Systematic temporal analysis of transcriptomic datasets using TrendCatcher identifies early and persistent neutrophil activation as a hallmark of severe COVID-19

Study code

Lead researcher
Jalees Rehman

Study type
Data only

Institution or company
Univeristy of Illinois at Chicago

Researcher type

Speciality area
Infection, Genomics and Rare Diseases, COVID


Cells respond to infections by changing the levels of genes. These changes can occur rapidly or slowly, sometimes genes increase and then decrease. We are developing a software program called TrendCatcher that finds the genes which change the most over time. We are especially interested in how COVID-19 changes genes in blood cells over time. By finding the genes that change the earliest, we may be able to understand which patients with COVID-19 will do well and which ones may do poorly. By identifying the patients who are the most vulnerable, one could start treating them early to prevent them from becoming very ill.