Interferon signaling gene expression as a diagnostic biomarker for monogenic interferonopathies.

Interferon signaling gene (ISG) expression scores are potential markers of inflammation with significance from cancer to genetic syndromes. In Aicardi Goutières Syndrome (AGS), a disorder of abnormal DNA and RNA metabolism, this score has potential as a diagnostic biomarker, although the approach to ISG calculation has not been standardized or validated. To optimize ISG calculation and validate ISG as a diagnostic biomarker, mRNA levels of 36 type I interferon response genes were quantified from 997 samples (including 334 AGS), and samples were randomized into training and test datasets. An independent validation cohort (n = 122) was also collected. ISGs were calculated using all potential combinations up to 6 genes. A 4-gene approach (IFI44L, IFI27, USP18, IFI6) was the best-performing model [area under the curve (AUC) of 0.8872 (training dataset), 0.9245 (test dataset)]. The majority of top performing gene combinations included IFI44L. Performance of IFI44L-alone was 0.8762 (training dataset) and 0.9580 (test dataset) by AUC. The top approaches were able to discriminate cases of genetic interferonopathy from control samples. This study validates the context of use for the ISG score as a diagnostic biomarker and underscores the importance of IFI44L in diagnosis of genetic interferonopathies.