169 results on '"Shields, Bm"'
Search Results
2. Evaluating associations between the benefits and risks of drug therapy in type 2 diabetes: a joint modeling approach
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Dennis JM, Shields BM, Jones AG, Pearson ER, Hattersley AT, and Henley WE
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diabetes mellitus ,type 2 ,Drug-Related Side Effects and Adverse Reactions ,Glycated Hemoglobin A ,Hypoglycemia ,Joint model ,Precision Medicine ,Infectious and parasitic diseases ,RC109-216 - Abstract
John M Dennis,1 Beverley M Shields,2 Angus G Jones,2 Ewan R Pearson,3 Andrew T Hattersley,2 William E Henley1 On behalf of the MASTERMIND consortium 1Health Statistics Group, University of Exeter Medical School, Exeter, UK; 2National Institute for Health Research Exeter Clinical Research Facility, University of Exeter Medical School, Exeter, UK; 3Division of Molecular and Clinical Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK Objective: Precision medicine drug therapy seeks to maximize efficacy and minimize harm for individual patients. This will be difficult if drug response and side effects are positively associated, meaning that patients likely to respond best are at increased risk of side effects. We applied joint longitudinal–survival models to evaluate associations between drug response (longitudinal outcome) and the risk of side effects (survival outcome) for patients initiating type 2 diabetes therapy. Study design and setting: Participants were randomized to metformin (MFN), sulfonylurea (SU), or thiazolidinedione (TZD) therapy in the A Diabetes Outcome Progression Trial (ADOPT) drug efficacy trial (n=4,351). Joint models were parameterized for 1) current HbA1c response (change from baseline in HbA1c) and 2) cumulative HbA1c response (total HbA1c change). Results: With MFN, greater HbA1c response did not increase the risk of gastrointestinal events (HR per 1% absolute greater current response 0.82 [95% CI 0.67, 1.01]; HR per 1% higher cumulative response 0.90 [95% CI 0.81, 1.00]). With SU, greater current response was associated with an increased risk of hypoglycemia (HR 1.41 [95% CI 1.04, 1.91]). With TZD, greater response was associated with an increased risk of edema (current HR 1.45 [95% CI 1.05, 2.01]; cumulative 1.22 [95% CI 1.07, 1.38]) but not fracture. Conclusion: Joint modeling provides a useful framework to evaluate the association between response to a drug and the risk of developing side effects. There may be great potential for widespread application of joint modeling to evaluate the risks and benefits of both new and established medications. Keywords: diabetes mellitus, type 2, drug-related side effects, HbA1c, hypoglycemia, joint model, precision medicine, thiazolidinediones, metformin, sulfonylurea compounds, ADOPT, edema
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- 2018
3. What to do with diabetes therapies when HbA1c lowering is inadequate: add, switch, or continue? A MASTERMIND study
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McGovern, AP, Dennis, JM, Shields, BM, Hattersley, AT, Pearson, ER, Jones, AG, Farmer, AJ, and Mastermind Consortium
- Abstract
BACKGROUND:It is unclear what to do when people with type 2 diabetes have had no or a limited glycemic response to a recently introduced medication. Intra-individual HbA1c variability can obscure true response. Some guidelines suggest stopping apparently ineffective therapy, but no studies have addressed this issue. METHODS:In a retrospective cohort analysis using the UK Clinical Practice Research Datalink (CPRD), we assessed the outcome of 55,530 patients with type 2 diabetes starting their second or third non-insulin glucose-lowering medication, with a baseline HbA1c > 58 mmol/mol (7.5%). For those with no HbA1c improvement or a limited response at 6 months (HbA1c fall
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- 2019
4. Frequency and phenotype of T1DM in the first six decades of life: a cross-sectional, genetically stratified survival analysis from UK Biobank
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Oram Ra, Shields Bm, Michael N. Weedon, Thomas Nj, Jones Se, and Hattersley At
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business.industry ,Medicine ,business ,Phenotype ,Biobank ,Survival analysis ,Demography - Published
- 2018
5. Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants
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Burton, PR, Clayton, DG, Cardon, LR, Craddock, N, Deloukas, P, Duncanson, A, Kwiatkowski, DP, McCarthy, MI, Ouwehand, WH, Samani, NJ, 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, Moskivina, V, Nikolov, I, O'Donovan, MC, Owen, MJ, Collier, DA, Elkin, A, Farmer, A, Williamson, R, McGuffin, P, Young, AH, Ferrier, IN, Ball, SG, Balmforth, AJ, Barrett, JH, Bishop, TD, Iles, MM, Maqbool, A, Yuldasheva, N, Hall, AS, Braund, PS, Dixon, RJ, Mangino, M, Stevens, S, Thompson, JR, 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, Matthew, CG, Barbour, J, Mohiuddin, MK, Todhunter, CE, Mansfield, JC, Ahmad, T, Cummings, FR, Jewell, DP, Webster, J, Brown, MJ, Lathrop, MG, 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, Hilder, 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, Hallgrimsdo'ttir, IB, Howie, BN, Su, Z, Teo, YY, Vukcevic, D, Bentley, D, Mitchell, SL, Newby, PR, Brand, OJ, Carr-Smith, J, Pearce, SH, Reveille, JD, Zhou, X, Sims, AM, Dowling, A, Taylor, J, Doan, T, Davis, JC, Savage, L, Ward, MM, Learch, TL, Weisman, MH, and Brown, M
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Linkage disequilibrium ,Multiple Sclerosis ,Genotype ,Population ,Single-nucleotide polymorphism ,Genome-wide association study ,Autoimmunity ,Breast Neoplasms ,Biology ,medicine.disease_cause ,Aminopeptidases ,Polymerase Chain Reaction ,Polymorphism, Single Nucleotide ,Linkage Disequilibrium ,Article ,Minor Histocompatibility Antigens ,Genetics ,medicine ,Humans ,Spondylitis, Ankylosing ,Receptors, Immunologic ,education ,Genetic association ,education.field_of_study ,Ankylosing spondylitis ,Thyroiditis, Autoimmune ,Chromosome Mapping ,Receptors, Interleukin ,medicine.disease ,Endoplasmic reticulum aminopeptidase 2 ,Genetics, Population ,Haplotypes ,Case-Control Studies ,Immunology ,North America - Abstract
We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases.
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- 2016
6. Practical Classification Guidelines for Diabetes in patients treated with insulin: a cross-sectional study of the accuracy of diabetes diagnosis
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Hope, SV, Wienand-Barnett, S, Shepherd, M, King, SM, Fox, C, Khunti, K, Oram, RA, Knight, BA, Hattersley, AT, Jones, AG, Shields, BM, Hope, SV, Wienand-Barnett, S, Shepherd, M, King, SM, Fox, C, Khunti, K, Oram, RA, Knight, BA, Hattersley, AT, Jones, AG, and Shields, BM
- Abstract
BACKGROUND: Differentiating between type 1 and type 2 diabetes is fundamental to ensuring appropriate management of patients, but can be challenging, especially when treating with insulin. The 2010 UK Practical Classification Guidelines for Diabetes were developed to help make the differentiation. AIM: To assess diagnostic accuracy of the UK guidelines against 'gold standard' definitions of type 1 and type 2 diabetes based on measured C-peptide levels. DESIGN AND SETTING: In total, 601 adults with insulin-treated diabetes and diabetes duration ≥5 years were recruited in Devon, Northamptonshire, and Leicestershire. METHOD: Baseline information and home urine sample were collected. Urinary C-peptide creatinine ratio (UCPCR) measures endogenous insulin production. Gold standard type 1 diabetes was defined as continuous insulin treatment within 3 years of diagnosis and absolute insulin deficiency (UCPCR<0.2 nmol/mmol ≥5 years post-diagnosis); all others classed as having type 2 diabetes. Diagnostic performance of the clinical criteria was assessed and other criteria explored using receiver operating characteristic (ROC) curves. RESULTS: UK guidelines correctly classified 86% of participants. Most misclassifications occurred in patients classed as having type 1 diabetes who had significant endogenous insulin levels (57 out of 601; 9%); most in those diagnosed ≥35 years and treated with insulin from diagnosis, where 37 out of 66 (56%) were misclassified. Time to insulin and age at diagnosis performed best in predicting long-term endogenous insulin production (ROC AUC = 0.904 and 0.871); BMI was a less strong predictor of diabetes type (AUC = 0.824). CONCLUSION: Current UK guidelines provide a pragmatic clinical approach to classification reflecting long-term endogenous insulin production; caution is needed in older patients commencing insulin from diagnosis, where misclassification rates are increased.
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- 2016
7. 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
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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
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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
8. The Lin28/let-7 axis regulates glucose metabolism
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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.
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- 2011
9. The HNF4A R76W mutation causes atypical dominant Fanconi syndrome in addition to a β cell phenotype
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Hamilton, Alexander, Bingham, C, McDonald, TJ, Cook, PR, Caswell, RC, Weedon, MN, Oram, RA, Shields, BM, Shepherd, M, Inward, Carol D, Hamilton-Shield, Julian P, Kohlhase, J, Ellard, S, and Hattersley, AT
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nutritional and metabolic diseases - Abstract
Background Mutation specific effects in monogenic disorders are rare. We describe atypical Fanconi syndrome caused by a specific heterozygous mutation in HNF4A. Heterozygous HNF4A mutations cause a beta cell phenotype of neonatal hyperinsulinism with macrosomia and young onset diabetes. Autosomal dominant idiopathic Fanconi syndrome (a renal proximal tubulopathy) is described but no genetic cause has been defined.Methods and Results We report six patients heterozygous for the p.R76W HNF4A mutation who have Fanconi syndrome and nephrocalcinosis in addition to neonatal hyperinsulinism and macrosomia. All six displayed a novel phenotype of proximal tubulopathy, characterised by generalised aminoaciduria, low molecular weight proteinuria, glycosuria, hyperphosphaturia and hypouricaemia, and additional features not seen in Fanconi syndrome: nephrocalcinosis, renal impairment, hypercalciuria with relative hypocalcaemia, and hypermagnesaemia. This was mutation specific, with the renal phenotype not being seen in patients with other HNF4A mutations. In silico modelling shows the R76 residue is directly involved in DNA binding and the R76W mutation reduces DNA binding affinity. The target(s) selectively affected by altered DNA binding of R76W that results in Fanconi syndrome is not known.Conclusions The HNF4A R76W mutation is an unusual example of a mutation specific phenotype, with autosomal dominant atypical Fanconi syndrome inaddition to the established beta cell phenotype.
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- 2014
10. Early growth genetics C. New loci associated with birgh weight identify genetic links between intrauterine growth and adult height and metabolism
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Horikoshi, M, Yaghootkar, H, Mook, Dennis, Sovio, U, Taal, Rob, Hennig, BJ, Bradfield, JP, St Pourcain, B, Evans, DM, Charoen, P, Kaakinen, M, Cousminer, DL, Lehtimaki, T, Kreiner-Moller, E, Warrington, NM, Bustamante, M, Feenstra, B, Berry, DJ, Thiering, E, Pfab, T, Barton, SJ, Shields, BM, Kerkhof, M, Leeuwen, Elisa, Fulford, AJ, Kutalik, Z, Zhao, JH, den Hoed, M, Mahajan, A, Lindi, V, Goh, LK, Hottenga, JJ (Jouke Jan), Wu, Fenny, Raitakari, OT, Harder, M, Meirhaeghe, A, Ntalla, I, Salem, RM, Jameson, KA, Zhou, K, Monies, D, Lagou, V, Kirin, M, Heikkinen, J, Adair, LS, Alkuraya, FS, Al-Odaib, A, Amouyel, P, Andersson, EAS, Bennett, AJ, Blakemore, AIF, Buxton, JL, Dallongeville, J, Das, Suman, de Geus, EJC, Estivill, X, Flexeder, C, Froguel, P, Geller, F, Godfrey, KM, Gottrand, F, Groves, CJ, Hansen, T, Hirschhorn, JN, Hofman, Bert, Hollegaard, MV, Hougaard, DM, Hypponen, E, Inskip, H, Isaacs, Aaron, Jorgensen, T, Kanaka-Gentenbein, C, Kemp, JP, Kiess, W, Kipelainen, TO, Klopp, N, Knight, BA, Kuzawa, CW, McMahon, G, Newnham, JP, Niinikoski, H, Oostra, Ben, Pedersen, L, Postma, DS, Ring, SM, Rivadeneira, Fernando, Robertson, NR, Sebert, S, Simell, O, Slowinski, T, Tiesler, CMT, Tonjes, A, Vaag, A, Viikari, JS, Vink, JM, Vissing, NH, Wareham, NJ, Willemsen, G, Witte, DR, Zhang, H, Zhao, J, Wilson, JF, Stumvoll, M, Prentice, AM, Meyer, BF, Pearson, ER, Boreham, CA, Cooper, C, Gilman, MW, Dedoussis, GV, Moreno, LA, Pedersen, O, Saarinen, M, Mohlke, KL, Boomsma, DI, Saw, SM, Lakka, TA, Korner, A, Loos, RJ, Ong, KK, Vollenweider, P, Duijn, Cornelia, Koppelman, GH, Hattersley, AT, Holloway, JW, Hocher, B, Heinrich, J, Power, C, Melbye, M, Guxens Junyent, Monica, Pennell, CE, Bonnelykke, K, Bisgaard, H, Eriksson, JG, Widen, E, Hakonarson, H, Uitterlinden, André, Pouta, A, Lawlor, DA, Smith, GD, Frayling, TM, McCarthy, M, Grant, SFA, Jaddoe, Vincent, Jarvelin, MR, Timpson, NJ, Prokopenko, I, Freathy, RM, Erasmus MC other, Epidemiology, Medical Microbiology & Infectious Diseases, Clinical Genetics, Internal Medicine, and Hematology
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- 2013
11. Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis
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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)
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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.
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- 2012
12. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease
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Jostins, Luke, Ripke, Stephan, Weersma, Rinse K., Duerr, Richard H., Mcgovern, Dermot P., Hui, Ken Y., Lee, James C., Philip Schumm, L., Sharma, Yashoda, Anderson, Carl A., Essers, Jonah, Mitrovic, Mitja, Ning, Kaida, Cleynen, Isabelle, Theatre, Emilie, Spain, Sarah L., Raychaudhuri, Soumya, Goyette, Philippe, Wei, Zhi, Abraham, Clara, Achkar, Jean Paul, Ahmad, Tariq, Amininejad, Leila, Ananthakrishnan, Ashwin N., Andersen, Vibeke, Andrews, Jane M., Baidoo, Leonard, Balschun, Tobias, Bampton, Peter A., Bitton, Alain, Boucher, Gabrielle, Brand, Stephan, Büning, Carsten, Cohain, Ariella, Cichon, Sven, D'Amato, Mauro, De Jong, Dirk, Devaney, Kathy L., Dubinsky, Marla, Edwards, Cathryn, Ellinghaus, David, Ferguson, Lynnette R., Franchimont, Denis, Fransen, Karin, Gearry, Richard, Georges, Michel, Gieger, Christian, Glas, Jürgen, Haritunians, Talin, Hart, Ailsa, Hawkey, Chris, Hedl, Matija, Xinli, Hu, Karlsen, Tom H., Kupcinskas, Limas, Kugathasan, Subra, Latiano, Anna, Laukens, Debby, Lawrance, Ian C., Lees, Charlie W., Louis, Edouard, Mahy, Gillian, Mansfield, John, Morgan, Angharad R., Mowat, Craig, Newman, William, Palmieri, Orazio, Ponsioen, Cyriel Y., Potocnik, Uros, Prescott, Natalie J., Regueiro, Miguel, Rotter, Jerome I., Russell, Richard K., Sanderson, Jeremy D., Sans, Miquel, Satsangi, Jack, Schreiber, Stefan, Simms, Lisa A., Sventoraityte, Jurgita, Targan, Stephan R., Taylor, Kent D., Tremelling, Mark, Verspaget, Hein W., De Vos, Martine, Wijmenga, Cisca, Wilson, David C., Winkelmann, Juliane, Xavier, Ramnik J., Zeissig, Sebastian, Zhang, Bin, Zhang, Clarence K., Zhao, Hongyu, Silverberg, Mark S., Annese, Vito, Hakonarson, Hakon, Brant, Steven R., Radford Smith, Graham, Mathew, Christopher G., Rioux, John D., Schadt, Eric E., Daly, Mark J., Franke, Andre, Parkes, Miles, Vermeire, Severine, Barrett, Jeffrey C., Cho, Judy H., Barclay, M, Peyrin Biroulet, L, Chamaillard, M, Colombel, Jf, Cottone, M, Croft, A, D'Incà, R, Halfvarson J, Hanigan K, Henderson, P, Hugot, Jp, Karban, A, Kennedy, Na, Khan, Ma, Lémann, M, Levine, A, Massey, D, Milla, M, Montgomery, Gw, Ng, Sm, Oikonomou, I, Peeters, H, Proctor, Dd, Rahier, Jf, Roberts, R, Rutgeerts, P, Seibold, F, Stronati, Laura, Taylor, Km, Törkvist, L, Ublick, K, Van Limbergen, J, Van Gossum, A, Vatn, Mh, Zhang, H, Zhang, W, Andrews, Jm, Bampton, Pa, Florin, Th, Gearry, R, Krishnaprasad, K, Lawrance, Ic, Mahy, G, Radford Smith, G, Roberts, Rl, Simms, La, Amininijad, L, Cleynen, I, Dewit, O, Franchimont, D, Georges, M, Laukens, D, Theatre, E, Vermeire, S, Aumais, G, Baidoo, L, Barrie AM 3rd, Beck, K, Bernard, Ej, Binion, Dg, Bitton, A, Brant, Sr, Cho, Jh, Cohen, A, Croitoru, K, Daly, Mj, Datta, Lw, Deslandres, C, Duerr, Rh, Dutridge, D, Ferguson, J, Fultz, J, Goyette, P, Greenberg, Gr, Haritunians, T, Jobin, G, Katz, S, Lahaie, Rg, Mcgovern, Dp, Nelson, L, Ning, K, Paré, P, Regueiro, Md, Rioux, Jd, Ruggiero, E, Schumm, L, Schwartz, M, Scott, R, Sharma, Y, Silverberg, Ms, Spears, D, Steinhart, A, Stempak, Jm, Swoger, Jm, Tsagarelis, C, Zhang, C, Zhao, H, Aerts, J, Ahmad, T, Arbury, H, Attwood, A, Auton, A, Ball, Sg, Balmforth, Aj, Barnes, C, Barrett, Jc, Barroso, I, Barton, A, Bennett, Aj, Bhaskar, S, Blaszczyk, K, Bowes, J, Brand, Oj, Braund, Ps, Bredin, F, Breen, G, Brown, Mj, Bruce, In, Bull, J, Burren, Os, Burton, J, Byrnes, J, Caesar, S, Cardin, N, Clee, Cm, Coffey, Aj, Connell, Jm, Conrad, Df, Cooper, Jd, Dominiczak, Af, Downes, K, Drummond, He, Dudakia, D, Dunham, A, Ebbs, B, Eccles, D, Edkins, S, Edwards, C, Elliot, A, Emery, P, Evans, Dm, Evans, G, Eyre, S, Farmer, A, Ferrier, In, Flynn, E, Forbes, A, Forty, L, Franklyn, Ja, Frayling, Tm, Freathy, Rm, Giannoulatou, E, Gibbs, P, Gilbert, P, Gordon Smith, K, Gray, E, Green, E, Groves, Cj, Grozeva, D, Gwilliam, R, Hall, A, Hammond, N, Hardy, M, Harrison, P, Hassanali, N, Hebaishi, H, Hines, S, Hinks, A, Hitman, Ga, Hocking, L, Holmes, C, Howard, E, Howard, P, Howson, Jm, Hughes, D, Hunt, S, Isaacs, Jd, Jain, M, Jewell, Dp, Johnson, T, Jolley, Jd, Jones, Ir, Jones, La, Kirov, G, Langford, Cf, Lango Allen, H, Lathrop, Gm, Lee, J, Lee, Kl, Lees, C, Lewis, K, Lindgren, Cm, Maisuria Armer, M, Maller, J, Mansfield, J, Marchini, Jl, Martin, P, Massey, Dc, Mcardle, Wl, Mcguffin, P, Mclay, Ke, Mcvean, G, Mentzer, A, Mimmack, Ml, Morgan, Ae, Morris, Ap, Mowat, C, Munroe, Pb, Myers, S, Newman, W, Nimmo, Er, O'Donovan, Mc, Onipinla, A, Ovington, Nr, Owen, Mj, Palin, K, Palotie, A, Parnell, K, Pearson, R, Pernet, D, Perry, Jr, Phillips, A, Plagnol, V, Prescott, Nj, Prokopenko, I, Quail, Ma, Rafelt, S, Rayner, Nw, Reid, Dm, Renwick, A, Ring, Sm, Robertson, N, Robson, S, Russell, E, St Clair, D, Sambrook, Jg, Sanderson, Jd, Sawcer, Sj, Schuilenburg, H, Scott, Ce, Seal, S, Shaw Hawkins, S, Shields, Bm, Simmonds, Mj, Smyth, Dj, Somaskantharajah, E, Spanova, K, Steer, S, Stephens, J, Stevens, He, Stirrups, K, Stone, Ma, Strachan, Dp, Su, Z, Symmons, Dp, Thompson, Jr, Thomson, W, Tobin, Md, Travers, Me, Turnbull, C, Vukcevic, D, Wain, Lv, Walker, M, Walker, Nm, Wallace, C, Warren Perry, M, Watkins, Na, Webster, J, Weedon, Mn, Wilson, Ag, Woodburn, M, Wordsworth, Bp, Yau, C, Young, Ah, Zeggini, E, Brown, Ma, Burton, Pr, Caulfield, Mj, Compston, A, Farrall, M, Gough, Sc, Hall, As, Hattersley, At, Hill, Av, Mathew, Cg, Pembrey, M, Satsangi, J, Stratton, Mr, Worthington, J, Hurles, Me, Duncanson, A, Ouwehand, Wh, Parkes, M, Rahman, N, Todd, Ja, Samani, Nj, Kwiatkowski, Dp, Mccarthy, Mi, Craddock, N, Deloukas, P, Donnelly, P, Blackwell, Jm, Bramon, E, Casas, Jp, Corvin, A, Jankowski, J, Markus, Hs, Palmer, Cn, Plomin, R, Rautanen, A, Trembath, Rc, Viswanathan, Ac, Wood, Nw, Spencer, Cc, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Pirinen, M, Strange, A, Blackburn, H, Bumpstead, Sj, Dronov, S, Gillman, M, Jayakumar, A, Mccann, Ot, Liddle, J, Potter, Sc, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P., AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, Gastroenterology and Hepatology, and Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI)
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Genome-wide association study ,Disease ,SUSCEPTIBILITY ,Inflammatory bowel disease ,NUMBER ,0302 clinical medicine ,Crohn Disease ,NETWORK ,Genetics ,0303 health sciences ,Multidisciplinary ,Genomics ,Ulcerative colitis ,3. Good health ,Colitis, Ulcerative ,Genetic Predisposition to Disease ,Genome, Human ,Haplotypes ,Humans ,Inflammatory Bowel Diseases ,Mycobacterium ,Mycobacterium Infections ,Mycobacterium tuberculosis ,Phenotype ,Polymorphism, Single Nucleotide ,Reproducibility of Results ,Genome-Wide Association Study ,Host-Pathogen Interactions ,IRGM ,Medical genetics ,030211 gastroenterology & hepatology ,EXPRESSION ,medicine.medical_specialty ,Immunology ,Biology ,Molecular gastro-enterology and hepatology Pathogenesis and modulation of inflammation [IGMD 2] ,TUBERCULOSIS ,03 medical and health sciences ,Medical research ,medicine ,Allele ,METAANALYSIS ,030304 developmental biology ,HYPER-IGE SYNDROME ,MUTATIONS ,medicine.disease ,RISK LOCI ,Genetic architecture ,digestive system diseases - Abstract
Crohn's disease and ulcerative colitis, the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry, with rising prevalence in other populations(1). Genome-wide association studies and subsequent meta-analyses of these two diseases(2,3) as separate phenotypes have implicated previously unsuspected mechanisms, such as autophagy(4), in their pathogenesis and showed that some IBD loci are shared with other inflammatory diseases(5). Here we expand on the knowledge of relevant pathways by undertaking a meta-analysis of Crohn's disease and ulcerative colitis genome-wide association scans, followed by extensive validation of significant findings, with a combined total of more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci, that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional (consistently favouring one allele over the course of human history) and balancing (favouring the retention of both alleles within populations) selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe considerable overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD.
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- 2012
13. Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes
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Strawbridge, Rj, Dupuis, J, Prokopenko, I, Barker, A, Ahlqvist, E, Rybin, D, Petrie, Jr, Travers, Me, Bouatia Naji, N, Dimas, As, Nica, A, Wheeler, E, Chen, H, Voight, Bf, Taneera, J, Kanoni, S, Peden, Jf, Turrini, F, Gustafsson, S, Zabena, C, Almgren, P, Barker, Dj, Barnes, D, Dennison, Em, Eriksson, Jg, Eriksson, P, Eury, E, Folkersen, L, Fox, Cs, Frayling, Tm, Goel, A, Gu, Hf, Horikoshi, M, Isomaa, B, Jackson, Au, Jameson, Ka, Kajantie, E, Kerr Conte, J, Kuulasmaa, T, Kuusisto, J, Loos, Rj, Luan, J, Makrilakis, K, Manning, Ak, Martínez Larrad MT, Narisu, N, Nastase Mannila, M, Ohrvik, J, Osmond, C, Pascoe, L, Payne, F, Sayer, Aa, Sennblad, B, Silveira, A, Stancáková, A, Stirrups, K, Swift, Aj, Syvänen, Ac, Tuomi, T, van 't Hooft FM, Walker, M, Weedon, Mn, Xie, W, Zethelius, B, Diagram, Consortium, Giant, Consortium, Muther, Consortium, Cardiogram, Consortium, C4d, Consortium, Ongen, H, Mälarstig, A, Hopewell, Jc, Saleheen, D, Chambers, J, Parish, S, Danesh, J, Kooner, J, Ostenson, Cg, Lind, L, Cooper, Cc, Serrano Ríos, M, Ferrannini, E, Forsen, Tj, Clarke, R, Franzosi, Mg, Seedorf, U, Watkins, H, Froguel, P, Johnson, P, Deloukas, P, Collins, Fs, Laakso, M, Dermitzakis, Et, Boehnke, M, Mccarthy, Mi, Wareham, Nj, Groop, L, Pattou, F, Gloyn, Al, Dedoussis, Gv, Lyssenko, V, Meigs, Jb, Barroso, I, Watanabe, Rm, Ingelsson, E, Langenberg, C, Hamsten, A, Voight BF, Florez J. C., 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, Hofmann, Om, Qi, L, Segrè, Av, van Hoek, M, Navarro, P, Ardlie, K, Balkau, B, Benediktsson, R, Bennett, Aj, Blagieva, R, Boerwinkle, E, Bonnycastle, Ll, Bengtsson Boström, K, Bravenboer, B, Bumpstead, S, Burtt, P, Charpentier, G, Chines, Ps, Cornelis, M, Couper, Dj, Crawford, G, Doney, As, Elliott, Ks, Elliott, Al, Erdos, Mr, Franklin, Cs, Gieger, C, Grarup, N, Green, T, Griffin, S, Groves, Cj, Guiducci, C, Hadjadj, S, Hassanali, N, Herder, C, Johnson, Pr, Jørgensen, T, Kao, Wh, Klopp, N, Kong, A, Kraft, P, Lauritzen, T, Li, M, Lieverse, A, Lindgren, Cm, Marre, M, Meitinger, T, Midthjell, K, Morken, Ma, Nilsson, P, Owen, Kr, Perry, Jr, Petersen, K, Platou, C, Proença, C, Rathmann, W, William Rayner, N, Robertson, Nr, Rocheleau, G, Roden, M, Sampson, Mj, Saxena, R, Shields, Bm, Shrader, P, Sigurdsson, G, Sparsø, T, Strassburger, K, Stringham, Hm, Sun, Q, Thorand, B, Tichet, J, van Dam RM, van Haeften TW, van Herpt, T, van Vliet JV, Bragi Walters, G, Wijmenga, C, Witteman, J, Bergman, Rn, Cauchi, S, Gyllensten, U, Hansen, T, Hide, Wa, Hitman, Ga, Hofman, A, Hunter, Dj, Hveem, K, Mohlke, Kl, Morris, Ad, Palmer, Cn, Pramstaller, Pp, Rudan, I, Sijbrands, E, Stein, Ld, Tuomilehto, J, Uitterlinden, A, Abecasis, Gr, Boehm, Bo, Campbell, H, Daly, Mj, Hattersley, At, Hu, Fb, Pankow, Js, Pedersen, O, Wichmann, E, Florez, Jc, Sladek, R, Thorsteinsdottir, U, Wilson, Jf, Illig, T, Stefansson, K, Altshuler, D, Speliotes, Ek, Berndt, Si, Monda, Kl, Allen, Hl, Mägi, R, Randall, Jc, Vedantam, S, Winkler, Tw, Workalemahu, T, Heid, Im, Wood, Ar, Weyant, Rj, Estrada, K, Liang, L, Nemesh, J, Park, Jh, Kilpeläinen, To, Yang, J, Esko, T, Feitosa, Mf, Kutalik, Z, Mangino, M, Scherag, A, Smith, Av, Welch, R, Zhao, Jh, Aben, Kk, Absher, Dm, Dixon, Al, Fisher, E, Glazer, Nl, Goddard, Me, Heard Costa NL, Hoesel, V, Hottenga, Jj, Johansson, Å, Johnson, T, Ketkar, S, Lamina, C, Li, S, Moffatt, Mf, Myers, Rh, Peters, Mj, Preuss, M, Ripatti, S, Rivadeneira, F, Sandholt, C, Timpson, Nj, Tyrer, Jp, van Wingerden, S, White, Cc, Wiklund, F, Barlassina, C, Chasman, Di, Cooper, Mn, Jansson, Jo, Lawrence, Rw, Pellikka, N, Shi, J, Thiering, E, Alavere, H, Alibrandi, Mt, Arnold, Am, Aspelund, T, Atwood, Ld, Balmforth, Aj, Ben Shlomo, Y, Bergmann, S, Biebermann, H, Blakemore, Ai, Boes, T, Bornstein, Sr, Brown, Mj, Buchanan, Ta, Busonero, F, Cappuccio, Fp, Cavalcanti Proença, C, Ida Chen YD, Chen, Cm, Coin, L, Connell, J, Day, In, den Heijer, M, Duan, J, Ebrahim, S, Elliott, P, Elosua, R, Eiriksdottir, G, Facheris, Mf, Felix, Sb, Fischer Posovszky, P, Folsom, Ar, Friedrich, N, Freimer, Nb, Fu, M, Gaget, S, Gejman, Pv, Geus, Ej, Gjesing, Ap, Goyette, P, Grässler, J, Greenawalt, Dm, Gudnason, V, Hartikainen, Al, Hall, As, Havulinna, As, Hayward, C, Heath, Ac, Hengstenberg, C, Hicks, Aa, Hinney, A, Homuth, G, Hui, J, Igl, W, Iribarren, C, Jacobs, Kb, Jarick, I, Jewell, E, John, U, Jousilahti, P, Jula, A, Kaakinen, M, Kaplan, Lm, Kathiresan, S, Kettunen, J, Kinnunen, L, Knowles, Jw, Kolcic, I, König, Ir, Koskinen, S, Kovacs, P, Kvaløy, K, Laitinen, J, Lantieri, O, Lanzani, C, Launer, Lj, Lecoeur, C, Terho, L, Lettre, G, Liu, J, Lokki, Ml, Lorentzon, M, Luben, Rn, Ludwig, B, Magic, Manunta, P, Marek, D, Martin, Ng, Mcardle, Wl, Mccarthy, A, Mcknight, B, Melander, O, Meyre, D, Montgomery, Gw, Mulic, R, Ngwa, Js, Nelis, M, Neville, Mj, Nyholt, Dr, O'Donnell, Cj, O'Rahilly, S, Ong, Kk, Oostra, B, Paré, G, Parker, An, Perola, M, Pichler, I, Pietiläinen, Kh, Platou, Cg, Polasek, O, Pouta, A, Rafelt, S, Raitakari, O, Rayner, Nw, Ridderstråle, M, Rief, W, Ruokonen, A, Rzehak, P, Salomaa, V, Sanders, Ar, Sandhu, Ms, Sanna, S, Saramies, J, Savolainen, Mj, Scherag, S, Schipf, S, Schreiber, S, Schunkert, H, Silander, K, Sinisalo, J, Siscovick, Ds, Smit, Jh, Soranzo, N, Sovio, U, Stephens, J, Surakka, I, Tammesoo, Ml, Tardif, Jc, Teder Laving, M, Teslovich, Tm, Thompson, Jr, Thomson, B, Tönjes, A, van Meurs JB, van Ommen GJ, Vatin, V, Viikari, J, Visvikis Siest, S, Vitart, V, Vogel, Ci, Waite, Ll, Wallaschofski, H, Walters, Gb, Widen, E, Wiegand, S, Wild, Sh, Willemsen, G, Witte, Dr, Witteman, Jc, Xu, J, Zhang, Q, Zgaga, L, Ziegler, A, Zitting, P, Beilby, Jp, Farooqi, Is, Hebebrand, J, Huikuri, Hv, James, Al, Kähönen, M, Levinson, Df, Macciardi, F, Nieminen, Ms, Ohlsson, C, Palmer, Lj, Ridker, Pm, Stumvoll, M, Beckmann, Js, Boeing, H, Dorret, I. B., Caulfield, Mj, Chanock, Sj, Cupples, La, Smith, Gd, Erdmann, J, Grönberg, H, Hall, P, Harris, Tb, Hayes, Rb, Heinrich, J, Jarvelin, Mr, Kaprio, J, Karpe, F, Khaw, Kt, Kiemeney, La, Krude, H, Lawlor, Da, Metspalu, A, Munroe, Pb, Ouwehand, Wh, Penninx, Bw, Peters, A, Quertermous, T, Reinehr, T, Rissanen, A, Samani, Nj, Schwarz, Pe, Shuldiner, Ar, Spector, Td, Uda, M, Valle, Tt, Wabitsch, M, Waeber, G, Shaun, P, Eric, E. S., Peter, M. V., Assimes, Tl, Borecki, Ib, Groop, Lc, Haritunians, T, Kaplan, Rc, O'Connell, Jr, Peltonen, L, Schlessinger, D, Strachan, Dp, van Duijn CM, Barroso, H, North, Ke, Hirschhorn, Jn, Nica, Ac, Parts, L, Glass, D, Nisbet, J, Barrett, A, Sekowska, M, Travers, M, Potter, S, Grundberg, E, Small, K, Hedman, Åk, Bataille, V, Bell, Jt, Surdulescu, G, Ingle, C, Nestle, Fo, di Meglio, P, Min, Jl, Wilk, A, Hammond, Cj, Yang, Tp, Montgomery, Sb, Zondervan, Kt, Durbin, R, Ahmadi, K, Reilly, Mp, Holm, H, Stewart, Af, Barbalic, M, Absher, D, Aherrahrou, Z, Allayee, H, Anand, Ss, Andersen, K, Anderson, Jl, Ardissino, D, Ball, Sg, Barnes, Ta, Becker, Dm, Becker, Lc, Berger, K, Bis, Jc, Boekholdt, Sm, Braund, Ps, Burnett, Ms, Buysschaert, I, Cardiogenics, Carlquist, Jf, Chen, L, Cichon, S, Codd, V, Davies, Rw, Dedoussis, G, Dehghan, A, Demissie, S, Devaney, Jm, Diemert, P, Do, R, Doering, A, Eifert, S, El Mokhtari NE, Ellis, Sg, Engert, Jc, Epstein, Se, de Faire, U, Fischer, M, Freyer, J, Gigante, B, Girelli, Domenico, Gretarsdottir, S, Gulcher, Jr, Halperin, E, Hammond, N, Hazen, Sl, Horne, Bd, Jones, Gt, Jukema, Jw, Kaiser, Ma, Kastelein, Jj, Kolovou, G, Laaksonen, R, Lambrechts, D, Leander, K, Lieb, W, Loley, C, Lotery, Aj, Mannucci, Pm, Maouche, S, Martinelli, Nicola, Mckeown, Pp, Meisinger, C, Merlini, Pa, Mooser, V, Morgan, T, Mühleisen, Tw, Muhlestein, Jb, Münzel, T, Musunuru, K, Nahrstaedt, J, Nelson, Cp, Nöthen, Mm, Olivieri, Oliviero, Patel, Rs, Patterson, Cc, Peyvandi, F, Qu, L, Quyyumi, Aa, Rader, Dj, Rallidis, Ls, Rice, C, Rosendaal, Fr, Rubin, D, Sampietro, Ml, Schadt, E, Schäfer, A, Schillert, A, Schrezenmeir, J, Schwartz, Sm, Sivananthan, M, Sivapalaratnam, S, Smith, A, Smith, Tb, Snoep, Jd, Spertus, Ja, Stark, K, Stoll, M, Tang, Wh, Tennstedt, S, Thorgeirsson, G, Tomaszewski, M, Uitterlinden, Ag, van Rij AM, Wells, Ga, Wichmann, He, Wild, Ps, Willenborg, C, Wright, Bj, Ye, S, Zeller, T, Cambien, F, Goodall, Ah, März, W, Blankenberg, S, Roberts, R, Mcpherson, R, Nilesh, J. S., Medical Research Council (MRC), Nica, Alexandra, Ongen, Halit, Dermitzakis, Emmanouil, ACS - Amsterdam Cardiovascular Sciences, Cardiology, Vascular Medicine, Biological Psychology, EMGO+ - Lifestyle, Overweight and Diabetes, Scherag, Andre (Beitragende*r), Hinney, Anke (Beitragende*r), Scherag, S. (Beitragende*r), Vogel, C (Beitragende*r), Hebebrand, Johannes (Beitragende*r), University of Groningen, Wheeler, Eleanor [0000-0002-8616-6444], Barnes, Daniel [0000-0002-3781-7570], Luan, Jian'an [0000-0003-3137-6337], Johnson, Kathleen [0000-0002-6823-3252], Danesh, John [0000-0003-1158-6791], Wareham, Nicholas [0000-0003-1422-2993], Barroso, Ines [0000-0001-5800-4520], Langenberg, Claudia [0000-0002-5017-7344], and Apollo - University of Cambridge Repository
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Male ,Netherlands Twin Register (NTR) ,endocrine system diseases ,Endocrinology, Diabetes and Metabolism ,medicine.medical_treatment ,Medizin ,Genome-wide association study ,Type 2 diabetes ,CORONARY HEART-DISEASE ,Fasting/blood ,0302 clinical medicine ,Insulin ,Glucose homeostasis ,ddc:576.5 ,Genome-wide ,Diabetes Mellitus, Type 2/blood/genetics/metabolism ,CARDIoGRAM Consortium ,POPULATION ,Proinsulin ,RISK ,Genetics ,0303 health sciences ,INSULIN SENSITIVITY ,11 Medical And Health Sciences ,Fasting ,Polymorphism, Single Nucleotide/genetics ,OBESITY ,Female ,type 2 diabetes ,Life Sciences & Biomedicine ,hormones, hormone substitutes, and hormone antagonists ,Insulin processing ,Adult ,medicine.medical_specialty ,endocrine system ,ENDOCRINOLOGY & METABOLISM ,SUSCEPTIBILITY LOCI ,Genotype ,030209 endocrinology & metabolism ,DIAGRAM Consortium ,Biology ,C4D Consortium ,Polymorphism, Single Nucleotide ,Molecular epidemiology [NCEBP 1] ,03 medical and health sciences ,Insulin resistance ,BETA-CELL FUNCTION ,SDG 3 - Good Health and Well-being ,Internal medicine ,GIANT Consortium ,Internal Medicine ,medicine ,Humans ,METAANALYSIS ,030304 developmental biology ,Science & Technology ,Genome, Human ,Hormonal regulation [IGMD 6] ,Genetic Variation ,nutritional and metabolic diseases ,proinsulin ,medicine.disease ,Proinsulin/blood ,TCF7L2 ,Endocrinology ,Diabetes Mellitus, Type 2 ,MuTHER Consortium ,GLUCOSE-HOMEOSTASIS ,Insulin/blood - Abstract
OBJECTIVE Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10−8). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10−4), improved β-cell function (P = 1.1 × 10−5), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10−6). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.
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- 2011
14. Identification of Novel Genetic Loci Associated with Thyroid Peroxidase Antibodies and Clinical Thyroid Disease
- Author
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Medici, Marco, Porcu, E, Pistis, G, Teumer, A, Brown, SJ, Jensen, RA, Rawal, R, Roef, GL, Plantinga, TS, Vermeulen, SH, Lahti, J, Simmonds, MJ, Husemoen, LLN, Freathy, RM, Shields, BM, Pietzner, D, Nagy, R, Broer, Linda, Chaker, Layal, Korevaar, Tim, Plia, MG, Sala, C, Volker, U, Richards, JB, Sweep, FC, Gieger, C, Corre, T, Kajantie, E, Thuesen, B, Taes, YE, Visser, Edward, Hattersley, AT, Kratzsch, J, Hamilton, A, Li, W (Wenguang), Homuth, G, Lobina, M, Mariotti, S, Soranzo, N, Cocca, M, Nauck, M, Spielhagen, C, Ross, A, Arnold, A, van de Bunt, M, Liyanarachchi, S, Heier, M, Grabe, HJ, Masciullo, C, Galesloot, TE, Lim, EM, Reischl, E, Leedman, PJ, Lai, S, Delitala, A, Bremner, AP, Philips, DIW, Beilby, JP, Mulas, A, Vocale, M, Abecasis, G, Forsen, T, James, A, Widen, E, Hui, J, Prokisch, H, Rietzschel, EE, Palotie, A, Feddema, P, Fletcher, SJ, Schramm, K, Rotter, JI, Kluttig, A, Radke, D, Traglia, M, Surdulescu, GL, He, HL, Franklyn, JA, Tiller, D, Vaidya, B, Meyer, T, Jorgensen, T, Eriksson, JG, O'Leary, PC, Wichmann, E, Hermus, AR, Psaty, BM, Ittermann, T, Hofman, Bert, Bosi, E, Schlessinger, D, Wallaschofski, H, Pirastu, N, Aulchenko, YS, de la Chapelle, A, Netea-Maier, RT, Gough, SCL, Meyer zu Schwabedissen, H, Frayling, TM, Kaufman, JM, Linneberg, A, Raikkonen, K, Smit, JWA, Kiemeney, LA, Rivadeneira, Fernando, Uitterlinden, André, Walsh, JP, Meisinger, C, Heijer, Mariska, Visser, Theo, Spector, TD, Wilson, SG, Voelzke, H, Cappola, A, Toniolo, D, Sanna, S, Naitza, S, Peeters, Robin, Medici, Marco, Porcu, E, Pistis, G, Teumer, A, Brown, SJ, Jensen, RA, Rawal, R, Roef, GL, Plantinga, TS, Vermeulen, SH, Lahti, J, Simmonds, MJ, Husemoen, LLN, Freathy, RM, Shields, BM, Pietzner, D, Nagy, R, Broer, Linda, Chaker, Layal, Korevaar, Tim, Plia, MG, Sala, C, Volker, U, Richards, JB, Sweep, FC, Gieger, C, Corre, T, Kajantie, E, Thuesen, B, Taes, YE, Visser, Edward, Hattersley, AT, Kratzsch, J, Hamilton, A, Li, W (Wenguang), Homuth, G, Lobina, M, Mariotti, S, Soranzo, N, Cocca, M, Nauck, M, Spielhagen, C, Ross, A, Arnold, A, van de Bunt, M, Liyanarachchi, S, Heier, M, Grabe, HJ, Masciullo, C, Galesloot, TE, Lim, EM, Reischl, E, Leedman, PJ, Lai, S, Delitala, A, Bremner, AP, Philips, DIW, Beilby, JP, Mulas, A, Vocale, M, Abecasis, G, Forsen, T, James, A, Widen, E, Hui, J, Prokisch, H, Rietzschel, EE, Palotie, A, Feddema, P, Fletcher, SJ, Schramm, K, Rotter, JI, Kluttig, A, Radke, D, Traglia, M, Surdulescu, GL, He, HL, Franklyn, JA, Tiller, D, Vaidya, B, Meyer, T, Jorgensen, T, Eriksson, JG, O'Leary, PC, Wichmann, E, Hermus, AR, Psaty, BM, Ittermann, T, Hofman, Bert, Bosi, E, Schlessinger, D, Wallaschofski, H, Pirastu, N, Aulchenko, YS, de la Chapelle, A, Netea-Maier, RT, Gough, SCL, Meyer zu Schwabedissen, H, Frayling, TM, Kaufman, JM, Linneberg, A, Raikkonen, K, Smit, JWA, Kiemeney, LA, Rivadeneira, Fernando, Uitterlinden, André, Walsh, JP, Meisinger, C, Heijer, Mariska, Visser, Theo, Spector, TD, Wilson, SG, Voelzke, H, Cappola, A, Toniolo, D, Sanna, S, Naitza, S, and Peeters, Robin
- Abstract
Author Summary Individuals with thyroid peroxidase antibodies (TPOAbs) have an increased risk of autoimmune thyroid diseases (AITD), which are common in the general population and associated with increased cardiovascular, metabolic and psychiatric morbidity and mortality. As the causative genes of TPOAbs and AITD remain largely unknown, we performed a genome-wide scan for TPOAbs in 18,297 individuals, with replication in 8,990 individuals. Significant associations were detected with variants at TPO, ATXN2, BACH2, MAGI3, and KALRN. Individuals carrying multiple risk variants also had a higher risk of increased thyroid-stimulating hormone levels (including subclinical and overt hypothyroidism), and a decreased risk of goiter. The MAGI3 and BACH2 variants were associated with an increased risk of hyperthyroidism, and the MAGI3 variant was also associated with an increased risk of hypothyroidism. This first genome-wide scan for TPOAbs identified five newly associated loci, three of which were also associated with clinical thyroid disease. With these markers we identified a large subgroup in the general population with a substantially increased risk of TPOAbs. These results provide insight into why individuals with thyroid autoimmunity do or do not eventually develop thyroid disease, and these markers may therefore predict which individuals are particularly at risk of developing clinical thyroid dysfunction. Autoimmune thyroid diseases (AITD) are common, affecting 2-5% of the general population. Individuals with positive thyroid peroxidase antibodies (TPOAbs) have an increased risk of autoimmune hypothyroidism (Hashimoto's thyroiditis), as well as autoimmune hyperthyroidism (Graves' disease). As the possible causative genes of TPOAbs and AITD remain largely unknown, we performed GWAS meta-analyses in 18,297 individuals for TPOAb-positivity (1769 TPOAb-positives and 16,528 TPOAb-negatives) and in 12,353 individuals for TPOAb serum levels, with replication in 8,9
- Published
- 2014
15. PMM.52 Lower circulating B12 in pregnancy is associated with higher maternal adiposity and insulin resistance in non-diabetic Caucasian women during and after pregnancy
- Author
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Knight, BA, primary, Shields, BM, additional, Hattersley, AT, additional, and Yajnik, CR, additional
- Published
- 2014
- Full Text
- View/download PDF
16. PMM.59 Maternal hypothyroxinaemia in pregnancy is associated with altered maternal metabolic parameters
- Author
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Knight, BA, primary, Shields, BM, additional, and Vaidya, B, additional
- Published
- 2014
- Full Text
- View/download PDF
17. A Meta-Analysis of Thyroid-Related Traits Reveals Novel Loci and Gender-Specific Differences in the Regulation of Thyroid Function
- Author
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Porcu, E, Medici, Marco, Pistis, G, Volpato, CB, Wilson, SG, Cappola, AR, Bos, SD (Steffan Daniel), Deelen, J, Heijer, Mariska, Freathy, RM, Lahti, J, Liu, CY, Lopez, LM, Nolte, IM (Ilja), O'Connell, JR, Tanaka, T, Trompet, S, Arnold, A, Bandinelli, S, Beekman, M, Bohringer, S, Brown, SJ, Buckley, BM, Camaschella, C, de Craen, AJM, Davies, G, de Visser, MCH, Ford, I, Forsen, T, Frayling, TM, Fugazzola, L, Gogele, M, Hattersley, AT, Hermus, AR, Hofman, Bert, Houwing-Duistermaat, JJ, Jensen, RA, Kajantie, E, Kloppenburg, M, Lim, EM, Masciullo, C, Mariotti, S, Minelli, C, Mitchell, BD, Nagaraja, R, Netea-Maier, RT, Palotie, A, Persani, L, Piras, MG, Psaty, BM, Raikkonen, K, Richards, JB, Rivadeneira, Fernando, Sala, C, Sabra, MM, Sattar, N, Shields, BM, Soranzo, N, Starr, JM, Stott, DJ, Sweep, FCGJ, Usala, G, van der Klauw, MM (Melanie), van Heemst, D, Mullem, Alies, Vermeulen, SH, Visser, Edward, Walsh, JP, Westendorp, RGJ, Widen, E, Zhai, GJ, Cucca, F, Deary, IJ, Eriksson, JG, Ferrucci, L, Fox, CS, Jukema, JW, Kiemeney, LA, Pramstaller, PP, Schlessinger, D, Shuldiner, AR, Slagboom, EP, Uitterlinden, André, Vaidya, B, Visser, Theo, Wolffenbuttel, BHR, Meulenbelt, I, Rotter, JI, Spector, TD, Hicks, AA, Toniolo, D, Sanna, S, Peeters, Robin, Naitza, S, Porcu, E, Medici, Marco, Pistis, G, Volpato, CB, Wilson, SG, Cappola, AR, Bos, SD (Steffan Daniel), Deelen, J, Heijer, Mariska, Freathy, RM, Lahti, J, Liu, CY, Lopez, LM, Nolte, IM (Ilja), O'Connell, JR, Tanaka, T, Trompet, S, Arnold, A, Bandinelli, S, Beekman, M, Bohringer, S, Brown, SJ, Buckley, BM, Camaschella, C, de Craen, AJM, Davies, G, de Visser, MCH, Ford, I, Forsen, T, Frayling, TM, Fugazzola, L, Gogele, M, Hattersley, AT, Hermus, AR, Hofman, Bert, Houwing-Duistermaat, JJ, Jensen, RA, Kajantie, E, Kloppenburg, M, Lim, EM, Masciullo, C, Mariotti, S, Minelli, C, Mitchell, BD, Nagaraja, R, Netea-Maier, RT, Palotie, A, Persani, L, Piras, MG, Psaty, BM, Raikkonen, K, Richards, JB, Rivadeneira, Fernando, Sala, C, Sabra, MM, Sattar, N, Shields, BM, Soranzo, N, Starr, JM, Stott, DJ, Sweep, FCGJ, Usala, G, van der Klauw, MM (Melanie), van Heemst, D, Mullem, Alies, Vermeulen, SH, Visser, Edward, Walsh, JP, Westendorp, RGJ, Widen, E, Zhai, GJ, Cucca, F, Deary, IJ, Eriksson, JG, Ferrucci, L, Fox, CS, Jukema, JW, Kiemeney, LA, Pramstaller, PP, Schlessinger, D, Shuldiner, AR, Slagboom, EP, Uitterlinden, André, Vaidya, B, Visser, Theo, Wolffenbuttel, BHR, Meulenbelt, I, Rotter, JI, Spector, TD, Hicks, AA, Toniolo, D, Sanna, S, Peeters, Robin, and Naitza, S
- Published
- 2013
18. Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls
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Craddock, N, Hurles, ME, Cardin, N, Pearson, RD, Plagnol, V, Robson, S, Vukcevic, D, Barnes, C, Conrad, DF, Giannoulatou, E, Holmes, C, Marchini, JL, Stirrups, K, Tobin, MD, Wain, LV, Yau, C, Aerts, J, Ahmad, T, Andrews, TD, Arbury, H, Attwood, A, Auton, A, Ball, SG, Balmforth, AJ, Barrett, JC, Barroso, I, Barton, A, Bennett, AJ, Bhaskar, S, Blaszczyk, K, Bowes, J, Brand, OJ, Braund, PS, Bredin, F, Breen, G, Brown, MJ, Bruce, IN, Bull, J, Burren, OS, Burton, J, Byrnes, J, Caesar, S, Clee, CM, Coffey, AJ, Connell, JMC, Cooper, JD, Dominiczak, AF, Downes, K, Drummond, HE, Dudakia, D, Dunham, A, Ebbs, B, Eccles, D, Edkins, S, Edwards, C, Elliot, A, Emery, P, Evans, DM, Evans, G, Eyre, S, Farmer, A, Ferrier, IN, Feuk, L, Fitzgerald, T, Flynn, E, Forbes, A, Forty, L, Franklyn, JA, Freathy, RM, Gibbs, P, Gilbert, P, Gokumen, O, Gordon-Smith, K, Gray, E, Green, E, Groves, CJ, Grozeva, D, Gwilliam, R, Hall, A, Hammond, N, Hardy, M, Harrison, P, Hassanali, N, Hebaishi, H, Hines, S, Hinks, A, Hitman, GA, Hocking, L, Howard, E, Howard, P, Howson, JMM, Hughes, D, Hunt, S, Isaacs, JD, Jain, M, Jewell, DP, Johnson, T, Jolley, JD, Jones, IR, Jones, LA, Kirov, G, Langford, CF, Lango-Allen, H, Lathrop, GM, Lee, J, Lee, KL, Lees, C, Lewis, K, Lindgren, CM, Maisuria-Armer, M, Maller, J, Mansfield, J, Martin, P, Massey, DCO, McArdle, WL, McGuffin, P, McLay, KE, Mentzer, A, Mimmack, ML, Morgan, AE, Morris, AP, Mowat, C, Myers, S, Newman, W, Nimmo, ER, O'Donovan, MC, Onipinla, A, Onyiah, I, Ovington, NR, Owen, MJ, Palin, K, Parnell, K, Pernet, D, Perry, JRB, Phillips, A, Pinto, D, Prescott, NJ, Prokopenko, I, Quail, MA, Rafelt, S, Rayner, NW, Redon, R, Reid, DM, Renwick, A, Ring, SM, Robertson, N, Russell, E, St Clair, D, Sambrook, JG, Sanderson, JD, Schuilenburg, H, Scott, CE, Scott, R, Seal, S, Shaw-Hawkins, S, Shields, BM, Simmonds, MJ, Smyth, DJ, Somaskantharajah, E, Spanova, K, Steer, S, Stephens, J, Stevens, HE, Stone, MA, Su, Z, Symmons, DPM, Thompson, JR, Thomson, W, Travers, ME, Turnbull, C, Valsesia, A, Walker, M, Walker, NM, Wallace, C, Warren-Perry, M, Watkins, NA, Webster, J, Weedon, MN, Wilson, AG, Woodburn, M, Wordsworth, BP, Young, AH, Zeggini, E, Carter, NP, Frayling, TM, Lee, C, McVean, G, Munroe, PB, Palotie, A, Sawcer, SJ, Scherer, SW, Strachan, DP, Tyler-Smith, C, Brown, MA, Burton, PR, Caulfield, MJ, Compston, A, Farrall, M, Gough, SCL, Hall, AS, Hattersley, AT, Hill, AVS, Mathew, CG, Pembrey, M, Satsangi, J, Stratton, MR, Worthington, J, Deloukas, P, Duncanson, A, Kwiatkowski, DP, McCarthy, MI, Ouwehand, WH, Parkes, M, Rahman, N, Todd, JA, Samani, NJ, Donnelly, P, Craddock, N, Hurles, ME, Cardin, N, Pearson, RD, Plagnol, V, Robson, S, Vukcevic, D, Barnes, C, Conrad, DF, Giannoulatou, E, Holmes, C, Marchini, JL, Stirrups, K, Tobin, MD, Wain, LV, Yau, C, Aerts, J, Ahmad, T, Andrews, TD, Arbury, H, Attwood, A, Auton, A, Ball, SG, Balmforth, AJ, Barrett, JC, Barroso, I, Barton, A, Bennett, AJ, Bhaskar, S, Blaszczyk, K, Bowes, J, Brand, OJ, Braund, PS, Bredin, F, Breen, G, Brown, MJ, Bruce, IN, Bull, J, Burren, OS, Burton, J, Byrnes, J, Caesar, S, Clee, CM, Coffey, AJ, Connell, JMC, Cooper, JD, Dominiczak, AF, Downes, K, Drummond, HE, Dudakia, D, Dunham, A, Ebbs, B, Eccles, D, Edkins, S, Edwards, C, Elliot, A, Emery, P, Evans, DM, Evans, G, Eyre, S, Farmer, A, Ferrier, IN, Feuk, L, Fitzgerald, T, Flynn, E, Forbes, A, Forty, L, Franklyn, JA, Freathy, RM, Gibbs, P, Gilbert, P, Gokumen, O, Gordon-Smith, K, Gray, E, Green, E, Groves, CJ, Grozeva, D, Gwilliam, R, Hall, A, Hammond, N, Hardy, M, Harrison, P, Hassanali, N, Hebaishi, H, Hines, S, Hinks, A, Hitman, GA, Hocking, L, Howard, E, Howard, P, Howson, JMM, Hughes, D, Hunt, S, Isaacs, JD, Jain, M, Jewell, DP, Johnson, T, Jolley, JD, Jones, IR, Jones, LA, Kirov, G, Langford, CF, Lango-Allen, H, Lathrop, GM, Lee, J, Lee, KL, Lees, C, Lewis, K, Lindgren, CM, Maisuria-Armer, M, Maller, J, Mansfield, J, Martin, P, Massey, DCO, McArdle, WL, McGuffin, P, McLay, KE, Mentzer, A, Mimmack, ML, Morgan, AE, Morris, AP, Mowat, C, Myers, S, Newman, W, Nimmo, ER, O'Donovan, MC, Onipinla, A, Onyiah, I, Ovington, NR, Owen, MJ, Palin, K, Parnell, K, Pernet, D, Perry, JRB, Phillips, A, Pinto, D, Prescott, NJ, Prokopenko, I, Quail, MA, Rafelt, S, Rayner, NW, Redon, R, Reid, DM, Renwick, A, Ring, SM, Robertson, N, Russell, E, St Clair, D, Sambrook, JG, Sanderson, JD, Schuilenburg, H, Scott, CE, Scott, R, Seal, S, Shaw-Hawkins, S, Shields, BM, Simmonds, MJ, Smyth, DJ, Somaskantharajah, E, Spanova, K, Steer, S, Stephens, J, Stevens, HE, Stone, MA, Su, Z, Symmons, DPM, Thompson, JR, Thomson, W, Travers, ME, Turnbull, C, Valsesia, A, Walker, M, Walker, NM, Wallace, C, Warren-Perry, M, Watkins, NA, Webster, J, Weedon, MN, Wilson, AG, Woodburn, M, Wordsworth, BP, Young, AH, Zeggini, E, Carter, NP, Frayling, TM, Lee, C, McVean, G, Munroe, PB, Palotie, A, Sawcer, SJ, Scherer, SW, Strachan, DP, Tyler-Smith, C, Brown, MA, Burton, PR, Caulfield, MJ, Compston, A, Farrall, M, Gough, SCL, Hall, AS, Hattersley, AT, Hill, AVS, Mathew, CG, Pembrey, M, Satsangi, J, Stratton, MR, Worthington, J, Deloukas, P, Duncanson, A, Kwiatkowski, DP, McCarthy, MI, Ouwehand, WH, Parkes, M, Rahman, N, Todd, JA, Samani, NJ, and Donnelly, P
- Abstract
Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to have an important role in genetic susceptibility to common disease. To address this we undertook a large, direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed approximately 19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated approximately 50% of all common CNVs larger than 500 base pairs. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with disease-IRGM for Crohn's disease, HLA for Crohn's disease, rheumatoid arthritis and type 1 diabetes, and TSPAN8 for type 2 diabetes-although in each case the locus had previously been identified in single nucleotide polymorphism (SNP)-based studies, reflecting our observation that most common CNVs that are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs that can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases.
- Published
- 2010
19. Variants in ADCY5 and near CCNL1 are associated with fetal growth and birth weight
- Author
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Freathy, RM, Mook-Kanamori, DO, Sovio, U, Prokopenko, I, Timpson, NJ, Berry, DJ, Warrington, NM, Widen, E, Hottenga, JJ, Kaakinen, M, Lange, LA, Bradfield, JP, Kerkhof, M, Marsh, JA, Maegi, R, Chen, C-M, Lyon, HN, Kirin, M, Adair, LS, Aulchenko, YS, Bennett, AJ, Borja, JB, Bouatia-Naji, N, Charoen, P, Coin, LJM, Cousminer, DL, de Geus, EJC, Deloukas, P, Elliott, P, Evans, DM, Froguel, P, Glaser, B, Groves, CJ, Hartikainen, A-L, Hassanali, N, Hirschhorn, JN, Hofman, A, Holly, JMP, Hyppoenen, E, Kanoni, S, Knight, BA, Laitinen, J, Lindgren, CM, McArdle, WL, O'Reilly, PF, Pennell, CE, Postma, DS, Pouta, A, Ramasamy, A, Rayner, NW, Ring, SM, Rivadeneira, F, Shields, BM, Strachan, DP, Surakka, I, Taanila, A, Tiesler, C, Uitterlinden, AG, van Duijn, CM, Wijga, AH, Willemsen, G, Zhang, H, Zhao, J, Wilson, JF, Steegers, EAP, Hattersley, AT, Eriksson, JG, Peltonen, L, Mohlke, KL, Grant, SFA, Hakonarson, H, Koppelman, GH, Dedoussis, GV, Heinrich, J, Gillman, MW, Palmer, LJ, Frayling, TM, Boomsma, DI, Smith, GD, Power, C, Jaddoe, VWV, Jarvelin, M-R, McCarthy, MI, Freathy, RM, Mook-Kanamori, DO, Sovio, U, Prokopenko, I, Timpson, NJ, Berry, DJ, Warrington, NM, Widen, E, Hottenga, JJ, Kaakinen, M, Lange, LA, Bradfield, JP, Kerkhof, M, Marsh, JA, Maegi, R, Chen, C-M, Lyon, HN, Kirin, M, Adair, LS, Aulchenko, YS, Bennett, AJ, Borja, JB, Bouatia-Naji, N, Charoen, P, Coin, LJM, Cousminer, DL, de Geus, EJC, Deloukas, P, Elliott, P, Evans, DM, Froguel, P, Glaser, B, Groves, CJ, Hartikainen, A-L, Hassanali, N, Hirschhorn, JN, Hofman, A, Holly, JMP, Hyppoenen, E, Kanoni, S, Knight, BA, Laitinen, J, Lindgren, CM, McArdle, WL, O'Reilly, PF, Pennell, CE, Postma, DS, Pouta, A, Ramasamy, A, Rayner, NW, Ring, SM, Rivadeneira, F, Shields, BM, Strachan, DP, Surakka, I, Taanila, A, Tiesler, C, Uitterlinden, AG, van Duijn, CM, Wijga, AH, Willemsen, G, Zhang, H, Zhao, J, Wilson, JF, Steegers, EAP, Hattersley, AT, Eriksson, JG, Peltonen, L, Mohlke, KL, Grant, SFA, Hakonarson, H, Koppelman, GH, Dedoussis, GV, Heinrich, J, Gillman, MW, Palmer, LJ, Frayling, TM, Boomsma, DI, Smith, GD, Power, C, Jaddoe, VWV, Jarvelin, M-R, and McCarthy, MI
- Abstract
To identify genetic variants associated with birth weight, we meta-analyzed six genome-wide association (GWA) studies (n = 10,623 Europeans from pregnancy/birth cohorts) and followed up two lead signals in 13 replication studies (n = 27,591). rs900400 near LEKR1 and CCNL1 (P = 2 x 10(-35)) and rs9883204 in ADCY5 (P = 7 x 10(-15)) were robustly associated with birth weight. Correlated SNPs in ADCY5 were recently implicated in regulation of glucose levels and susceptibility to type 2 diabetes, providing evidence that the well-described association between lower birth weight and subsequent type 2 diabetes has a genetic component, distinct from the proposed role of programming by maternal nutrition. Using data from both SNPs, we found that the 9% of Europeans carrying four birth weight-lowering alleles were, on average, 113 g (95% CI 89-137 g) lighter at birth than the 24% with zero or one alleles (P(trend) = 7 x 10(-30)). The impact on birth weight is similar to that of a mother smoking 4-5 cigarettes per day in the third trimester of pregnancy.
- Published
- 2010
20. Preanalytical sample handling of venous blood: how to ensure your glucose measurement is accurate and reliable
- Author
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Steele, AM, primary, Wensley, KJ, additional, Brewer, E, additional, Shields, BM, additional, Hattersley, AT, additional, and McDonald, TJ, additional
- Published
- 2013
- Full Text
- View/download PDF
21. Erratum: Corrigendum: Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis
- Author
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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, and McCarthy, MI
- Subjects
Genetics ,Scale (ratio) ,medicine ,Susceptibility locus ,Type 2 diabetes ,Biology ,medicine.disease ,Genetic association - Published
- 2011
22. Lessons from the mixed-meal tolerance test: use of 90-minute and fasting C-peptide in pediatric diabetes.
- Author
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Besser RE, Shields BM, Casas R, Hattersley AT, Ludvigsson J, Besser, Rachel E J, Shields, Beverley M, Casas, Rosaura, Hattersley, Andrew T, and Ludvigsson, Johnny
- Abstract
Objective: Mixed-meal tolerance test (MMTT) area under the curve C-peptide (AUC CP) is the gold-standard measure of endogenous insulin secretion in type 1 diabetes but is intensive and invasive to perform. The 90-min MMTT-stimulated CP ≥0.2 nmol/L (90CP) is related to improved clinical outcomes, and CP ≥0.1 nmol/L is the equivalent fasting measure (FCP). We assessed whether 90CP or FCP are alternatives to a full MMTT.Research Design and Methods: CP was measured during 1,334 MMTTs in 421 type 1 diabetes patients aged <18 years at 3, 9, 18, 48, and 72 months duration. We assessed: 1) correlation between mean AUC CP and 90CP or FCP; 2) sensitivity and specificity of 90CP ≥0.2 nmol/L and FCP ≥ 0.1 nmol/L to detect peak CP ≥0.2 nmol/L and the equivalent AUC CP; and 3) how the time taken to reach the CP peak varied with age of diagnosis and diabetes duration.Results: AUC CP was highly correlated to 90CP (r(s) = 0.96; P < 0.0001) and strongly correlated to FCP (r(s) = 0.84; P < 0.0001). AUC CP ≥23 nmol/L/150 min was the equivalent cutoff for peak CP ≥0.2 nmol/L (98% sensitivity/97% specificity). A 90CP ≥0.2 nmol/L correctly classified 96% patients using AUC or peak CP, whereas FCP ≥0.1 nmol/L classified 83 and 85% patients, respectively. There was only a small difference seen between peak and 90CP (median 0.02 nmol/L). The CP peak occurred earlier in patients with longer diabetes duration (6.1 min each 1-year increase in duration) and younger age (2.5 min each 1-year increase).Conclusions: 90CP is a highly sensitive and specific measure of AUC and peak CP in children and adolescents with type 1 diabetes and offers a practical alternative to a full MMTT. [ABSTRACT FROM AUTHOR]- Published
- 2013
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23. Urinary C-peptide creatinine ratio is a practical outpatient tool for identifying hepatocyte nuclear factor 1-{alpha}/hepatocyte nuclear factor 4-{alpha} maturity-onset diabetes of the young from long-duration type 1 diabetes.
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Besser RE, Shepherd MH, McDonald TJ, Shields BM, Knight BA, Ellard S, Hattersley AT, Besser, Rachel E J, Shepherd, Maggie H, McDonald, Timothy J, Shields, Beverley M, Knight, Bridget A, Ellard, Sian, and Hattersley, Andrew T
- Abstract
Objective: Hepatocyte nuclear factor 1-α (HNF1A)/hepatocyte nuclear factor 4-α (HNF4A) maturity-onset diabetes of the young (MODY) is frequently misdiagnosed as type 1 diabetes, and patients are inappropriately treated with insulin. Blood C-peptide can aid in the diagnosis of MODY, but practical reasons limit its widespread use. Urinary C-peptide creatinine ratio (UCPCR), a stable measure of endogenous insulin secretion, is a noninvasive alternative. We aimed to compare stimulated UCPCR in adults with HNF1A/4A MODY, type 1 diabetes, and type 2 diabetes.Research Design and Methods: Adults with diabetes for ≥ 5 years, without renal impairment, were studied (HNF1A MODY [n = 54], HNF4A MODY [n = 23], glucokinase MODY [n = 20], type 1 diabetes [n = 69], and type 2 diabetes [n = 54]). The UCPCR was collected in boric acid 120 min after the largest meal of the day and mailed for analysis. Receiver operating characteristic (ROC) curves were used to identify optimal UCPCR cutoffs to differentiate HNF1A/4A MODY from type 1 and type 2 diabetes.Results: UCPCR was lower in type 1 diabetes than HNF1A/4A MODY (median [interquartile range]) (<0.02 nmol/mmol [<0.02 to <0.02] vs. 1.72 nmol/mmol [0.98-2.90]; P < 0.0001). ROC curves showed excellent discrimination (area under curve [AUC] 0.98) and identified a cutoff UCPCR of ≥ 0.2 nmol/mmol for differentiating HNF1A/4A MODY from type 1 diabetes (97% sensitivity, 96% specificity). UCPCR was lower in HNF1A/4A MODY than in type 2 diabetes (1.72 nmol/mmol [0.98-2.90] vs. 2.47 nmol/mmol [1.4-4.13]); P = 0.007). ROC curves showed a weak distinction between HNF1A/4A MODY and type 2 diabetes (AUC 0.64).Conclusions: UCPCR is a noninvasive outpatient tool that can be used to discriminate HNF1A and HNF4A MODY from long-duration type 1 diabetes. To differentiate MODY from type 1 diabetes of >5 years' duration, UCPCR could be used to determine whether genetic testing is indicated. [ABSTRACT FROM AUTHOR]- Published
- 2011
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24. Effective treatment with oral sulfonylureas in patients with diabetes due to sulfonylurea receptor 1 (SUR1) mutations.
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Rafiq M, Flanagan SE, Patch AM, Shields BM, Ellard S, Hattersley AT, Neonatal Diabetes International Collaborative Group, Rafiq, Meena, Flanagan, Sarah E, Patch, Ann-Marie, Shields, Beverley M, Ellard, Sian, and Hattersley, Andrew T
- Abstract
Objective: Neonatal diabetes can result from mutations in the Kir6.2 or sulfonylurea receptor 1 (SUR1) subunits of the ATP-sensitive K(+) channel. Transfer from insulin to oral sulfonylureas in patients with neonatal diabetes due to Kir6.2 mutations is well described, but less is known about changing therapy in patients with SUR1 mutations. We aimed to describe the response to sulfonylurea therapy in patients with SUR1 mutations and to compare it with Kir6.2 mutations.Research Design and Methods: We followed 27 patients with SUR1 mutations for at least 2 months after attempted transfer to sulfonylureas. Information was collected on clinical features, treatment before and after transfer, and the transfer protocol used. We compared successful and unsuccessful transfer patients, glycemic control before and after transfer, and treatment requirements in patients with SUR1 and Kir6.2 mutations.Results: Twenty-three patients (85%) successfully transferred onto sulfonylureas without significant side effects or increased hypoglycemia and did not need insulin injections. In these patients, median A1C fell from 7.2% (interquartile range 6.6-8.2%) on insulin to 5.5% (5.3-6.2%) on sulfonylureas (P = 0.01). When compared with Kir6.2 patients, SUR1 patients needed lower doses of both insulin before transfer (0.4 vs. 0.7 units x kg(-1) x day(-1); P = 0.002) and sulfonylureas after transfer (0.26 vs. 0.45 mg x kg(-1) x day(-1); P = 0.005).Conclusions: Oral sulfonylurea therapy is safe and effective in the short term in most patients with diabetes due to SUR1 mutations and may successfully replace treatment with insulin injections. A different treatment protocol needs to be developed for this group because they require lower doses of sulfonylureas than required by Kir6.2 patients. [ABSTRACT FROM AUTHOR]- Published
- 2008
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25. Waist circumference: a predictive tool for insulin resistance.
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Steele AM, Shields BM, Knight B, and Pearson ER
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- 2005
26. Genome-wide association study identifies eight loci associated with blood pressure
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Newton-Cheh, C, Johnson, T, Gateva, V, Tobin, MD, Bochud, M, Coin, L, Najjar, SS, Zhao, JH, Heath, SC, Eyheramendy, S, Papadakis, K, Voight, BF, Scott, LJ, Zhang, F, Farrall, M, Tanaka, T, Wallace, C, Chambers, JC, Khaw, K, Nilsson, P, Van Der Harst, P, Polidoro, S, Grobbee, DE, Onland-Moret, NC, Bots, ML, Wain, LV, Elliot, KS, Teumer, A, Luan, J, Lucas, G, Kuusisto, J, Burton, PR, Hadley, D, McArdle, WL, Brown, M, Dominiczak, A, Newhouse, SJ, Samani, NJ, Webster, J, Zeggini, E, Beckmann, JS, Bergmann, S, Lim, N, Song, K, Vollenweider, P, Waeber, G, Waterworth, DM, Yuan, X, Groop, L, Orho-Melander, M, Allione, A, Di Gregorio, A, Guarrera, S, Panico, S, Ricceri, F, Romanazzi, V, Sacerdote, C, Vineis, P, Barroso, I, Sandhu, MS, Luben, RN, Crawford, GJ, Jousilahti, P, Perola, M, Boehnke, M, Bonnycastle, LL, Collins, FS, Jackson, AU, Mohlke, KL, Stringham, HM, Valle, TT, Willer, CJ, Bergman, RN, Morken, MA, Döring, A, Gieger, C, Illig, T, Meitinger, T, Org, E, Pfeufer, A, Wichmann, HE, Kathiresan, S, Marrugat, J, O'Donnell, CJ, Schwartz, SM, Siscovick, DS, Subirana, I, Freimer, NB, Hartikainen, A, McCarthy, MI, O'Reilly, PF, Peltonen, L, Pouta, A, De Jong, PE, Snieder, H, Van Gilst, WH, Clarke, R, Goel, A, Hamsten, A, Altshuler, D, Jarvelin, M, Elliott, P, Lakatta, EG, Forouhi, N, Wareham, NJ, Loos, RJF, Deloukas, P, Lathrop, GM, Zelenika, D, Strachan, DP, Soranzo, N, Williams, FM, Zhai, G, Spector, TD, Peden, JF, Watkins, H, Ferrucci, L, Caulfield, M, Munroe, PB, Berglund, G, Melander, O, Matullo, G, Uiterwaal, CS, van der Schouw, YT, Numans, ME, Ernst, F, Homuth, G, Völker, U, Elosua, R, Laakso, M, Connell, JM, Mooser, V, Salomaa, V, Tuomilehto, J, Laan, M, Navis, G, Seedorf, U, Syvänen, A, Tognoni, G, Sanna, S, Uda, M, Scheet, P, Schlessinger, D, Scuteri, A, Dörr, M, Felix, SB, Reffelmann, T, Lorbeer, R, Völzke, H, Rettig, R, Galan, P, Hercberg, S, Bingham, SA, Kooner, JS, Bandinelli, S, Meneton, P, Abecasis, G, Thompson, JR, Braga Marcano, CA, Barke, B, Dobson, R, Gungadoo, J, Lee, KL, Onipinla, A, Wallace, I, Xue, M, Clayton, DG, Leung, H, Nutland, S, Walker, NM, Todd, JA, Stevens, HE, Dunger, DB, Widmer, B, Downes, K, Cardon, LR, Kwiatkowski, DP, Barrett, JC, Evans, D, Morris, AP, Lindgren, CM, Rayner, NW, Timpson, NJ, Lyons, E, Vannberg, F, Hill, AVS, Teo, YY, Rockett, KA, Craddock, N, Attwood, AP, Bryan, C, Bumpstead, SJ, Chaney, A, Ghori, J, William, RG, Hunt, SE, Inouye, M, Keniry, E, King, E, McGinnis, R, Potter, S, Ravindrarajan, R, Whittaker, P, Withers, D, Bentley, D, Groves, CJ, Duncanson, A, Ouwehand, WH, Boorman, JP, Cant, B, Jolley, JD, Knight, AS, Koch, K, Taylor, NC, Watkins, NA, Winzer, T, Braund, PS, Dixon, RJ, Mangino, M, Stevens, S, Donnely, P, Davidson, D, Marchini, JL, Spencer, ICA, Cardin, NJ, Ferreira, T, Pereira-Gale, J, Hallgrimsdottir, IB, Howie, BN, Su, Z, Vukcevic, D, Easton, D, Everson, U, Hussey, JM, Meech, E, Prowse, CV, Walters, GR, Jones, RW, Ring, SM, Prembey, M, Breen, G, St Clair, D, Ceasar, S, Gordon-Smith, K, Fraser, C, Green, EK, Grozeva, D, Hamshere, ML, Holmans, PA, Jones, IR, Kirov, G, Moskovina, V, Nikolov, I, O'Donovan, MC, Owen, MJ, Collier, DA, Elkin, A, Farmer, A, Williamson, R, McGruffin, P, Young, AH, Ferrier, IN, Ball, SG, Balmforth, AJ, Barrett, JH, Bishop, DT, Iles, MM, Maqbool, A, Yuldasheva, N, Hall, AS, Bredin, F, Tremelling, M, Parkes, M, Drummond, H, Lees, CW, Nimmo, ER, Satsangi, J, Fisher, SA, Lewis, CM, Onnie, CM, Prescott, NJ, Mathew, CG, Forbes, A, Sanderson, J, Mathew, C, Barbour, J, Mohiuddin, MK, Todhunter, CE, Mansfield, JC, Ahmad, T, Cummings, FR, Jewell, DP, Barton, A, Bruce, IN, Donovan, H, Eyre, S, Gilbert, PD, Hider, SL, Hinks, AM, John, SL, Potter, C, Silman, AJ, Symmons, DPM, Thomson, W, Worthington, J, Frayling, TM, Freathy, RM, Lango, H, Perry, JRB, Weedon, MN, Hattersley, AT, Shields, BM, Hitman, GA, Walker, M, Newport, M, Sirugo, G, Conway, D, Jallow, M, Bradbury, LA, Pointon, JL, Brown, MA, Farrar, C, Wordsworth, P, Franklyn, JA, Heward, JM, Simmonds, MJ, Cough, SCL, Seal, S, Stratton, MR, Ban, M, Goris, A, Sawcer, SJ, Compston, A, Newton-Cheh, C, Johnson, T, Gateva, V, Tobin, MD, Bochud, M, Coin, L, Najjar, SS, Zhao, JH, Heath, SC, Eyheramendy, S, Papadakis, K, Voight, BF, Scott, LJ, Zhang, F, Farrall, M, Tanaka, T, Wallace, C, Chambers, JC, Khaw, K, Nilsson, P, Van Der Harst, P, Polidoro, S, Grobbee, DE, Onland-Moret, NC, Bots, ML, Wain, LV, Elliot, KS, Teumer, A, Luan, J, Lucas, G, Kuusisto, J, Burton, PR, Hadley, D, McArdle, WL, Brown, M, Dominiczak, A, Newhouse, SJ, Samani, NJ, Webster, J, Zeggini, E, Beckmann, JS, Bergmann, S, Lim, N, Song, K, Vollenweider, P, Waeber, G, Waterworth, DM, Yuan, X, Groop, L, Orho-Melander, M, Allione, A, Di Gregorio, A, Guarrera, S, Panico, S, Ricceri, F, Romanazzi, V, Sacerdote, C, Vineis, P, Barroso, I, Sandhu, MS, Luben, RN, Crawford, GJ, Jousilahti, P, Perola, M, Boehnke, M, Bonnycastle, LL, Collins, FS, Jackson, AU, Mohlke, KL, Stringham, HM, Valle, TT, Willer, CJ, Bergman, RN, Morken, MA, Döring, A, Gieger, C, Illig, T, Meitinger, T, Org, E, Pfeufer, A, Wichmann, HE, Kathiresan, S, Marrugat, J, O'Donnell, CJ, Schwartz, SM, Siscovick, DS, Subirana, I, Freimer, NB, Hartikainen, A, McCarthy, MI, O'Reilly, PF, Peltonen, L, Pouta, A, De Jong, PE, Snieder, H, Van Gilst, WH, Clarke, R, Goel, A, Hamsten, A, Altshuler, D, Jarvelin, M, Elliott, P, Lakatta, EG, Forouhi, N, Wareham, NJ, Loos, RJF, Deloukas, P, Lathrop, GM, Zelenika, D, Strachan, DP, Soranzo, N, Williams, FM, Zhai, G, Spector, TD, Peden, JF, Watkins, H, Ferrucci, L, Caulfield, M, Munroe, PB, Berglund, G, Melander, O, Matullo, G, Uiterwaal, CS, van der Schouw, YT, Numans, ME, Ernst, F, Homuth, G, Völker, U, Elosua, R, Laakso, M, Connell, JM, Mooser, V, Salomaa, V, Tuomilehto, J, Laan, M, Navis, G, Seedorf, U, Syvänen, A, Tognoni, G, Sanna, S, Uda, M, Scheet, P, Schlessinger, D, Scuteri, A, Dörr, M, Felix, SB, Reffelmann, T, Lorbeer, R, Völzke, H, Rettig, R, Galan, P, Hercberg, S, Bingham, SA, Kooner, JS, Bandinelli, S, Meneton, P, Abecasis, G, Thompson, JR, Braga Marcano, CA, Barke, B, Dobson, R, Gungadoo, J, Lee, KL, Onipinla, A, Wallace, I, Xue, M, Clayton, DG, Leung, H, Nutland, S, Walker, NM, Todd, JA, Stevens, HE, Dunger, DB, Widmer, B, Downes, K, Cardon, LR, Kwiatkowski, DP, Barrett, JC, Evans, D, Morris, AP, Lindgren, CM, Rayner, NW, Timpson, NJ, Lyons, E, Vannberg, F, Hill, AVS, Teo, YY, Rockett, KA, Craddock, N, Attwood, AP, Bryan, C, Bumpstead, SJ, Chaney, A, Ghori, J, William, RG, Hunt, SE, Inouye, M, Keniry, E, King, E, McGinnis, R, Potter, S, Ravindrarajan, R, Whittaker, P, Withers, D, Bentley, D, Groves, CJ, Duncanson, A, Ouwehand, WH, Boorman, JP, Cant, B, Jolley, JD, Knight, AS, Koch, K, Taylor, NC, Watkins, NA, Winzer, T, Braund, PS, Dixon, RJ, Mangino, M, Stevens, S, Donnely, P, Davidson, D, Marchini, JL, Spencer, ICA, Cardin, NJ, Ferreira, T, Pereira-Gale, J, Hallgrimsdottir, IB, Howie, BN, Su, Z, Vukcevic, D, Easton, D, Everson, U, Hussey, JM, Meech, E, Prowse, CV, Walters, GR, Jones, RW, Ring, SM, Prembey, M, Breen, G, St Clair, D, Ceasar, S, Gordon-Smith, K, Fraser, C, Green, EK, Grozeva, D, Hamshere, ML, Holmans, PA, Jones, IR, Kirov, G, Moskovina, V, Nikolov, I, O'Donovan, MC, Owen, MJ, Collier, DA, Elkin, A, Farmer, A, Williamson, R, McGruffin, P, Young, AH, Ferrier, IN, Ball, SG, Balmforth, AJ, Barrett, JH, Bishop, DT, Iles, MM, Maqbool, A, Yuldasheva, N, Hall, AS, Bredin, F, Tremelling, M, Parkes, M, Drummond, H, Lees, CW, Nimmo, ER, Satsangi, J, Fisher, SA, Lewis, CM, Onnie, CM, Prescott, NJ, Mathew, CG, Forbes, A, Sanderson, J, Mathew, C, Barbour, J, Mohiuddin, MK, Todhunter, CE, Mansfield, JC, Ahmad, T, Cummings, FR, Jewell, DP, Barton, A, Bruce, IN, Donovan, H, Eyre, S, Gilbert, PD, Hider, SL, Hinks, AM, John, SL, Potter, C, Silman, AJ, Symmons, DPM, Thomson, W, Worthington, J, Frayling, TM, Freathy, RM, Lango, H, Perry, JRB, Weedon, MN, Hattersley, AT, Shields, BM, Hitman, GA, Walker, M, Newport, M, Sirugo, G, Conway, D, Jallow, M, Bradbury, LA, Pointon, JL, Brown, MA, Farrar, C, Wordsworth, P, Franklyn, JA, Heward, JM, Simmonds, MJ, Cough, SCL, Seal, S, Stratton, MR, Ban, M, Goris, A, Sawcer, SJ, and Compston, A
- Abstract
Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5 million genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N ≤ 71,225 European ancestry, N ≤ 12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N = 29,136). We identified association between systolic or diastolic blood pressure and common variants in eight regions near the CYP17A1 (P = 7 × 10−24), CYP1A2 (P = 1 × 10−23), FGF5 (P = 1 × 10−21), SH2B3 (P = 3 × 10−18), MTHFR (P = 2 × 10−13), c10orf107 (P = 1 × 10−9), ZNF652 (P = 5 × 10−9) and PLCD3 (P = 1 × 10−8) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.
27. Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
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Romagnoni, A., Jegou, S., Van Steen, K., Wainrib, G., Hugot, J. -P., Peyrin-Biroulet, L., Chamaillard, M., Colombel, J. -F., Cottone, M., D'Amato, M., D'Inca, R., Halfvarson, J., Henderson, P., Karban, A., Kennedy, N. A., Khan, M. A., Lemann, M., Levine, A., Massey, D., Milla, M., S. M. E., Ng, Oikonomou, I., Peeters, H., Proctor, D. D., Rahier, J. -F., Rutgeerts, P., Seibold, F., Stronati, L., Taylor, K. M., Torkvist, L., Ublick, K., Van Limbergen, J., Van Gossum, A., Vatn, M. H., Zhang, H., Zhang, W., Andrews, J. M., Bampton, P. A., Barclay, M., Florin, T. H., Gearry, R., Krishnaprasad, K., Lawrance, I. C., Mahy, G., Montgomery, G. W., Radford-Smith, G., Roberts, R. L., Simms, L. A., Hanigan, K., Croft, A., Amininijad, L., Cleynen, I., Dewit, O., Franchimont, D., Georges, M., Laukens, D., Theatre, E., Vermeire, S., Aumais, G., Baidoo, L., Barrie, A. M., Beck, K., Bernard, E. -J., Binion, D. G., Bitton, A., Brant, S. R., Cho, J. H., Cohen, A., Croitoru, K., Daly, M. J., Datta, L. W., Deslandres, C., Duerr, R. H., Dutridge, D., Ferguson, J., Fultz, J., Goyette, P., Greenberg, G. R., Haritunians, T., Jobin, G., Katz, S., Lahaie, R. G., Mcgovern, D. P., Nelson, L., S. M., Ng, Ning, K., Pare, P., Regueiro, M. D., Rioux, J. D., Ruggiero, E., Schumm, L. P., Schwartz, M., Scott, R., Sharma, Y., Silverberg, M. S., Spears, D., Steinhart, A. H., Stempak, J. M., Swoger, J. M., Tsagarelis, C., Zhang, C., Zhao, H., Aerts, J., Ahmad, T., Arbury, H., Attwood, A., Auton, A., Ball, S. G., Balmforth, A. J., Barnes, C., Barrett, J. C., Barroso, I., Barton, A., Bennett, A. J., Bhaskar, S., Blaszczyk, K., Bowes, J., Brand, O. J., Braund, P. S., Bredin, F., Breen, G., Brown, M. J., Bruce, I. N., Bull, J., Burren, O. S., Burton, J., Byrnes, J., Caesar, S., Cardin, N., Clee, C. M., Coffey, A. J., MC Connell, J., Conrad, D. F., Cooper, J. D., Dominiczak, A. F., Downes, K., Drummond, H. E., Dudakia, D., Dunham, A., Ebbs, B., Eccles, D., Edkins, S., Edwards, C., Elliot, A., Emery, P., Evans, D. M., Evans, G., Eyre, S., Farmer, A., Ferrier, I. N., Flynn, E., Forbes, A., Forty, L., Franklyn, J. A., Frayling, T. M., Freathy, R. M., Giannoulatou, E., Gibbs, P., Gilbert, P., Gordon-Smith, K., Gray, E., Green, E., Groves, C. J., Grozeva, D., Gwilliam, R., Hall, A., Hammond, N., Hardy, M., Harrison, P., Hassanali, N., Hebaishi, H., Hines, S., Hinks, A., Hitman, G. A., Hocking, L., Holmes, C., Howard, E., Howard, P., Howson, J. M. M., Hughes, D., Hunt, S., Isaacs, J. D., Jain, M., Jewell, D. P., Johnson, T., Jolley, J. D., Jones, I. R., Jones, L. A., Kirov, G., Langford, C. F., Lango-Allen, H., Lathrop, G. M., Lee, J., Lee, K. L., Lees, C., Lewis, K., Lindgren, C. M., Maisuria-Armer, M., Maller, J., Mansfield, J., Marchini, J. L., Martin, P., Massey, D. C., Mcardle, W. L., Mcguffin, P., Mclay, K. E., Mcvean, G., Mentzer, A., Mimmack, M. L., Morgan, A. E., Morris, A. P., Mowat, C., Munroe, P. B., Myers, S., Newman, W., Nimmo, E. R., O'Donovan, M. C., Onipinla, A., Ovington, N. R., Owen, M. J., Palin, K., Palotie, A., Parnell, K., Pearson, R., Pernet, D., Perry, J. R., Phillips, A., Plagnol, V., Prescott, N. J., Prokopenko, I., Quail, M. A., Rafelt, S., Rayner, N. W., Reid, D. M., Renwick, A., Ring, S. M., Robertson, N., Robson, S., Russell, E., Clair, D. S., Sambrook, J. G., Sanderson, J. D., Sawcer, S. J., Schuilenburg, H., Scott, C. E., Seal, S., Shaw-Hawkins, S., Shields, B. M., Simmonds, M. J., Smyth, D. J., Somaskantharajah, E., Spanova, K., Steer, S., Stephens, J., Stevens, H. E., Stirrups, K., Stone, M. A., Strachan, D. P., Su, Z., Symmons, D. P. M., Thompson, J. R., Thomson, W., Tobin, M. D., Travers, M. E., Turnbull, C., Vukcevic, D., Wain, L. V., Walker, M., Walker, N. M., Wallace, C., Warren-Perry, M., Watkins, N. A., Webster, J., Weedon, M. N., Wilson, A. G., Woodburn, M., Wordsworth, B. P., Yau, C., Young, A. H., Zeggini, E., Brown, M. A., Burton, P. R., Caulfield, M. J., Compston, A., Farrall, M., Gough, S. C. L., Hall, A. S., Hattersley, A. T., Hill, A. V. S., Mathew, C. G., Pembrey, M., Satsangi, J., Stratton, M. R., Worthington, J., Hurles, M. E., Duncanson, A., Ouwehand, W. H., Parkes, M., Rahman, N., Todd, J. A., Samani, N. J., Kwiatkowski, D. P., Mccarthy, M. I., Craddock, N., Deloukas, P., Donnelly, P., Blackwell, J. M., Bramon, E., Casas, J. P., Corvin, A., Jankowski, J., Markus, H. S., Palmer, C. N., Plomin, R., Rautanen, A., Trembath, R. C., Viswanathan, A. C., Wood, N. W., Spencer, C. C. A., Band, G., Bellenguez, C., Freeman, C., Hellenthal, G., Pirinen, M., Strange, A., Blackburn, H., Bumpstead, S. J., Dronov, S., Gillman, M., Jayakumar, A., Mccann, O. T., Liddle, J., Potter, S. C., Ravindrarajah, R., Ricketts, M., Waller, M., Weston, P., Widaa, S., Whittaker, P., Romagnoni, A., Jegou, S., Van Steen, K., Wainrib, G., Hugot, J. -P., Peyrin-Biroulet, L., Chamaillard, M., Colombel, J. -F., Cottone, M., D'Amato, M., D'Inca, R., Halfvarson, J., Henderson, P., Karban, A., Kennedy, N. A., Khan, M. A., Lemann, M., Levine, A., Massey, D., Milla, M., Ng, S. M. E., Oikonomou, I., Peeters, H., Proctor, D. D., Rahier, J. -F., Rutgeerts, P., Seibold, F., Stronati, L., Taylor, K. M., Torkvist, L., Ublick, K., Van Limbergen, J., Van Gossum, A., Vatn, M. H., Zhang, H., Zhang, W., Andrews, J. M., Bampton, P. A., Barclay, M., Florin, T. H., Gearry, R., Krishnaprasad, K., Lawrance, I. C., Mahy, G., Montgomery, G. W., Radford-Smith, G., Roberts, R. L., Simms, L. A., Hanigan, K., Croft, A., Amininijad, L., Cleynen, I., Dewit, O., Franchimont, D., Georges, M., Laukens, D., Theatre, E., Vermeire, S., Aumais, G., Baidoo, L., Barrie, A. M., Beck, K., Bernard, E. -J., Binion, D. G., Bitton, A., Brant, S. R., Cho, J. H., Cohen, A., Croitoru, K., Daly, M. J., Datta, L. W., Deslandres, C., Duerr, R. H., Dutridge, D., Ferguson, J., Fultz, J., Goyette, P., Greenberg, G. R., Haritunians, T., Jobin, G., Katz, S., Lahaie, R. G., Mcgovern, D. P., Nelson, L., Ng, S. M., Ning, K., Pare, P., Regueiro, M. D., Rioux, J. D., Ruggiero, E., Schumm, L. P., Schwartz, M., Scott, R., Sharma, Y., Silverberg, M. S., Spears, D., Steinhart, A. H., Stempak, J. M., Swoger, J. M., Tsagarelis, C., Zhang, C., Zhao, H., Aerts, J., Ahmad, T., Arbury, H., Attwood, A., Auton, A., Ball, S. G., Balmforth, A. J., Barnes, C., Barrett, J. C., Barroso, I., Barton, A., Bennett, A. J., Bhaskar, S., Blaszczyk, K., Bowes, J., Brand, O. J., Braund, P. S., Bredin, F., Breen, G., Brown, M. J., Bruce, I. N., Bull, J., Burren, O. S., Burton, J., Byrnes, J., Caesar, S., Cardin, N., Clee, C. M., Coffey, A. J., MC Connell, J., Conrad, D. F., Cooper, J. D., Dominiczak, A. F., Downes, K., Drummond, H. E., Dudakia, D., Dunham, A., Ebbs, B., Eccles, D., Edkins, S., Edwards, C., Elliot, A., Emery, P., Evans, D. M., Evans, G., Eyre, S., Farmer, A., Ferrier, I. N., Flynn, E., Forbes, A., Forty, L., Franklyn, J. A., Frayling, T. M., Freathy, R. M., Giannoulatou, E., Gibbs, P., Gilbert, P., Gordon-Smith, K., Gray, E., Green, E., Groves, C. J., Grozeva, D., Gwilliam, R., Hall, A., Hammond, N., Hardy, M., Harrison, P., Hassanali, N., Hebaishi, H., Hines, S., Hinks, A., Hitman, G. A., Hocking, L., Holmes, C., Howard, E., Howard, P., Howson, J. M. M., Hughes, D., Hunt, S., Isaacs, J. D., Jain, M., Jewell, D. P., Johnson, T., Jolley, J. D., Jones, I. R., Jones, L. A., Kirov, G., Langford, C. F., Lango-Allen, H., Lathrop, G. M., Lee, J., Lee, K. L., Lees, C., Lewis, K., Lindgren, C. M., Maisuria-Armer, M., Maller, J., Mansfield, J., Marchini, J. L., Martin, P., Massey, D. C., Mcardle, W. L., Mcguffin, P., Mclay, K. E., Mcvean, G., Mentzer, A., Mimmack, M. L., Morgan, A. E., Morris, A. P., Mowat, C., Munroe, P. B., Myers, S., Newman, W., Nimmo, E. R., O'Donovan, M. C., Onipinla, A., Ovington, N. R., Owen, M. J., Palin, K., Palotie, A., Parnell, K., Pearson, R., Pernet, D., Perry, J. R., Phillips, A., Plagnol, V., Prescott, N. J., Prokopenko, I., Quail, M. A., Rafelt, S., Rayner, N. W., Reid, D. M., Renwick, A., Ring, S. M., Robertson, N., Robson, S., Russell, E., Clair, D. S., Sambrook, J. G., Sanderson, J. D., Sawcer, S. J., Schuilenburg, H., Scott, C. E., Seal, S., Shaw-Hawkins, S., Shields, B. M., Simmonds, M. J., Smyth, D. J., Somaskantharajah, E., Spanova, K., Steer, S., Stephens, J., Stevens, H. E., Stirrups, K., Stone, M. A., Strachan, D. P., Su, Z., Symmons, D. P. M., Thompson, J. R., Thomson, W., Tobin, M. D., Travers, M. E., Turnbull, C., Vukcevic, D., Wain, L. V., Walker, M., Walker, N. M., Wallace, C., Warren-Perry, M., Watkins, N. A., Webster, J., Weedon, M. N., Wilson, A. G., Woodburn, M., Wordsworth, B. P., Yau, C., Young, A. H., Zeggini, E., Brown, M. A., Burton, P. R., Caulfield, M. J., Compston, A., Farrall, M., Gough, S. C. L., Hall, A. S., Hattersley, A. T., Hill, A. V. S., Mathew, C. G., Pembrey, M., Satsangi, J., Stratton, M. R., Worthington, J., Hurles, M. E., Duncanson, A., Ouwehand, W. H., Parkes, M., Rahman, N., Todd, J. A., Samani, N. J., Kwiatkowski, D. P., Mccarthy, M. I., Craddock, N., Deloukas, P., Donnelly, P., Blackwell, J. M., Bramon, E., Casas, J. P., Corvin, A., Jankowski, J., Markus, H. S., Palmer, C. N., Plomin, R., Rautanen, A., Trembath, R. C., Viswanathan, A. C., Wood, N. W., Spencer, C. C. A., Band, G., Bellenguez, C., Freeman, C., Hellenthal, G., Pirinen, M., Strange, A., Blackburn, H., Bumpstead, S. J., Dronov, S., Gillman, M., Jayakumar, A., Mccann, O. T., Liddle, J., Potter, S. C., Ravindrarajah, R., Ricketts, M., Waller, M., Weston, P., Widaa, S., Whittaker, P., Daly, Mark J. [0000-0002-0949-8752], Apollo - University of Cambridge Repository, Hugot, Jean-Pierre [0000-0002-8446-6056], UCL - SSS/IREC/GAEN - Pôle d'Hépato-gastro-entérologie, UCL - (MGD) Service de gastro-entérologie, Romagnoni, A, Jegou, S, VAN STEEN, Kristel, Wainrib, G, Hugot, JP, Peyrin-Biroulet, L, Chamaillard, M, Colombel, JF, Cottone, M, D'Amato, M, D'Inca, R, Halfvarson, J, Henderson, P, Karban, A, Kennedy, NA, Khan, MA, Lemann, M, Levine, A, Massey, D, Milla, M, Ng, SME, Oikonomou, I, Peeters, H, Proctor, DD, Rahier, JF, Rutgeerts, P, Seibold, F, Stronati, L, Taylor, KM, Torkvist, L, Ublick, K, Van Limbergen, J, Van Gossum, A, Vatn, MH, Zhang, H, Zhang, W, Andrews, JM, Bampton, PA, Barclay, M, Florin, TH, Gearry, R, Krishnaprasad, K, Lawrance, IC, Mahy, G, Montgomery, GW, Radford-Smith, G, Roberts, RL, Simms, LA, Hanigan, K, Croft, A, Amininijad, L, Cleynen, I, Dewit, O, Franchimont, D, Georges, M, Laukens, D, Theatre, E, Vermeire, S, Aumais, G, Baidoo, L, Barrie, AM, Beck, K, Bernard, EJ, Binion, DG, Bitton, A, Brant, SR, Cho, JH, Cohen, A, Croitoru, K, Daly, MJ, Datta, LW, Deslandres, C, Duerr, RH, Dutridge, D, Ferguson, J, Fultz, J, Goyette, P, Greenberg, GR, Haritunians, T, Jobin, G, Katz, S, Lahaie, RG, McGovern, DP, Nelson, L, Ng, SM, Ning, K, Pare, P, Regueiro, MD, Rioux, JD, Ruggiero, E, Schumm, LP, Schwartz, M, Scott, R, Sharma, Y, Silverberg, MS, Spears, D, Steinhart, AH, Stempak, JM, Swoger, JM, Tsagarelis, C, Zhang, C, Zhao, HY, AERTS, Jan, Ahmad, T, Arbury, H, Attwood, A, Auton, A, Ball, SG, Balmforth, AJ, Barnes, C, Barrett, JC, Barroso, I, Barton, A, Bennett, AJ, Bhaskar, S, Blaszczyk, K, Bowes, J, Brand, OJ, Braund, PS, Bredin, F, Breen, G, Brown, MJ, Bruce, IN, Bull, J, Burren, OS, Burton, J, Byrnes, J, Caesar, S, Cardin, N, Clee, CM, Coffey, AJ, Mc Connell, J, Conrad, DF, Cooper, JD, Dominiczak, AF, Downes, K, Drummond, HE, Dudakia, D, Dunham, A, Ebbs, B, Eccles, D, Edkins, S, Edwards, C, Elliot, A, Emery, P, Evans, DM, Evans, G, Eyre, S, Farmer, A, Ferrier, IN, Flynn, E, Forbes, A, Forty, L, Franklyn, JA, Frayling, TM, Freathy, RM, Giannoulatou, E, Gibbs, P, Gilbert, P, Gordon-Smith, K, Gray, E, Green, E, Groves, CJ, Grozeva, D, Gwilliam, R, Hall, A, Hammond, N, Hardy, M, Harrison, P, Hassanali, N, Hebaishi, H, Hines, S, Hinks, A, Hitman, GA, Hocking, L, Holmes, C, Howard, E, Howard, P, Howson, JMM, Hughes, D, Hunt, S, Isaacs, JD, Jain, M, Jewell, DP, Johnson, T, Jolley, JD, Jones, IR, Jones, LA, Kirov, G, Langford, CF, Lango-Allen, H, Lathrop, GM, Lee, J, Lee, KL, Lees, C, Lewis, K, Lindgren, CM, Maisuria-Armer, M, Maller, J, Mansfield, J, Marchini, JL, Martin, P, Massey, DCO, McArdle, WL, McGuffin, P, McLay, KE, McVean, G, Mentzer, A, Mimmack, ML, Morgan, AE, Morris, AP, Mowat, C, Munroe, PB, Myers, S, Newman, W, Nimmo, ER, O'Donovan, MC, Onipinla, A, Ovington, NR, Owen, MJ, Palin, K, Palotie, A, Parnell, K, Pearson, R, Pernet, D, Perry, JRB, Phillips, A, Plagnol, V, Prescott, NJ, Prokopenko, I, Quail, MA, Rafelt, S, Rayner, NW, Reid, DM, Renwick, A, Ring, SM, Robertson, N, Robson, S, Russell, E, St Clair, D, Sambrook, JG, Sanderson, JD, Sawcer, SJ, Schuilenburg, H, Scott, CE, Seal, S, Shaw-Hawkins, S, Shields, BM, Simmonds, MJ, Smyth, DJ, Somaskantharajah, E, Spanova, K, Steer, S, Stephens, J, Stevens, HE, Stirrups, K, Stone, MA, Strachan, DP, Su, Z, Symmons, DPM, Thompson, JR, Thomson, W, Tobin, MD, Travers, ME, Turnbull, C, Vukcevic, D, Wain, LV, Walker, M, Walker, NM, Wallace, C, Warren-Perry, M, Watkins, NA, Webster, J, Weedon, MN, Wilson, AG, Woodburn, M, Wordsworth, BP, Yau, C, Young, AH, Zeggini, E, Brown, MA, Burton, PR, Caulfield, MJ, Compston, A, Farrall, M, Gough, SCL, Hall, AS, Hattersley, AT, Hill, AVS, Mathew, CG, Pembrey, M, Satsangi, J, Stratton, MR, Worthington, J, Hurles, ME, Duncanson, A, Ouwehand, WH, Parkes, M, Rahman, N, Todd, JA, Samani, NJ, Kwiatkowski, DP, McCarthy, MI, Craddock, N, Deloukas, P, Donnelly, P, Blackwell, JM, Bramon, E, Casas, JP, Corvin, A, Jankowski, J, Markus, HS, Palmer, CNA, Plomin, R, Rautanen, A, Trembath, RC, Viswanathan, AC, Wood, NW, Spencer, CCA, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Pirinen, M, Strange, A, Blackburn, H, Bumpstead, SJ, Dronov, S, Gillman, M, Jayakumar, A, McCann, OT, Liddle, J, Potter, SC, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, and Kwiatkowski, D
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Male ,692/4020/1503/257/1402 ,Genotype ,Genotyping Techniques ,LOCI ,45/43 ,lcsh:Medicine ,Polymorphism, Single Nucleotide ,Crohn's disease, genetics, genome wide association ,Article ,Deep Learning ,Crohn Disease ,INDEL Mutation ,Genetics research ,Humans ,genetics ,Genetic Predisposition to Disease ,129 ,lcsh:Science ,Alleles ,Science & Technology ,genome wide association ,RISK PREDICTION ,45 ,Models, Genetic ,lcsh:R ,Decision Trees ,692/308/2056 ,ASSOCIATION ,Multidisciplinary Sciences ,Crohn's disease ,Logistic Models ,Nonlinear Dynamics ,ROC Curve ,Area Under Curve ,Science & Technology - Other Topics ,lcsh:Q ,Female ,Neural Networks, Computer ,INFLAMMATORY-BOWEL-DISEASE ,Genome-Wide Association Study - Abstract
Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers. Tis work was supported by Fondation pour la Recherche Médical (ref DEI20151234405) and Investissements d’Avenir programme ANR-11-IDEX-0005-02, Sorbonne Paris Cite, Laboratoire d’excellence INFLAMEX. Te authors thank the students that participated to the wisdom of the crowd exercise.
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- 2019
28. Genome-wide association study identifies eight loci associated with blood pressure
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Peter Holmans, Udo Seedorf, Beverley M. Shields, Peter McGruffin, Arne Pfeufer, Steve Eyre, Nathalie J. Prescott, Michael Boehnke, Valentina Moskovina, Abiodun Onipinla, Leena Peltonen, Nadira Yuldasheva, Peter M. Nilsson, Valeria Romanazzi, Vincent Mooser, Göran Berglund, Alistair S. Hall, Dominic P. Kwiatkowski, Barry Widmer, Benjamin F. Voight, Stefania Bandinelli, Mark M. Iles, Sven Bergmann, Thomas Meitinger, James P. Boorman, Simonetta Guarrera, Nazneen Rahman, Murielle Bochud, Graham A. Hitman, Emma Keniry, Nelson B. Freimer, Richard Dobson, Francis S. Collins, Gerjan Navis, Jennifer L. Pointon, Richard N. Bergman, Ruth J. F. Loos, Roberto Lorbeer, Carolina A. Braga Marcano, Christian Gieger, Florian Ernst, Xin Yuan, Catherine Potter, Hazel E. Drummond, Allan H. Young, George Kirov, John F. Peden, Helen Stevens, David Clayton, Mattijs E. Numans, Katherine Gordon-Smith, Anne Farmer, Alastair Forbes, M. Khalid Mohiuddin, John A. Todd, Christopher G. Mathew, David A. Collier, Mark I. McCarthy, Francesca Bredin, Clive M. Onnie, Dan Davidson, Markus Perola, Pamela Whittaker, Yvonne T. van der Schouw, Rathi Ravindrarajan, I. C.A. Spencer, Teresa Ferreira, Nilesh J. Samani, Serge Hercberg, Gonçalo R. Abecasis, Christopher J. Groves, Nicholas John Craddock, Angela Döring, Edward G. Lakatta, Muminatou Jallow, Wendy L. McArdle, David Bentley, Susana Eyheramendy, Uwe Völker, Christopher Newton-Cheh, Jaspal S. Kooner, Hugh Watkins, Gavin Lucas, H. T. Leung, Marjo Ritta Jarvelin, Johanna Kuusisto, Wiek H. van Gilst, Wendy Thomson, Lou R. Cardon, Harold Snieder, Marju Orho-Melander, Patricia B. Munroe, Toshiko Tanaka, Jeffrey C. Barrett, Azhar Maqbool, Henry Völzke, John M. C. Connell, Elaine R. Nimmo, John R. B. Perry, Michael R. Stratton, Ralph McGinnis, Pekka Jousilahti, Michiel L. Bots, Ian Jones, Elizabeth Meech, Matthew A. Brown, Johannie Gungadoo, Jian'an Luan, Jilur Ghori, Richard J. Dixon, N. Charlotte Onland-Moret, Fulvio Ricceri, Anthony J. Balmforth, Catherine E. Todhunter, Inês Barroso, Sheila Bingham, Timo T. Valle, Fredrik O. Vannberg, Diana Zelenika, Stephen Sawcer, Anneli Pouta, David M. Evans, Cuno S. P. M. Uiterwaal, Pilar Galan, Georg Homuth, Hannah Donovan, David J. Conway, Paul Elliott, Alessandra Allione, Paul E. de Jong, Miles Parkes, Amy Chaney, John C. Chambers, Toby Johnson, Isaac Subirana, Vesela Gateva, Cathryn M. Lewis, Christopher J. O'Donnell, Hana Lango, David Schlessinger, Mark J. Caulfield, Thorsten Reffelmann, Jamie Barbour, Karen L. Mohlke, Sarah E. Hunt, Thilo Winzer, Frances M K Williams, Christopher Mathew, I. Wallace, Anuj Goel, Jaakko Tuomilehto, Louise V. Wain, Gabriel Crawford, Samantha L. Hider, Detelinea Grozeva, Elaine K. Green, Paul D. Gilbert, Peter S. Braund, Jaume Marrugat, Rainer Rettig, Pim van der Harst, Yik Ying Teo, Andrew P. Morris, Guiseppe Matullo, Serena Sanna, Cristen J. Willer, Suzannah Bumpstead, Niall C. Taylor, Jacques S. Beckmann, Pierre Meneton, Elin Org, Luigi Ferrucci, Doug Easton, Sheila Seal, Joanne M. Heward, Anne U. Jackson, Eleftheria Zeggini, Rachel M. Freathy, Maris Laan, Paul Wordsworth, Sarah Nutland, Kerstin Koch, Sian Ceasar, Anders Hamsten, Judith M. Hussey, Tariq Ahmad, Derek P. Jewell, Paul Scheet, Charlie W. Lees, C Farrar, Christopher Prowse, Markku Laakso, David St Clair, Kate Downes, Diederick E. Grobbee, Paul Burton, Simon C. Potter, Ian N. Bruce, Tim D. Spector, Anne Barton, H.-Erich Wichmann, Matthew J. Simmonds, David Hadley, Cecilia M. Lindgren, Gérard Waeber, Nigel W. Rayner, Melanie J. Newport, Manjinder S. Sandhu, Audrey Duncanson, Guangju Zhai, Simon Heath, Susan M. Ring, Alessandra Di Gregorio, Richard Williamson, Nicholas J. Wareham, Zhan Su, Olle Melander, John R. Thompson, Alexander Teumer, Sheila A. Fisher, Lachlan J. M. Coin, Leif Groop, Giovanni Tognoni, Amanda Elkin, Alan J. Silman, Jack Satsangi, Jane Worthington, Martin Farrall, John Webster, Niall Cardin, Neil Walker, Anna F. Dominiczak, Jeremy D. Sanderson, Damjan Vukcevic, Bryan Howie, Silvia Polidoro, Stephen G. Ball, Mark Tremelling, Stephen Newhouse, Stephen M. Schwartz, Lori L. Bonnycastle, Chris Wallace, Kijoung Song, Mario A. Morken, I. Nicol Ferrier, Beverley Barke, Paolo Vineis, Manuela Uda, Deborah P M Symmons, Emily J. Lyons, Mingzhan Xue, Timothy M. Frayling, Stephen C.L. Cough, David Withers, Adrian V. S. Hill, Suzanne Stevens, Jennifer Jolley, Marcus Dörr, Kirk A. Rockett, David B. Dunger, Mark Walker, Jayne A. Franklyn, Lisa Jones, David S. Siscovick, Ann-Christine Syvänen, Laura J. Scott, Morris J. Brown, Barbera Cant, Michael Inouye, Feng Zhang, Carlotta Sacerdote, Katherine S. Elliott, Jonathan Marchini, Peter Donnely, Michael John Owen, An Goris, Marcus Prembey, Andrew T. Hattersley, Gerome Breen, Marian L. Hamshere, Thomas Illig, Samer S. Najjar, Nicole Soranzo, Kay-Tee Khaw, Graham R. Walters, Willem H. Ouwehand, David P. Strachan, Martin D. Tobin, Alastair Compston, John C. Mansfield, David Altshuler, Salvatore Panico, Sekar Kathiresan, Dawn M. Waterworth, Michael N. Weedon, D. Timothy Bishop, Claire Bryan, Alexandra S. Knight, Kate L. Lee, Paul F. O'Reilly, Massimo Mangino, Michael Conlon O'Donovan, Jing Hua Zhao, Konstantinos A. Papadakis, Jennifer H. Barrett, Joanne Pereira-Gale, N J Timpson, Stephan B. Felix, Panos Deloukas, Nicholas A. Watkins, Anna-Liisa Hartikainen, Peter Vollenweider, Richard Jones, Anne Hinks, Fraser Cummings, Noha Lim, Linda A. Bradbury, Rhian G. William, Nita G. Forouhi, Roberto Eluosa, Ingeleif B. Hallgrimsdottir, Giorgio Sirugo, Robert Luben, Veikko Salomaa, Robert Clarke, Sally John, Ursula Everson, Emma King, Ivan Nikolov, Heather M. Stringham, Antony P. Attwood, Angelo Scuteri, Wellcome Trust Case Control Consortium, Burton, PR., Clayton, DG., Cardon, LR., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, DP., McCarthy, MI., Ouwehand, WH., Samani, NJ., Todd, JA., Donnelly, P., Barrett, JC., Davison, D., Easton, D., Evans, D., Leung, HT., Marchini, JL., Morris, AP., Spencer, IC., 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., Ball, SG., Balmforth, AJ., Barrett, JH., Bishop, DT., Iles, MM., Maqbool, A., Yuldasheva, N., Hall, AS., Braund, PS., Dixon, RJ., Mangino, M., Stevens, S., Thompson, JR., 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, GM., Connell, J., Dominiczak, A., Braga Marcano, CA., Burke, B., Dobson, R., Gungadoo, J., Lee, KL., Munroe, PB., Newhouse, SJ., Onipinla, A., Wallace, I., 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., Bryan, C., Bumpstead, SJ., Chaney, A., Downes, K., Ghori, J., Gwilliam, R., Hunt, SE., Inouye, M., Keniry, A., King, E., McGinnis, R., Potter, S., Ravindrarajah, R., Whittaker, P., Withers, D., Cardin, NJ., Ferreira, T., Pereira-Gale, J., Hallgrimsdóttir, IB., Howie, BN., Su, Z., Teo, YY., Vukcevic, D., Bentley, D., Life Course Epidemiology (LCE), Cardiovascular Centre (CVC), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Vascular Ageing Programme (VAP), and Medical Research Council (MRC)
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Hemodynamics ,Genome-wide association study ,Blood Pressure ,030204 cardiovascular system & hematology ,0302 clinical medicine ,Diastole ,11 Medical and Health Sciences ,POPULATION ,Genetics ,Genetics & Heredity ,RISK ,0303 health sciences ,education.field_of_study ,Econometric and Statistical Methods: General ,CELL-DIFFERENTIATION ,biology ,Intracellular Signaling Peptides and Proteins ,Chromosome Mapping ,Steroid 17-alpha-Hydroxylase ,COMMON VARIANTS ,3. Good health ,DNA-Binding Proteins ,Europe ,Cardiovascular Diseases ,PUBLIC-HEALTH ,BARTTERS-SYNDROME ,Blood Pressure/genetics ,Cardiovascular Diseases/genetics ,Cardiovascular Diseases/physiopathology ,Cytochrome P-450 CYP1A2/genetics ,DNA-Binding Proteins/genetics ,Diastole/genetics ,European Continental Ancestry Group/genetics ,Fibroblast Growth Factor 5/genetics ,Genetic Variation ,Genome-Wide Association Study ,Humans ,India ,Methylenetetrahydrofolate Reductase (NADPH2)/genetics ,Open Reading Frames/genetics ,Phospholipase C delta/genetics ,Polymorphism, Single Nucleotide ,Proteins/genetics ,Steroid 17-alpha-Hydroxylase/genetics ,Systole/genetics ,Wellcome Trust Case Control Consortium ,Life Sciences & Biomedicine ,hypertension ,Fibroblast Growth Factor 5 ,Systole ,Population ,European Continental Ancestry Group ,METHYLENETETRAHYDROFOLATE REDUCTASE GENE ,Single-nucleotide polymorphism ,LOW-RENIN HYPERTENSION ,White People ,Article ,03 medical and health sciences ,Open Reading Frames ,Fibroblast growth factor-5 ,Cytochrome P-450 CYP1A2 ,Geneeskunde(GENK) ,education ,Methylenetetrahydrofolate Reductase (NADPH2) ,Adaptor Proteins, Signal Transducing ,030304 developmental biology ,Genetic association ,genome-wide association ,Science & Technology ,MUTATIONS ,Proteins ,06 Biological Sciences ,POLYMORPHISM ,Blood pressure ,Methylenetetrahydrofolate reductase ,biology.protein ,biology.gene ,Phospholipase C delta ,Developmental Biology - Abstract
Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5 million genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N ≤ 71,225 European ancestry, N ≤ 12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N = 29,136). We identified association between systolic or diastolic blood pressure and common variants in eight regions near the CYP17A1 (P = 7 × 10(-24)), CYP1A2 (P = 1 × 10(-23)), FGF5 (P = 1 × 10(-21)), SH2B3 (P = 3 × 10(-18)), MTHFR (P = 2 × 10(-13)), c10orf107 (P = 1 × 10(-9)), ZNF652 (P = 5 × 10(-9)) and PLCD3 (P = 1 × 10(-8)) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.
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- 2009
29. Identification of novel genetic Loci associated with thyroid peroxidase antibodies and clinical thyroid disease
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Michela Traglia, Tom Forsén, Stefano Mariotti, Giorgio Pistis, Katharina Schramm, Jayne A. Franklyn, Suzanne J. Brown, Jürgen Kratzsch, Christian Gieger, W. Edward Visser, Matteo Vocale, Fred C.G.J. Sweep, Daniel Tiller, Anne R. Cappola, Massimiliano Cocca, Johannes W. A. Smit, Johan G. Eriksson, Peter O'Leary, Diana Pietzner, Lise Lotte N. Husemoen, Silvia Naitza, Peter J. Leedman, Alexander Hamilton, Hans J. Grabe, Ee Mun Lim, Jennie Hui, Beverley M. Shields, Allan Linneberg, Richard A. Jensen, Tim De Meyer, Stephen C. L. Gough, Layal Chaker, Henriette E. Meyer zu Schwabedissen, Matthew J. Simmonds, Alice M. Arnold, Marco Medici, Alexandra Bremner, Monia Lobina, Linda Broer, Theo S. Plantinga, Huiling He, Ad R. M. M. Hermus, Eero Kajantie, Daniela Toniolo, Rebecca Nagy, Sita H. Vermeulen, Eva Reischl, Romana T. Netea-Maier, John Beilby, Tessel E. Galesloot, Tim I M Korevaar, Fernando Rivadeneira, Henri Wallaschofski, Peter Feddema, Margit Heier, Uwe Völker, David Schlessinger, J. Brent Richards, Christa Meisinger, Gonçalo R. Abecasis, Rachel M. Freathy, Alessandro P Delitala, Theo J. Visser, Georg Homuth, Corrado Masciullo, Aarno Palotie, Timothy M. Frayling, Elisabeth Widen, Matthias Nauck, Till Ittermann, Betina H. Thuesen, Christin Spielhagen, Jari Lahti, W. G. Li, Nicola Pirastu, Tanguy Corre, Alan James, Lambertus A. Kiemeney, Cinzia Sala, Sandya Liyanarachchi, Bijay Vaidya, Jerome I. Rotter, Jean-Marc Kaufman, Rajesh Rawal, Albert Hofman, Alexander Teumer, Ernst E. Rietzschel, Robin P. Peeters, Henry Völzke, Serena Sanna, John P. Walsh, Greet Roef, Holger Prokisch, Albert de la Chapelle, Stephen J. Fletcher, Alexander Kluttig, Tim D. Spector, André G. Uitterlinden, Martin den Heijer, Alec H. Ross, Eric Wichmann, Katri Räikkönen, Yurii S. Aulchenko, Antonella Mulas, Martijn van de Bunt, David I. W. Philips, Gabriela L. Surdulescu, Andrew T. Hattersley, Dörte Radke, Scott Wilson, Maria Grazia Plia, Y. Taes, Torben Jørgensen, Nicole Soranzo, Bruce M. Psaty, Sandra Lai, Eleonora Porcu, Emanuele Bosi, Medici, M, Porcu, E, Pistis, G, Teumer, A, Brown, Sj, Jensen, Ra, Rawal, R, Roef, Gl, Plantinga, T, Vermeulen, Sh, Lahti, J, Simmonds, Mj, Husemoen, Ll, Freathy, Rm, Shields, Bm, Pietzner, D, Nagy, R, Broer, L, Chaker, L, Korevaar, Ti, Plia, Mg, Sala, C, Völker, U, Richards, Jb, Sweep, Fc, Gieger, C, Corre, T, Kajantie, E, Thuesen, B, Taes, Ye, Visser, We, Hattersley, At, Kratzsch, J, Hamilton, A, Li, W, Homuth, G, Lobina, M, Mariotti, S, Soranzo, N, Cocca, Massimiliano, Nauck, M, Spielhagen, C, Ross, A, Arnold, A, van de Bunt, M, Liyanarachchi, S, Heier, M, Grabe, Hj, Masciullo, C, Galesloot, Te, Lim, Em, Reischl, E, Leedman, Pj, Lai, S, Delitala, A, Bremner, Ap, Philips, Di, Beilby, Jp, Mulas, A, Vocale, M, Abecasis, G, Forsen, T, James, A, Widen, E, Hui, J, Prokisch, H, Rietzschel, Ee, Palotie, A, Feddema, P, Fletcher, Sj, Schramm, K, Rotter, Ji, Kluttig, A, Radke, D, Traglia, Michela, Surdulescu, Gl, He, H, Franklyn, Ja, Tiller, D, Vaidya, B, de Meyer, T, Jørgensen, T, Eriksson, Jg, O'Leary, Pc, Wichmann, E, Hermus, Ar, Psaty, Bm, Ittermann, T, Hofman, A, Bosi, E, Schlessinger, D, Wallaschofski, H, Pirastu, Nicola, Aulchenko, Y, de la Chapelle, A, Netea Maier, Rt, Gough, Sc, Meyer Zu Schwabedissen, H, Frayling, Tm, Kaufman, Jm, Linneberg, A, Räikkönen, K, Smit, Jw, Kiemeney, La, Rivadeneira, F, Uitterlinden, Ag, Walsh, Jp, Meisinger, C, den Heijer, M, Visser, Tj, Spector, Td, Wilson, Sg, Völzke, H, Cappola, A, Toniolo, D, Sanna, S, Naitza, S, Peeters, R. p. 1., Cocca, M, Traglia, M, Bosi, Emanuele, Pirastu, N, Peeters, Rp, Internal medicine, EMGO - Lifestyle, overweight and diabetes, Internal Medicine, Epidemiology, Cardiology, Clinical Genetics, Behavioural Sciences, Children's Hospital, Lastentautien yksikkö, Clinicum, Institute for Molecular Medicine Finland, Department of General Practice and Primary Health Care, Developmental Psychology Research Group, Genomics of Neurological and Neuropsychiatric Disorders, and Genomic Discoveries and Clinical Translation
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Cancer Research ,Goiter ,endocrine system diseases ,Graves' disease ,Vascular damage Radboud Institute for Health Sciences [Radboudumc 16] ,lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4] ,Thyrotropin ,Gastroenterology ,thyroid ,GRAVES-DISEASE ,Endocrinology ,0302 clinical medicine ,Risk Factors ,Medicine and Health Sciences ,Hashimoto Disease ,SYSTEMIC-LUPUS-ERYTHEMATOSUS ,Thyroid cancer ,Genetics (clinical) ,0303 health sciences ,Thyroid disease ,Thyroid ,IODIDE ORGANIFICATION DEFECTS ,COMMON VARIANTS ,Graves Disease ,3. Good health ,Women's cancers Radboud Institute for Health Sciences [Radboudumc 17] ,medicine.anatomical_structure ,Urological cancers Radboud Institute for Health Sciences [Radboudumc 15] ,Medicine ,HEART-FAILURE ,Research Article ,medicine.medical_specialty ,endocrine system ,lcsh:QH426-470 ,SUSCEPTIBILITY LOCI ,515 Psychology ,education ,030209 endocrinology & metabolism ,Biology ,Rare cancers Radboud Institute for Molecular Life Sciences [Radboudumc 9] ,Iodide Peroxidase ,Healthcare improvement science Radboud Institute for Health Sciences [Radboudumc 18] ,03 medical and health sciences ,Hypothyroidism ,SDG 3 - Good Health and Well-being ,Thyroid peroxidase ,Internal medicine ,Genetics ,medicine ,Humans ,ddc:610 ,Risk factor ,GENOME-WIDE ASSOCIATION ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Autoantibodies ,030304 developmental biology ,WHICKHAM SURVEY ,Thyroiditis, Autoimmune ,medicine.disease ,C420 Human Genetics ,RHEUMATOID-ARTHRITIS ,meta-analysis ,lcsh:Genetics ,meta-analysis, thyroid ,Genetic Loci ,Graves' Disease ,FEMALE RELATIVES ,Immunology ,biology.protein ,Inflammatory diseases Radboud Institute for Health Sciences [Radboudumc 5] ,3111 Biomedicine ,Genome-Wide Association Study - Abstract
Autoimmune thyroid diseases (AITD) are common, affecting 2-5% of the general population. Individuals with positive thyroid peroxidase antibodies (TPOAbs) have an increased risk of autoimmune hypothyroidism (Hashimoto's thyroiditis), as well as autoimmune hyperthyroidism (Graves' disease). As the possible causative genes of TPOAbs and AITD remain largely unknown, we performed GWAS meta-analyses in 18,297 individuals for TPOAb-positivity (1769 TPOAb-positives and 16,528 TPOAb-negatives) and in 12,353 individuals for TPOAb serum levels, with replication in 8,990 individuals. Significant associations (P, Author Summary Individuals with thyroid peroxidase antibodies (TPOAbs) have an increased risk of autoimmune thyroid diseases (AITD), which are common in the general population and associated with increased cardiovascular, metabolic and psychiatric morbidity and mortality. As the causative genes of TPOAbs and AITD remain largely unknown, we performed a genome-wide scan for TPOAbs in 18,297 individuals, with replication in 8,990 individuals. Significant associations were detected with variants at TPO, ATXN2, BACH2, MAGI3, and KALRN. Individuals carrying multiple risk variants also had a higher risk of increased thyroid-stimulating hormone levels (including subclinical and overt hypothyroidism), and a decreased risk of goiter. The MAGI3 and BACH2 variants were associated with an increased risk of hyperthyroidism, and the MAGI3 variant was also associated with an increased risk of hypothyroidism. This first genome-wide scan for TPOAbs identified five newly associated loci, three of which were also associated with clinical thyroid disease. With these markers we identified a large subgroup in the general population with a substantially increased risk of TPOAbs. These results provide insight into why individuals with thyroid autoimmunity do or do not eventually develop thyroid disease, and these markers may therefore predict which individuals are particularly at risk of developing clinical thyroid dysfunction.
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- 2014
30. A Meta-Analysis of Thyroid-Related Traits Reveals Novel Loci and Gender-Specific Differences in the Regulation of Thyroid Function
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McCarthy, M.I., Porcu, E., Medici, M., Pistis, G., Volpato, C.B., Wilson, S.G., Cappola, A.R., Bos, S.D., Deelen, J., den Heijer, M., Freathy, R.M., Lahti, J., Liu, C., Lopez, L.M., Nolte, I.M., O'Connell, J.R., Tanaka, T., Trompet, S., Arnold, A., Bandinelli, S., Beekman, M., Böhringer, S., Brown, S.J., Buckley, B.M., Camaschella, C., de Craen, A.J.M., Davies, G., de Visser, M.C.H., Ford, I., Forsen, T., Frayling, T.M., Fugazzola, L., Gögele, M., Hattersley, A.T., Hermus, A.R., Hofman, A., Houwing-Duistermaat, J.J., Jensen, R.A., Kajantie, E., Kloppenburg, M., Lim, E.M., Masciullo, C., Mariotti, S., Minelli, C., Mitchell, B.D., Nagaraja, R., Netea-Maier, R.T., Palotie, A., Persani, L., Piras, M.G., Psaty, B.M., Räikkönen, K., Richards, J.B., Rivadeneira, F., Sala, C., Sabra, M.M., Sattar, N., Shields, B.M., Soranzo, N., Starr, J.M., Stott, D.J., Sweep, F.C.G.J., Usala, G., van der Klauw, M.M., van Heemst, D., van Mullem, A., H.Vermeulen, S., Visser, W.E., Walsh, J.P., Westendorp, R.G.J., Widen, E., Zhai, G., Cucca, F., Deary, I.J., Eriksson, J.G., Ferrucci, L., Fox, C.S., Jukema, J.W., Kiemeney, L.A., Pramstaller, P.P., Schlessinger, D., Shuldiner, A.R., Slagboom, E.P., Uitterlinden, A.G., Vaidya, B., Visser, T.J., Wolffenbuttel, B.H.R., Meulenbelt, I., Rotter, J.I., Spector, T.D., Hicks, A.A., Toniolo, D., Sanna, S., Peeters, R.P., Naitza, S., Internal Medicine, Clinical Genetics, Public Health, Epidemiology, Internal medicine, ICaR - Circulation and metabolism, Behavioural Sciences, Clinicum, Department of General Practice and Primary Health Care, Children's Hospital, Lastentautien yksikkö, Institute for Molecular Medicine Finland, Haartman Institute (-2014), Department of Medical and Clinical Genetics, Diabetes and Obesity Research Program, Developmental Psychology Research Group, Genomics of Neurological and Neuropsychiatric Disorders, Genomic Discoveries and Clinical Translation, Life Course Epidemiology (LCE), Lifestyle Medicine (LM), Center for Liver, Digestive and Metabolic Diseases (CLDM), Porcu, E, Medici, M, Pistis, G, Volpato, Cb, Wilson, Sg, Cappola, Ar, Bos, Sd, Deelen, J, DEN HEIJER, M, Freathy, Rm, Lahti, J, Liu, C, Lopez, Lm, Nolte, Im, O'Connell, Jr, Tanaka, T, Trompet, S, Arnold, A, Bandinelli, S, Beekman, M, Böhringer, S, Brown, Sj, Buckley, Bm, Camaschella, Clara, DE CRAEN, Aj, Davies, G, DE VISSER, Mc, Ford, I, Forsen, T, Frayling, Tm, Fugazzola, L, Gögele, M, Hattersley, At, Hermus, Ar, Hofman, A, HOUWING DUISTERMAAT, Jj, Jensen, Ra, Kajantie, E, Kloppenburg, M, Lim, Em, Masciullo, C, Mariotti, S, Minelli, C, Mitchell, Bd, Nagaraja, R, NETEA MAIER, Rt, Palotie, A, Persani, L, Piras, Mg, Psaty, Bm, Räikkönen, K, Richards, Jb, Rivadeneira, F, Sala, C, Sabra, Mm, Sattar, N, Shields, Bm, Soranzo, N, Starr, Jm, Stott, Dj, Sweep, Fc, Usala, G, VAN DER KLAUW, Mm, VAN HEEMST, D, VAN MULLEM, A, Vermeulen, Sh, Visser, We, Walsh, Jp, Westendorp, Rg, Widen, E, Zhai, G, Cucca, F, Deary, Ij, Eriksson, Jg, Ferrucci, L, Fox, C, Jukema, Jw, Kiemeney, La, Pramstaller, Pp, Schlessinger, D, Shuldiner, Ar, Slagboom, Ep, Uitterlinden, Ag, Vaidya, B, Visser, Tj, Wolffenbuttel, Bh, Meulenbelt, I, Rotter, Ji, Spector, Td, Hicks, Aa, Toniolo, D, Sanna, S, Peeters, Rp, and Naitza, S.
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Male ,Cancer Research ,endocrine system diseases ,Factor binding protein 5 ,Thyroid Gland ,FACTOR BINDING PROTEIN-5 ,Thyrotropin ,Genome-wide association study ,Expression ,Aetiology, screening and detection [ONCOL 5] ,Growth ,Hyperthyroidism ,CLEFT-PALATE ,Serum TSH ,0302 clinical medicine ,Euthyroid ,Genetics (clinical) ,0303 health sciences ,Sex Characteristics ,factor binding protein-S ,Thyroid ,3. Good health ,medicine.anatomical_structure ,Phenotype ,NFIA ,Cleft palate ,GROWTH ,Genome wide Association ,Female ,Thyroid function ,hormones, hormone substitutes, and hormone antagonists ,Research Article ,Signal Transduction ,EXPRESSION ,medicine.medical_specialty ,endocrine system ,lcsh:QH426-470 ,cleft-palate ,515 Psychology ,education ,030209 endocrinology & metabolism ,Biology ,Polymorphism, Single Nucleotide ,Molecular epidemiology [NCEBP 1] ,03 medical and health sciences ,Thyroid-stimulating hormone ,Hypothyroidism ,SERUM TSH ,Internal medicine ,medicine ,Genetics ,Humans ,Hormonal regulation Translational research [IGMD 6] ,GENOME-WIDE ASSOCIATION ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Health aging / healthy living Cardiovascular diseases [IGMD 5] ,030304 developmental biology ,Molecular epidemiology Aetiology, screening and detection [NCEBP 1] ,Polymorphism, Genetic ,THYROTROPIN ,HORMONE PATHWAY GENES ,Hormonal regulation [IGMD 6] ,R1 ,Thyroxine ,Common variation ,lcsh:Genetics ,Endocrinology ,HYPOTHYROIDISM ,Hormone pathway genes ,genome-wide association ,Hormonal regulation Aetiology, screening and detection [IGMD 6] ,3111 Biomedicine ,COMMON VARIATION ,Hormone ,FOXE1 ,Genome-Wide Association Study ,Developmental Biology - Abstract
Thyroid hormone is essential for normal metabolism and development, and overt abnormalities in thyroid function lead to common endocrine disorders affecting approximately 10% of individuals over their life span. In addition, even mild alterations in thyroid function are associated with weight changes, atrial fibrillation, osteoporosis, and psychiatric disorders. To identify novel variants underlying thyroid function, we performed a large meta-analysis of genome-wide association studies for serum levels of the highly heritable thyroid function markers TSH and FT4, in up to 26,420 and 17,520 euthyroid subjects, respectively. Here we report 26 independent associations, including several novel loci for TSH (PDE10A, VEGFA, IGFBP5, NFIA, SOX9, PRDM11, FGF7, INSR, ABO, MIR1179, NRG1, MBIP, ITPK1, SASH1, GLIS3) and FT4 (LHX3, FOXE1, AADAT, NETO1/FBXO15, LPCAT2/CAPNS2). Notably, only limited overlap was detected between TSH and FT4 associated signals, in spite of the feedback regulation of their circulating levels by the hypothalamic-pituitary-thyroid axis. Five of the reported loci (PDE8B, PDE10A, MAF/LOC440389, NETO1/FBXO15, and LPCAT2/CAPNS2) show strong gender-specific differences, which offer clues for the known sexual dimorphism in thyroid function and related pathologies. Importantly, the TSH-associated loci contribute not only to variation within the normal range, but also to TSH values outside the reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings explain, respectively, 5.64% and 2.30% of total TSH and FT4 trait variance, and they improve the current knowledge of the regulation of hypothalamic-pituitary-thyroid axis function and the consequences of genetic variation for hypo- or hyperthyroidism., Author Summary Levels of thyroid hormones are tightly regulated by TSH produced in the pituitary, and even mild alterations in their concentrations are strong indicators of thyroid pathologies, which are very common worldwide. To identify common genetic variants associated with the highly heritable markers of thyroid function, TSH and FT4, we conducted a meta-analysis of genome-wide association studies in 26,420 and 17,520 individuals, respectively, of European ancestry with normal thyroid function. Our analysis identified 26 independent genetic variants regulating these traits, several of which are new, and confirmed previously detected polymorphisms affecting TSH (within the PDE8B gene and near CAPZB, MAF/LOC440389, and NR3C2) and FT4 (within DIO1) levels. Gender-specific differences in the genetic effects of several variants for TSH and FT4 levels were identified at several loci, which offer clues to understand the known sexual dimorphism in thyroid function and pathology. Of particular clinical interest, we show that TSH-associated loci contribute not only to normal variation, but also to TSH values outside reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings add to the developing landscape of the regulation of thyroid homeostasis and the consequences of genetic variation for thyroid related diseases.
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- 2013
31. A Genome-Wide Association Search for Type 2 Diabetes Genes in African Americans
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Palmer, Nicholette D, McDonough, Caitrin W, Hicks, Pamela J, Roh, Bong H, Wing, Maria R, An, S Sandy, Hester, Jessica M, Cooke, Jessica N, Bostrom, Meredith A, Rudock, Megan E, Talbert, Matthew E, Lewis, Joshua P, DIAGRAM Consortium, MAGIC Investigators, Ferrara, Assiamira, Lu, Lingyi, Ziegler, Julie T, Sale, Michele M, Divers, Jasmin, Shriner, Daniel, Adeyemo, Adebowale, Rotimi, Charles N, Ng, Maggie CY, Langefeld, Carl D, Freedman, Barry I, Bowden, Donald W, Voight, Benjamin F, Scott, Laura J, Steinthorsdottir, Valgerdur, Morris, Andrew P, Dina, Christian, Welch, Ryan P, Zeggini, Eleftheria, Huth, Cornelia, Aulchenko, Yurii S, Thorleifsson, Gudmar, McCulloch, Laura J, Ferreira, Teresa, Grallert, Harald, Amin, Najaf, Wu, Guanming, Willer, Cristen J, Raychaudhuri, Soumya, McCarroll, Steve A, Langenberg, Claudia, Hofmann, Oliver M, Dupuis, Josée, Qi, Lu, Segrè, Ayellet V, Van Hoek, Mandy, Navarro, Pau, Ardlie, Kristin, Balkau, Beverley, Benediktsson, Rafn, Bennett, Amanda J, Blagieva, Roza, Boerwinkle, Eric, Bonnycastle, Lori L, Boström, Kristina Bengtsson, Bravenboer, Bert, Bumpstead, Suzannah, Burtt, Noël P, Charpentier, Guillaume, Chines, Peter S, Cornelis, Marilyn, Couper, David J, Crawford, Gabe, Doney, Alex SF, Elliott, Katherine S, Elliott, Amanda L, Erdos, Michael R, Fox, Caroline S, Franklin, Christopher S, Ganser, Martha, Gieger, Christian, Grarup, Niels, Green, Todd, Griffin, Simon, Groves, Christopher J, Guiducci, Candace, Hadjadj, Samy, Hassanali, Neelam, Herder, Christian, Isomaa, Bo, Jackson, Anne U, Johnson, Paul RV, Jørgensen, Torben, Kao, Wen HL, Klopp, Norman, Kong, Augustine, Kraft, Peter, Kuusisto, Johanna, Lauritzen, Torsten, Li, Man, Lieverse, Aloysius, Lindgren, Cecilia M, Lyssenko, Valeriya, Marre, Michel, Meitinger, Thomas, Midthjell, Kristian, Morken, Mario A, Narisu, Narisu, Nilsson, Peter, Owen, Katharine R, Payne, Felicity, Perry, John RB, Petersen, Ann-Kristin, Platou, Carl, Proença, Christine, Prokopenko, Inga, Rathmann, Wolfgang, Rayner, N William, Robertson, Neil R, Rocheleau, Ghislain, Roden, Michael, Sampson, Michael J, Saxena, Richa, Shields, Beverley M, Shrader, Peter, Sigurdsson, Gunnar, Sparsø, Thomas, Strassburger, Klaus, Stringham, Heather M, Sun, Qi, Swift, Amy J, Thorand, Barbara, Tichet, Jean, Tuomi, Tiinamaija, Van Dam, Rob M, Van Haeften, Timon W, Van Herpt, Thijs, Van Vliet-Ostaptchouk, Jana V, Walters, G Bragi, Weedon, Michael N, Wijmenga, Cisca, Witteman, Jacqueline, Bergman, Richard N, Cauchi, Stephane, Collins, Francis S, Gloyn, Anna L, Gyllensten, Ulf, Hansen, Torben, Hide, Winston A, Hitman, Graham A, Hofman, Albert, Hunter, David J, Hveem, Kristian, Laakso, Markku, Mohlke, Karen L, Morris, Andrew D, Palmer, Colin NA, Pramstaller, Peter P, Rudan, Igor, Sijbrands, Eric, Stein, Lincoln D, Tuomilehto, Jaakko, Uitterlinden, Andre, Walker, Mark, Wareham, Nicholas J, Watanabe, Richard M, Abecasis, Goncalo R, Boehm, Bernhard O, Campbell, Harry, Daly, Mark J, Hattersley, Andrew T, Hu, Frank B, Meigs, James B, Pankow, James S, Pedersen, Oluf, Wichmann, H-Erich, Barroso, Inês, Florez, Jose C, Frayling, Timothy M, Groop, Leif, Sladek, Rob, Thorsteinsdottir, Unnur, Wilson, James F, Illig, Thomas, Froguel, Philippe, Van Duijn, Cornelia M, Stefansson, Kari, Altshuler, David, Boehnke, Michael, McCarthy, Mark I, Soranzo, Nicole, Wheeler, Eleanor, Glazer, Nicole L, Bouatia-Naji, Nabila, Mägi, Reedik, Randall, Joshua, Johnson, Toby, Elliott, Paul, Rybin, Denis, Henneman, Peter, Dehghan, Abbas, Hottenga, Jouke Jan, Song, Kijoung, Goel, Anuj, Egan, Josephine M, Lajunen, Taina, Doney, Alex, Kanoni, Stavroula, Cavalcanti-Proença, Christine, Kumari, Meena, Timpson, Nicholas J, Zabena, Carina, Ingelsson, Erik, An, Ping, O'Connell, Jeffrey, Luan, Jian'an, Elliott, Amanda, McCarroll, Steven A, Roccasecca, Rosa Maria, Pattou, François, Sethupathy, Praveen, Ariyurek, Yavuz, Barter, Philip, Beilby, John P, Ben-Shlomo, Yoav, Bergmann, Sven, Bochud, Murielle, Bonnefond, Amélie, Borch-Johnsen, Knut, Böttcher, Yvonne, Brunner, Eric, Bumpstead, Suzannah J, Chen, Yii-Der Ida, Chines, Peter, Clarke, Robert, Coin, Lachlan JM, Cooper, Matthew N, Crisponi, Laura, Day, Ian NM, De Geus, Eco JC, Delplanque, Jerome, Fedson, Annette C, Fischer-Rosinsky, Antje, Forouhi, Nita G, Frants, Rune, Franzosi, Maria Grazia, Galan, Pilar, Goodarzi, Mark O, Graessler, Jürgen, Grundy, Scott, Gwilliam, Rhian, Hallmans, Göran, Hammond, Naomi, Han, Xijing, Hartikainen, Anna-Liisa, Hayward, Caroline, Heath, Simon C, Hercberg, Serge, Hicks, Andrew A, Hillman, David R, Hingorani, Aroon D, Hui, Jennie, Hung, Joe, Jula, Antti, Kaakinen, Marika, Kaprio, Jaakko, Kesaniemi, Y Antero, Kivimaki, Mika, Knight, Beatrice, Koskinen, Seppo, Kovacs, Peter, Kyvik, Kirsten Ohm, Lathrop, G Mark, Lawlor, Debbie A, Le Bacquer, Olivier, Lecoeur, Cécile, Li, Yun, Mahley, Robert, Mangino, Massimo, Manning, Alisa K, Martínez-Larrad, María Teresa, McAteer, Jarred B, McPherson, Ruth, Meisinger, Christa, Melzer, David, Meyre, 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H, Willemsen, Gonneke, Witteman, Jaqueline CM, Yarnell, John WG, Zelenika, Diana, Zethelius, Björn, Zhai, Guangju, Zhao, Jing Hua, Zillikens, M Carola, Borecki, Ingrid B, Loos, Ruth JF, Meneton, Pierre, Magnusson, Patrik KE, Nathan, David M, Williams, Gordon H, Silander, Kaisa, Salomaa, Veikko, Smith, George Davey, Bornstein, Stefan R, Schwarz, Peter, Spranger, Joachim, Karpe, Fredrik, Shuldiner, Alan R, Cooper, Cyrus, Dedoussis, George V, Serrano-Ríos, Manuel, Lind, Lars, Palmer, Lyle J, Franks, Paul W, Ebrahim, Shah, Marmot, Michael, Kao, WH Linda, Pramstaller, Peter Paul, Wright, Alan F, Stumvoll, Michael, Hamsten, Anders, Buchanan, Thomas A, Valle, Timo T, Rotter, Jerome I, Siscovick, David S, Penninx, Brenda WJH, Boomsma, Dorret I, Deloukas, Panos, Spector, Timothy D, Ferrucci, Luigi, Cao, Antonio, Scuteri, Angelo, Schlessinger, David, Uda, Manuela, Ruokonen, Aimo, Jarvelin, Marjo-Riitta, Waterworth, Dawn M, Vollenweider, Peter, Peltonen, Leena, Mooser, Vincent, Sladek, Robert, 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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, Altshuler, D, 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, 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, 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Netherlands Twin Register (NTR) ,Male ,Adult ,African Americans/genetics ,Aged ,Case-Control Studies ,Cohort Studies ,Diabetes Mellitus, Type 2/ethnology ,Diabetes Mellitus, Type 2/genetics ,Female ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Genotype ,Humans ,Meta-Analysis as Topic ,Middle Aged ,Polymorphism, Single Nucleotide ,Validation Studies as Topic ,Medicin och hälsovetenskap ,Linkage disequilibrium ,Genetic Screens ,endocrine system diseases ,lcsh:Medicine ,Genome-wide association study ,Medical and Health Sciences ,0302 clinical medicine ,Endocrinology ,Genome Sequencing ,lcsh:Science ,Medicine(all) ,Genetics ,African Americans ,0303 health sciences ,education.field_of_study ,INSULIN-RESISTANCE ,Multidisciplinary ,Agricultural and Biological Sciences(all) ,LARGE-SCALE ASSOCIATION ,STAGE RENAL-DISEASE ,COMMON VARIANTS ,Genomics ,Medicine ,Research Article ,SUSCEPTIBILITY LOCI ,General Science & Technology ,Population ,Single-nucleotide polymorphism ,Biology ,DIAGRAM Consortium ,03 medical and health sciences ,MAGIC Investigators ,SDG 3 - Good Health and Well-being ,Genetic linkage ,MD Multidisciplinary ,Genome-Wide Association Studies ,SNP ,ddc:610 ,education ,Genotyping ,030304 developmental biology ,Diabetic Endocrinology ,LINKAGE ANALYSIS ,Biochemistry, Genetics and Molecular Biology(all) ,lcsh:R ,TCF7L2 GENE ,Case-control study ,Computational Biology ,nutritional and metabolic diseases ,Human Genetics ,Diabetes Mellitus Type 2 ,Stage renal-disease ,large-scale association ,Susceptibility loci ,Insulin-resistance ,Fasting glucose ,Tissue factor ,Homeodomain protein ,Linkage analysis ,Common variants ,TCF7L2 gene ,Black or African American ,Diabetes Mellitus, Type 2 ,TISSUE FACTOR ,Genetics of Disease ,HOMEODOMAIN PROTEIN ,Genetic Polymorphism ,lcsh:Q ,Genome Expression Analysis ,030217 neurology & neurosurgery ,Population Genetics ,FASTING GLUCOSE - Abstract
African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P
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- 2012
32. Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals
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Seppo Koskinen, Christian Herder, Daniel I. Chasman, Andrew R. Wood, Jonna L. Grimsby, J.F. Wilson, Day Inm., Massimo Mangino, Gonneke Willemsen, Robert W. Mahley, Cristian Pattaro, Nicole L. Glazer, T.B. Harris, Irene Pichler, M S Sandhu, D. van Heemst, Christine Proença, Martha Ganser, Robert A. Hegele, Richa Saxena, Eleftheria Zeggini, Markku Laakso, Peter Kraft, Judith B. Borja, Karen L. Mohlke, J B Richards, de Geus Ejc., Robert Sladek, Cristen J. Willer, Samy Hadjadj, S.M. Boekholdt, Gina M. Peloso, Kijoung Song, Sutapa Mukherjee, Gudmar Thorleifsson, Winston Hide, Mark I. McCarthy, Ruth E. Pakyz, Marian Beekman, Ayellet V. Segrè, Inga Prokopenko, Ping An, George Dedoussis, Danielle Posthuma, Jeanette Erdmann, Simon J. Griffin, Nilesh J. Samani, Inke R. König, Frank B. Hu, Lokki M-L., David M. Evans, Xiaohui Li, Valgerdur Steinthorsdottir, Aimo Ruokonen, A Pouta, Kerrin S. Small, Cecilia M. Lindgren, O Le Bacquer, Xijing Han, Florian Kronenberg, E Katsareli, Christian Dina, S. Gabriel, Jochen Spranger, James S. Pankow, M. Kloppenburg, Penninx Bwjh., Torben Hansen, Josh Smith, Jennie Hui, Gordon H. Williams, Mark Seielstad, Ingrid B. Borecki, Weihua Zhang, Peter P. Pramstaller, Stephen J. Sharp, Neil R. Robertson, Zee Ryl., Mike Sampson, Angela Silveira, C.M. van Duijn, Anders Hamsten, Peter Shrader, Denis Rybin, Chen Y-Di., Gunnar Sigurdsson, Michael Stumvoll, Russel Tracy, Mark O. Goodarzi, Göran Hallmans, Michael R. Erdos, Valeriya Lyssenko, Juha Saharinen, Sven Bergmann, Jeffrey R. O'Connell, Debbie A Lawlor, Thomas Meitinger, Yvonne Böttcher, Jérôme Delplanque, Sarah G. Buxbaum, Silvia Naitza, Shah Ebrahim, Graham A. Hitman, Angelo Scuteri, Aroon D. Hingorani, Heribert Schunkert, François Pattou, Claudia Lamina, A L Elliott, Sekar Kathiresan, Dawn M. Waterworth, Jennifer A. Brody, Thomas Quertermous, Leena Peltonen, Josephine M. Egan, Daniel J. Rader, J F Peden, Yarnell Jwg., Daniel S. Pearson, Pfeiffer Afh., P S Chines, N Vogelzangs, Susan Redline, Alka M. Kanaya, T B Harris, J. V. van Vliet-Ostaptchouk, Ghislain Rocheleau, Rune R. Frants, Olga D. Carlson, James G. Wilson, Melissa Garcia, Ong Rt-H., Mark J. Caulfield, Tanya M. Teslovich, Loo B-M., Beatrice Knight, Andreas Ziegler, Claudia Langenberg, Yoon Shin Cho, Paul M. Ridker, Mark J. Rieder, Praveen Sethupathy, Bert Bravenboer, J. Viikari, Matt Neville, Ioannis M. Stylianou, Andrew Walley, Jarvelin M-R., Jarred B. McAteer, Ronald M. Krauss, Augustine Kong, Oluf Pedersen, Mark J. Daly, Andrew P. Morris, Anna F. Dominiczak, Stéphane Cauchi, Michael Boehnke, Christopher J. O'Donnell, Barbara Thorand, Peter M. Nilsson, Aaron Isaacs, Deborah A. Nickerson, Roza Blagieva, Mary F. Feitosa, Nicholas J. Wareham, Robert Roberts, J S Kooner, K W van Dijk, Tiinamaija Tuomi, Paul Scheet, Lynda M. Rose, Albert V. Smith, Rafn Benediktsson, Chiara Sabatti, Candace Guiducci, Lee M. Kaplan, Aki S. Havulinna, Toby Johnson, Samuli Ripatti, Erik Ingelsson, Mario A. Morken, Carl G. P. Platou, Anke Tönjes, Qi Sun, Narisu Narisu, S J Bumpstead, Jose M. Ordovas, Alan B. Feranil, L Groop, P Chines, Sara M. Willems, Perry Jrb., Matthew A. Allison, Jan Scott, Cécile Lecoeur, Kastelein Jjp., Herman A. Taylor, Anyuan Cao, Christopher J. Groves, Lincoln D. Stein, Laura J. Scott, John Beilby, Kristin G. Ardlie, Christopher S. Franklin, Yoav Ben-Shlomo, B M Shields, N J Timpson, Marco Orrù, Amélie Bonnefond, Kiran Musunuru, Murielle Bochud, Udo Seedorf, Yongmei Liu, Guillaume Lettre, Lee J-Y., Alan R. Shuldiner, Ryan P. Welch, David J. Hunter, John Whitfield, Klaus Strassburger, Khaw K-T., Hartikainen A-L., Gunnar Sigurðsson, Lu Qi, Richard N. Bergman, G M Lathrop, Sigrid W. Fouchier, T van Herpt, David S. Siscovick, Igor Rudan, Richard M. Watanabe, Themistocles L. Assimes, Nicholas G. Martin, Ozren Polasek, Dhiraj Varma, K Kim, Oliver Hofmann, Nicholas D. Hastie, S Bumpstead, Jose C. Florez, Fernando Rivadeneira, Katharine R. Owen, Braxton D. Mitchell, Alisa K. Manning, Abbas Dehghan, Bruce Bartholow Duncan, Cisca Wijmenga, Timo T. Valle, Jaakko Kaprio, Mika Kivimäki, B Shields, Laila Simpson, Tim D. Spector, Paul W. Franks, Guangju Zhai, María Teresa Martínez-Larrad, Janssens Acjw., Kim L. Ward, Inês Barroso, Xiuqing Guo, Rosa Maria Roccasecca, Zari Dastani, Reijo Laaksonen, Wilmar Igl, Vincent Mooser, Niels Grarup, Cornelia Huth, Christian Gieger, Fabio Marroni, Jaakko Tuomilehto, Doney Asf., Andrew C. Edmondson, Christian Fuchsberger, Meena Kumari, David M. Nathan, Reedik Mägi, Solomon K. Musani, U de Faire, Knut Borch-Johnsen, Masahiro Koseki, Giuseppe Paolisso, Norman Klopp, Caroline S. Fox, Nelson B. Freimer, Mika Kähönen, Peter Henneman, Diana Zelenika, K Willems-Vandijk, Steven A. McCarroll, Paul Elliott, Wichmann H-E., J. C. Bis, Nita G. Forouhi, Antti Jula, Witteman Jcm., Fredrik Karpe, Joseph Hung, Antje Fischer-Rosinsky, Eric J. Brunner, Elena Gonzalez, Soumya Raychaudhuri, Jian'an Luan, Josée Dupuis, Joshua C. Randall, Taesung Park, Francis S. Collins, Lori L. Bonnycastle, Andrew A. Hicks, Peter Kovacs, Thomas Illig, Maja Barbalić, David Couper, Jaspal S. Kooner, Damien C. Croteau-Chonka, Gavin Lucas, P J Wagner, Young-Jin Kim, Yurii S. Aulchenko, Aurelian Bidulescu, Ingrid Meulenbelt, Pilar Galan, Iris M. Heid, Michael N. Weedon, Serena Sanna, Sarah H. Wild, Hivert M-F., Patricia B. Munroe, Johan G. Eriksson, Teresa Ferreira, Robert A. Scott, A. Sandbaek, Kenneth Rice, Veronique Vitart, Xin Yuan, Leslie A. Lange, Hilma Holm, Jorge R. Kizer, Timothy M. Frayling, Marika Kaakinen, Liu C-T., Petersen A-K., Peter Schwarz, G B Walters, Palmer Cna., Jean Tichet, Bernhard Paulweber, Ying Wu, Alyson Hall, Christopher T. Johansen, David Masson, Martin Ladouceur, Christie M. Ballantyne, Tai E-S., Robert Luben, Guillaume Charpentier, Angela Döring, Philip J. Barter, Ruth McPherson, Benjamin F. Voight, Wolfgang Rathmann, Mark Walker, Markus Perola, M. A. Province, Veikko Salomaa, James B. Meigs, George Davey Smith, Robert Clarke, Gerard Waeber, Stefania Bandinelli, Sally L. Ricketts, Kaisa Silander, Loos Rjf., Amanda J. Bennett, John C. Chambers, Marilyn C. Cornelis, L A Cupples, Andrew T. Hattersley, M Sandhu, Marju Orho-Melander, C M van Duijn, Olli T. Raitakari, David Meyre, Ida Surakka, Jouke-Jan Hottenga, Uh H-W., Kari Stefansson, David Melzer, P E Slagboom, Kristian Midthjell, Robert K. Semple, James P. Pirruccello, Aloysius G Lieverse, Åsa Johansson, Michael Roden, Felicity Payne, Eric J.G. Sijbrands, N P Burtt, David R. Hillman, Michael Marmot, Todd Green, Eric E. Schadt, Sijbrands Ejg., Tien Yin Wong, Coin Ljm., K B Boström, Olov Rolandsson, A D Morris, David Altshuler, Harald Grallert, L C Groop, Alan F. Wright, Karen Kapur, Xueling Sim, Philippe Froguel, K O Kyvik, T. Lauritzen, Linda S. Adair, Yavuz Ariyurek, Talin Haritunians, Toshiko Tanaka, Albert Hofman, MariaGrazia Franzosi, Nicholas L. Smith, Laura Crisponi, Andrew B. Singleton, A Uitterlinden, Bo Isomaa, Y A Kesaniemi, Anne U. Jackson, Christa Meisinger, Holly E. Syddall, Dorret I. Boomsma, Harry Campbell, Gonçalo R. Abecasis, Lyudmyla Kedenko, Christine Cavalcanti-Proença, G Crawford, Scott M. Grundy, Johnson Prv., Nuotio M-L., I Chen, J.H. Smit, Anuj Goel, M Li, David P. Strachan, Kenechi Ejebe, Beverley Balkau, Neelam Hassanali, Kristian Hveem, Pierre Meneton, R. Gwilliam, A J Swift, Caroline Hayward, J. Graessler, Carina Zabena, B. St Pourcain, Michel Marre, Margot Haun, Lyytikäinen L-P., Ben A. Oostra, Stefan Coassin, M. van Hoek, Nigel W. Rayner, John R. Thompson, Kurt Lohman, Ulla Sovio, Unnur Thorsteinsdottir, Naveed Sattar, Lyle J. Palmer, Ulf Gyllensten, A Elliott, Muredach P. Reilly, A Swift, Luigi Ferrucci, Syvänen A-C., Simon C. Potter, T.W. van Haeften, G Wu, Stefan Böhringer, Grant W. Montgomery, Edward G. Lakatta, Serkalem Demissie, Alex S. F. Doney, Najaf Amin, Lenore J. Launer, Hugh Watkins, Johanna Kuusisto, Lars Lind, Stefan R. Bornstein, Laura J. Rasmussen-Torvik, Terho Lehtimäki, Guillaume Paré, Sophie Visvikis-Siest, S C Heath, David Schlessinger, Juha Sinisalo, Kao Whl., Mark E. Cooper, Kati Kristiansson, Thomas W. Winkler, Thomas Sparsø, Laura J. McCulloch, Taina K. Lajunen, Alex N. Parker, Nabila Bouatia-Naji, Markku S. Nieminen, Peter Vollenweider, Wendy L. McArdle, G K Hovingh, Thomas A. Buchanan, Avan Aihie Sayer, M C Zillikens, Jing Hua Zhao, Naomi Hammond, Vilmundur Gudnason, Björn Zethelius, Panos Deloukas, Jacqueline C. M. Witteman, Eric Boerwinkle, Manuel Serrano-Ríos, Anna L. Gloyn, Katherine S. Elliott, A C Fedson, Torben Jørgensen, Nicole Soranzo, Heather M. Stringham, Bruce M. Psaty, A G Uitterlinden, Stavroula Kanoni, Christian Hengstenberg, Yun Li, Olle Melander, Alan R. Tall, Manuela Uda, Magnusson Pke., Christopher W. Kuzawa, V Mooser, R. M. van Dam, Jerome I. Rotter, Greenwood Cmt., Cyrus Cooper, Pau Navarro, Min Jin Go, Nancy L. Pedersen, Serge Hercberg, Bernhard O. Boehm, Eleanor Wheeler, Epidemiology, Medical Microbiology & Infectious Diseases, Clinical Genetics, Dastani, Z, Hivert, Mf, Timpson, N, Perry, Jr, Yuan, X, Scott, Ra, Henneman, P, Heid, Im, Kizer, Jr, Lyytikäinen, Lp, Fuchsberger, C, Tanaka, T, Morris, Ap, Small, K, Isaacs, A, Beekman, M, Coassin, S, Lohman, K, Qi, L, Kanoni, S, Pankow, J, Uh, Hw, Wu, Y, Bidulescu, A, Rasmussen Torvik, Lj, Greenwood, Cm, Ladouceur, M, Grimsby, J, Manning, Ak, Liu, Ct, Kooner, J, Mooser, Ve, Vollenweider, P, Kapur, Ka, Chambers, J, Wareham, Nj, Langenberg, C, Frants, R, Willems Vandijk, K, Oostra, Ba, Willems, Sm, Lamina, C, Winkler, Tw, Psaty, Bm, Tracy, Rp, Brody, J, Chen, I, Viikari, J, Kähönen, M, Pramstaller, Pp, Evans, Dm, St Pourcain, B, Sattar, N, Wood, Ar, Bandinelli, S, Carlson, Od, Egan, Jm, Böhringer, S, van Heemst, D, Kedenko, L, Kristiansson, K, Nuotio, Ml, Loo, Bm, Harris, T, Garcia, M, Kanaya, A, Haun, M, Klopp, N, Wichmann, He, Deloukas, P, Katsareli, E, Couper, Dj, Duncan, Bb, 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Charpentier, G, Chines, P, Cornelis, M, 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, 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, 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, Morris, Ad, Palmer, Cn, Rudan, I, Sijbrands, E, Stein, Ld, Tuomilehto, J, Uitterlinden, A, Walker, M, Watanabe, Rm, Abecasis, Gr, Boehm, Bo, Campbell, H, Daly, Mj, Hattersley, At, Pedersen, O, Barroso, I, Groop, L, Sladek, R, Thorsteinsdottir, U, Wilson, Jf, Illig, T, Froguel, P, van Duijn, Cm, Stefansson, K, Altshuler, D, Boehnke, M, Mccarthy, Mi, Soranzo, N, Wheeler, E, Glazer, Nl, Bouatia Naji, N, Mägi, R, Randall, J, Elliott, P, Rybin, D, Dehghan, A, Hottenga, Jj, Song, K, Goel, A, Lajunen, T, 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, 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, Hillman, Dr, Hingorani, Ad, Hui, J, Hung, J, 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, Martínez Larrad, Mt, Mcateer, Jb, Mcpherson, R, Meisinger, C, Melzer, D, Meyre, D, Mitchell, Bd, Mukherjee, S, Naitza, S, Neville, Mj, Orrù, M, Pakyz, R, Paolisso, Giuseppe, Pattaro, C, Pearson, D, Peden, Jf, Pedersen, Nl, Pfeiffer, Af, Pichler, I, Polasek, O, Posthuma, D, Potter, Sc, Pouta, A, Province, Ma, 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, 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, Diagram, Consortium, Giant, Consortium, Global B., Pgen Consortium, Borecki, Ib, Meneton, P, Magnusson, Pk, Nathan, Dm, Williams, Gh, Silander, K, Bornstein, Sr, Schwarz, P, Spranger, J, Karpe, F, Shuldiner, Ar, Cooper, C, Serrano Ríos, M, Lind, L, Palmer, Lj, Hu FB, 1st, Franks, Pw, Ebrahim, S, Marmot, M, Wright, Af, Stumvoll, M, Hamsten, A, Procardis, Consortium, Buchanan, Ta, Valle, Tt, Rotter, Ji, Penninx, Bw, Boomsma, Di, Cao, A, Scuteri, A, Schlessinger, D, Uda, M, Ruokonen, A, Jarvelin, Mr, Peltonen, L, Mooser, V, Magic, Investigator, Glgc, Consortium, Musunuru, K, Smith, Av, Edmondson, Ac, Stylianou, Im, Koseki, M, Pirruccello, Jp, Chasman, Di, Johansen, Ct, Fouchier, Sw, Peloso, Gm, Barbalic, M, Ricketts, Sl, Bis, Jc, Feitosa, Mf, Orho Melander, M, Melander, O, Li, X, Cho, Y, Go, Mj, Kim, Yj, Lee, Jy, Park, T, Kim, K, Sim, X, Ong, Rt, Croteau Chonka, Dc, Lange, La, Smith, Jd, Ziegler, A, Zhang, W, Zee, Ry, Whitfield, Jb, Thompson, Jr, Surakka, I, Smit, Jh, Sinisalo, J, Scott, J, Saharinen, J, Sabatti, C, Rose, Lm, Roberts, R, Rieder, M, Parker, An, Pare, G, O'Donnell, Cj, Nieminen, M, Nickerson, Da, Montgomery, Gw, Mcardle, W, Masson, D, Martin, Ng, Marroni, F, Lucas, G, Luben, R, Lokki, Ml, Lettre, G, Launer, Lj, Lakatta, Eg, Laaksonen, R, König, Ir, Khaw, Kt, Kaplan, Lm, Johansson, Å, Janssens, Ac, Igl, W, Hovingh, Gk, Hengstenberg, C, Havulinna, A, Hastie, Nd, Harris, Tb, Haritunians, T, Hall, A, Groop, Lc, Gonzalez, E, Freimer, Nb, Erdmann, J, Ejebe, Kg, Döring, A, Dominiczak, Af, Demissie, S, de Faire, U, Caulfield, Mj, Boekholdt, Sm, Assimes, Tl, Quertermous, T, Seielstad, M, Wong, Ty, Tai, E, Feranil, Ab, Kuzawa, Cw, Taylor HA, Jr, Gabriel, Sb, Holm, H, Gudnason, V, Krauss, Rm, Ordovas, Jm, Munroe, Pb, Tall, Ar, Hegele, Ra, Kastelein, Jj, Schadt, Ee, Strachan, Dp, Reilly, Mp, Samani, Nj, Schunkert, H, Cupples, La, Ridker, Pm, Rader, Dj, Kathiresan, S., Medical Research Council (MRC), Perry, John [0000-0001-6483-3771], Wareham, Nicholas [0000-0003-1422-2993], Langenberg, Claudia [0000-0002-5017-7344], Semple, Robert [0000-0001-6539-3069], Griffin, Simon [0000-0002-2157-4797], Barroso, Ines [0000-0001-5800-4520], Soranzo, Nicole [0000-0003-1095-3852], Wheeler, Eleanor [0000-0002-8616-6444], Luan, Jian'an [0000-0003-3137-6337], Forouhi, Nita [0000-0002-5041-248X], Sharp, Stephen [0000-0003-2375-1440], Sovio, Ulla [0000-0002-0799-1105], Zhao, Jing Hua [0000-0003-4930-3582], Luben, Robert [0000-0002-5088-6343], Khaw, Kay-Tee [0000-0002-8802-2903], Sandhu, Manjinder [0000-0002-2725-142X], Apollo - University of Cambridge Repository, Biological Psychology, Functional Genomics, Neuroscience Campus Amsterdam - Attention & Cognition, EMGO+ - Lifestyle, Overweight and Diabetes, Other departments, Experimental Vascular Medicine, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, Cardiology, Human genetics, Psychiatry, NCA - Attention & Cognition, EMGO - Lifestyle, overweight and diabetes, Lääketieteen yksikkö - School of Medicine, University of Tampere, Institute for Molecular Medicine Finland, Hjelt Institute (-2014), Clinicum, Department of General Practice and Primary Health Care, Department of Public Health, Haartman Institute (-2014), Transplantation Laboratory, Biostatistics Helsinki, Quantitative Genetics, Complex Disease Genetics, Genetic Epidemiology, DIAGRAM+ Consortium, MAGIC Consortium, GLGC Investigators, MuTHER Consortium, DIAGRAM Consortium, GIANT Consortium, Global B Pgen Consortium, Procardis Consortium, MAGIC investigators, GLGC Consortium, Olson, J., Kronmal, R., Robbins, J., Chaves, PH., Burke, G., Kuller, LH., Tracy, R., Gottdiener, J., Prineas, R., Becker, JT., Enright, P., Klein, R., and O'Leary, DH.
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Netherlands Twin Register (NTR) ,Male ,Insulin Resistance/genetics ,VARIANTS ,0302 clinical medicine ,POPULATION ,African Americans ,blood/genetics ,0303 health sciences ,education.field_of_study ,Adiponectin/blood ,Adiponectin/genetics ,Asian Continental Ancestry Group ,Cholesterol, HDL/genetics ,Diabetes Mellitus, Type 2/genetics ,European Continental Ancestry Group ,Female ,Gene Expression ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Glucose Tolerance Test ,Humans ,Metabolic Networks and Pathways ,Polymorphism, Single Nucleotide ,Waist-Hip Ratio ,Global B Pgen Consortium ,MAGIC investigators ,3. Good health ,Cholesterol ,Medicine ,Adiponectin ,Type 2 ,medicine.medical_specialty ,HDL ,Biolääketieteet - Biomedicine ,Single-nucleotide polymorphism ,DIAGRAM Consortium ,White People ,Molecular Genetics ,GLGC Consortium ,03 medical and health sciences ,Asian People ,SDG 3 - Good Health and Well-being ,GIANT Consortium ,Diabetes Mellitus ,Genetics ,DIAGRAM+ Consortium ,GENOME-WIDE ASSOCIATION ,Polymorphism ,education ,Biology ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,0604 Genetics ,Science & Technology ,GLGC Investigators ,nutritional and metabolic diseases ,ta3121 ,medicine.disease ,Obesity ,Black or African American ,blood/genetics, African Americans, Asian Continental Ancestry Group, Cholesterol ,genetics, Diabetes Mellitus ,genetics, European Continental Ancestry Group, Female, Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Glucose Tolerance Test, Humans, Insulin Resistance ,genetics, Male, Metabolic Networks and Pathways, Polymorphism ,Single Nucleotide, Waist-Hip Ratio ,Endocrinology ,Diabetes Mellitus, Type 2 ,Developmental Biology ,Type 2/genetics ,Cancer Research ,Type 2 diabetes ,QH426-470 ,030204 cardiovascular system & hematology ,LIPID CONCENTRATIONS ,GENETICS & HEREDITY ,Genetics (clinical) ,RISK ,2. Zero hunger ,INSULIN-RESISTANCE ,Glucose tolerance test ,medicine.diagnostic_test ,MAGIC Consortium ,Single Nucleotide ,ADIPOSE-TISSUE ,CORONARY-ARTERY-DISEASE ,Life Sciences & Biomedicine ,Research Article ,Clinical Research Design ,GENETIC-BASIS ,Population ,Insulin resistance ,Internal medicine ,Diabetes mellitus ,medicine ,ddc:610 ,030304 developmental biology ,RECEPTOR ,Cholesterol, HDL ,Human Genetics ,HDL/genetics ,3121 General medicine, internal medicine and other clinical medicine ,MuTHER Consortium ,3111 Biomedicine ,Procardis Consortium ,Insulin Resistance - Abstract
Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10−8–1.2×10−43). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p, Author Summary Serum adiponectin levels are highly heritable and are inversely correlated with the risk of type 2 diabetes (T2D), coronary artery disease, stroke, and several metabolic traits. To identify common genetic variants associated with adiponectin levels and risk of T2D and metabolic traits, we conducted a meta-analysis of genome-wide association studies of 45,891 multi-ethnic individuals. In addition to confirming that variants at the ADIPOQ and CDH13 loci influence adiponectin levels, our analyses revealed that 10 new loci also affecting circulating adiponectin levels. We demonstrated that expression levels of several genes in these candidate regions are associated with serum adiponectin levels. Using a powerful novel method to assess the contribution of the identified variants with other traits using summary-level results from large-scale GWAS consortia, we provide evidence that the risk alleles for adiponectin are associated with deleterious changes in T2D risk and metabolic syndrome traits (triglycerides, HDL, post-prandial glucose, insulin, and waist-to-hip ratio), demonstrating that the identified loci, taken together, impact upon metabolic disease.
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- 2012
33. Comment on Garvey et al. Association of Baseline Factors With Glycemic Outcomes in GRADE: A Comparative Effectiveness Randomized Clinical Trial. Diabetes Care 2024;47:562-570.
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Cardoso P, Young KG, Hattersley AT, Shields BM, Jones AG, and Dennis JM
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- Humans, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 drug therapy, Glycated Hemoglobin metabolism, Randomized Controlled Trials as Topic, Male, Female, Glycemic Control, Blood Glucose metabolism
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- 2024
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34. Safety and effectiveness of SGLT2 inhibitors in a UK population with type 2 diabetes and aged over 70 years: an instrumental variable approach.
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Güdemann LM, Young KG, Thomas NJM, Hopkins R, Challen R, Jones AG, Hattersley AT, Pearson ER, Shields BM, Bowden J, Dennis JM, and McGovern AP
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- Humans, Aged, Female, Male, United Kingdom epidemiology, Aged, 80 and over, Hypoglycemic Agents therapeutic use, Hypoglycemic Agents adverse effects, Diabetic Ketoacidosis epidemiology, Diabetic Ketoacidosis chemically induced, Treatment Outcome, Middle Aged, Sodium-Glucose Transporter 2 Inhibitors therapeutic use, Sodium-Glucose Transporter 2 Inhibitors adverse effects, Diabetes Mellitus, Type 2 drug therapy, Dipeptidyl-Peptidase IV Inhibitors therapeutic use, Dipeptidyl-Peptidase IV Inhibitors adverse effects
- Abstract
Aims/hypothesis: Older adults are under-represented in trials, meaning the benefits and risks of glucose-lowering agents in this age group are unclear. The aim of this study was to assess the safety and effectiveness of sodium-glucose cotransporter 2 inhibitors (SGLT2i) in people with type 2 diabetes aged over 70 years using causal analysis., Methods: Hospital-linked UK primary care data (Clinical Practice Research Datalink, 2013-2020) were used to compare adverse events and effectiveness in individuals initiating SGLT2i compared with dipeptidyl peptidase-4 inhibitors (DPP4i). Analysis was age-stratified: <70 years (SGLT2i n=66,810, DPP4i n=76,172), ≥70 years (SGLT2i n=10,419, DPP4i n=33,434). Outcomes were assessed using the instrumental variable causal inference method and prescriber preference as the instrument., Results: Risk of diabetic ketoacidosis was increased with SGLT2i in those aged ≥70 (incidence rate ratio compared with DPP4i: 3.82 [95% CI 1.12, 13.03]), but not in those aged <70 (1.12 [0.41, 3.04]). However, incidence rates with SGLT2i in those ≥70 was low (29.6 [29.5, 29.7]) per 10,000 person-years. SGLT2i were associated with similarly increased risk of genital infection in both age groups (incidence rate ratio in those <70: 2.27 [2.03, 2.53]; ≥70: 2.16 [1.77, 2.63]). There was no evidence of an increased risk of volume depletion, poor micturition control, urinary frequency, falls or amputation with SGLT2i in either age group. In those ≥70, HbA
1c reduction was similar between SGLT2i and DPP4i (-0.3 mmol/mol [-1.6, 1.1], -0.02% [0.1, 0.1]), but in those <70, SGLT2i were more effective (-4 mmol/mol [4.8, -3.1], -0.4% [-0.4, -0.3])., Conclusions/interpretation: Causal analysis suggests SGLT2i are effective in adults aged ≥70 years, but increase risk for genital infections and diabetic ketoacidosis. Our study extends RCT evidence to older adults with type 2 diabetes., (© 2024. The Author(s).)- Published
- 2024
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35. Comparison of Bayesian approaches for developing prediction models in rare disease: application to the identification of patients with Maturity-Onset Diabetes of the Young.
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Cardoso P, McDonald TJ, Patel KA, Pearson ER, Hattersley AT, Shields BM, and McKinley TJ
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- Humans, Case-Control Studies, Female, Diabetes Mellitus, Type 1 diagnosis, Male, Biomarkers analysis, Adolescent, Adult, Child, Bayes Theorem, Diabetes Mellitus, Type 2 diagnosis, Rare Diseases diagnosis
- Abstract
Background: Clinical prediction models can help identify high-risk patients and facilitate timely interventions. However, developing such models for rare diseases presents challenges due to the scarcity of affected patients for developing and calibrating models. Methods that pool information from multiple sources can help with these challenges., Methods: We compared three approaches for developing clinical prediction models for population screening based on an example of discriminating a rare form of diabetes (Maturity-Onset Diabetes of the Young - MODY) in insulin-treated patients from the more common Type 1 diabetes (T1D). Two datasets were used: a case-control dataset (278 T1D, 177 MODY) and a population-representative dataset (1418 patients, 96 MODY tested with biomarker testing, 7 MODY positive). To build a population-level prediction model, we compared three methods for recalibrating models developed in case-control data. These were prevalence adjustment ("offset"), shrinkage recalibration in the population-level dataset ("recalibration"), and a refitting of the model to the population-level dataset ("re-estimation"). We then developed a Bayesian hierarchical mixture model combining shrinkage recalibration with additional informative biomarker information only available in the population-representative dataset. We developed a method for dealing with missing biomarker and outcome information using prior information from the literature and other data sources to ensure the clinical validity of predictions for certain biomarker combinations., Results: The offset, re-estimation, and recalibration methods showed good calibration in the population-representative dataset. The offset and recalibration methods displayed the lowest predictive uncertainty due to borrowing information from the fitted case-control model. We demonstrate the potential of a mixture model for incorporating informative biomarkers, which significantly enhanced the model's predictive accuracy, reduced uncertainty, and showed higher stability in all ranges of predictive outcome probabilities., Conclusion: We have compared several approaches that could be used to develop prediction models for rare diseases. Our findings highlight the recalibration mixture model as the optimal strategy if a population-level dataset is available. This approach offers the flexibility to incorporate additional predictors and informed prior probabilities, contributing to enhanced prediction accuracy for rare diseases. It also allows predictions without these additional tests, providing additional information on whether a patient should undergo further biomarker testing before genetic testing., (© 2024. The Author(s).)
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- 2024
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36. Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis.
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Shields BM, Carlsson A, Patel K, Knupp J, Kaur A, Johnston D, Colclough K, Larsson HE, Forsander G, Samuelsson U, Hattersley A, and Ludvigsson J
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- Humans, Child, Male, Female, Adolescent, Hepatocyte Nuclear Factor 4 genetics, Hepatocyte Nuclear Factor 1-alpha genetics, Child, Preschool, Autoantibodies blood, Autoantibodies immunology, Glycated Hemoglobin analysis, Germinal Center Kinases genetics, Sweden, Glucokinase genetics, Diabetes Mellitus, Type 2 diagnosis, Diabetes Mellitus, Type 2 genetics
- Abstract
Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing "MODY calculator" cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish 'Better Diabetes Diagnosis' (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability > 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. ~ 1 in 10 positive test rate). Probability > 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis., (© 2024. The Author(s).)
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- 2024
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37. Phenotype-based targeted treatment of SGLT2 inhibitors and GLP-1 receptor agonists in type 2 diabetes.
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Cardoso P, Young KG, Nair ATN, Hopkins R, McGovern AP, Haider E, Karunaratne P, Donnelly L, Mateen BA, Sattar N, Holman RR, Bowden J, Hattersley AT, Pearson ER, Jones AG, Shields BM, McKinley TJ, and Dennis JM
- Subjects
- Male, Humans, Female, Hypoglycemic Agents adverse effects, Glucagon-Like Peptide-1 Receptor Agonists, Liraglutide therapeutic use, Bayes Theorem, Glucose, Phenotype, Glucagon-Like Peptide-1 Receptor, Diabetes Mellitus, Type 2 complications, Sodium-Glucose Transporter 2 Inhibitors therapeutic use, Sodium-Glucose Transporter 2 Inhibitors pharmacology
- Abstract
Aims/hypothesis: A precision medicine approach in type 2 diabetes could enhance targeting specific glucose-lowering therapies to individual patients most likely to benefit. We aimed to use the recently developed Bayesian causal forest (BCF) method to develop and validate an individualised treatment selection algorithm for two major type 2 diabetes drug classes, sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1-RA)., Methods: We designed a predictive algorithm using BCF to estimate individual-level conditional average treatment effects for 12-month glycaemic outcome (HbA
1c ) between SGLT2i and GLP1-RA, based on routine clinical features of 46,394 people with type 2 diabetes in primary care in England (Clinical Practice Research Datalink; 27,319 for model development, 19,075 for hold-out validation), with additional external validation in 2252 people with type 2 diabetes from Scotland (SCI-Diabetes [Tayside & Fife]). Differences in glycaemic outcome with GLP1-RA by sex seen in clinical data were replicated in clinical trial data (HARMONY programme: liraglutide [n=389] and albiglutide [n=1682]). As secondary outcomes, we evaluated the impacts of targeting therapy based on glycaemic response on weight change, tolerability and longer-term risk of new-onset microvascular complications, macrovascular complications and adverse kidney events., Results: Model development identified marked heterogeneity in glycaemic response, with 4787 (17.5%) of the development cohort having a predicted HbA1c benefit >3 mmol/mol (>0.3%) with SGLT2i over GLP1-RA and 5551 (20.3%) having a predicted HbA1c benefit >3 mmol/mol with GLP1-RA over SGLT2i. Calibration was good in hold-back validation, and external validation in an independent Scottish dataset identified clear differences in glycaemic outcomes between those predicted to benefit from each therapy. Sex, with women markedly more responsive to GLP1-RA, was identified as a major treatment effect modifier in both the UK observational datasets and in clinical trial data: HARMONY-7 liraglutide (GLP1-RA): 4.4 mmol/mol (95% credible interval [95% CrI] 2.2, 6.3) (0.4% [95% CrI 0.2, 0.6]) greater response in women than men. Targeting the two therapies based on predicted glycaemic response was also associated with improvements in short-term tolerability and long-term risk of new-onset microvascular complications., Conclusions/interpretation: Precision medicine approaches can facilitate effective individualised treatment choice between SGLT2i and GLP1-RA therapies, and the use of routinely collected clinical features for treatment selection could support low-cost deployment in many countries., (© 2024. The Author(s).)- Published
- 2024
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38. Performance of European prediction models for classification of type 1 and type 2 diabetes in Indians.
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Venkatesan U, Amutha A, Jones AG, Shields BM, Anjana RM, Unnikrishnan R, Mappillairaju B, and Mohan V
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- Humans, Male, Female, Adult, India epidemiology, Middle Aged, Adolescent, Young Adult, Retrospective Studies, Prognosis, Follow-Up Studies, Europe epidemiology, Biomarkers blood, Diabetes Mellitus, Type 2 epidemiology, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 diagnosis, Diabetes Mellitus, Type 1 epidemiology, Diabetes Mellitus, Type 1 blood, Diabetes Mellitus, Type 1 diagnosis
- Abstract
Aim: We aimed to determine the performance of European prediction models in an Indian population to classify type 1 diabetes(T1D) and type 2 diabetes(T2D)., Methods: We assessed discrimination and calibration of published models of diabetes classification, using retrospective data from electronic medical records of 83309 participants aged 18-50 years living in India. Diabetes type was defined based on C-peptide measurement and early insulin requirement. Models assessed combinations of clinical measurements: age at diagnosis, body mass index(mean = 26.6 kg/m
2 ), sex(male = 64.9 %), Glutamic acid decarboxylase(GAD) antibody, serum cholesterol, serum triglycerides, and high-density lipoprotein(HDL) cholesterol., Results: 67955 participants met inclusion criteria, of whom 0.8 % had T1D, which was markedly lower than model development cohorts. Model discrimination for clinical features was broadly similar in our Indian cohort compared to the European cohort: area under the receiver operating characteristic curve(AUC ROC) was 0.90 vs. 0.90 respectively, but was lower in the subset of young participants with measured GAD antibodies(n = 2404): and an AUC ROC of 0.87 when clinical features, sex, lipids and GAD antibodies were combined. All models substantially overestimated the likelihood of T1D, reflecting the lower prevalence of T1D in the Indian population. However, good model performance was achieved after recalibration by updating the model intercept and slope., Conclusion: Models for diabetes classification maintain the discrimination of T1D and T2D in this Indian population, where T2D is far more common, but require recalibration to obtain appropriate model probabilities. External validation and recalibration are needed before these tools can be used in non-European populations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Research Trust of DiabetesIndia (DiabetesIndia) and National Diabetes Obesity and Cholesterol Foundation (N-DOC). All rights reserved.)- Published
- 2024
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39. Risk factor associations for severe COVID-19, influenza and pneumonia in people with diabetes to inform future pandemic preparations: UK population-based cohort study.
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Hopkins R, Young KG, Thomas NJ, Godwin J, Raja D, Mateen BA, Challen RJ, Vollmer SJ, Shields BM, McGovern AP, and Dennis JM
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- Humans, Aged, Pandemics, Glycated Hemoglobin, Cohort Studies, COVID-19 Vaccines, Risk Factors, Obesity complications, Obesity epidemiology, United Kingdom epidemiology, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 epidemiology, COVID-19 epidemiology, Diabetes Mellitus, Type 1 complications, Diabetes Mellitus, Type 1 epidemiology, Influenza, Human epidemiology, Obesity, Morbid, Pneumonia epidemiology, Respiratory Tract Infections
- Abstract
Objective: This study aimed to compare clinical and sociodemographic risk factors for severe COVID-19, influenza and pneumonia, in people with diabetes., Design: Population-based cohort study., Setting: UK primary care records (Clinical Practice Research Datalink) linked to mortality and hospital records., Participants: Individuals with type 1 and type 2 diabetes (COVID-19 cohort: n=43 033 type 1 diabetes and n=584 854 type 2 diabetes, influenza and pneumonia cohort: n=42 488 type 1 diabetes and n=585 289 type 2 diabetes)., Primary and Secondary Outcome Measures: COVID-19 hospitalisation from 1 February 2020 to 31 October 2020 (pre-COVID-19 vaccination roll-out), and influenza and pneumonia hospitalisation from 1 September 2016 to 31 May 2019 (pre-COVID-19 pandemic). Secondary outcomes were COVID-19 and pneumonia mortality. Associations between clinical and sociodemographic risk factors and each outcome were assessed using multivariable Cox proportional hazards models. In people with type 2 diabetes, we explored modifying effects of glycated haemoglobin (HbA1c) and body mass index (BMI) by age, sex and ethnicity., Results: In type 2 diabetes, poor glycaemic control and severe obesity were consistently associated with increased risk of hospitalisation for COVID-19, influenza and pneumonia. The highest HbA1c and BMI-associated relative risks were observed in people aged under 70 years. Sociodemographic-associated risk differed markedly by respiratory infection, particularly for ethnicity. Compared with people of white ethnicity, black and south Asian groups had a greater risk of COVID-19 hospitalisation, but a lesser risk of pneumonia hospitalisation. Risk factor associations for type 1 diabetes and for type 2 diabetes mortality were broadly consistent with the primary analysis., Conclusions: Clinical risk factors of high HbA1c and severe obesity are consistently associated with severe outcomes from COVID-19, influenza and pneumonia, especially in younger people. In contrast, associations with sociodemographic risk factors differed by type of respiratory infection. This emphasises that risk stratification should be specific to individual respiratory infections., Competing Interests: Competing interests: BAM is an employee of Wellcome Trust; holds an honorary post at the Alan Turing Institute and University College London; and declares payments from the Medical Research Council, Health Data Research UK, British Heart Foundation, and Engineering and Physical Sciences Research Council (grant EP/N510129/). RJC declares research funding from Pfizer. SJV declares support from the University of Warwick, University of Kaiserslautern, and German Research Center for Artificial Intelligence; consulting fees from PUMAS; stock from Freshflow; and grant funding from The Alan Turing Institute (EP/N510129), Engineering and Physical Sciences Research Council, and Massachusetts Institute of Technology. APM received research funding from Eli Lilly and Company, Pfizer, and AstraZeneca. For all authors these are outside the submitted work; there are no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
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- 2024
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40. Clinical Prediction Models Combining Routine Clinical Measures Have High Accuracy in Identifying Youth-Onset Type 2 Diabetes Defined by Maintained Endogenous Insulin Secretion: The SEARCH for Diabetes in Youth Study.
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Jones AG, Shields BM, Oram RA, Dabelea DM, Hagopian WA, Lustigova E, Shah AS, Knupp J, Mottl AK, D'Agostino RB, Williams A, Marcovina SM, Pihoker C, Divers J, and Redondo MJ
- Abstract
Objective: With high prevalence of obesity and overlapping features between diabetes subtypes, accurately classifying youth-onset diabetes can be challenging. We aimed to develop prediction models that, using characteristics available at diabetes diagnosis, can identify youth who will retain endogenous insulin secretion at levels consistent with type 2 diabetes (T2D)., Research Design and Methods: We studied 2,966 youth with diabetes in the prospective SEARCH for Diabetes in Youth study (diagnosis age ≤19 years) to develop prediction models to identify participants with fasting C-peptide ≥250 pmol/L (≥0.75 ng/mL) after >3 years' (median 74 months) diabetes duration. Models included clinical measures at the baseline visit, at a mean diabetes duration of 11 months (age, BMI, sex, waist circumference, HDL cholesterol), with and without islet autoantibodies (GADA, IA-2A) and a Type 1 Diabetes Genetic Risk Score (T1DGRS)., Results: Models using routine clinical measures with or without autoantibodies and T1DGRS were highly accurate in identifying participants with C-peptide ≥0.75 ng/mL (17% of participants; 2.3% and 53% of those with and without positive autoantibodies) (area under the receiver operating characteristic curve [AUCROC] 0.95-0.98). In internal validation, optimism was very low, with excellent calibration (slope 0.995-0.999). Models retained high performance for predicting retained C-peptide in older youth with obesity (AUCROC 0.88-0.96) and in subgroups defined by self-reported race/ethnicity (AUCROC 0.88-0.97), autoantibody status (AUCROC 0.87-0.96), and clinically diagnosed diabetes types (AUCROC 0.81-0.92)., Conclusions: Prediction models combining routine clinical measures at diabetes diagnosis, with or without islet autoantibodies or T1DGRS, can accurately identify youth with diabetes who maintain endogenous insulin secretion in the range associated with T2D., (© 2024 by the American Diabetes Association.)
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- 2024
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41. Dirichlet process mixture models to impute missing predictor data in counterfactual prediction models: an application to predict optimal type 2 diabetes therapy.
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Cardoso P, Dennis JM, Bowden J, Shields BM, and McKinley TJ
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- Humans, Bayes Theorem, Clinical Decision-Making, Uncertainty, Diabetes Mellitus, Type 2 drug therapy
- Abstract
Background: The handling of missing data is a challenge for inference and regression modelling. A particular challenge is dealing with missing predictor information, particularly when trying to build and make predictions from models for use in clinical practice., Methods: We utilise a flexible Bayesian approach for handling missing predictor information in regression models. This provides practitioners with full posterior predictive distributions for both the missing predictor information (conditional on the observed predictors) and the outcome-of-interest. We apply this approach to a previously proposed counterfactual treatment selection model for type 2 diabetes second-line therapies. Our approach combines a regression model and a Dirichlet process mixture model (DPMM), where the former defines the treatment selection model, and the latter provides a flexible way to model the joint distribution of the predictors., Results: We show that DPMMs can model complex relationships between predictor variables and can provide powerful means of fitting models to incomplete data (under missing-completely-at-random and missing-at-random assumptions). This framework ensures that the posterior distribution for the parameters and the conditional average treatment effect estimates automatically reflect the additional uncertainties associated with missing data due to the hierarchical model structure. We also demonstrate that in the presence of multiple missing predictors, the DPMM model can be used to explore which variable(s), if collected, could provide the most additional information about the likely outcome., Conclusions: When developing clinical prediction models, DPMMs offer a flexible way to model complex covariate structures and handle missing predictor information. DPMM-based counterfactual prediction models can also provide additional information to support clinical decision-making, including allowing predictions with appropriate uncertainty to be made for individuals with incomplete predictor data., (© 2023. The Author(s).)
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- 2024
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42. Incretin hormone responses to carbohydrate and protein/fat are preserved in adults with sulfonylurea-treated KCNJ11 neonatal diabetes.
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Bowman P, Patel KA, McDonald TJ, Holst JJ, Hartmann B, Leveridge M, Shields BM, Hammersley S, Spaull SR, Knight BA, Flanagan SE, Shepherd MH, Andrews RC, and Hattersley AT
- Subjects
- Infant, Newborn, Adult, Humans, Incretins therapeutic use, Glucagon metabolism, Insulin metabolism, Blood Glucose metabolism, Gastric Inhibitory Polypeptide, Glucagon-Like Peptide 1, Diabetes Mellitus, Diabetes Mellitus, Type 2 metabolism
- Abstract
The incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), are thought to be the main drivers of insulin secretion in individuals with sulfonylurea (SU)-treated KCNJ11 permanent neonatal diabetes. The aim of this study was to assess for the first time the incretin hormone response to carbohydrate and protein/fat in adults with sulfonylurea-treated KCNJ11 permanent neonatal diabetes compared with that of controls without diabetes. Participants were given a breakfast high in carbohydrate and an isocaloric breakfast high in protein/fat on two different mornings. Incremental area under the curve and total area under the curve (0-240 minutes) for total GLP-1 and GIP were compared between groups, using non-parametric statistical methods. Post-meal GLP-1 and GIP secretion were similar in cases and controls, suggesting this process is adenosine triphosphate-sensitive potassium channel-independent. Future research will investigate whether treatments targeting the incretin pathway are effective in individuals with KCNJ11 permanent neonatal diabetes who do not have good glycemic control on sulfonylurea alone., (© 2023 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.)
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- 2023
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43. Recent UK type 2 diabetes treatment guidance represents a near whole population indication for SGLT2-inhibitor therapy.
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Young KG, Hopkins R, Shields BM, Thomas NJ, McGovern AP, and Dennis JM
- Subjects
- Humans, Aged, Sodium-Glucose Transporter 2, State Medicine, England, Diabetes Mellitus, Type 2 diagnosis, Diabetes Mellitus, Type 2 drug therapy, Diabetes Mellitus, Type 2 epidemiology, Sodium-Glucose Transporter 2 Inhibitors adverse effects, Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology, Cardiovascular Diseases prevention & control, Heart Failure, Atherosclerosis
- Abstract
Recent type 2 diabetes guidance from the UK's National Institute for Health and Care Excellence (NICE) proposes offering SGLT2-inhibitor therapy to people with established atherosclerotic cardiovascular disease (ASCVD) or heart failure, and considering SGLT2-inhibitor therapy for those at high-risk of cardiovascular disease defined as a 10-year cardiovascular risk of > 10% using the QRISK2 algorithm. We used a contemporary population-representative UK cohort of people with type 2 diabetes to assess the implications of this guidance. 93.1% of people currently on anti-hyperglycaemic treatment are now recommended or considered for SGLT2-inhibitor therapy under the new guidance, with the majority (59.6%) eligible on the basis of QRISK2 rather than established ASCVD or heart failure (33.6%). Applying these results to the approximately 2.20 million people in England currently on anti-hyperglycaemic medication suggests 1.75 million people will now be considered for additional SGLT2-inhibitor therapy, taking the total cost of SGLT2-inhibitor therapy in England to over £1 billion per year. Given that older people, those of non-white ethnic groups, and those at lower cardiovascular disease risk were underrepresented in the clinical trials which were used to inform this guidance, careful evaluation of the impact and safety of increased SGLT2-inhibitor prescribing across different populations is urgently required. Evidence of benefit should be weighed against the major cost implications for the UK National Health Service., (© 2023. The Author(s).)
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- 2023
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44. Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth.
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Beaumont RN, Flatley C, Vaudel M, Wu X, Chen J, Moen GH, Skotte L, Helgeland Ø, Solé-Navais P, Banasik K, Albiñana C, Ronkainen J, Fadista J, Stinson SE, Trajanoska K, Wang CA, Westergaard D, Srinivasan S, Sánchez-Soriano C, Bilbao JR, Allard C, Groleau M, Kuulasmaa T, Leirer DJ, White F, Jacques PÉ, Cheng H, Hao K, Andreassen OA, Åsvold BO, Atalay M, Bhatta L, Bouchard L, Brumpton BM, Brunak S, Bybjerg-Grauholm J, Ebbing C, Elliott P, Engelbrechtsen L, Erikstrup C, Estarlich M, Franks S, Gaillard R, Geller F, Grove J, Hougaard DM, Kajantie E, Morgen CS, Nohr EA, Nyegaard M, Palmer CNA, Pedersen OB, Rivadeneira F, Sebert S, Shields BM, Stoltenberg C, Surakka I, Thørner LW, Ullum H, Vaarasmaki M, Vilhjalmsson BJ, Willer CJ, Lakka TA, Gybel-Brask D, Bustamante M, Hansen T, Pearson ER, Reynolds RM, Ostrowski SR, Pennell CE, Jaddoe VWV, Felix JF, Hattersley AT, Melbye M, Lawlor DA, Hveem K, Werge T, Nielsen HS, Magnus P, Evans DM, Jacobsson B, Järvelin MR, Zhang G, Hivert MF, Johansson S, Freathy RM, Feenstra B, and Njølstad PR
- Subjects
- Female, Humans, Pregnancy, Birth Weight genetics, Fetal Development genetics, Insulin, Male, Genome-Wide Association Study, Placenta metabolism
- Abstract
A well-functioning placenta is essential for fetal and maternal health throughout pregnancy. Using placental weight as a proxy for placental growth, we report genome-wide association analyses in the fetal (n = 65,405), maternal (n = 61,228) and paternal (n = 52,392) genomes, yielding 40 independent association signals. Twenty-six signals are classified as fetal, four maternal and three fetal and maternal. A maternal parent-of-origin effect is seen near KCNQ1. Genetic correlation and colocalization analyses reveal overlap with birth weight genetics, but 12 loci are classified as predominantly or only affecting placental weight, with connections to placental development and morphology, and transport of antibodies and amino acids. Mendelian randomization analyses indicate that fetal genetically mediated higher placental weight is causally associated with preeclampsia risk and shorter gestational duration. Moreover, these analyses support the role of fetal insulin in regulating placental weight, providing a key link between fetal and placental growth., (© 2023. The Author(s).)
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- 2023
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45. Clinical prediction models combining routine clinical measures identify participants with youth-onset diabetes who maintain insulin secretion in the range associated with type 2 diabetes: The SEARCH for Diabetes in Youth Study.
- Author
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Jones AG, Shields BM, Oram RA, Dabelea DM, Hagopian WA, Lustigova E, Shah AS, Knupp J, Mottl AK, DÀgostino RB Jr, Williams A, Marcovina SM, Pihoker C, Divers J, and Redondo MJ
- Abstract
Objective: With the high prevalence of pediatric obesity and overlapping features between diabetes subtypes, accurately classifying youth-onset diabetes can be challenging. We aimed to develop prediction models that, using characteristics available at diabetes diagnosis, can identify youth who will retain endogenous insulin secretion at levels consistent with type 2 diabetes (T2D)., Methods: We studied 2,966 youth with diabetes in the prospective SEARCH study (diagnosis age ≤19 years) to develop prediction models to identify participants with fasting c-peptide ≥250 pmol/L (≥0.75ng/ml) after >3 years (median 74 months) of diabetes duration. Models included clinical measures at baseline visit, at a mean diabetes duration of 11 months (age, BMI, sex, waist circumference, HDL-C), with and without islet autoantibodies (GADA, IA-2A) and a Type 1 Diabetes Genetic Risk Score (T1DGRS)., Results: Models using routine clinical measures with or without autoantibodies and T1DGRS were highly accurate in identifying participants with c-peptide ≥0.75 ng/ml (17% of participants; 2.3% and 53% of those with and without positive autoantibodies) (area under receiver operator curve [AUCROC] 0.95-0.98). In internal validation, optimism was very low, with excellent calibration (slope=0.995-0.999). Models retained high performance for predicting retained c-peptide in older youth with obesity (AUCROC 0.88-0.96), and in subgroups defined by self-reported race/ethnicity (AUCROC 0.88-0.97), autoantibody status (AUCROC 0.87-0.96), and clinically diagnosed diabetes types (AUCROC 0.81-0.92)., Conclusion: Prediction models combining routine clinical measures at diabetes diagnosis, with or without islet autoantibodies or T1DGRS, can accurately identify youth with diabetes who maintain endogenous insulin secretion in the range associated with type 2 diabetes., Competing Interests: Duality of Interest RA is a co-Investigator on a Randox R&D research grant. The study has received translational industry-academic funding from Randox R&D relating to autoimmune genetic risk scores for prediction and classification of disease. There are no established patents, loyalties or licensing agreements relating to this grant. It is a 3 year grant (Feb 2022–2025). The approximate value is a £2.2m program grant on genetic risk scores across autoimmune disease. All other authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work.
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- 2023
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46. Correction to: The impact of population-level HbA 1c screening on reducing diabetes diagnostic delay in middle-aged adults: a UK Biobank analysis.
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Young KG, McGovern AP, Barroso I, Hattersley AT, Jones AG, Shields BM, Thomas NJ, and Dennis JM
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- 2023
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47. HbA 1c screening for the diagnosis of diabetes. Reply to Brož J, Brabec M, Krollová P et al [letter].
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Young KG, McGovern AP, Barroso I, Hattersley AT, Jones AG, Shields BM, Thomas NJ, and Dennis JM
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- Humans, Diabetes Mellitus diagnosis, Glycated Hemoglobin analysis
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- 2023
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48. Author Correction: Genetic effects on the timing of parturition and links to fetal birth weight.
- Author
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Solé-Navais P, Flatley C, Steinthorsdottir V, Vaudel M, Juodakis J, Chen J, Laisk T, LaBella AL, Westergaard D, Bacelis J, Brumpton B, Skotte L, Borges MC, Helgeland Ø, Mahajan A, Wielscher M, Lin F, Briggs C, Wang CA, Moen GH, Beaumont RN, Bradfield JP, Abraham A, Thorleifsson G, Gabrielsen ME, Ostrowski SR, Modzelewska D, Nohr EA, Hypponen E, Srivastava A, Talbot O, Allard C, Williams SM, Menon R, Shields BM, Sveinbjornsson G, Xu H, Melbye M, Lowe W Jr, Bouchard L, Oken E, Pedersen OB, Gudbjartsson DF, Erikstrup C, Sørensen E, Lie RT, Teramo K, Hallman M, Juliusdottir T, Hakonarson H, Ullum H, Hattersley AT, Sletner L, Merialdi M, Rifas-Shiman SL, Steingrimsdottir T, Scholtens D, Power C, West J, Nyegaard M, Capra JA, Skogholt AH, Magnus P, Andreassen OA, Thorsteinsdottir U, Grant SFA, Qvigstad E, Pennell CE, Hivert MF, Hayes GM, Jarvelin MR, McCarthy MI, Lawlor DA, Nielsen HS, Mägi R, Rokas A, Hveem K, Stefansson K, Feenstra B, Njolstad P, Muglia LJ, Freathy RM, Johansson S, Zhang G, and Jacobsson B
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- 2023
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49. Comparison of causal forest and regression-based approaches to evaluate treatment effect heterogeneity: an application for type 2 diabetes precision medicine.
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Venkatasubramaniam A, Mateen BA, Shields BM, Hattersley AT, Jones AG, Vollmer SJ, and Dennis JM
- Subjects
- Humans, Glycated Hemoglobin, Cohort Studies, Precision Medicine, Dipeptidyl Peptidase 4 therapeutic use, Sodium-Glucose Transporter 2 therapeutic use, Hypoglycemic Agents therapeutic use, Treatment Outcome, Diabetes Mellitus, Type 2 drug therapy, Dipeptidyl-Peptidase IV Inhibitors therapeutic use, Sodium-Glucose Transporter 2 Inhibitors therapeutic use
- Abstract
Objective: Precision medicine requires reliable identification of variation in patient-level outcomes with different available treatments, often termed treatment effect heterogeneity. We aimed to evaluate the comparative utility of individualized treatment selection strategies based on predicted individual-level treatment effects from a causal forest machine learning algorithm and a penalized regression model., Methods: Cohort study characterizing individual-level glucose-lowering response (6 month reduction in HbA1c) in people with type 2 diabetes initiating SGLT2-inhibitor or DPP4-inhibitor therapy. Model development set comprised 1,428 participants in the CANTATA-D and CANTATA-D2 randomised clinical trials of SGLT2-inhibitors versus DPP4-inhibitors. For external validation, calibration of observed versus predicted differences in HbA1c in patient strata defined by size of predicted HbA1c benefit was evaluated in 18,741 patients in UK primary care (Clinical Practice Research Datalink)., Results: Heterogeneity in treatment effects was detected in clinical trial participants with both approaches (proportion predicted to have a benefit on SGLT2-inhibitor therapy over DPP4-inhibitor therapy: causal forest: 98.6%; penalized regression: 81.7%). In validation, calibration was good with penalized regression but sub-optimal with causal forest. A strata with an HbA1c benefit > 10 mmol/mol with SGLT2-inhibitors (3.7% of patients, observed benefit 11.0 mmol/mol [95%CI 8.0-14.0]) was identified using penalized regression but not causal forest, and a much larger strata with an HbA1c benefit 5-10 mmol with SGLT2-inhibitors was identified with penalized regression (regression: 20.9% of patients, observed benefit 7.8 mmol/mol (95%CI 6.7-8.9); causal forest 11.6%, observed benefit 8.7 mmol/mol (95%CI 7.4-10.1)., Conclusions: Consistent with recent results for outcome prediction with clinical data, when evaluating treatment effect heterogeneity researchers should not rely on causal forest or other similar machine learning algorithms alone, and must compare outputs with standard regression, which in this evaluation was superior., (© 2023. The Author(s).)
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- 2023
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50. Age of Diagnosis Does Not Alter the Presentation or Progression of Robustly Defined Adult-Onset Type 1 Diabetes.
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Thomas NJ, Hill AV, Dayan CM, Oram RA, McDonald TJ, Shields BM, and Jones AG
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- Humans, Aged, Genetic Predisposition to Disease, C-Peptide, Prospective Studies, Autoantibodies, Diabetes Mellitus, Type 1 complications, Diabetes Mellitus, Type 2 complications
- Abstract
Objective: To determine whether presentation, progression, and genetic susceptibility of robustly defined adult-onset type 1 diabetes (T1D) are altered by diagnosis age., Research Design and Methods: We compared the relationship between diagnosis age and presentation, C-peptide loss (annual change in urine C-peptide-creatinine ratio [UCPCR]), and genetic susceptibility (T1D genetic risk score [GRS]) in adults with confirmed T1D in the prospective StartRight study, 1,798 adults with new-onset diabetes. T1D was defined in two ways: two or more positive islet autoantibodies (of GAD antibody, IA-2 antigen, and ZnT8 autoantibody) irrespective of clinical diagnosis (n = 385) or one positive islet autoantibody and a clinical diagnosis of T1D (n = 180)., Results: In continuous analysis, age of diagnosis was not associated with C-peptide loss for either definition of T1D (P > 0.1), with mean (95% CI) annual C-peptide loss in those diagnosed before and after 35 years of age (median age of T1D defined by two or more positive autoantibodies): 39% (31-46) vs. 44% (38-50) with two or more positive islet autoantibodies and 43% (33-51) vs. 39% (31-46) with clinician diagnosis confirmed by one positive islet autoantibody (P > 0.1). Baseline C-peptide and T1D GRS were unaffected by age of diagnosis or T1D definition (P > 0.1). In T1D defined by two or more autoantibodies, presentation severity was similar in those diagnosed before and after 35 years of age: unintentional weight loss, 80% (95% CI 74-85) vs. 82% (76-87); ketoacidosis, 24% (18-30) vs. 19% (14-25); and presentation glucose, 21 mmol/L (19-22) vs. 21 mmol/L (20-22) (all P ≥ 0.1). Despite similar presentation, older adults were less likely to be diagnosed with T1D, insulin-treated, or admitted to hospital., Conclusions: When adult-onset T1D is robustly defined, the presentation characteristics, progression, and T1D genetic susceptibility are not altered by age of diagnosis., (© 2023 by the American Diabetes Association.)
- Published
- 2023
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