Infectious Disease & Biomarker Discovery

Infectious Disease research projects involve the discovery of biomarkers to improve diagnosis, as well as deep phenotyping of human host responses in order to identify therapeutic strategies. Current projects underway in the laboratory, focused include research efforts in COVID-19, Lyme Disease, Sepsis and Influenza.

COVID-19

Understanding how to identify and treat COVID-19, the disease caused by SARS-CoV-2, is of crucial global public health importance. ISB was quick to initiate a coordinated institution wide COVID-19 project, working with several external research and corporate partners, including leveraging our instrumental relationship with Providence St. Joseph Health System and Swedish Medical Center. Data from this project is emerging rapidly with a focus on several key objectives:

• Develop diagnostic assays to detect SARS-CoV-2 infection at low virus load (in recovered patients)
• Identify potential design parameters for T cell vaccines
• Identify key development parameters for novel therapeutics
• Identify potential biomarkers to anticipate cardiac or other health risks associated with COVID-19 disease
• Compose polygenic risk scores to identify patient populations at highest risk of serious health consequences from infection by the SARS-CoV-2 virus

Lyme Disease

Incidence has doubled over the past few decades with ~30,000 confirmed new case per year, which is likely an underestimate due to undiagnosed disease. Current diagnostic tests are only effective several weeks after infection since they rely on the host development of antibodies. Projects in our group are focusing on identifying biomarkers that can be diagnostic of infection at a much earlier time point. Furthermore, we are seeking to identify biomarkers predictive of response to acute antibiotic therapies to clear the infection relative to those who suffer long term consequences of the disease. To date, we have identified several protein biomarkers that show promise on both of these domains.

We continue to leverage in-house proteomic technologies as well as our longitudinal PD3 cloud approaches to better understand Lyme disease infection and progression and potentially identify new therapeutic targets as well.

Current and recent funding for these projects include support from the Bay Area Lyme Foundation and the Wilke Cohen Lyme Disease Project.

Sepsis

Each year, ~2,000,000 people in the U.S. develop sepsis and over 250,000 of these people die. Clinicians need advanced support when they make rapid, high-stakes decisions about sepsis for individual patients. Personalized risk stratification can help save lives and reduce unnecessary and potentially harmful care.

Our lab, through a DoD funded study on post-operative sepsis, has developed blood biomarkers that can predict up to 3 days prior to diagnosis, with a 0.91 combined selectivity/sensitivity score. The current standard of care panel is 0.6 – 0.7. 

We are also collaborating with the Hadlock lab, who are using machine learning on electronic health records, to develop a more accurate, trustworthy risk score for clinicians; and the Heath lab who will leverage their technology to better understand the immune response to Sepsis to identify new therapeutic targets.

Recent papers include:

A biological function based biomarker panel optimization process. Lee MY, Kim TK, Walters KA, Wang K. Sci Rep. 2019 May 14;9(1):7365. doi: 10.1038/s41598-019-43779-2. PMID: 31089177 

Novel metrics for quantifying bacterial genome composition skews. Joesch-Cohen LM, Robinson M, Jabbari N, Lausted CG, Glusman G. BMC Genomics. 2018 Jul 11;19(1):528. doi: 10.1186/s12864-018-4913-5. PMID: 29996771

Whole genome sequence and comparative analysis of Borrelia burgdorferi MM1. Jabbari N, Glusman G, Joesch-Cohen LM, Reddy PJ, Moritz RL, Hood L, Lausted CG. PLoS One. 2018 Jun 11;13(6):e0198135. doi: 10.1371/journal.pone.0198135. eCollection 2018. PMID: 29889842 

mRNA transcript distribution bias between Borrelia burgdorferi bacteria and their outer membrane vesicles. Malge A, Ghai V, Reddy PJ, Baxter D, Kim TK, Moritz RL, Wang K. FEMS Microbiol Lett. 2018 Jul 1;365(13). doi: 10.1093/femsle/fny135. PMID: 29846577