3 research outputs found
cGAS-mediated induction of type I interferon due to inborn errors of histone pre-mRNA processing
International audienceInappropriate stimulation or defective negative regulation of the type I interferon response can lead to autoinflammation. In genetically uncharacterized cases of the type I interferonopathy Aicardi-GoutiĂšres syndrome, we identified biallelic mutations in LSM11 and RNU7-1, which encode components of the replication-dependent histone pre-mRNA-processing complex. Mutations were associated with the misprocessing of canonical histone transcripts and a disturbance of linker histone stoichiometry. Additionally, we observed an altered distribution of nuclear cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS) and enhanced interferon signaling mediated by the cGAS-stimulator of interferon genes (STING) pathway in patient-derived fibroblasts. Finally, we established that chromatin without linker histone stimulates cyclic guanosine monophosphate-adenosine monophosphate (cGAMP) production in vitro more efficiently. We conclude that nuclear histones, as key constituents of chromatin, are essential in suppressing the immunogenicity of self-DNA
A Novel 8-Predictors Signature to Predict Complicated Disease Course in Pediatric-onset Crohnâs Disease: A Population-based Study
International audienceBackground The identification of patients at high risk of a disabling disease course would be invaluable in guiding initial therapy in Crohnâs disease (CD). Our objective was to evaluate a combination of clinical, serological, and genetic factors to predict complicated disease course in pediatric-onset CD. Methods Data for pediatric-onset CD patients, diagnosed before 17 years of age between 1988 and 2004 and followed more than 5 years, were extracted from the population-based EPIMAD registry. The main outcome was defined by the occurrence of complicated behavior (stricturing or penetrating) and/or intestinal resection within the 5 years following diagnosis. Lasso logistic regression models were used to build a predictive model based on clinical data at diagnosis, serological data (ASCA, pANCA, anti-OmpC, anti-Cbir1, anti-Fla2, anti-Flax), and 369 candidate single nucleotide polymorphisms. Results In total, 156 children with an inflammatory (B1) disease at diagnosis were included. Among them, 35% (nâ
=â
54) progressed to a complicated behavior or an intestinal resection within the 5 years following diagnosis. The best predictive model (PREDICT-EPIMAD) included the location at diagnosis, pANCA, and 6 single nucleotide polymorphisms. This model showed good discrimination and good calibration, with an area under the curve of 0.80 after correction for optimism bias (sensitivity, 79%, specificity, 74%, positive predictive value, 61%, negative predictive value, 87%). Decision curve analysis confirmed the clinical utility of the model. Conclusions A combination of clinical, serotypic, and genotypic variables can predict disease progression in this population-based pediatric-onset CD cohort. Independent validation is needed before it can be used in clinical practice