Associations between SARS-CoV-2 Infection or COVID-19 Vaccination and Human Milk Composition: A Multi-Omics Approach (preprint)

The risk of contracting SARS-CoV-2 via human milk-feeding is virtually non-existent. Adverse effects of COVID-19 vaccination for lactating individuals are not different from the general population, and no evidence has been found that their infants exhibit adverse effects. Yet, there remains substantial hesitation among this population globally regarding the safety of these vaccines. Herein we aimed to determine if compositional changes in milk occur following infection or vaccination, including any evidence of vaccine components. Using an extensive multi-omics approach, we found that compared to unvaccinated individuals SARS-CoV-2 infection was associated with significant compositional differences in 67 proteins, 385 lipids, and 13 metabolites. In contrast, COVID-19 vaccination was not associated with any changes in lipids or metabolites, although it was associated with changes in 13 or fewer proteins. Compositional changes in milk differed by vaccine. Changes following vaccination were greatest after 1-6 hours for the mRNA-based Moderna vaccine (8 changed proteins), 3 days for the mRNA-based Pfizer (4 changed proteins), and adenovirus-based Johnson and Johnson (13 changed proteins) vaccines. Proteins that changed after both natural infection and Johnson and Johnson vaccine were associated mainly with systemic inflammatory responses. In addition, no vaccine components were detected in any milk sample. Together, our data provide evidence of only minimal changes in milk composition due to COVID-19 vaccination, with much greater changes after natural SARS-CoV-2 infection.

Cardiovascular symptoms of PASC are associated with trace-level cytokines that affect the function of human pluripotent stem cell derived cardiomyocytes (preprint)

Globally, over 65 million individuals are estimated to suffer from post-acute sequelae of COVID-19 (PASC). A large number of individuals living with PASC experience cardiovascular symptoms (i.e. chest pain and heart palpitations) (PASC-CVS). The role of chronic inflammation in these symptoms, in particular in individuals with symptoms persisting for >1 year after SARS-CoV-2 infection, remains to be clearly defined. In this cross-sectional study, blood samples were obtained from three different sites in Australia from individuals with i) a resolved SARS-CoV-2 infection (and no persistent symptoms i.e. Recovered), ii) individuals with prolonged PASC-CVS and iii) SARS-CoV-2 negative individuals. Individuals with PASC-CVS, relative to Recovered individuals, had a blood transcriptomic signature associated with inflammation. This was accompanied by elevated levels of pro-inflammatory cytokines (IL-12, IL-1beta;, MCP-1 and IL-6) at approximately 18 months post-infection. These cytokines were present in trace amounts, such that they could only be detected with the use of novel nanotechnology. Importantly, these trace-level cytokines had a direct effect on the functionality of pluripotent stem cell derived cardiomyocytes in vitro. This effect was not observed in the presence of dexamethasone. Plasma proteomics demonstrated further differences between PASC-CVS and Recovered patients at approximately 18 months post-infection including enrichment of complement and coagulation associated proteins in those with prolonged cardiovascular symptoms. Together, these data provide a new insight into the role of chronic inflammation in PASC-CVS and present nanotechnology as a possible novel diagnostic approach for the condition.

Community level variability in Bronx COVID-19 hospitalizations associated with differing viral variant adaptive strategies during the second year of the pandemic. (preprint)

The Bronx, New York, exhibited unique peaks in the number of COVID-19 cases and hospitalizations compared to national trends. To determine which features of the SARS-CoV-2 virus might underpin this local disease epidemiology, we conducted a comprehensive analysis of the genomic epidemiology of the four dominant strains of SARS-CoV-2 (Alpha, Iota, Delta and Omicron) responsible for COVID-19 cases in the Bronx between March 2020 and January 2023. Genomic analysis revealed similar viral fitness for Alpha and Iota variants in the Bronx compared to nationwide data. However, Delta and Omicron variants had increased fitness within the borough. While the transmission dynamics of most variants in the Bronx corresponded with mutational fitness-based predictions of transmissibility, the Delta variant presented as an exception. Epidemiological modeling confirms Delta's advantages of higher transmissibility, and suggested pre-existing immunity within the community counteracted Delta virulence, contributing to unexpectedly low Bronx hospitalizations compared to preceding strains. There were few novel T-cell epitope mutations in Delta compared to Iota which suggests Delta had fewer immune escape mechanisms to subvert pre-existing immunity within the Bronx. The combination of epidemiological models and quantifying amino acid changes in T-cell and antibody epitopes also revealed an evolutionary trade-off between Alphas higher transmissibility and Iotas immune evasion, potentially explaining why the Bronx Iota variant remained dominant despite the introduction of the nationwide dominant Alpha variant. Together, our study demonstrates that localized analyses and integration of orthogonal community-level datasets can provide key insights into the mechanisms of transmission and immunity patterns associated with regional COVID-19 incidence and disease severity that may be missed when analyzing broader datasets.

Increased luminal area of large conducting airways in patients with COVID-19 and post-acute sequelae of COVID-19 A retrospective case-control study (preprint)

Background Coronavirus disease 2019 (COVID-19) is associated with enlarged luminal areas of large conducting airways. In 10--30% of patients with acute COVID-19 infection, symptoms persist for more than 4 weeks (referred to as post-acute sequelae of COVID-19, or PASC), and it is unknown if airway changes are associated with this persistence. Thus, we aim to investigate if luminal area of large conducting airways is different between PASC and COVID-19 patients, and healthy controls. Methods In this retrospective case-control study seventy-five patients with PASC (48 females) were age-, height-, and sex-matched to 75 individuals with COVID-19 and 75 healthy controls. Using three-dimensional digital reconstruction from computed tomography imaging, we measured luminal areas of seven conducting airways, including trachea, right and left main bronchi, bronchus intermediate, right and left upper lobe, and left lower lobe bronchi. Findings Airway luminal areas between COVID-19 and PASC groups were not different (p>0.66). There were no group differences in airway luminal area (PASC vs control) for trachea and right main bronchus. However, in the remaining five airways, airway luminal areas were 12% to 39% larger among PASC patients compared to controls (p<0.05). Interpretation Patients diagnosed with COVID-19 and PASC have greater airway luminal area in most large conducting airways compared to healthy controls. No differences in luminal area between patients with COVID-19 and PASC suggest persistence of changes or insufficient time for complete reversal of changes. Funding National Heart, Lung, and Blood Institute (F32HL154320 to JWS; 5R35HL139854 to MJJ); Postdoctoral Fellowship from the Natural Sciences and Engineering Research Council of Canada (AHR).

Compartment-Specific Antibody Correlates of Protection to SARS-CoV-2 Omicron in Macaques (preprint)

Antibodies represent a primary mediator of protection against respiratory viruses such as SARS-CoV-2. Serum neutralizing antibodies (NAbs) are often considered a primary correlate of protection. However, detailed antibody profiles including characterization of antibody functions in different anatomic compartments are not well understood. Here we show that antibody correlates of protection against SARS-CoV-2 challenge are different in systemic versus mucosal compartments in rhesus macaques. In serum, neutralizing antibodies were the strongest correlate of protection and were linked to Spike-specific binding antibodies and other extra-neutralizing antibody functions that create a larger protective network. In contrast, in bronchiolar lavage (BAL), antibody-dependent cellular phagocytosis (ADCP) proved the strongest correlate of protection rather than NAbs. Within BAL, ADCP was linked to mucosal Spike-specific IgG, IgA/secretory IgA, and Fc{gamma}-receptor binding antibodies. Our results support a model in which antibodies with different functions mediate protection at different anatomic sites. The correlation of ADCP and other Fc functional antibody responses with protection in BAL suggests that these antibody responses may be critical for protection against SARS-CoV-2 Omicron challenge in mucosa.

Development and validation of a federated learning framework for detection of subphenotypes of multisystem inflammatory syndrome in children (preprint)

Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe post-acute sequela of SARS-CoV-2 infection. The highly diverse clinical features of MIS-C necessities characterizing its features by subphenotypes for improved recognition and treatment. However, jointly identifying subphenotypes in multi-site settings can be challenging. We propose a distributed multi-site latent class analysis (dMLCA) approach to jointly learn MIS-C subphenotypes using data across multiple institutions. Methods We used data from the electronic health records (EHR) systems across nine U.S. childrens hospitals. Among the 3,549,894 patients, we extracted 864 patients < 21 years of age who had received a diagnosis of MIS-C during an inpatient stay or up to one day before admission. Using MIS-C conditions, laboratory results, and procedure information as input features for the patients, we applied our dMLCA algorithm and identified three MIS-C subphenotypes. As validation, we characterized and compared more granular features across subphenotypes. To evaluate the specificity of the identified subphenotypes, we further compared them with the general subphenotypes identified in the COVID-19 infected patients. Findings Subphenotype 1 (46.1%) represents patients with a mild manifestation of MIS-C not requiring intensive care, with minimal cardiac involvement. Subphenotype 2 (25.3%) is associated with a high risk of shock, cardiac and renal involvement, and an intermediate risk of respiratory symptoms. Subphenotype 3 (28.6%) represents patients requiring intensive care, with a high risk of shock and cardiac involvement, accompanied by a high risk of >4 organ system being impacted. Importantly, for hospital-specific clinical decision-making, our algorithm also revealed a substantial heterogeneity in relative proportions of these three subtypes across hospitals. Properly accounting for such heterogeneity can lead to accurate characterization of the subphenotypes at the patient-level. Interpretation Our identified three MIS-C subphenotypes have profound implications for personalized treatment strategies, potentially influencing clinical outcomes. Further, the proposed algorithm facilitates federated subphenotyping while accounting for the heterogeneity across hospitals.

Longitudinal study of immunity to SARS-CoV2 in Ocrelizumab-treated multiple sclerosis patients up to 2 years after COVID-19 vaccination (preprint)

Objectives: 1. To plot the trajectory of humoral and cellular immune responses to the primary (two-dose) COVID-19 mRNA series and the third/booster dose in B-cell-depleted multiple sclerosis (MS) patients up to 2 years post-vaccination; 2. to identify predictors of immune responses to vaccination; and 3. to assess the impact of intercurrent COVID-19 infections on SARS CoV-2-specific immunity. Methods: 60 Ocrelizumab-treated MS patients were enrolled from NYU (New York) and University of Colorado (Anschutz) MS Centers. Samples were collected pre-vaccination, and then 4, 12, 24, and 48 weeks post-primary series, and 4, 12, 24, and 48 weeks post-booster. Binding anti-Spike antibody responses were assessed with multiplex bead-based immunoassay (MBI) and electrochemiluminescence (Elecsys(C), Roche Diagnostics), and neutralizing antibody responses with live-virus immunofluorescence-based microneutralization assay. Spike-specific cellular responses were assessed with IFN{gamma}/IL-2 ELISpot (Invitrogen) and, in a subset, by sequencing complementary determining regions (CDR)-3 within T-cell receptors (Adaptive Biotechnologies). A linear mixed effect model was used to compare antibody and cytokine levels across time points. Multivariate analyses identified predictors of immune responses. Results: The primary vaccination induced an 11-208-fold increase in binding and neutralizing antibody levels and a 3-4-fold increase in IFN{gamma}/IL-2 responses, followed by a modest decline in antibody but not cytokine responses. Booster dose induced a further 3-5-fold increase in binding antibodies and 4-5-fold increase in IFN{gamma}/IL-2, which were maintained for up to 1 year. Infections had a variable impact on immunity. Interpretation: Humoral and cellular benefits of COVID-19 vaccination in B-cell-depleted MS patients were sustained for up to 2 years when booster doses were administered.

Nowcasting Reported COVID-19 Hospitalizations Using De-Identified, Aggregated Medical Insurance Claims Data (preprint)

We propose, implement, and evaluate a method for nowcasting the daily number of new COVID-19 hospitalizations, at the level of individual US states, based on de-identified, aggregated medical insurance claims data. Our analysis proceeds under a hypothetical scenario in which, during the Delta wave, states only report data on the first day of each month, and on this day, report COVID-19 hospitalization counts for each day in the previous month. In this hypothetical scenario (just as in reality), medical insurance claims data continues to be available daily. At the beginning of each month, we train a regression model, using all data available thus far, to predict hospitalization counts from medical insurance claims. We then use this model to nowcast the (unseen) values of COVID-19 hospitalization counts from medical insurance claims, at each day in the following month. Our analysis uses properly-versioned data, which would have been available in real-time, at the time predictions are produced. In spite of the difficulties inherent to real-time estimation (e.g., latency and backfill) and the complex dynamics behind COVID-19 hospitalizations themselves, we find overall that medical insurance claims can be an accurate predictor of hospitalization reports, with mean absolute errors typically around 0.4 hospitalizations per 100,000 people, i.e., proportion of variance explained around 75%. Perhaps more importantly, we find that nowcasts made using medical insurance claims can qualitatively capture the dynamics (upswings and downswings) of hospitalization waves, which are key features that inform public health decision-making.

Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx (preprint)

Facilitating large-scale, cross-institutional collaboration in biomedical machine learning projects requires a trustworthy and resilient federated learning (FL) environment to ensure that sensitive information such as protected health information is kept confidential. In this work, we introduce APPFLx, a low-code FL framework that enables the easy setup, configuration, and running of FL experiments across organizational and administrative boundaries while providing secure end-to-end communication, privacy-preserving functionality, and identity management. APPFLx is completely agnostic to the underlying computational infrastructure of participating clients. We demonstrate the capability of APPFLx as an easy-to-use framework for accelerating biomedical studies across institutions and healthcare systems while maintaining the protection of private medical data in two case studies: (1) predicting participant age from electrocardiogram (ECG) waveforms, and (2) detecting COVID-19 disease from chest radiographs. These experiments were performed securely across heterogeneous compute resources, including a mixture of on-premise high-performance computing and cloud computing, and highlight the role of federated learning in improving model generalizability and performance when aggregating data from multiple healthcare systems. Finally, we demonstrate that APPFLx serves as a convenient and easy-to-use framework for accelerating biomedical studies across institutions and healthcare system while maintaining the protection of private medical data.

Lack of association between HLA and asymptomatic SARS-CoV-2 infection (preprint)

Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B*15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B*15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the US (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B*15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified. These findings suggest that memory T-cell immunity to seasonal coronaviruses does not strongly influence the outcome of SARS-CoV-2 infection in unvaccinated individuals.

High-throughput ML-guided design of diverse single-domain antibodies against SARS-CoV-2 (preprint)

Treating rapidly evolving pathogenic diseases such as COVID-19 requires a therapeutic approach that accommodates the emergence of viral variants over time. Our machine learning (ML)-guided sequence design platform combines high-throughput experiments with ML to generate highly diverse single-domain antibodies (VHHs) that bind and neutralize SARS-CoV-1 and SARS-CoV-2. Crucially, the model, trained using binding data against early SARS-CoV variants, accurately captures the relationship between VHH sequence and binding activity across a broad swathe of sequence space. We discover ML-designed VHHs that exhibit considerable cross-reactivity and successfully neutralize targets not seen during training, including the Delta and Omicron BA.1 variants of SARS-CoV-2. Our ML-designed VHHs include thousands of variants 4-15 mutations from the parent sequence with significantly improved activity, demonstrating that ML-guided sequence design can successfully navigate vast regions of sequence space to unlock and future-proof potential therapeutics against rapidly evolving pathogens.

Assessment of the effectiveness of required weekly COVID-19 surveillance antigen testing at a university (preprint)

ObjectivesTo mitigate the COVID-19 pandemic, many institutions implemented a regimen of periodic required testing, irrespective of symptoms. The effectiveness of this"surveillance testing" requires assessment. MethodsI fit a zero-inflated negative binomial model to COVID-19 testing and case investigation data between 1 November 2020 and 15 May 2021, from young adult subjects in one community. I compared the duration of symptoms at time of specimen collection in those diagnosed via (1) surveillance testing at a university, (2) the same universitys student health services, and (3) all other testing venues. ResultsThe data comprised 2926 records: 393 from surveillance testing, 493 from student health service, and 2040 from other venues. About 65% of people with COVID-19 detected via surveillance testing were already symptomatic at time of specimen collection. Predicted mean duration of pre-testing symptoms was 1.7 days (95% CI 1.59 to 1.84) for the community, 1.81 days (95% CI 1.62 to 1.99) for surveillance, and 2 days (95% CI 1.83 to 2.16) for student health service. The modelled "inflated" proportions of asymptomatic subjects from the surveillance stream and the other/community stream were comparable (odds ratio 0.95, p = 0.7709). Comparing surveillance testing with the student health service, the proportion of "excess" zero symptom durations was signficantly higher in the former (Chi-square = 12.08, p = 0.0005) ConclusionsSurveillance testing at a university detected 393 people with COVID-19, but no earlier in their trajectory than similar-aged people detected in the broader community. This casts some doubt on the public health value of such programs, which tend to be labor-intensive and expensive. 2 Three-question summary boxO_ST_ABSWhat is the current understanding of this subject?C_ST_ABSAssessments of long-term operational effectiveness of COVID-19 "surveillance testing" have not been published. What does this report add to the literature?During the 2020-2021 academic year at one university, people with COVID-19 detected via compulsory weekly surveillance antigen testing were equally likely to be symptomatic at time of detection, and for just as long, as similar-aged people detected via testing venues in the community. What are the implications for public health practice?Surveillance testing programs during the pandemic consumed a large amount of time, money, and effort. In future respiratory pandemics, resources might be better devoted to other mitigation measures.

Antibody response to symptomatic infection with SARS-CoV-2 Omicron variant viruses, December 2021 to June 2022 (preprint)

To describe humoral immune responses to symptomatic SARS-CoV-2 infection, we assessed immunoglobulin G binding antibody levels using a commercial multiplex bead assay against SARS-CoV-2 ancestral spike protein receptor binding domain (RBD) and nucleocapsid protein (N). We measured binding antibody units per mL (BAU/mL) during acute illness within 5 days of illness onset and during convalescence in 105 ambulatory patients with laboratory-confirmed SARS-CoV-2 infection with Omicron variant viruses. Comparing acute- to convalescent phase antibody concentrations, geometric mean anti-N antibody concentrations increased 47-fold from 5.5 to 259 BAU/mL. Anti-RBD antibody concentrations increased 2.5-fold from 1258 to 3189 BAU/mL.

Cost-effective boosting allocations in the post-Omicron era of COVID-19 management (preprint)

BackgroundFollowing widespread exposure to Omicron variants, COVID-19 has transitioned to endemic circulation. Populations now have diverse infection and vaccination histories, resulting in heterogeneous immune landscapes. Careful consideration of vaccination is required through the post-Omicron phase of COVID-19 management to minimise disease burden. We assess the impact and cost-effectiveness of targeted COVID-19 vaccination strategies to support global vaccination recommendations. MethodsWe integrated immunological, transmission, clinical and cost-effectiveness models, and simulated populations with different characteristics and immune landscapes. We calculated the expected number of infections, hospitalisations and deaths for different vaccine scenarios. Costs (from a healthcare perspective) were estimated for exemplar country income level groupings in the Western Pacific Region. Results are reported as incremental costs and disability-adjusted life years averted compared to no additional vaccination. Parameter and stochastic uncertainty were captured through scenario and sensitivity analysis. FindingsAcross different population demographics and income levels, we consistently found that annual elder-targeted boosting strategies are most likely to be cost-effective or cost-saving, while paediatric programs are unlikely to be cost-effective. Results remained consistent while accounting for uncertainties in the epidemiological and economic models. Half-yearly boosting may only be cost-effective in higher income settings with older population demographics and higher cost-effectiveness thresholds. InterpretationThe seresults demonstrate the value of continued booster vaccinations to protect against severe COVID-19 disease outcomes across high and middle-income settings and show that the biggest health gains relative to vaccine costs are achieved by targeting older age-groups. FundingFunded by the World Health Organization. O_TEXTBOXResearch in context Evidence before this studyWith COVID-19 now globally endemic, populations exhibit varying levels of natural and vaccine-acquired immunity to SARS-CoV-2. With widespread, if variable, immunity resulting in reduced severity of COVID-19 disease, re-evaluation of the ongoing value of vaccination is required. COVID-19 vaccination strategies must consider the cost-effectiveness of gains from vaccination given prior immunity, and in the context of income and health system capacity to manage COVID-19 alongside other pressing concerns. Few articles examine cost-effectiveness of COVID-19 vaccination strategies in populations with diverse characteristics and waning hybrid immunity, though there is a large body of literature that considers some combination of these elements or focus on one particular country. Consensus is that allocating vaccine doses to older age groups and those at higher risk of severe disease is most beneficial, albeit assuming either only past natural immunity or no waning immunity. These studies have either not included a cost-effectiveness analysis or, where present, have typically assumed a base case zero-vaccination scenario. Added value of this studyWe consider the contemporary situation where populations have varying degrees of hybrid immunity resulting from both prior infection and vaccination, and where the relevant cost-effectiveness analysis considers only future primary and booster doses in the population. We describe multiple demographics, using exemplar older and younger populations, in conjunction with low to high past vaccination coverage, low to high past natural infection incidence, and low to high income levels. Under these settings, we determine the cost-effectiveness of a range of targeted boosting strategies (who, when, what). Implications of all the available evidenceOur study highlights how future COVID-19 booster doses targeted towards older age groups at risk of severe outcomes can be cost-effective or cost-saving in high-income settings with populations that have a higher proportion of individuals at risk. In younger, lower-resourced settings, annual boosting of older age groups may still be cost-effective or cost-saving in some scenarios. We consistently find that pediatric vaccination is not cost-effective. Given the benefits of vaccination, especially to reduce severe disease, we show the importance of ongoing global efforts to provide and equitably distribute vaccines and strengthen adult immunisation programs. C_TEXTBOX

Influenza vaccine effectiveness against hospitalized SARS-CoV-2 infection (preprint)

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSSome studies conducted before the Delta and Omicron variant-dominant periods have indicated that influenza vaccination provided protection against COVID-19 infection or hospitalization, but these results were limited by small study cohorts and a lack of comprehensive data on patient characteristics. No studies have examined this question during the Delta and Omicron periods (08/01/2021 to 2/22/2022). MethodsWe conducted a retrospective cohort study of influenza-vaccinated and unvaccinated patients in the Corewell Health East(CHE, formerly known as Beaumont Health), Corewell Health West(CHW, formerly known as Spectrum Health) and Michigan Medicine (MM) healthcare system during the Delta-dominant and Omicron-dominant periods. We used a test-negative, case-control analysis to assess the effectiveness of the influenza vaccine against hospitalized SARS-CoV-2 outcome in adults, while controlling for individual characteristics as well as pandameic severity and waning immunity of COVID-19 vaccine. ResultsThe influenza vaccination has shown to provided some protection against SARS-CoV-2 hospitalized outcome across three main healthcare systems. CHE site (odds ratio [OR]=0.73, vaccine effectiveness [VE]=27%, 95% confidence interval [CI]: [18-35], p<0.001), CHW site (OR=0.85, VE=15%, 95% CI: [6-24], p<0.001), MM (OR=0.50, VE=50%, 95% CI: [40-58], p <0.001) and overall (OR=0.75, VE=25%, 95% CI: [20-30], p <0.001). ConclusionThe influenza vaccine provides a small degree of protection against SARS-CoV-2 infection across our study sites.

Peripheral Transcriptomics in Acute and Long-Term Kidney Dysfunction in SARS-CoV2 Infection (preprint)

Background. Acute kidney injury (AKI) is common in hospitalized patients with SARS-CoV2 infection despite vaccination and leads to long-term kidney dysfunction. However, peripheral blood molecular signatures in AKI from COVID-19 and their association with long-term kidney dysfunction are yet unexplored. Methods. In patients hospitalized with SARS-CoV2, we performed bulk RNA sequencing using peripheral blood mononuclear cells (PBMCs). We applied linear models accounting for technical and biological variability on RNA-Seq data accounting for false discovery rate (FDR) and compared the functional enrichment and pathway results to a historical sepsis-AKI cohort. Finally, we evaluated the association of these signatures with long-term trends in kidney function. Results. Of 283 patients, 106 had AKI. After adjustment for sex, age, mechanical ventilation, and chronic kidney disease (CKD), we identified 2635 significant differential gene expressions at FDR<0.05. Top canonical pathways were EIF2 signaling, oxidative phosphorylation, mTOR signaling, and Th17 signaling, indicating mitochondrial dysfunction and endoplasmic reticulum (ER) stress. Comparison with sepsis associated AKI showed considerable overlap of key pathways (48.14%). Using follow-up estimated glomerular filtration rate (eGFR) measurements from 115 patients, we found that 164/2635 (6.2%) of the significantly differentiated genes were associated with overall decrease in long-term kidney function. The strongest associations were autophagy, renal impairment via fibrosis and cardiac structure/function. Conclusions. We show that AKI in SARS-CoV2 is a multifactorial process with mitochondrial dysfunction driven by ER stress whereas long-term kidney function decline is associated with cardiac structure and function, and immune dysregulation. Functional overlap with sepsis-AKI also highlights common signatures indicating generalizability in therapeutic approaches.

Evaluation of the neutralising antibody response in human and hamster sera against SARS-CoV-2 variants up to and including BA.2.86 using an authentic virus neutralisation assay (preprint)

New vaccines, therapeutics and immunity elicited by natural infection create evolutionary pressure on SARS-CoV-2 to evolve and adapt to evade vaccine-induced and infection-elicited immunity. Vaccine and therapeutics developers thus find themselves in an "arms race" with the virus. The ongoing assessment of emerging SARS-CoV-2 variants remains essential as the global community transitions from an emergency response to a long-term management plan. Here, we describe how an authentic virus neutralisation assay using low passage clinical virus isolates has been employed to monitor resistance of emerging virus variants to neutralising antibodies from humans and experimentally infected hamsters. Sera and plasma from people who received three doses of a vaccine as well as those who received a bivalent booster were assessed against SARS-CoV-2 variants, up to and including BA.2.86. Contemporary or recent virus variants showed substantial resistance to neutralisation by antibodies from those who had received three vaccines but were still effectively neutralised by antibodies from individuals who had received a bivalent booster (ancestral/BA.1). Convalescent sera from hamsters that had been experimentally infected with one of seven virus variants (ancestral, BA.1, BA.4, BA.5.2.1, XBB.1.5, XBB.1.16, XBB.2.3) were also tested here. The most contemporary variant, BA.2.86, was effectively neutralised by sera from hamsters infected with XBB.1.5 and XBB.1.16 but it was not neutralised by sera from those infected with BA.5.2.1. These data support the recommendations given by the WHO that a new vaccine was required and should consist of an XBB sub-lineage antigen.

Anti-SARS-CoV-2 Antibody Levels Associated with COVID-19 Protection in Outpatients Tested for SARS-CoV-2, US Flu VE Network, October 2021 to June 2022 (preprint)

BackgroundWe assessed the association between antibody concentration [≤]5 days of symptom onset and COVID-19 illness among patients enrolled in a test-negative study MethodsFrom October 2021[boxh]June 2022, study sites in seven states enrolled and tested respiratory specimens from patients of all ages presenting with acute respiratory illness for SARS-CoV-2 infection using rRT-PCR. In blood specimens, we measured concentration of anti- SARS-CoV-2 antibodies against the ancestral strain spike protein receptor binding domain (RBD) and nucleocapsid (N) antigens in standardized binding antibody units (BAU/mL). Percent reduction in odds of symptomatic COVID-19 by anti-RBD antibody was estimated using logistic regression modeled as (1-adjusted odds ratio of COVID-19)x100, adjusting for COVID-19 vaccination status, age, site, and high-risk exposure. ResultsA total of 662 (33%) of 2,018 symptomatic patients tested positive for acute SARS- CoV-2 infection. During the Omicron-predominant period, geometric mean anti-RBD binding antibody concentrations measured 823 BAU/mL (95%CI:690[boxh]981) among COVID-19 case- patients versus 1,189 BAU/mL (95%CI:1,050[boxh]1,347) among SARS-CoV-2 test-negative patients. In the adjusted logistic regression, increasing levels of anti-RBD antibodies were associated with reduced odds of COVID-19 for both Delta and Omicron infections. ConclusionHigher anti-RBD antibodies in patients were associated with protection against symptomatic COVID-19 during emergence of SARS-CoV-2 Delta and Omicron variants.