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1. Dietary fatty acids and endometrial cancer risk within the European Prospective Investigation into Cancer and Nutrition

Author

Yammine, S. G., Huybrechts, I., Biessy, C., Dossus, L., Panico, S., Sánchez, M. J., Benetou, V., Turzanski-Fortner, R., Katzke, V., Idahl, A., Skeie, G., Olsen, K. Standahl, Tjønneland, A., Halkjaer, J., Colorado-Yohar, S., Heath, A. K., Sonestedt, E., Sartor, H., Schulze, M. B., Palli, D., Crous-Bou, M., Dorronsoro, A., Overvad, K., Gurrea, A. Barricarte, Severi, G., Vermeulen, R. C.H., Sandanger, T. M., Travis, R. C., Key, T., Amiano, P., Van Guelpen, B., Johansson, M., Sund, M., Tumino, R., Wareham, N., Sacerdote, C., Krogh, V., Brennan, P., Riboli, E., Weiderpass, E., Gunter, M. J., and Chajès, V.

Published
2023
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4. The role of plasma microseminoprotein-beta in prostate cancer: an observational nested case–control and Mendelian randomization study in the European prospective investigation into cancer and nutrition

Author

Smith Byrne, K., Appleby, P.N., Key, T.J., Holmes, M.V., Fensom, G.K., Agudo, A., Ardanaz, E., Boeing, H., Bueno-de-Mesquita, H.B., Chirlaque, M.D., Kaaks, R., Larrañaga, N., Palli, D., Perez-Cornago, A., Quirós, J.R., Ricceri, F., Sánchez, M.J., Tagliabue, G., Tsilidis, K.K., Tumino, R., Fortner, R.T., Ferrari, P., Riboli, E., Lilja, H., and Travis, R.C.

Published
2019
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6. Dietary intake of acrylamide and endometrial cancer risk in the European Prospective Investigation into Cancer and Nutrition cohort

Author

Obón-Santacana, M, Kaaks, R, Slimani, N, Lujan-Barroso, L, Freisling, H, Ferrari, P, Dossus, L, Chabbert-Buffet, N, Baglietto, L, Fortner, RT, Boeing, H, Tjønneland, A, Olsen, A, Overvad, K, Menéndez, V, Molina-Montes, E, Larrañaga, N, Chirlaque, M-D, Ardanaz, E, Khaw, K-T, Wareham, N, Travis, RC, Lu, Y, Merritt, MA, Trichopoulou, A, Benetou, V, Trichopoulos, D, Saieva, C, Sieri, S, Tumino, R, Sacerdote, C, Galasso, R, Bueno-de-Mesquita, HB, Wirfält, E, Ericson, U, Idahl, A, Ohlson, N, Skeie, G, Gram, IT, Weiderpass, E, Onland-Moret, NC, Riboli, E, and Duell, EJ

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Nutrition, Clinical Research, Prevention, Cancer, Aetiology, 2.2 Factors relating to the physical environment, Cardiovascular, Acrylamide, Cohort Studies, Diet, Eating, Endometrial Neoplasms, Female, Humans, Middle Aged, Nutritional Status, Prospective Studies, Risk, Risk Factors, Smoking, acrylamide, endometrial cancer, type-I endometrial cancer, cohort, nutrition, Oncology and Carcinogenesis, Public Health and Health Services, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundThree prospective studies have evaluated the association between dietary acrylamide intake and endometrial cancer (EC) risk with inconsistent results. The objective of this study was to evaluate the association between acrylamide intake and EC risk: for overall EC, for type-I EC, and in never smokers and never users of oral contraceptives (OCs). Smoking is a source of acrylamide, and OC use is a protective factor for EC risk.MethodsCox regression was used to estimate hazard ratios (HRs) for the association between acrylamide intake and EC risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Acrylamide intake was estimated from the EU acrylamide monitoring database, which was matched with EPIC questionnaire-based food consumption data. Acrylamide intake was energy adjusted using the residual method.ResultsNo associations were observed between acrylamide intake and overall EC (n=1382) or type-I EC risk (n=627). We observed increasing relative risks for type-I EC with increasing acrylamide intake among women who both never smoked and were non-users of OCs (HRQ5vsQ1: 1.97, 95% CI: 1.08-3.62; likelihood ratio test (LRT) P-value: 0.01, n=203).ConclusionsDietary intake of acrylamide was not associated with overall or type-I EC risk; however, positive associations with type I were observed in women who were both non-users of OCs and never smokers.

Published
2014

7. LB1740 Role of host epigenetics with skin microbiome in atopic dermatitis

Author

Yew, Y., primary, Tay, D., additional, Lim, S., additional, Wearne, S.J., additional, Mina, T., additional, Riboli, E., additional, Lee, E., additional, Lee, J., additional, Ngeow, J., additional, Elliott, P., additional, Thng, S.T., additional, Common, J.E., additional, Chambers, J., additional, and Loh, M., additional

Published
2023
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8. A prospective evaluation of plasma phospholipid fatty acids and breast cancer risk in the EPIC study

Author

Chajès, V., Assi, N., Biessy, C., Ferrari, P., Rinaldi, S., Slimani, N., Lenoir, G.M., Baglietto, L., His, M., Boutron-Ruault, M.C., Trichopoulou, A., Lagiou, P., Katsoulis, M., Kaaks, R., Kühn, T., Panico, S., Pala, V., Masala, G., Bueno-de-Mesquita, H.B., Peeters, P.H., van Gils, C., Hjartåker, A., Standahl Olsen, K., Borgund Barnung, R., Barricarte, A., Redondo-Sanchez, D., Menéndez, V., Amiano, P., Wennberg, M., Key, T., Khaw, K.T., Merritt, M.A., Riboli, E., Gunter, M.J., and Romieu, I.

Published
2017
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10. A body shape index (ABSI) is associated inversely with post-menopausal progesterone-receptor-negative breast cancer risk in a large European cohort

Author

Christakoudi, S, Tsilidis, KK, Dossus, L, Rinaldi, S, Weiderpass, E, Antoniussen, CS, Dahm, CC, Tjønneland, A, Mellemkjær, L, Katzke, V, Kaaks, R, Schulze, MB, Masala, G, Grioni, S, Panico, S, Tumino, R, Sacerdote, C, May, AM, Monninkhof, EM, Quirós, JR, Bonet, C, Sánchez, M-J, Amiano, P, Chirlaque, M-D, Guevara, M, Rosendahl, AH, Stocks, T, Perez-Cornago, A, Tin Tin, S, Heath, AK, Aglago, EK, Peruchet-Noray, L, Freisling, H, and Riboli, E

Subjects
Breast Neoplasms/complications, Somatotypes, Hip Size, Triple Negative Breast Neoplasms/complications, Waist Size, Middle Aged, Body Mass Index, Postmenopause, ABSI, Body shape, Breast cancer, Risk Factors, Humans, Female, Prospective Studies, Obesity, Progesterone
Abstract

BACKGROUND: Associations of body shape with breast cancer risk, independent of body size, are unclear because waist and hip circumferences are correlated strongly positively with body mass index (BMI).METHODS: We evaluated body shape with the allometric "a body shape index" (ABSI) and hip index (HI), which compare waist and hip circumferences, correspondingly, among individuals with the same weight and height. We examined associations of ABSI, HI, and BMI (per one standard deviation increment) with breast cancer overall, and according to menopausal status at baseline, age at diagnosis, and oestrogen and progesterone receptor status (ER+/-PR+/-) in multivariable Cox proportional hazards models using data from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.RESULTS: During a mean follow-up of 14.0 years, 9011 incident breast cancers were diagnosed among 218,276 women. Although there was little evidence for association of ABSI with breast cancer overall (hazard ratio HR = 0.984; 95% confidence interval: 0.961-1.007), we found borderline inverse associations for post-menopausal women (HR = 0.971; 0.942-1.000; n = 5268 cases) and breast cancers diagnosed at age ≥ 55 years (HR = 0.976; 0.951-1.002; n = 7043) and clear inverse associations for ER + PR- subtypes (HR = 0.894; 0.822-0.971; n = 726) and ER-PR- subtypes (HR = 0.906; 0.835-0.983 n = 759). There were no material associations with HI. BMI was associated strongly positively with breast cancer overall (HR = 1.074; 1.049-1.098), for post-menopausal women (HR = 1.117; 1.085-1.150), for cancers diagnosed at age ≥ 55 years (HR = 1.104; 1.076-1.132), and for ER + PR + subtypes (HR = 1.122; 1.080-1.165; n = 3101), but not for PR- subtypes.CONCLUSIONS: In the EPIC cohort, abdominal obesity evaluated with ABSI was not associated with breast cancer risk overall but was associated inversely with the risk of post-menopausal PR- breast cancer. Our findings require validation in other cohorts and with a larger number of PR- breast cancer cases.

Published
2023

11. Genome-wide Association Study of Bladder Cancer Reveals New Biological and Translational Insights

Author

Koutros, S., Kiemeney, L.A., Pal Choudhury, P., Milne, R.L., Lopez de Maturana, E., Ye, Y., Joseph, V., Florez-Vargas, O., Dyrskjøt, L., Figueroa, J., Dutta, D., Giles, G.G., Hildebrandt, M.A.T., Offit, K., Kogevinas, M., Weiderpass, E., McCullough, M.L., Freedman, N.D., Albanes, D., Kooperberg, C., Cortessis, V.K., Karagas, M.R., Johnson, A., Schwenn, M.R., Baris, D., Furberg, H., Bajorin, D.F., Cussenot, O., Cancel-Tassin, G., Benhamou, S., Kraft, P., Porru, S., Carta, A., Bishop, T., Southey, M.C., Matullo, G., Fletcher, T., Kumar, R., Taylor, J.A., Lamy, P., Prip, F., Kalisz, M., Weinstein, S.J., Hengstler, J.G., Selinski, S., Harland, M., Teo, M., Kiltie, A.E., Tardón, A., Serra, C., Carrato, A., García-Closas, R., Lloreta, J., Schned, A., Lenz, P., Riboli, E., Brennan, P., Tjønneland, A., Otto, T., Ovsiannikov, D., Volkert, F., Vermeulen, S.H., Aben, K.K.H., Galesloot, T.E., Turman, C., Vivo, I. De, Giovannucci, E., Hunter, D.J., Hohensee, C., Hunt, R., Patel, A.V., Huang, W.Y., Thorleifsson, G., Gago-Dominguez, M., Amiano, P., Golka, K., Stern, M.C., Yan, W., Liu, J., Li, S.A., Katta, S., Hutchinson, A., Hicks, B., Wheeler, W.A., Purdue, M.P., McGlynn, K.A., Kitahara, C.M., Haiman, C.A., Greene, M.H., Rafnar, T., Chatterjee, N., Chanock, S.J., Wu, X., Real, F.X., Silverman, D.T., Garcia-Closas, M., Stefansson, K., Prokunina-Olsson, L., Malats, N., and Rothman, N.

Abstract

BACKGROUND: Genomic regions identified by genome-wide association studies (GWAS) for bladder cancer risk provide new insights into etiology. OBJECTIVE: To identify new susceptibility variants for bladder cancer in a meta-analysis of new and existing genome-wide genotype data. DESIGN, SETTING, AND PARTICIPANTS: Data from 32 studies that includes 13,790 bladder cancer cases and 343,502 controls of European ancestry were used for meta-analysis. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSES: Log-additive associations of genetic variants were assessed using logistic regression models. A fixed-effects model was used for meta-analysis of the results. Stratified analyses were conducted to evaluate effect modification by sex and smoking status. A polygenic risk score (PRS) was generated on the basis of known and novel susceptibility variants and tested for interaction with smoking. RESULTS AND LIMITATIONS: Multiple novel bladder cancer susceptibility loci (6p.22.3, 7q36.3, 8q21.13, 9p21.3, 10q22.1, 19q13.33) as well as improved signals in three known regions (4p16.3, 5p15.33, 11p15.5) were identified, bringing the number of independent markers at genome-wide significance (p

Published
2023

12. Association of leukocyte DNA methylation changes with dietary folate and alcohol intake in the EPIC study

Author

Perrier, F., Viallon, V., Ambatipudi, S., Ghantous, A., Cuenin, C., Hernandez-Vargas, H., Chajès, V., Baglietto, L., Matejcic, M., Moreno-Macias, H., Kühn, T., Boeing, H., Karakatsani, A., Kotanidou, A., Trichopoulou, A., Sieri, S., Panico, S., Fasanelli, F., Dolle, M., Onland-Moret, C., Sluijs, I., Weiderpass, E., Quirós, J. R., Agudo, A., Huerta, J. M., Ardanaz, E., Dorronsoro, M., Tong, T. Y. N., Tsilidis, K., Riboli, E., Gunter, M. J., Herceg, Z., Ferrari, P., and Romieu, I.

Published
2019
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15. Plasma methionine, choline, betaine, and dimethylglycine in relation to colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC)

Author

Nitter, M., Norgård, B., de Vogel, S., Eussen, S.J.P.M., Meyer, K., Ulvik, A., Ueland, P.M., Nygård, O., Vollset, S.E., Bjørge, T., Tjønneland, A., Hansen, L., Boutron-Ruault, M., Racine, A., Cottet, V., Kaaks, R., Kühn, T., Trichopoulou, A., Bamia, C., Naska, A., Grioni, S., Palli, D., Panico, S., Tumino, R., Vineis, P., Bueno-de-Mesquita, H.B., van Kranen, H., Peeters, P.H., Weiderpass, E., Dorronsoro, M., Jakszyn, P., Sánchez, M., Argüelles, M., Huerta, J.M., Barricarte, A., Johansson, M., Ljuslinder, I., Khaw, K., Wareham, N., Freisling, H., Duarte-Salles, T., Stepien, M., Gunter, M.J., and Riboli, E.

Published
2014
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16. Circulating prolactin and breast cancer risk among pre- and postmenopausal women in the EPIC cohort

Author

Tikk, K., Sookthai, D., Johnson, T., Rinaldi, S., Romieu, I., Tjønneland, A., Olsen, A., Overvad, K., Clavel-Chapelon, F., Baglietto, L., Boeing, H., Trichopoulou, A., Lagiou, P., Trichopoulos, D., Palli, D., Pala, V., Tumino, R., Rosso, S., Panico, S., Agudo, A., Menéndez, V., Sánchez, M.-J., Amiano, P., Huerta Castaño, J.M., Ardanaz, E., Bueno-de-Mesquita, H.B., Monninkhof, E., Onland-Moret, C., Andersson, A., Sund, M., Weiderpass, E., Khaw, K.-T., Key, T.J., Travis, R.C., Gunter, M.J., Riboli, E., Dossus, L., and Kaaks, R.

Published
2014
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17. Physical activity, sex steroid, and growth factor concentrations in pre- and post-menopausal women: a cross-sectional study within the EPIC cohort

Author

Rinaldi, S., Kaaks, R., Friedenreich, C. M., Key, T. J., Travis, R., Biessy, C., Slimani, N., Overvad, K., Østergaard, J. N., Tjønneland, A., Olsen, A., Mesrine, S., Fournier, A., Dossus, L., Lukanova, A., Johnson, T., Boeing, H., Vigl, M., Trichopoulou, A., Benetou, V., Trichopoulos, D., Masala, G., Krogh, V., Tumino, R., Ricceri, F., Panico, S., Bueno-de-Mesquita, H. B., Monninkhof, E. M., May, A. M., Weiderpass, E., Quirós, J. R., Travier, N., Molina-Montes, E., Amiano, P., Huerta, J. M., Ardanaz, E., Sund, M., Johansson, M., Khaw, K. T., Wareham, N., Scalbert, A., Gunter, M. J., Riboli, E., and Romieu, I.

Published
2014

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

Author

Hageman, S., Pennells, L., Ojeda, F., Kaptoge, S., Kuulasmaa, K., Vries, T. de, Xu, Z., Kee, F., Chung, R., Wood, A., McEvoy, J.W., Veronesi, G., Bolton, T., Dendale, P., Ference, B.A., Halle, M., Timmis, A., Vardas, P., Danesh, J., Graham, I., Salomaa, V., Visseren, F., Bacquer, D. de, Blankenberg, S., Dorresteijn, J., Angelantonio, E. di, Achenbach, S., Aleksandrova, K., Amiano, P., Amouyel, P., Andersson, J., Bakker, S.J.L., Costa, R.B.D., Beulens, J.W.J., Blaha, M., Bobak, M., Boer, J.M.A., Bonet, C., Bonnet, F., Boutron-Ruault, M.C., Braaten, T., Brenner, H., Brunner, F., Brunner, E.J., Brunstrom, M., Buring, J., Butterworth, A.S., Capkova, N., Cesana, G., Chrysohoou, C., Colorado-Yohar, S., Cook, N.R., Cooper, C., Dahm, C.C., Davidson, K., Dennison, E., Castelnuovo, A. di, Donfrancesco, C., Dorr, M., Dorynska, A., Eliasson, M., Engstrom, G., Ferrari, P., Ferrario, M., Ford, I., Fu, M., Gansevoort, R.T., Giampaoli, S., Gillum, R.F., Camara, A.G. de la, Grassi, G., Hansson, P.O., Huculeci, R., Hveem, K., Iacoviello, L., Ikram, M.K., Jorgensen, T., Joseph, B., Jousilahti, P., Jukema, J.W., Kaaks, R., Katzke, V., Kavousi, M., Kiechl, S., Klotsche, J., Konig, W., Kronmal, R.A., Kubinova, R., Kucharska-Newton, A., Lall, K., Lehmann, N., Leistner, D., Linneberg, A., Pablos, D.L., Lorenz, T., Lu, W.T., Luksiene, D., Lyngbakken, M., Magnussen, C., Malyutina, S., Ibanez, A.M., Masala, G., Mathiesen, E.B., Matsushita, K., Meade, T.W., Melander, O., Meyer, H.E., Moons, K.G.M., Moreno-Iribas, C., Muller, D., Munzel, T., Nikitin, Y., Nordestgaard, B.G., Omland, T., Onland, C., Overvad, K., Packard, C., Pajak, A., Palmieri, L., Panagiotakos, D., Panico, S., Perez-Cornago, A., Peters, A., Pietila, A., Pikhart, H., Psaty, B.M., Quarti-Trevano, F., Garcia, J.R.Q., Riboli, E., Ridker, P.M., Rodriguez, B., Rodriguez-Barranco, M., Rosengren, A., Roussel, R., Sacerdote, C., Sans, S., Sattar, N., Schiborn, C., Schmidt, B., Schottker, B., Schulze, M., Schwartz, J.E., Selmer, R.M., Shea, S., Shipley, M.J., Sieri, S., Soderberg, S., Sofat, R., Tamosiunas, A., Thorand, B., Tillmann, T., Tjonneland, A., Tong, T.Y.N., Trichopoulou, A., Tumino, R., Tunstall-Pedoe, H., Tybjaerg-Hansen, A., Tzoulaki, J., Heijden, A. van der, Schouw, Y.T. van der, Verschuren, W.M.M., Volzke, H., Waldeyer, C., Wareham, N.J., Weiderpass, E., Weidinger, F., Wild, P., Willeit, J., Willeit, P., Wilsgaard, T., Woodward, M., Zeller, T., Zhang, D.D., Zhou, B., SCORE2 Working Grp, ESC Cardiovasc Risk Collaboration, collaboration, SCORE2 working group and ESC Cardiovascular risk, Groningen Institute for Organ Transplantation (GIOT), Groningen Kidney Center (GKC), Cardiovascular Centre (CVC), Epidemiology, Neurology, Achenbach, S, Aleksandrova, K, Amiano, P, San Sebastian, D, Amouyel, P, Andersson, J, Bakker, S, Da Providencia Costa, R, Beulens, J, Blaha, M, Bobak, M, Boer, J, Bonet, C, Bonnet, F, Boutron-Ruault, M, Braaten, T, Brenner, H, Brunner, F, Brunner, E, Brunström, M, Buring, J, Butterworth, A, Capkova, N, Cesana, G, Chrysohoou, C, Colorado-Yohar, S, Cook, N, Cooper, C, Dahm, C, Davidson, K, Dennison, E, Di Castelnuovo, A, Donfrancesco, C, Dörr, M, Doryńska, A, Eliasson, M, Engström, G, Ferrari, P, Ferrario, M, Ford, I, Fu, M, Gansevoort, R, Giampaoli, S, Gillum, R, Gómez de la Cámara, A, Grassi, G, Hansson, P, Huculeci, R, Hveem, K, Iacoviello, L, Ikram, M, Jørgensen, T, Joseph, B, Jousilahti, P, Wouter Jukema, J, Kaaks, R, Katzke, V, Kavousi, M, Kiechl, S, Klotsche, J, König, W, Kronmal, R, Kubinova, R, Kucharska-Newton, A, Läll, K, Lehmann, N, Leistner, D, Linneberg, A, Pablos, D, Lorenz, T, Lu, W, Luksiene, D, Lyngbakken, M, Magnussen, C, Malyutina, S, Ibañez, A, Masala, G, Mathiesen, E, Matsushita, K, Meade, T, Melander, O, Meyer, H, Moons, K, Moreno-Iribas, C, Muller, D, Münzel, T, Nikitin, Y, Nordestgaard, B, Omland, T, Onland, C, Overvad, K, Packard, C, Pająk, A, Palmieri, L, Panagiotakos, D, Panico, S, Perez-Cornago, A, Peters, A, Pietilä, A, Pikhart, H, Psaty, B, Quarti-Trevano, F, Garcia, J, Riboli, E, Ridker, P, Rodriguez, B, Rodriguez-Barranco, M, Rosengren, A, Roussel, R, Sacerdote, C, S, S, Sattar, N, Schiborn, C, Schmidt, B, Schöttker, B, Schulze, M, Schwartz, J, Selmer, R, Shea, S, Shipley, M, Sieri, S, Söderberg, S, Sofat, R, Tamosiunas, A, Thorand, B, Tillmann, T, Tjønneland, A, Tong, T, Trichopoulou, A, Tumino, R, Tunstall-Pedoe, H, Tybjaerg-Hansen, A, Tzoulaki, J, van der Heijden, A, van der Schouw, Y, Verschuren, W, Völzke, H, Waldeyer, C, Wareham, N, Weiderpass, E, Weidinger, F, Wild, P, Willeit, J, Willeit, P, Wilsgaard, T, Woodward, M, Zeller, T, Zhang, D, Zhou, B, and Apollo - University of Cambridge Repository

Subjects
Male, Cardiology, RATIONALE, Blood Pressure, Disease, 030204 cardiovascular system & hematology, PROFILE, ACUTE CORONARY EVENTS, VALIDATION, Europe/epidemiology, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, DESIGN, Clinical Research, Risk Factors, Diabetes mellitus, medicine, PARTICIPANTS, Humans, 030212 general & internal medicine, Risk factor, Aged, Primary prevention, business.industry, 10-year CVD risk, Incidence (epidemiology), Cardiovascular Diseases/epidemiology, Risk Prediction, Cardiovascular Disease, Primary Prevention, 10-year Cvd Risk, External validation, PRIMARY-CARE, Middle Aged, medicine.disease, Cardiovascular disease, Risk prediction, 3. Good health, Europe, Prediction algorithms, Blood pressure, Cardiovascular Diseases, Smoking status, Female, Cardiology and Cardiovascular Medicine, business, Algorithms, Demography
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. Acknowledgements We thank investigators and participants of the several studies that contributed data to the Emerging Risk Factors Collaboration (ERFC). This research has been conducted using the UK Biobank Resource under Application Number 26865. Data from the Clinical Practice Research Datalink (CPRD) were obtained under licence from the UK Medicines and Healthcare products Regulatory Agency (protocol 162RMn2). CPRD uses data provided by patients and collected by the NHS as part of their care and support. We thank all EPIC participants and staff for their contribution to the study, the laboratory teams at the Medical Research Council Epidemiology Unit for sample management and Cambridge Genomic Services for genotyping, Sarah Spackman for data management and the team at the EPIC-CVD Coordinating Centre for study co-ordination and administration. Funding The ERFC co-ordinating centre was underpinned by programme grants from the British Heart Foundation (SP/09/002; RG/13/13/30194; RG/18/13/33946), BHF Centre of Research Excellence (RE/18/1/34212), the UK Medical Research Council (MR/L003120/1), and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (BRC1215-20014), with project-specific support received from the UK NIHR [*], British United Provident Association UK Foundation and an unrestricted educational grant from GlaxoSmithKline. A variety of funding sources have supported recruitment, follow-up, and laboratory measurements in the studies contributing data to the ERFC, which are listed on the ERFC website (www.phpc.cam.ac.uk/ceu/erfc/list-of-studies). *The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. This work was supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation, and Wellcome. The MORGAM Project has received funding from EU projects MORGAM (Biomed BMH4-CT98-3183), GenomEUtwin (FP5, QLG2-CT-2002-01254), ENGAGE (FP7, HEALTH-F4-2007-201413),CHANCES (FP7, HEALTH-F3-2010-242244), BiomarCaRE (FP7,HEALTH-F2-2011-278913), euCanSHare (Horizon 2020, No. 825903) and AFFECT-EU (Horizon 2020, No. 847770); and Medical Research Council, London (G0601463, No. 80983: Biomarkers in the MORGAM Populations). This has supported central coordination, workshops and part of the activities of the MORGAM Data Centre, the MORGAM Laboratories and the MORGAM Participating Centres EPIC-CVD was funded by the European Research Council (268834), and the European Commission Framework Programme 7 (HEALTH-F2-2012-279233). This work was supported by the Estonian Research Council grant PUTs (PRG687, PUT1660, PUT1665, PRG184), by European Union through the European Regional Development Fund project no. MOBERA5 (Norface Network project no 462.16.107), by the Green ICT programme under Norway Grants 2014 – 2021 (grant number EU53928), by the European Union through Horizon 2020 grant no. 810645 and through the European Regional Development Fund (Project No. 2014-2020.4.01.16-0125) and by the PRECISE4Q consortium. PRECISE4Q project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement 777107. This work was partly funded through the CoMorMent project. CoMorMent has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement 847776. The KORA study was initiated and financed by the Helmholtz Zentrum Mu¨nchen—German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the State of Bavaria. The KORA study was supported by a research grant from the Virtual Institute of Diabetes Research (Helmholtz Zentrum Mu¨nchen), the Clinical Cooperation Group Diabetes between Ludwig-Maximilians-Universita¨t Mu¨nchen and Helmholtz Zentrum Mu¨nchen, and by the German Diabetes Center (DDZ). The HAPIEE project, Institute, was supported by grants from the Wellcome Trust (064947/Z/01/Z; WT081081) and US National Institute on Aging (1R01 and AG23522). The co-ordination of EPIC is financially supported by International Agency for Research on Cancer (IARC) and also by the Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, which has additional infrastructure support provided by the NIHR Imperial Biomedical Research Centre (BRC). The national cohorts are supported by: Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Ge´ne´rale de l’Education Nationale, Institut National de la Sante´ et de la Recherche Me´dicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), German Institute of Human Nutrition Potsdam Rehbruecke (DIfE), Federal Ministry of Education and Research (BMBF) (Germany); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy, Compagnia di SanPaolo and National Research Council (Italy); Dutch 2448 SCORE2 working group and ESC Cardiovascular Risk Collaboration Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS)—Instituto de Salud Carlos III (ISCIII), Regional Governments of Andalucı´a, Asturias, Basque Country, Murcia and Navarra, and the Catalan Institute of Oncology—ICO (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Ska˚ne and Va¨sterbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C8221/A29017 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk; MR/M012190/1 to EPIC-Oxford) (United Kingdom)

Published
2021

19. Body size at different ages and risk of six cancers: a Mendelian randomization and prospective cohort study

Author

Mariosa, D, Smith-Byrne, K, Richardson, TG, Ferrari, P, Gunter, MJ, Papadimitriou, N, Murphy, N, Christakoudi, S, Tsilidis, KK, Riboli, E, Muller, D, Purdue, MP, Chanock, SJ, Hung, RJ, Amos, CI, O'Mara, TA, Amiano, P, Pasanisi, F, Rodriguez-Barranco, M, Krogh, V, Tjønneland, A, Halkjær, J, Perez-Cornago, A, Chirlaque, M-D, Skeie, G, Rylander, C, Borch, KB, Aune, D, Heath, AK, Ward, HA, Schulze, M, Bonet, C, Weiderpass, E, Smith, GD, Brennan, P, Johansson, M, Mariosa, Daniela, Smith-Byrne, Karl, Richardson, Tom G, Ferrari, Pietro, Gunter, Marc J, Papadimitriou, Niko, Murphy, Neil, Christakoudi, Sofia, Tsilidis, Konstantinos K, Riboli, Elio, Muller, David, Purdue, Mark P, Chanock, Stephen J, Hung, Rayjean J, Amos, Christopher I, O'Mara, Tracy A, Amiano, Pilar, Pasanisi, Fabrizio, Rodriguez-Barranco, Miguel, Krogh, Vittorio, Tjønneland, Anne, Halkjær, Jytte, Perez-Cornago, Aurora, Chirlaque, María-Dolore, Skeie, Guri, Rylander, Charlotta, Borch, Kristin Benjaminsen, Aune, Dagfinn, Heath, Alicia K, Ward, Heather A, Schulze, Matthia, Bonet, Catalina, Weiderpass, Elisabete, Smith, George Davey, Brennan, Paul, and Johansson, Mattias

Subjects
Adult, SUSCEPTIBILITY LOCI, Epidemiology, OVARIAN-CANCER, Body Mass Index, 1117 Public Health and Health Services, POOLED ANALYSIS, Cohort Studies, MASS INDEX, Neoplasms, Body Size, Humans, Obesity, Prospective Studies, Genetics & Heredity, LIFE-COURSE, 0604 Genetics, Science & Technology, IDENTIFICATION, ENDOMETRIAL CANCER, Mendelian Randomization Analysis, Oncology, ADIPOSITY, Mathematical & Computational Biology, Life Sciences & Biomedicine, ANTHROPOMETRIC FACTORS, Genome-Wide Association Study
Abstract

It is unclear if body weight in early life affects cancer risk independently of adult body weight. To investigate this question for six obesity-related cancers, we performed univariable and multivariable analyses using i) Mendelian randomization (MR) analysis and ii) longitudinal analyses in prospective cohorts. Both the MR and longitudinal analyses indicated that larger body size at age 10 was associated with higher risk of endometrial (ORMR=1.61, 95%CI = 1.23-2.11) and kidney cancer (ORMR=1.40, 95%CI = 1.09-1.80). These associations were attenuated after accounting for adult body size in both the MR and cohort analyses. Early life BMI was not consistently associated with the other investigated cancers. The lack of clear independent risk associations suggests that early life BMI influences endometrial and kidney cancer risk mainly through pathways that are common with adult BMI.

Published
2022

20. Biomarkers of folate and vitamin B12 and breast cancer risk: report from the EPIC cohort

Author

Matejcic, M., de Batlle, J., Ricci, C., Biessy, C., Perrier, F., Huybrechts, I., Weiderpass, E., BoutronRuault, M.C., Cadeau, C., His, M., Cox, D.G., Boeing, H., Fortner, R.T., Kaaks, R., Lagiou, P., Trichopoulou, A., Benetou, V., Tumino, R., Panico, S., Sieri, S., Palli, D., Ricceri, F., BuenodeMesquita, H.B(as), Skeie, G., Amiano, P., Sánchez, M.J., Chirlaque, M.D., Barricarte, A., Quirós, J.R., Buckland, G., van Gils, C.H., Peeters, P.H., Key, T.J., Riboli, E., Gylling, B., ZeleniuchJacquotte, A., Gunter, M.J., Romieu, I., and Chajès, V.

Published
2017
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21. Consumption of fatty foods and incident type 2 diabetes in populations from eight European countries

Author

Buijsse, B., Boeing, H., Drogan, D., Schulze, M.B., Feskens, E.J., Amiano, P., Barricarte, A., Clavel-Chapelon, F., de Lauzon-Guillain, B., Fagherazzi, G., Fonseca-Nunes, A., Franks, P.W., Huerta, J.M., Jakobsen, M.U., Kaaks, R., Key, T.J., Khaw, K.T., Masala, G., Moskal, A., Nilsson, P.M., Overvad, K., Pala, V., Panico, S., Redondo, M.L., Ricceri, F., Rolandsson, O., Sanchez, M.-J., Sluijs, I., Spijkerman, A.M., Tjonneland, A., Tumino, R., van der A, D.L., van der Schouw, Y.T., Langenberg, C., Sharp, S.J., Forouhi, N.G., Riboli, E., and Wareham, N.J.

Subjects
Oils and fats, Edible -- Health aspects -- Consumption data, Type 2 diabetes -- Statistics, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVES: Diets high in saturated and trans fat and low in unsaturated fat may increase type 2 diabetes (T2D) risk, but studies on foods high in fat per unit weight are sparse. We assessed whether the intake of vegetable oil, butter, margarine, nuts and seeds and cakes and cookies is related to incident T2D. SUBJECTS/METHODS: A case-cohort study was conducted, nested within eight countries of the European Prospective Investigation into Cancer (EPIC), with 12 403 incident T2D cases and a subcohort of 16 835 people, identified from a cohort of 340 234 people. Diet was assessed at baseline (1991-1999) by country-specific questionnaires. Country-specific hazard ratios (HRs) across four categories of fatty foods (nonconsumers and tertiles among consumers) were combined with random-effects meta-analysis. RESULTS: After adjustment not including body mass index (BMI), nonconsumers of butter, nuts and seeds and cakes and cookies were at higher T2D risk compared with the middle tertile of consumption. Among consumers, cakes and cookies were inversely related to T2D (HRs across increasing tertiles 1.14, 1.00 and 0.92, respectively; P-trend < 0.0001). All these associations attenuated upon adjustment for BMI, except the higher risk of nonconsumers of cakes and cookies (HR 1.57). Higher consumption of margarine became positively associated after BMI adjustment (HRs across increasing consumption tertiles: 0.93, 1.00 and 1.12; P-trend 0.03). Within consumers, vegetable oil, butter and nuts and seeds were unrelated to T2D. CONCLUSIONS: Fatty foods were generally not associated with T2D, apart from weak positive association for margarine. The higher risk among nonconsumers of cakes and cookies needs further explanation. European Journal of Clinical Nutrition (2015) 69, 455-461; doi: 10.1038/ejcn.2014.249; published online 26 November 2014, INTRODUCTION Diet is considered to be a crucial factor in the development of type 2 diabetes (T2D) and there has been a considerable interest in the role of the fat [...]

Published
2015
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23. Fruits and vegetables consumption and the risk of histological subtypes of lung cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC)

Author

Büchner, F. L., Bueno-de-Mesquita, H. B., Linseisen, J., Boshuizen, H. C., Kiemeney, L. A. L. M., Ros, M. M., Overvad, K., Hansen, L., Tjonneland, A., Raaschou-Nielsen, O., Clavel-Chapelon, F., Boutron-Ruault, M.-C., Touillaud, M., Kaaks, R., Rohrmann, S., Boeing, H., Nöthlings, U., Trichopoulou, A., Zylis, D., Dilis, V., Palli, D., Sieri, S., Vineis, P., Tumino, R., Panico, S., Peeters, P. H. M., van Gils, C. H., Lund, E., Gram, I. T., Braaten, T., Martinez, C., Agudo, A., Arriola, L., Ardanaz, E., Navarro, C., Rodríguez, L., Manjer, J., Wirfält, E., Hallmans, G., Rasmuson, T., Key, T. J., Roddam, A. W., Bingham, S., Khaw, K.-T., Slimani, N., Bofetta, P., Byrnes, G., Norat, T., Michaud, D., and Riboli, E.

Published
2010

24. Milk intake and incident stroke and coronary heart disease in populations of European descent: A Mendelian Randomization study

Author

Vissers, L.E.T., Sluijs, I., Burgess, S., Forouhi, N.G., Freisling, H., Imamura, F., Nilsson, Torbjörn K., Renström, Frida, Weiderpass, E., Aleksandrova, K., Dahm, C.C., Perez-Cornago, A., Schulze, M.B., Tong, T.Y.N., Aune, D., Bonet, C., Boer, J.M.A., Boeing, H., Chirlaque, M.D., Conchi, M.I., Imaz, L., Jäger, S., Krogh, V., Kyrø, C., Masala, G., Melander, O., Overvad, K., Panico, S., Sánches, M.J., Sonestedt, E., Tjønneland, A., Tzoulaki, I., Verschuren, W.M.M., Riboli, E., Wareham, N.J., Danesh, J., Butterworth, A.S., and Van Der Schouw, Y.T.

Subjects
Näringslära, Nutrition and Dietetics, CHD, Milk, Mendelian Randomization, dairy, stroke
Abstract

Higher milk intake has been associated with a lower stroke risk, but not with risk of coronary heart disease (CHD). Residual confounding or reverse causation cannot be excluded. Therefore, we estimated the causal association of milk consumption with stroke and CHD risk through instrumental variable (IV) and gene-outcome analyses. IV analysis included 29,328 participants (4,611 stroke; 9,828 CHD) of the EPIC-CVD (8 European countries) and EPIC-NL case-cohort studies. rs4988235, a lactase persistence (LP) single nucleotide polymorphism which enables digestion of lactose in adulthood was used as genetic instrument. Intake of milk was first regressed on rs4988235 in a linear regression model. Next, associations of genetically predicted milk consumption with stroke and CHD were estimated using Prentice-weighted Cox regression. Gene-outcome analysis included 777,024 participants (50,804 cases) from MEGASTROKE (including EPIC-CVD), UK Biobank and EPIC-NL for stroke, and 483,966 participants (61,612 cases) from CARDIoGRAM, UK Biobank and EPIC-CVD and EPIC-NL for CHD. In IV analyses, each additional LP allele was associated with a higher intake of milk in EPIC-CVD (β=13.7 g/day; 95%CI: 8.4-19.1) and EPIC-NL (36.8 g/day; 20.0-53.5). Genetically predicted milk intake was not associated with stroke (HR per 25 g/day 1.05; 95%CI: 0.94-1.16) or CHD (1.02; 0.96-1.08). In gene-outcome analyses, there was no association of rs4988235 with risk of stroke (odds ratios 1.02; 0.99-1.05) or CHD (0.99; 0.95-1.03). Current Mendelian Randomization analysis does not provide evidence for a causal inverse relationship between milk consumption and stroke or CHD risk. MEGASTROKE

Published
2021

25. Dietary Folate Intake and Breast Cancer Risk: European Prospective Investigation Into Cancer and Nutrition

Author

de Batlle, J., Ferrari, P., Chajes, V., Park, J. Y., Slimani, N., McKenzie, F., Overvad, K., Roswall, N., Tjønneland, A., Boutron-Ruault, M. C., Clavel-Chapelon, F., Fagherazzi, G., Katzke, V., Kaaks, R., Bergmann, M. M., Trichopoulou, A., Lagiou, P., Trichopoulos, D., Palli, D., Sieri, S., Panico, S., Tumino, R., Vineis, P., Bueno-de-Mesquita, H. B., Peeters, P. H., Hjartåker, A., Engeset, D., Weiderpass, E., Sánchez, S., Travier, N., Sánchez, M. J., Amiano, P., Chirlaque, M. D., Barricarte Gurrea, A., Khaw, K. T., Key, T. J., Bradbury, K. E., Ericson, U., Sonestedt, E., Van Guelpen, B., Schneede, J., Riboli, E., and Romieu, I.

Published
2015
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26. Meat Intake and Bladder Cancer in a Prospective Study: A Role for Heterocyclic Aromatic Amines?

Author

Lumbreras, B., Garte, S., Overvad, K., Tjonneland, A., Clavel-Chapelon, F., Linseisen, J. P., Boeing, H., Trichopoulou, A., Palli, D., Peluso, M., Krogh, V., Tumino, R., Panico, S., Bueno-De-Mesquita, H. B., Peeters, P. H., Lund, E., Martinez, C., Dorronsoro, M., Barricarte, A., Chirlaque, M.-D., Quiros, J. R., Berglund, G., Hallmans, G., Day, N. E., Key, T. J., Saracci, R., Kaaks, R., Malaveille, C., Ferrari, P., Boffetta, P., Norat, T., Riboli, E., Gonzalez, C. A., and Vineis, P.

Published
2008
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27. Modified Mediterranean diet and survival after myocardial infarction: the EPIC-Elderly study

Author

Trichopoulou, A., Bamia, C., Norat, T., Overvad, K., Schmidt, E. B., Tjønneland, A., Halkjær, J., Clavel-Chapelon, F., Vercambre, M. -N., Boutron-Ruault, M. -C., Linseisen, J., Rohrmann, S., Boeing, H., Weikert, C., Benetou, V., Psaltopoulou, T., Orfanos, P., Boffetta, P., Masala, G., Pala, V., Panico, S., Tumino, R., Sacerdote, C., Bueno-de-Mesquita, H. B., Ocke, M. C., Peeters, P. H., Van der Schouw, Y. T., González, C., Sanchez, M. J., Chirlaque, M. D., Moreno, C., Larrañaga, N., Van Guelpen, B., Jansson, J. -H., Bingham, S., Khaw, K. -T., Spencer, E. A., Key, T., Riboli, E., and Trichopoulos, D.

Published
2007

28. Relationship of Alcohol Intake and Sex Steroid Concentrations in Blood in Pre- and Post-Menopausal Women: The European Prospective Investigation into Cancer and Nutrition

Author

Rinaldi, S., Peeters, P. H. M., Bezemer, I. D., Dossus, L., Biessy, C., Sacerdote, C., Berrino, F., Panico, S., Palli, D., Tumino, R., Khaw, K. T., Bingham, S., Allen, N. E., Key, T., Jensen, M. K., Overvad, K., Olsen, A., Tjonneland, A., Amiano, P., Ardanaz, E., Agudo, A., Martinez-García, C., Quirós, J. Ramón, Tormo, M. J., Nagel, G., Linseisen, J., Boeing, H., Schulz, M., Grobbee, D. E., Bueno-De-Mesquita, H. B., Koliva, M., Kyriazi, G., Thrichopoulou, A., Boutron-Ruault, M. C., Clavel-Chapelon, F., Ferrari, P., Slimani, N., Saracci, R., Riboli, E., and Kaaks, R.

Published
2006
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29. Milk intake and incident stroke and CHD in populations of European descent: a Mendelian randomisation study

Author

Vissers, L. E. T., primary, Sluijs, I., additional, Burgess, S., additional, Forouhi, N. G., additional, Freisling, H., additional, Imamura, F., additional, Nilsson, T. K., additional, Renström, F., additional, Weiderpass, E., additional, Aleksandrova, K., additional, Dahm, C. C., additional, Perez-Cornago, A., additional, Schulze, M. B., additional, Tong, T. Y. N., additional, Aune, D., additional, Bonet, C., additional, Boer, J. M. A., additional, Boeing, H., additional, Chirlaque, M. D., additional, Conchi, M. I., additional, Imaz, L., additional, Jäger, S., additional, Krogh, V., additional, Kyrø, C., additional, Masala, G., additional, Melander, O., additional, Overvad, K., additional, Panico, S., additional, Sánches, M. J., additional, Sonestedt, E., additional, Tjønneland, A., additional, Tzoulaki, I., additional, Verschuren, W. M. M., additional, Riboli, E., additional, Wareham, N. J., additional, Danesh, J., additional, Butterworth, A. S., additional, and van der Schouw, Y. T., additional

Published
2021
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30. Vitamin B6 intake, its active form pyridoxal 5'phosphate, and markers of B6 activity and catabolism

Author

Clasen, J, Heath, AK, Van Puyvelde, H, Huybrechts, I, Johansson, M, Ferrari, P, Park, JY, Brennan, P, Riboli, E, Muller, DC, and Cancer Research UK

Subjects
Science & Technology, Epidemiology, 0104 Statistics, Life Sciences & Biomedicine, Public, Environmental & Occupational Health, 1117 Public Health and Health Services
Abstract

Background Several biological pathways implicated in cancer risk rely on vitamin B6, which can be measured in its active form pyridoxal 5’-phosphate (PLP). Functional markers of B6 enzymatic activity have been proposed, including the homocysteine:cysteine ratio (Hcy:Cys, a marker of transsulfuration), 3-hydroxykynurenine ratio (HKr, a marker of tryptophan catabolism), and the 4-pyridoxic acid ratio (PAr, a marker of B6 catabolism). We investigated the extent to which these markers are associated with B6 intake. Methods Data from 4,750 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) study were included. We estimated the expected percentage change in each of the markers (PLP, Hcy:Cys, HKr, and PAr) for a doubling in B6 intake using log-linear Bayesian hierarchical regression models with log-transformed intake and biomarker data. Results The percent change (posterior mean [95% Credible Interval (CrI)]) for a doubling of B6 intake was 61.0 [51.2, 71.8] for PLP, -12.7 [-15.2, -9.9] for Hcy:Cys, -12.9 [-15.7, -9.9] for HKr, and 1.3 [-3.5, 6.2] for PAr. Conclusions B6 intake is most strongly associated with PLP, but is also associated with functional markers of transsulfuration and tryptophan catabolism, in the direction of increased activity in these pathways. There is no evidence of a linear association between vitamin B6 intake and catabolism. Key messages Our results show differing sensitivity of PLP, markers of tryptophan catabolism and transsulfuration, and vitamin B6 catabolism to B6 intake.

Published
2021

32. Dietary vitamin D intake and risk of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition: the EPIC-InterAct study

Author

Abbas, S, Linseisen, J, Rohrmann, S, Beulens, J W J, Buijsse, B, Amiano, P, Ardanaz, E, Balkau, B, Boeing, H, Clavel-Chapelon, F, Fagherazzi, G, Franks, P W, Gavrila, D, Grioni, S, Kaaks, R, Key, T J, Khaw, K T, Kühn, T, Mattiello, A, Molina-Montes, E, Nilsson, P M, Overvad, K, Quirós, J R, Rolandsson, O, Sacerdote, C, Saieva, C, Slimani, N, Sluijs, I, Spijkerman, A M W, Tjonneland, A, Tumino, R, van der A, D L, Zamora-Ros, R, Sharp, S J, Langenberg, C, Forouhi, N G, Riboli, E, and Wareham, N J

Published
2014
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33. No association between educational level and pancreatic cancer incidence in the European Prospective Investigation into Cancer and Nutrition

Author

van Boeckel, Petra G.A., Boshuizen, Hendriek C., Siersema, Peter D., Vrieling, Alina, Kunst, Anton E., Ye, Weimin, Sund, Malin, Michaud, Dominique S., Gallo, Valentina, Spencer, Elizabeth A., Trichopoulou, Antonia, Benetou, Vasiliki, Orfanos, Philippos, Cirera, Lluis, Duell, Eric J., Rohrmann, Sabine, Hemann, Silke, Masala, Giovanni, Manjer, Jonas, Mattiello, Amalia, Lindkvist, Bjorn, Sánchez, María-José, Pala, Valeria, Peeters, Petra H.M., Braaten, Tonje, Tjonneland, Anne, Dalton, Susanne Oksbjerg, Larranaga, Nerea, Dorronsoro, Miren, Overvad, Kim, Illner, Anne-Kathrin, Ardanaz, Eva, Marron, M., Straif, K., Riboli, E., and Bueno-de-Mesquita, B.

Published
2010
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35. Associations between dietary amino acid intakes and blood concentration levels

Author

Iguacel, I., Perez-Cornago, A., Van Puyvelde, H., Travis, R., Stepien, M., Scalbert, A., Casagrande, C., Weiderpass, E., Riboli, E., Schulze, M.B., Skeie, G., Bodén, S., Boeing, H., Cross, A.J., Harlid, S., Jensen, T.E., Huerta, J.M., Katzke, V., Kühn, T., Lujan-Barroso, L., Masala, G., Rodriguez-Barranco, M., Rostgaard-Hansen, A.L., van der Schouw, Y.T., Vermeulen, R., Tagliabue, G., Tjønneland, A., Trevisan, M., Ferrari, P., Gunter, M.J., Huybrechts, I., IRAS OH Epidemiology Chemical Agents, and dIRAS RA-2

Subjects
Dietary questionnaire, Nutrition and Dietetics, Blood levels, Dietary intake, Amino acids, Critical Care and Intensive Care Medicine, 24-H dietary recall
Abstract

Background and aims: Emerging evidence suggests a role of amino acids (AAs) in the development of various diseases including renal failure, liver cirrhosis, diabetes and cancer. However, mechanistic pathways and the effects of dietary AA intakes on circulating levels and disease outcomes are unclear. We aimed to compare protein and AA intakes, with their respective blood concentrations in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Methods: Dietary protein and AA intakes were assessed via the EPIC dietary questionnaires (DQ) and 24-h dietary recalls (24-HDR). A subsample of 3768 EPIC participants who were free of cancer had blood AA concentrations measured. To investigate how circulating levels relate to their respective intakes, dietary AA intake was examined in quintiles and ANOVA tests were run. Pearson correlations were examined for continous associations between intakes and blood concentrations. Results: Dietary AA intakes (assessed with the DQ) and blood AA concentrations were not strongly correlated (−0.15 ≤ r ≤ 0.17) and the direction of the correlations depended on AA class: weak positive correlations were found for most essential AAs (isoleucine, leucine, lysine, methionine, threonine, tryptophan, and valine) and conditionally essential AAs (arginine and tyrosine), while negative associations were found for non-essential AAs. Similar results were found when using the 24-HDR. When conducting ANOVA tests for essential AAs, higher intake quintiles were linked to higher blood AA concentrations, except for histidine and phenylalanine. For non-essential AAs and glycine, an inverse relationship was observed. Conditionally-essential AAs showed mixed results. Conclusions: Weak positive correlations and dose responses were found between most essential and conditionally essential AA intakes, and blood concentrations, but not for the non-essential AAs. These results suggest that intake of dietary AA might be related to physiological AA status, particularly for the essential AAs. However, these results should be further evaluated and confirmed in large-scale prospective studies.

Published
2021

36. Tobacco Smoking and Risk of Second Primary Lung Cancer

Author

Aredo, J.V., Luo, S.J., Gardner, R.M., Sanyal, N., Choi, E., Hickey, T.P., Riley, T.L., Huang, W.-Y., Kurian, A.W., Leung, A.N., Wilkens, L.R., Robbins, H.A., Riboli, E., Kaaks, R., Tjønneland, A., Vermeulen, R.C.H., Panico, S., Le Marchand, L., Amos, C.I., Hung, R.J., Freedman, N.D., Johansson, M., Cheng, I., Wakelee, H.A., Han, S.S., Sub IER overig, IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Sub Intelligent Systems, Sub IER overig, IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, and Sub Intelligent Systems

Subjects
Male, 0301 basic medicine, Oncology, Pulmonary and Respiratory Medicine, medicine.medical_specialty, Lung Neoplasms, RESECTION, medicine.medical_treatment, Second primary lung cancer, Smoking cessation, Ovarian cancer screening, Article, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal medicine, HISTORY, medicine, Humans, EPIDEMIOLOGY, Prospective Studies, Risk factor, Lung cancer, Lung, OUTCOMES, Surveillance, Proportional hazards model, business.industry, Smoking, Hazard ratio, Neoplasms, Second Primary, Second primary cancer, medicine.disease, Tobacco smoking, European Prospective Investigation into Cancer and Nutrition, MODEL, 030104 developmental biology, Socioeconomic Factors, 030220 oncology & carcinogenesis, SURVIVAL, Screening, business
Abstract

Introduction: Lung cancer survivors are at high risk of developing a second primary lung cancer (SPLC). However, SPLC risk factors have not been established and the impact of tobacco smoking remains controversial. We examined the risk factors for SPLC across multiple epidemiologic cohorts and evaluated the impact of smoking cessation on reducing SPLC risk.Methods: We analyzed data from 7059 participants in the Multiethnic Cohort (MEC) diagnosed with an initial primary lung cancer (IPLC) between 1993 and 2017. Cause-specific proportional hazards models estimated SPLC risk. We conducted validation studies using the Prostate, Lung,Colorectal, and Ovarian Cancer Screening Trial (N = 3423 IPLC cases) and European Prospective Investigation into Cancer and Nutrition (N = 4731 IPLC cases) cohorts and pooled the SPLC risk estimates using random effects meta analysis.Results: Overall, 163 MEC cases (2.3%) developed SPLC. Smoking pack-years (hazard ratio [HR] = 1.18 per 10 pack years, p < 0.001) and smoking intensity (HR = 1.30 per 10 cigarettes per day, p < 0.001) were significantly associated with increased SPLC risk. Individuals who met the 2013 U.S. Preventive Services Task Force's screening criteria at IPLC diagnosis also had an increased SPLC risk (HR = 1.92; p < 0.001). Validation studies with the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial and European Prospective Investigation into Cancer and Nutrition revealed consistent results. Meta-analysis yielded pooled HRs of 1.16 per 10 pack-years (p(meta) < 0.001), 1.25 per 10 cigarettes per day (p(meta) < 0.001), and 1.99 (p(meta) < 0.001) for meeting the U.S. Preventive Services Task Force's criteria. In MEC, smoking cessation after IPLC diagnosis was associated with an 83% reduction in SPLC risk (HR = 0.17; p < 0.001).Conclusions: Tobacco smoking is a risk factor for SPLC. Smoking cessation may reduce the risk of SPLC. Additional strategies for SPLC surveillance and screening are warranted. (C) 2021 International Association for the Study of Lung Cancer. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Published
2021

41. Healthy lifestyle index and risk of gastric adenocarcinoma in the EPIC cohort study

Author

Buckland, G., Travier, N., Huerta, J. M., Bueno-de-Mesquita, H. B(as), Siersema, P. D., Skeie, G., Weiderpass, E., Engeset, D., Ericson, U., Ohlsson, B., Agudo, A., Romieu, I., Ferrari, P., Freisling, H., Colorado-Yohar, S., Li, K., Kaaks, R., Pala, V., Cross, A. J., Riboli, E., Trichopoulou, A., Lagiou, P., Bamia, C., Boutron-Ruault, M. C., Fagherazzi, G., Dartois, L., May, A. M., Peeters, P. H., Panico, S., Johansson, M., Wallner, B., Palli, D., Key, T. J., Khaw, K. T., Ardanaz, E., Overvad, K., Tjnneland, A., Dorronsoro, M., Sánchez, M. J., Quirós, J. R., Naccarati, A., Tumino, R., Boeing, H., and Gonzalez, C. A.

Published
2015
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42. Diabetes and onset of natural menopause: results from the European Prospective Investigation into Cancer and Nutrition

Author

Brand, J.S., Onland-Moret, N.C., Eijkemans, M.J.C., Tjønneland, A., Roswall, N., Overvad, K., Fagherazzi, G., Clavel-Chapelon, F., Dossus, L., Lukanova, A., Grote, V., Bergmann, M.M., Boeing, H., Trichopoulou, A., Tzivoglou, M., Trichopoulos, D., Grioni, S., Mattiello, A., Masala, G., Tumino, R., Vineis, P., Bueno-de-Mesquita, H.B., Weiderpass, E., Redondo, M.L., Sánchez, M.J., Castaño, J.M. Huerta, Arriola, L., Ardanaz, E., Duell, E.J., Rolandsson, O., Franks, P.W., Butt, S., Nilsson, P., Khaw, K.T., Wareham, N., Travis, R., Romieu, I., Gunter, M.J., Riboli, E., and van der Schouw, Y.T.

Published
2015
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43. Plasma carotenoids, vitamin C, retinol and tocopherols levels and pancreatic cancer risk within the European Prospective Investigation into Cancer and Nutrition: A nested case–control study: Plasma micronutrients and pancreatic cancer risk

Author

Jeurnink, Suzanne M., Ros, Martine M., Leenders, Max, van Duijnhoven, Franzel J.B., Siersema, Peter D., Jansen, Eugene H.J.M., van Gils, Carla H., Bakker, Marije F., Overvad, Kim, Roswall, Nina, Tjønneland, Anne, Boutron-Ruault, Marie-Christine, Racine, Antoine, Cadeau, Claire, Grote, Verena, Kaaks, Rudolf, Aleksandrova, Krasimira, Boeing, Heiner, Trichopoulou, Antonia, Benetou, Vasiliki, Valanou, Elisavet, Palli, Domenico, Krogh, Vittorio, Vineis, Paolo, Tumino, Rosario, Mattiello, Amalia, Weiderpass, Elisabete, Skeie, Guri, Castaño, José María Huerta, Duell, Eric J., Barricarte, Aurelio, Molina-Montes, Esther, Argüelles, Marcial, Dorronsoro, Mire, Johansen, Dorthe, Lindkvist, Björn, Sund, Malin, Crowe, Francesca L., Khaw, Kay-Tee, Jenab, Mazda, Fedirko, Veronika, Riboli, E., and Bueno-de-Mesquita, H. B(as)

Published
2015
Full Text
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45. Cancer prevention through weight control—where are we in 2020?

Author

Anderson, AS, Renehan, AG, Saxton, JM, Bell, J, Cade, J, Cross, AJ, King, A, Riboli, E, Sniehotta, F, Treweek, S, Martin, RM, Beeken, R, and Mitrou, G

Subjects
Lifestyle modification, Cancer Research, Overweight, B400, COLORECTAL-CANCER, Cancer prevention, 0302 clinical medicine, Weight loss, UK NIHR Cancer and Nutrition Collaboration (Population Health Stream), Neoplasms, Epidemiology, Medicine, INSULIN-RESISTANCE, Public health, cancer prevention, public health, POSTMENOPAUSAL WOMEN, Oncology, LIFE-STYLE INTERVENTION, 030220 oncology & carcinogenesis, Perspective, MENDELIAN RANDOMIZATION, ICEP, medicine.symptom, Life Sciences & Biomedicine, medicine.medical_specialty, MEDLINE, B100, B300, B700, 1117 Public Health and Health Services, 03 medical and health sciences, Weight Loss, BREAST-CANCER, Animals, Humans, 1112 Oncology and Carcinogenesis, Oncology & Carcinogenesis, Intensive care medicine, Exercise, Science & Technology, business.industry, Cancer, A100, medicine.disease, Obesity, BODY-MASS INDEX, PHYSICAL-ACTIVITY, RISK-FACTORS, lifestyle modification, business, Risk Reduction Behavior
Abstract

Growing data from epidemiological studies highlight the association between excess body fat and cancer incidence, but good indicative evidence demonstrates that intentional weight loss, as well as increasing physical activity, offers much promise as a cost-effective approach for reducing the cancer burden. However, clear gaps remain in our understanding of how changes in body fat or levels of physical activity are mechanistically linked to cancer, and the magnitude of their impact on cancer risk. It is important to investigate the causal link between programmes that successfully achieve short-term modest weight loss followed by weight-loss maintenance and cancer incidence. The longer-term impact of weight loss and duration of overweight and obesity on risk reduction also need to be fully considered in trial design. These gaps in knowledge need to be urgently addressed to expedite the development and implementation of future cancer-control strategies. Comprehensive approaches to trial design, Mendelian randomisation studies and data-linkage opportunities offer real possibilities to tackle current research gaps. In this paper, we set out the case for why non-pharmacological weight-management trials are urgently needed to support cancer-risk reduction and help control the growing global burden of cancer.

Published
2021

46. Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study

Author

Stepien, M., Keski-Rahkonen, P., Kiss, A., Robinot, N., Duarte-Salles, T., Murphy, N., Perlemuter, G., Viallon, V., Tjønneland, A., Rostgaard-Hansen, A.L., Dahm, C.C., Overvad, K., Boutron-Ruault, M.-C., Mancini, F.R., Mahamat-Saleh, Y., Aleksandrova, K., Kaaks, R., Kühn, T., Trichopoulou, A., Karakatsani, A., Panico, S., Tumino, R., Palli, D., Tagliabue, G., Naccarati, A., Vermeulen, R.C.H., Bueno-de-Mesquita, H.B., Weiderpass, E., Skeie, G., Ramón Quirós, J., Ardanaz, E., Mokoroa, O., Sala, N., Sánchez, M.-J., Huerta, J.M., Winkvist, A., Harlid, S., Ohlsson, B., Sjöberg, K., Wareham, N., Khaw, K.-T., Ferrari, P., Rothwell, J.A., Gunter, M., Riboli, E., Scalbert, A., Jenab, M., IRAS OH Epidemiology Chemical Agents, and dIRAS RA-2

Subjects
untargeted metabolomics, Cancer Research, prospective observational cohort, Oncology, hepatocellular carcinoma
Abstract

Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.

Published
2021

47. Development and validation of a lifestyle-based model for colorectal cancer risk prediction: the LiFeCRC score

Author

Aleksandrova, K. Reichmann, R. Kaaks, R. Jenab, M. Bueno-de-Mesquita, H.B. Dahm, C.C. Eriksen, A.K. Tjønneland, A. Artaud, F. Boutron-Ruault, M.-C. Severi, G. Hüsing, A. Trichopoulou, A. Karakatsani, A. Peppa, E. Panico, S. Masala, G. Grioni, S. Sacerdote, C. Tumino, R. Elias, S.G. May, A.M. Borch, K.B. Sandanger, T.M. Skeie, G. Sánchez, M.-J. Huerta, J.M. Sala, N. Gurrea, A.B. Quirós, J.R. Amiano, P. Berntsson, J. Drake, I. van Guelpen, B. Harlid, S. Key, T. Weiderpass, E. Aglago, E.K. Cross, A.J. Tsilidis, K.K. Riboli, E. Gunter, M.J.

Abstract

Background: Nutrition and lifestyle have been long established as risk factors for colorectal cancer (CRC). Modifiable lifestyle behaviours bear potential to minimize long-term CRC risk; however, translation of lifestyle information into individualized CRC risk assessment has not been implemented. Lifestyle-based risk models may aid the identification of high-risk individuals, guide referral to screening and motivate behaviour change. We therefore developed and validated a lifestyle-based CRC risk prediction algorithm in an asymptomatic European population. Methods: The model was based on data from 255,482 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) study aged 19 to 70 years who were free of cancer at study baseline (1992–2000) and were followed up to 31 September 2010. The model was validated in a sample comprising 74,403 participants selected among five EPIC centres. Over a median follow-up time of 15 years, there were 3645 and 981 colorectal cancer cases in the derivation and validation samples, respectively. Variable selection algorithms in Cox proportional hazard regression and random survival forest (RSF) were used to identify the best predictors among plausible predictor variables. Measures of discrimination and calibration were calculated in derivation and validation samples. To facilitate model communication, a nomogram and a web-based application were developed. Results: The final selection model included age, waist circumference, height, smoking, alcohol consumption, physical activity, vegetables, dairy products, processed meat, and sugar and confectionary. The risk score demonstrated good discrimination overall and in sex-specific models. Harrell’s C-index was 0.710 in the derivation cohort and 0.714 in the validation cohort. The model was well calibrated and showed strong agreement between predicted and observed risk. Random survival forest analysis suggested high model robustness. Beyond age, lifestyle data led to improved model performance overall (continuous net reclassification improvement = 0.307 (95% CI 0.264–0.352)), and especially for young individuals below 45 years (continuous net reclassification improvement = 0.364 (95% CI 0.084–0.575)). Conclusions: LiFeCRC score based on age and lifestyle data accurately identifies individuals at risk for incident colorectal cancer in European populations and could contribute to improved prevention through motivating lifestyle change at an individual level. © 2020, The Author(s).

Published
2021

48. The blood metabolome of incident kidney cancer: A case-control study nested within the MetKid consortium

Author

Guida, F., Tan, V.Y., Corbin, L.J., Smith-Byrne, K., Alcala, K., Langenberg, C., Stewart, I.D., Butterworth, A.S., Surendran, P., Achaintre, D., Adamski, J., Exezarreta, P.A., Bergmann, M.M., Bull, C.J., Dahm, C.C., Gicquiau, A., Giles, G.G., Gunter, M.J., Haller, T., Langhammer, A., Larose, T.L., Ljungberg, B., Metspalu, A., Milne, R.L., Muller, D.C., Nøst, T.H., Sørgjerd, E.P., Prehn, C., Riboli, E., Rinaldi, S., Rothwell, J.A., Scalbert, A., Schmidt, J.A., Severi, G., Sieri, S., Vermeulen, R., Vincent, E.E., Waldenberger, M., Timpson, N.J., Johansson, M., Afd. Theologie, Sub Inorganic Chemistry and Catalysis, IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Langenberg, Claudia [0000-0002-5017-7344], Butterworth, Adam [0000-0002-6915-9015], Apollo - University of Cambridge Repository, Cancer Research UK, Guida, Florence [0000-0002-9652-2430], Tan, Vanessa Y. [0000-0001-7938-127X], Corbin, Laura J. [0000-0002-4032-9500], Alcala, Karine [0000-0003-2308-9880], Adamski, Jerzy [0000-0001-9259-0199], Bull, Caroline J. [0000-0002-2176-5120], Dahm, Christina C. [0000-0003-0481-2893], Giles, Graham G. [0000-0003-4946-9099], Langhammer, Arnulf [0000-0001-5296-6673], Ljungberg, Börje [0000-0002-4121-3753], Milne, Roger L. [0000-0001-5764-7268], Nøst, Therese H. [0000-0001-6805-3094], Pettersen Sørgjerd, Elin [0000-0002-5995-2386], Prehn, Cornelia [0000-0002-1274-4715], Riboli, Elio [0000-0001-6795-6080], Rothwell, Joseph A. [0000-0002-6927-3360], Scalbert, Augustin [0000-0001-6651-6710], Schmidt, Julie A. [0000-0002-7733-8750], Severi, Gianluca [0000-0001-7157-419X], Sieri, Sabina [0000-0001-5201-172X], Vincent, Emma E. [0000-0002-8917-7384], Timpson, Nicholas J. [0000-0002-7141-9189], Johansson, Mattias [0000-0002-3116-5081], Tan, Vanessa Y [0000-0001-7938-127X], Corbin, Laura J [0000-0002-4032-9500], Bull, Caroline J [0000-0002-2176-5120], Dahm, Christina C [0000-0003-0481-2893], Giles, Graham G [0000-0003-4946-9099], Milne, Roger L [0000-0001-5764-7268], Muller, David C [0000-0002-2350-0417], Nøst, Therese H [0000-0001-6805-3094], Rothwell, Joseph A [0000-0002-6927-3360], Schmidt, Julie A [0000-0002-7733-8750], Vincent, Emma E [0000-0002-8917-7384], Timpson, Nicholas J [0000-0002-7141-9189], Afd. Theologie, Sub Inorganic Chemistry and Catalysis, IRAS OH Epidemiology Chemical Agents, and dIRAS RA-2

Subjects
Male, Epidemiology, Single Nucleotide Polymorphisms, Physiology, Biochemistry, Body Mass Index, 0302 clinical medicine, Risk Factors, Metabolites, Medicine, Prospective Studies, Prospective cohort study, 11 Medical and Health Sciences, 2. Zero hunger, Medicine(all), 0303 health sciences, Cancer Risk Factors, Incidence, Neurochemistry, General Medicine, Neurotransmitters, Middle Aged, Kidney Neoplasms, 3. Good health, Europe, Oncology, Nephrology, 030220 oncology & carcinogenesis, Renal Cancer, Metabolome, Female, Metabolic Pathways, Metabolic Labeling, ICEP, Glutamate, Research Article, Victoria, Risk Assessment, 03 medical and health sciences, General & Internal Medicine, Genetics, Xenobiotic Metabolism, Humans, Metabolomics, Obesity, Risk factor, Molecular Biology Techniques, Molecular Biology, 030304 developmental biology, Aged, Medicine and health sciences, Cancer och onkologi, Biology and life sciences, business.industry, Case-control study, Cancer, Odds ratio, Mendelian Randomization Analysis, medicine.disease, Research and analysis methods, Metabolism, Cell Labeling, Medical Risk Factors, Cancer and Oncology, Case-Control Studies, business, Kidney cancer, Body mass index, Biomarkers, Neuroscience
Abstract

Background Excess bodyweight and related metabolic perturbations have been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI). Methods and findings We assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case–control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval [CI]: 0.68 to 0.83, p = 2.6 × 10−8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10−5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some—but not all—metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., −0.17 SD change [ßBMI] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10−5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10−3). While our results were robust across the participating studies, they were limited to study participants of European descent, and it will, therefore, be important to evaluate if our findings can be generalised to populations with different genetic backgrounds. Conclusions This study suggests a potentially important role of the blood metabolome in kidney cancer aetiology by highlighting a wide range of metabolites associated with the risk of developing kidney cancer and the extent to which changes in levels of these metabolites are driven by BMI—the principal modifiable risk factor of kidney cancer., In a case-control study, Florence Guida and colleagues identify metabolites associated with risk of kidney cancer, and use Mendelian randomization techniques to study the role of body mass index in this relationship., Author summary Why was this study done? Several modifiable risk factors have been established for kidney cancer, among which elevated body mass index (BMI) and obesity are central. The biological mechanisms underlying these relationships are poorly understood, but obesity-related metabolic perturbations may be important. What did the researchers do and find? We looked at the association between kidney cancer and the levels of 1,416 metabolites measured in blood on average 8 years before the disease onset. The study included 1,305 kidney cancer cases and 1,305 healthy controls. We found 25 metabolites robustly associated with kidney cancer risk. Specifically, multiple glycerophospholipids (GPLs) were inversely associated with risk, while several amino acids were positively associated with risk. Accounting for BMI highlighted that some—but not all—metabolites associated with kidney cancer risk are influenced by BMI. What do these findings mean? These findings illustrate the potential utility of prospectively measured metabolites in helping us to understand the aetiology of kidney cancer. By examining overlap between the metabolomic profile of prospective risk of kidney cancer and that of modifiable risk factors for the disease—in this case BMI—we can begin to identify biological pathways relevant to disease onset.

Published
2021

49. Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study

Author

Stepien, M. Keski-Rahkonen, P. Kiss, A. Robinot, N. Duarte-Salles, T. Murphy, N. Perlemuter, G. Viallon, V. Tjønneland, A. Rostgaard-Hansen, A.L. Dahm, C.C. Overvad, K. Boutron-Ruault, M.-C. Mancini, F.R. Mahamat-Saleh, Y. Aleksandrova, K. Kaaks, R. Kühn, T. Trichopoulou, A. Karakatsani, A. Panico, S. Tumino, R. Palli, D. Tagliabue, G. Naccarati, A. Vermeulen, R.C.H. Bueno-de-Mesquita, H.B. Weiderpass, E. Skeie, G. Ramón Quirós, J. Ardanaz, E. Mokoroa, O. Sala, N. Sánchez, M.-J. Huerta, J.M. Winkvist, A. Harlid, S. Ohlsson, B. Sjöberg, K. Schmidt, J.A. Wareham, N. Khaw, K.-T. Ferrari, P. Rothwell, J.A. Gunter, M. Riboli, E. Scalbert, A. Jenab, M.

Subjects
digestive system diseases
Abstract

Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development. © 2020 UICC

Published
2021

50. Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants

Author

Zhou, B, Carrillo-Larco, Rm, Danaei, G, Riley, Lm, Paciorek, Cj, Stevens, Ga, Gregg, Ew, Bennett, Je, Solomon, B, Singleton, Rk, Sophiea, Mk, Iurilli, Mlc, Lhoste, Vpf, Cowan, Mj, Savin, S, Woodward, M, Balanova, Y, Cifkova, R, Damasceno, A, Elliott, P, Farzadfar, F, He, J, Ikeda, N, Kengne, Ap, Khang, Yh, Kim, Hc, Laxmaiah, A, Lin, Hh, Maira, Pm, Miranda, Jj, Neuhauser, H, Sundstrom, J, Varghese, C, Widyahening, Is, Zdrojewski, T, Ezzati, M, Abarca-Gomez, L, Abdeen, Za, Rahim, Hfa, Abu-Rmeileh, Nm, Acosta-Cazares, B, Adams, Rj, Aekplakorn, W, Afsana, K, Afzal, S, Agdeppa, Ia, Aghazadeh-Attari, J, Aguilar-Salinas, Ca, Agyemang, C, Ahmad, Na, Ahmadi, A, Ahmadi, N, Ahmadizar, F, Ahmed, Sh, Ahrens, W, Ajlouni, K, Al-Raddadi, R, Alarouj, M, Albuhairan, F, Aldhukair, S, Ali, Mm, Alkandari, A, Alkerwi, A, Allin, K, Aly, E, Amarapurkar, Dn, Amougou, N, Amouyel, P, Andersen, Lb, Anderssen, Sa, Anjana, Rm, Ansari-Moghaddam, A, Ansong, D, Aounallah-Skhiri, H, Araujo, J, Ariansen, I, Aris, T, Arku, Re, Arlappa, N, Aryal, Kk, Aspelund, T, Assah, Fk, Assuncao, Mcf, Auvinen, J, Avdicova, M, Azevedo, A, Azimi-Nezhad, M, Azizi, F, Azmin, M, Babu, Bv, Bahijri, S, Balakrishna, N, Bamoshmoosh, M, Banach, M, Banadinovic, M, Bandosz, P, Banegas, Jr, Baran, J, Barbagallo, Cm, Barcelo, A, Barkat, A, Barreto, M, Barros, Ajd, Barros, Mvg, Bartosiewicz, A, Basit, A, Bastos, Jld, Bata, I, Batieha, Am, Batyrbek, A, Baur, La, Beaglehole, R, Belavendra, A, Ben Romdhane, H, Benet, M, Benson, Ls, Berkinbayev, S, Bernabe-Ortiz, A, Bettiol, H, Bezerra, J, Bhagyalaxmi, A, Bhargava, Sk, Bia, D, Biasch, K, Lele, Ecb, Bikbov, Mm, Bista, B, Bjerregaard, P, Bjertness, E, Bjertness, Mb, Bjorkelund, C, Bloch, Kv, Blokstra, A, Bo, S, Bobak, M, Boeing, H, Boggia, Jg, Boissonnet, Cp, Bojesen, Se, Bongard, V, Bonilla-Vargas, A, Bopp, M, Borghs, H, Bovet, P, Boyer, Cb, Braeckman, L, Brajkovich, I, Branca, F, Breckenkamp, J, Brenner, H, Brewster, Lm, Briceno, Y, Brito, M, Bruno, G, Bueno-de-Mesquita, Hb, 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Kazakbaeva, Ulrich Keil, Lital Keinan Boker, Sirkka Keinänen-Kiukaanniemi, Roya Kelishadi, Han Cg Kemper, Maryam Keramati, Alina Kerimkulova, Mathilde Kersting, Timothy Key, Yousef Saleh Khader, Davood Khalili, Kay-Tee Khaw, Bahareh Kheiri, Motahareh Kheradmand, Alireza Khosravi, Ursula Kiechl-Kohlendorfer, Stefan Kiechl, Japhet Killewo, Dong Wook Kim, Jeongseon Kim, Heidi Klakk, Magdalena Klimek, Jurate Klumbiene, Michael Knoflach, Elin Kolle, Patrick Kolsteren, Jukka P Kontto, Raija Korpelainen, Paul Korrovits, Jelena Kos, Seppo Koskinen, Katsuyasu Kouda, Sudhir Kowlessur, Slawomir Koziel, Jana Kratenova, Vilma Kriaucioniene, Peter Lund Kristensen, Steiner Krokstad, Daan Kromhout, Herculina S Kruger, Ruzena Kubinova, Renata Kuciene, Urho M Kujala, Zbigniew Kulaga, R Krishna Kumar, Pawel Kurjata, Yadlapalli S Kusuma, Vladimir Kutsenko, Kari Kuulasmaa, Catherine Kyobutungi, Tiina Laatikainen, Carl Lachat, Youcef Laid, Tai Hing Lam, Orlando Landrove, Vera Lanska, Georg Lappas, Bagher Larijani, Tint Swe Latt, Gwenaëlle Le Coroller, Khanh Le Nguyen Bao, Tuyen D Le, Jeannette Lee, Jeonghee Lee, Nils Lehmann, Terho Lehtimäki, Daniel Lemogoum, Naomi S Levitt, Yanping Li, Christa L Lilly, Wei-Yen Lim, M Fernanda Lima-Costa, Xu Lin, Yi-Ting Lin, Lars Lind, Vijaya Lingam, Allan Linneberg, Lauren Lissner, Mieczyslaw Litwin, Wei-Cheng Lo, Helle-Mai Loit, Esther Lopez-Garcia, Tania Lopez, Paulo A Lotufo, José Eugenio Lozano, Iva Lukačević Lovrenčić, Janice L Lukrafka, Dalia Luksiene, Annamari Lundqvist, Robert Lundqvist, Nuno Lunet, Michala Lustigová, Edyta Luszczki, Guansheng Ma, Jun Ma, George Ll Machado-Coelho, Aristides M Machado-Rodrigues, Enguerran Macia, Luisa M Macieira, Ahmed A Madar, Stefania Maggi, Dianna J Magliano, Emmanuella Magriplis, Gowri Mahasampath, Bernard Maire, Marjeta Majer, Marcia Makdisse, Fatemeh Malekzadeh, Reza Malekzadeh, Rahul Malhotra, Kodavanti Mallikharjuna Rao, Sofia K Malyutina, Lynell V Maniego, Yannis Manios, Jim I Mann, Fariborz 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D. A., Peres, Marco A., Peters, Annette, Petkeviciene, Janina, Peykari, Niloofar, Son Thai Pham, Pichardo, Rafael N., Pigeot, Iris, Pikhart, Hynek, Pilav, Aida, Pilotto, Lorenza, Pitakaka, Freda, Piwonska, Aleksandra, Pizarro, Andreia N., Plans-Rubio, Pedro, Polasek, Ozren, Porta, Miquel, Poudyal, Anil, Pourfarzi, Farhad, Pourshams, Akram, Poustchi, Hossein, Pradeepa, Rajendra, Price, Alison J., Price, Jacqueline F., Providencia, Rui, Puhakka, Soile E., Puiu, Maria, Punab, Margus, Qasrawi, Radwan F., Qorbani, Mostafa, Queiroz, Daniel, Tran Quoc Bao, Radic, Ivana, Radisauskas, Ricardas, Rahimikazerooni, Salar, Rahman, Mahfuzar, Raitakari, Olli, Raj, Manu, Rakhimova, Ellina M., Rao, Sudha Ramachandra, Ramachandran, Ambady, Ramos, Elisabete, Rampal, Lekhraj, Rampal, Sanjay, Rangel Reina, Daniel A., Rarra, Vayia, Rech, Cassiano Ricardo, Redon, Josep, Reganit, Paul Ferdinand M., Regecova, Valeria, Revilla, Luis, Rezaianzadeh, Abbas, Ribeiro, Robespierre, Riboli, Elio, Richter, Adrian, Rigo, Fernando, de Wit, Tobias F. Rinke, Ritti-Dias, Raphael M., Robitaille, Cynthia, Rodriguez-Artalejo, Fernando, del Cristo Rodriguez-Perez, Maria, Rodriguez-Villamizar, Laura A., Roggenbuck, Ulla, Rojas-Martinez, Rosalba, Romaguera, Dora, Romeo, Elisabetta L., Rosengren, Annika, Roy, Joel G. R., Rubinstein, Adolfo, Ruidavets, Jean-Bernard, Sandra Ruiz-Betancourt, Blanca, Ruiz-Castell, Maria, Rusakova, Iuliia A., Russo, Paola, Rutkowski, Marcin, Sabanayagam, Charumathi, Sabbaghi, Hamideh, Sachdev, Harshpal S., Sadjadi, Alireza, Safarpour, Ali Reza, Safi, Sare, Safiri, Saeid, Saidi, Olfa, Saki, Nader, Salanave, Benoit, Salazar Martinez, Eduardo, Salmeron, Diego, Salomaa, Veikko, Salonen, Jukka T., Salvetti, Massimo, Sanchez-Abanto, Jose, Sans, Susana, Santos, Diana A., Santos, Ina S., Santos, Lelita C., Santos, Maria Paula, Santos, Rute, Saramies, Jouko L., Sardinha, Luis B., Sarganas, Giselle, Sarrafzadegan, Nizal, Sathish, Thirunavukkarasu, Saum, Kai-Uwe, Savva, Savvas, Sawada, Norie, Sbaraini, Mariana, Scazufca, Marcia, Schaan, Beatriz D., Schargrodsky, Herman, Schipf, Sabine, Schmidt, Carsten O., Schnohr, Peter, Schoettker, Ben, Schramm, Sara, Schultsz, Constance, Schutte, Aletta E., Sebert, Sylvain, Sein, Aye Aye, Sen, Abhijit, Senbanjo, Idowu O., Sepanlou, Sadaf G., Servais, Jennifer, Shalnova, Svetlana A., Shamah-Levy, Teresa, Shamshirgaran, Morteza, Shanthirani, Coimbatore Subramaniam, Sharafkhah, Maryam, Sharma, Sanjib K., Shaw, Jonathan E., Shayanrad, Amaneh, Shayesteh, Ali Akbar, Shi, Zumin, Shibuya, Kenji, Shimizu-Furusawa, Hana, Shin, Dong Wook, Shirani, Majid, Shiri, Rahman, Shrestha, Namuna, Si-Ramlee, Khairil, Siani, Alfonso, Siantar, Rosalynn, Sibai, Abla M., de Moura Silva, Caroline Ramos, Santos Silva, Diego Augusto, Simon, Mary, Simons, Judith, Simons, Leon A., Sjostrom, Michael, Slowikowska-Hilczer, Jolanta, Slusarczyk, Przemyslaw, Smeeth, Liam, So, Hung-Kwan, Soares, Fernanda Cunha, Sobngwi, Eugene, Soderberg, Stefan, Soemantri, Agustinus, Sofat, Reecha, Solfrizzi, Vincenzo, Somi, Mohammad Hossein, Sonestedt, Emily, Song, Yi, Sorensen, Thorkild I. 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Goya, Wareham, Nicholas, Wei, Wenbin, Weres, Aneta, Werner, Bo, Whincup, Peter H., Widhalm, Kurt, Wiecek, Andrzej, Wilks, Rainford J., Willeit, Johann, Willeit, Peter, Williams, Emmanuel A., Wilsgaard, Tom, Wojtyniak, Bogdan, Wong-McClure, Roy A., Wong, Andrew, Wong, Tien Yin, Woo, Jean, Wu, Frederick C., Wu, Shouling, Wyszynska, Justyna, Xu, Haiquan, Xu, Liang, Yaacob, Nor Azwany, Yan, Weili, Yang, Ling, Yang, Xiaoguang, Yang, Yang, Yasuharu, Tabara, Ye, Xingwang, Yiallouros, Panayiotis K., Yoosefi, Moein, Yoshihara, Akihiro, You, San-Lin, Younger-Coleman, Novie O., Yusoff, Ahmad Faudzi, Zainuddin, Ahmad A., Zakavi, Seyed Rasoul, Zamani, Farhad, Zambon, Sabina, Zampelas, Antonis, Elisa Zapata, Maria, Zaw, Ko Ko, Zejglicova, Kristyna, Vrkic, Tajana Zeljkovic, Zeng, Yi, Zhang, Luxia, Zhao, Dong, Zhao, Ming-Hui, Zhen, Shiqi, Zheng, Yingfeng, Zholdin, Bekbolat, Zhu, Dan, Zins, Marie, Zitt, Emanuel, Zocalo, Yanina, Zoghlami, Nada, Zuniga Cisneros, Julio., School of Medicine, ACS - Diabetes & metabolism, APH - Global Health, Pulmonology, Medical Informatics, Adult Psychiatry, Global Health, APH - Quality of Care, APH - Methodology, Vascular Medicine, ACS - Atherosclerosis & ischemic syndromes, Anesthesiology, Graduate School, and ACS - Heart failure & arrhythmias

Subjects
Male, Latin Americans, Nutrition and Disease, Epidemiology, [SDV]Life Sciences [q-bio], Medizin, BLOOD-PRESSURE, 030204 cardiovascular system & hematology, Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants, Hypertension, Prevalence, Control, Tretament, GUIDELINES, Global Health, Worldwide trends, 0302 clinical medicine, Hypertension prevalence, Voeding en Ziekte, Medicine and Health Sciences, kohonnut verenpaine, Medicine, 030212 general & internal medicine, Prevention and Control, 11 Medical and Health Sciences, ComputingMilieux_MISCELLANEOUS, education.field_of_study, food and beverages, Public Health, Global Health, Social Medicine and Epidemiology, General Medicine, Noncommunicable diseases, Period prevalence, Middle Aged, kansainvälinen vertailu, 3142 Public health care science, environmental and occupational health, 3. Good health, MIDDLE-INCOME, Pooled analysis, SYSTEMATIC ANALYSIS, INCOME COUNTRIES, ADULTS, PREVENTION, MANAGEMENT, ADHERENCE, DIAGNOSIS, Western europe, [SDE]Environmental Sciences, Hypertension/diagnosis, NCD Risk Factor Collaboration (NCD-RisC), Female, B990 Subjects Allied to Medicine not elsewhere classified, Life Sciences & Biomedicine, Adult, health-care, esiintyvyys, Central asia, Population, Nursing, 3121 Internal medicine, 03 medical and health sciences, Medicine, General & Internal, Drug Therapy, General & Internal Medicine, Life Science, Humans, ddc:610, education, Antihypertensive Agents, VLAG, Aged, Science & Technology, Antihypertensive Agents/therapeutic use, business.industry, Omvårdnad, fungi, General and internal medicine, Estados de Saúde e de Doença, Taking medication, Treatment, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Blood pressure, Faculdade de Ciências Sociais, 3121 General medicine, internal medicine and other clinical medicine, lääkehoito, 1182 Biochemistry, cell and molecular biology, business, Demography
Abstract

Background: hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. Methods: we used data from 1990 to 2019 on people aged 30-79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. Findings: the number of people aged 30-79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306-359) million women and 317 (292-344) million men in 1990 to 626 (584-668) million women and 652 (604-698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55-62) of women and 49% (46-52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43-51) of women and 38% (35-41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20-27) for women and 18% (16-21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. Interpretation Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings., British Heart Foundation Centre of Research Excellence Grant; World Health Organization (WHO); Abdul Latif Jameel Institute for Disease and Emergency Analytics Fellowship

Published
2021

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