Kenneth Smith, MD, PhD
University of Cambridge
Title: Transcriptional Prediction of Outcome in SLE
The Study and What It Means to Patients
“We have discovered that lupus patients who develop more severe disease have a distinctive pattern of genes turned on in their white blood cells. My group will investigate whether this gene pattern can be used as a practical test for long-term lupus prognosis. Such a predictive test would allow for safer and more effective personalized treatment. We will also explore what causes this gene pattern, in the search for new treatment strategies.”
Like other autoimmune diseases, lupus behaves differently from person to person, with some people having an aggressive course while others have a more benign disease. When lupus develops doctors need to treat it “blind” – as they have no way of predicting which patients have naturally benign disease, requiring minimal treatment, and those who will require more intensive maintenance treatment. This is a major problem for patients and for the healthcare system. It means that patients who need more intensive therapy may not get it early, or that excessive and unnecessary treatment might expose patients to significant side-effects. Poorly targeted therapy also has a financial cost.
We have used “genomic” technology to measure the genes turned on in blood white cells in patients with lupus. Analysing this genomic data using advanced computational techniques has resulted in the discovery of a biomarker that predicts outcome in four different conditions; lupus, Crohn’s disease, ulcerative colitis, and vasculitis. We will recruit a further cohort of patients to confirm that this biomarker is useful in lupus, paving the way for its introduction to the clinic as a test predicting outcome. We will also study what drives these gene activation changes, in the expectation we will uncover new immune pathways controlling lupus that might lead to new treatment avenues in the future.
This project is built around recruitment of a well-characterised SLE patient cohort to be studied before and after treatment, which should replicate a CD8 T cell prognostic signature that we have previously described, allowing its adoption as a prognostic biomarker in the clinic. It will also allow us to begin to examine the biology underlying the signature in SLE, complementing work in other diseases and in particular examining the role played by interferon in determining long-term outcome through its effect on T cell exhaustion. This might allow induction of exhaustion in defined patients through co-stimulation or interferon blockade.