcriptomic datasets of airway epithelial cells subject to stimuli that could induce activation states relevant to asthma. We demonstrate that epithelial cultures infected with rhinovirus significantly upregulate childhood-onset asthma-associated genes. We show that this upregulation occurs specifically in non-ciliated epithelial cells. This enrichment for genes in asthma risk loci, or 'asthma heritability enrichment' is also significant for epithelial genes upregulated with influenza infection, but not with SARS-CoV-2 infection or cytokine activation. Additionally, cells from patients with asthma showed a stronger heritability enrichment compared to cells from healthy individuals. Overall, our results suggest that rhinovirus infection is an environmental factor that interacts with genetic risk factors through non-ciliated airway epithelial cells to drive childhood-onset asthma.

A response playbook for early detection and population surveillance of new SARS-CoV-2 variants in a regional public health laboratory (preprint)

Background: Timely genomic surveillance is required to inform public health responses to new SARS-CoV-2 variants. However, the processes involved in local genomic surveillance introduce inherent time constraints. The Regional Innovative Public Health Laboratory in Chicago developed and employed a genomic surveillance response playbook for the early detection and surveillance of emerging SARS-CoV-2 variants. Methods: The playbook outlines modifications to sampling strategies, laboratory workflows, and communication processes based on the emerging variant's predicted viral characteristics, observed public health impact in other jurisdictions and local community risk level. The playbook outlines procedures for implementing and reporting enhanced and accelerated genomic surveillance, including supplementing whole genome sequencing (WGS) with variant screening by quantitative PCR (qPCR). Results: The ability of the playbook to improve the response to an emerging variant was tested for SARS-CoV-2 Omicron BA.1. Increased submission of clinical remnant samples from local hospital laboratories enabled detection of a new variant at 1% prevalence with 95% confidence rather than 2% at baseline. Genotyping qPCR concurred with WGS lineage assignments in 99.9% of 1541 samples with results by both methods, and was more sensitive, providing lineage results in 90.4% of 1833 samples rather than 85.1% for WGS, while reducing the time to lineage result from 27 to 7 days. Conclusions: The genomic surveillance response playbook provides a structured, stepwise, and data-driven approach to responding to emerging SARS-CoV-2 variants. These pre-defined processes can streamline workflows and expedite the detection and public health response to emerging variants. Based on the processes piloted during the Omicron BA.1 response, this method has been applied to subsequent Omicron subvariants and can be readily applied to future SARS-CoV-2 emerging variants and other public health surveillance activities.

Molecular and Clinical Epidemiology of SARS-CoV-2 Infection Among Vaccinated and Unvaccinated Individuals in a Large Healthcare Organization from New Jersey (preprint)

New Jersey was among the first states impacted by the COVID-19 pandemic, with one of the highest overall death rates in the nation. Nevertheless, relatively few reports have been published focusing specifically on New Jersey. Here we report on molecular, clinical, and epidemiologic observations from the largest healthcare network in the state, in a cohort of vaccinated and unvaccinated individuals with laboratory-confirmed SARS-CoV-2 infection. We conducted molecular surveillance of SARS-CoV-2-positive nasopharyngeal swabs collected in nine hospitals from December 2020 through June 2022, using both whole genome sequencing (WGS) and a real-time RT-PCR screening assay targeting spike protein mutations found in variants of concern (VOC) within our region. De-identified clinical data were obtained retrospectively, including demographics, COVID-19 vaccination status, ICU admission, ventilator support, mortality, and medical history. Statistical analyses were performed to identify associations between SARS-CoV-2 variants, vaccination status, clinical outcomes, and medical risk factors. A total of 5,007 SARS-CoV-2-positive nasopharyngeal swabs were successfully screened and/or sequenced. Variant screening identified three predominant VOC, including Alpha (n =714), Delta (n =1,877), and Omicron (n =1,802). Omicron isolates were further sub-typed as BA.1 (n =899), BA.2 (n =853), and BA.4/BA.5 (n =50); the remaining 614 isolates were classified as “Other”. Approximately 31.5% (1,577/5,007) of the samples were associated with vaccine breakthrough infections, which increased in frequency following the emergence of Delta and Omicron. Severe clinical outcomes included ICU admission (336/5007 = 6.7%), ventilator support (236/5007 = 4.7%), and mortality (430/5007 = 8.6%), with increasing age being the most significant contributor to each (p <0.001). Unvaccinated individuals accounted for 79.7% (268/336) of ICU admissions, 78.3% (185/236) of ventilator cases, and 74.4% (320/430) of deaths. Highly significant (p <0.001) increases in mortality were observed in individuals with cardiovascular disease, hypertension, cancer, diabetes, and hyperlipidemia, but not with obesity, thyroid disease, or respiratory disease. Significant differences (p <0.001) in clinical outcomes were also noted between SARS-CoV-2 variants, including Delta, Omicron BA.1, and Omicron BA.2. Vaccination was associated with significantly improved clinical outcomes in our study, despite an increase in breakthrough infections associated with waning immunity, greater antigenic variability, or both. Underlying comorbidities contributed significantly to mortality in both vaccinated and unvaccinated individuals, with increasing risk based on the total number of comorbidities. Real-time RT-PCR-based screening facilitated timely identification of predominant variants using a minimal number of spike protein mutations, with faster turnaround time and reduced cost compared to WGS. Continued evolution of SARS-CoV-2 variants will likely require ongoing surveillance for new VOCs, with real-time assessment of clinical impact.

SARS-CoV-2 introductions to the island of Ireland (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had an unprecedented impact on the people of Ireland as waves of infection spread across the island during the global coronavirus disease 2019 (COVID-19) pandemic. Viral whole-genome sequencing (WGS) has provided insights into SARS-CoV-2 molecular mechanisms of pathogenicity and evolution and contributed to the development of anti-virals and vaccines. High levels of WGS have enabled effective SARS-CoV-2 genomic surveillance on the island of Ireland, leading to the generation of a sizeable data set with potential to provide additional insights into viral epidemiology. Because Ireland is an island, accurate documentation of travel rates to and from other regions, both by air and by sea, are available. Furthermore, the two distinct political jurisdictions on the island allow comparison of the impact of varying public health responses on viral dynamics, including SARS-CoV-2 introduction events. Using phylogenomic analysis incorporating sample collection date and location metadata, we identify multiple introduction and spreading events for all major viral lineages to the island of Ireland during the period studied (March 2020-June 2022). The majority of SARS-CoV-2 introductions originated from England, with frequent introductions from USA and northwestern Europe. The clusters of sequences predicted to derive from discrete introduction events ("introduction clusters") vary greatly in size, with some involving only one or two cases and others comprising thousands of samples. When introduction cluster samples are mapped sequentially by collection date, they appear predominantly in previously affected or adjacent areas. This mirroring of the phylogenetic relationships by the geospatiotemporal propagation of SARS-CoV-2 validates our analytic approach. By downsampling, we estimate the power to detect introductions to Ireland as a function of sequencing levels. Per capita normalisation of both sequencing levels and detected introductions accounts for biases due to differing sequencing efforts and total populations. This approach showed similar rates of introductions for all major lineages into Northern Ireland (NI) and Republic of Ireland (RoI) with the exception of Delta, which was higher in NI which is likely attributable to higher travel per capita. However, there were similar rates of Delta infection within NI and RoI, suggesting that although travel restrictions will reduce risk of introducing novel variants to the region, they may not substantially decrease total incidence. Our generalisable methodology to study introduction dynamics and optimal sequencing levels will assist public health authorities to select the most appropriate control measures and viral sequencing strategy.

Insights into the implementation of a whole genome sequencing report form (SRF) to reduce nosocomial SARS-CoV-2 within UK hospitals: a qualitative process evaluation using normalisation process theory (preprint)

Background Here we report on a process evaluation conducted as part of a large multisite non-randomised trial of the effectiveness of a whole genome sequence report form (SRF) to reduce nosocomial SARS-CoV-2 through changing infection prevention and control (IPC) behaviours during the COVID − 19 pandemic. We detail how the SRF was implemented across a heterogeneous purposive sub-sample of hospital trial sites (n = 5/14). Methods We conducted in-depth interviews from diverse professional staff (N = 39). Inductive thematic analysis initially explored participants’ accounts of implementing the SRF. The resulting data driven themes, concerning the way the SRF was used within sites, were then coded in relation to the key tenets of normalisation process theory (NPT). Results Factors that enabled the implementation of the SRF included: elements of the context such as health care professional passion; the existence of whole genome sequencing (WGS) infrastructure; effective communication channels, the creation of new connections across professionals and teams; the integration of SRF-led discussions within pre-existing meetings and the ability of a site to achieve a rapid turnaround time. In contrast, we found factors that constrained the use of the SRF included elements of the context such as the impact of the Alpha-variant overwhelming hospitals. In turn, dealing with COVID-19 breached the limited capacity of infection prevention and control (IPC) to respond to the SRF and ensure its routinisation. Conclusion We show preliminary support for the SRF being an acceptable, useable and potentially scalable way of enhancing existing IPC activities. However, the context of both the trial and the alpha wave of COVID-19 limit these insights. Clinical trial number https://www.isrctn.com/ISRCTN50212645, Registration date 20/05/2020

Genomic surveillance reveals circulation of multiple variants and lineages of SARS-CoV-2 during COVID-19 pandemic in Indian city of Bengaluru (preprint)

Genomic surveillance in response to coronavirus disease (COVID-19) pandemic is crucial for tracking spread, identify variants of concern (VoCs) and understand the evolution of its etiological agent, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). India has experienced three waves of COVID-19 cases, which includes a deadly wave of COVID-19 that was driven by the Delta lineages (second/Delta wave) followed by another wave driven by the Omicron lineages (third/Omicron wave). These waves were particularly dramatic in the metropolitan cities due to high population density. We evaluated the prevalence, and mutational spectrum of SARS-CoV-2 variants/lineages in one such megapolis, Bengaluru city, across these three waves between October 2020 and June 2022. 15,134 SARS-CoV-2 samples were subjected to whole genome sequencing (WGS). Phylogenetic analysis revealed, SARS-CoV-2 variants in Bengaluru city belonged to 18 clades and 196 distinct lineages. As expected, the Delta lineages were the most dominant lineages during the second wave of COVID-19. The Omicron lineage BA.2 and its sublineages accounted for most of the COVID-19 cases in the third wave. Most number of amino acid changes were observed in spike protein. Among the 18 clades, majority of the mutations and least similarity at nucleotide sequence level with the reference genome were observed in Omicron clades.

Dynamics of Influenza A and SARS-CoV-2 coinfections during the COVID-19 pandemic in India (preprint)

The SARS-CoV-2 exhibits similar aetiology, mode of transmission and clinical presentation as the H1N1pdm09 (a subtype of Influenza A) and Influenza A (other subtypes), and can exist as a coinfection in the same patient. It is essential to understand the coinfection dynamics of these viruses for effective management of the disease. This study examined 959 SARS-CoV-2 positive samples collected from the six states and three union territories in India from May to December 2022. The clinical data was accessed from the Integrated Health Information Platform (IHIP) and the Indian council of medical research (ICMR) COVID-19 data portal. The samples were tested for SARS-CoV-2, H1N1pdm09 and Influenza A using Reverse Transcriptase Real-Time Polymerase Chain Reaction q(RT-PCR). All 959 samples were subjected to SARS-CoV-2 whole genome sequencing (WGS) using Oxford Nanopore Next Generation Sequencing (NGS). From the 959 SARS-CoV-2 positive samples, 17.5% were co-infected with H1N1pdm09, 8.2% were co-infected with Influenza A, and 74.2% were only positive for SARS-CoV-2. The comparative analysis of viral load among the coinfected cases revealed that Influenza A and H1N1pdm09 had higher viral loads than SARS-CoV-2 in the studied samples. Out of 959 samples subjected to WGS, 815 and 144 were considered quality control (QC) passed, and QC failed, respectively, for SARS-CoV-2 variant calling. SARS-CoV-2 WGS identified 46 different variants belonging to the Omicron lineage. The SARS-CoV-2 and Influenza A coinfection group; and the SARS-CoV-2 and H1N1pdm09 coinfection group showed a higher proportion of symptomatic cases. This work demonstrates the need for coinfection analysis for the H1N1pdm09 virus, Influenza A virus and SARS-CoV-2 while studying the etiological agent in individuals with ILI/SARI symptoms. It is recommended that, in addition to determining the aetiology of ILI/SARI, an examination for H1N1pdm09 and Influenza A be conducted concurrently utilising molecular tools such as WGS and RT-PCR to understand the variant dynamics and the viral load for taking an informed decision during the patient management and treatment discourse.

LINE1-mediated reverse transcription and genomic integration of SARS-CoV-2 mRNA detected in virus-infected but not in viral mRNA-transfected cells (preprint)

SARS-CoV-2 sequences can be reverse-transcribed and integrated into the genomes of virus-infected cells by a LINE1-mediated retrotransposition mechanism. Whole genome sequencing (WGS) methods detected retrotransposed SARS-CoV-2 subgenomic sequences in virus-infected cells overexpressing LINE1, while an enrichment method (TagMap) identified retrotranspositions in cells that did not overexpress LINE1. LINE1 overexpression increased retrotranspositions about 1,000-fold as compared to non-overexpressing cells. Nanopore WGS can directly recover retrotransposed viral and flanking host sequences but its sensitivity depends on the depth of sequencing (a typical 20-fold sequencing depth would only examine 10 diploid cell equivalents). In contrast, TagMap enriches for the host-virus junctions and can interrogate up to 20,000 cells and is able to detect rare viral retrotranspositions in LINE1 non-overexpressing cells. Although Nanopore WGS is 10 - 20-fold more sensitive per tested cell, TagMap can interrogate 1,000 - 2,000-fold more cells and therefore can identify infrequent retrotranspositions. When comparing SARS-CoV-2 infection and viral nucleocapsid mRNA transfection by TagMap, retrotransposed SARS-CoV-2 sequences were only detected in infected but not in transfected cells. Retrotransposition in virus-infected in contrast to transfected cells may be facilitated because virus infection in contrast to viral RNA transfection results in significantly higher viral RNA levels and stimulates LINE1-expression which causes cellular stress.

Bioinformatic investigation of discordant sequence data for SARS-CoV-2: insights for robust genomic analysis during pandemic surveillance (preprint)

The capacity to undertake whole genome sequencing (WGS) in public health laboratories (PHLs) has grown rapidly in response to COVID-19, and SARS-CoV-2 genomic data has been invaluable for managing the pandemic. The public health response has been further supported by the rapid upgrade and implementation of laboratory and bioinformatic resources. However, there remains a high degree of variability in methods and capabilities between laboratories. In addition to evolving methodology and improved understanding of SARS-CoV-2, public health laboratories have become strained during surges in case numbers, adding to the difficulty of ensuring the highest data accuracy. Here, we formed a national working group comprised of laboratory scientists and bioinformaticians from Australia and New Zealand to improve data concordance across PHLs. Through investigating discordant sequence data from Australia's first external SARS-CoV-2 WGS proficiency testing program (PTP), we show that most discrepancies in genome assessment arose from intrahost variation. While others could be remedied using reasonable, parsimonious bioinformatic quality control. Furthermore, we demonstrate how multidisciplinary national working groups can inform guidelines in real time for bioinformatic quality acceptance criteria. Provision of technical feedback allows laboratory improvement during a pandemic in real time, enhancing public health responses.

A systematic outbreak investigation of SARS-CoV-2 transmission clusters in a tertiary academic care center (preprint)

Background We sought to decipher transmission pathways in healthcare-associated infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within our hospital by epidemiological work-up and complementary whole genome sequencing (WGS). We report the findings of the four largest epidemiologic clusters of SARS-CoV-2 transmission occurring during the second wave of the pandemic from 11/2020-12/2020.Methods At the University Hospital Basel, Switzerland, systematic outbreak investigation is initiated at detection of any nosocomial case of Coronavirus disease of 2019 (COVID-19), defined as polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infection occurring more than five days after admission. Clusters of nosocomial infections, defined as the detection of at least two positive patients and/or healthcare workers (HCWs) within one week with an epidemiological link, were further investigated by WGS on respective strains.Results The four epidemiologic clusters included 40 patients and 60 HCWs. Sequencing data was available for 70% of all involved cases (28 patients and 42 HCWs), confirmed epidemiologically suspected in house transmission in 33 cases (47.1% of sequenced cases) and excluded transmission in the remaining 37 cases (52.9%). Among cases with identical strains, epidemiologic work-up suggested transmission mainly through a ward-based exposure (24/33, 72.7%), more commonly affecting HCWs (16/24, 66.7%) than patients (8/24, 33.3%), followed by transmission between patients (6/33, 18.2%), and among HCWs and patients (3/33, 9.1%, respectively two HCWs and one patient).Conclusions Phylogenetic analyses revealed important insights into transmission pathways supporting less than 50% of epidemiologically suspected SARS-CoV-2 transmissions. The remainder of cases most likely reflect community-acquired infection randomly detected by outbreak investigation. Notably, most transmissions occurred between HCWs, possibly indicating lower perception of the risk of infection during contacts among HCWs.

Use of whole genome sequencing to estimate the contribution of immune evasion and waning immunity to decreasing COVID-19 vaccine effectiveness during alpha and delta variant waves (preprint)

Background: The decline in COVID-19 mRNA vaccine effectiveness (VE) is well established, however the impact of variant-specific immune evasion and waning protection remains unclear. Here, we use whole-genome-sequencing (WGS) to tease apart the contribution of these factors on the decline observed following the introduction of the Delta variant. Further, we evaluate the utility of calendar-period-based variant classification as an alternative to WGS. Methods: We conducted a test-negative-case-control study among people who received SARS-CoV-2 RT-PCR testing in the Yale New Haven Health System between April 1 and August 24, 2021. Variant classification was performed using WGS and secondarily by calendar-period. We estimated VE as one minus the ratio comparing the odds of infection among vaccinated and unvaccinated people. Results: Overall, 2,029 cases (RT-PCR positive, sequenced samples) and 343,985 controls (negative RT-PCRs) were included. VE 14-89 days after 2nd dose was significantly higher against WGS-classified Alpha infection (84.4%, 95% confidence interval: 75.6-90.0%) than Delta infection (68.9%, CI: 58.0-77.1%, p-value: 0.013). The odds of WGS-classified Delta infection were significantly higher 90-149 than 14-89 days after 2nd dose (Odds ratio: 1.6, CI: 1.2-2.3). While estimates of VE against calendar-period-classified infections approximated estimates against WGS-classified infections, calendar-period-based classification was subject to outcome misclassification (35% during Alpha period, 4% during Delta period). Conclusions: These findings suggest that both waning protection and variant-specific immune evasion contributed to the lower effectiveness. While estimates of VE against calendar-period-classified infections mirrored that against WGS-classified infections, our analysis highlights the need for WGS when variants are co-circulating and misclassification is likely.

BA.4/BA.5 early surge report Austria (preprint)

More than two years into the COVID-19 pandemic, the emergence of the Omicron subvariants BA.4 and BA.5 initiated the fifth wave. BA.4/BA.5 share identical spike proteins and are thus difficult to differentiate using standard diagnostic tests. The true frequency and diversity of the two variants in Austria is therefore largely unknown. Aim of this report is to take stock about the frequency and diversity of BA.4 & BA.5 and their subvariants based on whole genome sequencing (WGS) data as deposited at GISAID database. Results show that most sequenced cases belong to BA.5 (c. 86 %) rather than BA.4 (c. 14 %) and that most of the global diversity (24 out of 32 subvariants) of BA.4 and BA.5 in terms of subvariants described is already present in Austria. However, most cases can be attributed to a few subvariants (e.g. BA.5.1, BE.1.1, BA.5.3, BA.5.2.1) with high estimated growth advantage over BA.2 (ranging 103 to 159 %) and may be worth monitoring as the immediate wave unfolds.

A robust, highly multiplexed mass spectrometry assay to identify SARS-CoV-2 variants (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are characterized by differences in transmissibility and response to therapeutics. Therefore, discriminating among them is vital for surveillance, infection prevention, and patient care. While whole viral genome sequencing (WGS) is the "gold standard" for variant identification, molecular variant panels have become increasingly available. Most, however, are based on limited targets and have not undergone comprehensive evaluation. We assessed the diagnostic performance of the highly multiplexed Agena MassARRAY(R) SARS-CoV-2 Variant Panel v3 to identify variants in a diverse set of 391 SARS-CoV-2 clinical RNA specimens collected across our health systems in New York City, USA as well as in Bogota, Colombia (September 2, 2020 - March 2, 2022). We demonstrate almost perfect levels of interrater agreement between this assay and WGS for 9 of 11 variant calls ({kappa} [≥] 0.856) and 25 of 30 targets ({kappa} [≥] 0.820) tested on the panel. The assay had a high diagnostic sensitivity ([≥]93.67%) for contemporary variants (e.g., Iota, Alpha, Delta, Omicron [BA.1 sublineage]) and a high diagnostic specificity for all 11 variants ([≥]96.15%) and all 30 targets ([≥]94.34%) tested. Moreover, we highlight distinct target patterns that can be utilized to identify variants not yet defined on the panel including the Omicron BA.2 and other sublineages. These findings exemplify the power of highly multiplexed diagnostic panels to accurately call variants and the potential for target result signatures to elucidate new ones.

Metformin in aging and aging-related diseases: clinical applications and relevant mechanisms.

Aging is a natural process, which plays a critical role in the pathogenesis of a variety of diseases, i.e., aging-related diseases, such as diabetes, osteoarthritis, Alzheimer disease, cardiovascular diseases, cancers, obesity and other metabolic abnormalities. Metformin, the most widely used antidiabetic drug, has been reported to delay aging and display protective effect on attenuating progression of various aging-related diseases by impacting key hallmark events of aging, including dysregulated nutrient sensing, loss of proteostasis, mitochondrial dysfunction, altered intercellular communication, telomere attrition, genomic instability, epigenetic alterations, stem cell exhaustion and cellular senescence. In this review, we provide updated information and knowledge on applications of metformin in prevention and treatment of aging and aging-related diseases. We focus our discussions on the roles and underlying mechanisms of metformin in modulating aging and treating aging-related diseases.

Genome Screening, Reporting and Counseling for Healthy Populations (preprint)

Introduction: Rapid advancements of genome sequencing (GS) technologies have enhanced our understanding of the relationship between genes and human disease. In order to incorporate genomic information into the practice of medicine, new processes for the analysis, reporting and communication of GS data are needed. Methods: blood samples were collected from adults with a PCR-confirmed SARS-CoV-2 (COVID-19) diagnosis (target N=1500). GS was performed. Data was filtered and analyzed using custom pipelines and gene panels. We developed unique patient-facing materials, including an online intake survey, group counseling presentation, and consultation letters in addition to a comprehensive GS report. Results: The final report includes results generated from GS data: 1) Monogenic disease risks; 2) Carrier status; 3) Pharmacogenomic variants; 4) Polygenic risk scores for common conditions; 5) HLA genotype; 6) Genetic ancestry; 7) Blood group; and, 8) COVID-19 viral lineage. Participants complete pre-test genetic counseling and confirm preferences for secondary findings before receiving results. Counseling and referrals are initiated for clinically significant findings. Conclusion: We developed a genetic counseling, reporting, and return of results framework that integrates GS information across multiple areas of human health, presenting possibilities for the clinical application of comprehensive GS data in healthy individuals.

Low expression of EXOSC2 protects against clinical COVID-19 and impedes SARS-CoV-2 replication (preprint)

New therapeutic targets are a valuable resource in the struggle to reduce the morbidity and mortality associated with the COVID-19 pandemic, caused by the SARS-CoV-2 virus. Genome-wide association studies (GWAS) have identified risk loci, but some loci are associated with co-morbidities and are not specific to host-virus interactions. Here, we identify and experimentally validate a link between reduced expression of EXOSC2 and reduced SARS-CoV-2 replication. EXOSC2 was one of 332 host proteins examined, all of which interact directly with SARS-CoV-2 proteins; EXOSC2 interacts with Nsp8 which forms part of the viral RNA polymerase. Lung-specific eQTLs were identified from GTEx (v7) for each of the 332 host proteins. Aggregating COVID-19 GWAS statistics for gene-specific eQTLs revealed an association between increased expression of EXOSC2 and higher risk of clinical COVID-19 which survived stringent multiple testing correction. EXOSC2 is a component of the RNA exosome and indeed, LC-MS/MS analysis of protein pulldowns demonstrated an interaction between the SARS-CoV-2 RNA polymerase and the majority of human RNA exosome components. CRISPR/Cas9 introduction of nonsense mutations within EXOSC2 in Calu-3 cells reduced EXOSC2 protein expression, impeded SARS-CoV-2 replication and upregulated oligoadenylate synthase (OAS) genes, which have been linked to a successful immune response against SARS-CoV-2. Reduced EXOSC2 expression did not reduce cellular viability. OAS gene expression changes occurred independent of infection and in the absence of significant upregulation of other interferon-stimulated genes (ISGs). Targeted depletion or functional inhibition of EXOSC2 may be a safe and effective strategy to protect at-risk individuals against clinical COVID-19.