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1. Glycemic Control and Urinary Tract Infections in Women with Type 1 Diabetes: Results from the DCCT/EDIC

Author: Lenherr, Sara M, Clemens, J Quentin, Braffett, Barbara H, Cleary, Patricia A, Dunn, Rodney L, Hotaling, James M, Jacobson, Alan M, Kim, Catherine, Herman, William, Brown, Jeanette S, Wessells, Hunter, Sarma, Aruna V, Nathan, DM, Zinman, B, Crofford, O, Genuth, S, Brown-Friday, J, Crandall, J, Engel, H, Engel, S, Martinez, H, Phillips, M, Reid, M, Shamoon, H, Sheindlin, J, Gubitosi-Klug, R, Mayer, L, Pendegast, S, Zegarra, H, Miller, D, Singerman, L, Smith-Brewer, S, Novak, M, Quin, J, Genuth, Saul, Palmert, M, Brown, E, McConnell, J, Pugsley, P, Crawford, P, Dahms, W, Brillon, D, Lackaye, ME, Kiss, S, Chan, R, Orlin, A, Rubin, M, Reppucci, V, Lee, T, Heinemann, M, Chang, S, Levy, B, Jovanovic, L, Richardson, M, Bosco, B, Dwoskin, A, Hanna, R, Barron, S, Campbell, R, Bhan, A, Kruger, D, Jones, JK, Edwards, PA, Carey, JD, Angus, E, Thomas, A, Galprin, A, McLellan, M, Whitehouse, F, Bergenstal, R, Johnson, M, Gunyou, K, Thomas, L, Laechelt, J, Hollander, P, Spencer, M, Kendall, D, Cuddihy, R, Callahan, P, List, S, Gott, J, Rude, N, Olson, B, Franz, M, Castle, G, Birk, R, Nelson, J, Freking, D, Gill, L, Mestrezat, W, Etzwiler, D, Morgan, K, Aiello, LP, Golden, E, Arrigg, P, Asuquo, V, Beaser, R, Bestourous, L, and Cavallerano, J
Subjects: Medical Microbiology, Biomedical and Clinical Sciences, Infectious Diseases, Clinical Research, Urologic Diseases, Diabetes, Prevention, Reproductive health and childbirth, Renal and urogenital, Infection, Metabolic and endocrine, Adolescent, Adult, Blood Glucose, Body Mass Index, Diabetes Mellitus, Type 1, Female, Glycated Hemoglobin, Humans, Hypoglycemic Agents, Risk Factors, Surveys and Questionnaires, Urinary Incontinence, Urinary Tract Infections, Young Adult, DCCT/EDIC Research Group, diabetes mellitus, risk factors, urinary tract infections, Clinical Sciences, Urology & Nephrology, Clinical sciences
Abstract: PurposeWe examined the relationship between glycemic control and urinary tract infections in women with type 1 diabetes mellitus.Materials and methodsWomen enrolled in the Epidemiology of Diabetes Interventions and Complications study, the observational followup of the Diabetes Control and Complications Trial, were surveyed to assess the rate of physician diagnosed urinary tract infections in the preceding 12 months. The relationship between glycated hemoglobin levels and number of urinary tract infections in the previous 12 months was assessed using a multivariable Poisson regression model.ResultsA total of 572 women were evaluated at year 17. Mean age was 50.7 ± 7.2 years, mean body mass index was 28.6 ± 5.9 kg/m(2), mean type 1 diabetes duration was 29.8 ± 5.0 years and mean glycated hemoglobin was 8.0% ± 0.9%. Of these women 86 (15.0%) reported at least 1 physician diagnosed urinary tract infection during the last 12 months. Higher glycated hemoglobin levels were significantly associated with number of urinary tract infections such that for every unit increase (1%) in recent glycated hemoglobin level, there was a 21% (p=0.02) increase in urinary tract infection frequency in the previous 12 months after adjusting for race, hysterectomy status, urinary incontinence, sexual activity in the last 12 months, peripheral and autonomic neuropathy, and nephropathy.ConclusionsThe frequency of urinary tract infections increases with poor glycemic control in women with type 1 diabetes. This relationship is independent of other well described predictors of urinary tract infections and suggests that factors directly related to glycemic control may influence the risk of lower urinary tract infections.
Published: 2016

2. Epigenomic profiling reveals an association between persistence of DNA methylation and metabolic memory in the DCCT/EDIC type 1 diabetes cohort

Author: Chen, Zhuo, Miao, Feng, Paterson, Andrew D, Lachin, John M, Zhang, Lingxiao, Schones, Dustin E, Wu, Xiwei, Wang, Jinhui, Tompkins, Joshua D, Genuth, Saul, Braffett, Barbara H, Riggs, Arthur D, Natarajan, Rama, Nathan, DM, Zinman, B, Crofford, O, Genuth, S, Brown-Friday, J, Crandall, J, Engel, H, Engel, S, Martinez, H, Phillips, M, Reid, M, Shamoon, H, Sheindlin, J, Gubitosi-Klug, R, Mayer, L, Pendegast, S, Zegarra, H, Miller, D, Singerman, L, Smith-Brewer, S, Novak, M, Quin, J, Palmert, M, Brown, E, McConnell, J, Pugsley, P, Crawford, P, Dahms, W, Brillon, D, Lackaye, ME, Kiss, S, Chan, R, Orlin, A, Rubin, M, Reppucci, V, Lee, T, Heinemann, M, Chang, S, Levy, B, Jovanovic, L, Richardson, M, Bosco, B, Dwoskin, A, Hanna, R, Barron, S, Campbell, R, Bhan, A, Kruger, D, Jones, JK, Edwards, PA, Carey, JD, Angus, E, Thomas, A, Galprin, A, McLellan, M, Whitehouse, F, Bergenstal, R, Johnson, M, Gunyou, K, Thomas, L, Laechelt, J, Hollander, P, Spencer, M, Kendall, D, Cuddihy, R, Callahan, P, List, S, Gott, J, Rude, N, Olson, B, Franz, M, Castle, G, Birk, R, Nelson, J, Freking, D, Gill, L, Mestrezat, W, Etzwiler, D, Morgan, K, Aiello, LP, Golden, E, Arrigg, P, Asuquo, V, Beaser, R, and Bestourous, L
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Genetics, Nutrition, Human Genome, Diabetes, Prevention, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Adolescent, Adult, Carrier Proteins, Cell Line, Tumor, Cohort Studies, DNA Methylation, Diabetes Mellitus, Type 1, Epigenomics, Female, Genetic Loci, Glycated Hemoglobin, Humans, Male, DCCT/EDIC Research Group, DNA methylation, TXNIP, diabetic complications, epigenetics, metabolic memory
Abstract: We examined whether persistence of epigenetic DNA methylation (DNA-me) alterations at specific loci over two different time points in people with diabetes are associated with metabolic memory, the prolonged beneficial effects of intensive vs. conventional therapy during the Diabetes Control and Complications Trial (DCCT) on the progression of microvascular outcomes in the long-term follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) Study. We compared DNA-me profiles in genomic DNA of whole blood (WB) isolated at EDIC Study baseline from 32 cases (DCCT conventional therapy group subjects showing retinopathy or albuminuria progression by EDIC Study year 10) vs. 31 controls (DCCT intensive therapy group subjects without complication progression by EDIC year 10). DNA-me was also profiled in blood monocytes (Monos) of the same patients obtained during EDIC Study years 16-17. In WB, 153 loci depicted hypomethylation, and 225 depicted hypermethylation, whereas in Monos, 155 hypomethylated loci and 247 hypermethylated loci were found (fold change ≥1.3; P < 0.005; cases vs. controls). Twelve annotated differentially methylated loci were common in both WB and Monos, including thioredoxin-interacting protein (TXNIP), known to be associated with hyperglycemia and related complications. A set of differentially methylated loci depicted similar trends of associations with prior HbA1c in both WB and Monos. In vitro, high glucose induced similar persistent hypomethylation at TXNIP in cultured THP1 Monos. These results show that DNA-me differences during the DCCT persist at certain loci associated with glycemia for several years during the EDIC Study and support an epigenetic explanation for metabolic memory.
Published: 2016

3. Long-term complications in youth-onset type 2 diabetes

Author: Bjornstad, P, primary, Drews, KL, additional, Caprio, S, additional, Gubitosi-Klug, R, additional, Nathan, DM, additional, Tesfaldet, B, additional, Tryggestad, J, additional, White, NH, additional, and Zeitler, P, additional
Published: 2022
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4. Thenar hammer syndrome in a wrestler

Author: Hopkins, Nathan DM, primary and Jordan, Faye, additional
Published: 2022
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5. NATIONAL GUIDELINES FOR CHOLESTEROL SCREENING ALSO IDENTIFY RISK FOR UNRECOGNIZED GLUCOSE INTOLERANCE: THE FRAMINGHAM OFFSPRING STUDY

Author: Meigs, JB, Wilson, PWF, Nathan, DM, Cupples, LA, and Singer, DE
Published: 1996

6. Significance of epicardial and intrathoracic adipose tissue volume among type 1 diabetes patients in the DCCT/EDIC: A pilot study

Author: Darabian, S, Backlund, JYC, Cleary, PA, Sheidaee, N, Bebu, I, Lachin, JM, Budoff, MJ, Nathan, DM, Zinman, B, Crofford, O, Genuth, S, Brown-Friday, J, Crandall, J, Engel, H, Engel, S, Martinez, H, Phillips, M, Reid, M, Shamoon, H, Sheindlin, J, Gubitosi-Klug, R, Mayer, L, Pendegast, S, Zegarra, H, Miller, D, Singerman, L, Smith-Brewer, S, Novak, M, Quin, J, Palmert, M, Brown, E, McConnell, J, Pugsley, P, Crawford, P, Dahms, W, Brillon, D, Lackaye, ME, Kiss, S, Chan, R, Orlin, A, Rubin, M, Reppucci, V, Lee, T, Heinemann, M, Chang, S, Levy, B, Jovanovic, L, Richardson, M, Bosco, B, Dwoskin, A, Hanna, R, Barron, S, Campbell, R, Bhan, A, Kruger, D, Jones, JK, Edwards, PA, Carey, JD, Angus, E, Thomas, A, Galprin, A, McLellan, M, Whitehouse, F, Bergenstal, R, Johnson, M, Gunyou, K, Thomas, L, Laechelt, J, Hollander, P, Spencer, M, Kendall, D, Cuddihy, R, Callahan, P, List, S, Gott, J, Rude, N, Olson, B, Franz, M, Castle, G, Birk, R, Nelson, J, Freking, D, Gill, L, Mestrezat, W, Etzwiler, D, Morgan, K, and Aiello, LP
Subjects: DCCT/EDIC Research Group
Abstract: © 2016 Darabian et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Introduction: Type 1 diabetes (T1DM) patients are at increased risk of coronary artery disease (CAD). This pilot study sought to evaluate the relationship between epicardial adipose tissue (EAT) and intra-thoracic adipose tissue (IAT) volumes and cardio-metabolic risk factors in T1DM. Method: EAT/IAT volumes in 100 patients, underwent non-contrast cardiac computed tomography in the Diabetes Control and Complications Trial /Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study were measured by a certified reader. Fat was defined as pixels' density of -30 to -190 Hounsfield Unit. The associations were assessed using-Pearson partial correlation and linear regression models adjusted for gender and age with inverse probability sample weighting. Results: The weighted mean age was 43 years (range 32-57) and 53% were male. Adjusted for gender, Pearson correlation analysis showed a significant correlation between age and EAT/IAT volumes (both p
Published: 2016

7. Does Glucose Variability Influence the Relationship Between Mean Plasma Glucose and HbA1c Levels in Type 1 and Type 2 Diabetic Patients?

Author: Kuenen, Jc, Borg, R, Kuik, Dj, Zheng, H, Schoenfeld, D, Diamant, M, Nathan, Dm, Heine, Rj, Sartore, Giovanni, Lapolla, Annunziata, Internal medicine, Epidemiology and Data Science, EMGO - Lifestyle, overweight and diabetes, and ICaR - Ischemia and repair
Subjects: Research design, Adult, Blood Glucose, Male, medicine.medical_specialty, endocrine system diseases, Adolescent, Endocrinology, Diabetes and Metabolism, Type 2 diabetes, Young Adult, Glycation, Internal medicine, Diabetes mellitus, Internal Medicine, medicine, Humans, Pathophysiology/Complications, Glycemic, Original Research, Aged, Advanced and Specialized Nursing, Glycated Hemoglobin, Type 1 diabetes, Plasma glucose, business.industry, Confounding, nutritional and metabolic diseases, Middle Aged, medicine.disease, Endocrinology, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Female, business
Abstract: OBJECTIVE The A1C-Derived Average Glucose (ADAG) study demonstrated a linear relationship between HbA1c and mean plasma glucose (MPG). As glucose variability (GV) may contribute to glycation, we examined the association of several glucose variability indices and the MPG-HbA1c relationship. RESEARCH DESIGN AND METHODS Analyses included 268 patients with type 1 diabetes and 159 with type 2 diabetes. MPG during 3 months was calculated from 7-point self-monitored plasma glucose and continuous glucose monitoring. We calculated three different measures of GV and used a multiple-step regression model to determine the contribution of the respective GV measures to the MPG-HbA1c relationship. RESULTS GV, as reflected by SD and continuous overlapping net glycemic action, had a significant effect on the MPG-HbA1c relationship in type 1 diabetic patients so that high GV led to a higher HbA1c level for the same MPG. In type 1 diabetes, the impact of confounding and effect modification of a low versus high SD at an MPG level of 160 mg/dL on the HbA1c level is 7.02 vs. 7.43 and 6.96 vs. 7.41. All GV measures showed the same tendency. CONCLUSIONS In only type 1 diabetic patients, GV shows a significant interaction with MPG in the association with HbA1c. This effect is more pronounced at higher HbA1c levels. However, the impact of GV on the HbA1c level in type 1 diabetes is modest, particularly when HbA1c is close to the treatment target of 7%.
Published: 2011

8. Hypothesis-based analysis of gene-gene interactions and risk of myocardial infarction

Author: Lucas G1, Lluís-Ganella C, Subirana I, Musameh MD, Gonzalez JR, Nelson CP, Sentí M, Myocardial Infarction Genetics Consortium, Wellcome Trust Case Control Consortium, Schwartz SM, Siscovick D, O'Donnell CJ, Melander O, Salomaa V, Purcell S, Altshuler D, Samani NJ, Kathiresan S, Elosua R, Voight BF, Musunuru K, Ardissino D, Mannucci PM, Anand S, Engert JC, Schunkert H, Erdmann J, Reilly MP, Rader DJ, Morgan T, Spertus JA, Stoll M, Girelli D, McKeown PP, Patterson CC, Siscovick DS, Peltonen L, Merlini PA, Berzuini C, Bernardinelli L, Peyvandi F, Tubaro M, Celli P, Ferrario M, Fetiveau R, Marziliano N, Casari G, Galli M, Ribichini F, Rossi M, Bernardi F, Zonzin P, Piazza A, Yee J, Friedlander Y, Marrugat J, Lucas G, Sala J, Ramos R, Meigs JB, Williams G, Nathan DM, MacRae CA, Havulinna AS, Berglund G, Deloukas P, Donnelly P, Farrall M, Gough SC, Hall AS, Hattersley AT, Hill AV, Kwiatkowski DP, Mathew CG, McCarthy MI, Ouwehand WH, Parkes M, Pembrey M, Rahman N, Stratton MR, Todd JA, Worthington J, Burton PR, Clayton DG, Cardon LR, Craddock N, Duncanson A, Barrett JC, Davison D, Easton D, Evans D, Leung HT, Marchini JL, Morris AP, Spencer CC, Tobin MD, Attwood AP, Boorman JP, Cant B, Everson U, Hussey JM, Jolley JD, Knight AS, Koch K, Meech E, Nutland S, Prowse CV, Stevens HE, Taylor NC, Walters GR, Walker NM, Watkins NA, Winzer T, Jones RW, McArdle WL, Ring SM, Strachan DP, Ball SG, Balmforth AJ, Barrett JH, Bishop D, Iles MM, Maqbool A, Braund PS, Dixon RJ, Mangino M, Stevens S, Thompson JR, Bumpstead SJ, Chaney A, Downes K, Ghori MJ, Gwilliam R, Hunt SE, Inouye M, Keniry A, King E, McGinnis R, Potter S, Ravindrarajah R, Whittaker P, Widden C, Cardo LR, Cardin NJ, Ferreira T, Pereira-Gale J, Hallgrimsdottir IB, Howie BN, Su Z, Teo YY, Vukcevic D, Lucas, G1, Lluís-Ganella, C, Subirana, I, Musameh, Md, Gonzalez, Jr, Nelson, Cp, Sentí, M, Myocardial Infarction Genetics, Consortium, Wellcome Trust Case Control, Consortium, Schwartz, Sm, Siscovick, D, O'Donnell, Cj, Melander, O, Salomaa, V, Purcell, S, Altshuler, D, Samani, Nj, Kathiresan, S, Elosua, R, Voight, Bf, Musunuru, K, Ardissino, D, Mannucci, Pm, Anand, S, Engert, Jc, Schunkert, H, Erdmann, J, Reilly, Mp, Rader, Dj, Morgan, T, Spertus, Ja, Stoll, M, Girelli, D, Mckeown, Pp, Patterson, Cc, Peltonen, L, Merlini, Pa, Berzuini, C, Bernardinelli, L, Peyvandi, F, Tubaro, M, Celli, P, Ferrario, M, Fetiveau, R, Marziliano, N, Casari, G, Galli, M, Ribichini, F, Rossi, M, Bernardi, F, Zonzin, P, Piazza, A, Yee, J, Friedlander, Y, Marrugat, J, Lucas, G, Sala, J, Ramos, R, Meigs, Jb, Williams, G, Nathan, Dm, Macrae, Ca, Havulinna, A, Berglund, G, Deloukas, P, Donnelly, P, Farrall, M, Gough, Sc, Hall, A, Hattersley, At, Hill, Av, Kwiatkowski, Dp, Mathew, Cg, Mccarthy, Mi, Ouwehand, Wh, Parkes, M, Pembrey, M, Rahman, N, Stratton, Mr, Todd, Ja, Worthington, J, Burton, Pr, Clayton, Dg, Cardon, Lr, Craddock, N, Duncanson, A, Barrett, Jc, Davison, D, Easton, D, Evans, D, Leung, Ht, Marchini, Jl, Morris, Ap, Spencer, Cc, Tobin, Md, Attwood, Ap, Boorman, Jp, Cant, B, Everson, U, Hussey, Jm, Jolley, Jd, Knight, A, Koch, K, Meech, E, Nutland, S, Prowse, Cv, Stevens, He, Taylor, Nc, Walters, Gr, Walker, Nm, Watkins, Na, Winzer, T, Jones, Rw, Mcardle, Wl, Ring, Sm, Strachan, Dp, Ball, Sg, Balmforth, Aj, Barrett, Jh, Bishop, D, Iles, Mm, Maqbool, A, Braund, P, Dixon, Rj, Mangino, M, Stevens, S, Thompson, Jr, Bumpstead, Sj, Chaney, A, Downes, K, Ghori, Mj, Gwilliam, R, Hunt, Se, Inouye, M, Keniry, A, King, E, Mcginnis, R, Potter, S, Ravindrarajah, R, Whittaker, P, Widden, C, Cardo, Lr, Cardin, Nj, Ferreira, T, Pereira-Gale, J, Hallgrimsdottir, Ib, Howie, Bn, Su, Z, Teo, Yy, and Vukcevic, D
Subjects: Heredity, Epidemiology, Myocardial Infarction, lcsh:Medicine, Genome-wide association study, Coronary Artery Disease, Cardiovascular, Logistic regression, Risk Factors, Cardiac and Cardiovascular Systems, lcsh:Science, Genetics, 0303 health sciences, Multidisciplinary, Medicine (all), 030305 genetics & heredity, Genomics, Genetic Epidemiology, Medicine, Research Article, Human, Risk, Genotype, Genotypes, Reproducibility of Result, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, 03 medical and health sciences, Genome Analysis Tools, Genome-Wide Association Studies, Humans, Genetic Predisposition to Disease, Risk factor, Allele frequency, Genetic Association Studies, 030304 developmental biology, Genetic association, Biochemistry, Genetics and Molecular Biology (all), Complex Traits, Risk Factor, lcsh:R, Reproducibility of Results, Human Genetics, Epistasis, Genetic, Odds ratio, Genetic epidemiology, Agricultural and Biological Sciences (all), Genetics of Disease, Epistasis, Genetic Polymorphism, Infart de miocardi -- Epidemiologia, lcsh:Q, Population Genetics, Genome-Wide Association Study
Abstract: The genetic loci that have been found by genome-wide association studies to modulate risk of coronary heart disease explain only a fraction of its total variance, and gene-gene interactions have been proposed as a potential source of the remaining heritability. Given the potentially large testing burden, we sought to enrich our search space with real interactions by analyzing variants that may be more likely to interact on the basis of two distinct hypotheses: a biological hypothesis, under which MI risk is modulated by interactions between variants that are known to be relevant for its risk factors; and a statistical hypothesis, under which interacting variants individually show weak marginal association with MI. In a discovery sample of 2,967 cases of early-onset myocardial infarction (MI) and 3,075 controls from the MIGen study, we performed pair-wise SNP interaction testing using a logistic regression framework. Despite having reasonable power to detect interaction effects of plausible magnitudes, we observed no statistically significant evidence of interaction under these hypotheses, and no clear consistency between the top results in our discovery sample and those in a large validation sample of 1,766 cases of coronary heart disease and 2,938 controls from the Wellcome Trust Case-Control Consortium. Our results do not support the existence of strong interaction effects as a common risk factor for MI. Within the scope of the hypotheses we have explored, this study places a modest upper limit on the magnitude that epistatic risk effects are likely to have at the population level (odds ratio for MI risk 1.3–2.0, depending on allele frequency and interaction model).
Published: 2012

9. Identification of ADAMTS7 as a novel locus for coronary atherosclerosis and association of ABO with myocardial infarction in the presence of coronary atherosclerosis: two genome-wide association studies

Author: Reilly MP, Li M, He J, Ferguson JF, Stylianou IM, Mehta NN, Burnett MS, Devaney JM, Knouff CW, Thompson JR, Horne BD, Stewart AF, Assimes TL, Wild PS, Allayee H, Nitschke PL, Patel RS, Myocardial Infarction Genetics Consortium, Wellcome Trust Case Control Consortium, Martinelli N, Girelli D, Quyyumi AA, Anderson JL, Erdmann J, Hall AS, Schunkert H, Quertermous T, Blankenberg S, Hazen SL, Roberts R, Kathiresan S, Samani NJ, Epstein SE, Rader DJ, Qasim AN, DerOhannessian SL, Qu L, Cappola TP, Chen Z, Matthai W, Hakonarson HH, Wilensky R, Kent KM, Lindsay JM, Pichard AD, Satler L, Waksman R, Knoupf CW, Walker MC, Waterworth DM, Mosser V, Braund PS, Wright B, Balmforth AJ, Ball SG, Chen L, Wells GA, McPherson R, Lackner K, Munzel TF, Schillert A, Schnabel R, Zeller T, Ziegler A, Absher D, Hlatky MA, Iribaren C, Knowles JW, Linsel Nitschke P, König IR, Hengstenberg C, Nahrstaedt J, Peters A, Schreiber S, Wichmann E, Willenborg C, Su S, Bouzyk M, Vaccarino V, Zafari AM, Carlquist JF, Muhlestein JB, Olivieri O, Barnard J, Hartiala J, Tang WH, Burton PR, Clayton DG, Cardon LR, Craddock N, Deloukas P, Duncanson A, Kwiatkowski DP, McCarthy MI, Ouwehand WH, Todd JA, Donnelly P, Barrett JC, Davison D, Easton D, Evans DM, Leung HT, Marchini JL, Morris AP, Spencer CC, Tobin MD, Attwood AP, Boorman JP, Cant B, Everson U, Hussey JM, Jolley JD, Knight AS, Koch K, Meech E, Nutland S, Prowse CV, Stevens HE, Taylor NC, Walters GR, Walker NM, Watkins NA, Winzer T, Jones RW, McArdle WL, Ring SM, Strachan DP, Pembrey M, Breen G, St Clair D, Caesar S, Gordon Smith K, Jones L, Fraser C, Green EK, Grozeva D, Hamshere ML, Holmans PA, Jones IR, Kirov G, Moskvina V, Nikolov I, O'Donovan MC, Owen MJ, Collier DA, Elkin A, Farmer A, Williamson R, McGuffin P, Young AH, Ferrier IN, Barrett JH, Bishop DT, Iles MM, Maqbool A, Yuldasheva N, Dixon RJ, Mangino M, Stevens S, Bredin F, Tremelling M, Parkes M, Drummond H, Lees CW, Nimmo ER, Satsangi J, Fisher SA, Forbes A, Lewis CM, Onnie CM, Prescott NJ, Sanderson J, Mathew CG, Barbour J, Mohiuddin MK, Todhunter CE, Mansfield JC, Ahmad T, Cummings FR, Jewell DP, Webster J, Brown MJ, Lathrop M, Connell J, Dominiczak A, Marcano CA, Burke B, Dobson R, Gungadoo J, Lee KL, Munroe PB, Newhouse SJ, Onipinla A, Wallace C, Xue M, Caulfield M, Farrall M, Barton A, Bruce IN, Donovan H, Eyre S, Gilbert PD, Hider SL, Hinks AM, John SL, Potter C, Silman AJ, Symmons DP, Thomson W, Worthington J, Dunger DB, Widmer B, Frayling TM, Freathy RM, Lango H, Perry JR, Shields BM, Weedon MN, Hattersley AT, Hitman GA, Walker M, Elliott KS, Groves CJ, Lindgren CM, Rayner NW, Timpson NJ, Zeggini E, Newport M, Sirugo G, Lyons E, Vannberg F, Hill AV, Bradbury LA, Farrar C, Pointon JJ, Wordsworth P, Brown MA, Franklyn JA, Heward JM, Simmonds MJ, Gough SC, Seal S, Stratton MR, Rahman N, Ban M, Goris A, Sawcer SJ, Compston A, Conway D, Jallow M, Rockett KA, Bumpstead SJ, Chaney A, Downes K, Ghori MJ, Gwilliam R, Hunt SE, Inouye M, Keniry A, King E, McGinnis R, Potter S, Ravindrarajah R, Whittaker P, Widden C, Withers D, Cardin NJ, Ferreira T, Pereira Gale J, Hallgrimsdóttir IB, Bowie BN, Su Z, Teo YY, Vukcevic D, Bentley D, Meigs JB, Williams G, Nathan DM, MacRae CA, O'Donnell CJ, Ardissino D, Merlini PA, Berzuini C, Bernardinelli L, Peyvandi F, Tubaro M, Celli P, Ferrario M, Fetiveau R, Marziliano N, Galli M, Ribichini F, Rossi M, Bernardi F, Zonzin P, Piazza A, Mannucci PM, Schwartz SM, Siscovick DS, Yee J, Friedlander Y, Elosua R, Marrugat J, Lucas G, Subirana I, Sala J, Ramos R, Salomaa V, Havulinna AS, Peltonen L, Melander O, Berglund G, Voight BF, Hirschhorn JN, Asselta R, Duga S, Spreafico M, Musunuru K, Daly MJ, Purcell S, Surti A, Guiducci C, Gianniny L, Mirel D, Parkin M, Burtt N, Gabriel SB, CASARI , GIORGIO NEVIO, Reilly, Mp, Li, M, He, J, Ferguson, Jf, Stylianou, Im, Mehta, Nn, Burnett, M, Devaney, Jm, Knouff, Cw, Thompson, Jr, Horne, Bd, Stewart, Af, Assimes, Tl, Wild, P, Allayee, H, Nitschke, Pl, Patel, R, Myocardial Infarction Genetics, Consortium, Wellcome Trust Case Control, Consortium, Martinelli, N, Girelli, D, Quyyumi, Aa, Anderson, Jl, Erdmann, J, Hall, A, Schunkert, H, Quertermous, T, Blankenberg, S, Hazen, Sl, Roberts, R, Kathiresan, S, Samani, Nj, Epstein, Se, Rader, Dj, Qasim, An, Derohannessian, Sl, Qu, L, Cappola, Tp, Chen, Z, Matthai, W, Hakonarson, Hh, Wilensky, R, Kent, Km, Lindsay, Jm, Pichard, Ad, Satler, L, Waksman, R, Knoupf, Cw, Walker, Mc, Waterworth, Dm, Mosser, V, Braund, P, Wright, B, Balmforth, Aj, Ball, Sg, Chen, L, Wells, Ga, Mcpherson, R, Lackner, K, Munzel, Tf, Schillert, A, Schnabel, R, Zeller, T, Ziegler, A, Absher, D, Hlatky, Ma, Iribaren, C, Knowles, Jw, Linsel Nitschke, P, König, Ir, Hengstenberg, C, Nahrstaedt, J, Peters, A, Schreiber, S, Wichmann, E, Willenborg, C, Su, S, Bouzyk, M, Vaccarino, V, Zafari, Am, Carlquist, Jf, Muhlestein, Jb, Olivieri, O, Barnard, J, Hartiala, J, Tang, Wh, Burton, Pr, Clayton, Dg, Cardon, Lr, Craddock, N, Deloukas, P, Duncanson, A, Kwiatkowski, Dp, Mccarthy, Mi, Ouwehand, Wh, Todd, Ja, Donnelly, P, Barrett, Jc, Davison, D, Easton, D, Evans, Dm, Leung, Ht, Marchini, Jl, Morris, Ap, Spencer, Cc, Tobin, Md, Attwood, Ap, Boorman, Jp, Cant, B, Everson, U, Hussey, Jm, Jolley, Jd, Knight, A, Koch, K, Meech, E, Nutland, S, Prowse, Cv, Stevens, He, Taylor, Nc, Walters, Gr, Walker, Nm, Watkins, Na, Winzer, T, Jones, Rw, Mcardle, Wl, Ring, Sm, Strachan, Dp, Pembrey, M, Breen, G, St Clair, D, Caesar, S, Gordon Smith, K, Jones, L, Fraser, C, Green, Ek, Grozeva, D, Hamshere, Ml, Holmans, Pa, Jones, Ir, Kirov, G, Moskvina, V, Nikolov, I, O'Donovan, Mc, Owen, Mj, Collier, Da, Elkin, A, Farmer, A, Williamson, R, Mcguffin, P, Young, Ah, Ferrier, In, Barrett, Jh, Bishop, Dt, Iles, Mm, Maqbool, A, Yuldasheva, N, Dixon, Rj, Mangino, M, Stevens, S, Bredin, F, Tremelling, M, Parkes, M, Drummond, H, Lees, Cw, Nimmo, Er, Satsangi, J, Fisher, Sa, Forbes, A, Lewis, Cm, Onnie, Cm, Prescott, Nj, Sanderson, J, Mathew, Cg, Barbour, J, Mohiuddin, Mk, Todhunter, Ce, Mansfield, Jc, Ahmad, T, Cummings, Fr, Jewell, Dp, Webster, J, Brown, Mj, Lathrop, M, Connell, J, Dominiczak, A, Marcano, Ca, Burke, B, Dobson, R, Gungadoo, J, Lee, Kl, Munroe, Pb, Newhouse, Sj, Onipinla, A, Wallace, C, Xue, M, Caulfield, M, Farrall, M, Barton, A, Bruce, In, Donovan, H, Eyre, S, Gilbert, Pd, Hider, Sl, Hinks, Am, John, Sl, Potter, C, Silman, Aj, Symmons, Dp, Thomson, W, Worthington, J, Dunger, Db, Widmer, B, Frayling, Tm, Freathy, Rm, Lango, H, Perry, Jr, Shields, Bm, Weedon, Mn, Hattersley, At, Hitman, Ga, Walker, M, Elliott, K, Groves, Cj, Lindgren, Cm, Rayner, Nw, Timpson, Nj, Zeggini, E, Newport, M, Sirugo, G, Lyons, E, Vannberg, F, Hill, Av, Bradbury, La, Farrar, C, Pointon, Jj, Wordsworth, P, Brown, Ma, Franklyn, Ja, Heward, Jm, Simmonds, Mj, Gough, Sc, Seal, S, Stratton, Mr, Rahman, N, Ban, M, Goris, A, Sawcer, Sj, Compston, A, Conway, D, Jallow, M, Rockett, Ka, Bumpstead, Sj, Chaney, A, Downes, K, Ghori, Mj, Gwilliam, R, Hunt, Se, Inouye, M, Keniry, A, King, E, Mcginnis, R, Potter, S, Ravindrarajah, R, Whittaker, P, Widden, C, Withers, D, Cardin, Nj, Ferreira, T, Pereira Gale, J, Hallgrimsdóttir, Ib, Bowie, Bn, Su, Z, Teo, Yy, Vukcevic, D, Bentley, D, Meigs, Jb, Williams, G, Nathan, Dm, Macrae, Ca, O'Donnell, Cj, Ardissino, D, Merlini, Pa, Berzuini, C, Bernardinelli, L, Peyvandi, F, Tubaro, M, Celli, P, Ferrario, M, Fetiveau, R, Marziliano, N, Casari, GIORGIO NEVIO, Galli, M, Ribichini, F, Rossi, M, Bernardi, F, Zonzin, P, Piazza, A, Mannucci, Pm, Schwartz, Sm, Siscovick, D, Yee, J, Friedlander, Y, Elosua, R, Marrugat, J, Lucas, G, Subirana, I, Sala, J, Ramos, R, Salomaa, V, Havulinna, A, Peltonen, L, Melander, O, Berglund, G, Voight, Bf, Hirschhorn, Jn, Asselta, R, Duga, S, Spreafico, M, Musunuru, K, Daly, Mj, Purcell, S, Surti, A, Guiducci, C, Gianniny, L, Mirel, D, Parkin, M, Burtt, N, and Gabriel, Sb
Subjects: Adult, Male, medicine.medical_specialty, Linkage disequilibrium, ABO, ADAMTS7 Protein, ADAMTS7, Genome-wide association study, Coronary Angiography, Polymorphism, Single Nucleotide, Linkage Disequilibrium, ABO Blood-Group System, Coronary artery disease, Gene Frequency, ABO blood group system, Internal medicine, medicine, Genetic predisposition, Humans, Genetic Predisposition to Disease, cardiovascular diseases, Myocardial infarction, Genetic risk factor, genetic locus, Coronary atherosclerosis, Aged, business.industry, coronary atherosclerosis, General Medicine, Middle Aged, medicine.disease, ADAM Proteins, myocardial infarction, Genetic Loci, Cardiology, Myocardial infarction complications, Female, business, coronary artery disease, Genome-Wide Association Study
Abstract: BACKGROUND: We tested whether genetic factors distinctly contribute to either development of coronary atherosclerosis or, specifically, to myocardial infarction in existing coronary atherosclerosis. METHODS: We did two genome-wide association studies (GWAS) with coronary angiographic phenotyping in participants of European ancestry. To identify loci that predispose to angiographic coronary artery disease (CAD), we compared individuals who had this disorder (n=12,393) with those who did not (controls, n=7383). To identify loci that predispose to myocardial infarction, we compared patients who had angiographic CAD and myocardial infarction (n=5783) with those who had angiographic CAD but no myocardial infarction (n=3644). FINDINGS: In the comparison of patients with angiographic CAD versus controls, we identified a novel locus, ADAMTS7 (p=4·98×10(-13)). In the comparison of patients with angiographic CAD who had myocardial infarction versus those with angiographic CAD but no myocardial infarction, we identified a novel association at the ABO locus (p=7·62×10(-9)). The ABO association was attributable to the glycotransferase-deficient enzyme that encodes the ABO blood group O phenotype previously proposed to protect against myocardial infarction. INTERPRETATION: Our findings indicate that specific genetic predispositions promote the development of coronary atherosclerosis whereas others lead to myocardial infarction in the presence of coronary atherosclerosis. The relation to specific CAD phenotypes might modify how novel loci are applied in personalised risk assessment and used in the development of novel therapies for CAD. FUNDING: The PennCath and MedStar studies were supported by the Cardiovascular Institute of the University of Pennsylvania, by the MedStar Health Research Institute at Washington Hospital Center and by a research grant from GlaxoSmithKline. The funding and support for the other cohorts contributing to the paper are described in the webappendix.
Published: 2011

10. The Lin28/let-7 axis regulates glucose metabolism

Author: Zhu H, Shyh Chang N, Segrè AV, Shinoda G, Shah SP, Einhorn WS, Takeuchi A, Engreitz JM, Hagan JP, Kharas MG, Urbach A, Thornton JE, Triboulet R, Gregory RI, DIAGRAM Consortium, MAGIC Investigators, Altshuler D, Daley G.Q. Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP, Zeggini E, Huth C, Aulchenko YS, Thorleifsson G, McCulloch LJ, Ferreira T, Grallert H, Amin N, Wu G, Willer CJ, Raychaudhuri S, McCarroll SA, Langenberg C, Hofmann OM, Dupuis J, Qi L, van Hoek M, Navarro P, Ardlie K, Balkau B, Benediktsson R, Bennett AJ, Blagieva R, Boerwinkle E, Bonnycastle LL, Boström KB, Bravenboer B, Bumpstead S, Burtt NP, Charpentier G, Chines PS, Cornelis M, Couper DJ, Crawford G, Doney AS, Elliott KS, Elliott AL, Erdos MR, Fox CS, Franklin CS, Ganser M, Gieger C, Grarup N, Green T, Griffin S, Groves CJ, Guiducci C, Hadjadj S, Hassanali N, Herder C, Isomaa B, Jackson AU, Johnson PR, Jørgensen T, Kao WH, Klopp N, Kong A, Kraft P, Kuusisto J, Lauritzen T, Li M, Lieverse A, Lindgren CM, Lyssenko V, Marre M, Meitinger T, Midthjell K, Morken MA, Narisu N, Nilsson P, Owen KR, Payne F, Perry JR, Petersen AK, Platou C, Proença C, Prokopenko I, Rathmann W, Rayner NW, Robertson NR, Rocheleau G, Roden M, Sampson MJ, Saxena R, Shields BM, Shrader P, Sigurdsson G, Sparsø T, Strassburger K, Stringham HM, Sun Q, Swift AJ, Thorand B, Tichet J, Tuomi T, van Dam RM, van Haeften TW, van Herpt T, van Vliet Ostaptchouk JV, Walters GB, Weedon MN, Wijmenga C, Witteman J, Bergman RN, Cauchi S, Collins FS, Gloyn AL, Gyllensten U, Hansen T, Hide WA, Hitman GA, Hofman A, Hunter DJ, Hveem K, Laakso M, Mohlke KL, Morris AD, Palmer CN, Pramstaller PP, Rudan I, Sijbrands E, Stein LD, Tuomilehto J, Uitterlinden A, Walker M, Wareham NJ, Watanabe RM, Abecasis GR, Boehm BO, Campbell H, Daly MJ, Hattersley AT, Hu FB, Meigs JB, Pankow JS, Pedersen O, Wichmann HE, Barroso I, Florez JC, Frayling TM, Groop L, Sladek R, Thorsteinsdottir U, Wilson JF, Illig T, Froguel P, van Duijn CM, Stefansson K, Boehnke M, McCarthy MI, Soranzo N, Wheeler E, Glazer NL, Bouatia Naji N, Mägi R, Randall J, Johnson T, Elliott P, Rybin D, Henneman P, Dehghan A, Hottenga JJ, Song K, Goel A, Egan JM, Lajunen T, Doney A, Voight BF, Kanoni S, Cavalcanti Proença C, Kumari M, Timpson NJ, Zabena C, Ingelsson E, An P, O'Connell J, Luan J, Elliott A, Roccasecca RM, Pattou F, Sethupathy P, Ariyurek Y, Barter P, Beilby JP, Ben Shlomo Y, Bergmann S, Bochud M, Bonnefond A, Borch Johnsen K, Böttcher Y, Brunner E, Bumpstead SJ, Chen YD, Chines P, Clarke R, Coin LJ, Cooper MN, Crisponi L, Day IN, de Geus EJ, Delplanque J, Fedson AC, Fischer Rosinsky A, Forouhi NG, Frants R, Franzosi MG, Galan P, Goodarzi MO, Graessler J, Grundy S, Gwilliam R, Hallmans G, Hammond N, Han X, Hartikainen AL, Hayward C, Heath SC, Hercberg S, Hicks AA, Hillman DR, Hingorani AD, Hui J, Hung J, Jula A, Kaakinen M, Kaprio J, Kesaniemi YA, Kivimaki M, Knight B, Koskinen S, Kovacs P, Kyvik KO, Lathrop GM, Lawlor DA, Le Bacquer O, Lecoeur C, Li Y, Mahley R, Mangino M, Manning AK, Martínez Larrad MT, McAteer JB, McPherson R, Meisinger C, Melzer D, Meyre D, Mitchell BD, Mukherjee S, Naitza S, Neville MJ, Oostra BA, Orrù M, Pakyz R, Pattaro C, Pearson D, Peden JF, Pedersen NL, Perola M, Pfeiffer AF, Pichler I, Polasek O, Posthuma D, Potter SC, Pouta A, Province MA, Psaty BM, Rice K, Ripatti S, Rivadeneira F, Rolandsson O, Sandbaek A, Sandhu M, Sanna S, Sayer AA, Scheet P, Seedorf U, Sharp SJ, Shields B, Sigurðsson G, Sijbrands EJ, Silveira A, Simpson L, Singleton A, Smith NL, Sovio U, Swift A, Syddall H, Syvänen AC, Tanaka T, Tönjes A, Uitterlinden AG, van Dijk KW, Varma D, Visvikis Siest S, Vitart V, Vogelzangs N, Waeber G, Wagner PJ, Walley A, Ward KL, Watkins H, Wild SH, Willemsen G, Witteman JC, Yarnell JW, Zelenika D, Zethelius B, Zhai G, Zhao JH, Zillikens MC, Borecki IB, Loos RJ, Meneton P, Magnusson PK, Nathan DM, Williams GH, Silander K, Salomaa V, Smith GD, Bornstein SR, Schwarz P, Spranger J, Karpe F, Shuldiner AR, Cooper C, Dedoussis GV, Serrano Ríos M, Lind L, Palmer LJ, Franks PW, Ebrahim S, Marmot M, Wright AF, Stumvoll M, Hamsten A, Buchanan TA, Valle TT, Rotter JI, Siscovick DS, Penninx BW, Boomsma DI, Deloukas P, Spector TD, Ferrucci L, Cao A, Scuteri A, Schlessinger D, Uda M, Ruokonen A, Jarvelin MR, Waterworth DM, Vollenweider P, Peltonen L, Mooser V, Barroso I., PAOLISSO, Giuseppe, Zhu, H, Shyh Chang, N, Segrè, Av, Shinoda, G, Shah, Sp, Einhorn, W, Takeuchi, A, Engreitz, Jm, Hagan, Jp, Kharas, Mg, Urbach, A, Thornton, Je, Triboulet, R, Gregory, Ri, Diagram, Consortium, Magic, Investigator, Altshuler, D, Voight BF, Daley G. Q., Scott, Lj, Steinthorsdottir, V, Morris, Ap, Dina, C, Welch, Rp, Zeggini, E, Huth, C, Aulchenko, Y, Thorleifsson, G, Mcculloch, Lj, Ferreira, T, Grallert, H, Amin, N, Wu, G, Willer, Cj, Raychaudhuri, S, Mccarroll, Sa, Langenberg, C, Hofmann, Om, Dupuis, J, Qi, L, van Hoek, M, Navarro, P, Ardlie, K, Balkau, B, Benediktsson, R, Bennett, Aj, Blagieva, R, Boerwinkle, E, Bonnycastle, Ll, Boström, Kb, Bravenboer, B, Bumpstead, S, Burtt, Np, Charpentier, G, Chines, P, Cornelis, M, Couper, Dj, Crawford, G, Doney, A, Elliott, K, Elliott, Al, Erdos, Mr, Fox, C, Franklin, C, Ganser, M, Gieger, C, Grarup, N, Green, T, Griffin, S, Groves, Cj, Guiducci, C, Hadjadj, S, Hassanali, N, Herder, C, Isomaa, B, Jackson, Au, Johnson, Pr, Jørgensen, T, Kao, Wh, Klopp, N, Kong, A, Kraft, P, Kuusisto, J, Lauritzen, T, Li, M, Lieverse, A, Lindgren, Cm, Lyssenko, V, Marre, M, Meitinger, T, Midthjell, K, Morken, Ma, Narisu, N, Nilsson, P, Owen, Kr, Payne, F, Perry, Jr, Petersen, Ak, Platou, C, Proença, C, Prokopenko, I, Rathmann, W, Rayner, Nw, Robertson, Nr, Rocheleau, G, Roden, M, Sampson, Mj, Saxena, R, Shields, Bm, Shrader, P, Sigurdsson, G, Sparsø, T, Strassburger, K, Stringham, Hm, Sun, Q, Swift, Aj, Thorand, B, Tichet, J, Tuomi, T, van Dam, Rm, van Haeften, Tw, van Herpt, T, van Vliet Ostaptchouk, Jv, Walters, Gb, Weedon, Mn, Wijmenga, C, Witteman, J, Bergman, Rn, Cauchi, S, Collins, F, Gloyn, Al, Gyllensten, U, Hansen, T, Hide, Wa, Hitman, Ga, Hofman, A, Hunter, Dj, Hveem, K, Laakso, M, Mohlke, Kl, Morris, Ad, Palmer, Cn, Pramstaller, Pp, Rudan, I, Sijbrands, E, Stein, Ld, Tuomilehto, J, Uitterlinden, A, Walker, M, Wareham, Nj, Watanabe, Rm, Abecasis, Gr, Boehm, Bo, Campbell, H, Daly, Mj, Hattersley, At, Hu, Fb, Meigs, Jb, Pankow, J, Pedersen, O, Wichmann, He, Barroso, I, Florez, Jc, Frayling, Tm, Groop, L, Sladek, R, Thorsteinsdottir, U, Wilson, Jf, Illig, T, Froguel, P, van Duijn, Cm, Stefansson, K, Boehnke, M, Mccarthy, Mi, Soranzo, N, Wheeler, E, Glazer, Nl, Bouatia Naji, N, Mägi, R, Randall, J, Johnson, T, Elliott, P, Rybin, D, Henneman, P, Dehghan, A, Hottenga, Jj, Song, K, Goel, A, Egan, Jm, Lajunen, T, Voight, Bf, Kanoni, S, Cavalcanti Proença, C, Kumari, M, Timpson, Nj, Zabena, C, Ingelsson, E, An, P, O'Connell, J, Luan, J, Elliott, A, Roccasecca, Rm, Pattou, F, Sethupathy, P, Ariyurek, Y, Barter, P, Beilby, Jp, Ben Shlomo, Y, Bergmann, S, Bochud, M, Bonnefond, A, Borch Johnsen, K, Böttcher, Y, Brunner, E, Bumpstead, Sj, Chen, Yd, Clarke, R, Coin, Lj, Cooper, Mn, Crisponi, L, Day, In, de Geus, Ej, Delplanque, J, Fedson, Ac, Fischer Rosinsky, A, Forouhi, Ng, Frants, R, Franzosi, Mg, Galan, P, Goodarzi, Mo, Graessler, J, Grundy, S, Gwilliam, R, Hallmans, G, Hammond, N, Han, X, Hartikainen, Al, Hayward, C, Heath, Sc, Hercberg, S, Hicks, Aa, Hillman, Dr, Hingorani, Ad, Hui, J, Hung, J, Jula, A, Kaakinen, M, Kaprio, J, Kesaniemi, Ya, Kivimaki, M, Knight, B, Koskinen, S, Kovacs, P, Kyvik, Ko, Lathrop, Gm, Lawlor, Da, Le Bacquer, O, Lecoeur, C, Li, Y, Mahley, R, Mangino, M, Manning, Ak, Martínez Larrad, Mt, Mcateer, Jb, Mcpherson, R, Meisinger, C, Melzer, D, Meyre, D, Mitchell, Bd, Mukherjee, S, Naitza, S, Neville, Mj, Oostra, Ba, Orrù, M, Pakyz, R, Paolisso, Giuseppe, Pattaro, C, Pearson, D, Peden, Jf, Pedersen, Nl, Perola, M, Pfeiffer, Af, Pichler, I, Polasek, O, Posthuma, D, Potter, Sc, Pouta, A, Province, Ma, Psaty, Bm, Rice, K, Ripatti, S, Rivadeneira, F, Rolandsson, O, Sandbaek, A, Sandhu, M, Sanna, S, Sayer, Aa, Scheet, P, Seedorf, U, Sharp, Sj, Shields, B, Sigurðsson, G, Sijbrands, Ej, Silveira, A, Simpson, L, Singleton, A, Smith, Nl, Sovio, U, Swift, A, Syddall, H, Syvänen, Ac, Tanaka, T, Tönjes, A, Uitterlinden, Ag, van Dijk, Kw, Varma, D, Visvikis Siest, S, Vitart, V, Vogelzangs, N, Waeber, G, Wagner, Pj, Walley, A, Ward, Kl, Watkins, H, Wild, Sh, Willemsen, G, Witteman, Jc, Yarnell, Jw, Zelenika, D, Zethelius, B, Zhai, G, Zhao, Jh, Zillikens, Mc, Borecki, Ib, Loos, Rj, Meneton, P, Magnusson, Pk, Nathan, Dm, Williams, Gh, Silander, K, Salomaa, V, Smith, Gd, Bornstein, Sr, Schwarz, P, Spranger, J, Karpe, F, Shuldiner, Ar, Cooper, C, Dedoussis, Gv, Serrano Ríos, M, Lind, L, Palmer, Lj, Franks, Pw, Ebrahim, S, Marmot, M, Wright, Af, Stumvoll, M, Hamsten, A, Buchanan, Ta, Valle, Tt, Rotter, Ji, Siscovick, D, Penninx, Bw, Boomsma, Di, Deloukas, P, Spector, Td, Ferrucci, L, Cao, A, Scuteri, A, Schlessinger, D, Uda, M, Ruokonen, A, Jarvelin, Mr, Waterworth, Dm, Vollenweider, P, Peltonen, L, Mooser, V, and Barroso, I.
Published: 2011

11. Changes in Body Composition Over 8 Years in a Randomized Trial of a Lifestyle Intervention: The Look AHEAD Study

Author: Pownall, HJ, Bray, GA, Wagenknecht, LE, Walkup, MP, Heshka, S, Hubbard, VS, Hill, J, Kahn, SE, Nathan, DM, Schwartz, AV, and Johnson, KC
Subjects: Male, TYPE-2 DIABETES-MELLITUS, WEIGHT-LOSS, Endocrinology & Metabolism, Absorptiometry, Photon, Patient Education as Topic, Behavior Therapy, Weight Loss, MD Multidisciplinary, Humans, Obesity, OLDER-ADULTS, Life Style, Aged, Caloric Restriction, GENERAL-POPULATION, INSULIN-RESISTANCE, Science & Technology, Nutrition & Dietetics, Look AHEAD Research Group, FAT DISTRIBUTION, X-RAY ABSORPTIOMETRY, Middle Aged, Overweight, DISEASE RISK-FACTORS, Exercise Therapy, Weight Reduction Programs, Diabetes Mellitus, Type 2, CARDIOVASCULAR-DISEASE, Body Composition, Female, Life Sciences & Biomedicine, OBESE WOMEN, Follow-Up Studies
Abstract: Objective To determine the effects of an intensive lifestyle intervention versus a comparison group on body composition in obese or overweight persons with type 2 diabetes at baseline and at 1, 4, and 8 years. Methods Body composition was measured by dual‐energy X‐ray absorptiometry in a subset of 1019 Look AHEAD study volunteers randomized to intervention or comparison groups. The intervention was designed to achieve and maintain ≥7% weight loss through increased physical activity and reduced caloric intake. The comparison group received social support and diabetes education. Results At 1 year, the intervention group lost fat (5.6 ± 0.2 kg) and lean mass (2.3 ± 0.1 kg) but regained fat (∼100%) and lost lean mass between years 1 and 8. Between baseline and year 8, weight loss was greater in intervention versus comparison groups (4.0 ± 0.4 vs. 2.3 ± 0.4 kg); comparison group weight loss was mostly lean mass (2.1 ± 0.17 kg). Fat mass in the intervention group was lower than that of the comparison group at all post‐baseline time points. Conclusions Reduced fat mass may place the intervention group at a lower risk of obesity‐linked sequelae, a hypothesis that can be tested by future studies of this cohort.
Published: 2014

12. Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis

Author: Stahl, E. A., Wegmann, D., Trynka, G., Gutierrez Achury, J., Do, R., Voight, B. F., Kraft, P., Chen, R., Kallberg, H. J., F. A. S., Replication, D. G., Consortium, M. a., Genetics, M. I., Kathiresan, S., Wijmenga, C., Gregersen, P. K., Alfredsson, L., Siminovitch, K. A., Worthington, J., P. I. W., Raychaudhuri, S., Plenge, R. M., Voight, Bf, Scott, Lj, Steinthorsdottir, V, Morris, Ap, Dina, C, Welch, Rp, Zeggini, E, Huth, C, Aulchenko, Ys, Thorleifsson, G, Mcculloch, Lj, Ferreira, T, Grallert, H, Amin, N, Wu, G, Willer, Cj, Raychaudhuri, S, Mccarroll, Sa, Langenberg, C, Hofmann, Om, Dupuis, J, Qi, L, Segrè, Av, van Hoek, M, Navarro, P, Ardlie, K, Balkau, B, Benediktsson, R, Bennett, Aj, Blagieva, R, Boerwinkle, E, Bonnycastle, Ll, Boström, Kb, Bravenboer, B, Bumpstead, S, Burtt, Np, Charpentier, G, Chines, Ps, Cornelis, M, Couper, Dj, Crawford, G, Doney, As, Elliott, Ks, Elliott, Al, Erdos, Mr, Fox, Cs, Franklin, Cs, Ganser, M, Gieger, C, Grarup, N, Green, T, Griffin, S, Groves, Cj, Guiducci, C, Hadjadj, S, Hassanali, N, Herder, C, Isomaa, B, Jackson, Au, Johnson, Pr, Jørgensen, T, Kao, Wh, Klopp, N, Kong, A, Kraft, P, Kuusisto, J, Lauritzen, T, Li, M, Lieverse, A, Lindgren, Cm, Lyssenko, V, Marre, M, Meitinger, T, Midthjell, K, Morken, Ma, Narisu, N, Nilsson, P, Owen, Kr, Payne, F, Perry, Jr, Petersen, Ak, Platou, C, Proença, C, Prokopenko, I, Rathmann, W, Rayner, Nw, Robertson, Nr, Rocheleau, G, Roden, M, Sampson, Mj, Saxena, R, Shields, Bm, Shrader, P, Sigurdsson, G, Sparsø, T, Strassburger, K, Stringham, Hm, Sun, Q, Swift, Aj, Thorand, B, Tichet, J, Tuomi, T, van Dam RM, van Haeften TW, van Herpt, T, van Vliet Ostaptchouk JV, Walters, Gb, Weedon, Mn, Wijmenga, C, Witteman, J, Bergman, Rn, Cauchi, S, Collins, Fs, Gloyn, Al, Gyllensten, U, Hansen, T, Hide, Wa, Hitman, Ga, Hofman, A, Hunter, Dj, Hveem, K, Laakso, M, Mohlke, Kl, Morris, Ad, Palmer, Cn, Pramstaller, Pp, Rudan, I, Sijbrands, E, Stein, Ld, Tuomilehto, J, Uitterlinden, A, Walker, M, Wareham, Nj, Watanabe, Rm, Abecasis, Gr, Boehm, Bo, Campbell, H, Daly, Mj, Hattersley, At, Hu, Fb, Meigs, Jb, Pankow, Js, Pedersen, O, Wichmann, He, Barroso, I, Florez, Jc, Frayling, Tm, Groop, L, Sladek, R, Thorsteinsdottir, U, Wilson, Jf, Illig, T, Froguel, P, van Duijn CM, Stefansson, K, Altshuler, D, Boehnke, M, Mccarthy, Mi, Kathiresan, S, Williams, G, Nathan, Dm, Macrae, Ca, O'Donnell, Cj, Ardissino, D, Merlini, Pa, Berzuini, C, Bernardinelli, L, Peyvandi, F, Tubaro, M, Celli, P, Ferrario, M, Fetiveau, R, Marziliano, N, Casari, G, Galli, M, Ribichini, Flavio Luciano, Rossi, M, Bernardi, F, Zonzin, P, Piazza, A, Mannucci, Pm, Schwartz, Sm, Siscovick, Ds, Yee, J, Friedlander, Y, Elosua, R, Marrugat, J, Lucas, G, Subirana, I, Sala, J, Ramos, R, Salomaa, V, Havulinna, As, Peltonen, L, Melander, O, Berglund, G, Hirschhorn, Jn, Asselta, R, Duga, S, Spreafico, M, Musunuru, K, Purcell, S, Surti, A, Gianniny, L, Mirel, D, Parkin, M, Burtt, N, Gabriel, Sb, Stahl, Ea, Wegmann, D, Trynka, G, Gutierrez achury, J, Do, R, Voight, Bf, Kraft, P, Che, R, Kallberg, H, Kurreeman, F, Diabetes Genetics Replication And Meta analysis Consortium: Myocardial Infarction Genetics, Consortium, Casari, GIORGIO NEVIO, Kathiresan, S, Wijmenga, C, Gregersen, Pk, Alfredsson, L, Siminovitch, Ka, Worthington, J, De Bakker, Pi, Raychaudhuri, S, Plenge, Rm, and Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI)
Subjects: Multifactorial Inheritance, SUSCEPTIBILITY LOCI, GENETIC SUSCEPTIBILITY, Genome-wide association study, Single-nucleotide polymorphism, Disease, HEART-DISEASE, Biology, VARIANTS, Polymorphism, Single Nucleotide, Article, Arthritis, Rheumatoid, COMMON SNPS, Missing heritability problem, MISSING HERITABILITY, Rheumatoid, Genetic model, Genetic predisposition, Diabetes Mellitus, Humans, genetics, Genetic Predisposition to Disease, Human height, Polymorphism, GENOME-WIDE ASSOCIATION, Arthritis, genetics, Bayes Theorem, Cardiovascular Diseases, genetics, Case-Control Studies, Celiac Disease, genetics, Diabetes Mellitus, Type 2, genetics, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Genetics, CELIAC-DISEASE, Bayes Theorem, RISK LOCI, Genetic architecture, Celiac Disease, Diabetes Mellitus, Type 2, Cardiovascular Diseases, Genetic Loci, Case-Control Studies, HUMAN HEIGHT, Genome-Wide Association Study
Abstract: The genetic architectures of common, complex diseases are largely uncharacterized. We modeled the genetic architecture underlying genome-wide association study (GWAS) data for rheumatoid arthritis and developed a new method using polygenic risk-score analyses to infer the total liability-scale variance explained by associated GWAS SNPs. Using this method, we estimated that, together, thousands of SNPs from rheumatoid arthritis GWAS explain an additional 20% of disease risk (excluding known associated loci). We further tested this method on datasets for three additional diseases and obtained comparable estimates for celiac disease (43% excluding the major histocompatibility complex), myocardial infarction and coronary artery disease (48%) and type 2 diabetes (49%). Our results are consistent with simulated genetic models in which hundreds of associated loci harbor common causal variants and a smaller number of loci harbor multiple rare causal variants. These analyses suggest that GWAS will continue to be highly productive for the discovery of additional susceptibility loci for common diseases.
Published: 2012

13. Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

Author: Soranzo, N, Sanna, S, Wheeler, E, Gieger, C, Radke, D, Dupuis, J, Bouatia-Naji, N, Langenberg, C, Prokopenko, I, Stolerman, E, Sandhu, MS, Heeney, MM, Devaney, JM, Reilly, MP, Ricketts, SL, Stewart, AF, Voight, BF, Willenborg, C, Wright, B, Altshuler, D, Arking, D, Balkau, B, Barnes, D, Boerwinkle, E, Böhm, B, Bonnefond, A, Bonnycastle, LL, Boomsma, DI, Bornstein, SR, Böttcher, Y, Bumpstead, S, Burnett-Miller, MS, Campbell, H, Cao, A, Chambers, J, Clark, R, Collins, FS, Coresh, J, de Geus, EJ, Dei, M, Deloukas, P, Döring, A, Egan, JM, Elosua, R, Ferrucci, L, Forouhi, N, Fox, CS, Franklin, C, Franzosi, MG, Gallina, S, Goel, A, Graessler, J, Grallert, H, Greinacher, A, Hadley, D, Hall, A, Hamsten, A, Hayward, C, Heath, S, Herder, C, Homuth, G, Hottenga, JJ, Hunter-Merrill, R, Illig, T, Jackson, AU, Jula, A, Kleber, M, Knouff, CW, Kong, A, Kooner, J, Köttgen, A, Kovacs, P, Krohn, K, Kühnel, B, Kuusisto, J, Laakso, M, Lathrop, M, Lecoeur, C, Li, M, Loos, RJ, Luan, J, Lyssenko, V, Mägi, R, Magnusson, PK, Mälarstig, A, Mangino, M, Martínez-Larrad, MT, März, W, McArdle, WL, McPherson, R, Meisinger, C, Meitinger, T, Melander, O, Mohlke, KL, Mooser, VE, Morken, MA, Narisu, N, Nathan, DM, Nauck, M, O'Donnell, C, Oexle, K, Olla, N, Pankow, JS, Payne, F, Peden, JF, Pedersen, NL, Peltonen, L, Perola, M, Polasek, O, Porcu, E, Rader, DJ, Rathmann, W, Ripatti, S, Rocheleau, G, Roden, M, Rudan, I, Salomaa, V, Saxena, R, Schlessinger, D, Schunkert, H, Schwarz, P, Seedorf, U, Selvin, E, Serrano-Ríos, M, Shrader, P, Silveira, A, Siscovick, D, Song, K, Spector, TD, Stefansson, K, Steinthorsdottir, V, Strachan, DP, Strawbridge, R, Stumvoll, M, Surakka, I, Swift, AJ, Tanaka, T, Teumer, A, Thorleifsson, G, Thorsteinsdottir, U, Tönjes, A, Usala, G, Vitart, V, Völzke, H, Wallaschofski, H, Waterworth, DM, Watkins, H, Wichmann, HE, Wild, SH, Willemsen, G, Williams, GH, Wilson, JF, Winkelmann, J, Wright, AF, WTCCC, Zabena, C, Zhao, JH, Epstein, SE, Erdmann, J, Hakonarson, HH, Kathiresan, S, Khaw, KT, Roberts, R, Samani, NJ, Fleming, MD, Sladek, R, Abecasis, G, Boehnke, M, Froguel, P, Groop, L, McCarthy, MI, Kao, WH, Florez, JC, Uda, M, Wareham, NJ, Barroso, I, and Meigs, JB
Subjects: endocrine system diseases, nutritional and metabolic diseases
Published: 2010

14. Erratum: New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk (Nature Genetics (2010) 42 (105-116))

Author: Dupuis, J, Langenberg, C, Prokopenko, I, Saxena, R, Soranzo, N, Jackson, AU, Wheeler, E, Glazer, NL, Bouatia-Naji, N, Gloyn, AL, Lindgren, CM, Mägi, R, Morris, AP, Randall, J, Johnson, T, Elliott, P, Rybin, D, Thorleifsson, G, Steinthorsdottir, V, Henneman, P, Grallert, H, Dehghan, A, Hottenga, JJ, Franklin, CS, Navarro, P, Song, K, Goel, A, Perry, JRB, Egan, JM, Lajunen, T, Grarup, N, Sparsø, T, Doney, A, Voight, BF, Stringham, HM, Li, M, Kanoni, S, Shrader, P, Cavalcanti-Proença, C, Kumari, M, Qi, L, Timpson, NJ, Gieger, C, Zabena, C, Rocheleau, G, Ingelsson, E, An, P, O'Connell, J, Luan, J, Elliott, A, McCarroll, SA, Payne, F, Roccasecca, RM, Pattou, F, Sethupathy, P, Ardlie, K, Ariyurek, Y, Balkau, B, Barter, P, Beilby, JP, Ben-Shlomo, Y, Benediktsson, R, Bennett, AJ, Bergmann, S, Bochud, M, Boerwinkle, E, Bonnefond, A, Bonnycastle, LL, Borch-Johnsen, K, Böttcher, Y, Brunner, E, Bumpstead, SJ, Charpentier, G, Chen, Y-DI, Chines, P, Clarke, R, Coin, LJM, Cooper, MN, Cornelis, M, Crawford, G, Crisponi, L, Day, INM, De Geus, EJC, Delplanque, J, Dina, C, Erdos, MR, Fedson, AC, Fischer-Rosinsky, A, Forouhi, NG, Fox, CS, Frants, R, Franzosi, MG, Galan, P, Goodarzi, MO, Graessler, J, Groves, CJ, Grundy, S, Gwilliam, R, Gyllensten, U, Hadjadj, S, Hallmans, G, Hammond, N, Han, X, Hartikainen, A-L, Hassanali, N, Hayward, C, Heath, SC, Hercberg, S, Herder, C, Hicks, AA, Hillman, DR, Hingorani, AD, Hofman, A, Hui, J, Hung, J, Isomaa, B, Johnson, PRV, Jørgensen, T, Jula, A, Kaakinen, M, Kaprio, J, Kesaniemi, YA, Kivimaki, M, Knight, B, Koskinen, S, Kovacs, P, Kyvik, KO, Lathrop, GM, Lawlor, DA, Le Bacquer, O, Lecoeur, C, Li, Y, Lyssenko, V, Mahley, R, Mangino, M, Manning, AK, Martínez-Larrad, MT, McAteer, JB, McCulloch, LJ, McPherson, R, Meisinger, C, Melzer, D, Meyre, D, Mitchell, BD, Morken, MA, Mukherjee, S, Naitza, S, Narisu, N, Neville, MJ, Oostra, BA, Orr, M, Pakyz, R, Palmer, CNA, Paolisso, G, Pattaro, C, Pearson, D, Peden, JF, Pedersen, NL, Perola, M, Pfeiffer, AFH, Pichler, I, Polasek, O, Posthuma, D, Potter, SC, Pouta, A, Province, MA, Psaty, BM, Rathmann, W, Rayner, NW, Rice, K, Ripatti, S, Rivadeneira, F, Roden, M, Rolandsson, O, Sandbaek, A, Sandhu, M, Sanna, S, Sayer, AA, Scheet, P, Scott, LJ, Seedorf, U, Sharp, SJ, Shields, B, Sigursson, G, Sijbrands, EJG, Silveira, A, Simpson, L, Singleton, A, Smith, NL, Sovio, U, Swift, A, Syddall, H, Syvänen, A-C, Tanaka, T, Thorand, B, Tichet, J, Tönjes, A, Tuomi, T, Uitterlinden, AG, Van Dijk, KW, Van Hoek, M, Varma, D, Visvikis-Siest, S, Vitart, V, Vogelzangs, N, Waeber, G, Wagner, PJ, Walley, A, Walters, GB, Ward, KL, Watkins, H, Weedon, MN, Wild, SH, Willemsen, G, Witteman, JCM, Yarnell, JWG, Zeggini, E, Zelenika, D, Zethelius, B, Zhai, G, Zhao, JH, Zillikens, MC, Consortium, D, Consortium, G, Consortium, GB, Borecki, IB, Loos, RJF, Meneton, P, Magnusson, PKE, Nathan, DM, Williams, GH, Hattersley, AT, Silander, K, Salomaa, V, Smith, GD, Bornstein, SR, Schwarz, P, Spranger, J, Karpe, F, Shuldiner, AR, Cooper, C, Dedoussis, GV, Serrano-Ríos, M, Morris, AD, Lind, L, Palmer, LJ, Hu, FB, Franks, PW, Ebrahim, S, Marmot, M, Kao, WHL, Pankow, JS, Sampson, MJ, Kuusisto, J, Laakso, M, Hansen, T, Pedersen, O, Pramstaller, PP, Wichmann, HE, Illig, T, Rudan, I, Wright, AF, Stumvoll, M, Campbell, H, Wilson, JF, Hamsten, A, Bergman, RN, Buchanan, TA, Collins, FS, Mohlke, KL, Tuomilehto, J, Valle, TT, Altshuler, D, Rotter, JI, Siscovick, DS, Penninx, BWJH, Boomsma, DI, Deloukas, P, Spector, TD, Frayling, TM, Ferrucci, L, Kong, A, Thorsteinsdottir, U, Stefansson, K, Van Duijn, CM, Aulchenko, YS, Cao, A, Scuteri, A, Schlessinger, D, Uda, M, Ruokonen, A, Jarvelin, M-R, Waterworth, DM, Vollenweider, P, Peltonen, L, Mooser, V, Abecasis, GR, Wareham, NJ, Sladek, R, Froguel, P, Watanabe, RM, Meigs, JB, Groop, L, Boehnke, M, McCarthy, MI, Florez, JC, and Barroso, I
Published: 2010

15. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk (vol 42, pg 105, 2010)

Author: Dupuis, J, Langenberg, C, Prokopenko, I, Saxena, R, Soranzo, N, Jackson, AU, Wheeler, E, Glazer, NL, Bouatia-Naji, N, Gloyn, AL, Lindgren, CM, Maegi, R, Morris, AP, Randall, J, Johnson, T, Elliott, P, Rybin, D, Thorleifsson, G, Steinthorsdottir, V, Henneman, P, Grallert, H, Dehghan, A, Hottenga, JJ, Franklin, CS, Navarro, P, Song, K, Goel, A, Perry, JRB, Egan, JM, Lajunen, T, Grarup, N, Sparso, T, Doney, A, Voight, BF, Stringham, HM, Li, M, Kanoni, S, Shrader, P, Cavalcanti-Proenca, C, Kumari, M, Qi, L, Timpson, NJ, Gieger, C, Zabena, C, Rocheleau, G, Ingelsson, E, An, P, O'Connell, J, Luan, J, Elliott, A, McCarroll, SA, Payne, F, Roccasecca, RM, Pattou, F, Sethupathy, P, Ardlie, K, Ariyurek, Y, Balkau, B, Barter, P, Beilby, JP, Ben-Shlomo, Y, Benediktsson, R, Bennett, AJ, Bergmann, S, Bochud, M, Boerwinkle, E, Bonnefond, A, Bonnycastle, LL, Borch-Johnsen, K, Boettcher, Y, Brunner, E, Bumpstead, SJ, Charpentier, G, Chen, Y-DI, Chines, P, Clarke, R, Coin, LJM, Cooper, MN, Cornelis, M, Crawford, G, Crisponi, L, Day, INM, de Geus, EJC, Delplanque, J, Dina, C, Erdos, MR, Fedson, AC, Fischer-Rosinsky, A, Forouhi, NG, Fox, CS, Frants, R, Franzosi, MG, Galan, P, Goodarzi, MO, Graessler, J, Groves, CJ, Grundy, S, Gwilliam, R, Gyllensten, U, Hadjadj, S, Hallmans, G, Hammond, N, Han, X, Hartikainen, A-L, Hassanali, N, Hayward, C, Heath, SC, Hercberg, S, Herder, C, Hicks, AA, Hillman, DR, Hingorani, AD, Hofman, A, Hui, J, Hung, J, Isomaa, B, Johnson, PRV, Jorgensen, T, Jula, A, Kaakinen, M, Kaprio, J, Kesaniemi, YA, Kivimaki, M, Knight, B, Koskinen, S, Kovacs, P, Kyvik, KO, Lathrop, GM, Lawlor, DA, Le Bacquer, O, Lecoeur, C, Li, Y, Lyssenko, V, Mahley, R, Mangino, M, Manning, AK, Martinez-Larrad, MT, McAteer, JB, McCulloch, LJ, McPherson, R, Meisinger, C, Melzer, D, Meyre, D, Mitchell, BD, Morken, MA, Mukherjee, S, Naitza, S, Narisu, N, Neville, MJ, Oostra, BA, Orru, M, Pakyz, R, Palmer, CNA, Paolisso, G, Pattaro, C, Pearson, D, Peden, JF, Pedersen, NL, Perola, M, Pfeiffer, AFH, Pichler, I, Polasek, O, Posthuma, D, Potter, SC, Pouta, A, Province, MA, Psaty, BM, Rathmann, W, Rayner, NW, Rice, K, Ripatti, S, Rivadeneira, F, Roden, M, Rolandsson, O, Sandbaek, A, Sandhu, M, Sanna, S, Sayer, AA, Scheet, P, Scott, LJ, Seedorf, U, Sharp, SJ, Shields, B, Sigurosson, G, Sijbrands, EJG, Silveira, A, Simpson, L, Singleton, A, Smith, NL, Sovio, U, Swift, A, Syddall, H, Syvaenen, A-C, Tanaka, T, Thorand, B, Tichet, J, Toenjes, A, Tuomi, T, Uitterlinden, AG, van Dijk, KW, van Hoek, M, Varma, D, Visvikis-Siest, S, Vitart, V, Vogelzangs, N, Waeber, G, Wagner, PJ, Walley, A, Walters, GB, Ward, KL, Watkins, H, Weedon, MN, Wild, SH, Willemsen, G, Witteman, JCM, Yarnell, JWG, Zeggini, E, Zelenika, D, Zethelius, B, Zhai, G, Zhao, JH, Zillikens, MC, Borecki, IB, Loos, RJF, Meneton, P, Magnusson, PKE, Nathan, DM, Williams, GH, Hattersley, AT, Silander, K, Salomaa, V, Smith, GD, Bornstein, SR, Schwarz, P, Spranger, J, Karpe, F, Shuldiner, AR, Cooper, C, Dedoussis, GV, Serrano-Rios, M, Morris, AD, Lind, L, Palmer, LJ, Hu, FB, Franks, PW, Ebrahim, S, Marmot, M, Kao, WHL, Pankow, JS, Sampson, MJ, Kuusisto, J, Laakso, M, Hansen, T, Pedersen, O, Pramstaller, PP, Wichmann, HE, Illig, T, Rudan, I, Wright, AF, Stumvoll, M, Campbell, H, Wilson, JF, Hamsten, A, Bergman, RN, Buchanan, TA, Collins, FS, Mohlke, KL, Tuomilehto, J, Valle, TT, Altshuler, D, Rotter, JI, Siscovick, DS, Penninx, BWJH, Boomsma, DI, Deloukas, P, Spector, TD, Frayling, TM, Ferrucci, L, Kong, A, Thorsteinsdottir, U, Stefansson, K, van Duijn, CM, Aulchenko, YS, Cao, A, Scuteri, A, Schlessinger, D, Uda, M, Ruokonen, A, Jarvelin, M-R, Waterworth, DM, Vollenweider, P, Peltonen, L, Mooser, V, Abecasis, GR, Wareham, NJ, Sladek, R, Froguel, P, Watanabe, RM, Meigs, JB, Groop, L, Boehnke, M, McCarthy, MI, Florez, JC, Consortium, DIAGRAM, Consortium, GIANT, Consortium, GB, Consortium, P, and Investigators, IBMAGIC
Published: 2010

16. Associations between features of glucose exposure and A1C: the A1C-Derived Average Glucose (ADAG) study

Author: Borg, R, Kuenen, Jc, Carstensen, B, Zheng, H, Nathan, Dm, Heine, Rj, Nerup, J, BORCH JOHNSEN, K, Witte, Dr, ADAG STUDY GROUP, Sartore, Giovanni, and Lapolla, Annunziata
Published: 2010

17. Defining the role of common variation in the genomic and biological architecture of adult human height.

Author: Genomics (eMEMERGEGE) Consortium, MIGen Consortium, PAGEGE Consortium, LifeLines Cohort Study, Electronic Medical, Records, McCarty, CA., Starren, J., Peissig, P., Berg, R., Rasmussen, L., Linneman, J., Miller, A., Choudary, V., Chen, L., Waudby, C., Kitchner, T., Reeser, J., Fost, N., Ritchie, M., Wilke, RA., Chisholm, RL., Avila, PC., Greenland, P., Hayes, M., Kho, A., Kibbe, WA., Lemke, AA., Lowe, WL., Smith, ME., Wolf, WA., Pacheco, JA., Thompson, WK., Humowiecki, J., Law, M., Chute, C., Kullo, I., Koenig, B., de Andrade, M., Bielinski, S., Pathak, J., Savova, G., Wu, J., Henriksen, J., Ding, K., Hart, L., Palbicki, J., Larson, EB., Newton, K., Ludman, E., Spangler, L., Hart, G., Carrell, D., Jarvik, G., Crane, P., Burke, W., Fullerton, SM., Trinidad, SB., Carlson, C., Hutchinson, F., McDavid, A., Roden, DM., Clayton, E., Haines, JL., Masys, DR., Churchill, LR., Cornfield, D., Crawford, D., Darbar, D., Denny, JC., Malin, BA., Ritchie, MD., Schildcrout, JS., Xu, H., Ramirez, AH., Basford, M., Pulley, J., Alizadeh, B., de Boer RA., Boezen, HM., Bruinenberg, M., Franke, L., van der Harst, P., Hillege, HL., van der Klauw MM., Navis, G., Ormel, J., Postma, DS., Rosmalen, JG., Slaets, JP., Snieder, H., Stolk, RP., Wolffenbuttel, BH., Wijmenga, C., Kathiresan, S., Voight, BF., Purcell, S., Musunuru, K., Ardissino, D., Mannucci, PM., Anand, S., Engert, JC., Samani, NJ., Schunkert, H., Erdmann, J., Reilly, MP., Rader, DJ., Morgan, T., Spertus, JA., Stoll, M., Girelli, D., McKeown, PP., Patterson, CC., Siscovick, DS., O'Donnell, CJ., Elosua, R., Peltonen, L., Salomaa, V., Schwartz, SM., Melander, O., Altshuler, D., Merlini, PA., Berzuini, C., Bernardinelli, L., Peyvandi, F., Tubaro, M., Celli, P., Ferrario, M., Fetiveau, R., Marziliano, N., Casari, G., Galli, M., Ribichini, F., Rossi, M., Bernardi, F., Zonzin, P., Piazza, A., Yee, J., Friedlander, Y., Marrugat, J., Lucas, G., Subirana, I., Sala, J., Ramos, R., Meigs, JB., Williams, G., Nathan, DM., MacRae, CA., Havulinna, AS., Berglund, G., Voight, B., Hirschhorn, JN., Asselta, R., Duga, S., Spreafico, M., Daly, MJ., Nemesh, J., Korn, JM., McCarroll, SA., Surti, A., Guiducci, C., Gianniny, L., Mirel, D., Parkin, M., Burtt, N., Gabriel, SB., Thompson, JR., Braund, PS., Wright, BJ., Balmforth, AJ., Ball, SG., Hall, AS., Schunkert, I., Linsel-Nitschke, P., Lieb, W., Ziegler, A., König, IR., Hengstenberg, C., Fischer, M., Stark, K., Grosshennig, A., Preuss, M., Wichmann, HE., Schreiber, S., Ouwehand, W., Deloukas, P., Scholz, M., Cambien, F., Goodall, A., Li, M., Chen, Z., Wilensky, R., Matthai, W., Qasim, A., Hakonarson, HH., Devaney, J., Burnett, MS., Pichard, AD., Kent, KM., Satler, L., Lindsay, JM., Waksman, R., Knouff, CW., Waterworth, DM., Walker, MC., Mooser, V., Epstein, SE., Scheffold, T., Berger, K., Huge, A., Martinelli, N., Olivieri, O., Corrocher, R., König, I., Hólm, H., Thorleifsson, G., Thorsteinsdottir, U., Stefansson, K., Do, R., Xie, C., Siscovick, D., Matise, T., Buyske, 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D., Bakker, S.J., Beilby, J., Bergman, R.N., Bergmann, S., Biffar, R., Blangero, J., Boomsma, D.I., Bornstein, S.R., Bovet, P., Brambilla, P., Brown, M.J., Campbell, H., Caulfield, M.J., Chakravarti, A., Collins, R., Collins, F.S., Crawford, D.C., Cupples, L.A., Danesh, J., de Faire, U., den Ruijter, H.M., Erbel, R., Eriksson, J.G., Farrall, M., Ferrannini, E., Ferrières, J., Ford, I., Forouhi, N.G., Forrester, T., Gansevoort, R.T., Gejman, P.V., Gieger, C., Golay, A., Gottesman, O., Gudnason, V., Gyllensten, U., Haas, D.W., Hall, A.S., Harris, T.B., Hattersley, A.T., Heath, A.C., Hicks, A.A., Hindorff, L.A., Hingorani, A.D., Hofman, A., Hovingh, G.K., Humphries, S.E., Hunt, S.C., Hypponen, E., Jacobs, K.B., Jarvelin, M.R., Jousilahti, P., Jula, A.M., Kaprio, J., Kastelein, J.J., Kayser, M., Kee, F., Keinanen-Kiukaanniemi, S.M., Kiemeney, L.A., Kooner, J.S., Koskinen, S., Kovacs, P., Kraja, A.T., Kumari, M., Kuusisto, J., Lakka, T.A., Langenberg, C., Le Marchand, L., Lehtimäki, T., Lupoli, S., Madden, P.A., Männistö, S., Manunta, P., Marette, A., Matise, T.C., McKnight, B., Meitinger, T., Moll, F.L., Montgomery, G.W., Morris, A.D., Morris, A.P., Murray, J.C., Nelis, M., Ohlsson, C., Oldehinkel, A.J., Ong, K.K., Ouwehand, W.H., Pasterkamp, G., Peters, A., Pramstaller, P.P., Price, J.F., Qi, L., Raitakari, O.T., Rankinen, T., Rao, D.C., Rice, T.K., Rudan, I., Samani, N.J., Saramies, J., Sarzynski, M.A., Schwarz, P.E., Sebert, S., Sever, P., Shuldiner, A.R., Sinisalo, J., Steinthorsdottir, V., Stolk, R.P., Tardif, J.C., Tönjes, A., Tremblay, A., Tremoli, E., Virtamo, J., Vohl, M.C., Amouyel, P., Asselbergs, F.W., Assimes, T.L., Bochud, M., Boehm, B.O., Bottinger, E.P., Bouchard, C., Cauchi, S., Chambers, J.C., Chanock, S.J., Cooper, R.S., de Bakker, P.I., Dedoussis, G., Ferrucci, L., Franks, P.W., Froguel, P., Groop, L.C., Haiman, C.A., Hamsten, A., Hayes, M.G., Hui, J., Hunter, D.J., Hveem, K., Jukema, J.W., Kaplan, R.C., Kivimaki, M., Kuh, D., Laakso, M., Liu, Y., Martin, N.G., März, W., Melbye, M., Moebus, S., Munroe, P.B., Njølstad, I., Oostra, B.A., Palmer, C.N., Pedersen, N.L., Perola, M., Pérusse, L., Powell, J.E., Power, C., Quertermous, T., Rauramaa, R., Reinmaa, E., Ridker, P.M., Rivadeneira, F., Rotter, J.I., Saaristo, T.E., Saleheen, D., Schlessinger, D., Slagboom, P.E., Spector, T.D., Strauch, K., Stumvoll, M., Tuomilehto, J., Uusitupa, M., Völzke, H., Walker, M., Wareham, N.J., Watkins, H., Wichmann, H.E., Wilson, J.F., Zanen, P., Heid, I.M., Lindgren, C.M., Mohlke, K.L., Speliotes, E.K., Barroso, I., Fox, C.S., North, K.E., Strachan, D.P., Beckmann, J.S., Berndt, S.I., Boehnke, M., Borecki, I.B., McCarthy, M.I., Metspalu, A., Uitterlinden, A.G., van Duijn, C.M., Willer, C.J., Price, A.L., Lettre, G., Loos, R.J., Weedon, M.N., Ingelsson, E., O'Connell, J.R., Abecasis, G.R., Chasman, D.I., Goddard, M.E., Visscher, P.M., Hirschhorn, J.N., and Frayling, T.M.
Abstract: Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
Published: 2014

18. The association of TNFr2 and TNFα with insulin resistance and the influence of adipose tissue biomarkers in humans

Author: Hivert, MF, Sullivan, LM, Shrader, P, Fox, CS, Nathan, DM, D’Agostino, RB, Wilson, PWF, Benjamin, EJ, and Meigs, JB
Subjects: Male, Tumor Necrosis Factor-alpha, nutritional and metabolic diseases, Middle Aged, Article, Adipose Tissue, Multivariate Analysis, Humans, Receptors, Tumor Necrosis Factor, Type II, Female, Resistin, Adiponectin, Insulin Resistance, Biomarkers, Triglycerides, Aged
Abstract: Tumor necrosis factor alpha (TNFalpha) is a proinflammatory adipokine hypothesized to link obesity with insulin resistance. Functional studies suggest that TNFalpha acts through pathways involving adipokines and fatty acids to induce insulin resistance. We tested the hypothesis that the association of measures of TNFalpha activity with insulin resistance is independent of obesity and adipose tissue biomarkers. We analyzed data from 2131 participants (without diabetes) of the Framingham Offspring Study examination 7. The outcome of interest was insulin resistance, measured using the homeostasis model assessment (HOMA-IR). Tumor necrosis factor alpha activity was measured by plasma tumor necrosis factor alpha receptor 2 (TNFr2) or TNFalpha; possible confounders included adipose tissue biomarkers (plasma adiponectin, resistin, and triglycerides). We used multivariable age- and sex-adjusted linear regression analyses to adjust for waist circumference and for biomarkers individually and simultaneously, and in biomarker-stratified (above and below median) models. We found that TNFr2 was positively associated with HOMA-IR (r = 0.21, P.0001). In age- and sex-adjusted model, for each increase of 1 standard deviation of TNFr2 (SD = 746 pg/mL), the log (HOMA-IR) value was increased by 0.11 units (P.0001). Adjustment for waist circumference reduced the TNFr2 beta-coefficient (by about 45%), but the association between TNFr2 and HOMA-IR remained significant (P.0001). Tumor necrosis factor alpha receptor 2 was still associated to HOMA-IR after adding adiponectin, resistin, and triglycerides (individually and simultaneously). We found similar associations with plasma levels of TNFalpha. We conclude that, in a representative community sample, measures of TNFalpha activity are associated with insulin resistance, even after accounting for central adiposity and other adipose tissue biomarkers.
Published: 2009

19. Translating the A1C assay into estimated average glucose values

Author: Nathan, Dm, Kuenen, J, Borg, R, Zheng, H, Schoenfeld, D, Heine, Rj, and Lapolla, Annunziata
Published: 2009

20. Translating the A1C assay into estimated average glucose values

Author: Nathan, Dm, Kuenen, J, Borg, R, Zheng, H, Schoenfeld, D, Heine, Rj, Kerner, Gs, VAN IPEREN, A, Horton, E, Cohen, A, HERZLINGER BOTEIN, S, Paradis, J, Saudek, C, Moore, K, Greene, A, Islas, M, Nerup, J, Glumer, C, Mosca, A, Lapolla, Annunziata, Fedele, Domenico, and Sartore, Giovanni
Published: 2008

21. Consensus statement on the worldwide standardization of the hemoglobin A1C measurement - The American Diabetes Association, European Association for the Study of Diabetes, International Federation of Clinical Chemistry and Laboratory Medicine, and the International Diabetes Federation

Author: Hicks, J, Muller, M, Panteghini, M, John, G, Deeb, L, Buse, J, Nathan, Dm, Kahn, R, Ferrannini, Eleuterio, Heine, R, Silink, M, and Mbanya, Jc
Published: 2007

22. Genome-wide association for abdominal subcutaneous and visceral adipose reveals a novel locus for visceral fat in women.

Author: GIANT Consortium, MAGIC Consortium, GLGC Consortium, Dupuis, J., Langenberg, C., Prokopenko, I., Saxena, R., Soranzo, N., Jackson, AU., Wheeler, E., Glazer, NL., Bouatia-Naji, N., Gloyn, AL., Lindgren, CM., Mägi, R., Morris, AP., Randall, J., Johnson, T., Elliott, P., Rybin, D., Thorleifsson, G., Steinthorsdottir, V., Henneman, P., Grallert, H., Dehghan, A., Hottenga, JJ., Franklin, CS., Navarro, P., Song, K., Goel, A., Perry, JR., Egan, JM., Lajunen, T., Grarup, N., Sparsø, T., Doney, A., Voight, BF., Stringham, HM., Li, M., Kanoni, S., Shrader, P., Cavalcanti-Proença, C., Kumari, M., Qi, L., Timpson, NJ., Gieger, C., Zabena, C., Rocheleau, G., Ingelsson, E., An, P., O'Connell, J., Luan£££Jian'an£££ J., Elliott, A., McCarroll, SA., Payne, F., Roccasecca, RM., Pattou, F., Sethupathy, P., Ardlie, K., Ariyurek, Y., Balkau, B., Barter, P., Beilby, JP., Ben-Shlomo, Y., Benediktsson, R., Bennett, AJ., Bergmann, S., Bochud, M., Boerwinkle, E., Bonnefond, A., Bonnycastle, LL., Borch-Johnsen, K., Böttcher, Y., Brunner, E., Bumpstead, SJ., Charpentier, G., Chen, YD., Chines, P., Clarke, R., Coin, LJ., Cooper, MN., Cornelis, M., Crawford, G., Crisponi, L., Day, IN., de Geus EJ., Delplanque, J., Dina, C., Erdos, MR., Fedson, AC., Fischer-Rosinsky, A., Forouhi, NG., Fox, CS., Frants, R., Franzosi, MG., Galan, P., Goodarzi, MO., Graessler, J., Groves, CJ., Grundy, S., Gwilliam, R., Gyllensten, U., Hadjadj, S., Hallmans, G., Hammond, N., Han, X., Hartikainen, AL., Hassanali, N., Hayward, C., Heath, SC., Hercberg, S., Herder, C., Hicks, AA., Hillman, DR., Hingorani, AD., Hofman, A., Hui, J., Hung, J., Isomaa, B., Johnson, PR., Jørgensen, T., Jula, A., Kaakinen, M., Kaprio, J., Kesaniemi, YA., Kivimaki, M., Knight, B., Koskinen, S., Kovacs, P., Kyvik, KO., Lathrop, GM., Lawlor, DA., Le Bacquer, O., Lecoeur, C., Li, Y., Lyssenko, V., Mahley, R., Mangino, M., Manning, AK., Martínez-Larrad£££María Teresa£££ MT., McAteer, JB., McCulloch, LJ., McPherson, R., Meisinger, C., Melzer, D., Meyre, D., Mitchell, BD., Morken, MA., Mukherjee, S., Naitza, S., Narisu, N., Neville, MJ., Oostra, BA., Orrù, M., Pakyz, R., Palmer, CN., Paolisso, G., Pattaro, C., Pearson, D., Peden, JF., Pedersen, NL., Perola, M., Pfeiffer, AF., Pichler, I., Polasek, O., Posthuma, D., Potter, SC., Pouta, A., Province, MA., Psaty, BM., Rathmann, W., Rayner, NW., Rice, K., Ripatti, S., Rivadeneira, F., Roden, M., Rolandsson, O., Sandbaek, A., Sandhu, M., Sanna, S., Sayer, AA., Scheet, P., Scott, LJ., Seedorf, U., Sharp, SJ., Shields, B., Sigurðsson, G., Sijbrands, EJ., Silveira, A., Simpson, L., Singleton, A., Smith, NL., Sovio, U., Swift, A., Syddall, H., Syvänen, AC., Tanaka, T., Thorand, B., Tichet, J., Tönjes, A., Tuomi, T., Uitterlinden, AG., van Dijk KW., van Hoek, M., Varma, D., Visvikis-Siest, S., Vitart, V., Vogelzangs, N., Waeber, G., Wagner, PJ., Walley, A., Walters, GB., Ward, KL., Watkins, H., Weedon, MN., Wild, SH., Willemsen, G., Witteman, JC., Yarnell, JW., Zeggini, E., Zelenika, D., Zethelius, B., Zhai, G., Zhao, JH., Zillikens, MC., Borecki, IB., Loos, RJ., Meneton, P., Magnusson, PK., Nathan, DM., Williams, GH., Hattersley, AT., Silander, K., Salomaa, V., Smith, GD., Bornstein, SR., Schwarz, P., Spranger, J., Karpe, F., Shuldiner, AR., Cooper, C., Dedoussis, GV., Serrano-Ríos, M., Morris, AD., Lind, L., Palmer, LJ., Hu, FB., Franks, PW., Ebrahim, S., Marmot, M., Kao, WH., Pankow, JS., Sampson, MJ., Kuusisto, J., Laakso, M., Hansen, T., Pedersen, O., Pramstaller, PP., Wichmann, HE., Illig, T., Rudan, I., Wright, AF., Stumvoll, M., Campbell, H., Wilson, JF., Hamsten, A., Bergman, RN., Buchanan, TA., Collins, FS., Mohlke, KL., Tuomilehto, J., Valle, TT., Altshuler, D., Rotter, JI., Siscovick, DS., Penninx, BW., Boomsma, ID., Deloukas, P., Spector, TD., Frayling, TM., Ferrucci, L., Kong, A., Thorsteinsdottir, U., Stefansson, K., van Duijn CM., Aulchenko, YS., Cao, A., Scuteri, A., Schlessinger, D., Uda, M., Ruokonen, A., Jarvelin, MR., Waterworth, DM., Vollenweider, P., Peltonen, L., Mooser, V., Abecasis, RG., Wareham, NJ., Sladek, R., Froguel, P., Watanabe, RM., Meigs, JB., Groop, L., Boehnke, M., McCarthy, MI., Florez, JC., Barroso£££Inês£££ I., Fox, C.S., Liu, Y., White, C.C., Feitosa, M., Smith, A.V., Heard-Costa, N., Lohman, K., Johnson, A.D., Foster, M.C., Greenawalt, D.M., Griffin, P., Ding, J., Newman, A.B., Tylavsky, F., Miljkovic, I., Kritchevsky, S.B., Launer, L., Garcia, M., Eiriksdottir, G., Carr, J.J., Gudnason, V., Harris, T.B., Cupples, L.A., Borecki, I.B., GIANT Consortium, MAGIC Consortium, GLGC Consortium, Dupuis, J., Langenberg, C., Prokopenko, I., Saxena, R., Soranzo, N., Jackson, AU., Wheeler, E., Glazer, NL., Bouatia-Naji, N., Gloyn, AL., Lindgren, CM., Mägi, R., Morris, AP., Randall, J., Johnson, T., Elliott, P., Rybin, D., Thorleifsson, G., Steinthorsdottir, V., Henneman, P., Grallert, H., Dehghan, A., Hottenga, JJ., Franklin, CS., Navarro, P., Song, K., Goel, A., Perry, JR., Egan, JM., Lajunen, T., Grarup, N., Sparsø, T., Doney, A., Voight, BF., Stringham, HM., Li, M., Kanoni, S., Shrader, P., Cavalcanti-Proença, C., Kumari, M., Qi, L., Timpson, NJ., Gieger, C., Zabena, C., Rocheleau, G., Ingelsson, E., An, P., O'Connell, J., Luan£££Jian'an£££ J., Elliott, A., McCarroll, SA., Payne, F., Roccasecca, RM., Pattou, F., Sethupathy, P., Ardlie, K., Ariyurek, Y., Balkau, B., Barter, P., Beilby, JP., Ben-Shlomo, Y., Benediktsson, R., Bennett, AJ., Bergmann, S., Bochud, M., Boerwinkle, E., Bonnefond, A., Bonnycastle, LL., Borch-Johnsen, K., Böttcher, Y., Brunner, E., Bumpstead, SJ., Charpentier, G., Chen, YD., Chines, P., Clarke, R., Coin, LJ., Cooper, MN., Cornelis, M., Crawford, G., Crisponi, L., Day, IN., de Geus EJ., Delplanque, J., Dina, C., Erdos, MR., Fedson, AC., Fischer-Rosinsky, A., Forouhi, NG., Fox, CS., Frants, R., Franzosi, MG., Galan, P., Goodarzi, MO., Graessler, J., Groves, CJ., Grundy, S., Gwilliam, R., Gyllensten, U., Hadjadj, S., Hallmans, G., Hammond, N., Han, X., Hartikainen, AL., Hassanali, N., Hayward, C., Heath, SC., Hercberg, S., Herder, C., Hicks, AA., Hillman, DR., Hingorani, AD., Hofman, A., Hui, J., Hung, J., Isomaa, B., Johnson, PR., Jørgensen, T., Jula, A., Kaakinen, M., Kaprio, J., Kesaniemi, YA., Kivimaki, M., Knight, B., Koskinen, S., Kovacs, P., Kyvik, KO., Lathrop, GM., Lawlor, DA., Le Bacquer, O., Lecoeur, C., Li, Y., Lyssenko, V., Mahley, R., Mangino, M., Manning, AK., Martínez-Larrad£££María Teresa£££ MT., McAteer, JB., McCulloch, LJ., McPherson, R., Meisinger, C., Melzer, D., Meyre, D., Mitchell, BD., Morken, MA., Mukherjee, S., Naitza, S., Narisu, N., Neville, MJ., Oostra, BA., Orrù, M., Pakyz, R., Palmer, CN., Paolisso, G., Pattaro, C., Pearson, D., Peden, JF., Pedersen, NL., Perola, M., Pfeiffer, AF., Pichler, I., Polasek, O., Posthuma, D., Potter, SC., Pouta, A., Province, MA., Psaty, BM., Rathmann, W., Rayner, NW., Rice, K., Ripatti, S., Rivadeneira, F., Roden, M., Rolandsson, O., Sandbaek, A., Sandhu, M., Sanna, S., Sayer, AA., Scheet, P., Scott, LJ., Seedorf, U., Sharp, SJ., Shields, B., Sigurðsson, G., Sijbrands, EJ., Silveira, A., Simpson, L., Singleton, A., Smith, NL., Sovio, U., Swift, A., Syddall, H., Syvänen, AC., Tanaka, T., Thorand, B., Tichet, J., Tönjes, A., Tuomi, T., Uitterlinden, AG., van Dijk KW., van Hoek, M., Varma, D., Visvikis-Siest, S., Vitart, V., Vogelzangs, N., Waeber, G., Wagner, PJ., Walley, A., Walters, GB., Ward, KL., Watkins, H., Weedon, MN., Wild, SH., Willemsen, G., Witteman, JC., Yarnell, JW., Zeggini, E., Zelenika, D., Zethelius, B., Zhai, G., Zhao, JH., Zillikens, MC., Borecki, IB., Loos, RJ., Meneton, P., Magnusson, PK., Nathan, DM., Williams, GH., Hattersley, AT., Silander, K., Salomaa, V., Smith, GD., Bornstein, SR., Schwarz, P., Spranger, J., Karpe, F., Shuldiner, AR., Cooper, C., Dedoussis, GV., Serrano-Ríos, M., Morris, AD., Lind, L., Palmer, LJ., Hu, FB., Franks, PW., Ebrahim, S., Marmot, M., Kao, WH., Pankow, JS., Sampson, MJ., Kuusisto, J., Laakso, M., Hansen, T., Pedersen, O., Pramstaller, PP., Wichmann, HE., Illig, T., Rudan, I., Wright, AF., Stumvoll, M., Campbell, H., Wilson, JF., Hamsten, A., Bergman, RN., Buchanan, TA., Collins, FS., Mohlke, KL., Tuomilehto, J., Valle, TT., Altshuler, D., Rotter, JI., Siscovick, DS., Penninx, BW., Boomsma, ID., Deloukas, P., Spector, TD., Frayling, TM., Ferrucci, L., Kong, A., Thorsteinsdottir, U., Stefansson, K., van Duijn CM., Aulchenko, YS., Cao, A., Scuteri, A., Schlessinger, D., Uda, M., Ruokonen, A., Jarvelin, MR., Waterworth, DM., Vollenweider, P., Peltonen, L., Mooser, V., Abecasis, RG., Wareham, NJ., Sladek, R., Froguel, P., Watanabe, RM., Meigs, JB., Groop, L., Boehnke, M., McCarthy, MI., Florez, JC., Barroso£££Inês£££ I., Fox, C.S., Liu, Y., White, C.C., Feitosa, M., Smith, A.V., Heard-Costa, N., Lohman, K., Johnson, A.D., Foster, M.C., Greenawalt, D.M., Griffin, P., Ding, J., Newman, A.B., Tylavsky, F., Miljkovic, I., Kritchevsky, S.B., Launer, L., Garcia, M., Eiriksdottir, G., Carr, J.J., Gudnason, V., Harris, T.B., Cupples, L.A., and Borecki, I.B.
Abstract: Body fat distribution, particularly centralized obesity, is associated with metabolic risk above and beyond total adiposity. We performed genome-wide association of abdominal adipose depots quantified using computed tomography (CT) to uncover novel loci for body fat distribution among participants of European ancestry. Subcutaneous and visceral fat were quantified in 5,560 women and 4,997 men from 4 population-based studies. Genome-wide genotyping was performed using standard arrays and imputed to ~2.5 million Hapmap SNPs. Each study performed a genome-wide association analysis of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), VAT adjusted for body mass index, and VAT/SAT ratio (a metric of the propensity to store fat viscerally as compared to subcutaneously) in the overall sample and in women and men separately. A weighted z-score meta-analysis was conducted. For the VAT/SAT ratio, our most significant p-value was rs11118316 at LYPLAL1 gene (p = 3.1 × 10E-09), previously identified in association with waist-hip ratio. For SAT, the most significant SNP was in the FTO gene (p = 5.9 × 10E-08). Given the known gender differences in body fat distribution, we performed sex-specific analyses. Our most significant finding was for VAT in women, rs1659258 near THNSL2 (p = 1.6 × 10-08), but not men (p = 0.75). Validation of this SNP in the GIANT consortium data demonstrated a similar sex-specific pattern, with observed significance in women (p = 0.006) but not men (p = 0.24) for BMI and waist circumference (p = 0.04 [women], p = 0.49 [men]). Finally, we interrogated our data for the 14 recently published loci for body fat distribution (measured by waist-hip ratio adjusted for BMI); associations were observed at 7 of these loci. In contrast, we observed associations at only 7/32 loci previously identified in association with BMI; the majority of overlap was observed with SAT. Genome-wide association for visceral and subcutaneous fat revealed a SNP for VAT in
Published: 2012

23. Effects of fasting and glucose infusion on basal and overnight leptin concentrations in normal-weight women

Author: Grinspoon, SK, primary, Askari, H, additional, Landt, ML, additional, Nathan, DM, additional, Schoenfeld, DA, additional, Hayden, DL, additional, Laposata, M, additional, Hubbard, J, additional, and Klibanski, A, additional
Published: 1997
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24. Plasma 25-hydroxyvitamin D and progression to diabetes in patients at risk for diabetes: an ancillary analysis in the Diabetes Prevention Program.

Author: Pittas AG, Nelson J, Mitri J, Hillmann W, Garganta C, Nathan DM, Hu FB, Dawson-Hughes B, Diabetes Prevention Program Research Group, Pittas, Anastassios G, Nelson, Jason, Mitri, Joanna, Hillmann, William, Garganta, Cheryl, Nathan, David M, Hu, Frank B, and Dawson-Hughes, Bess
Abstract: Objective: To investigate the association between vitamin D status, assessed by plasma 25-hydroxyvitamin D, and risk of incident diabetes.Research Design and Methods: Prospective observational study with a mean follow-up of 2.7 years in the Diabetes Prevention Program (DPP), a multicenter trial comparing different strategies for prevention of diabetes in patients with prediabetes. We assessed the association between plasma 25-hydroxyvitamin D, measured repeatedly during follow-up, and incident diabetes in the combined placebo (n = 1,022) and intensive lifestyle (n = 1,017) randomized arms of the DPP. Variables measured at multiple study time points (25-hydroxyvitamin D, BMI, and physical activity) entered the analyses as time-varying "lagged" covariates, as the mean of the previous and current visits at which diabetes status was assessed.Results: After multivariate adjustment, including for the DPP intervention, participants in the highest tertile of 25-hydroxyvitamin D (median concentration, 30.1 ng/mL) had a hazard ratio of 0.72 (95% CI 0.56-0.90) for developing diabetes compared with participants in the lowest tertile (median concentration, 12.8 ng/mL). The association was in the same direction in placebo (0.70; 0.52-0.94) versus lifestyle arm (0.80; 0.54-1.17).Conclusions: Higher plasma 25-hydroxyvitamin D, assessed repeatedly, was associated with lower risk of incident diabetes in high-risk patients, after adjusting for lifestyle interventions (dietary changes, increased physical activity, and weight loss) known to decrease diabetes risk. Because of the observational nature of the study, the potential association between vitamin D and diabetes needs to be confirmed in intervention studies. [ABSTRACT FROM AUTHOR]
Published: 2012
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25. Myocardial structure, function, and scar in patients with type 1 diabetes mellitus.

Author: Turkbey EB, Backlund JY, Genuth S, Jain A, Miao C, Cleary PA, Lachin JM, Nathan DM, van der Geest RJ, Soliman EZ, Liu CY, Lima JA, Bluemke DA, DCCT/EDIC Research Group, Turkbey, Evrim B, Backlund, Jye-Yu C, Genuth, Saul, Jain, Aditya, Miao, Cuilian, and Cleary, Patricia A
Published: 2011
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26. Long-term renal outcomes of patients with type 1 diabetes mellitus and microalbuminuria: an analysis of the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications cohort.

Author: de Boer IH, Rue TC, Cleary PA, Lachin JM, Molitch ME, Steffes MW, Sun W, Zinman B, Brunzell JD, White NH, Danis RP, Davis MD, Hainsworth D, Hubbard LD, Nathan DM, and Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study Research Group
Published: 2011
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27. Levels of oxidized LDL and advanced glycation end products-modified LDL in circulating immune complexes are strongly associated with increased levels of carotid intima-media thickness and its progression in type 1 diabetes.

Author: Lopes-Virella MF, Hunt KJ, Baker NL, Lachin J, Nathan DM, Virella G, Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group, Lopes-Virella, Maria F, Hunt, Kelly J, Baker, Nathaniel L, Lachin, John, Nathan, David M, and Virella, G
Abstract: Objective: High cholesterol levels in circulating immune complexes (IC), surrogate markers of modified LDL, are associated with increased carotid intima-media thickness (IMT) and cardiovascular events in type 1 diabetes. Different modifications of LDL are involved in IC formation, but which of these are predictive of vascular events is not known. Therefore, we measured oxidized LDL (oxLDL), advanced glycation end products-modified LDL (AGE-LDL), and malondialdehyde-modified LDL (MDA-LDL) in IC and determined their relationship with increased carotid IMT and compared the strength of the association with that observed with conventional risk factors.Research Design and Methods: Levels of oxLDL, AGE-LDL, and MDA-LDL were measured in circulating IC isolated from sera of 479 patients of the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) cohort, collected at baseline. Internal and common carotid IMT were measured 8 and 14 years later by DCCT/EDIC.Results: OxLDL, AGE-LDL, and MDA-LDL levels in circulating IC were significantly correlated with diabetes duration, BMI, and lipid and blood pressure, but not with age. Multivariate logistic regression models indicated that individuals in the highest versus lowest quartile of oxLDL and AGE-LDL in IC had a 6.11-fold [confidence interval (CI) 2.51-14.8] and a 6.4-fold (CI 2.53-16.2) increase in the odds of having high carotid IMT, respectively, after adjusting for conventional risk factors. Parallel analyses resulted in odds ratios of 2.62 (CI 1.24, 5.55) for LDL-C, 1.45 (CI 0.69, 3.03) for diastolic blood pressure, and 2.33 (CI 1.09, 4.99) for A1C.Conclusions: OxLDL and AGE-LDL in circulating IC were significantly associated with progression and increased levels of carotid IMT in type 1 diabetes. [ABSTRACT FROM AUTHOR]
Published: 2011
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28. Associations between features of glucose exposure and A1C: the A1C-Derived Average Glucose (ADAG) study.

Author: Borg R, Kuenen JC, Carstensen B, Zheng H, Nathan DM, Heine RJ, Nerup J, Borch-Johnsen K, Witte DR, ADAG Study Group, Borg, Rikke, Kuenen, Judith C, Carstensen, Bendix, Zheng, Hui, Nathan, David M, Heine, Robert J, Nerup, Jorn, Borch-Johnsen, Knut, and Witte, Daniel R
Abstract: Objective: Various methods are used to quantify postprandial glycemia or glucose variability, but few have been compared and none are standardized. Our objective was to examine the relationship among common indexes of postprandial glycemia, overall hyperglycemia, glucose variability, and A1C using detailed glucose measures obtained during everyday life and to study which blood glucose values of the day provide the strongest prediction of A1C.Research Design and Methods: In the A1C-Derived Average Glucose (ADAG) study, glucose levels were monitored in 507 participants (268 type 1 diabetic, 159 type 2 diabetic, and 80 nondiabetic subjects) with continuous glucose monitoring (CGM) and frequent self-monitoring of blood glucose (SMBG) during 16 weeks. We calculated several indexes of glycemia and analyzed their intercorrelations. The association between glucose measurements at different times of the day (pre- and postprandial) and A1C was examined using multiple linear regression.Results: Indexes of glucose variability showed strong intercorrelation. Among postprandial indexes, the area under the glucose curve calculated from CGM 2 h after a meal correlated well with the 90-min SMBG postprandial measurements. Fasting blood glucose (FBG) levels were only moderately correlated with indexes of hyperglycemia and average or postprandial glucose levels. Indexes derived with SMBG strongly correlated with those from CGM. Some SMBG time points had a stronger association with A1C than others. Overall, preprandial glucose values had a stronger association with A1C than postprandial values for both diabetes types, particularly for type 2 diabetes.Conclusions: Indexes of glucose variability and average and postprandial glycemia intercorrelate strongly within each category. Variability indexes are weakly correlated with the other categories, indicating that these measures convey different information. FBG is not a clear indicator of general glycemia. Preprandial glucose values have a larger impact on A1C levels than postprandial values. [ABSTRACT FROM AUTHOR]
Published: 2010
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29. Modern-day clinical course of type 1 diabetes mellitus after 30 years' duration: the diabetes control and complications trial/epidemiology of diabetes interventions and complications and Pittsburgh epidemiology of diabetes complications experience (1983-2005)

Author: Nathan DM, Zinman B, Cleary PA, Backlund JY, Genuth S, Miller R, Orchard TJ, and Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Research Group
Published: 2009
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30. Medical management of hyperglycemia in type 2 diabetes: a consensus algorithm for the initiation and adjustment of therapy: a consensus statement of the American Diabetes Association and the European Association for the Study of Diabetes.

Author: Nathan DM, Buse JB, Davidson MB, Ferrannini E, Holman RR, Sherwin R, Zinman B, American Diabetes Association, Nathan, David M, Buse, John B, Davidson, Mayer B, Ferrannini, Ele, Holman, Rury R, Sherwin, Robert, Zinman, Bernard, and European Association for Study of Diabetes
Abstract: The consensus algorithm for the medical management of type 2 diabetes was published in August 2006 with the expectation that it would be updated, based on the availability of new interventions and new evidence to establish their clinical role. The authors continue to endorse the principles used to develop the algorithm and its major features. We are sensitive to the risks of changing the algorithm cavalierly or too frequently, without compelling new information. An update to the consensus algorithm published in January 2008 specifically addressed safety issues surrounding the thiazolidinediones. In this revision, we focus on the new classes of medications that now have more clinical data and experience. [ABSTRACT FROM AUTHOR]
Published: 2009
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31. Effect of aging on A1C levels in individuals without diabetes: evidence from the Framingham Offspring Study and the National Health and Nutrition Examination Survey 2001-2004.

Author: Pani LN, Korenda L, Meigs JB, Driver C, Chamany S, Fox CS, Sullivan L, D'Agostino RB, Nathan DM, Pani, Lydie N, Korenda, Leslie, Meigs, James B, Driver, Cynthia, Chamany, Shadi, Fox, Caroline S, Sullivan, Lisa, D'Agostino, Ralph B, and Nathan, David M
Abstract: Objective: Although glycemic levels are known to rise with normal aging, the nondiabetic A1C range is not age specific. We examined whether A1C was associated with age in nondiabetic subjects and in subjects with normal glucose tolerance (NGT) in two population-based cohorts.Research Design and Methods: We performed cross-sectional analyses of A1C across age categories in 2,473 nondiabetic participants of the Framingham Offspring Study (FOS) and in 3,270 nondiabetic participants from the National Health and Nutrition Examination Survey (NHANES) 2001-2004. In FOS, we examined A1C by age in a subset with NGT, i.e., after excluding those with impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT). Multivariate analyses were performed, adjusting for sex, BMI, fasting glucose, and 2-h postload glucose values.Results: In the FOS and NHANES cohorts, A1C levels were positively associated with age in nondiabetic subjects. Linear regression revealed 0.014- and 0.010-unit increases in A1C per year in the nondiabetic FOS and NHANES populations, respectively. The 97.5th percentiles for A1C were 6.0% and 5.6% for nondiabetic individuals aged <40 years in FOS and NHANES, respectively, compared with 6.6% and 6.2% for individuals aged >or=70 years (P(trend) < 0.001). The association of A1C with age was similar when restricted to the subset of FOS subjects with NGT and after adjustments for sex, BMI, fasting glucose, and 2-h postload glucose values.Conclusions: A1C levels are positively associated with age in nondiabetic populations even after exclusion of subjects with IFG and/or IGT. Further studies are needed to determine whether age-specific diagnostic and treatment criteria would be appropriate. [ABSTRACT FROM AUTHOR]
Published: 2008
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32. Translating the A1C assay into estimated average glucose values.

Author: Nathan DM, Kuenen J, Borg R, Zheng H, Schoenfeld D, Heine RJ, A1c-Derived Average Glucose Study Group, Nathan, David M, Kuenen, Judith, Borg, Rikke, Zheng, Hui, Schoenfeld, David, and Heine, Robert J
Abstract: Objective: The A1C assay, expressed as the percent of hemoglobin that is glycated, measures chronic glycemia and is widely used to judge the adequacy of diabetes treatment and adjust therapy. Day-to-day management is guided by self-monitoring of capillary glucose concentrations (milligrams per deciliter or millimoles per liter). We sought to define the mathematical relationship between A1C and average glucose (AG) levels and determine whether A1C could be expressed and reported as AG in the same units as used in self-monitoring.Research Design and Methods: A total of 507 subjects, including 268 patients with type 1 diabetes, 159 with type 2 diabetes, and 80 nondiabetic subjects from 10 international centers, was included in the analyses. A1C levels obtained at the end of 3 months and measured in a central laboratory were compared with the AG levels during the previous 3 months. AG was calculated by combining weighted results from at least 2 days of continuous glucose monitoring performed four times, with seven-point daily self-monitoring of capillary (fingerstick) glucose performed at least 3 days per week.Results: Approximately 2,700 glucose values were obtained by each subject during 3 months. Linear regression analysis between the A1C and AG values provided the tightest correlations (AG(mg/dl) = 28.7 x A1C - 46.7, R(2) = 0.84, P < 0.0001), allowing calculation of an estimated average glucose (eAG) for A1C values. The linear regression equations did not differ significantly across subgroups based on age, sex, diabetes type, race/ethnicity, or smoking status.Conclusions: A1C levels can be expressed as eAG for most patients with type 1 and type 2 diabetes. [ABSTRACT FROM AUTHOR]
Published: 2008
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33. Measuring psychological insulin resistance: barriers to insulin use.

Author: Larkin ME, Capasso VA, Chen C, Mahoney EK, Hazard B, Cagliero E, and Nathan DM
Abstract: PURPOSE: The purpose of this study is to explore the attitudes that contribute to psychological insulin resistance (PIR) in insulin-naive patients with type 2 diabetes and to identify predictors of PIR. METHODS: A prospective study using 2 self-report surveys and incorporating demographic and health variables was conducted to determine the prevalence of PIR among a sample of 100 adult, insulin-naive patients with type 2 diabetes at an outpatient diabetes center in a university-affiliated teaching hospital. RESULTS: Thirty-three percent of patients with type 2 diabetes were unwilling to take insulin. The most commonly expressed negative attitudes were concern regarding hypoglycemia, permanent need for insulin therapy, less flexibility, and feelings of failure. Less than 40% expressed fear of self-injection or thought that injections were painful. However, compared with willing subjects, unwilling subjects were more likely to fear injections and thought injections would be painful, life would be less flexible, and taking insulin meant health would deteriorate (P < .005 for all comparisons). Poorer general health and higher depression scores also correlated with PIR. CONCLUSIONS: The results of the surveys, which were generally consistent, identified several remediable misconceptions regarding insulin therapy and suggest targets for educational interventions. [ABSTRACT FROM AUTHOR]
Published: 2008
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34. How doctors choose medications to treat type 2 diabetes: a national survey of specialists and academic generalists.

Author: Grant RW, Wexler DJ, Watson AJ, Lester WT, Cagliero E, Campbell EG, Nathan DM, Grant, Richard W, Wexler, Deborah J, Watson, Alice J, Lester, William T, Cagliero, Enrico, Campbell, Eric G, and Nathan, David M
Abstract: Objective: Glycemic control remains suboptimal despite the wide range of available medications. More effective medication prescription might result in better control. However, the process by which physicians choose glucose-lowering medicines is poorly understood. We sought to study the means by which physicians choose medications for type 2 diabetic patients.Research Design and Methods: We surveyed 886 physician members of either the Society of General Internal Medicine (academic generalists, response rate 30%) or the American Diabetes Association (specialists, response rate 23%) currently managing patients with type 2 diabetes. Respondents weighed the importance of 15 patient, physician, and nonclinical factors when deciding which medications to prescribe for type 2 diabetic subjects at each of three management stages (initiation, use of second-line oral agents, and insulin).Results: Respondents reported using a median of five major considerations (interquartile range 4-6) at each stage. Frequently cited major considerations included overall assessment of the patient's health/comorbidity, A1C level, and patient's adherence behavior but not expert guidelines/hospital algorithms or patient age. For insulin initiation, academic generalists placed greater emphasis on patient adherence (76 vs. 60% of specialists, P < 0.001). These generalists also identified patient fear of injections (68%) and patient desire to prolong noninsulin therapy (68%) as major insulin barriers. Overall, qualitative factors (e.g., adherence, motivation, overall health assessment) were somewhat more highly considered than quantitative factors (e.g., A1C, age, weight) with mean aggregate scores of 7.3 vs. 6.9 on a scale of 0-10, P < 0.001.Conclusions: The physicians in our survey considered a wide range of qualitative and quantitative factors when making medication choices for hyperglycemia management. The apparent complexity of the medication choice process contrasts with current evidence-based treatment guidelines. [ABSTRACT FROM AUTHOR]
Published: 2007
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35. Impaired fasting glucose and impaired glucose tolerance: implications for care.

Author: Nathan DM, Davidson MB, DeFronzo RA, Heine RJ, Henry RR, Pratley R, and Zinman B
Published: 2007
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36. Finding new treatments for diabetes--how many, how fast... how good?

Author: Nathan DM and Nathan, David M
Published: 2007

37. Thiazolidinediones for initial treatment of type 2 diabetes?

Author: Nathan DM
Published: 2006

38. Management of hyperglycemia in type 2 diabetes: A consensus algorithm for the initiation and adjustment of therapy: a consensus statement from the American Diabetes Association and the European Association for the Study of Diabetes.

Author: Nathan DM, Buse JB, Davidson MB, Heine RJ, Holman RR, Sherwin R, Zinman B, Nathan, David M, Buse, John B, Davidson, Mayer B, Heine, Robert J, Holman, Rury R, Sherwin, Robert, and Zinman, Bernard
Published: 2006
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39. Hemostatic markers of endothelial dysfunction and risk of incident type 2 diabetes: the Framingham Offspring Study.

Author: Meigs JB, O'Donnell CJ, Tofler GH, Benjamin EJ, Fox CS, Lipinska I, Nathan DM, Sullivan LM, D'Agostino RB, Wilson PWF, Meigs, James B, O'donnell, Christopher J, Tofler, Geoffrey H, Benjamin, Emelia J, Fox, Caroline S, Lipinska, Izabela, Nathan, David M, Sullivan, Lisa M, D'Agostino, Ralph B, and Wilson, Peter W F
Abstract: Endothelial dysfunction may precede development of type 2 diabetes. We tested the hypothesis that elevated levels of hemostatic markers of endothelial dysfunction, plasminogen activator inhibitor-1 (PAI-1) antigen, and von Willebrand factor (vWF) antigen predicted incident diabetes independent of other diabetes risk factors. We followed 2,924 Framingham Offspring subjects (54% women, mean age 54 years) without diabetes at baseline (defined by treatment, fasting plasma glucose > or =7 or 2-h postchallenge glucose > or =11.1 mmol/l) over 7 years for new cases of diabetes (treatment or fasting plasma glucose > or =7.0 mmol/l). We used a series of regression models to estimate relative risks for diabetes per interquartile range (IQR) increase in PAI-1 (IQR 16.8 ng/ml) and vWF (IQR 66.8% of control) conditioned on baseline characteristics. Over follow-up, there were 153 new cases of diabetes. Age- and sex-adjusted relative risks of diabetes were 1.55 per IQR for PAI-1 (95% CI 1.41-1.70) and 1.49 for vWF (1.21-1.85). These effects remained after further adjustment for diabetes risk factors (including physical activity; HDL cholesterol, triglyceride, and blood pressure levels; smoking; parental history of diabetes; use of alcohol, nonsteroidal anti-inflammatory drugs, exogenous estrogen, or hypertension therapy; and impaired glucose tolerance), waist circumference, homeostasis model assessment of insulin resistance, and inflammation (assessed by levels of C-reactive protein): the adjusted relative risks were 1.18 per IQR for PAI-1 (1.01-1.37) and 1.39 for vWF (1.09-1.77). We conclude that in this community-based sample, plasma markers of endothelial dysfunction increased risk of incident diabetes independent of other diabetes risk factors including obesity, insulin resistance, and inflammation. [ABSTRACT FROM AUTHOR]
Published: 2006
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40. Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes.

Author: Nathan DM, Cleary PA, Backlund JC, Genuth SM, Lachin JM, Orchard TJ, Raskin P, Zinman B, Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study Research Group, Nathan, David M, Cleary, Patricia A, Backlund, Jye-Yu C, Genuth, Saul M, Lachin, John M, Orchard, Trevor J, Raskin, Philip, and Zinman, Bernard
Abstract: Background: Intensive diabetes therapy aimed at achieving near normoglycemia reduces the risk of microvascular and neurologic complications of type 1 diabetes. We studied whether the use of intensive therapy as compared with conventional therapy during the Diabetes Control and Complications Trial (DCCT) affected the long-term incidence of cardiovascular disease.Methods: The DCCT randomly assigned 1441 patients with type 1 diabetes to intensive or conventional therapy, treating them for a mean of 6.5 years between 1983 and 1993. Ninety-three percent were subsequently followed until February 1, 2005, during the observational Epidemiology of Diabetes Interventions and Complications study. Cardiovascular disease (defined as nonfatal myocardial infarction, stroke, death from cardiovascular disease, confirmed angina, or the need for coronary-artery revascularization) was assessed with standardized measures and classified by an independent committee.Results: During the mean 17 years of follow-up, 46 cardiovascular disease events occurred in 31 patients who had received intensive treatment in the DCCT, as compared with 98 events in 52 patients who had received conventional treatment. Intensive treatment reduced the risk of any cardiovascular disease event by 42 percent (95 percent confidence interval, 9 to 63 percent; P=0.02) and the risk of nonfatal myocardial infarction, stroke, or death from cardiovascular disease by 57 percent (95 percent confidence interval, 12 to 79 percent; P=0.02). The decrease in glycosylated hemoglobin values during the DCCT was significantly associated with most of the positive effects of intensive treatment on the risk of cardiovascular disease. Microalbuminuria and albuminuria were associated with a significant increase in the risk of cardiovascular disease, but differences between treatment groups remained significant (P< or =0.05) after adjusting for these factors.Conclusions: Intensive diabetes therapy has long-term beneficial effects on the risk of cardiovascular disease in patients with type 1 diabetes. [ABSTRACT FROM AUTHOR]
Published: 2005

41. Report of the National Heart, Lung, and Blood Institute -- National Institute of Diabetes and Digestive and Kidney Diseases Working Group on Cardiovascular Complications of Type 1 Diabetes Mellitus.

Author: Libby P, Nathan DM, Abraham K, Brunzell JD, Fradkin JE, Haffner SM, Hsueh W, Rewers M, Roberts BT, Savage PJ, Skarlatos S, Wassef M, and Rabadan-Diehl C
Published: 2005

42. Effect of intensive glycemic control on levels of markers of inflammation in type 1 diabetes mellitus in the Diabetes Control and Complications Trial.

Author: Schaumberg DA, Glynn RJ, Jenkins AJ, Lyons TJ, Rifai N, Manson JE, Ridker PM, and Nathan DM
Published: 2005

43. A controlled trial of population management: diabetes mellitus: putting evidence into practice (DM-PEP).

Author: Grant RW, Cagliero E, Sullivan CM, Dubey AK, Estey GA, Weil EM, Gesmundo J, Nathan DM, Singer DE, Chueh HC, Meigs JB, Grant, Richard W, Cagliero, Enrico, Sullivan, Christine M, Dubey, Anil K, Estey, Greg A, Weil, Eric M, Gesmundo, Joseph, Nathan, David M, and Singer, Daniel E
Abstract: Objective: Population-level strategies to organize and deliver care may improve diabetes management. We conducted a multiclinic controlled trial of population management in patients with type 2 diabetes.Research Design and Methods: We created diabetic patient registries (n = 3,079) for four primary care clinics within a single academic health center. In the intervention clinic (n = 898), a nurse practitioner used novel clinical software (PopMan) to identify patients on a weekly basis with outlying values for visit and testing intervals and last measured levels of HbA1c, LDL cholesterol, and blood pressure. For these patients, the nurse practitioner e-mailed a concise patient-specific summary of evidence-based management suggestions directly to primary care providers (PCPs). Population changes in risk factor testing, medication prescription, and risk factor levels from baseline (1 January 2000 to 31 August 2001) to follow-up (1 December 2001 to 31 July 2003) were compared with the three usual-care control clinics (n = 2,181).Results: Patients had a mean age of 65 years, were mostly white (81%), and the majority were insured by Medicare/Medicaid (62%). From baseline to follow-up, the increase in proportion of patients tested for HbA1c (P = 0.004) and LDL cholesterol (P < 0.001) was greater in the intervention than control sites. Improvements in diabetes-related medication prescription and levels of HbA1c, LDL cholesterol, and blood pressure in the intervention clinic were balanced by similar improvements in the control sites.Conclusions: Population-level clinical registries combined with summarized recommendations to PCPs had a modest effect on management. The intervention was limited by good overall quality of care at baseline and temporal improvements in all control clinics. It is unknown whether this intervention would have had greater impact in clinical settings with lower overall quality. Further research into more effective methods of translating population registry information into action is required. [ABSTRACT FROM AUTHOR]
Published: 2004
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44. Clinical inertia in the management of Type 2 diabetes metabolic risk factors.

Author: Grant RW, Cagliero E, Dubey AK, Gildesgame C, Chueh HC, Barry MJ, Singer DE, Nathan DM, and Meigs JB
Abstract: AIMS: Delays in the initiation and intensification of medical therapy may be one reason patients with diabetes do not reach evidence-based goals for metabolic control. We assessed intensification of medical therapy over time, comparing the management of hyperglycaemia, hypertension, and hyperlipidaemia. METHODS: Prospective cohort study of 598 adults with Type 2 diabetes receiving primary care in an academic medical centre from May 1997 to April 1999. We assessed whether patients failing to achieve standard treatment goals for haemoglobin A1c (HbA1c), systolic blood pressure (SBP), or low density lipoprotein (LDL) cholesterol when last measured during 12 months (Year 1, 5/97-4/98) had increases in their corresponding medical regimen during the following 12 months (Year 2, 5/98-4/99). RESULTS: Among untreated patients in Year 1, seven of 12 (58%) of those above goal for HbA1c were initiated on medical therapy in Year 2, compared with 16 of 48 (34%) above SBP goal (P=0.02) and 26 of 115 (23%) above LDL cholesterol goal (P=0.02). Among patients on therapy and above goal, 124 of 244 (51%) patients with elevated HbA1c had their regimen increased in Year 2, compared with 85 of 282 (30%) with elevated SBP (P<0.001) and 22 of 79 (30%) with elevated LDL cholesterol (P<0.001). From Year 1 to Year 2 there was a decline in the overall proportion of patients above goal for LDL cholesterol (from 58% to 45%, P=0.002) but not for HbA1c or blood pressure. CONCLUSIONS: Greater initiation and intensification of pharmaceutical therapy, particularly for elevated blood pressure or cholesterol, may represent a specific opportunity to improve metabolic control in Type 2 diabetes. [ABSTRACT FROM AUTHOR]
Published: 2004
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45. A controlled trial of web-based diabetes disease management: the MGH diabetes primary care improvement project.

Author: Meigs JB, Cagleiro E, Dubey A, Murphy-Sheehy P, Gildesgame C, Chueh H, Barry MJ, Singer DE, Nathan DM, Meigs, James B, Cagliero, Enrico, Dubey, Anil, Murphy-Sheehy, Patricia, Gildesgame, Catharyn, Chueh, Henry, Barry, Michael J, Singer, Daniel E, and Nathan, David M
Abstract: Objective: To test effects of a web-based decision support tool, the diabetes Disease Management Application (DMA), developed to improve evidence-based management of type 2 diabetes.Research Design and Methods: We conducted a group randomized controlled trial of 12 intervention and 14 control staff providers and 307 intervention and 291 control patients with type 2 diabetes in a hospital-based internal medicine clinic. Providers were randomly assigned from May 1998 through April 1999 to have access to the DMA (intervention) or not to have access (control). The DMA displays interactive patient-specific clinical data, treatment advice, and links to other web-based care resources. We compared patients in the intervention and control groups for changes in processes and outcomes of care from the year preceding the study through the year of the study by intention-to-treat analysis.Results: The DMA was used for 42% of scheduled patient visits. The number of HbA(1c) tests obtained per year increased significantly in the intervention group (+0.3 tests/year) compared with the control group (-0.04 tests/year, P = 0.008), as did the number of LDL cholesterol tests (intervention, +0.2 tests/year; control, +0.01 tests/year; P = 0.02) and the proportions of patients undergoing at least one foot examination per year (intervention, +9.8%; control, -0.7%; P = 0.003). Levels of HbA(1c) decreased by 0.2 in the intervention group and increased by 0.1 in the control group (P = 0.09); proportions of patients with LDL cholesterol levels <130 mg/dl increased by 20.3% in the intervention group and 10.5% in the control group (P = 0.5).Conclusions: Web-based patient-specific decision support has the potential to improve evidence-based parameters of diabetes care. [ABSTRACT FROM AUTHOR]
Published: 2003
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46. Clinical practice. Initial management of glycemia in type 2 diabetes mellitus.

Author: Nathan DM
Published: 2002

47. Immediate feedback of HbA1c levels improves glycemic control in type 1 and insulin-treated type 2 diabetic patients.

Author: Cagliero E, Levina EV, and Nathan DM
Abstract: OBJECTIVE: Accurate and reliable HbA1c results can be obtained at the time of the office visit by using benchtop analyzers. We tested the hypothesis that immediately available HbA1c results could improve glycemic control by changing physician or patient behavior or both. RESEARCH DESIGN AND METHODS: A randomized controlled trial was conducted in 201 type 1 and insulin-treated type 2 diabetic patients attending an academic diabetes center. HbA1c levels, changes in insulin therapy, and use of health care resources were assessed during a 12-month follow-up period. RESULTS: HbA1c levels decreased significantly at 6 and 12 months in the immediate assay group (-0.57 +/- 1.44 and -0.40 +/- 1.65%, respectively; P < 0.01) but did not change in the control group (-0.11 +/- 0.79 and -0.19 +/- 1.16%, respectively; NS). The changes were similar for both type 1 and type 2 diabetic patients. There were no differences in the rates of hypoglycemic events or use of health care resources. CONCLUSIONS: In the setting of a controlled randomized trial, the immediate feedback of HbA1c results at the time of patient encounters resulted in a significant improvement of glycemic control at 6-month follow-up and persisted for the 12-month study. The introduction of this assay was positively received by both patients and physicians. [ABSTRACT FROM AUTHOR]
Published: 1999
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48. Metabolic risk factors worsen continuously across the spectrum of nondiabetic glucose tolerance. The Framingham Offspring Study.

Author: Meigs JB, Nathan DM, Wilson PWF, Cupples LA, Singer DE, Meigs, J B, Nathan, D M, Wilson, P W, Cupples, L A, and Singer, D E
Abstract: Background: Categorical definitions for glucose intolerance imply that risk thresholds exist, but metabolic risk for type 2 diabetes mellitus or cardiovascular disease may increase continuously as glucose intolerance increases.Objective: To examine the distributions of the following metabolic risk factors across the spectrum of glucose tolerance: overall and central obesity, hypertension, low levels of high-density lipoprotein cholesterol, and increased triglyceride and insulin levels.Design: Cross-sectional analysis.Setting: The community-based Framingham Offspring Study.Participants: 2583 adults without previously diagnosed diabetes.Measurements: Clinical data; fasting glucose, insulin, and lipid levels; and glucose and insulin levels taken 2 hours after oral challenge were collected from 1991 to 1993. Glucose tolerance was determined by 1980 World Health Organization criteria. Patients with normal glucose tolerance were categorized into quintiles of fasting glucose. The distributions of each metabolic risk factor and the metabolic sum of the six risk factors were assessed across seven categories from the lowest quintile of normal fasting glucose level through impaired glucose tolerance and previously undiagnosed diabetes.Results: The mean age of patients was 54 years (range, 26 to 82 years); 52.7% of patients were women. Glucose tolerance testing found that 12.7% of patients had impaired glucose tolerance and 4.8% had previously undiagnosed diabetes. Multivariable-adjusted mean measures of risk factors and odds ratios for obesity, elevated waist-to-hip ratio, hypertension, low levels of high-density lipoprotein cholesterol, elevated triglyceride levels, and hyperinsulinemia showed continuous increases across the spectrum of nondiabetic glucose tolerance. Although a threshold effect near the upper range of nondiabetic glucose tolerance could not be ruled out for triglyceride levels in men and for insulin levels 2 hours after oral challenge in men and women, no other metabolic risk factors showed clear evidence of thresholds for increased risk.Conclusions: Metabolic risk factors for type 2 diabetes mellitus and for cardiovascular disease worsen continuously across the spectrum of glucose tolerance categories, beginning in the lowest quintiles of normal fasting glucose level. [ABSTRACT FROM AUTHOR]
Published: 1998
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49. Insulin: recent developments and common quandaries: diabetes treatment moves forward.

Author: Krieger DR, Nathan DM, and Schade DS
Abstract: Like all patients with type 1 diabetes, most with type 2 disease are ultimately treated with insulin. Advances in drug development and delivery systems are changing the way products are selected and used. [ABSTRACT FROM AUTHOR]
Published: 1998

50. Risk variable clustering in the insulin resistance syndrome. The Framingham Offspring Study.

Author: Meigs JB, D'Agostino RB Sr., Wilson PWF, Cupples LA, Nathan DM, Singer DE, Meigs, J B, D'Agostino, R B Sr, Wilson, P W, Cupples, L A, Nathan, D M, and Singer, D E
Published: 1997
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