129 results on '"Cederberg H"'
Search Results
2. Family history of type 2 diabetes increases the risk of both obesity and its complications: is type 2 diabetes a disease of inappropriate lipid storage?
- Author
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Cederberg, H., Stančáková, A., Kuusisto, J., Laakso, M., and Smith, U.
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- 2015
- Full Text
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3. 22-year trends in dysglycemia and body mass index:a population-based cohort study in Savitaipale, Finland
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Saramies, J. (Jouko), Koiranen, M. (Markku), Auvinen, J. (Juha), Uusitalo, H. (Hannu), Hussi, E. (Esko), Cederberg, H. (Henna), Keinänen-Kiukaanniemi, S. (Sirkka), Tuomilehto, J. (Jaakko), Saramies, J. (Jouko), Koiranen, M. (Markku), Auvinen, J. (Juha), Uusitalo, H. (Hannu), Hussi, E. (Esko), Cederberg, H. (Henna), Keinänen-Kiukaanniemi, S. (Sirkka), and Tuomilehto, J. (Jaakko)
- Abstract
Aims: We describe a 22-year prospective observational population-based study that determined the prevalence and incidence of type 2 diabetes (T2D) and intermediate hyperglycaemia (IH), obesity, hypertension, and disorders of lipid metabolism in a middle-age population in the Finnish municipality of Savitaipale. Methods: 1151 people participated in the baseline survey in 1996–1999, following two follow-up examinations, in 2007–2008 and 2018−2019. Follow-up studies comprised clinical measurements, 2-h oral glucose tolerance test and other biochemistry, questionnaires, and registry data. Results: The prevalence of T2D quadrupled to 27% and the proportion of normoglycemic people decreased from 73% to 44% while IH increased only slightly during the 22-year follow-up. A large proportion of people who died between the surveys were diabetic. The mean body mass index (BMI) did not, whereas mean waist circumference increased significantly, by 5−6 cm (P = 0.001) during the 22 years. Systolic blood pressure increased by 13−15 mmHg from baseline (P = 0.0001) but diastolic blood pressure did not. The mean plasma levels of total and LDL-cholesterol decreased 10.8% and 8.9% in women (P = 0.001), 21.5% and 22.2% in men (P = 0.001), respectively, while HDL-cholesterol and triglycerides remained stable. The proportion of those achieving targets in the treatment of dyslipidaemia increased significantly (P < 0.001). Conclusions: In this 22-year prospective follow-up study of in middle-aged Europeans with high participation rates, the progression of dysglycaemia to overt diabetes with aging was rapid, even without a significant change in BMI.
- Published
- 2021
4. Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts
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Atabaki-Pasdar, N, Ohlsson, M, Vinuela, A, Frau, F, Pomares-Millan, H, Haid, M, Jones, AG, Thomas, EL, Koivula, RW, Kurbasic, A, Mutie, PM, Fitipaldi, H, Fernandez, J, Dawed, AY, Giordano, GN, Forgie, IM, McDonald, TJ, Rutters, F, Cederberg, H, Chabanova, E, Dale, M, Masi, FD, Thomas, CE, Allin, KH, Hansen, TH, Heggie, A, Hong, M-G, Elders, PJM, Kennedy, G, Kokkola, T, Pedersen, HK, Mahajan, A, McEvoy, D, Pattou, F, Raverdy, V, Haussler, RS, Sharma, S, Thomsen, HS, Vangipurapu, J, Vestergaard, H, 't Hart, LM, Adamski, J, Musholt, PB, Brage, S, Brunak, S, Dermitzakis, E, Frost, G, Hansen, T, Laakso, M, Pedersen, O, Ridderstrale, M, Ruetten, H, Hattersley, AT, Walker, M, Beulens, JWJ, Mari, A, Schwenk, JM, Gupta, R, McCarthy, MI, Pearson, ER, Bell, JD, Pavo, I, Franks, PW, Epidemiology and Data Science, General practice, APH - Health Behaviors & Chronic Diseases, Amsterdam Reproduction & Development (AR&D), ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, APH - Aging & Later Life, Atabaki-Pasdar, Naeimeh [0000-0001-7229-1888], Ohlsson, Mattias [0000-0003-1145-4297], Viñuela, Ana [0000-0003-3771-8537], Pomares-Millan, Hugo [0000-0001-9245-4576], Haid, Mark [0000-0001-6118-1333], Jones, Angus G. [0000-0002-0883-7599], Thomas, E. Louise [0000-0003-4235-4694], Koivula, Robert W. [0000-0002-1646-4163], Kurbasic, Azra [0000-0002-1910-2619], Fitipaldi, Hugo [0000-0001-5352-2134], Dawed, Adem Y. [0000-0003-0224-2428], Forgie, Ian M. [0000-0002-8800-6145], Cederberg, Henna [0000-0003-2901-9373], Dale, Matilda [0000-0002-5788-7744], Masi, Federico De [0000-0003-4859-4170], Thomas, Cecilia Engel [0000-0001-6201-6380], Allin, Kristine H. [0000-0002-6880-5759], Hansen, Tue H. [0000-0001-5948-8993], Elders, Petra J. M. [0000-0002-5907-7219], Kennedy, Gwen [0000-0002-9856-3236], Kokkola, Tarja [0000-0002-3303-3912], Pedersen, Helle Krogh [0000-0001-9609-7377], Mahajan, Anubha [0000-0001-5585-3420], McEvoy, Donna [0000-0003-1546-5567], Häussler, Ragna S. [0000-0003-1664-8875], Vangipurapu, Jagadish [0000-0001-6657-2659], Vestergaard, Henrik [0000-0003-3090-269X], ‘t Hart, Leen M. [0000-0003-4401-2938], Brage, Soren [0000-0002-1265-7355], Frost, Gary [0000-0003-0529-6325], Hansen, Torben [0000-0001-8748-3831], Hattersley, Andrew T. [0000-0001-5620-473X], Mari, Andrea [0000-0002-1436-5591], Schwenk, Jochen M. [0000-0001-8141-8449], Gupta, Ramneek [0000-0001-6841-6676], McCarthy, Mark I. [0000-0002-4393-0510], Pearson, Ewan R. [0000-0001-9237-8585], Bell, Jimmy D. [0000-0003-3804-1281], Franks, Paul W. [0000-0002-0520-7604], Apollo - University of Cambridge Repository, HUS Abdominal Center, Clinicum, Department of Medicine, Endokrinologian yksikkö, Jones, Angus G [0000-0002-0883-7599], Thomas, E Louise [0000-0003-4235-4694], Koivula, Robert W [0000-0002-1646-4163], Dawed, Adem Y [0000-0003-0224-2428], Forgie, Ian M [0000-0002-8800-6145], Allin, Kristine H [0000-0002-6880-5759], Hansen, Tue H [0000-0001-5948-8993], Elders, Petra JM [0000-0002-5907-7219], Häussler, Ragna S [0000-0003-1664-8875], 't Hart, Leen M [0000-0003-4401-2938], Hattersley, Andrew T [0000-0001-5620-473X], Schwenk, Jochen M [0000-0001-8141-8449], McCarthy, Mark I [0000-0002-4393-0510], Pearson, Ewan R [0000-0001-9237-8585], Bell, Jimmy D [0000-0003-3804-1281], Franks, Paul W [0000-0002-0520-7604], and IMI
- Subjects
Male ,Proteomics ,Oral Glucose Suppression Test ,Biochemistry ,Machine Learning ,Fats ,Database and Informatics Methods ,Endocrinology ,Medicine and Health Sciences ,Insulin ,Prospective Studies ,11 Medical and Health Sciences ,GLOBAL EPIDEMIOLOGY ,INSULIN SENSITIVITY ,Proteomic Databases ,Liver Diseases ,Middle Aged ,Lipids ,Medicine ,Female ,Life Sciences & Biomedicine ,Research Article ,Computer and Information Sciences ,Endocrine Disorders ,BIOMARKERS ,Gastroenterology and Hepatology ,Research and Analysis Methods ,Risk Assessment ,Diabetes Complications ,Medicine, General & Internal ,SDG 3 - Good Health and Well-being ,Artificial Intelligence ,General & Internal Medicine ,NAFLD ,Diabetes Mellitus ,Humans ,Metabolomics ,Diabetic Endocrinology ,Pharmacology ,Science & Technology ,Models, Statistical ,Reproducibility of Results ,Biology and Life Sciences ,ALCOHOLIC STEATOHEPATITIS ,Hormones ,Pharmacologic-Based Diagnostics ,Fatty Liver ,Metabolism ,Biological Databases ,3121 General medicine, internal medicine and other clinical medicine ,Metabolic Disorders - Abstract
Background Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. Methods and findings We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (, In a modelling study, Naeimeh Atabaki-Pasdar and colleagues apply machine learning techniques to develop models to predict non-alcoholic fatty liver disease diagnosis using multi-omic and clinical data from individuals with and without type 2 diabetes in the IMI DIRECT cohorts., Author summary Why was this study done? Globally, about 1 in 4 adults have non-alcoholic fatty liver disease (NAFLD), which adversely affects energy homeostasis (in particular blood glucose concentrations), blood detoxification, drug metabolism, and food digestion. Although numerous noninvasive tests to detect NAFLD exist, these typically include inaccurate blood-marker tests or expensive imaging methods. The purpose of this work was to develop accurate noninvasive methods to aid in the clinical prediction of NAFLD. What did the researchers do and find? The analyses applied machine learning methods to data from the deep-phenotyped IMI DIRECT cohorts (n = 1,514) to identify sets of highly informative variables for the prediction of NAFLD. The criterion measure was liver fat quantified from MRI. We developed a total of 18 prediction models that ranged from very inexpensive models of modest accuracy to more expensive biochemistry- and/or omics-based models with high accuracy. We found that models using measures commonly collected in either clinical settings or research studies proved adequate for the prediction of NAFLD. The addition of detailed omics data significantly improved the predictive utility of these models. We also found that of all omics markers, proteomic markers yielded the highest predictive accuracy when appropriately combined. What do these findings mean? We envisage that these new approaches to predicting fatty liver may be of clinical value when screening at-risk populations for NAFLD. The identification of specific molecular features that underlie the development of NAFLD provides novel insights into the disease’s etiology, which may lead to the development of new treatments.
- Published
- 2020
5. A reference map of potential determinants for the human serum metabolome
- Author
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Bar, N., Korem, T., Weissbrod, O., Zeevi, D., Rothschild, D., Leviatan, S., Kosower, N., Lotan-Pompan, M., Weinberger, A., Le Roy, C. I., Menni, C., Visconti, A., Falchi, M., Spector, T. D., Vestergaard, H., Arumugam, M., Hansen, T., Allin, K., Hong, Mun-Gwan, Schwenk, Jochen M., Häussler, Ragna S., Dale, Matilda, Giorgino, T., Rodriquez, M., Perry, M., Nice, R., McDonald, T., Hattersley, A., Jones, A., Graefe-Mody, U., Baum, P., Grempler, R., Thomas, C. E., Masi, F. D., Brorsson, C. A., Mazzoni, G., Allesøe, R., Rasmussen, S., Gudmundsdóttir, V., Nielsen, A. M., Banasik, K., Tsirigos, K., Nilsson, B., Pedersen, H., Brunak, S., Karaderi, T., Lundgaard, A. T., Johansen, J., Gupta, R., Sackett, P. W., Tillner, J., Lehr, T., Scherer, N., Dings, C., Sihinevich, I., Loftus, H., Cabrelli, L., McEvoy, D., Mari, A., Bizzotto, R., Tura, A., ’t Hart, L., Dekkers, K., Leeuwen, N., Slieker, R., Rutters, F., Beulens, J., Nijpels, G., Koopman, A., Oort, S., Groeneveld, L., Groop, L., Elders, P., Viñuela, A., Ramisch, A., Dermitzakis, E., Ehrhardt, B., Jennison, C., Froguel, P., Canouil, M., Boneford, A., McVittie, I., Wake, D., Frau, F., Staerfeldt, H. -H, Adragni, K., Thomas, M., Wu, H., Pavo, I., Steckel-Hamann, B., Thomsen, H., Giordano, G. N., Fitipaldi, H., Ridderstråle, M., Kurbasic, A., Pasdar, N. A., Pomares-Millan, H., Mutie, P., Koivula, R., McRobert, N., McCarthy, M., Wesolowska-Andersen, A., Mahajan, A., Abdalla, M., Fernandez, J., Holl, R., Heggie, A., Deshmukh, H., Hennige, A., Bianzano, S., Thorand, B., Sharma, S., Grallert, H., Adam, J., Troll, M., Fritsche, A., Hill, A., Thorne, C., Hudson, M., Kuulasmaa, T., Vangipurapu, J., Laakso, M., Cederberg, H., Kokkola, T., Jiao, Y., Gough, S., Robertson, N., Verkindt, H., Raverdi, V., Caiazzo, R., Pattou, F., White, M., Donnelly, L., Brown, A., Palmer, C., Davtian, D., Dawed, A., Forgie, I., Pearson, E., Ruetten, H., Musholt, P., Bell, J., Thomas, E. L., Whitcher, B., Haid, M., Nicolay, C., Mourby, M., Kaye, J., Shah, N., Teare, H., Frost, G., Jablonka, B., Uhlen, M., Eriksen, R., Vogt, J., Dutta, A., Jonsson, A., Engelbrechtsen, L., Forman, A., Sondertoft, N., de Preville, N., Baltauss, T., Walker, M., Gassenhuber, J., Klintenberg, M., Bergstrom, M., Ferrer, J., Adamski, J., Franks, P. W., Pedersen, O., Segal, E., consortium, The IMI DIRECT, Bar, N., Korem, T., Weissbrod, O., Zeevi, D., Rothschild, D., Leviatan, S., Kosower, N., Lotan-Pompan, M., Weinberger, A., Le Roy, C. I., Menni, C., Visconti, A., Falchi, M., Spector, T. D., Vestergaard, H., Arumugam, M., Hansen, T., Allin, K., Hong, Mun-Gwan, Schwenk, Jochen M., Häussler, Ragna S., Dale, Matilda, Giorgino, T., Rodriquez, M., Perry, M., Nice, R., McDonald, T., Hattersley, A., Jones, A., Graefe-Mody, U., Baum, P., Grempler, R., Thomas, C. E., Masi, F. D., Brorsson, C. A., Mazzoni, G., Allesøe, R., Rasmussen, S., Gudmundsdóttir, V., Nielsen, A. M., Banasik, K., Tsirigos, K., Nilsson, B., Pedersen, H., Brunak, S., Karaderi, T., Lundgaard, A. T., Johansen, J., Gupta, R., Sackett, P. W., Tillner, J., Lehr, T., Scherer, N., Dings, C., Sihinevich, I., Loftus, H., Cabrelli, L., McEvoy, D., Mari, A., Bizzotto, R., Tura, A., ’t Hart, L., Dekkers, K., Leeuwen, N., Slieker, R., Rutters, F., Beulens, J., Nijpels, G., Koopman, A., Oort, S., Groeneveld, L., Groop, L., Elders, P., Viñuela, A., Ramisch, A., Dermitzakis, E., Ehrhardt, B., Jennison, C., Froguel, P., Canouil, M., Boneford, A., McVittie, I., Wake, D., Frau, F., Staerfeldt, H. -H, Adragni, K., Thomas, M., Wu, H., Pavo, I., Steckel-Hamann, B., Thomsen, H., Giordano, G. N., Fitipaldi, H., Ridderstråle, M., Kurbasic, A., Pasdar, N. A., Pomares-Millan, H., Mutie, P., Koivula, R., McRobert, N., McCarthy, M., Wesolowska-Andersen, A., Mahajan, A., Abdalla, M., Fernandez, J., Holl, R., Heggie, A., Deshmukh, H., Hennige, A., Bianzano, S., Thorand, B., Sharma, S., Grallert, H., Adam, J., Troll, M., Fritsche, A., Hill, A., Thorne, C., Hudson, M., Kuulasmaa, T., Vangipurapu, J., Laakso, M., Cederberg, H., Kokkola, T., Jiao, Y., Gough, S., Robertson, N., Verkindt, H., Raverdi, V., Caiazzo, R., Pattou, F., White, M., Donnelly, L., Brown, A., Palmer, C., Davtian, D., Dawed, A., Forgie, I., Pearson, E., Ruetten, H., Musholt, P., Bell, J., Thomas, E. L., Whitcher, B., Haid, M., Nicolay, C., Mourby, M., Kaye, J., Shah, N., Teare, H., Frost, G., Jablonka, B., Uhlen, M., Eriksen, R., Vogt, J., Dutta, A., Jonsson, A., Engelbrechtsen, L., Forman, A., Sondertoft, N., de Preville, N., Baltauss, T., Walker, M., Gassenhuber, J., Klintenberg, M., Bergstrom, M., Ferrer, J., Adamski, J., Franks, P. W., Pedersen, O., Segal, E., and consortium, The IMI DIRECT
- Abstract
The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites—in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites., QC 20211001
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- 2020
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6. Glucose control in diabetes: which target level to aim for?
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Laakso, M. and Cederberg, H.
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- 2012
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7. Relationship between maternal growth, infant birthweight and nutrient partitioning in teenage pregnancies
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Jones, R L, Cederberg, H MS, Wheeler, S J, Poston, L, Hutchinson, C J, Seed, P T, Oliver, R L, and Baker, P N
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- 2010
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8. Mutations at the human minisatellite MS32 integrated in yeast occur with high frequency in meiosis and involve complex recombination events
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Appelgren, H., Cederberg, H., and Rannug, U.
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- 1997
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9. Mutations occurring at the human minisatellite MS1 integrated in haploid yeast are similar to MS1 mutations in humans
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Maleki, S., Cederberg, H., and Rannug, U.
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- 1997
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10. Liraglutide and Renal Outcomes in Type 2 Diabetes
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Mann JFE, Ørsted DD, Brown-Frandsen K, Marso SP, Poulter NR, Rasmussen S, Tornøe K, Zinman B, Buse JB, LEADER Steering Committee and Investigators. 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Hinchey J, Leary MC, Pride Y, Wiviott S, Allen S, Mehr AP, Mutter WP, Parikh S, Ray S, Cheifetz A, Leffler D, Sheth S, Alexander E, Gaglia JL, Goessling W, Mitzner LD, Rosenberg C, Snow KJ, Wagner A, Piazza G, Abell S, Davis T, D'Emden M, Ding SA, Gilfillan C, Greenaway T, Gunawan F, Ho J, Jackson R, Kalra B, Lau SL, Lin J, MacIsaac R, Makepeace A, Malabu U, Marjason J, McCallum R, McLean M, Moin N, Petersons C, Price S, Roberts A, Roberts D, Sangla K, Stranks S, Tan Y, Thynne T, Walters J, Ward G, Wen W, Zhang J, Brix J, Feder A, Höbaus C, Höllerl F, Höller V, Kotter T, Kratz E, Krzizek EC, Leb-Stoeger U, Mader J, Mras N, Novak E, Obendorf F, Peric S, Pesau G, Prager R, Ribitsch A, Schnack C, Schernthaner G, Wascher T, Batens AH, Benhalima K, De Block C, Ernest P, Fouckova A, Jandrain B, Lapauw B, Letiexhe M, Mathieu C, Neven S, Peiffer F, Ruige J, Scheen A, Taes Y, Van Boxelaer I, Vandistel G, Van Durme Y, Verhaegen A, Alencar E, Alencar R, Almeida AC, Alves B, Alves E, Alves G, 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Odugbesan A, Oliver M, Oliver T, Olmeda C, O'Neil C, Oremus R, Ortega T, Ortiz-Santos S, Osborn T, Padmanabhan S, Papacostea O, Park I, Parker A, Parker K, Parker R, Patel C, Patel M, Patel R, Patino M, Patterson S, Paulson K, Paz A, Pemba R, Pepe C, Perez J, Perez T, Perry D, Phillips B, Phillips J, Pickett A, Pinson M, Pitzer R, Poduri M, Poehls J, Poteat T, Powell L, Prasad S, Prevost J, Price E, Priest D, Prieto L, Purewal T, Purighalla R, Purighalla U, Quadrel M, Qureshi A, Radhamma R, Rafla E, Rajab H, Ramalingam R, Ramirez A, Ramirez J, Ramirez K, Ramirez M, Randall M, Rangaraj U, Rao V, Rasmussen P, Rasouli N, Ray A, Reed J, Rems L, Renaud K, Reno M, Resnick M, Reusch J, Reynolds L, Rhoton K, Rhudy J, Ricci C, Rice L, Richardson A, Richardson L, Rickard H, Rickels M, Riff D, Rightenour N, Risser J, Rizvi A, Robertson J, Robinson A, Robinson R, Rockwell M, Rodriguez JP, Rodriguez M, Rojas M, Rojas W, Rooker-Morris L, Root C, Rose M, Rosenberg R, Rosenstock J, Roth M, Ruby R, Sachson R, Sack P, Sadler RK, Sahai S, Salazar J, Salgam M, Samal A, Samson A, Sanagorski R, Sanchez A, Sandberg J, Sanderson M, Sandoval J, Santiago E, Sapp T, Saunders J, Schill J, Schott C, Schreiman R, Schu D, Schuh K, Schutta M, Schwartz J, Schweppe L, Scofield H, Scribner A, Seal J, Sealock J, Seaton B, Sedlak-Hanslik T, Seekins K, Segal M, Seggelke S, Semenza S, Sentman P, Serra M, Seshadri P, Sevilla E, Shah S, Shaheen K, Shanik M, Shaw J, Sheets M, Shellabarger C, Sher J, Shippey J, Shivaswamy V, Shomali M, Shore D, Shroff P, Siddiqui T, Siegwald A, Silver R, Simmons D, Simons R, Sinan A, Singh M, Sirinvaravong S, Skero J, Slover-Zipf J, Small S, Smith B, Smith K, Smith M, Sohl J, Solarz SH, Soler D, Sood A, Sora N, Souchet A, Soule J, Sparks J, Spector L, Speicher R, Spillers L, Spivey T, Springer N, Sprouse H, St John J, Stacey A, Stacey H, Stafford M, Stagner E, Staples K, Steadman E, Steed R, Steeves G, Steinberg H, Stell C, Stirman E, Straub K, Strock E, Sue M, Suris O, Sutton T, Tabbah I, Talsania M, Tang R, Tapia J, Taylor K, Taylor-Hancher R, Teator R, Tekateka M, Temple B, Temple K, Teodori M, Tharp P, Thethi T, Theuma P, Thomas S, Thottan A, Thrasher J, Thrasher L, Tiemeyer M, Tinney I, Tobin T, Toma S, Tovar M, Townsend J, Trantow C, Traylor H, Trevino M, Troy M, Trumper D, Tryggestad J, Tucker C, Turner J, Turney R, Tuten C, Tyzack J, Ullo L, Underkofler C, Unger J, Urdanetta R, Valdivia V, Valenti S, Vanderheiden A, Vanderlinde-Wood M, Varma C, Vasquez E, Vazquez M, Vickery D, Villafuerte B, Villegas C, Vivar J, Vivekananthan K, Vo G, Vukojicic K, Wachter A, Wahl D, Waitmann J, Walker D, Walsh J, Walsh K, Walton A, Wang A, Wardell K, Watkins S, Watkinson J, Watts M, Watwe V, Weaver N, Weber R, Wedick C, Weeks D, Weeks L, Weindorff K, Weinstein R, Weiss S, Wenger K, Wentworth M, Werner A, West M, Whelan S, White B, White J, Whitmire M, Whittington R, Wical J, Wigley C, Wilkins F, Will K, Williams A, Wilson LE, Wince M, Wine S, Winkle P, Winner C, Wise J, Witte M, Wittenmyer J, Wood C, Wood R, Woodruff C, Worthington B, Wynn D, Wysham C, Xavier P, Yela S, Yenoby L, Young L, Younus N, Yourell V, Zaid M, Zubair I., Mann, Jfe, Ørsted, Dd, Brown-Frandsen, K, Marso, Sp, Poulter, Nr, Rasmussen, S, Tornøe, K, Zinman, B, Buse, Jb, Bergenstal R, LEADER Steering Committee and Investigators., Daniels, G, Moses, Ac, Nauck, M, Nissen, S, Pocock, S, Steinberg, W, Stockner, M, Kristensen, P, Ravn, L, Zychma, M, Flyvbjerg, A, Ford, I, Kloos, Rt, Schactman, Mj, Sleight, P, Swedberg, K, Tenner, Sm, Akalın, S, Arechavaleta, R, Bain, S, Babkowski, Mc, Benroubi, M, Berard, L, Comlekci, A, Czupryniak, L, Eliasson, B, Eriksson, M, Fonseca, V, Franek, E, Gross, J, Hafidh, K, Haluzik, M, Hayes, F, Huang, Yy, Jacob, S, Kaddaha, G, Khalil, A, Kilhovd, B, Laakso, M, Leiter, L, Lalic, N, Ji, L, Luedemann, J, Mannucci, E, Marre, M, Masmiquel, L, Mota, M, Omar, M, O’Shea, D, Pan, C, Petrie, J, Pieber, T, Pratley, R, Raz, I, Rea, R, Rutten, G, Satman, I, Shestakova, M, Simpson, R, Smith, D, Tack, C, Tarnow, L, Thomas, N, Van Gaal, L, Travert, F, Vidal, J, Warren, M, Yoon, Kh, Tuttle, Rm, Sheerman, Si, Hegedüs, L, Baerwald, H, Bergenstal, M, Celik, S, Dias, C, Eder, M, Fitzgibbons, S, Irvhage, L, Kloluckova, J, Kriulianski, R, Mcduffie, R, Moen, S, Paster, A, Saalfeld, Rm, Sankar, K, Shehaj, E, Swierzewska, P, Tiktin, M, Tovey, S, Gibson, Cm, Chakrabarti, Ak, Dashe, Jf, Hinchey, J, Leary, Mc, Pride, Y, Wiviott, S, Allen, S, Mehr, Ap, Mutter, Wp, Parikh, S, Ray, S, Cheifetz, A, Leffler, D, Sheth, S, Alexander, E, Gaglia, Jl, Goessling, W, Mitzner, Ld, Rosenberg, C, Snow, Kj, Wagner, A, Piazza, G, Abell, S, Davis, T, D'Emden, M, Ding, Sa, Gilfillan, C, Greenaway, T, Gunawan, F, Ho, J, Jackson, R, Kalra, B, Lau, Sl, Lin, J, Macisaac, R, Makepeace, A, Malabu, U, Marjason, J, Mccallum, R, Mclean, M, Moin, N, Petersons, C, Price, S, Roberts, A, Roberts, D, Sangla, K, Stranks, S, Tan, Y, Thynne, T, Walters, J, Ward, G, Wen, W, Zhang, J, Brix, J, Feder, A, Höbaus, C, Höllerl, F, Höller, V, Kotter, T, Kratz, E, Krzizek, Ec, Leb-Stoeger, U, Mader, J, Mras, N, Novak, E, Obendorf, F, Peric, S, Pesau, G, Prager, R, Ribitsch, A, Schnack, C, Schernthaner, G, Wascher, T, Batens, Ah, Benhalima, K, De Block, C, Ernest, P, Fouckova, A, Jandrain, B, Lapauw, B, Letiexhe, M, Mathieu, C, Neven, S, Peiffer, F, Ruige, J, Scheen, A, Taes, Y, Van Boxelaer, I, Vandistel, G, Van Durme, Y, Verhaegen, A, Alencar, E, Alencar, R, Almeida, Ac, B, Alve, Alves, E, Alves, G, Alves, J, Araujo, L, Arruda, V, Augusto, Ga, Baggentoss, R, Balestrassi, L, Barbosa, M, Barcelos, I, Belem, L, de Bem, A, Betti, Rt, Bona, R, Bosco, A, Branda, J, Bronstein, M, Bueno, T, Bulcão, T, Caiado, F, Camazzola, F, Cambréa, Mf, Campos, S, Canani, L, Carra, Mk, Caruso, S, Carvalho, N, Casillo, A, Castro, D, Cavalcanti, T, Cavichioli, V, Cercato, C, Chacra, A, Challela, W, Charchar, H, C, Chave, Chrisman, C, Correia-Deur, J, da Costa, A Jr, Costa, M, Costi, B, Coutinho, P, 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S, Pechmann, L, Costa da Penha, P, Perlamagna, L, Perotta, B, Pimentel, L, Pinto, M, Poço, C, Ponte, C, Prazeres, P, Quintao, E, Raduan, R, Rassi, Dt, Rassi, N, Reck, L, Montenegro, R Jr, Ribeiro, R, Rodovalho, S, Silveira Rodrigues, G, Rollin, G, Rossi, S, Sabino, C, Sales, Ap, Salles, J, Sampaio, Cr, Santana, L, Sato, V, da Silva Santos, M, Santos, Nl, Santos, R, Saraiva, J, Sartori, C, Sena, R, Sevilha, M, Sgarbi, J, Silva, D, D'albuquerque Silva, L, Silva, Me, Siqueira, K, Soares, S, Sobreira, W, Sousa, B, Souza, Ac, Souza, B, Tambascia, M, Tarantino, R, Tenor, F, Tomarchio, M, Triches, C, Tristão, Lj, Valenti, A, Vasques, E, Vencio, S, Vianna, A, Munhoz Vidotto, T, Vieira, S, Villar, H, Visconti, G, Volaco, A, Wajchenberg, B, Zanatta, L, Zimmerman, L, Abbott, Ec, Abu-Bakare, A, Advani, A, Allison, R, Bishara, P, Bowering, Ck, Cheng, A, Chouinard, S, Clayton, D, Conway, J, D'Amours, M, de Tugwell, B, Deyoung, P, D'Ignazio, G, Dube, F, Ekoe, Jm, Fagan, S, Garceau, C, Gottesman, I, 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I, Alvarado Ruíz, R, González Saldivar, G, Reyes Sánchez, R, Sánchez-Michel, Bl, Contreras Sandoval AY, Velasco Gutiérrez, A, Perez Verdín AE, Ramos Zavala MG, Abbink-Zandbergen, E, Ahdi, M, Bugter, A, van Dijk, M, Eisma, G, Erdtsieck, R, Gerards, M, Gerdes, V, Haak, H, Harbers, V, Hoogenberg, K, Huvers, F, Janssen, W, Kars, M, Kooy, A, Lafeber, M, Landewé-Cleuren, S, Lieverse, A, Meesters, E, Moerman, S, van Moorsel, D, Nijhuis, J, Smit, Cj, Thevissen, K, Timmerman Thijssen DM, Willemsen, A, Birkeland, K, Cooper, J, Gulseth, H, Hjelmesæth, J, Jørgensen, P, Kilhovd, Bk, Kulseng, B, Nicolaisen, B, Skadberg, Ø, Wium, C, Antkowiak-Piatyszek, K, Arciszewska, M, Bajkowska-Fiedziukiewicz, A, Bogdanski, P, Czubek, U, Cypryk, K, Dabrowski, J, Dabrowska, M, Dziedzic, S, Dziewit, T, Faligowska, M, Fedor-Plenkowska, G, Gajos, G, Galicka-Latala, D, Galuszka-Bilinska, A, Gladysz, I, Grycewicz, J, Hachula, G, Janas, I, Jazwinska-Tarnawska, E, Jedynasty, K, Jozefowska, M, Kaminska, A, Katra, B, 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T, Hagan, A, Hager, S, Haggag, A, Haggar, M, Hamilton, M, Hamlet, P, Hammond, J, Hansen, A, Harrell, W, Harris, E, Harris, K, Harris, M, Harrison, L, Hartman, I, Hatch, A, Hayes, D, Hayes, M, Heath, J, Heineman, R, Heinzman, A, Hendrick, M, Herbst, R, Hermayer, K, Hibbard, J, Hill, Wd, Hilliard, B, Hix, M, Hoch, B, Hollander, P, Holmes, Z, Horobetz, C, Horowitz, R, Hsieh, P, Hsieh, S, Htun, W, Huang, J, Huber, C, Hudson, T, Huizar, S, Hull, B, Hull, J, Hummer, K, Hundal, R, Hunt, G, Hunt, V, Hutchinson, P, Hwang, J, Iannamorelli, A, Iannuzzi, L, Ingram, M, Iram, N, Ismail-Beigi, F, Jabbour, S, Jackson, T, Jaen, L, Jain, V, Jannesari, R, Januski, V, Japa, U, Jarvis, K, Jayson, L, Jensen, R, Jester, D, Jocko, C, Johnson, C, Johnson, M, Johnston, K, Jones, D, Jones, J, Jordan, T, Juarez, M, Kaapuraala, A, Kain, A, Kaiser, V, Kamradt, K, Karatoprakli, P, Karegar, M, Karounos, C, Karounos, D, Karunaratne, H, Katalenich, B, Katic, K, Katz, M, Kaur, G, Kawa, A, Keib, C, Keider, G, Kem, D, 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E, Vazquez, M, Vickery, D, Villafuerte, B, Villegas, C, Vivar, J, Vivekananthan, K, Vo, G, Vukojicic, K, Wachter, A, Wahl, D, Waitmann, J, Walker, D, Walsh, J, Walsh, K, Walton, A, Wang, A, Wardell, K, Watkins, S, Watkinson, J, Watts, M, Watwe, V, Weaver, N, Weber, R, Wedick, C, Weeks, D, Weeks, L, Weindorff, K, Weinstein, R, Weiss, S, Wenger, K, Wentworth, M, Werner, A, West, M, Whelan, S, White, B, White, J, Whitmire, M, Whittington, R, Wical, J, Wigley, C, Wilkins, F, Will, K, Williams, A, Wilson, Le, Wince, M, Wine, S, Winkle, P, Winner, C, Wise, J, Witte, M, Wittenmyer, J, Wood, C, Wood, R, Woodruff, C, Worthington, B, Wynn, D, Wysham, C, Xavier, P, Yela, S, Yenoby, L, Young, L, Younus, N, Yourell, V, Zaid, M, Zubair, I., Mann J.F.E., Orsted D.D., Brown-Frandsen K., Marso S.P., Poulter N.R., Rasmussen S., Tornoe K., Zinman B., Buse J.B., and Buscemi S.
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Male ,Settore MED/09 - Medicina Interna ,Acute Kidney Injury ,Aged ,Albuminuria ,Creatinine ,Diabetes Mellitus, Type 2 ,Diabetic Nephropathies ,Double-Blind Method ,Female ,Follow-Up Studies ,Glomerular Filtration Rate ,Glucagon-Like Peptide 1 ,Humans ,Hypoglycemic Agents ,Intention to Treat Analysis ,Kidney Failure, Chronic ,Liraglutide ,Middle Aged ,Type 2 diabetes ,030204 cardiovascular system & hematology ,urologic and male genital diseases ,GLOMERULAR-FILTRATION-RATE ,KIDNEY-FUNCTION ,DISEASE ,law.invention ,Kidney Failure ,chemistry.chemical_compound ,0302 clinical medicine ,Randomized controlled trial ,law ,Medicine ,Settore MED/49 - Scienze Tecniche Dietetiche Applicate ,Chronic ,RISK ,Kidney ,Acute kidney injury ,11 Medical And Health Sciences ,General Medicine ,medicine.anatomical_structure ,TRIAL ,liraglutide, randomized controlled trial, type 2 diabetes, renal outcomes ,Life Sciences & Biomedicine ,Type 2 ,medicine.drug ,medicine.medical_specialty ,Renal function ,030209 endocrinology & metabolism ,CARDIOVASCULAR OUTCOMES ,Follow-Up Studie ,03 medical and health sciences ,Medicine, General & Internal ,General & Internal Medicine ,Diabetes mellitus ,Internal medicine ,Diabetes Mellitus ,Intensive care medicine ,Science & Technology ,business.industry ,MORTALITY ,medicine.disease ,INTENSIVE GLUCOSE CONTROL ,INDIVIDUALS ,chemistry ,Diabetic Nephropathie ,LEADER Steering Committee and Investigators ,business - Abstract
BACKGROUND: In a randomized, controlled trial that compared liraglutide, a glucagon-like peptide 1 analogue, with placebo in patients with type 2 diabetes and high cardiovascular risk who were receiving usual care, we found that liraglutide resulted in lower risks of the primary end point (nonfatal myocardial infarction, nonfatal stroke, or death from cardiovascular causes) and death. However, the long-term effects of liraglutide on renal outcomes in patients with type 2 diabetes are unknown. METHODS: We report the prespecified secondary renal outcomes of that randomized, controlled trial in which patients were assigned to receive liraglutide or placebo. The secondary renal outcome was a composite of new-onset persistent macroalbuminuria, persistent doubling of the serum creatinine level, end-stage renal disease, or death due to renal disease. The risk of renal outcomes was determined with the use of time-to-event analyses with an intention-to-treat approach. Changes in the estimated glomerular filtration rate and albuminuria were also analyzed. RESULTS: A total of 9340 patients underwent randomization, and the median follow-up of the patients was 3.84 years. The renal outcome occurred in fewer participants in the liraglutide group than in the placebo group (268 of 4668 patients vs. 337 of 4672; hazard ratio, 0.78; 95% confidence interval [CI], 0.67 to 0.92; P=0.003). This result was driven primarily by the new onset of persistent macroalbuminuria, which occurred in fewer participants in the liraglutide group than in the placebo group (161 vs. 215 patients; hazard ratio, 0.74; 95% CI, 0.60 to 0.91; P=0.004). The rates of renal adverse events were similar in the liraglutide group and the placebo group (15.1 events and 16.5 events per 1000 patient-years), including the rate of acute kidney injury (7.1 and 6.2 events per 1000 patient-years, respectively). CONCLUSIONS: This prespecified secondary analysis shows that, when added to usual care, liraglutide resulted in lower rates of the development and progression of diabetic kidney disease than placebo. (Funded by Novo Nordisk and the National Institutes of Health; LEADER ClinicalTrials.gov number, NCT01179048 .).
- Published
- 2017
11. The complete DNA sequence of yeast chromosome III
- Author
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Oliver, S.G., van der Aart, Q.J.M., Agostoni-Carbone, M.L., Aigle, M., Alberghina, L., Alexandraki, D., Antoine, G., Anwar, R., Ballesta, J.P.G., Benit, P., Berben, G., Bergantino, E., Biteau, N., Bolle, P.A., Bolotin-Fukuhara, M., Brown, A., Brown, A.J.P., Buhler, J.M., Carcano, C., Carignani, G., Cederberg, H., Chanet, R., Contreras, R., Crouzet, M., Daignan-Fornier, B., Defoor, E., Delgado, M., Demolder, J., Doira, C., Dubois, E., Dujon, B., Dusterhoft, A., Erdmann, D., Esteban, M., Fabre, F., Fairhead, C., Faye, G., Feldmann, H., Fiers, W., Francingues-Gaillard, M.C., Franco, L., Frontali, L., Fukuhara, H., Fuller, L.J., Galland, P., Gent, M.E., Gigot, D., Gilliquet, V., Glansdorff, N., Goffeau, A., Grenson, M., Grisanti, P., Grivell, L.A., de Haan, M., Haasemann, M., Hatat, D., Hoenicka, J., Hegemann, J., Herbert, C.J., Hilger, F., Hohmann, S., Hollenberg, C.P., Huse, K., Iborra, F., Indge, K.J., Isono, K., Jacq, C., Jacquet, M., James, C.M., Jauniaux, J.C., Jia, Y., Jimenez, A., Kelly, A., Kleinhans, U., Kreisl, P., Lanfranchi, G., Lewis, C., van der Linden, C.G., Lucchini, G., Lutzenkirchen, K., Maat, M.J., Mallet, L., Mannhaupt, G., Martegani, E., Mathieu, A., Maurer, C.T.C., McConnell, D., McKee, R.A., Messenguy, F., Mewes, H.W., Molemans, F., Montague, M.A., Muzi Falconi, M., Navas, L., Newlon, C.S., Noone, D., Pallier, C., Panzeri, L., Pearson, B.M., Perea, J., Philippsen, P., Pierard, A., Planta, R.J., Plevani, P., Poetsch, B., Pohl, F., Purnelle, B., Ramezani Rad, M., Rasmussen, S.W., Raynal, A., Remacha, M., Richterich, P., Roberts, A.B., Rodriguez, F., Sanz, E., Schaaff-Gerstenschlager, I., Scherens, B., Schweitzer, B., Shu, Y., Skala, J., Slonimski, P.P., Sor, F., Soustelle, C., Spiegelberg, R., Stateva, L.I., Steensma, H.Y., Steiner, S., Thierry, A., Thireos, G., Tzermia, M., Urrestarazu, L.A., Valle, G., Vetter, I., van Vliet-Reedijk, J.C., Voet, M., Volckaert, G., Vreken, P., Wang, H., Warmington, J.R., von Wettstein, D., Wicksteed, B.L., Wilson, C., Wurst, H., Xu, G., Yoshikawa, A., Zimmermann, F.K., and Sgouros, J.G.
- Subjects
Saccharomyces -- Genetic aspects ,Nucleotide sequence -- Research ,Plant chromosomes -- Research ,Genomes -- Research ,Environmental issues ,Science and technology ,Zoology and wildlife conservation - Published
- 1992
12. Large meta-analysis of genome-wide association studies identifies five loci for lean body mass
- Author
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Zillikens, MC, Demissie, S, Hsu, YH, Yerges-Armstrong, LM, Chou, WC, Stolk, L, Livshits, G, Broer, L, Johnson, T, Koller, DL, Kutalik, Z, Luan, J, Malkin, I, Ried, JS, Smith, AV, Thorleifsson, G, Vandenput, L, Hua Zhao, J, Zhang, W, Aghdassi, A, Åkesson, K, Amin, N, Baier, LJ, Barroso, I, Bennett, DA, Bertram, L, Biffar, R, Bochud, M, Boehnke, M, Borecki, IB, Buchman, AS, Byberg, L, Campbell, H, Campos Obanda, N, Cauley, JA, Cawthon, PM, Cederberg, H, Chen, Z, Cho, NH, Jin Choi, H, Claussnitzer, M, Collins, F, Cummings, SR, De Jager, PL, Demuth, I, Dhonukshe-Rutten, RAM, DIatchenko, L, Eiriksdottir, G, Enneman, AW, Erdos, M, Eriksson, JG, Eriksson, J, Estrada, K, Evans, DS, Feitosa, MF, Fu, M, Garcia, M, Gieger, C, Girke, T, Glazer, NL, and Grallert, H
- Abstract
© 2017 The Author(s). Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 × 10-8) or suggestively genome wide (p < 2.3 × 10-6). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass.
- Published
- 2017
13. Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.
- Author
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Zillikens, M.C., Demissie, S., Hsu, Y.H., Yerges-Armstrong, L.M., Chou, W.C., Stolk, L., Livshits, G., Broer, L., Johnson, T., Koller, D.L., Kutalik, Z., Luan, J., Malkin, I., Ried, J.S., Smith, A.V., Thorleifsson, G., Vandenput, L., Hua Zhao, J., Zhang, W., Aghdassi, A., Åkesson, K., Amin, N., Baier, L.J., Barroso, I., Bennett, D.A., Bertram, L., Biffar, R., Bochud, M., Boehnke, M., Borecki, I.B., Buchman, A.S., Byberg, L., Campbell, H., Campos Obanda, N., Cauley, J.A., Cawthon, P.M., Cederberg, H., Chen, Z., Cho, N.H., Jin Choi, H., Claussnitzer, M., Collins, F., Cummings, S.R., De Jager, P.L., Demuth, I., Dhonukshe-Rutten, RAM, Diatchenko, L., Eiriksdottir, G., Enneman, A.W., Erdos, M., Eriksson, J.G., Eriksson, J., Estrada, K., Evans, D.S., Feitosa, M.F., Fu, M., Garcia, M., Gieger, C., Girke, T., Glazer, N.L., Grallert, H., Grewal, J., Han, B.G., Hanson, R.L., Hayward, C., Hofman, A., Hoffman, E.P., Homuth, G., Hsueh, W.C., Hubal, M.J., Hubbard, A., Huffman, K.M., Husted, L.B., Illig, T., Ingelsson, E., Ittermann, T., Jansson, J.O., Jordan, J.M., Jula, A., Karlsson, M., Khaw, K.T., Kilpeläinen, T.O., Klopp, N., Kloth, JSL, Koistinen, H.A., Kraus, W.E., Kritchevsky, S., Kuulasmaa, T., Kuusisto, J., Laakso, M., Lahti, J., Lang, T., Langdahl, B.L., Launer, L.J., Lee, J.Y., Lerch, M.M., Lewis, J.R., Lind, L., Lindgren, C., Liu, Y., Liu, T., Ljunggren, Ö., Lorentzon, M., Luben, R.N., Maixner, W., McGuigan, F.E., Medina-Gomez, C., Meitinger, T., Melhus, H., Mellström, D., Melov, S., Michaëlsson, K., Mitchell, B.D., Morris, A.P., Mosekilde, L., Newman, A., Nielson, C.M., O'Connell, J.R., Oostra, B.A., Orwoll, E.S., Palotie, A., Parker, S., Peacock, M., Perola, M., Peters, A., Polasek, O., Prince, R.L., Räikkönen, K., Ralston, S.H., Ripatti, S., Robbins, J.A., Rotter, J.I., Rudan, I., Salomaa, V., Satterfield, S., Schadt, E.E., Schipf, S., Scott, L., Sehmi, J., Shen, J., Soo Shin, C., Sigurdsson, G., Smith, S., Soranzo, N., Stančáková, A., Steinhagen-Thiessen, E., Streeten, E.A., Styrkarsdottir, U., Swart, KMA, Tan, S.T., Tarnopolsky, M.A., Thompson, P., Thomson, C.A., Thorsteinsdottir, U., Tikkanen, E., Tranah, G.J., Tuomilehto, J., van Schoor, N.M., Verma, A., Vollenweider, P., Völzke, H., Wactawski-Wende, J., Walker, M., Weedon, M.N., Welch, R., Wichmann, H.E., Widen, E., Williams, FMK, Wilson, J.F., Wright, N.C., Xie, W., Yu, L., Zhou, Y., Chambers, J.C., Döring, A., van Duijn, C.M., Econs, M.J., Gudnason, V., Kooner, J.S., Psaty, B.M., Spector, T.D., Stefansson, K., Rivadeneira, F., Uitterlinden, A.G., Wareham, N.J., Ossowski, V., Waterworth, D., Loos, RJF, Karasik, D., Harris, T.B., Ohlsson, C., Kiel, D.P., Zillikens, M.C., Demissie, S., Hsu, Y.H., Yerges-Armstrong, L.M., Chou, W.C., Stolk, L., Livshits, G., Broer, L., Johnson, T., Koller, D.L., Kutalik, Z., Luan, J., Malkin, I., Ried, J.S., Smith, A.V., Thorleifsson, G., Vandenput, L., Hua Zhao, J., Zhang, W., Aghdassi, A., Åkesson, K., Amin, N., Baier, L.J., Barroso, I., Bennett, D.A., Bertram, L., Biffar, R., Bochud, M., Boehnke, M., Borecki, I.B., Buchman, A.S., Byberg, L., Campbell, H., Campos Obanda, N., Cauley, J.A., Cawthon, P.M., Cederberg, H., Chen, Z., Cho, N.H., Jin Choi, H., Claussnitzer, M., Collins, F., Cummings, S.R., De Jager, P.L., Demuth, I., Dhonukshe-Rutten, RAM, Diatchenko, L., Eiriksdottir, G., Enneman, A.W., Erdos, M., Eriksson, J.G., Eriksson, J., Estrada, K., Evans, D.S., Feitosa, M.F., Fu, M., Garcia, M., Gieger, C., Girke, T., Glazer, N.L., Grallert, H., Grewal, J., Han, B.G., Hanson, R.L., Hayward, C., Hofman, A., Hoffman, E.P., Homuth, G., Hsueh, W.C., Hubal, M.J., Hubbard, A., Huffman, K.M., Husted, L.B., Illig, T., Ingelsson, E., Ittermann, T., Jansson, J.O., Jordan, J.M., Jula, A., Karlsson, M., Khaw, K.T., Kilpeläinen, T.O., Klopp, N., Kloth, JSL, Koistinen, H.A., Kraus, W.E., Kritchevsky, S., Kuulasmaa, T., Kuusisto, J., Laakso, M., Lahti, J., Lang, T., Langdahl, B.L., Launer, L.J., Lee, J.Y., Lerch, M.M., Lewis, J.R., Lind, L., Lindgren, C., Liu, Y., Liu, T., Ljunggren, Ö., Lorentzon, M., Luben, R.N., Maixner, W., McGuigan, F.E., Medina-Gomez, C., Meitinger, T., Melhus, H., Mellström, D., Melov, S., Michaëlsson, K., Mitchell, B.D., Morris, A.P., Mosekilde, L., Newman, A., Nielson, C.M., O'Connell, J.R., Oostra, B.A., Orwoll, E.S., Palotie, A., Parker, S., Peacock, M., Perola, M., Peters, A., Polasek, O., Prince, R.L., Räikkönen, K., Ralston, S.H., Ripatti, S., Robbins, J.A., Rotter, J.I., Rudan, I., Salomaa, V., Satterfield, S., Schadt, E.E., Schipf, S., Scott, L., Sehmi, J., Shen, J., Soo Shin, C., Sigurdsson, G., Smith, S., Soranzo, N., Stančáková, A., Steinhagen-Thiessen, E., Streeten, E.A., Styrkarsdottir, U., Swart, KMA, Tan, S.T., Tarnopolsky, M.A., Thompson, P., Thomson, C.A., Thorsteinsdottir, U., Tikkanen, E., Tranah, G.J., Tuomilehto, J., van Schoor, N.M., Verma, A., Vollenweider, P., Völzke, H., Wactawski-Wende, J., Walker, M., Weedon, M.N., Welch, R., Wichmann, H.E., Widen, E., Williams, FMK, Wilson, J.F., Wright, N.C., Xie, W., Yu, L., Zhou, Y., Chambers, J.C., Döring, A., van Duijn, C.M., Econs, M.J., Gudnason, V., Kooner, J.S., Psaty, B.M., Spector, T.D., Stefansson, K., Rivadeneira, F., Uitterlinden, A.G., Wareham, N.J., Ossowski, V., Waterworth, D., Loos, RJF, Karasik, D., Harris, T.B., Ohlsson, C., and Kiel, D.P.
- Abstract
Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 × 10(-8)) or suggestively genome wide (p < 2.3 × 10(-6)). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass.Lean body mass is a highly heritable trait and is associated with various health conditions. Here, Kiel and colleagues perform a meta-analysis of genome-wide association studies for whole body lean body mass and find five novel genetic loci to be significantly associated.
- Published
- 2017
14. The Yeast Genome Directory
- Author
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Goffeau, A., Aert, R., Agostini-Carbone, M. L., Ahmed, A., Aigle, M., Alberghina, L., Albermann, K., Albers, M., Aldea, M., Alexandraki, D., Aljinovic, G., Allen, E., Alt-Mörbe, J., André, B., Andrews, S., Ansorge, W., Antoine, G., Anwar, R., Aparicio, A., Araujo, R., Arino, J., Arnold, F., Arroyo, J., Aviles, E., Backes, U., Baclet, M. C., Badcock, K., Bahr, A., Baladron, V., Ballesta, J. P. G., Bankier, A. T., Banrevi, A., Bargues, M., Baron, L., Barreiros, T., Barrell, B. G., Barthe, C., Barton, A. B., Baur, A., Bécam, A.-M., Becker, A., Becker, I., Beinhauer, J., Benes, V., Benit, P., Berben, G., Bergantino, E., Bergez, P., Berno, A., Bertani, I., Biteau, N., Bjourson, A. J., Blöcker, H., Blugeon, C., Bohn, C., Boles, E., Bolle, P. A., Bolotin-Fukuhara, M., Bordonné, R., Boskovic, J., Bossier, P., Botstein, D., Bou, G., Bowman, S., Boyer, J., Brandt, P., Brandt, T., Brendel, M., Brennan, T., Brinkman, R., Brown, A., Brown, A. J. P., Brown, D., Brückner, M., Bruschi, C. V., Buhler, J. M., Buitrago, M. J., Bussereau, F., Bussey, H., Camasses, A., Carcano, C., Carignani, G., Carpenter, J., Casamayor, A., Casas, C., Castagnoli, L., Cederberg, H., Cerdan, E., Chalwatzis, N., Chanet, R., Chen, E., Chéret, G., Cherry, J. M., Chillingworth, T., Christiansen, C., Chuat, J.-C., Chung, E., Churcher, C., Churcher, C. M., Clark, M. W., Clemente, M. L., Coblenz, A., Coglievina, M., Coissac, E., Colleaux, L., Connor, R., Contreras, R., Cooper, J., Copsey, T., Coster, F., Coster, R., Couch, J., Crouzet, M., Cziepluch, C., Daignan-Fornier, B., Dal Paro, F., Dang, D. V., D’Angelo, M., Davies, C. J., Davis, K., Davis, R. W., De Antoni, A., Dear, S., Dedman, K., Defoor, E., De Haan, M., Delaveau, Th., Del Bino, S., Delgado, M., Delius, H., Delneri, D., Del Rey, F., Demolder, J., Démolis, N., Devlin, K., de Wergifosse, P., Dietrich, F. S., Ding, H., Dion, C., Dipaolo, T., Doignon, F., Doira, C., Domdey, H., Dover, J., Du, Z., Dubois, E., Dujon, B., Duncan, M., Durand, P., Düsterhöft, A., Düsterhus, S., Eki, T., El Bakkoury, M., Eide, L. G., Entian, K.-D., Eraso, P., Erdmann, D., Erfle, H., Escribano, V., Esteban, M., Fabiani, L., Fabre, F., Fairhead, C., Fartmann, B., Favello, A., Faye, G., Feldmann, H., Fernandes, L., Feroli, F., Feuermann, M., Fiedler, T., Fiers, W., Fleig, U. N., Flöth, M., Fobo, G. M., Fortin, N., Foury, F., Francingues-Gaillard, M. C., Franco, L., Fraser, A., Friesen, J.D., Fritz, C., Frontali, L., Fukuhara, H., Fulton, L., Fuller, L. J., Gabel, C., Gaillardin, C., Gaillon, L., Galibert, F., Galisson, F., Galland, P., Gamo, F.-J., Gancedo, C., Garcia-Cantalejo, J. M., García-Gonzalez, M. I., Garcia-Ramirez, J. J., García-Saéz, M., Gassenhuber, H., Gatius, M., Gattung, S., Geisel, C., Gent, M. E., Gentles, S., Ghazvini, M., Gigot, D., Gilliquet, V., Glansdorff, N., Gómez-Peris, A., Gonzaléz, A., Goulding, S. E., Granotier, C., Greco, T., Grenson, M., Grisanti, P., Grivell, L. A., Grothues, D., Gueldener, U., Guerreiro, P., Guzman, E., Haasemann, M., Habbig, B., Hagiwara, H., Hall, J., Hallsworth, K., Hamlin, N., Hand, N. J., Hanemann, V., Hani, J., Hankeln, T., Hansen, M., Harris, D., Harris, D. E., Hartzell, G., Hatat, D., Hattenhorst, U., Hawkins, J., Hebling, U., Hegemann, J., Hein, C., Hennemann, A., Hennessy, K., Herbert, C. J., Hernandez, K., Hernando, Y., Herrero, E., Heumann, K., Heuss- Neitzel, D., Hewitt, N., Hiesel, R., Hilbert, H., Hilger, F., Hillier, L., Ho, C., Hoenicka, J., Hofmann, B., Hoheisel, J., Hohmann, S., Hollenberg, C. P., Holmstrøm, K., Horaitis, O., Horsnell, T. S., Huang, M.-E., Hughes, B., Hunicke-Smith, S., Hunt, S., Hunt, S. E., Huse, K., Hyman, R. W., Iborra, F., Indge, K. J., Iraqui Houssaini, I., Isono, K., Jacq, C., Jacquet, M., Jacquier, A., Jagels, K., Jäger, W., James, C. M., Jauniaux, J. C., Jia, Y., Jier, M., Jimenez, A., Johnson, D., Johnston, L., Johnston, M., Jones, M., Jonniaux, J.-L., Kaback, D. B., Kallesøe, T., Kalman, S., Kalogeropoulos, A., Karpfinger-Hartl, L., Kashkari, D., Katsoulou, C., Kayser, A., Kelly, A., Keng, T., Keuchel, H., Kiesau, P., Kirchrath, L., Kirsten, J., Kleine, K., Kleinhans, U., Klima, R., Komp, C., Kordes, E., Korol, S., Kötter, P., Krämer, C., Kramer, B., Kreisl, P., Kucaba, T., Kuester, H., Kurdi, O., Laamanen, P., Lafuente, M. J., Landt, O., Lanfranchi, G., Langston, Y., Lashkari, D., Latreille, P., Lauquin, G., Le, T., Legrain, P., Legros, Y., Lepingle, A., Lesveque, H., Leuther, H., Lew, H., Lewis, C., Li, Z. Y., Liebl, S., Lin, A., Lin, D., Logghe, M., Lohan, A. J. E., Louis, E. J., Lucchini, G., Lutzenkirchen, K., Lyck, R., Lye, G., Maarse, A. C., Maat, M. J., Macri, C., Madania, A., Maftahi, M., Maia e Silva, A., Maillier, E., Mallet, L., Mannhaupt, G., Manus, V., Marathe, R., Marck, C., Marconi, A., Mardis, E., Martegani, E., Martin, R., Mathieu, A., Maurer, C. T. C., Mazón, M. J., Mazzoni, C., McConnell, D., McDonald, S., McKee, R. A., McReynolds, A. D. K., Melchioretto, P., Menezes, S., Messenguy, F., Mewes, H. W., Michaux, G., Miller, N., Minenkova, O., Miosga, T., Mirtipati, S., Möller-Rieker, S., Möstl, D., Molemans, F., Monnet, A., Monnier, A-L., Montague, M. A., Moro, M., Mosedale, D., Möstl, D., Moule, S., Mouser, L., Murakami, Y., Müller-Auer, S., Mulligan, J., Murphy, L., Muzi Falconi, M., Naitou, M., Nakahara, K., Namath, A., Nasr, F., Navas, L., Nawrocki, A., Nelson, J., Nentwich, U., Netter, P., Neu, R., Newlon, C. S., Nhan, M., Nicaud, J.-M., Niedenthal, R. K., Nombela, C., Noone, D., Norgren, R., Nußbaumer, B., Obermaier, B., Odell, C., Öfner, P., Oh, C., Oliver, K., Oliver, S. G., Ouellette, B. F., Ozawa, M., Paces, V., Pallier, C., Pandolfo, D., Panzeri, L., Paoluzi, S., Parle-Mcdermott, A. G., Pascolo, S., Patricio, N., Pauley, A., Paulin, L., Pearson, B. M., Pearson, D., Peluso, D., Perea, J., Pérez-Alonso, M., Pérez-Ortin, J. E., Perrin, A., Petel, F. X., Pettersson, B., Pfeiffer, F., Philippsen, P., Piérard, A., Piravandi, E., Planta, R. J., Plevani, P., Poch, O., Poetsch, B., Pohl, F. M., Pohl, T. M., Pöhlmann, R., Poirey, R., Portetelle, D., Portillo, F., Potier, S., Proft, M., Prydz, H., Pujol, A., Purnelle, B., Puzos, V., Rajandream, M. A., Ramezani Rad, M., Rasmussen, S. W., Raynal, A., Rechmann, S., Remacha, M., Revuelta, J. L., Rice, P., Richard, G-F., Richterich, P., Rieger, M., Rifken, L., Riles, L., Rinaldi, T., Rinke, M., Roberts, A. B., Roberts, D., Rodriguez, F., Rodriguez-Belmonte, E., Rodriguez-Pousada, C., Rodriguez-Torres, A. M., Rose, M., Rossau, R., Rowley, N., Rupp, T., Ruzzi, M., Saeger, W., Saiz, J. E., Saliola, M., Salom, D., Saluz, H. P., Sánchez-Perez, M., Santos, M. A., Sanz, E., Sanz, J. E., Saren, A.-M., Sartorello, F., Sasanuma, M., Sasanuma, S-I., Scarcez, T., Schaaf-Gerstenschläger, I., Schäfer, B., Schäfer, M., Scharfe, M., Scherens, B., Schroff, N., Sen-Gupta, M., Shibata, T., Schmidheini, T., Schmidt, E. R., Schneider, C., Scholler, P., Schramm, S., Schreer, A., Schröder, M., Schwager, C., Schwarz, S., Schwarzlose, C., Schweitzer, B., Schweizer, M., Sdicu, A-M., Sehl, P., Sensen, C., Sgouros, J. G., Shogren, T., Shore, L., Shu, Y., Skala, J., Skelton, J., Slonimski, P. P., Smit, P. H. M., Smith, V., Soares, H., Soeda, E., Soler-Mira, A., Sor, F., Soriano, N., Souciet, J. L., Soustelle, C., Spiegelberg, R., Stateva, L. I., Steensma, H. Y., Stegemann, J., Steiner, S., Stellyes, L., Sterky, F., Storms, R. K., St. Peter, H., Stucka, R., Taich, A., Talla, E., Tarassov, I., Tashiro, H., Taylor, P., Teodoru, C., Tettelin, H., Thierry, A., Thireos, G., Tobiasch, E., Tovan, D., Trevaskis, E., Tsuchiya, Y., Tzermia, M., Uhlen, M., Underwood, A., Unseld, M., Urbanus, J. H. M., Urrestarazu, A., Ushinsky, S., Valens, M., Valle, G., Van Broekhoven, A., Vandenbol, M., Van Der Aart, Q. J. M., Van Der Linden, C. G., Van Dyck, L., Vanoni, M., Van Vliet-Reedijk, J. C., Vassarotti, A., Vaudin, M., Vaughan, K., Verhasselt, P., Vetter, I., Vierendeels, F., Vignati, D., Vilela, C., Vissers, S., Vleck, C., Vo, D. T., Vo, D. H., Voet, M., Volckaert, G., Von Wettstein, D., Voss, H., Vreken, P., Wagner, G., Walsh, S. V., Wambutt, R., Wang, H., Wang, Y., Warmington, J. R., Waterston, R., Watson, M. D., Weber, N., Wedler, E., Wedler, H., Wei, Y., Whitehead, S., Wicksteed, B. L., Wiemann, S., Wilcox, L., Wilson, C., Wilson, R., Winant, A., Winnett, E., Winsor, B., Wipfli, P., Wölfl, S., Wohldman, P., Wolf, K., Wolfe, K. H., Wright, L. F., Wurst, H., Xu, G., Yamasaki, M., Yelton, M. A., Yokohama, K., Yoshikawa, A., Yuping, S., Zaccaria, P., Zagulski, M., Zimmermann, F. K., Zimmermann, J., Zimmermann, M., Zhong, W-W., Zollner, A., and Zumstein, E.
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- 1997
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15. Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: Rationale and design of the epidemiological studies within the IMI DIRECT Consortium
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Koivula, R.W., Heggie, A., Barnett, A., Cederberg, H., Hansen, T.H., Koopman, A.D., Ridderstråle, M., Rutters, F., Vestergaard, H., Gupta, R., Herrgård, S., Heymans, M.W., Perry, M.H., Rauh, S., Siloaho, M., Teare, H.J., Thorand, B., Bell, J., Brunak, S., Frost, G., Jablonka, B., Mari, A., McDonald, T.J., Dekker, J.M., Hansen, T., Hattersley, A., Laakso, M., Pedersen, O., Koivisto, V., Ruetten, H., Walker, M., Pearson, E., Franks, P.W., DIRECT Consortium (), Epidemiology and Data Science, EMGO - Lifestyle, overweight and diabetes, APH - Methodology, CCA - Immuno-pathogenesis, Methodology and Applied Biostatistics, and EMGO+ - Lifestyle, Overweight and Diabetes
- Subjects
Blood Glucose ,Male ,Gerontology ,Epigenetic ,Gene-environment Interaction ,Genome ,Glycaemic Control ,Lifestyle ,Microbiome ,Prediabetes ,Proteome ,Transcriptome ,Type 2 Diabetes ,Epidemiology ,Endocrinology, Diabetes and Metabolism ,Type 2 diabetes ,Disease ,0302 clinical medicine ,Pregnancy ,HISTORY ,Glycaemic control ,Prospective Studies ,POPULATION ,0303 health sciences ,education.field_of_study ,INSULIN SENSITIVITY ,Diabetes ,Middle Aged ,GOLDBERG CUTOFF ,3. Good health ,CARDIOVASCULAR-DISEASE ,HASH(0x5038388) ,Cohort ,Female ,Diabetes Mellitus, Type 2/blood ,Life Sciences & Biomedicine ,Adult ,medicine.medical_specialty ,ENDOCRINOLOGY & METABOLISM ,Population ,MEDLINE ,Hypoglycemic Agents/therapeutic use ,030209 endocrinology & metabolism ,Endocrinology and Diabetes ,Article ,03 medical and health sciences ,Blood Glucose/drug effects ,SDG 17 - Partnerships for the Goals ,SDG 3 - Good Health and Well-being ,Diabetes mellitus ,Internal Medicine ,medicine ,Humans ,Hypoglycemic Agents ,COHORT ,Gene–environment interaction ,education ,Intensive care medicine ,Aged ,030304 developmental biology ,Science & Technology ,business.industry ,CONSUMPTION ,medicine.disease ,Gene-environment interaction ,Epidemiologic Studies ,ENDOCRINOLOGY ,Diabetes Mellitus, Type 2 ,RISK-FACTORS ,GLUCOSE-TOLERANCE ,business ,Biomarkers/blood ,RESISTANCE ,Biomarkers - Abstract
Aims/hypothesis The DIRECT (Diabetes Research on Patient Stratification) Study is part of a European Union Framework 7 Innovative Medicines Initiative project, a joint undertaking between four industry and 21 academic partners throughout Europe. The Consortium aims to discover and validate biomarkers that: (1) predict the rate of glycaemic deterioration before and after type 2 diabetes onset; (2) predict the response to diabetes therapies; and (3) help stratify type 2 diabetes into clearly definable disease subclasses that can be treated more effectively than without stratification. This paper describes two new prospective cohort studies conducted as part of DIRECT. Methods Prediabetic participants (target sample size 2,200-2,700) and patients with newly diagnosed type 2 diabetes (target sample size similar to 1,000) are undergoing detailed metabolic phenotyping at baseline and 18 months and 36 months later. Abdominal, pancreatic and liver fat is assessed using MRI. Insulin secretion and action are assessed using frequently sampled OGTTs in non-diabetic participants, and frequently sampled mixed-meal tolerance tests in patients with type 2 diabetes. Biosamples include venous blood, faeces, urine and nail clippings, which, among other biochemical analyses, will be characterised at genetic, transcriptomic, metabolomic, proteomic and metagenomic levels. Lifestyle is assessed using high-resolution triaxial accelerometry, 24 h diet record, and food habit questionnaires. Conclusinos/interpretation DIRECT will yield an unprecedented array of biomaterials and data. This resource, available through managed access to scientists within and outside the Consortium, will facilitate the development of new treatments and therapeutic strategies for the prevention and management of type 2 diabetes. Aims/hypothesis: The DIRECT (Diabetes Research on Patient Stratification) Study is part of a European Union Framework 7 Innovative Medicines Initiative project, a joint undertaking between four industry and 21 academic partners throughout Europe. The Consortium aims to discover and validate biomarkers that: (1) predict the rate of glycaemic deterioration before and after type 2 diabetes onset; (2) predict the response to diabetes therapies; and (3) help stratify type 2 diabetes into clearly definable disease subclasses that can be treated more effectively than without stratification. This paper describes two new prospective cohort studies conducted as part of DIRECT. Methods: Prediabetic participants (target sample size 2,200-2,700) and patients with newly diagnosed type 2 diabetes (target sample size ~1,000) are undergoing detailed metabolic phenotyping at baseline and 18 months and 36 months later. Abdominal, pancreatic and liver fat is assessed using MRI. Insulin secretion and action are assessed using frequently sampled OGTTs in non-diabetic participants, and frequently sampled mixed-meal tolerance tests in patients with type 2 diabetes. Biosamples include venous blood, faeces, urine and nail clippings, which, among other biochemical analyses, will be characterised at genetic, transcriptomic, metabolomic, proteomic and metagenomic levels. Lifestyle is assessed using high-resolution triaxial accelerometry, 24 h diet record, and food habit questionnaires. Conclusions/interpretation: DIRECT will yield an unprecedented array of biomaterials and data. This resource, available through managed access to scientists within and outside the Consortium, will facilitate the development of new treatments and therapeutic strategies for the prevention and management of type 2 diabetes.
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- 2014
16. Association of maternal smoking during pregnancy with aerobic fitness of offspring in young adulthood: a prospective cohort study
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Hagnäs, MP, primary, Cederberg, H, additional, Jokelainen, J, additional, Mikkola, I, additional, Rajala, U, additional, and Keinänen-Kiukaanniemi, S, additional
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- 2015
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17. Relationship of physical activity, unacylated ghrelin and gene variation with changes in cardiovascular risk factors during military service
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Cederberg, H. (Henna), Keinänen-Kiukaanniemi, S. (Sirkka), and Laakso, M. (Markku)
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cardiovascular risk factors ,body composition ,obesity ,geenit ,physical activity ,sydän- ja verisuonitautien riskitekijät ,ylipaino ,liikunta ,ghrelin ,varusmiespalvelus ,greliini ,genes ,military ,kehonkoostumus - Abstract
The increase in the prevalence of overweight and obesity parallels the increase in physical inactivity and sedentary lifestyle, and leads to the worsening of cardiorespiratory fitness. Both overweight and physical inactivity are recognised risk factors for the development of cardiovascular disease, insulin resistance and type 2 diabetes, but the independent effects of cardiorespiratory fitness and obesity on cardiovascular risk factors remain debated. Lifestyle interventions are the key treatment for overweight and obesity. There are however, limited data from large population-based studies on the efficacy of exercise in modifying cardiovascular risk factors in young adults. Many of the mechanisms underlying the changes in body composition and metabolism achieved by exercise interventions are not well understood. The role of adipokines, and particularly unacylated ghrelin has been proposed in relation to changes in glucose metabolism. Individuals also vary in their response to exercise, which is, at least in part, explained by genetic factors. Improved understanding of the gene-exercise interaction is needed for the development of more targeted intervention strategies. In Finland, military service is compulsory for men. Military service includes large amounts of physical exercise but no dietary restriction. The current study evaluated the health benefits of exercise in young men attending military service in the Sodankylä Jaeger Brigade from 2005 to 2006 (N=1,112, mean age 19.2 years). Changes in endurance and strength performance, body composition, cardiometabolic risk factors and unacylated ghrelin levels were recorded at the beginning and end of the military service (6 to 12 months follow-up). Improvement in cardiometabolic risk factors was observed with improved exercise performance, an association which was attributable to changes in weight and waist circumference. Increase in unacylated ghrelin level was associated with beneficial changes in body composition and fat distribution, as well as in lipid and glucose metabolism. Significant gene-exercise interactions were observed for variants in PPARG, IRS1 and TCF7L2 on changes in weight and/or body composition. This study shows the efficacy of physical activity for the improvement of cardiometabolic health among young men. It shows that unacylated ghrelin plays an important role in the improvement of body composition, and glucose and lipid metabolism achieved by exercise. Finally, the harmful effects of common genetic variants on body composition can be counteracted by improvement in exercise performance. Tiivistelmä Viimeaikaiset tutkimukset ovat osoittaneet, että väestötasolla ylipaino ja lihavuus lisääntyvät ja liikunta vähenee. Sekä ylipaino että vähäinen liikunta ovat tunnettuja sydän- ja verisuonitautien, insuliiniresistenssin ja tyypin 2 diabeteksen vaaratekijöitä. Monet interventiotutkimukset ovat osoittaneet, että elämäntapamuutokset ovat avainasemassa ylipainon ja lihavuuden hoidossa. Suurista väestöpohjaisista tutkimuksista saatu tieto liikunnan vaikutuksista nuorten aikuisten sydän- ja verisuonitautien vaaratekijöihin, kehonkoostumukseen ja aineenvaihduntaan on kuitenkin vähäistä. Greliinillä on ehdotettu olevan tärkeitä vaikutuksia glukoosiaineenvaihduntaan, mutta greliinin ja liikunnan yhteisvaikutuksista aineenvaihdunnan ja kehon muutoksiin on vain vähän tietoa. Vasteessa liikunta-interventioihin on lisäksi yksilökohtaisia eroja, jotka saattavat ainakin osittain selittyä geneettisillä tekijöillä. Näin ollen lisätieto geenien ja liikunnan välisistä interaktioista on tärkeää uusien, yksilökohtaisten hoitomuotojen kehittämiseksi. Varusmiespalvelus on maassamme pakollinen kaikille miehille, ja siihen sisältyy huomattava määrä liikuntaa ilman merkittäviä muutoksia ruokavaliossa. Tässä tutkimuksessa selvitettiin varusmiespalveluksen aikana tapahtuvan liikunnan ja kuntomuutosten terveyshyötyjä. Tutkimusaineiston muodostivat Sodankylän Jääkäriprikaatissa vuonna 2005 palvelukseen astuneet miehet (N=1112, keski-ikä 19.2 vuotta). Muutokset kestävyys- ja lihaskunnossa, kehonkoostumuksessa, sydän- ja verisuonisairauksien vaaratekijöissä, sekä asyloimattoman greliinin plasmatasoissa määritettiin palveluksen alussa ja lopussa (seuranta-aika 6–12 kk). Parantuneen fyysisen suorituskyvyn todettiin vaikuttavan edullisesti sydän- ja verisuonisairauksien vaaratekijöihin, joka liittyi samanaikaiseen painonlaskuun ja keskivartalolihavuuden vähenemiseen. Liikunnan ansiosta asyloimattoman greliinin plasmataso lisääntyi ja se oli yhteydessä edullisiin muutoksiin kehonkoostumuksessa ja rasvanjakautumisessa sekä glukoosi- ja lipidiaineenvaihdunnassa. Tärkeitä geeni-liikunta interaktioita todettiin insuliiniherkkyyttä säätelevien geenien (PPARG, IRS1 ja TCF7L2) vaikutuksissa painon ja/tai kehonkoostumuksen muutoksiin. Tutkimus osoitti liikunnan edullisen vaikutuksen nuorten miesten sydän- ja verisuonitautien vaaratekijöiden tasoihin. Tutkimus osoitti lisäksi, että liikunnan aiheuttamalla lisääntyneen asyloimattoman greliinin pitoisuudella oli edullisia vaikutuksia kehonkoostumukseen sekä glukoosi- ja lipidiaineenvaihduntaan. Myös insuliiniresistenssiä säätelevien geenien epäedullinen vaikutus kehonkoostumukseen väheni parantuneen fyysisen suorituskyvyn myötä.
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- 2011
18. The DEXLIFE study methods: Identifying novel candidate biomarkers that predict progression to type 2 diabetes in high risk individuals
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Andersen, G.S., primary, Thybo, T., additional, Cederberg, H., additional, Orešič, M., additional, Esteller, M., additional, Zorzano, A., additional, Carr, B., additional, Walker, M., additional, Cobb, J., additional, Clissmann, C., additional, O’Gorman, D.J., additional, and Nolan, J.J., additional
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- 2014
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19. Family history of type 2 diabetes increases the risk of both obesity and its complications: is type 2 diabetes a disease of inappropriate lipid storage?
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Cederberg, H., primary, Stančáková, A., additional, Kuusisto, J., additional, Laakso, M., additional, and Smith, U., additional
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- 2014
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20. Relationship of physical activity, unacylated ghrelin and gene variation with changes in cardiovascular risk factors during military service
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Keinänen-Kiukaanniemi, S. (Sirkka), Laakso, M. (Markku), Cederberg, H. (Henna), Keinänen-Kiukaanniemi, S. (Sirkka), Laakso, M. (Markku), and Cederberg, H. (Henna)
- Abstract
The increase in the prevalence of overweight and obesity parallels the increase in physical inactivity and sedentary lifestyle, and leads to the worsening of cardiorespiratory fitness. Both overweight and physical inactivity are recognised risk factors for the development of cardiovascular disease, insulin resistance and type 2 diabetes, but the independent effects of cardiorespiratory fitness and obesity on cardiovascular risk factors remain debated. Lifestyle interventions are the key treatment for overweight and obesity. There are however, limited data from large population-based studies on the efficacy of exercise in modifying cardiovascular risk factors in young adults. Many of the mechanisms underlying the changes in body composition and metabolism achieved by exercise interventions are not well understood. The role of adipokines, and particularly unacylated ghrelin has been proposed in relation to changes in glucose metabolism. Individuals also vary in their response to exercise, which is, at least in part, explained by genetic factors. Improved understanding of the gene-exercise interaction is needed for the development of more targeted intervention strategies. In Finland, military service is compulsory for men. Military service includes large amounts of physical exercise but no dietary restriction. The current study evaluated the health benefits of exercise in young men attending military service in the Sodankylä Jaeger Brigade from 2005 to 2006 (N=1,112, mean age 19.2 years). Changes in endurance and strength performance, body composition, cardiometabolic risk factors and unacylated ghrelin levels were recorded at the beginning and end of the military service (6 to 12 months follow-up). Improvement in cardiometabolic risk factors was observed with improved exercise performance, an association which was attributable to changes in weight and waist circumference. Increase in unacylated ghrelin level was associated with beneficial changes in body comp, Tiivistelmä Viimeaikaiset tutkimukset ovat osoittaneet, että väestötasolla ylipaino ja lihavuus lisääntyvät ja liikunta vähenee. Sekä ylipaino että vähäinen liikunta ovat tunnettuja sydän- ja verisuonitautien, insuliiniresistenssin ja tyypin 2 diabeteksen vaaratekijöitä. Monet interventiotutkimukset ovat osoittaneet, että elämäntapamuutokset ovat avainasemassa ylipainon ja lihavuuden hoidossa. Suurista väestöpohjaisista tutkimuksista saatu tieto liikunnan vaikutuksista nuorten aikuisten sydän- ja verisuonitautien vaaratekijöihin, kehonkoostumukseen ja aineenvaihduntaan on kuitenkin vähäistä. Greliinillä on ehdotettu olevan tärkeitä vaikutuksia glukoosiaineenvaihduntaan, mutta greliinin ja liikunnan yhteisvaikutuksista aineenvaihdunnan ja kehon muutoksiin on vain vähän tietoa. Vasteessa liikunta-interventioihin on lisäksi yksilökohtaisia eroja, jotka saattavat ainakin osittain selittyä geneettisillä tekijöillä. Näin ollen lisätieto geenien ja liikunnan välisistä interaktioista on tärkeää uusien, yksilökohtaisten hoitomuotojen kehittämiseksi. Varusmiespalvelus on maassamme pakollinen kaikille miehille, ja siihen sisältyy huomattava määrä liikuntaa ilman merkittäviä muutoksia ruokavaliossa. Tässä tutkimuksessa selvitettiin varusmiespalveluksen aikana tapahtuvan liikunnan ja kuntomuutosten terveyshyötyjä. Tutkimusaineiston muodostivat Sodankylän Jääkäriprikaatissa vuonna 2005 palvelukseen astuneet miehet (N=1112, keski-ikä 19.2 vuotta). Muutokset kestävyys- ja lihaskunnossa, kehonkoostumuksessa, sydän- ja verisuonisairauksien vaaratekijöissä, sekä asyloimattoman greliinin plasmatasoissa määritettiin palveluksen alussa ja lopussa (seuranta-aika 6–12 kk). Parantuneen fyysisen suorituskyvyn todettiin vaikuttavan edullisesti sydän- ja verisuonisairauksien vaaratekijöihin, joka liittyi samanaikaiseen painonlaskuun ja keskivartalolihavuuden vähenemiseen. Liikunnan ansiosta asyloimattoman greliinin plasmataso lisääntyi ja se oli yhteydessä edullisiin muutoksiin kehonkoostumuks
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- 2011
21. Association of maternal smoking during pregnancy with aerobic fitness of offspring in young adulthood: a prospective cohort study.
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Hagnäs, MP, Cederberg, H, Jokelainen, J, Mikkola, I, Rajala, U, Keinänen‐Kiukaanniemi, S, Hagnäs, M P, and Keinänen-Kiukaanniemi, S
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- *
EXERCISE for pregnant women , *PREGNANT women , *WOMEN'S tobacco use , *WEIGHT gain in pregnancy , *BODY mass index , *PREGNANCY complications , *ADULT children , *EXERCISE tests , *LONGITUDINAL method , *PASSIVE smoking , *PHYSICAL fitness , *PRENATAL exposure delayed effects - Abstract
Objective: We evaluated the association of maternal pre-pregnancy body mass index (BMI), gestational weight gain (GWG), and maternal smoking with aerobic fitness in young men aged 19-20 years.Design: A 19-year prospective cohort study.Setting: Data from the Northern Finland Birth Cohort 1986 (NFBC 1986) and the Sodankylä Jaeger Brigade, Finland, in 2005-6.Population: Mothers and the 508 offspring in the NFBC 1986 who entered military service at the Sodankylä Jaeger Brigade in 2005.Methods: Associations of weight, 12-minute running test (Cooper test), and muscle fitness index (MFI) of offspring on entry to military service were evaluated with antenatal factors, including maternal smoking, pre-pregnancy BMI, and GWG.Main Outcome Measures: Aerobic and muscle fitness of the offspring were evaluated by the Cooper test and MFI.Results: Maternal smoking during pregnancy was associated with lower aerobic fitness of male adolescents, measured by the Cooper test (2356 m; 95% confidence interval, 95% CI 2265-2446 m), compared with the offspring of mothers who did not smoke during pregnancy (2537 m, 95% CI 2499-2574 m). This association was independent of the BMIs of both the mother and the offspring, GWG, and the smoking and physical activity of offspring (regression coefficient -140.6 m, 95% CI -273.1 to -8.0 m). High maternal pre-pregnancy BMI and excessive GWG were also associated with lower aerobic fitness of the offspring; however, this association was mediated via the weight of the offspring.Conclusions: Maternal smoking during pregnancy may have a negative impact on the aerobic fitness of the offspring.Tweetable Abstract: Study shows that young men have lower aerobic fitness if their mothers smoked during pregnancy. [ABSTRACT FROM AUTHOR]- Published
- 2016
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22. RE: DNA damage detected by the alkaline comet assay in the liver of mice after oral administration of tetrachloroethylene. (Mutagenesis, 25, 133-138, 2010)
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Cederberg, H., primary, Henriksson, J., additional, and Binderup, M.-L., additional
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- 2010
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23. DNA damage detected by the alkaline comet assay in the liver of mice after oral administration of tetrachloroethylene
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Cederberg, H., primary, Henriksson, J., additional, and Binderup, M.-L., additional
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- 2009
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24. The complete sequence of the yeast chromosome III
- Author
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Oliver, S. G., van der Aart, Q. J. M., Agostoni Carbone, M. L., Aigle, M., Alberghina, L., Alexandraki, D., Antoine, G., Anwar, R., Ballesta, J. P. G., Benit, P., Berben, G., Bergantino, Elisabetta, Biteau, N., Bolle, P. A., Bolotin Fukuhara, M., Brown, A., Brown, A. J. P., Buhler, J. M., Carcano, C., Carignani, G., Cederberg, H., Chanet, R., Contreras, R., Crouzet, M., Daignan Fornier, B., Defoor, E., Delgado, M., Demolder, J., Doira, C., Dubois, E., Dujon, B., Dusterhoft, A., Erdmann, D., Esteban, M., Fabre, F., Fairhead, C., Faye, G., Feldmann, H., Fiers, W., Francingues Gaillard, M. C., Franco, L., Frontali, L., Fukuhara, H., Fuller, L. J., Galland, P., Gent, M. E., Gigot, D., Gilliquet, V., Glansdorff, N., Goffeau, A., Grenson, M., Grisanti, P., Grivell, L. A., de Haan, M., Haasemann, M., Hatat, D., Hoenicka, J., Hegemann, J., Herbert, C. J., Hilger, F., Hohmann, S., Hollenberg, C. P., Huse, K., Iborra, F., Indje, K. J., Isono, K., Jacq, C., Jacquet, M., James, C. M., Jauniaux, J. C., Jia, Y., Jimenez, A., Kelly, A., Kleinhans, U., Kreisl, P., Lanfranchi, Gerolamo, Lewis, C, Vanderlinden, C. G., Lucchini, G., Lutzenkirchen, K, Maat, M. J., Mallet, L., Mannhaupet, G., Martegani, E., Mathieu, A., Maurer, C. T. C., Mcconnell, D., Mckee, R. A., Messenguy, F., Mewes, H. W., Molemans, F., Montague, M. A., Muzi Falconi, M., Navas, L., Newlon, C. S., Noone, D., Pallier, C., Panzeri, L., Pearson, B. M., Perea, J., Philippsen, P., Pierard, A., Planta, R. J., Plevani, P., Poetsch, B., Pohl, F., Purnelle, B., Ramezani Rad, M., Rasmussen, S. W., Raynal, A., Remacha, M., Richterich, P., Roberts, A. B., Rodriguez, F., Sanz, E., Schaaff Gerstenschlager, I., Scherens, B., Schweitzer, B., Shu, Y., Skala, J., Slonimski, P. P., Sor, F., Soustelle, C., Spiegelberg, R., Stateva, L. I., Steensma, S., Steiner, H. Y., Thierry, A., Thireos, G., Tzermia, M., Urrestarazu, L. A., Valle, Giorgio, Vetter, I., van Vliet Reedijk, J. C., Voet, M., Volckaert, G., Vreken, P., Wang, H., Warmington, J. R., von Wettstein, D., Wicksteed, B. L., Wilson, C., Wurst, H., Xu, G., Yoshikawa, A., Zimmermann, F. K., and Sgouros, J. G.
- Published
- 1992
25. Polychlorinated biphenyls induce meiotic length mutations at the human minisatellite MS32 in yeast
- Author
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Appelgren, Henrik, primary, Hedenskog, Mona, additional, Sandstr�m, Charlotte, additional, Cederberg, H�kan, additional, and Rannug, Ulf, additional
- Published
- 1999
- Full Text
- View/download PDF
26. Somatic recombination, gene amplification and cancer
- Author
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Ramel, C, primary, Cederberg, H, additional, Magnusson, J, additional, Vogel, E, additional, Natarajan, A.T, additional, Mullender, L.H, additional, Nivard, J.M, additional, Parry, J.M, additional, Leyson, A, additional, Comendador, M.A, additional, Sierra, L.M, additional, Ferreiro, J.A, additional, and Consuegra, S, additional
- Published
- 1996
- Full Text
- View/download PDF
27. Certain tryptophan photoproducts are inhibitors of cytochrome p450-dependent mtuagenicity
- Author
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Rannug, U., primary, Agurell, E., additional, Rannug, A., additional, and Cederberg, H., additional
- Published
- 1992
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- View/download PDF
28. Cardiometabolic profile of people screened for high risk of type 2 diabetes in a national diabetes prevention programme (FIN-D2D)
- Author
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Saaristo T, Moilanen L, Jokelainen J, Korpi-Hyövälti E, Vanhala M, Saltevo J, Niskanen L, Peltonen M, Oksa H, Cederberg H, Tuomilehto J, Uusitupa M, and Keinänen-Kiukaanniemi S
- Published
- 2010
- Full Text
- View/download PDF
29. Postchallenge glucose, A1C, and fasting glucose as predictors of type 2 diabetes and cardiovascular disease: a 10-year prospective cohort study.
- Author
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Cederberg H, Saukkonen T, Laakso M, Jokelainen J, Härkönen P, Timonen M, Keinänen-Kiukaanniemi S, Rajala U, Cederberg, Henna, Saukkonen, Tuula, Laakso, Mauri, Jokelainen, Jari, Härkönen, Pirjo, Timonen, Markku, Keinänen-Kiukaanniemi, Sirkka, and Rajala, Ulla
- Abstract
Objective: A1C has been proposed as a new indicator for high risk of type 2 diabetes. The long-term predictive power and comparability of elevated A1C with the currently used high-risk indicators remain unclear. We assessed A1C, impaired glucose tolerance (IGT), and impaired fasting glucose (IFG) as predictors of type 2 diabetes and cardiovascular disease (CVD) at 10 years.Research Design and Methods: This prospective population-based study of 593 inhabitants from northern Finland, born in 1935, was conducted between 1996 and 2008. An oral glucose tolerance test (OGTT) was conducted at baseline and follow-up, and A1C was determined at baseline. Those with a history of diabetes were excluded from the study. Elevated A1C was defined as 5.7-6.4%. Incident type 2 diabetes was confirmed by two OGTTs. Cardiovascular outcome was measured as incident CVD or CVD mortality. Multivariate log-binomial regression models were used to predict diabetes, CVD, and CVD mortality at 10 years. Receiver operating characteristic curves compared predictive values of A1C, IGT, and IFG.Results: Incidence of diabetes during the follow-up was 17.1%. Two of three of the cases of newly diagnosed diabetes were predicted by a raise in >or=1 of the markers. Elevated A1C, IGT, or IFG preceded diabetes in 32.8, 40.6, and 21.9%, respectively. CVD was predicted by an intermediate and diabetic range of 2-h glucose but only by diabetic A1C levels in women.Conclusions: A1C predicted 10-year risk of type 2 diabetes at a range of A1C 5.7-6.4% but CVD only in women at A1C >or=6.5%. [ABSTRACT FROM AUTHOR]- Published
- 2010
- Full Text
- View/download PDF
30. Genotoxic effects of ethylene oxide and propylene oxide: a comparative study
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Agurell, Eva, primary, Cederberg, H., additional, Ehrenberg, L., additional, Lindahl-Kiessling, Kerstin, additional, Rannug, U., additional, and Törnqvist, Margareta, additional
- Published
- 1991
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- View/download PDF
31. Perspective. Some biological actions of alkylglycerols from shark liver oil.
- Author
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Pugliese PT, Jordan K, Cederberg H, and Brohult J
- Abstract
Shark liver oil has been used for over 40 years as both a therapeutic and preventive agent. The active ingredients in shark liver oil have been found to be a group of ether-linked glycerols known as alkylglycerols. Initial clinical use was for treating leukemias, and later to prevent radiation sickness from cancer x-ray therapy. Studies over the last 30 years have shown that alkylglycerols are multifunctional. The level of natural alkylglycerols rises within tumor cells, apparently in an effort to control cell growth. Recent studies indicate that the activation of protein kinase C, an essential step in cell proliferation, can be inhibited by alkylglycerols. This action suggests a competitive inhibition of 1.2-diacylglycerol by alkylglycerols. Further studies on the immunostimulatory action of alkylglycerols suggest a primary action on the macrophage. The process of macrophage activation has been demonstrated with both synthetic and natural alkylglycerols. While the exact mechanism has not been found, both an autocrine and paracrine system have been suggested. Shark liver is a major natural source of alkylglycerols, which have no known side effects in dosages of 100 mg three times a day. The information presented in this article suggests that alkylglycerols may be used both as an adjunct therapy in the treatment of neoplastic disorders and as an immune booster in infectious diseases. [ABSTRACT FROM AUTHOR]
- Published
- 1998
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- View/download PDF
32. Ueber das Glycyrrhizin.
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Tschirch, A. and Cederberg, H.
- Published
- 1907
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- View/download PDF
33. Meiotic interallelic conversion at the human minisatellite MS32 in yeast triggers recombination in several chromatids
- Author
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Appelgren, H., Cederberg, H., and Rannug, U.
- Published
- 1999
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- View/download PDF
34. Cis-regulation of inter-allelic exchanges in mutation at human minisatellite MS205 in yeast
- Author
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He, Q., Cederberg, H., Armour, J.A.L., May, C.A., and Rannug, U.
- Published
- 1999
- Full Text
- View/download PDF
35. Association of Ketone Body Levels With Hyperglycemia and Type 2 Diabetes in 9,398 Finnish Men
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Paananen, J., Collins, F. S., Boehnke, M., Soininen, P., Pihlajamaki, J., Cederberg, H., Vangipurapu, J., Civelek, M., Pajukanta, P., Mohlke, K. L., Lusis, A. J., Morken, M. A., Laakso, M., Mahendran, Y., Bonnycastle, L. L., Stancakova, A., Ala-Korpela, M., Kangas, A. J., Saleem, N. K., and Kuusisto, J.
- Subjects
3. Good health - Abstract
We investigated the association of the levels of ketone bodies (KBs) with hyperglycemia and with 62 genetic risk variants regulating glucose levels or type 2 diabetes in the population-based Metabolic Syndrome in Men (METSIM) study, including 9,398 Finnish men without diabetes or newly diagnosed type 2 diabetes. Increasing fasting and 2-h plasma glucose levels were associated with elevated levels of acetoacetate (AcAc) and β-hydroxybutyrate (BHB). AcAc and BHB predicted an increase in the glucose area under the curve in an oral glucose tolerance test, and AcAc predicted the conversion to type 2 diabetes in a 5-year follow-up of the METSIM cohort. Impaired insulin secretion, but not insulin resistance, explained these findings. Of the 62 single nucleotide polymorphisms associated with the risk of type 2 diabetes or hyperglycemia, the glucose-increasing C allele of GCKR significantly associated with elevated levels of fasting BHB levels. Adipose tissue mRNA expression levels of genes involved in ketolysis were significantly associated with insulin sensitivity (Matsuda index). In conclusion, high levels of KBs predicted subsequent worsening of hyperglycemia, and a common variant of GCKR was significantly associated with BHB levels.
36. The complete DNA sequence of yeast chromosome III
- Author
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Oliver, S. G., Aart, Q. J. M., Agostoni-Carbone, M. L., Aigle, M., Alberghina, L., Alexandraki, D., Antoine, G., Anwar, R., Ballesta, J. P. G., Benit, P., Berben, G., Bergantino, E., Biteau, N., Bolle, P. A., Bolotin-Fukuhara, M., Brown, A., Brown, A. J. P., Buhler, J. M., Carcano, C., Carignani, G., Cederberg, H., Chanet, R., Contreras, R., Crouzet, M., Daignan-Fornier, B., Defoor, E., Delgado, M., Demolder, J., Doira, C., Dubois, E., Dujon, B., Dusterhoft, A., Erdmann, D., Esteban, M., Fabre, F., Fairhead, C., Faye, G., Feldmann, H., Fiers, W., Francingues-Gaillard, M. C., Franco, L., Frontali, L., Fukuhara, H., Fuller, L. J., Galland, P., Gent, M. E., Gigot, D., Gilliquet, V., Glansdorff, N., Goffeau, A., Grenson, M., Grisanti, P., Grivell, L. A., Haan, M., Haasemann, M., Hatat, D., Hoenicka, J., Hegemann, J., Herbert, C. J., Hilger, F., Hohmann, S., Hollenberg, C. P., Huse, K., Iborra, F., Indge, K. J., Isono, K., Jacq, C., Jacquet, M., James, C. M., Jauniaux, J. C., Jia, Y., Jimenez, A., Kelly, A., Kleinhans, U., Kreisl, P., Lanfranchi, G., Lewis, C., Linden, C. G., Lucchini, G., Lutzenkirchen, K., Maat, M. J., Mallet, L., Mannhaupt, G., Martegani, E., Mathieu, A., Maurer, C. T. C., Mcconnell, D., Mckee, R. A., Messenguy, F., Mewes, H. W., Molemans, F., Montague, M. A., Falconi, M. M., Navas, L., Newlon, C. S., Noone, D., Pallier, C., Panzeri, L., and Pearson, B. M.
37. Computation of creep effects in prestressed concrete pressure vessels using dynamic relaxation
- Author
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Cederberg, H., primary and David, M., additional
- Published
- 1969
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- View/download PDF
38. Effects of bleomycin in somatic mutation and recombination test in Drosophila
- Author
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Cederberg, H
- Published
- 1988
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39. Induction of the mixed function oxygenase system in the somatic mutation and recombination test in Drosophila
- Author
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Magnusson, J., Cederberg, H., and Ramel, C.
- Published
- 1988
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- View/download PDF
40. Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits.
- Author
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Brown AA, Fernandez-Tajes JJ, Hong MG, Brorsson CA, Koivula RW, Davtian D, Dupuis T, Sartori A, Michalettou TD, Forgie IM, Adam J, Allin KH, Caiazzo R, Cederberg H, De Masi F, Elders PJM, Giordano GN, Haid M, Hansen T, Hansen TH, Hattersley AT, Heggie AJ, Howald C, Jones AG, Kokkola T, Laakso M, Mahajan A, Mari A, McDonald TJ, McEvoy D, Mourby M, Musholt PB, Nilsson B, Pattou F, Penet D, Raverdy V, Ridderstråle M, Romano L, Rutters F, Sharma S, Teare H, 't Hart L, Tsirigos KD, Vangipurapu J, Vestergaard H, Brunak S, Franks PW, Frost G, Grallert H, Jablonka B, McCarthy MI, Pavo I, Pedersen O, Ruetten H, Walker M, Adamski J, Schwenk JM, Pearson ER, Dermitzakis ET, and Viñuela A
- Subjects
- Humans, Phenotype, RNA, Messenger, Research Personnel, Multifactorial Inheritance, Genomics
- Abstract
We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue., (© 2023. Springer Nature Limited.)
- Published
- 2023
- Full Text
- View/download PDF
41. 22-year trends in dysglycemia and body mass index: A population-based cohort study in Savitaipale, Finland.
- Author
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Saramies J, Koiranen M, Auvinen J, Uusitalo H, Hussi E, Cederberg H, Keinänen-Kiukaanniemi S, and Tuomilehto J
- Subjects
- Body Mass Index, Cohort Studies, Female, Finland epidemiology, Follow-Up Studies, Humans, Male, Middle Aged, Prospective Studies, Risk Factors, Diabetes Mellitus, Type 2 diagnosis, Diabetes Mellitus, Type 2 epidemiology
- Abstract
Aims: We describe a 22-year prospective observational population-based study that determined the prevalence and incidence of type 2 diabetes (T2D) and intermediate hyperglycaemia (IH), obesity, hypertension, and disorders of lipid metabolism in a middle-age population in the Finnish municipality of Savitaipale., Methods: 1151 people participated in the baseline survey in 1996-1999, following two follow-up examinations, in 2007-2008 and 2018-2019. Follow-up studies comprised clinical measurements, 2-h oral glucose tolerance test and other biochemistry, questionnaires, and registry data., Results: The prevalence of T2D quadrupled to 27% and the proportion of normoglycemic people decreased from 73% to 44% while IH increased only slightly during the 22-year follow-up. A large proportion of people who died between the surveys were diabetic. The mean body mass index (BMI) did not, whereas mean waist circumference increased significantly, by 5-6 cm (P = 0.001) during the 22 years. Systolic blood pressure increased by 13-15 mmHg from baseline (P = 0.0001) but diastolic blood pressure did not. The mean plasma levels of total and LDL-cholesterol decreased 10.8% and 8.9% in women (P = 0.001), 21.5% and 22.2% in men (P = 0.001), respectively, while HDL-cholesterol and triglycerides remained stable. The proportion of those achieving targets in the treatment of dyslipidaemia increased significantly (P < 0.001)., Conclusions: In this 22-year prospective follow-up study of in middle-aged Europeans with high participation rates, the progression of dysglycaemia to overt diabetes with aging was rapid, even without a significant change in BMI., (Copyright © 2021 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)
- Published
- 2021
- Full Text
- View/download PDF
42. Profiles of Glucose Metabolism in Different Prediabetes Phenotypes, Classified by Fasting Glycemia, 2-Hour OGTT, Glycated Hemoglobin, and 1-Hour OGTT: An IMI DIRECT Study.
- Author
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Tura A, Grespan E, Göbl CS, Koivula RW, Franks PW, Pearson ER, Walker M, Forgie IM, Giordano GN, Pavo I, Ruetten H, Dermitzakis ET, McCarthy MI, Pedersen O, Schwenk JM, Adamski J, De Masi F, Tsirigos KD, Brunak S, Viñuela A, Mahajan A, McDonald TJ, Kokkola T, Vangipurapu J, Cederberg H, Laakso M, Rutters F, Elders PJM, Koopman ADM, Beulens JW, Ridderstråle M, Hansen TH, Allin KH, Hansen T, Vestergaard H, and Mari A
- Subjects
- Adult, Aged, Blood Glucose, Fasting blood, Female, Glucose Tolerance Test, Humans, Insulin Secretion, Male, Middle Aged, Phenotype, Glucose metabolism, Glucose Intolerance metabolism, Glycated Hemoglobin analysis, Insulin Resistance physiology, Prediabetic State metabolism
- Abstract
Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants ( N = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA
1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA1c indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). β-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISRr ), and insulin secretion potentiation ( P < 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISRr ( P < 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, P < 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence., (© 2021 by the American Diabetes Association.)- Published
- 2021
- Full Text
- View/download PDF
43. Genome-Wide Association Analysis of Pancreatic Beta-Cell Glucose Sensitivity.
- Author
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Deshmukh HA, Madsen AL, Viñuela A, Have CT, Grarup N, Tura A, Mahajan A, Heggie AJ, Koivula RW, De Masi F, Tsirigos KK, Linneberg A, Drivsholm T, Pedersen O, Sørensen TIA, Astrup A, Gjesing AAP, Pavo I, Wood AR, Ruetten H, Jones AG, Koopman ADM, Cederberg H, Rutters F, Ridderstrale M, Laakso M, McCarthy MI, Frayling TM, Ferrannini E, Franks PW, Pearson ER, Mari A, Hansen T, and Walker M
- Subjects
- Adult, Aged, Case-Control Studies, Cohort Studies, Diabetes Mellitus, Type 2 epidemiology, Diabetes Mellitus, Type 2 genetics, Diabetes Mellitus, Type 2 metabolism, Female, Genetic Predisposition to Disease, Genome-Wide Association Study statistics & numerical data, Glucose Intolerance epidemiology, Glucose Intolerance genetics, Glucose Intolerance metabolism, Glucose Tolerance Test, Humans, Insulin Secretion drug effects, Insulin-Secreting Cells metabolism, Insulin-Secreting Cells physiology, Male, Middle Aged, Pancreatic Function Tests statistics & numerical data, Polymorphism, Single Nucleotide, Prediabetic State epidemiology, Prediabetic State genetics, Prediabetic State metabolism, Glucose pharmacology, Insulin Secretion genetics, Insulin-Secreting Cells drug effects
- Abstract
Context: Pancreatic beta-cell glucose sensitivity is the slope of the plasma glucose-insulin secretion relationship and is a key predictor of deteriorating glucose tolerance and development of type 2 diabetes. However, there are no large-scale studies looking at the genetic determinants of beta-cell glucose sensitivity., Objective: To understand the genetic determinants of pancreatic beta-cell glucose sensitivity using genome-wide meta-analysis and candidate gene studies., Design: We performed a genome-wide meta-analysis for beta-cell glucose sensitivity in subjects with type 2 diabetes and nondiabetic subjects from 6 independent cohorts (n = 5706). Beta-cell glucose sensitivity was calculated from mixed meal and oral glucose tolerance tests, and its associations between known glycemia-related single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) SNPs were estimated using linear regression models., Results: Beta-cell glucose sensitivity was moderately heritable (h2 ranged from 34% to 55%) using SNP and family-based analyses. GWAS meta-analysis identified multiple correlated SNPs in the CDKAL1 gene and GIPR-QPCTL gene loci that reached genome-wide significance, with SNP rs2238691 in GIPR-QPCTL (P value = 2.64 × 10-9) and rs9368219 in the CDKAL1 (P value = 3.15 × 10-9) showing the strongest association with beta-cell glucose sensitivity. These loci surpassed genome-wide significance when the GWAS meta-analysis was repeated after exclusion of the diabetic subjects. After correction for multiple testing, glycemia-associated SNPs in or near the HHEX and IGF2B2 loci were also associated with beta-cell glucose sensitivity., Conclusion: We show that, variation at the GIPR-QPCTL and CDKAL1 loci are key determinants of pancreatic beta-cell glucose sensitivity., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Endocrine Society.)
- Published
- 2021
- Full Text
- View/download PDF
44. Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study.
- Author
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Gudmundsdottir V, Pedersen HK, Mazzoni G, Allin KH, Artati A, Beulens JW, Banasik K, Brorsson C, Cederberg H, Chabanova E, De Masi F, Elders PJ, Forgie I, Giordano GN, Grallert H, Gupta R, Haid M, Hansen T, Hansen TH, Hattersley AT, Heggie A, Hong MG, Jones AG, Koivula R, Kokkola T, Laakso M, Løngreen P, Mahajan A, Mari A, McDonald TJ, McEvoy D, Musholt PB, Pavo I, Prehn C, Ruetten H, Ridderstråle M, Rutters F, Sharma S, Slieker RC, Syed A, Tajes JF, Thomas CE, Thomsen HS, Vangipurapu J, Vestergaard H, Viñuela A, Wesolowska-Andersen A, Walker M, Adamski J, Schwenk JM, McCarthy MI, Pearson E, Dermitzakis E, Franks PW, Pedersen O, and Brunak S
- Subjects
- Cohort Studies, Gene Expression Regulation, Genome-Wide Association Study, Humans, Insulin, Insulin Resistance, Leukocytes, Diabetes Mellitus, Type 2 genetics, Diabetes Mellitus, Type 2 metabolism, Phenotype, Transcriptome
- Abstract
Background: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D., Methods: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts., Results: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling., Conclusions: Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.
- Published
- 2020
- Full Text
- View/download PDF
45. Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.
- Author
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Atabaki-Pasdar N, Ohlsson M, Viñuela A, Frau F, Pomares-Millan H, Haid M, Jones AG, Thomas EL, Koivula RW, Kurbasic A, Mutie PM, Fitipaldi H, Fernandez J, Dawed AY, Giordano GN, Forgie IM, McDonald TJ, Rutters F, Cederberg H, Chabanova E, Dale M, Masi F, Thomas CE, Allin KH, Hansen TH, Heggie A, Hong MG, Elders PJM, Kennedy G, Kokkola T, Pedersen HK, Mahajan A, McEvoy D, Pattou F, Raverdy V, Häussler RS, Sharma S, Thomsen HS, Vangipurapu J, Vestergaard H, 't Hart LM, Adamski J, Musholt PB, Brage S, Brunak S, Dermitzakis E, Frost G, Hansen T, Laakso M, Pedersen O, Ridderstråle M, Ruetten H, Hattersley AT, Walker M, Beulens JWJ, Mari A, Schwenk JM, Gupta R, McCarthy MI, Pearson ER, Bell JD, Pavo I, and Franks PW
- Subjects
- Diabetes Complications etiology, Female, Humans, Male, Middle Aged, Models, Statistical, Prospective Studies, Reproducibility of Results, Risk Assessment, Fatty Liver etiology, Machine Learning
- Abstract
Background: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning., Methods and Findings: We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (<5% or ≥5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Another key limitation of this study is that the prediction was done on a binary outcome of liver fat quantity (<5% or ≥5%) rather than a continuous one., Conclusions: In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community., Trial Registration: ClinicalTrials.gov NCT03814915., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: PWF is a consultant for Novo Nordisk, Lilly, and Zoe Global Ltd., and has received research grants from numerous diabetes drug companies. HR is an employee and shareholder of Sanofi. MIM: The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. MIM has served on advisory panels for Pfizer, NovoNordisk and Zoe Global, has received honoraria from Merck, Pfizer, Novo Nordisk and Eli Lilly, and research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier, and Takeda. As of June 2019, MIM is an employee of Genentech, and a holder of Roche stock. AM is a consultant for Lilly and has received research grants from several diabetes drug companies.
- Published
- 2020
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46. Future risk of metabolic syndrome in women with a previous LGA delivery stratified by gestational glucose tolerance: a prospective cohort study.
- Author
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Hakkarainen H, Huopio H, Cederberg H, Voutilainen R, and Heinonen S
- Subjects
- Adult, Case-Control Studies, Cohort Studies, Female, Finland epidemiology, Follow-Up Studies, Humans, Incidence, Pregnancy, Prospective Studies, Risk Factors, Young Adult, Diabetes, Gestational epidemiology, Fetal Macrosomia epidemiology, Metabolic Syndrome epidemiology
- Abstract
Background: Whether the delivery of a large-for-gestational-age (LGA) infant predicts future maternal metabolic syndrome (MetS) is not known. To this aim, we investigated the incidence of MetS and its components in women with or without a history of gestational diabetes mellitus (GDM) with a view to the birth weight of the offspring., Methods: Eight hundred seventy six women treated for their pregnancies in Kuopio University Hospital in 1989-2009 underwent a follow-up study (mean follow-up time 7.3 (SD 5.1) years), of whom 489 women with GDM and 385 normoglycemic controls. The women were stratified into two groups according to the newborn's birth weight: 10-90th percentile (appropriate-for-gestational-age; AGA) (n = 662) and > 90th percentile (LGA) (n = 116). MetS and its components were evaluated in the follow-up study according to the International Diabetes Federation criteria., Results: LGA vs. AGA delivery was associated with a higher incidence of MetS at follow-up in women with a background of GDM (54.4% vs. 43.6%), but not in women without GDM., Conclusion: An LGA delivery in women with GDM is associated with a higher risk of future MetS and this group is optimal to study preventive measures for MetS. In contrast, an LGA delivery after a normoglycemic pregnancy was not associated with an increased future maternal MetS risk.
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- 2018
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47. Delivery of an LGA infant and the maternal risk of diabetes: A prospective cohort study.
- Author
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Hakkarainen H, Huopio H, Cederberg H, Voutilainen R, and Heinonen S
- Subjects
- Adult, Biomarkers blood, Blood Glucose metabolism, Case-Control Studies, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 diagnosis, Diabetes, Gestational blood, Diabetes, Gestational diagnosis, Female, Finland, Gestational Age, Glucose Tolerance Test, Humans, Incidence, Infant, Newborn, Prediabetic State blood, Prediabetic State diagnosis, Pregnancy, Prognosis, Prospective Studies, Registries, Risk Assessment, Risk Factors, Time Factors, Young Adult, Birth Weight, Diabetes Mellitus, Type 2 epidemiology, Diabetes, Gestational epidemiology, Prediabetic State epidemiology
- Abstract
Aims: Was to determine whether the birth weight of the infant predicts prediabetes (impaired fasting glucose, impaired glucose tolerance, or both) and type 2 diabetes (T2DM) during long-term follow-up of women with or without gestational diabetes mellitus (GDM)., Methods: The women with or without GDM during their pregnancies in Kuopio University Hospital in 1989-2009 (n=876) were contacted and invited for an evaluation. They were stratified into two groups according to the newborn's birth weight: 10-90th percentile (appropriate-for-gestational-age; AGA) (n=662) and >90th percentile (large-for-gestational-age; LGA) (n=116). Glucose tolerance was investigated with an oral glucose tolerance test after a mean follow-up time of 7.3 (SD 5.1) years., Results: The incidence of T2DM was 11.8% and 0% in the women with and without GDM, respectively, after an LGA delivery. The incidence of prediabetes increased with offspring birth weight categories in the women with and without GDM: from 46.3% and 26.2% (AGA) to 52.9% and 29.2% (LGA), respectively., Conclusions: GDM women with LGA infants are at an increased risk for subsequent development of T2DM and therefore represent a target group for intervention to delay or prevent T2DM development. In contrast, an LGA delivery without GDM does not increase T2DM risk., (Copyright © 2018 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)
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- 2018
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48. Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.
- Author
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Zillikens MC, Demissie S, Hsu YH, Yerges-Armstrong LM, Chou WC, Stolk L, Livshits G, Broer L, Johnson T, Koller DL, Kutalik Z, Luan J, Malkin I, Ried JS, Smith AV, Thorleifsson G, Vandenput L, Hua Zhao J, Zhang W, Aghdassi A, Åkesson K, Amin N, Baier LJ, Barroso I, Bennett DA, Bertram L, Biffar R, Bochud M, Boehnke M, Borecki IB, Buchman AS, Byberg L, Campbell H, Campos Obanda N, Cauley JA, Cawthon PM, Cederberg H, Chen Z, Cho NH, Jin Choi H, Claussnitzer M, Collins F, Cummings SR, De Jager PL, Demuth I, Dhonukshe-Rutten RAM, Diatchenko L, Eiriksdottir G, Enneman AW, Erdos M, Eriksson JG, Eriksson J, Estrada K, Evans DS, Feitosa MF, Fu M, Garcia M, Gieger C, Girke T, Glazer NL, Grallert H, Grewal J, Han BG, Hanson RL, Hayward C, Hofman A, Hoffman EP, Homuth G, Hsueh WC, Hubal MJ, Hubbard A, Huffman KM, Husted LB, Illig T, Ingelsson E, Ittermann T, Jansson JO, Jordan JM, Jula A, Karlsson M, Khaw KT, Kilpeläinen TO, Klopp N, Kloth JSL, Koistinen HA, Kraus WE, Kritchevsky S, Kuulasmaa T, Kuusisto J, Laakso M, Lahti J, Lang T, Langdahl BL, Launer LJ, Lee JY, Lerch MM, Lewis JR, Lind L, Lindgren C, Liu Y, Liu T, Liu Y, Ljunggren Ö, Lorentzon M, Luben RN, Maixner W, McGuigan FE, Medina-Gomez C, Meitinger T, Melhus H, Mellström D, Melov S, Michaëlsson K, Mitchell BD, Morris AP, Mosekilde L, Newman A, Nielson CM, O'Connell JR, Oostra BA, Orwoll ES, Palotie A, Parker SCJ, Peacock M, Perola M, Peters A, Polasek O, Prince RL, Räikkönen K, Ralston SH, Ripatti S, Robbins JA, Rotter JI, Rudan I, Salomaa V, Satterfield S, Schadt EE, Schipf S, Scott L, Sehmi J, Shen J, Soo Shin C, Sigurdsson G, Smith S, Soranzo N, Stančáková A, Steinhagen-Thiessen E, Streeten EA, Styrkarsdottir U, Swart KMA, Tan ST, Tarnopolsky MA, Thompson P, Thomson CA, Thorsteinsdottir U, Tikkanen E, Tranah GJ, Tuomilehto J, van Schoor NM, Verma A, Vollenweider P, Völzke H, Wactawski-Wende J, Walker M, Weedon MN, Welch R, Wichmann HE, Widen E, Williams FMK, Wilson JF, Wright NC, Xie W, Yu L, Zhou Y, Chambers JC, Döring A, van Duijn CM, Econs MJ, Gudnason V, Kooner JS, Psaty BM, Spector TD, Stefansson K, Rivadeneira F, Uitterlinden AG, Wareham NJ, Ossowski V, Waterworth D, Loos RJF, Karasik D, Harris TB, Ohlsson C, and Kiel DP
- Abstract
A correction to this article has been published and is linked from the HTML version of this article.
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- 2017
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49. Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.
- Author
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Zillikens MC, Demissie S, Hsu YH, Yerges-Armstrong LM, Chou WC, Stolk L, Livshits G, Broer L, Johnson T, Koller DL, Kutalik Z, Luan J, Malkin I, Ried JS, Smith AV, Thorleifsson G, Vandenput L, Hua Zhao J, Zhang W, Aghdassi A, Åkesson K, Amin N, Baier LJ, Barroso I, Bennett DA, Bertram L, Biffar R, Bochud M, Boehnke M, Borecki IB, Buchman AS, Byberg L, Campbell H, Campos Obanda N, Cauley JA, Cawthon PM, Cederberg H, Chen Z, Cho NH, Jin Choi H, Claussnitzer M, Collins F, Cummings SR, De Jager PL, Demuth I, Dhonukshe-Rutten RAM, Diatchenko L, Eiriksdottir G, Enneman AW, Erdos M, Eriksson JG, Eriksson J, Estrada K, Evans DS, Feitosa MF, Fu M, Garcia M, Gieger C, Girke T, Glazer NL, Grallert H, Grewal J, Han BG, Hanson RL, Hayward C, Hofman A, Hoffman EP, Homuth G, Hsueh WC, Hubal MJ, Hubbard A, Huffman KM, Husted LB, Illig T, Ingelsson E, Ittermann T, Jansson JO, Jordan JM, Jula A, Karlsson M, Khaw KT, Kilpeläinen TO, Klopp N, Kloth JSL, Koistinen HA, Kraus WE, Kritchevsky S, Kuulasmaa T, Kuusisto J, Laakso M, Lahti J, Lang T, Langdahl BL, Launer LJ, Lee JY, Lerch MM, Lewis JR, Lind L, Lindgren C, Liu Y, Liu T, Liu Y, Ljunggren Ö, Lorentzon M, Luben RN, Maixner W, McGuigan FE, Medina-Gomez C, Meitinger T, Melhus H, Mellström D, Melov S, Michaëlsson K, Mitchell BD, Morris AP, Mosekilde L, Newman A, Nielson CM, O'Connell JR, Oostra BA, Orwoll ES, Palotie A, Parker SCJ, Peacock M, Perola M, Peters A, Polasek O, Prince RL, Räikkönen K, Ralston SH, Ripatti S, Robbins JA, Rotter JI, Rudan I, Salomaa V, Satterfield S, Schadt EE, Schipf S, Scott L, Sehmi J, Shen J, Soo Shin C, Sigurdsson G, Smith S, Soranzo N, Stančáková A, Steinhagen-Thiessen E, Streeten EA, Styrkarsdottir U, Swart KMA, Tan ST, Tarnopolsky MA, Thompson P, Thomson CA, Thorsteinsdottir U, Tikkanen E, Tranah GJ, Tuomilehto J, van Schoor NM, Verma A, Vollenweider P, Völzke H, Wactawski-Wende J, Walker M, Weedon MN, Welch R, Wichmann HE, Widen E, Williams FMK, Wilson JF, Wright NC, Xie W, Yu L, Zhou Y, Chambers JC, Döring A, van Duijn CM, Econs MJ, Gudnason V, Kooner JS, Psaty BM, Spector TD, Stefansson K, Rivadeneira F, Uitterlinden AG, Wareham NJ, Ossowski V, Waterworth D, Loos RJF, Karasik D, Harris TB, Ohlsson C, and Kiel DP
- Subjects
- 17-Hydroxysteroid Dehydrogenases genetics, ADAMTS Proteins genetics, Aldehyde Oxidoreductases genetics, Alpha-Ketoglutarate-Dependent Dioxygenase FTO genetics, Body Composition, Extracellular Matrix Proteins genetics, Humans, Insulin Receptor Substrate Proteins genetics, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Regulatory Elements, Transcriptional, Versicans genetics, Genome-Wide Association Study, Thinness genetics
- Abstract
Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 × 10
-8 ) or suggestively genome wide (p < 2.3 × 10-6 ). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass.Lean body mass is a highly heritable trait and is associated with various health conditions. Here, Kiel and colleagues perform a meta-analysis of genome-wide association studies for whole body lean body mass and find five novel genetic loci to be significantly associated.- Published
- 2017
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50. Predicting glycated hemoglobin levels in the non-diabetic general population: Development and validation of the DIRECT-DETECT prediction model - a DIRECT study.
- Author
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Rauh SP, Heymans MW, Koopman AD, Nijpels G, Stehouwer CD, Thorand B, Rathmann W, Meisinger C, Peters A, de Las Heras Gala T, Glümer C, Pedersen O, Cederberg H, Kuusisto J, Laakso M, Pearson ER, Franks PW, Rutters F, and Dekker JM
- Subjects
- Adult, Aged, Cohort Studies, Diabetes Mellitus, Type 2 blood, Female, Humans, Male, Middle Aged, Diabetes Mellitus, Type 2 epidemiology, Glycated Hemoglobin metabolism, Models, Statistical
- Abstract
Aims/hypothesis: To develop a prediction model that can predict HbA1c levels after six years in the non-diabetic general population, including previously used readily available predictors., Methods: Data from 5,762 initially non-diabetic subjects from three population-based cohorts (Hoorn Study, Inter99, KORA S4/F4) were combined to predict HbA1c levels at six year follow-up. Using backward selection, age, BMI, waist circumference, use of anti-hypertensive medication, current smoking and parental history of diabetes remained in sex-specific linear regression models. To minimize overfitting of coefficients, we performed internal validation using bootstrapping techniques. Explained variance, discrimination and calibration were assessed using R2, classification tables (comparing highest/lowest 50% HbA1c levels) and calibration graphs. The model was externally validated in 2,765 non-diabetic subjects of the population-based cohort METSIM., Results: At baseline, mean HbA1c level was 5.6% (38 mmol/mol). After a mean follow-up of six years, mean HbA1c level was 5.7% (39 mmol/mol). Calibration graphs showed that predicted HbA1c levels were somewhat underestimated in the Inter99 cohort and overestimated in the Hoorn and KORA cohorts, indicating that the model's intercept should be adjusted for each cohort to improve predictions. Sensitivity and specificity (95% CI) were 55.7% (53.9, 57.5) and 56.9% (55.1, 58.7) respectively, for women, and 54.6% (52.7, 56.5) and 54.3% (52.4, 56.2) for men. External validation showed similar performance in the METSIM cohort., Conclusions/interpretation: In the non-diabetic population, our DIRECT-DETECT prediction model, including readily available predictors, has a relatively low explained variance and moderate discriminative performance, but can help to distinguish between future highest and lowest HbA1c levels. Absolute HbA1c values are cohort-dependent., Competing Interests: The Novo Nordisk funding did not influence the scientific work, or have any influence on design, data collection, analyses or interpretation of the results. We can confirm that this does not alter our adherence to PLOS ONE policies on sharing data and materials.
- Published
- 2017
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