Predicting & Preventing Long-Haul COVID
As it relates to COVID-19, there seems to be an incredible amount of interest in the death rate which happens to be exceedingly, exceedingly low. Why I find this challenging is because there is another problem associated with this infection that isn’t getting the type of attention that it deserves. This goes by the common name, long-haul Covid. This simply means that after “recovering” from the initial infection, a fairly significant percentage of individuals continue to experience symptoms that at times may be debilitating.
Research just published has demonstrated an ability to actually predict who is at the greatest risk for developing long-term symptoms after COVID-19 infection. We will be interviewing today Dr. James Heath and Dr. Yapeng Su from the Institute for Systems Biology at the University of Washington. They have identified four characteristics that are clearly and strongly associated with persistent symptoms of Covid-19 and as such, this is important information for all of us. They include:
The presence of particular autoantibodies
- A high viral (RNA) load
- Type 2 diabetes
- Reactivation of the Epstein-Barr virus, which sits latent in the blood of most people following a childhood infection
I’ll tell you more about these dedicated researchers in the intro to the video, but you can find their bios below. Enjoy this interview!
- 0:00: Intro
- 3:40: Important Study on Longterm Effects
- 7:11: Predicting Severity of Disease
- 15:00: 4 Ways to Predict
- 21:30: Chronic EBV
- 26:00: Preventing Long-Haul Covid
- 39:08: Conclusion
James R. Heath
James Heath serves as the President of the Institute for Systems Biology in Seattle WA. Until early 2018 he was the Elizabeth W. Gilloon Professor of Chemistry at Caltech. For 15 years he directed the National Cancer Institute funded NSB Cancer Center program.
Dr. Heath received a BSc in 1984 from Baylor University and a PhD in chemistry in 1988 from Rice University, where he was the principal student involved in the Nobel Prize–winning discovery of C60 and the fullerenes. He was a Miller Fellow at UC Berkeley from 1988 to 1991 and served on the technical staff at IBM Watson Labs from 1991 to 1993. In 1994 he joined the faculty at UCLA. He founded the California NanoSystems Institute in 2000 and served as its director until moving to Caltech.
Dr. Heath’s lab works on fundamental problems at the interface of the chemical, physical, biological, and biomedical sciences, with focus areas of molecular biotechnologies and oncology. Dr. Heath has published around 400 refereed scientific publications with an h-index of 122.
He has received numerous awards, including a Public Service Commendation from California Governor Grey Davis, the Director’s Service Award from the NCI, the Sackler Prize, Irving Weinstein Award from the AACR, and he was named by Forbes in 2011 as one of the 7 most powerful innovators in the world.. He has founded several companies, including Integrated Diagnostics (sold to Biodesix in 2018), Indi Molecular, PACT Pharma, Sofie Biosciences, ISB BioAnalytica, and Isoplexis (now a public company).
Dr. Yapeng Su
Dr. Su received his Ph.D. degree at Caltech, co-advised by Prof. James R. Heath and Prof. David Baltimore. Yapeng’s Ph.D. research resided at the intersection of physical science, biotechnology, and systems biology with a particular focus on cancer. His research utilized systems biology approaches and various single-cell technologies to tackle one of the biggest problems in cancer: drug resistance. His Ph.D. thesis was awarded the highest honor of the Division of Chemistry and Chemical Engineering at Caltech.
After obtaining his Ph.D., Yapeng conducted a brief postdoc research scientist in Prof. Leroy Hood’s lab at the Institute for Systems Biology. In close collaboration with a group of world-leading immunologists (Prof. Mark M. Davis, Prof. Phil Greenberg, Prof. Raphael Gottardo, Prof. James R Heath, Prof. Jeff Bluestone, Prof. Lewis Lanier, Prof. Alan Aderem), Yapeng’s research in the Hood lab utilizes data science, multi-omic bulk, and single-cell analysis to investigate the systems immunology of COVID-19. Currently, Yapeng is a Mahan Fellow at the Fred Hutch Cancer Research Center. His research utilized systems-level big data and machine learning to provide rationales on how to better engineer live immune cells as an effective therapy for treating cancer.