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428 results on '"Wareham, N.J."'

1. Previous fracture and subsequent fracture risk: a meta-analysis to update FRAX

Author: Kanis, J.A., Johansson, H., McCloskey, E.V., Liu, E., Åkesson, K.E., Anderson, F.A., Azagra, R., Bager, C.L., Beaudart, C., Bischoff-Ferrari, H.A., Biver, E., Bruyère, O., Cauley, J.A., Center, J.R., Chapurlat, R., Christiansen, C., Cooper, C., Crandall, C.J., Cummings, S.R., da Silva, J.A.P., Dawson-Hughes, B., Diez-Perez, A., Dufour, A.B., Eisman, J.A., Elders, P.J.M., Ferrari, S., Fujita, Y., Fujiwara, S., Glüer, C.-C., Goldshtein, I., Goltzman, D., Gudnason, V., Hall, J., Hans, D., Hoff, M., Hollick, R.J., Huisman, M., Iki, M., Ish-Shalom, S., Jones, G., Karlsson, M.K., Khosla, S., Kiel, D.P., Koh, W.-P., Koromani, F., Kotowicz, M.A., Kröger, H., Kwok, T., Lamy, O., Langhammer, A., Larijani, B., Lippuner, K., Mellström, D., Merlijn, T., Nordström, A., Nordström, P., O’Neill, T.W., Obermayer-Pietsch, B., Ohlsson, C., Orwoll, E.S., Pasco, J.A., Rivadeneira, F., Schott, A.-M., Shiroma, E.J., Siggeirsdottir, K., Simonsick, E.M., Sornay-Rendu, E., Sund, R., Swart, K.M.A., Szulc, P., Tamaki, J., Torgerson, D.J., van Schoor, N.M., van Staa, T.P., Vila, J., Wareham, N.J., Wright, N.C., Yoshimura, N., Zillikens, M.C., Zwart, M., Vandenput, L., Harvey, N.C., Lorentzon, M., and Leslie, W.D.
Published: 2023
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2. An investigation of factors affecting changes in health behaviours during the COVID-19 pandemic in a UK population–based cohort study

Author: Braithwaite, V.S., Sharp, S.J., Koulman, A., Wareham, N.J., and Rennie, K.L.
Published: 2022
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3. Genetic insights into resting heart rate and its role in cardiovascular disease.

Author: Vegte, Y.J. van de, Eppinga, R.N., Ende, M.Y. van der, Hagemeijer, Y.P., Mahendran, Y., Salfati, E., Smith, A.V., Tan, V.Y., Arking, D.E., Ntalla, I., Appel, E.V., Schurmann, C., Brody, J.A., Rueedi, R., Polasek, O., Sveinbjornsson, G., Lecoeur, C., Ladenvall, C., Zhao, J.H., Isaacs, A., Wang, L., Luan, Jian'an, Hwang, S.J., Mononen, N., Auro, K., Jackson, A.U., Bielak, L.F., Zeng, L., Shah, N., Nethander, M., Campbell, A., Rankinen, T., Pechlivanis, S., Qi, L., Zhao, Wei, Rizzi, F., Tanaka, T., Robino, A., Cocca, M., Lange, L., Müller-Nurasyid, M., Roselli, C., Zhang, W, Kleber, M.E., Guo, X., Lin, H.J., Pavani, F., Galesloot, T.E., Noordam, R., Milaneschi, Y., Schraut, K.E., Hoed, M. den, Degenhardt, F., Trompet, S., Berg, M.E. van den, Pistis, G., Tham, Y.C., Weiss, S., Sim, X.S., Li, H.L., Most, P.J. van der, Nolte, I.M., Lyytikäinen, L.P., Said, M.A., Witte, D.R., Iribarren, C., Launer, L., Ring, S.M., Vries, P.S. de, Sever, P., Linneberg, A., Bottinger, E.P., Padmanabhan, S., Psaty, B.M., Sotoodehnia, N., Kolcic, I., Arnar, D.O., Gudbjartsson, D.F., Holm, H., Balkau, B., Silva, C.T., Newton-Cheh, C.H., Nikus, K., Salo, P., Mohlke, K.L., Peyser, P.A., Schunkert, H., Lorentzon, M., Lahti, J., Rao, D.C., Cornelis, M.C., Faul, J.D., Smith, J.A., Stolarz-Skrzypek, K., Bandinelli, S., Concas, M.P., Sinagra, G., Meitinger, T., Waldenberger, M., Sinner, M.F., Strauch, K., Delgado, G.E., Taylor, K.D., Yao, J., Foco, L., Melander, O., Graaf, J. de, Mutsert, R. de, Geus, E.J.C. de, Johansson, Å., Joshi, P.K., Lind, L., Franke, A., Macfarlane, P.W., Tarasov, K.V., Tan, N., Felix, S.B., Tai, E.S., Quek, D.Q., Snieder, H., Ormel, J., Ingelsson, M., Lindgren, C., Morris, A.P., Raitakari, O.T., Hansen, T., Assimes, T., Gudnason, V., Timpson, N.J., Morrison, A.C., Munroe, P.B., Strachan, D.P., Grarup, N., Loos, R.J.F., Heckbert, S.R., Vollenweider, P., Hayward, C., Stefansson, K., Froguel, P., Groop, L., Wareham, N.J., Duijn, C.M. van, Feitosa, M.F., O'Donnell, C.J., Kähönen, M., Perola, M., Boehnke, M., Kardia, S.L.R., Erdmann, J., Palmer, C.N.A., Ohlsson, C., Porteous, D.J., Eriksson, J.G., Bouchard, C., Moebus, S., Kraft, P., Weir, D.R., Cusi, D., Ferrucci, L., Ulivi, S., Girotto, G., Correa, A., Kääb, S., Peters, A., Chambers, J.C., Kooner, J.S., März, W., Rotter, J.I., Hicks, A.A., Smith, J.G., Kiemeney, L.A.L.M., Mook-Kanamori, D.O., Penninx, B.W.J.H., Gyllensten, U., Wilson, J.F., Burgess, S., Sundström, J., Lieb, W., Jukema, J.W., Eijgelsheim, M., Lakatta, E.L.M., Cheng, C.Y., Dörr, M., Wong, T.Y., Sabanayagam, C., Oldehinkel, A.J., Riese, H., Lehtimäki, T., Verweij, N., Harst, P. van der, Vegte, Y.J. van de, Eppinga, R.N., Ende, M.Y. van der, Hagemeijer, Y.P., Mahendran, Y., Salfati, E., Smith, A.V., Tan, V.Y., Arking, D.E., Ntalla, I., Appel, E.V., Schurmann, C., Brody, J.A., Rueedi, R., Polasek, O., Sveinbjornsson, G., Lecoeur, C., Ladenvall, C., Zhao, J.H., Isaacs, A., Wang, L., Luan, Jian'an, Hwang, S.J., Mononen, N., Auro, K., Jackson, A.U., Bielak, L.F., Zeng, L., Shah, N., Nethander, M., Campbell, A., Rankinen, T., Pechlivanis, S., Qi, L., Zhao, Wei, Rizzi, F., Tanaka, T., Robino, A., Cocca, M., Lange, L., Müller-Nurasyid, M., Roselli, C., Zhang, W, Kleber, M.E., Guo, X., Lin, H.J., Pavani, F., Galesloot, T.E., Noordam, R., Milaneschi, Y., Schraut, K.E., Hoed, M. den, Degenhardt, F., Trompet, S., Berg, M.E. van den, Pistis, G., Tham, Y.C., Weiss, S., Sim, X.S., Li, H.L., Most, P.J. van der, Nolte, I.M., Lyytikäinen, L.P., Said, M.A., Witte, D.R., Iribarren, C., Launer, L., Ring, S.M., Vries, P.S. de, Sever, P., Linneberg, A., Bottinger, E.P., Padmanabhan, S., Psaty, B.M., Sotoodehnia, N., Kolcic, I., Arnar, D.O., Gudbjartsson, D.F., Holm, H., Balkau, B., Silva, C.T., Newton-Cheh, C.H., Nikus, K., Salo, P., Mohlke, K.L., Peyser, P.A., Schunkert, H., Lorentzon, M., Lahti, J., Rao, D.C., Cornelis, M.C., Faul, J.D., Smith, J.A., Stolarz-Skrzypek, K., Bandinelli, S., Concas, M.P., Sinagra, G., Meitinger, T., Waldenberger, M., Sinner, M.F., Strauch, K., Delgado, G.E., Taylor, K.D., Yao, J., Foco, L., Melander, O., Graaf, J. de, Mutsert, R. de, Geus, E.J.C. de, Johansson, Å., Joshi, P.K., Lind, L., Franke, A., Macfarlane, P.W., Tarasov, K.V., Tan, N., Felix, S.B., Tai, E.S., Quek, D.Q., Snieder, H., Ormel, J., Ingelsson, M., Lindgren, C., Morris, A.P., Raitakari, O.T., Hansen, T., Assimes, T., Gudnason, V., Timpson, N.J., Morrison, A.C., Munroe, P.B., Strachan, D.P., Grarup, N., Loos, R.J.F., Heckbert, S.R., Vollenweider, P., Hayward, C., Stefansson, K., Froguel, P., Groop, L., Wareham, N.J., Duijn, C.M. van, Feitosa, M.F., O'Donnell, C.J., Kähönen, M., Perola, M., Boehnke, M., Kardia, S.L.R., Erdmann, J., Palmer, C.N.A., Ohlsson, C., Porteous, D.J., Eriksson, J.G., Bouchard, C., Moebus, S., Kraft, P., Weir, D.R., Cusi, D., Ferrucci, L., Ulivi, S., Girotto, G., Correa, A., Kääb, S., Peters, A., Chambers, J.C., Kooner, J.S., März, W., Rotter, J.I., Hicks, A.A., Smith, J.G., Kiemeney, L.A.L.M., Mook-Kanamori, D.O., Penninx, B.W.J.H., Gyllensten, U., Wilson, J.F., Burgess, S., Sundström, J., Lieb, W., Jukema, J.W., Eijgelsheim, M., Lakatta, E.L.M., Cheng, C.Y., Dörr, M., Wong, T.Y., Sabanayagam, C., Oldehinkel, A.J., Riese, H., Lehtimäki, T., Verweij, N., and Harst, P. van der
Abstract: Contains fulltext : 296013.pdf (Publisher’s version ) (Open Access), Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.
Published: 2023

4. Update of the fracture risk prediction tool FRAX: A systematic review of potential cohorts and analysis plan

Author: Vandenput, Lisbeth, Johansson, H., McCloskey, E. V., Liu, E., Akesson, Kristina E., Anderson, F.A., Azagra, R., Bager, C.L., Beaudart, Charlotte, Bischoff-Ferrari, H.A., Biver, E., Bruyère, Olivier, Cauley, J.A., Center, J.R., Chapulat, R., Christiansen, C., Cooper, Cyrus, Crandall, Carolyn J., Cummings, Steven, da Silva, J.A.P., Dawson-Hughes, Bess, Diez-Pérez, A., Dufour, Alyssa B., Eisman, J.A., Elders, Petra J.M., Ferrari, S., Fujita, Y., Fujiwara, S., Glüer, C.C., Goldstein, I., Goltzman, D., Gudnason, V., Hall, J., Hans, D., Hoff, M., Hollick, Rosemary J., Huisman, Martijn, Iki, M., Ish-Shalom, S., Jones, G., Karlsson, M.K., Khosla, Sundeep, Kiel, D.P., Koh, W-P, Koromani, F., Kotowicz, M.A., Kroger, H., Kwok, T., Lamy, Olivier, Langhammer, Arnulf, Larijani, Bagher, Lippuner, Kurt, Mellström, D, Merlijn, Thomas, Nordstrom, A., Nordstrom, P., O'Neill, T.W., Obermayer-Piestch, B., Harvey, Nicholas, Kanis, J A., Ohlsson, C., Orwoll, E.S., Pasco, J.A., Rivadeneira, F., Schei, B., Schott, A.M., Shiroma, E.J., Siggeirsdottir, K., Simonsick, E.M., Sornay-Rendu, E., Sund, R., Swart, K.M.A., Szulc, P., Tamaki, J., Torgerson, D.J., Van Schoor, N.M., van Staa, T.P., Vilas, J.C., Wareham, N.J, Wright, N.C., Yoshimura, N., Zillikens, M.C., Zwart, M., Lorentzon, M., and Leslie, W.D.
Abstract: Summary: We describe the collection of cohorts together with the analysis plan for an update of the fracture risk prediction tool FRAX with respect to current and novel risk factors. The resource comprises 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. Introduction: The availability of the fracture risk assessment tool FRAX® has substantially enhanced the targeting of treatment to those at high risk of fracture with FRAX now incorporated into more than 100 clinical osteoporosis guidelines worldwide. The aim of this study is to determine whether the current algorithms can be further optimised with respect to current and novel risk factors. Methods: A computerised literature search was performed in PubMed from inception until May 17, 2019, to identify eligible cohorts for updating the FRAX coefficients. Additionally, we searched the abstracts of conference proceedings of the American Society for Bone and Mineral Research, European Calcified Tissue Society and World Congress of Osteoporosis. Prospective cohort studies with data on baseline clinical risk factors and incident fractures were eligible. Results: Of the 836 records retrieved, 53 were selected for full-text assessment after screening on title and abstract. Twelve cohorts were deemed eligible and of these, 4 novel cohorts were identified. These cohorts, together with 60 previously identified cohorts, will provide the resource for constructing an updated version of FRAX comprising 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. For each known and candidate risk factor, multivariate hazard functions for hip fracture, major osteoporotic fracture and death will be tested using extended Poisson regression. Sex- and/or ethnicity-specific differences in the weights of the risk factors will be investigated. After meta-analyses of the cohort-specific beta coefficients for each risk factor, models comprising 10-year probability of hip and major osteoporotic fracture, with or without femoral neck bone mineral density, will be computed. Conclusions: These assembled cohorts and described models will provide the framework for an updated FRAX tool enabling enhanced assessment of fracture risk (PROSPERO (CRD42021227266)).
Published: 2022

5. Update of the fracture risk prediction tool FRAX : a systematic review of potential cohorts and analysis plan

Author: Vandenput, L., Johansson, H., McCloskey, E.V., Liu, E., Åkesson, K.E., Anderson, F.A., Azagra, R., Bager, C.L., Beaudart, C., Bischoff-Ferrari, H.A., Biver, E., Bruyère, O., Cauley, J.A., Center, J.R., Chapurlat, R., Christiansen, C., Cooper, C., Crandall, C.J., Cummings, S.R., da Silva, J.A.P., Dawson-Hughes, B., Diez-Perez, A., Dufour, A.B., Eisman, J.A., Elders, P.J.M., Ferrari, S., Fujita, Y., Fujiwara, S., Glüer, C.-C., Goldshtein, I., Goltzman, D., Gudnason, V., Hall, J., Hans, D., Hoff, M., Hollick, R.J., Huisman, M., Iki, M., Ish-Shalom, S., Jones, G., Karlsson, M.K., Khosla, S., Kiel, D.P., Koh, W.-P., Koromani, F., Kotowicz, M.A., Kröger, H., Kwok, T., Lamy, O., Langhammer, A., Larijani, B., Lippuner, K., Mellström, D., Merlijn, T., Nordström, Annika, Nordström, Peter, O’Neill, T.W., Obermayer-Pietsch, B., Ohlsson, C., Orwoll, E.S., Pasco, J.A., Rivadeneira, F., Schei, B., Schott, A.-M., Shiroma, E.J., Siggeirsdottir, K., Simonsick, E.M., Sornay-Rendu, E., Sund, R., Swart, K.M.A., Szulc, P., Tamaki, J., Torgerson, D.J., van Schoor, N.M., van Staa, T.P., Vila, J., Wareham, N.J., Wright, N.C., Yoshimura, N., Zillikens, M.C., Zwart, M., Harvey, N.C., Lorentzon, M., Leslie, W.D., Kanis, J.A., Vandenput, L., Johansson, H., McCloskey, E.V., Liu, E., Åkesson, K.E., Anderson, F.A., Azagra, R., Bager, C.L., Beaudart, C., Bischoff-Ferrari, H.A., Biver, E., Bruyère, O., Cauley, J.A., Center, J.R., Chapurlat, R., Christiansen, C., Cooper, C., Crandall, C.J., Cummings, S.R., da Silva, J.A.P., Dawson-Hughes, B., Diez-Perez, A., Dufour, A.B., Eisman, J.A., Elders, P.J.M., Ferrari, S., Fujita, Y., Fujiwara, S., Glüer, C.-C., Goldshtein, I., Goltzman, D., Gudnason, V., Hall, J., Hans, D., Hoff, M., Hollick, R.J., Huisman, M., Iki, M., Ish-Shalom, S., Jones, G., Karlsson, M.K., Khosla, S., Kiel, D.P., Koh, W.-P., Koromani, F., Kotowicz, M.A., Kröger, H., Kwok, T., Lamy, O., Langhammer, A., Larijani, B., Lippuner, K., Mellström, D., Merlijn, T., Nordström, Annika, Nordström, Peter, O’Neill, T.W., Obermayer-Pietsch, B., Ohlsson, C., Orwoll, E.S., Pasco, J.A., Rivadeneira, F., Schei, B., Schott, A.-M., Shiroma, E.J., Siggeirsdottir, K., Simonsick, E.M., Sornay-Rendu, E., Sund, R., Swart, K.M.A., Szulc, P., Tamaki, J., Torgerson, D.J., van Schoor, N.M., van Staa, T.P., Vila, J., Wareham, N.J., Wright, N.C., Yoshimura, N., Zillikens, M.C., Zwart, M., Harvey, N.C., Lorentzon, M., Leslie, W.D., and Kanis, J.A.
Abstract: Summary: We describe the collection of cohorts together with the analysis plan for an update of the fracture risk prediction tool FRAX with respect to current and novel risk factors. The resource comprises 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. Introduction: The availability of the fracture risk assessment tool FRAX® has substantially enhanced the targeting of treatment to those at high risk of fracture with FRAX now incorporated into more than 100 clinical osteoporosis guidelines worldwide. The aim of this study is to determine whether the current algorithms can be further optimised with respect to current and novel risk factors. Methods: A computerised literature search was performed in PubMed from inception until May 17, 2019, to identify eligible cohorts for updating the FRAX coefficients. Additionally, we searched the abstracts of conference proceedings of the American Society for Bone and Mineral Research, European Calcified Tissue Society and World Congress of Osteoporosis. Prospective cohort studies with data on baseline clinical risk factors and incident fractures were eligible. Results: Of the 836 records retrieved, 53 were selected for full-text assessment after screening on title and abstract. Twelve cohorts were deemed eligible and of these, 4 novel cohorts were identified. These cohorts, together with 60 previously identified cohorts, will provide the resource for constructing an updated version of FRAX comprising 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. For each known and candidate risk factor, multivariate hazard functions for hip fracture, major osteoporotic fracture and death will be tested using extended Poisson regression. Sex- and/or ethnicity-specific differences in the weights of the risk factors will be investigated. After meta-analyses of
Published: 2022
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6. The association between a biomarker score for fruit and vegetable intake and incident type 2 diabetes: the EPIC-Norfolk study

Author: Cooper, A.J.M., Sharp, S.J., Luben, R.N., Khaw, K.-T., Wareham, N.J., and Forouhi, N.G.
Subjects: Food research, Fruit -- Health aspects, Vegetables -- Health aspects, Type 2 diabetes -- Prevention, Ingestion -- Research, Food habits -- Research, Food/cooking/nutrition, Health
Abstract: BACKGROUND/OBJECTIVES: Biomarkers for a mixed fruit and vegetable (FV) diet are needed to provide a better understanding of the association between FV intake and type 2 diabetes. We aimed to examine the prospective association between a composite score comprised of three biomarkers of FV intake in free-living populations and incident diabetes. SUBJECTS/METHODS: A total of 318 incident diabetes cases and 926 controls from the EPIC (European Prospective Investigation of Cancer)-Norfolk study aged 40-79 years at baseline (1993-1997), completed 7-day prospective food diary and had plasma vitamin C and carotenoid measures. A composite biomarker score (CB-score) comprising the sum of plasma vitamin C, beta-carotene and lutein was derived. Odds ratios (ORs) and 95% confidence intervals (CIs) for incident diabetes were estimated using multivariable logistic regression. RESULTS: A strong inverse association was found between the CB-score and incident diabetes. The ORs (95% CI) of diabetes comparing quartiles Q2, Q3 and Q4 of the CB-score with Q1 (reference category) were 0.70 (0.49, 1.00), 0.34 (0.23, 0.52) and 0.19 (0.12, 0.32), respectively, and 0.49 (0.40, 0.58) per s.d. change in CB-score in a model adjusted for demographic and lifestyle factors. The association was marginally attenuated after additionally adjusting for body mass index and waist circumference (0.60 (0.49 and 0.74) per s.d. change in CB-score). CONCLUSIONS: A combination of biomarkers representing the intake of a mixed FV diet was strongly inversely associated with incident diabetes. These findings provide further support for measuring dietary biomarkers in studies of diet-disease associations and highlight the importance of consuming FV for the prevention of diabetes. European Journal of Clinical Nutrition (2015) 69, 449-454; doi: 10.1038/ejcn.2014.246; published online 12 November 2014, INTRODUCTION Fruit and vegetable (FV) intake has been advocated for the prevention of type 2 diabetes, (1) but the epidemiological findings are inconsistent. (2-7) This is likely owing, in part, [...]
Published: 2015
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7. 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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8. Using cohort studies in lifecourse epidemiology

Author: Cooper, C., Frank, J., Leyland, A., Hardy, R., Lawlor, D.A., Wareham, N.J., Dezateux, C., and Inskip, H.
Published: 2012
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9. Subclinical thyroid dysfunction and incident diabetes: a systematic review and an individual participant data analysis of prospective cohort studies

Author: Alwan, H., Villoz, F., Feller, M., Dullaart, R.P.F., Bakker, S.J.L., Peeters, R.P., Kavousi, M., Bauer, D.C., Cappola, A.R., Yeap, B.B., Walsh, J.P., Brown, S.J., Ceresini, G., Ferrucci, L., Gussekloo, J., Trompet, S., Iacoviello, M., Moon, J.H., Razvi, S., Bensenor, I.M., Azizi, F., Amouzegar, A., Valdes, S., Colomo, N., Wareham, N.J., Jukema, J.W., Westendorp, R.G.J., Kim, K.W., Rodondi, N., Giovane, C. del, Thyroid Studies Collaboration, Groningen Institute for Organ Transplantation (GIOT), Groningen Kidney Center (GKC), Internal Medicine, Epidemiology, Alwan, Heba [0000-0001-5516-6022], Bakker, Stephan JL [0000-0003-3356-6791], Peeters, Robin P [0000-0001-7732-9371], Yeap, Bu B [0000-0002-7612-5892], Razvi, Salman [0000-0002-9047-1556], Amouzegar, Atieh [0000-0001-9433-9408], and Apollo - University of Cambridge Repository
Subjects: Adult, Data Analysis, Male, Endocrinology, Diabetes and Metabolism, Clinical Sciences, Thyrotropin, 610 Medicine & health, Hyperthyroidism, Paediatrics and Reproductive Medicine, Cohort Studies, Endocrinology & Metabolism, Endocrinology, SDG 3 - Good Health and Well-being, Hypothyroidism, 360 Social problems & social services, Clinical Research, Diabetes Mellitus, Humans, Prospective Studies, Metabolic and endocrine, screening and diagnosis, Prevention, Diabetes, General Medicine, Middle Aged, Thyroid Diseases, Detection, Female, 4.2 Evaluation of markers and technologies
Abstract: ObjectiveFew prospective studies have assessed whether individuals with subclinical thyroid dysfunction are more likely to develop diabetes, with conflicting results. In this study, we conducted a systematic review of the literature and an individual participant data analysis of multiple prospective cohorts to investigate the association between subclinical thyroid dysfunction and incident diabetes.MethodsWe performed a systematic review of the literature in Medline, Embase, and the Cochrane Library from inception to February 11, 2022. A two-stage individual participant data analysis was conducted to compare participants with subclinical hypothyroidism and subclinical hyperthyroidism vs euthyroidism at baseline and the adjusted risk of developing diabetes at follow-up.ResultsAmong 61 178 adults from 18 studies, 49% were females, mean age was 58 years, and mean follow-up time was 8.2 years. At the last available follow-up, there was no association between subclinical hypothyroidism and incidence of diabetes (odds ratio (OR) = 1.02, 95% CI: 0.88–1.17, I2 = 0%) or subclinical hyperthyroidism and incidence of diabetes (OR = 1.03, 95% CI: 0.82–1.30, I2 = 0%), in age- and sex-adjusted analyses. Time-to-event analysis showed similar results (hazard ratio for subclinical hypothyroidism: 0.98, 95% CI: 0.87–1.11; hazard ratio for subclinical hyperthyroidism: 1.07, 95% CI: 0.88–1.29). The results were robust in all sub-group and sensitivity analyses.ConclusionsThis is the largest systematic review and individual participant data analysis to date investigating the prospective association between subclinical thyroid dysfunction and diabetes. We did not find an association between subclinical thyroid dysfunction and incident diabetes. Our results do not support screening patients with subclinical thyroid dysfunction for diabetes.Significance statementEvidence is conflicting regarding whether an association exists between subclinical thyroid dysfunction and incident diabetes. We therefore aimed to investigate whether individuals with subclinical thyroid dysfunction are more prone to develop diabetes in the long run as compared to euthyroid individuals. We included data from 18 international cohort studies with 61 178 adults and a mean follow-up time of 8.2 years. We did not find an association between subclinical hypothyroidism or subclinical hyperthyroidism at baseline and incident diabetes at follow-up. Our results have clinical implications as they neither support screening patients with subclinical thyroid dysfunction for diabetes nor treating them in the hope of preventing diabetes in the future. Objective: Few prospective studies have assessed whether individuals with subclinical thyroid dysfunction are more likely to develop diabetes, with conflicting results. In this study, we conducted a systematic review of the literature and an individual participant data analysis of multiple prospective cohorts to investigate the association between subclinical thyroid dysfunction and incident diabetes. Methods: We performed a systematic review of the literature in Medline, Embase, and the Cochrane Library from inception to February 11, 2022. A two-stage individual participant data analysis was conducted to compare participants with subclinical hypothyroidism and subclinical hyperthyroidism vs euthyroidism at baseline and the adjusted risk of developing diabetes at follow-up. Results: Among 61 178 adults from 18 studies, 49% were females, mean age was 58 years, and mean follow-up time was 8.2 years. At the last available follow-up, there was no association between subclinical hypothyroidism and incidence of diabetes (odds ratio (OR) = 1.02, 95% CI: 0.88-1.17, I2 = 0%) or subclinical hyperthyroidism and incidence of diabetes (OR = 1.03, 95% CI: 0.82-1.30, I2 = 0%), in age- and sex-adjusted analyses. Time-to-event analysis showed similar results (hazard ratio for subclinical hypothyroidism: 0.98, 95% CI: 0.87-1.11; hazard ratio for subclinical hyperthyroidism: 1.07, 95% CI: 0.88-1.29). The results were robust in all sub-group and sensitivity analyses. Conclusions: This is the largest systematic review and individual participant data analysis to date investigating the prospective association between subclinical thyroid dysfunction and diabetes. We did not find an association between subclinical thyroid dysfunction and incident diabetes. Our results do not support screening patients with subclinical thyroid dysfunction for diabetes. Significance statement: Evidence is conflicting regarding whether an association exists between subclinical thyroid dysfunction and incident diabetes. We therefore aimed to investigate whether individuals with subclinical thyroid dysfunction are more prone to develop diabetes in the long run as compared to euthyroid individuals. We included data from 18 international cohort studies with 61 178 adults and a mean follow-up time of 8.2 years. We did not find an association between subclinical hypothyroidism or subclinical hyperthyroidism at baseline and incident diabetes at follow-up. Our results have clinical implications as they neither support screening patients with subclinical thyroid dysfunction for diabetes nor treating them in the hope of preventing diabetes in the future.
Published: 2022
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10. 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

11. 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

12. Plant foods, dietary fibre and risk of ischaemic heart disease in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort

Author: Perez-Cornago, A. Crowe, F.L. Appleby, P.N. Bradbury, K.E. Wood, A.M. Jakobsen, M.U. Johnson, L. Sacerdote, C. Steur, M. Weiderpass, E. Würtz, A.M.L. Kühn, T. Katzke, V. Trichopoulou, A. Karakatsani, A. La Vecchia, C. Masala, G. Tumino, R. Panico, S. Sluijs, I. Skeie, G. Imaz, L. Petrova, D. Quirós, J.R. Yohar, S.M.C. Jakszyn, P. Melander, O. Sonestedt, E. Andersson, J. Wennberg, M. Aune, D. Riboli, E. Schulze, M.B. Di Angelantonio, E. Wareham, N.J. Danesh, J. Forouhi, N.G. Butterworth, A.S. Key, T.J.
Subjects: food and beverages
Abstract: Background: Epidemiological evidence indicates that diets rich in plant foods are associated with a lower risk of ischaemic heart disease (IHD), but there is sparse information on fruit and vegetable subtypes and sources of dietary fibre. This study examined the associations of major plant foods, their subtypes and dietary fibre with risk of IHD in the European Prospective Investigation into Cancer and Nutrition (EPIC). Methods: We conducted a prospective analysis of 490 311 men and women without a history of myocardial infarction or stroke at recruitment (12.6 years of follow-up, n cases = 8504), in 10 European countries. Dietary intake was assessed using validated questionnaires, calibrated with 24-h recalls. Multivariable Cox regressions were used to estimate hazard ratios (HR) of IHD. Results: There was a lower risk of IHD with a higher intake of fruit and vegetables combined [HR per 200 g/day higher intake 0.94, 95% confidence interval (CI): 0.90-0.99, P-trend = 0.009], and with total fruits (per 100 g/day 0.97, 0.95-1.00, P-trend = 0.021). There was no evidence for a reduced risk for fruit subtypes, except for bananas. Risk was lower with higher intakes of nuts and seeds (per 10 g/day 0.90, 0.82-0.98, P-trend = 0.020), total fibre (per 10 g/day 0.91, 0.85-0.98, P-trend = 0.015), fruit and vegetable fibre (per 4 g/day 0.95, 0.91-0.99, P-trend = 0.022) and fruit fibre (per 2 g/day 0.97, 0.95-1.00, P-trend = 0.045). No associations were observed between vegetables, vegetables subtypes, legumes, cereals and IHD risk. Conclusions: In this large prospective study, we found some small inverse associations between plant foods and IHD risk, with fruit and vegetables combined being the most strongly inversely associated with risk. Whether these small associations are causal remains unclear. © 2020 The Author(s) 2020. Published by Oxford University Press on behalf of the International Epidemiological Association.
Published: 2021

13. Blood polyphenol concentrations and differentiated thyroid carcinoma in women from the European Prospective Investigation into Cancer and Nutrition (EPIC) study

Author: Zamora-Ros, R., Lujan-Barroso, L., Achaintre, D., Franceschi, S., Kyrø, C., Overvad, K., Tjønneland, A., Truong, T., Lecuyer, L., Boutron-Ruault, M.-C., Katzke, V., Johnson, T.S., Schulze, M.B., Trichopoulou, A., Peppa, E., La Vechia, C., Masala, G., Pala, V., Panico, S., Tumino, R., Ricceri, F., Skeie, G., Ramón Quirós, J., Rodriguez-Barranco, M., Amiano, P., Chirlaque, M.-D., Ardanaz, E., Almquist, M., Hennings, J., Vermeulen, R., Wareham, N.J., Tong, T.Y.N., Aune, D., Byrnes, G., Weiderpass, E., Scalbert, A., Rinaldi, S., Agudo, A., Zamora-Ros, R., Lujan-Barroso, L., Achaintre, D., Franceschi, S., Kyrø, C., Overvad, K., Tjønneland, A., Truong, T., Lecuyer, L., Boutron-Ruault, M.-C., Katzke, V., Johnson, T.S., Schulze, M.B., Trichopoulou, A., Peppa, E., La Vechia, C., Masala, G., Pala, V., Panico, S., Tumino, R., Ricceri, F., Skeie, G., Ramón Quirós, J., Rodriguez-Barranco, M., Amiano, P., Chirlaque, M.-D., Ardanaz, E., Almquist, M., Hennings, J., Vermeulen, R., Wareham, N.J., Tong, T.Y.N., Aune, D., Byrnes, G., Weiderpass, E., Scalbert, A., Rinaldi, S., and Agudo, A.
Abstract: Background: Polyphenols are natural compounds with anticarcinogenic properties in cellular and animal models, but epidemiological evidence determining the associations of these compounds with thyroid cancer (TC) is lacking. Objectives: The aim of this study was to evaluate the relations between blood concentrations of 36 polyphenols and TC risk in EPIC (the European Prospective Investigation into Cancer and Nutrition). Methods: A nested case–control study was conducted on 273 female cases (210 papillary, 45 follicular, and 18 not otherwise specified TC tumors) and 512 strictly matched controls. Blood polyphenol concentrations were analyzed by HPLC coupled to tandem MS after enzymatic hydrolysis. Results: Using multivariable-adjusted conditional logistic regression models, caffeic acid (ORlog2: 0.55; 95% CI: 0.33, 0.93) and its dehydrogenated metabolite, 3,4-dihydroxyphenylpropionic acid (ORlog2: 0.84; 95% CI: 0.71, 0.99), were inversely associated with differentiated TC risk. Similar results were observed for papillary TC, but not for follicular TC. Ferulic acid was also inversely associated only with papillary TC (ORlog2: 0.68; 95% CI: 0.51, 0.91). However, none of these relations was significant after Bonferroni correction for multiple testing. No association was observed for any of the remaining polyphenols with total differentiated, papillary, or follicular TC. Conclusions: Blood polyphenol concentrations were mostly not associated with differentiated TC risk in women, although our study raises the possibility that high blood concentrations of caffeic, 3,4-dihydroxyphenylpropionic, and ferulic acids may be related to a lower papillary TC risk.
Published: 2021

14. Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability (Nature Communications, (2021), 12, 1, (24), 10.1038/s41467-020-19366-9)

Author: Lagou, V. (Vasiliki), Mägi, R. (Reedik), Hottenga, J.J. (Jouke Jan), Grallert, H. (Harald), Perry, J.R.B. (John R. B.), Bouatia-Naji, N. (Nabila), Marullo, L. (Letizia), Rybin, D. (Denis), Jansen, R. (Rick), Min, J.L. (Josine L.), Dimas, A.S. (Antigone), Ulrich, A. (Anna), Zudina, L. (Liudmila), Gådin, J.R. (Jesper R.), Jiang, L. (Longda), Faggian, A. (Alessia), Bonnefond, A. (Amélie), Fadista, J. (João), Stathopoulou, M.G. (Maria G), Isaacs, A.J. (Aaron), Willems, S.M. (Sara), Navarro, P. (Pau), Tanaka, T. (Toshiko), Jackson, A.U. (Anne U.), Montasser, M.E. (May E.), O’Connell, J.R. (Jeff R.), Bielak, L.F. (Lawrence F.), Webster, R.J. (Rebecca J.), Meitinger, T. (Thomas), Stafford, M., Pourcain, B.S. (Beate St), Timpson, N.J. (Nicholas J.), Salo, P. (Perttu), Shin, S.-Y., Amin, N. (Najaf), Smith, A.V. (Albert), Li, G. (Guo), Verweij, N. (Niek), Goel, A. (Anuj), Ford, I. (Ian), Johnson, P.C.D. (Paul C. D.), Johnson, T. (Toby), Kapur, K. (Karen), Thorleifsson, G. (Gudmar), Strawbridge, R.J. (Rona), Rasmussen-Torvik, L.J. (Laura), Esko, T. (Tõnu), Mihailov, E. (Evelin), Fall, T. (Tove), Fraser, R.M. (Ross), Mahajan, A. (Anubha), Kanoni, S. (Stavroula), Giedraitis, V. (Vilmantas), Kleber, M.E. (Marcus E.), Silbernagel, G. (Günther), Meyer, J. (Julia), Müller-Nurasyid, M. (Martina), Ganna, A. (Andrea), Sarin, A.-P., Yengo, L. (Loic), Shungin, D. (Dmitry), Luan, J. (Jian’an), Horikoshi, M. (Momoko), An, P. (Ping), Sanna, S. (Serena), Boettcher, Y. (Yvonne), Rayner, N.W. (Nigel William), Nolte, I.M. (Ilja), Zemunik, T. (Tatijana), Iperen, E. (Erik van), Kovacs, P. (Peter), Hastie, N. (Nick), Wild, S.H. (Sarah), McLachlan, S. (Stela), Campbell, S. (Susan), Polasek, O. (Ozren), Carlson, O.D. (Olga), Egan, J. (Josephine), Kieß, W. (Wieland), Willemsen, G. (Gonneke), Kuusisto, J. (Johanna), Laakso, M. (Markku), Dimitriou, M. (Maria), Hicks, A.A. (Andrew A.), Rauramaa, R. (Rainer), Bandinelli, S. (Stefania), Thorand, B. (Barbara), Liu, Y. (Yongmei), Miljkovic, I. (Iva), Kao, W.H.L. (Wen), Doney, A.S.F. (Alex), Perola, M. (Markus), Hingorani, A. (Aroon), Kivimaki, M. (Mika), Kumari, M. (Meena), Bennett, A.J. (Amanda J.), Groves, C.J. (Christopher J.), Herder, C. (Christian), Koistinen, H.A. (Heikki A.), Kinnunen, L. (Leena), Faire, U.D. (Ulf), Bakker, S.J.L. (Stephan), Uusitupa, M. (Matti), Palmer, C.N.A. (Colin N. A.), Jukema, J.W. (Jan Wouter), Sattar, N. (Naveed), Pouta, A. (Anneli), Snieder, H. (Harold), Boerwinkle, E.A. (Eric), Palmer, C.N.A. (Colin), Magnusson, P.K. (Patrik), Krus, U. (Ulrika), Scapoli, C. (Chiara), Geus, E.J.C. (Eco) de, Blüher, M. (Matthias), Wolffenbuttel, B.H.R. (Bruce), Province, M.A. (Michael A.), Abecasis, G.R. (Goncalo R.), Meigs, J.B. (James B.), Hovingh, G.K. (G. Kees), Lindström, J. (Jaana), Wilson, J.F. (James F.), Wright, A.F. (Alan F.), Dedoussis, G.V. (George), Bornstein, S.R. (Stefan), Schwarz, P.E.H. (Peter), Tönjes, A. (Anke), Winkelmann, B., Boehm, B.O. (Bernhard), März, W. (Winfried), Metspalu, A. (Andres), Price, J.F. (Jackie F.), Deloukas, P. (Panos), Körner, A. (Antje), Lakka, T.A. (Timo), Keinanen-Kiukaanniemi, S. (Sirkka), Saaristo, T. (Timo), Bergman, R.N. (Richard N.), Tuomilehto, J. (Jaakko), Wareham, N.J. (Nick), Langenberg, C. (Claudia), Männistö, S. (Satu), Franks, P.W. (Paul W.), Hayward, C. (Caroline), Vitart, V. (Veronique), Kaprio, J. (Jaakko), Visvikis-Siest, S. (Sophie), Balkau, B. (Beverley), Altshuler, D. (David), Rudan, I. (Igor), Stumvoll, M. (Michael), Campbell, H. (Harry), Duijn, C.M. (Cornelia) van, Gieger, C. (Christian), Illig, T. (Thomas), Ferrucci, L. (Luigi), Pedersen, N.L. (Nancy), Pramstaller, P.P. (Peter Paul), Boehnke, M. (Michael), Frayling, T.M. (Timothy M.), Shuldiner, A.R. (Alan R.), Peyser, P.A. (Patricia A.), Kardia, S.L.R. (Sharon L. R.), Palmer, L.J. (Lyle J.), Penninx, B.W.J.H. (Brenda), Meneton, P. (Pierre), Harris, T.B. (Tamara), Matullo, G., Harst, P. (Pim van der), Smith, G.D. (George Davey), Forouhi, N.G. (Nita), Loos, R.J.F. (Ruth J. F.), Salomaa, V. (Veikko), Soranzo, N. (Nicole), Boomsma, D.I. (Dorret I.), Groop, L. (Leif), Tuomi, T. (Tiinamaija), Hofman, A. (Albert), Munroe, P. (Patricia), Gudnason, V. (Vilmundur), Siscovick, D.S. (David), Watkins, H. (Hugh), Lecoeur, C. (Cécile), Vollenweider, P. (Peter), Franco-Cereceda, A. (Anders), Eriksson, P. (Per), Jarvelin, M.-R. (Marjo-Riitta), Zwart, J-A. (John-Anker), Hamsten, A. (Anders), Nicholson, G. (George), Karpe, F. (Fredrik), Frants, R.R. (Rune), Lindgren, C.M. (Cecilia M.), McCarthy, M.I. (Mark I.), Froguel, P. (Philippe), Kaakinen, M.A. (Marika A.), Lyssenko, V. (Valeriya), Watanabe, R.M. (Richard), Ingelsson, E. (Erik), Sijbrands, E.J.G. (Eric), Barroso, I.E. (Inês), Morris, A.P. (Andrew), Prokopenko, I. (Inga), Lagou, V. (Vasiliki), Mägi, R. (Reedik), Hottenga, J.J. (Jouke Jan), Grallert, H. (Harald), Perry, J.R.B. (John R. B.), Bouatia-Naji, N. (Nabila), Marullo, L. (Letizia), Rybin, D. (Denis), Jansen, R. (Rick), Min, J.L. (Josine L.), Dimas, A.S. (Antigone), Ulrich, A. (Anna), Zudina, L. (Liudmila), Gådin, J.R. (Jesper R.), Jiang, L. (Longda), Faggian, A. (Alessia), Bonnefond, A. (Amélie), Fadista, J. (João), Stathopoulou, M.G. (Maria G), Isaacs, A.J. (Aaron), Willems, S.M. (Sara), Navarro, P. (Pau), Tanaka, T. (Toshiko), Jackson, A.U. (Anne U.), Montasser, M.E. (May E.), O’Connell, J.R. (Jeff R.), Bielak, L.F. (Lawrence F.), Webster, R.J. (Rebecca J.), Meitinger, T. (Thomas), Stafford, M., Pourcain, B.S. (Beate St), Timpson, N.J. (Nicholas J.), Salo, P. (Perttu), Shin, S.-Y., Amin, N. (Najaf), Smith, A.V. (Albert), Li, G. (Guo), Verweij, N. (Niek), Goel, A. (Anuj), Ford, I. (Ian), Johnson, P.C.D. (Paul C. D.), Johnson, T. (Toby), Kapur, K. (Karen), Thorleifsson, G. (Gudmar), Strawbridge, R.J. (Rona), Rasmussen-Torvik, L.J. (Laura), Esko, T. (Tõnu), Mihailov, E. (Evelin), Fall, T. (Tove), Fraser, R.M. (Ross), Mahajan, A. (Anubha), Kanoni, S. (Stavroula), Giedraitis, V. (Vilmantas), Kleber, M.E. (Marcus E.), Silbernagel, G. (Günther), Meyer, J. (Julia), Müller-Nurasyid, M. (Martina), Ganna, A. (Andrea), Sarin, A.-P., Yengo, L. (Loic), Shungin, D. (Dmitry), Luan, J. (Jian’an), Horikoshi, M. (Momoko), An, P. (Ping), Sanna, S. (Serena), Boettcher, Y. (Yvonne), Rayner, N.W. (Nigel William), Nolte, I.M. (Ilja), Zemunik, T. (Tatijana), Iperen, E. (Erik van), Kovacs, P. (Peter), Hastie, N. (Nick), Wild, S.H. (Sarah), McLachlan, S. (Stela), Campbell, S. (Susan), Polasek, O. (Ozren), Carlson, O.D. (Olga), Egan, J. (Josephine), Kieß, W. (Wieland), Willemsen, G. (Gonneke), Kuusisto, J. (Johanna), Laakso, M. (Markku), Dimitriou, M. (Maria), Hicks, A.A. (Andrew A.), Rauramaa, R. (Rainer), Bandinelli, S. (Stefania), Thorand, B. (Barbara), Liu, Y. (Yongmei), Miljkovic, I. (Iva), Kao, W.H.L. (Wen), Doney, A.S.F. (Alex), Perola, M. (Markus), Hingorani, A. (Aroon), Kivimaki, M. (Mika), Kumari, M. (Meena), Bennett, A.J. (Amanda J.), Groves, C.J. (Christopher J.), Herder, C. (Christian), Koistinen, H.A. (Heikki A.), Kinnunen, L. (Leena), Faire, U.D. (Ulf), Bakker, S.J.L. (Stephan), Uusitupa, M. (Matti), Palmer, C.N.A. (Colin N. A.), Jukema, J.W. (Jan Wouter), Sattar, N. (Naveed), Pouta, A. (Anneli), Snieder, H. (Harold), Boerwinkle, E.A. (Eric), Palmer, C.N.A. (Colin), Magnusson, P.K. (Patrik), Krus, U. (Ulrika), Scapoli, C. (Chiara), Geus, E.J.C. (Eco) de, Blüher, M. (Matthias), Wolffenbuttel, B.H.R. (Bruce), Province, M.A. (Michael A.), Abecasis, G.R. (Goncalo R.), Meigs, J.B. (James B.), Hovingh, G.K. (G. Kees), Lindström, J. (Jaana), Wilson, J.F. (James F.), Wright, A.F. (Alan F.), Dedoussis, G.V. (George), Bornstein, S.R. (Stefan), Schwarz, P.E.H. (Peter), Tönjes, A. (Anke), Winkelmann, B., Boehm, B.O. (Bernhard), März, W. (Winfried), Metspalu, A. (Andres), Price, J.F. (Jackie F.), Deloukas, P. (Panos), Körner, A. (Antje), Lakka, T.A. (Timo), Keinanen-Kiukaanniemi, S. (Sirkka), Saaristo, T. (Timo), Bergman, R.N. (Richard N.), Tuomilehto, J. (Jaakko), Wareham, N.J. (Nick), Langenberg, C. (Claudia), Männistö, S. (Satu), Franks, P.W. (Paul W.), Hayward, C. (Caroline), Vitart, V. (Veronique), Kaprio, J. (Jaakko), Visvikis-Siest, S. (Sophie), Balkau, B. (Beverley), Altshuler, D. (David), Rudan, I. (Igor), Stumvoll, M. (Michael), Campbell, H. (Harry), Duijn, C.M. (Cornelia) van, Gieger, C. (Christian), Illig, T. (Thomas), Ferrucci, L. (Luigi), Pedersen, N.L. (Nancy), Pramstaller, P.P. (Peter Paul), Boehnke, M. (Michael), Frayling, T.M. (Timothy M.), Shuldiner, A.R. (Alan R.), Peyser, P.A. (Patricia A.), Kardia, S.L.R. (Sharon L. R.), Palmer, L.J. (Lyle J.), Penninx, B.W.J.H. (Brenda), Meneton, P. (Pierre), Harris, T.B. (Tamara), Matullo, G., Harst, P. (Pim van der), Smith, G.D. (George Davey), Forouhi, N.G. (Nita), Loos, R.J.F. (Ruth J. F.), Salomaa, V. (Veikko), Soranzo, N. (Nicole), Boomsma, D.I. (Dorret I.), Groop, L. (Leif), Tuomi, T. (Tiinamaija), Hofman, A. (Albert), Munroe, P. (Patricia), Gudnason, V. (Vilmundur), Siscovick, D.S. (David), Watkins, H. (Hugh), Lecoeur, C. (Cécile), Vollenweider, P. (Peter), Franco-Cereceda, A. (Anders), Eriksson, P. (Per), Jarvelin, M.-R. (Marjo-Riitta), Zwart, J-A. (John-Anker), Hamsten, A. (Anders), Nicholson, G. (George), Karpe, F. (Fredrik), Frants, R.R. (Rune), Lindgren, C.M. (Cecilia M.), McCarthy, M.I. (Mark I.), Froguel, P. (Philippe), Kaakinen, M.A. (Marika A.), Lyssenko, V. (Valeriya), Watanabe, R.M. (Richard), Ingelsson, E. (Erik), Sijbrands, E.J.G. (Eric), Barroso, I.E. (Inês), Morris, A.P. (Andrew), and Prokopenko, I. (Inga)
Abstract: The original version of this Article contained an error in Fig. 2, in which panels a and b were inadvertently swapped. This has now been corrected in the PDF and HTML versions of the Article.
Published: 2021
Full Text: View/download PDF

15. Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author: Lagou, V. (Vasiliki), Mägi, R. (Reedik), Hottenga, J.J. (Jouke Jan), Grallert, H. (Harald), Perry, J.R.B. (John R. B.), Bouatia-Naji, N. (Nabila), Marullo, L. (Letizia), Rybin, D. (Denis), Jansen, R. (Rick), Min, J. (Josine), Dimas, A.S. (Antigone), Ulrich, A. (Anna), Zudina, L. (Liudmila), Gådin, J.R. (Jesper R.), Jiang, L. (Longda), Faggian, A. (Alessia), Bonnefond, A. (Amélie), Fadista, J. (João), Stathopoulou, M.G. (Maria G), Isaacs, A. (Aaron), Willems, S.M. (Sara), Navarro, P. (Pau), Tanaka, T. (Toshiko), Jackson, A.U. (Anne U.), Montasser, M.E. (May E.), O’Connell, J.R. (Jeff R.), Bielak, L.F. (Lawrence F.), Webster, R.J. (Rebecca J.), Meitinger, T. (Thomas), Stafford, M., Pourcain, B.S. (Beate St), Timpson, N.J. (Nicholas J.), Salo, P. (Perttu), Shin, S.-Y., Amin, N. (Najaf), Smith, A.V. (Albert), Li, G. (Guo), Verweij, N. (Niek), Goel, A. (Anuj), Ford, I. (Ian), Johnson, P.C.D. (Paul C. D.), Johnson, T. (Toby), Kapur, K. (Karen), Thorleifsson, G. (Gudmar), Strawbridge, R.J. (Rona), Rasmussen-Torvik, L.J. (Laura), Esko, T. (Tõnu), Mihailov, E. (Evelin), Fall, T. (Tove), Fraser, R.M. (Ross), Mahajan, A. (Anubha), Kanoni, S. (Stavroula), Giedraitis, V. (Vilmantas), Kleber, M.E. (Marcus E.), Silbernagel, G. (Günther), Meyer, J. (Julia), Müller-Nurasyid, M. (Martina), Ganna, A. (Andrea), Sarin, A.-P., Yengo, L. (Loic), Shungin, D. (Dmitry), Luan, J. (Jian’an), Horikoshi, M. (Momoko), An, P. (Ping), Sanna, S. (Serena), Boettcher, Y. (Yvonne), Rayner, N.W. (Nigel William), Nolte, I.M. (Ilja), Zemunik, T. (Tatijana), Iperen, E. (Erik van), Kovacs, P. (Peter), Hastie, N. (Nick), Wild, S.H. (Sarah H.), McLachlan, S. (Stela), Campbell, S. (Susan), Polasek, O. (Ozren), Carlson, O.D. (Olga), Egan, J. (Josephine), Kieß, W. (Wieland), Willemsen, G. (Gonneke), Kuusisto, J. (Johanna), Laakso, M. (Markku), Dimitriou, M. (Maria), Hicks, A.A. (Andrew A.), Rauramaa, R. (Rainer), Bandinelli, S. (Stefania), Thorand, B. (Barbara), Liu, Y. (Yongmei), Miljkovic, I. (Iva), Kao, W.H.L. (Wen), Doney, A.S.F. (Alex), Perola, M. (Markus), Hingorani, A. (Aroon), Kivimaki, M. (Mika), Kumari, M. (Meena), Bennett, A.J. (Amanda J.), Groves, C.J. (Christopher J.), Herder, C. (Christian), Koistinen, H.A. (Heikki A.), Kinnunen, L. (Leena), Faire, U.D. (Ulf), Bakker, S.J.L. (Stephan), Uusitupa, M. (Matti), Palmer, C.N.A. (Colin N. A.), Jukema, J.W. (Jan Wouter), Sattar, N. (Naveed), Pouta, A. (Anneli), Snieder, H. (Harold), Boerwinkle, E.A. (Eric), Palmer, C.N.A. (Colin), Magnusson, P.K. (Patrik), Krus, U. (Ulrika), Scapoli, C. (Chiara), de Geus, E.J.C.N. (Eco J. C. N.), Blüher, M. (Matthias), Wolffenbuttel, B.H.R. (Bruce), Province, M.A. (Michael A.), Abecasis, G.R. (Goncalo R.), Meigs, J.B. (James B.), Hovingh, G.K. (G. Kees), Lindström, J. (Jaana), Wilson, J.F. (James F.), Wright, A.F. (Alan F.), Dedoussis, G.V. (George), Bornstein, S.R. (Stefan), Schwarz, P.E.H. (Peter), Tönjes, A. (Anke), Winkelmann, B., Boehm, B.O. (Bernhard O.), März, W. (Winfried), Metspalu, A. (Andres), Price, J.F. (Jackie F.), Deloukas, P. (Panos), Körner, A. (Antje), Lakka, T.A. (Timo), Keinanen-Kiukaanniemi, S. (Sirkka), Saaristo, T. (Timo), Bergman, R.N. (Richard N.), Tuomilehto, J. (Jaakko), Wareham, N.J. (Nick), Langenberg, C. (Claudia), Männistö, S. (Satu), Franks, P.W. (Paul W.), Hayward, C. (Caroline), Vitart, V. (Veronique), Kaprio, J. (Jaakko), Visvikis-Siest, S. (Sophie), Balkau, B. (Beverley), Altshuler, D. (David), Rudan, I. (Igor), Stumvoll, M. (Michael), Campbell, H. (Harry), van Duijn, C.M. (Cornelia M.), Gieger, C. (Christian), Illig, T. (Thomas), Ferrucci, L. (Luigi), Pedersen, N.L. (Nancy L.), Pramstaller, P.P. (Peter Paul), Boehnke, M. (Michael), Frayling, T.M. (Timothy M.), Shuldiner, A.R. (Alan R.), Peyser, P.A. (Patricia A.), Kardia, S.L.R. (Sharon L. R.), Palmer, L.J. (Lyle J.), Penninx, B.W.J.H. (Brenda), Meneton, P. (Pierre), Harris, T.B. (Tamara), Navis, G. (Gerjan), Harst, P. (Pim van der), Smith, G.D. (George Davey), Forouhi, N.G. (Nita), Loos, R.J.F. (Ruth), Salomaa, V. (Veikko), Soranzo, N. (Nicole), Boomsma, D.I. (Dorret I.), Groop, L. (Leif), Tuomi, T. (Tiinamaija), Hofman, A. (Albert), Munroe, P.B. (Patricia B.), Gudnason, V. (Vilmundur), Siscovick, D.S. (David), Watkins, H. (Hugh), Lecoeur, C. (Cécile), Vollenweider, P. (Peter), Franco-Cereceda, A. (Anders), Eriksson, P. (Per), Jarvelin, M.-R. (Marjo-Riitta), Zwart, J-A. (John-Anker), Hamsten, A. (Anders), Nicholson, G. (George), Karpe, F. (Fredrik), Frants, R.R. (Rune), Lindgren, C.M. (Cecilia M.), McCarthy, M.I. (Mark I.), Froguel, P. (Philippe), Kaakinen, M.A. (Marika A.), Lyssenko, V. (Valeriya), Watanabe, R.M. (Richard), Ingelsson, E. (Erik), Sijbrands, E.J.G. (Eric), Dupuis, J. (Josée), Barroso, I.E. (Inês), Morris, A.P. (Andrew P.), Prokopenko, I. (Inga), Lagou, V. (Vasiliki), Mägi, R. (Reedik), Hottenga, J.J. (Jouke Jan), Grallert, H. (Harald), Perry, J.R.B. (John R. B.), Bouatia-Naji, N. (Nabila), Marullo, L. (Letizia), Rybin, D. (Denis), Jansen, R. (Rick), Min, J. (Josine), Dimas, A.S. (Antigone), Ulrich, A. (Anna), Zudina, L. (Liudmila), Gådin, J.R. (Jesper R.), Jiang, L. (Longda), Faggian, A. (Alessia), Bonnefond, A. (Amélie), Fadista, J. (João), Stathopoulou, M.G. (Maria G), Isaacs, A. (Aaron), Willems, S.M. (Sara), Navarro, P. (Pau), Tanaka, T. (Toshiko), Jackson, A.U. (Anne U.), Montasser, M.E. (May E.), O’Connell, J.R. (Jeff R.), Bielak, L.F. (Lawrence F.), Webster, R.J. (Rebecca J.), Meitinger, T. (Thomas), Stafford, M., Pourcain, B.S. (Beate St), Timpson, N.J. (Nicholas J.), Salo, P. (Perttu), Shin, S.-Y., Amin, N. (Najaf), Smith, A.V. (Albert), Li, G. (Guo), Verweij, N. (Niek), Goel, A. (Anuj), Ford, I. (Ian), Johnson, P.C.D. (Paul C. D.), Johnson, T. (Toby), Kapur, K. (Karen), Thorleifsson, G. (Gudmar), Strawbridge, R.J. (Rona), Rasmussen-Torvik, L.J. (Laura), Esko, T. (Tõnu), Mihailov, E. (Evelin), Fall, T. (Tove), Fraser, R.M. (Ross), Mahajan, A. (Anubha), Kanoni, S. (Stavroula), Giedraitis, V. (Vilmantas), Kleber, M.E. (Marcus E.), Silbernagel, G. (Günther), Meyer, J. (Julia), Müller-Nurasyid, M. (Martina), Ganna, A. (Andrea), Sarin, A.-P., Yengo, L. (Loic), Shungin, D. (Dmitry), Luan, J. (Jian’an), Horikoshi, M. (Momoko), An, P. (Ping), Sanna, S. (Serena), Boettcher, Y. (Yvonne), Rayner, N.W. (Nigel William), Nolte, I.M. (Ilja), Zemunik, T. (Tatijana), Iperen, E. (Erik van), Kovacs, P. (Peter), Hastie, N. (Nick), Wild, S.H. (Sarah H.), McLachlan, S. (Stela), Campbell, S. (Susan), Polasek, O. (Ozren), Carlson, O.D. (Olga), Egan, J. (Josephine), Kieß, W. (Wieland), Willemsen, G. (Gonneke), Kuusisto, J. (Johanna), Laakso, M. (Markku), Dimitriou, M. (Maria), Hicks, A.A. (Andrew A.), Rauramaa, R. (Rainer), Bandinelli, S. (Stefania), Thorand, B. (Barbara), Liu, Y. (Yongmei), Miljkovic, I. (Iva), Kao, W.H.L. (Wen), Doney, A.S.F. (Alex), Perola, M. (Markus), Hingorani, A. (Aroon), Kivimaki, M. (Mika), Kumari, M. (Meena), Bennett, A.J. (Amanda J.), Groves, C.J. (Christopher J.), Herder, C. (Christian), Koistinen, H.A. (Heikki A.), Kinnunen, L. (Leena), Faire, U.D. (Ulf), Bakker, S.J.L. (Stephan), Uusitupa, M. (Matti), Palmer, C.N.A. (Colin N. A.), Jukema, J.W. (Jan Wouter), Sattar, N. (Naveed), Pouta, A. (Anneli), Snieder, H. (Harold), Boerwinkle, E.A. (Eric), Palmer, C.N.A. (Colin), Magnusson, P.K. (Patrik), Krus, U. (Ulrika), Scapoli, C. (Chiara), de Geus, E.J.C.N. (Eco J. C. N.), Blüher, M. (Matthias), Wolffenbuttel, B.H.R. (Bruce), Province, M.A. (Michael A.), Abecasis, G.R. (Goncalo R.), Meigs, J.B. (James B.), Hovingh, G.K. (G. Kees), Lindström, J. (Jaana), Wilson, J.F. (James F.), Wright, A.F. (Alan F.), Dedoussis, G.V. (George), Bornstein, S.R. (Stefan), Schwarz, P.E.H. (Peter), Tönjes, A. (Anke), Winkelmann, B., Boehm, B.O. (Bernhard O.), März, W. (Winfried), Metspalu, A. (Andres), Price, J.F. (Jackie F.), Deloukas, P. (Panos), Körner, A. (Antje), Lakka, T.A. (Timo), Keinanen-Kiukaanniemi, S. (Sirkka), Saaristo, T. (Timo), Bergman, R.N. (Richard N.), Tuomilehto, J. (Jaakko), Wareham, N.J. (Nick), Langenberg, C. (Claudia), Männistö, S. (Satu), Franks, P.W. (Paul W.), Hayward, C. (Caroline), Vitart, V. (Veronique), Kaprio, J. (Jaakko), Visvikis-Siest, S. (Sophie), Balkau, B. (Beverley), Altshuler, D. (David), Rudan, I. (Igor), Stumvoll, M. (Michael), Campbell, H. (Harry), van Duijn, C.M. (Cornelia M.), Gieger, C. (Christian), Illig, T. (Thomas), Ferrucci, L. (Luigi), Pedersen, N.L. (Nancy L.), Pramstaller, P.P. (Peter Paul), Boehnke, M. (Michael), Frayling, T.M. (Timothy M.), Shuldiner, A.R. (Alan R.), Peyser, P.A. (Patricia A.), Kardia, S.L.R. (Sharon L. R.), Palmer, L.J. (Lyle J.), Penninx, B.W.J.H. (Brenda), Meneton, P. (Pierre), Harris, T.B. (Tamara), Navis, G. (Gerjan), Harst, P. (Pim van der), Smith, G.D. (George Davey), Forouhi, N.G. (Nita), Loos, R.J.F. (Ruth), Salomaa, V. (Veikko), Soranzo, N. (Nicole), Boomsma, D.I. (Dorret I.), Groop, L. (Leif), Tuomi, T. (Tiinamaija), Hofman, A. (Albert), Munroe, P.B. (Patricia B.), Gudnason, V. (Vilmundur), Siscovick, D.S. (David), Watkins, H. (Hugh), Lecoeur, C. (Cécile), Vollenweider, P. (Peter), Franco-Cereceda, A. (Anders), Eriksson, P. (Per), Jarvelin, M.-R. (Marjo-Riitta), Zwart, J-A. (John-Anker), Hamsten, A. (Anders), Nicholson, G. (George), Karpe, F. (Fredrik), Frants, R.R. (Rune), Lindgren, C.M. (Cecilia M.), McCarthy, M.I. (Mark I.), Froguel, P. (Philippe), Kaakinen, M.A. (Marika A.), Lyssenko, V. (Valeriya), Watanabe, R.M. (Richard), Ingelsson, E. (Erik), Sijbrands, E.J.G. (Eric), Dupuis, J. (Josée), Barroso, I.E. (Inês), Morris, A.P. (Andrew P.), and Prokopenko, I. (Inga)
Abstract: Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
Published: 2021
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16. Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women

Author: Jones, G. (Garan), Trajanoska, K. (Katerina), Santanasto, A.J. (Adam J.), Stringa, N. (Najada), Kuo, C.-L. (Chia-Ling), Atkins, J.L. (Janice L.), Lewis, J.R. (Joshua), Duong, T.V. (ThuyVy), Hong, S. (Shengjun), Biggs, M.L. (M.), Luan, J. (Jian’an), Sarnowski, C., Lunetta, K.L. (Kathryn), Tanaka, T. (Toshiko), Wojczynski, M.K. (Mary ), Cvejkus, R. (Ryan), Nethander, M. (Maria), Ghasemi, S. (Sahar), Yang, J. (Jingyun), Zillikens, M.C. (Carola), Walter, S. (Stefan), Sicinski, K. (Kamil), Kague, E. (Erika), Ackert-Bicknell, C.L. (Cheryl L.), Arking, D.E. (Dan E.), Windham, B.G. (Gwen), Boerwinkle, E.A. (Eric), Grove, M.L. (Megan L.), Graff, M. (Misa), Spira, D. (Dominik), Demuth, I. (Ilja), Velde, N. (Nathalie) van der, de Groot, L.C.P.G.M. (Lisette C. P. G. M.), Psaty, B.M. (Bruce M.), Odden, M.C. (Michelle C.), Fohner, A.E. (Alison E.), Langenberg, C. (Claudia), Wareham, N.J. (Nick), Bandinelli, S. (Stefania), Schoor, N.M. (Natasja) van, Huisman, M. (Martijn), Tan, Q. (Qihua), Zmuda, J. (Joseph), Mellström, D. (Dan), Karlsson, M. (Magnus), Bennett, D.A. (David), Buchman, A.S. (Aron S.), De Jager, P., Uitterlinden, A.G. (Andre G.), Völker, U. (Uwe), Kocher, T. (Thomas), Teumer, A. (Alexander), Rodríguez-Mañas, L. (Leocadio), García, F.J. (Francisco J.), Carnicero, J.A. (José A.), Herd, P. (Pamela), Bertram, L. (Lars), Ohlsson, C. (Claes), Murabito, J. (Joanne), Melzer, D. (David), Kuchel, G.A. (George A.), Ferrucci, L. (Luigi), Karasik, D. (David), Rivadeneira Ramirez, F. (Fernando), Kiel, D.P. (Douglas P.), Pilling, L.C. (Luke C.), Jones, G. (Garan), Trajanoska, K. (Katerina), Santanasto, A.J. (Adam J.), Stringa, N. (Najada), Kuo, C.-L. (Chia-Ling), Atkins, J.L. (Janice L.), Lewis, J.R. (Joshua), Duong, T.V. (ThuyVy), Hong, S. (Shengjun), Biggs, M.L. (M.), Luan, J. (Jian’an), Sarnowski, C., Lunetta, K.L. (Kathryn), Tanaka, T. (Toshiko), Wojczynski, M.K. (Mary ), Cvejkus, R. (Ryan), Nethander, M. (Maria), Ghasemi, S. (Sahar), Yang, J. (Jingyun), Zillikens, M.C. (Carola), Walter, S. (Stefan), Sicinski, K. (Kamil), Kague, E. (Erika), Ackert-Bicknell, C.L. (Cheryl L.), Arking, D.E. (Dan E.), Windham, B.G. (Gwen), Boerwinkle, E.A. (Eric), Grove, M.L. (Megan L.), Graff, M. (Misa), Spira, D. (Dominik), Demuth, I. (Ilja), Velde, N. (Nathalie) van der, de Groot, L.C.P.G.M. (Lisette C. P. G. M.), Psaty, B.M. (Bruce M.), Odden, M.C. (Michelle C.), Fohner, A.E. (Alison E.), Langenberg, C. (Claudia), Wareham, N.J. (Nick), Bandinelli, S. (Stefania), Schoor, N.M. (Natasja) van, Huisman, M. (Martijn), Tan, Q. (Qihua), Zmuda, J. (Joseph), Mellström, D. (Dan), Karlsson, M. (Magnus), Bennett, D.A. (David), Buchman, A.S. (Aron S.), De Jager, P., Uitterlinden, A.G. (Andre G.), Völker, U. (Uwe), Kocher, T. (Thomas), Teumer, A. (Alexander), Rodríguez-Mañas, L. (Leocadio), García, F.J. (Francisco J.), Carnicero, J.A. (José A.), Herd, P. (Pamela), Bertram, L. (Lars), Ohlsson, C. (Claes), Murabito, J. (Joanne), Melzer, D. (David), Kuchel, G.A. (George A.), Ferrucci, L. (Luigi), Karasik, D. (David), Rivadeneira Ramirez, F. (Fernando), Kiel, D.P. (Douglas P.), and Pilling, L.C. (Luke C.)
Abstract: Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1p = 4 × 10−17), arthritis (GDF5p = 4 × 10−13), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing.
Published: 2021
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17. Fatty acids in the de novo lipogenesis pathway and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies.

Author: Imamura F., Fretts A.M., Marklund M., Ardisson Korat A.V., Yang W.-S., Lankinen M., Qureshi W., Helmer C., Chen T.-A., Virtanen J.K., Wong K., Bassett J.K., Murphy R., Tintle N., Yu C.I., Brouwer I.A., Chien K.-L., Chen Y.-Y., Wood A.C., del Gobbo L.C., Djousse L., Geleijnse J.M., Giles G.G., de Goede J., Gudnason V., Harris W.S., Hodge A., Hu F., Koulman A., Laakso M., Lind L., Lin H.-J., McKnight B., Rajaobelina K., Riserus U., Robinson J.G., Samieri C., Senn M., Siscovick D.S., Soedamah-Muthu S.S., Sotoodehnia N., Sun Q., Tsai M.Y., Tuomainen T.-P., Uusitupa M., Wagenknecht L.E., Wareham N.J., Wu J.H.Y., Micha R., Lemaitre R.N., Mozaffarian D., Forouhi N.G., Imamura F., Fretts A.M., Marklund M., Ardisson Korat A.V., Yang W.-S., Lankinen M., Qureshi W., Helmer C., Chen T.-A., Virtanen J.K., Wong K., Bassett J.K., Murphy R., Tintle N., Yu C.I., Brouwer I.A., Chien K.-L., Chen Y.-Y., Wood A.C., del Gobbo L.C., Djousse L., Geleijnse J.M., Giles G.G., de Goede J., Gudnason V., Harris W.S., Hodge A., Hu F., Koulman A., Laakso M., Lind L., Lin H.-J., McKnight B., Rajaobelina K., Riserus U., Robinson J.G., Samieri C., Senn M., Siscovick D.S., Soedamah-Muthu S.S., Sotoodehnia N., Sun Q., Tsai M.Y., Tuomainen T.-P., Uusitupa M., Wagenknecht L.E., Wareham N.J., Wu J.H.Y., Micha R., Lemaitre R.N., Mozaffarian D., and Forouhi N.G.
Abstract: Background De novo lipogenesis (DNL) is the primary metabolic pathway synthesizing fatty acids from carbohydrates, protein, or alcohol. Our aim was to examine associations of in vivo levels of selected fatty acids (16:0, 16:1n7, 18:0, 18:1n9) in DNL with incidence of type 2 diabetes (T2D). Methods and findings Seventeen cohorts from 12 countries (7 from Europe, 7 from the United States, 1 from Australia, 1 from Taiwan; baseline years = 1970-1973 to 2006-2010) conducted harmonized individual-level analyses of associations of DNL-related fatty acids with incident T2D. In total, we evaluated 65,225 participants (mean ages = 52.3-75.5 years; % women = 20.4%-62.3% in 12 cohorts recruiting both sexes) and 15,383 incident cases of T2D over the 9-year follow-up on average. Cohort-specific association of each of 16:0, 16:1n7, 18:0, and 18:1n9 with incident T2D was estimated, adjusted for demographic factors, socioeconomic characteristics, alcohol, smoking, physical activity, dyslipidemia, hypertension, menopausal status, and adiposity. Cohort-specific associations were meta-analyzed with an inverse-variance-weighted approach. Each of the 4 fatty acids positively related to incident T2D. Relative risks (RRs) per cohort-specific range between midpoints of the top and bottom quintiles of fatty acid concentrations were 1.53 (1.41-1.66; p < 0.001) for 16:0, 1.40 (1.33-1.48; p < 0.001) for 16:1n-7, 1.14 (1.05-1.22; p = 0.001) for 18:0, and 1.16 (1.07-1.25; p < 0.001) for 18:1n9. Heterogeneity was seen across cohorts (I2 = 51.1%-73.1% for each fatty acid) but not explained by lipid fractions and global geographical regions. Further adjusted for triglycerides (and 16:0 when appropriate) to evaluate associations independent of overall DNL, the associations remained significant for 16:0, 16:1n7, and 18:0 but were attenuated for 18:1n9 (RR = 1.03, 95% confidence interval (CI) = 0.94-1.13). These findings had limitations in potential reverse causation and residual confounding by impreci
Published: 2021

18. Genetic insights into biological mechanisms governing human ovarian ageing.

Author: Ruth K.S., Day F.R., Hussain J., Martinez-Marchal A., Aiken C.E., Azad A., Thompson D.J., Knoblochova L., Abe H., Tarry-Adkins J.L., Gonzalez J.M., Fontanillas P., Claringbould A., Bakker O.B., Sulem P., Walters R.G., Terao C., Turon S., Horikoshi M., Lin K., Onland-Moret N.C., Sankar A., Hertz E.P.T., Timshel P.N., Shukla V., Borup R., Olsen K.W., Aguilera P., Ferrer-Roda M., Huang Y., Stankovic S., Timmers P.R.H.J., Ahearn T.U., Alizadeh B.Z., Naderi E., Andrulis I.L., Arnold A.M., Aronson K.J., Augustinsson A., Bandinelli S., Barbieri C.M., Beaumont R.N., Becher H., Beckmann M.W., Benonisdottir S., Bergmann S., Bochud M., Boerwinkle E., Bojesen S.E., Bolla M.K., Boomsma D.I., Bowker N., Brody J.A., Broer L., Buring J.E., Campbell A., Campbell H., Castelao J.E., Catamo E., Chanock S.J., Chenevix-Trench G., Ciullo M., Corre T., Couch F.J., Cox A., Crisponi L., Cross S.S., Cucca F., Czene K., Smith G.D., de Geus E.J.C.N., de Mutsert R., De Vivo I., Demerath E.W., Dennis J., Dunning A.M., Dwek M., Eriksson M., Esko T., Fasching P.A., Faul J.D., Ferrucci L., Franceschini N., Frayling T.M., Gago-Dominguez M., Mezzavilla M., Garcia-Closas M., Gieger C., Giles G.G., Grallert H., Gudbjartsson D.F., Gudnason V., Guenel P., Haiman C.A., Hakansson N., Hall P., Hayward C., He C., He W., Heiss G., Hoffding M.K., Hopper J.L., Hottenga J.J., Hu F., Hunter D., Ikram M.A., Jackson R.D., Joaquim M.D.R., John E.M., Joshi P.K., Karasik D., Kardia S.L.R., Kartsonaki C., Karlsson R., Kitahara C.M., Kolcic I., Kooperberg C., Kraft P., Kurian A.W., Kutalik Z., La Bianca M., LaChance G., Langenberg C., Launer L.J., Laven J.S.E., Lawlor D.A., Le Marchand L., Li J., Lindblom A., Lindstrom S., Lindstrom T., Linet M., Liu Y.M., Liu S., Luan J., Magi R., Magnusson P.K.E., Mangino M., Mannermaa A., Marco B., Marten J., Martin N.G., Mbarek H., McKnight B., Medland S.E., Meisinger C., Meitinger T., Menni C., Metspalu A., Milani L., Milne R.L., Montgomery G.W., Mook-Kanamori D.O., Mulas A., Mulligan A.M., Nalls M.A., Newman A., Noordam R., Nutile T., Nyholt D.R., Olshan A.F., Olsson H., Painter J.N., Patel A.V., Pedersen N.L., Perjakova N., Peters A., Peters U., Pharoah P.D.P., Polasek O., Porcu E., Psaty B.M., Rahman I., Rennert G., Rennert H.S., Ridker P.M., Ring S.M., Robino A., Rose L.M., Rosendaal F.R., Rossouw J., Rudan I., Rueedi R., Ruggiero D., Sala C.F., Saloustros E., Sandler D.P., Sanna S., Sawyer E.J., Sarnowski C., Schlessinger D., Schmidt M.K., Schoemaker M.J., Schraut K.E., Scott C., Shekari S., Shrikhande A., Smith A.V., Smith B.H., Smith J.A., Sorice R., Southey M.C., Spector T.D., Spinelli J.J., Stampfer M., Stockl D., van Meurs J.B.J., Strauch K., Styrkarsdottir U., Swerdlow A.J., Tanaka T., Teras L.R., Teumer A., Thorsteinsdottir U., Timpson N.J., Toniolo D., Traglia M., Troester M.A., Truong T., Tyrrell J., Uitterlinden A.G., Ulivi S., Vachon C.M., Vitart V., Volker U., Vollenweider P., Volzke H., Wang Q., Wareham N.J., Weinberg C.R., Weir D.R., Wilcox A.N., van Dijk K.W., Willemsen G., Wilson J.F., Wolffenbuttel B.H.R., Wolk A., Wood A.R., Zhao W., Zygmunt M., Chen Z., Li L., Franke L., Burgess S., Deelen P., Pers T.H., Grondahl M.L., Andersen C.Y., Pujol A., Lopez-Contreras A.J., Daniel J.A., Stefansson K., Chang-Claude J., van der Schouw Y.T., Lunetta K.L., Chasman D.I., Easton D.F., Visser J.A., Ozanne S.E., Namekawa S.H., Solc P., Murabito J.M., Ong K.K., Hoffmann E.R., Murray A., Roig I., Perry J.R.B., Ruth K.S., Day F.R., Hussain J., Martinez-Marchal A., Aiken C.E., Azad A., Thompson D.J., Knoblochova L., Abe H., Tarry-Adkins J.L., Gonzalez J.M., Fontanillas P., Claringbould A., Bakker O.B., Sulem P., Walters R.G., Terao C., Turon S., Horikoshi M., Lin K., Onland-Moret N.C., Sankar A., Hertz E.P.T., Timshel P.N., Shukla V., Borup R., Olsen K.W., Aguilera P., Ferrer-Roda M., Huang Y., Stankovic S., Timmers P.R.H.J., Ahearn T.U., Alizadeh B.Z., Naderi E., Andrulis I.L., Arnold A.M., Aronson K.J., Augustinsson A., Bandinelli S., Barbieri C.M., Beaumont R.N., Becher H., Beckmann M.W., Benonisdottir S., Bergmann S., Bochud M., Boerwinkle E., Bojesen S.E., Bolla M.K., Boomsma D.I., Bowker N., Brody J.A., Broer L., Buring J.E., Campbell A., Campbell H., Castelao J.E., Catamo E., Chanock S.J., Chenevix-Trench G., Ciullo M., Corre T., Couch F.J., Cox A., Crisponi L., Cross S.S., Cucca F., Czene K., Smith G.D., de Geus E.J.C.N., de Mutsert R., De Vivo I., Demerath E.W., Dennis J., Dunning A.M., Dwek M., Eriksson M., Esko T., Fasching P.A., Faul J.D., Ferrucci L., Franceschini N., Frayling T.M., Gago-Dominguez M., Mezzavilla M., Garcia-Closas M., Gieger C., Giles G.G., Grallert H., Gudbjartsson D.F., Gudnason V., Guenel P., Haiman C.A., Hakansson N., Hall P., Hayward C., He C., He W., Heiss G., Hoffding M.K., Hopper J.L., Hottenga J.J., Hu F., Hunter D., Ikram M.A., Jackson R.D., Joaquim M.D.R., John E.M., Joshi P.K., Karasik D., Kardia S.L.R., Kartsonaki C., Karlsson R., Kitahara C.M., Kolcic I., Kooperberg C., Kraft P., Kurian A.W., Kutalik Z., La Bianca M., LaChance G., Langenberg C., Launer L.J., Laven J.S.E., Lawlor D.A., Le Marchand L., Li J., Lindblom A., Lindstrom S., Lindstrom T., Linet M., Liu Y.M., Liu S., Luan J., Magi R., Magnusson P.K.E., Mangino M., Mannermaa A., Marco B., Marten J., Martin N.G., Mbarek H., McKnight B., Medland S.E., Meisinger C., Meitinger T., Menni C., Metspalu A., Milani L., Milne R.L., Montgomery G.W., Mook-Kanamori D.O., Mulas A., Mulligan A.M., Nalls M.A., Newman A., Noordam R., Nutile T., Nyholt D.R., Olshan A.F., Olsson H., Painter J.N., Patel A.V., Pedersen N.L., Perjakova N., Peters A., Peters U., Pharoah P.D.P., Polasek O., Porcu E., Psaty B.M., Rahman I., Rennert G., Rennert H.S., Ridker P.M., Ring S.M., Robino A., Rose L.M., Rosendaal F.R., Rossouw J., Rudan I., Rueedi R., Ruggiero D., Sala C.F., Saloustros E., Sandler D.P., Sanna S., Sawyer E.J., Sarnowski C., Schlessinger D., Schmidt M.K., Schoemaker M.J., Schraut K.E., Scott C., Shekari S., Shrikhande A., Smith A.V., Smith B.H., Smith J.A., Sorice R., Southey M.C., Spector T.D., Spinelli J.J., Stampfer M., Stockl D., van Meurs J.B.J., Strauch K., Styrkarsdottir U., Swerdlow A.J., Tanaka T., Teras L.R., Teumer A., Thorsteinsdottir U., Timpson N.J., Toniolo D., Traglia M., Troester M.A., Truong T., Tyrrell J., Uitterlinden A.G., Ulivi S., Vachon C.M., Vitart V., Volker U., Vollenweider P., Volzke H., Wang Q., Wareham N.J., Weinberg C.R., Weir D.R., Wilcox A.N., van Dijk K.W., Willemsen G., Wilson J.F., Wolffenbuttel B.H.R., Wolk A., Wood A.R., Zhao W., Zygmunt M., Chen Z., Li L., Franke L., Burgess S., Deelen P., Pers T.H., Grondahl M.L., Andersen C.Y., Pujol A., Lopez-Contreras A.J., Daniel J.A., Stefansson K., Chang-Claude J., van der Schouw Y.T., Lunetta K.L., Chasman D.I., Easton D.F., Visser J.A., Ozanne S.E., Namekawa S.H., Solc P., Murabito J.M., Ong K.K., Hoffmann E.R., Murray A., Roig I., and Perry J.R.B.
Abstract: Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.Copyright © 2021, The Author(s), under exclusive licence to Springer Nature Limited.
Published: 2021

19. Salicylic acid and risk of colorectal cancer: A two-sample mendelian randomization study.

Author: Nounu A., Richmond R.C., Stewart I.D., Surendran P., Wareham N.J., Butterworth A., Weinstein S.J., Albanes D., Baron J.A., Hopper J.L., Figueiredo J.C., Newcomb P.A., Lindor N.M., Casey G., Platz E.A., Marchand L.L., Ulrich C.M., Li C.I., van Dujinhoven F.J.B., Gsur A., Campbell P.T., Moreno V., Vodicka P., Vodickova L., Amitay E., Alwers E., Chang-Claude J., Sakoda L.C., Slattery M.L., Schoen R.E., Gunter M.J., Castellvi-Bel S., Kim H.-R., Kweon S.-S., Chan A.T., Li L., Zheng W., Bishop D.T., Buchanan D.D., Giles G.G., Gruber S.B., Rennert G., Stadler Z.K., Harrison T.A., Lin Y., Keku T.O., Woods M.O., Schafmayer C., Van Guelpen B., Gallinger S., Hampel H., Berndt S.I., Pharoah P.D.P., Lindblom A., Wolk A., Wu A.H., White E., Peters U., Drew D.A., Scherer D., Bermejo J.L., Brenner H., Hoffmeister M., Williams A.C., Relton C.L., Nounu A., Richmond R.C., Stewart I.D., Surendran P., Wareham N.J., Butterworth A., Weinstein S.J., Albanes D., Baron J.A., Hopper J.L., Figueiredo J.C., Newcomb P.A., Lindor N.M., Casey G., Platz E.A., Marchand L.L., Ulrich C.M., Li C.I., van Dujinhoven F.J.B., Gsur A., Campbell P.T., Moreno V., Vodicka P., Vodickova L., Amitay E., Alwers E., Chang-Claude J., Sakoda L.C., Slattery M.L., Schoen R.E., Gunter M.J., Castellvi-Bel S., Kim H.-R., Kweon S.-S., Chan A.T., Li L., Zheng W., Bishop D.T., Buchanan D.D., Giles G.G., Gruber S.B., Rennert G., Stadler Z.K., Harrison T.A., Lin Y., Keku T.O., Woods M.O., Schafmayer C., Van Guelpen B., Gallinger S., Hampel H., Berndt S.I., Pharoah P.D.P., Lindblom A., Wolk A., Wu A.H., White E., Peters U., Drew D.A., Scherer D., Bermejo J.L., Brenner H., Hoffmeister M., Williams A.C., and Relton C.L.
Abstract: Salicylic acid (SA) has observationally been shown to decrease colorectal cancer (CRC) risk. Aspirin (acetylsalicylic acid, that rapidly deacetylates to SA) is an effective primary and secondary chemopreventive agent. Through a Mendelian randomization (MR) approach, we aimed to address whether levels of SA affected CRC risk, stratifying by aspirin use. A two-sample MR analysis was performed using GWAS summary statistics of SA (INTERVAL and EPIC-Norfolk, N = 14,149) and CRC (CCFR, CORECT, GECCO and UK Biobank, 55,168 cases and 65,160 controls). The DACHS study (4410 cases and 3441 controls) was used for replication and stratification of aspirin use. SNPs proxying SA were selected via three methods: (1) functional SNPs that influence the activity of aspirin-metabolising enzymes; (2) pathway SNPs present in enzymes' coding regions; and (3) genome-wide significant SNPs. We found no association between functional SNPs and SA levels. The pathway and genome-wide SNPs showed no association between SA and CRC risk (OR:1.03, 95% CI: 0.84-1.27 and OR: 1.08, 95% CI:0.86-1.34, respectively). Results remained unchanged upon aspirin use stratification. We found little evidence to suggest that an SD increase in genetically predicted SA protects against CRC risk in the general population and upon stratification by aspirin use.Copyright © 2021 by the authors. Li-censee MDPI, Basel, Switzerland.
Published: 2021

20. Blood polyphenol concentrations and differentiated thyroid carcinoma in women from the European Prospective Investigation into Cancer and Nutrition (EPIC) study

Author: IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Zamora-Ros, R., Lujan-Barroso, L., Achaintre, D., Franceschi, S., Kyrø, C., Overvad, K., Tjønneland, A., Truong, T., Lecuyer, L., Boutron-Ruault, M.-C., Katzke, V., Johnson, T.S., Schulze, M.B., Trichopoulou, A., Peppa, E., La Vechia, C., Masala, G., Pala, V., Panico, S., Tumino, R., Ricceri, F., Skeie, G., Ramón Quirós, J., Rodriguez-Barranco, M., Amiano, P., Chirlaque, M.-D., Ardanaz, E., Almquist, M., Hennings, J., Vermeulen, R., Wareham, N.J., Tong, T.Y.N., Aune, D., Byrnes, G., Weiderpass, E., Scalbert, A., Rinaldi, S., Agudo, A., IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Zamora-Ros, R., Lujan-Barroso, L., Achaintre, D., Franceschi, S., Kyrø, C., Overvad, K., Tjønneland, A., Truong, T., Lecuyer, L., Boutron-Ruault, M.-C., Katzke, V., Johnson, T.S., Schulze, M.B., Trichopoulou, A., Peppa, E., La Vechia, C., Masala, G., Pala, V., Panico, S., Tumino, R., Ricceri, F., Skeie, G., Ramón Quirós, J., Rodriguez-Barranco, M., Amiano, P., Chirlaque, M.-D., Ardanaz, E., Almquist, M., Hennings, J., Vermeulen, R., Wareham, N.J., Tong, T.Y.N., Aune, D., Byrnes, G., Weiderpass, E., Scalbert, A., Rinaldi, S., and Agudo, A.
Published: 2021

21. Associations of total legume, pulse, and soy consumption with incident type 2 diabetes: Federated meta-analysis of 27 studies from diverse world regions

Author: Pearce, M., Fanidi, A., Bishop, T.R.P., Sharp, S.J., Imamura, F., Dietrich, S., Akbaraly, T., Bes-Rastrollo, M., Beulens, J.W.J., Byberg, L., Canhada, S., Molina, M., Chen, Z., Cortes-Valencia, A., Du, H., Duncan, B.B., Harkanen, T., Hashemian, M., Kim, J., Kim, M.K., Kim, Y., Knekt, P., Kromhout, D., Lassale, C., Ridaura, R.L., Magliano, D.J., Malekzadeh, R., Marquez-Vidal, P., Martinez-Gonzalez, M.A., O'Donoghue, G., O'Gorman, D., Shaw, J.E., Soedamah-Muthu, S.S., Stern, D., Wolk, A., Woo, H.W., Wareham, N.J., Forouhi, N.G., Pearce, M., Fanidi, A., Bishop, T.R.P., Sharp, S.J., Imamura, F., Dietrich, S., Akbaraly, T., Bes-Rastrollo, M., Beulens, J.W.J., Byberg, L., Canhada, S., Molina, M., Chen, Z., Cortes-Valencia, A., Du, H., Duncan, B.B., Harkanen, T., Hashemian, M., Kim, J., Kim, M.K., Kim, Y., Knekt, P., Kromhout, D., Lassale, C., Ridaura, R.L., Magliano, D.J., Malekzadeh, R., Marquez-Vidal, P., Martinez-Gonzalez, M.A., O'Donoghue, G., O'Gorman, D., Shaw, J.E., Soedamah-Muthu, S.S., Stern, D., Wolk, A., Woo, H.W., Wareham, N.J., and Forouhi, N.G.
Abstract: Background The consumption of legumes is promoted as part of a healthy diet in many countries but associations of total and types of legume consumption with type 2 diabetes (T2D) are not well established. Analyses across diverse populations are lacking despite the availability of unpublished legume consumption data in prospective cohort studies. Objective To examine the prospective associations of total and types of legume intake with the risk of incident T2D. Methods Meta-analyses of associations between total legume, pulse, and soy consumption and T2D were conducted using a federated approach without physical data-pooling. Prospective cohorts were included if legume exposure and T2D outcome data were available and the cohort investigators agreed to participate. We estimated incidence rate ratios (IRRs) and CIs of associations using individual participant data including ≤42,473 incident cases among 807,785 adults without diabetes in 27 cohorts across the Americas, Eastern Mediterranean, Europe, and Western Pacific. Random-effects meta-analysis was used to combine effect estimates and estimate heterogeneity. Results Median total legume intake ranged from 0–140 g/d across cohorts. We observed a weak positive association between total legume consumption and T2D (IRR = 1.02, 95% CI: 1.01 to 1.04) per 20 g/d higher intake, with moderately high heterogeneity (I2 = 74%). Analysis by region showed no evidence of associations in the Americas, Eastern Mediterranean, and Western Pacific. The positive association in Europe (IRR = 1.05, 95% CI: 1.01 to 1.10, I2 = 82%) was mainly driven by studies from Germany, UK, and Sweden. No evidence of associations was observed for the consumption of pulses or soy. Conclusions These findings suggest no evidence of an association of legume intakes with T2D in several world regions. The positive association observed in some European studies warrants further investigation relating to ove
Published: 2021

22. Relationship between plasma fibrinogen and fiber intake in the EPIC-Norfolk cohort

Author: Freitas, R.N., Luben, R., Wareham, N.J., and Khaw, K.T.
Subjects: Blood plasma -- Physiological aspects -- Health aspects, Fibrinogen -- Physiological aspects -- Health aspects, Diet -- Physiological aspects -- Health aspects, Food/cooking/nutrition, Health
Abstract: Background/Objectives: Fiber-rich diets have been proposed to lower circulating levels of inflammatory makers. Our objective was to investigate cross-sectional relationships between fiber intake and plasma fibrinogen. Subjects/Methods: We examined the relationship between plasma fibrinogen and dietary fiber in 20 960 men and women, aged 45-75 years old, living in Norfolk, UK. Fiber intake was assessed using a food frequency questionnaire. Results: Mean fibrinogen levels were lower across the increasing quartiles of the fiber intake after adjusting for age, sex, body mass index, physical activity, smoking status and alcohol consumption, and total calories, percentage of energy intake from carbohydrate, protein and fat, with a difference of 0.08 g/l fibrinogen between first and fourth quartiles (P for trend Conclusions: Plasma fibrinogen levels appear to be inversely related to dietary fiber intake in middle-aged and older men and women. European journal of Clinical Nutrition (2012) 66, 443-451; doi: 10.1038/ejcn.2011.194; published online 23 November 2011 Keywords: fibrinogen; dietary fiber; cardiovascular risk; inflammation marker; epidemiology, Introduction Low-grade chronic inflammation has been proposed to be a key pathophysiological mechanism underlying the development of chronic diseases such as coronary heart diseases and diabetes mellitus (Pearson et al., [...]
Published: 2012
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23. Fibre intake in relation to serum total cholesterol levels and CHD risk: a comparison of dietary assessment methods

Author: Ward, H.A., Keogh, R., Lentjes, M., Luben, R.N., Wareham, N.J., and Khaw, K.-T.
Subjects: Coronary heart disease -- Physiological aspects -- Development and progression, Fiber in human nutrition -- Physiological aspects -- Health aspects, Food consumption -- Physiological aspects -- Health aspects, Diet -- Physiological aspects -- Health aspects, Medical screening -- Comparative analysis, Food/cooking/nutrition, Health
Abstract: Background/Objectives: Prospective diet diaries may be more accurate than retrospective food frequency questionnaires (FFQ). The objective of this study was to compare FFQ and 7-day diet diary (7DD) measurements of fibre intake with the incidence of coronary heart disease (CHD). Subjects/Methods: We compared 7DD and FFQ fibre intake in a nested case-control study in a population of 25 639 men and women aged 40-79 years, surveyed in 1993-97 and followed up until 2007. Among 2151 CHD cases and 5354 controls, FFQ and 7DD fibre intake (6g/day) was examined in relation to serum total cholesterol and CHD using linear and logistic regression adjusted for age and additionally for body mass index, physical activity, smoking status, family history of CHD, social class, diabetes, alcohol, energy, saturated fat and use of lipid lowering medication, antihypertensive medication or aspirin. Results: Age-adjusted serum total cholesterol was inversely associated with 7DD fibre among men and women, but with FFQ fibre among men only. In the multivariate analysis, associations with 7DD fibre were attenuated among men (regression coefficient-0.036 mmol/l, s.e. 0.021, P-value 0.087) and women (regression coefficient-0.069 mmol/l, s.e. 0.036, P-value 0.053), and were non-significant for FFQ fibre. Among men, age-adjusted CHD risk was inversely associated with 7DD fibre (odds ratio (OR) 0.84, 95% confidence interval (CI) 0.79-0.90), but not with FFQ fibre (OR 0.96, 95% CI 0.90-1.12). Among women, age-adjusted CHD risk was inversely associated with 7DD fibre (OR 0.83, 95% CI 0.75-0.93), and had a weaker inverse borderline-significant association with FFQ fibre (OR 0.93, 95% CI 0.87-1.01). Multivariate models yielded similar results. Conclusions: Inconsistencies in diet-CHD relationships in population studies may be associated with the use of different dietary assessment methods. European journal of Clinical Nutrition (2012) 66, 296-304; doi: 10.1038/ejcn.2011.184; published online 2 November 2011 Keywords: dietary assessment; fibre; heart disease; FFQ-diet record, Introduction It has long been acknowledged that it is not possible to measure dietary intake without error (Beaton, 1994), and myriad ways exist for food intake to be misreported or [...]
Published: 2012
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24. Effects of body size and sociodemographic characteristics on differences between self-reported and measured anthropometric data in middle-aged men and women: the EPIC-Norfolk study

Author: Park, J.Y., Mitrou, P.N, Keogh, R.H., Luben, R.N., Wareham, N.J., and Khaw, K.T.
Subjects: Body size -- Demographic aspects, Anthropometry -- Surveys, Food/cooking/nutrition, Health
Abstract: Background/Objectives: To investigate the effects of body size and sociodemographic characteristics on differences between self-reported (SR) and measured anthropometric data in men and women. Subjects/Methods: This study comprises 9933 men and 11 856 women aged 39-79 years at baseline survey (1993-1997) in the EPIC-Norfolk study (Norfolk arm of the European Investigation into Cancer and Nutrition Study). The effects of sex, measured height, weight, age group, educational level and social class on differences between SR and measured weight, height, body mass index (BMI), waist, hip and waist-to-hip ratio (WHR) were examined. Results: There were systematic differences between SR and measured anthropometric measurements by sex, measured height, weight and sociodemographic characteristics. Height was overestimated in both sexes while weight, waist, hip, and consequently, BMI and WHR were underestimated. Being male, shorter, heavier, older, and having no educational qualifications and manual occupation were independently associated with overreporting of height, and underreporting of weight was associated independently with being female, shorter, heavier, younger age, and higher education level and social class. Underreporting of waist circumference was strongly associated with being female and higher measured waist circumference, while underreporting of hip circumference was associated with being male and higher measured hip circumference. Furthermore, there was substantial degree of misclassification of BMI and waist circumference categories for both general and central obesity associated with SR data. Conclusions: These findings suggest that errors in SR anthropometric data, especially waist and hip circumference are influenced by actual body size as well as sociodemographic characteristics. These systematic differences may influence associations between SR anthropometric measures and health outcomes in epidemiological studies. European journal of Clinical Nutrition (2011) 65, 357-367; doi: 10.1038/ejcn.2010.259; published online 22 December 2010 Keywords: anthropometry; self-report; waist circumference; hip circumference; social class; educational level, Introduction Anthropometric measures are widely used in epidemiological studies as indicators of obesity, with body mass index (BMI), a weight-related measure, being the most frequently used. More recently, however, measures [...]
Published: 2011
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25. Refractive error, axial length and anterior chamber depth of the eye in British adults: the EPIC-Norfolk Eye Study

Author: Foster, P.J., Broadway, D.C., Hayat, S., Luben, R., Dalzell, N., Bingham, S., Wareham, N.J., and Khaw, K.-T.
Subjects: Anterior chamber (Eye) -- Demographic aspects, Anterior chamber (Eye) -- Physiological aspects, Anterior chamber (Eye) -- Research, Eye -- Refractive errors, Eye -- Distribution, Eye -- Demographic aspects, Eye -- Research, Company distribution practices, Health
Published: 2010

26. Factor VII, blood lipids and fat intake: gene-nutrient interaction and risk of coronary heart disease with the factor VII R353Q polymorphism

Author: Bowman, R., Joosen, A.M.C.P., Welch, A.A., Luben, R.N., Khaw, K.-T., Wareham, N.J., and Bingham, S.A.
Subjects: Biochemistry -- Research, Coronary heart disease -- Risk factors, Coronary heart disease -- Development and progression, Coronary heart disease -- Genetic aspects, Dietary fat -- Health aspects, Nutrient interactions -- Genetic aspects, Nutrient interactions -- Health aspects, Blood coagulation factors -- Genetic aspects, Blood coagulation factors -- Health aspects, Genetic polymorphisms -- Health aspects
Abstract: Background: The relation between dietary fat, blood lipids, plasma factor VII coagulant activity (FVllc) and risk of coronary heart disease (CHD) according to the R353Q polymorphism in the factor VII gene was assessed. Methods: Cross-sectional study of 15 073 individuals participating in the European Prospective Investigation of Cancer (EPIC) Norfolk, 7433 of which had FVllc available. Nested case-control study of 985 CHD cases and 2009 matched controls. Results: FVllc was significantly associated with total fat intake in females, especially in the RR homozygotes (standardized [beta] = 0.24; 95% confidence interval (95% CI) 0.08-0.40; P Conclusion: These results show a strong association between dietary fat intake and FVllc in women, and between serum triacylglycerol and cholesterol and FVllc levels in both genders. The R353Q genotype only marginally affected modulation of FVllc by dietary fat. The association between triacylglycerol and FVllc was significantly stronger in males carrying the Q allele than in those with the RR genotype. doi:10.1038/ejcn.2008.28; published online 9 April 2008 Keywords: coronary heart disease; diet; factor Vllc; R353Q polymorphism; serum lipids, Introduction Fat intake, especially saturated fatty acid (SFA) intake, is an important determinant of coronary heart disease (CHD) risk, either through its role in raising total low-density lipoprotein (LDL) cholesterol [...]
Published: 2009

27. Association between nutritional profiles of foods underlying Nutri-Score front-of-pack labels and mortality: EPIC cohort study in 10 European countries

Author: Deschasaux, M. Huybrechts, I. Julia, C. Hercberg, S. Egnell, M. Srour, B. Kesse-Guyot, E. Latino-Martel, P. Biessy, C. Casagrande, C. Murphy, N. Jenab, M. Ward, H.A. Weiderpass, E. Overvad, K. Tjønneland, A. Rostgaard-Hansen, A.L. Boutron-Ruault, M.-C. Mancini, F.R. Mahamat-Saleh, Y. Kühn, T. Katzke, V. Bergmann, M.M. Schulze, M.B. Trichopoulou, A. Karakatsani, A. Peppa, E. Masala, G. Agnoli, C. De Magistris, M.S. Tumino, R. Sacerdote, C. Boer, J.M.A. Monique Verschuren, W.M. Van Der Schouw, Y.T. Skeie, G. Braaten, T. Luisa Redondo, M. Agudo, A. Petrova, D. Colorado-Yohar, S.M. Barricarte, A. Amiano, P. Sonestedt, E. Ericson, U. Otten, J. Sundström, B. Wareham, N.J. Forouhi, N.G. Vineis, P. Tsilidis, K.K. Knuppel, A. Papier, K. Ferrari, P. Riboli, E. Gunter, M.J. Touvier, M.
Abstract: Objective To determine if the Food Standards Agency nutrient profiling system (FSAm-NPS), which grades the nutritional quality of food products and is used to derive the Nutri-Score front-of-packet label to guide consumers towards healthier food choices, is associated with mortality. Design Population based cohort study. Setting European Prospective Investigation into Cancer and Nutrition (EPIC) cohort from 23 centres in 10 European countries. Participants 521 324 adults; at recruitment, country specific and validated dietary questionnaires were used to assess their usual dietary intakes. A FSAm-NPS score was calculated for each food item per 100 g content of energy, sugars, saturated fatty acids, sodium, fibre, and protein, and of fruit, vegetables, legumes, and nuts. The FSAm-NPS dietary index was calculated for each participant as an energy weighted mean of the FSAm-NPS score of all foods consumed. The higher the score the lower the overall nutritional quality of the diet. Main outcome measure Associations between the FSAm-NPS dietary index score and mortality, assessed using multivariable adjusted Cox proportional hazards regression models. Results After exclusions, 501 594 adults (median follow-up 17.2 years, 8 162 730 person years) were included in the analyses. Those with a higher FSAm-NPS dietary index score (highest versus lowest fifth) showed an increased risk of all cause mortality (n=53 112 events from non-external causes; hazard ratio 1.07, 95% confidence interval 1.03 to 1.10, P
Published: 2020

28. A Body Shape Index (ABSI) achieves better mortality risk stratification than alternative indices of abdominal obesity: results from a large European cohort

Author: Christakoudi, S. Tsilidis, K.K. Muller, D.C. Freisling, H. Weiderpass, E. Overvad, K. Söderberg, S. Häggström, C. Pischon, T. Dahm, C.C. Zhang, J. Tjønneland, A. Halkjær, J. MacDonald, C. Boutron-Ruault, M.-C. Mancini, F.R. Kühn, T. Kaaks, R. Schulze, M.B. Trichopoulou, A. Karakatsani, A. Peppa, E. Masala, G. Pala, V. Panico, S. Tumino, R. Sacerdote, C. Quirós, J.R. Agudo, A. Sánchez, M.-J. Cirera, L. Barricarte-Gurrea, A. Amiano, P. Memarian, E. Sonestedt, E. Bueno-de-Mesquita, B. May, A.M. Khaw, K.-T. Wareham, N.J. Tong, T.Y.N. Huybrechts, I. Noh, H. Aglago, E.K. Ellingjord-Dale, M. Ward, H.A. Aune, D. Riboli, E.
Subjects: nutritional and metabolic diseases
Abstract: Abdominal and general adiposity are independently associated with mortality, but there is no consensus on how best to assess abdominal adiposity. We compared the ability of alternative waist indices to complement body mass index (BMI) when assessing all-cause mortality. We used data from 352,985 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk factors. During a mean follow-up of 16.1 years, 38,178 participants died. Combining in one model BMI and a strongly correlated waist index altered the association patterns with mortality, to a predominantly negative association for BMI and a stronger positive association for the waist index, while combining BMI with the uncorrelated A Body Shape Index (ABSI) preserved the association patterns. Sex-specific cohort-wide quartiles of waist indices correlated with BMI could not separate high-risk from low-risk individuals within underweight (BMI < 18.5 kg/m2) or obese (BMI ≥ 30 kg/m2) categories, while the highest quartile of ABSI separated 18–39% of the individuals within each BMI category, which had 22–55% higher risk of death. In conclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which could facilitate personalisation of screening, treatment and monitoring. © 2020, The Author(s).
Published: 2020

29. Consumption of nuts and seeds and pancreatic ductal adenocarcinoma risk in the European Prospective Investigation into Cancer and Nutrition

Author: Obón-Santacana, M., Luján-Barroso, L., Freisling, H., Naudin, S., Boutron-Ruault, M.-C., Mancini, F.R., Rebours, V., Kühn, T., Katzke, V., Boeing, H., Tjønneland, A., Olsen, A., Overvad, K., Lasheras, C., Rodríguez-Barranco, M., Amiano, P., Santiuste, C., Ardanaz, E., Khaw, K.-T., Wareham, N.J., Aune, D., Trichopoulou, A., Thriskos, P., Peppa, E., Masala, G., Grioni, S., Tumino, R., Panico, S., Bueno-de-Mesquita, B., Sciannameo, V., Vermeulen, R., Sonestedt, E., Sund, M., Weiderpass, E., Skeie, G., Riboli, E., Duell, E.J., IRAS OH Epidemiology Chemical Agents, and dIRAS RA-2
Subjects: prospective cohort study, pancreatic cancer, nuts, seeds, diet, EPIC, intake
Abstract: Four epidemiologic studies have assessed the association between nut intake and pancreatic cancer risk with contradictory results. The present study aims to investigate the relation between nut intake (including seeds) and pancreatic ductal adenocarcinoma (PDAC) risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Cox proportional hazards models were used to estimate hazards ratio (HR) and 95% confidence intervals (95% CI) for nut intake and PDAC risk. Information on intake of nuts was obtained from the EPIC country-specific dietary questionnaires. After a mean follow-up of 14 years, 476,160 participants were eligible for the present study and included 1,283 PDAC cases. No association was observed between consumption of nuts and PDAC risk (highest intake vs nonconsumers: HR, 0.89; 95% CI, 0.72–1.10; p-trend = 0.70). Furthermore, no evidence for effect-measure modification was observed when different subgroups were analyzed. Overall, in EPIC, the highest intake of nuts was not statistically significantly associated with PDAC risk.
Published: 2020

30. Lifestyle factors and risk of multimorbidity of cancer and cardiometabolic diseases: A multinational cohort study

Author: Freisling, H. Viallon, V. Lennon, H. Bagnardi, V. Ricci, C. Butterworth, A.S. Sweeting, M. Muller, D. Romieu, I. Bazelle, P. Kvaskoff, M. Arveux, P. Severi, G. Bamia, C. Kühn, T. Kaaks, R. Bergmann, M. Boeing, H. Tjønneland, A. Olsen, A. Overvad, K. Dahm, C.C. Menéndez, V. Agudo, A. Sánchez, M.-J. Amiano, P. Santiuste, C. Gurrea, A.B. Tong, T.Y.N. Schmidt, J.A. Tzoulaki, I. Tsilidis, K.K. Ward, H. Palli, D. Agnoli, C. Tumino, R. Ricceri, F. Panico, S. Picavet, H.S.J. Bakker, M. Monninkhof, E. Nilsson, P. Manjer, J. Rolandsson, O. Thysell, E. Weiderpass, E. Jenab, M. Riboli, E. Vineis, P. Danesh, J. Wareham, N.J. Gunter, M.J. Ferrari, P.
Abstract: Background: Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. Methods: In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs. Results: During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and women with healthy lifestyles. Conclusion: Pre-diagnostic healthy lifestyle behaviours were strongly inversely associated with the risk of cancer and cardiometabolic diseases, and with the prognosis of these diseases by reducing risk of multimorbidity. © 2020 The Author(s).
Published: 2020

31. Blood pressure and risk of cancer in the European Prospective Investigation into Cancer and Nutrition

Author: Christakoudi, S. Kakourou, A. Markozannes, G. Tzoulaki, I. Weiderpass, E. Brennan, P. Gunter, M. Dahm, C.C. Overvad, K. Olsen, A. Tjønneland, A. Boutron-Ruault, M.-C. Madika, A.-L. Severi, G. Katzke, V. Kühn, T. Bergmann, M.M. Boeing, H. Karakatsani, A. Martimianaki, G. Thriskos, P. Masala, G. Sieri, S. Panico, S. Tumino, R. Ricceri, F. Agudo, A. Redondo-Sánchez, D. Colorado-Yohar, S.M. Mokoroa, O. Melander, O. Stocks, T. Häggström, C. Harlid, S. Bueno-de-Mesquita, B. van Gils, C.H. Vermeulen, R.C.H. Khaw, K.-T. Wareham, N.J. Tong, T.Y.N. Freisling, H. Johansson, M. Lennon, H. Aune, D. Riboli, E. Trichopoulos, D. Trichopoulou, A. Tsilidis, K.K.
Abstract: Several studies have reported associations of hypertension with cancer, but not all results were conclusive. We examined the association of systolic (SBP) and diastolic (DBP) blood pressure with the development of incident cancer at all anatomical sites in the European Prospective Investigation into Cancer and Nutrition (EPIC). Hazard ratios (HRs) (95% confidence intervals) were estimated using multivariable Cox proportional hazards models, stratified by EPIC-participating center and age at recruitment, and adjusted for sex, education, smoking, body mass index, physical activity, diabetes and dietary (in women also reproductive) factors. The study included 307,318 men and women, with an average follow-up of 13.7 (standard deviation 4.4) years and 39,298 incident cancers. We confirmed the expected positive association with renal cell carcinoma: HR = 1.12 (1.08–1.17) per 10 mm Hg higher SBP and HR = 1.23 (1.14–1.32) for DBP. We additionally found positive associations for esophageal squamous cell carcinoma (SCC): HR = 1.16 (1.07–1.26) (SBP), HR = 1.31 (1.13–1.51) (DBP), weaker for head and neck cancers: HR = 1.08 (1.04–1.12) (SBP), HR = 1.09 (1.01–1.17) (DBP) and, similarly, for skin SCC, colon cancer, postmenopausal breast cancer and uterine adenocarcinoma (AC), but not for esophageal AC, lung SCC, lung AC or uterine endometroid cancer. We observed weak inverse associations of SBP with cervical SCC: HR = 0.91 (0.82–1.00) and lymphomas: HR = 0.97 (0.93–1.00). There were no consistent associations with cancers in other locations. Our results are largely compatible with published studies and support weak associations of blood pressure with cancers in specific locations and morphologies. © 2019 UICC
Published: 2020

32. The associations of major foods and fibre with risks of ischaemic and haemorrhagic stroke: A prospective study of 418 329 participants in the EPIC cohort across nine European countries

Author: Tong, T.Y.N. Appleby, P.N. Key, T.J. Dahm, C.C. Overvad, K. Olsen, A. Tjønneland, A. Katzke, V. Kühn, T. Boeing, H. Karakatsani, A. Peppa, E. Trichopoulou, A. Weiderpass, E. Masala, G. Grioni, S. Panico, S. Tumino, R. Boer, J.M.A. Verschuren, W.M.M. Quirós, J.R. Agudo, A. Rodríguez-Barranco, M. Imaz, L. Chirlaque, M.-D. Moreno-Iribas, C. Engström, G. Sonestedt, E. Lind, M. Otten, J. Khaw, K.-T. Aune, D. Riboli, E. Wareham, N.J. Imamura, F. Forouhi, N.G. Di Angelantonio, E. Wood, A.M. Butterworth, A.S. Perez-Cornago, A.
Abstract: Aim: To investigate the associations between major foods and dietary fibre with subtypes of stroke in a large prospective cohort. Methods and results: We analysed data on 418 329 men and women from nine European countries, with an average of 12.7 years of follow-up. Diet was assessed using validated country-specific questionnaires which asked about habitual intake over the past year, calibrated using 24-h recalls. Multivariable-adjusted Cox regressions were used to estimate hazard ratios (HRs) for ischaemic and haemorrhagic stroke associated with consumption of red and processed meat, poultry, fish, dairy foods, eggs, cereals, fruit and vegetables, legumes, nuts and seeds, and dietary fibre. For ischaemic stroke (4281 cases), lower risks were observed with higher consumption of fruit and vegetables combined (HR; 95% CI per 200 g/day higher intake, 0.87; 0.82-0.93, P-trend < 0.001), dietary fibre (per 10 g/day, 0.77; 0.69-0.86, P-trend < 0.001), milk (per 200 g/day, 0.95; 0.91-0.99, P-trend = 0.02), yogurt (per 100 g/day, 0.91; 0.85-0.97, P-trend = 0.004), and cheese (per 30 g/day, 0.88; 0.81-0.97, P-trend = 0.008), while higher risk was observed with higher red meat consumption which attenuated when adjusted for the other statistically significant foods (per 50 g/day, 1.07; 0.96-1.20, P-trend = 0.20). For haemorrhagic stroke (1430 cases), higher risk was associated with higher egg consumption (per 20 g/day, 1.25; 1.09-1.43, P-trend = 0.002). Conclusion: Risk of ischaemic stroke was inversely associated with consumption of fruit and vegetables, dietary fibre, and dairy foods, while risk of haemorrhagic stroke was positively associated with egg consumption. The apparent differences in the associations highlight the importance of examining ischaemic and haemorrhagic stroke subtypes separately. © 2020 The Author(s) 2020. Published by Oxford University Press on behalf of the European Society of Cardiology.
Published: 2020

33. Glycemic index, glycemic load, and risk of coronary heart disease: A pan-European cohort study

Author: Sieri, S. Agnoli, C. Grioni, S. Weiderpass, E. Mattiello, A. Sluijs, I. Sanchez, M.J. Jakobsen, M.U. Sweeting, M. van der Schouw, Y.T. Nilsson, L.M. Wennberg, P. Katzke, V.A. Kühn, T. Overvad, K. Tong, T.Y.N. Conchi, M.-I. Quirós, J.R. García-Torrecillas, J.M. Mokoroa, O. Gómez, J.-H. Tjønneland, A. Sonestedt, E. Trichopoulou, A. Karakatsani, A. Valanou, E. Boer, J.M.A. Monique Verschuren, W.M. Boutron-Ruault, M.-C. Fagherazzi, G. Madika, A.-L. Bergmann, M.M. Schulze, M.B. Ferrari, P. Freisling, H. Lennon, H. Sacerdote, C. Masala, G. Tumino, R. Riboli, E. Wareham, N.J. Danesh, J. Forouhi, N.G. Butterworth, A.S. Krogh, V.
Abstract: Background: High carbohydrate intake raises blood triglycerides, glucose, and insulin; reduces HDLs; and may increase risk of coronary heart disease (CHD). Epidemiological studies indicate that high dietary glycemic index (GI) and glycemic load (GL) are associated with increased CHD risk. Objectives: The aim of this study was to determine whether dietary GI, GL, and available carbohydrates are associated with CHD risk in both sexes. Methods: This large prospective study-the European Prospective Investigation into Cancer and Nutrition-consisted of 338,325 participants who completed a dietary questionnaire. HRs with 95% CIs for a CHD event, in relation to intake of GI, GL, and carbohydrates, were estimated using covariate-adjusted Cox proportional hazard models. Results: After 12.8 y (median), 6378 participants had experienced a CHD event. High GL was associated with greater CHD risk [HR 1.16 (95% CI: 1.02, 1.31) highest vs. lowest quintile, p-trend 0.035; HR 1.18 (95% CI: 1.07, 1.29) per 50 g/day of GL intake]. The association between GL and CHD risk was evident in subjects with BMI (in kg/m2) =25 [HR: 1.22 (95% CI: 1.11, 1.35) per 50 g/d] but not in those with BMI
Published: 2020

34. Mitochondrial DNA copy-number variation and pancreatic cancer risk in the prospective EPIC cohort

Author: Gentiluomo, M. Katzke, V.A. Kaaks, R. Tjønneland, A. Severi, G. Perduca, V. Boutron-Ruault, M.-C. Weiderpass, E. Ferrari, P. Johnson, T. Schulze, M.B. Bergmann, M. Trichopoulou, A. Karakatsani, A. Vecchia, C.L. Palli, D. Grioni, S. Panico, S. Tumino, R. Sacerdote, C. Bueno-De-Mesquita, B. Vermeulen, R. Sandanger, T.M. Ramón Quirós, J. Rodriguez-Barranco, M. Amiano, P. Colorado-Yohar, S. Ardanaz, E. Sund, M. Khaw, K.-T. Wareham, N.J. Schmidt, J.A. Jakszyn, P. Morelli, L. Canzian, F. Campa, D.
Abstract: Background: Mitochondrial DNA (mtDNA) copy number in peripheral blood has been found to be associated with risk of developing several cancers. However, data on pancreatic ductal adenocarcinoma (PDAC) are very limited. Methods: To further our knowledge on this topic, we measured relative mtDNA copy number by a quantitative real-time PCR assay in peripheral leukocyte samples of 476 PDAC cases and 357 controls nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Results: We observed lower mtDNA copy number with advancing age (P = 6.54 x 10-5) and with a high body mass index (BMI) level (P = 0.004) and no association with sex, smoking behavior, and alcohol consumption. We found an association between increased mtDNA copy number and decreased risk of developing PDAC with an odds ratios (OR) of 0.35 [95% confidence interval (CI), 0.16-0.79; P = 0.01] when comparing the fifth quintile with the first using an unconditional logistic regression and an OR of 0.19 (95% CI, 0.07-0.52; P = 0.001) with a conditional analysis. Analyses stratified by BMI showed an association between high mtDNA copy number and decreased risk in the stratum of normal weight, consistent with the main analyses. Conclusions: Our results suggest a protective effect of a higher number of mitochondria, measured in peripheral blood leukocytes, on PDAC risk. Impact: Our findings highlight the importance of understanding the mitochondrial biology in pancreatic cancer. © 2020 American Association for Cancer Research.
Published: 2020

35. Blood pressure and risk of cancer in the European Prospective Investigation into Cancer and Nutrition

Author: Christakoudi, S., Kakourou, A., Markozannes, G., Tzoulaki, I., Weiderpass, E., Brennan, P., Gunter, M., Dahm, C.C., Overvad, K., Olsen, A., Tjønneland, A., Boutron-Ruault, M.-C., Madika, A.-L., Severi, G., Katzke, V., Kühn, T., Bergmann, M.M., Boeing, H., Karakatsani, A., Martimianaki, G., Thriskos, P., Masala, G., Sieri, S., Panico, S., Tumino, R., Ricceri, F., Agudo, A., Redondo-Sánchez, D., Colorado-Yohar, S.M., Mokoroa, O., Melander, O., Stocks, T., Häggström, C., Harlid, S., Bueno-de-Mesquita, B., van Gils, C.H., Vermeulen, R.C.H., Khaw, K.-T., Wareham, N.J., Tong, T.Y.N., Freisling, H., Johansson, M., Lennon, H., Aune, D., Riboli, E., Trichopoulos, D., Trichopoulou, A., Tsilidis, K.K., Christakoudi, S., Kakourou, A., Markozannes, G., Tzoulaki, I., Weiderpass, E., Brennan, P., Gunter, M., Dahm, C.C., Overvad, K., Olsen, A., Tjønneland, A., Boutron-Ruault, M.-C., Madika, A.-L., Severi, G., Katzke, V., Kühn, T., Bergmann, M.M., Boeing, H., Karakatsani, A., Martimianaki, G., Thriskos, P., Masala, G., Sieri, S., Panico, S., Tumino, R., Ricceri, F., Agudo, A., Redondo-Sánchez, D., Colorado-Yohar, S.M., Mokoroa, O., Melander, O., Stocks, T., Häggström, C., Harlid, S., Bueno-de-Mesquita, B., van Gils, C.H., Vermeulen, R.C.H., Khaw, K.-T., Wareham, N.J., Tong, T.Y.N., Freisling, H., Johansson, M., Lennon, H., Aune, D., Riboli, E., Trichopoulos, D., Trichopoulou, A., and Tsilidis, K.K.
Abstract: Several studies have reported associations of hypertension with cancer, but not all results were conclusive. We examined the association of systolic (SBP) and diastolic (DBP) blood pressure with the development of incident cancer at all anatomical sites in the European Prospective Investigation into Cancer and Nutrition (EPIC). Hazard ratios (HRs) (95% confidence intervals) were estimated using multivariable Cox proportional hazards models, stratified by EPIC-participating center and age at recruitment, and adjusted for sex, education, smoking, body mass index, physical activity, diabetes and dietary (in women also reproductive) factors. The study included 307,318 men and women, with an average follow-up of 13.7 (standard deviation 4.4) years and 39,298 incident cancers. We confirmed the expected positive association with renal cell carcinoma: HR = 1.12 (1.08–1.17) per 10 mm Hg higher SBP and HR = 1.23 (1.14–1.32) for DBP. We additionally found positive associations for esophageal squamous cell carcinoma (SCC): HR = 1.16 (1.07–1.26) (SBP), HR = 1.31 (1.13–1.51) (DBP), weaker for head and neck cancers: HR = 1.08 (1.04–1.12) (SBP), HR = 1.09 (1.01–1.17) (DBP) and, similarly, for skin SCC, colon cancer, postmenopausal breast cancer and uterine adenocarcinoma (AC), but not for esophageal AC, lung SCC, lung AC or uterine endometroid cancer. We observed weak inverse associations of SBP with cervical SCC: HR = 0.91 (0.82–1.00) and lymphomas: HR = 0.97 (0.93–1.00). There were no consistent associations with cancers in other locations. Our results are largely compatible with published studies and support weak associations of blood pressure with cancers in specific locations and morphologies.
Published: 2020

36. Genomic analysis of diet composition finds novel loci and associations with health and lifestyle

Author: Meddens, S.F.W. (Fleur), Vlaming, R. (Ronald) de, Bowers, P. (Peter), Burik, C.A.P. (Casper A. P.), Linnér, R.K. (Richard Karlsson), Lee, C. (Chanwook), Okbay, A. (Aysu), Turley, P. (Patrick), Rietveld, C.A. (Cornelius A.), Fontana, M.A. (Mark Alan), Ghanbari, M. (Mohsen), Imamura, F. (Fumiaki), McMahon, G. (George), Most, P.J. (Peter) van der, Voortman, R.G. (Trudy), Wade, K.H. (Kaitlin H.), Anderson, E.L. (Emma L.), Braun, K.V.E. (Kim), Emmett, P.M. (Pauline M.), Esko, T. (Tõnu), Gonzalez, J.R. (Juan), Kiefte-de Jong, J.C. (Jessica), Langenberg, C. (Claudia), Luan, J. (Jian’an), Muka, T. (Taulant), Ring, S.M. (Susan), Rivadeneira, F. (Fernando), Snieder, H. (Harold), Rooij, F.J.A. (Frank) van, Wolffenbuttel, B.H.R. (Bruce), Smith, G.D. (George Davey), Franco, O.H. (Oscar H.), Forouhi, N.G. (Nita), Ikram, M.A. (Arfan), Uitterlinden, A.G. (André), van Vliet-Ostaptchouk, J.V. (Jana V.), Wareham, N.J. (Nick), Cesarini, D. (David), Harden, K.P. (K. Paige), Lee, J.J. (James J.), Benjamin, D.J. (Daniel J.), Chow, C.C. (Carson C.), Koellinger, P.D. (Philipp D.), Meddens, S.F.W. (Fleur), Vlaming, R. (Ronald) de, Bowers, P. (Peter), Burik, C.A.P. (Casper A. P.), Linnér, R.K. (Richard Karlsson), Lee, C. (Chanwook), Okbay, A. (Aysu), Turley, P. (Patrick), Rietveld, C.A. (Cornelius A.), Fontana, M.A. (Mark Alan), Ghanbari, M. (Mohsen), Imamura, F. (Fumiaki), McMahon, G. (George), Most, P.J. (Peter) van der, Voortman, R.G. (Trudy), Wade, K.H. (Kaitlin H.), Anderson, E.L. (Emma L.), Braun, K.V.E. (Kim), Emmett, P.M. (Pauline M.), Esko, T. (Tõnu), Gonzalez, J.R. (Juan), Kiefte-de Jong, J.C. (Jessica), Langenberg, C. (Claudia), Luan, J. (Jian’an), Muka, T. (Taulant), Ring, S.M. (Susan), Rivadeneira, F. (Fernando), Snieder, H. (Harold), Rooij, F.J.A. (Frank) van, Wolffenbuttel, B.H.R. (Bruce), Smith, G.D. (George Davey), Franco, O.H. (Oscar H.), Forouhi, N.G. (Nita), Ikram, M.A. (Arfan), Uitterlinden, A.G. (André), van Vliet-Ostaptchouk, J.V. (Jana V.), Wareham, N.J. (Nick), Cesarini, D. (David), Harden, K.P. (K. Paige), Lee, J.J. (James J.), Benjamin, D.J. (Daniel J.), Chow, C.C. (Carson C.), and Koellinger, P.D. (Philipp D.)
Abstract: We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10−8), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10−5) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (rg ≈ 0.15–0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|rg| ≈ 0.1–0.3) and positive genetic correlations with physical activity (rg ≈ 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (rg ≈−0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction.
Published: 2020
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37. Genome-wide Association Analysis in Humans Links Nucleotide Metabolism to Leukocyte Telomere Length

Author: Li, C. (Chen), Stoma, S. (Svetlana), Lotta, L.A. (Luca A.), Warner, S. (Sophie), Albrecht, E. (Eva), Allione, A. (Alessandra), Arp, P.P. (Pascal), Broer, L. (Linda), Buxton, J.L. (Jessica L.), Da Silva Couto Alves, A. (Alexessander), Deelen, J. (Joris), Fedko, I.O. (Iryna O.), Gordon, S.D. (Scott D.), Jiang, T. (Tao), Karlsson, R. (Robert), Kerrison, N. (Nicola), Loe, T.K. (Taylor K.), Mangino, M. (Massimo), Milaneschi, Y. (Yuri), Miraglio, B. (Benjamin), Pervjakova, N. (Natalia), Russo, A. (Alessia), Surakka, I. (Ida), Spek, A. (Ashley) van der, Verhoeven, J.E. (Josine E.), Amin, N. (Najaf), Beekman, M. (Marian), Blakemore, A.I. (Alexandra I.), Canzian, F. (Federico), Hamby, S.E. (Stephen E.), Hottenga, J.J. (Jouke Jan), Jones, P.D. (Peter D.), Jousilahti, P. (Pekka), Mägi, R. (Reedik), Medland, S.E. (Sarah), Montgomery, G.W. (Grant), Nyholt, D.R. (Dale), Perola, M. (Markus), Pietilainen, K.H. (Kirsi Hannele), Salomaa, V. (Veikko), Sillanpää, E. (Elina), Suchiman, H.E. (H. Eka), Heemst, D. (Diana) van, Willemsen, G. (Gonneke), Agudo, A. (Antonio), Boeing, H. (Heiner), Boomsma, D.I. (Dorret), Chirlaque, M.D. (M.), Fagherazzi, G. (Guy), Ferrari, P. (Pietro), Franks, P. (Paul), Gieger, C. (Christian), Hagen, K. (Knut), Gunter, M.J. (Marc J.), Hägg, S. (Sara), Hovatta, I. (Iiris), Imaz, L. (Liher), Kaprio, J. (Jaakko), Kaaks, R. (Rudolf), Key, T. (Tim), Krogh, V. (Vittorio), Martin, N.G. (Nicholas), Melander, O. (Olle), Metspalu, A. (Andres), Moreno, C. (Concha), Onland-Moret, N.C. (N. Charlotte), Nilsson, P. (Peter), Ong, K.K. (Ken K.), Overvad, K. (Kim), Palli, D. (Domenico), Panico, S. (Salvatore), Pedersen, N.L. (Nancy), Penninx, B.W.J.H. (Brenda), Quirós, J.R., Jarvelin, M.R. (Marjo Riitta), Rodríguez-Barranco, M. (Miguel), Scott, R.A. (Robert A.), Severi, G. (Gianluca), Slagboom, P.E. (Eline), Spector, T.D. (Timothy), Tjønneland, A. (Anne), Trichopoulou, A. (Antonia), Tumino, R. (Rosario), Uitterlinden, A.G. (André G.), Schouw, Y.T. (Yvonne) van der, Duijn, C.M. (Cornelia) van, Weiderpass, E. (Elisabete), Denchi, E.L. (Eros Lazzerini), Matullo, G., Butterworth, A.S. (Adam S.), Danesh, J. (John), Samani, N.J. (Nilesh), Wareham, N.J. (Nick), Nelson, C.P. (Christopher P.), Langenberg, C. (Claudia), Codd, V. (Veryan), Li, C. (Chen), Stoma, S. (Svetlana), Lotta, L.A. (Luca A.), Warner, S. (Sophie), Albrecht, E. (Eva), Allione, A. (Alessandra), Arp, P.P. (Pascal), Broer, L. (Linda), Buxton, J.L. (Jessica L.), Da Silva Couto Alves, A. (Alexessander), Deelen, J. (Joris), Fedko, I.O. (Iryna O.), Gordon, S.D. (Scott D.), Jiang, T. (Tao), Karlsson, R. (Robert), Kerrison, N. (Nicola), Loe, T.K. (Taylor K.), Mangino, M. (Massimo), Milaneschi, Y. (Yuri), Miraglio, B. (Benjamin), Pervjakova, N. (Natalia), Russo, A. (Alessia), Surakka, I. (Ida), Spek, A. (Ashley) van der, Verhoeven, J.E. (Josine E.), Amin, N. (Najaf), Beekman, M. (Marian), Blakemore, A.I. (Alexandra I.), Canzian, F. (Federico), Hamby, S.E. (Stephen E.), Hottenga, J.J. (Jouke Jan), Jones, P.D. (Peter D.), Jousilahti, P. (Pekka), Mägi, R. (Reedik), Medland, S.E. (Sarah), Montgomery, G.W. (Grant), Nyholt, D.R. (Dale), Perola, M. (Markus), Pietilainen, K.H. (Kirsi Hannele), Salomaa, V. (Veikko), Sillanpää, E. (Elina), Suchiman, H.E. (H. Eka), Heemst, D. (Diana) van, Willemsen, G. (Gonneke), Agudo, A. (Antonio), Boeing, H. (Heiner), Boomsma, D.I. (Dorret), Chirlaque, M.D. (M.), Fagherazzi, G. (Guy), Ferrari, P. (Pietro), Franks, P. (Paul), Gieger, C. (Christian), Hagen, K. (Knut), Gunter, M.J. (Marc J.), Hägg, S. (Sara), Hovatta, I. (Iiris), Imaz, L. (Liher), Kaprio, J. (Jaakko), Kaaks, R. (Rudolf), Key, T. (Tim), Krogh, V. (Vittorio), Martin, N.G. (Nicholas), Melander, O. (Olle), Metspalu, A. (Andres), Moreno, C. (Concha), Onland-Moret, N.C. (N. Charlotte), Nilsson, P. (Peter), Ong, K.K. (Ken K.), Overvad, K. (Kim), Palli, D. (Domenico), Panico, S. (Salvatore), Pedersen, N.L. (Nancy), Penninx, B.W.J.H. (Brenda), Quirós, J.R., Jarvelin, M.R. (Marjo Riitta), Rodríguez-Barranco, M. (Miguel), Scott, R.A. (Robert A.), Severi, G. (Gianluca), Slagboom, P.E. (Eline), Spector, T.D. (Timothy), Tjønneland, A. (Anne), Trichopoulou, A. (Antonia), Tumino, R. (Rosario), Uitterlinden, A.G. (André G.), Schouw, Y.T. (Yvonne) van der, Duijn, C.M. (Cornelia) van, Weiderpass, E. (Elisabete), Denchi, E.L. (Eros Lazzerini), Matullo, G., Butterworth, A.S. (Adam S.), Danesh, J. (John), Samani, N.J. (Nilesh), Wareham, N.J. (Nick), Nelson, C.P. (Christopher P.), Langenberg, C. (Claudia), and Codd, V. (Veryan)
Abstract: Leukocyte telomere length (LTL) is a heritable biomarker of genomic aging. In this study, we perform a genome-wide meta-analysis of LTL by pooling densely genotyped and imputed association results across large-scale European-descent studies including up to 78,592 individuals. We identify 49 genomic regions at a false dicovery rate (FDR) < 0.05 threshold and prioritize genes at 31, with five highlighting nucleotide metabolism as an important regulator of LTL. We report six genome-wide significant loci in or near SENP7, MOB1B, CARMIL1, PRRC2A, TERF2, and RFWD3, and our results support recently identified PARP1, POT1, ATM, and MPHOSPH6 loci. Phenome-wide analyses in >350,000 UK Biobank participants suggest that genetically shorter telomere length increases the risk of hypothyroidism and decreases the risk of thyroid cancer, lymphoma, and a range of proliferative conditions. Our results replicate previously reported associations with increased risk of coronary artery disease and lower risk for multiple cancer types. Our findings substantially expand current knowledge on genes that regulate LTL and their impact on human health and disease.
Published: 2020
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38. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

Author: Shah, S. (Sonia), Henry, A. (Albert), Roselli, C. (Carolina), Lin, H. (Honghuang), Sveinbjörnsson, G. (Garðar), Fatemifar, G. (Ghazaleh), Hedman, A.K. (Asa), Wilk, J.B. (Jemma), Morley, M.P. (Michael P.), Chaffin, M.D. (Mark D.), Helgadottir, H.T. (Hafdis), Verweij, N. (Niek), Dehghan, A. (Abbas), Almgren, P. (Peter), Andersson, C. (Charlotte), Aragam, K.G. (Krishna G.), Ärnlöv, J. (Johan), Backman, J.D. (Joshua D.), Biggs, M.L. (Mary L.), Bloom, H.L. (Heather L.), Brandimarto, J. (Jeffrey), Brown, M.R. (Michael R.), Buckbinder, L. (Leonard), Carey, D.J. (David J.), Chasman, D.I. (Daniel I.), Chen, X. (Xing), Chen, X. (Xu), Chung, J. (Jonathan), Chutkow, W. (William), Cook, J.P. (James P.), Delgado, G., Denaxas, S. (Spiros), Doney, A.S.F. (Alex), Dörr, M. (Marcus), Dudley, S.C. (Samuel C.), Dunn, M.E. (Michael E.), Engström, G., Esko, T. (Tõnu), Felix, S.B. (Stephan B.), Finan, C. (Chris), Ford, I. (Ian), Ghanbari, M. (Mohsen), Ghasemi, S. (Sahar), Giedraitis, V. (Vilmantas), Giulianini, F. (Franco), Gottdiener, J.S. (John), Gross, S. (Stefan), Guðbjartsson, D.F. (Daníel F.), Gutmann, R. (Rebecca), Haggerty, C.M. (Christopher M.), Harst, P. (Pim) van der, Hyde, C.L. (Craig L.), Ingelsson, E. (Erik), Jukema, J.W. (Jan Wouter), Kavousi, M. (Maryam), Khaw, K.-T. (Kay-Tee), Kleber, M.E. (Marcus), Køber, L. (Lars), Koekemoer, A. (Andrea), Langenberg, C. (Claudia), Kao, W.H.L. (Wen), Lindgren, C.M. (Cecilia M.), London, B. (Barry), Lotta, L.A. (Luca A.), Lovering, R.C. (Ruth C.), Luan, J., Magnusson, P.K. (Patrik), Mahajan, A. (Anubha), Margulies, K.B. (Kenneth B.), Ye, S. (Shu), Melander, O. (Olle), Mordi, I.R. (Ify R.), Morgan, T. (Thomas), Morris, A.D. (Andrew D.), Morris, A.P. (Andrew), Morrison, A.C. (Alanna C.), Nagle, M.W. (Michael W.), Nelson, C.P. (Christopher P.), Niessner, A. (Alexander), Niiranen, T. (Teemu), O’Donoghue, M.L. (Michelle L.), Owens, A.T. (Anjali T.), Palmer, C.N.A. (Colin N. A.), Parry, H.M. (Helen M.), Perola, M. (Markus), Portilla-Fernandez, E. (Eliana), Psaty, B.M. (Bruce M.), Abecasis, G. (Goncalo), Backman, J. (Joshua), Bai, X. (Xiaodong), Balasubramanian, S. (Suganthi), Banerjee, N. (Nilanjana), Baras, A. (Aris), Barnard, L. (Leland), Beechert, C. (Christina), Blumenfeld, A. (Andrew), Cantor, M. (Michael), Chai, Y. (Yating), Coppola, G. (Giovanni), Damask, A. (Amy), Dewey, F. (Frederick), Economides, A. (Aris), Eom, G. (Gisu), Forsythe, C. (Caitlin), Fuller, E.D. (Erin D.), Gu, Z. (Zhenhua), Gurski, L. (Lauren), Guzzardo, P.M. (Paloma M.), Habegger, L. (Lukas), Hahn, Y. (Young), Hawes, A. (Alicia), van Hout, C. (Cristopher), Jones, M.B. (Marcus B.), Khalid, S. (Shareef), Lattari, M. (Michael), Li, A. (Alexander), Lin, N. (Nan), Liu, D. (Daren), Lopez, A. (Alexander), Manoochehri, K. (Kia), Marchini, J. (Jonathan), Marcketta, A. (Anthony), Maxwell, E.K. (Evan K.), McCarthy, S. (Shane), Mitnaul, L.J. (Lyndon), O’Dushlaine, C. (Colm), Overton, J.D. (John D.), Padilla, M.S. (Maria Sotiropoulos), Paulding, C. (Charles), Penn, J. (John), Pradhan, M. (Manasi), Reid, J.G. (Jeffrey G.), Schleicher, T.D. (Thomas D.), Schurmann, C. (Claudia), Shuldiner, A. (Alan), Staples, J.C. (Jeffrey C.), Sun, D. (Dylan), Toledo, K. (Karina), Ulloa, R.H. (Ricardo H.), Widom, L. (Louis), Wolf, S.E. (Sarah E.), Yadav, A. (Ashish), Ye, B. (Bin), Rice, K.M. (Kenneth), Ridker, P.M. (Paul M.), Romaine, S.P.R. (Simon P. R.), Rotter, J.I. (Jerome I.), Salo, P. (Perttu), Salomaa, V. (Veikko), Setten, J. (Jessica) van, Shalaby, A.A. (Alaa A.), Smelser, D.T. (Diane T.), Smith, N.L. (Nicholas L.), Stender, S. (Steen), Stott, D.J. (David. J.), Svensson, P. (Per), Tammesoo, M.L., Taylor, K.D. (Kent D.), Teder-Laving, M. (Maris), Teumer, A. (Alexander), Thorgeirsson, G. (Guðmundur), Thorsteinsdottir, U. (Unnur), Torp-Pedersen, C. (Christian Tobias), Trompet, S. (Stella), Tyl, B. (Benoit), Uitterlinden, A.G. (Andre G.), Veluchamy, A. (Abirami), Völker, U. (Uwe), Voors, A.A. (Adriaan A.), Wang, X. (Xiaosong), Wareham, N.J. (Nick), Waterworth, D. (Dawn), Weeke, P.E. (Peter E.), Weiss, R. (Ram), Wiggins, K.L. (Kerri L.), Xing, H. (Heming), Yerges-Armstrong, L.M. (Laura), Yu, B. (Bing), Zannad, F. (Faiez), Zhao, J.H. (Jing Hua), Hemingway, H., Samani, N.J. (Nilesh J.), McMurray, J.J.V. (John J. V.), Yang, J. (Jian), Visscher, P.M. (Peter M.), Newton-Cheh, C. (Christopher), Mälarstig, A. (Anders), Holm, H. (Hilma), Lubitz, S.A. (Steven), Sattar, N. (Naveed), Holmes, M.V. (Michael), Cappola, T.P. (Thomas P.), Asselbergs, F.W. (Folkert), Hingorani, A. (Aroon), Kuchenbaecker, K.B. (Karoline), Ellinor, P.T. (Patrick), Lang, C.C. (Chim C.), Stefansson, K. (Kari), Smith, J.G. (J Gustav), Vasan, R.S. (Ramachandran Srini), Swerdlow, D.I. (Daniel), Lumbers, R.T. (R. Thomas), Shah, S. (Sonia), Henry, A. (Albert), Roselli, C. (Carolina), Lin, H. (Honghuang), Sveinbjörnsson, G. (Garðar), Fatemifar, G. (Ghazaleh), Hedman, A.K. (Asa), Wilk, J.B. (Jemma), Morley, M.P. (Michael P.), Chaffin, M.D. (Mark D.), Helgadottir, H.T. (Hafdis), Verweij, N. (Niek), Dehghan, A. (Abbas), Almgren, P. (Peter), Andersson, C. (Charlotte), Aragam, K.G. (Krishna G.), Ärnlöv, J. (Johan), Backman, J.D. (Joshua D.), Biggs, M.L. (Mary L.), Bloom, H.L. (Heather L.), Brandimarto, J. (Jeffrey), Brown, M.R. (Michael R.), Buckbinder, L. (Leonard), Carey, D.J. (David J.), Chasman, D.I. (Daniel I.), Chen, X. (Xing), Chen, X. (Xu), Chung, J. (Jonathan), Chutkow, W. (William), Cook, J.P. (James P.), Delgado, G., Denaxas, S. (Spiros), Doney, A.S.F. (Alex), Dörr, M. (Marcus), Dudley, S.C. (Samuel C.), Dunn, M.E. (Michael E.), Engström, G., Esko, T. (Tõnu), Felix, S.B. (Stephan B.), Finan, C. (Chris), Ford, I. (Ian), Ghanbari, M. (Mohsen), Ghasemi, S. (Sahar), Giedraitis, V. (Vilmantas), Giulianini, F. (Franco), Gottdiener, J.S. (John), Gross, S. (Stefan), Guðbjartsson, D.F. (Daníel F.), Gutmann, R. (Rebecca), Haggerty, C.M. (Christopher M.), Harst, P. (Pim) van der, Hyde, C.L. (Craig L.), Ingelsson, E. (Erik), Jukema, J.W. (Jan Wouter), Kavousi, M. (Maryam), Khaw, K.-T. (Kay-Tee), Kleber, M.E. (Marcus), Køber, L. (Lars), Koekemoer, A. (Andrea), Langenberg, C. (Claudia), Kao, W.H.L. (Wen), Lindgren, C.M. (Cecilia M.), London, B. (Barry), Lotta, L.A. (Luca A.), Lovering, R.C. (Ruth C.), Luan, J., Magnusson, P.K. (Patrik), Mahajan, A. (Anubha), Margulies, K.B. (Kenneth B.), Ye, S. (Shu), Melander, O. (Olle), Mordi, I.R. (Ify R.), Morgan, T. (Thomas), Morris, A.D. (Andrew D.), Morris, A.P. (Andrew), Morrison, A.C. (Alanna C.), Nagle, M.W. (Michael W.), Nelson, C.P. (Christopher P.), Niessner, A. (Alexander), Niiranen, T. (Teemu), O’Donoghue, M.L. (Michelle L.), Owens, A.T. (Anjali T.), Palmer, C.N.A. (Colin N. A.), Parry, H.M. (Helen M.), Perola, M. (Markus), Portilla-Fernandez, E. (Eliana), Psaty, B.M. (Bruce M.), Abecasis, G. (Goncalo), Backman, J. (Joshua), Bai, X. (Xiaodong), Balasubramanian, S. (Suganthi), Banerjee, N. (Nilanjana), Baras, A. (Aris), Barnard, L. (Leland), Beechert, C. (Christina), Blumenfeld, A. (Andrew), Cantor, M. (Michael), Chai, Y. (Yating), Coppola, G. (Giovanni), Damask, A. (Amy), Dewey, F. (Frederick), Economides, A. (Aris), Eom, G. (Gisu), Forsythe, C. (Caitlin), Fuller, E.D. (Erin D.), Gu, Z. (Zhenhua), Gurski, L. (Lauren), Guzzardo, P.M. (Paloma M.), Habegger, L. (Lukas), Hahn, Y. (Young), Hawes, A. (Alicia), van Hout, C. (Cristopher), Jones, M.B. (Marcus B.), Khalid, S. (Shareef), Lattari, M. (Michael), Li, A. (Alexander), Lin, N. (Nan), Liu, D. (Daren), Lopez, A. (Alexander), Manoochehri, K. (Kia), Marchini, J. (Jonathan), Marcketta, A. (Anthony), Maxwell, E.K. (Evan K.), McCarthy, S. (Shane), Mitnaul, L.J. (Lyndon), O’Dushlaine, C. (Colm), Overton, J.D. (John D.), Padilla, M.S. (Maria Sotiropoulos), Paulding, C. (Charles), Penn, J. (John), Pradhan, M. (Manasi), Reid, J.G. (Jeffrey G.), Schleicher, T.D. (Thomas D.), Schurmann, C. (Claudia), Shuldiner, A. (Alan), Staples, J.C. (Jeffrey C.), Sun, D. (Dylan), Toledo, K. (Karina), Ulloa, R.H. (Ricardo H.), Widom, L. (Louis), Wolf, S.E. (Sarah E.), Yadav, A. (Ashish), Ye, B. (Bin), Rice, K.M. (Kenneth), Ridker, P.M. (Paul M.), Romaine, S.P.R. (Simon P. R.), Rotter, J.I. (Jerome I.), Salo, P. (Perttu), Salomaa, V. (Veikko), Setten, J. (Jessica) van, Shalaby, A.A. (Alaa A.), Smelser, D.T. (Diane T.), Smith, N.L. (Nicholas L.), Stender, S. (Steen), Stott, D.J. (David. J.), Svensson, P. (Per), Tammesoo, M.L., Taylor, K.D. (Kent D.), Teder-Laving, M. (Maris), Teumer, A. (Alexander), Thorgeirsson, G. (Guðmundur), Thorsteinsdottir, U. (Unnur), Torp-Pedersen, C. (Christian Tobias), Trompet, S. (Stella), Tyl, B. (Benoit), Uitterlinden, A.G. (Andre G.), Veluchamy, A. (Abirami), Völker, U. (Uwe), Voors, A.A. (Adriaan A.), Wang, X. (Xiaosong), Wareham, N.J. (Nick), Waterworth, D. (Dawn), Weeke, P.E. (Peter E.), Weiss, R. (Ram), Wiggins, K.L. (Kerri L.), Xing, H. (Heming), Yerges-Armstrong, L.M. (Laura), Yu, B. (Bing), Zannad, F. (Faiez), Zhao, J.H. (Jing Hua), Hemingway, H., Samani, N.J. (Nilesh J.), McMurray, J.J.V. (John J. V.), Yang, J. (Jian), Visscher, P.M. (Peter M.), Newton-Cheh, C. (Christopher), Mälarstig, A. (Anders), Holm, H. (Hilma), Lubitz, S.A. (Steven), Sattar, N. (Naveed), Holmes, M.V. (Michael), Cappola, T.P. (Thomas P.), Asselbergs, F.W. (Folkert), Hingorani, A. (Aroon), Kuchenbaecker, K.B. (Karoline), Ellinor, P.T. (Patrick), Lang, C.C. (Chim C.), Stefansson, K. (Kari), Smith, J.G. (J Gustav), Vasan, R.S. (Ramachandran Srini), Swerdlow, D.I. (Daniel), and Lumbers, R.T. (R. Thomas)
Abstract: Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.
Published: 2020
Full Text: View/download PDF

39. Consumption of nuts and seeds and pancreatic ductal adenocarcinoma risk in the European Prospective Investigation into Cancer and Nutrition

Author: IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Obón-Santacana, M., Luján-Barroso, L., Freisling, H., Naudin, S., Boutron-Ruault, M.-C., Mancini, F.R., Rebours, V., Kühn, T., Katzke, V., Boeing, H., Tjønneland, A., Olsen, A., Overvad, K., Lasheras, C., Rodríguez-Barranco, M., Amiano, P., Santiuste, C., Ardanaz, E., Khaw, K.-T., Wareham, N.J., Aune, D., Trichopoulou, A., Thriskos, P., Peppa, E., Masala, G., Grioni, S., Tumino, R., Panico, S., Bueno-de-Mesquita, B., Sciannameo, V., Vermeulen, R., Sonestedt, E., Sund, M., Weiderpass, E., Skeie, G., Riboli, E., Duell, E.J., IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Obón-Santacana, M., Luján-Barroso, L., Freisling, H., Naudin, S., Boutron-Ruault, M.-C., Mancini, F.R., Rebours, V., Kühn, T., Katzke, V., Boeing, H., Tjønneland, A., Olsen, A., Overvad, K., Lasheras, C., Rodríguez-Barranco, M., Amiano, P., Santiuste, C., Ardanaz, E., Khaw, K.-T., Wareham, N.J., Aune, D., Trichopoulou, A., Thriskos, P., Peppa, E., Masala, G., Grioni, S., Tumino, R., Panico, S., Bueno-de-Mesquita, B., Sciannameo, V., Vermeulen, R., Sonestedt, E., Sund, M., Weiderpass, E., Skeie, G., Riboli, E., and Duell, E.J.
Published: 2020

40. Blood pressure and risk of cancer in the European Prospective Investigation into Cancer and Nutrition

Author: IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Christakoudi, S., Kakourou, A., Markozannes, G., Tzoulaki, I., Weiderpass, E., Brennan, P., Gunter, M., Dahm, C.C., Overvad, K., Olsen, A., Tjønneland, A., Boutron-Ruault, M.-C., Madika, A.-L., Severi, G., Katzke, V., Kühn, T., Bergmann, M.M., Boeing, H., Karakatsani, A., Martimianaki, G., Thriskos, P., Masala, G., Sieri, S., Panico, S., Tumino, R., Ricceri, F., Agudo, A., Redondo-Sánchez, D., Colorado-Yohar, S.M., Mokoroa, O., Melander, O., Stocks, T., Häggström, C., Harlid, S., Bueno-de-Mesquita, B., van Gils, C.H., Vermeulen, R.C.H., Khaw, K.-T., Wareham, N.J., Tong, T.Y.N., Freisling, H., Johansson, M., Lennon, H., Aune, D., Riboli, E., Trichopoulos, D., Trichopoulou, A., Tsilidis, K.K., IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Christakoudi, S., Kakourou, A., Markozannes, G., Tzoulaki, I., Weiderpass, E., Brennan, P., Gunter, M., Dahm, C.C., Overvad, K., Olsen, A., Tjønneland, A., Boutron-Ruault, M.-C., Madika, A.-L., Severi, G., Katzke, V., Kühn, T., Bergmann, M.M., Boeing, H., Karakatsani, A., Martimianaki, G., Thriskos, P., Masala, G., Sieri, S., Panico, S., Tumino, R., Ricceri, F., Agudo, A., Redondo-Sánchez, D., Colorado-Yohar, S.M., Mokoroa, O., Melander, O., Stocks, T., Häggström, C., Harlid, S., Bueno-de-Mesquita, B., van Gils, C.H., Vermeulen, R.C.H., Khaw, K.-T., Wareham, N.J., Tong, T.Y.N., Freisling, H., Johansson, M., Lennon, H., Aune, D., Riboli, E., Trichopoulos, D., Trichopoulou, A., and Tsilidis, K.K.
Published: 2020

41. Improved cardiovascular risk prediction using plasma proteomics in primary prevention

Author: Hoogeveen, R.M., primary, Pereira, J. P. Belo, additional, Nurmohamed, N.S., additional, Zampoleri, V., additional, Bom, M., additional, Baragetti, A., additional, Boekholdt, M.S., additional, Knaapen, P., additional, Khaw, K.-T., additional, Wareham, N.J., additional, Groen, B., additional, Catapano, A.L., additional, Koenig, W., additional, Levin, E., additional, and Stroes, E., additional
Published: 2020
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42. Tissue factor serum levels and the risk of future coronary artery disease in apparently healthy men and women: the EPIC‐Norfolk prospective population study

Author: KELLER, T.T., NAGEL, C., TE VELTHUIS, H., GERDES, V.E.A., WAREHAM, N.J., BINGHAM, S.A., LUBEN, R., HACK, C.E., REITSMA, P.H., LEVI, M., KHAW, K.T., and BOEKHOLDT, S.M.
Published: 2006
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43. Fibrinogen plasma levels modify the association between the factor XIII Val34Leu variant and risk of coronary artery disease: the EPIC‐Norfolk prospective population study

Author: BOEKHOLDT, S.M., SANDHU, M.S., WAREHAM, N.J., LUBEN, R., REITSMA, P.H., and KHAW, K‐T
Published: 2006
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44. Cross-sectional association between total level and type of alcohol consumption and glycosylated haemoglobin level: the EPIC-Norfolk Study

Author: Harding, A.-H., Sargeant, L.A., Khawl, K.-T., Welch, A., Oakes, S., Luben, R.N., Bingham, S., Day, N.E., and Wareham, N.J.
Subjects: Drinking of alcoholic beverages -- Health aspects, Drinking of alcoholic beverages -- Demographic aspects, Glycosylated hemoglobin -- Measurement
Abstract: Objective: To investigate the association between total level and type of alcohol consumed and glycaemia. Design: Cross-sectional study. Setting: The EPIC-Norfolk Study, a population-based cohort study of diet and chronic disease. Subjects and methods: Non-diabetic men (n=2842) and women (n=3572), aged 40 -78 y. Alcohol intake was assessed by self-reported questionnaire, and glycaemia measured by glycosylated haemoglobin ([HbA.sub.1c]). Results: Ten percent of men and 18% of women reported drinking no alcohol. Among drinkers, median alcohol intake was 8 units/week for men and 3 units/week for women. In analyses stratified by sex and adjusted for age, total energy intake, education, fruit and vegetable intake, smoking, family history of diabetes, physical activity, body mass index and waist:hip ratio, alcohol intake was inversely associated with [HbA.sub.1c] in men and women, although the association was stronger in women. A 1 unit/week increase in alcohol intake was associated with 0.0049% (s.e.=0.00223; P-value=0.028) and 0.017% (s.e.=0.00343; P-value Conclusion: Alcohol intake was associated with lower [HbA.sub.1c] level, an association not explained by confounding. The distinction between type of alcohol consumed was particularly important in men. Sponsorship: NJW is an IVJRC Clinician Scientist Fellow. doi:10.1038/sj.ejcn.1601408 Keywords: alcohol; glycosylated haemoglobin; diabetes mellitus; epidemiology, Introduction Hyperglycaemia, as measured by glycosylated haemoglobin ([HbA.sub.1c]), is related to all-cause and cardiovascular disease (CVD) mortality. In the EPIC-Norfolk study, [HbA.sub.1c] was positively related to all-cause and coronary heart [...]
Published: 2002

45. Fruit and vegetable intake and population glycosylated haemoglobin levels: the EPIC-Norfolk Study. (Original Communication)

Author: Sargeant, L.A., Khaw, K.T., Bingham, S., Day, N.E., Luben, R.N., Oakes, S., Welch, A., and Wareham, N.J.
Subjects: Food habits -- Research, Fruit -- Nutritional aspects, Vegetables -- Nutritional aspects, Diabetes -- Prevention, Glucose metabolism -- Research
Abstract: Objective: To investigate whether self-reported frequency of fruit and vegetable consumption was associated with [HbA.sub.1C] levels in individuals not known to have diabetes, and what dietary and lifestyle factors might explain this association. Design: Cross-sectional study. Setting: The EPIC-Norfolk Study, a population-based cohort study of diet and chronic disease. Subjects and methods: A total of 2678 men and 3318 women (45 -74 y) not known to have diabetes reported weekly consumption of fruit, green leafy vegetables and other vegetables. Results: Among men, 274 (10.2%) reported seldom or never eating fruit and 127 (4.7%) seldom or never eating green leafy vegetables. Corresponding numbers in women were 157 (4.7%) and 92 (2.8%), respectively. Participants who reported never or seldom having both fruit and green leafy vegetables had higher mean (s.d.) [HbA.sub.1C] measurements (5.43% (0.71)) than those who reported more frequent consumption (5.34% (0.67); P=0.046). Differences by category of fruit or green leafy vegetable consumption were not substantially changed after adjustment for saturated fat, dietary fibre and plasma vitamin C. Conclusion: These findings support the hypothesis that high intake of fruit and green leafy vegetables may influence glucose metabolism independent of dietary fibre or vitamin C alone and that increased consumption may contribute to the prevention of diabetes. Sponsorship: NJW is an MRC Clinician Scientist Fellow. Descriptors: fruit; vegetables; glycosylated haemoglobin; diabetes mellitus; epidemiology, Introduction Recommendations to increase fruit and vegetable consumption to five servings daily are prominent features of health promotion programmes (National Cancer Institute & Produce for Better-Health 1994; Foerster et al, [...]
Published: 2001

46. A combined heart rate and movement sensor: proof of concept and preliminary testing study

Author: Rennie, K., Rowsell, T., Jebb, S.A., Holburn, D., and Wareham, N.J.
Subjects: Transducers, Biomedical -- Usage, Transducers, Biomedical -- Methods, Bioenergetics -- Measurement, Energy metabolism -- Measurement
Abstract: Objective: Heart rate monitoring has previously been used as a technique for measuring energy expenditure (EE) in field studies. However, the combination of heart rate monitoring with movement sensoring could have theoretical advantages compared to either method used alone. Therefore, this study was undertaken to develop and validate a new combined heart rate monitor and movement sensor instrument (HR+M) for measuring EE. Methods: The HR+M instrument is a single-piece instrument worn around the chest which records minute-by-minute heart rate and movement. Eight subjects underwent an individual calibration in which EE and heart rate were measured at rest and during a sub-maximal bicycle ergometer test. They then wore the HR + M for 24 hours in a whole-body calorimeter and underwent a standard protocol including periods of physical activity and inactivity. Minute-by-minute heart rate was converted to EE using individual calibration curves with the motion data discriminating between periods of inactivity and activity at low heart rate levels. EE was also calculated using the HRFlex method which relies on heart rate alone. Both estimates of EE were compared to EE measured in the whole-body calorimeter. Results: The mean percentage error of the HR + M method calculating TEE compared with the gold standard of the calorimeter measurement was 0.00% (95% CI of the mean error -0.25, 1.25). The HRFIex method using the heart rate information alone resulted in a mean percentage error of 16.5% (95% CI of the mean error -0.57, 1.76). Conclusions: This preliminary test of HR+M demonstrates its ability to estimate EE and the pattern of EE and activity throughout the day. Further validation studies in free-living individuals are necessary. Sponsorship: NJW is an MRC Clinician Scientist Fellow. KLR holds an MRC PhD scholarship. Descriptors: heart rate monitor; movement sensor; energy expenditure European Journal of Clinical Nutrition (2000) 54, 409-414, Introduction The development of objective and valid methods for assessing energy expenditure (EE) in population-based studies is an important goal. Such methods would be useful in assessing the strength and [...]
Published: 2000

47. Derivation and validation of diabetes risk score for urban Asian Indians

Author: Ramachandran, A., Snehalatha, C., Vijay, V., Wareham, N.J., and Colagiuri, S.
Published: 2005
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48. Inflammatory biomarkers and the prediction of coronary events among people at intermediate risk: the EPIC-Norfolk prospective population study

Author: Rana, J.S., Cote, M., Despres, J.-P., Sandhu, M.S., Talmud, P.J., Ninio, E., Wareham, N.J., Kastelein, J.J.P., Zwinderman, A.H., Khaw, K.-T., and Boekholdt, S.M.
Subjects: Biological markers -- Research, C-reactive protein -- Physiological aspects, C-reactive protein -- Measurement, C-reactive protein -- Research, Coronary heart disease -- Risk factors, Coronary heart disease -- Research, Health
Published: 2009

49. World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions

Author: Angelantonio, E. di, Kaptoge, S., Pennells, L., Bacquer, D. de, Cooney, M.T., Kavousi, M., Stevens, G., Riley, L., Savin, S., Altay, S., Amouyel, P., Assmann, G., Bell, S., Ben-Shlomo, Y., Berkman, L., Beulens, J.W., Bjorkelund, C., Blaha, M.J., Blazer, D.G., Bolton, T., Bonita, R., Brenner, B.H., Brunner, E.J., Casiglia, E., Chamnan, P., Choi, Y.H., Chowdhury, R., Coady, S., Crespo, C.J., Cushman, M., Dagenais, G.R., D'Agostino, R.B., Daimon, M., Davidson, K.W., Engstrom, G., Fang, X.H., Ford, I., Gallacher, J., Gansevoort, R.T., Gaziano, T.A., Giampaoli, S., Grandits, G., Grimsgaard, S., Grobbee, D.E., Gudnason, V., Guo, Q., Humphries, S., Iso, H., Jukema, J.W., Kauhanen, J., Kengne, A.P., Khalili, D., Khan, T., Knuiman, M., Koenig, W., Kromhout, D., Krumholz, H.M., Lam, T.H., Laughlin, G., Ibanez, A.M., Moons, K.G.M., Nietert, P.J., Ninomiya, T., Nordestgaard, B.G., O'Donnell, C., Palmieri, L., Patel, A., Perel, P., Price, J.F., Costa, R.B.D.E., Ridker, P.M., Rodriguez, B., Rosengren, A., Roussel, R., Sakurai, M., Salomaa, V., Sato, S., Schottker, B., Shara, N., Shaw, J.E., Shin, H.C., Simons, L.A., Sofianopoulou, E., Sundstrom, J., Tolonen, H., Ueshima, H., Volzke, H., Wallace, R.B., Wareham, N.J., Willeit, P., Wood, D., Wood, A., Zhao, D., Onuma, O., Woodward, M., Danaei, G., Roth, G., Mendis, S., Graham, I., Varghese, C., Ezzati, M., Jackson, R., Danesh, J., Nambi, V., Matsushita, K., Couper, D., Diabetes, A., Zimmet, P.Z., Barr, E.L.M., Atkins, R., Whincup, P.H., Study, B., Kiechl, S., Willeit, J., Rungger, G., Sofat, R., Dale, C., Casas, J.P., Tikhonoff, V., Hunt, K.J., Sutherland, S.E., Psaty, B.M., Tracy, R., Frikke-Schmidt, R., Jensen, G.B., Schnohr, P., Donfrancesco, C., Vanuzzo, D., Panico, S., Balkau, B., Bonnet, F., Fumeron, F., Simons, J., McLachlan, S., Guralnik, J., Khaw, K.T., Brenner, H., Zhang, Y., Holleczek, B., Cohort, F., Vartiainen, E., Jousilahti, P., Harald, K., Massaro, J.J., Pencina, M., Ramachandran, V., Susa, S., Oizumi, T., Kayama, T., Wilhelmsen, L., Lissner, L., Hange, D., Mehlig, K., Hata, J., Yoshida, D., Hirakawa, Y., Rutters, F., Elders, P.J.M., Kyowa, I., Kiyama, M., Yamagishi, K., Tuomainen, T.P., Virtanen, J., Salonen, J.T., Meade, T.W., Nilsson, P.M., Melander, O., Boer, I.H. de, DeFilippis, A.P., Kuller, L.H., Juan, S.I., Gillum, R.F., Kirkland, S., Shimbo, D., Schwartz, J.E., Imano, H., Harst, P. van der, Hillige, J.L., Bakker, S.J., Dallongeville, J., Ferrieres, J., Moitry, M., Stott, D.J., Despres, J.P., Laughlin, G.A., Daniels, L.B., McEvoy, L.K., Aspelund, T., Thorsson, B., Gudmundsson, E.F., Aribas, E., Rueda-Ochoa, O.L., Ikram, M.K., Heshmatollah, A., Ikram, M.A., Dorr, M., Nauck, M., Howard, B., Can, G., Ishizaki, M., Wilsgaard, T., Mathiesen, E., Giedraitis, V., Ingelsson, M., Cook, N., Buring, J., Schouw, Y.T. van der, Claessen, H., Rothenbacher, D., Arndt, V., Study, W.I., Shipley, M., Packard, C., Robertson, M., Young, R., Feskens, E., Geleijnse, J.M., Fang, X., Gu, D.F., Huxley, R., Imai, Y., Kim, H.C., Pan, W.H., Rodgers, A., Suh, I., Town, A., Okayama, A., Maegawa, H., Nakamura, M., Aoki, N., Wu, Z.S., Yao, C.H., Luszcz, M., Tang, Z., Liu, L.S., Xie, J.X., Norton, R., Ameratunga, S., MacMahon, S., Whitlock, G., Knuiman, M.W., Christensen, H., Wu, X.G., Zhou, J., Yu, X.H., Tamakoshi, W.A., Wu, Z.L., Chen, L.Q., Shan, G.L., Sritara, P., Duan, X.F., Li, Y.H., Jiang, C.Q., Woo, J., Ho, S.C., Hong, Z., Huang, M.S., Zhou, B., Fuh, J.L., Kita, Y., Choudhury, S.R., Jee, S.H., Kim, Woodward, M, Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Epidemiology, Epidemiology and Data Science, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, and APH - Health Behaviors & Chronic Diseases
Subjects: Male, 10-YEAR RISK, BLOOD-PRESSURE, 0302 clinical medicine, Risk Factors, Medicine and Health Sciences, Medicine, Uganda, Cardiac and Cardiovascular Systems, Prospective Studies, 030212 general & internal medicine, Aged, 80 and over, Medicine(all), Kardiologi, lcsh:Public aspects of medicine, PRIMARY-CARE, Public Health, Global Health, Social Medicine and Epidemiology, General Medicine, Middle Aged, 3. Good health, Pooled analysis, Cardiovascular Diseases, Egypt, Female, Adult, PROSPECTIVE COHORTS, 030231 tropical medicine, 195 COUNTRIES, Primary care, World Health Organization, Risk Assessment, Article, World health, POOLED ANALYSIS, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Primary prevention, Environmental health, SYSTEMATIC ANALYSIS, Humans, Aged, CHINESE POPULATION, Chinese population, business.industry, Individual participant data, lcsh:RA1-1270, R1, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Disease risk, business, INDIVIDUAL PARTICIPANT DATA, PRIMARY PREVENTION
Abstract: Background: To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. Methods: In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40–80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. Findings: Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0·685 (95% CI 0·629–0·741) to 0·833 (0·783–0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40–64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. Interpretation: We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. Funding: World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research. The WHO CVD Risk Chart Working Group, for complete list of authors see http://dx.doi.org/10.1016/S2214-109X(19)30318-3
Published: 2019

50. Coffee and tea drinking in relation to the risk of differentiated thyroid carcinoma: results from the European Prospective Investigation into Cancer and Nutrition (EPIC) study

Author: Zamora-Ros, R. Alghamdi, M.A. Cayssials, V. Franceschi, S. Almquist, M. Hennings, J. Sandström, M. Tsilidis, K.K. Weiderpass, E. Boutron-Ruault, M.-C. Hammer Bech, B. Overvad, K. Tjønneland, A. Petersen, K.E.N. Mancini, F.R. Mahamat-Saleh, Y. Bonnet, F. Kühn, T. Fortner, R.T. Boeing, H. Trichopoulou, A. Bamia, C. Martimianaki, G. Masala, G. Grioni, S. Panico, S. Tumino, R. Fasanelli, F. Skeie, G. Braaten, T. Lasheras, C. Salamanca-Fernández, E. Amiano, P. Chirlaque, M.-D. Barricarte, A. Manjer, J. Wallström, P. Bueno-de-Mesquita, H.B. Peeters, P.H. Khaw, K.-T. Wareham, N.J. Schmidt, J.A. Aune, D. Byrnes, G. Scalbert, A. Agudo, A. Rinaldi, S.
Abstract: Purpose: Coffee and tea constituents have shown several anti-carcinogenic activities in cellular and animal studies, including against thyroid cancer (TC). However, epidemiological evidence is still limited and inconsistent. Therefore, we aimed to investigate this association in a large prospective study. Methods: The study was conducted in the EPIC (European Prospective Investigation into Cancer and Nutrition) cohort, which included 476,108 adult men and women. Coffee and tea intakes were assessed through validated country-specific dietary questionnaires. Results: During a mean follow-up of 14 years, 748 first incident differentiated TC cases (including 601 papillary and 109 follicular TC) were identified. Coffee consumption (per 100 mL/day) was not associated either with total differentiated TC risk (HRcalibrated 1.00, 95% CI 0.97–1.04) or with the risk of TC subtypes. Tea consumption (per 100 mL/day) was not associated with the risk of total differentiated TC (HRcalibrated 0.98, 95% CI 0.95–1.02) and papillary tumor (HRcalibrated 0.99, 95% CI 0.95–1.03), whereas an inverse association was found with follicular tumor risk (HRcalibrated 0.90, 95% CI 0.81–0.99), but this association was based on a sub-analysis with a small number of cancer cases. Conclusions: In this large prospective study, coffee and tea consumptions were not associated with TC risk. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
Published: 2019

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