Skip to main content
Log in

Dissecting the Causal Genetic Mechanisms of Coronary Heart Disease

  • Genetics (AJ Marian, Section Editor)
  • Published:
Current Atherosclerosis Reports Aims and scope Submit manuscript

Abstract

Large-scale genome-wide association studies (GWAS) have identified 46 loci that are associated with coronary heart disease (CHD). Additionally, 104 independent candidate variants (false discovery rate of 5 %) have been identified (Schunkert H, Konig IR, Kathiresan S, Reilly MP, Assimes TL, Holm H et al. Nat Genet 43:333–8, 2011; Deloukas P, Kanoni S, Willenborg C, Farrall M, Assimes TL, Thompson JR et al. Nat Genet 45:25–33, 2012; C4D Genetics Consortium. Nat Genet 43:339–44, 2011). The majority of the causal genes in these loci function independently of conventional risk factors. It is postulated that a number of the CHD-associated genes regulate basic processes in the vascular cells involved in atherosclerosis, and that study of the signaling pathways that are modulated in this cell type by causal regulatory variation will provide critical new insights for targeting the initiation and progression of disease. In this review, we will discuss the types of experimental approaches and data that are critical to understanding the molecular processes that underlie the disease risk at 9p21.3, TCF21, SORT1, and other CHD-associated loci.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Schunkert H, Konig IR, Kathiresan S, Reilly MP, Assimes TL, Holm H, et al. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat Genet. 2011;43:333–8. One of two large initial meta-analyses for coronary heart disease, identified 13 new loci and investigated causal gene identity with eQTL analyses.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  2. Deloukas P, Kanoni S, Willenborg C, Farrall M, Assimes TL, Thompson JR, et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat Genet. 2012;45:25–33. Large meta-analysis of Metabochip data performing fine-mapping in known coronary disease loci, identifying new alleles in known associated loci, and identified novel loci from list of marginally associated variants. Employed early pathway analysis of GWAS data.

    Article  PubMed  CAS  Google Scholar 

  3. C4D Genetics Consortium. A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease. Nat Genet 2011;43:339–44. One of two large initial meta-analyses for coronary heart disease, employed Caucasian and South Asians genome-wide data, identified five new loci.

  4. Schaub MA, Boyle AP, Kundaje A, Batzoglou S, Snyder M. Linking disease associations with regulatory information in the human genome. Genome Res. 2012;22:1748–59.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  5. Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS, et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A. 2009;106:9362–7.

    Article  PubMed Central  PubMed  Google Scholar 

  6. Maurano MT, Humbert R, Rynes E, Thurman RE, Haugen E, Wang H, et al. Systematic localization of common disease-associated variation in regulatory DNA. Science. 2012;337:1190–5. One of a number of superb studies emanating from the ENCODE consortium, this publication described the use of DNAse I hypersensitivity assays to link disease causal variation to regulatory genetic regions.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  7. Nicolae DL, Gamazon E, Zhang W, Duan S, Dolan ME, Cox NJ. Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet. 2010;6:e1000888.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  8. Musunuru K, Strong A, Frank-Kamenetsky M, Lee NE, Ahfeldt T, Sachs KV, et al. From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus. Nature. 2010;466:714–9.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  9. Pomerantz MM, Ahmadiyeh N, Jia L, Herman P, Verzi MP, Doddapaneni H, et al. The 8q24 cancer risk variant rs6983267 shows long-range interaction with MYC in colorectal cancer. Nat Genet. 2009;41:882–4.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  10. Tuupanen S, Turunen M, Lehtonen R, Hallikas O, Vanharanta S, Kivioja T, et al. The common colorectal cancer predisposition SNP rs6983267 at chromosome 8q24 confers potential to enhanced Wnt signaling. Nat Genet. 2009;41:885–90.

    Article  PubMed  CAS  Google Scholar 

  11. Conde L, Bracci PM, Richardson R, Montgomery SB, Skibola CF. Integrating GWAS and expression data for functional characterization of disease-associated SNPs: an application to follicular lymphoma. Am J Hum Genet. 2013;92:126–30. Work described in this paper used allele-specific expression and innovative analysis methods to map disease loci in follicular lymphoma.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  12. Savic D, Ye H, Aneas I, Park SY, Bell GI, Nobrega MA. Alterations in TCF7L2 expression define its role as a key regulator of glucose metabolism. Genome Res. 2011;21:1417–25.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  13. Pittman AM, Naranjo S, Webb E, Broderick P, Lips EH, van Wezel T, et al. The colorectal cancer risk at 18q21 is caused by a novel variant altering SMAD7 expression. Genome Res. 2009;19:987–93.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  14. Pittman AM, Naranjo S, Jalava SE, Twiss P, Ma Y, Olver B, et al. Allelic variation at the 8q23.3 colorectal cancer risk locus functions as a cis-acting regulator of EIF3H. PLoS Genet. 2010;6:e1001126.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  15. Wasserman NF, Aneas I, Nobrega MA. An 8q24 gene desert variant associated with prostate cancer risk confers differential in vivo activity to a MYC enhancer. Genome Res. 2010;20:1191–7.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  16. Karczewski KJ, Dudley JT, Kukurba KR, Chen R, Butte AJ, Montgomery SB, et al. Systematic functional regulatory assessment of disease-associated variants. Proc Natl Acad Sci U S A. 2013;110:9607–12. These data suggest that variation-related alteration of NFkB binding may be a common mechnaism for complex human disease.

    Article  PubMed Central  PubMed  Google Scholar 

  17. Schodel J, Bardella C, Sciesielski LK, Brown JM, Pugh CW, Buckle V, et al. Common genetic variants at the 11q13.3 renal cancer susceptibility locus influence binding of HIF to an enhancer of cyclin D1 expression. Nat Genet. 2012;44(420–5):S1–2.

    Google Scholar 

  18. Chen K, Song F, Calin GA, Wei Q, Hao X, Zhang W. Polymorphisms in microRNA targets: a gold mine for molecular epidemiology. Carcinogenesis. 2008;29:1306–11.

    Article  PubMed  CAS  Google Scholar 

  19. Ryan BM, Robles AI, Harris CC. Genetic variation in microRNA networks: the implications for cancer research. Nat Rev Cancer. 2010;10:389–402.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  20. Liu Y, Aryee MJ, Padyukov L, Fallin MD, Hesselberg E, Runarsson A, et al. Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nat Biotechnol. 2013;31:142–7.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  21. Leung A, Schones DE, Natarajan R. Using epigenetic mechanisms to understand the impact of common disease causing alleles. Curr Opin Immunol. 2012;24:558–63.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  22. Kumar V, Westra HJ, Karjalainen J, Zhernakova DV, Esko T, Hrdlickova B, et al. Human disease-associated genetic variation impacts large intergenic non-coding RNA expression. PLoS Genet. 2013;9:e1003201. Important observations pointing to lncRNAs as possible intermediaries for linking causal variation to protein coding function.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  23. Popadin K, Gutierrez-Arcelus M, Dermitzakis ET, Antonarakis SE. Genetic and epigenetic regulation of human lincRNA gene expression. Am J Hum Genet. 2013;93:1015–26.

    Article  PubMed  CAS  Google Scholar 

  24. Gaffney DJ. Global properties and functional complexity of human gene regulatory variation. PLoS Genet. 2013;9:e1003501.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  25. Howie B, Marchini J, Stephens M. Genotype imputation with thousands of genomes. G3 (Bethesda). 2011;1:457–70.

    Article  Google Scholar 

  26. Zaitlen N, Pasaniuc B, Gur T, Ziv E, Halperin E. Leveraging genetic variability across populations for the identification of causal variants. Am J Hum Genet. 2010;86:23–33.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  27. Kral BG, Mathias RA, Suktitipat B, Ruczinski I, Vaidya D, Yanek LR, et al. A common variant in the CDKN2B gene on chromosome 9p21 protects against coronary artery disease in Americans of African ancestry. J Hum Genet. 2011;56(3):224–9. Small association study for CHD in African Americans identified a novel association in the CDKN2B gene, showing the importance of doing association studies in non-Caucasian groups and in African Americans in particular who have shorter regions of linkage disequilibrium.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  28. Lu X, Wang L, Chen S, He L, Yang X, Shi Y, et al. Genome-wide association study in Han Chinese identifies four new susceptibility loci for coronary artery disease. Nat Genet. 2012;44:890–4. Important GWAS study showing replication of a number of Caucasian CHD associated variants and identifying new associated loci in an East Asian population.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  29. Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat Methods. 2013;10:1213–8.

    Article  PubMed  CAS  Google Scholar 

  30. Pique-Regi R, Degner JF, Pai AA, Gaffney DJ, Gilad Y, Pritchard JK. Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data. Genome Res. 2011;21:447–55.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  31. Miller CL, Anderson DR, Kundu RK, Raiesdana A, Nurnberg ST, Diaz R, et al. Disease-related growth factor and embryonic signaling pathways modulate an enhancer of TCF21 expression at the 6q23.2 coronary heart disease locus. PLoS Genet. 2013;9:e1003652. Initial study from the authors investigating mechanisms by which causal variation, and upstream signaling pathways, regulate CHD gene TCF21 expression.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  32. Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136:215–33.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  33. Nicoloso MS, Sun H, Spizzo R, Kim H, Wickramasinghe P, Shimizu M, et al. Single-nucleotide polymorphisms inside microRNA target sites influence tumor susceptibility. Cancer Res. 2010;70:2789–98.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  34. Miller CL, Haas U, Diaz R, Leeper NJ, Kundu RK, Patolla B, Assimes TL, Kaiser FJ, Ljubica P, Hedin U, Maegdefessel L, Schunkert H, Erdmann J, Quertermous T, Sczakiel G. Coronary heart disease-associated variation in TCF21 disrupts a miR-224 binding site and miRNA-mediated regulation. 2014;in press.

  35. Schadt EE, Molony C, Chudin E, Hao K, Yang X, Lum PY, et al. Mapping the genetic architecture of gene expression in human liver. PLoS Biol. 2008;6:e107.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  36. Stranger BE, Montgomery SB, Dimas AS, Parts L, Stegle O, Ingle CE, et al. Patterns of cis regulatory variation in diverse human populations. PLoS Genet. 2012;8:e1002639. This study investigates the genetics of gene expression in multiple populations, providing insights regarding the transferability of regulatory variation across different racial /ethnic groups.

  37. Zhong H, Beaulaurier J, Lum PY, Molony C, Yang X, Macneil DJ, et al. Liver and adipose expression associated SNPs are enriched for association to type 2 diabetes. PLoS Genet. 2010;6:e1000932.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  38. Lango Allen H, Estrada K, Lettre G, Berndt SI, Weedon MN, Rivadeneira F, et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature. 2010;467:832–8.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  39. Lonsdale J, Thomas J, Salvatore M, Phillips R, Lo E, Shad S, et al. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013;45:580–5.

    Article  CAS  Google Scholar 

  40. Lefebvre JF, Vello E, Ge B, Montgomery SB, Dermitzakis ET, Pastinen T, et al. Genotype-based test in mapping cis-regulatory variants from allele-specific expression data. PLoS One. 2012;7:e38667.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  41. Ria M, Lagercrantz J, Samnegard A, Boquist S, Hamsten A, Eriksson P. A common polymorphism in the promoter region of the TNFSF4 gene is associated with lower allele-specific expression and risk of myocardial infarction. PLoS One. 2011;6:e17652.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  42. Milani L, Lundmark A, Nordlund J, Kiialainen A, Flaegstad T, Jonmundsson G, et al. Allele-specific gene expression patterns in primary leukemic cells reveal regulation of gene expression by CpG site methylation. Genome Res. 2009;19:1–11.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  43. Valle L, Serena-Acedo T, Liyanarachchi S, Hampel H, Comeras I, Li Z, et al. Germline allele-specific expression of TGFBR1 confers an increased risk of colorectal cancer. Science. 2008;321:1361–5.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  44. Battle A, Mostafavi S, Zhu X, Potash JB, Weissman MM, McCormick C, et al. Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals. Genome Res. 2014;24:14–24.

    Article  PubMed  CAS  Google Scholar 

  45. Campino S, Forton J, Raj S, Mohr B, Auburn S, Fry A, et al. Validating discovered Cis-acting regulatory genetic variants: application of an allele specific expression approach to HapMap populations. PLoS One. 2008;3:e4105.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  46. Li Y, Grupe A, Rowland C, Nowotny P, Kauwe JS, Smemo S, et al. DAPK1 variants are associated with Alzheimer’s disease and allele-specific expression. Hum Mol Genet. 2006;15:2560–8.

    Article  PubMed  CAS  Google Scholar 

  47. Serre D, Gurd S, Ge B, Sladek R, Sinnett D, Harmsen E, et al. Differential allelic expression in the human genome: a robust approach to identify genetic and epigenetic cis-acting mechanisms regulating gene expression. PLoS Genet. 2008;4:e1000006.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  48. Sun W. A statistical framework for eQTL mapping using RNA-seq data. Biometrics. 2012;68:1–11.

    Article  PubMed Central  PubMed  Google Scholar 

  49. Zhang R, Li X, Ramaswami G, Smith KS, Turecki G, Montgomery GW, Li JB. Quantifying RNA allelic ratios by microfluidics-based multiplex PCR and sequencing. Nature Methods 2013;in press.

  50. McPherson R, Pertsemlidis A, Kavaslar N, Stewart A, Roberts R, Cox DR, et al. A common allele on chromosome 9 associated with coronary heart disease. Science. 2007;316:1488–91. One of two early studies identifying association of 9p21.3 with CHD.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  51. Helgadottir A, Thorleifsson G, Manolescu A, Gretarsdottir S, Blondal T, Jonasdottir A, et al. A common variant on chromosome 9p21 affects the risk of myocardial infarction. Science. 2007;316:1491–3. One of two early studies identifying association of 9p21.3 with CHD.

    Article  PubMed  CAS  Google Scholar 

  52. WTCCC. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447:661–78.

    Article  CAS  Google Scholar 

  53. Pasmant E, Laurendeau I, Heron D, Vidaud M, Vidaud D, Bieche I. Characterization of a germ-line deletion, including the entire INK4/ARF locus, in a melanoma-neural system tumor family: identification of ANRIL, an antisense noncoding RNA whose expression coclusters with ARF. Cancer Res. 2007;67:3963–9.

    Article  PubMed  CAS  Google Scholar 

  54. Cunnington MS, Keavney B. Genetic mechanisms mediating atherosclerosis susceptibility at the chromosome 9p21 locus. Curr Atheroscler Rep 2011;13:193–201. At chromosome 9p21. Arterioscler Thromb Vasc Biol 2010;30:620–7.

    Google Scholar 

  55. Holdt LM, Beutner F, Scholz M, Gielen S, Gabel G, Bergert H, et al. ANRIL expression is associated with atherosclerosis risk at chromosome 9p21. Arterioscler Thromb Vasc Biol. 2010;30:620–7. Studies showing that ANRIL expression is associated with atherosclerosis risk.

  56. Liu Y, Sanoff HK, Cho H, Burd CE, Torrice C, Mohlke KL, et al. INK4/ARF transcript expression is associated with chromosome 9p21 variants linked to atherosclerosis. PLoS ONE. 2009;4:e5027.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  57. Jarinova O, Stewart AF, Roberts R, Wells G, Lau P, Naing T, et al. Functional Analysis of the Chromosome 9p21.3 Coronary Artery Disease Risk Locus. Arterioscler Thromb Vasc Biol. 2009;29:1671–7.

    Article  PubMed  CAS  Google Scholar 

  58. Cunnington MS, Santibanez Koref M, Mayosi BM, Burn J, Keavney B. Chromosome 9p21 SNPs Associated with Multiple Disease Phenotypes Correlate with ANRIL Expression. PLoS Genet. 2010;6:e1000899.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  59. Yu W, Gius D, Onyango P, Muldoon-Jacobs K, Karp J, Feinberg AP, et al. Epigenetic silencing of tumour suppressor gene p15 by its antisense RNA. Nature. 2008;451:202–6.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  60. Kotake Y, Nakagawa T, Kitagawa K, Suzuki S, Liu N, Kitagawa M, et al. Long non-coding RNA ANRIL is required for the PRC2 recruitment to and silencing of p15(INK4B) tumor suppressor gene. Oncogene. 2011;30:1956–62.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  61. Harismendy O, Notani D, Song X, Rahim NG, Tanasa B, Heintzman N, et al. 9p21 DNA variants associated with coronary artery disease impair interferon-gamma signalling response. Nature. 2011;470:264–8.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  62. Leeper NJ, Raiesdana A, Kojima Y, Kundu RK, Cheng H, Maegdefessel L, et al. Loss of CDKN2B promotes p53-dependent smooth muscle cell apoptosis and aneurysm formation. Arterioscler Thromb Vasc Biol. 2013;33:e1–10.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  63. Visel A, Zhu Y, May D, Afzal V, Gong E, Attanasio C, et al. Targeted deletion of the 9p21 non-coding coronary artery disease risk interval in mice. Nature. 2010;464:409–12.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  64. Matys V, Kel-Margoulis OV, Fricke E, Liebich I, Land S, Barre-Dirrie A, et al. TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes. Nucleic Acids Res. 2006;34:D108–10.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  65. Portales-Casamar E, Thongjuea S, Kwon AT, Arenillas D, Zhao X, Valen E, et al. JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles. Nucleic Acids Res. 2010;38:D105–10.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  66. Quandt K, Frech K, Karas H, Wingender E, Werner T. MatInd and MatInspector: new fast and versatile tools for detection of consensus matches in nucleotide sequence data. Nucleic Acids Res. 1995;23:4878–84.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  67. Newburger DE, Bulyk ML. UniPROBE: an online database of protein binding microarray data on protein-DNA interactions. Nucleic Acids Res. 2009;37:D77–82.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  68. Montgomery SB, Griffith OL, Sleumer MC, Bergman CM, Bilenky M, Pleasance ED, et al. ORegAnno: an open access database and curation system for literature-derived promoters, transcription factor binding sites and regulatory variation. Bioinformatics. 2006;22:637–40.

    Article  PubMed  CAS  Google Scholar 

  69. Portales-Casamar E, Arenillas D, Lim J, Swanson MI, Jiang S, McCallum A, et al. The PAZAR database of gene regulatory information coupled to the ORCA toolkit for the study of regulatory sequences. Nucleic Acids Res. 2009;37:D54–60.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  70. Jolma A, Yan J, Whitington T, Toivonen J, Nitta KR, Rastas P, et al. DNA-binding specificities of human transcription factors. Cell. 2013;152:327–39.

    Article  PubMed  CAS  Google Scholar 

  71. Kel AE, Gossling E, Reuter I, Cheremushkin E, Kel-Margoulis OV, Wingender E. MATCH: A tool for searching transcription factor binding sites in DNA sequences. Nucleic Acids Res. 2003;31:3576–9.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  72. Knight JC, Keating BJ, Rockett KA, Kwiatkowski DP. In vivo characterization of regulatory polymorphisms by allele-specific quantification of RNA polymerase loading. Nat Genet. 2003;33:469–75. Elegant study looking at the transcriptional mechanism for allele-specific expression, this study introduced the concept of allele-specific binding assays.

    Article  PubMed  CAS  Google Scholar 

  73. Kheradpour P, Ernst J, Melnikov A, Rogov P, Wang L, Zhang X, et al. Systematic dissection of regulatory motifs in 2000 predicted human enhancers using a massively parallel reporter assay. Genome Res. 2013;23:800–11.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  74. Kwasnieski JC, Mogno I, Myers CA, Corbo JC, Cohen BA. Complex effects of nucleotide variants in a mammalian cis-regulatory element. Proc Natl Acad Sci U S A. 2012;109:19498–503.

    Article  PubMed Central  PubMed  Google Scholar 

  75. Arnold CD, Gerlach D, Stelzer C, Boryn LM, Rath M, Stark A. Genome-wide quantitative enhancer activity maps identified by STARR-seq. Science. 2013;339:1074–7.

    Article  PubMed  CAS  Google Scholar 

  76. Gaulton KJ, Nammo T, Pasquali L, Simon JM, Giresi PG, Fogarty MP, et al. A map of open chromatin in human pancreatic islets. Nat Genet. 2010;42:255–9.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  77. Wang Y, Zhang WY, Hu S, Lan F, Lee AS, Huber B, et al. Genome editing of human embryonic stem cells and induced pluripotent stem cells with zinc finger nucleases for cellular imaging. Circ Res. 2012;111:1494–503.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  78. Meng X, Noyes MB, Zhu LJ, Lawson ND, Wolfe SA. Targeted gene inactivation in zebrafish using engineered zinc-finger nucleases. Nat Biotechnol. 2008;26:695–701.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  79. Zhu C, Smith T, McNulty J, Rayla AL, Lakshmanan A, Siekmann AF, et al. Evaluation and application of modularly assembled zinc-finger nucleases in zebrafish. Development. 2011;138:4555–64.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  80. Gopalakrishnan K, Kumarasamy S, Abdul-Majeed S, Kalinoski AL, Morgan EE, Gohara AF, et al. Targeted disruption of Adamts16 gene in a rat genetic model of hypertension. Proc Natl Acad Sci U S A. 2012;109:20555–9.

    Article  PubMed Central  PubMed  Google Scholar 

  81. Mali P, Yang L, Esvelt KM, Aach J, Guell M, DiCarlo JE, et al. RNA-guided human genome engineering via Cas9. Science. 2013;339:823–6.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  82. Wang H, Yang H, Shivalila CS, Dawlaty MM, Cheng AW, Zhang F, et al. One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering. Cell. 2013;153:910–8. Cas9 mRNA and single-guide RNAs were introduced into embryonic stem cells or induced pluripotent stem cells to show rapid genome editing in vivo.

    Google Scholar 

  83. Gilbert LA, Larson MH, Morsut L, Liu Z, Brar GA, Torres SE, et al. CRISPR-mediated modular RNA-guided regulation of transcription in eukaryotes. Cell. 2013;154:442–51. Work described in this publication revealed the ability of dCas9 protein to serve as a general platform for RNA-guded targeting, laying groundwork for the use of this approach to the identification of causal variation in cultured human cells, and the rapid manipulation of genomic sequences in vivo.

    Article  PubMed  CAS  Google Scholar 

  84. Yen K, Vinayachandran V, Batta K, Koerber RT, Pugh BF. Genome-wide nucleosome specificity and directionality of chromatin remodelers. Cell. 2012;149:1461–73.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  85. Butter F, Davison L, Viturawong T, Scheibe M, Vermeulen M, Todd JA, et al. Proteome-wide analysis of disease-associated SNPs that show allele-specific transcription factor binding. PLoS Genet. 2012;8:e1002982.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  86. Zhao J, Ohsumi TK, Kung JT, Ogawa Y, Grau DJ, Sarma K, et al. Genome-wide identification of polycomb-associated RNAs by RIP-seq. Mol Cell. 2010;40:939–53.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  87. Scheibe M, Butter F, Hafner M, Tuschl T, Mann M. Quantitative mass spectrometry and PAR-CLIP to identify RNA-protein interactions. Nucleic Acids Res. 2012;40:9897–902.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  88. Shalek AK, Satija R, Adiconis X, Gertner RS, Gaublomme JT, Raychowdhury R, et al. Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature. 2013;498:236–40.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  89. Nica AC, Montgomery SB, Dimas AS, Stranger BE, Beazley C, Barroso I, et al. Candidate causal regulatory effects by integration of expression QTLs with complex trait genetic associations. PLoS Genet. 2010;6:e1000895.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  90. Laurila PP, Surakka I, Sarin AP, Yetukuri L, Hyotylainen T, Soderlund S, et al. Genomic, transcriptomic, and lipidomic profiling highlights the role of inflammation in individuals with low high-density lipoprotein cholesterol. Arterioscler Thromb Vasc Biol. 2013;33:847–57.

    Article  PubMed  CAS  Google Scholar 

  91. Chung RH, Chen YE. A two-stage random forest-based pathway analysis method. PLoS One. 2012;7:e36662.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  92. Califano A, Butte AJ, Friend S, Ideker T, Schadt E. Leveraging models of cell regulation and GWAS data in integrative network-based association studies. Nat Genet. 2012;44:841–7.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  93. Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, et al. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 2012;22:1790–7.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  94. Ward LD, Kellis M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 2012;40:D930–4.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  95. Griffith OL, Montgomery SB, Bernier B, Chu B, Kasaian K, Aerts S, et al. ORegAnno: an open-access community-driven resource for regulatory annotation. Nucleic Acids Res. 2008;36:D107–13.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  96. Bernstein BE, Birney E, Dunham I, Green ED, Gunter C, Snyder M. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57–74.

    Article  PubMed  CAS  Google Scholar 

  97. Bernstein BE, Stamatoyannopoulos JA, Costello JF, Ren B, Milosavljevic A, Meissner A, et al. The NIH, Roadmap Epigenomics Mapping Consortium. Nat Biotechnol. 2010;28:1045–8.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  98. Savic D, Bell GI, Nobrega MA. An in vivo cis-regulatory screen at the type 2 diabetes associated TCF7L2 locus identifies multiple tissue-specific enhancers. PLoS One. 2012;7:e36501.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  99. Jao LE, Wente SR, Chen W. Efficient multiplex biallelic zebrafish genome editing using a CRISPR nuclease system. Proc Natl Acad Sci U S A. 2013;110:13904–9.

    Article  PubMed Central  PubMed  Google Scholar 

  100. Zhong H, Yang X, Kaplan LM, Molony C, Schadt EE. Integrating pathway analysis and genetics of gene expression for genome-wide association studies. Am J Hum Genet. 2010;86:581–91.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

Download references

Compliance with Ethics Guidelines

Conflict of Interest

Clint L. Miller, Themistocles L. Assimes, Stephen B. Montgomery, and Thomas Quertermous declare that they have no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas Quertermous.

Additional information

This article is part of the Topical Collection on Genetics

Rights and permissions

Reprints and permissions

About this article

Cite this article

Miller, C.L., Assimes, T.L., Montgomery, S.B. et al. Dissecting the Causal Genetic Mechanisms of Coronary Heart Disease. Curr Atheroscler Rep 16, 406 (2014). https://doi.org/10.1007/s11883-014-0406-4

Download citation

  • Published:

  • DOI: https://doi.org/10.1007/s11883-014-0406-4

Keywords

Navigation