Serum Autoantibodies Differentiate Rheumatoid Arthritis Subgroups

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Presented By: Jaeyun Sung, PhD
Speaker Biography:
Jaeyun (Jae) Sung, PhD, is a computational biologist at Mayo Clinic in Rochester, MN. He holds the positions of Senior Associate Consultant and Assistant Professor in the Divisions of Surgery Research and Rheumatology, and the Center for Individualized Medicine's Microbiomics Program. He received his BS in Chemical Engineering from Georgia Tech, followed by an MS and PhD in Chemical Engineering from the University of Illinois at Urbana-Champaign. Dr. Sung completed postdoctoral fellowships at the Asia-Pacific Center for Theoretical Physics in South Korea, and subsequently at Massachusetts General Hospital and the Broad Institute before joining Mayo Clinic. The primary goal of Dr. Sung s research is to develop novel computational tools to advance precision medicine, with a specific focus on patients with autoimmune/inflammatory disorders. His biomedical data science research group primarily analyzes multi-omic data to discover biomarkers and to understand the relationship between the human microbiome and health. In his free time, Jae enjoys traveling the world, playing sports, and catching up on his favorite podcasts and periodicals.

Webinar: Serum Autoantibodies Differentiate Rheumatoid Arthritis Subgroups
Webinar Abstract:
Patients with rheumatoid arthritis (RA) can be categorized as either anti-citrullinated protein antibody-positive (ACPA+) or‍ negative (ACPA-). In this webinar, Dr. Sung will present his research exploring a broad range of serological autoantibodies to uncover immunological differences between these RA subgroups using data from ACPA+ RA patients, ACPA- RA patients, and matched‍ healthy controls.

Learning Objectives:
Learn how 1600+ IgG autoantibodies from serum were screened, yielding biologically relevant and immunologically significant insights.
Discover the distinct autoantibody profiles identified in ACPA+ and ACPA- patients.
Understand which proteins and their associated biological processes were predominantly targeted by these autoantibodies.
Explore the implications of autoantibody biomarkers in RA subgroups and their correlation with the Clinical Disease Activity Index, a measure of disease activity.
Examine how autoantibody biomarker signatures can enhance patient stratification and diagnostic accuracy in RA.

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