Jake Chen, Ph.D., chief bioinformatics officer at UAB Informatics Institute, is the latest winner of the School of Medicine’s Featured Discovery. This initiative celebrates important research from School of Medicine faculty members.
Chen and colleagues’ paper, “PAGER-CoV: a comprehensive collection of pathways, annotated gene-lists, and gene signatures for coronavirus disease studies,” was recently published in Nucleic Acids Research.
PAGER-CoV is a web-based database curated specifically for COVID-19 functional genomics research. The cutting-edge database holds nearly 12,000 pieces of genetic information called PAGs, which stand for “pathways, annotated gene-lists, and gene-signatures,” 1,549 candidate drug targets, and almost 20 million PAG-to-PAG association relationships on SARS-CoV-2.
Chen says, “A year after COVID-19 was declared a ‘pandemic,’ it has become increasingly urgent to understand the precision medicine of COVID-19, such as what downstream events following the SARS-CoV-2 infection have taken place in different populations, leading some to critical conditions while others cure with minimal symptoms.”
PAGER-CoV will be an essential knowledge base to help characterize the different biochemical processes taking place in the bodies of COVID-19 “long haulers,” which can be quite different from patients who recovered completely.
Moreover, PAGER-CoV can help biomedical researchers interpret RNA-sequencing, single-cell RNA-sequencing, and proteomics study results to better understand COVID-19 host response under various conditions. This can lead to tailored intervention strategies for treating COVID-19 patients.
As the nation considers the one-year anniversary of the COVID-19 pandemic, modern and progressive technology like PAGER-CoV is responsible for the rapid understanding of SARS-CoV-2.
Because of researchers and scientists like Chen, there is hope.
Read the full publication here.
The School of Medicine communications staff sat down with Dr. Chen to gain insights about the research of this study, UAB, and the science community.
Q: What compelled you to pursue this research?
In the spring of 2020, our research routine was disrupted by COVID. We conceived this project to leverage our strengths in bioinformatics research and available student time for literature curation.
Q: What was your most unexpected finding?
There was an inadequate description of biological pathways following coronavirus infection in humans. By constructing data for PAGER-CoV, we observed that SARS-CoV-2 infection-induced biological processes, which include inflammation, immune system regulation, organ damage, and organ repair, can be extensive—corresponding to every clinical symptom described in clinical studies.
For example, COVID-19 has been found to cause neurological systems breakdowns in some patients. In PAGER-CoV, we identified several neuroimmune-related pathways, annotated gene-lists, and gene signatures (PAGs) within close neighborhoods of SARS-CoV-2 infection-related genes.
Q: How do you feel your research will impact the science community and its relevance to human disease?
Biomedical researchers who are interested in developing tailored therapeutic solutions for COVID-19 should find PAGER-CoV useful. They can search the database to analyze what PAGs from prior non-COVID biomedical studies may also be enriched within the input gene list. Moreover, they can navigate these enriched PAGs to their upstream, downstream, or related PAG neighbors such that we can construct global pictures of what unique biological processes may have taken place in their studied patient samples.
Q: When did you know you had an important discovery?
The discovery has just started with our tool. We computed all the SARS-CoV-2 related PAG-to-PAG relationships using computer algorithms developed for studying other human diseases such as cancer. When we enter the input gene, e.g., “ACE2,” and can navigate to numerous immunity-related PAGs in the PAGER-CoV database, we know that the database would provide not only discovery opportunities for us but many biological researchers asking similar types of questions.
Q: How has being at UAB and living in Birmingham affected your research?
In our UAB lab named “ai.MED” we work on a broad set of disease biology problems using bioinformatics, systems biology modeling, and machine learning techniques. This work was made possible thanks to the generous support of UAB, the School of Medicine, and the UAB Informatics Institute. The interdisciplinary culture and the prior investment in the biomedical informatics infrastructure enabled us to respond quickly to the pandemic, leading to public sharing and research publication in only a few months.
Q: What made you come to UAB?
I was recruited to the newly founded Informatics Institute in 2016 from Indiana University School of Informatics. I was intrigued by the opportunity to perform bioinformatics research in collaboration with clinicians and translational researchers.
Q: What do you find makes the science community here (at UAB) unique?
The availability of diverse expertise across virtually every aspect of medicine. The interdisciplinary research collaboration culture. World-class scientists as colleagues. And smart, hard-working trainees.