Clinical, Molecular and Functional Biomarkers for PROgnosis, Pathomechanisms and Treatment Strategies of COVID-19 (PROVID) - (PROVID-CAPNETZ)

Overview

The pandemic triggered by the new SARS-CoV-2 presents the German health system with previously unknown challenges. There are currently no effective therapies for the treatment of the SARS-CoV-2 lung disease Covid-19. The aim of the joint project PROVID is to draw conclusions from the often very different clinical appearance of infections with the SARS-CoV-2 pathogen in order to improve patient care through targeted clinical management. The effects of infections with the SARS-CoV-2 pathogen are wide-ranging and include a spectrum from symptomlessness to infections of the upper respiratory tract, uncomplicated but also severe pneumonia with lung failure and high mortality. PROVID will first check whether certain host factors determine the severity and / or the course of Covid-19. Research is also being carried out into whether the molecular and clinical values of Covid-19 patients differ from those of patients with pneumonia caused by other pathogens. In addition, it will be tested whether specific molecular markers describe the severity of the disease and are suitable as an aid for targeted therapy for Covid-19. PROVID is an interdisciplinary joint project made up of three sub-projects that are being implemented at three locations (Charitè-Universitätsmedizin Berlin, Universität Leipzig IMISE and CAPNETZ STIFTUNG / Hannover). PROVID is based on three clinical research platforms with a high track record in recruiting patients with high-quality data and biomaterials on the one hand and guideline-changing results on the other hand: CAPNETZ (competence network CAP, since 2002, world's largest database and biobank for CAP), PROGRESS (Pneumonia Research Network on Genetic Resistance and Susceptibility for the Evolution of Severe Sepsis, since 2007) and CAPSyS (systems medicine of community-acquired pneumonia, since 2014). The COVID-19 patients are recruited into 3 different patient cohorts via these 3 research platforms. 1\. PROVID-CAPNETZ, 2. PROVID-PROGRESS, 3. PROVID-CAPSyS.

Infections with the novel Severe Acute Respiratory Syndrome - Coronavirus-2 (SARS-CoV-2) manifest with a broad spectrum of clinical presentations, ranging from asymptomatic to upper respiratory tract infections, uncomplicated pneumonia and severe pneumonia with respiratory failure and high lethality. Despite more than 1.7 Mio. documented infections worldwide, a profound lack of knowledge impedes clinical management and the development of therapies. COVID-19-associated pneumonia and lung injury differ in relevant details from any of the known types of pneumonia that cause respiratory failure, including viral infections like influenza or MERS-CoV. Thus, it is unclear whether specific decision guidelines established for pneumonia are applicable or whether these need to be refined for COVID-19. That is why the PROVID consortium was founded with BMBF funding. The PROVID consortium thus aims to characterize the host- and virusdependent mechanisms associated with the clinical appearance of COVID-19 to improve patient care through advances in risk stratification and clinical management. Specifically, we aim to test the hypotheses that, 1. host factors (transcriptional response/RNA, proteins, antibodies) determine the severity and/or course of COVID-19, 2. molecular and clinical determinants of COVID-19 differ from those previously deciphered in other types of pneumonia and they can be used as molecular predictors for disease progression, 3. specific molecular markers of severe disease can be tested as therapeutic targets for COVID-19. 4. In addition to presently pursued antivirals and immunomodulators, the stabilization of the pulmonary barrier function could establish a third line for an effective therapy. In PROVID we synergistically combine our expertise in the areas of pneumonia and ARDS, infection immunology, molecular and medical virology, lung physiology and endothelial cell biology, experimental lung infection research, statistics and bioinformatics.