Tiannan talks about the Guomics COVID-19 research progresses in HUPO connect 2020
In search of clues, Guo and colleagues analyzed hundreds of molecular changes in blood samples collected from 53 healthy people and 46 people with COVID-19, including 21 with severe disease involving respiratory distress and decreased blood-oxygen levels. Their studies turned up more than 470 proteins and metabolites that differed in people with COVID-19 compared to healthy people. Of those, levels of about 300 were associated with disease severity. Further analysis revealed that the majority of proteins and metabolites on the list are associated with the suppression or dysregulation of one of three biological processes. Two processes are related to the immune system, including early immune responses and the function of particular scavenging immune cells called macrophages. The third relates to the function of platelets, which are sticky, disc-shaped cell fragments that play an essential role in blood clotting. Such biological insights might help pave the way for potentially effective new ways to treat COVID-19 down the road. Next, the researchers turned to “machine learning” to explore the possibility that such molecular changes also might be used to predict mild versus severe COVID-19.
NIH Director's Blog:
To ensure that people with coronavirus disease 2019 (COVID-19) get the care they need, it would help if a simple blood test could predict early on which patients are most likely to progress to severe and life-threatening illness—and which are more likely to recover without much need for medical intervention. Now, researchers have provided some of the first evidence that such a test might be possible.
Using proteomics in big data-driven precision medicine for the fight against prostate cancer.
“I got diagnosed with prostate cancer on Friday 13th. As my doctor spoke about Gleason scores, probabilities of survival, incontinence and impotence, why surgery would be good and what kind would make the most sense, his voice literally faded out like every movie or TV show about a guy being told he had cancer…,” said Mike.* “Right after I got the news, I promptly got on my computer and Googled ‘men who had prostate cancer.’ As I learned more about my disease (one of the key learnings is not to Google ‘people who died of prostate cancer’ immediately after being diagnosed with prostate cancer), I was able to wrap my head around the fact that I was incredibly fortunate. Fortunate because my cancer was detected early enough to treat and also because my internist gave me a test he didn’t have to. That test saved my life.” Three months later, after successful treatment, Mike was cancer-free.
Shortly after our last release of coronavirus research findings , Westlake University released another breakthrough in COVID-19 research. Tiannan Guo and co-workers identified characteristic molecular changes in the sera from severe #COVID-19 cases, allowing prediction of severe cases using a machine learning model based on serum protein and metabolite biomarkers.
The Guomics Laboratory of Big Proteomic Data, led by Assistant Professor Tiannan Guo, performed the first proteomic and metabolomic characterization of #COVID-19 sera, and managed to identified a series of characteristic biomarkers indicating the severity of COVID-19 patients.
Unique insights from thought leaders and researchers in the field of precision medicine, posing and discussing important questions about current challenges and future direction.
High-throughput proteomics of FFPE tissue samples