Genetic architecture of Multiple Sclerosis patients in the French national OFSEP-HD cohort
Julien ParisiD, Nayane dos Santos Brito SilvaiD, Igor FaddeenkoviD, Martin E. MoriniD, Léo BoussametiD, Stanislas DemuthiD, Mitra BarzineiD, Anna Serova-Erard, François Cornélis, Sonia BourguibaiD, Sophie LimouiD, Françis GuilleminiD, Sandra VukusiciD, Romain CaseyiD, Jonathan EpsteiniD, Anne KerbratiD, Emmanuelle LerayiD, Éric ThouvenotiD, Guillaume MatheyiD, Laure MicheliD, Emmanuelle Le PageiD, Jerome De SezeiD, Christine Lebrun‐FrénayiD, Caroline PapeixiD, Jonathan CironiD, , Pierre‐Antoine GourraudiD
Abstract
Multiple Sclerosis (MS) is a central nervous system (CNS) autoimmune inflammatory disease targeting the myelin sheath and affecting 2.8 million patients worldwide, mostly in economically advanced countries. The OFSEP-HD (French Multiple Sclerosis Registry - High Definition) multi-centric cohort comprises 2,667 genetic samples of patients with MS including 5 years of clinical, biological and imaging follow up. Here we described the genetic background of the cohort using data generated from the Affymetrix Precision Medicine Research Array (PMRA) genotyping chips to collect 888,799 genomic variants, and up to 8.5 million variants after imputation. Our analysis focused on genetic ancestry, admixture analysis and Human Leukocyte Antigen (HLA) including haplotypes inference. Principal Components Analysis (PCA) clustering identified seven ancestral clusters with 2177 patients (85.6 %) from clearly defined European ancestry. We observed 232 MS patients from North-African genetic ancestry while 120 of those patients (51.7%) did not self-report North-African origins, highlighting once again the limitations of self-assessed population descriptors. To promote data sharing we implemented the generation of a realistic and anonymous synthetic dataset using an adaptation of a known synthetic data generation methodology. This work unveils the genetic landscape and heterogeneous profiles of the OFSEP-HD cohort and proposes an open synthetic genetic dataset for further analyses.
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