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• W2897821286 abstract "HomeCirculation: Genomic and Precision MedicineVol. 11, No. 9Genetic Susceptibility Loci for Cardiovascular Disease and Their Impact on Atherosclerotic Plaques Open AccessResearch ArticlePDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissionsDownload Articles + Supplements ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toSupplemental MaterialOpen AccessResearch ArticlePDF/EPUBGenetic Susceptibility Loci for Cardiovascular Disease and Their Impact on Atherosclerotic Plaques Sander W. van der Laan, MD, PhD, Marten A. Siemelink, MD, PhD, Saskia Haitjema, MD, PhD, Hassan Foroughi Asl, PhD, Ljubica Perisic, PhD, Michal Mokry, MD, PhD, Jessica van Setten, PhD, Rainer Malik, PhD, Martin Dichgans, MD, PhD, Bradford B. Worrall, MD, PhD, METASTROKE Collaboration of the International Stroke Genetics Consortium Nilesh J. Samani, MD, Heribert Schunkert, MD, PhD, Jeanette Erdmann, PhD, Ulf Hedin, MD, PhD, Gabrielle Paulsson-Berne, PhD, Johan L.M. Björkegren, PhD, Gert J. de Borst, MD, PhD, Folkert W. Asselbergs, MD, PhD, Hester M. Den Ruijter, PhD, Paul I.W. de Bakker, PhD and Gerard Pasterkamp, MD, PhD Sander W. van der LaanSander W. van der Laan Sander W. van der Laan, PhD, Laboratory of Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands. Email E-mail Address: [email protected] Laboratory of Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University Utrecht, The Netherlands (S.W.v.d.L., M.A.S., S.H., H.M.d.R., G.P.) *Drs Siemelink, Haitjema, Foroughi Asl, and Perisic are joint second authors. Search for more papers by this author , Marten A. SiemelinkMarten A. Siemelink Laboratory of Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University Utrecht, The Netherlands (S.W.v.d.L., M.A.S., S.H., H.M.d.R., G.P.) Department of Clinical Genetics, University Medical Center Utrecht, University Utrecht, The Netherlands (M.A.S.) *Drs Siemelink, Haitjema, Foroughi Asl, and Perisic are joint second authors. Search for more papers by this author , Saskia HaitjemaSaskia Haitjema Laboratory of Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University Utrecht, The Netherlands (S.W.v.d.L., M.A.S., S.H., H.M.d.R., G.P.) *Drs Siemelink, Haitjema, Foroughi Asl, and Perisic are joint second authors. Search for more papers by this author , Hassan Foroughi AslHassan Foroughi Asl Cardiovascular Genomics Group, Division of Vascular Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden (H.F.A.) *Drs Siemelink, Haitjema, Foroughi Asl, and Perisic are joint second authors. Search for more papers by this author , Ljubica PerisicLjubica Perisic Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden (L.P., U.H.) *Drs Siemelink, Haitjema, Foroughi Asl, and Perisic are joint second authors. Search for more papers by this author , Michal MokryMichal Mokry Department of Pediatrics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, University Utrecht, The Netherlands (M.M.) Regenerative Medicine Center Utrecht, University Medical Center Utrecht, University Utrecht, The Netherlands (M.M.) Search for more papers by this author , Jessica van SettenJessica van Setten Department of Cardiology, Division of Heart & Lungs, University Medical Center Utrecht, University Utrecht, The Netherlands (F.W.A., J.v.S.) Search for more papers by this author , Rainer MalikRainer Malik Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany (R.M., M.D.). Search for more papers by this author , Martin DichgansMartin Dichgans Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-University (LMU) Munich, Munich, Germany (R.M., M.D.). Munich Cluster for Systems Neurology (SyNergy), Munich, Germany (M.D.). Search for more papers by this author , Bradford B. WorrallBradford B. Worrall Departments of Neurology and Public Health Sciences, University of Virginia, Charlottesville (B.B.W.). Search for more papers by this author , METASTROKE Collaboration of the International Stroke Genetics Consortium ‡Drs de Bakker and Pasterkamp contributed equally as senior authors to this work. Search for more papers by this author , Nilesh J. SamaniNilesh J. Samani Department of Cardiovascular Sciences, University of Leicester (N.J.S.) NIHR Leicester Biomedical Research Unit Centre, BHF Cardiovascular Research Centre, Glenfield Hospital, Leicester, United Kingdom (N.J.S.). NIHR Leicester Biomedical Research Unit Centre, BHF Cardiovascular Research Centre, Glenfield Hospital, Leicester, United Kingdom (N.J.S.). Search for more papers by this author , Heribert SchunkertHeribert Schunkert Deutsches Herzzentrum München, Klinik an der TU München, Munich Heart Alliance (DZHK), Germany (H.S., J.E.). Search for more papers by this author , Jeanette ErdmannJeanette Erdmann Deutsches Herzzentrum München, Klinik an der TU München, Munich Heart Alliance (DZHK), Germany (H.S., J.E.). Search for more papers by this author , Ulf HedinUlf Hedin Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden (L.P., U.H.) Search for more papers by this author , Gabrielle Paulsson-BerneGabrielle Paulsson-Berne Unit of Cardiovascular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Sweden (G.P.-B.) Search for more papers by this author , Johan L.M. BjörkegrenJohan L.M. Björkegren CMM, Karolinska Institutet, Stockholm, Sweden. Department of Genetics & Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York (J.L.M.B.). Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden (J.L.M.B.). Clinical Gene Networks AB, Stockholm,Sweden (J.L.M.B.). Search for more papers by this author , Gert J. de BorstGert J. de Borst Division of Surgical Specialties, Department of Surgery, University Medical Center Utrecht, University Utrecht, The Netherlands (G.J.d.B.) Search for more papers by this author , Folkert W. AsselbergsFolkert W. Asselbergs Department of Cardiology, Division of Heart & Lungs, University Medical Center Utrecht, University Utrecht, The Netherlands (F.W.A., J.v.S.) Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, University Utrecht, The Netherlands (P.I.W.d.B.) Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University Utrecht, The Netherlands (P.I.W.d.B.) Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University Utrecht, The Netherlands (P.I.W.d.B.) Laboratory of Clinical Chemistry and Hematology, Division Laboratories and Pharmacy, University Medical Center Utrecht, University Utrecht, The Netherlands (G.P.) Durrer Center for Cardiogenetic Research, Netherlands Heart Institute, Utrecht (F.W.A.). Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom (F.W.A.). Institute of Health Informatics, University College London, London, United Kingdom (F.W.A.). Search for more papers by this author , Hester M. Den RuijterHester M. Den Ruijter Department of Cardiology, Division of Heart & Lungs, University Medical Center Utrecht, University Utrecht, The Netherlands (F.W.A., J.v.S.) Search for more papers by this author , Paul I.W. de BakkerPaul I.W. de Bakker Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, University Utrecht, The Netherlands (P.I.W.d.B.) Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, University Utrecht, The Netherlands (P.I.W.d.B.) †A list of all Individual members is given in the Appendix. Search for more papers by this author and Gerard PasterkampGerard Pasterkamp Laboratory of Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University Utrecht, The Netherlands (S.W.v.d.L., M.A.S., S.H., H.M.d.R., G.P.) Department of Clinical Genetics, University Medical Center Utrecht, University Utrecht, The Netherlands (M.A.S.) Laboratory of Clinical Chemistry and Hematology, Division Laboratories and Pharmacy, University Medical Center Utrecht, University Utrecht, The Netherlands (G.P.) †A list of all Individual members is given in the Appendix. Search for more papers by this author Originally published17 Sep 2018https://doi.org/10.1161/CIRCGEN.118.002115Circulation: Genomic and Precision Medicine. 2018;11:e002115Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: September 17, 2018: Previous Version of Record AbstractBackground:Atherosclerosis is a chronic inflammatory disease in part caused by lipid uptake in the vascular wall, but the exact underlying mechanisms leading to acute myocardial infarction and stroke remain poorly understood. Large consortia identified genetic susceptibility loci that associate with large artery ischemic stroke and coronary artery disease. However, deciphering their underlying mechanisms are challenging. Histological studies identified destabilizing characteristics in human atherosclerotic plaques that associate with clinical outcome. To what extent established susceptibility loci for large artery ischemic stroke and coronary artery disease relate to plaque characteristics is thus far unknown but may point to novel mechanisms.Methods:We studied the associations of 61 established cardiovascular risk loci with 7 histological plaque characteristics assessed in 1443 carotid plaque specimens from the Athero-Express Biobank Study. We also assessed if the genotyped cardiovascular risk loci impact the tissue-specific gene expression in 2 independent biobanks, Biobank of Karolinska Endarterectomy and Stockholm Atherosclerosis Gene Expression.Results:A total of 21 established risk variants (out of 61) nominally associated to a plaque characteristic. One variant (rs12539895, risk allele A) at 7q22 associated to a reduction of intraplaque fat, P=5.09×10−6 after correction for multiple testing. We further characterized this 7q22 Locus and show tissue-specific effects of rs12539895 on HBP1 expression in plaques and COG5 expression in whole blood and provide data from public resources showing an association with decreased LDL (low-density lipoprotein) and increase HDL (high-density lipoprotein) in the blood.Conclusions:Our study supports the view that cardiovascular susceptibility loci may exert their effect by influencing the atherosclerotic plaque characteristics.IntroductionAtherosclerosis refers to the lifelong process of lesion formation and progression in the inner linings of arteries1 and underlies coronary artery disease (CAD) and large artery ischemic stroke (LAS).2 CAD and LAS are complex diseases with a shared genetic architecture.3,4 To date, meta-analyses of genome-wide association studies (GWAS) identified multiple genetic loci for CAD5 and 4 for LAS.6–8 Despite this progress, it has proven challenging to interpret these findings in terms of the underlying biological mechanisms or to formulate testable therapeutic hypotheses.Histological analyses of atherosclerotic plaques have provided insight into the process of atherosclerosis.1 The high-risk lesion characterized by variability in lipid, inflammatory, calcific, and thrombotic components is prone to destabilization and rupture,1,9,10 resulting in acute cardiovascular disease.10–13 But the extent to which common sequence variation that associates to CAD and LAS risk also relates to advanced destabilizing atherosclerotic lesion characteristics remains unclear.The Athero-Express (AE) Biobank Study,9 STAGE (Stockholm Atherosclerosis Gene Expression),14 and BiKE (Biobank of Karolinska Endarterectomy)15,16 are 3 independent, deeply phenotyped biobank studies comprising individuals undergoing surgical interventions. The AE assesses the genetic architecture of histologically analyzed plaque specimens and plaque-derived DNA methylation. STAGE and BiKE focus on the genetics of tissue-specific differential gene expression.Here we specifically investigated the association of 61 established susceptibility loci for CAD and LAS to plaque characteristics in the AE study. We find that these risk loci are broadly albeit nominally associated with human atherosclerotic plaque characteristics. We report that the risk allele (A) of 1 variant (rs12539895) on chromosome 7q22 near COG5 and HBP1 was significantly associated with a reduction in intraplaque fat (P=5.09×10−6 after correction for multiple testing). To further increase our understanding of this association, we investigated the effects of common variants at 7q22 on carotid plaque DNA methylation and tissue-specific gene expression, by combining data from the AE, STAGE, and BiKE studies.Methods and MaterialThis study complies with the Declaration of Helsinki, and all participants provided informed consent. The medical ethical committees of the respective hospitals approved these studies.The data, analytic methods, and study materials will be made available to other researchers for purposes of reproducing the results or replicating the procedure. The raw omics data are available through the European Genome-Phenome Archive. The main scripts used for the quality control and the (meta-)analysis of the data are available through GitHub (https://github.com/swvanderlaan/publications under doi: 10.5281/zenodo.1069531).The Methods and Material can be found in the Data Supplement.ResultsClinical Characteristics of the 3 CohortsFor this study, we included individuals from 3 independent biobank studies, the AE,9 BiKE,15,16 and STAGE.14 Each study included patients with clinically significant arterial stenosis that are similar at baseline (Table 1).Table 1. Clinical Characteristics of the AE, BiKE, and STAGECharacteristicAEBiKESTAGEn=1439n=127n=109Male, N (%)977 (67.89)100 (78.74)98 (90.00)Age, y (SD)68.79 (9.31)70.56 (8.90)65.90 (8.00)History, N (%) Cerebrovascular disease1184 (82.28)101 (79.53)9 (8.00) Coronary artery disease429 (29.81)26 (20.47)100 (91.74) Peripheral arterial disease251 (17.44)n/rn/rRisk factors Type 2 diabetes mellitus332 (23.07)32 (25.20)24 (22.00) Hypertension1231 (85.55)106 (83.46)70 (64.00) Current smoker492 (34.19)61 (48.03)7 (6.00) BMI25.95 (24.02–28.39)26.44 (23.70–28.40)25.93 (23.66–28.19) eGFR72.26 (58.79–85.38)n/r55.36 (48.02–62.70) TC4.64 (3.84–5.50)4.30 (3.70–5.22)3.94 (3.24–4.63) LDL2.70 (2.03–3.40)2.30 (1.90–3.00)2.00 (1.46–2.53) HDL1.11 (0.90–1.38)1.10 (0.90–1.30)1.45 (1.28–1.62) TG1.40 (1.00–2.00)1.45 (1.00–2.12)1.23 (0.85–1.60)Medication, N (%) Antihypertensives1104 (76.72)110 (86.61)96 (88.00) LLDs1112 (77.28)106 (83.46)13 (12.00) Antithrombotics1272 (88.39)29 (22.83)93 (85.00)Symptoms, N (%) Asymptomatic195 (13.55)40 (31.50)n/r Ocular221 (15.36)25 (19.68)n/r TIA635 (44.13)27(21.26)n/r Stroke383 (26.62)32 (36.78)n/rSurgery, N (%) De novo1363 (94.72)n/rn/r Restenosis46 (3.20)2002n/r Period, y2002–201320022009For more details, refer to Material and Methods section. Cerebrovascular disease history includes ischemic stroke and TIA. Coronary artery disease history includes coronary artery disease, myocardial infarction, percutaneous coronary intervention, and coronary artery bypass graft. Peripheral disease history includes diagnosed peripheral arterial occlusive disease, femoral artery interventions, and ankle-brachial index <70. Type 2 diabetes mellitus and hypertension include all individuals with diagnosed type 2 diabetes mellitus or hypertension, respectively, and those on appropriate medication. Current smokers include all individuals smoking up to 6 mo until the surgery date. BMI, kg/m2. eGFR rate was based on the Modification of Diet in Renal Disease formula, mL/min per 1.73 m2. All lipids are in mmol/L. Antihypertensives include all antihypertension medication. Antithrombotics include clopidogrel, dipyridamole, acenocoumarin, ascal, and anti-platelet drugs. Carotid symptoms are the symptoms before surgery, which are the indication for surgery. Surgery includes de novo stenotic arteries, or re-stenotic arteries (restenosis), and the surgery period (in y) is indicated. Categorical risk factors are noted in N (%), continuous risk factors are in median (IQR) unless otherwise indicated. AE indicates Athero-Express; BiKE, Biobank of Karolinska Endarterectomy; BMI, body mass index; eGFR, estimated glomerular filtration rate; HDL, high-density lipoprotein; IQR, interquartile range; LDL, low-density lipoprotein; LLDs, lipid-lowering drugs including statins and other lipid-lowering drugs; STAGE, Stockholm Atherosclerosis Gene Expression; TC, total cholesterol; TG, triglycerides; and TIA, transient ischemic attack.Single-Variant Analysis of CAD and LAS Associated Loci With Plaque CharacteristicsIn the AE we correlated 61 established susceptibility loci for CAD and LAS5–8 to commonly assessed plaque characteristics; 5 Loci identified in a GWAS for bipolar disorder17,18 served as negative controls (these 66 variants are listed in Table I in the Data Supplement). There were 21 (out of 61) cardiovascular risk alleles nominally associated with plaque characteristics and 0 (out of 5) bipolar disorder associated variants (at a nominal P<0.05; Tables 2 and 3).Table 2. CAD and LAS Susceptibility Loci and Their Association With Quantitative Plaque PhenotypesPhenotypeLocusVariantChromosomalBPAllelesCAFβ (SEM)P ValueDiseaseGWAS Dir.MacrophagesBCAS3rs72127981759,013,488C/T0.154−0.137 (0.054)0.011CAD−SMCsLIPArs14124441091,002,927T/C0.3630.083 (0.040)0.036CAD−COL4A1/A2rs1183877613111,040,681A/G0.2610.103 (0.042)0.015CAD−Vessel densitySWAP70rs10840293119,751,196A/G0.5690.079 (0.040)0.046CAD+KSR2rs1183015712118,265,441G/T0.3950.109 (0.040)6.97×10−3CAD−UBE2Zrs465221746,988,597T/C0.540−0.080 (0.038)0.034CAD−SMCs6p21.1rs556621644,594,159G/T0.6980.101 (0.041)0.015LAS−Per variant the reported locus, the chromosomal BP, the effect and other allele (Alleles), as well as the CAF is given. For each variant the effect size (β)±SEM is relative to the coded allele with its P value of association with the quantitative plaque phenotype. Also indicated is the disease (CAD or LAS) to which the respective variant was originally associated in the GWAS. Additional per variant statistics are in Table I in the Data Supplement. BP indicates base pair position; CAD, coronary artery disease; CAF, coded allele frequency; GWAS, genome-wide association study; GWAS Dir., the direction of effect in the CAD GWAS; LAS, large artery stroke; and SMCs, smooth muscle cells.One variant (rs12539895) significantly associated with a reduction of intraplaque fat after correction for multiple testing, with a per A-allele odds ratio=0.63, 95% CI, 0.51–0.77; P=5.09×10−6 (Table 3; Figure 1). This intronic single-nucleotide variant is located on chromosome 7q22 in the gene encoding for conserved oligomeric Golgi complex subunit 5 (COG5). Overall, intraplaque fat was the plaque characteristic that was the most commonly associated with CAD risk loci (6 out of 21 with a nominal P<0.05).Table 3. CAD and LAS Susceptibility Loci and Their Association With Semi-Quantitative Plaque PhenotypesPhenotypeLocusVariantChromosomalBPAllelesCAFOR (95% CI)P ValueDiseaseGWAS Dir.CalcificationWDR12chr2:203828796:I2203,828,796CTA/C0.1260.74 (0.58–0.94)0.012CAD+ZNF259-APOA5-APOA1rs96418411116,648,917C/G0.8611.26 (1.01–1.58)0.043CAD+LDLRrs562898211911,188,247A/G0.1061.59 (1.21–2.07)6.29×10−4CAD−KCNE2 (gene desert)rs284510642135,593,827A/G0.1140.71 (0.55–0.91)7.92×10−3CAD−CollagenNOS3rs39182267150,690,176T/C0.0761.73 (1.03–2.90)0.031CAD−SMG6rs216172172,126,504C/G0.3300.78 (0.64–0.95)0.012CAD−Intraplaque fatMIA3rs671809371222,823,743G/T0.7151.27 (1.02–1.56)0.029CAD+ZEB2-ACO74093.1rs176786832145,286,559G/T0.0881.38 (1.00–1.92)0.049CAD−7q22rs125398957107,091,849A/C0.2340.63 (0.51–0.77)5.09×10−6CAD−NOS3rs39182267150,690,176T/C0.0761.73 (1.03–2.90)0.031CAD+TRIB1rs29540298126,490,972T/A0.4750.77 (0.65–0.92)3.54×10−3CAD−ABOrs25190939136,141,870T/C0.1991.27 (1.02–1.59)0.034CAD−IPHLIPArs14124441091,002,927T/C0.3621.27 (1.07–1.52)6.33×10−3CAD−CalcificationTSPAN2 (1p13.2)rs121223411115,655,690G/C0.2571.19 (1.00–1.43)0.048LAS+Per variant the reported locus, the chromosomal BP, the effect and other allele (Alleles), as well as the CAF is given. The OR±95% CI is relative to the risk allele with its associated P value. Also indicated is the disease (CAD or LAS) to which the respective variant was originally associated in the GWAS. Additional per variant statistics are in Table I in the Data Supplement. Intraplaque fat, as <10% vs >10% fat per the total plaque area. BP indicates base pair position; CAD, coronary artery disease; CAF, coded allele frequency; GWAS, genome-wide association study; GWAS Dir., indicates the direction of effect in the CAD GWAS; IPH, intraplaque hemorrhage; LAS, large artery stroke; and OR, odds ratio.Download figureDownload PowerPointFigure 1. Associations of genetic variants in 7q22 with carotid intraplaque fat. Rs12539895 was previously associated with coronary artery disease (CAD; purple). The strongest association was for a deletion chr7:106901393 (triglycerides [TG] >T; P=2.14×10−7; pink). The x axis shows the chromosomal position relative to 1000G (March 2012, Hg19). The lower shows refSeq canonical genes from UCSC (the black arrow indicates the direction of transcription). The lefty axis shows the −log10(P value) of the association with intraplaque fat. The righty axis shows the recombination rate (gray line in the middle). The middle shows each associated variant colored by the r2 relative to rs12539895. The legend in the upper right corner shows the r2 color scale. The per variant annotation key is depicted in the bottom left corner. Made using LocusZoom version 1.3 and SNiPA.19,20 COG5 indicates component of oligomeric Golgi complex 5; CpG, cytosine-guanine dinucleotide; eQTL, expression quantitative trait loci; HBP1, HMG-box transcription factor 1; and mQTL, methylation quantitative trait loci.CAD loci also nominally associated with atherosclerotic plaque collagen content, smooth muscle cell (SMC) percentage, the percentage of macrophages, the extent of calcification, intraplaque hemorrhage, and intraplaque vessel density (Tables 2 and 3). Two LAS susceptibility loci (near TSPAN2 on 1p13.2 and rs556621 on 6p21.1) nominally associated with intraplaque calcification and SMCs, respectively.As expected, none of the negative control bipolar disorder risk-variants associated with any of the plaque characteristics.Gene-Based Analysis of CAD and LAS Associated Loci With Plaque CharacteristicsWe mapped 787 genes to the 66 loci and applied gene-based association tests using VEGAS2 (Versatile Gene-based Association Study 2)21,22 on the 7 measured plaque characteristics (Material in the Data Supplement). One gene, HMG-box transcription factor 1 (HBP1), on chromosome 7q22 significantly associated with intraplaque fat (P=9.0×10−7 corrected for 7 traits and 787 genes, Table II in the Data Supplement). Consistent with this result, the top single-nucleotide variant in HBP1 identified by VEGAS2, rs10953530 (odds ratio=1.63, 95% CI, 1.33–2.00 per A-allele, P=1.84×10−6; Table II in the Data Supplement), is in strong LD (r2=0.90) with rs12539895, the top association signal in COG5.Tissue-Specific Effects of Cardiovascular Risk Loci on Gene Expression in STAGE and BiKEGiven the single-variant and gene-based association presented above, we further explored the 7q22 locus with respect to regional gene regulation and expression. Genetic variants could regulate gene expression by altering transcription factor binding or splice sites in plaques or other relevant tissues; such variants are known as expression quantitative trait loci. We associated variants in 7q22 with regional gene expression in diseased tissues from the STAGE and BiKE studies and tissues from the general population in the public Genotype-Tissue Expression project.23In STAGE, the rs12539895 associated with a reduction of COG5 expression in atherosclerotic arterial wall tissue, internal mammary artery, and whole blood (Table III in the Data Supplement). Overall, 21 variants associated with expression of 10 genes across 6 tissues at a false-discovery rate Q≤0.05; most expression quantitative trait loci were found in liver and whole blood tissue (Figure I in the Data Supplement).In BiKE 3 correlated variants significantly associated with an increase of HBP1 expression in carotid plaques, P=7.0×10−6; these are proxies for rs12539895 (LD r2>0.90; Figure 2; Table IV in the Data Supplement). The same alleles decrease CAD risk and intraplaque fat (Table IV in the Data Supplement). Given the association of rs12539895 with reduced intraplaque fat and the central role of the LDL (low-density lipoprotein) receptor (encoded by LDLR) in lipid uptake, we investigated if regional gene expression correlated to LDLR expression in carotid plaques from BIKE. Indeed, carotid plaque expression of PRKAR2B, COG5, DUS4L, and CBLL1 was significantly correlated to LDLR expression (P<4.6×10−3 after correction for 11 genes tested; Table V in the Data Supplement).Download figureDownload PowerPointFigure 2. Association of rs3815148 with HBP1 expression in carotid plaques. Rs3815148 is a proxy (LD r2=0.91) for rs12539895 and associated (P=7.0×10−6) with HBP1 expression in carotid plaques from BiKE. A, Regional association of variants with HBP1 expression in carotid plaques. The x axis shows the chromosomal position relative to 1000G (March 2012, Hg19) and refSeq canonical genes (green) from UCSC (the black arrow indicates the direction of transcription). The lefty axis shows the −log10P value of the association with HBP1 expression. The righty axis shows the recombination rate (gray line). The middle shows each associated variant colored by the r2 relative to rs12539895. The legend in the upper right corner shows the r2 color scale. B, Boxplot of the association of rs3815148 with HBP1 expression. Proxy data based on 1000G phase 3, version 5 data from SNiPA.20 Made using LocusZoom version 1.3.19Tissue-Specific Effects of Cardiovascular Risk Loci on Gene Expression in the General PopulationIn contrast, data from the Genotype-Tissue Expression project, comprising 48 pathology tissues of individuals from the general population, indicates that rs12539895 only associates to increased expression HBP1 in testis, sun-exposed skin of the lower leg, and tibial artery (Table VI in the Data Supplement) and increased expression of BCAP29 in lung tissues. In addition, proxies of rs12539895 (LD r2>0.80) associate with differential expression in tibial nerves, skeletal muscle cells, sigmoid colon, and basal ganglia (Table VI in the Data Supplement).Tissue-Specific Sequence Variation Effects on MethylationSequence variation may regulate gene expression indirectly through changes in DNA methylation at sites rich of cytosine-guanine dinucleotides (CpGs) and in a tissue-specific manner.24 To uncover cis-acting methylation quantitative trait loci we associated genetic variants in 7q22 with the methylation of CpGs mapped to the same region in plaques from the AE. A perfect proxy for rs12539895, rs80341862, was significantly associated with a decrease in methylation of a CpG at the 3´ UTR of COG5 and HBP1 (false discovery rate Q value=5.41×10−9 after 1000 permutations; Table VII in the Data Supplement). However, the decreased methylation of this CpG (cg24556660) did not correlate to intraplaque fat (odds ratio=0.98, 95% CI, 0.92–1.05; P=0.62).COG5 and HBP1 Are Expressed in Carotid PlaquesAlthough it is clear that COG5 and HBP1 are expressed in various tissues (Tables IV and VI in the Data Supplement), no data exist on spatial distribution in atherosclerotic lesions. We investigated the spatial localization in carotid plaques from the AE using immunohistochemistry specific for COG5 (component of oligomeric Golgi complex 5) and HBP1 (HMG-box transcription factor 1; Figure II in the Data Supplement). Figure III in the Data Supplement shows that COG5 is expressed in most cells in plaques, whereas HBP1 is expressed primarily in cells with a foam-cell like morphology (Figure IV in the Data Supplement).Cardiovascular Risk Factors and the 7q22 LocusThe dominant causal contributing factors for cardiovascular disease risk are circulating lipid proteins, presumably leading to changes in intraplaque fat. As the intraplaque fat and CAD associated alleles correlate with gene expression in relevant tissues for lipid metabolism (liver) and atherosclerosis (carotid plaques, arterial wall tissues, and whole blood), we speculated that these variants may associate to circulating blood lipid levels too. Indeed, data from the Global Lipids Genetics Consortium25 revealed that the risk-reducing allele of rs12539895 also associated with a decrease in circulating LDL and an increase in HDL (high-density lipoprotein) but not with other cardiovascular risk factors (Table VIII in the Data Supplement).Polygenic Association of Clinically Relevant Variants With Plaque PhenotypesBecause of the central role of atherosclerosis in CAD and LAS and the presumed polygenic nature of these complex diseases, we further tested the contribution of modestly associated variants, ascertained through GWAS, on atherosclerotic characteristics. We summed genetic variation weighted by the effect on" @default.
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• W2897821286 title "Genetic Susceptibility Loci for Cardiovascular Disease and Their Impact on Atherosclerotic Plaques" @default.
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