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1. SCORE2-OP risk prediction algorithms: estimating incident cardiovascular event risk in older persons in four geographical risk regions

Author

Vries, T.I. de, Cooney, M.T., Selmer, R.M., Hageman, S.H.J., Pennells, L.A., Wood, A., Kaptoge, S., Xu, Z., Westerink, J., Rabanal, K.S., Tell, G.S., Meyer, H.E., Igland, J., Ariansen, I., Matsushita, K., Blaha, M.J., Nambi, V., Peters, R., Beckett, N., Antikainen, R., Bulpitt, C.J., Muller, M., Emmelot-Vonk, M.H., Trompet, S., Jukema, W., Ference, B.A., Halle, M., Timmis, A.D., Vardas, P.E., Dorresteijn, J.A.N., Bacquer, D. de, Angelantonio, E. di, Visseren, F.L.J., Graham, I.M., SCORE2-OP Working Grp, ESC Cardiovasc Risk Collaboration, Internal medicine, ACS - Atherosclerosis & ischemic syndromes, and APH - Aging & Later Life

Subjects
Cardiovascular event, Male, Myocardial Infarction, Blood Pressure, 030204 cardiovascular system & hematology, 03 medical and health sciences, 0302 clinical medicine, Clinical Research, Risk Factors, Primary prevention, Environmental health, Medicine, Humans, 030212 general & internal medicine, Aged, Risk assessment, Aged, 80 and over, business.industry, 10-Year CVD risk, Cardiovascular disease, Risk prediction, Stroke, Prediction algorithms, Older persons, Cardiovascular Diseases, Heart Disease Risk Factors, Female, Cardiology and Cardiovascular Medicine, business, Algorithms
Abstract

Aims The aim of this study was to derive and validate the SCORE2-Older Persons (SCORE2-OP) risk model to estimate 5- and 10-year risk of cardiovascular disease (CVD) in individuals aged over 70 years in four geographical risk regions. Methods and results Sex-specific competing risk-adjusted models for estimating CVD risk (CVD mortality, myocardial infarction, or stroke) were derived in individuals aged over 65 without pre-existing atherosclerotic CVD from the Cohort of Norway (28 503 individuals, 10 089 CVD events). Models included age, smoking status, diabetes, systolic blood pressure, and total- and high-density lipoprotein cholesterol. Four geographical risk regions were defined based on country-specific CVD mortality rates. Models were recalibrated to each region using region-specific estimated CVD incidence rates and risk factor distributions. For external validation, we analysed data from 6 additional study populations {338 615 individuals, 33 219 CVD validation cohorts, C-indices ranged between 0.63 [95% confidence interval (CI) 0.61–0.65] and 0.67 (0.64–0.69)}. Regional calibration of expected-vs.-observed risks was satisfactory. For given risk factor profiles, there was substantial variation across the four risk regions in the estimated 10-year CVD event risk. Conclusions The competing risk-adjusted SCORE2-OP model was derived, recalibrated, and externally validated to estimate 5- and 10-year CVD risk in older adults (aged 70 years or older) in four geographical risk regions. These models can be used for communicating the risk of CVD and potential benefit from risk factor treatment and may facilitate shared decision-making between clinicians and patients in CVD risk management in older persons.

Published
2021

3. Effect of alirocumab on lipoprotein(a) and cardiovascular risk after acute coronary syndrome

Author

Bittner, V. A. (Vera A.), Szarek, M. (Michael), Aylward, P. E. (Philip E.), Bhatt, D. L. (Deepak L.), Diaz, R. (Rafael), Edelberg, J. M. (Jay M.), Fras, Z. (Zlatko), Goodman, S. G. (Shaun G.), Halvorsen, S. (Sigrun), Hanotin, C. (Corinne), Harrington, R. A. (Robert A.), Jukema, W. (Wouter), Loizeau, V. (Virginie), Moriarty, P. M. (Patrick M.), Moryusef, A. (Angèle), Pordy, R. (Robert), Roe, M. T. (Matthew T.), Sinnaeve, P. (Peter), Tsimikas, S. (Sotirios), Vogel, R. (Robert), White, H. D. (Harvey D.), Zahger, D. (Doron), Zeiher, A. M. (Andreas M.), Steg, G. (Gabriel), Schwartz, G. G. (Gregory G.), and Huikuri, H. (Heikki)

Subjects
low-density lipoprotein cholesterol, proprotein convertase subtilisin/kexin type 9 inhibition, lipids (amino acids, peptides, and proteins), acute coronary syndromes, alirocumab, cardiovascular diseases, major adverse cardiovascular events
Abstract

Background: Lipoprotein(a) concentration is associated with cardiovascular events. Alirocumab, a proprotein convertase subtilisin/kexin type 9 inhibitor, lowers lipoprotein(a) and low-density lipoprotein cholesterol (LDL-C). Objectives: A pre-specified analysis of the placebo-controlled ODYSSEY Outcomes trial in patients with recent acute coronary syndrome (ACS) determined whether alirocumab-induced changes in lipoprotein(a) and LDL-C independently predicted major adverse cardiovascular events (MACE). Methods: One to 12 months after ACS, 18,924 patients on high-intensity statin therapy were randomized to alirocumab or placebo and followed for 2.8 years (median). Lipoprotein(a) was measured at randomization and 4 and 12 months thereafter. The primary MACE outcome was coronary heart disease death, nonfatal myocardial infarction, ischemic stroke, or hospitalization for unstable angina. Results: Baseline lipoprotein(a) levels (median: 21.2 mg/dl; interquartile range [IQR]: 6.7 to 59.6 mg/dl) and LDL-C [corrected for cholesterol content in lipoprotein(a)] predicted MACE. Alirocumab reduced lipoprotein(a) by 5.0 mg/dl (IQR: 0 to 13.5 mg/dl), corrected LDL-C by 51.1 mg/dl (IQR: 33.7 to 67.2 mg/dl), and reduced the risk of MACE (hazard ratio [HR]: 0.85; 95% confidence interval [CI]: 0.78 to 0.93). Alirocumab-induced reductions of lipoprotein(a) and corrected LDL-C independently predicted lower risk of MACE, after adjustment for baseline concentrations of both lipoproteins and demographic and clinical characteristics. A 1-mg/dl reduction in lipoprotein(a) with alirocumab was associated with a HR of 0.994 (95% CI: 0.990 to 0.999; p = 0.0081). Conclusions: Baseline lipoprotein(a) and corrected LDL-C levels and their reductions by alirocumab predicted the risk of MACE after recent ACS. Lipoprotein(a) lowering by alirocumab is an independent contributor to MACE reduction, which suggests that lipoprotein(a) should be an independent treatment target after ACS. (ODYSSEY Outcomes: Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab; NCT01663402)

Published
2020

7. Testing cognitive function in elderly populations: the PROSPER study. (Paper)

Author

Houx, P.J., Shepherd, J., Blauw, G-J., Murphy, M.B., Ford, I., Bollen, E.L., Buckley, B., Stott, D.J., Jukema, W., Hyland, M., Gaw, A., Norrie, J., Kamper, A.M., Perry, I.J., MacFarlane, P.W., Meinders, A. Edo, Sweeney, B.J., Packard, C.J., Twomey, C., Cobbe, S.M., and Westendorp, R.G.

Subjects
Cognition disorders in old age -- Diagnosis -- Research, Examinations -- Validity, Neuropsychological tests -- Evaluation -- Research, Health, Psychology and mental health, Diagnosis, Evaluation, Research
Abstract

Objectives: For large scale follow up studies with non-demented patients in which cognition is an endpoint, there is a need for short, inexpensive, sensitive, and reliable neuropsychological tests that are [...]

Published
2002

13. Mendelian randomization analysis of cholesteryl ester transfer protein and subclinical atherosclerosis: A population-based study

Author

Christen, T., Trompet, S., Noordam, R., Blauw, L.L., Gast, K.B., Rensen, P.C.N., Dijk, K.W. van, Rosendaal, F.R., Mutsert, R. de, Jukema, W., and NEO Study

Subjects
0301 basic medicine, Male, Epidemiology, Endocrinology, Diabetes and Metabolism, 030204 cardiovascular system & hematology, Carotid Intima-Media Thickness, Body Mass Index, Cohort Studies, chemistry.chemical_compound, 0302 clinical medicine, Anacetrapib, Risk Factors, Medicine, Ultrasonography, education.field_of_study, Nutrition and Dietetics, Framingham Risk Score, biology, Cohort, Mendelian Randomization Analysis, Middle Aged, Cholesterol, lipids (amino acids, peptides, and proteins), Female, Cardiology and Cardiovascular Medicine, Cohort study, Adult, medicine.medical_specialty, Genotype, Population, Polymorphism, Single Nucleotide, 03 medical and health sciences, Internal medicine, Cholesterylester transfer protein, Mendelian randomization, Internal Medicine, Humans, education, Alleles, Triglycerides, Aged, business.industry, Atherosclerosis, Cholesterol Ester Transfer Proteins, 030104 developmental biology, Endocrinology, Reverse cholesterol transport, chemistry, biology.protein, business, Body mass index
Abstract

Background Several trials to prevent cardiovascular disease by inhibiting cholesteryl ester transfer protein (CETP) have failed, except Randomized EValuation of the Effects of Anacetrapib through Lipid-modification. Thus far, it is unclear to what extent CETP is causally related to measures of atherosclerosis. Objective The aim of the article was to study the causal relationship between genetically determined CETP concentration and carotid intima-media thickness (cIMT) in a population-based cohort study. Methods In the Netherlands Epidemiology of Obesity study, participants were genotyped, and cIMT was measured by ultrasonography. We examined the relation between a weighted genetic risk score for CETP concentration, based on 3 single-nucleotide polymorphisms that have previously been shown to largely determine CETP concentration and cIMT using Mendelian randomization in the total population and in strata by sex, Framingham 10-year risk, (pre)diabetes, high-density lipoprotein cholesterol, triglycerides, and statin use. Results We analyzed 5655 participants (56% women) with a mean age of 56 (range 44–66) years, body mass index of 26 (range 17–61) kg/m 2 , and serum CETP of 2.47 (range 0.68–5.33) μg/mL. There was no evidence for a causal relation between genetically determined CETP and cIMT in the total population, but associations were differently directed in men (16 μm per μg/mL increase in genetically determined CETP; 95% confidence interval: −8, 39) and women (−8 μm; −25, 9). Genetically determined CETP appeared to be associated with cIMT in normoglycemic men (26 μm; −1, 52) and in (pre)diabetic women (48 μm; −2, 98). Conclusion In this population-based study, there was no causal relation between genetically determined CETP concentration and cIMT in the total population although we observed directionally differing effects in men and women. Stratified results suggested associations in individuals with different cardiometabolic risk factor profiles, which require replication.

Published
2018

15. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Author

Justice, A. E. (Anne E.), Winkler, T. W. (Thomas W.), Feitosa, M. F. (Mary F.), Graff, M. (Misa), Fisher, V. A. (Virginia A.), Young, K. (Kristin), Barata, L. (Llilda), Deng, X. (Xuan), Czajkowski, J. (Jacek), Hadley, D. (David), Ngwa, J. S. (Julius S.), Ahluwalia, T. S. (Tarunveer S.), Chu, A. Y. (Audrey Y.), Heard-Costa, N. L. (Nancy L.), Lim, E. (Elise), Perez, J. (Jeremiah), Eicher, J. D. (John D.), Kutalik, Z. (Zoltan), Xue, L. (Luting), Mahajan, A. (Anubha), Renstrom, F. (Frida), Wu, J. (Joseph), Qi, Q. (Qibin), Ahmad, S. (Shafqat), Alfred, T. (Tamuno), Amin, N. (Najaf), Bielak, L. F. (Lawrence F.), Bonnefond, A. (Amelie), Bragg, J. (Jennifer), Cadby, G. (Gemma), Chittani, M. (Martina), Coggeshall, S. (Scott), Corre, T. (Tanguy), Direk, N. (Nese), Eriksson, J. (Joel), Fischer, K. (Krista), Gorski, M. (Mathias), Harder, M. N. (Marie Neergaard), Horikoshi, M. (Momoko), Huang, T. (Tao), Huffman, J. E. (Jennifer E.), Jackson, A. U. (Anne U.), Justesen, J. M. (Johanne Marie), Kanoni, S. (Stavroula), Kinnunen, L. (Leena), Kleber, M. E. (Marcus E.), Komulainen, P. (Pirjo), Kumari, M. (Meena), Lim, U. (Unhee), Luan, J. (Jian'an), Lyytikäinen, L.-P. (Leo-Pekka), Mangino, M. (Massimo), Manichaikul, A. (Ani), Marten, J. (Jonathan), Middelberg, R. P. (Rita P. S.), Mueller-Nurasyid, M. (Martina), Navarro, P. (Pau), Perusse, L. (Louis), Pervjakova, N. (Natalia), Sarti, C. (Cinzia), Smith, A. V. (Albert Vernon), Smith, J. A. (Jennifer A.), Stancakova, A. (Alena), Strawbridge, R. J. (Rona J.), Stringham, H. M. (Heather M.), Sung, Y. J. (Yun Ju), Tanaka, T. (Toshiko), Teumer, A. (Alexander), Trompet, S. (Stella), van der Laan, S. W. (Sander W.), van der Most, P. J. (Peter J.), Van Vliet-Ostaptchouk, J. V. (Jana V.), Vedantam, S. L. (Sailaja L.), Verweij, N. (Niek), Vink, J. M. (Jacqueline M.), Vitart, V. (Veronique), Wu, Y. (Ying), Yengo, L. (Loic), Zhang, W. (Weihua), Zhao, J. H. (Jing Hua), Zimmermann, M. E. (Martina E.), Zubair, N. (Niha), Abecasis, G. R. (Goncalo R.), Adair, L. S. (Linda S.), Afaq, S. (Saima), Afzal, U. (Uzma), Bakker, S. J. (Stephan J. L.), Bartz, T. M. (Traci M.), Beilby, J. (John), Bergman, R. N. (Richard N.), Bergmann, S. (Sven), Biffar, R. (Reiner), Blangero, J. (John), Boerwinkle, E. (Eric), Bonnycastle, L. L. (Lori L.), Bottinger, E. (Erwin), Braga, D. (Daniele), Buckley, B. M. (Brendan M.), Buyske, S. (Steve), Campbell, H. (Harry), Chambers, J. C. (John C.), Collins, F. S. (Francis S.), Curran, J. E. (Joanne E.), de Borst, G. J. (Gert J.), de Craen, A. J. (Anton J. M.), de Geus, E. J. (Eco J. C.), Dedoussis, G. (George), Delgado, G. E. (Graciela E.), den Ruijter, H. M. (Hester M.), Eiriksdottir, G. (Gudny), Eriksson, A. L. (Anna L.), Esko, T. (Tonu), Faul, J. D. (Jessica D.), Ford, I. (Ian), Forrester, T. (Terrence), Gertow, K. (Karl), Gigante, B. (Bruna), Glorioso, N. (Nicola), Gong, J. (Jian), Grallert, H. (Harald), Grammer, T. B. (Tanja B.), Grarup, N. (Niels), Haitjema, S. (Saskia), Hallmans, G. (Goran), Hamsten, A. (Anders), Hansen, T. (Torben), Harris, T. B. (Tamara B.), Hartman, C. A. (Catharina A.), Hassinen, M. (Maija), Hastie, N. D. (Nicholas D.), Heath, A. C. (Andrew C.), Hernandez, D. (Dena), Hindorff, L. (Lucia), Hocking, L. J. (Lynne J.), Hollensted, M. (Mette), Holmen, O. L. (Oddgeir L.), Homuth, G. (Georg), Hottenga, J. J. (Jouke Jan), Huang, J. (Jie), Hung, J. (Joseph), Hutri-Kähönen, N. (Nina), Ingelsson, E. (Erik), James, A. L. (Alan L.), Jansson, J.-O. (John-Olov), Järvelin, M.-R. (Marjo-Riitta), Jhun, M. A. (Min A.), Jorgensen, M. E. (Marit E.), Juonala, M. (Markus), Kähönen, M. (Mika), Karlsson, M. (Magnus), Koistinen, H. A. (Heikki A.), Kolcic, I. (Ivana), Kolovou, G. (Genovefa), Kooperberg, C. (Charles), Kramer, B. K. (Bernhard K.), Kuusisto, J. (Johanna), Kvaloy, K. (Kirsti), Lakka, T. A. (Timo A.), Langenberg, C. (Claudia), Launer, L. J. (Lenore J.), Leander, K. (Karin), Lee, N. R. (Nanette R.), Lind, L. (Lars), Lindgren, C. M. (Cecilia M.), Linneberg, A. (Allan), Lobbens, S. (Stephane), Loh, M. (Marie), Lorentzon, M. (Mattias), Luben, R. (Robert), Lubke, G. (Gitta), Ludolph-Donislawski, A. (Anja), Lupoli, S. (Sara), Madden, P. A. (Pamela A. F.), Männikkö, R. (Reija), Marques-Vidal, P. (Pedro), Martin, N. G. (Nicholas G.), McKenzie, C. A. (Colin A.), McKnight, B. (Barbara), Mellstrom, D. (Dan), Menni, C. (Cristina), Montgomery, G. W. (Grant W.), Musk, A. W. (A. W. (Bill)), Narisu, N. (Narisu), Nauck, M. (Matthias), Nolte, I. M. (Ilja M.), Oldehinkel, A. J. (Albertine J.), Olden, M. (Matthias), Ong, K. K. (Ken K.), Padmanabhan, S. (Sandosh), Peyser, P. A. (Patricia A.), Pisinger, C. (Charlotta), Porteous, D. J. (David J.), Raitakari, O. T. (Olli T.), Rankinen, T. (Tuomo), Rao, D. C. (D. C.), Rasmussen-Torvik, L. J. (Laura J.), Rawal, R. (Rajesh), Rice, T. (Treva), Ridker, P. M. (Paul M.), Rose, L. M. (Lynda M.), Bien, S. A. (Stephanie A.), Rudan, I. (Igor), Sanna, S. (Serena), Sarzynski, M. A. (Mark A.), Sattar, N. (Naveed), Savonen, K. (Kai), Schlessinger, D. (David), Scholtens, S. (Salome), Schurmann, C. (Claudia), Scott, R. A. (Robert A.), Sennblad, B. (Bengt), Siemelink, M. A. (Marten A.), Silbernagel, G. (Gunther), Slagboom, P. E. (P. Eline), Snieder, H. (Harold), Staessen, J. A. (Jan A.), Stott, D. J. (David J.), Swertz, M. A. (Morris A.), Swift, A. J. (Amy J.), Taylor, K. D. (Kent D.), Tayo, B. O. (Bamidele O.), Thorand, B. (Barbara), Thuillier, D. (Dorothee), Tuomilehto, J. (Jaakko), Uitterlinden, A. G. (Andre G.), Vandenput, L. (Liesbeth), Vohl, M.-C. (Marie-Claude), Volzke, H. (Henry), Vonk, J. M. (Judith M.), Waeber, G. (Gerard), Waldenberger, M. (Melanie), Westendorp, R. G. (R. G. J.), Wild, S. (Sarah), Willemsen, G. (Gonneke), Wolffenbuttel, B. H. (Bruce H. R.), Wong, A. (Andrew), Wright, A. F. (Alan F.), Zhao, W. (Wei), Zillikens, M. C. (M. Carola), Baldassarre, D. (Damiano), Balkau, B. (Beverley), Bandinelli, S. (Stefania), Boger, C. A. (Carsten A.), Boomsma, D. I. (Dorret I.), Bouchard, C. (Claude), Bruinenberg, M. (Marcel), Chasman, D. I. (Daniel I.), Chen, Y. I. (Yii-Der Ida), Chines, P. S. (Peter S.), Cooper, R. S. (Richard S.), Cucca, F. (Francesco), Cusi, D. (Daniele), de Faire, U. (Ulf), Ferrucci, L. (Luigi), Franks, P. W. (Paul W.), Froguel, P. (Philippe), Gordon-Larsen, P. (Penny), Grabe, H.-J. (Hans-Jorgen), Gudnason, V. (Vilmundur), Haiman, C. A. (Christopher A.), Hayward, C. (Caroline), Hveem, K. (Kristian), Johnson, A. D. (Andrew D.), Jukema, W. (Wouter), Kardia, S. L. (Sharon L. R.), Kivimäki, M. (Mika), Kooner, J. S. (Jaspal S.), Kuh, D. (Diana), Laakso, M. (Markku), Lehtimäki, T. (Terho), Le Marchand, L. (Loic), Marz, W. (Winfried), McCarthy, M. I. (Mark I.), Metspalu, A. (Andres), Morris, A. P. (Andrew P.), Ohlsson, C. (Claes), Palmer, L. J. (Lyle J.), Pasterkamp, G. (Gerard), Pedersen, O. (Oluf), Peters, A. (Annette), Peters, U. (Ulrike), Polasek, O. (Ozren), Psaty, B. M. (Bruce M.), Qi, L. (Lu), Rauramaa, R. (Rainer), Smith, B. H. (Blair H.), Sorensen, T. I. (Thorkild I. A.), Strauch, K. (Konstantin), Tiemeier, H. (Henning), Tremoli, E. (Elena), Van der Harst, P. (Pim), Vestergaard, H. (Henrik), Vollenweider, P. (Peter), Wareham, N. J. (Nicholas J.), Weir, D. R. (David R.), Whitfield, J. B. (John B.), Wilson, J. F. (James F.), Tyrrell, J. (Jessica), Frayling, T. M. (Timothy M.), Barroso, I. (Ines), Boehnke, M. (Michael), Deloukas, P. (Panagiotis), Fox, C. S. (Caroline S.), Hirschhorn, J. N. (Joel N.), Hunter, D. J. (David J.), Spector, T. D. (Tim D.), Strachan, D. P. (David P.), van Duijn, C. M. (Cornelia M.), Heid, I. M. (Iris M.), Mohlke, K. L. (Karen L.), Marchini, J. (Jonathan), Loos, R. J. (Ruth J. F.), Kilpeläinen, T. O. (Tuomas O.), Liu, C.-T. (Ching-Ti), Borecki, I. B. (Ingrid B.), North, K. E. (Kari E.), Cupples, L. A. (L. Adrienne), Justice, A. E. (Anne E.), Winkler, T. W. (Thomas W.), Feitosa, M. F. (Mary F.), Graff, M. (Misa), Fisher, V. A. (Virginia A.), Young, K. (Kristin), Barata, L. (Llilda), Deng, X. (Xuan), Czajkowski, J. (Jacek), Hadley, D. (David), Ngwa, J. S. (Julius S.), Ahluwalia, T. S. (Tarunveer S.), Chu, A. Y. (Audrey Y.), Heard-Costa, N. L. (Nancy L.), Lim, E. (Elise), Perez, J. (Jeremiah), Eicher, J. D. (John D.), Kutalik, Z. (Zoltan), Xue, L. (Luting), Mahajan, A. (Anubha), Renstrom, F. (Frida), Wu, J. (Joseph), Qi, Q. (Qibin), Ahmad, S. (Shafqat), Alfred, T. (Tamuno), Amin, N. (Najaf), Bielak, L. F. (Lawrence F.), Bonnefond, A. (Amelie), Bragg, J. (Jennifer), Cadby, G. (Gemma), Chittani, M. (Martina), Coggeshall, S. (Scott), Corre, T. (Tanguy), Direk, N. (Nese), Eriksson, J. (Joel), Fischer, K. (Krista), Gorski, M. (Mathias), Harder, M. N. (Marie Neergaard), Horikoshi, M. (Momoko), Huang, T. (Tao), Huffman, J. E. (Jennifer E.), Jackson, A. U. (Anne U.), Justesen, J. M. (Johanne Marie), Kanoni, S. (Stavroula), Kinnunen, L. (Leena), Kleber, M. E. (Marcus E.), Komulainen, P. (Pirjo), Kumari, M. (Meena), Lim, U. (Unhee), Luan, J. (Jian'an), Lyytikäinen, L.-P. (Leo-Pekka), Mangino, M. (Massimo), Manichaikul, A. (Ani), Marten, J. (Jonathan), Middelberg, R. P. (Rita P. S.), Mueller-Nurasyid, M. (Martina), Navarro, P. (Pau), Perusse, L. (Louis), Pervjakova, N. (Natalia), Sarti, C. (Cinzia), Smith, A. V. (Albert Vernon), Smith, J. A. (Jennifer A.), Stancakova, A. (Alena), Strawbridge, R. J. (Rona J.), Stringham, H. M. (Heather M.), Sung, Y. J. (Yun Ju), Tanaka, T. (Toshiko), Teumer, A. (Alexander), Trompet, S. (Stella), van der Laan, S. W. (Sander W.), van der Most, P. J. (Peter J.), Van Vliet-Ostaptchouk, J. V. (Jana V.), Vedantam, S. L. (Sailaja L.), Verweij, N. (Niek), Vink, J. M. (Jacqueline M.), Vitart, V. (Veronique), Wu, Y. (Ying), Yengo, L. (Loic), Zhang, W. (Weihua), Zhao, J. H. (Jing Hua), Zimmermann, M. E. (Martina E.), Zubair, N. (Niha), Abecasis, G. R. (Goncalo R.), Adair, L. S. (Linda S.), Afaq, S. (Saima), Afzal, U. (Uzma), Bakker, S. J. (Stephan J. L.), Bartz, T. M. (Traci M.), Beilby, J. (John), Bergman, R. N. (Richard N.), Bergmann, S. (Sven), Biffar, R. (Reiner), Blangero, J. (John), Boerwinkle, E. (Eric), Bonnycastle, L. L. (Lori L.), Bottinger, E. (Erwin), Braga, D. (Daniele), Buckley, B. M. (Brendan M.), Buyske, S. (Steve), Campbell, H. (Harry), Chambers, J. C. (John C.), Collins, F. S. (Francis S.), Curran, J. E. (Joanne E.), de Borst, G. J. (Gert J.), de Craen, A. J. (Anton J. M.), de Geus, E. J. (Eco J. C.), Dedoussis, G. (George), Delgado, G. E. (Graciela E.), den Ruijter, H. M. (Hester M.), Eiriksdottir, G. (Gudny), Eriksson, A. L. (Anna L.), Esko, T. (Tonu), Faul, J. D. (Jessica D.), Ford, I. (Ian), Forrester, T. (Terrence), Gertow, K. (Karl), Gigante, B. (Bruna), Glorioso, N. (Nicola), Gong, J. (Jian), Grallert, H. (Harald), Grammer, T. B. (Tanja B.), Grarup, N. (Niels), Haitjema, S. (Saskia), Hallmans, G. (Goran), Hamsten, A. (Anders), Hansen, T. (Torben), Harris, T. B. (Tamara B.), Hartman, C. A. (Catharina A.), Hassinen, M. (Maija), Hastie, N. D. (Nicholas D.), Heath, A. C. (Andrew C.), Hernandez, D. (Dena), Hindorff, L. (Lucia), Hocking, L. J. (Lynne J.), Hollensted, M. (Mette), Holmen, O. L. (Oddgeir L.), Homuth, G. (Georg), Hottenga, J. J. (Jouke Jan), Huang, J. (Jie), Hung, J. (Joseph), Hutri-Kähönen, N. (Nina), Ingelsson, E. (Erik), James, A. L. (Alan L.), Jansson, J.-O. (John-Olov), Järvelin, M.-R. (Marjo-Riitta), Jhun, M. A. (Min A.), Jorgensen, M. E. (Marit E.), Juonala, M. (Markus), Kähönen, M. (Mika), Karlsson, M. (Magnus), Koistinen, H. A. (Heikki A.), Kolcic, I. (Ivana), Kolovou, G. (Genovefa), Kooperberg, C. (Charles), Kramer, B. K. (Bernhard K.), Kuusisto, J. (Johanna), Kvaloy, K. (Kirsti), Lakka, T. A. (Timo A.), Langenberg, C. (Claudia), Launer, L. J. (Lenore J.), Leander, K. (Karin), Lee, N. R. (Nanette R.), Lind, L. (Lars), Lindgren, C. M. (Cecilia M.), Linneberg, A. (Allan), Lobbens, S. (Stephane), Loh, M. (Marie), Lorentzon, M. (Mattias), Luben, R. (Robert), Lubke, G. (Gitta), Ludolph-Donislawski, A. (Anja), Lupoli, S. (Sara), Madden, P. A. (Pamela A. F.), Männikkö, R. (Reija), Marques-Vidal, P. (Pedro), Martin, N. G. (Nicholas G.), McKenzie, C. A. (Colin A.), McKnight, B. (Barbara), Mellstrom, D. (Dan), Menni, C. (Cristina), Montgomery, G. W. (Grant W.), Musk, A. W. (A. W. (Bill)), Narisu, N. (Narisu), Nauck, M. (Matthias), Nolte, I. M. (Ilja M.), Oldehinkel, A. J. (Albertine J.), Olden, M. (Matthias), Ong, K. K. (Ken K.), Padmanabhan, S. (Sandosh), Peyser, P. A. (Patricia A.), Pisinger, C. (Charlotta), Porteous, D. J. (David J.), Raitakari, O. T. (Olli T.), Rankinen, T. (Tuomo), Rao, D. C. (D. C.), Rasmussen-Torvik, L. J. (Laura J.), Rawal, R. (Rajesh), Rice, T. (Treva), Ridker, P. M. (Paul M.), Rose, L. M. (Lynda M.), Bien, S. A. (Stephanie A.), Rudan, I. (Igor), Sanna, S. (Serena), Sarzynski, M. A. (Mark A.), Sattar, N. (Naveed), Savonen, K. (Kai), Schlessinger, D. (David), Scholtens, S. (Salome), Schurmann, C. (Claudia), Scott, R. A. (Robert A.), Sennblad, B. (Bengt), Siemelink, M. A. (Marten A.), Silbernagel, G. (Gunther), Slagboom, P. E. (P. Eline), Snieder, H. (Harold), Staessen, J. A. (Jan A.), Stott, D. J. (David J.), Swertz, M. A. (Morris A.), Swift, A. J. (Amy J.), Taylor, K. D. (Kent D.), Tayo, B. O. (Bamidele O.), Thorand, B. (Barbara), Thuillier, D. (Dorothee), Tuomilehto, J. (Jaakko), Uitterlinden, A. G. (Andre G.), Vandenput, L. (Liesbeth), Vohl, M.-C. (Marie-Claude), Volzke, H. (Henry), Vonk, J. M. (Judith M.), Waeber, G. (Gerard), Waldenberger, M. (Melanie), Westendorp, R. G. (R. G. J.), Wild, S. (Sarah), Willemsen, G. (Gonneke), Wolffenbuttel, B. H. (Bruce H. R.), Wong, A. (Andrew), Wright, A. F. (Alan F.), Zhao, W. (Wei), Zillikens, M. C. (M. Carola), Baldassarre, D. (Damiano), Balkau, B. (Beverley), Bandinelli, S. (Stefania), Boger, C. A. (Carsten A.), Boomsma, D. I. (Dorret I.), Bouchard, C. (Claude), Bruinenberg, M. (Marcel), Chasman, D. I. (Daniel I.), Chen, Y. I. (Yii-Der Ida), Chines, P. S. (Peter S.), Cooper, R. S. (Richard S.), Cucca, F. (Francesco), Cusi, D. (Daniele), de Faire, U. (Ulf), Ferrucci, L. (Luigi), Franks, P. W. (Paul W.), Froguel, P. (Philippe), Gordon-Larsen, P. (Penny), Grabe, H.-J. (Hans-Jorgen), Gudnason, V. (Vilmundur), Haiman, C. A. (Christopher A.), Hayward, C. (Caroline), Hveem, K. (Kristian), Johnson, A. D. (Andrew D.), Jukema, W. (Wouter), Kardia, S. L. (Sharon L. R.), Kivimäki, M. (Mika), Kooner, J. S. (Jaspal S.), Kuh, D. (Diana), Laakso, M. (Markku), Lehtimäki, T. (Terho), Le Marchand, L. (Loic), Marz, W. (Winfried), McCarthy, M. I. (Mark I.), Metspalu, A. (Andres), Morris, A. P. (Andrew P.), Ohlsson, C. (Claes), Palmer, L. J. (Lyle J.), Pasterkamp, G. (Gerard), Pedersen, O. (Oluf), Peters, A. (Annette), Peters, U. (Ulrike), Polasek, O. (Ozren), Psaty, B. M. (Bruce M.), Qi, L. (Lu), Rauramaa, R. (Rainer), Smith, B. H. (Blair H.), Sorensen, T. I. (Thorkild I. A.), Strauch, K. (Konstantin), Tiemeier, H. (Henning), Tremoli, E. (Elena), Van der Harst, P. (Pim), Vestergaard, H. (Henrik), Vollenweider, P. (Peter), Wareham, N. J. (Nicholas J.), Weir, D. R. (David R.), Whitfield, J. B. (John B.), Wilson, J. F. (James F.), Tyrrell, J. (Jessica), Frayling, T. M. (Timothy M.), Barroso, I. (Ines), Boehnke, M. (Michael), Deloukas, P. (Panagiotis), Fox, C. S. (Caroline S.), Hirschhorn, J. N. (Joel N.), Hunter, D. J. (David J.), Spector, T. D. (Tim D.), Strachan, D. P. (David P.), van Duijn, C. M. (Cornelia M.), Heid, I. M. (Iris M.), Mohlke, K. L. (Karen L.), Marchini, J. (Jonathan), Loos, R. J. (Ruth J. F.), Kilpeläinen, T. O. (Tuomas O.), Liu, C.-T. (Ching-Ti), Borecki, I. B. (Ingrid B.), North, K. E. (Kari E.), and Cupples, L. A. (L. Adrienne)

Abstract

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

Published
2017

16. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Author

Justice, AE, Winkler, TW, Feitosa, MF, Graff, M, Fisher, V A, Young, K, Barata, L, Deng, X, Czajkowski, J, Hadley, D, Ngwa, JS, Ahluwalia, TS, Chu, AY, Heard-Costa, NL, Lim, E, Perez, J, Eicher, JD, Kutalik, Z, Xue, L, Mahajan, A, Renstrom, F, Wu, J, Qi, QB, Ahmad, Shahzad, Alfred, T, Amin, Najaf, Bielak, LF, Bonnefond, A, Bragg, J, Cadby, G, Chittani, M, Coggeshall, S, Corre, T, Direk, N, Eriksson, J, Fischer, K, Gorski, M, Harder, MN, Horikoshi, M, Huang, T, Huffman, JE, Jackson, AU, Justesen, JM, Kanoni, S, Kinnunen, L, Kleber, ME, Komulainen, P, Kumari, M, Lim, U, Luan, J, Lyytikainen, LP, Mangino, M, Manichaikul, A, Marten, J, Middelberg, RPS, Mueller-Nurasyid, M, Navarro, P, Perusse, L, Pervjakova, N, Sarti, C, Smith, AV, Smith, JA, Stancakova, A, Strawbridge, RJ, Stringham, HM, Sung, YJ, Tanaka, T, Teumer, A, Trompet, S, van der Laan, SW, van der Most, PJ, van Vliet-Ostaptchouk, JV, Vedantam, SL, Verweij, N (Niek), Vink, JM, Vitart, V, Wu, Fenny, Yengo, L, Zhang, WH, Zhao, JH, Zimmermann, ME, Zubair, N, Abecasis, GR, Adair, LS, Afaq, S, Afzal, U, Bakker, SJL, Bartz, TM, Beilby, J, Bergman, RN, Bergmann, S, Biffar, R, Blangero, J, Boerwinkle, E, Bonnycastle, LL, Bottinger, E, Braga, D, Buckley, BM, Buyske, S, Campbell, H, Chambers, JC, Collins, FS, Curran, JE, de Borst, GJ, de Craen, AJM, de Geus, EJC, Dedoussis, G, Delgado, GE, den Ruijter, HM, Eiriksdottir, G, Eriksson, AL, Esko, T, Faul, JD, Ford, I, Forrester, T, Gertow, K, Gigante, B, Glorioso, N, Gong, J, Grallert, H, Grammer, TB, Grarup, N, Haitjema, S, Hallmans, G, Hamsten, A, Hansen, T, Harris, TB, Hartman, CA, Hassinen, M, Hastie, ND, Heath, AC, Hernandez, D, Hindorff, L, Hocking, LJ, Hollensted, M, Holmen, OL, Homuth, G, Hottenga, JJ, Huang, J, Hung, J, Hutri-Kahonen, N, Ingelsson, E, James, AL, Jansson, JO, Jarvelin, MR, Jhun, MA, Jorgensen, ME, Juonala, M, Kahonen, M, Karlsson, M, Koistinen, HA, Kolcic, I, Kolovou, G, Kooperberg, C, Kramer, BK, Kuusisto, J, Kvaloy, K, Lakka, TA, Langenberg, C, Launer, LJ, Leander, K, Lee, NR, Lind, L, Lindgren, CM, Linneberg, A, Lobbens, S, Loh, M, Lorentzon, M, Luben, R, Lubke, G, Ludolph-Donislawski, A, Lupoli, S, Madden, PAF, Mannikko, R, Marques-Vidal, P, Martin, NG, McKenzie, CA, McKnight, B, Mellstrom, D, Menni, C, Montgomery, GW, Musk, AW, Narisu, N, Nauck, M, Nolte, IM, Oldehinkel, AJ, Olden, M, Ong, KK, Padmanabhan, S, Peyser, PA, Pisinger, C, Porteous, DJ, Raitakari, OT, Rankinen, T, Rao, DC, Rasmussen-Torvik, LJ, Rawal, R, Rice, T, Ridker, PM, Rose, LM, Bien, SA, Rudan, I, Sanna, S, Sarzynski, MA, Sattar, N, Savonen, K, Schlessinger, D, Scholtens, s, Schurmann, C, Scott, RA, Sennblad, B, Siemelink, MA, Silbernagel, G, Slagboom, PE (Eline), Snieder, H, Staessen, JA, Stott, DJ, Swertz, MA, Swift, AJ, Taylor, KD, Tayo, BO, Thorand, B, Thuillier, D, Tuomilehto, J, Uitterlinden, André, Vandenput, L, Vohl, MC, Volzke, H, Vonk, JM, Waeber, G, Waldenberger, M, Westendorp, RGJ, Wild, S, Willemsen, G, Wolffenbuttel, BHR, Wong, A, Wright, AF, Zhao, W, Zillikens, M.C., Baldassarre, D, Balkau, B, Bandinelli, S, Boger, CA, Boomsma, DI, Bouchard, C, Bruinenberg, M, Chasman, DI, Chen, YDI, Chines, PS, Cooper, RS, Cucca, F, Cusi, D, de Faire, U, Ferrucci, L, Franks, PW, Froguel, P, Gordon-Larsen, P, Grabe, HJ, Gudnason, V, Haiman, CA, Hayward, C, Hveem, K, Johnson, AD, Jukema, W, Kardia, SLR, Kivimaki, M, Kooner, JS, Kuh, D, Laakso, M, Lehtimaki, T, Le Marchand, L, Marz, W, McCarthy, MI, Metspalu, A, Morris, AP, Ohlsson, C, Palmer, LJ, Pasterkamp, G, Pedersen, O, Peters, A, Peters, U, Polasek, O, Psaty, BM, Qi, L, Rauramaa, R, Smith, BH, Sorensen, TIA, Strauch, K, Tiemeier, Henning, Tremoli, E, van der Harst, P, Vestergaard, H, Vollenweider, P, Wareham, NJ, Weir, DR, Whitfield, JB, Wilson, JF, Tyrrell, J, Frayling, TM, Barroso, I, Boehnke, M, Deloukas, P, Fox, CS, Hirschhorn, JN, Hunter, DJ, Spector, TD, Strachan, DP, Duijn, Cornelia, Heid, IM, Mohlke, KL, Marchini, J, Loos, RJF, Kilpelainen, TO, Liu, CT, Borecki, IB, North, KE, Cupples, LA, Justice, AE, Winkler, TW, Feitosa, MF, Graff, M, Fisher, V A, Young, K, Barata, L, Deng, X, Czajkowski, J, Hadley, D, Ngwa, JS, Ahluwalia, TS, Chu, AY, Heard-Costa, NL, Lim, E, Perez, J, Eicher, JD, Kutalik, Z, Xue, L, Mahajan, A, Renstrom, F, Wu, J, Qi, QB, Ahmad, Shahzad, Alfred, T, Amin, Najaf, Bielak, LF, Bonnefond, A, Bragg, J, Cadby, G, Chittani, M, Coggeshall, S, Corre, T, Direk, N, Eriksson, J, Fischer, K, Gorski, M, Harder, MN, Horikoshi, M, Huang, T, Huffman, JE, Jackson, AU, Justesen, JM, Kanoni, S, Kinnunen, L, Kleber, ME, Komulainen, P, Kumari, M, Lim, U, Luan, J, Lyytikainen, LP, Mangino, M, Manichaikul, A, Marten, J, Middelberg, RPS, Mueller-Nurasyid, M, Navarro, P, Perusse, L, Pervjakova, N, Sarti, C, Smith, AV, Smith, JA, Stancakova, A, Strawbridge, RJ, Stringham, HM, Sung, YJ, Tanaka, T, Teumer, A, Trompet, S, van der Laan, SW, van der Most, PJ, van Vliet-Ostaptchouk, JV, Vedantam, SL, Verweij, N (Niek), Vink, JM, Vitart, V, Wu, Fenny, Yengo, L, Zhang, WH, Zhao, JH, Zimmermann, ME, Zubair, N, Abecasis, GR, Adair, LS, Afaq, S, Afzal, U, Bakker, SJL, Bartz, TM, Beilby, J, Bergman, RN, Bergmann, S, Biffar, R, Blangero, J, Boerwinkle, E, Bonnycastle, LL, Bottinger, E, Braga, D, Buckley, BM, Buyske, S, Campbell, H, Chambers, JC, Collins, FS, Curran, JE, de Borst, GJ, de Craen, AJM, de Geus, EJC, Dedoussis, G, Delgado, GE, den Ruijter, HM, Eiriksdottir, G, Eriksson, AL, Esko, T, Faul, JD, Ford, I, Forrester, T, Gertow, K, Gigante, B, Glorioso, N, Gong, J, Grallert, H, Grammer, TB, Grarup, N, Haitjema, S, Hallmans, G, Hamsten, A, Hansen, T, Harris, TB, Hartman, CA, Hassinen, M, Hastie, ND, Heath, AC, Hernandez, D, Hindorff, L, Hocking, LJ, Hollensted, M, Holmen, OL, Homuth, G, Hottenga, JJ, Huang, J, Hung, J, Hutri-Kahonen, N, Ingelsson, E, James, AL, Jansson, JO, Jarvelin, MR, Jhun, MA, Jorgensen, ME, Juonala, M, Kahonen, M, Karlsson, M, Koistinen, HA, Kolcic, I, Kolovou, G, Kooperberg, C, Kramer, BK, Kuusisto, J, Kvaloy, K, Lakka, TA, Langenberg, C, Launer, LJ, Leander, K, Lee, NR, Lind, L, Lindgren, CM, Linneberg, A, Lobbens, S, Loh, M, Lorentzon, M, Luben, R, Lubke, G, Ludolph-Donislawski, A, Lupoli, S, Madden, PAF, Mannikko, R, Marques-Vidal, P, Martin, NG, McKenzie, CA, McKnight, B, Mellstrom, D, Menni, C, Montgomery, GW, Musk, AW, Narisu, N, Nauck, M, Nolte, IM, Oldehinkel, AJ, Olden, M, Ong, KK, Padmanabhan, S, Peyser, PA, Pisinger, C, Porteous, DJ, Raitakari, OT, Rankinen, T, Rao, DC, Rasmussen-Torvik, LJ, Rawal, R, Rice, T, Ridker, PM, Rose, LM, Bien, SA, Rudan, I, Sanna, S, Sarzynski, MA, Sattar, N, Savonen, K, Schlessinger, D, Scholtens, s, Schurmann, C, Scott, RA, Sennblad, B, Siemelink, MA, Silbernagel, G, Slagboom, PE (Eline), Snieder, H, Staessen, JA, Stott, DJ, Swertz, MA, Swift, AJ, Taylor, KD, Tayo, BO, Thorand, B, Thuillier, D, Tuomilehto, J, Uitterlinden, André, Vandenput, L, Vohl, MC, Volzke, H, Vonk, JM, Waeber, G, Waldenberger, M, Westendorp, RGJ, Wild, S, Willemsen, G, Wolffenbuttel, BHR, Wong, A, Wright, AF, Zhao, W, Zillikens, M.C., Baldassarre, D, Balkau, B, Bandinelli, S, Boger, CA, Boomsma, DI, Bouchard, C, Bruinenberg, M, Chasman, DI, Chen, YDI, Chines, PS, Cooper, RS, Cucca, F, Cusi, D, de Faire, U, Ferrucci, L, Franks, PW, Froguel, P, Gordon-Larsen, P, Grabe, HJ, Gudnason, V, Haiman, CA, Hayward, C, Hveem, K, Johnson, AD, Jukema, W, Kardia, SLR, Kivimaki, M, Kooner, JS, Kuh, D, Laakso, M, Lehtimaki, T, Le Marchand, L, Marz, W, McCarthy, MI, Metspalu, A, Morris, AP, Ohlsson, C, Palmer, LJ, Pasterkamp, G, Pedersen, O, Peters, A, Peters, U, Polasek, O, Psaty, BM, Qi, L, Rauramaa, R, Smith, BH, Sorensen, TIA, Strauch, K, Tiemeier, Henning, Tremoli, E, van der Harst, P, Vestergaard, H, Vollenweider, P, Wareham, NJ, Weir, DR, Whitfield, JB, Wilson, JF, Tyrrell, J, Frayling, TM, Barroso, I, Boehnke, M, Deloukas, P, Fox, CS, Hirschhorn, JN, Hunter, DJ, Spector, TD, Strachan, DP, Duijn, Cornelia, Heid, IM, Mohlke, KL, Marchini, J, Loos, RJF, Kilpelainen, TO, Liu, CT, Borecki, IB, North, KE, and Cupples, LA

Published
2017

17. Integrating Genetic, Transcriptional, and Functional Analyses to Identify 5 Novel Genes for Atrial Fibrillation

Author

Sinner, M.F., Tucker, N.R., Lunetta, K.L., Ozaki, K., Smith, J.G., Trompet, S., Bis, J.C., Lin, H.H., Chung, M.K., Nielsen, J.B., Lubitz, S.A., Krijthe, B.P., Magnani, J.W., Ye, J.C., Gollob, M.H., Tsunoda, T., Muller-Nurasyid, M., Lichtner, P., Peters, A., Dolmatova, E., Kubo, M., Smith, J.D., Psaty, B.M., Smith, N.L., Jukema, W., Chasman, D.I., Albert, C.M., Ebana, Y., Furukawa, T., MacFarlane, P.W., Harris, T.B., Darbar, D., Dorr, M., Holst, A.G., Svendsen, J.H., Hofman, A., Uitterlinden, A.G., Gudnason, V., Isobe, M., Malik, R., Dichgans, M., Rosand, J., Wagoner, D.R. van, Benjamin, E.J., Milan, D.J., Melander, O., Heckbert, S.R., Ford, I., Liu, Y.M., Barnard, J., Olesen, M.S., Stricker, B.H.C., Tanaka, T., Kaeaeb, S., Ellinor, P.T., METASTROKE Consortium AFGen Consor, Epidemiology, and Internal Medicine

Subjects
Male, single nucleotide, Genotype, Ubiquitin-Protein Ligases, Quantitative Trait Loci, Muscle Proteins, Quantitative trait locus, Bioinformatics, Article, polymorphism, Japan, Polymorphism (computer science), Physiology (medical), medicine, Animals, Humans, Genetic Predisposition to Disease, atrial fibrillation, genetics, Genotyping, Aged, Homeodomain Proteins, Fibrillation, business.industry, Chromosome Mapping, Nuclear Proteins, Atrial fibrillation, Middle Aged, Zebrafish Proteins, zebrafish, medicine.disease, Confidence interval, Europe, Repressor Proteins, Genetic Loci, Connexin 43, Gene Knockdown Techniques, Relative risk, Expression quantitative trait loci, gene expression, Female, epidemiology, medicine.symptom, T-Box Domain Proteins, Cardiology and Cardiovascular Medicine, business, Transcription Factors
Abstract

Background— Atrial fibrillation (AF) affects >30 million individuals worldwide and is associated with an increased risk of stroke, heart failure, and death. AF is highly heritable, yet the genetic basis for the arrhythmia remains incompletely understood. Methods and Results— To identify new AF-related genes, we used a multifaceted approach, combining large-scale genotyping in 2 ethnically distinct populations, cis-eQTL ( expression quantitative trait loci ) mapping, and functional validation. Four novel loci were identified in individuals of European descent near the genes NEURL (rs12415501; relative risk [RR]=1.18; 95% confidence interval [CI], 1.13–1.23; P =6.5×10 −16 ), GJA1 (rs13216675; RR=1.10; 95% CI, 1.06–1.14; P =2.2×10 −8 ), TBX5 (rs10507248; RR=1.12; 95% CI, 1.08–1.16; P =5.7×10 −11 ), and CAND2 (rs4642101; RR=1.10; 95% CI, 1.06–1.14; P =9.8×10 −9 ). In Japanese, novel loci were identified near NEURL (rs6584555; RR=1.32; 95% CI, 1.26–1.39; P =2.0×10 −25 ) and CUX2 (rs6490029; RR=1.12; 95% CI, 1.08–1.16; P =3.9×10 −9 ). The top single-nucleotide polymorphisms or their proxies were identified as cis-eQTLs for the genes CAND2 ( P =2.6×10 −19 ), GJA1 ( P =2.66×10 −6 ), and TBX5 ( P =1.36×10 −5 ). Knockdown of the zebrafish orthologs of NEURL and CAND2 resulted in prolongation of the atrial action potential duration (17% and 45%, respectively). Conclusions— We have identified 5 novel loci for AF. Our results expand the diversity of genetic pathways implicated in AF and provide novel molecular targets for future biological and pharmacological investigation.

Published
2014

19. Plasma CETP is derived from hepatic kupffer cells rather than adipose tissue

Author

Blauw, L., primary, de Mutsert, R., additional, Wang, Y., additional, Lamb, H., additional, de Roos, A., additional, Rosendaal, F., additional, Jukema, W., additional, van der Tuin, S., additional, Rensen, S., additional, Shiri-Sverdlov, R., additional, Atanasovska, B., additional, Fu, J., additional, Buurman, W., additional, Greve, J.W., additional, Hofker, M., additional, Willems van Dijk, K., additional, and Rensen, P., additional

Published
2016
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24. Local cre-mediated gene recombination in vascular smooth muscle cells in mice

Author

Zadelaar, A.S.M., Boesten, L.S.M., Pires, N.M.M., Nieuwkoop, A. van, Biessen, E.A.L., Jukema, W., Havekes, L.M., Vlijmen, B.J.M. van, Dijk, K.W. van, and TNO Kwaliteit van Leven

Subjects
Biomedical Research, Mouse, Physiology, Drug derivative, Smooth muscle fiber, Drug delivery system, Myocytes, Smooth Muscle, Cre recombinase, Mice, Transgenic, Muscle, Smooth, Vascular, Mice, Drug Delivery Systems, Smooth muscle, Transgenic mouse, Cre/loxP, Genetics, Pathology, Animals, Promoter Regions, Genetic, Polymer delivery device, Recombination, Genetic, Genetic recombination, Integrases, Animal, Promoter region, 4-hydroxytamoxifen, Rosa26, Drug effect, Getabolism, Tamoxifen, Local, vascular smooth muscle, Cytology, 4 hydroxytamoxifen
Abstract

Here we describe a means to conditionally modify genes at a predefined and localized region of the vasculature using a perivascular drug delivery device (PDD). A 4-hydroxytamoxifen (4-OHT)-eluting PDD was applied around the carotid or femoral artery of a mouse strain carrying both the tamoxifen-inducible and smooth muscle cell (SMC)-specific Cre-recombinase (SM-Cre-ERT2) transgene and a stop-floxed β-galactosidase gene in the Rosa26 locus: the SM-CreERT2(ki)/rosa26 mouse. A dose and time curve of 0-10% (w/w) 4-OHT and 0-14 days application of the PDD in SM-CreERT2(ki)/rosa26 mice showed optimal gene recombination at 1% (w/w) 4-OHT loading at 7 days post application (carotid artery 2.4±1.8%; femoral artery 4.0±3.8% of SMCs). The unique 4-OHT-eluting PDD allowed us to achieve SMC-specific recombination in the same order of magnitude as compared to systemic tamoxifen administration. In addition, recombination was completely confined to the PDD-treated vessel wall segment. Thus, local application of a 4-OHT-eluting PDD results in vascular SMC-specific Cre-mediated recombination in SM-CreER T2(ki)/rosa26 mice without affecting additional SMCs. © Springer 2006. Chemicals / CAS: 4 hydroxytamoxifen, 65213-48-1, 68392-35-8; tamoxifen, 10540-29-1; 4-hydroxytamoxifen, 68392-35-8; Cre recombinase, 2.7.7.-; Integrases, 2.7.7.-; Tamoxifen, 10540-29-1

Published
2006

31. Testing cognitive function in elderly populations: the PROSPER study

Author

Hyland, M., Cobbe, S.M., Gaw, A., Westendorp, R.G., Norrie, J., Kamper, A.M., Perry, I.J., MacFarlane, P.W., Meinders, A.E., Sweeney, B.J., Packard, C.J., Twomey, C., Houx, P.J., Shepherd, J., Blauw, G-J., Murphy, M.B., Ford, I., Bollen, E.L., Buckley, B., Stott, D.J., and Jukema, W.

Abstract

OBJECTIVES: For large scale follow up studies with non-demented patients in which cognition is an endpoint, there is a need for short, inexpensive, sensitive, and reliable neuropsychological tests that are suitable for repeated measurements. The commonly used Mini-Mental-State-Examination fulfils only the first two requirements. METHODS: In the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER), 5804 elderly subjects aged 70 to 82 years were examined using a learning test (memory), a coding test (general speed), and a short version of the Stroop test (attention). Data presented here were collected at dual baseline, before randomisation for active treatment. RESULTS: The tests proved to be reliable (with test/retest reliabilities ranging from acceptable (r=0.63) to high (r=0.88) and sensitive to detect small differences in subjects from different age categories. All tests showed significant practice effects: performance increased from the first measurement to the first follow up after two weeks. CONCLUSION: Normative data are provided that can be used for one time neuropsychological testing as well as for assessing individual and group change. Methods for analysing cognitive change are proposed.

Published
2002

37. Targeting glycolysis in endothelial cells to prevent intraplaque neovascularization and atherogenesis in mice

Author

Perrotta, Paola, Quax, P.H.A., Martinet, W., Vries, M.R. de, De Meyer, G.R.Y., Jukema, W., Hamming, J., Bot, I., Leiden University, and Martinet, Wim

Subjects
PFKFB3, Endothelial cells, Intraplaque angiogenesis, Glycolysis, Vein graft, Vulnerable plaque
Abstract

In recent years, the study of endothelial cell (EC) metabolism has led to the discovery of novel regulatory mechanisms and potential new targets for vascular-related diseases. Despite the fact that ECs have readily available oxygen in the blood, they mainly generate ATP via anaerobic glycolysis rather than Krebs cycle. In the context of atherosclerosis, there has been growing interest in understanding how EC metabolism affects plaque formation and intraplaque (IP) angiogenesis, which has been identified as a contributing factor for plaque vulnerability in human atherosclerosis.Among the enzymes involved in glycolytic flux modulation, PFKFB3 plays a critical role for the proliferation and migration of ECs. PFKFB3 is upregulated in atheroprone regions of arterial vessels and in carotid plaques of patients with elevated levels of lipoprotein(a). The experimental work of this thesis focuses on PFKFB3 as a modulator of EC glycolysis and its effects on atherosclerosis progression and IP angiogenesis.In the first part of this thesis, a pharmacological study with partial glycolysis inhibitor 3PO in the context of advanced atherosclerotic plaques is described. 3PO treatment restrains IP angiogenesis and plaque frequency but it does not affect plaque size and composition in ApoE-/-Fbn1C1039G+/- mice. In addition, a 3PO-mediated reduction in plaque formation is also observed in ApoE-/- mice that develop plaques without IP neovascularization.Furthermore, EC-specific PFKFB3 deletion leads to a significant reduction in plaque size, IP angiogenesis and hemorrhagic complications in a vein graft model. These findings suggest that endothelial glycolysis inhibition may represent a new therapeutic strategy to slow down plaque progression in vein grafts.A study performed in collaboration with the University of Aberdeen is also presented in this thesis. Here the development of a new PFKFB3-targeted PET radiotracer, [18F]ZCDD083, for in vivo plaque imaging is described. The specificity of the tracer for atherosclerotic plaques is demonstrated by a combination of ex vivo autoradiography and en face Oil Red O staining. This tracer is a promising non-invasive diagnostic tool to detect rupture-prone atherosclerotic plaques,Finally, a novel imaging method for a three-dimensional reconstruction of the IP vessel network is presented. This method is based on iDISCO immunolabeling and confocal microscopy. It may represent a novel tool to investigate the causal relationship between IP angiogenesis and atherogenesis.Overall, the experimental data generated in this thesis strongly argue for a critical role of EC metabolism in the formation and progression of atherosclerosis in addition to IP angiogenesis.

Published
2021

38. Fusion of X-ray angiography and optical coherence tomography for coronary flow simulation

Author

Li, Y., Reiber, J.H.C., Lelieveldt, B.P.F., Tu, S., Jukema, W., Birgelen, C. von, Siebes, M., and Leiden University

Subjects
Fractional flow reserve, Shear stress, Bioresorbable Stents, Angiography, 3D reconstruction, Optical Coherence Tomography, Computational fluid dynamics
Abstract

In conclusion, this thesis proposes a new approach for reconstruction of coronary artery and the implanted BRS by fusion of OCT and X-ray angiography to analyze intracoronary ESS in vivo. The studies conducted in this thesis demonstrate the feasibility of the proposed approach to analyze the detailed local coronary hemodynamics in patients, including the SS patterns after BRS implantation in coronary bifurcations. We observed that in vivo assessment of ESS was closely related to: (1) reconstruction of the side branches; (2) reconstruction of the BRS; (3) patient-specific flow; (4) post-processing portion size in which ESS was calculated. Based on these findings, we propose the following standard analysis procedures for assessment of intracoronary ESS in vivo: (1) reconstruct both the main vessel and its side branches to create a more accurate geometric model. (2) reconstruct BRS in naturally-bent shape and include it in the CFD analysis for assessment of ESS after BRS implantation; (3) use patient-specific coronary flow in the CFD analysis to have more accurate boundary condition; (4) set the proportion size according to the interrogated region of interest for quantification of the ESS in portions.

Published
2018

39. Invasive evaluation of coronary artery compliance modification after intracoronary lithotripsy.

Author

Oliveri F, Van Oort M, Al Amri I, Bingen B, Van der Kley F, Jukema W, and Montero J

Subjects
Humans, Male, Coronary Angiography, Treatment Outcome, Middle Aged, Female, Coronary Artery Disease therapy, Coronary Artery Disease diagnostic imaging, Coronary Artery Disease physiopathology, Aged, Vascular Stiffness, Lithotripsy methods, Coronary Vessels diagnostic imaging, Coronary Vessels physiopathology
Published
2024
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40. Patient-Reported Satisfaction with Thyroid Hormone Replacement Therapy for Subclinical Hypothyroidism in Older Adults: A Pooled Analysis of Individual Participant Data from Two Randomized Controlled Trials.

Author

Ravensberg J, Poortvliet RKE, Du Puy R, Rodondi N, Blum M, Kearney P, McCarthy VJC, Quinn T, Dekkers O, Jukema W, Mooijaart S, and Gussekloo J

Subjects
Humans, Female, Aged, Male, Aged, 80 and over, Thyrotropin blood, Double-Blind Method, Randomized Controlled Trials as Topic, Patient Reported Outcome Measures, Treatment Outcome, Hypothyroidism drug therapy, Hypothyroidism blood, Thyroxine therapeutic use, Hormone Replacement Therapy, Patient Satisfaction
Abstract

Background: The benefit of levothyroxine treatment of subclinical hypothyroidism (SCH) is subject to debate. This study compared treatment satisfaction between older adults with SCH using levothyroxine or placebo. Methods: We analyzed pooled individual participant data from two randomized, double-blind, placebo-controlled trials investigating the effects of levothyroxine treatment in older adults with SCH. Community-dwelling participants aged ≥65 years, with SCH (persistent thyrotropin levels 4.60-19.99 mIU/L for >3 months and normal free T4 level), were included. Intervention dose titration until thyrotropin levels normalized, with a mock dose adjustment of placebo. Treatment satisfaction was determined during the final study visit using the Treatment Satisfaction Questionnaire for Medication (TSQM), encompassing perceived effectiveness, side effects, convenience, and global satisfaction, along with the participants' desire to continue study medication after the trial. Results: We included 536 participants. At baseline, the median (interquartile range [IQR]) age was 74.9 (69.7-81.4) years, and 292 (55%) were women. The median (IQR) thyrotropin levels were 5.80 (5.10-7.00) mIU/L at baseline in both groups; at final visit, 4.97 (3.90-6.35) mIU/L in the placebo and 3.24 (2.49-4.41) mIU/L in the levothyroxine group. After treatment, the groups did not differ significantly in global satisfaction (mean difference [CI] -1.1 [-4.5 to 2.1], p = 0.48), nor in any other domain of treatment satisfaction. These results held true regardless of baseline thyrotropin levels or symptom burden. No major differences were found in the numbers of participants who wished to continue medication after the trial (levothyroxine 35% vs. placebo 27%), did not wish to continue (levothyroxine 27% vs. placebo 30%), or did not know (levothyroxine 37% vs. placebo 42%) ( p = 0.14). In a subpopulation with high symptom burden from hypothyroid symptoms at baseline, those using levothyroxine more often desired to continue the medication after the trial than those using placebo (mean difference [CI]: -21.1% [-35.6% to -6.5%]). Conclusion: These pooled data from two RCTs showed no major differences in treatment satisfaction between older adults receiving levothyroxine or placebo. This finding has important implications for decision-making regarding initiating levothyroxine treatment for SCH. Our findings generally support refraining from routinely prescribing levothyroxine in older adults with SCH.

Published
2024
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41. Ticagrelor Versus Clopidogrel in Older Patients with NSTE-ACS Using Oral Anticoagulation: A Sub-Analysis of the POPular Age Trial.

Author

Gimbel ME, Tavenier AH, Bor W, Hermanides RS, de Vrey E, Heestermans T, Gin MTJ, Waalewijn R, Hofma S, den Hartog F, Jukema W, von Birgelen C, Voskuil M, Kelder J, Deneer V, and Ten Berg JM

Abstract

There are no randomised data on which antiplatelet agent to use in elderly patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) and an indication for oral anticoagulation (OAC). The randomised POPular Age trial, in patients of 70 years or older with NSTE-ACS, showed a reduction in bleeding without increasing thrombotic events in patients using clopidogrel as compared to ticagrelor. In this sub-analysis of the POPular AGE trial, we compare clopidogrel with ticagrelor in patients with a need for oral anticoagulation. The follow-up duration was one year. The primary bleeding outcome was Platelet Inhibition and Patient Outcomes (PLATO) major and minor bleeding. The primary thrombotic outcome consisted of cardiovascular death, myocardial infarction and stroke. The primary net clinical benefit outcome was a composite of all-cause death, myocardial infarction, stroke, and PLATO major and minor bleeding. A total of 184/1011 (18.2%) patients on OAC were included in this subanalysis; 83 were randomized to clopidogrel and 101 to ticagrelor. The primary bleeding outcome was lower in the clopidogrel group (17/83, 20.9%) compared to the ticagrelor group (33/101, 33.5%; p = 0.051), as was the thrombotic outcome (7/83, 8.4% vs. 19/101, 19.2%; p = 0.035) and the primary net clinical benefit outcome (23/83, 27.7% vs. 49/101, 48.5%; p = 0.003). In this subgroup of patients using OAC, clopidogrel reduced PLATO major and minor bleeding compared to ticagrelor without increasing thrombotic risk. This analysis therefore suggests that, in line with the POPular Age trial, clopidogrel is a better option than ticagrelor in NSTE-ACS patients ≥70 years using OAC.

Published
2020
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42. Clopidogrel versus ticagrelor or prasugrel in patients aged 70 years or older with non-ST-elevation acute coronary syndrome (POPular AGE): the randomised, open-label, non-inferiority trial.

Author

Gimbel M, Qaderdan K, Willemsen L, Hermanides R, Bergmeijer T, de Vrey E, Heestermans T, Tjon Joe Gin M, Waalewijn R, Hofma S, den Hartog F, Jukema W, von Birgelen C, Voskuil M, Kelder J, Deneer V, and Ten Berg J

Subjects
Acute Coronary Syndrome mortality, Aged, Aged, 80 and over, Clopidogrel adverse effects, Female, Humans, Male, Myocardial Infarction prevention & control, Platelet Aggregation Inhibitors adverse effects, Prasugrel Hydrochloride adverse effects, Stroke prevention & control, Ticagrelor adverse effects, Acute Coronary Syndrome drug therapy, Clopidogrel therapeutic use, Platelet Aggregation Inhibitors therapeutic use, Prasugrel Hydrochloride therapeutic use, Ticagrelor therapeutic use
Abstract

Background: Current guidelines recommend potent platelet inhibition with ticagrelor or prasugrel in patients after an acute coronary syndrome. However, data about optimal platelet inhibition in older patients are scarce. We aimed to investigate the safety and efficacy of clopidogrel compared with ticagrelor or prasugrel in older patients with non-ST-elevation acute coronary syndrome (NSTE-ACS)., Methods: We did the open-label, randomised controlled POPular AGE trial in 12 sites (ten hospitals and two university hospitals) in the Netherlands. Patients aged 70 years or older with NSTE-ACS were enrolled and randomly assigned in a 1:1 ratio using an internet-based randomisation procedure with block sizes of six to receive a loading dose of clopidogrel 300 mg or 600 mg, or ticagrelor 180 mg or prasugrel 60 mg, and then a maintenance dose for the duration of 12 months (clopidogrel 75 mg once daily, ticagrelor 90 mg twice daily, or prasugrel 10 mg once daily) on top of standard care. Patient and treating physicians were aware of the allocated treatment strategy, but the outcome assessors were masked to treatment allocation. Primary bleeding outcome consisted of PLATelet inhibition and patient Outcomes (PLATO; major or minor bleeding [superiority hypothesis]). Co-primary net clinical benefit outcome consisted of all-cause death, myocardial infarction, stroke, PLATO major and minor bleeding (non-inferiority hypothesis, margin of 2%). Follow-up duration was 12 months. Analyses were done on intention-to-treat basis. This trial is registered with the Netherlands Trial Register (NL3804), ClinicalTrials.gov (NCT02317198), and EudraCT (2013-001403-37)., Findings: Between June 10, 2013, and Oct 17, 2018, 1002 patients were randomly assigned to clopidogrel (n=500) or ticagrelor or prasugrel (n=502). Because 475 (95%) patients received ticagrelor in the ticagrelor or prasugrel group, we will refer to this group as the ticagrelor group. Premature discontinuation of the study drug occurred in 238 (47%) of 502 ticagrelor group patients randomly assigned to ticagrelor, and in 112 (22%) of 500 patients randomly assigned to clopidogrel. Primary bleeding outcome was significantly lower in the clopidogrel group (88 [18%] of 500 patients) than in the ticagrelor group (118 [24%] of 502; hazard ratio 0·71, 95% CI 0·54 to 0·94; p=0·02 for superiority). Co-primary net clinical benefit outcome was non-inferior for the use of clopidogrel (139 [28%]) versus ticagrelor (161 [32%]; absolute risk difference -4%, 95% CI -10·0 to 1·4; p=0·03 for non-inferiority). The most important reasons for discontinuation were occurrence of bleeding (n=38), dyspnoea (n=40), and the need for treatment with oral anticoagulation (n=35)., Interpretation: In patients aged 70 years or older presenting with NSTE-ACS, clopidogrel is a favourable alternative to ticagrelor, because it leads to fewer bleeding events without an increase in the combined endpoint of all-cause death, myocardial infarction, stroke, and bleeding. Clopidogrel could be an alternative P2Y12 inhibitor especially for elderly patients with a higher bleeding risk., Funding: ZonMw., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Published
2020
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43. Proteomic Bioprofiles and Mechanistic Pathways of Progression to Heart Failure.

Author

Ferreira JP, Verdonschot J, Collier T, Wang P, Pizard A, Bär C, Björkman J, Boccanelli A, Butler J, Clark A, Cleland JG, Delles C, Diez J, Girerd N, González A, Hazebroek M, Huby AC, Jukema W, Latini R, Leenders J, Levy D, Mebazaa A, Mischak H, Pinet F, Rossignol P, Sattar N, Sever P, Staessen JA, Thum T, Vodovar N, Zhang ZY, Heymans S, and Zannad F

Subjects
Aged, Case-Control Studies, Disease Progression, Female, Humans, Male, Proteomics, Biomarkers blood, Heart Failure blood, Heart Failure physiopathology, Proteome analysis
Abstract

Background Identifying the mechanistic pathways potentially associated with incident heart failure (HF) may provide a basis for novel preventive strategies. Methods and Results To identify proteomic biomarkers and the potential underlying mechanistic pathways that may be associated with incident HF defined as the first hospitalization for HF, a nested-matched case-control design was used with cases (incident HF) and controls (without HF) selected from 3 cohorts (>20 000 individuals). Controls were matched on cohort, follow-up time, age, and sex. Two independent sample sets (a discovery set with 286 cases and 591 controls and a replication set with 276 cases and 280 controls) were used to discover and replicate the findings. Two hundred fifty-two circulating proteins in the plasma were studied. Adjusting for the matching variables age, sex, and follow-up time (and correcting for multiplicity of tests), 89 proteins were found to be associated with incident HF in the discovery phase, of which 38 were also associated with incident HF in the replication phase. These 38 proteins pointed to 4 main network clusters underlying incident HF: (1) inflammation and apoptosis, indicated by the expression of the TNF (tumor necrosis factor)-family members; (2) extracellular matrix remodeling, angiogenesis and growth, indicated by the expression of proteins associated with collagen metabolism, endothelial function, and vascular homeostasis; (3) blood pressure regulation, indicated by the expression of natriuretic peptides and proteins related to the renin-angiotensin-aldosterone system; and (4) metabolism, associated with cholesterol and atherosclerosis. Conclusions Clusters of biomarkers associated with mechanistic pathways leading to HF were identified linking inflammation, apoptosis, vascular function, matrix remodeling, blood pressure control, and metabolism. These findings provide important insight on the pathophysiological mechanisms leading to HF. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT02556450.

Published
2019
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44. Genetic variation in galectin-3 gene associates with cognitive function at old age.

Author

Trompet S, Jukema W, Mooijaart SP, Ford I, Stott DJ, Westendorp RG, and de Craen AJ

Subjects
Aged, Aged, 80 and over, Aging blood, C-Reactive Protein metabolism, Cross-Sectional Studies, Female, Gene Frequency, Genetic Association Studies, Genotype, Humans, Male, Neuropsychological Tests, Prospective Studies, Retrospective Studies, Aging genetics, Cognition physiology, Cognition Disorders genetics, Galectin 3 genetics, Polymorphism, Single Nucleotide genetics
Abstract

Inflammation plays an important role in the development of cognitive decline and dementia in old age. Galectin-3 is known for its role in acute and chronic inflammation. We assessed whether genetic variation in the LGALS3 gene, encoding for galectin-3, associates with cognitive function in the 5804 participants of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER). The rs4644, rs4652, and rs1009977 polymorphisms were genotyped to cover the genomic region of the LGALS3 gene. Subjects carrying the variant alleles of each LGALS3 single nucleotide polymorphism (SNP) had significantly higher baseline C-reactive protein concentrations (p < 0.01). Carriers of the variant alleles had significantly worse performance at baseline compared with carriers of the wild-type allele (all p < 0.05). In the longitudinal analysis, we found that carriers of the variant alleles had worse performance at the attention tasks compared with carriers of the wild-type allele. Although observed differences were small, these data suggest that genetic variation in the LGALS3 gene might be associated with cognitive function in an elderly population. Further research is warranted to confirm these results., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Published
2012
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45. Pre-infarction angina predicts thrombus burden in patients admitted for ST-segment elevation myocardial infarction.

Author

Ahmed TA, Sorgdrager BJ, Cannegieter SC, van der Laarse A, Schalij MJ, and Jukema W

Subjects
Aged, Coronary Angiography, Coronary Thrombosis diagnostic imaging, Electrocardiography, Female, Humans, Male, Middle Aged, Myocardial Infarction complications, Myocardial Infarction pathology, Myocardial Infarction physiopathology, Platelet Glycoprotein GPIIb-IIIa Complex antagonists & inhibitors, Ventricular Function, Left, Angina Pectoris physiopathology, Angioplasty, Balloon, Coronary, Coronary Thrombosis etiology, Myocardial Infarction therapy
Abstract

Aims: In patients with ST-elevation myocardial infarction (STEMI), high thrombotic burden, subsequent distal embolisation and myocardial no-reflow remain a large obstacle that may negate the benefits of urgent coronary revascularisation. We aimed at assessing the predictors of: 1) thrombus grade in patients undergoing primary percutaneous coronary intervention (PPCI) and 2) infarct size, in order to optimise therapy to reduce thrombus burden., Methods and Results: One-hundred and fifty-three consecutive patients presenting with STEMI and undergoing PPCI were included. Thrombus was evaluated by angiography and scored according to the TIMI study group score. Next, patients were categorised into two groups that had either high thrombus grade (HTG; score 4-5) or low thrombus grade (LTG; score 1-3). We evaluated predictors of angiographic thrombus grade among a number of clinical, angiographic and laboratory data. We also assessed infarct size and scintigraphic left ventricular ejection fraction (LVEF) at three months in both patient groups. Ninety-four patients (58±11 years; 75% males) presented with HTG, whereas 59 patients (58±12 years; 78% males) presented with LTG. Pre-infarction angina (PIA) was more frequently encountered in the LTG group than in the HTG group (25% vs. 10%, p=0.009). Pre-procedural TIMI flow was significantly lower in the HTG group (p<0.001), and thrombosuction was more frequently applied in the HTG group (p<0.001). Absence of PIA (OR=0.29, 95% CI=0.11-0.75, p=0.01) and proximal culprit lesion (OR=2.10, 95% CI=1.02-4.36, p=0.04) were the only independent predictors of HTG. HTG proved an independent predictor of higher peak levels of creatine kinase (CK) (p<0.001) and troponin T (p<0.001), as well as lower LVEF (p=0.05) along with male gender and absence of prior statin therapy., Conclusions: Absence of PIA and proximal culprit lesions are associated with higher thrombus grade. Higher thrombus grade is associated with larger infarct size and slightly worse LV function. This may have clinical implications in planning strategies, particularly regarding pharmacotherapy, that aim to decrease thrombus burden prior to stent implantation.

Published
2012
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46. Assessment of obstruction length and optimal viewing angle from biplane X-ray angiograms.

Author

Tu S, Koning G, Jukema W, and Reiber JH

Subjects
Coronary Angiography instrumentation, Humans, Phantoms, Imaging, Predictive Value of Tests, Reproducibility of Results, Coronary Angiography methods, Coronary Stenosis diagnostic imaging, Imaging, Three-Dimensional, Radiographic Image Interpretation, Computer-Assisted, Tomography, X-Ray Computed instrumentation
Abstract

Three-dimensional quantitative coronary angiography (3D QCA) has been encouraged by the increasing need to better assess vessel dimensions and geometry for interventional purposes. A novel 3D QCA system based on biplane X-ray angiograms is presented in this paper. By correcting for the isocenter offset and by improving the epipolar constraint for corresponding two angiographic projections, accurate and robust reconstruction of the vessel centerline is achieved and the reproducibility of its applications, e.g., the assessments of obstruction length and optimal viewing angle, is guaranteed. The accuracy and variability in assessing the obstruction length and optimal bifurcation viewing angle were investigated by using phantom experiments. The segment length assessed by 3D QCA correlated well with the true wire segment length (r (2) = 0.999) and the accuracy and precision were 0.04 +/- 0.25 mm (P < 0.01). 3D QCA slightly underestimated the rotation angle (difference: -1.5 degrees +/- 3.6 degrees , P < 0.01), while no significant difference was observed for the angulation angle (difference: -0.2 degrees +/- 2.4 degrees , P = 0.54). In conclusion, the new 3D QCA approach allows highly accurate and precise assessments of obstruction length and optimal viewing angle from X-ray angiography.

Published
2010
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47. High Innate Production Capacity of Proinflammatory Cytokines Increases Risk for Death from Cancer: Results of the PROSPER Study.

Author

Trompet S, de Craen AJ, Mooijaart S, Stott DJ, Ford I, Sattar N, Jukema W, and Westendorp RG

Abstract

PURPOSE: Various lines of evidence suggest that proinflammatory factors may play a role in tumor growth and metastasis, the leading cause of cancer-related mortality. However, most evidence originates from animal models, only few human studies reported an association between proinflammatory cytokines and death from cancer. Here, we investigated the association between circulating levels and innate production capacity of proinflammatory cytokines and cancer incidence and mortality in the PROspective Study on Pravastatin in the Elderly at Risk (PROSPER). EXPERIMENTAL DESIGN: Circulating levels of interleukin 6 (IL-6) and C-reactive protein were measured in all 5,804 participants of the PROSPER study. The innate production capacity of IL-6, IL-1beta, and tumor necrosis factor alpha (TNF-alpha) were measured in a random sample of 403 subjects. RESULTS: We showed that high circulating inflammatory markers were associated with an increased risk for cancer incidence and death from cancer during follow-up (all P < 0.05). Moreover, high innate proinflammatory cytokine production capacity is associated with an increased risk for death from cancer (all P < 0.04) but not with higher cancer incidence during follow-up (all P > 0.6). CONCLUSIONS: High innate production capacity of proinflammatory cytokines is associated with an increased risk for death from cancer, probably because of increased tumor growth and metastasis. Because there was no association between innate production capacity and cancer incidence, the association between circulating levels and cancer incidence at least partially reflects reversed causality. (Clin Cancer Res 2009;15(24):7744-8).

Published
2009
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48. Coronary angiography enhancement for visualization.

Author

Tu S, Koning G, Tuinenburg JC, Jukema W, Zhang S, Chen Y, and Reiber JH

Subjects
Humans, Observer Variation, Predictive Value of Tests, Reproducibility of Results, Algorithms, Coronary Angiography, Coronary Artery Disease diagnostic imaging, Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted
Abstract

High quality visualization on X-ray angiograms is of great significance both for the diagnosis of vessel abnormalities and for coronary interventions. Algorithms for improving the visualization of detailed vascular structures without significantly increasing image noise are currently demanded in the market. A new algorithm called stick-guided lateral inhibition (SGLI) is presented for increasing the visibility of coronary vascular structures. A validation study was set up to compare the SGLI algorithm with the conventional unsharp masking (UM) algorithm on 20 still frames of coronary angiographic images. Ten experienced QCA analysts and nine cardiologists from various centers participated in the validation. Sample scoring value (SSV) and observer agreement value (OAV) were defined to evaluate the validation result, in terms of enhancing performance and observer agreement, respectively. The mean of SSV was concluded to be 77.1 +/- 11.9%, indicating that the SGLI algorithm performed significantly better than the UM algorithm (P-value < 0.001). The mean of the OAV was concluded to be 70.3%, indicating that the average agreement with respect to a senior cardiologist was 70.3%. In conclusion, this validation study clearly demonstrates the superiority of the SGLI algorithm in the visualization of coronary arteries from X-ray angiograms.

Published
2009
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49. Platelet receptor P2RY12 haplotypes predict restenosis after percutaneous coronary interventions.

Author

Rudez G, Pons D, Leebeek F, Monraats P, Schrevel M, Zwinderman A, de Winter R, Tio R, Doevendans P, Jukema W, and de Maat M

Subjects
Aged, Alleles, Coronary Disease blood, Coronary Restenosis blood, Coronary Restenosis etiology, Female, Follow-Up Studies, Gene Frequency, Haplotypes, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Receptors, Purinergic P2Y12, Risk Factors, Stents, Angioplasty, Balloon, Coronary, Blood Platelets metabolism, Coronary Disease genetics, Coronary Disease therapy, Coronary Restenosis genetics, Receptors, Purinergic P2 genetics
Abstract

The platelet receptor P2Y12 (gene symbol P2RY12) is involved in several processes that contribute to restenosis after percutaneous coronary interventions (PCI). Therefore, common variation in the P2Y12 gene may serve as a useful marker for risk stratification. We studied whether common variation in the platelet receptor P2Y12 gene affects the risk of restenosis after PCI. Comprehensive coverage of common variation in the P2Y12 gene was obtained by genotyping five haplotype-tagging SNPs (ht-SNPs) in 2,062 PCI-treated patients who received a stent and participated in the GENetic DEterminants of Restenosis (GENDER) Study. Haplotypes were inferred and their association with target vessel revascularization (TVR) was studied. Seven P2Y12 haplotypes were identified with an allelic frequency above 5% (designated here H1 to H7) of which two (H5 and H7) were associated with a higher risk of TVR (hazard ratios [HR]=1.4, 95% confidence interval [CI]=1.0-2.0; and HR=1.6, 95% CI=1.2-2.0, respectively) than the reference P2Y12 haplotype (H1), which contains the common alleles of all five P2Y12 ht-SNPs. Our study shows that common variation in the P2Y12 gene predicts restenosis in PCI-treated patients.

Published
2008
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50. Local Cre-mediated gene recombination in vascular smooth muscle cells in mice.

Author

Zadelaar SM, Boesten LS, Pires NM, van Nieuwkoop A, Biessen EA, Jukema W, Havekes LM, van Vlijmen BJ, and Willems van Dijk K

Subjects
Animals, Drug Delivery Systems, Integrases genetics, Mice, Mice, Transgenic, Muscle, Smooth, Vascular cytology, Muscle, Smooth, Vascular pathology, Promoter Regions, Genetic, Tamoxifen analogs & derivatives, Tamoxifen pharmacology, Integrases physiology, Muscle, Smooth, Vascular metabolism, Myocytes, Smooth Muscle metabolism, Recombination, Genetic drug effects
Abstract

Here we describe a means to conditionally modify genes at a predefined and localized region of the vasculature using a perivascular drug delivery device (PDD). A 4-hydroxytamoxifen (4-OHT)-eluting PDD was applied around the carotid or femoral artery of a mouse strain carrying both the tamoxifen-inducible and smooth muscle cell (SMC)-specific Cre-recombinase (SM-Cre-ER(T2)) transgene and a stop-floxed beta-galactosidase gene in the Rosa26 locus: the SM-CreER(T2)(ki)/rosa26 mouse. A dose and time curve of 0-10% (w/w) 4-OHT and 0-14 days application of the PDD in SM-CreER(T2)(ki)/rosa26 mice showed optimal gene recombination at 1% (w/w) 4-OHT loading at 7 days post application (carotid artery 2.4+/-1.8%; femoral artery 4.0+/-3.8% of SMCs). The unique 4-OHT-eluting PDD allowed us to achieve SMC-specific recombination in the same order of magnitude as compared to systemic tamoxifen administration. In addition, recombination was completely confined to the PDD-treated vessel wall segment. Thus, local application of a 4-OHT-eluting PDD results in vascular SMC-specific Cre-mediated recombination in SM-CreER(T2)(ki)/rosa26 mice without affecting additional SMCs.

Published
2006
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