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51. PHOENIX (Picking up Hidden Osteoporosis Effectively during Normal CT Imaging without additional X-rays): protocol for a randomised, multicentre feasibility study

Author

Poole, Kenneth ES, Chappell, Daniel DG, Clark, Emma, Fleming, Jane, Shepstone, Lee, Turmezei, Thomas D, Wagner, Adam P, Willoughby, Karen, Kaptoge, Stephen K, Poole, Kenneth ES [0000-0003-4546-7352], Chappell, Daniel DG [0000-0002-1958-6246], Fleming, Jane [0000-0002-8127-2061], Wagner, Adam P [0000-0002-9101-3477], Willoughby, Karen [0000-0002-2039-1155], and Apollo - University of Cambridge Repository

Subjects
Male, X-Rays, rheumatology, back pain, computed tomography, General Medicine, spine, bone diseases, diagnostic radiology, Feasibility Studies, Humans, Multicenter Studies as Topic, Osteoporosis, Spinal Fractures, Female, Tomography, X-Ray Computed, Osteoporotic Fractures, Aged, Randomized Controlled Trials as Topic
Abstract

IntroductionTwo million out of the UK’s 5 million routine diagnostic CT scans performed each year incorporate the thoracolumbar spine or pelvic region. Up to one-third reveal undiagnosed osteoporosis or vertebral fractures. We developed an intervention, Picking up Hidden Osteoporosis Effectively during Normal CT Imaging without additional X-rays (‘PHOENIX’), to facilitate early detection and management of osteoporosis in people attending hospitals for CT scans.Methods and analysisA multicentre, randomised, pragmatic feasibility study. From the general CT-attending population, women aged ≥65 years and men aged ≥75 years attending for CT scans are invited to participate, via a novel consent form incorporating Fracture Risk Assessment (FRAX) questions. Those at increased 10-year risk (within the amber or red zones of the UK FRAX graphical outputs for further action) are block randomised (1:1:1) to (1) PHOENIX intervention, (2) active control or (3) usual care. The PHOENIX intervention comprises (i) retrieving the CT scans using the NHS Image Exchange Portal, (ii) Mindways QCT Pro software analysis of CT hip and spine none density with CT vertebral fracture assessment, (iii) sending the participants’ general practitioner (GP) a clinical report including diagnosis, necessary investigations and recommended treatment. Baseline CT scans from groups 2 and 3 are assessed with the PHOENIX intervention only at study end. Assuming 25% attrition, the study is powered to find a predicted superior osteoporosis treatment rate with PHOENIX (20%) vs 16% among patients whose GPs were sent the FRAX questionnaire only (active control) and 5% in the usual care group. Five hospitals are participating to determine feasibility. The co-primary feasibility outcome measures are (a) ability to randomise 375 patients within 10 months and (b) retention of 75% of survivors, completing their 1-year bone health outcome questionnaire. Secondary 1-year outcomes include osteoporosis/vertebral fracture identification rates and osteoporosis treatment rates. Stakeholder acceptability and economic aspects are evaluated.Ethics and disseminationApproved by committee (National Research Ethics Service) East of England (EE) as REF/19/EE/0176. Dissemination will be through the Royal Osteoporosis Society (to patients and public) as well as to clinician peers via national and international bone/rheumatology scientific and clinical meetings.Trial registration numberISRCTN14722819.

Published
2022

52. Mild-to-Moderate Kidney Dysfunction and Cardiovascular Disease:Observational and Mendelian Randomization Analyses

Author

Gaziano, Liam, Sun, Luanluan, Arnold, Matthew, Bell, Steven, Cho, Kelly, Kaptoge, Stephen K., Song, Rebecca J., Burgess, Stephen, Posner, Daniel C., Mosconi, Katja, Robinson-Cohen, Cassianne, Mason, Amy M., Bolton, Thomas R., Tao, Ran, Allara, Elias, Schubert, Petra, Chen, Lingyan, Staley, James R., Staplin, Natalie, Altay, Servet, Amiano, Pilar, Arndt, Volker, Ärnlöv, Johan, Barr, Elizabeth L.M., Björkelund, Cecilia, Boer, Jolanda M.A., Brenner, Hermann, Casiglia, Edoardo, Chiodini, Paolo, Cooper, Jackie A., Coresh, Josef, Cushman, Mary, Dankner, Rachel, Davidson, Karina W., De Jongh, Renate T., Donfrancesco, Chiara, Engström, Gunnar, Freisling, Heinz, De La Cámara, Agustín Gómez, Gudnason, Vilmundur, Hankey, Graeme J., Hansson, Per Olof, Heath, Alicia K., Hoorn, Ewout J., Imano, Hironori, Jassal, Simerjot K., Kaaks, Rudolf, Wood, AM, Angelantonio, Emanuele Di, Gaziano, Liam, Sun, Luanluan, Arnold, Matthew, Bell, Steven, Cho, Kelly, Kaptoge, Stephen K., Song, Rebecca J., Burgess, Stephen, Posner, Daniel C., Mosconi, Katja, Robinson-Cohen, Cassianne, Mason, Amy M., Bolton, Thomas R., Tao, Ran, Allara, Elias, Schubert, Petra, Chen, Lingyan, Staley, James R., Staplin, Natalie, Altay, Servet, Amiano, Pilar, Arndt, Volker, Ärnlöv, Johan, Barr, Elizabeth L.M., Björkelund, Cecilia, Boer, Jolanda M.A., Brenner, Hermann, Casiglia, Edoardo, Chiodini, Paolo, Cooper, Jackie A., Coresh, Josef, Cushman, Mary, Dankner, Rachel, Davidson, Karina W., De Jongh, Renate T., Donfrancesco, Chiara, Engström, Gunnar, Freisling, Heinz, De La Cámara, Agustín Gómez, Gudnason, Vilmundur, Hankey, Graeme J., Hansson, Per Olof, Heath, Alicia K., Hoorn, Ewout J., Imano, Hironori, Jassal, Simerjot K., Kaaks, Rudolf, Wood, AM, and Angelantonio, Emanuele Di

Abstract

Background: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. Methods: Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. Results: There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values <60 or >105 mL·min-1·1.73 m-2, compared with those with eGFR between 60 and 105 mL·min-1·1.73 m-2. Mendelian randomization analyses for CHD showed an association among participants with eGFR <60 mL·min-1·1.73 m-2, with a 14% (95% CI, 3%-27%) higher CHD risk per 5 mL·min-1·1.73 m-2 lower genetically predicted eGFR, but not for those with eGFR >105 mL·min-1·1.73 m-2. Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. Conclusions: In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventiv

Published
2022

53. SCORE2 models allow consideration of sex-specific cardiovascular disease risks by region

Author

Interne Geneeskunde Vasculaire, MS Interne Geneeskunde, Circulatory Health, Hageman, Steven, Pennells, Lisa, Ojeda, Francisco, Kaptoge, Stephen, Dorresteijn, Jannick, Angelantonio, Emanuele Di, SCORE2 working group and ESC Cardiovascular Risk Collaboration, Interne Geneeskunde Vasculaire, MS Interne Geneeskunde, Circulatory Health, Hageman, Steven, Pennells, Lisa, Ojeda, Francisco, Kaptoge, Stephen, Dorresteijn, Jannick, Angelantonio, Emanuele Di, and SCORE2 working group and ESC Cardiovascular Risk Collaboration

Published
2022

56. Association of shorter leucocyte telomere length with risk of frailty

Author

Bountziouka, Vasiliki, primary, Nelson, Christopher P., additional, Codd, Veryan, additional, Wang, Qingning, additional, Musicha, Crispin, additional, Allara, Elias, additional, Kaptoge, Stephen, additional, Di Angelantonio, Emanuele, additional, Butterworth, Adam S., additional, Thompson, John R., additional, Curtis, Elizabeth M., additional, Wood, Angela M., additional, Danesh, John N., additional, Harvey, Nicholas C., additional, Cooper, Cyrus, additional, and Samani, Nilesh J., additional

Published
2022
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57. Estimating dose-response relationships for vitamin D with coronary heart disease, stroke, and all-cause mortality: observational and Mendelian randomisation analyses

Author

Drechsler, Christiane, Bolland, Mark J., Reid, Ian, Willeit, Johann, Schett, Georg, Santer, Peter, Sofat, Reecha, Taylor, Julie, Dale, Caroline, Prince, Richard L., Ben-Shlomo, Yoav, Gallacher, John, Jensen, Gorm B., Frikke-Schmidt, Ruth, Bojesen, Stig Egil, Benn, Marianne, Wulff, Anders B., Krogh, Signe V., Schierbeck, Louise Lind, Kaptoge, Stephen, Wareham, Nicholas, Schöttker, Ben, Zhu, Anna, Holleczek, Bernd, Dennison, Elaine, Jameson, Karen, Schleithoff, Stefanie Schulze, Frisch, Sabine, Linneberg, Allan, Skaaby, Tea, Kårhus, Line Lund, de Jongh, Renate T., Visser, Marjolein, Dobnig, Harald, Robinson-Cohen, Cassianne, Siscovick, David S., Kestenbaum, Bryan R., McConnachie, Alex, Sattar, Naveed, Morrison, David, Lundqvist, Annamari, Cawthon, Peggy M., Albertorio, Juan R., Jukema, J Wouter, Trompet, Stella, Kearney, Patricia, Dörr, Marcus, Völzke, Henry, Nauck, Matthias, Rossing, Peter, Persson, Frederik, Marniemi, Jukka, Vazquez, Victoria, Sundström, Johan, Risérus, Ulf, Michaëlsson, Karl, Emberson, Jonathan, Leon, David, and Kivimäki, Mika

Abstract

Background:\ud Randomised trials of vitamin D supplementation for cardiovascular disease and all-cause mortality have generally reported null findings. However, generalisability of results to individuals with low vitamin D status is unclear. We aimed to characterise dose-response relationships between 25-hydroxyvitamin D (25[OH]D) concentrations and risk of coronary heart disease, stroke, and all-cause mortality in observational and Mendelian randomisation frameworks.\ud \ud Methods:\ud Observational analyses were undertaken using data from 33 prospective studies comprising 500 962 individuals with no known history of coronary heart disease or stroke at baseline. Mendelian randomisation analyses were performed in four population-based cohort studies (UK Biobank, EPIC-CVD, and two Copenhagen population-based studies) comprising 386 406 middle-aged individuals of European ancestries, including 33 546 people who developed coronary heart disease, 18 166 people who had a stroke, and 27 885 people who died. Primary outcomes were coronary heart disease, defined as fatal ischaemic heart disease (International Classification of Diseases 10th revision code I20-I25) or non-fatal myocardial infarction (I21-I23); stroke, defined as any cerebrovascular disease (I60-I69); and all-cause mortality.\ud \ud Findings:\ud Observational analyses suggested inverse associations between incident coronary heart disease, stroke, and all-cause mortality outcomes with 25(OH)D concentration at low 25(OH)D concentrations. In population-wide genetic analyses, there were no associations of genetically-predicted 25(OH)D with coronary heart disease, stroke, or all-cause mortality. However, for the participants with vitamin D deficiency (25[OH]D concentration

Published
2021

59. RETRACTED: Estimating dose-response relationships for vitamin D with coronary heart disease, stroke, and all-cause mortality: observational and Mendelian randomisation analyses

Author

Sofianopoulou, Eleni, Kaptoge, Stephen K, Afzal, Shoaib, Jiang, Tao, Gill, Dipender, Gundersen, Thomas E, Bolton, Thomas R, Allara, Elias, Arnold, Matthew G, Mason, Amy M, Chung, Ryan, Pennells, Lisa A M, Shi, Fanchao, Sun, Luanluan, Willeit, Peter, Forouhi, Nita G, Langenberg, Claudia, Sharp, Stephen J, Panico, Salvatore, Engström, Gunnar, Melander, Olle, Tong, Tammy Y N, Perez-Cornago, Aurora, Norberg, Margareta, Johansson, Ingegerd, Katzke, Verena, Srour, Bernard, José Sánchez, María, Redondo-Sánchez, Daniel, Olsen, Anja, Dahm, Christina C, Overvad, Kim, Brustad, Magritt, Skeie, Guri, Moreno-Iribas, Conchi, Onland-Moret, N Charlotte, van der Schouw, Yvonne T, Tsilidis, Konstantinos K, Heath, Alicia K, Agnoli, Claudia, Krogh, Vittorio, de Boer, Ian H, Kobylecki, Camilla Jannie, Çolak, Yunus, Zittermann, Armin, Sundström, Johan, Welsh, Paul, Weiderpass, Elisabete, Aglago, Elom K, Ferrari, Pietro, Clarke, Robert, Boutron, Marie-Christine, Severi, Gianluca, MacDonald, Conor, Providencia, Rui, Masala, Giovanna, Zamora Ros, Raul, Boer, Jolanda, Verschuren, WM Monique, Cawthon, Peggy, Schierbeck, Louise L, Cooper, Cyrus, Schulze, Matthias B, Bergmann, Manuela M, Hannemann, Anke, Kiechl, Stefan, Brenner, Hermann, van Schoor, Natasja M, Albertorio, Juan R, Sacerdote, Carlotta, Linneberg, Allan, Kårhus, Line L, Huerta, José María, Imaz, Liher, Joergensen, Christel, Ben-Shlomo, Yoav, Lundqvist, Annamari, Gallacher, John, Sattar, Naveed, Wood, Angela M, Wareham, Nicholas J, Nordestgaard, Børge G, Di Angelantonio, Emanuele, Danesh, John, Butterworth, Adam S, and Burgess, Stephen

Published
2021
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60. Modifiable traits, healthy behaviours, and leucocyte telomere length

Author

Bountziouka, Vasiliki, primary, Musicha, Crispin, additional, Allara, Elias, additional, Kaptoge, Stephen, additional, Wang, Qingning, additional, Di Angelantonio, Emanuele, additional, Butterworth, Adam S, additional, Thompson, John R, additional, Danesh, John N, additional, Wood, Angela M, additional, Nelson, Christopher P, additional, Codd, Veryan, additional, and Samani, Nilesh J, additional

Published
2021
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61. Estimating dose-response relationships for vitamin D with coronary heart disease, stroke, and all-cause mortality: observational and Mendelian randomisation analyses

Author

Sofianopoulou, Eleni, primary, Kaptoge, Stephen K, additional, Afzal, Shoaib, additional, Jiang, Tao, additional, Gill, Dipender, additional, Gundersen, Thomas E, additional, Bolton, Thomas R, additional, Allara, Elias, additional, Arnold, Matthew G, additional, Mason, Amy M, additional, Chung, Ryan, additional, Pennells, Lisa A M, additional, Shi, Fanchao, additional, Sun, Luanluan, additional, Willeit, Peter, additional, Forouhi, Nita G, additional, Langenberg, Claudia, additional, Sharp, Stephen J, additional, Panico, Salvatore, additional, Engström, Gunnar, additional, Melander, Olle, additional, Tong, Tammy Y N, additional, Perez-Cornago, Aurora, additional, Norberg, Margareta, additional, Johansson, Ingegerd, additional, Katzke, Verena, additional, Srour, Bernard, additional, José Sánchez, María, additional, Redondo-Sánchez, Daniel, additional, Olsen, Anja, additional, Dahm, Christina C, additional, Overvad, Kim, additional, Brustad, Magritt, additional, Skeie, Guri, additional, Moreno-Iribas, Conchi, additional, Onland-Moret, N Charlotte, additional, van der Schouw, Yvonne T, additional, Tsilidis, Konstantinos K, additional, Heath, Alicia K, additional, Agnoli, Claudia, additional, Krogh, Vittorio, additional, de Boer, Ian H, additional, Kobylecki, Camilla Jannie, additional, Çolak, Yunus, additional, Zittermann, Armin, additional, Sundström, Johan, additional, Welsh, Paul, additional, Weiderpass, Elisabete, additional, Aglago, Elom K, additional, Ferrari, Pietro, additional, Clarke, Robert, additional, Boutron, Marie-Christine, additional, Severi, Gianluca, additional, MacDonald, Conor, additional, Providencia, Rui, additional, Masala, Giovanna, additional, Zamora Ros, Raul, additional, Boer, Jolanda, additional, Verschuren, WM Monique, additional, Cawthon, Peggy, additional, Schierbeck, Louise L, additional, Cooper, Cyrus, additional, Schulze, Matthias B, additional, Bergmann, Manuela M, additional, Hannemann, Anke, additional, Kiechl, Stefan, additional, Brenner, Hermann, additional, van Schoor, Natasja M, additional, Albertorio, Juan R, additional, Sacerdote, Carlotta, additional, Linneberg, Allan, additional, Kårhus, Line L, additional, Huerta, José María, additional, Imaz, Liher, additional, Joergensen, Christel, additional, Ben-Shlomo, Yoav, additional, Lundqvist, Annamari, additional, Gallacher, John, additional, Sattar, Naveed, additional, Wood, Angela M, additional, Wareham, Nicholas J, additional, Nordestgaard, Børge G, additional, Di Angelantonio, Emanuele, additional, Danesh, John, additional, Butterworth, Adam S, additional, and Burgess, Stephen, additional

Published
2021
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62. Assessing Risk Prediction Models Using Individual Participant Data From Multiple Studies

Author

Pennells, Lisa, Kaptoge, Stephen, White, Ian R., Thompson, Simon G., Wood, Angela M., Tipping, Robert W., Folsom, Aaron R., Couper, David J., Ballantyne, Christie M., Coresh, Josef, Goya Wannamethee, S., Morris, Richard W., Kiechl, Stefan, Willeit, Johann, Willeit, Peter, Schett, Georg, Ebrahim, Shah, Lawlor, Debbie A., Yarnell, John W., Gallacher, John, Cushman, Mary, Psaty, Bruce M., Tracy, Russ, Tybjærg-Hansen, Anne, Price, Jackie F., Lee, Amanda J., McLachlan, Stela, Khaw, Kay-Tee, Wareham, Nicholas J., Brenner, Hermann, Schöttker, Ben, Müller, Heiko, Jansson, Jan-Håkan, Wennberg, Patrik, Salomaa, Veikko, Harald, Kennet, Jousilahti, Pekka, Vartiainen, Erkki, Woodward, Mark, DʼAgostino, Ralph B., Bladbjerg, Else-Marie, Jørgensen, Torben, Kiyohara, Yutaka, Arima, Hisatomi, Doi, Yasufumi, Ninomiya, Toshiharu, Dekker, Jacqueline M., Nijpels, Giel, Stehouwer, Coen D. A., Kauhanen, Jussi, Salonen, Jukka T., Meade, Tom W., Cooper, Jackie A., Cushman, Mary, Folsom, Aaron R., Psaty, Bruce M., Shea, Steven, Döring, Angela, Kuller, Lewis H., Grandits, Greg, Gillum, Richard F., Mussolino, Michael, Rimm, Eric B., Hankinson, Sue E., Manson, JoAnn E., Pai, Jennifer K., Kirkland, Susan, Shaffer, Jonathan A., Shimbo, Daichi, Bakker, Stephan J. L., Gansevoort, Ron T., Hillege, Hans L., Amouyel, Philippe, Arveiler, Dominique, Evans, Alun, Ferrières, Jean, Sattar, Naveed, Westendorp, Rudi G., Buckley, Brendan M., Cantin, Bernard, Lamarche, Benoît, Barrett-Connor, Elizabeth, Wingard, Deborah L., Bettencourt, Richele, Gudnason, Vilmundur, Aspelund, Thor, Sigurdsson, Gunnar, Thorsson, Bolli, Kavousi, Maryam, Witteman, Jacqueline C., Hofman, Albert, Franco, Oscar H., Howard, Barbara V., Zhang, Ying, Best, Lyle, Umans, Jason G., Onat, Altan, Sundström, Johan, Michael Gaziano, J., Stampfer, Meir, Ridker, Paul M., Michael Gaziano, J., Ridker, Paul M., Marmot, Michael, Clarke, Robert, Collins, Rory, Fletcher, Astrid, Brunner, Eric, Shipley, Martin, Kivimäki, Mika, Ridker, Paul M., Buring, Julie, Cook, Nancy, Ford, Ian, Shepherd, James, Cobbe, Stuart M., Robertson, Michele, Walker, Matthew, Watson, Sarah, Alexander, Myriam, Butterworth, Adam S., Angelantonio, Emanuele Di, Gao, Pei, Haycock, Philip, Kaptoge, Stephen, Pennells, Lisa, Thompson, Simon G., Walker, Matthew, Watson, Sarah, White, Ian R., Wood, Angela M., Wormser, David, and Danesh, John

Published
2014
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63. Estimating individual lifetime risk of incident cardiovascular events in adults with Type 2 diabetes: an update and geographical calibration of the DIAbetes Lifetime perspective model (DIAL2).

Author

Østergaard, Helena Bleken, Hageman, Steven H J, Read, Stephanie H, Taylor, Owen, Pennells, Lisa, Kaptoge, Stephen, Petitjean, Carmen, Xu, Zhe, Shi, Fanchao, McEvoy, John William, Herrington, William, Visseren, Frank L J, Wood, Angela, Eliasson, Björn, Sattar, Naveed, Wild, Sarah, Angelantonio, Emanuele Di, and Dorresteijn, Jannick A N

Published
2023
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64. A genome-wide meta-analysis yields 46 new loci associating with biomarkers of iron homeostasis

Author

Bell, Steven, Allara, Elias, Ramond, Anna, Paul, Dirk, Howson, Joanna, Astle, William, Surendran, Praveen, Jiang, Tao, Akbari, Parsa, Kaptoge, Stephen, Wood, Angela, Peters, James, Soranzo, Nicole, Ouwehand, Willem, Butterworth, Adam, Danesh, John, Di Angelantonio, Emanuele, Bell, Steven [0000-0001-6774-3149], Allara, Elias [0000-0002-1634-8330], Paul, Dirk [0000-0002-8230-0116], Astle, William [0000-0001-8866-6672], Kaptoge, Stephen [0000-0002-1155-4872], Wood, Angela [0000-0002-7937-304X], Soranzo, Nicole [0000-0003-1095-3852], Ouwehand, Willem [0000-0002-7744-1790], Butterworth, Adam [0000-0002-6915-9015], Danesh, John [0000-0003-1158-6791], Di Angelantonio, Emanuele [0000-0001-8776-6719], and Apollo - University of Cambridge Repository

Subjects
Iron Overload, Anemia, Iron-Deficiency, Genotype, Denmark, Iron, Iceland, Transferrin, Genetic Variation, Risk Assessment, United Kingdom, Phenotype, Genetic Loci, Risk Factors, Ferritins, Homeostasis, Humans, health care economics and organizations, Biomarkers, Genome-Wide Association Study
Abstract

Iron is essential for many biological functions and iron deficiency and overload have major health implications. We performed a meta-analysis of three genome-wide association studies from Iceland, the UK and Denmark of blood levels of ferritin (N=246,139), total iron binding capacity (N=135,430), iron (N=163,511) and transferrin saturation (N=131,471). We found 62 independent sequence variants associating with iron homeostasis parameters at 56 loci, including 46 novel loci. Variants at DUOX2, F5, SLC11A2 and TMPRSS6 associate with iron deficiency anemia, while variants at TF, HFE, TFR2 and TMPRSS6 associate with iron overload. A HBS1L-MYB intergenic region variant associates both with increased risk of iron overload and reduced risk of iron deficiency anemia. The DUOX2 missense variant is present in 14% of the population, associates with all iron homeostasis biomarkers, and increases the risk of iron deficiency anemia by 29%. The associations implicate proteins contributing to the main physiological processes involved in iron homeostasis: iron sensing and storage, inflammation, absorption of iron from the gut, iron recycling, erythropoiesis and bleeding/menstruation.

Published
2020
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65. Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture

Author

Zheng, Hou-Feng, Forgetta, Vincenzo, Hsu, Yi-Hsiang, Estrada, Karol, Rosello-Diez, Alberto, Leo, Paul J., Dahia, Chitra L., Park-Min, Kyung Hyun, Tobias, Jonathan H., Kooperberg, Charles, Kleinman, Aaron, Styrkarsdottir, Unnur, Liu, Ching-Ti, Uggla, Charlotta, Evans, Daniel S., Nielson, Carrie M., Walter, Klaudia, Pettersson-Kymmer, Ulrika, McCarthy, Shane, Eriksson, Joel, Kwan, Tony, Jhamai, Mila, Trajanoska, Katerina, Memari, Yasin, Min, Josine, Huang, Jie, Danecek, Petr, Wilmot, Beth, Li, Rui, Chou, Wen-Chi, Mokry, Lauren E., Moayyeri, Alireza, Claussnitzer, Melina, Cheng, Chia-Ho, Cheung, Warren, Medina-Gómez, Carolina, Ge, Bing, Chen, Shu-Huang, Choi, Kwangbom, Oei, Ling, Fraser, James, Kraaij, Robert, Hibbs, Matthew A., Gregson, Celia L., Paquette, Denis, Hofman, Albert, Wibom, Carl, Tranah, Gregory J., Marshall, Mhairi, Gardiner, Brooke B., Cremin, Katie, Auer, Paul, Hsu, Li, Ring, Sue, Tung, Joyce Y., Thorleifsson, Gudmar, Enneman, Anke W., van Schoor, Natasja M., de Groot, Lisette C. P. G. M., van der Velde, Nathalie, Melin, Beatrice, Kemp, John P., Christiansen, Claus, Sayers, Adrian, Zhou, Yanhua, Calderari, Sophie, van Rooij, Jeroen, Carlson, Chris, Peters, Ulrike, Berlivet, Soizik, Dostie, Josée, Uitterlinden, Andre G., Williams, Stephen R., Farber, Charles, Grinberg, Daniel, LaCroix, Andrea Z., Haessler, Jeff, Chasman, Daniel I., Giulianini, Franco, Rose, Lynda M., Ridker, Paul M., Eisman, John A., Nguyen, Tuan V., Center, Jacqueline R., Nogues, Xavier, Garcia-Giralt, Natalia, Launer, Lenore L., Gudnason, Vilmunder, Mellström, Dan, Vandenput, Liesbeth, Amin, Najaf, van Duijn, Cornelia M., Karlsson, Magnus K., Ljunggren, Östen, Svensson, Olle, Hallmans, Göran, Rousseau, François, Giroux, Sylvie, Bussière, Johanne, Arp, Pascal P., Koromani, Fjorda, Prince, Richard L., Lewis, Joshua R., Langdahl, Bente L., Hermann, Pernille A., Jensen, Jens-Erik B., Kaptoge, Stephen, Khaw, Kay-Tee, Reeve, Jonathan, Formosa, Melissa M., Xuereb-Anastasi, Angela, Åkesson, Kristina, McGuigan, Fiona E., Garg, Gaurav, Olmos, Jose M., Zarrabeitia, Maria T., Riancho, Jose A., Ralston, Stuart H., Alonso, Nerea, Jiang, Xi, Goltzman, David, Pastinen, Tomi, Grundberg, Elin, Gauguier, Dominique, Orwoll, Eric S., Karasik, David, Davey-Smith, George, Smith, Albert V., Siggeirsdottir, Kristin, Harris, Tamara B., Zillikens, Carola M., van Meurs, Joyce B. J., Thorsteinsdottir, Unnur, Maurano, Matthew T., Timpson, Nicholas J., Soranzo, Nicole, Durbin, Richard, Wilson, Scott G., Ntzani, Evangelia E., Brown, Matthew A., Stefansson, Kari, Hinds, David A., Spector, Tim, Cupples, Adrienne L., Ohlsson, Claes, Greenwood, Celia M. T., Jackson, Rebecca D., Rowe, David W., Loomis, Cynthia A., Evans, David M., Ackert-Bicknell, Cheryl L., Joyner, Alexandra L., Duncan, Emma L., Kiel, Douglas P., Rivadeneira, Fernando, and Richards, Brent J.

Published
2015
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67. Association of Cardiometabolic Multimorbidity With Mortality

Author

Di Angelantonio, Emanuele, Kaptoge, Stephen, Wormser, David, Willeit, Peter, Butterworth, Adam S., Bansal, Narinder, O’Keeffe, Linda M., Gao, Pei, Wood, Angela M., Burgess, Stephen, Freitag, Daniel F., Pennells, Lisa, Peters, Sanne A., Hart, Carole L., Håheim, Lise Lund, Gillum, Richard F., Nordestgaard, Børge G., Psaty, Bruce M., Yeap, Bu B., Knuiman, Matthew W., Nietert, Paul J., Kauhanen, Jussi, Salonen, Jukka T., Kuller, Lewis H., Simons, Leon A., van der Schouw, Yvonne T., Barrett-Connor, Elizabeth, Selmer, Randi, Crespo, Carlos J., Rodriguez, Beatriz, Verschuren, W. M. Monique, Salomaa, Veikko, Svärdsudd, Kurt, van der Harst, Pim, Björkelund, Cecilia, Wilhelmsen, Lars, Wallace, Robert B., Brenner, Hermann, Amouyel, Philippe, Barr, Elizabeth L. M., Iso, Hiroyasu, Onat, Altan, Trevisan, Maurizio, D’Agostino, Ralph B., Sr, Cooper, Cyrus, Kavousi, Maryam, Welin, Lennart, Roussel, Ronan, Hu, Frank B., Sato, Shinichi, Davidson, Karina W., Howard, Barbara V., Leening, Maarten, Rosengren, Annika, Dörr, Marcus, Deeg, Dorly J. H., Kiechl, Stefan, Stehouwer, Coen D. A., Nissinen, Aulikki, Giampaoli, Simona, Donfrancesco, Chiara, Kromhout, Daan, Price, Jackie F., Peters, Annette, Meade, Tom W., Casiglia, Edoardo, Lawlor, Debbie A., Gallacher, John, Nagel, Dorothea, Franco, Oscar H., Assmann, Gerd, Dagenais, Gilles R., Jukema, J. Wouter, Sundström, Johan, Woodward, Mark, Brunner, Eric J., Khaw, Kay-Tee, Wareham, Nicholas J., Whitsel, Eric A., Njølstad, Inger, Hedblad, Bo, Wassertheil-Smoller, Sylvia, Engström, Gunnar, Rosamond, Wayne D., Selvin, Elizabeth, Sattar, Naveed, Thompson, Simon G., and Danesh, John

Published
2015
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68. Telomere Length and Risk of Incident Fracture and Arthroplasty: Findings From UK Biobank.

Author

Curtis, Elizabeth M., Codd, Veryan, Nelson, Christopher, D'Angelo, Stefania, Wang, Qingning, Allara, Elias, Kaptoge, Stephen, Matthews, Paul M., Tobias, Jonathan H., Danesh, John, Cooper, Cyrus, Samani, Nilesh J., and Harvey, Nicholas C.

Abstract

We investigated independent associations between telomere length and risk of fracture and arthroplasty in UK Biobank participants. Leukocyte telomere length (LTL) was measured in baseline samples using a validated polymerase chain reaction (PCR) method. We used, in men and women separately, Cox proportional hazards models to calculate the hazard ratio (HR) for incident fracture (any, osteoporotic) or arthroplasty (hip or knee) over 1,186,410 person‐years of follow‐up. Covariates included age, white cell count, ethnicity, smoking, alcohol, physical activity, and menopause (women). In further analyses we adjusted for either estimated bone mineral density (eBMD) from heel quantitative ultrasound, handgrip strength, gait speed, total fat mass (bioimpedance), or blood biomarkers, all measured at baseline (2006–2010). We studied 59,500 women and 51,895 men, mean ± standard deviation (SD) age 56.4 ± 8.0 and 57.0 ± 8.3 years, respectively. During follow‐up there were 5619 fractures; 5285 hip and 4261 knee arthroplasties. In confounder‐adjusted models, longer LTL was associated with reduced risk of incident knee arthroplasty in both men (HR/SD 0.93; 95% confidence interval [CI], 0.88–0.97) and women (0.92; 95% CI, 0.88–0.96), and hip arthroplasty in men (0.91; 95% CI, 0.87–0.95), but not women (0.98; 95% CI, 0.94–1.01). Longer LTL was weakly associated with reduced risk of any incident fracture in women (HR/SD 0.96; 95% CI, 0.93–1.00) with less evidence in men (0.98; 95% CI, 0.93–1.02). Associations with incident outcomes were not materially altered by adjustment for heel eBMD, grip strength, gait speed, fat mass, or blood biomarker measures. In this, the largest study to date, longer LTL was associated with lower risk of incident knee or hip arthroplasty, but only weakly associated with lower risk of fracture. The relative risks were low at a population level, but our findings suggest that common factors acting on the myeloid and musculoskeletal systems might influence later life musculoskeletal outcomes. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR). [ABSTRACT FROM AUTHOR]

Published
2022
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69. Adult height and the risk of cause-specific death and vascular morbidity in 1 million people: individual participant meta-analysis

Author

Wormser, David, Angelantonio, Emanuele Di, Kaptoge, Stephen, Wood, Angela M, Gao, Pei, Sun, Qi, Walldius, Göran, Selmer, Randi, Verschuren, WM Monique, Bueno-de-Mesquita, H Bas, Engström, Gunnar, Ridker, Paul M, Njølstad, Inger, Iso, Hiroyasu, Holme, Ingar, Giampaoli, Simona, Tunstall-Pedoe, Hugh, Gaziano, J Michael, Brunner, Eric, Kee, Frank, Tosetto, Alberto, Meisinger, Christa, Brenner, Hermann, Ducimetiere, Pierre, Whincup, Peter H, Tipping, Robert W, Ford, Ian, Cremer, Peter, Hofman, Albert, Wilhelmsen, Lars, Clarke, Robert, Boer, Ian H de, Jukema, J Wouter, Ibañez, Alejandro Marín, Lawlor, Debbie A, DʼAgostino, Ralph B, Rodriguez, Beatriz, Casiglia, Edoardo, Stehouwer, Coen DA, Simons, Leon A, Nietert, Paul J, Barrett-Connor, Elizabeth, Panagiotakos, Demosthenes B, Björkelund, Cecilia, Strandberg, Timo E, Wassertheil-Smoller, Sylvia, Blazer, Dan G, Meade, Tom W, Welin, Lennart, Svärdsudd, Kurt, Woodward, Mark, Nissinen, Aulikki, Kromhout, Daan, Jørgensen, Torben, Tilvis, Reijo S, Guralnik, Jack M, Rosengren, Annika, Taylor, James O, Kiechl, Stefan, Dagenais, Gilles R, Gerry, F, Fowkes, R, Wallace, Robert B, Khaw, Kay-Tee, Shaffer, Jonathan A, Visser, Marjolein, Kauhanen, Jussi, Salonen, Jukka T, Gallacher, John, Ben-Shlomo, Yoav, Kitamura, Akihiko, Sundström, Johan, Wennberg, Patrik, Kiyohara, Yutaka, Daimon, Makoto, de la Cámara, Agustin Gómez, Cooper, Jackie A, Onat, Altan, Devereux, Richard, Mukamal, Kenneth J, Dankner, Rachel, Knuiman, Matthew W, Crespo, Carlos J, Gansevoort, Ron T, Goldbourt, Uri, Nordestgaard, Børge G, Shaw, Jonathan E, Mussolino, Michael, Nakagawa, Hidaeki, Fletcher, Astrid, Kuller, Lewis H, Gillum, Richard F, Gudnason, Vilmundur, Assmann, Gerd, Wald, Nicholas, Jousilahti, Pekka R, Greenland, Philip, Trevisan, Maurizio, Ulmer, Hanno, Butterworth, Adam S, Folsom, Aaron R, Davey-Smith, George, Hu, Frank B, Danesh, John, Tipping, Robert W, Ford, Charles E, Simpson, Lara M, Walldius, Göran, Jungner, Ingmar, Folsom, Aaron R, Demerath, Ellen W, Franceschini, Nora, Lutsey, Pamela L, Panagiotakos, Demosthenes B, Pitsavos, Christos, Chrysohoou, Christina, Stefanadis, Christodoulos, Shaw, Jonathan E, Atkins, Robert, Zimmet, Paul Z, Barr, Elizabeth LM, Knuiman, Matthew W, Whincup, Peter H, Wannamethee, S Goya, Morris, Richard W, Willeit, Johann, Kiechl, Stefan, Weger, Siegfried, Oberhollenzer, Friedrich, Wald, Nicholas, Ebrahim, Shah, Lawlor, Debbie A, Gallacher, John, Ben-Shlomo, Yoav, Yarnell, John WG, Casiglia, Edoardo, Tikhonoff, Valérie, Greenland, Philip, Shay, Christina M, Garside, Daniel B, Nietert, Paul J, Sutherland, Susan E, Bachman, David L, Keil, Julian E, de Boer, Ian H, Kizer, Jorge R, Psaty, Bruce M, Mukamal, Kenneth J, Nordestgaard, Børge G, Tybjærg-Hansen, Anne, Jensen, Gorm B, Schnohr, Peter, Giampaoli, Simona, Palmieri, Luigi, Panico, Salvatore, Pilotto, Lorenza, Vanuzzo, Diego, de la Cámara, Agustin Gómez, Simons, Leon A, Simons, Judith, McCallum, John, Friedlander, Yechiel, Gerry, F, Fowkes, R, Price, Jackie F, Lee, Amanda J, Taylor, James O, Guralnik, Jack M, Phillips, Caroline L, Wallace, Robert B, Kohout, Frank J, Cornoni-Huntley, Joan C, Guralnik, Jack M, Blazer, Dan G, Guralnik, Jack M, Phillips, Caroline L, Phillips, Caroline L, Guralnik, Jack M, Khaw, Kay-Tee, Wareham, Nicholas J, Brenner, Hermann, Schöttker, Ben, Müller, Heiko, Rothenbacher, Dietrich, Wennberg, Patrik, Jansson, Jan-Håkan, Nissinen, Aulikki, Donfrancesco, Chiara, Giampaoli, Simona, Woodward, Mark, Vartiainen, Erkki, Jousilahti, Pekka R, Harald, Kennet, Salomaa, Veikko, DʼAgostino, Ralph B, Vasan, Ramachandran S, Fox, Caroline S, Pencina, Michael J, Daimon, Makoto, Oizumi, Toshihide, Kayama, Takamasa, Kato, Takeo, Bladbjerg, Else-Marie, Jørgensen, Torben, Møller, Lars, Jespersen, Jørgen, Dankner, Rachel, Chetrit, Angela, Lubin, Flora, Svärdsudd, Kurt, Eriksson, Henry, Welin, Lennart, Lappas, Georgios, Rosengren, Annika, Lappas, Georgios, Welin, Lennart, Svärdsudd, Kurt, Eriksson, Henry, Lappas, Georgios, Bengtsson, Calle, Lissner, Lauren, Björkelund, Cecilia, Cremer, Peter, Nagel, Dorothea, Strandberg, Timo E, Salomaa, Veikko, Tilvis, Reijo S, Miettinen, Tatu A, Tilvis, Reijo S, Strandberg, Timo E, Kiyohara, Yutaka, Arima, Hisatomi, Doi, Yasufumi, Ninomiya, Toshiharu, Rodriguez, Beatriz, Dekker, Jacqueline M, Nijpels, Giel, Stehouwer, Coen DA, Hu, Frank B, Sun, Qi, Rimm, Eric B, Willett, Walter C, Iso, Hiroyasu, Kitamura, Akihiko, Yamagishi, Kazumasa, Noda, Hiroyuki, Goldbourt, Uri, Vartiainen, Erkki, Jousilahti, Pekka R, Harald, Kennet, Salomaa, Veikko, Kauhanen, Jussi, Salonen, Jukka T, Kurl, Sudhir, Tuomainen, Tomi-Pekka, Poppelaars, Jan L, Deeg, Dorly JH, Visser, Marjolein, Meade, Tom W, De Stavola, Bianca Lucia, Hedblad, Bo, Nilsson, Peter, Engström, Gunnar, Verschuren, WM Monique, Blokstra, Anneke, de Boer, Ian H, Shea, Steven J, Meisinger, Christa, Thorand, Barbara, Koenig, Wolfgang, Döring, Angela, Verschuren, WM Monique, Blokstra, Anneke, Bueno-de-Mesquita, H Bas, Wilhelmsen, Lars, Rosengren, Annika, Lappas, Georgios, Fletcher, Astrid, Nitsch, Dorothea, Kuller, Lewis H, Grandits, Greg, Tverdal, Aage, Selmer, Randi, Nystad, Wenche, Mussolino, Michael, Gillum, Richard F, Hu, Frank B, Sun, Qi, Manson, JoAnn E, Rimm, Eric B, Hankinson, Susan E, Meade, Tom W, De Stavola, Bianca Lucia, Cooper, Jackie A, Bauer, Kenneth A, Davidson, Karina W, Kirkland, Susan, Shaffer, Jonathan A, Shimbo, Daichi, Kitamura, Akihiko, Iso, Hiroyasu, Sato, Shinichi, Holme, Ingar, Selmer, Randi, Tverdal, Aage, Nystad, Wenche, Nakagawa, Hidaeki, Miura, Katsuyuki, Sakurai, Masaru, Ducimetiere, Pierre, Jouven, Xavier, Bakker, Stephan JL, Gansevoort, Ron T, van der Harst, Pim, Hillege, Hans L, Crespo, Carlos J, Garcia-Palmieri, Mario R, Kee, Frank, Amouyel, Philippe, Arveiler, Dominique, Ferrières, Jean, Schulte, Helmut, Assmann, Gerd, Jukema, J Wouter, de Craen, Anton JM, Sattar, Naveed, Stott, David J, Cantin, Bernard, Lamarche, Benoît, Després, Jean-Pierre, Dagenais, Gilles R, Barrett-Connor, Elizabeth, Bergstrom, Jaclyn, Bettencourt, Richele R, Buisson, Catherine, Gudnason, Vilmundur, Aspelund, Thor, Sigurdsson, Gunnar, Thorsson, Bolli, Trevisan, Maurizio, Hofman, Albert, Ikram, M Arfan, Tiemeier, Henning, Witteman, Jacqueline CM, Tunstall-Pedoe, Hugh, Tavendale, Roger, Lowe, Gordon DO, Woodward, Mark, Devereux, Richard, Yeh, Jeun-Liang, Ali, Tauqeer, Calhoun, Darren, Ben-Shlomo, Yoav, Davey-Smith, George, Onat, Altan, Can, Günay, Nakagawa, Hidaeki, Sakurai, Masaru, Nakamura, Koshi, Morikawa, Yuko, Njølstad, Inger, Mathiesen, Ellisiv B, Løchen, Maja-Lisa, Wilsgaard, Tom, Sundström, Johan, Ingelsson, Erik, Michaëlsson, Karl, Cederholm, Tommy, Gaziano, J Michael, Buring, Julie, Ridker, Paul M, Gaziano, J Michael, Ridker, Paul M, Ulmer, Hanno, Diem, Günter, Concin, Hans, Rodeghiero, Francesco, Tosetto, Alberto, Wassertheil-Smoller, Sylvia, Manson, JoAnn E, Marmot, Michael, Clarke, Robert, Fletcher, Astrid, Brunner, Eric, Shipley, Martin, Kivimaki, Mika, Ridker, Paul M, Buring, Julie, Ford, Ian, Robertson, Michele, Ibañez, Alejandro Marín, Feskens, Edith, Geleijnse, Johanna M, Kromhout, Daan, Walker, Matthew, Watson, Sarah, Alexander, Myriam, Butterworth, Adam S, Angelantonio, Emanuele Di, Franco, Oscar H, Gao, Pei, Gobin, Reeta, Haycock, Philip, Kaptoge, Stephen, Seshasai, Sreenivasa R Kondapally, Lewington, Sarah, Pennells, Lisa, Rapsomaniki, Eleni, Sarwar, Nadeem, Thompson, Alexander, Thompson, Simon G, Walker, Matthew, Watson, Sarah, White, Ian R, Wood, Angela M, Wormser, David, Zhao, Xiaohui, and Danesh, John

Published
2012
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70. Shorter leukocyte telomere length is associated with adverse COVID-19 outcomes: A cohort study in UK Biobank

Author

Wang, Qingning, primary, Codd, Veryan, additional, Raisi-Estabragh, Zahra, additional, Musicha, Crispin, additional, Bountziouka, Vasiliki, additional, Kaptoge, Stephen, additional, Allara, Elias, additional, Di Angelantonio, Emanuele, additional, Butterworth, Adam S., additional, Wood, Angela M., additional, Thompson, John R., additional, Petersen, Steffen E, additional, Harvey, Nicholas C., additional, Danesh, John N., additional, Samani, Nilesh J., additional, and Nelson, Christopher P., additional

Published
2021
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71. Association of leucocyte telomere length with frailty: a large–scale cross–sectional analysis in UK Biobank

Author

Bountziouka, Vasiliki, primary, Nelson, Christopher P, additional, Codd, Veryan, additional, Wang, Qingning, additional, Musicha, Crispin, additional, Allara, Elias, additional, Kaptoge, Stephen, additional, Angelantonio, Emanuele Di, additional, Butterworth, Adam S, additional, Thompson, John R, additional, Curtis, Elizabeth M, additional, Wood, Angela M, additional, Danesh, John N, additional, Harvey, Nicholas C, additional, Cooper, Cyrus, additional, and Samani, Nilesh J, additional

Published
2021
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72. Accuracy of four lateral flow immunoassays for anti SARS-CoV-2 antibodies: a head-to-head comparative study

Author

Jones, Hayley E, primary, Mulchandani, Ranya, additional, Taylor-Phillips, Sian, additional, Ades, A E, additional, Shute, Justin, additional, Perry, Keith R, additional, Chandra, Nastassya L, additional, Brooks, Tim, additional, Charlett, Andre, additional, Hickman, Matthew, additional, Oliver, Isabel, additional, Kaptoge, Stephen, additional, Danesh, John, additional, Di Angelantonio, Emanuele, additional, and Wyllie, David, additional

Published
2021
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73. A genome-wide meta-analysis yields 46 new loci associating with biomarkers of iron homeostasis

Author

Bell, Steven, Rigas, Andreas S., Magnusson, Magnus K., Ferkingstad, Egil, Allara, Elias, Bjornsdottir, Gyda, Ramond, Anna, Sørensen, Erik, Halldorsson, Gisli H., Paul, Dirk S., Burgdorf, Kristoffer S., Eggertsson, Hannes P., Howson, Joanna M. M., Thørner, Lise W., Kristmundsdottir, Snaedis, Astle, William J., Erikstrup, Christian, Sigurdsson, Jon K., Vuckovic, Dragana, Dinh, Khoa M., Tragante, Vinicius, Surendran, Praveen, Pedersen, Ole B., Vidarsson, Brynjar, Jiang, Tao, Paarup, Helene M., Onundarson, Pall T., Akbari, Parsa, Nielsen, Kaspar R., Lund, Sigrun H., Juliusson, Kristinn, Magnusson, Magnus I., Frigge, Michael L., Oddsson, Asmundur, Olafsson, Isleifur, Kaptoge, Stephen, Hjalgrim, Henrik, Runarsson, Gudmundur, Wood, Angela M., Jonsdottir, Ingileif, Hansen, Thomas F., Sigurdardottir, Olof, Stefansson, Hreinn, Rye, David, Peters, James E., Westergaard, David, Holm, Hilma, Soranzo, Nicole, Banasik, Karina, Thorleifsson, Gudmar, Ouwehand, Willem H., Thorsteinsdottir, Unnur, Roberts, David J., Sulem, Patrick, Butterworth, Adam S., Gudbjartsson, Daniel F., Danesh, John, Brunak, Søren, Di Angelantonio, Emanuele, Ullum, Henrik, Stefansson, Kari, Andersen, Steffen, Burgdorf, Kristoffer, Jemec, Gregor, Jennum, Poul, Johansson, Pär, Nielsen, Kasper R., Nyegaard, Mette, Petersen, Mikkel, Werge, Thomas, Stefánsson, Hreinn, Thorsteinsdóttir, Unnur, Bell, Steven [0000-0001-6774-3149], Magnusson, Magnus K. [0000-0001-8593-4934], Ferkingstad, Egil [0000-0001-8090-7988], Allara, Elias [0000-0002-1634-8330], Halldorsson, Gisli H. [0000-0001-7067-9862], Paul, Dirk S. [0000-0002-8230-0116], Eggertsson, Hannes P. [0000-0002-1674-9978], Howson, Joanna M. M. [0000-0001-7618-0050], Erikstrup, Christian [0000-0001-6551-6647], Tragante, Vinicius [0000-0002-8223-8957], Pedersen, Ole B. [0000-0003-2312-5976], Paarup, Helene M. [0000-0003-1281-1567], Akbari, Parsa [0000-0001-9210-4760], Lund, Sigrun H. [0000-0002-3806-2296], Frigge, Michael L. [0000-0003-2984-535X], Oddsson, Asmundur [0000-0002-4606-5163], Jonsdottir, Ingileif [0000-0001-8339-150X], Hansen, Thomas F. [0000-0001-6703-7762], Stefansson, Hreinn [0000-0002-9331-6666], Westergaard, David [0000-0003-0128-8432], Holm, Hilma [0000-0002-9517-6636], Soranzo, Nicole [0000-0003-1095-3852], Banasik, Karina [0000-0003-2489-2499], Ouwehand, Willem H. [0000-0002-7744-1790], Sulem, Patrick [0000-0001-7123-6123], Butterworth, Adam S. [0000-0002-6915-9015], Gudbjartsson, Daniel F. [0000-0002-5222-9857], Brunak, Søren [0000-0003-0316-5866], Stefansson, Kari [0000-0003-1676-864X], and Apollo - University of Cambridge Repository

Subjects
45, 631/208/457/649, 692/308/2056, 45/43, article
Abstract

Iron is essential for many biological functions and iron deficiency and overload have major health implications. We performed a meta-analysis of three genome-wide association studies from Iceland, the UK and Denmark of blood levels of ferritin (N = 246,139), total iron binding capacity (N = 135,430), iron (N = 163,511) and transferrin saturation (N = 131,471). We found 62 independent sequence variants associating with iron homeostasis parameters at 56 loci, including 46 novel loci. Variants at DUOX2, F5, SLC11A2 and TMPRSS6 associate with iron deficiency anemia, while variants at TF, HFE, TFR2 and TMPRSS6 associate with iron overload. A HBS1L-MYB intergenic region variant associates both with increased risk of iron overload and reduced risk of iron deficiency anemia. The DUOX2 missense variant is present in 14% of the population, associates with all iron homeostasis biomarkers, and increases the risk of iron deficiency anemia by 29%. The associations implicate proteins contributing to the main physiological processes involved in iron homeostasis: iron sensing and storage, inflammation, absorption of iron from the gut, iron recycling, erythropoiesis and bleeding/menstruation.

Published
2021
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74. Comparison of four methods to measure haemoglobin concentrations in whole blood donors (COMPARE): A diagnostic accuracy study

Author

Bell, Steven, Sweeting, Michael, Ramond, Anna, Chung, Ryan, Kaptoge, Stephen, Walker, Matthew, Bolton, Thomas, Sambrook, Jennifer, Moore, Carmel, McMahon, Amy, Fahle, Sarah, Cullen, Donna, Mehenny, Susan, Wood, Angela M, Armitage, Jane, Ouwehand, Willem H, Miflin, Gail, Roberts, David J, Danesh, John, Di Angelantonio, Emanuele, COMPARE Study Group, Bell, Steven [0000-0001-6774-3149], Sweeting, Michael [0000-0003-0980-8965], Ramond, Anna [0000-0002-9958-3693], Fahle, Sarah [0000-0002-4359-9952], Wood, Angela M [0000-0002-7937-304X], Armitage, Jane [0000-0001-8691-9226], Ouwehand, Willem H [0000-0002-7744-1790], Di Angelantonio, Emanuele [0000-0001-8776-6719], and Apollo - University of Cambridge Repository

Subjects
Adult, Male, Adolescent, haemoglobin screening, Blood Donors, gravimetry, inappropriate bleeding, Sensitivity and Specificity, Donor Selection, Hemoglobins, Young Adult, HemoCue, Humans, non-invasive haemoglobin measurement, Aged, Aged, 80 and over, inappropriate deferral, Cross-Over Studies, Anemia, Middle Aged, Reference Standards, Spectrophotometry, whole blood donor, Hemoglobinometry, Female, Biomarkers
Abstract

OBJECTIVE: To compare four haemoglobin measurement methods in whole blood donors. BACKGROUND: To safeguard donors, blood services measure haemoglobin concentration in advance of each donation. NHS Blood and Transplant's (NHSBT) customary method have been capillary gravimetry (copper sulphate), followed by venous spectrophotometry (HemoCue) for donors failing gravimetry. However, NHSBT's customary method results in 10% of donors being inappropriately bled (ie, with haemoglobin values below the regulatory threshold). METHODS: We compared the following four methods in 21 840 blood donors (aged ≥18 years) recruited from 10 NHSBT centres in England, with the Sysmex XN-2000 haematology analyser, the reference standard: (1) NHSBT's customary method; (2) "post donation" approach, that is, estimating current haemoglobin concentration from that measured by a haematology analyser at a donor's most recent prior donation; (3) "portable haemoglobinometry" (using capillary HemoCue); (4) non-invasive spectrometry (using MBR Haemospect or Orsense NMB200). We assessed sensitivity; specificity; proportion who would have been inappropriately bled, or rejected from donation ("deferred") incorrectly; and test preference. RESULTS: Compared with the reference standard, the methods ranged in test sensitivity from 17.0% (MBR Haemospect) to 79.0% (portable haemoglobinometry) in men, and from 19.0% (MBR Haemospect) to 82.8% (portable haemoglobinometry) in women. For specificity, the methods ranged from 87.2% (MBR Haemospect) to 99.9% (NHSBT's customary method) in men, and from 74.1% (Orsense NMB200) to 99.8% (NHSBT's customary method) in women. The proportion of donors who would have been inappropriately bled ranged from 2.2% in men for portable haemoglobinometry to 18.9% in women for MBR Haemospect. The proportion of donors who would have been deferred incorrectly with haemoglobin concentration above the minimum threshold ranged from 0.1% in men for NHSBT's customary method to 20.3% in women for OrSense. Most donors preferred non-invasive spectrometry. CONCLUSION: In the largest study reporting head-to-head comparisons of four methods to measure haemoglobin prior to blood donation, our results support replacement of NHSBT's customary method with portable haemoglobinometry.

Published
2021
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76. Estimating dose-response relationships for vitamin D with coronary heart disease, stroke, and all-cause mortality: observational and Mendelian randomisation analyses

Author

Sofianopoulou, Eleni, Kaptoge, Stephen K, Afzal, Shoaib, Jiang, Tao, Gill, Dipender, Gundersen, Thomas E, Bolton, Thomas R, Allara, Elias, Arnold, Matthew G, Mason, Amy M, Chung, Ryan, Pennells, Lisa A M, Shi, Fanchao, Sun, Luanluan, Willeit, Peter, Forouhi, Nita G, Langenberg, Claudia, Sharp, Stephen J, Panico, Salvatore, Engström, Gunnar, Melander, Olle, Tong, Tammy Y N, Perez-Cornago, Aurora, Norberg, Margareta, Johansson, Ingegerd, Katzke, Verena, Srour, Bernard, José Sánchez, María, Redondo-Sánchez, Daniel, Olsen, Anja, Dahm, Christina C, Overvad, Kim, Brustad, Magritt, Skeie, Guri, Moreno-Iribas, Conchi, Onland-Moret, N Charlotte, van der Schouw, Yvonne T, Tsilidis, Konstantinos K, Heath, Alicia K, Agnoli, Claudia, Krogh, Vittorio, de Boer, Ian H, Kobylecki, Camilla Jannie, Çolak, Yunus, Zittermann, Armin, Sundström, Johan, Welsh, Paul, Weiderpass, Elisabete, Aglago, Elom K, Ferrari, Pietro, Sofianopoulou, Eleni, Kaptoge, Stephen K, Afzal, Shoaib, Jiang, Tao, Gill, Dipender, Gundersen, Thomas E, Bolton, Thomas R, Allara, Elias, Arnold, Matthew G, Mason, Amy M, Chung, Ryan, Pennells, Lisa A M, Shi, Fanchao, Sun, Luanluan, Willeit, Peter, Forouhi, Nita G, Langenberg, Claudia, Sharp, Stephen J, Panico, Salvatore, Engström, Gunnar, Melander, Olle, Tong, Tammy Y N, Perez-Cornago, Aurora, Norberg, Margareta, Johansson, Ingegerd, Katzke, Verena, Srour, Bernard, José Sánchez, María, Redondo-Sánchez, Daniel, Olsen, Anja, Dahm, Christina C, Overvad, Kim, Brustad, Magritt, Skeie, Guri, Moreno-Iribas, Conchi, Onland-Moret, N Charlotte, van der Schouw, Yvonne T, Tsilidis, Konstantinos K, Heath, Alicia K, Agnoli, Claudia, Krogh, Vittorio, de Boer, Ian H, Kobylecki, Camilla Jannie, Çolak, Yunus, Zittermann, Armin, Sundström, Johan, Welsh, Paul, Weiderpass, Elisabete, Aglago, Elom K, and Ferrari, Pietro

Published
2021
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77. Estimating dose-response relationships for vitamin D with coronary heart disease, stroke, and all-cause mortality:observational and Mendelian randomisation analyses

Author

Sofianopoulou, Eleni, Kaptoge, Stephen K., Afzal, Shoaib, Jiang, Tao, Gill, Dipender, Gundersen, Thomas E., Bolton, Thomas R., Allara, Elias, Arnold, Matthew G., Mason, Amy M., Chung, Ryan, Pennells, Lisa A.M., Shi, Fanchao, Sun, Luanluan, Willeit, Peter, Forouhi, Nita G., Langenberg, Claudia, Sharp, Stephen J., Panico, Salvatore, Engström, Gunnar, Melander, Olle, Tong, Tammy Y.N., Perez-Cornago, Aurora, Norberg, Margareta, Johansson, Ingegerd, Katzke, Verena, Srour, Bernard, José Sánchez, María, Redondo-Sánchez, Daniel, Olsen, Anja, Dahm, Christina C., Overvad, Kim, Brustad, Magritt, Skeie, Guri, Moreno-Iribas, Conchi, Onland-Moret, N. Charlotte, van der Schouw, Yvonne T., Tsilidis, Konstantinos K., Heath, Alicia K., Agnoli, Claudia, Krogh, Vittorio, de Boer, Ian H., Kobylecki, Camilla Jannie, Çolak, Yunus, Zittermann, Armin, Sundström, Johan, Welsh, Paul, Schierbeck, Louise L., Linneberg, Allan, Nordestgaard, Børge G., Sofianopoulou, Eleni, Kaptoge, Stephen K., Afzal, Shoaib, Jiang, Tao, Gill, Dipender, Gundersen, Thomas E., Bolton, Thomas R., Allara, Elias, Arnold, Matthew G., Mason, Amy M., Chung, Ryan, Pennells, Lisa A.M., Shi, Fanchao, Sun, Luanluan, Willeit, Peter, Forouhi, Nita G., Langenberg, Claudia, Sharp, Stephen J., Panico, Salvatore, Engström, Gunnar, Melander, Olle, Tong, Tammy Y.N., Perez-Cornago, Aurora, Norberg, Margareta, Johansson, Ingegerd, Katzke, Verena, Srour, Bernard, José Sánchez, María, Redondo-Sánchez, Daniel, Olsen, Anja, Dahm, Christina C., Overvad, Kim, Brustad, Magritt, Skeie, Guri, Moreno-Iribas, Conchi, Onland-Moret, N. Charlotte, van der Schouw, Yvonne T., Tsilidis, Konstantinos K., Heath, Alicia K., Agnoli, Claudia, Krogh, Vittorio, de Boer, Ian H., Kobylecki, Camilla Jannie, Çolak, Yunus, Zittermann, Armin, Sundström, Johan, Welsh, Paul, Schierbeck, Louise L., Linneberg, Allan, and Nordestgaard, Børge G.

Abstract

Background: Randomised trials of vitamin D supplementation for cardiovascular disease and all-cause mortality have generally reported null findings. However, generalisability of results to individuals with low vitamin D status is unclear. We aimed to characterise dose-response relationships between 25-hydroxyvitamin D (25[OH]D) concentrations and risk of coronary heart disease, stroke, and all-cause mortality in observational and Mendelian randomisation frameworks. Methods: Observational analyses were undertaken using data from 33 prospective studies comprising 500 962 individuals with no known history of coronary heart disease or stroke at baseline. Mendelian randomisation analyses were performed in four population-based cohort studies (UK Biobank, EPIC-CVD, and two Copenhagen population-based studies) comprising 386 406 middle-aged individuals of European ancestries, including 33 546 people who developed coronary heart disease, 18 166 people who had a stroke, and 27 885 people who died. Primary outcomes were coronary heart disease, defined as fatal ischaemic heart disease (International Classification of Diseases 10th revision code I20-I25) or non-fatal myocardial infarction (I21-I23); stroke, defined as any cerebrovascular disease (I60-I69); and all-cause mortality. Findings: Observational analyses suggested inverse associations between incident coronary heart disease, stroke, and all-cause mortality outcomes with 25(OH)D concentration at low 25(OH)D concentrations. In population-wide genetic analyses, there were no associations of genetically-predicted 25(OH)D with coronary heart disease, stroke, or all-cause mortality. However, for the participants with vitamin D deficiency (25[OH]D concentration <25 nmol/L), genetic analyses provided strong evidence for an inverse association with all-cause mortality (odds ratio [OR] per 10 nmol/L increase in genetically-predicted 25[OH]D concentration 0·69 [95% CI 0·59–0·80]; p<0·0001) and non-significant inverse ass

Published
2021

78. SCORE2 risk prediction algorithms:new models to estimate 10-year risk of cardiovascular disease in Europe

Author

Hageman, Steven, Pennells, Lisa, Ojeda, Francisco, Kaptoge, Stephen, Kuulasmaa, Kari, de Vries, Tamar, Xu, Zhe, Kee, Frank, Chung, Ryan, Wood, Angela, McEvoy, John William, Veronesi, Giovanni, Bolton, Thomas, Dendale, Paul, Ference, Brian A., Halle, Martin, Timmis, Adam, Vardas, Panos, Danesh, John, Graham, Ian, Salomaa, Veikko, Visseren, Frank, De Bacquer, Dirk, Blankenberg, Stefan, Dorresteijn, Jannick, Di Angelantonio, Emanuele, Achenbach, Stephan, Aleksandrova, Krasimira, Amiano, Pilar, Amouyel, Philippe, Andersson, Jonas, Bakker, Stephan J. L., Costa, Rui Bebiano Da Providencia, Beulens, Joline W. J., Blaha, Michael, Bobak, Martin, Boer, Jolanda M. A., Bonet, Catalina, Bonnet, Fabrice, Boutron-Ruault, Marie-Christine, Braaten, Tonje, Brenner, Hermann, Brunner, Fabian, Brunner, Eric J., Brunstrom, Mattias, Jørgensen, Torben, Linneberg, Allan, Overvad, Kim, Tjønneland, Anne, Tybjaerg-Hansen, Anne, Hageman, Steven, Pennells, Lisa, Ojeda, Francisco, Kaptoge, Stephen, Kuulasmaa, Kari, de Vries, Tamar, Xu, Zhe, Kee, Frank, Chung, Ryan, Wood, Angela, McEvoy, John William, Veronesi, Giovanni, Bolton, Thomas, Dendale, Paul, Ference, Brian A., Halle, Martin, Timmis, Adam, Vardas, Panos, Danesh, John, Graham, Ian, Salomaa, Veikko, Visseren, Frank, De Bacquer, Dirk, Blankenberg, Stefan, Dorresteijn, Jannick, Di Angelantonio, Emanuele, Achenbach, Stephan, Aleksandrova, Krasimira, Amiano, Pilar, Amouyel, Philippe, Andersson, Jonas, Bakker, Stephan J. L., Costa, Rui Bebiano Da Providencia, Beulens, Joline W. J., Blaha, Michael, Bobak, Martin, Boer, Jolanda M. A., Bonet, Catalina, Bonnet, Fabrice, Boutron-Ruault, Marie-Christine, Braaten, Tonje, Brenner, Hermann, Brunner, Fabian, Brunner, Eric J., Brunstrom, Mattias, Jørgensen, Torben, Linneberg, Allan, Overvad, Kim, Tjønneland, Anne, and Tybjaerg-Hansen, Anne

Abstract

Aims The aim of this study was to develop, validate, and illustrate an updated prediction model (SCORE2) to estimate 10-year fatal and non-fatal cardiovascular disease (CVD) risk in individuals without previous CVD or diabetes aged 40-69 years in Europe.Methods and results We derived risk prediction models using individual-participant data from 45 cohorts in 13 countries (677 684 individuals, 30 121 CVD events). We used sex-specific and competing risk-adjusted models, including age, smoking status, systolic blood pressure, and total- and HDL-cholesterol. We defined four risk regions in Europe according to country-specific CVD mortality, recalibrating models to each region using expected incidences and risk factor distributions. Region-specific incidence was estimated using CVD mortality and incidence data on 10 776 466 individuals. For external validation, we analysed data from 25 additional cohorts in 15 European countries (1 133 181 individuals, 43 492 CVD events). After applying the derived risk prediction models to external validation cohorts, C-indices ranged from 0.67 (0.65-0.68) to 0.81 (0.76-0.86). Predicted CVD risk varied several-fold across European regions. For example, the estimated 10-year CVD risk for a 50-year-old smoker, with a systolic blood pressure of 140 mmHg, total cholesterol of 5.5 mmol/L, and HDL-cholesterol of 1.3 mmol/L, ranged from 5.9% for men in low- risk countries to 14.0% for men in very high-risk countries, and from 4.2% for women in low-risk countries to 13.7% for women in very high-risk countries.Conclusion SCORE2-a new algorithm derived, calibrated, and validated to predict 10-year risk of first-onset CVD in European populations-enhances the identification of individuals at higher risk of developing CVD across Europe.

Published
2021

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

Author

Interne Geneeskunde Vasculaire, MS Interne Geneeskunde, Circulatory Health, MS Geriatrie, de Vries, Tamar, I, Cooney, Marie Therese, Selmer, Randi M., Hageman, Steven H. J., Pennells, Lisa A., Wood, Angela, Kaptoge, Stephen, Xu, Zhe, Westerink, Jan, Rabanal, Kjersti S., Tell, Grethe S., Meyer, Haakon E., Igland, Jannicke, Ariansen, Inger, Matsushita, Kunihiro, Blaha, Michael J., Nambi, Vijay, Peters, Ruth, Beckett, Nigel, Antikainen, Riitta, Bulpitt, Christopher J., Muller, Majon, Emmelot-Vonk, Marielle H., Trompet, Stella, Jukema, Wouter, Ference, Brian A., Halle, Martin, Timmis, Adam D., Vardas, Panos E., Dorresteijn, Jannick A. N., De Bacquer, Dirk, Di Angelantonio, Emanuele, Visseren, Frank L. J., Graham, Ian M., Interne Geneeskunde Vasculaire, MS Interne Geneeskunde, Circulatory Health, MS Geriatrie, de Vries, Tamar, I, Cooney, Marie Therese, Selmer, Randi M., Hageman, Steven H. J., Pennells, Lisa A., Wood, Angela, Kaptoge, Stephen, Xu, Zhe, Westerink, Jan, Rabanal, Kjersti S., Tell, Grethe S., Meyer, Haakon E., Igland, Jannicke, Ariansen, Inger, Matsushita, Kunihiro, Blaha, Michael J., Nambi, Vijay, Peters, Ruth, Beckett, Nigel, Antikainen, Riitta, Bulpitt, Christopher J., Muller, Majon, Emmelot-Vonk, Marielle H., Trompet, Stella, Jukema, Wouter, Ference, Brian A., Halle, Martin, Timmis, Adam D., Vardas, Panos E., Dorresteijn, Jannick A. N., De Bacquer, Dirk, Di Angelantonio, Emanuele, Visseren, Frank L. J., and Graham, Ian M.

Published
2021

81. Genetic determinants of heel bone properties: genome-wide association meta-analysis and replication in the GEFOS/GENOMOS consortium

Author

Moayyeri, Alireza, Hsu, Yi-Hsiang, Karasik, David, Estrada, Karol, Xiao, Su-Mei, Nielson, Carrie, Srikanth, Priya, Giroux, Sylvie, Wilson, Scott G., Zheng, Hou-Feng, Smith, Albert V., Pye, Stephen R., Leo, Paul J., Teumer, Alexander, Hwang, Joo-Yeon, Ohlsson, Claes, McGuigan, Fiona, Minster, Ryan L., Hayward, Caroline, Olmos, José M., Lyytikäinen, Leo-Pekka, Lewis, Joshua R., Swart, Karin M.A., Masi, Laura, Oldmeadow, Chris, Holliday, Elizabeth G., Cheng, Sulin, van Schoor, Natasja M., Harvey, Nicholas C., Kruk, Marcin, del Greco M, Fabiola, Igl, Wilmar, Trummer, Olivia, Grigoriou, Efi, Luben, Robert, Liu, Ching-Ti, Zhou, Yanhua, Oei, Ling, Medina-Gomez, Carolina, Zmuda, Joseph, Tranah, Greg, Brown, Suzanne J., Williams, Frances M., Soranzo, Nicole, Jakobsdottir, Johanna, Siggeirsdottir, Kristin, Holliday, Kate L., Hannemann, Anke, Go, Min Jin, Garcia, Melissa, Polasek, Ozren, Laaksonen, Marika, Zhu, Kun, Enneman, Anke W., McEvoy, Mark, Peel, Roseanne, Sham, Pak Chung, Jaworski, Maciej, Johansson, Åsa, Hicks, Andrew A., Pludowski, Pawel, Scott, Rodney, Dhonukshe-Rutten, Rosalie A.M., van der Velde, Nathalie, Kähönen, Mika, Viikari, Jorma S., Sievänen, Harri, Raitakari, Olli T., González-Macías, Jesús, Hernández, Jose L., Mellström, Dan, Ljunggren, Östen, Cho, Yoon Shin, Völker, Uwe, Nauck, Matthias, Homuth, Georg, Völzke, Henry, Haring, Robin, Brown, Matthew A., McCloskey, Eugene, Nicholson, Geoffrey C., Eastell, Richard, Eisman, John A., Jones, Graeme, Reid, Ian R., Dennison, Elaine M., Wark, John, Boonen, Steven, Vanderschueren, Dirk, Wu, Frederick C.W., Aspelund, Thor, Richards, Brent J., Bauer, Doug, Hofman, Albert, Khaw, Kay-Tee, Dedoussis, George, Obermayer-Pietsch, Barbara, Gyllensten, Ulf, Pramstaller, Peter P., Lorenc, Roman S., Cooper, Cyrus, Kung, Annie Wai Chee, Lips, Paul, Alen, Markku, Attia, John, Brandi, Maria Luisa, de Groot, Lisette C.P.G.M., Lehtimäki, Terho, Riancho, José A., Campbell, Harry, Liu, Yongmei, Harris, Tamara B., Akesson, Kristina, Karlsson, Magnus, Lee, Jong-Young, Wallaschofski, Henri, Duncan, Emma L., OʼNeill, Terence W., Gudnason, Vilmundur, Spector, Timothy D., Rousseau, François, Orwoll, Eric, Cummings, Steven R., Wareham, Nick J., Rivadeneira, Fernando, Uitterlinden, Andre G., Prince, Richard L., Kiel, Douglas P., Reeve, Jonathan, and Kaptoge, Stephen K.

Published
2014
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82. Glycated Hemoglobin Measurement and Prediction of Cardiovascular Disease

Author

Di Angelantonio, Emanuele, Gao, Pei, Khan, Hassan, Butterworth, Adam S., Wormser, David, Kaptoge, Stephen, Kondapally Seshasai, Sreenivasa Rao, Thompson, Alex, Sarwar, Nadeem, Willeit, Peter, Ridker, Paul M, Barr, Elizabeth L. M., Khaw, Kay-Tee, Psaty, Bruce M., Brenner, Hermann, Balkau, Beverley, Dekker, Jacqueline M., Lawlor, Debbie A., Daimon, Makoto, Willeit, Johann, Njølstad, Inger, Nissinen, Aulikki, Brunner, Eric J., Kuller, Lewis H., Price, Jackie F., Sundström, Johan, Knuiman, Matthew W., Feskens, Edith J. M., Verschuren, W. M. M., Wald, Nicholas, Bakker, Stephan J. L., Whincup, Peter H., Ford, Ian, Goldbourt, Uri, Gómez-de-la-Cámara, Agustín, Gallacher, John, Simons, Leon A., Rosengren, Annika, Sutherland, Susan E., Björkelund, Cecilia, Blazer, Dan G., Wassertheil-Smoller, Sylvia, Onat, Altan, Marín Ibañez, Alejandro, Casiglia, Edoardo, Jukema, Wouter J., Simpson, Lara M., Giampaoli, Simona, Nordestgaard, Børge G., Selmer, Randi, Wennberg, Patrik, Kauhanen, Jussi, Salonen, Jukka T., Dankner, Rachel, Barrett-Connor, Elizabeth, Kavousi, Maryam, Gudnason, Vilmundur, Evans, Denis, Wallace, Robert B., Cushman, Mary, D’Agostino, Ralph B., Sr, Umans, Jason G., Kiyohara, Yutaka, Nakagawa, Hidaeki, Sato, Shinichi, Gillum, Richard F., Folsom, Aaron R., van der Schouw, Yvonne T., Moons, Karel G., Griffin, Simon J., Sattar, Naveed, Wareham, Nicholas J., Selvin, Elizabeth, Thompson, Simon G., and Danesh, John

Published
2014
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84. A genome-wide copy number association study of osteoporotic fractures points to the 6p25.1 locus

Author

Oei, Ling, Hsu, Yi-Hsiang, Styrkarsdottir, Unnur, Eussen, Bert H, de Klein, Annelies, Peters, Marjolein J, Halldorsson, Bjarni, Liu, Ching-Ti, Alonso, Nerea, Kaptoge, Stephen K, Thorleifsson, Gudmar, Hallmans, Göran, Hocking, Lynne J, Husted, Lise Bjerre, Jameson, Karen A, Kruk, Marcin, Lewis, Joshua R, Patel, Millan S, Scollen, Serena, Svensson, Olle, Trompet, Stella, van Schoor, Natasja M, Zhu, Kun, Buckley, Brendan M, Cooper, Cyrus, Ford, Ian, Goltzman, David, González-Macías, Jesús, Langdahl, Bente Lomholt, Leslie, William D, Lips, Paul, Lorenc, Roman S, Olmos, José M, Pettersson-Kymmer, Ulrika, Reid, David M, Riancho, José A, Slagboom, P Eline, Garcia-Ibarbia, Carmen, Ingvarsson, Thorvaldur, Johannsdottir, Hrefna, Luben, Robert, Medina-Gómez, Carolina, Arp, Pascal, Nandakumar, Kannabiran, Palsson, Stefan Th, Sigurdsson, Gunnar, van Meurs, Joyce B J, Zhou, Yanhua, Hofman, Albert, Jukema, J Wouter, Pols, Huibert A P, Prince, Richard L, Cupples, L Adrienne, Marshall, Christian R, Pinto, Dalila, Sato, Daisuke, Scherer, Stephen W, Reeve, Jonathan, Thorsteinsdottir, Unnur, Karasik, David, Richards, J Brent, Stefansson, Kari, Uitterlinden, André G, Ralston, Stuart H, Ioannidis, John P A, Kiel, Douglas P, Rivadeneira, Fernando, and Estrada, Karol

Published
2014
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86. Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies

Author

Pennells, Lisa, Kaptoge, Stephen, Wood, Angela, Sweeting, Mike, Zhao, Xiaohui, White, Ian, Burgess, Stephen, Willeit, Peter, Bolton, Thomas, Moons, Karel G M, van der Schouw, Yvonne T, Selmer, Randi, Khaw, Kay-Tee, Gudnason, Vilmundur, Assmann, Gerd, Amouyel, Philippe, Salomaa, Veikko, Kivimaki, Mika, Nordestgaard, Børge G, Blaha, Michael J, Kuller, Lewis H, Brenner, Hermann, Gillum, Richard F, Meisinger, Christa, Ford, Ian, Knuiman, Matthew W, Rosengren, Annika, Lawlor, Debbie A, Völzke, Henry, Cooper, Cyrus, Marín Ibañez, Alejandro, Casiglia, Edoardo, Kauhanen, Jussi, Cooper, Jackie A, Rodriguez, Beatriz, Sundström, Johan, Barrett-Connor, Elizabeth, Dankner, Rachel, Nietert, Paul J, Davidson, Karina W, Wallace, Robert B, Blazer, Dan G, Björkelund, Cecilia, Donfrancesco, Chiara, Krumholz, Harlan M, Nissinen, Aulikki, Davis, Barry R, Coady, Sean, Whincup, Peter H, Jørgensen, Torben, Ducimetiere, Pierre, Trevisan, Maurizio, Engström, Gunnar, Crespo, Carlos J, Meade, Tom W, Visser, Marjolein, Kromhout, Daan, Kiechl, Stefan, Daimon, Makoto, Price, Jackie F, Gómez de la Cámara, Agustin, Wouter Jukema, J, Lamarche, Benoît, Onat, Altan, Simons, Leon A, Kavousi, Maryam, Ben-Shlomo, Yoav, Gallacher, John, Dekker, Jacqueline M, Arima, Hisatomi, Shara, Nawar, Tipping, Robert W, Roussel, Ronan, Brunner, Eric J, Koenig, Wolfgang, Sakurai, Masaru, Pavlovic, Jelena, Gansevoort, Ron T, Nagel, Dorothea, Goldbourt, Uri, Barr, Elizabeth L M, Palmieri, Luigi, Njølstad, Inger, Sato, Shinichi, Monique Verschuren, W M, Varghese, Cherian V, Graham, Ian, Onuma, Oyere, Greenland, Philip, Woodward, Mark, Ezzati, Majid, Psaty, Bruce M, Sattar, Naveed, Jackson, Rod, Ridker, Paul M, Cook, Nancy R, D'Agostino, Ralph B, Thompson, Simon G, Danesh, John, Di Angelantonio, Emanuele, Simpson, Lara M, Pressel, Sara L, Couper, David J, Nambi, Vijay, Matsushita, Kunihiro, Folsom, Aaron R, Shaw, Jonathan E, Magliano, Dianna J, Zimmet, Paul Z, Wannamethee, S Goya, Willeit, Johann, Santer, Peter, Egger, Georg, Casas, Juan Pablo, Amuzu, Antointtte, Tikhonoff, Valérie, Sutherland, Susan E, Cushman, Mary, Søgaard, Anne Johanne, Håheim, Lise Lund, Ariansen, Inger, Tybjærg-Hansen, Anne, Jensen, Gorm B, Schnohr, Peter, Giampaoli, Simona, Vanuzzo, Diego, Panico, Salvatore, Balkau, Beverley, Bonnet, Fabrice, Marre, Michel, de la Cámara, Agustin Gómez, Rubio Herrera, Miguel Angel, Friedlander, Yechiel, McCallum, John, McLachlan, Stela, Guralnik, Jack, Phillips, Caroline L, Wareham, Nick, Schöttker, Ben, Saum, Kai-Uwe, Holleczek, Bernd, Tolonen, Hanna, Vartiainen, Erkki, Jousilahti, Pekka, Harald, Kennet, D’Agostino, Ralph B, Massaro, Joseph M, Pencina, Michael, Vasan, Ramachandran, Kayama, Takamasa, Kato, Takeo, Oizumi, Toshihide, Jespersen, Jørgen, Møller, Lars, Bladbjerg, Else Marie, Chetrit, A, Wilhelmsen, Lars, Lissner, Lauren, Dennison, Elaine, Kiyohara, Yutaka, Ninomiya, Toshiharu, Doi, Yasufumi, Nijpels, Giel, Stehouwer, Coen D A, Kazumasa, Yamagishi, Iso, Hiroyasu, Kurl, Sudhir, Tuomainen, Tomi-Pekka, Salonen, Jukka T, Deeg, Dorly J H, Nilsson, Peter M, Hedblad, Bo, Melander, Olle, De Boer, Ian H, DeFilippis, Andrew Paul, Verschuren, W M Monique, Watt, Graham, Tverdal, Aage, Kirkland, Susan, Shimbo, Daichi, Shaffer, Jonathan, Bakker, Stephan J L, van der Harst, Pim, Hillege, Hans L, Dallongeville, Jean, Schulte, Helmut, Trompet, Stella, Smit, Roelof A J, Stott, David J, Després, Jean-Pierre, Cantin, Bernard, Dagenais, Gilles R, Laughlin, Gail, Wingard, Deborah, Aspelund, Thor, Eiriksdottir, Gudny, Gudmundsson, Elias Freyr, Ikram, Arfan, van Rooij, Frank J A, Franco, Oscar H, Rueda-Ochoa, Oscar L, Muka, Taulant, Glisic, Marija, Tunstall-Pedoe, Hugh, Howard, Barbara V, Zhang, Ying, Jolly, Stacey, Davey-Smith, George, Can, Günay, Yüksel, Hüsniye, Nakagawa, Hideaki, Morikawa, Yuko, Miura, Katsuyuki, Ingelsson, Martin, Giedraitis, Vilmantas, Gaziano, J Michael, Shipley, Martin, Arndt, Volker, Cook, Nancy, Ibañez, Alejandro Marín, Geleijnse, Johanna M, Epidemiology, Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, University of Iceland, Pennells, Lisa [0000-0002-8594-3061], Kaptoge, Stephen [0000-0002-1155-4872], Wood, Angela [0000-0002-7937-304X], Sweeting, Michael [0000-0003-0980-8965], Zhao, Xiaohui [0000-0001-9922-2815], Burgess, Stephen [0000-0001-5365-8760], Danesh, John [0000-0003-1158-6791], Di Angelantonio, Emanuele [0000-0001-8776-6719], Apollo - University of Cambridge Repository, Nutrition and Health, APH - Aging & Later Life, APH - Societal Participation & Health, APH - Health Behaviors & Chronic Diseases, Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Life Course Epidemiology (LCE), AGEM - Endocrinology, metabolism and nutrition, Internal medicine, Epidemiology and Data Science, İÜC, Lisa, Pennell, Stephen, Kaptoge, Angela, Wood, Mike, Sweeting, Xiaohui, Zhao, Ian, White, Stephen, Burge, Peter, Willeit, Thomas, Bolton, Karel G M, Moon, Yvonne T, van der Schouw, Randi, Selmer, Kay-Tee, Khaw, Vilmundur, Gudnason, Gerd, Assmann, Philippe, Amouyel, Veikko, Salomaa, Mika, Kivimaki, Børge G, Nordestgaard, Michael J, Blaha, Lewis H, Kuller, Hermann, Brenner, Richard F, Gillum, Christa, Meisinger, Ian, Ford, Matthew W, Knuiman, Annika, Rosengren, Debbie A, Lawlor, Henry, Völzke, Cyrus, Cooper, Alejandro, Marín Ibañez, Edoardo, Casiglia, Jussi, Kauhanen, Jackie A, Cooper, Beatriz, Rodriguez, Johan, Sundström, Elizabeth, Barrett-Connor, Rachel, Dankner, Paul J, Nietert, Karina W, Davidson, Robert B, Wallace, Dan G, Blazer, Cecilia, Björkelund, Chiara, Donfrancesco, Harlan M, Krumholz, Aulikki, Nissinen, Barry R, Davi, Sean, Coady, Peter H, Whincup, Torben, Jørgensen, Pierre, Ducimetiere, Maurizio, Trevisan, Gunnar, Engström, Carlos J, Crespo, Tom W, Meade, Marjolein, Visser, Daan, Kromhout, Stefan, Kiechl, Makoto, Daimon, Jackie F, Price, Agustin, Gómez de la Cámara, J, Wouter Jukema, Benoît, Lamarche, Altan, Onat, Leon A, Simon, Maryam, Kavousi, Yoav, Ben-Shlomo, John, Gallacher, Jacqueline M, Dekker, Hisatomi, Arima, Nawar, Shara, Robert W, Tipping, Ronan, Roussel, Eric J, Brunner, Wolfgang, Koenig, Masaru, Sakurai, Jelena, Pavlovic, Ron T, Gansevoort, Dorothea, Nagel, Uri, Goldbourt, Elizabeth L M, Barr, Luigi, Palmieri, Inger, Njølstad, Shinichi, Sato, W M, Monique Verschuren, Cherian V, Varghese, Ian, Graham, Oyere, Onuma, Philip, Greenland, Mark, Woodward, Majid, Ezzati, Bruce M, Psaty, Sattar, W Tipping, Naveerobert, M Simpson, Lara, L Pressel, Sara, J Couper, David, Nambi, Vijay, Matsushita, Kunihiro, R Folsom, Aaron, E Shaw, Jonathan, J Magliano, Dianna, Z Zimmet, Paul, W Knuiman, Matthew, H Whincup, Peter, Goya Wannamethee, S, Willeit, Johann, Santer, Peter, Egger, Georg, Pablo Casas, Juan, Amuzu, Antoinette, Ben-Shlomo, Yoav, Gallacher, John, Tikhonoff, Valérie, Casiglia, Edoardo, E Sutherland, Susan, J Nietert, Paul, Cushman, Mary, M Psaty, Bruce, Johanne Søgaard, Anne, Lund Håheim, Lise, Ariansen, Inger, Tybjærg-Hansen, Anne, B Jensen, Gorm, Schnohr, Peter, Giampaoli, Simona, Vanuzzo, Diego, Panico, Salvatore, Palmieri, Luigi, Balkau, Beverley, Bonnet, Fabrice, Marre, Michel, Gómez de la Cámara, Agustin, Angel Rubio Herrera, Miguel, Friedlander, Yechiel, Mccallum, John, Mclachlan, Stela, Guralnik, Jack, L Phillips, Caroline, Khaw, Kay-Tee, Wareham, Nick, Schöttker, Ben, Saum, Kai-Uwe, Holleczek, Bernd, Nissinen, Aulikki, Tolonen, Hanna, Donfrancesco, Chiara, Vartiainen, Erkki, Jousilahti, Pekka, Harald, Kennet, B D’Agostino, Ralph, M Massaro, Joseph, Pencina, Michael, Vasan, Ramachandran, Kayama, Takamasa, Kato, Takeo, Oizumi, Toshihide, Jespersen, Jørgen, Møller, Lar, Marie Bladbjerg, Else, Chetrit, A, Rosengren, Annika, Wilhelmsen, Lar, Björkelund, Cecilia, Lissner, Lauren, Nagel, Dorothea, Dennison, Elaine, Kiyohara, Yutaka, Ninomiya, Toshiharu, Doi, Yasufumi, Rodriguez, Beatriz, Nijpels, Giel, A Stehouwer, Coen D, Sato, Shinichi, Kazumasa, Yamagishi, Iso, Hiroyasu, Goldbourt, Uri, Salomaa, Veikko, Kurl, Sudhir, Tuomainen, Tomi-Pekka, T Salonen, Jukka, Visser, Marjolein, H Deeg, Dorly J, W Meade, Tom, M Nilsson, Peter, Hedblad, Bo, Melander, Olle, H De Boer, Ian, Paul DeFilippis, Andrew, M Monique Verschuren, W, Sattar, Naveed, Watt, Graham, Meisinger, Christa, Koenig, Wolfgang, H Kuller, Lewi, Tverdal, Aage, F Gillum, Richard, A Cooper, Jackie, Kirkland, Susan, Shimbo, Daichi, Shaffer, Jonathan, Ducimetiere, Pierre, L Bakker, Stephan J, van der Harst, Pim, L Hillege, Han, J Crespo, Carlo, Amouyel, Philippe, Dallongeville, Jean, Assmann, Gerd, Schulte, Helmut, Trompet, Stella, J Smit, Roelof A, J Stott, David, T van der Schouw, Yvonne, Després, Jean-Pierre, Cantin, Bernard, R Dagenais, Gille, Laughlin, Gail, Wingard, Deborah, Trevisan, Maurizio, Aspelund, Thor, Eiriksdottir, Gudny, Freyr Gudmundsson, Elia, Ikram, Arfan, A van Rooij, Frank J, H Franco, Oscar, L Rueda-Ochoa, Oscar, Muka, Taulant, Glisic, Marija, Tunstall-Pedoe, Hugh, Völzke, Henry, V Howard, Barbara, Zhang, Ying, Jolly, Stacey, Davey-Smith, George, Can, Günay, Yüksel, Hüsniye, Nakagawa, Hideaki, Morikawa, Yuko, Miura, Katsuyuki, Njølstad, Inger, Ingelsson, Martin, Giedraitis, Vilmanta, M Ridker, Paul, Michael Gaziano, J, Kivimaki, Mika, Shipley, Martin, J Brunner, Eric, Arndt, Volker, Brenner, Hermann, Cook, Nancy, Ford, Ian, Marín Ibañez, Alejandro, M Geleijnsed, Johanna, Rod, Jackson, Paul M, Ridker, Nancy R, Cook, Ralph B, D'Agostino, Simon G, Thompson, John, Danesh, and Emanuele, Di Angelantonio

Subjects
Male, Cardiac & Cardiovascular Systems, Nutrition and Disease, Prevention and Epidemiology, PREDICTION, Áhættuþættir, 030204 cardiovascular system & hematology, GUIDELINES, 0302 clinical medicine, Risk Factors, Voeding en Ziekte, FRAMINGHAM, Discrimination, Medicine, Cardiac and Cardiovascular Systems, Blóðrásarsjúkdómar, Prospective Studies, Prospective cohort study, Non-U.S. Gov't, 1102 Cardiorespiratory Medicine and Haematology, CALIBRATION, Kardiologi, Framingham Risk Score, Emerging Risk Factors Collaboration, SCORES, Research Support, Non-U.S. Gov't, Incidence (epidemiology), Middle Aged, Cardiovascular disease, Justice and Strong Institutions, Risk prediction, ddc, 3. Good health, Cardiovascular Diseases, Meta-analysis, Cohort, Calibration, Female, Risk assessment, Cardiology and Cardiovascular Medicine, Algorithm, Life Sciences & Biomedicine, Algorithms, SDG 16 - Peace, Risk algorithms, DISEASE PREVENTION, Research Support, Risk Assessment, VALIDATION, 03 medical and health sciences, Clinical Research, Journal Article, Humans, ddc:610, Risk factor, VLAG, Aged, Science & Technology, business.industry, SDG 16 - Peace, Justice and Strong Institutions, 030229 sport sciences, R1, STATIN USE, Cardiovascular System & Hematology, Cardiovascular System & Cardiology, business, PRIMARY PREVENTION, TASK-FORCE
Abstract

Publisher's version (útgefin grein), Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after 'recalibration', a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied. Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at 'high' 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29-39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22-24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44-51 such individuals using original algorithms, in contrast to 37-39 individuals with recalibrated algorithms. Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need., The work of the co-ordinating centre was funded by the UK Medical Research Council (G0800270), British Heart Foundation (SP/09/ 002), British Heart Foundation Cambridge Cardiovascular Centre of Excellence, UK National Institute for Health Research Cambridge Biomedical Research Centre, European Research Council (268834), and European Commission Framework Programme 7 (HEALTH-F2-2012-279233). The Emerging Risk Factor Collaboration’s website https://www.phpc.cam.ac.uk/ceu/erfc/list-of-studies/ has compiled a list provided by investigators of some of the funders of the component studies in this analysis. I.W. was supported by the Medical Research Council Unit Programme MC_UU_12023/21. M.K. is supported by the Netherlands Organization for Scientific Research (NWO) Veni grant (Veni, 91616079). J.P. is supported by Erasmus Mundus Western Balkans (ERAWEB), a project funded by the European Commission.

Published
2019

87. PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies

Author

Wolff, Robert F, Moons, Karel GM, Riley, Richard D, Whiting, Penny F, Westwood, Marie, Collins, Gary S, Reitsma, Johannes B, Kleijnen, Jos, Mallett, Sue, Altman, Doug, Bossuyt, Patrick, Cook, Nancy R, D'Amico, Gennaro, Debray, Thomas PA, Deeks, Jon, De Groot, Joris, Di Angelantonio, Emanuele, Fahey, Tom, Harrell, Frank, Hayden, Jill A, Heymans, Martijn W, Hooft, Lotty, Hyde, Chris, Ioannidis, John, Iorio, Alfonso, Kaptoge, Stephen, Knottnerus, Andre, Leeflang, Mariska, Nixon, Frances, Perel, Pablo, Phillips, Bob, Raatz, Heike, Riemsma, Rob, Rovers, Maroeska, Rutjes, Anne WS, Sauerbrei, Willi, Sauerland, Stefan, Scheibler, Fueloep, Scholten, Rob, Schuit, Ewoud, Steyerberg, Ewout, Tan, Toni, Ter Riet, Gerben, Van Der Windt, Danielle, Vergouwe, Yvonne, Vickers, Andrew, Wood, Angela M, Grp, PROBAST, Grp, PROBAST Steering, Grp, PROBAST Delphi, Family Medicine, RS: CAPHRI - R6 - Promoting Health & Personalised Care, RS: CAPHRI - R5 - Optimising Patient Care, Bureau FHML, Public Health, Di Angelantonio, Emanuele [0000-0001-8776-6719], Kaptoge, Stephen [0000-0002-1155-4872], Wood, Angela [0000-0002-7937-304X], and Apollo - University of Cambridge Repository

Subjects
Delphi Technique, Delphi method, MEDLINE, 01 natural sciences, Decision Support Techniques, 03 medical and health sciences, All institutes and research themes of the Radboud University Medical Center, 0302 clinical medicine, Bias, Diagnosis, Internal Medicine, Medicine, Humans, 030212 general & internal medicine, 0101 mathematics, computer.programming_language, Models, Statistical, business.industry, CARDIOVASCULAR RISK, Explanation, 010102 general mathematics, DIAGNOSIS TRIPOD, INDIVIDUAL PROGNOSIS, General Medicine, Evidence-based medicine, Prognosis, R1, Data science, Critical appraisal, Systematic review, Research Design, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], Model risk, business, RA, computer, Predictive modelling, Delphi, Systematic Reviews as Topic
Abstract

Prediction models in health care use predictors to estimate for an individual the probability that a condition or disease is already present (diagnostic model) or will occur in the future (prognostic model). Publications on prediction models have become more common in recent years, and competing prediction models frequently exist for the same outcome or target population. Health care providers, guideline developers, and policymakers are often unsure which model to use or recommend, and in which persons or settings. Hence, systematic reviews of these studies are increasingly demanded, required, and performed. A key part of a systematic review of prediction models is examination of risk of bias and applicability to the intended population and setting. To help reviewers with this process, the authors developed PROBAST (Prediction model Risk Of Bias ASsessment Tool) for studies developing, validating, or updating (for example, extending) prediction models, both diagnostic and prognostic. PROBAST was developed through a consensus process involving a group of experts in the field. It includes 20 signaling questions across 4 domains (participants, predictors, outcome, and analysis). This explanation and elaboration document describes the rationale for including each domain and signaling question and guides researchers, reviewers, readers, and guideline developers in how to use them to assess risk of bias and applicability concerns. All concepts are illustrated with published examples across different topics. The latest version of the PROBAST checklist, accompanying documents, and filled-in examples can be downloaded from www.probast.org.

Published
2019

88. Cardiovascular risk factors are associated with venous thromboembolism

Author

Gregson, John, Kaptoge, Stephen, Bolton, Thomas, Pennells, Lisa, Willeit, Peter, Burgess, Stephen, Bell, Steven, Sweeting, Michael, Rimm, Eric B., Kabrhel, Christopher, Zoller, Bengt, Assmann, Gerd, Gudnason, Vilmundur, Folsom, Aaron R., Arndt, Volker, Fletcher, Astrid, Norman, Paul E., Nordestgaard, Borge G., Kitamura, Akihiko, Mahmoodi, Bakhtawar K., Whincup, Peter H., Knuiman, Matthew, Salomaa, Veikko, Meisinger, Christa, Koenig, Wolfgang, Kavousi, Maryam, Voelzke, Henry, Cooper, Jackie A., Ninomiya, Toshiharu, Casiglia, Edoardo, Rodriguez, Beatriz, Ben-Shlomo, Yoav, Despres, Jean-Pierre, Simons, Leon, Barrett-Connor, Elizabeth, Bjorkelund, Cecilia, Notdurfter, Marlene, Kromhout, Daan, Price, Jackie, Sutherland, Susan E., Sundstroem, Johan, Kauhanen, Jussi, Gallacher, John, Beulens, Joline W. J., Dankner, Rachel, Cooper, Cyrus, Giampaoli, Simona, Deen, Jason F., Gomez de la Camara, Agustin, Kuller, Lewis H., Rosengren, Annika, Svensson, Peter J., Nagel, Dorothea, Crespo, Carlos J., Brenner, Hermann, Albertorio-Diaz, Juan R., Atkins, Robert, Brunner, Eric J., Shipley, Martin, Njolstad, Inger, Lawlor, Deborah A., van der Schouw, Yvonne T., Selmer, Randi Marie, Trevisan, Maurizio, Verschuren, W. M. Monique, Greenland, Philip, Wassertheil-Smoller, Sylvia, Lowe, Gordon D. O., Wood, Angela M., Butterworth, Adam S., Thompson, Simon G., Danesh, John, Di Angelantonio, Emanuele, Meade, Tom, Rosamond, Wayne, Whitsel, Eric, Cushman, Mary, Barr, Elizabeth L. M., Shaw, Jonathan E., Zimmet, Paul Z., Kiechl, Stefan, Weger, Siegfried, Willeit, Johann, Amuzu, Antoinette, Dale, Caroline, Casas, Juan P., Tikhonoff, Valerie, Nietert, Paul, Tybjaerg-Hansen, Anne, Frikke-Schmidt, Ruth, Jensen, Gorm B., Lora Pablos, David, Cancelas Navia, Pilar, McLachlan, Stela, Schoettker, Ben, Saum, Kai-Uwe, Holleczek, Bernd, Ariansen, Inger, Meyer, Haakon E., Haheim, Lise Lund, Vartiainen, Erkki, Jousilahti, Pekka, Harald, Kennet, Wilhelmsen, Lars, Dennison, Elaine, Syddall, Holly, Westbury, Leo, Flicker, Leon, Hankey, Graeme J., Golledge, Jonathan, Doi, Yasufumi, Kiyohara, Yutaka, Elders, Petra, Stehouwer, Coen, Jensen, Majken, Iso, Hiroyasu, Yamagishi, Kazumasa, Sudhir, Kurl, Tuomainen, Tomi-Pekka, Salonen, Jukka T., Boer, Jolanda M. A., Blokstra, Anneke, Melander, Olle, Nilsson, Peter M., Engstrom, Gunnar, Palmieri, Luigi, Vanuzzo, Diego, Peters, Annette, Thorand, Barbara, Heier, Margit, Hu, Frank B., Manson, JoAnn E., Meijer, Karina, Gansevoort, Ron T., Schulte, Helmut, Sluijs, Ivonne, Cantin, Bernard, Lamarche, Benoit, Dagenais, Gilles R., McEvoy, Linda, Laughlin, Gail, Daniels, Lori B., Aspelund, Thor, Gudmundsson, Elias Freyr, Thorsson, Bolli, Leening, Maarten J. G., Ikram, M. Arfan, Franco, Oscar H., Tunstall-Pedoe, Hugh, Werner, Andre, Devereux, Richard, Jolly, Stacey, Smith, George Davey, Can, Gunay, Yuksel, Husniye, Altay, Servet, Ingelsson, Martin, Giedraitis, Vilmantas, Claessen, Heiner, Rothenbacher, Dietrich, Parikh, Nisha, I, Eaton, Charles, Kivimaki, Mika, Feskens, Edith, Geleijnse, Johanna M., Spackman, Sarah, Walker, Matthew, Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Kaptoge, Stephen [0000-0002-1155-4872], Pennells, Lisa [0000-0002-8594-3061], Burgess, Stephen [0000-0001-5365-8760], Bell, Steven [0000-0001-6774-3149], Sweeting, Michael [0000-0003-0980-8965], Wood, Angela [0000-0002-7937-304X], Butterworth, Adam [0000-0002-6915-9015], Danesh, John [0000-0003-1158-6791], Di Angelantonio, Emanuele [0000-0001-8776-6719], Apollo - University of Cambridge Repository, Epidemiology, ACS - Diabetes & metabolism, APH - Health Behaviors & Chronic Diseases, Epidemiology and Data Science, and ACS - Heart failure & arrhythmias

Subjects
Male, Outcome Assessment, ALCOHOL-CONSUMPTION, Coronary Disease, 030204 cardiovascular system & hematology, Body Mass Index, 0302 clinical medicine, Risk Factors, Outcome Assessment, Health Care, Cardiac and Cardiovascular Systems, 030212 general & internal medicine, Prospective Studies, DEEP-VEIN THROMBOSIS, Prospective cohort study, Original Investigation, Venous Thrombosis, education.field_of_study, Kardiologi, Hazard ratio, INDIVIDUAL-PARTICIPANT DATA, Venous Thromboembolism, Middle Aged, Biobank, 3. Good health, Pulmonary embolism, ddc, Cardiovascular Diseases, OBESITY, Female, SMOKING, Cardiology and Cardiovascular Medicine, Cohort study, Adult, medicine.medical_specialty, PULMONARY-EMBOLISM, Population, 03 medical and health sciences, Internal medicine, medicine, Journal Article, Diabetes Mellitus, Online First, Life Science, Humans, CORONARY-HEART-DISEASE, ddc:610, Obesity, Pulmonary Embolism, Smoking, United Kingdom, Risk factor, education, METAANALYSIS, VLAG, Global Nutrition, Wereldvoeding, business.industry, Research, DIABETES-MELLITUS, medicine.disease, Health Care, LIPOPROTEIN, business, Body mass index
Abstract

Key Points Question To what extent are established cardiovascular risk factors associated with risk of venous thromboembolism (VTE)? Findings In this analysis of individual participant data from the Emerging Risk Factors Collaboration and the UK Biobank including 1.1 million participants, among a panel of several established cardiovascular risk factors, older age, smoking, and greater adiposity were consistently associated with higher VTE risk. Meaning There is overlap in at least some of the major population determinants of important venous and arterial thrombotic diseases., This analysis of data from the Emerging Risk Factors Collaboration and the UK Biobank estimates the associations of major cardiovascular risk factors with venous thromboembolism., Importance It is uncertain to what extent established cardiovascular risk factors are associated with venous thromboembolism (VTE). Objective To estimate the associations of major cardiovascular risk factors with VTE, ie, deep vein thrombosis and pulmonary embolism. Design, Setting, and Participants This study included individual participant data mostly from essentially population-based cohort studies from the Emerging Risk Factors Collaboration (ERFC; 731 728 participants; 75 cohorts; years of baseline surveys, February 1960 to June 2008; latest date of follow-up, December 2015) and the UK Biobank (421 537 participants; years of baseline surveys, March 2006 to September 2010; latest date of follow-up, February 2016). Participants without cardiovascular disease at baseline were included. Data were analyzed from June 2017 to September 2018. Exposures A panel of several established cardiovascular risk factors. Main Outcomes and Measures Hazard ratios (HRs) per 1-SD higher usual risk factor levels (or presence/absence). Incident fatal outcomes in ERFC (VTE, 1041; coronary heart disease [CHD], 25 131) and incident fatal/nonfatal outcomes in UK Biobank (VTE, 2321; CHD, 3385). Hazard ratios were adjusted for age, sex, smoking status, diabetes, and body mass index (BMI). Results Of the 731 728 participants from the ERFC, 403 396 (55.1%) were female, and the mean (SD) age at the time of the survey was 51.9 (9.0) years; of the 421 537 participants from the UK Biobank, 233 699 (55.4%) were female, and the mean (SD) age at the time of the survey was 56.4 (8.1) years. Risk factors for VTE included older age (ERFC: HR per decade, 2.67; 95% CI, 2.45-2.91; UK Biobank: HR, 1.81; 95% CI, 1.71-1.92), current smoking (ERFC: HR, 1.38; 95% CI, 1.20-1.58; UK Biobank: HR, 1.23; 95% CI, 1.08-1.40), and BMI (ERFC: HR per 1-SD higher BMI, 1.43; 95% CI, 1.35-1.50; UK Biobank: HR, 1.37; 95% CI, 1.32-1.41). For these factors, there were similar HRs for pulmonary embolism and deep vein thrombosis in UK Biobank (except adiposity was more strongly associated with pulmonary embolism) and similar HRs for unprovoked vs provoked VTE. Apart from adiposity, these risk factors were less strongly associated with VTE than CHD. There were inconsistent associations of VTEs with diabetes and blood pressure across ERFC and UK Biobank, and there was limited ability to study lipid and inflammation markers. Conclusions and Relevance Older age, smoking, and adiposity were consistently associated with higher VTE risk.

Published
2019

89. Polygenic basis and biomedical consequences of telomere length variation

Author

Codd, Veryan, primary, Wang, Qingning, additional, Allara, Elias, additional, Musicha, Crispin, additional, Kaptoge, Stephen, additional, Stoma, Svetlana, additional, Jiang, Tao, additional, Hamby, Stephen E., additional, Braund, Peter S., additional, Bountziouka, Vasiliki, additional, Budgeon, Charley A., additional, Denniff, Matthew, additional, Swinfield, Chloe, additional, Papakonstantinou, Manolo, additional, Sheth, Shilpi, additional, Nanus, Dominika E., additional, Warner, Sophie C., additional, Wang, Minxian, additional, Khera, Amit V., additional, Eales, James, additional, Ouwehand, Willem H., additional, Thompson, John R, additional, Angelantonio, Emanuele Di, additional, Wood, Angela M., additional, Butterworth, Adam S., additional, Danesh, John N., additional, Nelson, Christopher P., additional, and Samani, Nilesh J., additional

Published
2021
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90. Older biological age is associated with adverse COVID-19 outcomes: A cohort study in UK Biobank

Author

Wang, Qingning, primary, Codd, Veryan, additional, Raisi-Estabragh, Zahra, additional, Musicha, Crispin, additional, Bountziouka, Vasiliki, additional, Kaptoge, Stephen, additional, Allara, Elias, additional, Angelantonio, Emanuele Di, additional, Butterworth, Adam S., additional, Wood, Angela M., additional, Thompson, John R., additional, Petersen, Steffen E, additional, Harvey, Nicholas C., additional, Danesh, John N., additional, Samani, Nilesh J., additional, and Nelson, Christopher P., additional

Published
2021
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91. Long-term interleukin-6 levels and subsequent risk of coronary heart disease: two new prospective studies and a systematic review

Author

Danesh, John, Kaptoge, Stephen, Mann, Andrea G., Sarwar, Nadeem, Wood, Angela, Angleman, Sara B., Wensley, Frances, Higgins, Julian P.T., Lennon, Lucy, Eiriksdottir, Gudny, Rumley, Ann, Whincup, Peter H., Lowe, Gordon D.O., and Gudnason, Vilmundur

Subjects
Biological sciences
Abstract

Background The relevance to coronary heart disease (CHD) of cytokines that govern inflammatory cascades, such as interleukin-6 (IL-6), may be underestimated because such mediators are short acting and prone to fluctuations. We evaluated associations of long-term circulating IL-6 levels with CHD risk (defined as nonfatal myocardial infarction [MI] or fatal CHD) in two population-based cohorts, involving serial measurements to enable correction for within-person variability. We updated a systematic review to put the new findings in context. Methods and Findings Measurements were made in samples obtained at baseline from 2,138 patients who had a first-ever nonfatal MI or died of CHD during follow-up, and from 4,267 controls in two cohorts comprising 24,230 participants. Correction for within-person variability was made using data from repeat measurements taken several years apart in several hundred participants. The yearto-year variability of IL-6 values within individuals was relatively high (regression dilution ratios of 0.41, 95% confidence interval [CI] 0.28-0.53, over 4 y, and 0.35, 95% CI 0.23-0.48, over 12 y). Ignoring this variability, we found an odds ratio for CHD, adjusted for several established risk factors, of 1.46 (95% CI 1.29-1.65) per 2 standard deviation (SD) increase of baseline IL-6 values, similar to that for baseline C-reactive protein. After correction for within-person variability, the odds ratio for CHD was 2.14 (95% CI 1.45-3.15) with long-term average ('usual') IL-6, similar to those for some established risk factors. Increasing IL-6 levels were associated with progressively increasing CHD risk. An updated systematic review of electronic databases and other sources identified 15 relevant previous population-based prospective studies of IL-6 and clinical coronary outcomes (i.e., MI or coronary death). Including the two current studies, the 17 available prospective studies gave a combined odds ratio of 1.61 (95% CI 1.42-1.83) per 2 SD increase in baseline IL-6 (corresponding to an odds ratio of 3.34 [95% CI 2.45-4.56] per 2 SD increase in usual [long-term average] IL-6 levels). Conclusions Long-term IL-6 levels are associated with CHD risk about as strongly as are some major established risk factors, but causality remains uncertain. These findings highlight the potential relevance of IL-6-mediated pathways to CHD., Introduction As atherosclerosis may be an inflammatory condition [1], there is interest in the relevance of various circulating inflammatory markers to cardiovascular diseases [2]. Inflammatory cascades are propagated by proximal [...]

Published
2008

92. Large-scale analysis of associating between LRP5 and LRP6 variants and osteoporosis

Author

van Meurs, Joyce B.J., Trikalinos, Thomas A., Ralston, Stuart H., Balcells, Susana, Brandi, Maria Luisa, Brixen, Kim, Kiel, Douglas P., Langdahl, Bente L., Lips, Paul, Ljunggren, Osten, Lorenc, Roman, Obermayer-Pietsch, Barbara, Ohlsson, Claes, Pettersson, Ulrika, Reid, David M., Rousseau, Francois, Scollen, Serena, Van Hul, Wim, Agueda, Lidia, Akesson, Kristina, Benevolenskaya, Lidia I., Ferrari, Serge L., Hallmans, Goran, Hofman, Albert, Husted, Lise Bjerre, Kruk, Marcin, Kaptoge, Stephen, Karasik, David, Karlsson, Magnus K., Lorentzon, Mattias, Masi, Laura, McGuigan, Fiona E.A., Mellstrom, Dan, Mosekilde, Leif, Nogues, Xavier, Pols, Huibert A.P., Reeve, Jonathan, Renner, Wilfried, Rivadeneira, Fernando, van Schoor, and Natasja M.

Subjects
Fractures -- Risk factors, Fractures -- Health aspects, Osteoporosis -- Genetic aspects, Low density lipoprotein receptors -- Research, Mutation (Biology) -- Research, Bones -- Density, Bones -- Genetic aspects
Abstract

A study to examine whether mutations to low-density lipoprotein receptor-related protein 5 (LRP5) and LRP6 affected bone mineral density (BMD) and increased the risk of fractures was conducted. Results revealed that LRP5 variants were commonly associated with BMD and increased risk of fractures.

Published
2008

93. Accuracy of UK Rapid Test Consortium (UK-RTC) 'AbC-19 Rapid Test' for detection of previous SARS-CoV-2 infection in key workers: test accuracy study

Author

Mulchandani, Ranya, Jones, Hayley E, Taylor-Phillips, Sian, Shute, Justin, Perry, Keith, Jamarani, Shabnam, Brooks, Tim, Charlett, Andre, Hickman, Matthew, Oliver, Isabel, Kaptoge, Stephen, Danesh, John, Di Angelantonio, Emanuele, Ades, Anthony E, Wyllie, David H, Armitage, Jane, Borrow, Ray, Boyes, John, Cullen, Donna, Hormis, Anil, Linley, Ezra, Mehenny, Susan, Miflin, Gail, Moore, Carmel, Moore, Philippa, Reckless, Ian, Roberts, David J, Sambrook, Jennifer, and Todd, Neil

Subjects
Male, medicine.medical_specialty, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Health Personnel, Population, Pneumonia, Viral, serology, 030204 cardiovascular system & hematology, Sensitivity and Specificity, Serology, 03 medical and health sciences, Betacoronavirus, 0302 clinical medicine, COVID-19 Testing, Predictive Value of Tests, Internal medicine, False positive paradox, medicine, Humans, 030212 general & internal medicine, education, Pandemics, Immunoassay, education.field_of_study, medicine.diagnostic_test, business.industry, Clinical Laboratory Techniques, SARS-CoV-2, Research, lateral flow immunoassay, COVID-19, Covid19, General Medicine, test accuracy, Confidence interval, Police, United Kingdom, Test (assessment), Predictive value of tests, Firefighters, Female, Reagent Kits, Diagnostic, business, Coronavirus Infections
Abstract

Objective To assess the accuracy of the AbC-19 Rapid Test lateral flow immunoassay for the detection of previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Design Test accuracy study. Setting Laboratory based evaluation. Participants 2847 key workers (healthcare staff, fire and rescue officers, and police officers) in England in June 2020 (268 with a previous polymerase chain reaction (PCR) positive result (median 63 days previously), 2579 with unknown previous infection status); and 1995 pre-pandemic blood donors. Main outcome measures AbC-19 sensitivity and specificity, estimated using known negative (pre-pandemic) and known positive (PCR confirmed) samples as reference standards and secondly using the Roche Elecsys anti-nucleoprotein assay, a highly sensitive laboratory immunoassay, as a reference standard in samples from key workers. Results Test result bands were often weak, with positive/negative discordance by three trained laboratory staff for 3.9% of devices. Using consensus readings, for known positive and negative samples sensitivity was 92.5% (95% confidence interval 88.8% to 95.1%) and specificity was 97.9% (97.2% to 98.4%). Using an immunoassay reference standard, sensitivity was 94.2% (90.7% to 96.5%) among PCR confirmed cases but 84.7% (80.6% to 88.1%) among other people with antibodies. This is consistent with AbC-19 being more sensitive when antibody concentrations are higher, as people with PCR confirmation tended to have more severe disease whereas only 62% (218/354) of seropositive participants had had symptoms. If 1 million key workers were tested with AbC-19 and 10% had actually been previously infected, 84 700 true positive and 18 900 false positive results would be projected. The probability that a positive result was correct would be 81.7% (76.8% to 85.8%). Conclusions AbC-19 sensitivity was lower among unselected populations than among PCR confirmed cases of SARS-CoV-2, highlighting the scope for overestimation of assay performance in studies involving only PCR confirmed cases, owing to “spectrum bias.” Assuming that 10% of the tested population have had SARS-CoV-2 infection, around one in five key workers testing positive with AbC-19 would be false positives. Study registration ISRCTN 56609224.

Published
2020

95. Meta‐analysis of non‐linear exposure‐outcome relationships using individual participant data: A comparison of two methods

Author

White, Ian R., Kaptoge, Stephen, Royston, Patrick, and Sauerbrei, Willi

Subjects
Male, prognostic research, Models, Statistical, multivariate meta‐analysis, Coronary Disease, fractional polynomials, Middle Aged, random effects models, Body Mass Index, Meta-Analysis as Topic, Nonlinear Dynamics, meta‐analysis, Risk Factors, Humans, Female, Mortality, Research Articles, Research Article
Abstract

Non‐linear exposure‐outcome relationships such as between body mass index (BMI) and mortality are common. They are best explored as continuous functions using individual participant data from multiple studies. We explore two two‐stage methods for meta‐analysis of such relationships, where the confounder‐adjusted relationship is first estimated in a non‐linear regression model in each study, then combined across studies. The “metacurve” approach combines the estimated curves using multiple meta‐analyses of the relative effect between a given exposure level and a reference level. The “mvmeta” approach combines the estimated model parameters in a single multivariate meta‐analysis. Both methods allow the exposure‐outcome relationship to differ across studies. Using theoretical arguments, we show that the methods differ most when covariate distributions differ across studies; using simulated data, we show that mvmeta gains precision but metacurve is more robust to model mis‐specification. We then compare the two methods using data from the Emerging Risk Factors Collaboration on BMI, coronary heart disease events, and all‐cause mortality (>80 cohorts, >18 000 events). For each outcome, we model BMI using fractional polynomials of degree 2 in each study, with adjustment for confounders. For metacurve, the powers defining the fractional polynomials may be study‐specific or common across studies. For coronary heart disease, metacurve with common powers and mvmeta correctly identify a small increase in risk in the lowest levels of BMI, but metacurve with study‐specific powers does not. For all‐cause mortality, all methods identify a steep U‐shape. The metacurve and mvmeta methods perform well in combining complex exposure‐disease relationships across studies.

Published
2018

98. Polygenic risk scores in cardiovascular risk prediction: A cohort study and modelling analyses

Author

Sun, Luanluan, primary, Pennells, Lisa, additional, Kaptoge, Stephen, additional, Nelson, Christopher P., additional, Ritchie, Scott C., additional, Abraham, Gad, additional, Arnold, Matthew, additional, Bell, Steven, additional, Bolton, Thomas, additional, Burgess, Stephen, additional, Dudbridge, Frank, additional, Guo, Qi, additional, Sofianopoulou, Eleni, additional, Stevens, David, additional, Thompson, John R., additional, Butterworth, Adam S., additional, Wood, Angela, additional, Danesh, John, additional, Samani, Nilesh J., additional, Inouye, Michael, additional, and Di Angelantonio, Emanuele, additional

Published
2021
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99. Telomere Length and Risk of Incident Fracture and Arthroplasty: Findings From UK Biobank

Author

Curtis, Elizabeth M., primary, Codd, Veryan, additional, Nelson, Christopher, additional, D'Angelo, Stefania, additional, Wang, Qingning, additional, Allara, Elias, additional, Kaptoge, Stephen, additional, Matthews, Paul M., additional, Tobias, Jonathan H., additional, Danesh, John, additional, Cooper, Cyrus, additional, Samani, Nilesh J., additional, and Harvey, Nicholas C., additional

Published
2020
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