Identification and characterization of Long COVID-19 patients by whole blood transcriptomics

• Applicants: Dr. Anna Aschenbrenner; Professor Dr. Robert Bals; Professor Ezio Bonifacio, Ph.D.; Professor Dr. Julien Gagneur; Professor Dr. Stefan Janssen; Professorin Dr. Verena Keitel-Anselmino; Professor Dr. Andreas Keller; Privatdozent Dr. Florian Kurth; Professor Dr. Ingo Kurth; Dr. Denise Kühnert; Professor Dr. Peter Nürnberg; Professor Stephan Ossowski, Ph.D.; Dr. Anna Poetsch; Professor Dr. Olaf Riess; Professor Philip Caspar Rosenstiel, Ph.D.; Professor Dr. Leif Erik Sander; Professor Dr. Joachim L. Schultze; Professor Oliver Stegle, Ph.D.; Dr. Thomas Ulas
• Subject Area: General Genetics and Functional Genome Biology ; Clinical Infectiology and Tropical Medicine
• Term: from 2021 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 466168626

Increasing evidence indicates a rising prevalence for Long COVID-19, a recently coined term for non-recovering patients with persisting clinical symptoms for more than six months after acute COVID-19. Although a derailed immune system has been postulated as a possible cause, there are currently no means of identifying Long COVID-19 patients early post acute COVID-19. We have recently demonstrated the use of whole blood transcriptomics to build disease classifiers for acute COVID-19 as well as dissect disease heterogeneity by molecular phenotypes. The DeCOI (German COVID-19 Omics) network has established patient cohorts at multiple sites in Germany, which have already proven tremendously valuable in the analysis and understanding of acute COVID-19. Bringing together clinical scientists, DFG-funded sequencing centers, and computational experts, we will combine the knowledge and expertise in clinical infectiology, genomics and machine learning to shed light on Long COVID-19. We will use the samples from these cohorts to establish whole blood transcriptome signatures and classifiers to identify Long COVID-19 patients and determine their molecular phenotypes to elucidate disease heterogeneity. Further, we will identify possible genetic susceptibility for Long COVID-19 by aberrant expression analysis as well as assessing blood-derived microbial profiles as potential biomarker. Collectively, these analyses will enable the identification of molecular mechanisms of Long-COVID-19-related biology and potential therapeutic targets for further exploitation in clinical trials.

• DFG Programme: Research Grants