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Coronary Artery Disease: HELP
Articles from NIH Bethesda
Based on 260 articles published since 2010
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These are the 260 published articles about Coronary Artery Disease that originated from NIH Bethesda during 2010-2020.
 
+ Citations + Abstracts
Pages: 1 · 2 · 3 · 4 · 5 · 6 · 7 · 8 · 9 · 10 · 11
51 Article Individualizing Revascularization Strategy for Diabetic Patients With Multivessel Coronary Disease. 2019

Qintar, Mohammed / Humphries, Karin H / Park, Julie E / Arnold, Suzanne V / Tang, Yuanyuan / Jones, Phillip / Salisbury, Adam C / Kureshi, Faraz / Farkouh, Michael E / Fuster, Valentin / Cohen, David J / Spertus, John A. ·Saint Luke's Mid America Heart Institute and the University of Missouri-Kansas City, Kansas City, Missouri. Electronic address: qintarm@umkc.edu. · University of British Columbia, Vancouver, British Columbia, Canada. · Saint Luke's Mid America Heart Institute and the University of Missouri-Kansas City, Kansas City, Missouri. · Austin Heart, St. David's Heart and Vascular, Austin, Texas; National Institutes of Health, National Heart, Lung, and Blood Institute, Bethesda, Maryland. · Peter Munk Cardiac Centre and the Heart and Stroke Richard Lewar Centre, University of Toronto, Toronto, Ontario, Canada. · Zena and Michael Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain. ·J Am Coll Cardiol · Pubmed #31623766.

ABSTRACT: BACKGROUND: In patients with diabetes and multivessel coronary artery disease (CAD), the FREEDOM (Future Revascularization Evaluation in Patients with Diabetes Mellitus: Optimal Management of Multivessel Disease) trial demonstrated that, on average, coronary artery bypass grafting (CABG) was superior to percutaneous coronary intervention (PCI) for major acute cardiovascular events (MACE) and angina reduction. Nonetheless, multivessel PCI remains a common revascularization strategy in the real world. OBJECTIVES: To translate the results of FREEDOM to individual patients in clinical practice, risk models of the heterogeneity of treatment benefit were built. METHODS: Using patient-level data from 1,900 FREEDOM patients, the authors developed models to predict 5-year MACE (all-cause mortality, nonfatal myocardial infarction, and nonfatal stroke) and 1-year angina after CABG and PCI using baseline covariates and treatment interactions. Parsimonious models were created to support clinical use. The models were internally validated using bootstrap resampling, and the MACE model was externally validated in a large real-world registry. RESULTS: The 5-year MACE occurred in 346 (18.2%) patients, and 310 (16.3%) had angina at 1 year. The MACE model included 8 variables and treatment interactions with smoking status (c = 0.67). External validation in stable CAD (c = 0.65) and ACS (c = 0.68) demonstrated comparable performance. The 6-variable angina model included a treatment interaction with SYNTAX score (c = 0.67). PCI was never superior to CABG, and CABG was superior to PCI for MACE in 54.5% of patients and in 100% of patients with history of smoking. CONCLUSIONS: To help disseminate the results of FREEDOM, the authors created a personalized risk prediction tool for patients with diabetes and multivessel CAD that could be used in shared decision-making for CABG versus PCI by estimating each patient's personal outcomes with both treatments.

52 Article Trends in Death Rate 2009 to 2018 Following Percutaneous Coronary Intervention Stratified by Acuteness of Presentation. 2019

Gajanana, Deepakraj / Weintraub, William S / Kolm, Paul / Rogers, Toby / Iantorno, Micaela / Ben-Dor, Itsik / Khalid, Nauman / Shlofmitz, Evan / Khan, Jaffar M / Chen, Yuefeng / Musallam, Anees / Kajita, Alexandre H / Hashim, Hayder / Satler, Lowell F / Torguson, Rebecca / Waksman, Ron. ·Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia. · Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia; Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland. · Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, District of Columbia. Electronic address: ron.waksman@medstar.net. ·Am J Cardiol · Pubmed #31547993.

ABSTRACT: Percutaneous coronary intervention (PCI) has evolved dramatically, along with patient complexity. We studied trends in in-hospital mortality with changes in patient complexity over the last decade stratified by clinical presentation. The study population included all patients presenting to the cardiac catheterization lab between January 2009 and July 2018. Expected in-hospital mortality was calculated using the National Cardiovascular Data Registry CathPCI risk scoring system. Yearly mean in-hospital mortality rates (%) were plotted and smoothed by weighted least squares regression for each presentation: ST-elevation myocardial infarction (STEMI), non-ST-elevation acute coronary syndrome (NSTE-ACS), and stable ischemic coronary artery disease (SI CAD). The overall cohort included 13,732 patients who underwent PCI during the study period, of whom 2,142 were for STEMI, 2,836 for NSTE-ACS, and 8,754 for SI CAD. Indications for PCI have changed over time, with more PCIs being performed for NSTE-ACS and STEMI than for SI CAD. NSTE-ACS and STEMI patients had a steady decrease in in-hospital mortality over time compared with SI CAD patients. Overall observed mortality continues to decrease in NSTE-ACS patients, with reduction in the observed mortality rate within the STEMI population to below expected since 2013. Patient complexity has not changed significantly. These results may be attributed to improved patient selection coupled with optimal pharmacotherapy with more robust therapies during procedure and hospitalization.

53 Article Prognostic implications of QRS dispersion for major adverse cardiovascular events in asymptomatic women and men: the Multi-Ethnic Study of Atherosclerosis. 2019

Jain, Rahul / Gautam, Sandeep / Wu, Colin / Shen, Changyu / Jain, Aditya / Giesdal, Ola / Chahal, Harjit / Lin, Hongbo / Bluemke, David A / Soliman, Elsayed Z / Nazarian, Saman / Lima, João A C. ·Department of Cardiology, Krannert Institute of Cardiology, Indiana University School of Medicine, 1800 N. Capitol Avenue, Indianapolis, IN, 46202, USA. rahujain@iu.edu. · Division of Cardiology, Johns Hopkins School of Medicine, Baltimore, MD, USA. rahujain@iu.edu. · Division of Cardiovascular Medicine, University of Missouri, Columbia, MO, USA. · Division of Cardiology, Johns Hopkins School of Medicine, Baltimore, MD, USA. · Office of Biostatistics Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA. · Department of Biostatistics, School of Medicine and Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA. · Radiology and Imaging Sciences, National Institute of Health, Bethesda, MD, USA. · Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention and Department of Internal Medicine, Cardiology Section, Wake Forest School of Medicine, Winston-Salem, NC, USA. ·J Interv Card Electrophysiol · Pubmed #31482330.

ABSTRACT: BACKGROUND: QRS dispersion measured as the difference between maximal and minimal QRS duration in the standard 12-lead electrocardiogram has been shown to be associated with increased mortality in heart failure (HF) patients and increased arrhythmic events in patients with cardiomyopathy. AIMS: This study sought to examine the prognostic association between baseline QRS dispersion and future cardiovascular events in individuals without known prior cardiovascular disease. METHODS: The association of QRS dispersion with cardiovascular events was examined in 6510 MESA (Multi-Ethnic Study of Atherosclerosis) participants. Participants with bundle branch block were excluded. Study participants were divided into two groups based on the 95th percentile of QRS dispersion (QRS dispersion < 34 ms [group I] and QRS dispersion ≥ 34 ms [group II]). Cox proportional hazard models adjusting for demographic and clinical risk factors were used to examine the association of QRS dispersion with incident cardiovascular events (major adverse cardiovascular events [MACE]) and mortality. Analysis was repeated by forcing Framingham risk factors. RESULTS: Mean age was 62 ± 10 years in group I and 63 ± 10 years in group II (P = 0.02). QRS dispersion ≥ 34 ms was associated significantly with MACE (HR 1.30; 95% CI 1.04-1.62) and mortality (HR 1.33; 95% CI 1.03-1.73) after adjustment for cardiovascular risk factors and potential cofounders. Similar results were seen for mortality after adjustment for Framingham risk factors. CONCLUSION: QRS dispersion ≥ 34 ms predicts cardiovascular events and mortality.

54 Article Serum active 1,25(OH) 2019

Playford, Martin P / Dey, Amit K / Zierold, Claudia / Joshi, Aditya A / Blocki, Frank / Bonelli, Fabrizio / Rodante, Justin A / Harrington, Charlotte L / Rivers, Joshua P / Elnabawi, Youssef A / Chen, Marcus Y / Ahlman, Mark A / Teague, Heather L / Mehta, Nehal N. ·Section of Inflammation and Cardiometabolic Diseases, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA. · DIaSorin Inc, 1951 Northwestern Avenue, Stillwater, MN, USA. · Section of Inflammation and Cardiometabolic Diseases, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA. Electronic address: nehal.mehta@nih.gov. ·Atherosclerosis · Pubmed #31450013.

ABSTRACT: BACKGROUND AND AIMS: Vitamin D exists as an inactive 25-hydroxyvitamin D (25(OH)D) in the bloodstream, which is converted to active 1,25-dihydroxyvitaminD (1,25(OH) METHODS: Consecutive psoriasis patients (N = 122) at baseline underwent FDG PET/CT and CCTA scans to measure visceral adipose volume, aortic vascular uptake of FDG, and coronary plaque burden respectively. Blood levels of both 1,25(OH) RESULTS: The psoriasis cohort was middle-aged (mean ± SD: 49.6 ± 13.0), predominantly male (n = 71, 58%), in majority Caucasians (n = 98, 80%), and had moderate-to-severe skin disease [psoriasis area severity index score, PASI score, med. (IQR): 5.5 (3.2-10.7)], with almost one-fourth of the cohort on biologic psoriasis therapy for skin disease management (n = 32, 27%) at baseline. Interestingly, serum levels of 1,25(OH) CONCLUSIONS: In conclusion, we demonstrate that low 1,25(OH)

55 Article Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease. 2019

Agha, Golareh / Mendelson, Michael M / Ward-Caviness, Cavin K / Joehanes, Roby / Huan, TianXiao / Gondalia, Rahul / Salfati, Elias / Brody, Jennifer A / Fiorito, Giovanni / Bressler, Jan / Chen, Brian H / Ligthart, Symen / Guarrera, Simonetta / Colicino, Elena / Just, Allan C / Wahl, Simone / Gieger, Christian / Vandiver, Amy R / Tanaka, Toshiko / Hernandez, Dena G / Pilling, Luke C / Singleton, Andrew B / Sacerdote, Carlotta / Krogh, Vittorio / Panico, Salvatore / Tumino, Rosario / Li, Yun / Zhang, Guosheng / Stewart, James D / Floyd, James S / Wiggins, Kerri L / Rotter, Jerome I / Multhaup, Michael / Bakulski, Kelly / Horvath, Steven / Tsao, Philip S / Absher, Devin M / Vokonas, Pantel / Hirschhorn, Joel / Fallin, M Daniele / Liu, Chunyu / Bandinelli, Stefania / Boerwinkle, Eric / Dehghan, Abbas / Schwartz, Joel D / Psaty, Bruce M / Feinberg, Andrew P / Hou, Lifang / Ferrucci, Luigi / Sotoodehnia, Nona / Matullo, Giuseppe / Peters, Annette / Fornage, Myriam / Assimes, Themistocles L / Whitsel, Eric A / Levy, Daniel / Baccarelli, Andrea A. ·Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York (G.A., A.A.B.). · Population Sciences Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD (M.M.M., D.L., R.J.). · Framingham Heart Study, MA (M.M.M., D.L.). · Department of Cardiology, Boston Children's Hospital, MA (M.M.M.). · National Health and Environmental Effects Research Laboratory, Environmental Public Health Division, Chapel Hill, NC (C.K.W.C.). · Institute of Epidemiology II, Helmholtz Institute, Ingolstaedter Landstrasse 1, Neuherberg, Germany (C.K.W.C.). · Hebrew SeniorLife, Harvard Medical School, Boston, MA (R.J.). · The Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD (T.X.H.). · Department of Epidemiology (R.G.), University of North Carolina, Chapel Hill. · Department of Medicine, Stanford University School of Medicine, CA (E.S., P.S.T.). · Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle (J.A.B., J.S.F., K.L.W.). · Italian Institute for Genomic Medicine (IIGM/HuGeF) and Department of Medical Sciences, University of Turin, Italy (G.F., S.G., G.P.). · Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston (J.B.). · Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD (B.H.C., T.T.). · Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands (S.L.). · Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY (E.C., A.C.J.). · Research Unit Molecualr Epidemiology, Helmholtz Zentrum München, Germany (S.W., C.G.). · Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD (A.R.V., M.M.). · Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD (D.G.H., A.B.S.). · Epidemiology and Public Health Group, University of Exeter Medical School, United Kingdom (L.C.P.). · Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital and Center for Cancer Prevention (CPO), Turin, Italy (C.S.). · Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy (V.K.). · Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy (S.P.). · Cancer Registry And Histopathology Department, Civic- M.P. Arezzo2 Hospital, Asp Ragusa, Italy (R.T.). · Department of Genetics, Department of Biostatistics, Department of Computer Science (Y.L.), University of North Carolina, Chapel Hill. · Curriculum in Bioinformatics and Computational Biology, Department of Genetics, and Department of Statistics (G.Z.), University of North Carolina, Chapel Hill. · Carolina Population Center and Department of Epidemiology (J.D.S.), University of North Carolina, Chapel Hill. · The Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, CA (J.I.R.). · Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor (K.B.). · Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles (S.H.). · HudsonAlpha institute of Biotechnology, Huntsville, AL (D.M.A.). · VA Normative Aging Study, VA Boston Healthcare System, Department of Medicine, Boston University School of Medicine, MA (P.V.). · Department of Medicine, Division of Endocrinology, Boston Children's Hospital, MA (J.H.). · Departments of Medicine and Pediatrics, Harvard Medical School, Boston, MA (J.H.). · Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (M.D.F.). · Department of Biostatistics, Boston University School of Public Health, MA (C.L.). · Azienda Sanitaria, USL Centro Firenze, Italy (S.B.). · Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston (E.B.). · Human Genome Sequencing Center, Baylor College of Medicine, TX (E.B.). · Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of 346 Public Health, Imperial College London, United Kingdom (A.D.). · Department of Epidemiology and Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA (J.D.S.). · Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle (B.M.P.). · Kaiser Permanente Washington Health Research Institute, Seattle (B.M.P.). · Departments of Medicine, Biomedical Engineering, and Mental Health, Johns Hopkins University, Baltimore, MD (A.P.F.). · Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL (L.H.). · Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD (L.F.). · Division of Cardiology, Departments of Medicine and Epidemiology, Cardiovascular Health Research Unit, University of Washington, Seattle (N.S.). · Helmholtz Zentrum München, Institute of Epidemiology, Neuherberg, Germany; German Research Center for Cardiovascular Disease (DzHK e.V. - partner site Munich), Germany (A.P.). · Ludwig-Maximilians University, Institute for Biometry, Medical Information Science and Epidemiology, Munich, Germany (A.P.). · Brown Foundation Institute of Molecular Medicine McGovern Medical School, and Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston (M.F.). · Department of Medicine (Cardiovascular Medicine), and Department of Health Research & Policy, Stanford University School of Medicine, CA (T.L.A.). · Department of Epidemiology, Gillings School of Global Public Health, and Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill (E.A.W.). ·Circulation · Pubmed #31424985.

ABSTRACT: BACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts. METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts. RESULTS: Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts. CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.

56 Article Coronary Artery Calcium From Early Adulthood to Middle Age and Left Ventricular Structure and Function. 2019

Yared, Guilherme S / Moreira, Henrique T / Ambale-Venkatesh, Bharath / Vasconcellos, Henrique D / Nwabuo, Chike C / Ostovaneh, Mohammad R / Reis, Jared P / Lloyd-Jones, Donald M / Schreiner, Pamela J / Lewis, Cora E / Sidney, Stephen / Carr, John J / Gidding, Samuel S / Lima, João A C. ·Division of Cardiology, Johns Hopkins University, Baltimore, MD (G.S.Y., H.T.M., B.A.-V., H.D.V., C.C.N., M.R.O., J.A.C.L.). · Division of Cardiology, University of São Paulo, Ribeirão Preto, Brazil (H.T.M.). · Division of Cardiovascular Sciences, National Heart Lung and Blood Institute, Bethesda, MD (J.P.R.). · Department of Preventive Medicine, Northwestern University, Chicago, IL (D.M.L.-J.). · Division of Epidemiology and Community Health, University of Minnesota, Minneapolis (P.J.S.). · Division of Preventive Medicine, University of Alabama at Birmingham (C.E.L.). · Division of Research, Kaiser Permanente Division of Research, Oakland, CA (S.S.). · Departments of Radiology, Biomedical Informatics, and Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN (J.J.C.). · The FH Foundation, Pasadena, CA (S.S.G.). ·Circ Cardiovasc Imaging · Pubmed #31195818.

ABSTRACT: Background The relationship of coronary artery calcium (CAC) with adverse cardiac remodeling is not well established. We aimed to study the association of CAC in middle age and change in CAC from early adulthood to middle age with left ventricular (LV) function. Methods CAC score was measured by computed tomography at CARDIA study (Coronary Artery Risk Development in Young Adults) year-15 examination and at year-25 examination (Y25) in 3043 and 3189 participants, respectively. CAC score was assessed as a continuous variable and log-transformed to account for nonlinearity. Change in CAC from year-15 examination to Y25 was evaluated as the absolute difference of log-transformed CAC from year-15 examination to Y25. LV structure and function were evaluated by echocardiography at Y25. Results At Y25, mean age was 50.1±3.6 years, 56.6% women, 52.4% black. In the multivariable analysis at Y25, higher CAC was related to higher LV mass (β=1.218; adjusted P=0.007), higher LV end-diastolic volume (β=0.811; adjusted P=0.007), higher LV end-systolic volume (β=0.350; adjusted P=0.048), higher left atrial volume (β=0.214; adjusted P=0.009), and higher E/e' ratio (β=0.059; adjusted P=0.014). CAC was measured at both year-15 examination and Y25 in 2449 individuals. Higher change in CAC score during follow-up was independently related to higher LV mass index in blacks (β=4.789; adjusted P<0.001), but not in whites (β=1.051; adjusted P=0.283). Conclusions Higher CAC in middle age is associated with higher LV mass and volumes and worse LV diastolic function. Being free of CAC from young adulthood to middle age correlates to better LV function at middle age. Higher change in CAC score during follow-up is independently related to higher LV mass index in blacks.

57 Article Diagnosis of obstructive coronary artery disease using computed tomography angiography in patients with stable chest pain depending on clinical probability and in clinically important subgroups: meta-analysis of individual patient data. 2019

Haase, Robert / Schlattmann, Peter / Gueret, Pascal / Andreini, Daniele / Pontone, Gianluca / Alkadhi, Hatem / Hausleiter, Jörg / Garcia, Mario J / Leschka, Sebastian / Meijboom, Willem B / Zimmermann, Elke / Gerber, Bernhard / Schoepf, U Joseph / Shabestari, Abbas A / Nørgaard, Bjarne L / Meijs, Matthijs F L / Sato, Akira / Ovrehus, Kristian A / Diederichsen, Axel C P / Jenkins, Shona M M / Knuuti, Juhani / Hamdan, Ashraf / Halvorsen, Bjørn A / Mendoza-Rodriguez, Vladimir / Rochitte, Carlos E / Rixe, Johannes / Wan, Yung Liang / Langer, Christoph / Bettencourt, Nuno / Martuscelli, Eugenio / Ghostine, Said / Buechel, Ronny R / Nikolaou, Konstantin / Mickley, Hans / Yang, Lin / Zhang, Zhaqoi / Chen, Marcus Y / Halon, David A / Rief, Matthias / Sun, Kai / Hirt-Moch, Beatrice / Niinuma, Hiroyuki / Marcus, Roy P / Muraglia, Simone / Jakamy, Réda / Chow, Benjamin J / Kaufmann, Philipp A / Tardif, Jean-Claude / Nomura, Cesar / Kofoed, Klaus F / Laissy, Jean-Pierre / Arbab-Zadeh, Armin / Kitagawa, Kakuya / Laham, Roger / Jinzaki, Masahiro / Hoe, John / Rybicki, Frank J / Scholte, Arthur / Paul, Narinder / Tan, Swee Y / Yoshioka, Kunihiro / Röhle, Robert / Schuetz, Georg M / Schueler, Sabine / Coenen, Maria H / Wieske, Viktoria / Achenbach, Stephan / Budoff, Matthew J / Laule, Michael / Newby, David E / Dewey, Marc / Anonymous4951133. ·Department of Radiology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany. · Institute of Medical Statistics, Computer Sciences and Data Science, University Hospital of Friedrich Schiller University Jena, Jena, Germany. · Department of Cardiology, Henri Mondor Hospital, University Paris Est Créteil, Créteil, France. · Department of Cardiology and Radiology, Centro Cardiologico Monzino IRCCS, University of Milan, Milan, Italy. · Centro Cardiologico Monzino, IRCCS, Milan, Italy. · Department of Radiology, University Hospital Zurich, Zurich, Switzerland. · Medizinische Klinik und Poliklinik I, Ludwig-Maximilians-Universität München, Munich, Germany. · Department of Cardiology, Montefiore, University Hospital for the Albert Einstein College of Medicine, NY, USA. · Department of Radiology, Kantonsspital St Gallen, St Gallen, Switzerland. · Department of Cardiology, Erasmus University Medical Centre, Rotterdam, Netherlands. · Department of Cardiology, Clinique Universitaire St Luc, Institut de Recherche Clinique et Expérimentale, Brussels, Belgium. · Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA. · Modarres Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. · Department of Cardiology, Aarhus Universtity Hostipal, Aarhus, Denmark. · Department of Cardiology, University Medical Centre Utrecht, Utrecht, Netherlands. · Cardiovascular Division, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan. · Department of Cardiology, Odense University Hospital, Odense, Denmark. · Department of Cardiology, Glasgow Royal Infirmary and Stobhill Hospital, Glasgow, UK. · Turku University Hospital and University of Turku, Turku, Finland. · Department of Cardiovascular Imaging, Department of Cardiology, Rabin Medical Center, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel. · Medical Department, Ostfold Hospital Trust, Grålum, Norway. · Department of Cardiology, National Institute of Cardiology and Cardiovascular Surgery, Havana, Cuba. · Heart Institute, InCor, University of São Paulo Medical School, São Paulo, Brazil. · Department of Cardiology, Kerckhoff Heart Centre, Bad Nauheim, Germany. · Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Chang Gung Memorial Hospital at Linkou, Taoyaun City, Taiwan. · Heart and Diabetes Center NRW in Bad Oeynhausen, University Clinic of the Ruhr-University Bochum, Bochum, Germany. · Department of Cardiology, Centro Hospitalar de Vila Nova de Gaia, Vila Nova de Gaia, Portugal. · Department of Internal Medicine, University of Rome Tor Vergata, Rome, Italy. · Department of Cardiology, Centre Chirurgical Marie Lannelongue, Le Plessis Robinson, France. · Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland. · Department of Diagnostic and Interventional Radiology, University Hospital of Tübingen, Tübingen, Germany. · Department of Radiology, Beijing Anzhen Hospital, Beijing, China. · National Heart and Blood Institute, National Institutes of Health, Bethesda, MD, USA. · Cardiovascular Clinical Research Unit, Lady Davis Carmel Medical Center, Haifa, Israel. · Department of Radiology, Baotou Central Hospital, Inner Mongolia Province, China. · St Luke's International Hospital, Tokyo, Japan. · Department of Cardiology, S Chiara Hospital, Trento, Italy. · Department of Cardiology, University Hospital Pitié-Salpêtrière, Paris, France. · University of Ottawa, Heart Institute, Ottawa, Ontario, Canada. · Montreal Heart Institute, Université de Montréal, Montréal, Canada. · Albert Einstein Hospital, São Paulo, Brazil. · The Heart Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark. · Department of Diagnostic Imaging and Interventional Radiology, Bichat University Hospital, Paris, France. · Division of Cardiology, Johns Hopkins Hospital, Johns Hopkins University, Baltimore, MD, USA. · Mie University Hospital, Tsu, Japan. · BIDMC/Harvard Medical School, Department of Cardiology, Beth Israel Deaconess Medical Center, Harvard University, Boston, MA, USA. · Department of Radiology, Keio University Hospital, Tokyo, Japan. · Department of Radiology, Mount Elizabeth Hospital, Singapore. · Department of Radiology, University of Ottawa, Ottawa, Ontario, Canada. · Department of Cardiology, Leiden University Medical Centre, Leiden, Netherlands. · Department of Medical Imaging, Western University, London, Ontario, Canada. · National Heart Centre, Singapore, Singapore. · Iwate Medical University, Morioka, Japan. · Department of Cardiology, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany. · University of California Los Angeles, Los Angeles, CA, USA. · British Heart Foundation, University of Edinburgh, Edinburgh, UK. · Department of Radiology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany dewey@charite.de. ·BMJ · Pubmed #31189617.

ABSTRACT: OBJECTIVE: To determine whether coronary computed tomography angiography (CTA) should be performed in patients with any clinical probability of coronary artery disease (CAD), and whether the diagnostic performance differs between subgroups of patients. DESIGN: Prospectively designed meta-analysis of individual patient data from prospective diagnostic accuracy studies. DATA SOURCES: Medline, Embase, and Web of Science for published studies. Unpublished studies were identified via direct contact with participating investigators. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Prospective diagnostic accuracy studies that compared coronary CTA with coronary angiography as the reference standard, using at least a 50% diameter reduction as a cutoff value for obstructive CAD. All patients needed to have a clinical indication for coronary angiography due to suspected CAD, and both tests had to be performed in all patients. Results had to be provided using 2×2 or 3×2 cross tabulations for the comparison of CTA with coronary angiography. Primary outcomes were the positive and negative predictive values of CTA as a function of clinical pretest probability of obstructive CAD, analysed by a generalised linear mixed model; calculations were performed including and excluding non-diagnostic CTA results. The no-treat/treat threshold model was used to determine the range of appropriate pretest probabilities for CTA. The threshold model was based on obtained post-test probabilities of less than 15% in case of negative CTA and above 50% in case of positive CTA. Sex, angina pectoris type, age, and number of computed tomography detector rows were used as clinical variables to analyse the diagnostic performance in relevant subgroups. RESULTS: Individual patient data from 5332 patients from 65 prospective diagnostic accuracy studies were retrieved. For a pretest probability range of 7-67%, the treat threshold of more than 50% and the no-treat threshold of less than 15% post-test probability were obtained using CTA. At a pretest probability of 7%, the positive predictive value of CTA was 50.9% (95% confidence interval 43.3% to 57.7%) and the negative predictive value of CTA was 97.8% (96.4% to 98.7%); corresponding values at a pretest probability of 67% were 82.7% (78.3% to 86.2%) and 85.0% (80.2% to 88.9%), respectively. The overall sensitivity of CTA was 95.2% (92.6% to 96.9%) and the specificity was 79.2% (74.9% to 82.9%). CTA using more than 64 detector rows was associated with a higher empirical sensitivity than CTA using up to 64 rows (93.4% CONCLUSIONS: In a no-treat/treat threshold model, the diagnosis of obstructive CAD using coronary CTA in patients with stable chest pain was most accurate when the clinical pretest probability was between 7% and 67%. Performance of CTA was not influenced by the angina pectoris type and was slightly higher in men and lower in older patients. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42012002780.

58 Article Mendelian randomisation analyses find pulmonary factors mediate the effect of height on coronary artery disease. 2019

Marouli, Eirini / Del Greco, M Fabiola / Astley, Christina M / Yang, Jian / Ahmad, Shafqat / Berndt, Sonja I / Caulfield, Mark J / Evangelou, Evangelos / McKnight, Barbara / Medina-Gomez, Carolina / van Vliet-Ostaptchouk, Jana V / Warren, Helen R / Zhu, Zhihong / Hirschhorn, Joel N / Loos, Ruth J F / Kutalik, Zoltan / Deloukas, Panos. ·1William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ UK. · 2Centre for Genomic Health, Life Sciences, Queen Mary University of London, London, EC1M 6BQ UK. · Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lubeck, Bolzano, 39100 Italy. · 4Boston Children's Hospital, Boston, MA 02115 USA. · 5Broad Institute of Harvard and MIT, Cambridge, MA 02142 USA. · 6Institute for Molecular Bioscience, University of Queensland, Brisbane, 4072 QLD Australia. · 7Queensland Brain Institute, The University of Queensland, Brisbane, 4072 QLD Australia. · 8Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115 USA. · 9Division of Preventive Medicine, Harvard Medical School, Department of Medicine, Brigham and Women's Hospital, Boston, MA 02215 USA. · 10Department of Medical Sciences, Molecular Epidemiology, Uppsala University, Uppsala, 751 41 Sweden. · Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892 USA. · 12National Institute for Health Research, Barts Cardiovascular Biomedical Research Center, Queen Mary University of London, London, EC1M 6BQ UK. · 13Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG UK. · 14Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, 45110 Greece. · 15Department of Biostatistics, University of Washington, Seattle, WA 98101 USA. · 16Department of Internal Medicine, Erasmus Medical Center, Rotterdam, 3015 GE The Netherlands. · 17Department of Epidemiology, Erasmus Medical Center, Rotterdam, 3015 GE The Netherlands. · 18Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, 9713 GZ The Netherlands. · 19The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029 USA. · 20Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, 1010 Switzerland. · 21Swiss Institute of Bioinformatics, Lausanne, 1015 Switzerland. · 22Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, 21589 Saudi Arabia. ·Commun Biol · Pubmed #30937401.

ABSTRACT: There is evidence that lower height is associated with a higher risk of coronary artery disease (CAD) and increased risk of type 2 diabetes (T2D). It is not clear though whether these associations are causal, direct or mediated by other factors. Here we show that one standard deviation higher genetically determined height (~6.5 cm) is causally associated with a 16% decrease in CAD risk (OR = 0.84, 95% CI 0.80-0.87). This causal association remains after performing sensitivity analyses relaxing pleiotropy assumptions. The causal effect of height on CAD risk is reduced by 1-3% after adjustment for potential mediators (lipids, blood pressure, glycaemic traits, body mass index, socio-economic status). In contrast, our data suggest that lung function (measured by forced expiratory volume [FEV1] and forced vital capacity [FVC]) is a mediator of the effect of height on CAD. We observe no direct causal effect of height on the risk of T2D.

59 Article Does prior coronary angioplasty affect outcomes of surgical coronary revascularization? Insights from the STICH trial. 2019

Nicolau, Jose C / Stevens, Susanna R / Al-Khalidi, Hussein R / Jatene, Fabio B / Furtado, Remo H M / Dallan, Luis A O / Lisboa, Luiz A F / Desvigne-Nickens, Patrice / Haddad, Haissam / Jolicoeur, E Marc / Petrie, Mark C / Doenst, Torsten / Michler, Robert E / Ohman, E Magnus / Maddury, Jyotsna / Ali, Imtiaz / Deja, Marek A / Rouleau, Jean L / Velazquez, Eric J / Hill, James A. ·Instituto do Coracao (InCor), Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil. Electronic address: jose.nicolau@incor.usp.br. · Duke Clinical Research Institute and Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA. · Instituto do Coracao (InCor), Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil. · Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA. · Department of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. · Montreal Heart Institute, Université de Montréal, Quebec, Canada. · BHF Cardiovascular Research Centre, University of Glasgow, Glasgow, United Kingdom. · Department of Cardiothoracic Surgery, University of Jena, Jena, Germany. · Department of Cardiothoracic Surgery, Montefiore Medical Center/Albert Einstein College of Medicine, New York, NY, USA. · Department of Cardiology, Nizams Institute of Medical Sciences, Hyderabad, India. · Libin Cardiovascular Institute of Alberta, University of Calgary, Foothills Medical Centre, Calgary, Alberta, Canada. · Department of Cardiac Surgery, Medical University of Silesia, Katowice, Poland. · Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA. · Department of Medicine, University of Florida, Gainesville, FL, USA. ·Int J Cardiol · Pubmed #30929973.

ABSTRACT: BACKGROUND: The STICH trial showed superiority of coronary artery bypass plus medical treatment (CABG) over medical treatment alone (MED) in patients with left ventricular ejection fraction (LVEF) ≤35%. In previous publications, percutaneous coronary intervention (PCI) prior to CABG was associated with worse prognosis. OBJECTIVES: The main purpose of this study was to analyse if prior PCI influenced outcomes in STICH. METHODS AND RESULTS: Patients in the STICH trial (n = 1212), followed for a median time of 9.8 years, were included in the present analyses. In the total population, 156 had a prior PCI (74 and 82, respectively, in the MED and CABG groups). In those with vs. without prior PCI, the adjusted hazard-ratios (aHRs) were 0.92 (95% CI = 0.74-1.15) for all-cause mortality, 0.85 (95% CI = 0.64-1.11) for CV mortality, and 1.43 (95% CI = 1.15-1.77) for CV hospitalization. In the group randomized to CABG without prior PCI, the aHRs were 0.82 (95% CI = 0.70-0.95) for all-cause mortality, 0.75 (95% CI = 0.62-0.90) for CV mortality and 0.67 (95% CI = 0.56-0.80) for CV hospitalization. In the group randomized to CABG with prior PCI, the aHRs were 0.76 (95% CI = 0.50-1.15) for all-cause mortality, 0.81 (95% CI = 0.49-1.36) for CV mortality and 0.61 (95% CI = 0.41-0.90) for CV hospitalization. There was no evidence of interaction between randomized treatment and prior PCI for any endpoint (all adjusted p > 0.05). CONCLUSION: In the STICH trial, prior PCI did not affect the outcomes of patients whether they were treated medically or surgically, and the superiority of CABG over MED remained unchanged regardless of prior PCI. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov; Identifier: NCT00023595.

60 Article Coronary Calcium Characteristics as Predictors of Major Adverse Cardiac Events in Symptomatic Patients: Insights From the CORE 320 Multinational Study. 2019

Lo-Kioeng-Shioe, Mallory S / Vavere, Andrea L / Arbab-Zadeh, Armin / Schuijf, Joanne D / Rochitte, Carlos E / Chen, Marcus Y / Rief, Matthias / Kofoed, Klaus F / Clouse, Melvin E / Scholte, Arthur J / Miller, Julie M / Betoko, Aisha / Blaha, Michael J / Cox, Christopher / Deckers, Jaap W / Lima, Joao A C. ·1 Department of Cardiology Johns Hopkins Hospital and School of Medicine Baltimore MD. · 2 Department of Cardiology Erasmus Medical Center Erasmus University Rotterdam Rotterdam the Netherlands. · 3 Toshiba Medical Systems Europe BV Zoetermeer the Netherlands. · 4 Department of Cardiology InCor Heart Lung and Blood Institute University of Sao Paulo Medical School Sao Paulo Brazil. · 5 National Heart Lung and Blood Institute National Institutes of Health Bethesda MD. · 6 Department of Radiology Charité Medical School Humboldt Berlin, Germany. · 7 Department of Cardiology Heart Center University of Copenhagen Copenhagen Denmark. · 8 Department of Cardiology Beth Israel Deaconess Medical Center Harvard University Boston MA. · 9 Department of Cardiology Leiden University Medical Center Leiden the Netherlands. · 10 Johns Hopkins Bloomberg School of Public Health Baltimore MD. ·J Am Heart Assoc · Pubmed #30879377.

ABSTRACT: Background The predictive value of coronary artery calcium ( CAC ) has been widely studied; however, little is known about specific characteristics of CAC that are most predictive. We aimed to determine the independent associations of Agatston score, CAC volume, CAC area, CAC mass, and CAC density score with major adverse cardiac events in patients with suspected coronary artery disease. Methods and Results A total of 379 symptomatic participants, aged 45 to 85 years, referred for invasive coronary angiography, who underwent coronary calcium scanning and computed tomography angiography as part of the CORE 320 (Combined Noninvasive Coronary Angiography and Myocardial Perfusion Imaging Using 320 Detector Computed Tomography) study, were included. Agatston score, CAC volume, area, mass, and density were computed on noncontrast images. Stenosis measurements were made on contrast-enhanced images. The primary outcome of 2-year major adverse cardiac events (30 revascularizations [>182 days of index catheterization], 5 myocardial infarctions, 1 cardiac death, 9 hospitalizations, and 1 arrhythmia) occurred in 32 patients (8.4%). Associations were estimated using multivariable proportional means models. Median age was 62 (interquartile range, 56-68) years, 34% were women, and 56% were white. In separate models, the Agatston, volume, and density scores were all significantly associated with higher risk of major adverse cardiac events after adjustment for age, sex, race, and statin use; density was the strongest predictor in all CAC models. CAC density did not provide incremental value over Agatston score after adjustment for diameter stenosis, age, sex, and race. Conclusions In symptomatic patients, CAC density was the strongest independent predictor of major adverse cardiac events among CAC scores, but it did not provide incremental value beyond the Agatston score after adjustment for diameter stenosis.

61 Article Racial Differences in Maintaining Optimal Health Behaviors Into Middle Age. 2019

Booth, John N / Allen, Norrina B / Calhoun, David / Carson, April P / Deng, Luqin / Goff, David C / Redden, David T / Reis, Jared P / Shimbo, Daichi / Shikany, James M / Sidney, Stephen / Spring, Bonnie / Lewis, Cora E / Muntner, Paul. ·Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama. Electronic address: jnbooth@uab.edu. · Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois. · Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, Alabama. · Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama. · Division of Cardiovascular Disease, National Heart Lung and Blood Institute, Bethesda, Maryland. · Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama. · Department of Medicine, Columbia University, New York, New York. · Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, Alabama. · Division of Research, Kaiser Permanente Northern California, Oakland, California. ·Am J Prev Med · Pubmed #30777156.

ABSTRACT: INTRODUCTION: Earlier development of cardiovascular disease risk factors in blacks versus whites may result from differences in maintaining health behaviors. Age-specific racial differences in maintaining health behaviors from ages 18 to 50 years were determined. METHODS: In 1985-1986, the population-based Coronary Artery Risk Development in Young Adults study enrolled 5,115 participants aged 18-30 years. In 2017, a total of 2,485 blacks and 2,407 whites with one or more optimal health behaviors at baseline who attended one or more of seven follow-up exams over 25 years (i.e., through 2010-2011) were analyzed. The primary outcome, maintaining four or more optimal health behaviors, included BMI <25; never smoking; ≥150 minutes/week of moderate to vigorous physical activity; no/moderate alcohol intake (women/men: zero to seven/zero to 14 drinks per week); and Dietary Approaches to Stop Hypertension diet adherence score ≥15 (i.e., baseline highest quartile). Hazard ratios comparing blacks with whites for maintaining optimal health behaviors were calculated among participants with each optimal behavior at baseline. RESULTS: From ages 18 to 50 years, 2.6% of blacks and 9.2% of whites maintained four or more optimal health behaviors (for optimal BMI: 16.0% and 30.1%, smoking status: 74.6% and 78.4%, physical activity: 17.7% and 21.4%, alcohol intake: 68.4% and 64.6%, diet adherence: 3.9% and 10.3%, respectively). The multivariable adjusted hazard ratio comparing blacks with whites was 0.63 (95% CI=0.56, 0.72) for maintaining four or more optimal health behaviors (for optimal BMI: 0.82 [95% CI=0.66, 1.01], smoking status: 0.57 [95% CI=0.52, 0.62], physical activity: 0.83 [95% CI=0.75, 0.91], alcohol intake: 1.19 [95% CI=1.03, 1.37], diet adherence: 0.71 [95% CI=0.61, 0.82]). CONCLUSIONS: Fewer blacks than whites maintained four or more optimal health behaviors until age 50 years, but maintenance was low among both races.

62 Article Automated Pixel-Wise Quantitative Myocardial Perfusion Mapping by CMR to Detect Obstructive Coronary Artery Disease and Coronary Microvascular Dysfunction: Validation Against Invasive Coronary Physiology. 2019

Kotecha, Tushar / Martinez-Naharro, Ana / Boldrini, Michele / Knight, Daniel / Hawkins, Philip / Kalra, Sundeep / Patel, Deven / Coghlan, Gerry / Moon, James / Plein, Sven / Lockie, Tim / Rakhit, Roby / Patel, Niket / Xue, Hui / Kellman, Peter / Fontana, Marianna. ·Institute of Cardiovascular Science, University College London, United Kingdom; Royal Free Hospital, London, United Kingdom. · Royal Free Hospital, London, United Kingdom; Division of Medicine, University College London, United Kingdom. · Division of Medicine, University College London, United Kingdom. · Royal Free Hospital, London, United Kingdom. · Institute of Cardiovascular Science, University College London, United Kingdom; Barts Heart Centre, London, United Kingdom. · Institute of Cardiovascular and Metabolic Medicine, University of Leeds, United Kingdom. · National Heart, Lung, and Blood Institute, National Institute of Health, Bethesda, Maryland. · Royal Free Hospital, London, United Kingdom; Division of Medicine, University College London, United Kingdom. Electronic address: m.fontana@ucl.ac.uk. ·JACC Cardiovasc Imaging · Pubmed #30772231.

ABSTRACT: OBJECTIVES: This study sought to assess the performance of cardiovascular magnetic resonance (CMR) myocardial perfusion mapping against invasive coronary physiology reference standards for detecting coronary artery disease (CAD, defined by fractional flow reserve [FFR] ≤0.80), microvascular dysfunction (MVD) (defined by index of microcirculatory resistance [IMR] ≥25) and the ability to differentiate between the two. BACKGROUND: Differentiation of epicardial (CAD) and MVD in patients with stable angina remains challenging. Automated in-line CMR perfusion mapping enables quantification of myocardial blood flow (MBF) to be performed rapidly within a clinical workflow. METHODS: Fifty patients with stable angina and 15 healthy volunteers underwent adenosine stress CMR at 1.5T with quantification of MBF and myocardial perfusion reserve (MPR). FFR and IMR were measured in 101 coronary arteries during subsequent angiography. RESULTS: Twenty-seven patients had obstructive CAD and 23 had nonobstructed arteries (7 normal IMR, 16 abnormal IMR). FFR positive (epicardial stenosis) areas had significantly lower stress MBF (1.47 ± 0.48 ml/g/min) and MPR (1.75 ± 0.60) than FFR-negative IMR-positive (MVD) areas (stress MBF: 2.10 ± 0.35 ml/g/min; MPR: 2.41 ± 0.79) and normal areas (stress MBF: 2.47 ± 0.50 ml/g/min; MPR: 2.94 ± 0.81). Stress MBF ≤1.94 ml/g/min accurately detected obstructive CAD on a regional basis (area under the curve: 0.90; p < 0.001). In patients without regional perfusion defects, global stress MBF <1.82 ml/g/min accurately discriminated between obstructive 3-vessel disease and MVD (area under the curve: 0.94; p < 0.001). CONCLUSIONS: This novel automated pixel-wise perfusion mapping technique can be used to detect physiologically significant CAD defined by FFR, MVD defined by IMR, and to differentiate MVD from multivessel coronary disease. A CMR-based diagnostic algorithm using perfusion mapping for detection of epicardial disease and MVD warrants further clinical validation.

63 Article Impact of Abnormal Coronary Reactivity on Long-Term Clinical Outcomes in Women. 2019

AlBadri, Ahmed / Bairey Merz, C Noel / Johnson, B Delia / Wei, Janet / Mehta, Puja K / Cook-Wiens, Galen / Reis, Steven E / Kelsey, Sheryl F / Bittner, Vera / Sopko, George / Shaw, Leslee J / Pepine, Carl J / Ahmed, Bina. ·Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia. · Barbra Streisand Women's Heart Center, Cedars-Sinai Heart Institute, Los Angeles, California. Electronic address: Noel.BaireyMerz@cshs.org. · Cardiovascular Institute, University of Pittsburgh, Pittsburgh, Pennsylvania. · Barbra Streisand Women's Heart Center, Cedars-Sinai Heart Institute, Los Angeles, California. · Biostatistics and Bioinformatics Research Center, Cedars-Sinai Medical Center, Los Angeles, California. · Division of Cardiovascular Disease, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama. · Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland. · Division of Cardiovascular Medicine, University of Florida College of Medicine, Gainesville, Florida. · Division of Cardiovascular Disease, Department of Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire. ·J Am Coll Cardiol · Pubmed #30765035.

ABSTRACT: BACKGROUND: Currently as many as one-half of women with suspected myocardial ischemia have no obstructive coronary artery disease (CAD), and abnormal coronary reactivity (CR) is commonly found. OBJECTIVES: The authors prospectively investigated CR and longer-term adverse cardiovascular outcomes in women with and with no obstructive CAD in the National Heart, Lung, and Blood Institute-sponsored WISE (Women's Ischemia Syndrome Evaluation) study. METHODS: Women (n = 224) with signs and symptoms of ischemia underwent CR testing. Coronary flow reserve and coronary blood flow were obtained to test microvascular function, whereas epicardial CR was tested by coronary dilation response to intracoronary (IC) acetylcholine and IC nitroglycerin. All-cause mortality, major adverse cardiovascular events (MACE) (cardiovascular death, myocardial infarction, stroke, and heart failure), and angina hospitalizations served as clinical outcomes over a median follow-up of 9.7 years. RESULTS: The authors identified 129 events during the follow-up period. Low coronary flow reserve was a predictor of increased MACE rate (hazard ratio [HR]: 1.06; 95% confidence interval [CI]: 1.01 to 1.12; p = 0.021), whereas low coronary blood flow was associated with increased risk of mortality (HR: 1.12; 95% CI: 1.01 to 1.24; p = 0.038) and MACE (HR: 1.11; 95% CI: 1.03 to 1.20; p = 0.006) after adjusting for cardiovascular risk factors. In addition, a decrease in cross-sectional area in response to IC acetylcholine was associated with higher hazard of angina hospitalization (HR: 1.05; 95% CI: 1.02 to 1.07; p < 0.0001). There was no association between epicardial IC-nitroglycerin dilation and outcomes. CONCLUSIONS: On longer-term follow-up, impaired microvascular function predicts adverse cardiovascular outcomes in women with signs and symptoms of ischemia. Evaluation of CR abnormality can identify those at higher risk of adverse outcomes in the absence of significant CAD. (Women's Ischemia Syndrome Evaluation [WISE]; NCT00000554).

64 Article Coronary artery plaque characteristics and treatment with biologic therapy in severe psoriasis: results from a prospective observational study. 2019

Elnabawi, Youssef A / Dey, Amit K / Goyal, Aditya / Groenendyk, Jacob W / Chung, Jonathan H / Belur, Agastya D / Rodante, Justin / Harrington, Charlotte L / Teague, Heather L / Baumer, Yvonne / Keel, Andrew / Playford, Martin P / Sandfort, Veit / Chen, Marcus Y / Lockshin, Benjamin / Gelfand, Joel M / Bluemke, David A / Mehta, Nehal N. ·Section of Inflammation and Cardiometabolic Disease, National Heart, Lung, and Blood Institute; National Institutes of Health, Bethesda, MD, USA. · DermAssociates, Silver Spring, MD, USA. · Department of Dermatology, University of Pennsylvania, Philadelphia, PA, USA. · Department of Radiology, University of Wisconsin, Madison, WI, USA. ·Cardiovasc Res · Pubmed #30721933.

ABSTRACT: AIMS: The use of biologic therapy has increased over the past decade well beyond primary autoimmune diseases. Indeed, a recent trial using an anti-IL-1beta antibody reduced second myocardial infarction (MI) in those who have had MI. Psoriasis is a chronic inflammatory disease often treated with biologics when severe, is associated with increased risk of MI, in part driven by high-risk coronary plaque phenotypes by coronary computed tomography angiography (CCTA). We hypothesized that we would observe a reduction in inflammatory-driven phenotypes of coronary plaque, including non-calcified coronary plaque burden and lipid-rich necrotic core in those treated with biologic therapy after one-year compared with non-biologic therapy. METHODS AND RESULTS: In a prospective, observational study, 290 participants were recruited from 1 January 2013 through 31 October 2018 with 215 completing one-year follow-up. Of the 238, 121 consecutive participants who were biologic treatment naïve at baseline were included. A blinded reader (blinded to patient demographics, visit and treatment) quantified total coronary plaque burden and plaque subcomponents (calcified and non-calcified) in the three main coronary vessels >2 mm using dedicated software (QAngio, Medis, Netherlands). Psoriasis patients were middle-aged [mean (standard deviation) age, 50.5 (12.1) years], mostly male (n = 70, 58%) with low cardiovascular risk by Framingham score [median (interquartile range, IQR), 3 (1-6)] and had moderate to severe skin disease at baseline [median (IQR) Psoriasis Area Severity Index, PASI, 8.6 (5.3-14.0)]. Biologic therapy was associated with a 6% reduction in non-calcified plaque burden (P = 0.005) reduction in necrotic core (P = 0.03), with no effect on fibrous burden (P = 0.71). Decrease in non-calcified plaque burden in the biologic treated group was significant compared with slow plaque progression in non-biologic treated (Δ, -0.07 mm2 vs. 0.06 mm2; P = 0.02) and associated with biologic treatment beyond adjustment for traditional cardiovascular risk factors (β = 0.20, P = 0.02). CONCLUSION: In this observational study, we demonstrate that biologic therapy in severe psoriasis was associated with favourable modulation of coronary plaque indices by CCTA. These findings highlight the importance of systemic inflammation in coronary artery disease and support the conduct of larger, randomized trials.

65 Article Burden of medical co-morbidities and benefit from surgical revascularization in patients with ischaemic cardiomyopathy. 2019

Ambrosy, Andrew P / Stevens, Susanna R / Al-Khalidi, Hussein R / Rouleau, Jean L / Bouabdallaoui, Nadia / Carson, Peter E / Adlbrecht, Christopher / Cleland, John G F / Dabrowski, Rafal / Golba, Krzysztof S / Pina, Ileana L / Sueta, Carla A / Roy, Ambuj / Sopko, George / Bonow, Robert O / Velazquez, Eric J / Anonymous451102. ·Division of Cardiology, The Permanente Medical Group, San Francisco, CA, USA. · Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA. · Department of Biostatistics and Bioinformatics, Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA. · Research Center, Montreal Heart Institute, Montreal, Quebec, Canada. · Department of Cardiology, Washington Veterans Affairs Medical Center, Washington, DC, USA. · 4th Medical Department, Karl Landsteiner Institute for Cardiovascular and Critical Care Research, Hietzing Hospital, Vienna, Austria. · Robertson Centre for Biostatistics and Clinical Trials, University of Glasgow, Glasgow, Scotland, UK. · 2nd Department of Coronary Artery Disease, Institute of Cardiology, Warsaw, Poland. · Department of Electrocardiology and Heart Failure, School of Health Sciences, Medical University of Silesia, Katowice, Poland. · Albert Einstein College of Medicine, Montefiore Medical Center, New York, NY, USA. · Division of Cardiology, University of North Carolina School of Medicine, Chapel Hill, NC, USA. · Department of Cardiology, All India Institute of Medical Sciences, New Delhi, India. · Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA. · Northwestern University Feinberg School of Medicine, Chicago, IL, USA. · Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA. ·Eur J Heart Fail · Pubmed #30698316.

ABSTRACT: AIMS: The landmark STICH trial found that surgical revascularization compared to medical therapy alone improved survival in patients with heart failure (HF) of ischaemic aetiology and an ejection fraction (EF) ≤ 35%. However, the interaction between the burden of medical co-morbidities and the benefit from surgical revascularization has not been previously described in patients with ischaemic cardiomyopathy. METHODS AND RESULTS: The STICH trial (ClinicalTrials.gov Identifier: NCT00023595) enrolled patients ≥ 18 years of age with coronary artery disease amenable to coronary artery bypass grafting (CABG) and an EF ≤ 35%. Eligible participants were randomly assigned 1:1 to receive medical therapy (MED) (n = 602) or MED/CABG (n = 610). A modified Charlson co-morbidity index (CCI) based on the availability of data and study definitions was calculated by summing the weighted points for all co-morbid conditions. Patients were divided into mild/moderate (CCI 1-4) and severe (CCI ≥ 5) co-morbidity. Cox proportional hazards models were used to evaluate the association between CCI and outcomes and the interaction between severity of co-morbidity and treatment effect. The study population included 349 patients (29%) with a mild/moderate CCI score and 863 patients (71%) with a severe CCI score. Patients with a severe CCI score had greater functional limitations based on 6-min walk test and impairments in health-related quality of life as assessed by the Kansas City Cardiomyopathy Questionnaire. A total of 161 patients (Kaplan-Meier rate = 50%) with a mild/moderate CCI score and 579 patients (Kaplan-Meier rate = 69%) with a severe CCI score died over a median follow-up of 9.8 years. After adjusting for baseline confounders, patients with a severe CCI score were at higher risk for all-cause mortality (hazard ratio 1.44, 95% confidence interval 1.19-1.74; P < 0.001). There was no interaction between CCI score and treatment effect on survival (P = 0.756). CONCLUSIONS: More than 70% of patients had a severe burden of medical co-morbidities at baseline, which was independently associated with increased risk of death. There was not a differential benefit of surgical revascularization with respect to survival based on severity of co-morbidity.

66 Article Reduced radiation dose with model based iterative reconstruction coronary artery calcium scoring. 2019

Choi, Andrew D / Leifer, Eric S / Yu, Jeannie H / Datta, Tanuka / Bronson, Kathie C / Rollison, Shirley F / Schuzer, John L / Steveson, Chloe / Shanbhag, Sujata M / Chen, Marcus Y. ·Advanced Cardiovascular Imaging Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA; Division of Cardiology, and Department of Radiology, The George Washington University School of Medicine, Washington, DC, USA. · The Office of Biostatistics Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA. · Advanced Cardiovascular Imaging Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA. · Division of Cardiology, and Department of Radiology, The George Washington University School of Medicine, Washington, DC, USA. · Canon Medical Systems Corporation, Otawara, Japan. · Advanced Cardiovascular Imaging Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA. Electronic address: marcus.chen@nih.gov. ·Eur J Radiol · Pubmed #30691659.

ABSTRACT: Assessing coronary artery calcium (CAC) is a valuable tool for individualizing cardiac risk assessment. In CAC scanning, this technical report assesses the use of a true model-based iterative reconstruction algorithm using forward projected model-based iterative reconstruction ("FIRST") and assess whether FIRST allows for reduced radiation dose CAC scanning on 320-detector row computed tomography (320-CT). Here, 100 consecutive patients prospectively underwent reduced and standard dose scans. For the patients (59 ± 9 years, 61% male) stratified by Agatston categories 0, 1-10, 11-100, 101-400,> 400, agreement between reduced dose with FIRST versus standard dose with FBP was excellent at 81% (95% CI: 73-88%) with kappa 0.74 (95% CI: 0.64-0.85). Median radiation exposure was 75% lower for reduced (0.35 mSv) versus standard dose (1.37 mSv) scans. In conclusion, agreement was excellent for reduced dose with FIRST and standard dose with FBP in 320-detector row CT CAC imaging in well-established categories of cardiovascular risk. These methods make it possible to reduce radiation exposure by 75%.

67 Article Quantitative myocardial perfusion in coronary artery disease: A perfusion mapping study. 2019

Knott, Kristopher D / Camaioni, Claudia / Ramasamy, Anantharaman / Augusto, Joao A / Bhuva, Anish N / Xue, Hui / Manisty, Charlotte / Hughes, Rebecca K / Brown, Louise A E / Amersey, Rajiv / Bourantas, Christos / Kellman, Peter / Plein, Sven / Moon, James C. ·University College London, Institute of Cardiovascular Science, London, UK. · Barts Heart Centre, St Bartholomew's Hospital, London, UK. · National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, Maryland, USA. · Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK. ·J Magn Reson Imaging · Pubmed #30684288.

ABSTRACT: BACKGROUND: Cardiac MR stress perfusion remains a qualitative technique in clinical practice due to technical and postprocessing challenges. However, automated inline perfusion mapping now permits myocardial blood flow (MBF, ml/g/min) quantification on-the-fly without user input. PURPOSE: To investigate the diagnostic performance of this novel technique in detecting occlusive coronary artery disease (CAD) in patients scheduled to undergo coronary angiography. STUDY TYPE: Prospective, observational. SUBJECTS: Fifty patients with suspected CAD and 24 healthy volunteers. FIELD STRENGTH: 1.5T. SEQUENCE: "Dual" sequence multislice 2D saturation recovery. ASSESSMENT: All patients underwent cardiac MR with perfusion mapping and invasive coronary angiography; the healthy volunteers had MR with perfusion mapping alone. STATISTICAL TESTS: Comparison between numerical variables was performed using an independent t-test. Receiver operator characteristic (ROC) curves were generated for transmyocardial, endocardial stress MBF, and myocardial perfusion reserve (MPR, the stress:rest MBF ratio) to diagnose severe (>70%) stenoses as measured by 3D quantitative coronary angiography (QCA). ROC curves were compared by the method of DeLong et al. RESULTS: Compared with volunteers, patients had lower stress MBF and MPR even in vessels with <50% stenosis (2.00 vs. 3.08 ml/g/min, respectively). As stenosis severity increased (<50%, 50-70%, >70%), MBF and MPR decreased. To diagnose occlusive (>70%) CAD, endocardial and transmyocardial stress MBF were superior to MPR (area under the curve 0.92 [95% CI 0.86-0.97] vs. 0.90 [95% CI 0.84-0.95] and 0.80 [95% CI 0.72-0.87], respectively). An endocardial threshold of 1.31 ml/g/min provided a per-coronary artery sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 90%, 82%, 50%, and 98%, with a per-patient diagnostic performance of 100%, 66%, 57%, and 100%, respectively. DATA CONCLUSION: Perfusion mapping can diagnose occlusive CAD with high accuracy and, in particular, high sensitivity and NPV make it a potential "rule-out" test. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:756-762.

68 Article Coronary artery calcium scoring with photon-counting CT: first in vivo human experience. 2019

Symons, Rolf / Sandfort, Veit / Mallek, Marissa / Ulzheimer, Stefan / Pourmorteza, Amir. ·Radiology and Imaging Sciences - National Institutes of Health Clinical Center, Bethesda, MD, USA. · Department of Imaging & Pathology, University Hospitals Leuven, Leuven, Belgium. · Siemens Healthcare GmbH, Forchheim, Germany. · Radiology and Imaging Sciences - National Institutes of Health Clinical Center, Bethesda, MD, USA. amir.pourmorteza@emory.edu. · Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA. amir.pourmorteza@emory.edu. · Department of Radiology and Imaging Sciences, Winship Cancer Institute of Emory University, 1701 Uppergate Drive, Suite 5018A, Atlanta, GA, 30322, USA. amir.pourmorteza@emory.edu. ·Int J Cardiovasc Imaging · Pubmed #30635819.

ABSTRACT: To evaluate the performance of photon-counting detector (PCD) computed tomography (CT) for coronary artery calcium (CAC) score imaging at standard and reduced radiation doses compared to conventional energy-integrating detector (EID) CT. A dedicated cardiac CT phantom, ten ex vivo human hearts, and ten asymptomatic volunteers underwent matched EID and PCD CT scans at different dose settings without ECG gating. CAC score, contrast, and contrast-to-noise ratio (CNR) were calculated in the cardiac CT phantom. CAC score accuracy and reproducibility was assessed in the ex vivo hearts. Standard radiation dose (120 kVp, reference mAs = 80) in vivo CAC scans were compared against dose-reduced CAC scans (75% dose reduction; reference mAs = 20) for image quality and CAC score reproducibility. Interstudy agreement was assessed by using intraclass correlation (ICC), linear regression, and Bland-Altman analysis with 95% confidence interval limits of agreement (LOA). Calcium-soft tissue contrast and CNR were significantly higher for the PCD CAC scans in the cardiac CT phantom (all P < 0.01). Ex vivo hearts: CAC score reproducibility was significantly higher for the PCD scans at the lowest dose setting (50 mAs) (P = 0.002); score accuracy was similar for both detector systems at all dose settings. In vivo scans: the agreement between standard dose and low dose CAC score was significantly better for the PCD than for the EID with narrower LOA in Bland-Altman analysis, linear regression slopes closer to 1 (0.96 vs. 0.84), and higher ICC values (0.98 vs. 0.93, respectively). Phantom and in vivo human studies showed PCD may significantly improve CAC score image quality and/or reduce CAC score radiation dose while maintaining diagnostic image quality.

69 Article The association of obesity and coronary artery disease genes with response to SSRIs treatment in major depression. 2019

Amare, Azmeraw T / Schubert, Klaus Oliver / Tekola-Ayele, Fasil / Hsu, Yi-Hsiang / Sangkuhl, Katrin / Jenkins, Gregory / Whaley, Ryan M / Barman, Poulami / Batzler, Anthony / Altman, Russ B / Arolt, Volker / Brockmöller, Jürgen / Chen, Chia-Hui / Domschke, Katharina / Hall-Flavin, Daniel K / Hong, Chen-Jee / Illi, Ari / Ji, Yuan / Kampman, Olli / Kinoshita, Toshihiko / Leinonen, Esa / Liou, Ying-Jay / Mushiroda, Taisei / Nonen, Shinpei / Skime, Michelle K / Wang, Liewei / Kato, Masaki / Liu, Yu-Li / Praphanphoj, Verayuth / Stingl, Julia C / Bobo, William V / Tsai, Shih-Jen / Kubo, Michiaki / Klein, Teri E / Weinshilboum, Richard M / Biernacka, Joanna M / Baune, Bernhard T. ·Discipline of Psychiatry, School of Medicine, University of Adelaide, North Terrace, Adelaide, SA, 5005, Australia. · South Australian Academic Health Science and Translation Centre, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, SA, Australia. · Northern Adelaide Local Health Network, Mental Health Services, Adelaide, SA, Australia. · Epidemiology Branch, Division of Intramural Population Health Research, National Institute of Child Health and Human Development, Institute, National Institutes of Health, Bethesda, MD, USA. · HSL Institute for Aging Research, Harvard Medical School, Boston, MA, USA. · Program for Quantitative Genomics, Harvard School of Public Health, Boston, MA, USA. · Biomedical Data Science, Stanford University, Stanford, CA, USA. · Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA. · Department of Bioengineering, Stanford University, Stanford, CA, USA. · Department of Psychiatry and Psychotherapy, University of Muenster, Muenster, Germany. · Department of Clinical Pharmacology, University Göttingen, Göttingen, Germany. · Department of Psychiatry, Taipei Medical University-Shuangho Hospital, New Taipei City, Taiwan. · Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Freiburg, Freiburg, Germany. · Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA. · Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan. · Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan. · Department of Psychiatry, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland. · Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA. · Department of Psychiatry, Seinäjoki Hospital District, Seinäjoki, Finland. · Department of Neuropsychiatry, Kansai Medical University, Osaka, Japan. · Department of Psychiatry, Tampere University Hospital, Tampere, Finland. · RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan. · Department of Pharmacy, Hyogo University of Health Sciences, Kobe, Hyogo, Japan. · Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan. · Center for Medical Genetics Research, Department of Mental Health, Ministry of Public Health Bangkok, Rajanukul Institute, Bangkok, Thailand. · Research Division Federal Institute for Drugs and Medical Devices, Bonn, Germany. · Discipline of Psychiatry, School of Medicine, University of Adelaide, North Terrace, Adelaide, SA, 5005, Australia. bernhard.Baune@adelaide.edu.au. ·J Neural Transm (Vienna) · Pubmed #30610379.

ABSTRACT: Selective serotonin reuptake inhibitors (SSRIs) are first-line antidepressants for the treatment of major depressive disorder (MDD). However, treatment response during an initial therapeutic trial is often poor and is difficult to predict. Heterogeneity of response to SSRIs in depressed patients is partly driven by co-occurring somatic disorders such as coronary artery disease (CAD) and obesity. CAD and obesity may also be associated with metabolic side effects of SSRIs. In this study, we assessed the association of CAD and obesity with treatment response to SSRIs in patients with MDD using a polygenic score (PGS) approach. Additionally, we performed cross-trait meta-analyses to pinpoint genetic variants underpinnings the relationship of CAD and obesity with SSRIs treatment response. First, PGSs were calculated at different p value thresholds (P

70 Article Low-Dose Methotrexate for the Prevention of Atherosclerotic Events. 2019

Ridker, Paul M / Everett, Brendan M / Pradhan, Aruna / MacFadyen, Jean G / Solomon, Daniel H / Zaharris, Elaine / Mam, Virak / Hasan, Ahmed / Rosenberg, Yves / Iturriaga, Erin / Gupta, Milan / Tsigoulis, Michelle / Verma, Subodh / Clearfield, Michael / Libby, Peter / Goldhaber, Samuel Z / Seagle, Roger / Ofori, Cyril / Saklayen, Mohammad / Butman, Samuel / Singh, Narendra / Le May, Michel / Bertrand, Olivier / Johnston, James / Paynter, Nina P / Glynn, Robert J / Anonymous2700968. ·From the Center for Cardiovascular Disease Prevention, Division of Preventive Medicine (P.M.R., B.M.E., A.P., J.G.M., E.Z., V.M., N.P.P., R.J.G.), and the Divisions of Cardiovascular Medicine (P.M.R., B.M.E., P.L., S.Z.G.) and Rheumatology (D.H.S.), Brigham and Women's Hospital, Boston · the National Heart, Lung, and Blood Institute, Bethesda, MD (A.H., Y.R., E.I.) · McMaster University, Hamilton (M.G.), the Canadian Collaborative Research Network, Brampton (M.T.), St. Michael's Hospital, Toronto (S.V.), the University of Ottawa Heart Institute, Ottawa (M.L.M.), and KMH Cardiology, Diagnostic and Research Centres, Mississauga (J.J.), ON, and Laval University, Quebec City, QB (O.B.) - all in Canada · Touro University, Vallejo, CA (M.C.) · Cardiology Associates Carolina, Morganton, NC (R.S.) · Wooster Community Hospital, Wooster (C.O.), and Dayton Veteran Affairs Medical Center, Dayton (M.S.) - both in Ohio · Verde Valley Medical Center, Cottonwood, AZ (S.B.) · and Atlanta Heart Specialists, Atlanta (N.S.). ·N Engl J Med · Pubmed #30415610.

ABSTRACT: BACKGROUND: Inflammation is causally related to atherothrombosis. Treatment with canakinumab, a monoclonal antibody that inhibits inflammation by neutralizing interleukin-1β, resulted in a lower rate of cardiovascular events than placebo in a previous randomized trial. We sought to determine whether an alternative approach to inflammation inhibition with low-dose methotrexate might provide similar benefit. METHODS: We conducted a randomized, double-blind trial of low-dose methotrexate (at a target dose of 15 to 20 mg weekly) or matching placebo in 4786 patients with previous myocardial infarction or multivessel coronary disease who additionally had either type 2 diabetes or the metabolic syndrome. All participants received 1 mg of folate daily. The primary end point at the onset of the trial was a composite of nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. Near the conclusion of the trial, but before unblinding, hospitalization for unstable angina that led to urgent revascularization was added to the primary end point. RESULTS: The trial was stopped after a median follow-up of 2.3 years. Methotrexate did not result in lower interleukin-1β, interleukin-6, or C-reactive protein levels than placebo. The final primary end point occurred in 201 patients in the methotrexate group and in 207 in the placebo group (incidence rate, 4.13 vs. 4.31 per 100 person-years; hazard ratio, 0.96; 95% confidence interval [CI], 0.79 to 1.16). The original primary end point occurred in 170 patients in the methotrexate group and in 167 in the placebo group (incidence rate, 3.46 vs. 3.43 per 100 person-years; hazard ratio, 1.01; 95% CI, 0.82 to 1.25). Methotrexate was associated with elevations in liver-enzyme levels, reductions in leukocyte counts and hematocrit levels, and a higher incidence of non-basal-cell skin cancers than placebo. CONCLUSIONS: Among patients with stable atherosclerosis, low-dose methotrexate did not reduce levels of interleukin-1β, interleukin-6, or C-reactive protein and did not result in fewer cardiovascular events than placebo. (Funded by the National Heart, Lung, and Blood Institute; CIRT ClinicalTrials.gov number, NCT01594333.).

71 Article Coronary Artery Calcium Scores and Atherosclerotic Cardiovascular Disease Risk Stratification in Smokers. 2019

Leigh, Adam / McEvoy, John W / Garg, Parveen / Carr, J Jeffrey / Sandfort, Veit / Oelsner, Elizabeth C / Budoff, Matthew / Herrington, David / Yeboah, Joseph. ·Heart and Vascular Center of Excellence, Wake Forest University School of Medicine, Winston Salem, North Carolina. · Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland. · Division of Cardiovascular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California. · Departments of Cardiology and Radiology, Vanderbilt University School of Medicine, Nashville, Tennessee. · Clinical Center, National Institutes of Health, Bethesda, Maryland. · Departments of Medicine and Epidemiology, Columbia University, New York, New York. · Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles, Torrance California. · Heart and Vascular Center of Excellence, Wake Forest University School of Medicine, Winston Salem, North Carolina. Electronic address: jyeboah@wakehealth.edu. ·JACC Cardiovasc Imaging · Pubmed #29454784.

ABSTRACT: OBJECTIVES: This study assessed the utility of the pooled cohort equation (PCE) and/or coronary artery calcium (CAC) for atherosclerotic cardiovascular disease (ASCVD) risk assessment in smokers, especially those who were lung cancer screening eligible (LCSE). BACKGROUND: The U.S. Preventive Services Task Force recommended and the Centers for Medicare & Medicaid Services currently pays for annual screening for lung cancer with low-dose computed tomography scans in a specified group of cigarette smokers. CAC can be obtained from these low-dose scans. The incremental utility of CAC for ASCVD risk stratification remains unclear in this high-risk group. METHODS: Of 6,814 MESA (Multi-Ethnic Study of Atherosclerosis) participants, 3,356 (49.2% of total cohort) were smokers (2,476 former and 880 current), and 14.3% were LCSE. Kaplan-Meier, Cox proportional hazards, area under the curve, and net reclassification improvement (NRI) analyses were used to assess the association between PCE and/or CAC and incident ASCVD. Incident ASCVD was defined as coronary death, nonfatal myocardial infarction, or fatal or nonfatal stroke. RESULTS: Smokers had a mean age of 62.1 years, 43.5% were female, and all had a mean of 23.0 pack-years of smoking. The LCSE sample had a mean age of 65.3 years, 39.1% were female, and all had a mean of 56.7 pack-years of smoking. After a mean of 11.1 years of follow-up 13.4% of all smokers and 20.8% of LCSE smokers had ASCVD events; 6.7% of all smokers and 14.2% of LCSE smokers with CAC = 0 had an ASCVD event during the follow-up. One SD increase in the PCE 10-year risk was associated with a 68% increase risk for ASCVD events in all smokers (hazard ratio: 1.68; 95% confidence interval: 1.57 to 1.80) and a 22% increase in risk for ASCVD events in the LCSE smokers (hazard ratio: 1.22; 95% confidence interval: 1.00 to 1.47). CAC was associated with increased ASCVD risk in all smokers and in LCSE smokers in all the Cox models. The C-statistic of the PCE for ASCVD was higher in all smokers compared with LCSE smokers (0.693 vs. 0.545). CAC significantly improved the C-statistics of the PCE in all smokers but not in LCSE smokers. The event and nonevent net reclassification improvements for all smokers and LCSE smokers were 0.018 and -0.126 versus 0.16 and -0.196, respectively. CONCLUSIONS: In this well-characterized, multiethnic U.S. cohort, CAC was predictive of ASCVD in all smokers and in LCSE smokers but modestly improved discrimination over and beyond the PCE. However, 6.7% of all smokers and 14.2% of LCSE smokers with CAC = 0 had an ASCVD event during follow-up.

72 Article Variability in Ejection Fraction Measured By Echocardiography, Gated Single-Photon Emission Computed Tomography, and Cardiac Magnetic Resonance in Patients With Coronary Artery Disease and Left Ventricular Dysfunction. 2018

Pellikka, Patricia A / She, Lilin / Holly, Thomas A / Lin, Grace / Varadarajan, Padmini / Pai, Ramdas G / Bonow, Robert O / Pohost, Gerald M / Panza, Julio A / Berman, Daniel S / Prior, David L / Asch, Federico M / Borges-Neto, Salvador / Grayburn, Paul / Al-Khalidi, Hussein R / Miszalski-Jamka, Karol / Desvigne-Nickens, Patrice / Lee, Kerry L / Velazquez, Eric J / Oh, Jae K. ·Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota. · Duke Clinical Research Institute, Durham, North Carolina. · Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois. · Department of Medicine, Loma Linda University, Loma Linda, California. · Department of Cardiology, Loma Linda University, Loma Linda, California. · Department of Medicine, Riverside School of Medicine, University of California, Riverside. · Department of Cardiology, Riverside School of Medicine, University of California, Riverside. · Westchester Medical Center, New York Medical College, Valhalla. · Cedars-Sinai Medical Center, Los Angeles, California. · Department of Cardiology, St Vincent's Hospital, University of Melbourne, Melbourne, Australia. · Department of Medicine, St Vincent's Hospital, University of Melbourne, Melbourne, Australia. · Section of Interventional Cardiology, MedStar Washington Hospital Center, Washington, DC. · Division of Nuclear Medicine, Department of Radiology, Duke University School of Medicine, Durham, North Carolina. · Division of Cardiology, Department of Medicine, Duke Clinical Research Institute, Durham, North Carolina. · Cardiology Section, Department of Internal Medicine, Baylor University Medical Center, Dallas, Texas. · Department of Biostatistics and Bioinformatics, Duke Clinical Research Institute, Durham, North Carolina. · Division of Magnetic Resonance Imaging, Silesian Center for Heart Diseases, Zabrze, Poland. · Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland. ·JAMA Netw Open · Pubmed #30646130.

ABSTRACT: Importance: Clinical decisions are frequently based on measurement of left ventricular ejection fraction (LVEF). Limited information exists regarding inconsistencies in LVEF measurements when determined by various imaging modalities and the potential impact of such variability. Objective: To determine the intermodality variability of LVEF measured by echocardiography, gated single-photon emission computed tomography (SPECT), and cardiovascular magnetic resonance (CMR) in patients with left ventricular dysfunction. Design, Setting, and Participants: International multicenter diagnostic study with LVEF imaging performed at 127 clinical sites in 26 countries from July 24, 2002, to May 5, 2007, and measured by core laboratories. Secondary study of clinical diagnostic measurements of LVEF in the Surgical Treatment for Ischemic Heart Failure (STICH), a randomized trial to identify the optimal treatment strategy for patients with LVEF of 35% or less and coronary artery disease. Data analysis was conducted from March 19, 2016, to May 29, 2018. Main Outcomes and Measures: At baseline, most patients had an echocardiogram and subsets of patients underwent SPECT and/or CMR. Left ventricular ejection fraction was measured by a core laboratory for each modality independent of the results of other modalities, and measurements were compared among imaging methods using correlation, Bland-Altman plots, and coverage probability methods. Association of LVEF by each method and death was assessed. Results: A total of 2032 patients (mean [SD] age, 60.9 [9.6] years; 1759 [86.6%] male) with baseline LVEF data were included. Correlation of LVEF between modalities was r = 0.601 (for biplane echocardiography and SPECT [n = 385]), r = 0.493 (for biplane echocardiography and CMR [n = 204]), and r = 0.660 (for CMR and SPECT [n = 134]). Bland-Altman plots showed only moderate agreement in LVEF measurements from all 3 core laboratories with no substantial overestimation or underestimation of LVEF by any modality. The percentage of observations that fell within a range of 5% ranged from 43% to 54% between different imaging modalities. Conclusions and Relevance: In this international multicenter study of patients with coronary artery disease and reduced LVEF, there was substantial variation between modalities in LVEF determination by core laboratories. This variability should be considered in clinical management and trial design. Trial Registration: Clinicaltrials.gov Identifier: NCT00023595.

73 Article Association Between Oxidation-Modified Lipoproteins and Coronary Plaque in Psoriasis. 2018

Sorokin, Alexander V / Kotani, Kazuhiko / Elnabawi, Youssef A / Dey, Amit K / Sajja, Aparna P / Yamada, Shingo / Ueda, Masashi / Harrington, Charlotte L / Baumer, Yvonne / Rodante, Justin A / Gelfand, Joel M / Chen, Marcus Y / Joshi, Aditya A / Playford, Martin P / Remaley, Alan T / Mehta, Nehal N. ·From the Section of Inflammation and Cardiometabolic Diseases, Cardiovascular Branch, (A.V.S., Y.A.E., A.K.D., A.P.S., C.L.H., Y.B., J.A.R., M.Y.C., A.A.J., M.P.P., N.N.M.), National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD. · Department of Clinical Laboratory Medicine, Jichi Medical University, Shimotsuke-City, Tochigi, Japan (K.K.). · Shino-Test Corporation, Sagamihara, Japan (S.Y.). · Hokenkagaku-West, Co, Ltd, Kyoto-City, Japan (M.U.). · Department of Dermatology, Perelman School of Medicine (J.M.G.). · Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia (J.M.G.). · Section of Lipoprotein Metabolism, Translational Vascular Medicine Branch (A.T.R.), National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD. ·Circ Res · Pubmed #30571459.

ABSTRACT: RATIONALE: Psoriasis is a systemic inflammatory skin disease associated with cardiovascular disease and lipid dysfunction. However, traditional lipid parameters have limited prognostic value, whereas assessing oxidation-modified lipids in this inflammatory driven condition may capture additional risk. Recently, a study showed that psoriasis was associated with increased lipid-rich coronary plaques; therefore, investigating potential relationships with oxidation-modified lipids may speed understanding of increased cardiovascular disease in psoriasis. OBJECTIVE: To understand whether oxidation-modified lipids associate with traditional lipid phenotypes, cardiometabolic disease biomarkers, and total coronary plaque, with focus on noncalcified burden (NCB) by coronary computed tomographic angiography in psoriasis. METHODS AND RESULTS: Psoriasis subjects and controls (n=252) had profiling for oxidation-modified LDL (low-density lipoprotein), HDL (high-density lipoprotein), Lp(a) (lipoprotein[a]), cholesterol efflux capacity, lipoprotein particle size and number by NMR spectroscopy, and PON-1 (paraoxonase-1) activity. Blinded coronary computed tomographic angiography coronary artery disease characterization included total burden, NCB, and dense-calcified burden. Compared with healthy volunteers, psoriasis subjects were older (mean age, 50.1), had increased body mass index, and homeostatic model assessment of insulin resistance. Psoriasis subjects had increase in oxidized Lp(a), Lp(a), and oxidized HDL (oxHDL; P <0.05 for all) with significant association of oxidized LDL (β=0.10; P=0.020) and oxHDL (β=-0.11; P=0.007) with NCB. Moreover, psoriasis subjects expressed significantly higher PON-1 (kU/µL) activity compared with healthy volunteers (8.55±3.21 versus 6.24±3.82; P=0.01). Finally, psoriasis treatment was associated with a reduction in oxHDL (U/mL; 203.79±88.40 versus 116.36±85.03; P<0.001) and with a concomitant decrease in NCB at 1 year (1.04±0.44 versus 0.95±0.32; P=0.03). CONCLUSIONS: Traditional lipids did not capture risk of lipid-rich plaque as assessed by NCB, whereas assaying oxidation-modification of lipids revealed significant association with oxidized LDL and oxHDL. The PON-1 activity was increased in psoriasis suggesting possible compensatory antioxidative effect. Psoriasis treatment was associated with a reduction in oxHDL. These findings support performance of larger studies to understand oxidation-modified lipids in inflammatory states.

74 Article Society of Thoracic Surgeons Risk Score and EuroSCORE-2 Appropriately Assess 30-Day Postoperative Mortality in the STICH Trial and a Contemporary Cohort of Patients With Left Ventricular Dysfunction Undergoing Surgical Revascularization. 2018

Bouabdallaoui, Nadia / Stevens, Susanna R / Doenst, Torsten / Petrie, Mark C / Al-Attar, Nawwar / Ali, Imtiaz S / Ambrosy, Andrew P / Barton, Anna K / Cartier, Raymond / Cherniavsky, Alexander / Demondion, Pierre / Desvigne-Nickens, Patrice / Favaloro, Robert R / Gradinac, Sinisa / Heinisch, Petra / Jain, Anil / Jasinski, Marek / Jouan, Jerome / Kalil, Renato A K / Menicanti, Lorenzo / Michler, Robert E / Rao, Vivek / Smith, Peter K / Zembala, Marian / Velazquez, Eric J / Al-Khalidi, Hussein R / Rouleau, Jean L / Anonymous3481116. ·Departments of Medicine, ontreal Heart Institute, University of Montreal, Canada (N.B., J.L.R.). · M. Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC. (S.R.S.). · Department of Cardiothoracic Surgery, Jena University Hospital, Friedrich-Schiller-University Jena, Germany (T.D., P.H.). · Department of Cardiology, Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom (M.C.P.). · Department of Cardiology, Golden Jubilee National Hospital, Glasgow, United Kingdom (M.C.P., N.A.-A, A.K.B.). · Section of Cardiac Surgery, Department of Cardiac Sciences, Libin CV Institute, University of Calgary, Canada (I.S.A.). · Department of Medicine, Duke University School of Medicine, Durham, NC. (A.P.A., E.J.V.). · Cardiac Surgery, ontreal Heart Institute, University of Montreal, Canada (R.C.). · Research Institute of Circulation Pathology, Novosibirsk, Russia (A.C.). · Department of Cardiac Surgery, La Pitié Salpêtrière, Assistance Publique des Hôpitaux de Paris, Université Pierre et Marie Curie-Paris 6, France (P.D.). · National Heart, Lung, and Blood Institute, Bethesda, MD (P.D.-N.). · Department of Cardiac Surgery, University Hospital Favaloro Foundation, Buenos Aires, Argentina (R.R.F.). · Dedinje Cardiovascular Institute, University of Belgrade School of Medicine, Serbia (S.G.). · Department of Cardiac Surgery, SAL Hospital and Medical Institute, Ahmedabad, India (A.J.). · Department of Cardiac Surgery, Wroclaw Medical University, Poland (M.J.). · Department of Cardiovascular Surgery, Georges Pompidou European Hospital and University Paris-Descartes, Sorbonne Paris-Cité, France (J.J.). · Postgraduate Program, Instituto de Cardiologia/FUC and UFCSPA, Porto Alegre, Brazil (R.A.K.K.). · Department of Cardiac Surgery, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy (L.M.). · Department of Cardiothoracic and Vascular Surgery, Montefiore Medical Center, Albert Einstein College of Medicine, New York City, NY (R.E.M.). · Division of Cardiovascular Surgery, Peter Munk Cardiac Centre, Toronto General Institute, University Health Network, University of Toronto, Canada (V.R.). · Department of Surgery, Duke University School of Medicine, Durham, NC. (P.K.S.). · Department of Cardiac, Vascular and Endovascular Surgery and Transplantology, Silesian Center for Heart Diseases in Zabrze, Poland Medical University of Silesia in Katowice, Poland (M.Z.). · Departments of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC. (H.R.A.-K.). ·Circ Heart Fail · Pubmed #30571194.

ABSTRACT: BACKGROUND: The STICH trial (Surgical Treatment for Ischemic Heart Failure) demonstrated a survival benefit of coronary artery bypass grafting in patients with ischemic cardiomyopathy and left ventricular dysfunction. The Society of Thoracic Surgeons (STS) risk score and the EuroSCORE-2 (ES2) are used for risk assessment in cardiac surgery, with little information available about their accuracy in patients with left ventricular dysfunction. We assessed the ability of the STS score and ES2 to evaluate 30-day postoperative mortality risk in STICH and a contemporary cohort (CC) of patients with a left ventricle ejection fraction ≤35% undergoing coronary artery bypass grafting outside of a trial setting. METHODS AND RESULTS: The STS and ES2 scores were calculated for 814 STICH patients and 1246 consecutive patients in a CC. There were marked variations in 30-day postoperative mortality risk from 1 patient to another. The STS scores consistently calculated lower risk scores than ES2 (1.5 versus 2.9 for the CC and 0.9 versus 2.4 for the STICH cohort), and underestimated postoperative mortality risk. The STS and ES2 scores had moderately good C statistics: CC (0.727, 95% CI: 0.650-0.803 for STS, and 0.707, 95% CI: 0.620-0.795 for ES2); STICH (0.744, 95% CI: 0.677-0.812, for STS and 0.736, 95% CI: 0.665-0.808 for ES2). Despite the CC patients having higher STS and ES2 scores than STICH patients, mortality (3.5%) was lower than that of STICH (4.8%), suggesting a possible decrease in postoperative mortality over the past decade. CONCLUSIONS: The 30-day postoperative mortality risk of coronary artery bypass grafting in patients with left ventricular dysfunction varies markedly. Both the STS and ES2 score are effective in evaluating risk, although the STS score tend to underestimate risk. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00023595.

75 Article Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders. 2018

Ligthart, Symen / Vaez, Ahmad / Võsa, Urmo / Stathopoulou, Maria G / de Vries, Paul S / Prins, Bram P / Van der Most, Peter J / Tanaka, Toshiko / Naderi, Elnaz / Rose, Lynda M / Wu, Ying / Karlsson, Robert / Barbalic, Maja / Lin, Honghuang / Pool, René / Zhu, Gu / Macé, Aurélien / Sidore, Carlo / Trompet, Stella / Mangino, Massimo / Sabater-Lleal, Maria / Kemp, John P / Abbasi, Ali / Kacprowski, Tim / Verweij, Niek / Smith, Albert V / Huang, Tao / Marzi, Carola / Feitosa, Mary F / Lohman, Kurt K / Kleber, Marcus E / Milaneschi, Yuri / Mueller, Christian / Huq, Mahmudul / Vlachopoulou, Efthymia / Lyytikäinen, Leo-Pekka / Oldmeadow, Christopher / Deelen, Joris / Perola, Markus / Zhao, Jing Hua / Feenstra, Bjarke / Anonymous2601133 / Amini, Marzyeh / Anonymous2611133 / Lahti, Jari / Schraut, Katharina E / Fornage, Myriam / Suktitipat, Bhoom / Chen, Wei-Min / Li, Xiaohui / Nutile, Teresa / Malerba, Giovanni / Luan, Jian'an / Bak, Tom / Schork, Nicholas / Del Greco M, Fabiola / Thiering, Elisabeth / Mahajan, Anubha / Marioni, Riccardo E / Mihailov, Evelin / Eriksson, Joel / Ozel, Ayse Bilge / Zhang, Weihua / Nethander, Maria / Cheng, Yu-Ching / Aslibekyan, Stella / Ang, Wei / Gandin, Ilaria / Yengo, Loïc / Portas, Laura / Kooperberg, Charles / Hofer, Edith / Rajan, Kumar B / Schurmann, Claudia / den Hollander, Wouter / Ahluwalia, Tarunveer S / Zhao, Jing / Draisma, Harmen H M / Ford, Ian / Timpson, Nicholas / Teumer, Alexander / Huang, Hongyan / Wahl, Simone / Liu, YongMei / Huang, Jie / Uh, Hae-Won / Geller, Frank / Joshi, Peter K / Yanek, Lisa R / Trabetti, Elisabetta / Lehne, Benjamin / Vozzi, Diego / Verbanck, Marie / Biino, Ginevra / Saba, Yasaman / Meulenbelt, Ingrid / O'Connell, Jeff R / Laakso, Markku / Giulianini, Franco / Magnusson, Patrik K E / Ballantyne, Christie M / Hottenga, Jouke Jan / Montgomery, Grant W / Rivadineira, Fernando / Rueedi, Rico / Steri, Maristella / Herzig, Karl-Heinz / Stott, David J / Menni, Cristina / Frånberg, Mattias / St Pourcain, Beate / Felix, Stephan B / Pers, Tune H / Bakker, Stephan J L / Kraft, Peter / Peters, Annette / Vaidya, Dhananjay / Delgado, Graciela / Smit, Johannes H / Großmann, Vera / Sinisalo, Juha / Seppälä, Ilkka / Williams, Stephen R / Holliday, Elizabeth G / Moed, Matthijs / Langenberg, Claudia / Räikkönen, Katri / Ding, Jingzhong / Campbell, Harry / Sale, Michele M / Chen, Yii-Der I / James, Alan L / Ruggiero, Daniela / Soranzo, Nicole / Hartman, Catharina A / Smith, Erin N / Berenson, Gerald S / Fuchsberger, Christian / Hernandez, Dena / Tiesler, Carla M T / Giedraitis, Vilmantas / Liewald, David / Fischer, Krista / Mellström, Dan / Larsson, Anders / Wang, Yunmei / Scott, William R / Lorentzon, Matthias / Beilby, John / Ryan, Kathleen A / Pennell, Craig E / Vuckovic, Dragana / Balkau, Beverly / Concas, Maria Pina / Schmidt, Reinhold / Mendes de Leon, Carlos F / Bottinger, Erwin P / Kloppenburg, Margreet / Paternoster, Lavinia / Boehnke, Michael / Musk, A W / Willemsen, Gonneke / Evans, David M / Madden, Pamela A F / Kähönen, Mika / Kutalik, Zoltán / Zoledziewska, Magdalena / Karhunen, Ville / Kritchevsky, Stephen B / Sattar, Naveed / Lachance, Genevieve / Clarke, Robert / Harris, Tamara B / Raitakari, Olli T / Attia, John R / van Heemst, Diana / Kajantie, Eero / Sorice, Rossella / Gambaro, Giovanni / Scott, Robert A / Hicks, Andrew A / Ferrucci, Luigi / Standl, Marie / Lindgren, Cecilia M / Starr, John M / Karlsson, Magnus / Lind, Lars / Li, Jun Z / Chambers, John C / Mori, Trevor A / de Geus, Eco J C N / Heath, Andrew C / Martin, Nicholas G / Auvinen, Juha / Buckley, Brendan M / de Craen, Anton J M / Waldenberger, Melanie / Strauch, Konstantin / Meitinger, Thomas / Scott, Rodney J / McEvoy, Mark / Beekman, Marian / Bombieri, Cristina / Ridker, Paul M / Mohlke, Karen L / Pedersen, Nancy L / Morrison, Alanna C / Boomsma, Dorret I / Whitfield, John B / Strachan, David P / Hofman, Albert / Vollenweider, Peter / Cucca, Francesco / Jarvelin, Marjo-Riitta / Jukema, J Wouter / Spector, Tim D / Hamsten, Anders / Zeller, Tanja / Uitterlinden, André G / Nauck, Matthias / Gudnason, Vilmundur / Qi, Lu / Grallert, Harald / Borecki, Ingrid B / Rotter, Jerome I / März, Winfried / Wild, Philipp S / Lokki, Marja-Liisa / Boyle, Michael / Salomaa, Veikko / Melbye, Mads / Eriksson, Johan G / Wilson, James F / Penninx, Brenda W J H / Becker, Diane M / Worrall, Bradford B / Gibson, Greg / Krauss, Ronald M / Ciullo, Marina / Zaza, Gianluigi / Wareham, Nicholas J / Oldehinkel, Albertine J / Palmer, Lyle J / Murray, Sarah S / Pramstaller, Peter P / Bandinelli, Stefania / Heinrich, Joachim / Ingelsson, Erik / Deary, Ian J / Mägi, Reedik / Vandenput, Liesbeth / van der Harst, Pim / Desch, Karl C / Kooner, Jaspal S / Ohlsson, Claes / Hayward, Caroline / Lehtimäki, Terho / Shuldiner, Alan R / Arnett, Donna K / Beilin, Lawrence J / Robino, Antonietta / Froguel, Philippe / Pirastu, Mario / Jess, Tine / Koenig, Wolfgang / Loos, Ruth J F / Evans, Denis A / Schmidt, Helena / Smith, George Davey / Slagboom, P Eline / Eiriksdottir, Gudny / Morris, Andrew P / Psaty, Bruce M / Tracy, Russell P / Nolte, Ilja M / Boerwinkle, Eric / Visvikis-Siest, Sophie / Reiner, Alex P / Gross, Myron / Bis, Joshua C / Franke, Lude / Franco, Oscar H / Benjamin, Emelia J / Chasman, Daniel I / Dupuis, Josée / Snieder, Harold / Dehghan, Abbas / Alizadeh, Behrooz Z / and others. ·Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CA, the Netherlands. · Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen 9700 RB, the Netherlands; Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran. · Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen 9700 RB, the Netherlands; Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu 51010, Estonia. · Université de Lorraine, INSERM, IGE-PCV, 54000 Nancy, France. · Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CA, the Netherlands; Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA. · Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK. · Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen 9700 RB, the Netherlands. · Translational Gerontology Branch, National Institute on Aging, Baltimore, MD 21224, USA. · Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen 9700 RB, the Netherlands; Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen 9713 GZ, the Netherlands. · Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA 02215, USA. · Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA. · Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden. · University of Split School of Medicine, Split 21000, Croatia. · Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA. · Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam 1081 BT, the Netherlands; Amsterdam Public Health research institute, VU University Medical Center, Amsterdam 1081 BT, the Netherlands. · QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia. · Department of Computational Biology, University of Lausanne, Lausanne 1010, Switzerland; Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne 1010, Switzerland. · Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Sardinia 08045, Italy. · Department of Cardiology, Leiden University Medical Center, Leiden 2300 RC, the Netherlands; Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden 2333 ZA, the Netherlands. · Department of Twin Research & Genetic Epidemiology, King's College London, London SE1 7EH, UK; NIHR Biomedical Research Centre at Guy's and St. Thomas' Foundation Trust, London SE1 9RT, UK. · Unit of Genomics of Complex Diseases, Institut d'Investigació Biomèdica Sant Pau, Barcelona 08025, Spain; Cardiovascular Medicine Unit, Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm 17176, Sweden. · University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD 4102, Australia; MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK. · Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen 9700 RB, the Netherlands; Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen 9713 GZ, the Netherlands; MRC Epidemiology Unit, University of Cambridge School of Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK. · Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine and Ernst-Moritz-Arndt University Greifswald, Greifswald 17475, Germany; German Centre for Cardiovascular Research, Partner Site Greifswald, Greifswald 17475, Germany. · University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen 9713 AV, the Netherlands. · Icelandic Heart Association, Kopavogur 201, Iceland; Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland. · Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. · Institute of Epidemiology II, Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany; German Center for Diabetes Research, Partner Site Munich, Munich 85764, Germany. · Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63108-2212, USA. · Department of Epidemiology and Prevention, Public Health Sciences, Wake Forest University Health Sciences, Winston-Salem, NC 27157, USA. · Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim 68167, Germany. · Department of Psychiatry, Amsterdam Neuroscience and Amsterdam Public Health Research Institute, Amsterdam University Medical Center/GGZ inGeest Research & Innovation, Amsterdam 1081 HJ, the Netherlands. · Department of General and Interventional Cardiology, University Heart Center Hamburg, Hamburg 20246, Germany; Institute of Medical Biometry and Statistics, University Medical Center Schleswig-Holstein, Campus Luebeck, Lübeck 23562, Germany; German Center for Cardiovascular Research, Partner Site RhineMain, 55131 Mainz, Germany. · Transplantation Laboratory, Medicum, University of Helsinki, Helsinki 00014, Finland. · Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33014, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere 33520, Finland. · Hunter Medical Research Institute, New Lambon Heights, NSW 2305, Australia; Centre for Clinical Epidemiology & Biostatistics, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia. · Molecular Epidemiology, Leiden University Medical Center, Leiden 2333 ZC, the Netherlands; Max Planck Institute for Biology of Ageing, Cologne 50931, Germany. · National Institute for Health and Welfare, Helsinki 00271, Finland. · MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge CB2 0QQ, UK. · Department of Epidemiology Research, Statens Serum Institut, Copenhagen 2300, Denmark. · Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki 00014, Finland; Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki 00014, Finland; Folkhälsan Research Centre, Helsinki 00250, Finland. · Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH16 4UX, UK. · Human Genetics Center, School of Public Health and Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX 77030, USA. · Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand. · Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA. · Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 90502, USA. · Institute of Genetics and Biophysics "A. Buzzati-Traverso," Consiglio Nazionale delle Ricerche, Napoli 80131, Italy. · Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona 37134, Italy. · Interdisciplinary Center Psychopathology and Emotion regulation, University Medical Center Groningen, University of Groningen, Groningen 9700 RB, the Netherlands. · Human Biology, J. Craig Venter Institute, La Jolla, CA 92037, USA; Quantitative Medicine, Translational Genomics Research Institute, Phoenix, AZ 85004, USA. · Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano 39100, Italy. · Institute of Epidemiology, Helmholtz Zentrum München - German Research Centre for Environmental Health, Neuherberg 85764, Germany; Ludwig Maximilian University of Munich, Dr. von Hauner Children's Hospital, Munich 80337, Germany. · Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK. · Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK. · Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu 51010, Estonia. · Department of Internal Medicine and Clinical Nutrition, University of Gothenburg, Gothenburg 41345, Sweden. · Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109-5618, USA. · Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK; Department of Cardiology, Ealing Hospital, Middlesex UB1 3HW, UK. · Bioinformatics Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg 413 90, Sweden. · Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA. · Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. · Medical School, University of Western Australia, Perth, WA 6009, Australia. · AREA Science Park, Trieste 34149, Italy. · Centre National de la Recherche Scientifique UMR 8199, University of Lille, Institut Pasteur de Lille, European Genomic Institute for Diabetes, FR 3508, 59000 Lille, France; Program in Complex Trait Genomics, Institute for Molecular Bioscience, University of Queensland, St. Lucia, Brisbane, QLD 4072, Australia. · Support OU, Institute of Genetic and Biomedic Research, Consiglio Nazionale delle Ricerche, Sassari 7100, Italy. · Fred Hutchinson Cancer Research Center, Public Health Sciences Division, Mail Stop M3-A410, 1100 Fairview Ave. N., Seattle, WA, USA. · Clinical Division of Neurogeriatrics, Department of Neurology, Medical University Graz, Graz 8036, Austria; Institute of Medical Informatics, Statistics and Documentation, Medical University Graz, Graz 8036, Austria. · Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA. · Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. · Department of Medical Statistics and Bio-informatics, Section Molecular Epidemiology, Leiden University Medical Center, Leiden 2333 ZC, the Netherlands. · Steno Diabetes Center Copenhagen, Gentofte 2820, Denmark; Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2100, Denmark. · Center for Integrative Genomics, School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA. · Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam 1081 BT, the Netherlands; Amsterdam Public Health research institute, VU University Medical Center, Amsterdam 1081 BT, the Netherlands; Neuroscience Campus Amsterdam, Amsterdam 1081 HV, the Netherlands. · Robertson Centre for Biostatistics, University of Glasgow, Glasgow G12 8QQ, UK. · MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK. · Department SHIP-KEF, Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany. · Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. · Boston VA Research Institute, Inc., Boston, MA 02130, USA. · Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden 2333 ZC, the Netherlands. · GeneSTAR Research Center, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. · Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK. · Institute for Maternal and Child Health, IRCCS "Burlo Garofolo," Trieste 34140, Italy. · Centre National de la Recherche Scientifique UMR 8199, University of Lille, Institut Pasteur de Lille, European Genomic Institute for Diabetes, FR 3508, 59000 Lille, France. · Institute of Molecular Genetics, Consiglio Nazionale delle Ricerche, Pavia 27100, Italy. · Gottfried Schatz Research Center, Institute for Molecular Biology and Biochemistry, 8010 Graz, Austria. · Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio 70210, Finland. · Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA; Methodist DeBakey Heart and Vascular Center, Houston, TX 77030, USA. · Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam 1081 BT, the Netherlands. · Department of Internal Medicine, Erasmus University Medical Center, Rotterdam 3015 CN, the Netherlands. · Department of Computational Biology, University of Lausanne, Lausanne 1010, Switzerland; Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland. · Department of Physiology, Institute of Biomedicine, University of Oulu, Medical Research Center Oulu and Oulu University Hospital, Oulu 90014, Finland; Biocenter Oulu, University of Oulu, Oulu 90220, Finland; Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan 60-512, Poland. · Institute of Cardiovascular and Medical Sciences, Faculty of Medicine, University of Glasgow, Glasgow G12 8QQ, UK. · Department of Twin Research & Genetic Epidemiology, King's College London, London SE1 7EH, UK. · Cardiovascular Medicine Unit, Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm 17176, Sweden; Department of Numerical Analysis and Computer Science, Stockholm University, Stockholm 100 44, Sweden. · MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK; Donders Institute, Radboud University, Nijmegen 6525 XD, the Netherlands. · German Centre for Cardiovascular Research, Partner Site Greifswald, Greifswald 17475, Germany; Department for Internal Medicine B, University Medicine Greifswald, Greifswald 17475, Germany. · Department of Epidemiology Research, Statens Serum Institut, Copenhagen 2300, Denmark; Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2100, Denmark. · Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen 9713 GZ, the Netherlands. · Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherber 85764, Germany. · Center for Thrombosis and Hemostasis, University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany. · Heart and Lung Center, Helsinki University Hospital and Helsinki University, Helsinki 00029, Finland. · Department of Neurology, University of Virginia, Charlottesville, VA 22908, USA. · Molecular Epidemiology, Leiden University Medical Center, Leiden 2333 ZC, the Netherlands. · Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki 00014, Finland. · Department of Internal Medicine/Geriatrics, Wake Forest University Health Sciences, Winston-Salem, NC 27157, USA. · Busselton Population Medical Research Institute, Sir Charles Gairdner Hospital, Nedlands, WA 6009, Australia; Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, WA 6009, Australia. · Institute of Genetics and Biophysics "A. Buzzati-Traverso," Consiglio Nazionale delle Ricerche, Napoli 80131, Italy; IRCCS Neuromed, Pozzilli (IS) 86077, Italy. · Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK. · Department of Pediatrics and Rady Children's Hospital, School of Medicine, University of California, San Diego, La Jolla, CA 92037, USA. · Center for Cardiovascular Health, Tulane University, New Orleans, LA 70112, USA. · Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD 20892, USA. · Department of Public Health and Caring Sciences, Molecular Geriatrics, Uppsala University, Uppsala 752 37, Sweden. · Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK. · Department of Medical Sciences, Uppsala University, Uppsala 751 41, Sweden. · Department of Medicine, Case Cardiovascular Research Institute, Case Western Reserve University, Harrington Heart & Vascular Institute, University Hospitals, Cleveland, OH 44106, USA. · Department of Internal Medicine and Clinical Nutrition, University of Gothenburg, Gothenburg 41345, Sweden; Geriatric Medicine, Sahlgrenska University Hospital, Mölndal 431 80, Sweden. · PathWest Laboratory Medicine WA, Nedlands, WA 6009, Australia; School of Biomedical Sciences, University of Western Australia, Crawley, Perth, WA 6009, Australia. · Medical Sciences, Surgical and Health Department, University of Trieste, Trieste 34137, Italy. · INSERM U1018, Centre de Recherche en Epidémiologie et Santé des Populations, Team 5 (EpReC, Renal, and Cardiovascular Epidemiology), Université de Versailles Saint-Quentin-en-Yvelines, Université Paris-Saclay, Villejuif 94807, France. · Clinical Division of Neurogeriatrics, Department of Neurology, Medical University Graz, Graz 8036, Austria. · Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA. · Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. · Department of Rheumatology, Leiden University Medical Center, Leiden 2300 RC, the Netherlands; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden 2333 ZC, the Netherlands. · Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA. · Busselton Population Medical Research Institute, Sir Charles Gairdner Hospital, Nedlands, WA 6009, Australia; Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Nedlands, WA 6009, Australia. · Department of Psychiatry, Washington University School of Medicine, 4560 Clayton Ave., Suite 1000, St. Louis, MO 63110, USA. · Department of Clinical Physiology, Tampere University Hospital, Tampere 33520, Finland; Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere 33520, Finland. · Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne 1010, Switzerland. · Center for Life Course Health Research, Faculty of Medicine, University of Oulu, 90014 Oulun yliopisto, Finland. · Gerontology and Geriatric Medicine, Sticht Center on Aging and Rehabilitation, Wake Forest University Health Sciences, Winston-Salem, NC 27157, USA. · BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow G12 8TA, UK. · Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK. · Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD 20892, USA. · Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland. · Hunter Medical Research Institute, New Lambon Heights, NSW 2305, Australia; Centre for Clinical Epidemiology & Biostatistics, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia; John Hunter Hospital, New Lambton Heights, NWS 2305, Australia. · Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden 2333 ZA, the Netherlands. · Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki 00014, Finland; Hospital for Children and Adolescents, Helsinki University Central Hospital and University of Helsinki, Helsinki 00290, Finland; Department of Obstetrics and Gynaecology, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu 90014, Finland. · Division of Nephrology and Dialysis, Columbus-Gemelli University Hospital, Università Cattolica del Sacro Cuore, Roma 168, Italy. · Institute of Epidemiology, Helmholtz Zentrum München - German Research Centre for Environmental Health, Neuherberg 85764, Germany. · Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA. · Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK; Alzheimer's Scotland Dementia Research Centre, University of Edinburgh, Edinburgh EH8 9JZ, UK. · Department of Clinical Sciences and Orthopaedic Surgery, Lund University, Malmo 20502, Sweden. · Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK; Department of Cardiology, Ealing Hospital, Middlesex UB1 3HW, UK; Imperial College Healthcare NHS Trust, London W12 0HS, UK; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore; MRC-PHE Centre for Environment and Health, Imperial College London, London W2 1PG, UK. · Center for Life Course Health Research, Faculty of Medicine, University of Oulu, 90014 Oulun yliopisto, Finland; Unit of Primary Health Care, Oulu University Hospital, Oulu 90220, Finland. · Department of Epidemiology and Public Health, University College Cork, Cork T12 K8AF, Ireland. · Institute of Epidemiology II, Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany; German Center for Cardiovascular Research, Partner Site Munich Heart Alliance, 80636 Munich, Germany. · Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany; Genetic Epidemiology, Institute of Medical Informatics, Biometry, and Epidemiology, Faculty of Medicine, Ludwig Maximilian University of Munich, Neuherberg 85764, Germany. · Institute of Human Genetics, Technische Universität München, Munich 85764, Germany; Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg 85764, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich 81377, Germany. · Hunter Medical Research Institute, New Lambon Heights, NSW 2305, Australia; Information-Based Medicine Stream, Hunter Medical Research Institute, New Lambton Heights, NSW 2305, Australia. · Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA. · Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA. · Population Health Research Institute, St. George's, University of London, London SW17 0RE, UK. · Department of Internal Medicine, Centre Hospitalier Universitaire Vaudois, Lausanne 1011, Switzerland. · Biocenter Oulu, University of Oulu, Oulu 90220, Finland; Center for Life Course Health Research, Faculty of Medicine, University of Oulu, 90014 Oulun yliopisto, Finland; Unit of Primary Health Care, Oulu University Hospital, Oulu 90220, Finland; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London W2 1PG, UK; Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Kingston Lane, Uxbridge, Middlesex UB8 3PH, UK. · Department of Cardiology, Leiden University Medical Center, Leiden 2300 RC, the Netherlands; Durrer Center for Cardiogenetic Research, Amsterdam 3501 DG, the Netherlands; Interuniversity Cardiology Institute of the Netherlands, Utrecht 3511 EP, the Netherlands. · Cardiovascular Medicine Unit, Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm 17176, Sweden. · Department of General and Interventional Cardiology, University Heart Center Hamburg, Hamburg 20246, Germany; German Center for Cardiovascular Research, Partner Site RhineMain, 55131 Mainz, Germany. · Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CA, the Netherlands; Department of Internal Medicine, Erasmus University Medical Center, Rotterdam 3015 CN, the Netherlands. · German Centre for Cardiovascular Research, Partner Site Greifswald, Greifswald 17475, Germany; Institute for Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald 17475, Germany. · Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA. (and more) ·Am J Hum Genet · Pubmed #30388399.

ABSTRACT: C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10

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