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Genome-wide meta-analysis identifies novel loci of plaque burden in carotid artery

  • Janne Pott
    Affiliations
    Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany

    LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
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  • Ralph Burkhardt
    Affiliations
    LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany

    Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital, Leipzig, Germany
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  • Frank Beutner
    Affiliations
    LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany

    Heart Center Leipzig, Leipzig, Germany
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  • Katrin Horn
    Affiliations
    Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
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  • Andrej Teren
    Affiliations
    LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany

    Heart Center Leipzig, Leipzig, Germany
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  • Holger Kirsten
    Affiliations
    Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany

    LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
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  • Lesca M. Holdt
    Affiliations
    LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany

    Institute for Laboratory Medicine, Ludwig-Maximilians University, Munich, Germany
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  • Gerhard Schuler
    Affiliations
    Heart Center Leipzig, Leipzig, Germany
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  • Daniel Teupser
    Affiliations
    LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany

    Institute for Laboratory Medicine, Ludwig-Maximilians University, Munich, Germany
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  • Markus Loeffler
    Affiliations
    Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany

    LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
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  • Joachim Thiery
    Affiliations
    LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany

    Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital, Leipzig, Germany
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  • Markus Scholz
    Correspondence
    Corresponding author. Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.
    Affiliations
    Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany

    LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
    Search for articles by this author

      Highlights

      • We performed genome-wide association analysis of carotid plaque (PS) in two cohorts.
      • We detected two loci with genome-wide significance and two with suggestive evidence.
      • 9p21 locus of coronary artery disease (CAD) showed strongest association with PS.
      • We observed an enrichment of PS associations for known CAD loci.

      Abstract

      Background and aims

      Carotid artery plaque is an established marker of subclinical atherosclerosis and common patho-mechanisms with coronary artery disease (CAD) are hypothesized. We aimed to identify genetic variants associated with carotid plaque and to examine the potential shared genetic basis with CAD.

      Methods

      After investigating the reliability of plaque detection, we performed a genome-wide meta-association study in two independent cohorts (LIFE-Adult, n = 4037 and LIFE-Heart, n = 3152) for carotid plaque score (PS), defined as the sum of the plaque load of common carotid artery and carotid bulb. Further, we analyzed whether previously reported CAD and stroke loci were also associated with PS.

      Results

      We identified two loci with genome-wide significance for PS. One locus is the known CAD-locus at chromosome 9p21 (lead SNP rs9644862, p = 8.73 × 10−12). We also describe a novel locus on chromosome 10q24 within the SFXN2 gene as the most probable candidate (lead SNP rs2902548, p = 1.97 × 10−8). In addition, 17 out of 58 known CAD loci and six of 17 known stroke loci were associated with PS at a nominal level of significance.

      Conclusions

      We showed that PS is a reliable trait to analyze genetics of atherosclerosis. Two new loci of genome-wide significant association with PS were found. The observed non-random overlap of CAD and PS associations strengthens the hypothesis of a shared genetic basis for these atherosclerotic manifestations.

      Keywords

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      References

        • Kessler T.
        • Erdmann J.
        • Schunkert H.
        Genetics of coronary artery disease and myocardial infarction–2013.
        Curr. Cardiol. Rep. 2013; 15: 368https://doi.org/10.1007/s11886-013-0368-0
        • Nikpay M.
        • Goel A.
        • Won H.-H.
        • Hall L.M.
        • et al.
        A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease.
        Nat. Genet. 2015; 47: 1121-1130https://doi.org/10.1038/ng.3396
        • Lorenz M.W.
        • Markus H.S.
        • Bots M.L.
        • Rosvall M.
        • et al.
        Prediction of clinical cardiovascular events with carotid intima-media thickness: a systematic review and meta-analysis.
        Circulation. 2007; 115: 459-467https://doi.org/10.1161/CIRCULATIONAHA.106.628875
        • Bots M.L.
        • Sutton-Tyrrell K.
        Lessons from the past and promises for the future for carotid intima-media thickness.
        J. Am. Coll. Cardiol. 2012; 60: 1599-1604https://doi.org/10.1016/j.jacc.2011.12.061
        • den Ruijter H.M.
        • Peters S.A.E.
        • Anderson T.J.
        • Britton A.R.
        • et al.
        Common carotid intima-media thickness measurements in cardiovascular risk prediction: a meta-analysis.
        JAMA. 2012; 308: 796-803https://doi.org/10.1001/jama.2012.9630
        • Sillesen H.
        • Muntendam P.
        • Adourian A.
        • Entrekin R.
        • et al.
        Carotid plaque burden as a measure of subclinical atherosclerosis: comparison with other tests for subclinical arterial disease in the High Risk Plaque BioImage study.
        JACC. Cardiovasc. imaging. 2012; 5: 681-689https://doi.org/10.1016/j.jcmg.2012.03.013
        • Inaba Y.
        • Chen J.A.
        • Bergmann S.R.
        Carotid plaque, compared with carotid intima-media thickness, more accurately predicts coronary artery disease events: a meta-analysis.
        Atherosclerosis. 2012; 220: 128-133https://doi.org/10.1016/j.atherosclerosis.2011.06.044
        • Weissgerber A.
        • Scholz M.
        • Teren A.
        • Sandri M.
        • et al.
        The value of noncoronary atherosclerosis for identifying coronary artery disease: results of the Leipzig LIFE heart study.
        Clin. Res. Cardiol. official J. Ger. Cardiac Soc. 2016; 105: 172-181https://doi.org/10.1007/s00392-015-0900-x
        • Bis J.C.
        • Kavousi M.
        • Franceschini N.
        • Isaacs A.
        • et al.
        Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque.
        Nat. Genet. 2011; 43: 940-947https://doi.org/10.1038/ng.920
        • den Hoed M.
        • Strawbridge R.J.
        • Almgren P.
        • Gustafsson S.
        • et al.
        GWAS-identified loci for coronary heart disease are associated with intima-media thickness and plaque presence at the carotid artery bulb.
        Atherosclerosis. 2015; 239: 304-310https://doi.org/10.1016/j.atherosclerosis.2015.01.032
        • Della-Morte D.
        • Wang L.
        • Beecham A.
        • Blanton S.H.
        • et al.
        Novel genetic variants modify the effect of smoking on carotid plaque burden in Hispanics.
        J. neurological Sci. 2014; 344: 27-31https://doi.org/10.1016/j.jns.2014.06.006
        • Dichgans M.
        • Malik R.
        • Konig I.R.
        • Rosand J.
        • et al.
        Shared genetic susceptibility to ischemic stroke and coronary artery disease: a genome-wide analysis of common variants.
        Stroke; a J. Cereb. circulation. 2014; 45: 24-36https://doi.org/10.1161/STROKEAHA.113.002707
        • NINDS Stroke Genetics Network (SiGN)
        International Stroke Genetics Consortium (ISGC), Loci associated with ischaemic stroke and its subtypes (SiGN): a genome-wide association study.
        Lancet Neurology. 2016; 15: 174-184https://doi.org/10.1016/S1474-4422(15)00338-5
        • Adams H.P.J.R.
        • Bendixen B.H.
        • Kappelle L.J.
        • Biller J.
        • et al.
        Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in acute stroke treatment.
        Stroke. 1993; 24: 35-41
        • Loeffler M.
        • Engel C.
        • Ahnert P.
        • Alfermann D.
        • et al.
        The LIFE-Adult-Study: objectives and design of a population-based cohort study with 10,000 deeply phenotyped adults in Germany.
        BMC public health. 2015; 15: 691https://doi.org/10.1186/s12889-015-1983-z
        • Beutner F.
        • Teupser D.
        • Gielen S.
        • Holdt L.M.
        • et al.
        Rationale and design of the Leipzig (LIFE) Heart Study: phenotyping and cardiovascular characteristics of patients with coronary artery disease.
        PloS one. 2011; 6: e29070https://doi.org/10.1371/journal.pone.0029070
        • Stein J.H.
        • Korcarz C.E.
        • Hurst R.T.
        • Lonn E.
        • et al.
        Use of carotid ultrasound to identify subclinical vascular disease and evaluate cardiovascular disease risk: a consensus statement from the American society of echocardiography carotid intima-media thickness task force. Endorsed by the Society for Vascular Medicine.
        J. Am. Soc. Echocardiogr. official Publ. Am. Soc. Echocardiogr. 2008; 21 (quiz 189-90): 93-111https://doi.org/10.1016/j.echo.2007.11.011
      1. Affymetrix, I., Axiom Genotyping Solution Data Analysis Guide.

        • Laurie C.C.
        • Doheny K.F.
        • Mirel D.B.
        • Pugh E.W.
        • et al.
        Quality control and quality assurance in genotypic data for genome-wide association studies.
        Genet. Epidemiol. 2010; 34: 591-602https://doi.org/10.1002/gepi.20516
        • Wang J.
        An estimator for pairwise relatedness using molecular markers.
        Genetics. 2002; 160: 1203-1215
        • Patterson N.
        • Price A.L.
        • Reich D.
        Population structure and eigenanalysis.
        PLoS Genet. 2006; 2: e190https://doi.org/10.1371/journal.pgen.0020190
        • Chang C.C.
        • Chow C.C.
        • Tellier L.C.
        • Vattikuti S.
        • et al.
        Second-generation PLINK: rising to the challenge of larger and richer datasets.
        GigaScience. 2015; 4: 7https://doi.org/10.1186/s13742-015-0047-8
      2. Shaun Purcell, C. C., PLINK.

        • Konig I.R.
        • Loley C.
        • Erdmann J.
        • Ziegler A.
        How to include chromosome X in your genome-wide association study.
        Genet. Epidemiol. 2014; 38: 97-103https://doi.org/10.1002/gepi.21782
        • Auton A.
        • Brooks L.D.
        • Durbin R.M.
        • Garrison E.P.
        • et al.
        A global reference for human genetic variation.
        Nature. 2015; 526: 68-74https://doi.org/10.1038/nature15393
        • Delaneau O.
        • Howie B.
        • Cox A.J.
        • Zagury J.-F.
        • et al.
        Haplotype estimation using sequencing reads.
        Am. J. Hum. Genet. 2013; 93: 687-696https://doi.org/10.1016/j.ajhg.2013.09.002
        • Howie B.N.
        • Donnelly P.
        • Marchini J.
        A flexible and accurate genotype imputation method for the next generation of genome-wide association studies.
        PLoS Genet. 2009; 5: e1000529https://doi.org/10.1371/journal.pgen.1000529
        • Welter D.
        • MacArthur J.
        • Morales J.
        • Burdett T.
        • et al.
        The NHGRI GWAS Catalog, a curated resource of SNP-trait associations.
        Nucleic acids Res. 2014; 42: D1001-D1006https://doi.org/10.1093/nar/gkt1229
        • Kirsten H.
        • Al-Hasani H.
        • Holdt L.
        • Gross A.
        • et al.
        Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding locidagger.
        Hum. Mol. Genet. 2015; 24: 4746-4763https://doi.org/10.1093/hmg/ddv194
        • Yu G.
        • Wang L.-G.
        • Yan G.-R.
        • He Q.-Y.
        DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis.
        Bioinforma. Oxf. Engl. 2015; 31: 608-609https://doi.org/10.1093/bioinformatics/btu684
        • Kircher M.
        • Witten D.M.
        • Jain P.
        • O'Roak B.J.
        • et al.
        A general framework for estimating the relative pathogenicity of human genetic variants.
        Nat. Genet. 2014; 46: 310-315https://doi.org/10.1038/ng.2892
        • Geisel M.H.
        • Coassin S.
        • Hessler N.
        • Bauer M.
        • et al.
        Update of the effect estimates for common variants associated with carotid intima media thickness within four independent samples: the Bonn IMT Family Study, the Heinz Nixdorf Recall Study, the SAPHIR Study and the Bruneck Study.
        Atherosclerosis. 2016; 249: 83-87https://doi.org/10.1016/j.atherosclerosis.2016.03.042
        • Schunkert H.
        • Konig I.R.
        • Kathiresan S.
        • Reilly M.P.
        • et al.
        Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.
        Nat. Genet. 2011; 43: 333-338https://doi.org/10.1038/ng.784
      3. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans.
        Sci. (New York, N.Y.). 2015; 348: 648-660https://doi.org/10.1126/science.1262110
        • Westra H.-J.
        • Peters M.J.
        • Esko T.
        • Yaghootkar H.
        • et al.
        Systematic identification of trans eQTLs as putative drivers of known disease associations.
        Nat. Genet. 2013; 45: 1238-1243https://doi.org/10.1038/ng.2756
      4. A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease.
        Nat. Genet. 2011; 43: 339-344https://doi.org/10.1038/ng.782
        • Chinn S.
        A simple method for converting an odds ratio to effect size for use in meta-analysis.
        Statistics Med. 2000; 19: 3127-3131
        • Holdt L.M.
        • Hoffmann S.
        • Sass K.
        • Langenberger D.
        • et al.
        Alu elements in ANRIL non-coding RNA at chromosome 9p21 modulate atherogenic cell functions through trans-regulation of gene networks.
        PLoS Genet. 2013; 9: e1003588https://doi.org/10.1371/journal.pgen.1003588
        • Holdt L.M.
        • Sass K.
        • Gabel G.
        • Bergert H.
        • et al.
        Expression of Chr9p21 genes CDKN2B (p15(INK4b)), CDKN2A (p16(INK4a), p14(ARF)) and MTAP in human atherosclerotic plaque.
        Atherosclerosis. 2011; 214: 264-270https://doi.org/10.1016/j.atherosclerosis.2010.06.029
        • Holdt L.M.
        • Stahringer A.
        • Sass K.
        • Pichler G.
        • et al.
        Circular non-coding RNA ANRIL modulates ribosomal RNA maturation and atherosclerosis in humans.
        Nat. Commun. 2016; 7: 12429https://doi.org/10.1038/ncomms12429
        • Holdt L.M.
        • Beutner F.
        • Scholz M.
        • Gielen S.
        • et al.
        ANRIL expression is associated with atherosclerosis risk at chromosome 9p21.
        Arteriosclerosis, Thrombosis, Vasc. Biol. 2010; 30: 620-627https://doi.org/10.1161/ATVBAHA.109.196832
        • Holdt L.M.
        • Teupser D.
        Recent studies of the human chromosome 9p21 locus, which is associated with atherosclerosis in human populations.
        Arteriosclerosis, Thrombosis, Vasc. Biol. 2012; 32: 196-206https://doi.org/10.1161/ATVBAHA.111.232678