Glatiramer acetate is used therapeutically in multiple sclerosis but also known for adverse effects including elevated coronary artery disease (CAD) risk. The mechanisms underlying the cardiovascular side effects of the medication are unclear. Here, we made use of the chromosomal variation in the genes that are known to be affected by glatiramer treatment. Focusing on genes and gene products reported by drug-gene interaction database to interact with glatiramer acetate we explored a large meta-analysis on CAD genome-wide association studies aiming firstly, to investigate whether variants in these genes also affect cardiovascular risk and secondly, to identify new CAD risk genes. We traced association signals in a 200-kb region around genomic positions of genes interacting with glatiramer in up to 60 801 CAD cases and 123 504 controls. We validated the identified association in additional 21 934 CAD cases and 76 087 controls. We identified three new CAD risk alleles within the TGFB1 region on chromosome 19 that independently affect CAD risk. The lead SNP rs12459996 was genome-wide significantly associated with CAD in the extended meta-analysis (odds ratio 1.09, p = 1.58×10−12). The other two SNPs at the locus were not in linkage disequilibrium with the lead SNP and by a conditional analysis showed p-values of 4.05 × 10−10 and 2.21 × 10−6. Thus, studying genes reported to interact with glatiramer acetate we identified genetic variants that concordantly with the drug increase the risk of CAD. Of these, TGFB1 displayed signal for association. Indeed, the gene has been associated with CAD previously in both in vivo and in vitro studies. Here we establish genome-wide significant association with CAD in large human samples.
Bibliographical noteFunding Information:
Funding:Thisworkwassupportedbygrantsfrom theFondationLeducq(CADgenomics: UnderstandingCADGenes,12CVD02),theGerman FederalMinistryofEducationandResearch (BMBF)withintheframeworkofthee:Med researchandfundingconcept(e:AtheroSysMed, grant01ZX1313A-2014andSysInflame,grant
ThisworkwassupportedbygrantsfromtheFondationLeducq(CADgenomics:Understanding CADGenes,12CVD02),theGermanFederalMinistryofEducationandResearch(BMBF)within the framework of the e:Med research and funding concept (e:A ther oS ysM ed, grant 01ZX1313A-2014 and S ysI nflame, grant 01ZX1306A), and the European Union Seventh Framework Pro-grammeFP7/2007-2013undergrantagreementnoHEALTH-F2-2013-601456(CVgenes-a t-t ar-get).FurthergrantswerereceivedfromtheDFGaspartoftheSonderforschungsbereich CRC 1123(B2).T.K.wassupportedbyaDZHKRotationGrant.I.B.wassupportedbytheDeutsche Forschungsgemeinschaft(DFG)clusterofexcellence‘InflammationatInterfaces’.F.W.A.issup-portedbyaDekkerscholarship-JuniorStaffMember2014T001-NetherlandsHeartFoundation andUCLHospitalsNIHRBiomedicalResearchCentre.
© 2017 Brænne et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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