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1.  Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization 
Arking, Dan E. | Pulit, Sara L. | Crotti, Lia | van der Harst, Pim | Munroe, Patricia B. | Koopmann, Tamara T. | Sotoodehnia, Nona | Rossin, Elizabeth J. | Morley, Michael | Wang, Xinchen | Johnson, Andrew D. | Lundby, Alicia | Gudbjartsson, Daníel F. | Noseworthy, Peter A. | Eijgelsheim, Mark | Bradford, Yuki | Tarasov, Kirill V. | Dörr, Marcus | Müller-Nurasyid, Martina | Lahtinen, Annukka M. | Nolte, Ilja M. | Smith, Albert Vernon | Bis, Joshua C. | Isaacs, Aaron | Newhouse, Stephen J. | Evans, Daniel S. | Post, Wendy S. | Waggott, Daryl | Lyytikäinen, Leo-Pekka | Hicks, Andrew A. | Eisele, Lewin | Ellinghaus, David | Hayward, Caroline | Navarro, Pau | Ulivi, Sheila | Tanaka, Toshiko | Tester, David J. | Chatel, Stéphanie | Gustafsson, Stefan | Kumari, Meena | Morris, Richard W. | Naluai, Åsa T. | Padmanabhan, Sandosh | Kluttig, Alexander | Strohmer, Bernhard | Panayiotou, Andrie G. | Torres, Maria | Knoflach, Michael | Hubacek, Jaroslav A. | Slowikowski, Kamil | Raychaudhuri, Soumya | Kumar, Runjun D. | Harris, Tamara B. | Launer, Lenore J. | Shuldiner, Alan R. | Alonso, Alvaro | Bader, Joel S. | Ehret, Georg | Huang, Hailiang | Kao, W.H. Linda | Strait, James B. | Macfarlane, Peter W. | Brown, Morris | Caulfield, Mark J. | Samani, Nilesh J. | Kronenberg, Florian | Willeit, Johann | Smith, J. Gustav | Greiser, Karin H. | zu Schwabedissen, Henriette Meyer | Werdan, Karl | Carella, Massimo | Zelante, Leopoldo | Heckbert, Susan R. | Psaty, Bruce M. | Rotter, Jerome I. | Kolcic, Ivana | Polašek, Ozren | Wright, Alan F. | Griffin, Maura | Daly, Mark J. | Arnar, David O. | Hólm, Hilma | Thorsteinsdottir, Unnur | Denny, Joshua C. | Roden, Dan M. | Zuvich, Rebecca L. | Emilsson, Valur | Plump, Andrew S. | Larson, Martin G. | O'Donnell, Christopher J. | Yin, Xiaoyan | Bobbo, Marco | D'Adamo, Adamo P. | Iorio, Annamaria | Sinagra, Gianfranco | Carracedo, Angel | Cummings, Steven R. | Nalls, Michael A. | Jula, Antti | Kontula, Kimmo K. | Marjamaa, Annukka | Oikarinen, Lasse | Perola, Markus | Porthan, Kimmo | Erbel, Raimund | Hoffmann, Per | Jöckel, Karl-Heinz | Kälsch, Hagen | Nöthen, Markus M. | consortium, HRGEN | den Hoed, Marcel | Loos, Ruth J.F. | Thelle, Dag S. | Gieger, Christian | Meitinger, Thomas | Perz, Siegfried | Peters, Annette | Prucha, Hanna | Sinner, Moritz F. | Waldenberger, Melanie | de Boer, Rudolf A. | Franke, Lude | van der Vleuten, Pieter A. | Beckmann, Britt Maria | Martens, Eimo | Bardai, Abdennasser | Hofman, Nynke | Wilde, Arthur A.M. | Behr, Elijah R. | Dalageorgou, Chrysoula | Giudicessi, John R. | Medeiros-Domingo, Argelia | Barc, Julien | Kyndt, Florence | Probst, Vincent | Ghidoni, Alice | Insolia, Roberto | Hamilton, Robert M. | Scherer, Stephen W. | Brandimarto, Jeffrey | Margulies, Kenneth | Moravec, Christine E. | Fabiola Del, Greco M. | Fuchsberger, Christian | O'Connell, Jeffrey R. | Lee, Wai K. | Watt, Graham C.M. | Campbell, Harry | Wild, Sarah H. | El Mokhtari, Nour E. | Frey, Norbert | Asselbergs, Folkert W. | Leach, Irene Mateo | Navis, Gerjan | van den Berg, Maarten P. | van Veldhuisen, Dirk J. | Kellis, Manolis | Krijthe, Bouwe P. | Franco, Oscar H. | Hofman, Albert | Kors, Jan A. | Uitterlinden, André G. | Witteman, Jacqueline C.M. | Kedenko, Lyudmyla | Lamina, Claudia | Oostra, Ben A. | Abecasis, Gonçalo R. | Lakatta, Edward G. | Mulas, Antonella | Orrú, Marco | Schlessinger, David | Uda, Manuela | Markus, Marcello R.P. | Völker, Uwe | Snieder, Harold | Spector, Timothy D. | Ärnlöv, Johan | Lind, Lars | Sundström, Johan | Syvänen, Ann-Christine | Kivimaki, Mika | Kähönen, Mika | Mononen, Nina | Raitakari, Olli T. | Viikari, Jorma S. | Adamkova, Vera | Kiechl, Stefan | Brion, Maria | Nicolaides, Andrew N. | Paulweber, Bernhard | Haerting, Johannes | Dominiczak, Anna F. | Nyberg, Fredrik | Whincup, Peter H. | Hingorani, Aroon | Schott, Jean-Jacques | Bezzina, Connie R. | Ingelsson, Erik | Ferrucci, Luigi | Gasparini, Paolo | Wilson, James F. | Rudan, Igor | Franke, Andre | Mühleisen, Thomas W. | Pramstaller, Peter P. | Lehtimäki, Terho J. | Paterson, Andrew D. | Parsa, Afshin | Liu, Yongmei | van Duijn, Cornelia | Siscovick, David S. | Gudnason, Vilmundur | Jamshidi, Yalda | Salomaa, Veikko | Felix, Stephan B. | Sanna, Serena | Ritchie, Marylyn D. | Stricker, Bruno H. | Stefansson, Kari | Boyer, Laurie A. | Cappola, Thomas P. | Olsen, Jesper V. | Lage, Kasper | Schwartz, Peter J. | Kääb, Stefan | Chakravarti, Aravinda | Ackerman, Michael J. | Pfeufer, Arne | de Bakker, Paul I.W. | Newton-Cheh, Christopher
Nature genetics  2014;46(8):826-836.
The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal Mendelian Long QT Syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals we identified 35 common variant QT interval loci, that collectively explain ∼8-10% of QT variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 novel QT loci in 298 unrelated LQTS probands identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode for proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies novel candidate genes for ventricular arrhythmias, LQTS,and SCD.
doi:10.1038/ng.3014
PMCID: PMC4124521  PMID: 24952745
genome-wide association study; QT interval; Long QT Syndrome; sudden cardiac death; myocardial repolarization; arrhythmias
2.  The association of statin use with reduced incidence of venous thromboembolism: a population-based cohort study 
BMJ Open  2014;4(11):e005862.
Objectives
Venous thromboembolism (VTE) continues to be a frequent medical emergency requiring rapid recognition so as to reach diagnosis and initiate anticoagulation therapy. The use of statins in addition to reducing the incidence of arterial thrombosis for decreasing the incidence and reoccurrence of VTE is reported. The aim of our study was to explore the association between statin usage and the incidence of new VTE at the population level during a 10-year follow-up.
Design
Population-based historic cohort.
Setting
The Health 2000 Survey was based on a nationally representative sample.
Participants
8028 individuals aged 30 years or over in Finland.
Primary and secondary outcome measures
The primary end point event was the first ever hospitalisation due to one of the following causes: pulmonary embolism (International Classification of Diseases-10 I26), cerebral venous non-pyogenic thrombosis (I63.6), or venous thrombosis (I80.9–189).
Results
The preselected explanatory variables applied to the Poisson regression model were statin usage (no/yes) during follow-up (2000–2011) and several baseline data (age, sex; usage of blood glucose lowering drugs, vitamin K antagonists and antiplatelet agents). We observed 136 VTE events, the incidence of 1.72 (95% CI 1.44 to 2.04) per 1000 person-years. Current statin usage did not associate with the incidence of VTE according to the univariate model (rate ratio (RR) 0.93, 0.56 to 1.52), but when adjusted with baseline variables (age, sex, medications) the RR declined to 0.60 (0.36 to 1.00, p=0.04).
Conclusions
Statin use offers protection against first ever VTE events and appears as a primary prevention tool in patients without anticoagulation or antiplatelet medication.
doi:10.1136/bmjopen-2014-005862
PMCID: PMC4225235  PMID: 25377011
EPIDEMIOLOGY
3.  Infancy-Onset Dietary Counseling of Low-Saturated-Fat Diet Improves Insulin Sensitivity in Healthy Adolescents 15–20 Years of Age 
Diabetes Care  2013;36(10):2952-2959.
OBJECTIVE
We reported previously that low-saturated-fat dietary counseling started in infancy improves insulin sensitivity in healthy children 9 years of age. The aim of this study was to evaluate the effect of lifelong dietary counseling on insulin sensitivity in healthy adolescents between 15 and 20 years of age. In addition, we examined dietary fiber intake and the polyunsaturated fatty acid (PUFA) + monounsaturated (MUFA)-to-saturated fatty acid (SFA) ratio in the intervention and control adolescents and the association of these dietary factors with homeostasis model of insulin resistance (HOMA-IR).
RESEARCH DESIGN AND METHODS
The study comprised adolescents participating in the randomized, controlled Special Turku Coronary Risk Factor Intervention Project (STRIP) study, which aims to guide the study participants toward a diet beneficial for cardiovascular health. HOMA-IR was assessed annually between 15 and 20 years of age (n = 518; intervention, n = 245; control, n = 273), along with diet, BMI, pubertal status, serum cotinine concentrations, and physical activity. Dietary counseling was given biannually during the follow-up.
RESULTS
HOMA-IR was lower (7.5% on average) in the intervention group than in the control group between 15 and 20 years of age (P = 0.0051). The intervention effect was similar in girls and boys. The PUFA+MUFA-to-SFA ratio was higher (P < 0.0001) and the dietary fiber (g/MJ) intake was higher (P = 0.0058) in the intervention group compared with the control group. There was no association between the PUFA+MUFA-to-/SFA ratio and HOMA-IR, whereas dietary fiber intake (g/MJ) was associated with HOMA-IR in girls (P < 0.0001).
CONCLUSIONS
Dietary counseling initiated in infancy and maintained until 20 years of age was associated with improved insulin sensitivity in adolescents.
doi:10.2337/dc13-0361
PMCID: PMC3781523  PMID: 23801725
4.  Recruitment and Baseline Characteristics of Participants in the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER)—A Randomized Controlled Lifestyle Trial † 
Our aim is to describe the study recruitment and baseline characteristics of the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) study population. Potential study participants (age 60–77 years, the dementia risk score ≥6) were identified from previous population-based survey cohorts and invited to the screening visit. To be eligible, cognitive performance measured at the screening visit had to be at the mean level or slightly lower than expected for age. Of those invited (n = 5496), 48% (n = 2654) attended the screening visit, and finally 1260 eligible participants were randomized to the intervention and control groups (1:1). The screening visit non-attendees were slightly older, less educated, and had more vascular risk factors and diseases present. The mean (SD) age of the randomized participants was 69.4 (4.7) years, Mini-Mental State Examination 26.7 (2.0) points, systolic blood pressure 140.1 (16.2) mmHg, total serum cholesterol 5.2 (1.0) mmol/L for, and fasting glucose 6.1 (0.9) mmol/L for, with no difference between intervention and control groups. Several modifiable risk factors were present at baseline indicating an opportunity for the intervention. The FINGER study will provide important information on the effect of lifestyle intervention to prevent cognitive impairment among at risk persons.
doi:10.3390/ijerph110909345
PMCID: PMC4199023  PMID: 25211775
cognitive impairment; dementia; Alzheimer’s disease; lifestyle; intervention; randomized controlled trial
5.  Arterial Blood Pressure and Long-Term Exposure to Traffic-Related Air Pollution: An Analysis in the European Study of Cohorts for Air Pollution Effects (ESCAPE) 
Environmental Health Perspectives  2014;122(9):896-905.
Background: Long-term exposure to air pollution has been hypothesized to elevate arterial blood pressure (BP). The existing evidence is scarce and country specific.
Objectives: We investigated the cross-sectional association of long-term traffic-related air pollution with BP and prevalent hypertension in European populations.
Methods: We analyzed 15 population-based cohorts, participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE). We modeled residential exposure to particulate matter and nitrogen oxides with land use regression using a uniform protocol. We assessed traffic exposure with traffic indicator variables. We analyzed systolic and diastolic BP in participants medicated and nonmedicated with BP-lowering medication (BPLM) separately, adjusting for personal and area-level risk factors and environmental noise. Prevalent hypertension was defined as ≥ 140 mmHg systolic BP, or ≥ 90 mmHg diastolic BP, or intake of BPLM. We combined cohort-specific results using random-effects meta-analysis.
Results: In the main meta-analysis of 113,926 participants, traffic load on major roads within 100 m of the residence was associated with increased systolic and diastolic BP in nonmedicated participants [0.35 mmHg (95% CI: 0.02, 0.68) and 0.22 mmHg (95% CI: 0.04, 0.40) per 4,000,000 vehicles × m/day, respectively]. The estimated odds ratio (OR) for prevalent hypertension was 1.05 (95% CI: 0.99, 1.11) per 4,000,000 vehicles × m/day. Modeled air pollutants and BP were not clearly associated.
Conclusions: In this first comprehensive meta-analysis of European population-based cohorts, we observed a weak positive association of high residential traffic exposure with BP in nonmedicated participants, and an elevated OR for prevalent hypertension. The relationship of modeled air pollutants with BP was inconsistent.
Citation: Fuks KB, Weinmayr G, Foraster M, Dratva J, Hampel R, Houthuijs D, Oftedal B, Oudin A, Panasevich S, Penell J, Sommar JN, Sørensen M, Tittanen P, Wolf K, Xun WW, Aguilera I, Basagaña X, Beelen R, Bots ML, Brunekreef B, Bueno-de-Mesquita HB, Caracciolo B, Cirach M, de Faire U, de Nazelle A, Eeftens M, Elosua R, Erbel R, Forsberg B, Fratiglioni L, Gaspoz JM, Hilding A, Jula A, Korek M, Krämer U, Künzli N, Lanki T, Leander K, Magnusson PK, Marrugat J, Nieuwenhuijsen MJ, Östenson CG, Pedersen NL, Pershagen G, Phuleria HC, Probst-Hensch NM, Raaschou-Nielsen O, Schaffner E, Schikowski T, Schindler C, Schwarze PE, Søgaard AJ, Sugiri D, Swart WJ, Tsai MY, Turunen AW, Vineis P, Peters A, Hoffmann B. 2014. Arterial blood pressure and long-term exposure to traffic-related air pollution: an analysis in the European Study of Cohorts for Air Pollution Effects (ESCAPE). Environ Health Perspect 122:896–905; http://dx.doi.org/10.1289/ehp.1307725
doi:10.1289/ehp.1307725
PMCID: PMC4154218  PMID: 24835507
6.  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 | O’Donnell, 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
7.  A blood pressure genetic risk score is a significant predictor of incident cardiovascular events in 32,669 individuals 
Hypertension  2013;61(5):987-994.
Recent genome-wide association studies (GWASs) have identified genetic variants associated with blood pressure (BP). We investigated whether genetic risk scores (GRSs) constructed of these variants would predict incident cardiovascular disease (CVD) events. We genotyped 32 common single nucleotide polymorphisms (SNPs) in several Finnish cohorts, with up to 32,669 individuals after exclusion of prevalent CVD cases. The median follow-up was 9.8 years, during which 2,295 incident CVD events occurred. We created GRSs separately for systolic (SBP) and diastolic BP (DBP) by multiplying the risk allele count of each SNP by the effect size estimated in published GWASs. We performed Cox regression analyses with and without adjustment for clinical factors including BP at baseline in each cohort. The results were combined by inverse variance-weighted fixed-effects meta-analysis. The GRSs were strongly associated with SBP and DBP and baseline hypertension (all p<10−62). Hazard ratios comparing the highest quintiles of SBP and DBP genetic risk scores with the lowest quintiles after adjustment for age, age squared and sex, were 1.25 (1.07–1.46, p = 0.006) and 1.23 (1.05–1.43, p = 0.01), respectively, for incident coronary heart disease; 1.24 (1.01–1.53, p = 0.04) and 1.35 (1.09–1.66, p = 0.005) for incident stroke; and 1.23 (1.08–1.40, p = 2×10−6) and 1.26 (1.11–1.44, p = 5×10−4) for composite CVD. In conclusion, BP findings from GWASs are strongly replicated. GRSs comprised of bona fide BP SNPs predicted cardiovascular disease risk, consistent with a life-long effect on BP of these variants collectively.
doi:10.1161/HYPERTENSIONAHA.111.00649
PMCID: PMC3648219  PMID: 23509078
Hypertension; blood pressure; genetics; cardiovascular disease; prospective cohort study; genetic risk score
8.  Discovery and Refinement of Loci Associated with Lipid Levels 
Willer, Cristen J. | Schmidt, Ellen M. | Sengupta, Sebanti | Peloso, Gina M. | Gustafsson, Stefan | Kanoni, Stavroula | Ganna, Andrea | Chen, Jin | Buchkovich, Martin L. | Mora, Samia | Beckmann, Jacques S. | Bragg-Gresham, Jennifer L. | Chang, Hsing-Yi | Demirkan, Ayşe | Den Hertog, Heleen M. | Do, Ron | Donnelly, Louise A. | Ehret, Georg B. | Esko, Tõnu | Feitosa, Mary F. | Ferreira, Teresa | Fischer, Krista | Fontanillas, Pierre | Fraser, Ross M. | Freitag, Daniel F. | Gurdasani, Deepti | Heikkilä, Kauko | Hyppönen, Elina | Isaacs, Aaron | Jackson, Anne U. | Johansson, Åsa | Johnson, Toby | Kaakinen, Marika | Kettunen, Johannes | Kleber, Marcus E. | Li, Xiaohui | Luan, Jian’an | Lyytikäinen, Leo-Pekka | Magnusson, Patrik K.E. | Mangino, Massimo | Mihailov, Evelin | Montasser, May E. | Müller-Nurasyid, Martina | Nolte, Ilja M. | O’Connell, Jeffrey R. | Palmer, Cameron D. | Perola, Markus | Petersen, Ann-Kristin | Sanna, Serena | Saxena, Richa | Service, Susan K. | Shah, Sonia | Shungin, Dmitry | Sidore, Carlo | Song, Ci | Strawbridge, Rona J. | Surakka, Ida | Tanaka, Toshiko | Teslovich, Tanya M. | Thorleifsson, Gudmar | Van den Herik, Evita G. | Voight, Benjamin F. | Volcik, Kelly A. | Waite, Lindsay L. | Wong, Andrew | Wu, Ying | Zhang, Weihua | Absher, Devin | Asiki, Gershim | Barroso, Inês | Been, Latonya F. | Bolton, Jennifer L. | Bonnycastle, Lori L | Brambilla, Paolo | Burnett, Mary S. | Cesana, Giancarlo | Dimitriou, Maria | Doney, Alex S.F. | Döring, Angela | Elliott, Paul | Epstein, Stephen E. | Ingi Eyjolfsson, Gudmundur | Gigante, Bruna | Goodarzi, Mark O. | Grallert, Harald | Gravito, Martha L. | Groves, Christopher J. | Hallmans, Göran | Hartikainen, Anna-Liisa | Hayward, Caroline | Hernandez, Dena | Hicks, Andrew A. | Holm, Hilma | Hung, Yi-Jen | Illig, Thomas | Jones, Michelle R. | Kaleebu, Pontiano | Kastelein, John J.P. | Khaw, Kay-Tee | Kim, Eric | Klopp, Norman | Komulainen, Pirjo | Kumari, Meena | Langenberg, Claudia | Lehtimäki, Terho | Lin, Shih-Yi | Lindström, Jaana | Loos, Ruth J.F. | Mach, François | McArdle, Wendy L | Meisinger, Christa | Mitchell, Braxton D. | Müller, Gabrielle | Nagaraja, Ramaiah | Narisu, Narisu | Nieminen, Tuomo V.M. | Nsubuga, Rebecca N. | Olafsson, Isleifur | Ong, Ken K. | Palotie, Aarno | Papamarkou, Theodore | Pomilla, Cristina | Pouta, Anneli | Rader, Daniel J. | Reilly, Muredach P. | Ridker, Paul M. | Rivadeneira, Fernando | Rudan, Igor | Ruokonen, Aimo | Samani, Nilesh | Scharnagl, Hubert | Seeley, Janet | Silander, Kaisa | Stančáková, Alena | Stirrups, Kathleen | Swift, Amy J. | Tiret, Laurence | Uitterlinden, Andre G. | van Pelt, L. Joost | Vedantam, Sailaja | Wainwright, Nicholas | Wijmenga, Cisca | Wild, Sarah H. | Willemsen, Gonneke | Wilsgaard, Tom | Wilson, James F. | Young, Elizabeth H. | Zhao, Jing Hua | Adair, Linda S. | Arveiler, Dominique | Assimes, Themistocles L. | Bandinelli, Stefania | Bennett, Franklyn | Bochud, Murielle | Boehm, Bernhard O. | Boomsma, Dorret I. | Borecki, Ingrid B. | Bornstein, Stefan R. | Bovet, Pascal | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chambers, John C. | Chen, Yii-Der Ida | Collins, Francis S. | Cooper, Richard S. | Danesh, John | Dedoussis, George | de Faire, Ulf | Feranil, Alan B. | Ferrières, Jean | Ferrucci, Luigi | Freimer, Nelson B. | Gieger, Christian | Groop, Leif C. | Gudnason, Vilmundur | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hingorani, Aroon | Hirschhorn, Joel N. | Hofman, Albert | Hovingh, G. Kees | Hsiung, Chao Agnes | Humphries, Steve E. | Hunt, Steven C. | Hveem, Kristian | Iribarren, Carlos | Järvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kaprio, Jaakko | Kesäniemi, Antero | Kivimaki, Mika | Kooner, Jaspal S. | Koudstaal, Peter J. | Krauss, Ronald M. | Kuh, Diana | Kuusisto, Johanna | Kyvik, Kirsten O. | Laakso, Markku | Lakka, Timo A. | Lind, Lars | Lindgren, Cecilia M. | Martin, Nicholas G. | März, Winfried | McCarthy, Mark I. | McKenzie, Colin A. | Meneton, Pierre | Metspalu, Andres | Moilanen, Leena | Morris, Andrew D. | Munroe, Patricia B. | Njølstad, Inger | Pedersen, Nancy L. | Power, Chris | Pramstaller, Peter P. | Price, Jackie F. | Psaty, Bruce M. | Quertermous, Thomas | Rauramaa, Rainer | Saleheen, Danish | Salomaa, Veikko | Sanghera, Dharambir K. | Saramies, Jouko | Schwarz, Peter E.H. | Sheu, Wayne H-H | Shuldiner, Alan R. | Siegbahn, Agneta | Spector, Tim D. | Stefansson, Kari | Strachan, David P. | Tayo, Bamidele O. | Tremoli, Elena | Tuomilehto, Jaakko | Uusitupa, Matti | van Duijn, Cornelia M. | Vollenweider, Peter | Wallentin, Lars | Wareham, Nicholas J. | Whitfield, John B. | Wolffenbuttel, Bruce H.R. | Ordovas, Jose M. | Boerwinkle, Eric | Palmer, Colin N.A. | Thorsteinsdottir, Unnur | Chasman, Daniel I. | Rotter, Jerome I. | Franks, Paul W. | Ripatti, Samuli | Cupples, L. Adrienne | Sandhu, Manjinder S. | Rich, Stephen S. | Boehnke, Michael | Deloukas, Panos | Kathiresan, Sekar | Mohlke, Karen L. | Ingelsson, Erik | Abecasis, Gonçalo R.
Nature genetics  2013;45(11):10.1038/ng.2797.
Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and total cholesterol are heritable, modifiable, risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,578 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5×10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian, and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipids are often associated with cardiovascular and metabolic traits including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio, and body mass index. Our results illustrate the value of genetic data from individuals of diverse ancestries and provide insights into biological mechanisms regulating blood lipids to guide future genetic, biological, and therapeutic research.
doi:10.1038/ng.2797
PMCID: PMC3838666  PMID: 24097068
9.  Common variants associated with plasma triglycerides and risk for coronary artery disease 
Do, Ron | Willer, Cristen J. | Schmidt, Ellen M. | Sengupta, Sebanti | Gao, Chi | Peloso, Gina M. | Gustafsson, Stefan | Kanoni, Stavroula | Ganna, Andrea | Chen, Jin | Buchkovich, Martin L. | Mora, Samia | Beckmann, Jacques S. | Bragg-Gresham, Jennifer L. | Chang, Hsing-Yi | Demirkan, Ayşe | Den Hertog, Heleen M. | Donnelly, Louise A. | Ehret, Georg B. | Esko, Tõnu | Feitosa, Mary F. | Ferreira, Teresa | Fischer, Krista | Fontanillas, Pierre | Fraser, Ross M. | Freitag, Daniel F. | Gurdasani, Deepti | Heikkilä, Kauko | Hyppönen, Elina | Isaacs, Aaron | Jackson, Anne U. | Johansson, Åsa | Johnson, Toby | Kaakinen, Marika | Kettunen, Johannes | Kleber, Marcus E. | Li, Xiaohui | Luan, Jian'an | Lyytikäinen, Leo-Pekka | Magnusson, Patrik K.E. | Mangino, Massimo | Mihailov, Evelin | Montasser, May E. | Müller-Nurasyid, Martina | Nolte, Ilja M. | O'Connell, Jeffrey R. | Palmer, Cameron D. | Perola, Markus | Petersen, Ann-Kristin | Sanna, Serena | Saxena, Richa | Service, Susan K. | Shah, Sonia | Shungin, Dmitry | Sidore, Carlo | Song, Ci | Strawbridge, Rona J. | Surakka, Ida | Tanaka, Toshiko | Teslovich, Tanya M. | Thorleifsson, Gudmar | Van den Herik, Evita G. | Voight, Benjamin F. | Volcik, Kelly A. | Waite, Lindsay L. | Wong, Andrew | Wu, Ying | Zhang, Weihua | Absher, Devin | Asiki, Gershim | Barroso, Inês | Been, Latonya F. | Bolton, Jennifer L. | Bonnycastle, Lori L | Brambilla, Paolo | Burnett, Mary S. | Cesana, Giancarlo | Dimitriou, Maria | Doney, Alex S.F. | Döring, Angela | Elliott, Paul | Epstein, Stephen E. | Eyjolfsson, Gudmundur Ingi | Gigante, Bruna | Goodarzi, Mark O. | Grallert, Harald | Gravito, Martha L. | Groves, Christopher J. | Hallmans, Göran | Hartikainen, Anna-Liisa | Hayward, Caroline | Hernandez, Dena | Hicks, Andrew A. | Holm, Hilma | Hung, Yi-Jen | Illig, Thomas | Jones, Michelle R. | Kaleebu, Pontiano | Kastelein, John J.P. | Khaw, Kay-Tee | Kim, Eric | Klopp, Norman | Komulainen, Pirjo | Kumari, Meena | Langenberg, Claudia | Lehtimäki, Terho | Lin, Shih-Yi | Lindström, Jaana | Loos, Ruth J.F. | Mach, François | McArdle, Wendy L | Meisinger, Christa | Mitchell, Braxton D. | Müller, Gabrielle | Nagaraja, Ramaiah | Narisu, Narisu | Nieminen, Tuomo V.M. | Nsubuga, Rebecca N. | Olafsson, Isleifur | Ong, Ken K. | Palotie, Aarno | Papamarkou, Theodore | Pomilla, Cristina | Pouta, Anneli | Rader, Daniel J. | Reilly, Muredach P. | Ridker, Paul M. | Rivadeneira, Fernando | Rudan, Igor | Ruokonen, Aimo | Samani, Nilesh | Scharnagl, Hubert | Seeley, Janet | Silander, Kaisa | Stančáková, Alena | Stirrups, Kathleen | Swift, Amy J. | Tiret, Laurence | Uitterlinden, Andre G. | van Pelt, L. Joost | Vedantam, Sailaja | Wainwright, Nicholas | Wijmenga, Cisca | Wild, Sarah H. | Willemsen, Gonneke | Wilsgaard, Tom | Wilson, James F. | Young, Elizabeth H. | Zhao, Jing Hua | Adair, Linda S. | Arveiler, Dominique | Assimes, Themistocles L. | Bandinelli, Stefania | Bennett, Franklyn | Bochud, Murielle | Boehm, Bernhard O. | Boomsma, Dorret I. | Borecki, Ingrid B. | Bornstein, Stefan R. | Bovet, Pascal | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chambers, John C. | Chen, Yii-Der Ida | Collins, Francis S. | Cooper, Richard S. | Danesh, John | Dedoussis, George | de Faire, Ulf | Feranil, Alan B. | Ferrières, Jean | Ferrucci, Luigi | Freimer, Nelson B. | Gieger, Christian | Groop, Leif C. | Gudnason, Vilmundur | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hingorani, Aroon | Hirschhorn, Joel N. | Hofman, Albert | Hovingh, G. Kees | Hsiung, Chao Agnes | Humphries, Steve E. | Hunt, Steven C. | Hveem, Kristian | Iribarren, Carlos | Järvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kaprio, Jaakko | Kesäniemi, Antero | Kivimaki, Mika | Kooner, Jaspal S. | Koudstaal, Peter J. | Krauss, Ronald M. | Kuh, Diana | Kuusisto, Johanna | Kyvik, Kirsten O. | Laakso, Markku | Lakka, Timo A. | Lind, Lars | Lindgren, Cecilia M. | Martin, Nicholas G. | März, Winfried | McCarthy, Mark I. | McKenzie, Colin A. | Meneton, Pierre | Metspalu, Andres | Moilanen, Leena | Morris, Andrew D. | Munroe, Patricia B. | Njølstad, Inger | Pedersen, Nancy L. | Power, Chris | Pramstaller, Peter P. | Price, Jackie F. | Psaty, Bruce M. | Quertermous, Thomas | Rauramaa, Rainer | Saleheen, Danish | Salomaa, Veikko | Sanghera, Dharambir K. | Saramies, Jouko | Schwarz, Peter E.H. | Sheu, Wayne H-H | Shuldiner, Alan R. | Siegbahn, Agneta | Spector, Tim D. | Stefansson, Kari | Strachan, David P. | Tayo, Bamidele O. | Tremoli, Elena | Tuomilehto, Jaakko | Uusitupa, Matti | van Duijn, Cornelia M. | Vollenweider, Peter | Wallentin, Lars | Wareham, Nicholas J. | Whitfield, John B. | Wolffenbuttel, Bruce H.R. | Altshuler, David | Ordovas, Jose M. | Boerwinkle, Eric | Palmer, Colin N.A. | Thorsteinsdottir, Unnur | Chasman, Daniel I. | Rotter, Jerome I. | Franks, Paul W. | Ripatti, Samuli | Cupples, L. Adrienne | Sandhu, Manjinder S. | Rich, Stephen S. | Boehnke, Michael | Deloukas, Panos | Mohlke, Karen L. | Ingelsson, Erik | Abecasis, Goncalo R. | Daly, Mark J. | Neale, Benjamin M. | Kathiresan, Sekar
Nature genetics  2013;45(11):1345-1352.
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10−8 for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
doi:10.1038/ng.2795
PMCID: PMC3904346  PMID: 24097064
10.  Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture 
Berndt, Sonja I. | Gustafsson, Stefan | Mägi, Reedik | Ganna, Andrea | Wheeler, Eleanor | Feitosa, Mary F. | Justice, Anne E. | Monda, Keri L. | Croteau-Chonka, Damien C. | Day, Felix R. | Esko, Tõnu | Fall, Tove | Ferreira, Teresa | Gentilini, Davide | Jackson, Anne U. | Luan, Jian’an | Randall, Joshua C. | Vedantam, Sailaja | Willer, Cristen J. | Winkler, Thomas W. | Wood, Andrew R. | Workalemahu, Tsegaselassie | Hu, Yi-Juan | Lee, Sang Hong | Liang, Liming | Lin, Dan-Yu | Min, Josine L. | Neale, Benjamin M. | Thorleifsson, Gudmar | Yang, Jian | Albrecht, Eva | Amin, Najaf | Bragg-Gresham, Jennifer L. | Cadby, Gemma | den Heijer, Martin | Eklund, Niina | Fischer, Krista | Goel, Anuj | Hottenga, Jouke-Jan | Huffman, Jennifer E. | Jarick, Ivonne | Johansson, Åsa | Johnson, Toby | Kanoni, Stavroula | Kleber, Marcus E. | König, Inke R. | Kristiansson, Kati | Kutalik, Zoltán | Lamina, Claudia | Lecoeur, Cecile | Li, Guo | Mangino, Massimo | McArdle, Wendy L. | Medina-Gomez, Carolina | Müller-Nurasyid, Martina | Ngwa, Julius S. | Nolte, Ilja M. | Paternoster, Lavinia | Pechlivanis, Sonali | Perola, Markus | Peters, Marjolein J. | Preuss, Michael | Rose, Lynda M. | Shi, Jianxin | Shungin, Dmitry | Smith, Albert Vernon | Strawbridge, Rona J. | Surakka, Ida | Teumer, Alexander | Trip, Mieke D. | Tyrer, Jonathan | Van Vliet-Ostaptchouk, Jana V. | Vandenput, Liesbeth | Waite, Lindsay L. | Zhao, Jing Hua | Absher, Devin | Asselbergs, Folkert W. | Atalay, Mustafa | Attwood, Antony P. | Balmforth, Anthony J. | Basart, Hanneke | Beilby, John | Bonnycastle, Lori L. | Brambilla, Paolo | Bruinenberg, Marcel | Campbell, Harry | Chasman, Daniel I. | Chines, Peter S. | Collins, Francis S. | Connell, John M. | Cookson, William | de Faire, Ulf | de Vegt, Femmie | Dei, Mariano | Dimitriou, Maria | Edkins, Sarah | Estrada, Karol | Evans, David M. | Farrall, Martin | Ferrario, Marco M. | Ferrières, Jean | Franke, Lude | Frau, Francesca | Gejman, Pablo V. | Grallert, Harald | Grönberg, Henrik | Gudnason, Vilmundur | Hall, Alistair S. | Hall, Per | Hartikainen, Anna-Liisa | Hayward, Caroline | Heard-Costa, Nancy L. | Heath, Andrew C. | Hebebrand, Johannes | Homuth, Georg | Hu, Frank B. | Hunt, Sarah E. | Hyppönen, Elina | Iribarren, Carlos | Jacobs, Kevin B. | Jansson, John-Olov | Jula, Antti | Kähönen, Mika | Kathiresan, Sekar | Kee, Frank | Khaw, Kay-Tee | Kivimaki, Mika | Koenig, Wolfgang | Kraja, Aldi T. | Kumari, Meena | Kuulasmaa, Kari | Kuusisto, Johanna | Laitinen, Jaana H. | Lakka, Timo A. | Langenberg, Claudia | Launer, Lenore J. | Lind, Lars | Lindström, Jaana | Liu, Jianjun | Liuzzi, Antonio | Lokki, Marja-Liisa | Lorentzon, Mattias | Madden, Pamela A. | Magnusson, Patrik K. | Manunta, Paolo | Marek, Diana | März, Winfried | Mateo Leach, Irene | McKnight, Barbara | Medland, Sarah E. | Mihailov, Evelin | Milani, Lili | Montgomery, Grant W. | Mooser, Vincent | Mühleisen, Thomas W. | Munroe, Patricia B. | Musk, Arthur W. | Narisu, Narisu | Navis, Gerjan | Nicholson, George | Nohr, Ellen A. | Ong, Ken K. | Oostra, Ben A. | Palmer, Colin N.A. | Palotie, Aarno | Peden, John F. | Pedersen, Nancy | Peters, Annette | Polasek, Ozren | Pouta, Anneli | Pramstaller, Peter P. | Prokopenko, Inga | Pütter, Carolin | Radhakrishnan, Aparna | Raitakari, Olli | Rendon, Augusto | Rivadeneira, Fernando | Rudan, Igor | Saaristo, Timo E. | Sambrook, Jennifer G. | Sanders, Alan R. | Sanna, Serena | Saramies, Jouko | Schipf, Sabine | Schreiber, Stefan | Schunkert, Heribert | Shin, So-Youn | Signorini, Stefano | Sinisalo, Juha | Skrobek, Boris | Soranzo, Nicole | Stančáková, Alena | Stark, Klaus | Stephens, Jonathan C. | Stirrups, Kathleen | Stolk, Ronald P. | Stumvoll, Michael | Swift, Amy J. | Theodoraki, Eirini V. | Thorand, Barbara | Tregouet, David-Alexandre | Tremoli, Elena | Van der Klauw, Melanie M. | van Meurs, Joyce B.J. | Vermeulen, Sita H. | Viikari, Jorma | Virtamo, Jarmo | Vitart, Veronique | Waeber, Gérard | Wang, Zhaoming | Widén, Elisabeth | Wild, Sarah H. | Willemsen, Gonneke | Winkelmann, Bernhard R. | Witteman, Jacqueline C.M. | Wolffenbuttel, Bruce H.R. | Wong, Andrew | Wright, Alan F. | Zillikens, M. Carola | Amouyel, Philippe | Boehm, Bernhard O. | Boerwinkle, Eric | Boomsma, Dorret I. | Caulfield, Mark J. | Chanock, Stephen J. | Cupples, L. Adrienne | Cusi, Daniele | Dedoussis, George V. | Erdmann, Jeanette | Eriksson, Johan G. | Franks, Paul W. | Froguel, Philippe | Gieger, Christian | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hengstenberg, Christian | Hicks, Andrew A. | Hingorani, Aroon | Hinney, Anke | Hofman, Albert | Hovingh, Kees G. | Hveem, Kristian | Illig, Thomas | Jarvelin, Marjo-Riitta | Jöckel, Karl-Heinz | Keinanen-Kiukaanniemi, Sirkka M. | Kiemeney, Lambertus A. | Kuh, Diana | Laakso, Markku | Lehtimäki, Terho | Levinson, Douglas F. | Martin, Nicholas G. | Metspalu, Andres | Morris, Andrew D. | Nieminen, Markku S. | Njølstad, Inger | Ohlsson, Claes | Oldehinkel, Albertine J. | Ouwehand, Willem H. | Palmer, Lyle J. | Penninx, Brenda | Power, Chris | Province, Michael A. | Psaty, Bruce M. | Qi, Lu | Rauramaa, Rainer | Ridker, Paul M. | Ripatti, Samuli | Salomaa, Veikko | Samani, Nilesh J. | Snieder, Harold | Sørensen, Thorkild I.A. | Spector, Timothy D. | Stefansson, Kari | Tönjes, Anke | Tuomilehto, Jaakko | Uitterlinden, André G. | Uusitupa, Matti | van der Harst, Pim | Vollenweider, Peter | Wallaschofski, Henri | Wareham, Nicholas J. | Watkins, Hugh | Wichmann, H.-Erich | Wilson, James F. | Abecasis, Goncalo R. | Assimes, Themistocles L. | Barroso, Inês | Boehnke, Michael | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Frayling, Timothy | Groop, Leif C. | Haritunian, Talin | Heid, Iris M. | Hunter, David | Kaplan, Robert C. | Karpe, Fredrik | Moffatt, Miriam | Mohlke, Karen L. | O’Connell, Jeffrey R. | Pawitan, Yudi | Schadt, Eric E. | Schlessinger, David | Steinthorsdottir, Valgerdur | Strachan, David P. | Thorsteinsdottir, Unnur | van Duijn, Cornelia M. | Visscher, Peter M. | Di Blasio, Anna Maria | Hirschhorn, Joel N. | Lindgren, Cecilia M. | Morris, Andrew P. | Meyre, David | Scherag, André | McCarthy, Mark I. | Speliotes, Elizabeth K. | North, Kari E. | Loos, Ruth J.F. | Ingelsson, Erik
Nature genetics  2013;45(5):501-512.
Approaches exploiting extremes of the trait distribution may reveal novel loci for common traits, but it is unknown whether such loci are generalizable to the general population. In a genome-wide search for loci associated with upper vs. lower 5th percentiles of body mass index, height and waist-hip ratio, as well as clinical classes of obesity including up to 263,407 European individuals, we identified four new loci (IGFBP4, H6PD, RSRC1, PPP2R2A) influencing height detected in the tails and seven new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3, ZZZ3) for clinical classes of obesity. Further, we show that there is large overlap in terms of genetic structure and distribution of variants between traits based on extremes and the general population and little etiologic heterogeneity between obesity subgroups.
doi:10.1038/ng.2606
PMCID: PMC3973018  PMID: 23563607
11.  Chromosome X-Wide Association Study Identifies Loci for Fasting Insulin and Height and Evidence for Incomplete Dosage Compensation 
PLoS Genetics  2014;10(2):e1004127.
The X chromosome (chrX) represents one potential source for the “missing heritability” for complex phenotypes, which thus far has remained underanalyzed in genome-wide association studies (GWAS). Here we demonstrate the benefits of including chrX in GWAS by assessing the contribution of 404,862 chrX SNPs to levels of twelve commonly studied cardiometabolic and anthropometric traits in 19,697 Finnish and Swedish individuals with replication data on 5,032 additional Finns. By using a linear mixed model, we estimate that on average 2.6% of the additive genetic variance in these twelve traits is attributable to chrX, this being in proportion to the number of SNPs in the chromosome. In a chrX-wide association analysis, we identify three novel loci: two for height (rs182838724 near FGF16/ATRX/MAGT1, joint P-value = 2.71×10−9, and rs1751138 near ITM2A, P-value = 3.03×10−10) and one for fasting insulin (rs139163435 in Xq23, P-value = 5.18×10−9). Further, we find that effect sizes for variants near ITM2A, a gene implicated in cartilage development, show evidence for a lack of dosage compensation. This observation is further supported by a sex-difference in ITM2A expression in whole blood (P-value = 0.00251), and is also in agreement with a previous report showing ITM2A escapes from X chromosome inactivation (XCI) in the majority of women. Hence, our results show one of the first links between phenotypic variation in a population sample and an XCI-escaping locus and pinpoint ITM2A as a potential contributor to the sexual dimorphism in height. In conclusion, our study provides a clear motivation for including chrX in large-scale genetic studies of complex diseases and traits.
Author Summary
The X chromosome (chrX) analyses have often been neglected in large-scale genome-wide association studies. Given that chrX contains a considerable proportion of DNA, we wanted to examine how the variation in the chromosome contributes to commonly studied phenotypes. To this end, we studied the associations of over 400,000 chrX variants with twelve complex phenotypes, such as height, in almost 25,000 Northern European individuals. Demonstrating the value of assessing chrX associations, we found that as a whole the variation in the chromosome influences the levels of many of these phenotypes and further identified three new genomic regions where the variants associate with height or fasting insulin levels. In one of these three associated regions, the region near ITM2A, we observed that there is a sex difference in the genetic effects on height in a manner consistent with a lack of dosage compensation in this locus. Further supporting this observation, ITM2A has been shown to be among those chrX genes where the X chromosome inactivation is incomplete. Identifying phenotype associations in regions like this where chrX allele dosages are not balanced between men and women can be particularly valuable in helping us to understand why some characteristics differ between sexes.
doi:10.1371/journal.pgen.1004127
PMCID: PMC3916240  PMID: 24516404
12.  The prevalence of metabolic syndrome and metabolically healthy obesity in Europe: a collaborative analysis of ten large cohort studies 
Background
Not all obese subjects have an adverse metabolic profile predisposing them to developing type 2 diabetes or cardiovascular disease. The BioSHaRE-EU Healthy Obese Project aims to gain insights into the consequences of (healthy) obesity using data on risk factors and phenotypes across several large-scale cohort studies. Aim of this study was to describe the prevalence of obesity, metabolic syndrome (MetS) and metabolically healthy obesity (MHO) in ten participating studies.
Methods
Ten different cohorts in seven countries were combined, using data transformed into a harmonized format. All participants were of European origin, with age 18–80 years. They had participated in a clinical examination for anthropometric and blood pressure measurements. Blood samples had been drawn for analysis of lipids and glucose. Presence of MetS was assessed in those with obesity (BMI ≥ 30 kg/m2) based on the 2001 NCEP ATP III criteria, as well as an adapted set of less strict criteria. MHO was defined as obesity, having none of the MetS components, and no previous diagnosis of cardiovascular disease.
Results
Data for 163,517 individuals were available; 17% were obese (11,465 men and 16,612 women). The prevalence of obesity varied from 11.6% in the Italian CHRIS cohort to 26.3% in the German KORA cohort. The age-standardized percentage of obese subjects with MetS ranged in women from 24% in CHRIS to 65% in the Finnish Health2000 cohort, and in men from 43% in CHRIS to 78% in the Finnish DILGOM cohort, with elevated blood pressure the most frequently occurring factor contributing to the prevalence of the metabolic syndrome. The age-standardized prevalence of MHO varied in women from 7% in Health2000 to 28% in NCDS, and in men from 2% in DILGOM to 19% in CHRIS. MHO was more prevalent in women than in men, and decreased with age in both sexes.
Conclusions
Through a rigorous harmonization process, the BioSHaRE-EU consortium was able to compare key characteristics defining the metabolically healthy obese phenotype across ten cohort studies. There is considerable variability in the prevalence of healthy obesity across the different European populations studied, even when unified criteria were used to classify this phenotype.
doi:10.1186/1472-6823-14-9
PMCID: PMC3923238  PMID: 24484869
Harmonization; Obesity; Metabolic syndrome; Cardiovascular disease; Metabolically healthy
13.  Risk Stratification by Self-Measured Home Blood Pressure across Categories of Conventional Blood Pressure: A Participant-Level Meta-Analysis 
PLoS Medicine  2014;11(1):e1001591.
Jan Staessen and colleagues compare the risk of cardiovascular, cardiac, or cerebrovascular events in patients with elevated office blood pressure vs. self-measured home blood pressure.
Please see later in the article for the Editors' Summary
Background
The Global Burden of Diseases Study 2010 reported that hypertension is worldwide the leading risk factor for cardiovascular disease, causing 9.4 million deaths annually. We examined to what extent self-measurement of home blood pressure (HBP) refines risk stratification across increasing categories of conventional blood pressure (CBP).
Methods and Findings
This meta-analysis included 5,008 individuals randomly recruited from five populations (56.6% women; mean age, 57.1 y). All were not treated with antihypertensive drugs. In multivariable analyses, hazard ratios (HRs) associated with 10-mm Hg increases in systolic HBP were computed across CBP categories, using the following systolic/diastolic CBP thresholds (in mm Hg): optimal, <120/<80; normal, 120–129/80–84; high-normal, 130–139/85–89; mild hypertension, 140–159/90–99; and severe hypertension, ≥160/≥100.
Over 8.3 y, 522 participants died, and 414, 225, and 194 had cardiovascular, cardiac, and cerebrovascular events, respectively. In participants with optimal or normal CBP, HRs for a composite cardiovascular end point associated with a 10-mm Hg higher systolic HBP were 1.28 (1.01–1.62) and 1.22 (1.00–1.49), respectively. At high-normal CBP and in mild hypertension, the HRs were 1.24 (1.03–1.49) and 1.20 (1.06–1.37), respectively, for all cardiovascular events and 1.33 (1.07–1.65) and 1.30 (1.09–1.56), respectively, for stroke. In severe hypertension, the HRs were not significant (p≥0.20). Among people with optimal, normal, and high-normal CBP, 67 (5.0%), 187 (18.4%), and 315 (30.3%), respectively, had masked hypertension (HBP≥130 mm Hg systolic or ≥85 mm Hg diastolic). Compared to true optimal CBP, masked hypertension was associated with a 2.3-fold (1.5–3.5) higher cardiovascular risk. A limitation was few data from low- and middle-income countries.
Conclusions
HBP substantially refines risk stratification at CBP levels assumed to carry no or only mildly increased risk, in particular in the presence of masked hypertension. Randomized trials could help determine the best use of CBP vs. HBP in guiding BP management. Our study identified a novel indication for HBP, which, in view of its low cost and the increased availability of electronic communication, might be globally applicable, even in remote areas or in low-resource settings.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Globally, hypertension (high blood pressure) is the leading risk factor for cardiovascular disease and is responsible for 9.4 million deaths annually from heart attacks, stroke, and other cardiovascular diseases. Hypertension, which rarely has any symptoms, is diagnosed by measuring blood pressure, the force that blood circulating in the body exerts on the inside of large blood vessels. Blood pressure is highest when the heart is pumping out blood (systolic blood pressure) and lowest when the heart is refilling (diastolic blood pressure). European guidelines define optimal blood pressure as a systolic blood pressure of less than 120 millimeters of mercury (mm Hg) and a diastolic blood pressure of less than 80 mm Hg (a blood pressure of less than 120/80 mm Hg). Normal blood pressure, high-normal blood pressure, and mild hypertension are defined as blood pressures in the ranges 120–129/80–84 mm Hg, 130–139/85–89 mm Hg, and 140–159/90–99 mm Hg, respectively. A blood pressure of more than 160 mm Hg systolic or 100 mm Hg diastolic indicates severe hypertension. Many factors affect blood pressure; overweight people and individuals who eat salty or fatty food are at high risk of developing hypertension. Lifestyle changes and/or antihypertensive drugs can be used to control hypertension.
Why Was This Study Done?
The current guidelines for the diagnosis and management of hypertension recommend risk stratification based on conventionally measured blood pressure (CBP, the average of two consecutive measurements made at a clinic). However, self-measured home blood pressure (HBP) more accurately predicts outcomes because multiple HBP readings are taken and because HBP measurement avoids the “white-coat effect”—some individuals have a raised blood pressure in a clinical setting but not at home. Could risk stratification across increasing categories of CBP be refined through the use of self-measured HBP, particularly at CBP levels assumed to be associated with no or only mildly increased risk? Here, the researchers undertake a participant-level meta-analysis (a study that uses statistical approaches to pool results from individual participants in several independent studies) to answer this question.
What Did the Researchers Do and Find?
The researchers included 5,008 individuals recruited from five populations and enrolled in the International Database of Home Blood Pressure in Relation to Cardiovascular Outcome (IDHOCO) in their meta-analysis. CBP readings were available for all the participants, who measured their HBP using an oscillometric device (an electronic device for measuring blood pressure). The researchers used information on fatal and nonfatal cardiovascular, cardiac, and cerebrovascular (stroke) events to calculate the hazard ratios (HRs, indicators of increased risk) associated with a 10-mm Hg increase in systolic HBP across standard CBP categories. In participants with optimal CBP, an increase in systolic HBP of 10-mm Hg increased the risk of any cardiovascular event by nearly 30% (an HR of 1.28). Similar HRs were associated with a 10-mm Hg increase in systolic HBP for all cardiovascular events among people with normal and high-normal CBP and with mild hypertension, but for people with severe hypertension, systolic HBP did not significantly add to the prediction of any end point. Among people with optimal, normal, and high-normal CBP, 5%, 18.4%, and 30.4%, respectively, had a HBP of 130/85 or higher (“masked hypertension,” a higher blood pressure in daily life than in a clinical setting). Finally, compared to individuals with optimal CBP without masked hypertension, individuals with masked hypertension had more than double the risk of cardiovascular disease.
What Do These Findings Mean?
These findings indicate that HBP measurements, particularly in individuals with masked hypertension, refine risk stratification at CBP levels assumed to be associated with no or mildly elevated risk of cardiovascular disease. That is, HBP measurements can improve the prediction of cardiovascular complications or death among individuals with optimal, normal, and high-normal CBP but not among individuals with severe hypertension. Clinical trials are needed to test whether the identification and treatment of masked hypertension leads to a reduction of cardiovascular complications and is cost-effective compared to the current standard of care, which does not include HBP measurements and does not treat people with normal or high-normal CBP. Until then, these findings provide support for including HBP monitoring in primary prevention strategies for cardiovascular disease among individuals at risk for masked hypertension (for example, people with diabetes), and for carrying out HBP monitoring in people with a normal CBP but unexplained signs of hypertensive target organ damage.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001591.
This study is further discussed in a PLOS Medicine Perspective by Mark Caulfield
The US National Heart, Lung, and Blood Institute has patient information about high blood pressure (in English and Spanish) and a guide to lowering high blood pressure that includes personal stories
The American Heart Association provides information on high blood pressure and on cardiovascular diseases (in several languages); it also provides personal stories about dealing with high blood pressure
The UK National Health Service Choices website provides detailed information for patients about hypertension (including a personal story) and about cardiovascular disease
The World Health Organization provides information on cardiovascular disease and controlling blood pressure; its A Global Brief on Hypertension was published on World Health Day 2013
The UK charity Blood Pressure UK provides information about white-coat hypertension and about home blood pressure monitoring
MedlinePlus provides links to further information about high blood pressure, heart disease, and stroke (in English and Spanish)
doi:10.1371/journal.pmed.1001591
PMCID: PMC3897370  PMID: 24465187
14.  Prevalence of arrhythmia-associated gene mutations and risk of sudden cardiac death in the Finnish population 
Annals of medicine  2013;45(4):328-335.
Background
Sudden cardiac death (SCD) remains a major cause of death in Western Countries. It has a heritable component, but previous molecular studies have mainly focused on common genetic variants. We studied the prevalence, clinical phenotypes, and risk of SCD presented by ten rare mutations previously associated with arrhythmogenic right ventricular cardiomyopathy, long QT syndrome, or catecholaminergic polymorphic ventricular tachycardia.
Methods
The occurrence of ten arrhythmia-associated mutations was determined in four large prospective population cohorts (FINRISK 1992, 1997, 2002, and Health 2000, n = 28,465) and two series of forensic autopsies (The Helsinki Sudden Death Study and The Tampere Autopsy Study, n = 825). Follow-up data was collected from national registries.
Results
The ten mutations showed a combined prevalence of 79 per 10,000 individuals in Finland and six of them showed remarkable geographic clustering. Of a total of 715 SCD cases, seven (1.0%) carried one of the ten mutations assayed: three carried KCNH2 R176W, one KCNH2 L552S, two PKP2 Q59L, and one RYR2 R3570W.
Conclusions
Arrhythmia-associated mutations are prevalent in the general Finnish population but do not seem to present a major risk factor for SCD, at least during a mean of 10-year follow-up of a random adult population sample.
doi:10.3109/07853890.2013.783995
PMCID: PMC3778376  PMID: 23651034
Arrhythmia; Genetic epidemiology; Genetics; Mutation; Sudden cardiac death
15.  Circulating Metabolite Predictors of Glycemia in Middle-Aged Men and Women 
Diabetes Care  2012;35(8):1749-1756.
OBJECTIVE
Metabolite predictors of deteriorating glucose tolerance may elucidate the pathogenesis of type 2 diabetes. We investigated associations of circulating metabolites from high-throughput profiling with fasting and postload glycemia cross-sectionally and prospectively on the population level.
RESEARCH DESIGN AND METHODS
Oral glucose tolerance was assessed in two Finnish, population-based studies consisting of 1,873 individuals (mean age 52 years, 58% women) and reexamined after 6.5 years for 618 individuals in one of the cohorts. Metabolites were quantified by nuclear magnetic resonance spectroscopy from fasting serum samples. Associations were studied by linear regression models adjusted for established risk factors.
RESULTS
Nineteen circulating metabolites, including amino acids, gluconeogenic substrates, and fatty acid measures, were cross-sectionally associated with fasting and/or postload glucose (P < 0.001). Among these metabolic intermediates, branched-chain amino acids, phenylalanine, and α1-acid glycoprotein were predictors of both fasting and 2-h glucose at 6.5-year follow-up (P < 0.05), whereas alanine, lactate, pyruvate, and tyrosine were uniquely associated with 6.5-year postload glucose (P = 0.003–0.04). None of the fatty acid measures were prospectively associated with glycemia. Changes in fatty acid concentrations were associated with changes in fasting and postload glycemia during follow-up; however, changes in branched-chain amino acids did not follow glucose dynamics, and gluconeogenic substrates only paralleled changes in fasting glucose.
CONCLUSIONS
Alterations in branched-chain and aromatic amino acid metabolism precede hyperglycemia in the general population. Further, alanine, lactate, and pyruvate were predictive of postchallenge glucose exclusively. These gluconeogenic precursors are potential markers of long-term impaired insulin sensitivity that may relate to attenuated glucose tolerance later in life.
doi:10.2337/dc11-1838
PMCID: PMC3402262  PMID: 22563043
16.  Genome-wide association analyses identify 18 new loci associated with serum urate concentrations 
Köttgen, Anna | Albrecht, Eva | Teumer, Alexander | Vitart, Veronique | Krumsiek, Jan | Hundertmark, Claudia | Pistis, Giorgio | Ruggiero, Daniela | O’Seaghdha, Conall M | Haller, Toomas | Yang, Qiong | Tanaka, Toshiko | Johnson, Andrew D | Kutalik, Zoltán | Smith, Albert V | Shi, Julia | Struchalin, Maksim | Middelberg, Rita P S | Brown, Morris J | Gaffo, Angelo L | Pirastu, Nicola | Li, Guo | Hayward, Caroline | Zemunik, Tatijana | Huffman, Jennifer | Yengo, Loic | Zhao, Jing Hua | Demirkan, Ayse | Feitosa, Mary F | Liu, Xuan | Malerba, Giovanni | Lopez, Lorna M | van der Harst, Pim | Li, Xinzhong | Kleber, Marcus E | Hicks, Andrew A | Nolte, Ilja M | Johansson, Asa | Murgia, Federico | Wild, Sarah H | Bakker, Stephan J L | Peden, John F | Dehghan, Abbas | Steri, Maristella | Tenesa, Albert | Lagou, Vasiliki | Salo, Perttu | Mangino, Massimo | Rose, Lynda M | Lehtimäki, Terho | Woodward, Owen M | Okada, Yukinori | Tin, Adrienne | Müller, Christian | Oldmeadow, Christopher | Putku, Margus | Czamara, Darina | Kraft, Peter | Frogheri, Laura | Thun, Gian Andri | Grotevendt, Anne | Gislason, Gauti Kjartan | Harris, Tamara B | Launer, Lenore J | McArdle, Patrick | Shuldiner, Alan R | Boerwinkle, Eric | Coresh, Josef | Schmidt, Helena | Schallert, Michael | Martin, Nicholas G | Montgomery, Grant W | Kubo, Michiaki | Nakamura, Yusuke | Tanaka, Toshihiro | Munroe, Patricia B | Samani, Nilesh J | Jacobs, David R | Liu, Kiang | D’Adamo, Pio | Ulivi, Sheila | Rotter, Jerome I | Psaty, Bruce M | Vollenweider, Peter | Waeber, Gerard | Campbell, Susan | Devuyst, Olivier | Navarro, Pau | Kolcic, Ivana | Hastie, Nicholas | Balkau, Beverley | Froguel, Philippe | Esko, Tõnu | Salumets, Andres | Khaw, Kay Tee | Langenberg, Claudia | Wareham, Nicholas J | Isaacs, Aaron | Kraja, Aldi | Zhang, Qunyuan | Wild, Philipp S | Scott, Rodney J | Holliday, Elizabeth G | Org, Elin | Viigimaa, Margus | Bandinelli, Stefania | Metter, Jeffrey E | Lupo, Antonio | Trabetti, Elisabetta | Sorice, Rossella | Döring, Angela | Lattka, Eva | Strauch, Konstantin | Theis, Fabian | Waldenberger, Melanie | Wichmann, H-Erich | Davies, Gail | Gow, Alan J | Bruinenberg, Marcel | Study, LifeLines Cohort | Stolk, Ronald P | Kooner, Jaspal S | Zhang, Weihua | Winkelmann, Bernhard R | Boehm, Bernhard O | Lucae, Susanne | Penninx, Brenda W | Smit, Johannes H | Curhan, Gary | Mudgal, Poorva | Plenge, Robert M | Portas, Laura | Persico, Ivana | Kirin, Mirna | Wilson, James F | Leach, Irene Mateo | van Gilst, Wiek H | Goel, Anuj | Ongen, Halit | Hofman, Albert | Rivadeneira, Fernando | Uitterlinden, Andre G | Imboden, Medea | von Eckardstein, Arnold | Cucca, Francesco | Nagaraja, Ramaiah | Piras, Maria Grazia | Nauck, Matthias | Schurmann, Claudia | Budde, Kathrin | Ernst, Florian | Farrington, Susan M | Theodoratou, Evropi | Prokopenko, Inga | Stumvoll, Michael | Jula, Antti | Perola, Markus | Salomaa, Veikko | Shin, So-Youn | Spector, Tim D | Sala, Cinzia | Ridker, Paul M | Kähönen, Mika | Viikari, Jorma | Hengstenberg, Christian | Nelson, Christopher P | Consortium, CARDIoGRAM | Consortium, DIAGRAM | Consortium, ICBP | Consortium, MAGIC | Meschia, James F | Nalls, Michael A | Sharma, Pankaj | Singleton, Andrew B | Kamatani, Naoyuki | Zeller, Tanja | Burnier, Michel | Attia, John | Laan, Maris | Klopp, Norman | Hillege, Hans L | Kloiber, Stefan | Choi, Hyon | Pirastu, Mario | Tore, Silvia | Probst-Hensch, Nicole M | Völzke, Henry | Gudnason, Vilmundur | Parsa, Afshin | Schmidt, Reinhold | Whitfield, John B | Fornage, Myriam | Gasparini, Paolo | Siscovick, David S | Polašek, Ozren | Campbell, Harry | Rudan, Igor | Bouatia-Naji, Nabila | Metspalu, Andres | Loos, Ruth J F | van Duijn, Cornelia M | Borecki, Ingrid B | Ferrucci, Luigi | Gambaro, Giovanni | Deary, Ian J | Wolffenbuttel, Bruce H R | Chambers, John C | März, Winfried | Pramstaller, Peter P | Snieder, Harold | Gyllensten, Ulf | Wright, Alan F | Navis, Gerjan | Watkins, Hugh | Witteman, Jacqueline C M | Sanna, Serena | Schipf, Sabine | Dunlop, Malcolm G | Tönjes, Anke | Ripatti, Samuli | Soranzo, Nicole | Toniolo, Daniela | Chasman, Daniel I | Raitakari, Olli | Kao, W H Linda | Ciullo, Marina | Fox, Caroline S | Caulfield, Mark | Bochud, Murielle | Gieger, Christian
Nature genetics  2012;45(2):145-154.
Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.
doi:10.1038/ng.2500
PMCID: PMC3663712  PMID: 23263486
17.  A COMMON VARIANT NEAR KCNJ2 GENE IS ASSOCIATED WITH T-PEAK TO T-END INTERVAL 
Background
T-peak to T-end (TPE) interval on the electrocardiogram (ECG) is a measure of myocardial dispersion of repolarization and is associated with increased risk of ventricular arrhythmias. The genetic factors affecting the TPE interval are largely unknown.
Objective
We sought to identify common genetic variants that affect the TPE-interval duration in the general population.
Methods
We performed a genome-wide association study on 1 870 individuals of Finnish origin participating in the Health 2000 Study. TPE interval was measured from T-peak to T-wave end in leads II, V2 and V5 on resting ECGs and the mean of these TPE intervals was adjusted for age, sex and Cornell voltage-duration product. We sought replication for a genome-wide significant result in the 3 745 subjects from the Framingham Heart Study.
Results
We identified a locus on 17q24 that was associated with the TPE interval. The minor allele of the common variant rs7219669 was associated with a 1.8-ms shortening of the TPE interval (P=1.1×10−10). The association was replicated in the Framingham Heart Study (−1.5 ms, P=1.3×10−4).The overall effect estimate of rs7219669 in the two studies was −1.7 ms (P=5.7×10−14). The common variant rs7219669 maps downstream of KCNJ2 gene, in which rare mutations cause congenital Long- and Short-QT syndromes.
Conclusion
The common variant rs7219669 is associated with the TPE interval and is thus a candidate to modify repolarization-related arrhythmia susceptibility in individuals carrying the major allele of this polymorphism.
doi:10.1016/j.hrthm.2012.02.019
PMCID: PMC3690340  PMID: 22342860
Electrocardiography; Repolarization; T wave; Epidemiology; Genetics; Polymorphism
18.  The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis 
Fall, Tove | Hägg, Sara | Mägi, Reedik | Ploner, Alexander | Fischer, Krista | Horikoshi, Momoko | Sarin, Antti-Pekka | Thorleifsson, Gudmar | Ladenvall, Claes | Kals, Mart | Kuningas, Maris | Draisma, Harmen H. M. | Ried, Janina S. | van Zuydam, Natalie R. | Huikari, Ville | Mangino, Massimo | Sonestedt, Emily | Benyamin, Beben | Nelson, Christopher P. | Rivera, Natalia V. | Kristiansson, Kati | Shen, Huei-yi | Havulinna, Aki S. | Dehghan, Abbas | Donnelly, Louise A. | Kaakinen, Marika | Nuotio, Marja-Liisa | Robertson, Neil | de Bruijn, Renée F. A. G. | Ikram, M. Arfan | Amin, Najaf | Balmforth, Anthony J. | Braund, Peter S. | Doney, Alexander S. F. | Döring, Angela | Elliott, Paul | Esko, Tõnu | Franco, Oscar H. | Gretarsdottir, Solveig | Hartikainen, Anna-Liisa | Heikkilä, Kauko | Herzig, Karl-Heinz | Holm, Hilma | Hottenga, Jouke Jan | Hyppönen, Elina | Illig, Thomas | Isaacs, Aaron | Isomaa, Bo | Karssen, Lennart C. | Kettunen, Johannes | Koenig, Wolfgang | Kuulasmaa, Kari | Laatikainen, Tiina | Laitinen, Jaana | Lindgren, Cecilia | Lyssenko, Valeriya | Läärä, Esa | Rayner, Nigel W. | Männistö, Satu | Pouta, Anneli | Rathmann, Wolfgang | Rivadeneira, Fernando | Ruokonen, Aimo | Savolainen, Markku J. | Sijbrands, Eric J. G. | Small, Kerrin S. | Smit, Jan H. | Steinthorsdottir, Valgerdur | Syvänen, Ann-Christine | Taanila, Anja | Tobin, Martin D. | Uitterlinden, Andre G. | Willems, Sara M. | Willemsen, Gonneke | Witteman, Jacqueline | Perola, Markus | Evans, Alun | Ferrières, Jean | Virtamo, Jarmo | Kee, Frank | Tregouet, David-Alexandre | Arveiler, Dominique | Amouyel, Philippe | Ferrario, Marco M. | Brambilla, Paolo | Hall, Alistair S. | Heath, Andrew C. | Madden, Pamela A. F. | Martin, Nicholas G. | Montgomery, Grant W. | Whitfield, John B. | Jula, Antti | Knekt, Paul | Oostra, Ben | van Duijn, Cornelia M. | Penninx, Brenda W. J. H. | Davey Smith, George | Kaprio, Jaakko | Samani, Nilesh J. | Gieger, Christian | Peters, Annette | Wichmann, H.-Erich | Boomsma, Dorret I. | de Geus, Eco J. C. | Tuomi, TiinaMaija | Power, Chris | Hammond, Christopher J. | Spector, Tim D. | Lind, Lars | Orho-Melander, Marju | Palmer, Colin Neil Alexander | Morris, Andrew D. | Groop, Leif | Järvelin, Marjo-Riitta | Salomaa, Veikko | Vartiainen, Erkki | Hofman, Albert | Ripatti, Samuli | Metspalu, Andres | Thorsteinsdottir, Unnur | Stefansson, Kari | Pedersen, Nancy L. | McCarthy, Mark I. | Ingelsson, Erik | Prokopenko, Inga
PLoS Medicine  2013;10(6):e1001474.
In this study, Prokopenko and colleagues provide novel evidence for causal relationship between adiposity and heart failure and increased liver enzymes using a Mendelian randomization study design.
Please see later in the article for the Editors' Summary
Background
The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.
Methods and Findings
We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses.
Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001).
Conclusions
We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.
Please see later in the article for the Editors' Summary
Editors' Summary
Cardiovascular disease (CVD)—disease that affects the heart and/or the blood vessels—is a major cause of illness and death worldwide. In the US, for example, coronary heart disease—a CVD in which narrowing of the heart's blood vessels by fatty deposits slows the blood supply to the heart and may eventually cause a heart attack—is the leading cause of death, and stroke—a CVD in which the brain's blood supply is interrupted—is the fourth leading cause of death. Globally, both the incidence of CVD (the number of new cases in a population every year) and its prevalence (the proportion of the population with CVD) are increasing, particularly in low- and middle-income countries. This increasing burden of CVD is occurring in parallel with a global increase in the incidence and prevalence of obesity—having an unhealthy amount of body fat (adiposity)—and of metabolic diseases—conditions such as diabetes in which metabolism (the processes that the body uses to make energy from food) is disrupted, with resulting high blood sugar and damage to the blood vessels.
Why Was This Study Done?
Epidemiological studies—investigations that record the patterns and causes of disease in populations—have reported an association between adiposity (indicated by an increased body mass index [BMI], which is calculated by dividing body weight in kilograms by height in meters squared) and cardiometabolic traits such as coronary heart disease, stroke, heart failure (a condition in which the heart is incapable of pumping sufficient amounts of blood around the body), diabetes, high blood pressure (hypertension), and high blood cholesterol (dyslipidemia). However, observational studies cannot prove that adiposity causes any particular cardiometabolic trait because overweight individuals may share other characteristics (confounding factors) that are the real causes of both obesity and the cardiometabolic disease. Moreover, it is possible that having CVD or a metabolic disease causes obesity (reverse causation). For example, individuals with heart failure cannot do much exercise, so heart failure may cause obesity rather than vice versa. Here, the researchers use “Mendelian randomization” to examine whether adiposity is causally related to various cardiometabolic traits. Because gene variants are inherited randomly, they are not prone to confounding and are free from reverse causation. It is known that a genetic variant (rs9939609) within the genome region that encodes the fat-mass- and obesity-associated gene (FTO) is associated with increased BMI. Thus, an investigation of the associations between rs9939609 and cardiometabolic traits can indicate whether obesity is causally related to these traits.
What Did the Researchers Do and Find?
The researchers analyzed the association between rs9939609 (the “instrumental variable,” or IV) and BMI, between rs9939609 and 24 cardiometabolic traits, and between BMI and the same traits using genetic and health data collected in 36 population-based studies of nearly 200,000 individuals of European descent. They then quantified the strength of the causal association between BMI and the cardiometabolic traits by calculating “IV estimators.” Higher BMI showed a causal relationship with heart failure, metabolic syndrome (a combination of medical disorders that increases the risk of developing CVD), type 2 diabetes, dyslipidemia, hypertension, increased blood levels of liver enzymes (an indicator of liver damage; some metabolic disorders involve liver damage), and several other cardiometabolic traits. All the IV estimators were similar to the BMI–cardiovascular trait associations (observational estimates) derived from the same individuals, with the exception of diabetes, where the causal estimate was higher than the observational estimate, probably because the observational estimate is based on a single BMI measurement, whereas the causal estimate considers lifetime changes in BMI.
What Do These Findings Mean?
Like all Mendelian randomization studies, the reliability of the causal associations reported here depends on several assumptions made by the researchers. Nevertheless, these findings provide support for many previously suspected and biologically plausible causal relationships, such as that between adiposity and hypertension. They also provide new insights into the causal effect of obesity on liver enzyme levels and on heart failure. In the latter case, these findings suggest that a one-unit increase in BMI might increase the incidence of heart failure by 17%. In the US, this corresponds to 113,000 additional cases of heart failure for every unit increase in BMI at the population level. Although additional studies are needed to confirm and extend these findings, these results suggest that global efforts to reduce the burden of obesity will likely also reduce the occurrence of CVD and metabolic disorders.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001474.
The American Heart Association provides information on all aspects of cardiovascular disease and tips on keeping the heart healthy, including weight management (in several languages); its website includes personal stories about stroke and heart attacks
The US Centers for Disease Control and Prevention has information on heart disease, stroke, and all aspects of overweight and obesity (in English and Spanish)
The UK National Health Service Choices website provides information about cardiovascular disease and obesity, including a personal story about losing weight
The World Health Organization provides information on obesity (in several languages)
The International Obesity Taskforce provides information about the global obesity epidemic
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
MedlinePlus provides links to other sources of information on heart disease, on vascular disease, on obesity, and on metabolic disorders (in English and Spanish)
The International Association for the Study of Obesity provides maps and information about obesity worldwide
The International Diabetes Federation has a web page that describes types, complications, and risk factors of diabetes
doi:10.1371/journal.pmed.1001474
PMCID: PMC3692470  PMID: 23824655
19.  Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits 
Randall, Joshua C. | Winkler, Thomas W. | Kutalik, Zoltán | Berndt, Sonja I. | Jackson, Anne U. | Monda, Keri L. | Kilpeläinen, Tuomas O. | Esko, Tõnu | Mägi, Reedik | Li, Shengxu | Workalemahu, Tsegaselassie | Feitosa, Mary F. | Croteau-Chonka, Damien C. | Day, Felix R. | Fall, Tove | Ferreira, Teresa | Gustafsson, Stefan | Locke, Adam E. | Mathieson, Iain | Scherag, Andre | Vedantam, Sailaja | Wood, Andrew R. | Liang, Liming | Steinthorsdottir, Valgerdur | Thorleifsson, Gudmar | Dermitzakis, Emmanouil T. | Dimas, Antigone S. | Karpe, Fredrik | Min, Josine L. | Nicholson, George | Clegg, Deborah J. | Person, Thomas | Krohn, Jon P. | Bauer, Sabrina | Buechler, Christa | Eisinger, Kristina | Bonnefond, Amélie | Froguel, Philippe | Hottenga, Jouke-Jan | Prokopenko, Inga | Waite, Lindsay L. | Harris, Tamara B. | Smith, Albert Vernon | Shuldiner, Alan R. | McArdle, Wendy L. | Caulfield, Mark J. | Munroe, Patricia B. | Grönberg, Henrik | Chen, Yii-Der Ida | Li, Guo | Beckmann, Jacques S. | Johnson, Toby | Thorsteinsdottir, Unnur | Teder-Laving, Maris | Khaw, Kay-Tee | Wareham, Nicholas J. | Zhao, Jing Hua | Amin, Najaf | Oostra, Ben A. | Kraja, Aldi T. | Province, Michael A. | Cupples, L. Adrienne | Heard-Costa, Nancy L. | Kaprio, Jaakko | Ripatti, Samuli | Surakka, Ida | Collins, Francis S. | Saramies, Jouko | Tuomilehto, Jaakko | Jula, Antti | Salomaa, Veikko | Erdmann, Jeanette | Hengstenberg, Christian | Loley, Christina | Schunkert, Heribert | Lamina, Claudia | Wichmann, H. Erich | Albrecht, Eva | Gieger, Christian | Hicks, Andrew A. | Johansson, Åsa | Pramstaller, Peter P. | Kathiresan, Sekar | Speliotes, Elizabeth K. | Penninx, Brenda | Hartikainen, Anna-Liisa | Jarvelin, Marjo-Riitta | Gyllensten, Ulf | Boomsma, Dorret I. | Campbell, Harry | Wilson, James F. | Chanock, Stephen J. | Farrall, Martin | Goel, Anuj | Medina-Gomez, Carolina | Rivadeneira, Fernando | Estrada, Karol | Uitterlinden, André G. | Hofman, Albert | Zillikens, M. Carola | den Heijer, Martin | Kiemeney, Lambertus A. | Maschio, Andrea | Hall, Per | Tyrer, Jonathan | Teumer, Alexander | Völzke, Henry | Kovacs, Peter | Tönjes, Anke | Mangino, Massimo | Spector, Tim D. | Hayward, Caroline | Rudan, Igor | Hall, Alistair S. | Samani, Nilesh J. | Attwood, Antony Paul | Sambrook, Jennifer G. | Hung, Joseph | Palmer, Lyle J. | Lokki, Marja-Liisa | Sinisalo, Juha | Boucher, Gabrielle | Huikuri, Heikki | Lorentzon, Mattias | Ohlsson, Claes | Eklund, Niina | Eriksson, Johan G. | Barlassina, Cristina | Rivolta, Carlo | Nolte, Ilja M. | Snieder, Harold | Van der Klauw, Melanie M. | Van Vliet-Ostaptchouk, Jana V. | Gejman, Pablo V. | Shi, Jianxin | Jacobs, Kevin B. | Wang, Zhaoming | Bakker, Stephan J. L. | Mateo Leach, Irene | Navis, Gerjan | van der Harst, Pim | Martin, Nicholas G. | Medland, Sarah E. | Montgomery, Grant W. | Yang, Jian | Chasman, Daniel I. | Ridker, Paul M. | Rose, Lynda M. | Lehtimäki, Terho | Raitakari, Olli | Absher, Devin | Iribarren, Carlos | Basart, Hanneke | Hovingh, Kees G. | Hyppönen, Elina | Power, Chris | Anderson, Denise | Beilby, John P. | Hui, Jennie | Jolley, Jennifer | Sager, Hendrik | Bornstein, Stefan R. | Schwarz, Peter E. H. | Kristiansson, Kati | Perola, Markus | Lindström, Jaana | Swift, Amy J. | Uusitupa, Matti | Atalay, Mustafa | Lakka, Timo A. | Rauramaa, Rainer | Bolton, Jennifer L. | Fowkes, Gerry | Fraser, Ross M. | Price, Jackie F. | Fischer, Krista | KrjutÅ¡kov, Kaarel | Metspalu, Andres | Mihailov, Evelin | Langenberg, Claudia | Luan, Jian'an | Ong, Ken K. | Chines, Peter S. | Keinanen-Kiukaanniemi, Sirkka M. | Saaristo, Timo E. | Edkins, Sarah | Franks, Paul W. | Hallmans, Göran | Shungin, Dmitry | Morris, Andrew David | Palmer, Colin N. A. | Erbel, Raimund | Moebus, Susanne | Nöthen, Markus M. | Pechlivanis, Sonali | Hveem, Kristian | Narisu, Narisu | Hamsten, Anders | Humphries, Steve E. | Strawbridge, Rona J. | Tremoli, Elena | Grallert, Harald | Thorand, Barbara | Illig, Thomas | Koenig, Wolfgang | Müller-Nurasyid, Martina | Peters, Annette | Boehm, Bernhard O. | Kleber, Marcus E. | März, Winfried | Winkelmann, Bernhard R. | Kuusisto, Johanna | Laakso, Markku | Arveiler, Dominique | Cesana, Giancarlo | Kuulasmaa, Kari | Virtamo, Jarmo | Yarnell, John W. G. | Kuh, Diana | Wong, Andrew | Lind, Lars | de Faire, Ulf | Gigante, Bruna | Magnusson, Patrik K. E. | Pedersen, Nancy L. | Dedoussis, George | Dimitriou, Maria | Kolovou, Genovefa | Kanoni, Stavroula | Stirrups, Kathleen | Bonnycastle, Lori L. | Njølstad, Inger | Wilsgaard, Tom | Ganna, Andrea | Rehnberg, Emil | Hingorani, Aroon | Kivimaki, Mika | Kumari, Meena | Assimes, Themistocles L. | Barroso, Inês | Boehnke, Michael | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Frayling, Timothy | Groop, Leif C. | Haritunians, Talin | Hunter, David | Ingelsson, Erik | Kaplan, Robert | Mohlke, Karen L. | O'Connell, Jeffrey R. | Schlessinger, David | Strachan, David P. | Stefansson, Kari | van Duijn, Cornelia M. | Abecasis, Gonçalo R. | McCarthy, Mark I. | Hirschhorn, Joel N. | Qi, Lu | Loos, Ruth J. F. | Lindgren, Cecilia M. | North, Kari E. | Heid, Iris M.
PLoS Genetics  2013;9(6):e1003500.
Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
Author Summary
Men and women differ substantially regarding height, weight, and body fat. Interestingly, previous work detecting genetic effects for waist-to-hip ratio, to assess body fat distribution, has found that many of these showed sex-differences. However, systematic searches for sex-differences in genetic effects have not yet been conducted. Therefore, we undertook a genome-wide search for sexually dimorphic genetic effects for anthropometric traits including 133,723 individuals in a large meta-analysis and followed promising variants in further 137,052 individuals, including a total of 94 studies. We identified seven loci with significant sex-difference including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were significant in women, but not in men. Of interest is that sex-difference was only observed for waist phenotypes, but not for height or body-mass-index. We found no evidence for sex-differences with opposite effect direction for men and women. The PPARG locus is of specific interest due to its link to diabetes genetics and therapy. Our findings demonstrate the importance of investigating sex differences, which may lead to a better understanding of disease mechanisms with a potential relevance to treatment options.
doi:10.1371/journal.pgen.1003500
PMCID: PMC3674993  PMID: 23754948
20.  A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance 
Manning, Alisa K. | Hivert, Marie-France | Scott, Robert A. | Grimsby, Jonna L. | Bouatia-Naji, Nabila | Chen, Han | Rybin, Denis | Liu, Ching-Ti | Bielak, Lawrence F. | Prokopenko, Inga | Amin, Najaf | Barnes, Daniel | Cadby, Gemma | Hottenga, Jouke-Jan | Ingelsson, Erik | Jackson, Anne U. | Johnson, Toby | Kanoni, Stavroula | Ladenvall, Claes | Lagou, Vasiliki | Lahti, Jari | Lecoeur, Cecile | Liu, Yongmei | Martinez-Larrad, Maria Teresa | Montasser, May E. | Navarro, Pau | Perry, John R. B. | Rasmussen-Torvik, Laura J. | Salo, Perttu | Sattar, Naveed | Shungin, Dmitry | Strawbridge, Rona J. | Tanaka, Toshiko | van Duijn, Cornelia M. | An, Ping | de Andrade, Mariza | Andrews, Jeanette S. | Aspelund, Thor | Atalay, Mustafa | Aulchenko, Yurii | Balkau, Beverley | Bandinelli, Stefania | Beckmann, Jacques S. | Beilby, John P. | Bellis, Claire | Bergman, Richard N. | Blangero, John | Boban, Mladen | Boehnke, Michael | Boerwinkle, Eric | Bonnycastle, Lori L. | Boomsma, Dorret I. | Borecki, Ingrid B. | Böttcher, Yvonne | Bouchard, Claude | Brunner, Eric | Budimir, Danijela | Campbell, Harry | Carlson, Olga | Chines, Peter S. | Clarke, Robert | Collins, Francis S. | Corbatón-Anchuelo, Arturo | Couper, David | de Faire, Ulf | Dedoussis, George V | Deloukas, Panos | Dimitriou, Maria | Egan, Josephine M | Eiriksdottir, Gudny | Erdos, Michael R. | Eriksson, Johan G. | Eury, Elodie | Ferrucci, Luigi | Ford, Ian | Forouhi, Nita G. | Fox, Caroline S | Franzosi, Maria Grazia | Franks, Paul W | Frayling, Timothy M | Froguel, Philippe | Galan, Pilar | de Geus, Eco | Gigante, Bruna | Glazer, Nicole L. | Goel, Anuj | Groop, Leif | Gudnason, Vilmundur | Hallmans, Göran | Hamsten, Anders | Hansson, Ola | Harris, Tamara B. | Hayward, Caroline | Heath, Simon | Hercberg, Serge | Hicks, Andrew A. | Hingorani, Aroon | Hofman, Albert | Hui, Jennie | Hung, Joseph | Jarvelin, Marjo Riitta | Jhun, Min A. | Johnson, Paul C.D. | Jukema, J Wouter | Jula, Antti | Kao, W.H. | Kaprio, Jaakko | Kardia, Sharon L. R. | Keinanen-Kiukaanniemi, Sirkka | Kivimaki, Mika | Kolcic, Ivana | Kovacs, Peter | Kumari, Meena | Kuusisto, Johanna | Kyvik, Kirsten Ohm | Laakso, Markku | Lakka, Timo | Lannfelt, Lars | Lathrop, G Mark | Launer, Lenore J. | Leander, Karin | Li, Guo | Lind, Lars | Lindstrom, Jaana | Lobbens, Stéphane | Loos, Ruth J. F. | Luan, Jian’an | Lyssenko, Valeriya | Mägi, Reedik | Magnusson, Patrik K. E. | Marmot, Michael | Meneton, Pierre | Mohlke, Karen L. | Mooser, Vincent | Morken, Mario A. | Miljkovic, Iva | Narisu, Narisu | O’Connell, Jeff | Ong, Ken K. | Oostra, Ben A. | Palmer, Lyle J. | Palotie, Aarno | Pankow, James S. | Peden, John F. | Pedersen, Nancy L. | Pehlic, Marina | Peltonen, Leena | Penninx, Brenda | Pericic, Marijana | Perola, Markus | Perusse, Louis | Peyser, Patricia A | Polasek, Ozren | Pramstaller, Peter P. | Province, Michael A. | Räikkönen, Katri | Rauramaa, Rainer | Rehnberg, Emil | Rice, Ken | Rotter, Jerome I. | Rudan, Igor | Ruokonen, Aimo | Saaristo, Timo | Sabater-Lleal, Maria | Salomaa, Veikko | Savage, David B. | Saxena, Richa | Schwarz, Peter | Seedorf, Udo | Sennblad, Bengt | Serrano-Rios, Manuel | Shuldiner, Alan R. | Sijbrands, Eric J.G. | Siscovick, David S. | Smit, Johannes H. | Small, Kerrin S. | Smith, Nicholas L. | Smith, Albert Vernon | Stančáková, Alena | Stirrups, Kathleen | Stumvoll, Michael | Sun, Yan V. | Swift, Amy J. | Tönjes, Anke | Tuomilehto, Jaakko | Trompet, Stella | Uitterlinden, Andre G. | Uusitupa, Matti | Vikström, Max | Vitart, Veronique | Vohl, Marie-Claude | Voight, Benjamin F. | Vollenweider, Peter | Waeber, Gerard | Waterworth, Dawn M | Watkins, Hugh | Wheeler, Eleanor | Widen, Elisabeth | Wild, Sarah H. | Willems, Sara M. | Willemsen, Gonneke | Wilson, James F. | Witteman, Jacqueline C.M. | Wright, Alan F. | Yaghootkar, Hanieh | Zelenika, Diana | Zemunik, Tatijana | Zgaga, Lina | Wareham, Nicholas J. | McCarthy, Mark I. | Barroso, Ines | Watanabe, Richard M. | Florez, Jose C. | Dupuis, Josée | Meigs, James B. | Langenberg, Claudia
Nature genetics  2012;44(6):659-669.
Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and beta-cell dysfunction, but contributed little to our understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways may be uncovered by accounting for differences in body mass index (BMI) and potential interaction between BMI and genetic variants. We applied a novel joint meta-analytical approach to test associations with fasting insulin (FI) and glucose (FG) on a genome-wide scale. We present six previously unknown FI loci at P<5×10−8 in combined discovery and follow-up analyses of 52 studies comprising up to 96,496non-diabetic individuals. Risk variants were associated with higher triglyceride and lower HDL cholesterol levels, suggestive of a role for these FI loci in insulin resistance pathways. The localization of these additional loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.
doi:10.1038/ng.2274
PMCID: PMC3613127  PMID: 22581228
21.  Outcome-Driven Thresholds for Home Blood Pressure Measurement 
Hypertension  2012;61(1):27-34.
The lack of outcome-driven operational thresholds limits the clinical application of home blood pressure (BP) measurement. Our objective was to determine an outcome-driven reference frame for home BP measurement. We measured home and clinic BP in 6470 participants (mean age, 59.3 years; 56.9% women; 22.4% on antihypertensive treatment) recruited in Ohasama, Japan (n=2520); Montevideo, Uruguay (n=399); Tsurugaya, Japan (n=811); Didima, Greece (n=665); and nationwide in Finland (n=2075). In multivariable-adjusted analyses of individual subject data, we determined home BP thresholds, which yielded 10-year cardiovascular risks similar to those associated with stages 1 (120/80 mm Hg) and 2 (130/85 mm Hg) prehypertension, and stages 1 (140/90 mm Hg) and 2 (160/100 mm Hg) hypertension on clinic measurement. During 8.3 years of follow-up (median), 716 cardiovascular end points, 294 cardiovascular deaths, 393 strokes, and 336 cardiac events occurred in the whole cohort; in untreated participants these numbers were 414, 158, 225, and 194, respectively. In the whole cohort, outcome-driven systolic/diastolic thresholds for the home BP corresponding with stages 1 and 2 prehypertension and stages 1 and 2 hypertension were 121.4/77.7, 127.4/79.9, 133.4/82.2, and 145.4/86.8 mm Hg; in 5018 untreated participants, these thresholds were 118.5/76.9, 125.2/79.7, 131.9/82.4, and 145.3/87.9 mm Hg, respectively. Rounded thresholds for stages 1 and 2 prehypertension and stages 1 and 2 hypertension amounted to 120/75, 125/80, 130/85, and 145/90 mm Hg, respectively. Population-based outcome-driven thresholds for home BP are slightly lower than those currently proposed in hypertension guidelines. Our current findings could inform guidelines and help clinicians in diagnosing and managing patients.
doi:10.1161/HYPERTENSIONAHA.111.00100
PMCID: PMC3607331  PMID: 23129700
home blood pressure measurement; blood pressure; hypertension; epidemiology; thresholds
22.  The International Database of HOme blood pressure in relation to Cardiovascular Outcome (IDHOCO): moving from baseline characteristics to research perspectives 
The objective of this study is to construct an International Database of HOme blood pressure in relation to Cardiovascular Outcome (IDHOCO). The main goal of this database is to determine outcome-based diagnostic thresholds for the self-measured home blood pressure (BP). Secondary objectives include investigating the predictive value of white-coat and masked hypertension, morning and evening BP, BP and heart rate variability, and the home arterial stiffness index. We also aim to determine an optimal schedule for home BP measurements that provides the most accurate risk stratification. Eligible studies are population-based, have fatal as well as nonfatal outcomes available for analysis, comply with ethical standards, and have been previously published in peer-reviewed journals. In a meta-analysis based on individual subject data, composite and cause-specific cardiovascular events will be related to various indexes derived by home BP measurement. The analyses will be stratified by a cohort and adjusted for the clinic BP and established cardiovascular risk factors. The database includes 6753 subjects from five cohorts recruited in Ohasama, Japan (n = 2777); Finland (n = 2075); Tsurugaya, Japan (n = 836); Didima, Greece (n = 665); and Montevideo, Uruguay (n = 400). In these five cohorts, during a total of 62 106 person-years of follow-up (mean 9.2 years), 852 subjects died and 740 participants experienced a fatal or nonfatal cardiovascular event. IDHOCO provides a unique opportunity to investigate several hypotheses that could not reliably be studied in individual studies. The results of these analyses should be of help to clinicians involved in the management of patients with suspected or established hypertension.
doi:10.1038/hr.2012.97
PMCID: PMC3606707  PMID: 22763485
BP measurement; epidemiology; home; self-measurement
23.  Genome-wide association study identifies multiple loci influencing human serum metabolite levels 
Nature genetics  2012;44(3):269-276.
Nuclear magnetic resonance assays allow for measurement of a wide range of metabolic phenotypes. We report here the results of a GWAS on 8,330 Finnish individuals genotyped and imputed at 7.7 million SNPs for a range of 216 serum metabolic phenotypes assessed by NMR of serum samples. We identified significant associations (P < 2.31 × 10−10) at 31 loci, including 11 for which there have not been previous reports of associations to a metabolic trait or disorder. Analyses of Finnish twin pairs suggested that the metabolic measures reported here show higher heritability than comparable conventional metabolic phenotypes. In accordance with our expectations, SNPs at the 31 loci associated with individual metabolites account for a greater proportion of the genetic component of trait variance (up to 40%) than is typically observed for conventional serum metabolic phenotypes. The identification of such associations may provide substantial insight into cardiometabolic disorders.
doi:10.1038/ng.1073
PMCID: PMC3605033  PMID: 22286219
24.  Causal Relationship between Obesity and Vitamin D Status: Bi-Directional Mendelian Randomization Analysis of Multiple Cohorts 
PLoS Medicine  2013;10(2):e1001383.
A mendelian randomization study based on data from multiple cohorts conducted by Karani Santhanakrishnan Vimaleswaran and colleagues re-examines the causal nature of the relationship between vitamin D levels and obesity.
Background
Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis.
Methods and Findings
We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects.
Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10−27). The BMI allele score was associated both with BMI (p = 6.30×10−62) and 25(OH)D (−0.06% [95% CI −0.10 to −0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10−57 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: −4.2 [95% CI −7.1 to −1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores).
Conclusions
On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Obesity—having an unhealthy amount of body fat—is increasing worldwide. In the US, for example, a third of the adult population is now obese. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Although there is a genetic contribution to obesity, people generally become obese by consuming food and drink that contains more energy than they need for their daily activities. Thus, obesity can be prevented by having a healthy diet and exercising regularly. Compared to people with a healthy weight, obese individuals have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. They also have a higher risk of vitamin D deficiency, another increasingly common public health concern. Vitamin D, which is essential for healthy bones as well as other functions, is made in the skin after exposure to sunlight but can also be obtained through the diet and through supplements.
Why Was This Study Done?
Observational studies cannot prove that obesity causes vitamin D deficiency because obese individuals may share other characteristics that reduce their circulating 25-hydroxy vitamin D [25(OH)D] levels (referred to as confounding). Moreover, observational studies cannot indicate whether the larger vitamin D storage capacity of obese individuals (vitamin D is stored in fatty tissues) lowers their 25(OH)D levels or whether 25(OH)D levels influence fat accumulation (reverse causation). If obesity causes vitamin D deficiency, monitoring and treating vitamin D deficiency might alleviate some of the adverse health effects of obesity. Conversely, if low vitamin D levels cause obesity, encouraging people to take vitamin D supplements might help to control the obesity epidemic. Here, the researchers use bi-directional “Mendelian randomization” to examine the direction and causality of the relationship between BMI and 25(OH)D. In Mendelian randomization, causality is inferred from associations between genetic variants that mimic the influence of a modifiable environmental exposure and the outcome of interest. Because gene variants do not change over time and are inherited randomly, they are not prone to confounding and are free from reverse causation. Thus, if a lower vitamin D status leads to obesity, genetic variants associated with lower 25(OH)D concentrations should be associated with higher BMI, and if obesity leads to a lower vitamin D status, then genetic variants associated with higher BMI should be associated with lower 25(OH)D concentrations.
What Did the Researchers Do and Find?
The researchers created a “BMI allele score” based on 12 BMI-related gene variants and two “25(OH)D allele scores,” which are based on gene variants that affect either 25(OH)D synthesis or breakdown. Using information on up to 42,024 participants from 21 studies, the researchers showed that the BMI allele score was associated with both BMI and with 25(OH)D levels among the study participants. Based on this information, they calculated that each 10% increase in BMI will lead to a 4.2% decrease in 25(OH)D concentrations. By contrast, although both 25(OH)D allele scores were strongly associated with 25(OH)D levels, neither score was associated with BMI. This lack of an association between 25(OH)D allele scores and obesity was confirmed using data from more than 100,000 individuals involved in 46 studies that has been collected by the GIANT (Genetic Investigation of Anthropometric Traits) consortium.
What Do These Findings Mean?
These findings suggest that a higher BMI leads to a lower vitamin D status whereas any effects of low vitamin D status on BMI are likely to be small. That is, these findings provide evidence for obesity as a causal factor in the development of vitamin D deficiency but not for vitamin D deficiency as a causal factor in the development of obesity. These findings suggest that population-level interventions to reduce obesity should lead to a reduction in the prevalence of vitamin D deficiency and highlight the importance of monitoring and treating vitamin D deficiency as a means of alleviating the adverse influences of obesity on health.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001383.
The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish); a data brief provides information about the vitamin D status of the US population
The World Health Organization provides information on obesity (in several languages)
The UK National Health Service Choices website provides detailed information about obesity and a link to a personal story about losing weight; it also provides information about vitamin D
The International Obesity Taskforce provides information about the global obesity epidemic
The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish)
The US Office of Dietary Supplements provides information about vitamin D (in English and Spanish)
MedlinePlus has links to further information about obesity and about vitamin D (in English and Spanish)
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
Overview and details of the collaborative large-scale genetic association study (D-CarDia) provide information about vitamin D and the risk of cardiovascular disease, diabetes and related traits
doi:10.1371/journal.pmed.1001383
PMCID: PMC3564800  PMID: 23393431
25.  Genome-Wide Screen for Metabolic Syndrome Susceptibility Loci Reveals Strong Lipid Gene Contribution but No Evidence for Common Genetic Basis for Clustering of Metabolic Syndrome Traits 
Background
Genome-wide association (GWA) studies have identified several susceptibility loci for metabolic syndrome (MetS) component traits, but have had variable success in identifying susceptibility loci to the syndrome as an entity. We conducted a GWA study on MetS and its component traits in four Finnish cohorts consisting of 2637 MetS cases and 7927 controls, both free of diabetes, and followed the top loci in an independent sample with transcriptome and NMR-based metabonomics data. Furthermore, we tested for loci associated with multiple MetS component traits using factor analysis and built a genetic risk score for MetS.
Methods and Results
A previously known lipid locus, APOA1/C3/A4/A5 gene cluster region (SNP rs964184), was associated with MetS in all four study samples (P=7.23×10−9 in meta-analysis). The association was further supported by serum metabolite analysis, where rs964184 associated with various VLDL, TG, and HDL metabolites (P=0.024-1.88×10−5). Twenty-two previously identified susceptibility loci for individual MetS component traits were replicated in our GWA and factor analysis. Most of these associated with lipid phenotypes and none with two or more uncorrelated MetS components. A genetic risk score, calculated as the number of alleles in loci associated with individual MetS traits, was strongly associated with MetS status.
Conclusions
Our findings suggest that genes from lipid metabolism pathways have the key role in the genetic background of MetS. We found little evidence for pleiotropy linking dyslipidemia and obesity to the other MetS component traits such as hypertension and glucose intolerance.
doi:10.1161/CIRCGENETICS.111.961482
PMCID: PMC3378651  PMID: 22399527
metabolic syndrome; risk factors; genome-wide association study; meta-analysis; lipids

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