Formulating a gene signature for diagnosis of autoimmune and infectious diseases

Abstract

When patients with an underlying autoimmune condition such as juvenile idiopathic arthritis or lupus report life-threatening symptoms, physicians need to quickly determine whether these symptoms are caused by an acute infection or a complication of their autoimmune condition. As immunosuppressive drugs are harmful to someone undergoing an infection, accurate and timely diagnosis is critical. In recent years, host-response-based diagnostics have shown promise in accurately and non-invasively diagnosing a number of infectious and autoimmune diseases. Here, we collected and curated blood transcriptome profiles of 14,587 patients from 42 countries across 122 independent datasets and grouped them into infectious, autoimmune, and healthy control categories. Using a novel statistical framework, we created two gene signatures from this data: one to differentiate patients with autoimmune or infectious diseases from healthy individuals and another to differentiate between patients with autoimmune or infectious diseases. Both signatures achieve an area under the receiver operating characteristics curve (AUROC) of >0.87 on completely independent datasets. Because our training and testing data included heterogeneity across many factors, these gene signatures can be utilized in diverse clinical populations. Furthermore, these signatures can aid physicians across a broad range of clinical scenarios, where existing diagnostics are invasive, expensive, or non-specific.