DELINEATING FACTORS ASSOCIATED WITH ASYMPTOMATIC PRIMARY SARS-CoV-2 INFECTION

Background: SARS-CoV-2 infection leads to a broad range of clinical manifestations, from no symptoms to critical illness. Pre-stimulated innate defenses, rapid induction of SARS-CoV-2 responses and pre-existing crossreactive immunity to circulating human coronaviruses (HCoV) may early dampen SARS-CoV-2 infection, preventing symptomatic disease. Here we explore SARS-CoV-2 and HCoV antibody impact on asymptomatic infection in individuals first encountering SARS-CoV-2 in March 2020-March 2021 participating in a longitudinal pediatric cohort (n=2917) and a cross-sectional adult and children diagnostic cohort (n=882) in Switzerland. Method(s): Antibodies (Ab) to S1 of the four HCoV strains and SARS-CoV-2 antigens S1, RBD, S2 and N were determined in saliva (n=4993) and serum (n=7486) samples. Mucosal and systemic neutralization activity against wildtype SARS-CoV-2-Wuhan, and Alpha, Delta and Omicron (BA.2) variants of concerns (VoC) was assessed by pseudovirus neutralization in a subset of individuals. Result(s): Analysis of simultaneously sampled saliva and plasma revealed a strong correlation of mucosal and systemic SARS-CoV-2 anti-spike responses in recent infection. Notably, pre-existing high HCoV antibody response was significantly associated with higher systemic (IgG, IgA, and IgM, p< 0.001) and mucosal (IgG, p=0.03) SARS-CoV-2 responses following SARS-CoV-2 infection. Adjusting for age and sex, we found four saliva SARS-CoV-2 Ab parameters, namely total Ig S2, total Ig S1, IgA S2 and IgM S1 (p< 0.001, p< 0.001, p=0.02, p=0.01 respectively), inversely associated with salivary viral load highlighting the impact of mucosal Ab response on viral suppression. Saliva neutralization activity was modest but surprisingly broad, retaining same level activity against Wuhan, Alpha and Delta, but not Omicron BA.2, whereas plasma neutralization activity showed the typical decrease for all three VoCs compared to Wuhan. Most interestingly, asymptomatic individuals presented with higher IgG S2 antibody reactivity in saliva (p=0.03) and higher pre-existing HCoV-S1 IgG activity in plasma (HKU1, p=0.04) and saliva (total hCoV, p=0.02) suggesting immune factors that restrict disease severity. Conclusion(s): Focusing on a SARS-CoV-2 infection and vaccine naive population, our study reveals interdependencies of systemic and mucosal SARS-CoV-2 and HCoV immunity following primary SARS-CoV-2 infection and locates reactivities linked with reduced viral load and asymptomatic infection.

FUNCTIONALLY IMPAIRED ANTIBODY RESPONSE TO BNT162B2 BOOSTER VACCINATION IN CVID IgG RESPONDERS.

BACKGROUND: While previous studies described the production of IgG-antibodies in a subgroup of CVID-patients following mRNA-vaccinations with bnt162b2 SARS-CoV2 (CVID responders), the functionality of these antibodies in terms of avidity as measured by the dissociation rate constant (kdis) and the antibody response to booster immunization has not been studied. OBJECTIVE: In CVID responders and healthy individuals the avidity of anti-SARS-CoV-2 serum-antibodies and their neutralization capacity as measured by surrogate virus neutralizing antibodies were analyzed in addition to IgG-, IgM- and IgA-antibody levels and the response of circulating follicular T-helper cells after a third vaccination with BNT162b2 SARS-CoV2 mRNA-vaccine. METHODS: Binding IgG, IgA and IgM serum levels were analyzed by ELISA in CVID-patients responding to the primary vaccination (CVID responders, n=10) and healthy controls (n=41). The binding-avidity of anti-spike antibodies was investigated using biolayer interferometry in combination with biotin-labelled receptor-binding-domain (RBD) of SARS-CoV2 spike-protein and streptavidin-labelled sensors. Antigen-specific recall T-cell responses were assessed by measuring activation-induced markers by flow cytometry. RESULTS: After the third vaccination with BNT162b2 IgG-, IgM and IgA-antibody levels, sVNT levels and antibody avidity were lower in CVID responders as compared to healthy. In contrast αSpike-avidity was comparable in CVID responders and healthy individuals following primary vaccination. Follicular T-helper cell response to booster vaccination in CVID-responders was significantly reduced when compared to healthy individuals. CONCLUSION: Impaired affinity-maturation during booster-response provides new insight into CVID pathophysiology.

A proteomic survival predictor for COVID-19 patients in intensive care.

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care.

Olfactory dysfunction in Long-COVID

Aim The project aims to examine chemosensory dysfunction in long-COVID with a focus on olfactory function about 9 months after SARS-CoV-II-infection. Material and Methods In this population-based cross sectional study, PCR-confirmed SARS-CoV-2 outpatients were examined between November and June 2020 at Kiel university hospital. Data on medical history and chemosensory function were collected via questionnaires and a Visual Analogue Scale (VAS), olfactory performance was psychophysically objectified using the Sniffin' Sticks test. Results A total of 376 female and 290 male patients were included with a mean age of 48.2 years ranging from 19 to 87 years. The mean follow-up was 9.09 months (range 1.64-15.18) after initial positive PCR-testing. The prevalence for olfactory dysfunction (OD) during infection was 66,1 %. 33,7 % of the subjects reported persistent OD subjectively at the time of examination (female 28,8 %, male 42,3 %). T-test analysis showed a significant decline of reported olfactory evaluation from before COVID-19 to the time of examination based on VAS (p < 0.001). 34,6 % of the subjects were tested hyposmic or anosmic by Sniffin' Sticks. A significant correlation was shown between a subjective estimation of OD by the patients and an objectively tested OD (p < 0.001). The TDI-score correlated positively with the amount of time (in months) that passed since PCR-testing (p < 0.001). Discussion OD in SARS-CoV-II-infection is frequent and can be persistent long beyond the acute phase of ilness. We demonstrated that anamnestic OD is significantly related to psychophysically tested OD. Therefore one can conclude that a subjective OD is a likely predictor of an actual objective OD. Furthermore, OD shows a tendency to improve over time.

Gustatory dysfunction in long COVID

Background This study aims to investigate the prevalence and long-term development of gustatory dysfunction (GD) after COVID-19. Methods In the population-based cross-sectional COVIDOM-study, 667 patients above the age of 18 years (mean 48.2) who tested positive for SARSCoV- 2 via PCR-testing on average 9.09 months ago were examined between November 2020 and June 2021. Extensive medical history taking was conducted via questionnaires. Participants were asked to rate their ability to taste before, during and after COVID-19 on a Visual Analogue Scale (VAS) ranging from 0 to 10. Whole mouth gustatory testing with Taste Strips for the qualities sweet, sour, salty, and bitter was performed. Results 60.9 % (406 of 667) participants reported gustatory impairment during their infection. Out of those, 56.9 % perceived this symptom as severe and 13.3 % noticed it as the earliest symptom. At the time of our examination, 36.2 % had a persistent subjective GD, defined as a lower score on the VAS than before COVID-19 (mean difference -0.9 points). This difference was significant (p < 0.001). In the testing, 7.3 % (47 of 667) participants had a GD, defined as the correct identification of less than three out of four Taste Strips. No signifi- cant correlation was found between subjectively persistent and tested GD (p = 0.250). Conclusions SARS-CoV-2 seems to frequently affect the gustatory function in the long term as well, what might have an influence on patients' everyday-life. However, Patients' own perception does not always correspond with psychophysiological testing which might be caused by the common difficulty to differentiate between the chemosensory senses of taste and smell.

OxoScan-MS: Oxonium ion scanning mass spectrometry facilitates plasma glycoproteomics in large scale (preprint)

Protein glycosylation is a complex and heterogeneous post-translational modification. Specifically, the human plasma proteome is rich in glycoproteins, and as protein glycosylation is frequently dysregulated in disease, glycoproteomics is considered an underexplored resource for biomarker discovery. Here, we present OxoScan-MS, a data-independent mass spectrometric acquisition technology and data analysis software that facilitates sensitive, fast, and cost-effective glycoproteome profiling of plasma and serum samples in large cohort studies. OxoScan-MS quantifies glycosylated peptide features by exploiting a scanning quadrupole to assign precursors to oxonium ions, glycopeptide-specific fragments. OxoScan-MS reaches a high level of sensitivity and selectivity in untargeted glycopeptide profiling, such that it can be efficiently used with fast microflow chromatography without a need for experimental enrichment of glycopeptides from neat plasma. We apply OxoScan-MS to profile the plasma glycoproteomic in an inpatient cohort hospitalised due to severe COVID-19, and obtain precise quantities for 1,002 glycopeptide features. We reveal that severe COVID-19 induces differential glycosylation in disease-relevant plasma glycoproteins, including IgA, fibrinogen and alpha-1-antitrypsin. Thus, with OxoScan-MS we present a strategy for quantitatively mapping glycoproteomes that scales to hundreds and thousands of samples, and report glycoproteomic changes in severe COVID-19.

Workin' moms ain't doing so bad: Evidence on the gender gap in working hours at the outset of the COVID-19 pandemic

Objective: In this project, we study changes in the working hours of men and women with and without children in the early phase of the COVID-19 crisis in Germany until August 2020. Background: The COVID-19 outbreak in Europe led to a sharp decrease in economic activity, along with temporary closures of childcare facilities and schools. Subsequent changes in working hours in the early phase of the pandemic and during summer 2020 may have contributed to inequalities between men and women or parents and non-parents respectively. Method: We use a unique panel dataset containing monthly survey data of the Institute for Employment Research (the IAB-HOPP) combined with administrative data of the German Federal Employment Agency. We run regression models with the change in working hours (before the crisis vs. working time at each panel wave) as the dependent variable and gender, parental status, and childcare arrangement as the main independent variables. Results: We observe a comparable reduction in working hours for both men and women during the spring lockdown. However, only the working hours of women recover and return to their pre-crisis level in summer 2020. Most surprisingly, having children has an accelerating effect on recovery for mothers but not for fathers. At the end of the observation period, fathers do not recover as fully as mothers do. Conclusion: These results challenge concerns about a temporary or possibly persistent 'retraditionalisation' of gender roles during the COVID-19 crisis.

Antigen-Specific CD4+ T-Cell Activation in Primary Antibody Deficiency After BNT162b2 mRNA COVID-19 Vaccination

Previous studies on immune responses following COVID-19 vaccination in patients with common variable immunodeficiency (CVID) were inconclusive with respect to the ability of the patients to produce vaccine-specific IgG antibodies, while patients with milder forms of primary antibody deficiency such as immunoglobulin isotype deficiency or selective antibody deficiency have not been studied at all. In this study we examined antigen-specific activation of CXCR5-positive and CXCR5-negative CD4+ memory cells and also isotype-specific and functional antibody responses in patients with CVID as compared to other milder forms of primary antibody deficiency and healthy controls six weeks after the second dose of BNT162b2 vaccine against SARS-CoV-2. Expression of the activation markers CD25 and CD134 was examined by multi-color flow cytometry on CD4+ T cell subsets stimulated with SARS-CoV-2 spike peptides, while in parallel IgG and IgA antibodies and surrogate virus neutralization antibodies against SARS-CoV-2 spike protein were measured by ELISA. The results show that in CVID and patients with other milder forms of antibody deficiency normal IgG responses (titers of spike protein-specific IgG three times the detection limit or more) were associated with intact vaccine-specific activation of CXCR5-negative CD4+ memory T cells, despite defective activation of circulating T follicular helper cells. In contrast, CVID IgG nonresponders showed defective vaccine-specific and superantigen-induced activation of both CD4+T cell subsets. In conclusion, impaired TCR-mediated activation of CXCR5-negative CD4+ memory T cells following stimulation with vaccine antigen or superantigen identifies patients with primary antibody deficiency and impaired IgG responses after BNT162b2 vaccination.

A proteomic survival predictor for COVID-19 patients in intensive care (preprint)

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Comprehensively capturing the host physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index and APACHE II score were poor predictors of survival. Plasma proteomics instead identified 14 proteins that showed concentration trajectories different between survivors and non-survivors. A proteomic predictor trained on single samples obtained at the first time point at maximum treatment level (i.e. WHO grade 7) and weeks before the outcome, achieved accurate classification of survivors in an exploratory (AUROC 0.81) as well as in the independent validation cohort (AUROC of 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that predictors derived from plasma protein levels have the potential to substantially outperform current prognostic markers in intensive care.

A time-resolved proteomic and prognostic map of COVID-19.

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.

Ultra-fast proteomics with Scanning SWATH.

Accurate quantification of the proteome remains challenging for large sample series and longitudinal experiments. We report a data-independent acquisition method, Scanning SWATH, that accelerates mass spectrometric (MS) duty cycles, yielding quantitative proteomes in combination with short gradients and high-flow (800 µl min-1) chromatography. Exploiting a continuous movement of the precursor isolation window to assign precursor masses to tandem mass spectrometry (MS/MS) fragment traces, Scanning SWATH increases precursor identifications by ~70% compared to conventional data-independent acquisition (DIA) methods on 0.5-5-min chromatographic gradients. We demonstrate the application of ultra-fast proteomics in drug mode-of-action screening and plasma proteomics. Scanning SWATH proteomes capture the mode of action of fungistatic azoles and statins. Moreover, we confirm 43 and identify 11 new plasma proteome biomarkers of COVID-19 severity, advancing patient classification and biomarker discovery. Thus, our results demonstrate a substantial acceleration and increased depth in fast proteomic experiments that facilitate proteomic drug screens and clinical studies.

A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcome (preprint)

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. There is an urgent need for predictive markers that can guide clinical decision-making, inform about the effect of experimental therapies, and point to novel therapeutic targets. Here, we characterize the time-dependent progression of COVID-19 through different stages of the disease, by measuring 86 accredited diagnostic parameters and plasma proteomes at 687 sampling points, in a cohort of 139 patients during hospitalization. We report that the time-resolved patient molecular phenotypes reflect an initial spike in the systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution and immunomodulation. Further, we show that the early host response is predictive for the disease trajectory and gives rise to proteomic and diagnostic marker signatures that classify the need for supplemental oxygen therapy and mechanical ventilation, and that predict the time to recovery of mildly ill patients. In severely ill patients, the molecular phenotype of the early host response predicts survival, in two independent cohorts and weeks before outcome. We also identify age-specific molecular response to COVID-19, which involves increased inflammation and lipoprotein dysregulation in older patients. Our study provides a deep and time resolved molecular characterization of COVID-19 disease progression, and reports biomarkers for risk-adapted treatment strategies and molecular disease monitoring. Our study demonstrates accurate prognosis of COVID-19 outcome from proteomic signatures recorded weeks earlier.

Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection.

The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.

Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics (preprint)

The COVID-19 pandemic is an unprecedented global challenge. Highly variable in its presentation, spread and clinical outcome, novel point-of-care diagnostic classifiers are urgently required. Here, we describe a set of COVID-19 clinical classifiers discovered using a newly designed low-cost high-throughput mass spectrometry-based platform. Introducing a new sample preparation pipeline coupled with short-gradient high-flow liquid chromatography and mass spectrometry, our methodology facilitates clinical implementation and increases sample throughput and quantification precision. Providing a rapid assessment of serum or plasma samples at scale, we report 27 biomarkers that distinguish mild and severe forms of COVID-19, of which some may have potential as therapeutic targets. These proteins highlight the role of complement factors, the coagulation system, inflammation modulators as well as pro-inflammatory signalling upstream and downstream of Interleukin 6. Application of novel methodologies hence transforms proteomics from a research tool into a rapid-response, clinically actionable technology adaptable to infectious outbreaks. Highlights- A completely redesigned clinical proteomics platform increases throughput and precision while reducing costs. - 27 biomarkers are differentially expressed between WHO severity grades for COVID-19. - The study highlights potential therapeutic targets that include complement factors, the coagulation system, inflammation modulators as well as pro-inflammatory signalling both upstream and downstream of interleukin 6.