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5. 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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10. Cardiovascular, renal and liver protection with novel antidiabetic agents beyond blood glucose lowering in type 2 diabetes: Consensus article from the European Society of Hypertension Working Group on Obesity, Diabetes and the High-risk Patient

Author

Kotsis, V. Jordan, J. Stabouli, S. Antza, C. Micic, D. Jelaković, B. Schlaich, M.P. Nilsson, P.M. Kreutz, R. Mancia, G. Tsioufis, K. Grassi, G.

Subjects
endocrine system, endocrine system diseases, nutritional and metabolic diseases, human activities
Abstract

The prevalence of type 2 diabetes (T2D) has increased over the past few decades. T2D has a strong genetic propensity that becomes overt when a patient is exposed to a typical Western lifestyle, gain weight and becomes obese, whereas weight loss protects from the development of T2D. Except of lifestyle modifications, the choice of the appropriate treatment is essential in the management of patients with T2D and appears critical for the obese population with T2D. The new pharmacological approach for the treatment of T2D, sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide 1 receptor agonists, seems to be effective not only in the management of T2D but also for weight loss, reduction of blood pressure and improvement of nonalcoholic fatty liver disease. Sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide 1 analogues reduced cardiovascular risk, prevented cardiovascular disease and mortality, thereby playing an important role in the treatment of obese patients with hypertension and T2D. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.

Published
2020

12. Gut microbiota composition in relation to intake of added sugar, sugar-sweetened beverages and artificially sweetened beverages in the Malmö Offspring Study

Author

Ramne, S., Brunkwall, L., Ericson, U., Gray, N., Kuhnle, G.G.C., Nilsson, P.M., Orho-Melander, M., Sonestedt, E., Ramne, S., Brunkwall, L., Ericson, U., Gray, N., Kuhnle, G.G.C., Nilsson, P.M., Orho-Melander, M., and Sonestedt, E.

Abstract

Purpose It has been suggested that a high intake of sugar or sweeteners may result in an unfavorable microbiota composition; however, evidence is lacking. Hence, in this exploratory epidemiological study, we aim to examine if intake of added sugar, sugar-sweetened beverages (SSBs) or artificially sweetened beverages (ASBs) associate with the gut microbiota composition. Methods Participants (18–70 years) in the Malmö Offspring Study have provided blood, urine, and fecal samples and completed both web-based 4 day food records and short food frequency questionnaires. The gut microbiota was assessed by 16S rRNA sequencing, processed in QIIME and matched to Greengenes (v.13.8), giving 64 included genera after filtering. Intake of added sugar (n = 1371) (also supported by the overnight urinary sugar biomarker in a subgroup n = 577), SSBs (n = 1086) and ASBs (n = 1085) were examined as exposures in negative binomial regressions. Results Various genera nominally associated with intake of added sugar, SSBs, and ASBs. Only the negative association between SSB intake and Lachnobacterium remained significant after multiple testing correction. A positive association between SSB intake and the Firmicutes:Bacteroidetes ratio was also observed. Conclusion In this wide population, the cross-sectional associations between added sugar and sweet beverage intake and the gut microbiota are modest, but the results suggest that SSB intake is associated negatively with the genus Lachnobacterium and positively with the Firmicutes:Bacteroidetes ratio. Larger studies, preferably using metagenomic sequencing, are needed to further evaluate if a link exists between intake of sugars and sweeteners and the human gut microbiota.

Published
2020

13. Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

Author

Folkersen, L., Gustafsson, S., Wang, Q., Hansen, D.H., Hedman, Å.K., Schork, A., Page, K., Zhernakova, D.V., Wu, Y., Peters, J., Eriksson, N., Bergen, S.E., Boutin, T.S., Bretherick, A.D., Enroth, S., Kalnapenkis, A., Gådin, J.R., Suur, B.E., Chen, Y., Matic, L., Gale, J.D., Lee, J., Zhang, W., Quazi, A., Ala-Korpela, M., Choi, S.H., Claringbould, A., Danesh, J., Davey Smith, G., de Masi, F., Elmståhl, S., Engström, G., Fauman, E., Fernandez, C., Franke, L., Franks, P.W., Giedraitis, V., Haley, C., Hamsten, A., Ingason, A., Johansson, Å., Joshi, P.K., Lind, L., Lindgren, C.M., Lubitz, S., Palmer, T., Macdonald-Dunlop, E., Magnusson, M., Melander, O., Michaelsson, K., Morris, A.P., Mägi, R., Nagle, M.W., Nilsson, P.M., Nilsson, J., Orho-Melander, M., Polasek, O., Prins, B., Pålsson, E., Qi, T., Sjögren, M., Sundström, J., Surendran, P., Võsa, U., Werge, T., Wernersson, R., Westra, H.-J., Yang, J., Zhernakova, A., Ärnlöv, J., Fu, J., Smith, J.G., Esko, T., Hayward, C., Gyllensten, U., Landen, M., Siegbahn, A., Wilson, J.F., Wallentin, L., Butterworth, A.S., Holmes, M.V., Ingelsson, E., Mälarstig, A., Folkersen, L., Gustafsson, S., Wang, Q., Hansen, D.H., Hedman, Å.K., Schork, A., Page, K., Zhernakova, D.V., Wu, Y., Peters, J., Eriksson, N., Bergen, S.E., Boutin, T.S., Bretherick, A.D., Enroth, S., Kalnapenkis, A., Gådin, J.R., Suur, B.E., Chen, Y., Matic, L., Gale, J.D., Lee, J., Zhang, W., Quazi, A., Ala-Korpela, M., Choi, S.H., Claringbould, A., Danesh, J., Davey Smith, G., de Masi, F., Elmståhl, S., Engström, G., Fauman, E., Fernandez, C., Franke, L., Franks, P.W., Giedraitis, V., Haley, C., Hamsten, A., Ingason, A., Johansson, Å., Joshi, P.K., Lind, L., Lindgren, C.M., Lubitz, S., Palmer, T., Macdonald-Dunlop, E., Magnusson, M., Melander, O., Michaelsson, K., Morris, A.P., Mägi, R., Nagle, M.W., Nilsson, P.M., Nilsson, J., Orho-Melander, M., Polasek, O., Prins, B., Pålsson, E., Qi, T., Sjögren, M., Sundström, J., Surendran, P., Võsa, U., Werge, T., Wernersson, R., Westra, H.-J., Yang, J., Zhernakova, A., Ärnlöv, J., Fu, J., Smith, J.G., Esko, T., Hayward, C., Gyllensten, U., Landen, M., Siegbahn, A., Wilson, J.F., Wallentin, L., Butterworth, A.S., Holmes, M.V., Ingelsson, E., and Mälarstig, A.

Abstract

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.

Published
2020

18. Incidence of severe knee and hip osteoarthritis in relation to different measures of body mass: a population-based prospective cohort study

Author

Lohmander, L.S., Gerhardsson de Verdier, M., Rollof, J., Nilsson, P.M., and Engstrom, G.

Subjects
Osteoarthritis -- Distribution, Osteoarthritis -- Demographic aspects, Osteoarthritis -- Physiological aspects, Osteoarthritis -- Research, Body mass index -- Research, Knee -- Diseases, Hip -- Diseases, Company distribution practices, Health
Published
2009

19. Plasma markers of inflammation and incidence of hospitalisations for COPD: results from a population-based cohort study

Author

Engstrom, G., Segelstorm, N., Ekberg-Aronsson, M., Nilsson, P.M., Lindgarde, F., and Lofdahl, C.-G.

Subjects
Biological markers -- Research, Lung diseases, Obstructive -- Development and progression, Lung diseases, Obstructive -- Statistics, Lung diseases, Obstructive -- Research, Blood proteins -- Physiological aspects, Blood proteins -- Research, Hospitals -- Admission and discharge, Hospitals -- Statistics, Hospitals -- Research, Health
Published
2009

20. 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

21. Association of Estimated Pulse Wave Velocity with Survival: A Secondary Analysis of SPRINT

Author

Vlachopoulos, C. Terentes-Printzios, D. Laurent, S. Nilsson, P.M. Protogerou, A.D. Aznaouridis, K. Xaplanteris, P. Koutagiar, I. Tomiyama, H. Yamashina, A. Sfikakis, P.P. Tousoulis, D.

Abstract

Importance: Aortic stiffness, as assessed by carotid-femoral pulse wave velocity, is an independent predictor of future events in individuals with hypertension. Recent data suggest a predictive role of estimated pulse wave velocity (ePWV) calculated by previously published equations using age and blood pressure in future events in individuals with hypertension. Objective: To investigate whether ePWV and its response to treatment predict survival in the Systolic Blood Pressure Intervention Trial (SPRINT). Design, Setting, and Participants: This exploratory, hypothesis-generating, post hoc secondary analysis conducted from October 1, 2018, to August 31, 2019, examined data from 9361 participants in SPRINT and calculated ePWV at baseline and at 12 months. Adjusted hazard ratios (HRs) with 95% CIs of ePWV per 1 SD were estimated using Cox proportional hazards regression models. A total of 8450 patients were assigned to 4 groups according to their treatment allocation and their response in ePWV after 12 months. Interventions: Participants were assigned a systolic blood pressure target of less than 120 mm Hg (intensive treatment) or less than 140 mm Hg (standard treatment). Main Outcomes and Measures: The primary composite cardiovascular outcome was myocardial infarction, other acute coronary syndromes, stroke, heart failure, or death from cardiovascular causes. Results: In the SPRINT population (3332 women and 6029 men; mean [SD] age, 67.9 [9.4] years), ePWV predicted the primary outcome (HR, 1.30 [95% CI, 1.17-1.43]; P

Published
2019

23. Exploration of biomarkers for subclinical atherosclerosis in an African population using a proteomics chip targeted at inflammation and cardiovascular disease

Author

10060871 - Malan, Leoné, 12076341 - Mels, Catharina Martha Cornelia, Jujic, A., Malan, L., Mels, C., Nilsson, P.M., Magnusson, M., 10060871 - Malan, Leoné, 12076341 - Mels, Catharina Martha Cornelia, Jujic, A., Malan, L., Mels, C., Nilsson, P.M., and Magnusson, M.

Abstract

Introduction: The evolving use of multiplex proteomic platforms provides an excellent tool for investigating associations between multiple proteins and subclinical atherosclerotic disease. In this study, we evaluated the impact of a multiplex protein panel, on carotid intima-media thickness (cIMT) as a marker of subclinical atherosclerosis. Purpose: We used a multiplex proteomic platform to identify possible associations between proteins and subclinical carotid atherosclerosis as measured by carotid ultrasound in an African population. Methods: In the Sympathetic Activity and Ambulatory Blood Pressure in Africans (SABPA) study, 92 proteins from the Proseek Multiplex CVD III 96×96 (Olink Bioscience, Sweden) were analyzed in 378 participants (mean age 44.7±9.6 years, 50.6% women, 10.8% with known cardiovascular disease). Carotid ultrasound was performed for measurements of the carotid intima-media thickness (cIMT, mean 0.663±0.127 mm) and calculation of cross-sectional wall area (CSWA, mean 13.5±4.4mm2), a measure of target organ damage. Possible associations between the proteins, and cIMT and CSWA, respectively, were explored using linear regression models. A two-sided Bonferroni corrected P-value of 0.05/92=5.4x10–4 was considered statistically significant in the crude analysis. Results: Of 18 proteins (1 standard deviation of change of ln-transformed values) that were Bonferroni-corrected (p≤5.4x10–4) significantly associated with cIMT and/or CWAS in crude analyses, the following remained significant after further adjustment for age, sex, waist circumference, systolic blood pressure, smoking and total cholesterol: growth-differentiation factor-15 (GDF15; β 0.017, p=0.050), E-selectin (SELE; β 0.019, p=0.017), carboxypeptidase A1 (CPA1; β 0.019, p=0.019), C-C motif chemokine 15 (CCL15; β 0.031, p<0.001), chitinase-3-like protein 1 (CHI3L1; β 0.021, p=0.007), the hemoglobin scavenger receptor (CD163; β 0.021, p=0.008) and osteoprotegerin (OPG; β 0.022, p=0.004). As f

Published
2019

25. Obesity and cardiovascular risk: A call for action from the European Society of Hypertension Working Group of Obesity, Diabetes and the High-risk Patient and European Association for the Study of Obesity: Part A: Mechanisms of obesity induced hypertension, diabetes and dyslipidemia and practice guidelines for treatment

Author

Kotsis, V. Jordan, J. Micic, D. Finer, N. Leitner, D.R. Toplak, H. Tokgozoglu, L. Athyros, V. Elisaf, M. Filippatos, T.D. Redon, J. Redon, P. Antza, C. Tsioufis, K. Grassi, G. Seravalle, G. Coca, A. Sierra, C. Lurbe, E. Stabouli, S. Jelakovic, B. Nilsson, P.M.

Abstract

Obesity is a key factor for cardiovascular diseases and complications. Obesity is associated with hypertension, dyslipidemia and type II diabetes, which are the major predictors of cardiovascular disease in the future. It predisposes for atrial fibrillation, heart failure, sudden cardiac death, renal disease and ischemic stroke that are the main causes of cardiovascular hospitalization and mortality. As obesity and the cardiovascular effects on the vessels and the heart start early in life, even from childhood, it is important for health policies to prevent obesity very early before the disease manifestation emerge. Key roles in the prevention are strategies to increase physical exercise, reduce body weight and to prevent or treat hypertension, lipids disorders and diabetes earlier and efficiently to prevent cardiovascular complications. Epidemiology and mechanisms of obesity-induced hypertension, diabetes and dyslipidemia will be reviewed and the role of lifestyle modification and treatment strategies in obesity will be updated and analyzed. The best treatment options for people with obesity, hypertension, diabetes and dyslipidemia will discussed. Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.

Published
2018

26. Obesity and cardiovascular risk: A call for action from the European Society of Hypertension Working Group of Obesity, Diabetes and the High-risk Patient and European Association for the Study of Obesity: Part B: Obesity-induced cardiovascular disease, early prevention strategies and future research directions

Author

Kotsis, V. Tsioufis, K. Antza, C. Seravalle, G. Coca, A. Sierra, C. Lurbe, E. Stabouli, S. Jelakovic, B. Redon, J. Redon, P. Nilsson, P.M. Jordan, J. Micic, D. Finer, N. Leitner, D.R. Toplak, H. Tokgozoglu, L. Athyros, V. Elisaf, M. Filippatos, T.D. Grassi, G.

Abstract

Obesity predisposes for atrial fibrillation, heart failure, sudden cardiac death, renal disease and ischemic stroke, which are the main causes of cardiovascular hospitalization and mortality. As obesity and the cardiovascular effects on the vessels and the heart start early in life, even from childhood, it is important for health policies to prevent obesity very early before the disease manifestation emerge. Key roles in the prevention are strategies to increase physical exercise, reduce body weight and to prevent or treat hypertension, lipids disorders and diabetes earlier and efficiently to prevent cardiovascular complications. Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.

Published
2018

27. NT-proBNP and metabolic risk factors in two ethnic groups: the SABPA cohort study

Author

Jujic, A. Amra, Malan, L., Melander, O., Nilsson, P.M., Fedorowski, A., and 10060871 - Malan, Leoné

Abstract

Background: Natriuretic peptides are vasoactive peptides with several metabolic actions. Purpose: We aimed to explore associations of N-terminal pro-brain natriuretic peptide (NT-proBNP) with metabolic traits in a mixed ethnic African-Caucasian cohort. Methods: Within the Sympathetic activity and Ambulatory Blood Pressure in African Prospective cohort study (SABPA), baseline examination was performed between 2008 and 2009, and re-examination after a 3-year follow-up in 397 South African teachers (African n = 194; Caucasian n = 203). Results: In cross-sectional linear regression analyses, each 1SD increment of age and sex adjusted NT-proBNP was inversely associated with body weight (ß = -2.23; p = 0.042), body mass index (ß = -1.01; p = 0.007), waist circumference (ß = -1.82; p = 0.033), HbA1c (ß = -0.14 %; p = 0.009), insulin (ß = -1.66; p = 0.002), homeostatic model assessment of insulin resistance (ß = -0.47; p = 0.006) and triglyceride levels (ß = -0.04; p = 0.002). Intra-ethnic differences were observed, where lower NT-proBNP levels affected glucometabolic status stronger among Africans. Each 1SD increment of age, sex, waist circumference and follow-up time adjusted NT-proBNP was associated with reduced odds of incident diabetes, and subjects within the highest quartile of NT-proBNP were at lowest risk compared with the lowest quartile (OR 0.24; CI95% 0.06-0.96; p = 0.041). Conclusions: In a cohort consisting of two ethnic groups, NT-proBNP in the high normal range is associated with lower prevalence of metabolic risk factors such as high BMI, increased waist circumference, impaired glucose tolerance, high insulin levels and hypertriglyceridemia, with strongest associations for Africans. Inspite of similar NT-proBNP concentrations, BNP may affect the propensity for metabolic disturbances differently in Africans and Caucasians

Published
2018

29. NT-proBNP and metabolic risk factors in two ethnic groups: the SABPA cohort study

Author

10060871 - Malan, Leoné, Jujic, A. Amra, Malan, L., Melander, O., Nilsson, P.M., Fedorowski, A., 10060871 - Malan, Leoné, Jujic, A. Amra, Malan, L., Melander, O., Nilsson, P.M., and Fedorowski, A.

Abstract

Background: Natriuretic peptides are vasoactive peptides with several metabolic actions. Purpose: We aimed to explore associations of N-terminal pro-brain natriuretic peptide (NT-proBNP) with metabolic traits in a mixed ethnic African-Caucasian cohort. Methods: Within the Sympathetic activity and Ambulatory Blood Pressure in African Prospective cohort study (SABPA), baseline examination was performed between 2008 and 2009, and re-examination after a 3-year follow-up in 397 South African teachers (African n = 194; Caucasian n = 203). Results: In cross-sectional linear regression analyses, each 1SD increment of age and sex adjusted NT-proBNP was inversely associated with body weight (ß = -2.23; p = 0.042), body mass index (ß = -1.01; p = 0.007), waist circumference (ß = -1.82; p = 0.033), HbA1c (ß = -0.14 %; p = 0.009), insulin (ß = -1.66; p = 0.002), homeostatic model assessment of insulin resistance (ß = -0.47; p = 0.006) and triglyceride levels (ß = -0.04; p = 0.002). Intra-ethnic differences were observed, where lower NT-proBNP levels affected glucometabolic status stronger among Africans. Each 1SD increment of age, sex, waist circumference and follow-up time adjusted NT-proBNP was associated with reduced odds of incident diabetes, and subjects within the highest quartile of NT-proBNP were at lowest risk compared with the lowest quartile (OR 0.24; CI95% 0.06-0.96; p = 0.041). Conclusions: In a cohort consisting of two ethnic groups, NT-proBNP in the high normal range is associated with lower prevalence of metabolic risk factors such as high BMI, increased waist circumference, impaired glucose tolerance, high insulin levels and hypertriglyceridemia, with strongest associations for Africans. Inspite of similar NT-proBNP concentrations, BNP may affect the propensity for metabolic disturbances differently in Africans and Caucasians

Published
2018

34. Supplementary Material for: Increased Levels of Copeptin, a Surrogate Marker of Arginine Vasopressin, Are Associated with an Increased Risk of Chronic Kidney Disease in a General Population

Author

Tasevska I., Enhörning S., Christensson A., Persson M., Nilsson P.M., Melander O., Tasevska I., Enhörning S., Christensson A., Persson M., Nilsson P.M., and Melander O.

Abstract

Background: Our aim was to test if plasma copeptin, a stable surrogate marker of arginine vasopressin, predicts decline of glomerular filtration rate (GFR) and risk of chronic kidney disease (CKD). Methods: We measured copeptin and renal function at the Malmö Diet and Cancer Cardiovascular Cohort baseline exam and reassessed renal function after a follow-up time of 16.6 ± 1.5 years (n = 3,186). Furthermore, we defined CKD based on an estimated GFR (eGFR) calculated by the Modification of Diet in Renal Disease (MDRD) <60 (CKD_60MDRD), <45 (CKD_45MDRD) and <30 (CKD_30MDRD) ml/min/1.73 m2. Results: After multivariate adjustment (gender, age, baseline eGFR, smoking status, systolic blood pressure, antihypertensive treatment and follow-up time), copeptin (beta-coefficient per 1 SD increment of copeptin) was independently associated with significantly greater annual decline of eGFR (ml/min/1.73 m2) according to the MDRD formula (OR 0.057, 95% CI 0.022-0.093; p = 0.001) as well as according to the CKD Epidemiology Collaboration (CKD-EPI) formula (OR 0.050, 95% CI 0.022-0.077; p < 0.001). Each SD increment of copeptin independently predicted incident CKD_60MDRD (OR 1.19, 95% CI 1.04-1.36; p = 0.010), CKD_45MDRD (OR 1.33, 95% CI 1.04-1.71; p = 0.026) and CKD_30MDRD (OR 3.69, 95% CI 1.41-9.66; p = 0.008). The relationship between copeptin and CKD defined by CKD-EPI gave similar results. Conclusion: Our data suggest that increased levels of copeptin independently predict decline in eGFR and greater risk of new-onset CKD.

Published
2016
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41. [OP.3D.03] ASSOCIATION BETWEEN NEUTROPHIL TO LYMPHOCYTE RATIO AND ARTERIAL STIFFNESS IN A POPULATION SAMPLE

Author

Huguet, E., primary, Maccallini, G., additional, Pardini, P., additional, Obregon, S., additional, Hidalgo, M., additional, Haehnel, M., additional, Carrizo, P., additional, Koretzky, M., additional, Di Leva, A., additional, Inserra, F., additional, Botto, F., additional, Scuteri, A., additional, Nilsson, P.M., additional, and Kotliar, C., additional

Published
2016
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44. Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

Author

Gaulton, K. (Kyle), Ferreira, T. (Teresa), Lee, Y. (Yeji), Raimondo, A. (Anne), Mägi, R. (Reedik), Reschen, M.E. (Michael E.), Mahajan, A. (Anubha), Locke, A. (Adam), Rayner, N.W. (Nigel William), Robertson, N.R. (Neil), Scott, R.A. (Robert), Prokopenko, I. (Inga), Scott, L.J. (Laura), Green, T. (Todd), Sparsø, T. (Thomas), Thuillier, D. (Dorothee), Yengo, L. (Loic), Grallert, H. (Harald), Wahl, S. (Simone), Frånberg, M. (Mattias), Strawbridge, R.J. (Rona), Kestler, H. (Hans), Chheda, H. (Himanshu), Eisele, L. (Lewin), Gustafsson, S. (Stefan), Steinthorsdottir, V. (Valgerdur), Thorleifsson, G. (Gudmar), Qi, L. (Lu), Karssen, L.C. (Lennart), Leeuwen, E.M. (Elisa) van, Willems, S.M. (Sara), Li, M. (Man), Chen, H. (Han), Fuchsberger, C. (Christian), Kwan, P. (Phoenix), Ma, C. (Clement), Linderman, M. (Michael), Lu, Y. (Yingchang), Thomsen, S.K. (Soren K.), Rundle, J.K. (Jana K.), Beer, N.L. (Nicola L.), Bunt, M. (Martijn) van de, Chalisey, A. (Anil), Kang, H.M. (Hyun Min), Voight, B.F. (Benjamin), Abecasis, G.R. (Gonçalo), Almgren, P. (Peter), Baldassarre, D. (Damiano), Balkau, B. (Beverley), Benediktsson, R. (Rafn), Blüher, M. (Matthias), Boeing, H. (Heiner), Bonnycastle, L.L. (Lori), Bottinger, E.P. (Erwin P.), Burtt, N.P. (Noël), Carey, J. (Jason), Charpentier, G. (Guillaume), Chines, P.S. (Peter), Cornelis, M. (Marilyn), Couper, D.J. (David J.), Crenshaw, A. (Andrew), Dam, R.M. (Rob) van, Doney, A.S.F. (Alex), Dorkhan, M. (Mozhgan), Edkins, T. (Ted), Eriksson, J.G. (Johan G.), Esko, T. (Tõnu), Eury, E. (Elodie), Fadista, J. (João), Flannick, J. (Jason), Fontanillas, P. (Pierre), Fox, C.S. (Caroline), Franks, P.W. (Paul W.), Gertow, K. (Karl), Gieger, C. (Christian), Gigante, B. (Bruna), Gottesman, R.F. (Rebecca), Grant, G.B. (George), Grarup, N. (Niels), Groves, C.J. (Christopher J.), Hassinen, M. (Maija), Have, C.T. (Christian T.), Herder, C. (Christian), Holmen, O.L. (Oddgeir), Hreidarsson, A.B. (Astradur), Humphries, S.E. (Steve E.), Hunter, D.J. (David J.), Jackson, A.U. (Anne), Jonsson, A. (Anna), Jørgensen, M.E. (Marit E.), Jørgensen, T. (Torben), Kao, W.H.L. (Wen), Kerrison, N.D. (Nicola D.), Kinnunen, L. (Leena), Klopp, N. (Norman), Kong, A. (Augustine), Kovacs, P. (Peter), Kraft, P. (Peter), Kravic, J. (Jasmina), Langford, C. (Cordelia), Leander, K. (Karin), Liang, L. (Liming), Lichtner, P. (Peter), Lindgren, C.M. (Cecilia M.), Lindholm, B. (Bengt), Linneberg, A. (Allan), Liu, C.-T. (Ching-Ti), Lobbens, S. (Stéphane), Luan, J. (Jian'fan), Lyssenko, V. (Valeriya), Männistö, S. (Satu), McLeod, O. (Olga), Meyer, J. (Jobst), Mihailov, E. (Evelin), Mirza, G. (Ghazala), Mühleisen, T.W. (Thomas), Müller-Nurasyid, M. (Martina), Navarro, C. (Carmen), Nöthen, M.M. (Markus), Oskolkov, N.N. (Nikolay N.), Owen, K.R. (Katharine), Palli, D. (Domenico), Pechlivanis, S. (Sonali), Peltonen, L. (Leena Johanna), Perry, J.R.B. (John), Platou, C.P. (Carl), Roden, M. (Michael), Ruderfer, D. (Douglas), Rybin, D. (Denis), Van Der Schouw, Y.T. (Yvonne T.), Sennblad, B. (Bengt), Sigurosson, G. (Gunnar), Stancáková, A. (Alena), Steinbach, D., Storm, P. (Petter), Strauch, K. (Konstantin), Stringham, H.M. (Heather), Sun, Q., Thorand, B. (Barbara), Tikkanen, E. (Emmi), Tönjes, A. (Anke), Trakalo, J. (Joseph), Tremoli, E. (Elena), Tuomi, T. (Tiinamaija), Wennauer, R. (Roman), Wiltshire, S. (Steven), Wood, A.R. (Andrew), Zeggini, E. (Eleftheria), Dunham, I. (Ian), Birney, E. (Ewan), Pasquali, L. (Lorenzo), Ferrer, J. (Jorge), Loos, R.J.F. (Ruth), Dupuis, J. (Josée), Florez, J.C. (Jose), Boerwinkle, E.A. (Eric), Pankow, J.S. (James), Duijn, C.M. (Cornelia) van, Sijbrands, E.J.G. (Eric), Meigs, J.B. (James B.), Hu, F.B. (Frank), Thorsteinsdottir, U. (Unnur), Zwart, J-A. (John-Anker), Lakka, T.A. (Timo), Rauramaa, R. (Rainer), Stumvoll, M. (Michael), Pedersen, N.L. (Nancy L.), Lind, L. (Lars), Keinanen-Kiukaanniemi, S. (Sirkka), Korpi-Hyövälti, E. (Eeva), Saaristo, T. (Timo), Saltevo, J. (Juha), Kuusisto, J. (Johanna), Laakso, M. (Markku), Metspalu, A. (Andres), Erbel, R. (Raimund), Jöckel, K.-H. (Karl-Heinz), Moebus, S. (Susanne), Ripatti, S. (Samuli), Salomaa, V. (Veikko), Ingelsson, E. (Erik), Boehm, B.O. (Bernhard), Bergman, R.N. (Richard N.), Collins, F.S. (Francis S.), Mohlke, K.L. (Karen L.), Koistinen, H. (Heikki), Tuomilehto, J. (Jaakko), Hveem, K. (Kristian), Njølstad, I. (Inger), Deloukas, P. (Panagiotis), Donnelly, P.J. (Peter J.), Frayling, T.M. (Timothy), Hattersley, A.T. (Andrew), Faire, U. (Ulf) de, Hamsten, A. (Anders), Illig, T. (Thomas), Peters, A. (Annette), Cauchi, S. (Stephane), Sladek, R. (Rob), Froguel, P. (Philippe), Hansen, T. (Torben), Pedersen, O. (Oluf), Morris, A.D. (Andrew), Palmer, C.N.A. (Collin N. A.), Kathiresan, S. (Sekar), Melander, O. (Olle), Nilsson, P.M. (Peter M.), Groop, L. (Leif), Barroso, I.E. (Inês), Langenberg, C. (Claudia), Wareham, N.J. (Nicholas J.), O'Callaghan, C.A. (Christopher A.), Gloyn, A.L. (Anna), Altshuler, D. (David), Boehnke, M. (Michael), Teslovich, T.M. (Tanya M.), McCarthy, M.I. (Mark), Morris, A.P. (Andrew), Gaulton, K. (Kyle), Ferreira, T. (Teresa), Lee, Y. (Yeji), Raimondo, A. (Anne), Mägi, R. (Reedik), Reschen, M.E. (Michael E.), Mahajan, A. (Anubha), Locke, A. (Adam), Rayner, N.W. (Nigel William), Robertson, N.R. (Neil), Scott, R.A. (Robert), Prokopenko, I. (Inga), Scott, L.J. (Laura), Green, T. (Todd), Sparsø, T. (Thomas), Thuillier, D. (Dorothee), Yengo, L. (Loic), Grallert, H. (Harald), Wahl, S. (Simone), Frånberg, M. (Mattias), Strawbridge, R.J. (Rona), Kestler, H. (Hans), Chheda, H. (Himanshu), Eisele, L. (Lewin), Gustafsson, S. (Stefan), Steinthorsdottir, V. (Valgerdur), Thorleifsson, G. (Gudmar), Qi, L. (Lu), Karssen, L.C. (Lennart), Leeuwen, E.M. (Elisa) van, Willems, S.M. (Sara), Li, M. (Man), Chen, H. (Han), Fuchsberger, C. (Christian), Kwan, P. (Phoenix), Ma, C. (Clement), Linderman, M. (Michael), Lu, Y. (Yingchang), Thomsen, S.K. (Soren K.), Rundle, J.K. (Jana K.), Beer, N.L. (Nicola L.), Bunt, M. (Martijn) van de, Chalisey, A. (Anil), Kang, H.M. (Hyun Min), Voight, B.F. (Benjamin), Abecasis, G.R. (Gonçalo), Almgren, P. (Peter), Baldassarre, D. (Damiano), Balkau, B. (Beverley), Benediktsson, R. (Rafn), Blüher, M. (Matthias), Boeing, H. (Heiner), Bonnycastle, L.L. (Lori), Bottinger, E.P. (Erwin P.), Burtt, N.P. (Noël), Carey, J. (Jason), Charpentier, G. (Guillaume), Chines, P.S. (Peter), Cornelis, M. (Marilyn), Couper, D.J. (David J.), Crenshaw, A. (Andrew), Dam, R.M. (Rob) van, Doney, A.S.F. (Alex), Dorkhan, M. (Mozhgan), Edkins, T. (Ted), Eriksson, J.G. (Johan G.), Esko, T. (Tõnu), Eury, E. (Elodie), Fadista, J. (João), Flannick, J. (Jason), Fontanillas, P. (Pierre), Fox, C.S. (Caroline), Franks, P.W. (Paul W.), Gertow, K. (Karl), Gieger, C. (Christian), Gigante, B. (Bruna), Gottesman, R.F. (Rebecca), Grant, G.B. (George), Grarup, N. (Niels), Groves, C.J. (Christopher J.), Hassinen, M. (Maija), Have, C.T. (Christian T.), Herder, C. (Christian), Holmen, O.L. (Oddgeir), Hreidarsson, A.B. (Astradur), Humphries, S.E. (Steve E.), Hunter, D.J. (David J.), Jackson, A.U. (Anne), Jonsson, A. (Anna), Jørgensen, M.E. (Marit E.), Jørgensen, T. (Torben), Kao, W.H.L. (Wen), Kerrison, N.D. (Nicola D.), Kinnunen, L. (Leena), Klopp, N. (Norman), Kong, A. (Augustine), Kovacs, P. (Peter), Kraft, P. (Peter), Kravic, J. (Jasmina), Langford, C. (Cordelia), Leander, K. (Karin), Liang, L. (Liming), Lichtner, P. (Peter), Lindgren, C.M. (Cecilia M.), Lindholm, B. (Bengt), Linneberg, A. (Allan), Liu, C.-T. (Ching-Ti), Lobbens, S. (Stéphane), Luan, J. (Jian'fan), Lyssenko, V. (Valeriya), Männistö, S. (Satu), McLeod, O. (Olga), Meyer, J. (Jobst), Mihailov, E. (Evelin), Mirza, G. (Ghazala), Mühleisen, T.W. (Thomas), Müller-Nurasyid, M. (Martina), Navarro, C. (Carmen), Nöthen, M.M. (Markus), Oskolkov, N.N. (Nikolay N.), Owen, K.R. (Katharine), Palli, D. (Domenico), Pechlivanis, S. (Sonali), Peltonen, L. (Leena Johanna), Perry, J.R.B. (John), Platou, C.P. (Carl), Roden, M. (Michael), Ruderfer, D. (Douglas), Rybin, D. (Denis), Van Der Schouw, Y.T. (Yvonne T.), Sennblad, B. (Bengt), Sigurosson, G. (Gunnar), Stancáková, A. (Alena), Steinbach, D., Storm, P. (Petter), Strauch, K. (Konstantin), Stringham, H.M. (Heather), Sun, Q., Thorand, B. (Barbara), Tikkanen, E. (Emmi), Tönjes, A. (Anke), Trakalo, J. (Joseph), Tremoli, E. (Elena), Tuomi, T. (Tiinamaija), Wennauer, R. (Roman), Wiltshire, S. (Steven), Wood, A.R. (Andrew), Zeggini, E. (Eleftheria), Dunham, I. (Ian), Birney, E. (Ewan), Pasquali, L. (Lorenzo), Ferrer, J. (Jorge), Loos, R.J.F. (Ruth), Dupuis, J. (Josée), Florez, J.C. (Jose), Boerwinkle, E.A. (Eric), Pankow, J.S. (James), Duijn, C.M. (Cornelia) van, Sijbrands, E.J.G. (Eric), Meigs, J.B. (James B.), Hu, F.B. (Frank), Thorsteinsdottir, U. (Unnur), Zwart, J-A. (John-Anker), Lakka, T.A. (Timo), Rauramaa, R. (Rainer), Stumvoll, M. (Michael), Pedersen, N.L. (Nancy L.), Lind, L. (Lars), Keinanen-Kiukaanniemi, S. (Sirkka), Korpi-Hyövälti, E. (Eeva), Saaristo, T. (Timo), Saltevo, J. (Juha), Kuusisto, J. (Johanna), Laakso, M. (Markku), Metspalu, A. (Andres), Erbel, R. (Raimund), Jöckel, K.-H. (Karl-Heinz), Moebus, S. (Susanne), Ripatti, S. (Samuli), Salomaa, V. (Veikko), Ingelsson, E. (Erik), Boehm, B.O. (Bernhard), Bergman, R.N. (Richard N.), Collins, F.S. (Francis S.), Mohlke, K.L. (Karen L.), Koistinen, H. (Heikki), Tuomilehto, J. (Jaakko), Hveem, K. (Kristian), Njølstad, I. (Inger), Deloukas, P. (Panagiotis), Donnelly, P.J. (Peter J.), Frayling, T.M. (Timothy), Hattersley, A.T. (Andrew), Faire, U. (Ulf) de, Hamsten, A. (Anders), Illig, T. (Thomas), Peters, A. (Annette), Cauchi, S. (Stephane), Sladek, R. (Rob), Froguel, P. (Philippe), Hansen, T. (Torben), Pedersen, O. (Oluf), Morris, A.D. (Andrew), Palmer, C.N.A. (Collin N. A.), Kathiresan, S. (Sekar), Melander, O. (Olle), Nilsson, P.M. (Peter M.), Groop, L. (Leif), Barroso, I.E. (Inês), Langenberg, C. (Claudia), Wareham, N.J. (Nicholas J.), O'Callaghan, C.A. (Christopher A.), Gloyn, A.L. (Anna), Altshuler, D. (David), Boehnke, M. (Michael), Teslovich, T.M. (Tanya M.), McCarthy, M.I. (Mark), and Morris, A.P. (Andrew)

Abstract

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.

Published
2015
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45. Rare coding variants and X-linked loci associated with age at menarche

Author

Lunetta, K.L. (Kathryn), Day, F.R. (Felix), Sulem, P. (Patrick), Ruth, K.S. (Katherine S.), Tung, J.Y. (Joyce Y.), Hinds, D.A. (David A.), Esko, T. (Tõnu), Elks, C.E. (Cathy), Altmaier, E.L. (Elizabeth), He, C. (Chunyan), Huffman, J.E. (Jennifer), Mihailov, E. (Evelin), Porcu, E. (Eleonora), Robino, A. (Antonietta), Rose, L.M. (Lynda), Schick, U.M. (Ursula), Stolk, L. (Lisette), Teumer, A. (Alexander), Thompson, D. (Deborah), Traglia, M. (Michela), Wang, C.A. (Carol A.), Yerges-Armstrong, L.M. (Laura), Antoniou, A.C. (Antonis), Barbieri, C. (Caterina), Coviello, A.D. (Andrea), Cucca, F. (Francesco), Demerath, E.W. (Ellen), Dunning, A.M. (Alison), Gandin, I. (Ilaria), Grove, M.L. (Megan L.), Gudbjartsson, D.F. (Daniel), Hocking, L.J. (Lynne), Hofman, A. (Albert), Huang, J. (Jian), Jackson, R.D. (Rebecca), Karasik, D. (David), Kriebel, J. (Jennifer), Lange, E.M. (Ethan), Lange, L.A. (Leslie), Langenberg, C. (Claudia), Li, X. (Xin), Luan, J., Mägi, R. (Reedik), Morrison, A.C. (Alanna), Padmanabhan, S. (Sandosh), Pirie, A. (Ailith), Polasek, O. (Ozren), Porteous, D.J. (David J.), Reiner, A. (Alexander), Rivadeneira Ramirez, F. (Fernando), Rudan, I. (Igor), Sala, C. (Cinzia), Schlessinger, D. (David), Scott, R.A. (Robert), Stöckl, D. (Doris), Visser, J.A. (Jenny), Völker, U. (Uwe), Vozzi, D. (Diego), Wilson, J.G. (James), Zygmunt, M. (Marek), Boerwinkle, E.A. (Eric), Buring, J.E. (Julie), Crisponi, L. (Laura), Easton, D.F. (Douglas), Hayward, C. (Caroline), Hu, F.B. (Frank), Liu, S. (Simin), Metspalu, A. (Andres), Pennell, C.E. (Craig), Ridker, P.M. (Paul), Strauch, K. (Konstantin), Streeten, E.A. (Elizabeth), Toniolo, D. (Daniela), Uitterlinden, A.G. (André), Ulivi, S. (Shelia), Völzke, H. (Henry), Wareham, N.J. (Nick), Wellons, M. (Melissa), Franceschini, N. (Nora), Chasman, D.I. (Daniel), Thorsteinsdottir, U. (Unnur), Murray, A. (Anna), Zwart, J-A. (John-Anker), Murabito, J. (Joanne), Ong, K.K. (Ken), Perry, J.R.B. (John), Forouhi, N.G. (Nita G.), Kerrison, N.D. (Nicola D.), Sharp, S.J. (Stephen J.), Sims, M.A. (Matthew), Barroso, I.E. (Inês), Deloukas, P. (Panagiotis), McCarthy, M.I. (Mark), Arriola, L. (Larraitz), Balkau, B. (Beverley), Barricarte, A. (Aurelio), Boeing, H. (Heiner), Franks, P.W., Gonzalez, C. (Carlos), Grioni, S. (Sara), Kaaks, R. (Rudolf), Key, T.J. (Timothy J.), Navarro, C. (Carmen), Nilsson, P.M. (Peter M.), Overvad, K. (Kim), Palli, D. (Domenico), Panico, S. (Salvatore), Quirós, J.R., Rolandsson, O. (Olov), Sacerdote, C. (Carlotta), Sánchez, M.-J. (María-José), Slimani, N. (Nadia), Tjonneland, A. (Anne), Tumino, R. (Rosario), Van Der A, D.L. (Daphne L.), Schouw, Y.T. (Yvonne) van der, Riboli, E. (Elio), Smith, B.H. (Blair), Campbell, A. (Archie), Deary, I.J. (Ian), McIntosh, A.M. (Andrew), Lunetta, K.L. (Kathryn), Day, F.R. (Felix), Sulem, P. (Patrick), Ruth, K.S. (Katherine S.), Tung, J.Y. (Joyce Y.), Hinds, D.A. (David A.), Esko, T. (Tõnu), Elks, C.E. (Cathy), Altmaier, E.L. (Elizabeth), He, C. (Chunyan), Huffman, J.E. (Jennifer), Mihailov, E. (Evelin), Porcu, E. (Eleonora), Robino, A. (Antonietta), Rose, L.M. (Lynda), Schick, U.M. (Ursula), Stolk, L. (Lisette), Teumer, A. (Alexander), Thompson, D. (Deborah), Traglia, M. (Michela), Wang, C.A. (Carol A.), Yerges-Armstrong, L.M. (Laura), Antoniou, A.C. (Antonis), Barbieri, C. (Caterina), Coviello, A.D. (Andrea), Cucca, F. (Francesco), Demerath, E.W. (Ellen), Dunning, A.M. (Alison), Gandin, I. (Ilaria), Grove, M.L. (Megan L.), Gudbjartsson, D.F. (Daniel), Hocking, L.J. (Lynne), Hofman, A. (Albert), Huang, J. (Jian), Jackson, R.D. (Rebecca), Karasik, D. (David), Kriebel, J. (Jennifer), Lange, E.M. (Ethan), Lange, L.A. (Leslie), Langenberg, C. (Claudia), Li, X. (Xin), Luan, J., Mägi, R. (Reedik), Morrison, A.C. (Alanna), Padmanabhan, S. (Sandosh), Pirie, A. (Ailith), Polasek, O. (Ozren), Porteous, D.J. (David J.), Reiner, A. (Alexander), Rivadeneira Ramirez, F. (Fernando), Rudan, I. (Igor), Sala, C. (Cinzia), Schlessinger, D. (David), Scott, R.A. (Robert), Stöckl, D. (Doris), Visser, J.A. (Jenny), Völker, U. (Uwe), Vozzi, D. (Diego), Wilson, J.G. (James), Zygmunt, M. (Marek), Boerwinkle, E.A. (Eric), Buring, J.E. (Julie), Crisponi, L. (Laura), Easton, D.F. (Douglas), Hayward, C. (Caroline), Hu, F.B. (Frank), Liu, S. (Simin), Metspalu, A. (Andres), Pennell, C.E. (Craig), Ridker, P.M. (Paul), Strauch, K. (Konstantin), Streeten, E.A. (Elizabeth), Toniolo, D. (Daniela), Uitterlinden, A.G. (André), Ulivi, S. (Shelia), Völzke, H. (Henry), Wareham, N.J. (Nick), Wellons, M. (Melissa), Franceschini, N. (Nora), Chasman, D.I. (Daniel), Thorsteinsdottir, U. (Unnur), Murray, A. (Anna), Zwart, J-A. (John-Anker), Murabito, J. (Joanne), Ong, K.K. (Ken), Perry, J.R.B. (John), Forouhi, N.G. (Nita G.), Kerrison, N.D. (Nicola D.), Sharp, S.J. (Stephen J.), Sims, M.A. (Matthew), Barroso, I.E. (Inês), Deloukas, P. (Panagiotis), McCarthy, M.I. (Mark), Arriola, L. (Larraitz), Balkau, B. (Beverley), Barricarte, A. (Aurelio), Boeing, H. (Heiner), Franks, P.W., Gonzalez, C. (Carlos), Grioni, S. (Sara), Kaaks, R. (Rudolf), Key, T.J. (Timothy J.), Navarro, C. (Carmen), Nilsson, P.M. (Peter M.), Overvad, K. (Kim), Palli, D. (Domenico), Panico, S. (Salvatore), Quirós, J.R., Rolandsson, O. (Olov), Sacerdote, C. (Carlotta), Sánchez, M.-J. (María-José), Slimani, N. (Nadia), Tjonneland, A. (Anne), Tumino, R. (Rosario), Van Der A, D.L. (Daphne L.), Schouw, Y.T. (Yvonne) van der, Riboli, E. (Elio), Smith, B.H. (Blair), Campbell, A. (Archie), Deary, I.J. (Ian), and McIntosh, A.M. (Andrew)

Abstract

More than 100 loci have been identified for age at menarche by genome-wide association studies; however, collectively these explain only ∼ 3% of the trait variance. Here we test two overlooked sources of variation in 192,974 European ancestry women: low-frequency protein-coding variants and X-chromosome variants. Five missense/nonsense variants (in ALMS1/LAMB2/TNRC6A/TACR3/PRKAG1) are associated with age at menarche (minor allele frequencies 0.08-4.6%; effect sizes 0.08-1.25 years per allele; P<5 × 10-8). In addition, we identify common X-chromosome loci at IGSF1 (rs762080, P=9.4 × 10-13) and FAAH2 (rs5914101, P=4.9 × 10-10). Highlighted genes implicate cellular energy homeostasis, post-transcriptional gene silencing and fatty-acid amide signalling. A frequently reported mutation in TACR3 for idiopathic hypogonatrophic hypogonadism (p.W275X) is associated with 1.25-year-later menarche (P=2.8 × 10-11), illustrating the utility of population studies to estimate the penetrance of reportedly pathogenic mutations. Collectively, these novel variants explain ∼0.5% variance, indicating that these overlooked sources of variation do not substantially explain the 'missing heritability' of this complex trait.

Published
2015
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46. Natural history and physiological determinants of changes in glucose tolerance in a non-diabetic population: the RISC Study

Author

Ferrannini, E., Natali, A., Muscelli, E., Nilsson, P.M., Golay, A., Laakso, M., Beck-Nielsen, H., Mari, A., Heine, R.J., Dekker, J.M., Nijpels, G., Internal medicine, Epidemiology and Data Science, General practice, and EMGO - Lifestyle, overweight and diabetes

Subjects
Adult, Male, medicine.medical_specialty, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Population, Dysglycaemia progression, Insulin resistance, Risk Factors, Insulin-Secreting Cells, Internal medicine, Diabetes mellitus, Glucose Intolerance, Internal Medicine, medicine, Humans, education, ddc:613, education.field_of_study, business.industry, Incidence, Insulin, Diabetes, Beta cell function, Glucose tolerance, Middle Aged, Models, Theoretical, Glucose clamp technique, medicine.disease, Obesity, Europe, Phenotype, Endocrinology, Quartile, Cardiovascular Diseases, Glucose Clamp Technique, Female, Beta cell, business, Follow-Up Studies
Abstract

AIMS/HYPOTHESIS: The natural history and physiological determinants of glucose intolerance in subjects living in Europe have not been investigated. The aim of this study was to increase our understanding of this area. METHODS: We analysed the data from a population-based cohort of 1,048 non-diabetic, normotensive men and women (aged 30-60 years) in whom insulin sensitivity was measured by the glucose clamp technique (M/I index; average glucose infusion rate/steady-state insulin concentration) and beta cell function was estimated by mathematical modelling of the oral glucose tolerance test at baseline and 3 years later. RESULTS: Seventy-seven per cent of the participants had normal glucose tolerance (NGT) and 5% were glucose intolerant both at baseline and follow up; glucose tolerance worsened in 13% (progressors) and improved in 6% (regressors). The metabolic phenotype of the latter three groups was similar (higher prevalence of familial diabetes, older age, higher waist-to-hip ratio, higher fasting and 2 h plasma glucose, higher fasting and 2 h plasma insulin, lower insulin sensitivity and reduced beta cell glucose sensitivity with increased absolute insulin secretion). Adjusting for these factors in a logistic model, progression was predicted by insulin resistance (bottom M/I quartile, OR 2.52 [95% CI 1.51-4.21]) and beta cell glucose insensitivity (bottom quartile, OR 2.39 [95% CI 1.6-3.93]) independently of waist-to-hip ratio (OR 1.44 [95% CI 1.13-1.84] for one SD). At follow up, insulin sensitivity and beta cell glucose sensitivity were unchanged in the stable NGT and stable non-NGT groups, worsened in progressors and improved in regressors. CONCLUSIONS/INTERPRETATION: Glucose tolerance deteriorates over time in young, healthy Europids. Progressors, regressors and glucose-intolerant participants share a common baseline phenotype. Insulin sensitivity and beta cell glucose sensitivity predict and track changes in glucose tolerance independently of sex, age and obesity.

Published
2011

48. 4B.07

Author

Pareek, M., primary, Nielsen, M.L., additional, Leósdóttir, M., additional, Nilsson, P.M., additional, and Olsen, M.H., additional

Published
2015
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49. 5B.07

Author

Pareek, M., primary, Nielsen, M.L., additional, Olesen, T.B., additional, Leósdóttir, M., additional, Nilsson, P.M., additional, and Olsen, M.H., additional

Published
2015
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50. PP.25.04

Author

Pareek, M., primary, Nielsen, M., additional, Olesen, T., additional, Leósdóttir, M., additional, Nilsson, P.M., additional, and Olsen, M.H., additional

Published
2015
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