Differential associations between SARS-CoV-2 infection, perceived burden of the pandemic and mental health in the German population-based cohort for digital health research (preprint)

Introduction: Understanding the potential adverse effects of the Covid-19-pandemic remains a challenge for public mental health. In this regard, the differentiation between potential consequences of actual infection with SARS-CoV-2 and the subjective burden of the pandemic due to measures and restrictions to daily life remains elusive. Methods: Here we investigated the differential association between infection with SARS-Cov-2 and subjective burden of the pandemic in a study cohort of 7601 participants from the German population-based cohort for digital health research (DigiHero), who were recruited between March 4th and April 25th 2022. Data was collected using the online survey tool LimeSurvey between March and October 2022 in consecutive surveys, which included questionnaires on infection status and symptoms following COVID-19 as well as retrospective assessment of the subjective burden of the pandemic. Results: We observed an association of a past SARS-CoV-2 infection on deteriorated mental health related symptoms, whereas no association or interaction with burden of the pandemic occurred. The association was driven by participants with persistent symptoms 12 weeks after acute infection. On a symptom specific level, neuropsychiatric symptoms such as exhaustion and fatigue, concentration deficits as well as problems with memory function were the primary drivers of the association. Conclusion: Our findings underscore the impact of SARS-CoV-2 infections on mental health in patients suffering from ongoing symptoms 12 weeks after infection. As the association between SARS-CoV-2 infection and mental health appeared more pronounced in populations with higher vulnerability for mental disorders, increased attention should be dedicated towards these subgroups regarding the prevention of infection.

Liquid biomarkers of macrophage dysregulation and circulating spike protein illustrate the biological heterogeneity in patients with post-acute sequelae of COVID-19 (preprint)

Post-acute sequelae of COVID-19 (PASC) are long-term consequences of SARS-CoV-2 infection that can substantially impair quality of life. Underlying mechanisms ranging from persistent virus to innate and adaptive immune dysregulation have been discussed. Here, we profiled plasma of 181 individuals from the cohort study for digital health research in Germany (DigiHero) including individuals after mild to moderate COVID-19 with or without PASC and uninfected controls. We focused on soluble factors related to monocyte/macrophage biology and on circulating SARS-CoV-2 spike (S1) protein as potential biomarker for persistent viral reservoirs. At a median time of eight months after infection, we found pronounced dysregulation in almost all tested soluble factors including both pro-inflammatory and pro-fibrotic cytokines. These perturbations were remarkably independent of ongoing symptoms, but further correlation and regression analyses suggested PASC specific patterns involving CCL2/MCP-1 and IL-8 as well as long-term persistence of high IL-5 and IL-17F levels. None of the analyzed factors correlated with the detectability or levels of circulating S1 indicating that this represents an independent subset of patients with PASC. This data confirms prior evidence of immune dysregulation and persistence of viral protein in PASC and illustrates its biological heterogeneity that still awaits correlation with clinically defined PASC subtypes.

Rapid hypermutation B cell trajectory recruits previously primed B cells upon third SARS-CoV-2 mRNA vaccination (preprint)

High antibody affinity against the ancestral SARS-CoV-2 strain seems to be necessary (but not always sufficient) for the control of emerging immune-escape variants. Therefore, aiming at strong B cell somatic hypermutation - not only at high antibody titers - is a priority when utilizing vaccines that are not targeted at individual variants. Here, we developed a next-generation sequencing based SARS-CoV-2 B cell tracking protocol to rapidly determine the level of immunoglobulin somatic hypermutation at distinct points during the immunization period. The percentage of somatically hypermutated B cells in the SARS-CoV-2 specific repertoire was low after the primary vaccination series, evolved further over months and increased steeply after boosting. The third vaccination mobilized not only naive, but also antigen-experienced B cell clones into further rapid somatic hypermutation trajectories indicating increased affinity. Together, the strongly mutated post-booster repertoires and antibodies deriving from this may explain why the booster, but not the primary vaccination series, offers some protection against immune-escape variants such as Omicron B.1.1.529.

From online data collection to identification of disease mechanisms: The IL-1beta, IL-6 and TNF-alpha; cytokine triad is associated with post-acute sequelae of COVID-19 in a digital research cohort (preprint)

Post-acute sequelae of COVID-19 (PASC) emerge as a global problem with unknown molecular drivers. In a digital epidemiology approach, we rapidly recruited 8,077 individuals out of 129,733 households in Halle (Saale) to the cohort study for digital health research in Germany (DigiHero). These responded to a basic questionnaire followed by a PASC-focused survey and blood sampling in case of prior positive SARS-CoV-2 testing in their household. The presented analysis is based on the first 318 DigiHero participants, the majority thereof after mild infections. PASC were reported in 67.8% of cases, consisted predominantly in fatigue, dyspnea and concentration deficit, persisted in 60% over the follow-up period of on average eight months and their resolution was unaffected by post-infection vaccination. PASC was not associated with post-COVID-19 autoantibodies, but with elevated levels of IL-1{beta}, IL-6 and TNF-. Blood profiling and single-cell data from validation cohorts with early infection suggested the induction of these cytokines in COVID-19 lung pro-inflammatory macrophages creating a self-sustaining feedback loop. Our data indicate a long-lasting cytokine triad -potentially underlying PASC symptoms - to be driven by macrophage primed during infection. We demonstrate how the combination of digital epidemiology with selective biobanking can rapidly generate hints towards disease mechanisms.

From Online Data Collection to Identification of Disease Mechanisms: The IL-1ß, IL-6 and TNF-α Cytokine Triad Is Associated With Post-Acute Sequelae of COVID-19 in a Digital Research Cohort (preprint)

Background: The COVID-19 pandemic called for a fast conduct of studies to establish vaccines and therapies, but also to identify the natural history and drivers of post-acute sequelae of COVID-19 (PASC). Digital epidemiology may serve this aim by rapidly generating large sample sizes allowing dedicated analyses of biomaterial in a subsample of interest.Methods: Of 129,733 households in Halle (Saale) invited to the cohort study for digital health research in Germany (DigiHero), 8,077 individuals participated, among these 919 that reported prior positive SARS-CoV-2 testing in their households. These were invited to respond to a PASC-focused questionnaire and to undergo blood sampling for cytokine and autoantibody profiling. Cytokine profiles were validated in a second cohort with early infections and single-cell transcriptomics datasets.Results: The analysis is based on the first 318 DigiHero participants, 258 thereof on average eight months after mostly mild infection. PASC were reported in 67.8% of cases and consisted predominantly in fatigue, dyspnea and concentration deficit. The recovery from PASC was not associated with post-infection vaccination suggesting that it may not be driven by a cryptic SARS-CoV-2 reservoir. We confirmed the high percentage of individuals with autoantibodies after COVID-19, but found no association with PASC. While our data show that a broad range of cytokines remain deregulated long after infection, IL-1ß, IL-6 and TNF-α represented a triad that was associated with PASC. Blood profiling and single-cell data from early infection indicated that these cytokines are induced in COVID-19 lung pro-inflammatory macrophages creating a feedback loop that may trigger their long-term activation.Conclusion: We provide evidence for a long-lasting cytokine signature potentially underlying many of the clinical symptoms of PASC that may be driven by macrophage primed during acute infection. This study demonstrates how the combination of digital epidemiology with selective biobanking can rapidly generate hints towards disease mechanisms.Funding Information: This project was partially funded by the CRC 841 of the German Research Foundation (to MB) as well as by the Medical Faculty of the Martin-Luther-University Halle (Saale).Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: The study was approved by the institutional review board (approval numbers 2020-076) and conducted in accordance with the ethical principles stated by the Declaration of Helsinki. Informed written consent was obtained from all participants or legal representatives.

Machine Learning Identifies ICU Outcome Predictors in a Multicenter COVID-19 Cohort. (preprint)

Background. Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes.Methods. A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results. 1,039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions. Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models.Trial registration. “ClinicalTrials” (clinicaltrials.gov) under NCT04455451

Landscape of Public T Cell Receptors Associated with Recovery from COVID-19 (preprint)

T cells play an essential role in COVID-19, but characteristics of beneficial clones remain unclear. By analysis of clonal trajectories, we identified recovery-associated expanding T cell clones many of which carrying public T cell receptors (TCRs). Mining the immune repertoires of unrelated COVID-19 cases for these sequences revealed T cells with exact TCR complementarity-determining region 3 identity that were more abundant in recovering than in fatal cases. These TCRs were also found in subjects not previously exposed to the virus, with lower representation in repertoires from risk groups like aged individuals or cancer patients. Together, our data indicate that a significant part of the recovery-associated T cell response in COVID-19 may be mediated by public TCRs that are present in repertoires of unexposed individuals. The lower representation of these clones in repertoires of risk groups or failure to expand such clones may contribute to more unfavorable clinical COVID-19 courses.Funding: This project was partially funded by the CRC 841 of the German Research Foundation (toMB) as well as by the Martin-Luther-University Halle (Saale).Conflict of Interest: The authors declare no competing interests.Ethical Approval: Blood collection of COVID-19 patients was performed under institutional review board approvals number 2020-039 and 11/17. Blood collection of pre-pandemic samples was performed under approval of ethics committee of the medical association Hamburg (project number PV4767) and the ethics committee of the medical faculty of MartinLuther-University Halle-Wittenberg (project number 2014-75). Written informed consent was received from all participants. The study has been performed in accordance with the declaration of Helsinki of 1975.

Living Repository of Millions of T and B Cell Receptor Sequences from Patients with COVID-19 (preprint)

We profiled adaptive immunity in COVID-19 patients with active infection or after recovery and created a living repository of currently >14 million B and T cell receptor (BCR/TCR) sequences from blood of these patients. The B cell response showed converging IGHV3-driven BCR clusters closely associated with SARS-CoV-2 antibodies. Clonality and skewing of TCR repertoires was associated with interferon type I and III responses, early CD4+/CD8+ activation and counterregulation by BTLA, Tim-3, PD-1, TIGIT and CD73. Tfh, Th17-like and nonconventional (but not classical anti-viral) Th1 polarizations were induced. COVID-19 specific T cell responses were driven by TCR clusters shared between patients with a characteristic trajectory of clonotypes and traceability over the disease course. Our cohort – especially the subset with effective viral clearance – reveals fundamental insight into adaptive immunity to SARS-CoV-2 with the living repository providing a bottleneck resource for the scientific community urgently needed to inform therapeutic concepts and vaccine development.Conflict of Interest: The authors declare no competing interests.Ethical Approval: Blood collection was performed under institutional review board approvals number 2020-039 and 11/17.