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1. Corrigendum: Rare coding variants and X-linked loci associated with age at menarche

Author

Lunetta, K.L., Day, F.R., Sulem, P., Ruth, K.S., Tung, J.Y., Hinds, D.A., Esko, T., Elks, C.E., Altmaier, E., He, C., Huffman, J.E., Mihailov, E., Porcu, E., Robino, A., Rose, L.M., Schick, U.M., Stolk, L., Teumer, A., Thompson, D.J., Traglia, M., Wang, C.A., Yerges-Armstrong, L.M., Antoniou, A.C., Barbieri, C., Coviello, A.D., Cucca, F., Demerath, E.W., Dunning, A.M., Gandin, I., Grove, M.L., Gudbjartsson, D.F., Hocking, L.J., Hofman, A., Huang, J., Jackson, R.D., Karasik, D., Kriebel, J., Lange, E.M., Lange, L.A., Langenberg, C., Li, X., Luan, J., Mägi, R., Morrison, A.C., Padmanabhan, S., Pirie, A., Polasek, O., Porteous, D.J., Reiner, A.P., Rivadeneira, F., Rudan, I., Sala, C.F., Schlessinger, D., Scott, R.A., Stöckl, D., Visser, J.A., Völker, U., Vozzi, D., Wilson, J.G., Zygmunt, M., EPIC-Interact Consortium (), Generation Scotland Consortium (), Boerwinkle, E., Buring, J.E., Crisponi, L., Easton, D.F., Hayward, C., Hu, F.B., Liu, S., Metspalu, A., Pennell, C.E., Ridker, P.M., Strauch, K., Streeten, E.A., Toniolo, D., Uitterlinden, A.G., Ulivi, S., Völzke, H., Wareham, N.J., Wellons, M., Franceschini, N., Chasman, D.I., Thorsteinsdottir, U., Murray, A., Stefansson, K., Murabito, J.M., Ong, K.K., and Perry, J.R.

Subjects
Adult, Adolescent, Genotype, Mutation, Missense, Immunoglobulins, Cell Cycle Proteins, Penetrance, AMP-Activated Protein Kinases, Autoantigens, White People, Young Adult, Gene Frequency, Genes, X-Linked, Humans, Aged, Menarche, Chromosomes, Human, X, Hypogonadism, Fatty Acids, Age Factors, Genetic Variation, Membrane Proteins, Proteins, RNA-Binding Proteins, Receptors, Neurokinin-3, Middle Aged, Corrigenda, Amides, Phenotype, Codon, Nonsense, Female, RNA Interference, Laminin, Energy Metabolism, Signal Transduction
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; P5 × 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

2. Impact of the adipokine adiponectin and the hepatokine fetuin-A on the development of type 2 diabetes: prospective cohort- and cross-sectional phenotyping studies

Author

Stefan, N., Sun, Q., Fritsche, A., Machann, J., Schick, F., Gerst, F., Jeppesen, C., Joost, H.G., Hu, F.B., Boeing, H., Ullrich, S., Häring, H.-U., and Schulze, M.B.

Subjects
Adult, Male, Risk, alpha-2-HS-Glycoprotein, Physiology, Epidemiology, lcsh:Medicine, Nonalcoholic Steatohepatitis, Gastroenterology and Hepatology, Biochemistry, Body Mass Index, Endocrinology, Glucose Intolerance, Medicine and Health Sciences, Diabetes Mellitus, Humans, Insulin, Prospective Studies, Obesity, lcsh:Science, Cardiovascular Disease Epidemiology, Aged, Nutrition, Diabetic Endocrinology, Endocrine Physiology, Liver Diseases, Body Weight, lcsh:R, Biology and Life Sciences, Middle Aged, Hormones, Type 2 Diabetes, Biomarker Epidemiology, Cross-Sectional Studies, Phenotype, Diabetes Mellitus, Type 2, Physiological Parameters, Metabolic Disorders, Multivariate Analysis, Female, lcsh:Q, Adiponectin, Insulin Resistance, Waist Circumference, Biomarkers, Research Article
Abstract

BACKGROUND: Among adipokines and hepatokines, adiponectin and fetuin-A were consistently found to predict the incidence of type 2 diabetes, both by regulating insulin sensitivity. OBJECTIVE: To determine to what extent circulating adiponectin and fetuin-A are independently associated with incident type 2 diabetes in humans, and the major mechanisms involved. METHODS: Relationships with incident diabetes were tested in two cohort studies: within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study (628 cases) and the Nurses' Health Study (NHS; 470 cases). Relationships with body fat compartments, insulin sensitivity and insulin secretion were studied in the Tübingen Lifestyle Intervention Program (TULIP; N = 358). RESULTS: Circulating adiponectin and fetuin-A, independently of several confounders and of each other, associated with risk of diabetes in EPIC-Potsdam (RR for 1 SD: adiponectin: 0.45 [95% CI 0.37-0.54], fetuin-A: 1.18 [1.05-1.32]) and the NHS (0.51 [0.42-0.62], 1.35 [1.16-1.58]). Obesity measures considerably attenuated the association of adiponectin, but not of fetuin-A. Subjects with low adiponectin and concomitantly high fetuin-A had the highest risk. Whereas both proteins were independently (both p

Published
2014

3. Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies

Author

Nettleton, J.A., McKeown, N.M., Kanoni, S., Lemaitre, R.N., Hivert, M.F., Ngwa, J., van Rooij, F.J., Sonestedt, E., Wojczynski, M.K., Ye, Z., Tanaka, T., Garcia, M., Anderson, J.S., Follis, J.L., Djousse, L., Mukamal, K., Papoutsakis, C., Mozaffarian, D., Zillikens, M.C., Bandinelli, S., Bennett, A.J., Borecki, I.B., Feitosa, M.F., Ferrucci, L., Forouhi, N.G., Groves, C.J., Hallmans, G., Harris, T., Hofman, A., Houston, D.K., Hu, F.B., Johansson, I., Kritchevsky, S.B., Langenberg, C., Launer, L., Liu, Y., Loos, R.J., Nalls, M., Orho-Melander, M., Renstrom, F., Rice, K., Riserus, U., Rolandsson, O., Rotter, J.I., Saylor, G., Sijbrands, E.J., Sjogren, P., Smith, A., Steingrímsdóttir, L., Uitterlinden, A.G., Wareham, N.J., Prokopenko, I., Pankow, J.S., van Duijn, C.M., Florez, J.C., Witteman, J.C., Dupuis, J., Dedoussis, G.V., Ordovas, J.M., Ingelsson, E., Cupples, L., Siscovick, D.S., Franks, P.W., Meigs, J.B., MAGIC Investigators, Dupuis, J., Claudia, L., Prokopenko, I., Saxena, R., Soranzo, N., Jackson, A.U., Wheeler, E., Glazer, N.L., Bouatia-Naji, N., Lindgren, C.M., Mägi, R., Morris, A.P., Randal, J., Rybin, D., Johnson, T., Henneman, P., Gieger, C., Thorleifsson, G., Steinthorsdottir, V., Dehghan, A., Hottenga, J.J., Franklin, C.S., Navarro, P., Song, K., Goe, A., Perry, J.R., Lajunen, T., Grallert, H., Li, M., Stringham, H.M., Kumari, M., Timpson, N.J., Shrader, P., Ingelsson, E., Zabena, C., O'Connell, J., Cavalcanti-Proença, C., Luan, J., Elliott, A., McCarroll, S.A., Payne, F., Roccasecca, R.M., Sethupathy, P., Andrew, T., Ariyurek, Y., Balkau, B., Barter, P., Bennett, A.J., Ben-Shlomo, Y., Bergmann, S., Bochud, M., Boerwinkle, E., Bonnefond, A., Bonnycastle, L.L., Böttcher, Y., Brunner, E., Bumpstead, S.J., Chen, Y.D., Chines, P., Clarke, R., Coin, L.J., Crawford, G.J., Crisponi, L., Day, I.N., Geus, Ed, Dina, C., Doney, A., Egan, J.M., Elliott, P., Erdos, M.R., Fischer-Rosinsky, A., Forouhi, N.G., Fox, C.S., Frants, R., Franzosi, M.G., Galan, P., Goodarzi, M.O., Graessler, J., Groves, C.J., Grundy, S., Gwilliam, R., Hallmans, G., Hammond, N., Han, X., Hartikainen, A.L., Hayward, C., Heath, S.C., Hercberg, S., Herder, C., Hicks, A.A., Hingorani, A.D., Hofman, A., Isomaa, B., Jula, A., Kaakinen, M., Kanoni, S., Kesaniemi, Y.A., Kivimaki, M., Knight, B., Koskinen, S., Kovacs, P., Lathrop, G.M., Lawlor, D.A., Li, Y., Lyssenko, V., Mahley, R., Mangino, M., Manning, A.K., Martínez-Larrad, M.T., McAteer, J.B., McPherson, R., Meisinger, C., Melzer, D., Meyre, D., Mitchell, B.D., Morken, M.A., Naitza, S., Narisu, N., Neville, M.J., Oostra, B.A., Orrù, M., Pakyz, R., Palmer, C.N., Paolisso, G., Pattaro, C., Pearson, D., Peden, J.F., Perola, M., Pfeiffer, A.F., Pichler, I., Polasek, O., Posthuma, D., Potter, S.C., Pouta, A., Psaty, B.M., Rathmann, W., Rayner, N.W., Rice, K., Ripatti, S., Rivadeneira, F., Rolandsson, O., Sandhu, M., Sanna, S., Sayer, A.A., Scheet, P., Scott, L.J., Seedorf, U., Sharp, S.J., Shields, B., Sijbrands, E.J., Silveira, A., Singleton, A., Smith, N.L., Sovio, U., Swift, A., Syddall, H., Syvänen, A.C., Tanaka, T., Tönjes, A., Tuomi, T., Uitterlinden, A.G., van Dijk, K.W., Varma, D., Visvikis-Siest, S., Vitart, V., Vogelzangs, N., Waeber, G., Wagner, P.J., Watkins, H., Weedon, M.N., Wild, S.H., Willemsen, G., Witteman, J.C., Yarnell, J.W., Zelenika, D., Zethelius, B., Zhai, G., Zhao, J.H., Zillikens, M.C., GIANT Consortium, X., Global BPgen Consortium, X., Loos, R.J., Meneton, P., Nathan, D.M., Williams, G.H., Hattersley, A.T., Silander, K., Salomaa, V., Smith, G.D., Bornstein, S.R., Schwarz, P., Spranger, J., Karpe, F., Shuldiner, A.R., Cooper, C., Dedoussis, G.V., Serrano-Ríos, M., Morris, A.D., Lind, L., Franks, P.W., Ebrahim, S., Marmot, M., Kuusisto, J., Laakso, M., Kao, W.H., Pankow, J.S., Pramstaller, P.P., Wichmann, H.E., Illig, T., Rudan, I., Wright, A., Stumvoll, M., Campbell, H., Wilson, J.F., Hamsten, A., Bergman, R.N., Buchanan, T.A., Collins, F.S., Mohlke, K.L., Tuomilehto, J., Valle, T.T., Altshuler, D., Rotter, J.I., Siscovick, D.S., Penninx, B.W., Boomsma, D., Deloukas, P., Spector, T.D., Frayling, T.M., Ferrucci, L., Kong, A., Thorsteinsdottir, U., Stefansson, K., van Duijn, C.M., Aulchenko, Y.S., Cao, A., Scuteri, A., Schlessinger, D., Uda, M., Ruokonen, A., Jarvelin, M.R., Waterworth, D.M., Vollenweider, P., Peltonen, L., Mooser, V., Abecasis, G.R., Wareham, N.J., Sladek, R., Froguel, P., Watanabe, R.M., Meigs, J.B., Groop, L., Boehnke, M., McCarthy, M.I., Florez, J.C., and Barroso, I.

Subjects
Adult, Blood Glucose, Male, Genotype, Reviews/Commentaries/ADA Statements, Fasting, Middle Aged, Polymorphism, Single Nucleotide, White People, Genetic Loci, Humans, Insulin, Female, Aged, Blood Glucose/genetics, Blood Glucose/metabolism, Edible Grain, European Continental Ancestry Group, Fasting/blood, Genetic Loci/genetics, Genome-Wide Association Study, Insulin/blood, Insulin/genetics, Polymorphism, Single Nucleotide/genetics, Meta-Analysis
Abstract

OBJECTIVE Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin. RESEARCH DESIGN AND METHODS Via meta-analysis of data from 14 cohorts comprising ∼48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value

Published
2010

4. Alcohol consumption, mediating biomarkers, and risk of type 2 diabetes among middle-aged women

Author

Beulens, J.W.J., Rimm, E.B., Hu, F.B., Hendriks, H.F.J., Mukamal, K.J., and TNO Kwaliteit van Leven

Subjects
Adult, Questionnaires, Alcohol Drinking, Unclassified drug, Drinking behavior, Physiology, Intercellular adhesion molecule 1, Case control study, Interleukin 6, Coronary Disease, Physiological Sciences, Major clinical study, Pathophysiology, Coronary artery disease, Article, Endothelial leukocyte adhesion molecule 1, Disease association, Diabetes mellitus, Tumor necrosis factor alpha receptor 2, Risk Factors, Vascular endothelium, Prevalence, Humans, Insulin, Alcohol consumption, Protein blood level, Obesity, Endothelial dysfunction, Exercise, Life Style, Tumor necrosis factor alpha receptor, Inflammation, C reactive protein, Smoking, Insulin resistance, Middle Aged, Biological marker, Blood, Diabetes Mellitus, Type 2, Body mass, Health, Vascular cell adhesion molecule 1, Biological Markers, Female, Non insulin dependent diabetes mellitus, Endothelium, Vascular, Adiponectin, Controlled study
Abstract

OBJECTIVE - The purpose of this study was to investigate whether adiponectin concentrations and biomarkers of inflammation, endothelial dysfunction, and insulin resistance mediate the association between alcohol consumption and diabetes. RESEARCH DESIGN AND METHODS - In a nested case-control study of 705 women with incident diabetes and 787 matched control subjects, we examined the adjusted relationship between baseline alcohol consumption and risk of diabetes before and after adjustment for markers of inflammation/endothelial dysfunction (C-reactive protein, vascular cell adhesion molecule-1, intercellular adhesion molecule-1, E-selectin, tumor necrosis factor-α receptor 2, and interleukin-6), fasting insulin, and adiponectin concentrations. RESULTS- Alcohol consumption was associated with a decreased risk of diabetes (odds ratio per 12.5 g/day increment in alcohol use 0.58; 95% CI 0.49-0.69; P < 0.001). Adjustment for BMI attenuated the association by 25%. None of the markers of inflammation or fasting insulin appeared to account for >2% of the observed relationship. Without adjustment for BMI, these biomarkers individually explained slightly more of the association, but < 10% in all cases. Adiponectin accounted for 25% in a fully adjusted model and for 29% without adjustment for BMI. CONCLUSIONS - In this population of women, alcohol consumption was inversely associated with risk of type 2 diabetes. Adiponectin appeared to be a mediator of this association, but circulating biomarkers of inflammation, endothelial dysfunction, and fasting insulin did not explain this association. These results suggest that further research is needed into the potentially mediating roles of other biomarkers affected by alcohol consumption. © 2008 by the American Diabetes Association.

Published
2008

5. Dietary α-Linolenic Acid, Marine ω-3 Fatty Acids, and Mortality in a Population With High Fish Consumption: Findings From the PREvención con DIeta MEDiterránea (PREDIMED) Study

Author

Sala-Vila, A., Guasch-Ferré, Marta, Hu, F.B., Sánchez-Tainta, A., Bulló, M., Serra-Mir, M., López-Sabater, C., Sorlí, J.V., Arós, F., Fiol, M., Muñoz, M.A., Riera, C., Francés, F., Vinyoles, E., Guarner, A., Márquez, F., Guillén, M., Rovira, M.A., Piñol, J.L., Sacanella, E., Basora, T., García, Y., Rovira, A., Santamaría, M.I., Mata, M., de Juan, C., Ruiz-Gutiérrez, Valentina, Pages, M.A., Brau, A., Urtasun-Samper, A., Ruano, C., Tresserra-Rimbau, A., de Santamaría, L., Llopis-Osorio, E., Marti, A., Chiva, G., Moñino, M., Mitjavila, M.T., Valderas, P., Arranz, S., Carrasco, P., Alonso Gómez, A., Galera, A., Alonso, A., Baena, J.M., Basterra-Gortari, F. Javier, Carratalá-Calvo, A., Gil Zarzosa, J., García, M., Pérez-Heras, A., Frontera, G., Oller, M., Benavent, J., Gea, A., Ginard, M., Amat, J., Gueto Rubio, M.V., Diaz-López, A., Clos, J., Pla, I., Amorós, M., Bonet, M.T., Baby, P., de la Torre, Rafael, Martín, M.T., Lapetra, José, Lamuela-Raventós, Rosa M., García-Valdueza, M., Sánchez, M.S., Martin, F., Macías-Gutiérrez, B., Altirriba, J., Tort, R., Isach, A., Fitó, Montserrat, Sarmiendo De La Fe, F., Romero, S., Costa, B., Elosúa, R., García, L., Cabré, J.J., Babio, N., Santana-Santana, A.J., Fernández-Ballart, J., Hernández, J.M., García García, M., Ibarrola-Jurado, Nuria, San Vicente, J., Toledo, E., Buil-Cosiales, P., Ruiz-Canela, M., Vargas López, E., Simón, C., de Diego Salas, J., Sanjulián, B., Felipe, I., Falcón-Sanabria, I., Serra-Majem, L., Trias, F., Díez-Espino, Javier, Viñas, C., Martínez, E., Extremera-Urabayen, V., Núñez-Córdoba, J.M., Proenza, A., Santos, J.M., García-Arellano, A., Marrugat, J., González, J.I., Ferrer, M., Arroyo-Azpa, C., García-Pérez, L., Villanueva-Tellería, J., Cortés-Ugalde, F., Gilabert, R., de la Cruz, E., Sagredo-Arce, T., Ros, E., Duaso, I., Jurado-Ruíz, Enrique, Sarasa, I., De La Noceda-Montoy, M.D.G., Saiz, C., Mengual, L., Vigata-López, M.D., Portolés, O., Giménez, F.J., Montero Romero, Emilio, Verdú, J.M., Martínez, P., Coltell, O., Ortiz, A.P., Soler, Y., Cofán, M., Guillem-Saiz, P., Osma, R., Yuste, M.C., Quiles, L., Ruiz-Baixauli, J., Estruch, R., Pascual, V., Baca Osorio, A., Fiol, F., Bertolín-Muñoz, A., Salaverría, I., del Hierro, T., Corella, D., Razquin, C., Portillo, M.P., Algorta, J., Sánchez Luque, J.J., Ramos, A., Francisco, S., Jover, A., Parra, L., García, J., Covas, María Isabel, Medina-Remón, Alexander, Iglesias, C., Tello, S., Sáez, G., Zazpe, I., Salas-Salvadó, J., Prieto, R., Liroz, M., Vila, J., Álvarez-Pérez, J., Molina, C., Schröder, H., Díaz Benítez, E., Bautista-Castaño, Inmaculada, Martínez-González, M.A., Doménech, M., Godoy, D., Manzano, E., Maldonado-Díaz, I., Flores, G., Quinzavos, L., Churio-Beraza, B., Sánchez-Villegas, A., Barragán, R., Sorli, M., Castro, I., Gómez-Gracia, Enrique, Roura, P., García Roselló, J., Henríquez, P., Tur, J., Ortega-Calvo, M., Fernández-Crehuet, Joaquín, Benítez Pont, R., Bianchi Alba, M., Wärnberg, J., Loma-Osorio, A., Alegret, C., Gómez-Huelgas, R., Asensio, E.M., Alfredo Martínez, J., Bargalló, N., Martínez-González, J., Román, P., Bes-Rastrollo, M., Velasco García, V., García, F.José, Iglesias, P., González, R., Goñi, E., Muñoz-Aguayo, Daniel, Corchado, Y., Millán, S., Sanz, E., Mayoral, E., Leal, M., Martínez-Lapiscina, E.H., Lama, C., Padres, E., Ortega-Azorín, C., Pintó, Xavier, Altés, A., Figueras, R., Solanich, X., Pujol, R., Castellote-Bargalló, A. I., Simón-García, C., Arceiz Campo, M.T., Corbella, E., Valls-Pedret, C., Serrano-Martínez, M., Casas, R., Martín-Rillo, M.J., Cabezas, C., Universitat de Barcelona, Instituto de Salud Carlos III, Centro Nacional de Investigaciones Cardiovasculares (España), and Ministerio de Ciencia e Innovación (España)

Subjects
Male, Gerontology, Time Factors, Epidemiology, modelos de riesgos proporcionales, humanos, 030204 cardiovascular system & hematology, chemistry.chemical_compound, 0302 clinical medicine, Risk Factors, estudios prospectivos, evaluación de riesgos, Medicine, Nuts, Sudden cardian death, 030212 general & internal medicine, Food science, Longitudinal Studies, Prospective Studies, mediana edad, Original Research, Diet and Nutrition, Aged, 80 and over, chemistry.chemical_classification, education.field_of_study, anciano, alpha-Linolenic acid, dieta, Factors de risc en les malalties, Hàbits alimentaris, Fatty Acids, ω-3 fatty acids, Fatty acids in human nutrition, alpha-Linolenic Acid, distribución de la ji al cuadrado, Middle Aged, Cardiovascular system, nutrition, Cardiovascular Diseases, Female, Dieta, Cardiology and Cardiovascular Medicine, Nutritive Value, conducta de reducción del riesgo, Risk factors in diseases, Food habits, Population, enfermedades cardiovasculares, 030209 endocrinology & metabolism, Juglans, Risk Assessment, sudden cardiac death, 03 medical and health sciences, alimentos del mar, factores de tiempo, Mediterranean cooking, Àcids grassos en la nutrició, Fatty Acids, Omega-3, Cuina mediterrània, Peix com a aliment, Humans, factores de riesgo, análisis multifactorial, education, Olive Oil, Dieta -- Mediterrània, Regió de la, Dieta mediterranea, ácidos grasos, α-linolenic acid, Aged, Proportional Hazards Models, Sistema cardiovascular, Chi-Square Distribution, business.industry, Correction, Fatty acid, Hàbits alimentaris -- Mediterrània, Regió de la, Protective Factors, Fish consumption, Predimed, Diet, nueces, chemistry, Seafood, Spain, Multivariate Analysis, valor nutritivo, estudios longitudinales, fatty acid, business, Risk Reduction Behavior, ácido alfa-linolénico
Abstract

12 Páginas.-- 6 Tablas.-- 1 Figura, Background-Epidemiological evidence suggests a cardioprotective role of α-linolenic acid (ALA), a plant-derived ω-3 fatty acid. It is unclear whether ALA is beneficial in a background of high marine ω-3 fatty acids (long-chain n-3 polyunsaturated fatty acids) intake. In persons at high cardiovascular risk from Spain, a country in which fish consumption is customarily high, we investigated whether meeting the International Society for the Study of Fatty Acids and Lipids recommendation for dietary ALA (0.7% of total energy) at baseline was related to all-cause and cardiovascular disease mortality. We also examined the effect of meeting the society's recommendation for long-chain n-3 polyunsaturated fatty acids (≥500 mg/day). Methods and Results-We longitudinally evaluated 7202 participants in the PREvención con DIeta MEDiterránea (PREDIMED) trial. Multivariable-adjusted Cox regressionmodels were fitted to estimate hazard ratios. ALA intake correlated towalnut consumption (r=0.94). During a 5.9-y follow-up, 431 deaths occurred (104 cardiovascular disease, 55 coronary heart disease, 32 sudden cardiac death, 25 stroke). The hazard ratios formeeting ALArecommendation (n=1615, 22.4%) were 0.72 (95% CI 0.56-0.92) for all-causemortality and 0.95 (95% CI 0.58-1.57) for fatal cardiovascular disease. The hazard ratios formeeting the recommendation for long-chain n-3 polyunsaturated fatty acids (n=5452, 75.7%) were 0.84 (95% CI 0.67-1.05) for all-causemortality, 0.61 (95% CI 0.39-0.96) for fatal cardiovascular disease, 0.54 (95% CI 0.29-0.99) for fatal coronary heart disease, and 0.49 (95% CI 0.22-1.01) for sudden cardiac death. The highest reduction in all-cause mortality occurred in participants meeting both recommendations (hazard ratio 0.63 [95% CI 0.45-0.87]). Conclusions-In participants without prior cardiovascular disease and high fish consumption, dietary ALA, supplied mainly by walnuts and olive oil, relates inversely to all-cause mortality, whereas protection from cardiac mortality is limited to fish-derived long-chain n-3 polyunsaturated fatty acids., This study was funded in part by Instituto de Salud Carlos III (ISCIII) (Spanish Ministry of Economy) through grants RTIC G03/140, RTIC RD 06/0045, Centro Nacional de Investigaciones Cardiovasculares CNIC 06/2007, ISCIII FIS PS09/01292, the Spanish Ministry of Science and Innovation (MICINN) AGL2010‐22319‐C03‐02 and AGL2009‐13906‐C02‐02, and an unrestricted grant from the California Walnut Commission. Sala‐Vila holds a Miguel Servet I fellowship from the Ministry of Economy and Competitiveness through the ISCIII.

6. Combined associations of body weight and lifestyle factors with all cause and cause specific mortality in men and women: prospective cohort study

Author

Yanping Li, Frank B. Hu, JoAnn E. Manson, Luigi Fontana, Walter C. Willett, Nicola Veronese, Veronese, N., Li, Y., Manson, J.E., Willett, W.C., Fontana, L., and Hu, F.B.

Subjects
Gerontology, Adult, Male, Statistics as Topic, Disease, 030204 cardiovascular system & hematology, Lower risk, Body Mass Index, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Sex Factors, Bias, Environmental health, Neoplasms, Cause of Death, Diabetes Mellitus, Medicine, Health Status Indicators, Humans, 030212 general & internal medicine, Longitudinal Studies, Prospective Studies, Prospective cohort study, f body weight, Life Style, Cause of death, Aged, 2. Zero hunger, business.industry, Research, Hazard ratio, Body Weight, Bias (Epidemiology), Cardiovascular Diseases, Diabetes Mellitus, Type 2, Female, Health Surveys, Middle Aged, United States, lifestyle factors, General Medicine, Confidence interval, 3. Good health, business, Body mass index, Type 2, Cohort study
Abstract

Objective To evaluate the combined associations of diet, physical activity, moderate alcohol consumption, and smoking with body weight on risk of all cause and cause specific mortality. Design Longitudinal study with up to 32 years of follow-up. Setting Nurses’ Health Study (1980-2012) and Health Professionals Follow-up Study (1986-2012). Participants 74 582 women from the Nurses’ Health Study and 39 284 men from the Health Professionals Follow-up Study who were free from cardiovascular disease and cancer at baseline. Main outcome measures Exposures included body mass index (BMI), score on the alternate healthy eating index, level of physical activity, smoking habits, and alcohol drinking while outcome was mortality (all cause, cardiovascular, cancer). Cox proportional hazard models were used to calculate the adjusted hazard ratios of all cause, cancer, and cardiovascular mortality with their 95% confidence intervals across categories of BMI, with 22.5-24.9 as the reference. Results During up to 32 years of follow-up, there were 30 013 deaths (including 10 808 from cancer and 7189 from cardiovascular disease). In each of the four categories of BMI studied (18.5-22.4, 22.5-24.9, 25-29.9, ≥30), people with one or more healthy lifestyle factors had a significantly lower risk of total, cardiovascular, and cancer mortality than individuals with no low risk lifestyle factors. A combination of at least three low risk lifestyle factors and BMI between 18.5-22.4 was associated with the lowest risk of all cause (hazard ratio 0.39, 95% confidence interval 0.35 to 0.43), cancer (0.40, 0.34 to 0.47), and cardiovascular (0.37, 0.29 to 0.46) mortality, compared with those with BMI between 22.5-24.9 and none of the four low risk lifestyle factors. Conclusion Although people with a higher BMI can have lower risk of premature mortality if they also have at least one low risk lifestyle factor, the lowest risk of premature mortality is in people in the 18.5-22.4 BMI range with high score on the alternate healthy eating index, high level of physical activity, moderate alcohol drinking, and who do not smoke. It is important to consider diet and lifestyle factors in the evaluation of the association between BMI and mortality.

Published
2016

7. Causal relationship between obesity and vitamin D status: bi-directional Mendelian randomization analysis of multiple cohorts

Author

Benjamin Voight, Guillaume Pare, Ruth Loos, Michael Preuss, Åsa Johansson, Eco De Geus, Michael Weedon, Marjo-Riitta Jarvelin, Joyce Van Meurs, Torben Jørgensen, Kirsi Pietiläinen, Nicole Glazer, Mattias Lorentzon, Braxton Mitchell, Nicole Soranzo, Patricia Munroe, Ozren Polasek, Elisabeth Thiering, Marika Kaakinen, Carla Vogel, Jennie Hui, Elina Hypponen, ROBERTO ELOSUA, Amanda Bennett, Michael Stumvoll, Andrew Hattersley, Peter P Pramstaller, Lambertus Kiemeney, Sophie Visvikis-Siest, Vilmundur Gudnason, John Whittaker, Aroon Hingorani, Thor Aspelund, Dale Nyholt, Mary Feitosa, Vimal Karani, Mika Kähönen, Lachlan Coin, Malcolm Dunlop, Josee Dupuis, Terho Lehtimäki, Peter Visscher, Katja Aben, Daniel Witte, Cyrus Cooper, Stefan Pilz, Willem Ouwehand, Eleanor Wheeler, Peter Kovacs, Debbie A Lawlor, Kevin Jacobs, Evropi Theodoratou, Hana Lango Allen, Rosanda Mulic, Rui Li, Stephen Kritchevsky, Philippe Froguel, Soumya Raychaudhuri, Cornelia Van Duijn, Andrew Wood, Chiara Lanzani, Tonu Esko, Sadaf Farooqi, Reedik Mägi, Gerard Waeber, Claes Ohlsson, André Scherag, Marcus Kleber, Thomas Meitinger, Lina Zgaga, Denise Houston, Karl Michaëlsson, Robert Weyant, Thomas Wang, Paul Elliott, Robert Luben, Albert Vernon Smith, MANUELA UDA, Gonneke Willemsen, Mark McCarthy, Cecilia Lindgren, Olle Melander, Igor Rudan, Maris Teder-Laving, Liesbeth Vandenput, Vimaleswaran, K, Berry, Dj, Lu, C, Tikkanen, E, Pilz, S, Hiraki, Lt, Cooper, Jd, Dastani, Z, Li, R, Houston, Dk, Wood, Ar, Michaëlsson, K, Vandenput, L, Zgaga, L, YERGES ARMSTRONG, Lm, Mccarthy, Mi, Dupuis, J, Kaakinen, M, Kleber, Me, Jameson, K, Arden, N, Raitakari, O, Viikari, J, Lohman, Kk, Ferrucci, L, Melhus, H, Ingelsson, E, Byberg, L, Lind, L, Lorentzon, M, Salomaa, V, Campbell, H, Dunlop, M, Mitchell, Bd, Herzig, Kh, Pouta, A, Hartikainen, Al, Manunta, Paolo, Streeten, Ea, Theodoratou, E, Jula, A, Wareham, Nj, Ohlsson, C, Frayling, Tm, Kritchevsky, Sb, Spector, Td, Richards, Jb, Lehtimäki, T, Ouwehand, Wh, Kraft, P, Cooper, C, März, W, Power, C, Loos, Rj, Wang, Tj, Järvelin, Mr, Whittaker, Jc, Hingorani, Ad, Hyppönen, E., Council, Medical Research, Biological Psychology, EMGO+ - Lifestyle, Overweight and Diabetes, Institute for Molecular Medicine Finland, Haartman Institute (-2014), Transplantation Laboratory, Vimaleswaran, Karani S, Berry, Diane J, Lu, Chen, Tikkanen, Emmi, Hyppönen, Elina, Genetic Investigation of Anthropometric Traits (GIANT) Consortium, Hinney, Anke (Beitragende*r), Scherag, Susann (Beitragende*r), Hebebrand, Johannes (Beitragende*r), Epidemiology and Data Science, Psychiatry, EMGO - Lifestyle, overweight and diabetes, Genetic Investigation of Anthropometric Traits-GIANT Consortium, Speliotes, E.K., Willer, C.J., Berndt, S.I., Monda, K.L., Thorleifsson, G., Jackson, A.U., Allen, H.L., Lindgren, C.M., Jian'an, L., Mägi, R., Randall, J.C., Vedantam, S., Winkler, T.W., Qi, L., Workalemahu, T., Heid, I.M., Steinthorsdottir, V., Stringham, H.M., Weedon, M.N., Wheeler, E., Wood, A.R., Ferreira, T., Weyant, R.J., Segrè, A.V., Estrada, K., Liang, L., Nemesh, J., Park, J.H., Gustafsson, S., Kilpeläinen, T.O., Yang, J., Bouatia-Naji, N., Tõnu, E., Feitosa, M.F., Kutalik, Z., Mangino, M., Raychaudhuri, S., Scherag, A., Smith, A.V., Welch, R., Zhao, J.H., Aben, K.K., Absher, D.M., Amin, N., Dixon, A.L., Fisher, E., Glazer, N.L., Goddard, M.E., Heard-Costa, N.L., Hoesel, V., Hottenga, J.J., Johansson, Å., Johnson, T., Ketkar, S., Lamina, C., Li, S., Moffatt, M.F., Myers, R.H., Narisu, N., Perry, J.R., Peters, M.J., Preuss, M., Ripatti, S., Rivadeneira, F., Sandholt, C., Scott, L.J., Timpson, N.J., Tyrer, J.P., van Wingerden, S., Watanabe, R.M., White, C.C., Wiklund, F., Barlassina, C., Chasman, D.I., Cooper, M.N., Jansson, J.O., Lawrence, R.W., Pellikka, N., Prokopenko, I., Shi, J., Thiering, E., Alavere, H., Alibrandi, M.T., Almgren, P., Arnold, A.M., Aspelund, T., Atwood, L.D., Balkau, B., Balmforth, A.J., Bennett, A.J., Ben-Shlomo, Y., Bergman, R.N., Bergmann, S., Biebermann, H., Blakemore, A.I., Boes, T., Bonnycastle, L.L., Bornstein, S.R., Brown, M.J., Buchanan, T.A., Busonero, F., Campbell, H., Cappuccio, F.P., Cavalcanti-Proença, C., Chen, Y.D., Chen, C.M., Chines, P.S., Clarke, R., Coin, L., Connell, J., Day, I.N., Heijer, M., Duan, J., Ebrahim, S., Elliott, P., Elosua, R., Eiriksdottir, G., Erdos, M.R., Eriksson, J.G., Facheris, M.F., Felix, S.B., Fischer-Posovszky, P., Folsom, A.R., Friedrich, N., Freimer, N.B., Fu, M., Gaget, S., Gejman, P.V., Geus, E.J., Gieger, C., Gjesing, A.P., Goel, A., Goyette, P., Grallert, H., Gräßler, J., Greenawalt, D.M., Groves, C.J., Gudnason, V., Guiducci, C., Hartikainen, A.L., Hassanali, N., Hall, A.S., Havulinna, A.S., Hayward, C., Heath, A.C., Hengstenberg, C., Hicks, A.A., Hinney, A., Hofman, A., Homuth, G., Hui, J., Igl, W., Iribarren, C., Isomaa, B., Jacobs, K.B., Jarick, I., Jewell, E., John, U., Jørgensen, T., Jousilahti, P., Jula, A., Kaakinen, M., Kajantie, E., Kaplan, L.M., Kathiresan, S., Kettunen, J., Kinnunen, L., Knowles, J.W., Kolcic, I., König, I.R., Koskinen, S., Kovacs, P., Kuusisto, J., Kraft, P., Kvaløy, K., Laitinen, J., Lantieri, O., Lanzani, C., Launer, L.J., Lecoeur, C., Lehtimäki, T., Lettre, G., Liu, J., Lokki, M.L., Lorentzon, M., Luben, R.N., Ludwig, B., Manunta, P., Marek, D., Marre, M., Martin, N.G., McArdle, W.L., McCarthy, A., McKnight, B., Meitinger, T., Melander, O., Meyre, D., Midthjell, K., Montgomery, G.W., Morken, M.A., Morris, A.P., Mulic, R., Ngwa, J.S., Nelis, M., Neville, M.J., Nyholt, D.R., O'Donnell, C.J., O'Rahilly, S., Ong, K.K., Oostra, B., Paré, G., Parker, A.N., Perola, M., Pichler, I., Pietiläinen, K.H., Platou, C.G., Polasek, O., Pouta, A., Rafelt, S., Raitakari, O., Rayner, N.W., Ridderstråle, M., Rief, W., Ruokonen, A., Robertson, N.R., Rzehak, P., Salomaa, V., Sanders, A.R., Sandhu, M.S., Sanna, S., Saramies, J., Savolainen, M.J., Scherag, S., Schipf, S., Schreiber, S., Schunkert, H., Silander, K., Sinisalo, J., Siscovick, D.S., Smit, J.H., Soranzo, N., Sovio, U., Stephens, J., Surakka, I., Swift, AJ., Tammesoo, M.L., Tardif, J.C., Teder-Laving, M., Teslovich, T.M., Thompson, J.R., Thomson, B., Tönjes, A., Tuomi, T., van Meurs, J.B., van Ommen, G.J., Vatin, V., Viikari, J., Visvikis-Siest, S., Vitart, V., Vogel, C.I., Voight, B.F., Waite, L.L., Wallaschofski, H., Walters, G.B., Widen, E., Wiegand, S., Wild, S.H., Willemsen, G., Witte, D.R., Witteman, J.C., Xu, J., Zhang, Q., Zgaga, L., Ziegler, A., Zitting, P., Beilby, J.P., Farooqi, I.S., Hebebrand, J., Huikuri, H.V., James, AL., Kähönen, M., Levinson, D.F., Macciardi, F., Nieminen, M.S., Ohlsson, C., Palmer, L.J., Ridker, P.M., Stumvoll, M., Beckmann, J.S., Boeing, H., Boerwinkle, E., Boomsma, D.I., Caulfield, M.J., Chanock, S.J., Collins, F.S., Cupples, L.A., Smith, G.D., Erdmann, J., Froguel, P., Grönberg, H., Gyllensten, U., Hall, P., Hansen, T., Harris, T.B., Hattersley, A.T., Hayes, R.B., Heinrich, J., Hu, F.B., Hveem, K., Illig, T., Jarvelin, M.R., Kaprio, J., Karpe, F., Khaw, K.T., Kiemeney, L.A., Krude, H., Laakso, M., Lawlor, D.A., Metspalu, A., Munroe, P.B., Ouwehand, W.H., Pedersen, O., Penninx, B.W., Peters, A., Pramstaller, P.P., Quertermous, T., Reinehr, T., Rissanen, A., Rudan, I., Samani, N.J., Schwarz, P.E., Shuldiner, A.R., Spector, T.D., Tuomilehto, J., Uda, M., Uitterlinden, A., Valle, T.T., Wabitsch, M., Waeber, G., Wareham, N.J., Watkins, H., Wilson, J.F., Wright, A.F., Zillikens, M.C., Chatterjee, N., McCarroll, S.A., Purcell, S., Schadt, E.E., Visscher, P.M., Assimes, T.L., Borecki, I.B., Deloukas, P., Fox, C.S., Groop, L.C., Haritunians, T., Hunter, D.J., Kaplan, R.C., Mohlke, K.L., O'Connell, J.R., Peltonen, L., Schlessinger, D., Strachan, D.P., van Duijn, C.M., Wichmann, H.E., Frayling, T.M., Thorsteinsdottir, U., Abecasis, G.R., Barroso, I., Boehnke, M., Stefansson, K., North, K.E., McCarthy, M.I., Hirschhorn, J.N., Ingelsson, E., Loos, R.J., Medical Research Council (MRC), and National Institute for Health Research

Subjects
Male, Netherlands Twin Register (NTR), Medicin och hälsovetenskap, obesity, 25-HYDROXYVITAMIN D, D INSUFFICIENCY, Epidemiology, Medizin, vitamin D, Aetiology, screening and detection [ONCOL 5], Medical and Health Sciences, Gastroenterology, Body Mass Index, chemistry.chemical_compound, 0302 clinical medicine, Risk Factors, GENETIC-VARIANTS, Medicine, 030212 general & internal medicine, Vitamin D, 2. Zero hunger, Genetics, Aged, 80 and over, Evidence-Based Medicine, Confounding, 11 Medical And Health Sciences, General Medicine, Middle Aged, 3. Good health, PREVALENCE, Europe, Phenotype, Genetic Epidemiology, Biological Markers, Female, Life Sciences & Biomedicine, Research Article, Vitamin, Adult, medicine.medical_specialty, vitamin D deficiency, genetic variants, Genetic Investigation of Anthropometric Traits-GIANT Consortium, European Continental Ancestry Group, 030209 endocrinology & metabolism, Single-nucleotide polymorphism, body mass index, Polymorphism, Single Nucleotide, Risk Assessment, White People, COMMON OBESITY, 03 medical and health sciences, D DEFICIENCY, Medicine, General & Internal, SDG 3 - Good Health and Well-being, General & Internal Medicine, Internal medicine, Mendelian randomization, Vitamin D and neurology, INSTRUMENTAL VARIABLES, Humans, Genetic Predisposition to Disease, Obesity, GENOME-WIDE ASSOCIATION, Biology, Molecular epidemiology Aetiology, screening and detection [NCEBP 1], Aged, Science & Technology, Population Biology, business.industry, CARDIOVASCULAR-DISEASE RISK, ta3121, Mendelian Randomization Analysis, medicine.disease, Vitamin D Deficiency, BODY-MASS INDEX, chemistry, Genetic epidemiology, 3121 General medicine, internal medicine and other clinical medicine, Multivariate Analysis, North America, Genetic Polymorphism, Linear Models, business, Body mass index, Population Genetics, Biomarkers
Abstract

A mendelian randomization study based on data from multiple cohorts conducted by Karani Santhanakrishnan Vimaleswaran and colleagues re-examines the causal nature of the relationship between vitamin D levels and obesity., Background Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. Methods and Findings We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10−27). The BMI allele score was associated both with BMI (p = 6.30×10−62) and 25(OH)D (−0.06% [95% CI −0.10 to −0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10−57 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: −4.2 [95% CI −7.1 to −1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores). Conclusions On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency. Please see later in the article for the Editors' Summary, Editors' Summary Background Obesity—having an unhealthy amount of body fat—is increasing worldwide. In the US, for example, a third of the adult population is now obese. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Although there is a genetic contribution to obesity, people generally become obese by consuming food and drink that contains more energy than they need for their daily activities. Thus, obesity can be prevented by having a healthy diet and exercising regularly. Compared to people with a healthy weight, obese individuals have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. They also have a higher risk of vitamin D deficiency, another increasingly common public health concern. Vitamin D, which is essential for healthy bones as well as other functions, is made in the skin after exposure to sunlight but can also be obtained through the diet and through supplements. Why Was This Study Done? Observational studies cannot prove that obesity causes vitamin D deficiency because obese individuals may share other characteristics that reduce their circulating 25-hydroxy vitamin D [25(OH)D] levels (referred to as confounding). Moreover, observational studies cannot indicate whether the larger vitamin D storage capacity of obese individuals (vitamin D is stored in fatty tissues) lowers their 25(OH)D levels or whether 25(OH)D levels influence fat accumulation (reverse causation). If obesity causes vitamin D deficiency, monitoring and treating vitamin D deficiency might alleviate some of the adverse health effects of obesity. Conversely, if low vitamin D levels cause obesity, encouraging people to take vitamin D supplements might help to control the obesity epidemic. Here, the researchers use bi-directional “Mendelian randomization” to examine the direction and causality of the relationship between BMI and 25(OH)D. In Mendelian randomization, causality is inferred from associations between genetic variants that mimic the influence of a modifiable environmental exposure and the outcome of interest. Because gene variants do not change over time and are inherited randomly, they are not prone to confounding and are free from reverse causation. Thus, if a lower vitamin D status leads to obesity, genetic variants associated with lower 25(OH)D concentrations should be associated with higher BMI, and if obesity leads to a lower vitamin D status, then genetic variants associated with higher BMI should be associated with lower 25(OH)D concentrations. What Did the Researchers Do and Find? The researchers created a “BMI allele score” based on 12 BMI-related gene variants and two “25(OH)D allele scores,” which are based on gene variants that affect either 25(OH)D synthesis or breakdown. Using information on up to 42,024 participants from 21 studies, the researchers showed that the BMI allele score was associated with both BMI and with 25(OH)D levels among the study participants. Based on this information, they calculated that each 10% increase in BMI will lead to a 4.2% decrease in 25(OH)D concentrations. By contrast, although both 25(OH)D allele scores were strongly associated with 25(OH)D levels, neither score was associated with BMI. This lack of an association between 25(OH)D allele scores and obesity was confirmed using data from more than 100,000 individuals involved in 46 studies that has been collected by the GIANT (Genetic Investigation of Anthropometric Traits) consortium. What Do These Findings Mean? These findings suggest that a higher BMI leads to a lower vitamin D status whereas any effects of low vitamin D status on BMI are likely to be small. That is, these findings provide evidence for obesity as a causal factor in the development of vitamin D deficiency but not for vitamin D deficiency as a causal factor in the development of obesity. These findings suggest that population-level interventions to reduce obesity should lead to a reduction in the prevalence of vitamin D deficiency and highlight the importance of monitoring and treating vitamin D deficiency as a means of alleviating the adverse influences of obesity on health. Additional Information Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001383. The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish); a data brief provides information about the vitamin D status of the US population The World Health Organization provides information on obesity (in several languages) The UK National Health Service Choices website provides detailed information about obesity and a link to a personal story about losing weight; it also provides information about vitamin D The International Obesity Taskforce provides information about the global obesity epidemic The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish) The US Office of Dietary Supplements provides information about vitamin D (in English and Spanish) MedlinePlus has links to further information about obesity and about vitamin D (in English and Spanish) Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages) Overview and details of the collaborative large-scale genetic association study (D-CarDia) provide information about vitamin D and the risk of cardiovascular disease, diabetes and related traits

Published
2013
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