1. Cystic fibrosis–related diabetes onset can be predicted using biomarkers measured at birth
- Author
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Emmanuelle Brochiero, Pearce G. Wilcox, Lara Bilodeau, Mays Merjaneh, Nancy Morrison, Lisa J. Strug, Angela Hillaby, Julie Avolio, Katherine Keenan, Lynda Lazosky, Jennifer Itterman, Michael D. Parkins, Émilie Maille, Naim Panjwani, Mark A. Chilvers, Lei Sun, Jennifer Pike, Richard van Wylick, Yu Chung Lin, Raquel Consunji-Araneta, Caroline Burgess, Lorna Kosteniuk, Lori Fairservice, Christine Donnelly, Natalie Henderson, Damien Adam, Scott M. Blackman, Dimas Mateos-Corral, Bradley S. Quon, Mary Jackson, Janna Brusky, Felix Ratjen, Elizabeth Tullis, Garry R. Cutting, Clare Smith, Melinda Solomon, Harriet Corvol, Valerie Levesque, Daniel Hughes, Fan Lin, Nathalie Vadeboncoeur, Candice Bjornson, Yves Berthiaume, Guillaume Côté-Maurais, Anne L. Stephenson, Winnie Leung, Shaikh Iqbal, Jiafen Gong, Johanna M. Rommens, Mary Jane Smith, Paula Barrett, Joe Reisman, Terry Viczko, Katie Griffin, Danny Veniott, Vanessa McMahon, Stéphanie Bégin, April Price, Emma Karlsen, and Andrea Dale
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Oncology ,medicine.medical_specialty ,business.industry ,Trypsinogen ,Cystic fibrosis-related diabetes ,Prevalence ,medicine.disease ,Cystic fibrosis ,Article ,Human genetics ,chemistry.chemical_compound ,chemistry ,Disease severity ,Diabetes mellitus ,Internal medicine ,Medicine ,business ,Genetics (clinical) ,Genetic association - Abstract
Purpose Cystic fibrosis (CF), caused by pathogenic variants in the CF transmembrane conductance regulator (CFTR), affects multiple organs including the exocrine pancreas, which is a causal contributor to cystic fibrosis–related diabetes (CFRD). Untreated CFRD causes increased CF-related mortality whereas early detection can improve outcomes. Methods Using genetic and easily accessible clinical measures available at birth, we constructed a CFRD prediction model using the Canadian CF Gene Modifier Study (CGS; n = 1,958) and validated it in the French CF Gene Modifier Study (FGMS; n = 1,003). We investigated genetic variants shown to associate with CF disease severity across multiple organs in genome-wide association studies. Results The strongest predictors included sex, CFTR severity score, and several genetic variants including one annotated to PRSS1, which encodes cationic trypsinogen. The final model defined in the CGS shows excellent agreement when validated on the FGMS, and the risk classifier shows slightly better performance at predicting CFRD risk later in life in both studies. Conclusion We demonstrated clinical utility by comparing CFRD prevalence rates between the top 10% of individuals with the highest risk and the bottom 10% with the lowest risk. A web-based application was developed to provide practitioners with patient-specific CFRD risk to guide CFRD monitoring and treatment.
- Published
- 2021
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