5 research outputs found
Diagnostic yield of next-generation sequencing in very early-onset inflammatory bowel diseases: a multicenter study (vol 12, pg 1104, 2021)
Transplantation and immunomodulatio
La cryptosporidiose, une cause de diarrhée aiguë : revue de la littérature et étude rétrospective des cas dans le département de pédiatrie du CHU de Rouen
International audienc
RĂ©sultats prĂ©liminaires de lâĂ©tude Profil-Eo : diffĂ©rents profils dâĆsophagite Ă Ă©osinophiles (allergique et non allergique) selon de multiples immunomarquages tissulaires
Introduction (contexte de la recherche): LâĆsophagite Ă Ă©osinophiles (EoE) a une physiopathologie encore incomplĂštement comprise. Sa prĂ©sence accrue chez les patients atopiques et Ă©galement chez des patients sans antĂ©cĂ©dent atopique fait suggĂ©rer lâexistence de phĂ©notypes cliniques et physiopathologiques diffĂ©rents.Objectif: Ăvaluer lâimplication de lâallergie notamment alimentaire dans lâEoE en recherchant lâexistence de plusieurs phĂ©notypes dâEoE : allergique (A) et non allergique (nA) selon diffĂ©rents immunomarquages
Diagnostic yield of next-generation sequencing in very early-onset inflammatory bowel diseases: A multicentre study
Background and Aims An expanding number of monogenic defects have been identified as causative of severe forms of very early-onset inflammatory bowel diseases [VEO-IBD]. The present study aimed at defining how next-generation sequencing [NGS] methods can be used to improve identification of known molecular diagnosis and to adapt treatment. Methods A total of 207 children were recruited in 45 paediatric centres through an international collaborative network [ESPGHAN GENIUS working group] with a clinical presentation of severe VEO-IBD [n = 185] or an anamnesis suggestive of a monogenic disorder [n = 22]. Patients were divided at inclusion into three phenotypic subsets: Predominantly small bowel inflammation, colitis with perianal lesions, and colitis only. Methods to obtain molecular diagnosis included functional tests followed by specific Sanger sequencing, custom-made targeted NGS, and in selected cases whole exome sequencing [WES] of parents-child trios. Genetic findings were validated clinically and/or functionally. Results Molecular diagnosis was achieved in 66/207 children [32%]: 61% with small bowel inflammation, 39% with colitis and perianal lesions, and 18% with colitis only. Targeted NGS pinpointed gene mutations causative of atypical presentations, and identified large exonic copy number variations previously missed by WES. Conclusions Our results lead us to propose an optimised diagnostic strategy to identify known monogenic causes of severe IBD
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