Predictive Biomarkers of Post-COVID syndrome

Currently more hundred million people world-wide were infected with the virus that causes COronaVIrus dDsease 2019 (COVID-19), with an overall mortality rate of approximately 2%. While majority of the patients recovers from the COVID-19 disease, approximately 10 to 30 % of the patients suffers from the so-called long COVID or post COVID disease, which means long and incomplete recovery from the infection. Patients with long COVID syndrome complain about diverse symptoms, such as fatigue, exhaustion, headache, debility, cough, chest pain, or palpitation and inability to stand up due to quickly developing tachycardia, or drop of the blood pressure. Several patients are off sick for months, or even over one year. In accordance to the several organ-related symptoms, long COVID syndrome is called as a new multi-organ disease. In spite of intensive research, currently insufficient data exist to explain the reason of the disease, and there is no therapeutics against long-COVID syndrome. The aim of our study is to investigate several possible biomarkers from the blood, which are in association with the altered immunological response after COVID-19 infection and are correlated with the clinical symptoms. We will include 300 patients with long COVID syndrome in the study, as well as 50 patients with ischemic heart disease (caused by subclinical chronic inflammation, leading to atherosclerotic changes of the different vessel wall layers), and 50 healthy controls. Individuals in the control groups should have had at least one COVID-19 vaccine, and no proven COVID infection. All patients are invited to complete the 6-month follow-up to control the disease course and laboratory parameter. Patients will undergo electrocardiogram, heart ultrasound investigation, lung function test, blood pressure measurement and laboratory investigations. The blood level of ACE2 (receptor of the SARS-COV-2 virus cell entry), protein biomarker panel and further molecular biomarkers will be investigated by high-throughput molecular biological technologies, and the findings will be validated by usual laboratory techniques, such as Western-blot or quantitative PCR. Data will be collected in a n network database, containing all clinical and laboratory and imaging parameter, and will be analysed by contemporary bioinformatical network analysis. We will construct a computer-based target prediction model, with which we will search therapeutics for long COVID syndrome. Additionall y, our cluster and network analysis will allow to predict the presence and outcome of the long COVID syndrome.