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1. Prognostic value of serial measurements of gdf-15 in acute heart failure

Author

Gurgoze, M. T., Baart, S. J., Kardys, I., Akkerhuis, K. M., Manintveld, O. C., Postmus, D., Hillege, H. L., Van Vark, L. C., Asselbergs, F. W., La-Rocca, H. P. Brunner, Van den Bos, E. J., Pinto, Y. M., Boersma, E., Life Course Epidemiology (LCE), Value, Affordability and Sustainability (VALUE), Groningen Kidney Center (GKC), and Cardiovascular Centre (CVC)

Published
2021

4. Major lipids, apolipoproteins, and risk of vascular disease

Author

Emerging Risk Factors Collaboration, Di Angelantonio E, Sarwar N, Perry P, Kaptoge S, Ray KK, Thompson A, Wood AM, Lewington S, Sattar N, Packard CJ, Collins R, Thompson SG, Tipping RW, Ford CE, Pressel SL, Walldius G, Jungner I, Folsom AR, Chambless LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Goldbourt U, Benderly M, Tanne D, Whincup PH, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Santer P, Mayr A, Wald N, Ebrahim S, Lawlor DA, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Psaty BM, Tracy RP, Tybjaerg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Smith FB, Taylor J, Guralnik JM, Phillips CL, Wallace R, Guralnik J, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Rodriguez B, Dekker JM, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Deeg DJ, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engstrom G, Verschuren WM, Blokstra A, Döring A, Koenig W, Meisinger C, Mraz W, Verschure WM, Bas Bueno de Mesquita H, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson J, Knottenbelt C, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Ford I, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe GD, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Lind L, Giedraitis V, Lannfelt L, Gaziano JM, Stampfer M, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Marmot M, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Cobbe SM, Robertson M, He Y, Marin Ibañez A, Feskens EJ, Kromhout D, Walker M, Watson S, Erqou S, Orfei L, Pennells L, Perry PL, Alexander M, Wensley F, White IR, Danesh J., PANICO, SALVATORE, Developmental Genetics, EMGO+ - Lifestyle, Overweight and Diabetes, Epidemiology and Data Science, General practice, Psychiatry, EMGO - Lifestyle, overweight and diabetes, Emerging Risk Factors, Collaboration, Di Angelantonio, E, Sarwar, N, Perry, P, Kaptoge, S, Ray, Kk, Thompson, A, Wood, Am, Lewington, S, Sattar, N, Packard, Cj, Collins, R, Thompson, Sg, Tipping, Rw, Ford, Ce, Pressel, Sl, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Goldbourt, U, Benderly, M, Tanne, D, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, R, Guralnik, J, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Rodriguez, B, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engstrom, G, Verschuren, Wm, Blokstra, A, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Verschure, Wm, Bas Bueno de Mesquita, H, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, Knottenbelt, C, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Ford, I, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Lind, L, Giedraitis, V, Lannfelt, L, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Marmot, M, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Robertson, M, He, Y, Marin Ibañez, A, Feskens, Ej, Kromhout, D, Walker, M, Watson, S, Erqou, S, Orfei, L, Pennells, L, Perry, Pl, Alexander, M, Wensley, F, White, Ir, and Danesh, J.

Subjects
medicine.medical_specialty, Apolipoprotein B, biology, Triglyceride, business.industry, Vascular disease, Cholesterol, Proportional hazards model, Hazard ratio, Context (language use), General Medicine, 11 Medical And Health Sciences, medicine.disease, Gastroenterology, Article, chemistry.chemical_compound, Endocrinology, chemistry, Internal medicine, General & Internal Medicine, biology.protein, Medicine, lipids (amino acids, peptides, and proteins), Myocardial infarction, business
Abstract

Udgivelsesdato: 2009-Nov-11 CONTEXT: Associations of major lipids and apolipoproteins with the risk of vascular disease have not been reliably quantified. OBJECTIVE: To assess major lipids and apolipoproteins in vascular risk. DESIGN, SETTING, AND PARTICIPANTS: Individual records were supplied on 302,430 people without initial vascular disease from 68 long-term prospective studies, mostly in Europe and North America. During 2.79 million person-years of follow-up, there were 8857 nonfatal myocardial infarctions, 3928 coronary heart disease [CHD] deaths, 2534 ischemic strokes, 513 hemorrhagic strokes, and 2536 unclassified strokes. MAIN OUTCOME MEASURES: Hazard ratios (HRs), adjusted for several conventional factors, were calculated for 1-SD higher values: 0.52 log(e) triglyceride, 15 mg/dL high-density lipoprotein cholesterol (HDL-C), 43 mg/dL non-HDL-C, 29 mg/dL apolipoprotein AI, 29 mg/dL apolipoprotein B, and 33 mg/dL directly measured low-density lipoprotein cholesterol (LDL-C). Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. RESULTS: The rates of CHD per 1000 person-years in the bottom and top thirds of baseline lipid distributions, respectively, were 2.6 and 6.2 with triglyceride, 6.4 and 2.4 with HDL-C, and 2.3 and 6.7 with non-HDL-C. Adjusted HRs for CHD were 0.99 (95% CI, 0.94-1.05) with triglyceride, 0.78 (95% CI, 0.74-0.82) with HDL-C, and 1.50 (95% CI, 1.39-1.61) with non-HDL-C. Hazard ratios were at least as strong in participants who did not fast as in those who did. The HR for CHD was 0.35 (95% CI, 0.30-0.42) with a combination of 80 mg/dL lower non-HDL-C and 15 mg/dL higher HDL-C. For the subset with apolipoproteins or directly measured LDL-C, HRs were 1.50 (95% CI, 1.38-1.62) with the ratio non-HDL-C/HDL-C, 1.49 (95% CI, 1.39-1.60) with the ratio apo B/apo AI, 1.42 (95% CI, 1.06-1.91) with non-HDL-C, and 1.38 (95% CI, 1.09-1.73) with directly measured LDL-C. Hazard ratios for ischemic stroke were 1.02 (95% CI, 0.94-1.11) with triglyceride, 0.93 (95% CI, 0.84-1.02) with HDL-C, and 1.12 (95% CI, 1.04-1.20) with non-HDL-C. CONCLUSION: Lipid assessment in vascular disease can be simplified by measurement of either total and HDL cholesterol levels or apolipoproteins without the need to fast and without regard to triglyceride.

Published
2016
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5. High-sensitivity C-reactive protein predicts 10-year cardiovascular outcome after percutaneous coronary intervention

Author

Oemrawsingh, R.M., Cheng, J.M., Martijn Akkerhuis, K., Kardys, I., Degertekin, M., Van Geuns, R.-J., Van Domburg, R.T., Oemrawsingh, R.M., Cheng, J.M., Martijn Akkerhuis, K., Kardys, I., Degertekin, M., Van Geuns, R.-J., Van Domburg, R.T., and Yeditepe Üniversitesi

Subjects
cardiovascular diseases, Prognosis, C-reactive protein, Percutaneous coronary intervention
Abstract

Aims: This study aimed to evaluate the prognostic value of high-sensitivity C-reactive protein (hsCRP) during 10-year follow-up after percutaneous coronary intervention (PCI). Methods and results: Between April and October 2002, hsCRP was measured in 468 all-comer patients who underwent PCI with sirolimus-eluting stent implantation for stable coronary artery disease or acute coronary syndrome. The primary endpoint was the composite of all-cause mortality or myocardial infarction at 10-year follow-up. Kaplan-Meier event curves displayed ongoing divergence of the hsCRP groups (hsCRP 3 mg/L: 43.1%). After adjustment for established cardiovascular risk factors and clinical presentation in a Cox regression model, higher CRP levels were associated with a higher incidence of the composite endpoint (>3 mg/L vs.

Published
2016

8. Collaborative pooled analysis of data on C-reactive protein gene variants and coronary disease: judging causality by Mendelian randomisation

Author

Danesh, J, Collaborat, CRPCHDG, Hingorani, A, Wensley, F, Casas, JP, Smeeth, L, Samani, NJ, Hall, A, Whincup, P, Morris, R, Lawlor, DA, Smith, GD, Timpson, N, Ebrahim, S, Brown, M, Sandhu, M, Reiner, A, Psaty, B, Lange, L, Cushman, M, Tracy, R, Nordestgaard, BG, Tybjaerg-Hansen, A, Zacho, J, Hung, J, Thompson, P, Beilby, J, Palmer, LJ, Fowkes, G, Lowe, G, Tzoulaki, I, Kumari, M, Overvad, K, Khaw, KT, Benjamin, EJ, Larson, MG, Yamamoto, JF, Chiodini, B, Franzosi, M, Norman, PE, Hankey, GJ, Jamrozik, K, Palmer, L, Rimm, E, Pai, J, Heckbert, S, Bis, J, Yusuf, S, Anand, S, Engert, J, Collins, R, Melander, O, Berglund, G, Ladenvall, P, Johansson, L, Jansson, JH, Hallmans, G, Humphries, S, Manson, J, Saleheen, D, Frossard, P, Sattar, N, Robertson, M, Shepherd, J, Schaefer, E, Hofman, A, Witteman, JCM, Kardys, I, de Faire, U, Bennet, A, O'Reilly, D, McMahon, A, Packard, C, Clarke, R, Greenland, P, Bowden, J, Di Angelantonio, E, Shah, T, Verzilli, C, Walker, M, and Wittaker, J

Subjects
Research design, Pathology, medicine.medical_specialty, Heart disease, Epidemiology, Coronary Disease, Bioinformatics, medicine, Humans, Cooperative Behavior, Prospective cohort study, Inflammation, Polymorphism, Genetic, biology, business.industry, C-reactive protein, Haplotype, Case-control study, medicine.disease, Causality, C-Reactive Protein, Haplotypes, Research Design, Case-Control Studies, biology.protein, Cell activation, business
Abstract

Many prospective studies have reported associations between circulating C-reactive protein (CRP) levels and risk of coronary heart disease (CHD), but causality remains uncertain. Studies of CHD are being conducted that involve measurement of common polymorphisms of the CRP gene known to be associated with circulating concentrations, thereby utilising these variants as proxies for circulating CRP levels. By analysing data from several studies examining the association between relevant CRP polymorphisms and CHD risk, the present collaboration will undertake a Mendelian randomisation analysis to help assess the likelihood of any causal relevance of CRP levels to CHD risk. A central database is being established containing individual data on CRP polymorphisms, circulating CRP levels, and major coronary outcomes as well as age, sex and other relevant characteristics. Associations between CRP polymorphisms or haplotypes and CHD will be evaluated under different circumstances. This collaboration comprises, at present, about 37,000 CHD outcomes and about 120,000 controls, which should yield suitably precise findings to help judge causality. This work should advance understanding of the relevance of low-grade inflammation to CHD and indicate whether or not CRP itself is involved in long-term pathogenesis.

Published
2008
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9. C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis

Author

Emerging Risk Factors Collaboration, Kaptoge S, Di Angelantonio E, Lowe G, Pepys MB, Thompson SG, Collins R, Danesh JTipping RW, Ford CE, Pressel SL, Walldius G, Jungner I, Folsom AR, Chambless L, Ballantyne CM, Panagiotakos D, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman MW, Goldbourt U, Benderly M, Tanne D, Whincup P, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Mayr A, Schett G, Wald N, Ebrahim S, Lawlor D, Yarnell J, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Psaty BM, Tracy R, Tybjaerg Hansen A, Nordestgaard BG, Zacho J, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, de la Cámara AG, Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee A, Taylor J, Guralnik JM, Phillips CL, Wallace RB, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Benjamin EJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Kiyohara Y, Arima H, Doi Y, Ninomiya T, Rodriguez B, Dekker J, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Laukkanen JA, Deeg DJ, Bremmer MA, Meade TW, Cooper JA, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Shea S, Döring A, Koenig W, Meisinger C, Bueno de Mesquita HB, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum RF, Mussolino M, Hankinson S, Manson JE, Knottenbelt C, Bauer KA, Davidson K, Kirkland S, Shaffer J, Korin MR, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Luc G, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Packard CJ, Sattar N, Westendorp RG, Buckley BM, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt RR, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler MM, Hofman A, Tunstall Pedoe H, Tavendale R, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Basu S, Cederholm T, Byberg L, Gaziano JM, Stampfer M, Ridker PM, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Wassertheil Smoller S, Marmot IM, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Shepherd J, Cobbe S, Ford I, Robertson M, He Y, Ibañez AM, Feskens EJ, Walker M, Watson S, Erqou S, Lewington S, Pennells L, Perry PL, Ray KK, Sarwar N, Alexander M, Thompson A, White IR, Wood AM, Danesh J., PANICO, SALVATORE, Interne Geneeskunde, MUMC+: MA Interne Geneeskunde (3), RS: CARIM School for Cardiovascular Diseases, General practice, EMGO - Lifestyle, overweight and diabetes, Psychiatry, EMGO - Mental health, Emerging Risk Factors, Collaboration, Kaptoge, S, Di Angelantonio, E, Lowe, G, Pepys, Mb, Thompson, Sg, Collins, R, Danesh JTipping, Rw, Ford, Ce, Pressel, Sl, Walldius, G, Jungner, I, Folsom, Ar, Chambless, L, Ballantyne, Cm, Panagiotakos, D, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, Mw, Goldbourt, U, Benderly, M, Tanne, D, Whincup, P, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Mayr, A, Schett, G, Wald, N, Ebrahim, S, Lawlor, D, Yarnell, J, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, R, Tybjaerg Hansen, A, Nordestgaard, Bg, Zacho, J, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, de la Cámara, Ag, Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, A, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, Rb, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Benjamin, Ej, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, J, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Laukkanen, Ja, Deeg, Dj, Bremmer, Ma, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Shea, S, Döring, A, Koenig, W, Meisinger, C, Bueno de Mesquita, Hb, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, Rf, Mussolino, M, Hankinson, S, Manson, Je, Knottenbelt, C, Bauer, Ka, Davidson, K, Kirkland, S, Shaffer, J, Korin, Mr, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Luc, G, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Packard, Cj, Sattar, N, Westendorp, Rg, Buckley, Bm, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, Rr, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, Mm, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Basu, S, Cederholm, T, Byberg, L, Gaziano, Jm, Stampfer, M, Ridker, Pm, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Wassertheil Smoller, S, Marmot, Im, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Shepherd, J, Cobbe, S, Ford, I, Robertson, M, He, Y, Ibañez, Am, Feskens, Ej, Walker, M, Watson, S, Erqou, S, Lewington, S, Pennells, L, Perry, Pl, Ray, Kk, Sarwar, N, Alexander, M, Thompson, A, White, Ir, Wood, Am, and Danesh, J.

Subjects
Lung Diseases, Male, Databases, Factual, Plasma-fibrinogen, Blood Pressure, Coronary Disease, 030204 cardiovascular system & hematology, Associations, Body Mass Index, Low-density-lipoprotein, Leukocyte Count, 0302 clinical medicine, Risk Factors, Neoplasms, 030212 general & internal medicine, Stroke, Framingham Risk Score, biology, Smoking, 11 Medical And Health Sciences, General Medicine, Articles, Middle Aged, 3. Good health, C-Reactive Protein, Cholesterol, Regression Analysis, low-density lipoprotein cardiovascular-disease nonvascular mortality regression dilution plasma-fibrinogen mendelian randomization independent predictor prospective cohorts vascular-disease inflammation, Female, Risk assessment, medicine.medical_specialty, Alcohol Drinking, Regression dilution, Motor Activity, Risk Assessment, 03 medical and health sciences, Sex Factors, Cardiovascular-disease, General & Internal Medicine, Internal medicine, Diabetes Mellitus, medicine, Humans, Women, Risk factor, Serum Albumin, Triglycerides, Inflammation, Markers, Independent predictor, Interleukin-6, business.industry, Vascular disease, C-reactive protein, Fibrinogen, medicine.disease, Surgery, Relative risk, biology.protein, Nonvascular mortality, business, Biomarkers
Abstract

Udgivelsesdato: 2010-Jan-9 BACKGROUND: Associations of C-reactive protein (CRP) concentration with risk of major diseases can best be assessed by long-term prospective follow-up of large numbers of people. We assessed the associations of CRP concentration with risk of vascular and non-vascular outcomes under different circumstances. METHODS: We meta-analysed individual records of 160 309 people without a history of vascular disease (ie, 1.31 million person-years at risk, 27 769 fatal or non-fatal disease outcomes) from 54 long-term prospective studies. Within-study regression analyses were adjusted for within-person variation in risk factor levels. RESULTS: Log(e) CRP concentration was linearly associated with several conventional risk factors and inflammatory markers, and nearly log-linearly with the risk of ischaemic vascular disease and non-vascular mortality. Risk ratios (RRs) for coronary heart disease per 1-SD higher log(e) CRP concentration (three-fold higher) were 1.63 (95% CI 1.51-1.76) when initially adjusted for age and sex only, and 1.37 (1.27-1.48) when adjusted further for conventional risk factors; 1.44 (1.32-1.57) and 1.27 (1.15-1.40) for ischaemic stroke; 1.71 (1.53-1.91) and 1.55 (1.37-1.76) for vascular mortality; and 1.55 (1.41-1.69) and 1.54 (1.40-1.68) for non-vascular mortality. RRs were largely unchanged after exclusion of smokers or initial follow-up. After further adjustment for fibrinogen, the corresponding RRs were 1.23 (1.07-1.42) for coronary heart disease; 1.32 (1.18-1.49) for ischaemic stroke; 1.34 (1.18-1.52) for vascular mortality; and 1.34 (1.20-1.50) for non-vascular mortality. INTERPRETATION: CRP concentration has continuous associations with the risk of coronary heart disease, ischaemic stroke, vascular mortality, and death from several cancers and lung disease that are each of broadly similar size. The relevance of CRP to such a range of disorders is unclear. Associations with ischaemic vascular disease depend considerably on conventional risk factors and other markers of inflammation. FUNDING: British Heart Foundation, UK Medical Research Council, BUPA Foundation, and GlaxoSmithKline.

Published
2010
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10. Emerging Risk Factors Collaboration. Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies

Author

hompson S, Kaptoge S, White I, Wood A, Thompson SG, White IR, Wood AM, Perry PL, Danesh J, Tipping RW, Ford CE, Simpson LM, Walldius G, Jungner I, Chambless LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Goldbourt U, Benderly M, Tanne D, Whincup PH, Wannamethee SG, Morris RW, Willeit J, Kiechl S, Santer P, Mayr A, Lawlor DA, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, Cushman M, Tracy RP, Tybjærg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Giampaoli S, Palmieri L, Vanuzzo D, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Taylor J, Guralnik JM, Wallace R, Guralnik J, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Lappas G, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Kiyohara Y, Arima H, Doi Y, Ninomiya T, Rodriguez B, Dekker JM, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Tuomainen TP, Deeg DJ, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engstrom G, Verschuren WM, Blokstra A, Shea S, Döring A, Koenig W, Meisinger C, Mraz W, Bas Bueno de Mesquita H, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson JE, Knottenbelt C, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Crespo CJ, Garcia MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Packard CJ, Sattar N, Ford I, Cantin B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe GD, Ben Shlomo Y, Davey Smith G, Howard BV, Zhang Y, Umans J, Onat A, Wilsgaard T, Ingelsson E, Lind L, Giedraitis V, Lannfelt L, Gaziano JM, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Wassertheil Smoller S, Marmot M, Clarke R, Collins R, Brunner E, Shipley M, Buring J, Cobbe SM, Robertson M, He Y, Marín Ibañez A, Feskens EJ, Kromhout D, Di Angelantonio E, Erqou S, Lewington S, Orfei L, Pennells L, Ray KK, Sarwar N, Alexander M, Thompson A, Walker M, Watson S, Wensley F, Perry P, Danesh J., PANICO, SALVATORE, Hompson, S, Kaptoge, S, White, I, Wood, A, Thompson, Sg, White, Ir, Wood, Am, Perry, Pl, Danesh, J, Tipping, Rw, Ford, Ce, Simpson, Lm, Walldius, G, Jungner, I, Chambless, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Goldbourt, U, Benderly, M, Tanne, D, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Tracy, Rp, Tybjærg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Taylor, J, Guralnik, Jm, Wallace, R, Guralnik, J, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Lappas, G, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engstrom, G, Verschuren, Wm, Blokstra, A, Shea, S, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bas Bueno de Mesquita, H, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, Je, Knottenbelt, C, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Crespo, Cj, Garcia, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, Cj, Sattar, N, Ford, I, Cantin, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Ben Shlomo, Y, Davey Smith, G, Howard, Bv, Zhang, Y, Umans, J, Onat, A, Wilsgaard, T, Ingelsson, E, Lind, L, Giedraitis, V, Lannfelt, L, Gaziano, Jm, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Wassertheil Smoller, S, Marmot, M, Clarke, R, Collins, R, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Robertson, M, He, Y, Marín Ibañez, A, Feskens, Ej, Kromhout, D, Di Angelantonio, E, Erqou, S, Lewington, S, Orfei, L, Pennells, L, Ray, Kk, Sarwar, N, Alexander, M, Thompson, A, Walker, M, Watson, S, Wensley, F, Perry, P, and Danesh, J.

Published
2010

11. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality

Author

Emerging Risk Factors Collaboration, Erqou S, Kaptoge S, Perry PL, Di Angelantonio E, Thompson A, White IR, Marcovina SM, Collins R, Thompson SG, Tipping RW, Ford CE, Simpson LM, Walldius G, Jungner I, Folsom AR, Chambless L, Panagiotakos D, Pitsavos C, Chrysohoou C, Stefanadis C, Goldbourt U, Benderly M, Tanne D, Whincup P, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Santer P, Mayr A, Wald N, Ebrahim S, Lawlor D, Yarnell J, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Cushman M, Psaty BM, Tracy R, Tybjaerg Hansen A, Nordestgaard BG, Frikke Schmidt R, Kamstrup PR, Giampaoli S, Palmieri L, Vanuzzo D, Pilotto L, Gómez de la Cámara A, Gómez Gerique JA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee A, Smith FB, Taylor J, Guralnik JM, Phillips CL, Wallace RB, Blazer DG, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Wolf PA, Vasan RS, Pencina MJ, Bladbjerg EM, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Rosengren A, Wilhelmsen L, Lappas G, Eriksson H, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Tilvis RS, Strandberg TE, Rodriguez B, Dekker J, Nijpels G, Stehouwer CD, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Salonen JT, Nyyssönen K, Tuomainen TP, Deeg DJ, Poppelaars JL, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Döring A, Koenig W, Meisinger C, Mraz W, Bueno de Mesquita HB, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum RF, Mussolino M, Hankinson S, Manson JE, Cooper JA, Bauer KA, Naito Y, Holme I, Nakagawa H, Miura K, Ducimetiere P, Jouven X, Luc G, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrieres J, Schulte H, Assmann G, Shepherd J, Packard CJ, Sattar N, Ford I, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Daniels LB, Laughlin GA, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler MM, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe G, Ben Shlomo Y, Davey Smith G, Howard BV, Zhang Y, Best L, Umans J, Onat A, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Ingelsson E, Sundström J, Lind L, Lannfelt L, Gaziano JM, Stampfer M, Ridker PM, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Marmot M, Clarke R, Fletcher A, Brunner E, Shipley M, Buring J, Cobbe S, Robertson M, He Y, Marin Ibanñez A, Feskens E, Kromhout D, Walker M, Watson S, Lewington S, Orfei L, Pennells L, Ray KK, Sarwar N, Alexander M, Wensley F, Wood AM, Danesh J., PANICO, SALVATORE, Developmental Genetics, EMGO+ - Lifestyle, Overweight and Diabetes, Emerging Risk Factors, Collaboration, Erqou, S, Kaptoge, S, Perry, Pl, Di Angelantonio, E, Thompson, A, White, Ir, Marcovina, Sm, Collins, R, Thompson, Sg, Tipping, Rw, Ford, Ce, Simpson, Lm, Walldius, G, Jungner, I, Folsom, Ar, Chambless, L, Panagiotakos, D, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Goldbourt, U, Benderly, M, Tanne, D, Whincup, P, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, D, Yarnell, J, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Cushman, M, Psaty, Bm, Tracy, R, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Kamstrup, Pr, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Gómez de la Cámara, A, Gómez Gerique, Ja, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, A, Smith, Fb, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, Rb, Blazer, Dg, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, Te, Rodriguez, B, Dekker, J, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, Dj, Poppelaars, Jl, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bueno de Mesquita, Hb, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, Rf, Mussolino, M, Hankinson, S, Manson, Je, Cooper, Ja, Bauer, Ka, Naito, Y, Holme, I, Nakagawa, H, Miura, K, Ducimetiere, P, Jouven, X, Luc, G, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, Cj, Sattar, N, Ford, I, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Daniels, Lb, Laughlin, Ga, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, Mm, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, G, Ben Shlomo, Y, Davey Smith, G, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Ingelsson, E, Sundström, J, Lind, L, Lannfelt, L, Gaziano, Jm, Stampfer, M, Ridker, Pm, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Marmot, M, Clarke, R, Fletcher, A, Brunner, E, Shipley, M, Buring, J, Cobbe, S, Robertson, M, He, Y, Marin Ibanñez, A, Feskens, E, Kromhout, D, Walker, M, Watson, S, Lewington, S, Orfei, L, Pennells, L, Ray, Kk, Sarwar, N, Alexander, M, Wensley, F, Wood, Am, and Danesh, J.

Subjects
medicine.medical_specialty, Context (language use), Coronary Disease, Article, Risk Factors, General & Internal Medicine, Internal medicine, Cause of Death, medicine, Humans, Myocardial infarction, Prospective cohort study, Stroke, biology, business.industry, 11 Medical And Health Sciences, General Medicine, Lipoprotein(a), medicine.disease, Surgery, Relative risk, Nested case-control study, biology.protein, business, Cohort study
Abstract

Udgivelsesdato: 2009-Jul-22 CONTEXT: Circulating concentration of lipoprotein(a) (Lp[a]), a large glycoprotein attached to a low-density lipoprotein-like particle, may be associated with risk of coronary heart disease (CHD) and stroke. OBJECTIVE: To assess the relationship of Lp(a) concentration with risk of major vascular and nonvascular outcomes. STUDY SELECTION: Long-term prospective studies that recorded Lp(a) concentration and subsequent major vascular morbidity and/or cause-specific mortality published between January 1970 and March 2009 were identified through electronic searches of MEDLINE and other databases, manual searches of reference lists, and discussion with collaborators. DATA EXTRACTION: Individual records were provided for each of 126,634 participants in 36 prospective studies. During 1.3 million person-years of follow-up, 22,076 first-ever fatal or nonfatal vascular disease outcomes or nonvascular deaths were recorded, including 9336 CHD outcomes, 1903 ischemic strokes, 338 hemorrhagic strokes, 751 unclassified strokes, 1091 other vascular deaths, 8114 nonvascular deaths, and 242 deaths of unknown cause. Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. Analyses excluded participants with known preexisting CHD or stroke at baseline. DATA SYNTHESIS: Lipoprotein(a) concentration was weakly correlated with several conventional vascular risk factors and it was highly consistent within individuals over several years. Associations of Lp(a) with CHD risk were broadly continuous in shape. In the 24 cohort studies, the rates of CHD in the top and bottom thirds of baseline Lp(a) distributions, respectively, were 5.6 (95% confidence interval [CI], 5.4-5.9) per 1000 person-years and 4.4 (95% CI, 4.2-4.6) per 1000 person-years. The risk ratio for CHD, adjusted for age and sex only, was 1.16 (95% CI, 1.11-1.22) per 3.5-fold higher usual Lp(a) concentration (ie, per 1 SD), and it was 1.13 (95% CI, 1.09-1.18) following further adjustment for lipids and other conventional risk factors. The corresponding adjusted risk ratios were 1.10 (95% CI, 1.02-1.18) for ischemic stroke, 1.01 (95% CI, 0.98-1.05) for the aggregate of nonvascular mortality, 1.00 (95% CI, 0.97-1.04) for cancer deaths, and 1.00 (95% CI, 0.95-1.06) for nonvascular deaths other than cancer. CONCLUSION: Under a wide range of circumstances, there are continuous, independent, and modest associations of Lp(a) concentration with risk of CHD and stroke that appear exclusive to vascular outcomes.

Published
2009
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12. The Emerging Risk Factors Collaboration: analysis of individual data on lipid, inflammatory and other markers in over 1.1 million participants in 104 prospective studies of cardiovascular diseases

Author

Danesh, J, Erqou, S, Walker, M, Thompson, Sg, Tipping, R, Ford, C, Pressel, S, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, Edoardo, Tikhonoff, Valerie, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, S, Vanuzzo, D, Pilotto, L, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, J, Phillips, C, Wallace, R, Blazer, D, Khaw, Kt, Jansson, Jh, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, Rs, Pencina, Mj, Bladbjerg, Em, Jorgensen, T, Moller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Bjorkelund, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, T, Rodriguez, B, Bouter, Lm, Heine, Rj, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, J, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, D, Poppelaars, Jl, Meade, T, Cooper, J, Hedblad, B, Berglund, G, Engstrom, G, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Kuller, L, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, De Stavola, B, Knottenbelt, C, Cooper, Ja, Bauer, Ka, Rosenberg, Rd, Naito, Y, Holme, I, Nakagawa, H, Miura, H, Ducimetiere, P, Jouven, X, Crespo, C, Garcia Palmieri, M, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, C, Sattar, N, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, D, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Ben Shlomo, Y, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Meade, Tw, Njolstad, I, Mathiesen, E, Lochen, Ml, Wilsgaard, T, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Rodeghiero, F, Tosetto, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Ford, I, Robertson, M, He, Y, Ibanez, Am, Feskens, Ej, Kromhout, D, Collins, R, Di Angelantonio, E, Kaptoge, S, Lewington, S, Orfei, L, Pennells, L, Perry, P, Ray, K, Sarwar, N, Scherman, M, Thompson, A, Watson, S, Wensley, F, White, Ir, Wood, Am, Emerging Risk Factors Collaboration, Interne Geneeskunde, RS: NUTRIM School of Nutrition and Translational Research in Metabolism, RS: CARIM School for Cardiovascular Diseases, Movement Behavior, Executive board Vrije Universiteit, Clinical Child and Family Studies, Sociology and Social Gerontology, Earth and Climate, Environmental Policy Analysis, Developmental Genetics, Danesh, J, Erqou, S, Walker, M, Thompson, Sg, Tipping, R, Ford, C, Pressel, S, Walldius, G, Jungner, I, Folsom, Ar, Chambless, Le, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Willeit, J, Kiechl, S, Santer, P, Mayr, A, Wald, N, Ebrahim, S, Lawlor, Da, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, Cushman, M, Psaty, Bm, Tracy, Rp, Tybjaerg Hansen, A, Nordestgaard, Bg, Frikke Schmidt, R, Giampaoli, S, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Smith, Fb, Taylor, J, Guralnik, J, Phillips, C, Wallace, R, Blazer, D, Khaw, Kt, Jansson, Jh, Donfrancesco, C, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Wolf, Pa, Vasan, R, Pencina, Mj, Bladbjerg, Em, Jorgensen, T, Moller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Bjorkelund, C, Cremer, P, Nagel, D, Tilvis, R, Strandberg, T, Rodriguez, B, Bouter, Lm, Heine, Rj, Dekker, Jm, Nijpels, G, Stehouwer, Cd, Rimm, E, Pai, J, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Salonen, Jt, Nyyssönen, K, Tuomainen, Tp, Deeg, D, Poppelaars, Jl, Meade, T, Cooper, J, Hedblad, B, Berglund, G, Engstrom, G, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Kuller, L, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, J, De Stavola, B, Knottenbelt, C, Cooper, Ja, Bauer, Ka, Rosenberg, Rd, Naito, Y, Holme, I, Nakagawa, H, Miura, H, Ducimetiere, P, Jouven, X, Crespo, C, Garcia Palmieri, M, Amouyel, P, Arveiler, D, Evans, A, Ferrieres, J, Schulte, H, Assmann, G, Shepherd, J, Packard, C, Sattar, N, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, D, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Ben Shlomo, Y, Howard, Bv, Zhang, Y, Best, L, Umans, J, Onat, A, Meade, Tw, Njolstad, I, Mathiesen, E, Lochen, Ml, Wilsgaard, T, Gaziano, Jm, Stampfer, M, Ridker, P, Ulmer, H, Diem, G, Concin, H, Rodeghiero, F, Tosetto, A, Brunner, E, Shipley, M, Buring, J, Cobbe, Sm, Ford, I, Robertson, M, He, Y, Ibanez, Am, Feskens, Ej, Kromhout, D, Collins, R, Di Angelantonio, E, Kaptoge, S, Lewington, S, Orfei, L, Pennells, L, Perry, P, Ray, K, Sarwar, N, Scherman, M, Thompson, A, Watson, S, Wensley, F, White, Ir, and Wood, A. M.

Subjects
Databases, Factual, Nutrition and Disease, Epidemiology, Inflammatory markers, middle-aged men, Disease, Leukocyte Count, c-reactive protein, Risk Factors, Voeding en Ziekte, adult-treatment-panel, Prospective Studies, Myocardial infarction, Prospective cohort study, education.field_of_study, biology, plasma-fibrinogen, Asia, Eastern, Confounding, density-lipoprotein cholesterol, Cardiovascular disease, Lipids, myocardial-infarction, Coronary heart disease, Cardiovascular Diseases, Meta-analysis, Lipoproteins, HDL, high blood cholesterol, medicine.medical_specialty, low-dose aspirin, Population, 10-year follow-up, SDG 3 - Good Health and Well-being, Albumins, medicine, Humans, education, Triglycerides, VLAG, Inflammation, Estimation, business.industry, C-reactive protein, medicine.disease, Surgery, Emergency medicine, biology.protein, business, coronary-heart-disease, Biomarkers
Abstract

Many long-term prospective studies have reported on associations of cardiovascular diseases with circulating lipid markers and/or inflammatory markers. Studies have not, however, generally been designed to provide reliable estimates under different circumstances and to correct for within-person variability. The Emerging Risk Factors Collaboration has established a central database on over 1.1 million participants from 104 prospective population-based studies, in which subsets have information on lipid and inflammatory markers, other characteristics, as well as major cardiovascular morbidity and cause-specific mortality. Information on repeat measurements on relevant characteristics has been collected in approximately 340,000 participants to enable estimation of and correction for within-person variability. Re-analysis of individual data will yield up to approximately 69,000 incident fatal or nonfatal first ever major cardiovascular outcomes recorded during about 11.7 million person years at risk. The primary analyses will involve age-specific regression models in people without known baseline cardiovascular disease in relation to fatal or nonfatal first ever coronary heart disease outcomes. This initiative will characterize more precisely and in greater detail than has previously been possible the shape and strength of the age-and sex-specific associations of several lipid and inflammatory markers with incident coronary heart disease outcomes (and, secondarily,with other incident cardiovascular outcomes) under a wide range of circumstances. It will, therefore, help to determine to what extent such associations are independent from possible confounding factors and to what extent such markers (separately and in combination) provide incremental predictive value.

Published
2007
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13. A framework for quantifying net benefits of alternative prognostic models

Author

Rapsomaniki, E., White, I. R., Wood, A. M., Thompson, S. G., Tipping, R. W., Ford, C. E., Simpson, L. M., Folsom, A. R., Chambless, L. E., Panagiotakos, D. B., Pitsavos, C., Chrysohoou, C., Stefanadis, C., Knuiman, M., Whincup, P. H., Wannamethee, S. G., Morris, R. W., Kiechl, S., Willeit, J., Oberhollenzer, F., Mayr, A., Wald, N., Lawlor, D. A., Yarnell, J. W., Gallacher, J., Casiglia, E., Tikhonoff, V., Nietert, P. J., Sutherland, S. E., Bachman, D. L., Keil, J. E., Cushman, M., Tracy, R., Tybjaerg-Hansen, A., Nordestgaard, B. G., Frikke-Schmidt, R., Giampaoli, S., Palmieri, L., Panico, S., Vanuzzo, D., Pilotto, L., Gomez de la Camara, A., Gomez Gerique, J. A., Simons, L., Mccallum, J., Friedlander, Y., Lee, A. J., Taylor, J., Guralnik, J. M., Wallace, R., Blazer, D. G., Khaw, K. -T., Schottker, B., Muller, H., Rothenbacher, D., Jansson, J. -H., Wennberg, P., Nissinen, A., Donfrancesco, C., Salomaa, V., Harald, K., Jousilahti, P., Vartiainen, E., Woodward, M., D'Agostino Sr, R. B., Wolf, P. A., Vasan, R. S., Pencina, M. J., Bladbjerg, E. -M., Jorgensen, T., Moller, L., Jespersen, J., Dankner, R., Chetrit, A., Lubin, F., Rosengren, A., Lappas, G., Eriksson, H., Bjorkelund, C., Lissner, L., Bengtsson, C., Nagel, D., Kiyohara, Y., Arima, H., Doi, Y., Ninomiya, T., Rodriguez, B., Dekker, J. M., Nijpels, G., Stehouwer, C. D. A., Iso, H., Kitamura, A., Yamagishi, K., Noda, H., Goldbourt, U., Kauhanen, J., Salonen, J. T., Cooper, J. A., Verschuren, W. M. M., Blokstra, A., Shea, S., Doring, A., Meisinger, C., Bueno-de-Mesquita, H. B., Kuller, L. H., Grandits, G., Gillum, R. F., Mussolino, M., Bauer, K. A., Kirkland, S., Shaffer, J., Korin, M. R., Sato, S., Amouyel, P., Arveiler, D., Evans, A., Ferrieres, J., Schulte, H., Assmann, G., Westendorp, R. G., Buckley, B. M., Packard, C. J., Sattar, N., Cantin, B., Despres, J. -P., Dagenais, G. R., Barrett-Connor, E., Wingard, D. L., Bettencourt, R., Gudnason, V., Aspelund, T., Sigurdsson, G., Thorsson, B., Witteman, J., Kardys, I., Tiemeier, H., Hofman, A., Tunstall-Pedoe, H., Tavendale, R., Lowe, G. D. O., Howard, B. V., Zhang, Y., Best, L., Umans, J., Ben-Shlomo, Y., Davey-Smith, G., Njolstad, I., Wilsgaard, T., Ingelsson, E., Lind, L., Giedraitis, V., Lannfelt, L., Gaziano, J. M., Stampfer, M., Ridker, P., Wassertheil-Smoller, S., Manson, J. E., Marmot, M., Clarke, R., Fletcher, A., Brunner, E., Shipley, M., Buring, J., Shepherd, J., Cobbe, S. M., Ford, I., Robertson, M., Marin Ibanez, A., Feskens, E. J. M., Kromhout, D., Interne Geneeskunde, and RS: CARIM School for Cardiovascular Diseases

Subjects
Nutrition and Disease, Epidemiology, Cost effectiveness, Cost-Benefit Analysis, cardiovascular-disease, Kaplan-Meier Estimate, 01 natural sciences, Health informatics, 010104 statistics & probability, 0302 clinical medicine, cardiovascular disease, Voeding en Ziekte, Econometrics, Medicine, 030212 general & internal medicine, Research Articles, competing risks, validation, Framingham Risk Score, Cost–benefit analysis, coronary heart-disease, Discriminant Analysis, cohort, Prognosis, 3. Good health, Cardiovascular Diseases, Meta-analysis, Risk assessment, metaanalysis, Statistics and Probability, reclassification, Context (language use), risk score, Risk Assessment, screening strategies, statins, 03 medical and health sciences, Meta-Analysis as Topic, Humans, 0101 mathematics, cost-effectiveness, Proportional Hazards Models, VLAG, business.industry, Proportional hazards model, Cardiovascular disease, Competing risks, Cost-effectiveness, Net benefit, Screening strategies, Epidemiologic Research Design, predictive ability, R1, meta-analysis, roc curve, business, net benefit
Abstract

New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks. Copyright © 2011 John Wiley & Sons, Ltd.

Published
2012
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14. Association between C reactive protein and coronary heart disease: mendelian randomisation analysis based on individual participant data

Author

Wensley, F, Gao, P, Burgess, S, Kaptoge, S, Di Angelantonio, E, Shah, T, Engert, JC, Clarke, R, Davey-Smith, G, Nordestgaard, BG, Saleheen, D, Samani, NJ, Sandhu, M, Anand, S, Pepys, MB, Smeeth, L, Whittaker, J, Casas, JP, Thompson, SG, Hingorani, AD, Danesh, J, Eiriksdottir, G, Harris, TB, Launer, LJ, Gudnason, V, Folsom, AR, Andrews, G, Ballantyne, CM, Hall, AS, Braund, PS, Balmforth, AJ, Whincup, PH, Morris, R, Lawlor, DA, Lowe, GDO, Timpson, N, Ebrahim, S, Ben-Shlomo, Y, Tybjaerg-Hansen, A, Zacho, J, Brown, M, Ricketts, SL, Ashford, S, Lange, L, Reiner, A, Cushman, M, Tracy, R, Wu, C, Ge, J, Zou, Y, Sun, A, Hung, J, McQuillan, B, Thompson, P, Beilby, J, Warrington, N, Palmer, LJ, Wanner, C, Drechsler, C, Hoffmann, MM, Fowkes, FGR, Tzoulaki, I, Kumari, M, Miller, M, Marmot, M, Onland-Moret, C, van der Schouw, YT, Boer, JM, Wijmenga, C, Khaw, K-T, Vasan, RS, Schnabel, RB, Yamamoto, JF, Benjamin, EJ, Schunkert, H, Erdmann, J, Koenig, IR, Hengstenberg, C, Chiodini, B, Franzosi, MG, Pietri, S, Gori, F, Rudock, M, Liu, Y, Lohman, K, Humphries, SE, Hamsten, A, Norman, PE, Hankey, GJ, Jamrozik, K, Rimm, EB, Pai, JK, Psaty, BM, Heckbert, SR, Bis, JC, Yusuf, S, Xie, C, Collins, R, Bennett, D, Kooner, J, Chambers, J, Elliott, P, Maerz, W, Kleber, ME, Boehm, BO, Winkelmann, BR, Melander, O, Berglund, G, Koenig, W, Thorand, B, Baumert, J, Peters, A, Manson, J, Cooper, JA, Talmud, PJ, Ladenvall, P, Johansson, L, Jansson, J-H, Hallmans, G, Reilly, MP, Qu, L, Li, M, Rader, DJ, Watkins, H, Hopewell, J, Frossard, P, Sattar, N, Robertson, M, Shepherd, J, Schaefer, E, Hofman, A, Witteman, JCM, Kardys, I, Dehghan, A, de Faire, U, Bennet, A, Gigante, B, Leander, K, Peters, B, Maitland-van der Zee, AH, de Boer, A, Klungel, O, Greenland, P, Dai, J, Liu, S, Brunner, E, Kivimaki, M, O'Reilly, D, Ford, I, Packard, CJ, Dis, CRPCH, CIHDS, CC, CUPID, C, Medical Research Council (MRC), University of Groningen, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Pulmonology, and Coronel Institute of Occupational Health

Subjects
Male, Coronary Disease, Bioinformatics, Gene Frequency, MARKERS, Polymorphism (computer science), Risk Factors, Myocardial infarction, Prospective Studies, Prospective cohort study, General Environmental Science, Genetics, RISK, biology, General Engineering, Mendelian Randomization Analysis, General Medicine, Middle Aged, C-Reactive Protein, 1117 Public Health And Health Services, CARDIOVASCULAR-DISEASE, Meta-analysis, symbols, Female, Life Sciences & Biomedicine, Ischaemic Heart Disease, Polymorphism, Single Nucleotide, Molecular Genetics, symbols.namesake, Medicine, General & Internal, INFLAMMATION, Drugs: Cardiovascular System, General & Internal Medicine, medicine, INSTRUMENTAL VARIABLES, Humans, C Reactive Protein Coronary Heart Disease Genetics Collaboration (CCGC), Allele frequency, METAANALYSIS, POLYMORPHISMS, Science & Technology, business.industry, Research, C-reactive protein, medicine.disease, GENE, MYOCARDIAL-INFARCTION, ATHEROSCLEROSIS, Mendelian inheritance, biology.protein, General Earth and Planetary Sciences, business
Abstract

Objective To use genetic variants as unconfounded proxies of C reactive protein concentration to study its causal role in coronary heart disease. Design Mendelian randomisation meta-analysis of individual participant data from 47 epidemiological studies in 15 countries. Participants 194 418 participants, including 46 557 patients with prevalent or incident coronary heart disease. Information was available on four CRP gene tagging single nucleotide polymorphisms (rs3093077, rs1205, rs1130864, rs1800947), concentration of C reactive protein, and levels of other risk factors. Main outcome measures Risk ratios for coronary heart disease associated with genetically raised C reactive protein versus risk ratios with equivalent differences in C reactive protein concentration itself, adjusted for conventional risk factors and variability in risk factor levels within individuals. Results CRP variants were each associated with up to 30% per allele difference in concentration of C reactive protein (P

Published
2011

15. Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables

Author

Burgess, Stephen, Thompson, Simon G, CRP CHD Genetics Collaboration, Burgess, S, Thompson, SG, Andrews, G, Samani, NJ, Hall, A, Whincup, P, Morris, R, Lawlor, DA, Davey Smith, G, Timpson, N, Ebrahim, S, Ben-Shlomo, Y, Brown, M, Ricketts, S, Sandhu, M, Reiner, A, Psaty, B, Lange, L, Cushman, M, Hung, J, Thompson, P, Beilby, J, Warrington, N, Palmer, LJ, Nordestgaard, BG, Tybjaerg-Hansen, A, Zacho, J, Wu, C, Lowe, G, Tzoulaki, I, Kumari, M, Yamamoto, JF, Chiodini, B, Franzosi, M, Hankey, GJ, Jamrozik, K, Palmer, L, Rimm, E, Pai, J, Heckbert, S, Bis, J, Anand, S, Engert, J, Collins, R, Clarke, R, Melander, O, Berglund, G, Ladenvall, P, Johansson, L, Jansson, J-H, Hallmans, G, Hingorani, A, Humphries, S, Manson, J, Watkins, H, Hopewell, J, Saleheen, D, Frossard, R, Danesh, J, Sattar, N, Robertson, M, Shepherd, J, Schaefer, E, Hofman, A, Witteman, JCM, Kardys, I, de Faire, U, Bennet, A, Ford, I, Packard, C, Lawlor, Debbie A, Davey Smith, George, Casas, JP, Smeeth, L, Wensley, F, Bowden, J, Di Angelantonio, E, Gao, P, Shah, T, Verzilli, C, Walker, M, Whittaker, J, Danesh, John [0000-0003-1158-6791], Sandhu, Manjinder [0000-0002-2725-142X], Burgess, Stephen [0000-0001-5365-8760], Di Angelantonio, Emanuele [0000-0001-8776-6719], Thompson, Simon [0000-0002-5274-7814], and Apollo - University of Cambridge Repository

Subjects
Genetic Markers, C-Reactive Protein, Models, Statistical, Phenotype, Meta-Analysis as Topic, Fibrinogen, Humans, Bayes Theorem, Biostatistics, Polymorphism, Single Nucleotide
Abstract

Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies, in which it is not necessary that the same genetic markers are measured in each study. This provides an overall estimate of the causal relationship between the phenotype and the outcome, and an assessment of its heterogeneity across studies. As an example, we estimate the causal relationship of blood concentrations of C-reactive protein on fibrinogen levels using data from 11 studies. These methods provide a flexible framework for efficient estimation of causal relationships derived from multiple studies. Issues discussed include weak instrument bias, analysis of binary outcome data such as disease risk, missing genetic data, and the use of haplotypes.

Published
2010

16. Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables

Author

Burgess, S, Thompson, SG, Andrews, G, Samani, NJ, Hall, A, Whincup, P, Morris, R, Lawlor, DA, Davey Smith, G, Timpson, N, Ebrahim, S, Ben-Shlomo, Y, Brown, M, Ricketts, S, Sandhu, M, Reiner, A, Psaty, B, Lange, L, Cushman, M, Hung, J, Thompson, P, Beilby, J, Warrington, N, Palmer, LJ, Nordestgaard, BG, Tybjaerg-Hansen, A, Zacho, J, Wu, C, Lowe, G, Tzoulaki, I, Kumari, M, Yamamoto, JF, Chiodini, B, Franzosi, M, Hankey, GJ, Jamrozik, K, Palmer, L, Rimm, E, Pai, J, Heckbert, S, Bis, J, Anand, S, Engert, J, Collins, R, Clarke, R, Melander, O, Berglund, G, Ladenvall, P, Johansson, L, Jansson, JH, Hallmans, G, Hingorani, A, Humphries, S, Manson, J, Watkins, H, Hopewell, J, Saleheen, D, Frossard, R, Danesh, J, Sattar, N, Robertson, M, Shepherd, J, Schaefer, E, Hofman, A, Witteman, JC, Kardys, I, de Faire, U, Bennet, A, Ford, I, Packard, C, Casas, JP, Smeeth, L, Wensley, F, Bowden, J, Di Angelantonio, E, Gao, P, Shah, T, Verzilli, C, Walker, M, and Whittaker, J

Subjects
Genetic Markers, Statistics and Probability, Epidemiology, Bayesian probability, Context (language use), Bayes Theorem, Biostatistics, Polymorphism, Single Nucleotide, Article, Hierarchical database model, Bayes' theorem, Meta-Analysis as Topic, Statistics, Mendelian randomization, Econometrics, Humans, Models, Statistical, Instrumental variable, C-Reactive Protein/genetics/metabolism, Fibrinogen, Regression, Fibrinogen/metabolism, C-Reactive Protein, Phenotype, Meta-analysis
Abstract

Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies, in which it is not necessary that the same genetic markers are measured in each study. This provides an overall estimate of the causal relationship between the phenotype and the outcome, and an assessment of its heterogeneity across studies. As an example, we estimate the causal relationship of blood concentrations of C-reactive protein on fibrinogen levels using data from 11 studies. These methods provide a flexible framework for efficient estimation of causal relationships derived from multiple studies. Issues discussed include weak instrument bias, analysis of binary outcome data such as disease risk, missing genetic data, and the use of haplotypes. Stat Med

Published
2010

17. Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies

Author

Thompson, S. Kaptoge, S. White, I. Wood, A. Perry, P. Danesh, J. The Emerging Risk Factors Collaboration Thompson, S.G. Kaptoge, S. White, I.R. Wood, A.M. Perry, P.L. Tipping, R.W. Ford, C.E. Simpson, L.M. Walldius, G. Jungner, I. Chambless, L.E. Panagiotakos, D.B. Pitsavos, C. Chrysohoou, C. Stefanadis, C. Knuiman, M. Goldbourt, U. Benderly, M. Tanne, D. Whincup, P.H. Wannamethee, S.G. Morris, R.W. Willeit, J. Kiechl, S. Santer, P. Mayr, A. Lawlor, D.A. Yarnell, J.W.G. Gallacher, J. Casiglia, E. Tikhonoff, V. Nietert, P.J. Sutherland, S.E. Bachman, D.L. Keil, J.E. Cushman, M. Tracy, R.P. Tybjærg-Hansen, A. Nordestgaard, B.G. Benn, M. Frikke- Schmidt, R. Giampaoli, S. Palmieri, L. Panico, S. Vanuzzo, D. Gómez de la Cámara, A. Gómez- Gerique, J.A. Simons, L. McCallum, J. Friedlander, Y. Fowkes, F.G.R. Lee, A.J. Taylor, J. Guralnik, J.M. Wallace, R. Guralnik, J. Blazer, D.G. Guralnik, J.M. Guralnik, J.M. Khaw, K.-T. Brenner, H. Raum, E. Müller, H. Rothenbacher, D. Jansson, J.H. Wennberg, P. Nissinen, A. Donfrancesco, C. Salomaa, V. Harald, K. Jousilahti, P. Vartiainen, E. Woodward, M. D'Agostino, R.B. Vasan, R.S. Pencina, M.J. Bladbjerg, E.M. Jørgensen, T. Jespersen, J. Møller, L. Dankner, R. Chetrit, A. Lubin, F. Rosengren, A. Lappas, G. Björkelund, C. Lissner, L. Bengtsson, C. Cremer, P. Nagel, D. Tilvis, R.S. Strandberg, T.E. Kiyohara, Y. Arima, H. Doi, Y. Ninomiya, T. Rodriguez, B. Dekker, J.M. Nijpels, G. Stehouwer, C.D.A. Rimm, E. Pai, J.K. Sato, S. Kitamura, A. Iso, H. Goldbourt, U. Noda, H. Harald, K. Jousilahti, P. Vartiainen, E. Salonen, J.T. Tuomainen, T.-P. Deeg, D.J.H. Poppelaars, J.L. Meade, T.W. Cooper, J.A. Hedblad, B. Berglund, G. Engstrom, G. Verschuren, W.M.M. Blokstra, A. Cushman, M. Shea, S. Döring, A. Koenig, W. Meisinger, C. Mraz, W. Bas Bueno-de-Mesquita, H. Kuller, L.H. Grandits, G. Selmer, R. Tverdal, A. Nystad, W. Gillum, R. Mussolino, M. Rimm, E. Manson, J.E. Pai, J.K. Meade, T.W. Cooper, J.A. Cooper, J.A. Knottenbelt, C. Bauer, K.A. Naito, Y. Holme, I. Hankinson, S. Tverdal, A. Nystad, W. Nakagawa, H. Miura, K. Ducimetiere, P. Jouven, X. Crespo, C.J. Garcia Palmieri, M.R. Amouyel, P. Arveiler, D. Evans, A. Ferrieres, J. Schulte, H. Assmann, G. Shepherd, J. Packard, C.J. Sattar, N. Ford, I. Cantin, B. Després, J.-P. Dagenais, G.R. Barrett-Connor, E. Wingard, D.L. Bettencourt, R. Gudnason, V. Aspelund, T. Sigurdsson, G. Thorsson, B. Trevisan, M. Witteman, J. Kardys, I. Breteler, M. Hofman, A. Tunstall-Pedoe, H. Tavendale, R. Lowe, G.D.O. Ben-Shlomo, Y. Howard, B.V. Zhang, Y. Umans, J. Onat, A. Davey-Smith, G. Wilsgaard, T. Ingelsson, E. Lind, L. Giedraitis, V. Lannfelt, L. Gaziano, J.M. Ridker, P. Gaziano, J.M. Ridker, P. Ulmer, H. Diem, G. Concin, H. Tosetto, A. Rodeghiero, F. Wassertheil-Smoller, S. Manson, J.E. Marmot, M. Clarke, R. Collins, R. Brunner, E. Shipley, M. Ridker, P. Buring, J. Shepherd, J. Cobbe, S.M. Robertson, M. He, Y. Marín Ibañez, A. Feskens, E.J.M. Kromhout, D. Collins, R. Di Angelantonio, E. Erqou, S. Kaptoge, S. Lewington, S. Orfei, L. Pennells, L. Perry, P.L. Ray, K.K. Sarwar, N. Alexander, M. Thompson, A. Thompson, S.G. Walker, M. Watson, S. Wensley, F. White, I.R. Wood, A.M.

Abstract

Background Meta-analysis of individual participant time-to-event data from multiple prospective epidemiological studies enables detailed investigation of exposure-risk relationships, but involves a number of analytical challenges. Methods This article describes statistical approaches adopted in the Emerging Risk Factors Collaboration, in which primary data from more than 1 million participants in more than 100 prospective studies have been collated to enable detailed analyses of various risk markers in relation to incident cardiovascular disease outcomes. Results Analyses have been principally based on Cox proportional hazards regression models stratified by sex, undertaken in each study separately. Estimates of exposure-risk relationships, initially unadjusted and then adjusted for several confounders, have been combined over studies using meta-analysis. Methods for assessing the shape of exposure-risk associations and the proportional hazards assumption have been developed. Estimates of interactions have also been combined using meta-analysis, keeping separate within-and between-study information. Regression dilution bias caused by measurement error and within-person variation in exposures and confounders has been addressed through the analysis of repeat measurements to estimate corrected regression coefficients. These methods are exemplified by analysis of plasma fibrinogen and risk of coronary heart disease, and Stata code is made available. Conclusion Increasing numbers of meta-analyses of individual participant data from observational data are being conducted to enhance the statistical power and detail of epidemiological studies. The statistical methods developed here can be used to address the needs of such analyses. © The Author 2010; all rights reserved.

Published
2010

18. Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality

Author

Tipping, R.W. Ford, C.E. Simpson, L.M. Walldius, G. Jungner, I. Folsom, A.R. Chambless, L. Panagiotakos, D. Pitsavos, C. Chrysohoou, C. Stefanadis, C. Goldbourt, U. Benderly, M. Tanne, D. Whincup, P. Wannamethee, S.G. Morris, R.W. Kiechl, S. Willeit, J. Santer, P. Mayr, A. Wald, N. Ebrahim, S. Lawlor, D. Yarnell, J. Gallacher, J. Casiglia, E. Tikhonoff, V. Nietert, P.J. Sutherland, S.E. Bachman, D.L. Cushman, M. Psaty, B.M. Tracy, R. Tybjærg-Hansen, A. Nordestgaard, B.G. Frikke-Schmidt, R. Kamstrup, P.R. Giampaoli, S. Palmieri, L. Panico, S. Vanuzzo, D. Pilotto, L. De La Cámara, A.G. Gómez Gerique, J.A. Simons, L. McCallum, J. Friedlander, Y. Fowkes, F.G.R. Lee, A. Smith, F.B. Taylor, J. Guralnik, J.M. Phillips, C.L. Wallace, R.B. Blazer, D.G. Brenner, H. Raum, E. Müller, H. Rothenbacher, D. Jansson, J.-H. Wennberg, P. Nissinen, A. Donfrancesco, C. Salomaa, V. Harald, K. Jousilahti, P. Vartiainen, E. Woodward, M. D’Agostino, R.B. Wolf, P.A. Vasan, R.S. Pencina, M.J. Bladbjerg, E.-M. Jørgensen, T. Møller, L. Jespersen, J. Dankner, R. Chetrit, A. Lubin, F. Rosengren, A. Wilhelmsen, L. Lappas, G. Eriksson, H. Björkelund, C. Lissner, L. Bengtsson, C. Cremer, P. Nagel, D. Tilvis, R.S. Strandberg, T.E. Rodriguez, B. Dekker, J. Nijpels, G. Stehouwer, C.D.A. Rimm, E. Pai, J.K. Sato, S. Iso, H. Kitamura, A. Noda, H. Salonen, J.T. Nyyssönen, K. Tuomainen, T.-P. Deeg, D.J.H. Poppelaars, J.L. Hedblad, B. Berglund, G. Engström, G. Verschuren, W.M.M. Blokstra, A. Döring, A. Koenig, W. Meisinger, C. Mraz, W. Bueno-De-Mesquita, H.B. Kuller, L.H. Grandits, G. Selmer, R. Tverdal, A. Nystad, W. Gillum, R.F. Mussolino, M. Hankinson, S. Manson, J.E. Cooper, J.A. Bauer, K.A. Naito, Y. Holme, I. Nakagawa, H. Miura, K. Ducimetiere, P. Jouven, X. Luc, G. Crespo, C.J. Garcia Palmieri, M.R. Amouyel, P. Arveiler, D. Evans, A. Ferrieres, J. Schulte, H. Assmann, G. Shepherd, J. Packard, C.J. Sattar, N. Ford, I. Cantin, B. Lamarche, B. Després, J.-P. Dagenais, G.R. Barrett-Connor, E. Daniels, L.B. Laughlin, G.A. Gudnason, V. Aspelund, T. Sigurdsson, G. Thorsson, B. Trevisan, M. Witteman, J. Kardys, I. Breteler, M.M.B. Hofman, A. Tunstall-Pedoe, H. Tavendale, R. Lowe, G. Ben-Shlomo, Y. Davey-Smith, G. Howard, B.V. Zhang, Y. Best, L. Umans, J. Onat, A. Njølstad, I. Mathiesen, E.B. Løchen, M.-L. Wilsgaard, T. Ingelsson, E. Sundström, J. Lind, L. Lannfelt, L. Gaziano, J.M. Stampfer, M. Ridker, P.M. Ulmer, H. Diem, G. Concin, H. Tosetto, A. Rodeghiero, F. Marmot, M. Clarke, R. Collins, R. Fletcher, A. Brunner, E. Shipley, M. Buring, J. Cobbe, S. Robertson, M. He, Y. Ibañez, A.M. Feskens, E. Kromhout, D. Walker, M. Watson, S. Di Angelantonio, E. Erqou, S. Kaptoge, S. Lewington, S. Orfei, L. Pennells, L. Perry, P.L. Ray, K.K. Sarwar, N. Alexander, M. Thompson, A. Thompson, S.G. Wensley, F. White, I.R. Wood, A.M. Danesh, J.

Abstract

Context Circulating concentration of lipoprotein(a) (Lp[a]), a large glycoprotein attached to a low-density lipoprotein–like particle, may be associated with risk of coronary heart disease (CHD) and stroke. Objective To assess the relationship of Lp(a) concentration with risk of major vascular and nonvascular outcomes. Study Selection Long-term prospective studies that recorded Lp(a) concentration and subsequent major vascular morbidity and/or cause-specific mortality published between January 1970 and March 2009 were identified through electronic searches of MEDLINE and other databases, manual searches of reference lists, and discussion with collaborators. Data Extraction Individual records were provided for each of 126 634 participants in 36 prospective studies. During 1.3 million person-years of follow-up, 22 076 firstever fatal or nonfatal vascular disease outcomes or nonvascular deaths were recorded, including 9336 CHD outcomes, 1903 ischemic strokes, 338 hemorrhagic strokes, 751 unclassified strokes, 1091 other vascular deaths, 8114 nonvascular deaths, and 242 deaths of unknown cause. Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. Analyses excluded participants with known preexisting CHD or stroke at baseline. Data Synthesis Lipoprotein(a) concentration was weakly correlated with several conventional vascular risk factors and it was highly consistent within individuals over several years. Associations of Lp(a) with CHD risk were broadly continuous in shape. In the 24 cohort studies, the rates of CHD in the top and bottom thirds of baseline Lp(a) distributions, respectively, were 5.6 (95% confidence interval [CI], 5.4-5.9) per 1000 personyears and 4.4 (95% CI, 4.2-4.6) per 1000 person-years. The risk ratio for CHD, adjusted for age and sex only, was 1.16 (95% CI, 1.11-1.22) per 3.5-fold higher usual Lp(a) concentration (ie, per 1 SD), and it was 1.13 (95% CI, 1.09-1.18) following further adjustment for lipids and other conventional risk factors. The corresponding adjusted risk ratios were 1.10 (95% CI, 1.02-1.18) for ischemic stroke, 1.01 (95% CI, 0.98-1.05) for the aggregate of nonvascular mortality, 1.00 (95% CI, 0.97-1.04) for cancer deaths, and 1.00 (95% CI, 0.95-1.06) for nonvascular deaths other than cancer. Conclusion Under a wide range of circumstances, there are continuous, independent, and modest associations of Lp(a) concentration with risk of CHD and stroke that appear exclusive to vascular outcomes. ©2009 American Medical Association. All rights reserved.

Published
2009

19. Collaborative meta-analysis of individual participant data from observationalstudies of Lp-PLA2 and cardiovascular diseases

Author

THE LP PLA STUDIES COLLABORATION, Ballantyne, C, Cushman, M, Psaty, B, Furberg, C, Khaw, Kt, Sandhu, M, Oldgren, J, Rossi, Gianpaolo, Maiolino, G, Cesari, M, Lenzini, Livia, James, Sk, Rimm, E, Collins, R, Anderson, J, Koenig, W, Brenner, H, Rothenbacher, D, Berglund, G, Persson, M, Berger, P, Brilakis, E, Mcconnell, Jp, Sacco, R, Elkind, M, Talmud, P, Cannon, Cp, Packard, C, BARRETT CONNOR, E, Hofman, A, Kardys, I, Witteman, Jc, Criqui, M, Corsetti, Jp, Rainwater, Dl, Moss, Aj, Robins, S, Bloomfield, H, Collins, D, WASSERTHEIL SMOLLER, S, Ridker, P, Danesh, J, Gu, D, Nelson, Jj, Thompson, S, Zalewski, A, Zariffa, N, DI ANGELANTONIO, E, Kaptoge, S, Thompson, A, Walker, M, Watson, S, and Wood, A.

Published
2007

21. A Common Polymorphism in the Complement Factor H Gene Is Associated With Increased Risk of Myocardial Infarction: The Rotterdam Study

Author

Kardys, I., Klaver, C.C.W., Despriet, D.D.G., Bergen, A.A.B., Uitterlinden, A.G., Hofman, A., Oostra, B.A., Duijn, C.M. van, de Jong, P.T.V.M., Witteman, J.C.M., and Netherlands Institute for Neuroscience (NIN)

Abstract

OBJECTIVES: This study was designed to investigate the association between a common polymorphism (Tyr402His, rs1061170) in the complement factor H (CFH) gene and risk of coronary heart disease. BACKGROUND: The evidence that inflammation is an important mechanism in atherogenesis is growing. C-reactive protein (CRP), complement factors, and complement regulatory factors have all been linked to coronary heart disease. The CFH gene is an important regulator of the alternative complement cascade. We investigated its association with coronary heart disease. METHODS: The study was embedded in the Rotterdam Study, a prospective population-based study among men and women aged 55 years and over. A total of 5,520 participants without history of coronary heart disease was genotyped for the Tyr402His polymorphism of the CFH gene. Cox proportional hazards analysis was used to determine risk of myocardial infarction for Tyr402His genotypes. RESULTS: Mean age among participants was 69.5 years (SD 9.1 years). The overall frequency of the His allele was 36%; genotype frequencies were 41%, 45%, and 14% for TyrTyr, TyrHis, and HisHis, respectively. During a mean follow-up period of 8.4 years, 226 myocardial infarctions occurred. After adjustment for age, gender, established cardiovascular risk factors, and CRP level, HisHis homozygotes had a hazard ratio of 1.77 (95% confidence interval 1.23 to 2.55) for myocardial infarction. Total cholesterol level, diabetes mellitus, and smoking modified the effect. The Tyr402His polymorphism was not associated with established cardiovascular risk factors or CRP level. CONCLUSIONS: Our data suggest that the CFH gene determines susceptibility to myocardial infarction. This finding underscores the importance of the alternative complement system in cardiovascular disease.

Published
2006

22. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies

Author

Emerging Risk Factors Collaboration, Sarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, Di Angelantonio E, Ingelsson E, Lawlor DA, Selvin E, Stampfer M, Stehouwer CD, Lewington S, Pennells L, Thompson A, Sattar N, White IR, Ray KK, Danesh J. Tipping RW, Ford CE, Pressel SL, Folsom AR, Chambless LE, Wagenknecht LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Whincup PH, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Oberhollenzer F, Mayr A, Wald N, Ebrahim S, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, de Boer IH, Kizer JR, Mukamal KJ, Tybjaerg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Palmieri L, Vanuzzo D, Pilotto L, de la Cámara AG, Rubio MA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Taylor J, Guralnik JM, Phillips CL, Wallace R, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Giampaoli S, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Vasan RS, Fox CS, Pencina MJ, Bladbjerg E, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Wilhelmsen L, Eriksson H, Svärdsudd K, Welin L, Rosengren A, Lappas G, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Strandberg TE, Tilvis RS, Miettinen TA, Kiyohara Y, Arima H, Doi Y, Ninomiya T, Rodriguez B, Dekker JM, Nijpels G, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Goldbourt U, Nyyssönen K, Tuomainen TP, Salonen JT, Deeg D, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Cushman M, Psaty BM, Shea S, Döring A, Koenig W, Meisinger C, Mraz W, Bueno de Mesquita HB, Fletcher A, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson JE, Bauer KA, Davidson KW, Kirkland S, Shaffer J, Korin MR, Holme I, Ducimetiere P, Jouven X, Bakker SJ, Gansevoort RT, Hillege HL, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrières J, Schulte H, Assmann G, Westendorp RG, Buckley BM, Packard CJ, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe GD, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Hergenç G, Can G, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Zethelius B, Risérus U, Berne C, Gaziano JM, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Tinker L, Liu S, Marmot IM, Clarke R, Collins R, Brunner E, Shipley M, Buring J, Shepherd J, Cobbe SM, Ford I, Robertson M, Ibañez AM, Feskens EJ, Kromhout D, Walker M, Watson S, Alexander M, Erqou S, Haycock P, Perry PL, Thompson SG, Wood AM, Wormser D, Danesh J., PANICO, SALVATORE, Interne Geneeskunde, RS: NUTRIM - R1 - Metabolic Syndrome, RS: CARIM School for Cardiovascular Diseases, Emerging Risk Factors, Collaboration, Sarwar, N, Gao, P, Seshasai, Sr, Gobin, R, Kaptoge, S, Di Angelantonio, E, Ingelsson, E, Lawlor, Da, Selvin, E, Stampfer, M, Stehouwer, Cd, Lewington, S, Pennells, L, Thompson, A, Sattar, N, White, Ir, Ray, Kk, Danesh J., Tipping RW, Ford, Ce, Pressel, Sl, Folsom, Ar, Chambless, Le, Wagenknecht, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Oberhollenzer, F, Mayr, A, Wald, N, Ebrahim, S, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, de Boer, Ih, Kizer, Jr, Mukamal, Kj, Tybjaerg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, de la Cámara, Ag, Rubio, Ma, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, R, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Giampaoli, S, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Vasan, R, Fox, C, Pencina, Mj, Bladbjerg, E, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Wilhelmsen, L, Eriksson, H, Svärdsudd, K, Welin, L, Rosengren, A, Lappas, G, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Strandberg, Te, Tilvis, R, Miettinen, Ta, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, Jm, Nijpels, G, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Nyyssönen, K, Tuomainen, Tp, Salonen, Jt, Deeg, D, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Cushman, M, Psaty, Bm, Shea, S, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bueno de Mesquita, Hb, Fletcher, A, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, Je, Bauer, Ka, Davidson, Kw, Kirkland, S, Shaffer, J, Korin, Mr, Holme, I, Ducimetiere, P, Jouven, X, Bakker, Sj, Gansevoort, Rt, Hillege, Hl, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrières, J, Schulte, H, Assmann, G, Westendorp, Rg, Buckley, Bm, Packard, Cj, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Hergenç, G, Can, G, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Zethelius, B, Risérus, U, Berne, C, Gaziano, Jm, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Tinker, L, Liu, S, Marmot, Im, Clarke, R, Collins, R, Brunner, E, Shipley, M, Buring, J, Shepherd, J, Cobbe, Sm, Ford, I, Robertson, M, Ibañez, Am, Feskens, Ej, Kromhout, D, Walker, M, Watson, S, Alexander, M, Erqou, S, Haycock, P, Perry, Pl, Thompson, Sg, Wood, Am, Wormser, D, Danesh, J., and University of Groningen

Subjects
Adult, Blood Glucose, Male, medicine.medical_specialty, PATHOPHYSIOLOGY, 030209 endocrinology & metabolism, Coronary Disease, Disease, 030204 cardiovascular system & hematology, THERAPY, Diabetes Complications, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Diabetes mellitus, Internal medicine, General & Internal Medicine, medicine, Diabetes Mellitus, Humans, CORONARY-HEART-DISEASE, Prospective cohort study, Stroke, Aged, Glucose Metabolism Disorders, business.industry, Vascular disease, MORTALITY, Absolute risk reduction, ASIA-PACIFIC REGION, WOMEN, General Medicine, Fasting, 11 Medical And Health Sciences, Articles, Middle Aged, medicine.disease, Impaired fasting glucose, 3. Good health, Endocrinology, Blood pressure, ATHEROSCLEROSIS, Cardiovascular Diseases, CARDIOVASCULAR-DISEASES, Female, coronary-heart-disease asia-pacific region cardiovascular-diseases task-force pathophysiology atherosclerosis mortality therapy women, business, TASK-FORCE
Abstract

Summary Background Uncertainties persist about the magnitude of associations of diabetes mellitus and fasting glucose concentration with risk of coronary heart disease and major stroke subtypes. We aimed to quantify these associations for a wide range of circumstances. Methods We undertook a meta-analysis of individual records of diabetes, fasting blood glucose concentration, and other risk factors in people without initial vascular disease from studies in the Emerging Risk Factors Collaboration. We combined within-study regressions that were adjusted for age, sex, smoking, systolic blood pressure, and body-mass index to calculate hazard ratios (HRs) for vascular disease. Findings Analyses included data for 698 782 people (52 765 non-fatal or fatal vascular outcomes; 8·49 million person-years at risk) from 102 prospective studies. Adjusted HRs with diabetes were: 2·00 (95% CI 1·83–2·19) for coronary heart disease; 2·27 (1·95–2·65) for ischaemic stroke; 1·56 (1·19–2·05) for haemorrhagic stroke; 1·84 (1·59–2·13) for unclassified stroke; and 1·73 (1·51–1·98) for the aggregate of other vascular deaths. HRs did not change appreciably after further adjustment for lipid, inflammatory, or renal markers. HRs for coronary heart disease were higher in women than in men, at 40–59 years than at 70 years and older, and with fatal than with non-fatal disease. At an adult population-wide prevalence of 10%, diabetes was estimated to account for 11% (10–12%) of vascular deaths. Fasting blood glucose concentration was non-linearly related to vascular risk, with no significant associations between 3·90 mmol/L and 5·59 mmol/L. Compared with fasting blood glucose concentrations of 3·90–5·59 mmol/L, HRs for coronary heart disease were: 1·07 (0·97–1·18) for lower than 3·90 mmol/L; 1·11 (1·04–1·18) for 5·60–6·09 mmol/L; and 1·17 (1·08–1·26) for 6·10–6·99 mmol/L. In people without a history of diabetes, information about fasting blood glucose concentration or impaired fasting glucose status did not significantly improve metrics of vascular disease prediction when added to information about several conventional risk factors. Interpretation Diabetes confers about a two-fold excess risk for a wide range of vascular diseases, independently from other conventional risk factors. In people without diabetes, fasting blood glucose concentration is modestly and non-linearly associated with risk of vascular disease. Funding British Heart Foundation, UK Medical Research Council, and Pfizer.

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25. Collaborative meta-analysis of individual participant data from observational studies of Lp-PLA(2) and cardiovascular diseases

Author

Ballantyne, C., Cushman, M., Psaty, B., Furberg, C., Khaw, K. T., Sandhu, M., Oldgren, J., Rossi, G. P., Maiolino, G., Cesari, M., Lenzini, L., James, S. K., Rimm, E., Collins, R., Anderson, J., Koenig, W., Hermann Brenner, Rothenbacher, D., Berglund, G., Persson, M., Berger, P., Brilakis, E., Mcconnell, J. P., Sacco, R., Elkind, M., Talmud, P., Cannon, C. P., Packard, C., Barrett-Connor, E., Hofman, A., Kardys, I., Witteman, J. C. M., Criqui, M., Corsetti, J. P., Rainwater, D. L., Moss, A. J., Robins, S., Bloomfield, H., Collins, D., Ridker, P., Danesh, J., Gu, D., Nelson, J. J., Thompson, S., Zalewski, A., Di Angelantonio, E., Kaptoge, S., Thompson, A., Watson, S., and Wood, A.

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