Paediatric safety assessment of BNT162b2 vaccination in a multistate hospital-based electronic health record system in the USA: a retrospective analysis.

BACKGROUND: The emergency use authorisation of BNT162b2 (tozinameran; Comirnaty, Pfizer-BioNTech) for children aged 5-17 years has resulted in rapid vaccination in the paediatric population. However, there are few studies of adverse events associated with vaccination in children. The aim of this study was to systematically assess the adverse events of two-dose BNT162b2 vaccination in the paediatric population. METHODS: We conducted a retrospective analysis of patient electronic health records (EHRs) of children aged 5-17 years who received the primary two-dose series of the BNT162b2 vaccine between Jan 5, 2021, and Aug 5, 2022, at the Mayo Clinic Health System (MN, FL, AZ, IA, and WI), USA. Using natural language processing, we automatically curated adverse events reported by physicians in EHR clinical notes before and after vaccination. To determine significant adverse events after BNT162b2 vaccination, we calculated risk differences, which was defined as the percentage difference between the rate of children with an adverse event after a vaccine dose and the baseline rate of children with an adverse event before vaccination. 95% CIs and p values were calculated using the Miettinen and Nurminen score method. FINDINGS: 56 436 individuals aged 5-17 years (20 227 aged 5-11 years and 36 209 aged 12-17 years) with EHRs in the Mayo Clinic Health Systems were included in the study. Overall, the reporting of adverse events remained low in passive surveillance. Serious adverse events were rare after the first and second doses of BNT162b2, with rates of anaphylaxis (six [0·01%] of 56 436), myocarditis (five [0·01%]), and pericarditis (three [0·01%]) consistent with previous studies. Among the 20 227 5-11-year-olds, there were increased risks of fatigue (58 after second dose vs 41 before first dose; risk difference [RD]dose2 0·08% [95% CI -0·01 to 0·18], p=0·044) and fever (104 after second dose vs 77 before first dose; RDdose2 0·13% [0·00 to 0·27], p=0·022) after the second dose. Among the 36 209 12-17-year-olds, there were increased risks of arthralgia (69 after second dose vs 48 before first dose; RDdose2 0·06% [-0·00 to 0·12], p=0·026), chills (58 after second dose vs 40 before first dose; RDdose2 0·05% [-0·00 to 0·11], p=0·034), and myalgia (96 after second dose vs 73 before first dose; RDdose2 0·06% [-0·01 to 0·14], p=0·038) after the second dose. Although the overall incidence was low, there was an increased risk of myocarditis in males aged 12-17 years after the second dose (five after second dose vs zero before first dose; RDdose2 0·03% [0·01 to 0·07], p=0·013), with median age being 15 years (IQR 14 to 16). INTERPRETATION: Overall, this data suggests that vaccination with BNT162b2 in the paediatric population is generally safe and well-tolerated. Further research is warranted to investigate the basis for the increased risk of myocarditis in adolescent males. Additionally, further studies are needed to confirm whether the findings in our study population apply to the whole vaccinated paediatric population. FUNDING: nference.

Durability analysis of the highly effective mRNA-1273 vaccine against COVID-19.

COVID-19 vaccines are effective, but breakthrough infections have been increasingly reported. We conducted a test-negative case-control study to assess the durability of protection against symptomatic infection after vaccination with mRNA-1273. We fit conditional logistic regression (CLR) models stratified on residential county and calendar date of SARS-CoV-2 PCR testing to assess the association between the time elapsed since vaccination and the odds of symptomatic infection, adjusted for several covariates. There were 2,364 symptomatic individuals who had a positive SARS-CoV-2 PCR test after full vaccination with mRNA-1273 ("cases") and 12,949 symptomatic individuals who contributed 15,087 negative tests after full vaccination ("controls"). The odds of symptomatic infection were significantly higher 250 days after full vaccination compared to the date of full vaccination (Odds Ratio [OR]: 2.47, 95% confidence interval [CI]: 1.19-5.13). The odds of non-COVID-19 associated hospitalization and non-COVID-19 pneumonia (negative control outcomes) remained relatively stable over the same time interval (Day 250 ORNon-COVID Hospitalization: 0.68, 95% CI: 0.47-1.0; Day 250 ORNon-COVID Pneumonia: 1.11, 95% CI: 0.24-5.2). The odds of symptomatic infection remained significantly lower almost 300 days after the first mRNA-1273 dose as compared to 4 days after the first dose, when immune protection approximates the unvaccinated state (OR: 0.26, 95% CI: 0.17-0.39). Low rates of COVID-19 associated hospitalization or death in this cohort precluded analyses of these severe outcomes. In summary, mRNA-1273 robustly protected against symptomatic SARS-CoV-2 infection at least 8 months after full vaccination, but the degree of protection waned over this time period.

Third dose vaccination with mRNA-1273 or BNT162b2 vaccines improves protection against SARS-CoV-2 infection.

As of 2021 November 29, booster vaccination against SARS-CoV-2 infection has been recommended for all individuals aged 18 years and older in the United States. A key reason for this recommendation is the expectation that a booster vaccine dose can alleviate observed waning of vaccine effectiveness (VE). Although initial reports of booster effectiveness have been positive, the level of protection from booster vaccination is unclear. We conducted two studies to assess the impact of booster vaccination, with BNT162b2 or mRNA-1273, on the incidence of SARS-CoV-2 infection between August and December 2021. We first compared SARS-CoV-2 infection incidence in cohorts of 3-dose vaccine recipients to incidence in matched cohorts of 2-dose vaccine recipients (cohort size = 24,539 for BNT162b2 and 14,004 for mRNA-1273). Additionally, we applied a test-negative study design to compare the level of protection against symptomatic infection in 3-dose recipients to that observed in recent 2-dose primary vaccine series recipients. The 3-dose recipients experienced a significantly lower incidence rate of SARS-CoV-2 infection than the matched 2-dose cohorts (BNT162b2 Incidence Rate Ratio: 0.11, 95% CI: 0.09 to 0.13 and mRNA-1273 IRR: 0.11, 95% CI: 0.08 to 0.15). Results from the test-negative study showed the third vaccine dose mitigated waning of VE, with the risk of symptomatic infection in 3-dose recipients being comparable to that observed 7 to 73 days after the primary vaccine series. These results show that 3-dose vaccine regimens with BNT162b2 or mRNA-1273 are effective at reducing SARS-CoV-2 infection and support the widespread administration of booster vaccine doses.

Quantifying the immunological distinctiveness of emerging SARS-CoV-2 variants in the context of prior regional herd exposure.

The COVID-19 pandemic has seen the persistent emergence of immune-evasive SARS-CoV-2 variants under the selection pressure of natural and vaccination-acquired immunity. However, it is currently challenging to quantify how immunologically distinct a new variant is compared to all the prior variants to which a population has been exposed. Here, we define "Distinctiveness" of SARS-CoV-2 sequences based on a proteome-wide comparison with all prior sequences from the same geographical region. We observe a correlation between Distinctiveness relative to contemporary sequences and future change in prevalence of a newly circulating lineage (Pearson r = 0.75), suggesting that the Distinctiveness of emergent SARS-CoV-2 lineages is associated with their epidemiological fitness. We further show that the average Distinctiveness of sequences belonging to a lineage, relative to the Distinctiveness of other sequences that occur at the same place and time (n = 944 location/time data points), is predictive of future increases in prevalence (Area Under the Curve, AUC = 0.88 [95% confidence interval 0.86 to 0.90]). By assessing the Delta variant in India versus Brazil, we show that the same lineage can have different Distinctiveness-contributing positions in different geographical regions depending on the other variants that previously circulated in those regions. Finally, we find that positions that constitute epitopes contribute disproportionately (20-fold higher than the average position) to Distinctiveness. Overall, this study suggests that real-time assessment of new SARS-CoV-2 variants in the context of prior regional herd exposure via Distinctiveness can augment genomic surveillance efforts.

SARS-CoV-2 and influenza coinfection throughout the COVID-19 pandemic: an assessment of coinfection rates, cohort characteristics, and clinical outcomes.

Case reports of patients infected with COVID-19 and influenza virus ("flurona") have raised questions around the prevalence and severity of coinfection. Using data from HHS Protect Public Data Hub, NCBI Virus, and CDC FluView, we analyzed trends in SARS-CoV-2 and influenza hospitalized coinfection cases and strain prevalences. We also characterized coinfection cases across the Mayo Clinic Enterprise from January 2020 to April 2022. We compared expected and observed coinfection case counts across different waves of the pandemic and assessed symptoms and outcomes of coinfection and COVID-19 monoinfection cases after propensity score matching on clinically relevant baseline characteristics. From both the Mayo Clinic and nationwide datasets, the observed coinfection rate for SARS-CoV-2 and influenza has been higher during the Omicron era (2021 December 14 to 2022 April 2) compared to previous waves, but no higher than expected assuming infection rates are independent. At the Mayo Clinic, only 120 coinfection cases were observed among 197,364 SARS-CoV-2 cases. Coinfected patients were relatively young (mean age: 26.7 years) and had fewer serious comorbidities compared to monoinfected patients. While there were no significant differences in 30-day hospitalization, ICU admission, or mortality rates between coinfected and matched COVID-19 monoinfection cases, coinfection cases reported higher rates of symptoms including congestion, cough, fever/chills, headache, myalgia/arthralgia, pharyngitis, and rhinitis. While most coinfection cases observed at the Mayo Clinic occurred among relatively healthy individuals, further observation is needed to assess outcomes among subpopulations with risk factors for severe COVID-19 such as older age, obesity, and immunocompromised status.

Expanding repertoire of SARS-CoV-2 deletion mutations contributes to evolution of highly transmissible variants.

The emergence of highly transmissible SARS-CoV-2 variants and vaccine breakthrough infections globally mandated the characterization of the immuno-evasive features of SARS-CoV-2. Here, we systematically analyzed 2.13 million SARS-CoV-2 genomes from 188 countries/territories (up to June 2021) and performed whole-genome viral sequencing from 102 COVID-19 patients, including 43 vaccine breakthrough infections. We identified 92 Spike protein mutations that increased in prevalence during at least one surge in SARS-CoV-2 test positivity in any country over a 3-month window. Deletions in the Spike protein N-terminal domain were highly enriched for these 'surge-associated mutations' (Odds Ratio = 14.19, 95% CI 6.15-32.75, p value = 3.41 × 10-10). Based on a longitudinal analysis of mutational prevalence globally, we found an expanding repertoire of Spike protein deletions proximal to an antigenic supersite in the N-terminal domain that may be one of the key contributors to the evolution of highly transmissible variants. Finally, we generated clinically annotated SARS-CoV-2 whole genome sequences from 102 patients and identified 107 unique mutations, including 78 substitutions and 29 deletions. In five patients, we identified distinct deletions between residues 85-90, which reside within a linear B cell epitope. Deletions in this region arose contemporaneously on a diverse background of variants across the globe since December 2020. Overall, our findings based on genomic-epidemiology and clinical surveillance suggest that the genomic deletion of dispensable antigenic regions in SARS-CoV-2 may contribute to the evasion of immune responses and the evolution of highly transmissible variants.

Inference from longitudinal laboratory tests characterizes temporal evolution of COVID-19-associated coagulopathy (CAC).

Temporal inference from laboratory testing results and triangulation with clinical outcomes extracted from unstructured electronic health record (EHR) provider notes is integral to advancing precision medicine. Here, we studied 246 SARS-CoV-2 PCR-positive (COVIDpos) patients and propensity-matched 2460 SARS-CoV-2 PCR-negative (COVIDneg) patients subjected to around 700,000 lab tests cumulatively across 194 assays. Compared to COVIDneg patients at the time of diagnostic testing, COVIDpos patients tended to have higher plasma fibrinogen levels and lower platelet counts. However, as the infection evolves, COVIDpos patients distinctively show declining fibrinogen, increasing platelet counts, and lower white blood cell counts. Augmented curation of EHRs suggests that only a minority of COVIDpos patients develop thromboembolism, and rarely, disseminated intravascular coagulopathy (DIC), with patients generally not displaying platelet reductions typical of consumptive coagulopathies. These temporal trends provide fine-grained resolution into COVID-19 associated coagulopathy (CAC) and set the stage for personalizing thromboprophylaxis.

On the Origins of Omicron's Unique Spike Gene Insertion.

The emergence of a heavily mutated SARS-CoV-2 variant (Omicron; Pango lineage B.1.1.529 and BA sublineages) and its rapid spread to over 75 countries raised a global public health alarm. Characterizing the mutational profile of Omicron is necessary to interpret its clinical phenotypes which are shared with or distinctive from those of other SARS-CoV-2 variants. We compared the mutations of the initially circulating Omicron variant (now known as BA.1) with prior variants of concern (Alpha, Beta, Gamma, and Delta), variants of interest (Lambda, Mu, Eta, Iota, and Kappa), and ~1500 SARS-CoV-2 lineages constituting ~5.8 million SARS-CoV-2 genomes. Omicron's Spike protein harbors 26 amino acid mutations (23 substitutions, 2 deletions, and 1 insertion) that are distinct compared to other variants of concern. While the substitution and deletion mutations appeared in previous SARS-CoV-2 lineages, the insertion mutation (ins214EPE) was not previously observed in any other SARS-CoV-2 lineage. Here, we consider and discuss various mechanisms through which the nucleotide sequence encoding for ins214EPE could have been acquired, including local duplication, polymerase slippage, and template switching. Although we are not able to definitively determine the mechanism, we highlight the plausibility of template switching. Analysis of the homology of the inserted nucleotide sequence and flanking regions suggests that this template-switching event could have involved the genomes of SARS-CoV-2 variants (e.g., the B.1.1 strain), other human coronaviruses that infect the same host cells as SARS-CoV-2 (e.g., HCoV-OC43 or HCoV-229E), or a human transcript expressed in a host cell that was infected by the Omicron precursor.

Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study.

BACKGROUND: COVID-19 is a multi-system disorder with high variability in clinical outcomes among patients who are admitted to hospital. Although some cytokines such as interleukin (IL)-6 are believed to be associated with severity, there are no early biomarkers that can reliably predict patients who are more likely to have adverse outcomes. Thus, it is crucial to discover predictive markers of serious complications. METHODS: In this retrospective cohort study, we analysed samples from 455 participants with COVID-19 who had had a positive SARS-CoV-2 RT-PCR result between April 14, 2020, and Dec 1, 2020 and who had visited one of three Mayo Clinic sites in the USA (Minnesota, Arizona, or Florida) in the same period. These participants were assigned to three subgroups depending on disease severity as defined by the WHO ordinal scale of clinical improvement (outpatient, severe, or critical). Our control cohort comprised of 182 anonymised age-matched and sex-matched plasma samples that were available from the Mayo Clinic Biorepository and banked before the COVID-19 pandemic. We did a deep profiling of circulatory cytokines and other proteins, lipids, and metabolites from both cohorts. Most patient samples were collected before, or around the time of, hospital admission, representing ideal samples for predictive biomarker discovery. We used proximity extension assays to quantify cytokines and circulatory proteins and tandem mass spectrometry to measure lipids and metabolites. Biomarker discovery was done by applying an AutoGluon-tabular classifier to a multiomics dataset, producing a stacked ensemble of cutting-edge machine learning algorithms. Global proteomics and glycoproteomics on a subset of patient samples with matched pre-COVID-19 plasma samples was also done. FINDINGS: We quantified 1463 cytokines and circulatory proteins, along with 902 lipids and 1018 metabolites. By developing a machine-learning-based prediction model, a set of 102 biomarkers, which predicted severe and clinical COVID-19 outcomes better than the traditional set of cytokines, were discovered. These predictive biomarkers included several novel cytokines and other proteins, lipids, and metabolites. For example, altered amounts of C-type lectin domain family 6 member A (CLEC6A), ether phosphatidylethanolamine (P-18:1/18:1), and 2-hydroxydecanoate, as reported here, have not previously been associated with severity in COVID-19. Patient samples with matched pre-COVID-19 plasma samples showed similar trends in muti-omics signatures along with differences in glycoproteomics profile. INTERPRETATION: A multiomic molecular signature in the plasma of patients with COVID-19 before being admitted to hospital can be exploited to predict a more severe course of disease. Machine learning approaches can be applied to highly complex and multidimensional profiling data to reveal novel signatures of clinical use. The absence of validation in an independent cohort remains a major limitation of the study. FUNDING: Eric and Wendy Schmidt.

SARS-CoV-2 and influenza coinfection throughout the COVID-19 pandemic: an assessment of coinfection rates, cohort characteristics, and clinical outcomes

Case reports of patients infected with COVID-19 and influenza virus (“flurona”) have raised questions around the prevalence and severity of coinfection. Using data from HHS Protect Public Data Hub, NCBI Virus, and CDC FluView, we analyzed trends in SARS-CoV-2 and influenza hospitalized coinfection cases and strain prevalences. We also characterized coinfection cases across the Mayo Clinic Enterprise from January 2020 to April 2022. We compared expected and observed coinfection case counts across different waves of the pandemic and assessed symptoms and outcomes of coinfection and COVID-19 monoinfection cases after propensity score matching on clinically relevant baseline characteristics. From both the Mayo Clinic and nationwide datasets, the observed coinfection rate for SARS-CoV-2 and influenza has been higher during the Omicron era (2021 December 14 to 2022 April 2) compared to previous waves, but no higher than expected assuming infection rates are independent. At the Mayo Clinic, only 120 coinfection cases were observed among 197,364 SARS-CoV-2 cases. Coinfected patients were relatively young (mean age: 26.7 years) and had fewer serious comorbidities compared to monoinfected patients. While there were no significant differences in 30-day hospitalization, ICU admission, or mortality rates between coinfected and matched COVID-19 monoinfection cases, coinfection cases reported higher rates of symptoms including congestion, cough, fever/chills, headache, myalgia/arthralgia, pharyngitis, and rhinitis. While most coinfection cases observed at the Mayo Clinic occurred among relatively healthy individuals, further observation is needed to assess outcomes among subpopulations with risk factors for severe COVID-19 such as older age, obesity, and immunocompromised status.

Durability analysis of the highly effective BNT162b2 vaccine against COVID-19.

COVID-19 vaccines are effective, but breakthrough infections have been increasingly reported. We conducted a test-negative case-control study to assess the durability of protection after full vaccination with BNT162b2 against polymerase chain reaction (PCR)-confirmed symptomatic SARS-CoV-2 infection, in a national medical practice from January 2021 through January 2022. We fit conditional logistic regression (CLR) models stratified on residential county and calendar time of testing to assess the association between time elapsed since vaccination and the odds of symptomatic infection or non-COVID-19 hospitalization (negative control), adjusted for several covariates. There were 5,985 symptomatic individuals with a positive test after full vaccination with BNT162b2 (cases) and 32,728 negative tests contributed by 27,753 symptomatic individuals after full vaccination (controls). The adjusted odds of symptomatic infection were higher 250 days after full vaccination versus at the date of full vaccination (Odds Ratio [OR]: 3.62, 95% CI: 2.52 to 5.20). The odds of infection were still lower 285 days after the first BNT162b2 dose as compared to 4 days after the first dose (OR: 0.50, 95% CI: 0.37 to 0.67), when immune protection approximates the unvaccinated status. Low rates of COVID-19 associated hospitalization or death in this cohort precluded analyses of these severe outcomes. The odds of non-COVID-19 associated hospitalization (negative control) decreased with time since vaccination, suggesting a possible underestimation of waning protection by this approach due to confounding factors. In summary, BNT162b2 strongly protected against symptomatic SARS-CoV-2 infection for at least 8 months after full vaccination, but the degree of protection waned significantly over this period.

Surveillance of Safety of 3 Doses of COVID-19 mRNA Vaccination Using Electronic Health Records.

Importance: Recent reports on waning of COVID-19 vaccine-induced immunity have led to the approval and rollout of additional doses and booster vaccinations. Individuals at increased risk of SARS-CoV-2 infection are receiving additional vaccine doses in addition to the regimen that was tested in clinical trials. Risks and adverse event profiles associated with additional vaccine doses are currently not well understood. Objective: To evaluate the safety of third-dose vaccination with US Food and Drug Administration (FDA)-approved COVID-19 mRNA vaccines. Design, Setting, and Participants: This cohort study was conducted using electronic health record (EHR) data from December 2020 to October 2021 from the multistate Mayo Clinic Enterprise. Participants included all 47 999 individuals receiving 3-dose COVID-19 mRNA vaccines within the study setting who met study inclusion criteria. Participants were divided into 2 cohorts by vaccine brand administered and served as their own control groups, with no comparison made between cohorts. Data were analyzed from September through November 2021. Exposures: Three doses of an FDA-authorized COVID-19 mRNA vaccine, BNT162b2 or mRNA-1273. Main Outcomes and Measures: Vaccine-associated adverse events were assessed via EHR report. Adverse event risk was quantified using the percentage of study participants who reported the adverse event within 14 days after each vaccine dose and during a 14-day control period, immediately preceding the first vaccine dose. Results: Among 47 999 individuals who received 3-dose COVID-19 mRNA vaccines, 38 094 individuals (21 835 [57.3%] women; median [IQR] age, 67.4 [52.5-76.5] years) received BNT162b2 (79.4%) and 9905 individuals (5099 [51.5%] women; median [IQR] age, 67.7 [59.5-73.9] years) received mRNA-1273 (20.6%). Reporting of severe adverse events remained low after the third vaccine dose, with rates of pericarditis (0.01%; 95% CI, 0%-0.02%), anaphylaxis (0%; 95% CI, 0%-0.01%), myocarditis (0%; 95% CI, 0%-0.01%), and cerebral venous sinus thrombosis (no individuals) consistent with results from earlier studies. Significantly more individuals reported low-severity adverse events after the third dose compared with after the second dose, including fatigue (2360 individuals [4.92%] vs 1665 individuals [3.47%]; P < .001), lymphadenopathy (1387 individuals [2.89%] vs 995 individuals [2.07%]; P < .001), nausea (1259 individuals [2.62%] vs 979 individuals [2.04%]; P < .001), headache (1185 individuals [2.47%] vs 992 individuals [2.07%]; P < .001), arthralgia (1019 individuals [2.12%] vs 816 individuals [1.70%]; P < .001), myalgia (956 individuals [1.99%] vs 784 individuals [1.63%]; P < .001), diarrhea (817 individuals [1.70%] vs 595 individuals [1.24%]; P < .001), fever (533 individuals [1.11%] vs 391 individuals [0.81%]; P < .001), vomiting (528 individuals [1.10%] vs 385 individuals [0.80%]; P < .001), and chills (224 individuals [0.47%] vs 175 individuals [0.36%]; P = .01). Conclusions and Relevance: This study found that although third-dose vaccination against SARS-CoV-2 infection was associated with increased reporting of low-severity adverse events, risk of severe adverse events remained comparable with risk associated with the standard 2-dose regime. These findings suggest the safety of third vaccination doses in individuals who were eligible for booster vaccination at the time of this study.

Genetic alteration of human MYH6 is mimicked by SARS-CoV-2 polyprotein: mapping viral variants of cardiac interest.

Acute cardiac injury has been observed in a subset of COVID-19 patients, but the molecular basis for this clinical phenotype is unknown. It has been hypothesized that molecular mimicry may play a role in triggering an autoimmune inflammatory reaction in some individuals after SARS-CoV-2 infection. Here we investigate if linear peptides contained in proteins that are primarily expressed in the heart also occur in the SARS-CoV-2 proteome. Specifically, we compared the library of 136,704 8-mer peptides from 144 human proteins (including splicing variants) to 9926 8-mers from all the viral proteins in the reference SARS-CoV-2 proteome. No 8-mers were exactly identical between the reference human proteome and the reference SARS-CoV-2 proteome. However, there were 45 8-mers that differed by only one amino acid when compared to the reference SARS-CoV-2 proteome. Interestingly, analysis of protein-coding mutations from 141,456 individuals showed that one of these 8-mers from the SARS-CoV-2 Replicase polyprotein 1a/1ab (KIALKGGK) is identical to an MYH6 peptide encoded by the c.5410 C > A (Q1804K) genetic variation, which has been observed at low prevalence in Africans/African Americans (0.08%), East Asians (0.3%), South Asians (0.06%), and Latino/Admixed Americans (0.003%). Furthermore, analysis of 4.85 million SARS-CoV-2 genomes from over 200 countries shows that viral evolution has already resulted in 20 additional 8-mer peptides that are identical to human heart-enriched proteins encoded by reference sequences or genetic variants. Whether such mimicry contributes to cardiac inflammation during or after COVID-19 illness warrants further experimental evaluation. We suggest that SARS-CoV-2 variants harboring peptides identical to human cardiac proteins should be investigated as "viral variants of cardiac interest".

High diversity in Delta variant across countries revealed by genome-wide analysis of SARS-CoV-2 beyond the Spike protein.

The highly contagious Delta variant of SARS-CoV-2 has become a prevalent strain globally and poses a public health challenge around the world. While there has been extensive focus on understanding the amino acid mutations in the Delta variant's Spike protein, the mutational landscape of the rest of the SARS-CoV-2 proteome (25 proteins) remains poorly understood. To this end, we performed a systematic analysis of mutations in all the SARS-CoV-2 proteins from nearly 2 million SARS-CoV-2 genomes from 176 countries/territories. Six highly prevalent missense mutations in the viral life cycle-associated Membrane (I82T), Nucleocapsid (R203M, D377Y), NS3 (S26L), and NS7a (V82A, T120I) proteins are almost exclusive to the Delta variant compared to other variants of concern (mean prevalence across genomes: Delta = 99.74%, Alpha = 0.06%, Beta = 0.09%, and Gamma = 0.22%). Furthermore, we find that the Delta variant harbors a more diverse repertoire of mutations across countries compared to the previously dominant Alpha variant. Overall, our study underscores the high diversity of the Delta variant between countries and identifies a list of amino acid mutations in the Delta variant's proteome for probing the mechanistic basis of pathogenic features such as high viral loads, high transmissibility, and reduced susceptibility against neutralization by vaccines.

Comparative effectiveness of mRNA-1273 and BNT162b2 against symptomatic SARS-CoV-2 infection.

BACKGROUND: mRNA coronavirus disease 2019 (COVID-19) vaccines are safe and effective, but increasing reports of breakthrough infections highlight the need to vigilantly monitor and compare the effectiveness of these vaccines. METHODS: We retrospectively compared protection against symptomatic infection conferred by mRNA-1273 and BNT162b2 at Mayo Clinic sites from December 2020 to September 2021. We used a test-negative case-control design to estimate vaccine effectiveness (VE) and to compare the odds of symptomatic infection after full vaccination with mRNA-1273 versus BNT162b2, while adjusting for age, sex, race, ethnicity, geography, comorbidities, and calendar time of vaccination and testing. FINDINGS: Both vaccines were highly effective over the study duration (VEmRNA-1273: 84.1%, 95% confidence interval [CI]: 81.6%-86.2%; VEBNT162b2: 75.6%, 95% CI: 72.2%-78.7%), but their effectiveness was reduced during July-September (VEmRNA-1273: 75.6%, 95% CI: 70.1%-80%; VEBNT162b2: 63.5%, 95% CI: 55.8%-69.9%) as compared to December-May (VEmRNA-1273: 93.7%, 95% CI: 90.4%-95.9%; VEBNT162b2: 85.7%, 95% CI: 81.4%-88.9%). Adjusted for demographic characteristics, clinical comorbidities, time of vaccination, and time of testing, the odds of experiencing a symptomatic breakthrough infection were lower after full vaccination with mRNA-1273 than with BNT162b2 (odds ratio: 0.60; 95% CI: 0.55-0.67). CONCLUSIONS: Both mRNA-1273 and BNT162b2 strongly protect against symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. It is imperative to continue monitoring and comparing available vaccines over time and with respect to emerging variants to inform public and global health decisions. FUNDING: This study was funded by nference.

Intravenous bamlanivimab use associates with reduced hospitalization in high-risk patients with mild to moderate COVID-19.

BACKGROUNDClinical data to support the use of bamlanivimab for the treatment of outpatients with mild to moderate coronavirus disease-19 (COVID-19) are needed.METHODS2335 Patients who received single-dose bamlanivimab infusion between November 12, 2020, and February 17, 2021, were compared with a propensity-matched control of 2335 untreated patients with mild to moderate COVID-19 at Mayo Clinic facilities across 4 states. The primary outcome was the rate of hospitalization at days 14, 21, and 28.RESULTSThe median age of the population was 63 years; 47.3% of the bamlanivimab-treated cohort were 65 years or more; 49.3% were female and 50.7% were male. High-risk characteristics included hypertension (54.2%), BMI greater than or equal to 35 (32.4%), diabetes mellitus (26.5%), chronic lung disease (25.1%), malignancy (16.6%), and renal disease (14.5%). Patients who received bamlanivimab had lower all-cause hospitalization rates at days 14 (1.5% vs. 3.5%; risk ratio [RR], 0.41), 21 (1.9% vs. 3.9%; RR, 0.49), and 28 (2.5% vs. 3.9%; RR, 0.63). Secondary exploratory outcomes included lower intensive care unit (ICU) admission rates at days 14 (0.14% vs. 1%; RR, 0.14), 21 (0.25% vs.1%; RR, 0.25), and 28 (0.56% vs.1.1%; RR. 0.51) and lower all-cause mortality at days 14 (0% vs. 0.33%), 21 (0.05% vs. 0.4%; RR,0.13), and 28 (0.11% vs. 0.44%; RR, 0.26). Adverse events were uncommon with bamlanivimab, occurring in 19 of 2355 patients, and were most commonly fever (n = 6), nausea (n = 5), and lightheadedness (n = 3).CONCLUSIONSAmong high-risk patients with mild to moderate COVID-19, treatment with bamlanivimab was associated with a statistically significant lower rate of hospitalization, ICU admission, and mortality compared with usual care.FUNDINGMayo Clinic.

Casirivimab-Imdevimab treatment is associated with reduced rates of hospitalization among high-risk patients with mild to moderate coronavirus disease-19.

BACKGROUND: Real-world clinical data to support the use of casirivimab-imdevimab for the treatment of outpatients with mild to moderate coronavirus disease-19 (COVID-19) is needed. This study aimed to assess the outcomes of casirivimab-imdevimab treatment of mild to moderate COVID-19. METHODS: A retrospective cohort of 696 patients who received casirivimab-imdevimab between December 4, 2020 and April 9, 2021 was compared to a propensity-matched control of 696 untreated patients with mild to moderate COVID-19 at Mayo Clinic sites in Arizona, Florida, Minnesota, and Wisconsin. Primary outcome was rate of hospitalization at days 14, 21 and 28 after infusion. FINDINGS: The median age of the antibody-treated cohort was 63 years (interquartile range, 52-71); 45·5% were ≥65 years old; 51.4% were female. High-risk characteristics were hypertension (52.4%), body mass index ≥35 (31.0%), diabetes mellitus (24.6%), chronic lung disease (22.1%), chronic renal disease (11.4%), congestive heart failure (6.6%), and compromised immune function (6.7%). Compared to the propensity-matched untreated control, patients who received casirivimab-imdevimab had significantly lower all-cause hospitalization rates at day 14 (1.3% vs 3.3%; Absolute Difference: 2.0%; 95% confidence interval (CI): 0.5-3.7%), day 21 (1.3% vs 4.2%; Absolute Difference: 2.9%; 95% CI: 1.2-4.7%), and day 28 (1.6% vs 4.8%; Absolute Difference: 3.2%; 95% CI: 1.4-5.1%). Rates of intensive care unit admission and mortality at days 14, 21 and 28 were similarly low for antibody-treated and untreated groups. INTERPRETATION: Among high-risk patients with mild to moderate COVID-19, casirivimab-imdevimab treatment was associated with a significantly lower rate of hospitalization. FUNDING: Mayo Clinic.

Mapping each pre-existing condition's association to short-term and long-term COVID-19 complications.

Understanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage ~1.1 million clinical notes from 1803 hospitalized COVID-19 patients and deep neural network models to characterize associations between 21 pre-existing conditions and the development of 20 complications (e.g. respiratory, cardiovascular, renal, and hematologic) of COVID-19 infection throughout the course of infection (i.e. 0-30 days, 31-60 days, and 61-90 days). Pleural effusion was the most frequent complication of early COVID-19 infection (89/1803 patients, 4.9%) followed by cardiac arrhythmia (45/1803 patients, 2.5%). Notably, hypertension was the most significant risk factor associated with 10 different complications including acute respiratory distress syndrome, cardiac arrhythmia, and anemia. The onset of new complications after 30 days is rare and most commonly involves pleural effusion (31-60 days: 11 patients, 61-90 days: 9 patients). Lastly, comparing the rates of complications with a propensity-matched COVID-negative hospitalized population confirmed the importance of hypertension as a risk factor for early-onset complications. Overall, the associations between pre-COVID conditions and COVID-associated complications presented here may form the basis for the development of risk assessment scores to guide clinical care pathways.

Cerebral Venous Sinus Thrombosis is not Significantly Linked to COVID-19 Vaccines or Non-COVID Vaccines in a Large Multi-State Health System.

OBJECTIVE: To assess the association of COVID-19 vaccines and non-COVID-19 vaccines with cerebral venous sinus thrombosis (CVST). MATERIALS AND METHOD: We retrospectively analyzed a cohort of 771,805 vaccination events across 266,094 patients in the Mayo Clinic Health System between 01/01/2017 and 03/15/2021. The primary outcome was a positive diagnosis of CVST, identified either by the presence of a corresponding ICD code or by an NLP algorithm which detected positive diagnosis of CVST within free-text clinical notes. For each vaccine we calculated the relative risk by dividing the incidence of CVST in the 30 days following vaccination to that in the 30 days preceding vaccination. RESULTS: We identified vaccination events for all FDA-approved COVID-19 vaccines including Pfizer-BioNTech (n = 94,818 doses), Moderna (n = 36,350 doses) and Johnson & Johnson - J&J (n = 1,745 doses). We also identified vaccinations events for 10 common FDA-approved non-COVID-19 vaccines (n = 771,805 doses). There was no statistically significant difference in the incidence rate of CVST in 30-days before and after vaccination for any vaccine in this population. We further found the baseline CVST incidence in the study population between 2017 and 2021 to be 45 to 98 per million patient years. CONCLUSIONS: This real-world evidence-based study finds that CVST is rare and is not significantly associated with COVID-19 vaccination in our patient cohort. Limitations include the rarity of CVST in our dataset, a relatively small number of J&J COVID-19 vaccination events, and the use of a population drawn from recipients of a SARS-CoV-2 PCR test in a single health system.

Real-time analysis of a mass vaccination effort confirms the safety of FDA-authorized mRNA COVID-19 vaccines.

BACKGROUND: As the coronavirus disease 2019 (COVID-19) vaccination campaign unfolds, it is important to continuously assess the real-world safety of Food and Drug Administration (FDA)-authorized vaccines. Curation of large-scale electronic health records (EHRs) enables near-real-time safety evaluations that were not previously possible. METHODS: In this retrospective study, we deployed deep neural networks over a large EHR system to automatically curate the adverse effects mentioned by physicians in over 1.2 million clinical notes between December 1, 2020 and April 20, 2021. We compared notes from 68,266 individuals who received at least one dose of BNT162b2 (n = 51,795) or mRNA-1273 (n = 16,471) to notes from 68,266 unvaccinated individuals who were matched by demographic, geographic, and clinical features. FINDINGS: Individuals vaccinated with BNT162b2 or mRNA-1273 had a higher rate of return to the clinic, but not the emergency department, after both doses compared to unvaccinated controls. The most frequently documented adverse effects within 7 days of each vaccine dose included myalgia, headache, and fatigue, but the rates of EHR documentation for each side effect were remarkably low compared to those derived from active solicitation during clinical trials. Severe events, including anaphylaxis, facial paralysis, and cerebral venous sinus thrombosis, were rare and occurred at similar frequencies in vaccinated and unvaccinated individuals. CONCLUSIONS: This analysis of vaccine-related adverse effects from over 1.2 million EHR notes of more than 130,000 individuals reaffirms the safety and tolerability of the FDA-authorized mRNA COVID-19 vaccines in practice. FUNDING: This study was funded by nference.