Longitudinal viscosity of blood plasma for rapid COVID-19 prognostics (preprint)

Blood Plasma Viscosity (PV) is an established biomarker for numerous diseases. While PV colloquially refers to the shear viscosity, there is a second viscosity component--the bulk viscosity--that describes the irreversible fluid compressibility on short time scales. The bulk viscosity is acutely sensitive to solid-like suspensions, and obtainable via the longitudinal viscosity from acoustic attenuation measurements. Whether it has diagnostic value remains unexplored yet may be pertinent given the association of diverse pathologies with the formation of plasma suspensions, such as fibrin-microstructures in COVID-19 and long-COVID. Here we show that the longitudinal PV measured using Brillouin Light Scattering (BLS) can serve as a proxy for the shear PV of blood plasma, and exhibits a temperature dependence consistent with increased suspension concentrations in severe COVID-patient plasma. Our results open a new avenue for PV diagnostics based on the longitudinal PV, and show that BLS can provide a means for its clinical implementation.

Efficacy and tolerability of Sotrovimab, Molnupiravir and Nirmatrelvir/Ritonavir for non-hospitalized patients at high risk for COVID-19: a retrospective, single-center analysis. (preprint)

Background The use of outpatient antiviral treatment for high-risk patients with coronavirus disease 19 (COVID-19) is crucial in preventing progression to severe COVID-19 and reducing hospitalization rates. Objective The main goal of this retrospective, single-center analysis was to assess the feasibility and potential clinical impact of an outpatient administration of various available antiviral agents including sotrovimab (SOT), nirmatrelvir/ritonavir (N/R), molnupiravir (MOL) to COVID-19 patients at high risk for disease progression. In addition, hospital admission rates between groups. side effects and subjective treatment effects were assessed. Methods We conducted a retrospective analysis on 2606 outpatient individuals with mild to moderate COVID-19 at risk for disease progression, hospitalization, or death. After receiving either SOT (420/2606), MOL (1788/2606) or N/R (398/2606), patients were followed- up with regard to primary (hospitalization rate) and secondary (treatment and side effects) outcomes by phone. Result A total of 2606 patients were treated at the outpatient clinic, of whom 420 were treated with SOT, 398 with N/R and 1788 with MOL. 10 patients (3.2%) who were treated with SOT were later hospitalized and 1 patient had to be admitted to the ICU. In comparison, 11 patients (0.8%) who received MOL were admitted to hospital (2 admissions to the intensive care unit (ICU). No hospital/ICU admission was registered for patients who received N/R. In contrast, 46 patients (14.3%) who received N/R reported strong to severe side effects, exceeding SOT with 2.6% of the patients (8 patients in total) and MOL with 5% (69 patients) reporting strong to severe side effects. A reduction in COVID symptoms after the medication administration was experienced by 43% (132 patients) in the SOT group, 43% (572 patients) in the MOL group and 67% (115 patients) in the N/R group, respectively. In over 60-year-olds and chronic kidney disease, no subjective symptom improvement is to be expected with MOL. Women have a 1.2 elevated chance of symptom improvement with treatment with MOL. Conclusion Hospitalization rates in high-risk patients who received SOT, MOL or N/R were low, particularly in patients who received N/R. All antiviral drugs were well tolerated, but side effects were more frequent in patients with N/R. However, N/R showed the greatest subjective treatment effect.

Human primary Omicron BA.1 and BA.2 infections result in sub-lineage-specific neutralization (preprint)

The recently emerged Omicron variant is the most antigenically distinct SARS-CoV-2 variant of concern to date. As the heavily mutated spike protein enables escape from neutralizing antibodies, we studied the neutralizing activities of sera after Omicron BA.1 and BA.2 infections of naïve and vaccinated individuals. We show that primary BA.1 infections yielded reduced neutralizing antibody titers against wildtype (WT), Delta, and BA.2, while serum samples from individuals after BA.2 infection showed no cross-neutralization against the other variants. Fully vaccinated individuals were still able to neutralize both Omicron sub-lineages up to three months after vaccination, and Omicron-breakthrough infections showed equal cross-neutralizing activities against WT, Delta, BA.1, and BA.2. Our data demonstrate that Omicron variants are able to enhance cross-neutralizing antibodies in pre-immune individuals. Primary infections with one of the Omicron sub-lineages, however, induced variant-specific neutralizing antibodies. In particular, BA.2 infections generated a sub-lineage-specific response, emphasizing its antigenic distance.

The Systemic Renin-Angiotensin System in COVID-19 (preprint)

Introduction: SARS-CoV-2 gains cell entry via angiotensin-converting enzyme (ACE) 2, a membrane-bound enzyme of the “alternative” (alt) renin-angiotensin system (RAS). ACE2 counteracts angiotensin II by converting it to potentially protective angiotensin 1–7.Methods Using mass spectrometry, we assessed key metabolites of the classical RAS (angiotensins I–II) and alt-RAS (angiotensins 1–7 and 1–5) pathways as well as ACE and ACE2 concentrations in 159 patients hospitalized with COVID-19, stratified by disease severity (severe, n = 76; non-severe: n = 83). Plasma renin activity (PRA-S) was calculated as the sum of RAS metabolites. We estimated ACE activity using the angiotensin II:I ratio (ACE-S) and estimated systemic alt-RAS activation using the ratio of alt-RAS axis metabolites to PRA-S (ALT-S). We applied mixed linear models to assess how PRA-S and ACE/ACE2 concentrations affected ALT-S, ACE-S, and angiotensins II and 1–7.Results Median angiotensin I and II levels were higher with severe versus non-severe COVID-19 (both p < 0.05), demonstrating activation of classical RAS. The difference disappeared with analysis limited to patients not taking a RAS inhibitor. ALT-S in severe COVID-19 increased with time (days 1–6: 0.12; days 11–16: 0.22) and correlated with ACE2 concentration (r = 0.831). ACE-S was lower in severe versus non-severe COVID-19 (p < 0.001), but ACE concentrations were similar between groups and weakly correlated with ACE-S (r = 0.232). ACE2 and ACE-S trajectories in severe COVID-19, however, did not differ between survivors and non-survivors. Overall RAS alteration in severe COVID-19 resembled severity of disease-matched patients with influenza. In mixed linear models, renin activity most strongly predicted angiotensin II and 1–7 levels. ACE2 also predicted angiotensin 1–7 levels and ALT-S. No single factor or the combined model, however, could fully explain ACE-S. ACE2 and ACE-S trajectories in severe COVID-19 did not differ between survivors and non-survivors.Conclusions Angiotensin II was elevated in severe COVID-19 but markedly influenced by RAS inhibitors and driven by overall RAS activation. ACE-S was significantly lower with severe COVID-19 and did not correlate with ACE concentrations. A shift to the alt-RAS axis because of increased ACE2 could partially explain the relative reduction in angiotensin II levels.

Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a cohort study (preprint)

Background The SARS CoV-2 pandemic remains a worldwide challenge. The CRIT Cov U pilot study generated a urinary proteomic biomarker consisting of 50 peptides (COV50), which predicted death and disease progression. Following the interim analysis demanded by the German government, the full dataset was analysed to consolidate findings and propose clinical applications. Methods In eight European countries, 1012 adults with PCR-confirmed COVID-19 were followed up for death and progression along the 8 point WHO scale. Capillary electrophoresis coupled with mass spectrometry was used for urinary proteomic profiling. Statistical methods included logistic regression, receiver operating curve analysis with comparison of the area under curve (AUC) between nested models. Hospitalisation costs were derived from the care facility corresponding with the Markov chain probability of reaching WHO scores ranging from 3 to 8 and flat-rate hospitalistion costs standardised across countries. Findings The entry WHO scores were 1-3, 4-5 and 6 in 445 (44,0%), 529 (52,3%), and 38 (3,8%) patients, of whom 119 died and 271 progressed. The standardised odds ratios associated with COV50 for death were 2,44 (95% CI, 2,05-2,92) unadjusted and 1,67 (1,34-2,07) if adjusted for sex, age, body mass index, comorbidities and baseline WHO score, and 1,79 (1,60-2,01) and 1,63 (1,40-1,90), respectively, for disease progression (p<0,0001 for all). The predictive accuracy of optimised COV50 thresholds were 74,4% (95% CI, 71,6-77,1) for mortality (threshold 0,47) and 67,4% (64,1-70,3) for disease progression (threshold 0,04). On top of covariables and the baseline WHO score, these thresholds improved AUCs from 0,835 to 0,853 (p=0,0331) and from 0,697 to 0,730 (p=0,0008) for death and progression, respectively. Of 196 ambulatory patients, 194 (99,0%) did not reach the 0,04 threshold. Earlier intervention guided by high-risk COV50 levels should reduce hospital days with cost reductions expressed per 1000 patient-days ranging from MEuro 1,208 (95% percentile interval, 1,035-1,406) at low risk (COV50 <0,04) to MEuro 4,503 (4,107-4,864) at high risk (COV50 above 0,04 and age above 65 years). Interpretation The urinary proteomic COV50 marker is accurate in predicting adverse COVID-19 outcomes. Even in mild-to-moderate PCR-confirmed infections (WHO scores 1-5), the 0,04 threshold justifies earlier drug treatment, thereby reducing hospitalisation days and costs.

Development and external validation of a logistic regression derived formula based on repeated routine hematological measurements predicting survival of hospitalized Covid-19 patients (preprint)

Background: The Covid-19 pandemic has become a global public health crisis and providing optimal patient care while preventing a collapse of the health care system is a principal objective worldwide. Objective: To develop and validate a prognostic model based on routine hematological parameters to predict uncomplicated disease progression to support the decision for an earlier discharge. Design: Development and refinement of a multivariable logistic regression model with subsequent external validation. The time course of several hematological variables until four days after admission were used as predictors. Variables were first selected based on subject matter knowledge; their number was further reduced using likelihood ratio-based backward elimination in random bootstrap samples. Setting: Model development based on three Austrian hospitals, validation cohorts from two Austrian and one Swedish hospital. Participants: Model development based on 363 survivors and 78 non-survivors of Covid-19 hospitalized in Austria. External validation based on 492 survivors and 61 non-survivors hospitalized in Austria and Sweden. Outcome: In-hospital death. Main Results: The final model includes age, fever upon admission, parameters derived from C-reactive protein (CRP) concentration, platelet count and creatinine concentration, approximating their baseline values (CRP, creatinine) and change over time (CRP, platelet count). In Austrian validation cohorts both discrimination and calibration of this model were good, with c indices of 0.93 (95% CI 0.90 - 0.96) in a cohort from Vienna and 0.93 (0.88 - 0.98) in one from Linz. The model performance seems independent of how long symptoms persisted before admission. In a small Swedish validation cohort, the model performance was poorer (p = 0.008) compared with Austrian cohorts with a c index of 0.77 (0.67 - 0.88), potentially due to substantial differences in patient demographics and clinical routine. Conclusions: Here we describe a formula, requiring only variables routinely acquired in hospitals, which allows to estimate death probabilities of hospitalized patients with Covid-19. The model could be used as a decision support for earlier discharge of low-risk patients to reduce the burden on the health care system. The model could further be used to monitor whether patients should be admitted to hospital in countries with health care systems with emphasis on outpatient care (e.g. Sweden).

SARS-CoV-2 escapes CD8 T cell surveillance via mutations in MHC-I restricted epitopes (preprint)

CD8+ T cell immunity to SARS-CoV-2 has been implicated in COVID-19 severity and virus control, though direct evidence has been lacking so far. Here, we identified non-synonymous mutations in MHC-I restricted CD8+ T cell epitopes after deep sequencing of 747 SARS-CoV- 2 virus isolates. Mutant peptides exhibited diminished or abrogated MHC-I binding, which was associated with a loss of recognition and functional responses by CD8+ T cells isolated from HLA-matched COVID-19 patients. Our findings highlight the capacity of SARS-CoV-2 to subvert CD8+ T cell surveillance through escape mutations in MHCI-restricted viral epitopes. This provides evolutionary evidence for CD8+ T cell immunity controlling SARS-CoV-2 with consequences for COVID-19 vaccine design.

SARSeq, a robust and highly multiplexed NGS assay for parallel detection of SARS-CoV2 and other respiratory infections (preprint)

During a pandemic, mitigation as well as protection of system-critical or vulnerable institutions requires massive parallel, yet cost effective testing to monitor the spread of agents such as the current SARS-CoV2 virus. Here we present SARSeq, saliva analysis by RNA sequencing, as an approach to monitor presence of SARS-CoV2 and other respiratory viruses performed on tens of thousands of samples in parallel. SARSeq is based on next generation sequencing of multiple amplicons generated in parallel in a multiplexed RT-PCR reaction. It relies on a two-dimensional unique dual indexing strategy using four indices in total for unambiguous and scalable assignment of reads to individual samples. We calibrated this method using dilutions of synthetic RNA and virions to show sensitivity down to few molecules, and applied it to hundreds of patient samples validating robust performance across various sample types. Double blinded benchmarking to gold-standard quantitative RT-PCR performed in a clinical setting and a human diagnostics laboratory showed robust performance up to a Ct of 36. The false positive rate, likely due to cross contamination during sample pipetting, was estimated at 0.04-0.1%. In addition to SARS-CoV2, SARSeq detects Influenza A and B viruses as well as human rhinovirus and can be easily expanded to include detection of other pathogens. In sum, SARSeq is an ideal platform for differential diagnostic of respiratory diseases at a scale, as is required during a pandemic.

Mutational dynamics and transmission properties of SARS-CoV-2 superspreading events in Austria (preprint)

Superspreading events shape the COVID-19 pandemic. Here we provide a national-scale analysis of SARS-CoV-2 outbreaks in Austria, a country that played a major role for virus transmission across Europe and beyond. Capitalizing on a national epidemiological surveillance system, we performed deep whole-genome sequencing of virus isolates from 576 samples to cover major Austrian SARS-CoV-2 clusters. Our data chart a map of early viral spreading in Europe, including the path from low-frequency mutations to fixation. Detailed epidemiological surveys enabled us to calculate the effective SARS-CoV-2 population bottlenecks during transmission and unveil time-resolved intra-patient viral quasispecies dynamics. This study demonstrates the power of integrating deep viral genome sequencing and epidemiological data to better understand how SARS-CoV-2 spreads through populations. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

Scalable, rapid and highly sensitive isothermal detection of SARS-CoV-2 for laboratory and home testing (preprint)

Global efforts to combat the Covid-19 pandemic caused by the beta coronavirus SARS-CoV-2 are currently based on RT-qPCR-based diagnostic tests. However, their high cost, moderate throughput and reliance on sophisticated equipment limit widespread implementation. Loop-mediated isothermal amplification after reverse transcription (RT-LAMP) is an alternative detection method that has the potential to overcome these limitations. Here we present a rapid, robust, highly sensitive and versatile RT-LAMP based SARS-CoV-2 detection assay. Our forty-minute procedure bypasses a dedicated RNA isolation step, is insensitive to carry-over contamination, and uses a hydroxynaphthol blue (HNB)-based colorimetric readout, which allows robust SARS-CoV-2 detection from various sample types. Based on this assay we have substantially increased sensitivity and scalability by a simple nucleic acid enrichment step (bead-LAMP), established a pipette-free version for home testing (HomeDip-LAMP), and developed a version with open source enzymes that could be produced in any molecular biology setting. Our advanced, universally applicable RT-LAMP assay is a major step towards population-scale SARS-CoV-2 testing.

NK cell receptor NKG2C deletion and HLA-E variants are risk factors for severe COVID-19 (preprint)

Patients infected with SARS-CoV-2 may show mild infection or may develop severe coronavirus disease 2019 (COVID-19). In the present study, we investigated whether there is an association between the severity of COVID-19 and the naturally occurring human genetic variants in the natural killer (NK) cell NKG2C receptor (NKG2Cwt/del) and its cellular ligand HLA-E (HLA-E*0101/0103). Both factors are essential components of the NKG2C+ NK cell response and important parts of the defence against pulmonary viral infection. NKG2Cdel and HLA-E*0101 were significantly overrepresented in hospitalized patients (p=0.0006 and p=0.01, respectively) and particularly in critically ill patients requiring intensive care (p<0.0001 and p=0.01, respectively), compared to patients with mild symptoms or healthy controls. Both genetic variants were found to be independent risk factors for severe COVID-19. The data highlight that specific NKG2C+ NK cell responses play an important role against SARS-CoV-2 and that variations thereof may significantly influence the severity of disease.