Genetics paired with CT angiography in the setting of atherosclerosis.

[1]  B. Nallamothu,et al.  FFR(CT): a new technology in search of a clinical application. , 2015, European heart journal.

[2]  D. Andreini,et al.  Rationale and design of the Prospective LongitudinAl Trial of FFRCT: Outcome and Resource IMpacts study. , 2015, American heart journal.

[3]  Matthias Gutberlet,et al.  Clinical outcomes of fractional flow reserve by computed tomographic angiography-guided diagnostic strategies vs. usual care in patients with suspected coronary artery disease: the prospective longitudinal trial of FFRCT: outcome and resource impacts study , 2015, European heart journal.

[4]  Joel T. Dudley,et al.  Genome-wide significant loci: how important are they? Systems genetics to understand heritability of coronary artery disease and other common complex disorders. , 2015, Journal of the American College of Cardiology.

[5]  C. Liakos,et al.  2013 ESH/ESC Guidelines for the Management of Arterial Hypertension: What Has Changed in Daily Clinical Practice? , 2015, High Blood Pressure & Cardiovascular Prevention.

[6]  S. Keleş,et al.  Integromic Analysis of Genetic Variation and Gene Expression Identifies Networks for Cardiovascular Disease Phenotypes , 2015, Circulation.

[7]  Kathleen F. Kerr,et al.  Association of low-density lipoprotein cholesterol-related genetic variants with aortic valve calcium and incident aortic stenosis. , 2014, JAMA.

[8]  S. Murray,et al.  Precision phenotyping, panomics, and system-level bioinformatics to delineate complex biologies of atherosclerosis: rationale and design of the "Genetic Loci and the Burden of Atherosclerotic Lesions" study. , 2014, Journal of cardiovascular computed tomography.

[9]  P.-Y. Zhang,et al.  Impact of epigenetics in the management of cardiovascular disease: a review. , 2014, European review for medical and pharmacological sciences.

[10]  Julia Stehli,et al.  Accuracy of coronary CT angiography using a submillisievert fraction of radiation exposure: comparison with invasive coronary angiography. , 2014, Journal of the American College of Cardiology.

[11]  Werner Jaschke,et al.  The diagnostic and prognostic value of coronary CT angiography in asymptomatic high-risk patients: a cohort study , 2014, Open Heart.

[12]  K. Anstrom,et al.  PROspective Multicenter Imaging Study for Evaluation of chest pain: rationale and design of the PROMISE trial. , 2014, American heart journal.

[13]  T. Lüscher,et al.  The ACC/AHA 2013 guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular disease risk in adults: the good the bad and the uncertain: a comparison with ESC/EAS guidelines for the management of dyslipidaemias 2011. , 2014, European heart journal.

[14]  Erika Check Hayden,et al.  Technology: The $1,000 genome , 2014, Nature.

[15]  T. Lehtimäki,et al.  Genome-Wide Association Study Identifies 3 Genomic Loci Significantly Associated With Serum Levels of Homoarginine: The AtheroRemo Consortium , 2013, Circulation. Cardiovascular genetics.

[16]  A. Korte,et al.  The advantages and limitations of trait analysis with GWAS: a review , 2013, Plant Methods.

[17]  Charles A. Taylor,et al.  Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. , 2013, Journal of the American College of Cardiology.

[18]  R. Hinton.  Genetic and Environmental Factors Contributing to Cardiovascular Malformation: A Unified Approach to Risk , 2013, Journal of the American Heart Association.

[19]  L. Game,et al.  The use of next-generation sequencing in clinical diagnosis of familial hypercholesterolemia , 2013, Genetics in Medicine.

[20]  P. Douglas,et al.  A Blood-Based Gene Expression Test for Obstructive Coronary Artery Disease Tested in Symptomatic Nondiabetic Patients Referred for Myocardial Perfusion Imaging The COMPASS Study , 2013, Circulation. Cardiovascular genetics.

[21]  S. Kishi,et al.  Polymorphism in the human matrix Gla protein gene is associated with the progression of vascular calcification in maintenance hemodialysis patients , 2013, Clinical and Experimental Nephrology.

[22]  E. Boerwinkle,et al.  Association of Genome-Wide Variation With Highly Sensitive Cardiac Troponin-T Levels in European Americans and Blacks: A Meta-Analysis From Atherosclerosis Risk in Communities and Cardiovascular Health Studies , 2013, Circulation. Cardiovascular genetics.

[23]  P. Joshi,et al.  A peripheral blood gene expression score is associated with plaque volume and phenotype by intravascular ultrasound with radiofrequency backscatter analysis: results from the ATLANTA study. , 2013, Cardiovascular diagnosis and therapy.

[24]  P. Lucatelli,et al.  Evidence for a Strong Genetic Influence on Carotid Plaque Characteristics: An International Twin Study , 2012, Stroke.

[25]  W. Kraus,et al.  A gender-specific blood-based gene expression score for assessing obstructive coronary artery disease in nondiabetic patients: results of the Personalized Risk Evaluation and Diagnosis in the Coronary Tree (PREDICT) trial. , 2012, American heart journal.

[26]  Michael R. Hayden,et al.  Whole-Genome Sequencing: The New Standard of Care? , 2012, Science.

[27]  V. Fuster,et al.  Acute Coronary Events , 2012, Circulation.

[28]  M. Reilly,et al.  Genetic Basis of Atherosclerosis: Insights From Mice and Humans , 2012, Circulation research.

[29]  T. Furey,et al.  Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets. , 2011, Genome research.

[30]  K. Shianna,et al.  Exome sequencing: the expert view , 2011, Genome Biology.

[31]  Eric Banks,et al.  Comparing strategies to fine-map the association of common SNPs at chromosome 9p21 with type 2 diabetes and myocardial infarction , 2011, Nature Genetics.

[32]  Szilard Voros,et al.  Development of a blood-based gene expression algorithm for assessment of obstructive coronary artery disease in non-diabetic patients , 2011, BMC Medical Genomics.

[33]  Mary G. George,et al.  Forecasting the Future of Cardiovascular Disease in the United States: A Policy Statement From the American Heart Association , 2011, Circulation.

[34]  Zhen Qian,et al.  Prospective validation of standardized, 3-dimensional, quantitative coronary computed tomographic plaque measurements using radiofrequency backscatter intravascular ultrasound as reference standard in intermediate coronary arterial lesions: results from the ATLANTA (assessment of tissue characterist , 2011, JACC. Cardiovascular interventions.

[35]  Szilard Voros,et al.  Multicenter Validation of the Diagnostic Accuracy of a Blood-Based Gene Expression Test for Assessing Obstructive Coronary Artery Disease in Nondiabetic Patients , 2010, Annals of Internal Medicine.

[36]  P. Tontonoz,et al.  Genome-Wide Association Studies Identify New Targets in Cardiovascular Disease , 2010, Science Translational Medicine.

[37]  M. Girolami,et al.  Recommendations for Biomarker Identification and Qualification in Clinical Proteomics , 2010, Science Translational Medicine.

[38]  E. Tuzcu,et al.  Intravascular ultrasound-derived measures of coronary atherosclerotic plaque burden and clinical outcome. , 2010, Journal of the American College of Cardiology.

[39]  M. King,et al.  Genetic Heterogeneity in Human Disease , 2010, Cell.

[40]  M. Fornage,et al.  Associations of Lipoprotein Lipase Gene Polymorphisms With Longitudinal Plasma Lipid Trends in Young Adults: The Coronary Artery Risk Development in Young Adults (CARDIA) Study , 2010, Circulation. Cardiovascular genetics.

[41]  J. Asimit,et al.  Region-based analysis in genome-wide association study of Framingham Heart Study blood lipid phenotypes , 2009, BMC proceedings.

[42]  V. Bajic,et al.  Multi-Organ Expression Profiling Uncovers a Gene Module in Coronary Artery Disease Involving Transendothelial Migration of Leukocytes and LIM Domain Binding 2: The Stockholm Atherosclerosis Gene Expression (STAGE) Study , 2009, PLoS genetics.

[43]  N. Weissman,et al.  Advances in intravascular imaging. , 2009, Circulation. Cardiovascular interventions.

[44]  F. Sera,et al.  Optimal stent-sizing with intravascular ultrasound contributes to complete neointimal coverage after sirolimus-eluting stent implantation assessed by angioscopy. , 2009, JACC. Cardiovascular interventions.

[45]  R. Bauer,et al.  Noncalcified atherosclerotic plaque burden at coronary CT angiography: a better predictor of ischemia at stress myocardial perfusion imaging than calcium score and stenosis severity. , 2009, AJR. American journal of roentgenology.

[46]  Gorka Bastarrika,et al.  Reproducibility of Automated Noncalcified Coronary Artery Plaque Burden Assessment at Coronary CT Angiography , 2009, Journal of thoracic imaging.

[47]  Joshua M. Korn,et al.  Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants , 2009, Nature Genetics.

[48]  Robert A. Hegele,et al.  Plasma lipoproteins: genetic influences and clinical implications , 2009, Nature Reviews Genetics.

[49]  D. Dries.  STATISTICAL GENETICS: GENE MAPPING THROUGH LINKAGE AND ASSOCIATION , 2008 .

[50]  A. Caixeta,et al.  Assessing intermediate coronary lesions: angiographic prediction of lesion severity on intravascular ultrasound. , 2007, The Journal of invasive cardiology.

[51]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[52]  P. Libby,et al.  Atherosclerosis: the path from genomics to therapeutics. , 2007, Journal of the American College of Cardiology.

[53]  J. Hokanson,et al.  Polymorphisms of the Renin-Angiotensin System Genes Predict Progression of Subclinical Coronary Atherosclerosis , 2007, Diabetes.

[54]  Chi Pui Pang,et al.  HTRA1 promoter polymorphism in wet age-related macular degeneration. , 2007, Science.

[55]  N. Weissman,et al.  New imaging techniques for diagnosing coronary artery disease , 2006, Canadian Medical Association Journal.

[56]  R. Mayeux.  Mapping the new frontier: complex genetic disorders. , 2005, The Journal of clinical investigation.

[57]  J. Ott,et al.  Complement Factor H Polymorphism in Age-Related Macular Degeneration , 2005, Science.

[58]  Sui Huang.  Gene expression profiling, genetic networks, and cellular states: an integrating concept for tumorigenesis and drug discovery , 1999, Journal of Molecular Medicine.

[59]  W. Fennell,et al.  Randomized, double-blind study comparing saruplase with streptokinase therapy in acute myocardial infarction: the COMPASS Equivalence Trial. Comparison Trial of Saruplase and Streptokinase (COMASS) Investigators. , 1998, Journal of the American College of Cardiology.

[60]  R. Peto,et al.  Clinical trial methodology , 1978, Nature.

[61]  T. Iwasaka,et al.  MYOCARDIAL INFARCTION , 1944, British heart journal.

[62]  S. Malhotra,et al.  A selection of recent, original research papers , 2015, Journal of Nuclear Cardiology.

[63]  E. Halperin,et al.  Relation of genetic profile and novel circulating biomarkers with coronary plaque phenotype as determined by intravascular ultrasound: rationale and design of the ATHEROREMO-IVUS study. , 2014, EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology.

[64]  Mulugeta Gebregziabher,et al.  Reproducibility of noncalcified coronary artery plaque burden quantification from coronary CT angiography across different image analysis platforms. , 2014, AJR. American journal of roentgenology.

[65]  Michael H. Olsen,et al.  ESH / ESC Guidelines for the management of arterial hypertension , 2013 .

[66]  T. Manolio,et al.  How to Interpret a Genome-wide Association Study Topic Collections , 2022 .

[67]  J. Murabito,et al.  Bmc Medical Genetics Genome-wide Association Study for Subclinical Atherosclerosis in Major Arterial Territories in the Nhlbi's Framingham Heart Study , 2022 .

[68]  E. Boerwinkle,et al.  Bmc Medical Genetics Genome-wide Association Study for Renal Traits in the Framingham Heart and Atherosclerosis Risk in Communities Studies , 2022 .