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1.  Association analyses of 249,796 individuals reveal eighteen new loci associated with body mass index 
Speliotes, Elizabeth K. | Willer, Cristen J. | Berndt, Sonja I. | Monda, Keri L. | Thorleifsson, Gudmar | Jackson, Anne U. | Allen, Hana Lango | Lindgren, Cecilia M. | Luan, Jian’an | Mägi, Reedik | Randall, Joshua C. | Vedantam, Sailaja | Winkler, Thomas W. | Qi, Lu | Workalemahu, Tsegaselassie | Heid, Iris M. | Steinthorsdottir, Valgerdur | Stringham, Heather M. | Weedon, Michael N. | Wheeler, Eleanor | Wood, Andrew R. | Ferreira, Teresa | Weyant, Robert J. | Segré, Ayellet V. | Estrada, Karol | Liang, Liming | Nemesh, James | Park, Ju-Hyun | Gustafsson, Stefan | Kilpeläinen, Tuomas O. | Yang, Jian | Bouatia-Naji, Nabila | Esko, Tõnu | Feitosa, Mary F. | Kutalik, Zoltán | Mangino, Massimo | Raychaudhuri, Soumya | Scherag, Andre | Smith, Albert Vernon | Welch, Ryan | Zhao, Jing Hua | Aben, Katja K. | Absher, Devin M. | Amin, Najaf | Dixon, Anna L. | Fisher, Eva | Glazer, Nicole L. | Goddard, Michael E. | Heard-Costa, Nancy L. | Hoesel, Volker | Hottenga, Jouke-Jan | Johansson, Åsa | Johnson, Toby | Ketkar, Shamika | Lamina, Claudia | Li, Shengxu | Moffatt, Miriam F. | Myers, Richard H. | Narisu, Narisu | Perry, John R.B. | Peters, Marjolein J. | Preuss, Michael | Ripatti, Samuli | Rivadeneira, Fernando | Sandholt, Camilla | Scott, Laura J. | Timpson, Nicholas J. | Tyrer, Jonathan P. | van Wingerden, Sophie | Watanabe, Richard M. | White, Charles C. | Wiklund, Fredrik | Barlassina, Christina | Chasman, Daniel I. | Cooper, Matthew N. | Jansson, John-Olov | Lawrence, Robert W. | Pellikka, Niina | Prokopenko, Inga | Shi, Jianxin | Thiering, Elisabeth | Alavere, Helene | Alibrandi, Maria T. S. | Almgren, Peter | Arnold, Alice M. | Aspelund, Thor | Atwood, Larry D. | Balkau, Beverley | Balmforth, Anthony J. | Bennett, Amanda J. | Ben-Shlomo, Yoav | Bergman, Richard N. | Bergmann, Sven | Biebermann, Heike | Blakemore, Alexandra I.F. | Boes, Tanja | Bonnycastle, Lori L. | Bornstein, Stefan R. | Brown, Morris J. | Buchanan, Thomas A. | Busonero, Fabio | Campbell, Harry | Cappuccio, Francesco P. | Cavalcanti-Proença, Christine | Chen, Yii-Der Ida | Chen, Chih-Mei | Chines, Peter S. | Clarke, Robert | Coin, Lachlan | Connell, John | Day, Ian N.M. | Heijer, Martin den | Duan, Jubao | Ebrahim, Shah | Elliott, Paul | Elosua, Roberto | Eiriksdottir, Gudny | Erdos, Michael R. | Eriksson, Johan G. | Facheris, Maurizio F. | Felix, Stephan B. | Fischer-Posovszky, Pamela | Folsom, Aaron R. | Friedrich, Nele | Freimer, Nelson B. | Fu, Mao | Gaget, Stefan | Gejman, Pablo V. | Geus, Eco J.C. | Gieger, Christian | Gjesing, Anette P. | Goel, Anuj | Goyette, Philippe | Grallert, Harald | Gräßler, Jürgen | Greenawalt, Danielle M. | Groves, Christopher J. | Gudnason, Vilmundur | Guiducci, Candace | Hartikainen, Anna-Liisa | Hassanali, Neelam | Hall, Alistair S. | Havulinna, Aki S. | Hayward, Caroline | Heath, Andrew C. | Hengstenberg, Christian | Hicks, Andrew A. | Hinney, Anke | Hofman, Albert | Homuth, Georg | Hui, Jennie | Igl, Wilmar | Iribarren, Carlos | Isomaa, Bo | Jacobs, Kevin B. | Jarick, Ivonne | Jewell, Elizabeth | John, Ulrich | Jørgensen, Torben | Jousilahti, Pekka | Jula, Antti | Kaakinen, Marika | Kajantie, Eero | Kaplan, Lee M. | Kathiresan, Sekar | Kettunen, Johannes | Kinnunen, Leena | Knowles, Joshua W. | Kolcic, Ivana | König, Inke R. | Koskinen, Seppo | Kovacs, Peter | Kuusisto, Johanna | Kraft, Peter | Kvaløy, Kirsti | Laitinen, Jaana | Lantieri, Olivier | Lanzani, Chiara | Launer, Lenore J. | Lecoeur, Cecile | Lehtimäki, Terho | Lettre, Guillaume | Liu, Jianjun | Lokki, Marja-Liisa | Lorentzon, Mattias | Luben, Robert N. | Ludwig, Barbara | Manunta, Paolo | Marek, Diana | Marre, Michel | Martin, Nicholas G. | McArdle, Wendy L. | McCarthy, Anne | McKnight, Barbara | Meitinger, Thomas | Melander, Olle | Meyre, David | Midthjell, Kristian | Montgomery, Grant W. | Morken, Mario A. | Morris, Andrew P. | Mulic, Rosanda | Ngwa, Julius S. | Nelis, Mari | Neville, Matt J. | Nyholt, Dale R. | ODonnell, Christopher J. | O’Rahilly, Stephen | Ong, Ken K. | Oostra, Ben | Paré, Guillaume | Parker, Alex N. | Perola, Markus | Pichler, Irene | Pietiläinen, Kirsi H. | Platou, Carl G.P. | Polasek, Ozren | Pouta, Anneli | Rafelt, Suzanne | Raitakari, Olli | Rayner, Nigel W. | Ridderstråle, Martin | Rief, Winfried | Ruokonen, Aimo | Robertson, Neil R. | Rzehak, Peter | Salomaa, Veikko | Sanders, Alan R. | Sandhu, Manjinder S. | Sanna, Serena | Saramies, Jouko | Savolainen, Markku J. | Scherag, Susann | Schipf, Sabine | Schreiber, Stefan | Schunkert, Heribert | Silander, Kaisa | Sinisalo, Juha | Siscovick, David S. | Smit, Jan H. | Soranzo, Nicole | Sovio, Ulla | Stephens, Jonathan | Surakka, Ida | Swift, Amy J. | Tammesoo, Mari-Liis | Tardif, Jean-Claude | Teder-Laving, Maris | Teslovich, Tanya M. | Thompson, John R. | Thomson, Brian | Tönjes, Anke | Tuomi, Tiinamaija | van Meurs, Joyce B.J. | van Ommen, Gert-Jan | Vatin, Vincent | Viikari, Jorma | Visvikis-Siest, Sophie | Vitart, Veronique | Vogel, Carla I. G. | Voight, Benjamin F. | Waite, Lindsay L. | Wallaschofski, Henri | Walters, G. Bragi | Widen, Elisabeth | Wiegand, Susanna | Wild, Sarah H. | Willemsen, Gonneke | Witte, Daniel R. | Witteman, Jacqueline C. | Xu, Jianfeng | Zhang, Qunyuan | Zgaga, Lina | Ziegler, Andreas | Zitting, Paavo | Beilby, John P. | Farooqi, I. Sadaf | Hebebrand, Johannes | Huikuri, Heikki V. | James, Alan L. | Kähönen, Mika | Levinson, Douglas F. | Macciardi, Fabio | Nieminen, Markku S. | Ohlsson, Claes | Palmer, Lyle J. | Ridker, Paul M. | Stumvoll, Michael | Beckmann, Jacques S. | Boeing, Heiner | Boerwinkle, Eric | Boomsma, Dorret I. | Caulfield, Mark J. | Chanock, Stephen J. | Collins, Francis S. | Cupples, L. Adrienne | Smith, George Davey | Erdmann, Jeanette | Froguel, Philippe | Grönberg, Henrik | Gyllensten, Ulf | Hall, Per | Hansen, Torben | Harris, Tamara B. | Hattersley, Andrew T. | Hayes, Richard B. | Heinrich, Joachim | Hu, Frank B. | Hveem, Kristian | Illig, Thomas | Jarvelin, Marjo-Riitta | Kaprio, Jaakko | Karpe, Fredrik | Khaw, Kay-Tee | Kiemeney, Lambertus A. | Krude, Heiko | Laakso, Markku | Lawlor, Debbie A. | Metspalu, Andres | Munroe, Patricia B. | Ouwehand, Willem H. | Pedersen, Oluf | Penninx, Brenda W. | Peters, Annette | Pramstaller, Peter P. | Quertermous, Thomas | Reinehr, Thomas | Rissanen, Aila | Rudan, Igor | Samani, Nilesh J. | Schwarz, Peter E.H. | Shuldiner, Alan R. | Spector, Timothy D. | Tuomilehto, Jaakko | Uda, Manuela | Uitterlinden, André | Valle, Timo T. | Wabitsch, Martin | Waeber, Gérard | Wareham, Nicholas J. | Watkins, Hugh | Wilson, James F. | Wright, Alan F. | Zillikens, M. Carola | Chatterjee, Nilanjan | McCarroll, Steven A. | Purcell, Shaun | Schadt, Eric E. | Visscher, Peter M. | Assimes, Themistocles L. | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Groop, Leif C. | Haritunians, Talin | Hunter, David J. | Kaplan, Robert C. | Mohlke, Karen L. | O’Connell, Jeffrey R. | Peltonen, Leena | Schlessinger, David | Strachan, David P. | van Duijn, Cornelia M. | Wichmann, H.-Erich | Frayling, Timothy M. | Thorsteinsdottir, Unnur | Abecasis, Gonçalo R. | Barroso, Inês | Boehnke, Michael | Stefansson, Kari | North, Kari E. | McCarthy, Mark I. | Hirschhorn, Joel N. | Ingelsson, Erik | Loos, Ruth J.F.
Nature genetics  2010;42(11):937-948.
Obesity is globally prevalent and highly heritable, but the underlying genetic factors remain largely elusive. To identify genetic loci for obesity-susceptibility, we examined associations between body mass index (BMI) and ~2.8 million SNPs in up to 123,865 individuals, with targeted follow-up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity-susceptibility loci and identified 18 new loci associated with BMI (P<5×10−8), one of which includes a copy number variant near GPRC5B. Some loci (MC4R, POMC, SH2B1, BDNF) map near key hypothalamic regulators of energy balance, and one is near GIPR, an incretin receptor. Furthermore, genes in other newly-associated loci may provide novel insights into human body weight regulation.
doi:10.1038/ng.686
PMCID: PMC3014648  PMID: 20935630
2.  Distribution, Determinants,and Normal Reference Values of Thoracic and Abdominal Aortic Diameters by Computed Tomography (From the Framingham Heart Study) 
The American journal of cardiology  2013;111(10):1510-1516.
Current screening and detection of asymptomatic aortic aneurysms is largely based on uniform cut-point diameters. Our objective was to define normal aortic diameters in asymptomatic men and women in a community-based cohort and to determine the association between aortic diameters and traditional risk factors for cardiovascular disease (CVD).Measurements of the diameter of the ascending aorta(AA), descending thoracic aorta (DTA), infrarenal abdominal (IRA) and lower abdominal aorta (LAA) were acquired from 3,431 Framingham Heart Study participants. Mean diameters were stratified by sex, age, and body surface area (BSA). Univariate associations with risk factor levels were examined and multivariable linear regression analysis was used to assess the significance of covariate-adjusted relations with aortic diameters. For men, the average diameter was 34.1 mm for AA, 25.8 mm for DTA, 19.3 mm for IRA and 18.7 mm for LAA.For women, the average diameter was 31.9 mm for AA, 23.1 mm for DTA, 16.7 mm for IRA, and 16.0 mm for LAA. The mean aorticdiameters were strongly correlated (p<0.0001) with age and BSA in age-adjusted analyses, and these relations remained significant in multivariable regression analyses. Positive associations of diastolic BP with AA and DTA in both sexes and pack years of cigarette smoking with DTA in women and with IRA in men and women were observed. In conclusion, average diameters of the thoracic and abdominal aorta by CT are larger in men compared with women, vary significantly with age and BSA, and are associated with modifiable CVD risk factors including diastolic blood pressure and cigarette smoking.
doi:10.1016/j.amjcard.2013.01.306
PMCID: PMC3644324  PMID: 23497775
Aortic diameter; computed tomography; sex; age; body surface area
3.  Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease 
PLoS Genetics  2014;10(7):e1004502.
The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions.
Author Summary
Sudden death due to heart attack ranks among the top causes of death in the world, and family studies have shown that genetics has a substantial effect on heart disease risk. Recent studies suggest that multiple genetic factors each with modest effects are necessary for the development of CAD, but the genes and molecular processes involved remain poorly understood. We conducted an integrative genomics study where we used the information of gene-gene interactions to capture groups of genes that are most likely to increase heart disease risk. We not only confirmed the importance of several known CAD risk processes such as the metabolism and transport of cholesterol, immune response, and blood coagulation, but also revealed many novel processes such as neuroprotection, cell cycle, and proteolysis that were not previously implicated in CAD. In particular, we highlight several genes such as GLO1 with key regulatory roles within these processes not detected by the first wave of genetic analyses. These results highlight the value of integrating population genetic data with diverse resources that functionally annotate the human genome. Such integration facilitates the identification of novel molecular processes involved in the pathogenesis of CAD as well as potential novel targets for the development of efficacious therapeutic interventions.
doi:10.1371/journal.pgen.1004502
PMCID: PMC4102418  PMID: 25033284
5.  Circulating CD31+ Leukocyte Frequency is Associated with Cardiovascular Risk Factors 
Atherosclerosis  2013;229(1):228-233.
Objectives
CD31 identifies a heterogeneous population of cells in the blood, consisting of mature leukocytes and platelets, as well as smaller numbers of endothelial and progenitor cells. Because unfractionated CD31+ blood cells have demonstrated angiogenic properties in vivo, we hypothesized that circulating CD31+ cells would be related to the presence of cardiovascular risk factors in humans.
Methods and Results
We studied 1,487 participants, free of cardiovascular disease, from the Framingham Offspring Study. Using anti-human CD31 and CD45 antibodies, distinct CD31+/CD45+ leukocyte populations were enumerated in blood samples by FACS analysis. We used linear regression analyses to investigate the relation of each cell phenotype with cardiovascular risk factors. We identified 3 distinct leukocyte populations: CD31-, CD31dim, and CD31bright cells. Using forward/side scatter analyses, CD31- and CD31dim cells mapped to lymphoid gates while CD31bright cells were monocytoid. In multivariable analyses, higher frequency of CD31bright cells was associated with older age, male sex, and CRP (all P<0.001). In contrast, CD31dim was inversely associated with age, male sex, CRP, and smoking (all P<0.01). Framingham Risk Score was positively associated with CD31bright frequency (P=0.002), and negatively associated with CD31dim frequency (P=0.020).
Conclusions
CD31+ staining identifies 2 major leukocyte populations, CD31bright and CD31dim, which demonstrated significant and opposite associations with cardiovascular risk in humans. Further research is needed to define the biological and potential therapeutic roles of CD31+ subpopulations in vascular disease.
doi:10.1016/j.atherosclerosis.2013.04.017
PMCID: PMC3984590  PMID: 23701996
epidemiology; CD31; leukocytes; endothelial cells; cardiovascular risk factors
6.  GRASP: analysis of genotype–phenotype results from 1390 genome-wide association studies and corresponding open access database 
Bioinformatics  2014;30(12):i185-i194.
Summary: We created a deeply extracted and annotated database of genome-wide association studies (GWAS) results. GRASP v1.0 contains >6.2 million SNP-phenotype association from among 1390 GWAS studies. We re-annotated GWAS results with 16 annotation sources including some rarely compared to GWAS results (e.g. RNAediting sites, lincRNAs, PTMs).
Motivation: To create a high-quality resource to facilitate further use and interpretation of human GWAS results in order to address important scientific questions.
Results: GWAS have grown exponentially, with increases in sample sizes and markers tested, and continuing bias toward European ancestry samples. GRASP contains >100 000 phenotypes, roughly: eQTLs (71.5%), metabolite QTLs (21.2%), methylation QTLs (4.4%) and diseases, biomarkers and other traits (2.8%). cis-eQTLs, meQTLs, mQTLs and MHC region SNPs are highly enriched among significant results. After removing these categories, GRASP still contains a greater proportion of studies and results than comparable GWAS catalogs. Cardiovascular disease and related risk factors pre-dominate remaining GWAS results, followed by immunological, neurological and cancer traits. Significant results in GWAS display a highly gene-centric tendency. Sex chromosome X (OR = 0.18[0.16-0.20]) and Y (OR = 0.003[0.001-0.01]) genes are depleted for GWAS results. Gene length is correlated with GWAS results at nominal significance (P ≤ 0.05) levels. We show this gene-length correlation decays at increasingly more stringent P-value thresholds. Potential pleotropic genes and SNPs enriched for multi-phenotype association in GWAS are identified. However, we note possible population stratification at some of these loci. Finally, via re-annotation we identify compelling functional hypotheses at GWAS loci, in some cases unrealized in studies to date.
Conclusion: Pooling summary-level GWAS results and re-annotating with bioinformatics predictions and molecular features provides a good platform for new insights.
Availability: The GRASP database is available at http://apps.nhlbi.nih.gov/grasp.
Contact: johnsonad2@nhlbi.nih.gov
doi:10.1093/bioinformatics/btu273
PMCID: PMC4072913  PMID: 24931982
7.  Assessing the phenotypic effects in the general population of rare variants in genes for a dominant mendelian form of diabetes 
Nature genetics  2013;45(11):1380-1385.
Genome sequencing can identify individuals in the general population who harbor rare coding variants in genes for Mendelian disorders1–7 – and who consequently may have increased disease risk. However, previous studies of rare variants in phenotypically extreme individuals have ascertainment bias and may demonstrate inflated effect size estimates8–12. We sequenced seven genes for maturity-onset diabetes of the young (MODY)13 in well-phenotyped population samples14,15 (n=4,003). Rare variants were filtered according to prediction criteria used to identify disease-causing mutations: i) previously-reported in MODY, and ii) stringent de novo thresholds satisfied (rare, conserved, protein damaging). Approximately 1.5% and 0.5% of randomly selected Framingham and Jackson Heart Study individuals carried variants from these two classes, respectively. However, the vast majority of carriers remained euglycemic through middle age. Accurate estimates of variant effect sizes from population-based sequencing are needed to avoid falsely predicting a significant fraction of individuals as at risk for MODY or other Mendelian diseases.
doi:10.1038/ng.2794
PMCID: PMC4051627  PMID: 24097065
8.  Identification of heart rate–associated loci and their effects on cardiac conduction and rhythm disorders 
den Hoed, Marcel | Eijgelsheim, Mark | Esko, Tõnu | Brundel, Bianca J J M | Peal, David S | Evans, David M | Nolte, Ilja M | Segrè, Ayellet V | Holm, Hilma | Handsaker, Robert E | Westra, Harm-Jan | Johnson, Toby | Isaacs, Aaron | Yang, Jian | Lundby, Alicia | Zhao, Jing Hua | Kim, Young Jin | Go, Min Jin | Almgren, Peter | Bochud, Murielle | Boucher, Gabrielle | Cornelis, Marilyn C | Gudbjartsson, Daniel | Hadley, David | Van Der Harst, Pim | Hayward, Caroline | Heijer, Martin Den | Igl, Wilmar | Jackson, Anne U | Kutalik, Zoltán | Luan, Jian’an | Kemp, John P | Kristiansson, Kati | Ladenvall, Claes | Lorentzon, Mattias | Montasser, May E | Njajou, Omer T | O’Reilly, Paul F | Padmanabhan, Sandosh | Pourcain, Beate St. | Rankinen, Tuomo | Salo, Perttu | Tanaka, Toshiko | Timpson, Nicholas J | Vitart, Veronique | Waite, Lindsay | Wheeler, William | Zhang, Weihua | Draisma, Harmen H M | Feitosa, Mary F | Kerr, Kathleen F | Lind, Penelope A | Mihailov, Evelin | Onland-Moret, N Charlotte | Song, Ci | Weedon, Michael N | Xie, Weijia | Yengo, Loic | Absher, Devin | Albert, Christine M | Alonso, Alvaro | Arking, Dan E | de Bakker, Paul I W | Balkau, Beverley | Barlassina, Cristina | Benaglio, Paola | Bis, Joshua C | Bouatia-Naji, Nabila | Brage, Søren | Chanock, Stephen J | Chines, Peter S | Chung, Mina | Darbar, Dawood | Dina, Christian | Dörr, Marcus | Elliott, Paul | Felix, Stephan B | Fischer, Krista | Fuchsberger, Christian | de Geus, Eco J C | Goyette, Philippe | Gudnason, Vilmundur | Harris, Tamara B | Hartikainen, Anna-liisa | Havulinna, Aki S | Heckbert, Susan R | Hicks, Andrew A | Hofman, Albert | Holewijn, Suzanne | Hoogstra-Berends, Femke | Hottenga, Jouke-Jan | Jensen, Majken K | Johansson, Åsa | Junttila, Juhani | Kääb, Stefan | Kanon, Bart | Ketkar, Shamika | Khaw, Kay-Tee | Knowles, Joshua W | Kooner, Angrad S | Kors, Jan A | Kumari, Meena | Milani, Lili | Laiho, Päivi | Lakatta, Edward G | Langenberg, Claudia | Leusink, Maarten | Liu, Yongmei | Luben, Robert N | Lunetta, Kathryn L | Lynch, Stacey N | Markus, Marcello R P | Marques-Vidal, Pedro | Leach, Irene Mateo | McArdle, Wendy L | McCarroll, Steven A | Medland, Sarah E | Miller, Kathryn A | Montgomery, Grant W | Morrison, Alanna C | Müller-Nurasyid, Martina | Navarro, Pau | Nelis, Mari | O’Connell, Jeffrey R | ODonnell, Christopher J | Ong, Ken K | Newman, Anne B | Peters, Annette | Polasek, Ozren | Pouta, Anneli | Pramstaller, Peter P | Psaty, Bruce M | Rao, Dabeeru C | Ring, Susan M | Rossin, Elizabeth J | Rudan, Diana | Sanna, Serena | Scott, Robert A | Sehmi, Jaban S | Sharp, Stephen | Shin, Jordan T | Singleton, Andrew B | Smith, Albert V | Soranzo, Nicole | Spector, Tim D | Stewart, Chip | Stringham, Heather M | Tarasov, Kirill V | Uitterlinden, André G | Vandenput, Liesbeth | Hwang, Shih-Jen | Whitfield, John B | Wijmenga, Cisca | Wild, Sarah H | Willemsen, Gonneke | Wilson, James F | Witteman, Jacqueline C M | Wong, Andrew | Wong, Quenna | Jamshidi, Yalda | Zitting, Paavo | Boer, Jolanda M A | Boomsma, Dorret I | Borecki, Ingrid B | Van Duijn, Cornelia M | Ekelund, Ulf | Forouhi, Nita G | Froguel, Philippe | Hingorani, Aroon | Ingelsson, Erik | Kivimaki, Mika | Kronmal, Richard A | Kuh, Diana | Lind, Lars | Martin, Nicholas G | Oostra, Ben A | Pedersen, Nancy L | Quertermous, Thomas | Rotter, Jerome I | van der Schouw, Yvonne T | Verschuren, W M Monique | Walker, Mark | Albanes, Demetrius | Arnar, David O | Assimes, Themistocles L | Bandinelli, Stefania | Boehnke, Michael | de Boer, Rudolf A | Bouchard, Claude | Caulfield, W L Mark | Chambers, John C | Curhan, Gary | Cusi, Daniele | Eriksson, Johan | Ferrucci, Luigi | van Gilst, Wiek H | Glorioso, Nicola | de Graaf, Jacqueline | Groop, Leif | Gyllensten, Ulf | Hsueh, Wen-Chi | Hu, Frank B | Huikuri, Heikki V | Hunter, David J | Iribarren, Carlos | Isomaa, Bo | Jarvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kiemeney, Lambertus A | van der Klauw, Melanie M | Kooner, Jaspal S | Kraft, Peter | Iacoviello, Licia | Lehtimäki, Terho | Lokki, Marja-Liisa L | Mitchell, Braxton D | Navis, Gerjan | Nieminen, Markku S | Ohlsson, Claes | Poulter, Neil R | Qi, Lu | Raitakari, Olli T | Rimm, Eric B | Rioux, John D | Rizzi, Federica | Rudan, Igor | Salomaa, Veikko | Sever, Peter S | Shields, Denis C | Shuldiner, Alan R | Sinisalo, Juha | Stanton, Alice V | Stolk, Ronald P | Strachan, David P | Tardif, Jean-Claude | Thorsteinsdottir, Unnur | Tuomilehto, Jaako | van Veldhuisen, Dirk J | Virtamo, Jarmo | Viikari, Jorma | Vollenweider, Peter | Waeber, Gérard | Widen, Elisabeth | Cho, Yoon Shin | Olsen, Jesper V | Visscher, Peter M | Willer, Cristen | Franke, Lude | Erdmann, Jeanette | Thompson, John R | Pfeufer, Arne | Sotoodehnia, Nona | Newton-Cheh, Christopher | Ellinor, Patrick T | Stricker, Bruno H Ch | Metspalu, Andres | Perola, Markus | Beckmann, Jacques S | Smith, George Davey | Stefansson, Kari | Wareham, Nicholas J | Munroe, Patricia B | Sibon, Ody C M | Milan, David J | Snieder, Harold | Samani, Nilesh J | Loos, Ruth J F
Nature genetics  2013;45(6):621-631.
Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate–increasing and heart rate–decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.
doi:10.1038/ng.2610
PMCID: PMC3696959  PMID: 23583979
9.  Overlap Between Common Genetic Polymorphisms Underpinning Kidney Traits and Cardiovascular Disease Phenotypes: The CKDGen Consortium 
Background
Chronic kidney disease is associated with cardiovascular disease. We tested for evidence of a shared genetic basis to these traits.
Study Design
We conducted two targeted analyses. First, we examined whether known single nucleotide polymorphisms (SNPs) underpinning kidney traits were associated with a series of vascular phenotypes. Additionally, we tested whether vascular SNPs were associated with markers of kidney damage. Significance was set to 1.5 × 10-4 (0.05/325 tests).
Setting & Participants
Vascular outcomes were analyzed in participants from the AortaGen (20,634), CARDIoGRAM (86,995), CHARGE Eye (15,358), CHARGE IMT (31,181), ICBP (69,395) and NeuroCHARGE (12,385) consortia. Tests for kidney outcomes were conducted in up to 67,093 participants from the CKDGen consortium.
Predictor
We used 19 kidney SNPs and 64 vascular SNPs.
Outcomes & Measurements
Vascular outcomes tested were blood pressure, coronary artery disease, carotid intima-media thickness, pulse wave velocity, retinal venular caliber and brain white matter lesions. Kidney outcomes were estimated glomerular filtration rate and albuminuria.
Results
In general, we found that kidney disease variants were not associated with vascular phenotypes (127 of 133 tests were non-significant). The one exception was rs653178 near SH2B3 (SH2B adaptor protein 3), which showed direction-consistent association with systolic (p=9.3E-10) and diastolic (p=1.6E-14) blood pressure and coronary artery disease (p=2.2E-6), all previously reported. Similarly, the 64 SNPs associated with vascular phenotypes were not associated with kidney phenotypes (187 of 192 tests were non-significant), with the exception of 2 high-correlated SNPs at the SH2B3 locus (p=1.06E-07 and p=7.05E-08).
Limitations
Combined effect size of the SNPs for kidney and vascular outcomes may be too low to detect shared genetic associations.
Conclusions
Overall, although we confirmed one locus (SH2B3) as associated with both kidney and cardiovascular disease, our primary findings suggest that there is little overlap between kidney and cardiovascular disease risk variants in the overall population. The reciprocal risks of kidney and cardiovascular disease may not be genetically mediated, but rather a function of the disease milieu itself.
doi:10.1053/j.ajkd.2012.12.024
PMCID: PMC3660426  PMID: 23474010
10.  Gene Expression Signatures of Coronary Heart Disease 
Objective
To identify transcriptomic biomarkers of coronary heart disease (CHD) in 188 CHD cases and 188 age- and sex-matched controls who were participants in the Framingham Heart Study.
Approach and results
A total of 35 genes were differentially expressed in CHD cases vs. controls at FDR<0.5 including GZMB, TMEM56 and GUK1. Cluster analysis revealed three gene clusters associated with CHD, two linked to increased erythrocyte production and a third to reduced natural killer (NK) and T cell activity in CHD cases. Exon-level results corroborated and extended the gene-level results. Alternative splicing analysis suggested that GUK1 and 38 other genes were differentially spliced in CHD cases vs. controls. Gene ontology analysis linked ubiquitination and T-cell-related pathways with CHD.
Conclusion
Two bioinformatically defined groups of genes show consistent associations with CHD. Our findings are consistent with the hypotheses that hematopoesis is up-regulated in CHD, possibly reflecting a compensatory mechanism, and that innate immune activity is disrupted in CHD or altered by its treatment. Transcriptomic signatures may be useful in identifying pathways associated with CHD and point toward novel therapeutic targets for its treatment and prevention.
doi:10.1161/ATVBAHA.112.301169
PMCID: PMC3684247  PMID: 23539218
Gene expression; coronary heart disease; myocardial infarction; coronary artery disease; transcriptomics; biomarkers
11.  A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease 
Objective
Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD.
Approach and Results
We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified.
Conclusions
Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk.
doi:10.1161/ATVBAHA.112.300112
PMCID: PMC3752786  PMID: 23539213
Gene expression; coronary heart disease; systems biology; coexpression network
12.  Common variants in and near IRS1 and subclinical cardiovascular disease in the Framingham Heart Study 
Atherosclerosis  2013;229(1):149-154.
Objective
Common variants at the 2q36.3-IRS1 locus are associated with insulin resistance (IR), type 2 diabetes (T2D) and coronary artery disease (CAD) in large-scale association studies. We tested the hypothesis that variants at this locus are associated with subclinical atherosclerosis traits.
Methods
We studied 2740 Framingham Heart Study participants (54.9% women; mean age 57.8 years) with measures of coronary artery or abdominal aortic calcium, internal and common carotid intimamedia thickness, and ankle-brachial index (ABI). We tested 1) four SNPs previously shown to be associated with IR (rs2972146, rs2943650), T2D (rs2943641) or CAD (rs2943634) and 2) any SNP at 2q36.3-IRS1, for association with subclinical atherosclerosis traits, adjusting for atherosclerosis risk factors. We set type 1 error rate for test 1) as 0.05/5 traits = P < 0.01, and for test 2) as 0.05 divided by the effective number of independent tests, divided by 5 for the number of traits analyzed.
Results
We found no association between the four known SNPs and subclinical atherosclerosis, but identified one SNP (rs10167219, r2 with rs2943634 = 0.07) at 2q36.3 that was significantly associated with ABI (corrected P = 0.009). However, rs10167219 was not associated with ABI (P = 0.70) in 35,404 participants in a published ABI association study.
Conclusion
Common variants at the 2q36.3-IRS1 locus were not associated with subclinical atherosclerosis traits in this study which was adequately powered to find associations with moderate effect size. Although IR and T2D may be mechanistically linked to CAD via subclinical atherosclerosis, an alternate mechanism for the IR-T2D-CAD associations at 2q36.3-IRS1 must be postulated.
doi:10.1016/j.atherosclerosis.2013.03.037
PMCID: PMC4040123  PMID: 23659870
IRS1; 2q36.3; Genetic association; Subclinical atherosclerosis; Ankle-brachial index
13.  Whole Genome Sequence-Based Analysis of a Model Complex Trait, High Density Lipoprotein Cholesterol 
Nature genetics  2013;45(8):899-901.
We describe initial steps for interrogating whole genome sequence (WGS) data to characterize the genetic architecture of a complex trait, such as high density lipoprotein cholesterol (HDL-C). We estimate that common variation contributes more to HDL-C heritability than rare variation, and screening for Mendelian dyslipidemia variants identified individuals with extreme HDL-C. WGS analyses highlight the value of regulatory and non-protein coding regions of the genome in addition to protein coding regions.
doi:10.1038/ng.2671
PMCID: PMC4030301  PMID: 23770607
14.  Genetic variation associated with circulating monocyte count in the eMERGE Network 
Human Molecular Genetics  2013;22(10):2119-2127.
With white blood cell count emerging as an important risk factor for chronic inflammatory diseases, genetic associations of differential leukocyte types, specifically monocyte count, are providing novel candidate genes and pathways to further investigate. Circulating monocytes play a critical role in vascular diseases such as in the formation of atherosclerotic plaque. We performed a joint and ancestry-stratified genome-wide association analyses to identify variants specifically associated with monocyte count in 11 014 subjects in the electronic Medical Records and Genomics Network. In the joint and European ancestry samples, we identified novel associations in the chromosome 16 interferon regulatory factor 8 (IRF8) gene (P-value = 2.78×10(−16), β = −0.22). Other monocyte associations include novel missense variants in the chemokine-binding protein 2 (CCBP2) gene (P-value = 1.88×10(−7), β = 0.30) and a region of replication found in ribophorin I (RPN1) (P-value = 2.63×10(−16), β = −0.23) on chromosome 3. The CCBP2 and RPN1 region is located near GATA binding protein2 gene that has been previously shown to be associated with coronary heart disease. On chromosome 9, we found a novel association in the prostaglandin reductase 1 gene (P-value = 2.29×10(−7), β = 0.16), which is downstream from lysophosphatidic acid receptor 1. This region has previously been shown to be associated with monocyte count. We also replicated monocyte associations of genome-wide significance (P-value = 5.68×10(−17), β = −0.23) at the integrin, alpha 4 gene on chromosome 2. The novel IRF8 results and further replications provide supporting evidence of genetic regions associated with monocyte count.
doi:10.1093/hmg/ddt010
PMCID: PMC3633369  PMID: 23314186
15.  Relations of Long-Term and Contemporary Lipid Levels and Lipid Genetic Risk Scores with Coronary Artery Calcium in the Framingham Heart Study 
Objectives
This study evaluated the association of timing of lipid levels and lipid genetic risk score (GRS) with subclinical atherosclerosis.
Background
Atherosclerosis is a slowly progressive disorder influenced by suboptimal lipid levels. Long-term versus contemporary lipid levels may more strongly impact the development of coronary artery calcium (CAC).
Methods
Framingham Heart Study (FHS) Offspring Cohort participants (n=1156, 44%M, 63±9 years) underwent serial fasting lipids [low-density lipoprotein (LDL-C), high-density lipoprotein, and triglycerides], Exam 1 (1971–1975) – Exam 7 (1998–2001). FHS Third Generation Cohort participants (n=1954, 55%M, 45±6 years) had fasting lipid profiles assessed, 2002–2005. Computed tomography (2002–2005) measured CAC. Lipid GRSs were computed from significantly associated single nucleotide polymorphisms. The association between early, long-term average, and contemporary lipids, and lipid GRS, with elevated CAC was assessed using logistic regression.
Results
In FHS Offspring, Exam 1 and long-term average versus Exam 7 lipid measurements, including untreated lipid levels, were strongly associated with elevated CAC. In the FHS Third Generation, contemporary lipids were associated with CAC. The LDL-C GRS was associated with CAC (age/sex-adjusted OR 1.14, 95%CI 1.00–1.29, p=0.04). However, addition of the GRS to the lipid models did not result in a significant increase in the OR or C-statistic for any lipid measure.
Conclusions
Early and long-term average lipid levels, as compared with contemporary measures, are more strongly associated with elevated CAC. Lipid GRS was associated with lipid levels but did not predict elevated CAC. Adult early and long-term average lipid levels provide important information when assessing subclinical atherosclerosis and cardiovascular risk.
doi:10.1016/j.jacc.2012.09.007
PMCID: PMC3702262  PMID: 23141485
Lipids; Genetic risk score; Coronary artery calcium
16.  A Genome-Wide Association Study of the Human Metabolome in a Community-Based Cohort 
Cell metabolism  2013;18(1):130-143.
SUMMARY
Because metabolites are hypothesized to play key roles as markers and effectors of cardio-metabolic diseases, recent studies have sought to annotate the genetic determinants of circulating metabolite levels. We report a genome-wide association study (GWAS) of 217 plasma metabolites, including >100 not measured in prior GWAS, in 2,076 participants of the Framingham Heart Study. For the majority of analytes, we find that estimated heritability explains >20% of inter-individual variation, and that variation attributable to heritable factors is greater than that attributable to clinical factors. Further, we identify 31 genetic loci associated with plasma metabolites, including 23 that have not previously been reported. Importantly, we include GWAS results for all surveyed metabolites, and demonstrate how this information highlights a role for AGXT2 in cholesterol ester and triacylglycerol metabolism. Thus, our study outlines the relative contributions of inherited and clinical factors on the plasma metabolome and provides a resource for metabolism research.
doi:10.1016/j.cmet.2013.06.013
PMCID: PMC3973158  PMID: 23823483
17.  Identification of Nine Novel Loci Associated with White Blood Cell Subtypes in a Japanese Population 
PLoS Genetics  2011;7(6):e1002067.
White blood cells (WBCs) mediate immune systems and consist of various subtypes with distinct roles. Elucidation of the mechanism that regulates the counts of the WBC subtypes would provide useful insights into both the etiology of the immune system and disease pathogenesis. In this study, we report results of genome-wide association studies (GWAS) and a replication study for the counts of the 5 main WBC subtypes (neutrophils, lymphocytes, monocytes, basophils, and eosinophils) using 14,792 Japanese subjects enrolled in the BioBank Japan Project. We identified 12 significantly associated loci that satisfied the genome-wide significance threshold of P<5.0×10−8, of which 9 loci were novel (the CDK6 locus for the neutrophil count; the ITGA4, MLZE, STXBP6 loci, and the MHC region for the monocyte count; the SLC45A3-NUCKS1, GATA2, NAALAD2, ERG loci for the basophil count). We further evaluated associations in the identified loci using 15,600 subjects from Caucasian populations. These WBC subtype-related loci demonstrated a variety of patterns of pleiotropic associations within the WBC subtypes, or with total WBC count, platelet count, or red blood cell-related traits (n = 30,454), which suggests unique and common functional roles of these loci in the processes of hematopoiesis. This study should contribute to the understanding of the genetic backgrounds of the WBC subtypes and hematological traits.
Author Summary
White blood cells (WBCs) are blood cells that mediate immune systems and defend the body against foreign microorganisms. It is well known that WBCs consist of various subtypes of cells with distinct roles, although the genetic background of each of the WBC subtypes has yet to be examined. In this study, we report genome-wide association studies (GWAS) for the 5 main WBC subtypes (neutrophils, lymphocytes, monocytes, basophils, and eosinophils) using 14,792 Japanese subjects. We identified 12 significantly associated genetic loci, and 9 of them were novel. Evaluation of the associations of these identified loci in cohorts of Caucasian populations demonstrated both ethnically common and divergent genetic backgrounds of the WBC subtypes. These loci also indicated a variety of patterns of pleiotropic associations within the hematological traits, including the other WBC subtypes, total WBC count, platelet count, or red blood cell-related traits, which suggests unique and common functional roles of these loci in the processes of hematopoiesis.
doi:10.1371/journal.pgen.1002067
PMCID: PMC3128095  PMID: 21738478
18.  Prevalence and Distribution of Abdominal Aortic Calcium by Sex and Age-Group in a Community-based Cohort (From The Framingham Heart Study) 
The American journal of cardiology  2012;110(6):891-896.
Abdominal aortic calcium (AAC) is associated with incident cardiovascular disease but the age and sex-related distribution of AAC in a community-dwelling population free of standard cardiovascular disease risk factors has not been described. A total of 3285 participants (aged 50.2±9.9 years) in the Framingham Heart Study Offspring and Third Generation cohorts underwent abdominal multidetector computed tomography (MDCT) scanning during 1998-2005. The presence and amount of AAC was quantified (Agatston score) by an experienced reader using standardized criteria. A healthy referent subsample (N=1656, 803 men) free of hypertension, hyperlipidemia, diabetes, obesity and smoking was identified, and participants were stratified by sex and age group (<45, 45-54, 55-64, 65-74, ≥75 years). The prevalence and burden of AAC increased monotonically and supralinearly with age in both sexes but was greater in men than women in each age group. Below age 45 <16% of referent-subsample participants had any quantifiable AAC, while above age 65 nearly 90% of referent participants had >0 AAC. Across the entire study sample, AAC prevalence and burden similarly increased with greater age. Defining the 90th percentile of referent group AAC as “high,” the prevalence of high AAC was 19% for each sex in the overall study sample. AAC also increased across categories of 10-year coronary heart disease risk, as calculated using the Framingham Risk Score, in the entire study sample. We found AAC to be widely prevalent, with the burden of AAC associated with 10-year coronary risk, in a white, free-living adult cohort.
doi:10.1016/j.amjcard.2012.05.020
PMCID: PMC3432173  PMID: 22727181
atherosclerosis; aorta; calcification; computed tomography; epidemiology
20.  Resequencing and clinical associations of the 9p21.3 region: a comprehensive investigation in the Framingham Heart Study 
Circulation  2013;127(7):799-810.
Background
9p21.3 is among the most strongly replicated regions for cardiovascular disease (CVD). There are few reports of sequencing the associated 9p21.3 interval. We set out to sequence the 9p21.3 region followed by a comprehensive study of genetic associations with clinical and subclinical CVD and its risk factors, and with copy number variation and gene expression, in the Framingham Heart Study (FHS).
Methods and Results
We sequenced 281 individuals (n=94 with myocardial infarction, n=94 with high coronary artery calcium levels, and n=93controls free of elevated coronary artery calcium or myocardial infarction) followed by genotyping and association in >7,000 additional FHS individuals. We assessed genetic associations with clinical and subclinical CVD, risk factor phenotypes, and gene expression levels of protein-coding genes CDKN2A and CDKN2B as well as the non-coding gene ANRIL in freshly harvested leukocytes and platelets. Within this large sample we found strong associations of 9p21.3 variants with increased risk for myocardial infarction, higher coronary artery calcium levels, and larger abdominal aorta diameters, and no evidence for association with traditional CVD risk factors. No common protein-coding variation, variants in splice donor or acceptor sites, or CNV events were observed. By contrast, strong associations were observed between genetic variants and gene expression, particularly for a short isoform of ANRIL and for CDKN2B.
Conclusions
Our thorough genomic characterization of 9p21.3 suggests common variants likely account for observed disease associations, and provide further support for the hypothesis that complex regulatory variation affecting ANRIL and CDKN2B gene expression may contribute to increased risk for clinically apparent and subclinical coronary artery disease and aortic disease.
doi:10.1161/CIRCULATIONAHA.112.111559
PMCID: PMC3686634  PMID: 23315372
genetics; myocardial infarction; risk factors; atherosclerosis; calcium
21.  Atherosclerotic Biomarkers and Aortic Atherosclerosis by Cardiovascular Magnetic Resonance Imaging in the Framingham Heart Study 
Background
The relations between subclinical atherosclerosis and inflammatory biomarkers have generated intense interest but their significance remains unclear. We sought to determine the association between a panel of biomarkers and subclinical aortic atherosclerosis in a community‐based cohort.
Methods and Results
We evaluated 1547 participants of the Framingham Heart Study Offspring cohort who attended the 7th examination cycle and underwent both cardiovascular magnetic resonance imaging (CMR) and assays for 10 biomarkers associated with atherosclerosis: high‐sensitivity C‐reactive protein, fibrinogen, intercellular adhesion molecule‐1, interleukin‐6, interleukin‐18, lipoprotein‐associated phospholipase‐A2 activity and mass, monocyte chemoattractant protein‐1, P‐selectin, and tumor necrosis factor receptor‐2. In logistic regression analysis, we found no significant association between the biomarker panel and the presence of aortic plaque (global P=0.53). Using Tobit regression with aortic plaque as a continuous variable, we noted a modest association between biomarker panel and aortic plaque volume in age‐ and sex‐adjusted analyses (P=0.003). However, this association was attenuated after further adjustment for clinical covariates (P=0.09).
Conclusions
In our community‐based cohort, we found no significant association between our multibiomarker panel and aortic plaque. Our results underscore the strengths and limitations of the use of biomarkers for the identification of subclinical atherosclerosis and the importance of traditional risk factors.
doi:10.1161/JAHA.113.000307
PMCID: PMC3886740  PMID: 24242683
aorta; atherosclerosis; biomarkers; cardiovascular magnetic resonance imaging
23.  Development and Application of a Longitudinal ECG Repository: the Framingham Heart Study 
Journal of electrocardiology  2012;45(6):673-676.
The electrocardiogram (ECG) has wide-spread use in clinical care and research. Despite its extensive use and study, important gaps remain in examining prospective, repeated longitudinal ECG measures and their association with cardiovascular outcomes. The Framingham Heart Study (FHS) is a community-based study designed to examine risk factors and outcomes associated with cardiovascular disease. Here we describe a novel effort in the FHS to develop a unique resource: serial ECGs conducted on three generations of study participants spanning multiple decades (1986 to the present). We describe the FHS and the role the ECG has had in conducting cardiovascular epidemiology in the FHS. We then describe potential applications for a longitudinal ECG repository. We expect the Framingham ECG repository to enhance cardiovascular research and epidemiologic study. Such a resource will complement the FHS’ phenotypic and genotypic characterization, facilitating novel investigations of cardiovascular epidemiology.
doi:10.1016/j.jelectrocard.2012.06.016
PMCID: PMC3483375  PMID: 22832152
electrocardiography; epidemiology; repository; Framingham
24.  Left Ventricular Trabeculae and Papillary Muscles: Correlation With Clinical and Cardiac Characteristics and Impact on Cardiovascular Magnetic Resonance Measures of Left Ventricular Anatomy and Function 
JACC. Cardiovascular imaging  2012;5(11):1115-1123.
Objective
We sought to assess the relationship of left ventricular (LV) trabeculae and papillary muscles (TPM) with clinical characteristics in a community-based, free living adult cohort and to determine the effect of TPM on quantitative measures of LV volume, mass and ejection fraction (EF).
Background
Hypertrabeculation has been associated with adverse cardiovascular events, but the distribution and clinical correlates of the volume and mass of the TPM in a normal left ventricle have not been well characterized.
Methods
Short-axis cine cardiovascular magnetic resonance (CMR) images, obtained using a steady-state free precession sequence, from 1494 members of the Framingham Offspring cohort were analyzed using software that automatically segments TPM. Absolute TPM volume, TPM as a fraction of end-diastolic volume (TPM/EDV), and TPM mass as a fraction of LV mass (TPMm/LVM) were determined on all Offspring and in a referent group of Offspring free of clinical cardiovascular disease and hypertension.
Results
In the referent group (aged 61±9 years, with 262 men and 423 women) TPM was 23±3 % of LV EDV in both sexes (p=0.9). TPM/EDV decreased with age (p<0.02) but was not associated with body mass index (BMI). TPMm/LVM was inversely correlated with age (p<0.0001), BMI (p<0.018) and systolic blood pressure (p<0.0001). Among all 1494 participants (699 men) LV volumes decreased 23%, LV mass increased 28% and EF increased by 7.5 EF units (p<0.0001) when TPM were considered myocardial mass rather than part of the LV blood pool.
Conclusions
Global CMR LV parameters are significantly affected by whether TPM are considered as part of the LV blood pool or as part of LV mass. Our cross-sectional data from a healthy referent group of adults free of clinical cardiovascular disease demonstrate that TPM/EDV decreases with increasing age in both sexes, but is not related to hypertension or obesity.
doi:10.1016/j.jcmg.2012.05.015
PMCID: PMC3502069  PMID: 23153911
magnetic resonance imaging; population study; trabeculae; papillary muscle; left ventricular ejection fraction
25.  A Genetic Risk Score is Associated with Incident Cardiovascular Disease and Coronary Artery Calcium - The Framingham Heart Study 
Background
Limited data exist regarding the use of a genetic risk score for predicting risk of incident cardiovascular disease (CVD) in US based samples.
Methods and Results
Using findings from recent GWAS, we constructed genetic risk scores (GRS) comprised of 13 genetic variants associated with myocardial infarction (MI) or other manifestations of CHD and 102 genetic variants associated with CHD or its major risk factors. We also updated the 13 SNP GRS with 16 SNPs recently discovered by GWAS. We estimated the association, discrimination and risk reclassification of each GRS for incident cardiovascular events and for prevalent coronary artery calcium (CAC).
In analyses adjusted for age, sex, CVD risk factors and parental history of CVD, the 13 SNP GRS was significantly associated with incident hard CHD (HR 1.07, 95% CI 1.00-1.15, p=0.04), CVD (hazard ratio [HR] per-allele 1.05, 95% confidence interval [CI] 1.01-1.09; p=0.03), and high CAC (defined as >75th age and sex-specific percentile; odds ratio [OR] per-allele 1.18, 95% CI 1.11-1.26, p=3.4 × 10-7). The GRS did not improve discrimination for incident CHD or CVD but led to modest improvements in risk reclassification. However, significant improvements in discrimination and risk reclassification were observed for the prediction of high CAC. The addition of 16 newly discovered SNPs to the 13 SNP GRS did not significantly modify these results.
Conclusions
A GRS comprised of 13 SNPs associated with coronary disease is an independent predictor of cardiovascular events and of high CAC, modestly improves risk reclassification for incident CHD and significant improves discrimination for high CAC. The addition of recently discovered SNPs did not significantly improve the performance of this GRS.
doi:10.1161/CIRCGENETICS.111.961342
PMCID: PMC3292865  PMID: 22235037
Genetics; single nucleotide polymorphisms; cardiovascular disease; coronary heart disease; risk prediction; reclassification

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