Updated antibody research by Lupus Foundation of America Gary S. Gilkeson Career Development Awardee May Choi identifies subgroups of lupus patients with different outcomes based on long-term autoantibody data with the aid of artificial intelligence. An autoantibody is a type of protein produced when the body’s immune system is attacking itself, promoting inflammation and tissue damage. Antibody blood tests are used to help clinicians diagnose the disease. 

A group of 805 people newly diagnosed with lupus were examined. Their demographic, clinical and blood was analyzed for five years.

The analysis revealed four autoantibody profiles of lupus outcomes:

  1. Cluster 1 – Identified by the biomarkers anti-Sm and anti-RNP – typically youngest at disease onset and of Asian or African ancestry. At year 5, this group had the highest disease activity and most likely to be on immunosuppressive therapy.
  2. Cluster 2 – Low frequency of anti-dsDNA and high anti-DFS70 – typically oldest at disease onset. At year 5, this group had the lowest disease activity and least likely to have kidney disease and to be on immunosuppressive medications.
  3. Cluster 3 – High frequency of antiphospholipid antibodies – typically of European ancestry, elevated body mass index. At year 5, most likely to have kidney disease and neuropsychiatric involvement that included strokes and seizures.
  4. Cluster 4 – High frequency of anti-SSA/Ro60, anti-SSB/La, anti-Ro52/TIM21, anti-ribosomal P, anti-dsDNA anti-histone – At year 5, exhibited low complements (proteins that protect the body against infections).

“Better lupus disease identification and prediction of disease outcome can help clinicians implement a more personalized approach to effectively monitor, evaluate, and treat patients.” Says Dr. May Choi lead study author and Gary S. Gilkeson Career Development Awardee with the Lupus Foundation of America.

Learn more about Dr. Choi and her research efforts. 

Read this study