Learning to Decode the Immune System to Diagnose Disease

Adaptive published the original proof-of-concept for this project (Emerson, et al. Nat Genet. 2017), demonstrating that shared TCRs can be used as a basis for diagnosing viral infection. Since then, we have further demonstrated the applicability of this work in covid, Lyme and other diseases (see publications). Despite the enormous complexity of the immune response, the elegant simplicity of this approach shows how common immunological solutions to pathogens can be used to provide a window into what the immune system is actively targeting. In principle, this approach can be extended and augmented with antigen-specific binding data to provide diagnostics for cancers, infections and autoimmune diseases. To date, we have sequenced the T-cell repertoires of tens of thousands of individuals affected by one of the several specific diseases we are initially pursuing based on unmet clinical need and our understanding of the underlying immunology:

  • Oncology: Ovarian cancer, Pancreatic cancer.
  • Autoimmune disease: Type I diabetes, Celiac disease, Crohn’s disease.
  • Infectious Disease: COVID-19, Lyme disease.
  • Other diseases with an unmet need for a blood-based diagnostic.

People

Portrait of Pan Deng

Pan Deng

Senior Researcher

Portrait of Liang He

Liang He

Senior Researcher

Portrait of Tie-Yan Liu

Tie-Yan Liu

Distinguished Scientist, Microsoft Research AI for Science

Portrait of Bin Shao

Bin Shao

Senior Principal Research Manager

Portrait of Yingce Xia

Yingce Xia

Principle Researcher