SARS-CoV-2 Omicron subvariant genomic variation associations with immune evasion in Northern California: A retrospective cohort study.

Background: The possibility of association between SARS-CoV-2 genomic variation and immune evasion is not known among persons with Omicron variant SARS-CoV-2 infection. Methods: In a retrospective cohort, using Poisson regression adjusting for sociodemographic variables and month of infection, we examined associations between individual non-lineage defining mutations and SARS-CoV-2 immunity status, defined as a) no prior recorded infection, b) not vaccinated but with at least one prior recorded infection, c) complete primary series vaccination, and/or d) primary series vaccination and ≥ 1 booster. We identified all non-synonymous single nucleotide polymorphisms (SNPs), insertions and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. We also examined correlations between the presence of SNPs with each other, with subvariants, and over time. Results: Seventy-nine mutations met inclusion criteria. Among 15,566 persons infected with Omicron SARS-CoV-2, 1,825 (12%) were unvaccinated with no prior recorded infection, 360 (2%) were unvaccinated with a recorded prior infection, 13,381 (86%) had a complete primary series vaccination, and 9,172 (58%) had at least one booster. After examining correlation between SNPs, 79 individual non-lineage defining mutations were organized into 38 groups. After correction for multiple testing, no individual SNPs or SNP groups were significantly associated with immunity status levels. Conclusions: Genomic variation identified within SARS-CoV-2 Omicron specimens was not significantly associated with immunity status, suggesting that contribution of non-lineage defining SNPs to immune evasion is minimal. Larger-scale surveillance of SARS-CoV-2 genomes linked with clinical data can help provide information to inform future vaccine development.

Evaluation of Pre-Analytical Variables for Human Papillomavirus Primary Screening from Self-Collected Vaginal Swabs.

Human papillomavirus (HPV) primary screening is an effective approach to assessing cervical cancer risk. Self-collected vaginal swabs can expand testing access, but the data defining analytical performance criteria necessary for adoption of self-collected specimens are limited, especially for those occurring outside the clinic, where the swab remains dry during transport. Here, we evaluated the performance of self-collected vaginal swabs for HPV detection using the Cobas 6800. There was insignificant variability between swabs self-collected by the same individual (n = 15 participants collecting 5 swabs per participant), measured by amplification of HPV and human ß-globin control DNA. Comparison of self-collected vaginal swab and provider-collected cervical samples (n = 144 pairs) proved highly concordant for HPV detection (total agreement = 90.3%; positive percentage agreement = 84.2%). There was no relationship between the number of dry storage days and amplification of HPV (n = 68; range, 4 to 41 days). Exposure of self-collected dry swabs to extreme summer and winter temperatures did not affect testing outcomes. A second internal control (RNase P) demonstrated that lack of amplification for ß-globin from self-collected specimens was consistent with poor, but not absent, cellularity. These data suggest that self-collected vaginal samples enable accurate clinical HPV testing, and that extended ambient dry storage or exposure to extreme temperatures does not influence HPV detection. Furthermore, lack of ß-globin amplification in HPV-negative samples accurately identified participants who required recollection.

Severe Acute Respiratory Syndrome Coronavirus 2 Delta Variant Genomic Variation Associated With Breakthrough Infection in Northern California: A Retrospective Cohort Study.

BACKGROUND: The association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic variation and breakthrough infection is not well defined among persons with Delta variant SARS-CoV-2 infection. METHODS: In a retrospective cohort, we assessed whether individual nonlineage defining mutations and overall genomic variation (including low-frequency alleles) were associated with breakthrough infection, defined as SARS-CoV-2 infection after coronavirus disease 2019 primary vaccine series. We identified all nonsynonymous single-nucleotide polymorphisms, insertions, and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. Using Poisson regression, we assessed the association with breakthrough infection for each individual mutation and a viral genomic risk score. RESULTS: Thirty-six mutations met our inclusion criteria. Among 12 744 persons infected with Delta variant SARS-CoV-2, 5949 (47%) were vaccinated and 6795 (53%) were unvaccinated. Viruses with a viral genomic risk score in the highest quintile were 9% more likely to be associated with breakthrough infection than viruses in the lowest quintile, but including the risk score improved overall predictive model performance (measured by C statistic) by only +0.0006. CONCLUSIONS: Genomic variation within SARS-CoV-2 Delta variant was weakly associated with breakthrough infection, but several potential nonlineage defining mutations were identified that might contribute to immune evasion by SARS-CoV-2.

Risk of severe clinical outcomes among persons with SARS-CoV-2 infection with differing levels of vaccination during widespread Omicron (B.1.1.529) and Delta (B.1.617.2) variant circulation in Northern California: A retrospective cohort study.

Background: The incidence of and risk factors for severe clinical outcomes with the Omicron (B.1.1.529) SARS-CoV-2 variant have not been well-defined. Methods: We conducted a retrospective cohort study to assess risks of severe clinical outcomes within 21 days after SARS-CoV-2 diagnosis in a large, diverse, integrated health system. Findings: Among 118,078 persons with incident SARS-CoV-2 infection, 48,101 (41%) were during the Omicron period and 69,977 (59%) during the Delta (B.1.617.2) period. Cumulative incidence of any hospitalization (2.4% versus 7.8%; adjusted hazard ratio [aHR] 0.55; 95% confidence interval [CI] (0.51-0.59), with low-flow oxygen support (1.6% versus 6.4%; aHR 0.46; CI 0.43-0.50), with high-flow oxygen support (0.6% versus 2.8%; aHR 0.47; CI 0.41-0.54), with invasive mechanical ventilation (0.1% versus 0.7%; aHR 0.43; CI 0.33-0.56), and death (0.2% versus 0.7%; aHR 0.54; CI 0.42-0.70) were lower in the Omicron than the Delta period. The risk of hospitalization was higher among unvaccinated persons (aHR 8.34; CI 7.25-9.60) and those who completed a primary COVID-19 vaccination series (aHR 1.72; CI 1.49-1.97) compared with those who completed a primary vaccination series and an additional dose. The strongest risk factors for all severe clinical outcomes were older age, higher body mass index and select comorbidities. Interpretation: Persons with SARS-CoV-2 infection were significantly less likely to develop severe clinical outcomes during the Omicron period compared with the Delta period. COVID-19 primary vaccination and additional doses were associated with reduced risk of severe clinical outcomes among those with SARS-CoV-2 infection. Funding: National Cancer Institute and The Permanente Medical Group.

Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19.

Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.

Semi-quantitative, high throughput analysis of SARS-CoV-2 neutralizing antibodies: Measuring the level and duration of immune response antibodies post infection/vaccination.

The question associated with efficacy and longevity of SARS-CoV-2 protection post-vaccination is paramount. The cPass surrogate virus neutralization test (sVNT) has gained popularity globally as a dual application assay for: 1. Accurate SARS-CoV-2 population surveillance (seroprevalence) analysis and 2. Revealing the presence of antibodies that block and effectively neutralize the interaction between the SARS-CoV-2 receptor binding domain and the host cell ACE2 receptor in recovered or vaccinated individuals. This study describes an approach for accurate quantification of neutralizing antibodies using the cPass sVNT with an automated workflow on the Tecan EVO and Dynex Agility platforms that is applicable to other liquid handling systems. This methodology was used to assess the stability of SARS-CoV-2 neutralizing antibodies between freeze/thaw and refrigerated sample storage conditions. Furthermore, a subset of twenty-five samples from SARS-CoV-2 infected/recovered individuals revealed a 600-fold difference in the neutralizing antibody response where low titers were represented in about half of the samples. Finally, pre- and post-vaccination samples were tested for neutralizing antibodies using the qualitative and semi-quantitative cPass sVNT protocols revealing undetectable or relatively low levels after the first vaccine dose and a decline in levels longitudinally over the months following the second dose. This wide range in neutralizing (blocking) antibodies from both natural infection and vaccination supports a differential immune response that may be attributed to several physiological and genetic factors underlining the potential for measuring SARS-CoV-2 neutralizing antibody titer levels post-vaccination to help ensure robust and prolonged immunity.

Improved Gonorrhea and Chlamydia Testing Among Men Who Have Sex With Men Living With HIV Through Implementation of Self-Collected Tests.

ABSTRACT: We implemented self-collected gonorrhea/chlamydia testing in 17 medical centers in California serving men who have sex with men living with HIV. From 2012 to 2018, gonorrhea/chlamydia testing increased from 45.2% to 63.4%. Among those tested, rectal testing increased from 42.0% to 77.3%; pharyngeal testing increased from 31.0% to 79.9% (all, Ptrend < 0.0001).

New-Onset IgG Autoantibodies in Hospitalized Patients with COVID-19.

Coronavirus Disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), is associated with a wide range of clinical manifestations, including autoimmune features and autoantibody production. We developed three different protein arrays to measure hallmark IgG autoantibodies associated with Connective Tissue Diseases (CTDs), Anti-Cytokine Antibodies (ACA), and anti-viral antibody responses in 147 hospitalized COVID-19 patients in three different centers. Autoantibodies were identified in approximately 50% of patients, but in <15% of healthy controls. When present, autoantibodies largely targeted autoantigens associated with rare disorders such as myositis, systemic sclerosis and CTD overlap syndromes. Anti-nuclear antibodies (ANA) were observed in ∼25% of patients. Patients with autoantibodies tended to demonstrate one or a few specificities whereas ACA were even more prevalent, and patients often had antibodies to multiple cytokines. Rare patients were identified with IgG antibodies against angiotensin converting enzyme-2 (ACE-2). A subset of autoantibodies and ACA developed de novo following SARS-CoV-2 infection while others were transient. Autoantibodies tracked with longitudinal development of IgG antibodies that recognized SARS-CoV-2 structural proteins such as S1, S2, M, N and a subset of non-structural proteins, but not proteins from influenza, seasonal coronaviruses or other pathogenic viruses. COVID-19 patients with one or more autoantibodies tended to have higher levels of antibodies against SARS-CoV-2 Nonstructural Protein 1 (NSP1) and Methyltransferase (ME). We conclude that SARS-CoV-2 causes development of new-onset IgG autoantibodies in a significant proportion of hospitalized COVID-19 patients and are positively correlated with immune responses to SARS-CoV-2 proteins.

Proinflammatory IgG Fc structures in patients with severe COVID-19.

Severe acute respiratory syndrome coronavirus 2 infections can cause coronavirus disease 2019 (COVID-19), which manifests with a range of severities from mild illness to life-threatening pneumonia and multi-organ failure. Severe COVID-19 is characterized by an inflammatory signature, including high levels of inflammatory cytokines, alveolar inflammatory infiltrates and vascular microthrombi. Here we show that patients with severe COVID-19 produced a unique serologic signature, including an increased likelihood of IgG1 with afucosylated Fc glycans. This Fc modification on severe acute respiratory syndrome coronavirus 2 IgGs enhanced interactions with the activating Fcγ receptor FcγRIIIa; when incorporated into immune complexes, Fc afucosylation enhanced production of inflammatory cytokines by monocytes, including interleukin-6 and tumor necrosis factor. These results show that disease severity in COVID-19 correlates with the presence of proinflammatory IgG Fc structures, including afucosylated IgG1.

Proinflammatory IgG Fc structures in patients with severe COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections can cause Coronavirus Disease 2019 (COVID-19), which manifests with a range of severities from mild illness to life threatening pneumonia and multi-organ failure. Severe COVID-19 is characterized by an inflammatory signature including high levels of inflammatory cytokines, alveolar inflammatory infiltrates and vascular microthrombi. Here we show that severe COVID-19 patients produced a unique serologic signature, including increased IgG1 with afucosylated Fc glycans. This Fc modification on SARS-CoV-2 IgGs enhanced interactions with the activating FcγR, FcγRIIIa; when incorporated into immune complexes, Fc afucosylation enhanced production of inflammatory cytokines by monocytes, including IL-6 and TNF. These results show that disease severity in COVID-19 correlates with the presence of afucosylated IgG1, a pro-inflammatory IgG Fc modification.