Abstract
Background : Inter-individual differences in treatment response are marked in multiple sclerosis (MS). This is true for Natalizumab (NTZ), to which a subset of patients displays sub-optimal treatment response. We conducted a multi-centric genome-wide association study (GWAS), with additional pathway and network analysis to identify genetic predictors of response to NTZ. Methods : MS patients from three different centers were included. Response to NTZ was dichotomized, nominating responders (R) relapse-free patients and non-responders (NR) all the others, over a follow-up of 4 years. Association analysis on ~ 4.7 M imputed autosomal common single-nucleotide polymorphisms (SNPs) was performed fitting logistic regression models, adjusted for baseline covariates, followed by meta-analysis at SNP and gene level. Finally, these signals were projected onto STRING interactome, to elicit modules and hub genes linked to response. Results : Overall, 1834 patients were included: 119 from Italy (R = 94, NR = 25), 81 from Germany (R = 61, NR = 20), and 1634 from Sweden (R = 1349, NR = 285). The top-associated variant was rs11132400T (p = 1.33 × 10–6, OR = 0.58), affecting expression of several genes in the locus, like KLKB1. The interactome analysis implicated a module of 135 genes, with over-representation of terms like canonical WNT signaling pathway (padjust = 7.08 × 10–6). Response-associated genes like GRB2 and LRP6, already implicated in MS pathogenesis, were topologically prioritized within the module. Conclusion : This GWAS, the largest pharmacogenomic study of response to NTZ, suggested MS-implicated genes and Wnt/β-catenin signaling pathway, an essential component for blood–brain barrier formation and maintenance, to be related to treatment response.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin > Munich Cluster for Systems Neurology (SyNergy) |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-123141-1 |
ISSN: | 0340-5354 |
Sprache: | Englisch |
Dokumenten ID: | 123141 |
Datum der Veröffentlichung auf Open Access LMU: | 13. Dez. 2024 15:15 |
Letzte Änderungen: | 13. Dez. 2024 15:15 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198 |