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Selected Publication:

SHR Neuro Cancer Cardio Lipid Metab Microb

Borghini, L; Png, E; Binder, A; Wright, VJ; Pinnock, E; de Groot, R; Hazelzet, J; Emonts, M; Van der Flier, M; Schlapbach, LJ; Anderson, S; Secka, F; Salas, A; Fink, C; Carrol, ED; Pollard, AJ; Coin, LJ; Kuijpers, TW; Martinon-Torres, F; Zenz, W; Levin, M; Hibberd, ML; Davila, S; EUCLIDS consortium.
Identification of regulatory variants associated with genetic susceptibility to meningococcal disease.
Sci Rep. 2019; 9(1):6966-6966 Doi: 10.1038/s41598-019-43292-6 [OPEN ACCESS]
Web of Science PubMed PUBMED Central FullText FullText_MUG

 

Co-authors Med Uni Graz
Binder Alexander
Zenz Werner
Study Group Members Med Uni Graz:
Kohlfürst Daniela
Walcher Wolfgang
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Abstract:
Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes.

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