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1. Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity

Author

Yaghootkar, Hanieh, Zhang, Yiying, Spracklen, Cassandra N, Karaderi, Tugce, Huang, Lam Opal, Bradfield, Jonathan, Schurmann, Claudia, Fine, Rebecca S, Preuss, Michael H, Kutalik, Zoltan, Wittemans, Laura BL, Lu, Yingchang, Metz, Sophia, Willems, Sara M, Li-Gao, Ruifang, Grarup, Niels, Wang, Shuai, Molnos, Sophie, Sandoval-Zárate, América A, Nalls, Mike A, Lange, Leslie A, Haesser, Jeffrey, Guo, Xiuqing, Lyytikäinen, Leo-Pekka, Feitosa, Mary F, Sitlani, Colleen M, Venturini, Cristina, Mahajan, Anubha, Kacprowski, Tim, Wang, Carol A, Chasman, Daniel I, Amin, Najaf, Broer, Linda, Robertson, Neil, Young, Kristin L, Allison, Matthew, Auer, Paul L, Blüher, Matthias, Borja, Judith B, Bork-Jensen, Jette, Carrasquilla, Germán D, Christofidou, Paraskevi, Demirkan, Ayse, Doege, Claudia A, Garcia, Melissa E, Graff, Mariaelisa, Guo, Kaiying, Hakonarson, Hakon, Hong, Jaeyoung, Ida Chen, Yii-Der, Jackson, Rebecca, Jakupović, Hermina, Jousilahti, Pekka, Justice, Anne E, Kähönen, Mika, Kizer, Jorge R, Kriebel, Jennifer, LeDuc, Charles A, Li, Jin, Lind, Lars, Luan, Jian'an, Mackey, David A, Mangino, Massimo, Männistö, Satu, Martin Carli, Jayne F, Medina-Gomez, Carolina, Mook-Kanamori, Dennis O, Morris, Andrew P, de Mutsert, Renée, Nauck, Matthias, Prokic, Ivana, Pennell, Craig E, Pradhan, Arund D, Psaty, Bruce M, Raitakari, Olli T, Scott, Robert A, Skaaby, Tea, Strauch, Konstantin, Taylor, Kent D, Teumer, Alexander, Uitterlinden, Andre G, Wu, Ying, Yao, Jie, Walker, Mark, North, Kari E, Kovacs, Peter, Ikram, M Arfan, van Duijn, Cornelia M, Ridker, Paul M, Lye, Stephen, Homuth, Georg, Ingelsson, Erik, Spector, Tim D, McKnight, Barbara, Province, Michael A, Lehtimäki, Terho, Adair, Linda S, Rotter, Jerome I, Reiner, Alexander P, and Wilson, James G

Subjects
Genetics, Nutrition, Prevention, Obesity, Aetiology, 2.1 Biological and endogenous factors, Oral and gastrointestinal, Metabolic and endocrine, Cardiovascular, Stroke, Cancer, Adiposity, Gene Expression Regulation, Developmental, Genetic Variation, Genotype, Humans, Leptin, Models, Molecular, Protein Conformation, Racial Groups, Medical and Health Sciences, Endocrinology & Metabolism
Abstract

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10-16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.

Published
2020

2. A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

Author

van Zuydam, Natalie R, Ahlqvist, Emma, Sandholm, Niina, Deshmukh, Harshal, Rayner, N William, Abdalla, Moustafa, Ladenvall, Claes, Ziemek, Daniel, Fauman, Eric, Robertson, Neil R, McKeigue, Paul M, Valo, Erkka, Forsblom, Carol, Harjutsalo, Valma, Perna, Annalisa, Rurali, Erica, Marcovecchio, M Loredana, Igo, Robert P, Salem, Rany M, Perico, Norberto, Lajer, Maria, Käräjämäki, Annemari, Imamura, Minako, Kubo, Michiaki, Takahashi, Atsushi, Sim, Xueling, Liu, Jianjun, van Dam, Rob M, Jiang, Guozhi, Tam, Claudia HT, Luk, Andrea OY, Lee, Heung Man, Lim, Cadmon KP, Szeto, Cheuk Chun, So, Wing Yee, Chan, Juliana CN, Ang, Su Fen, Dorajoo, Rajkumar, Wang, Ling, Clara, Tan Si Hua, McKnight, Amy-Jayne, Duffy, Seamus, Pezzolesi, Marcus G, Marre, Michel, Gyorgy, Beata, Hadjadj, Samy, Hiraki, Linda T, Ahluwalia, Tarunveer S, Almgren, Peter, Schulz, Christina-Alexandra, Orho-Melander, Marju, Linneberg, Allan, Christensen, Cramer, Witte, Daniel R, Grarup, Niels, Brandslund, Ivan, Melander, Olle, Paterson, Andrew D, Tregouet, David, Maxwell, Alexander P, Lim, Su Chi, Ma, Ronald CW, Tai, E Shyong, Maeda, Shiro, Lyssenko, Valeriya, Tuomi, Tiinamaija, Krolewski, Andrzej S, Rich, Stephen S, Hirschhorn, Joel N, Florez, Jose C, Dunger, David, Pedersen, Oluf, Hansen, Torben, Rossing, Peter, Remuzzi, Giuseppe, Brosnan, Mary Julia, Palmer, Colin NA, Groop, Per-Henrik, Colhoun, Helen M, Groop, Leif C, McCarthy, Mark I, Koivula, S, Uggeldahl, T, Forslund, T, Halonen, A, Koistinen, A, Koskiaho, P, Laukkanen, M, Saltevo, J, Tiihonen, M, Forsen, M, Granlund, H, Jonsson, A-C, Nyroos, B, Kinnunen, P, Orvola, A, Salonen, T, Vähänen, A, Paldanius, Kotka R, and Riihelä, M

Subjects
Diabetes, Genetics, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Good Health and Well Being, Adult, Aged, Aged, 80 and over, Case-Control Studies, Diabetes Mellitus, Type 2, Diabetic Nephropathies, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Kidney Failure, Chronic, Male, Middle Aged, Polymorphism, Single Nucleotide, Renal Insufficiency, Chronic, Finnish Diabetic Nephropathy Study, Hong Kong Diabetes Registry Theme-based Research Scheme Project Group, Warren 3 and Genetics of Kidneys in Diabetes (GoKinD) Study Group, GENIE (GEnetics of Nephropathy an International Effort) Consortium, Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) Research Group, SUrrogate markers for Micro- and Macrovascular hard endpoints for Innovative diabetes Tools (SUMMIT) Consortium, Medical and Health Sciences, Endocrinology & Metabolism
Abstract

Identification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 × 10-8) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.

Published
2018

3. An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

Author

Scott, Robert A, Scott, Laura J, Mägi, Reedik, Marullo, Letizia, Gaulton, Kyle J, Kaakinen, Marika, Pervjakova, Natalia, Pers, Tune H, Johnson, Andrew D, Eicher, John D, Jackson, Anne U, Ferreira, Teresa, Lee, Yeji, Ma, Clement, Steinthorsdottir, Valgerdur, Thorleifsson, Gudmar, Qi, Lu, Van Zuydam, Natalie R, Mahajan, Anubha, Chen, Han, Almgren, Peter, Voight, Ben F, Grallert, Harald, Müller-Nurasyid, Martina, Ried, Janina S, Rayner, William N, Robertson, Neil, Karssen, Lennart C, van Leeuwen, Elisabeth M, Willems, Sara M, Fuchsberger, Christian, Kwan, Phoenix, Teslovich, Tanya M, Chanda, Pritam, Li, Man, Lu, Yingchang, Dina, Christian, Thuillier, Dorothee, Yengo, Loic, Jiang, Longda, Sparso, Thomas, Kestler, Hans A, Chheda, Himanshu, Eisele, Lewin, Gustafsson, Stefan, Frånberg, Mattias, Strawbridge, Rona J, Benediktsson, Rafn, Hreidarsson, Astradur B, Kong, Augustine, Sigurðsson, Gunnar, Kerrison, Nicola D, Luan, Jian'an, Liang, Liming, Meitinger, Thomas, Roden, Michael, Thorand, Barbara, Esko, Tõnu, Mihailov, Evelin, Fox, Caroline, Liu, Ching-Ti, Rybin, Denis, Isomaa, Bo, Lyssenko, Valeriya, Tuomi, Tiinamaija, Couper, David J, Pankow, James S, Grarup, Niels, Have, Christian T, Jørgensen, Marit E, Jørgensen, Torben, Linneberg, Allan, Cornelis, Marilyn C, van Dam, Rob M, Hunter, David J, Kraft, Peter, Sun, Qi, Edkins, Sarah, Owen, Katharine R, Perry, John RB, Wood, Andrew R, Zeggini, Eleftheria, Tajes-Fernandes, Juan, Abecasis, Goncalo R, Bonnycastle, Lori L, Chines, Peter S, Stringham, Heather M, Koistinen, Heikki A, Kinnunen, Leena, Sennblad, Bengt, Mühleisen, Thomas W, Nöthen, Markus M, Pechlivanis, Sonali, Baldassarre, Damiano, Gertow, Karl, Humphries, Steve E, Tremoli, Elena, Klopp, Norman, Meyer, Julia, and Steinbach, Gerald

Subjects
Human Genome, Diabetes, Obesity, Genetics, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Diabetes Mellitus, Type 2, Gene Expression Regulation, Genetic Variation, Genome-Wide Association Study, Humans, White People, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Medical and Health Sciences, Endocrinology & Metabolism
Abstract

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

Published
2017

4. A Low-Frequency Inactivating Akt2 Variant Enriched in the Finnish Population is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk.

Author

Manning, Alisa, Highland, Heather M, Gasser, Jessica, Sim, Xueling, Tukiainen, Taru, Fontanillas, Pierre, Grarup, Niels, Rivas, Manuel A, Mahajan, Anubha, Locke, Adam E, Cingolani, Pablo, Pers, Tune H, Viñuela, Ana, Brown, Andrew A, Wu, Ying, Flannick, Jason, Fuchsberger, Christian, Gamazon, Eric R, Gaulton, Kyle J, Im, Hae Kyung, Teslovich, Tanya M, Blackwell, Thomas W, Bork-Jensen, Jette, Burtt, Noël P, Chen, Yuhui, Green, Todd, Hartl, Christopher, Kang, Hyun Min, Kumar, Ashish, Ladenvall, Claes, Ma, Clement, Moutsianas, Loukas, Pearson, Richard D, Perry, John RB, Rayner, N William, Robertson, Neil R, Scott, Laura J, van de Bunt, Martijn, Eriksson, Johan G, Jula, Antti, Koskinen, Seppo, Lehtimäki, Terho, Palotie, Aarno, Raitakari, Olli T, Jacobs, Suzanne BR, Wessel, Jennifer, Chu, Audrey Y, Scott, Robert A, Goodarzi, Mark O, Blancher, Christine, Buck, Gemma, Buck, David, Chines, Peter S, Gabriel, Stacey, Gjesing, Anette P, Groves, Christopher J, Hollensted, Mette, Huyghe, Jeroen R, Jackson, Anne U, Jun, Goo, Justesen, Johanne Marie, Mangino, Massimo, Murphy, Jacquelyn, Neville, Matt, Onofrio, Robert, Small, Kerrin S, Stringham, Heather M, Trakalo, Joseph, Banks, Eric, Carey, Jason, Carneiro, Mauricio O, DePristo, Mark, Farjoun, Yossi, Fennell, Timothy, Goldstein, Jacqueline I, Grant, George, Hrabé de Angelis, Martin, Maguire, Jared, Neale, Benjamin M, Poplin, Ryan, Purcell, Shaun, Schwarzmayr, Thomas, Shakir, Khalid, Smith, Joshua D, Strom, Tim M, Wieland, Thomas, Lindstrom, Jaana, Brandslund, Ivan, Christensen, Cramer, Surdulescu, Gabriela L, Lakka, Timo A, Doney, Alex SF, Nilsson, Peter, Wareham, Nicholas J, Langenberg, Claudia, Varga, Tibor V, Franks, Paul W, Rolandsson, Olov, Rosengren, Anders H, and Farook, Vidya S

Subjects
Genetics, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Black or African American, Alleles, Asian People, Case-Control Studies, Diabetes Mellitus, Type 2, Fasting, Finland, Gene Frequency, Genetic Predisposition to Disease, Genotype, Hispanic or Latino, Humans, Insulin, Insulin Resistance, Odds Ratio, Proto-Oncogene Proteins c-akt, White People, Medical and Health Sciences, Endocrinology & Metabolism
Abstract

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.

Published
2017

5. Genome-Wide Association Study of the Modified Stumvoll Insulin Sensitivity Index Identifies BCL2 and FAM19A2 as Novel Insulin Sensitivity Loci

Author

Walford, Geoffrey A, Gustafsson, Stefan, Rybin, Denis, Stančáková, Alena, Chen, Han, Liu, Ching-Ti, Hong, Jaeyoung, Jensen, Richard A, Rice, Ken, Morris, Andrew P, Mägi, Reedik, Tönjes, Anke, Prokopenko, Inga, Kleber, Marcus E, Delgado, Graciela, Silbernagel, Günther, Jackson, Anne U, Appel, Emil V, Grarup, Niels, Lewis, Joshua P, Montasser, May E, Landenvall, Claes, Staiger, Harald, Luan, Jian’an, Frayling, Timothy M, Weedon, Michael N, Xie, Weijia, Morcillo, Sonsoles, Martínez-Larrad, María Teresa, Biggs, Mary L, Chen, Yii-Der Ida, Corbaton-Anchuelo, Arturo, Færch, Kristine, Gómez-Zumaquero, Juan Miguel, Goodarzi, Mark O, Kizer, Jorge R, Koistinen, Heikki A, Leong, Aaron, Lind, Lars, Lindgren, Cecilia, Machicao, Fausto, Manning, Alisa K, Martín-Núñez, Gracia María, Rojo-Martínez, Gemma, Rotter, Jerome I, Siscovick, David S, Zmuda, Joseph M, Zhang, Zhongyang, Serrano-Rios, Manuel, Smith, Ulf, Soriguer, Federico, Hansen, Torben, Jørgensen, Torben J, Linnenberg, Allan, Pedersen, Oluf, Walker, Mark, Langenberg, Claudia, Scott, Robert A, Wareham, Nicholas J, Fritsche, Andreas, Häring, Hans-Ulrich, Stefan, Norbert, Groop, Leif, O’Connell, Jeff R, Boehnke, Michael, Bergman, Richard N, Collins, Francis S, Mohlke, Karen L, Tuomilehto, Jaakko, März, Winfried, Kovacs, Peter, Stumvoll, Michael, Psaty, Bruce M, Kuusisto, Johanna, Laakso, Markku, Meigs, James B, Dupuis, Josée, Ingelsson, Erik, and Florez, Jose C

Subjects
Biomedical and Clinical Sciences, Genetics, Prevention, Human Genome, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Chemokines, CC, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Insulin Receptor Substrate Proteins, Insulin Resistance, Male, Polymorphism, Single Nucleotide, Proto-Oncogene Proteins c-bcl-2, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract

Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium. Discovery for genetic association was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, and BMI and in a model analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI (model 3). In model 3, three variants reached genome-wide significance: rs13422522 (NYAP2; P = 8.87 × 10(-11)), rs12454712 (BCL2; P = 2.7 × 10(-8)), and rs10506418 (FAM19A2; P = 1.9 × 10(-8)). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardiometabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci.

Published
2016

6. Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogeneity

Author

Dimas, Antigone S, Lagou, Vasiliki, Barker, Adam, Knowles, Joshua W, Mägi, Reedik, Hivert, Marie-France, Benazzo, Andrea, Rybin, Denis, Jackson, Anne U, Stringham, Heather M, Song, Ci, Fischer-Rosinsky, Antje, Boesgaard, Trine Welløv, Grarup, Niels, Abbasi, Fahim A, Assimes, Themistocles L, Hao, Ke, Yang, Xia, Lecoeur, Cécile, Barroso, Inês, Bonnycastle, Lori L, Böttcher, Yvonne, Bumpstead, Suzannah, Chines, Peter S, Erdos, Michael R, Graessler, Jurgen, Kovacs, Peter, Morken, Mario A, Narisu, Narisu, Payne, Felicity, Stancakova, Alena, Swift, Amy J, Tönjes, Anke, Bornstein, Stefan R, Cauchi, Stéphane, Froguel, Philippe, Meyre, David, Schwarz, Peter EH, Häring, Hans-Ulrich, Smith, Ulf, Boehnke, Michael, Bergman, Richard N, Collins, Francis S, Mohlke, Karen L, Tuomilehto, Jaakko, Quertemous, Thomas, Lind, Lars, Hansen, Torben, Pedersen, Oluf, Walker, Mark, Pfeiffer, Andreas FH, Spranger, Joachim, Stumvoll, Michael, Meigs, James B, Wareham, Nicholas J, Kuusisto, Johanna, Laakso, Markku, Langenberg, Claudia, Dupuis, Josée, Watanabe, Richard M, Florez, Jose C, Ingelsson, Erik, McCarthy, Mark I, Prokopenko, Inga, and Investigators, on behalf of the MAGIC

Subjects
Biomedical and Clinical Sciences, Genetics, Diabetes, Autoimmune Disease, Clinical Research, Prevention, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Alleles, Cluster Analysis, Diabetes Mellitus, Type 2, Female, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Insulin, Insulin Resistance, Insulin Secretion, Insulin-Secreting Cells, Male, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, Transcription Factors, MAGIC Investigators, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract

Patients with established type 2 diabetes display both β-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.

Published
2014

7. No Interactions Between Previously Associated 2-Hour Glucose Gene Variants and Physical Activity or BMI on 2-Hour Glucose Levels

Author

Scott, Robert A, Chu, Audrey Y, Grarup, Niels, Manning, Alisa K, Hivert, Marie-France, Shungin, Dmitry, Tönjes, Anke, Yesupriya, Ajay, Barnes, Daniel, Bouatia-Naji, Nabila, Glazer, Nicole L, Jackson, Anne U, Kutalik, Zoltán, Lagou, Vasiliki, Marek, Diana, Rasmussen-Torvik, Laura J, Stringham, Heather M, Tanaka, Toshiko, Aadahl, Mette, Arking, Dan E, Bergmann, Sven, Boerwinkle, Eric, Bonnycastle, Lori L, Bornstein, Stefan R, Brunner, Eric, Bumpstead, Suzannah J, Brage, Soren, Carlson, Olga D, Chen, Han, Chen, Yii-Der Ida, Chines, Peter S, Collins, Francis S, Couper, David J, Dennison, Elaine M, Dowling, Nicole F, Egan, Josephine S, Ekelund, Ulf, Erdos, Michael R, Forouhi, Nita G, Fox, Caroline S, Goodarzi, Mark O, Grässler, Jürgen, Gustafsson, Stefan, Hallmans, Göran, Hansen, Torben, Hingorani, Aroon, Holloway, John W, Hu, Frank B, Isomaa, Bo, Jameson, Karen A, Johansson, Ingegerd, Jonsson, Anna, Jørgensen, Torben, Kivimaki, Mika, Kovacs, Peter, Kumari, Meena, Kuusisto, Johanna, Laakso, Markku, Lecoeur, Cécile, Lévy-Marchal, Claire, Li, Guo, Loos, Ruth JF, Lyssenko, Valeri, Marmot, Michael, Marques-Vidal, Pedro, Morken, Mario A, Müller, Gabriele, North, Kari E, Pankow, James S, Payne, Felicity, Prokopenko, Inga, Psaty, Bruce M, Renström, Frida, Rice, Ken, Rotter, Jerome I, Rybin, Denis, Sandholt, Camilla H, Sayer, Avan A, Shrader, Peter, Schwarz, Peter EH, Siscovick, David S, Stančáková, Alena, Stumvoll, Michael, Teslovich, Tanya M, Waeber, Gérard, Williams, Gordon H, Witte, Daniel R, Wood, Andrew R, Xie, Weijia, Boehnke, Michael, Cooper, Cyrus, Ferrucci, Luigi, Froguel, Philippe, Groop, Leif, Kao, WH Linda, Vollenweider, Peter, Walker, Mark, Watanabe, Richard M, Pedersen, Oluf, and Meigs, James B

Subjects
Biomedical and Clinical Sciences, Clinical Research, Genetics, Diabetes, Prevention, Obesity, Nutrition, 2.1 Biological and endogenous factors, Aetiology, 2.3 Psychological, social and economic factors, Metabolic and endocrine, Blood Glucose, Body Mass Index, Epigenesis, Genetic, Gene Expression Regulation, Genotype, Humans, Life Style, Motor Activity, Polymorphism, Single Nucleotide, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract

Gene-lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13-0.31], P = 1.63 × 10(-6)). All SNPs were associated with 2-h glucose (β = 0.06-0.12 mmol/allele, P ≤ 1.53 × 10(-7)), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene-lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.

Published
2012

9. Recessive Genome-Wide Meta-analysis Illuminates Genetic Architecture of Type 2 Diabetes

Author

O’Connor, Mark J., primary, Schroeder, Philip, additional, Huerta-Chagoya, Alicia, additional, Cortés-Sánchez, Paula, additional, Bonàs-Guarch, Silvía, additional, Guindo-Martínez, Marta, additional, Cole, Joanne B., additional, Kaur, Varinderpal, additional, Torrents, David, additional, Veerapen, Kumar, additional, Grarup, Niels, additional, Kurki, Mitja, additional, Rundsten, Carsten F., additional, Pedersen, Oluf, additional, Brandslund, Ivan, additional, Linneberg, Allan, additional, Hansen, Torben, additional, Leong, Aaron, additional, Florez, Jose C., additional, and Mercader, Josep M., additional

Published
2021
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10. Recessive Genome-Wide Meta-analysis Illuminates Genetic Architecture of Type 2 Diabetes.

Author

O'Connor, Mark J., Schroeder, Philip, Huerta-Chagoya, Alicia, Cortés-Sánchez, Paula, Bonàs-Guarch, Silvía, Guindo-Martínez, Marta, Cole, Joanne B., Kaur, Varinderpal, Torrents, David, Veerapen, Kumar, Grarup, Niels, Kurki, Mitja, Rundsten, Carsten F., Pedersen, Oluf, Brandslund, Ivan, Linneberg, Allan, Hansen, Torben, Leong, Aaron, Florez, Jose C., and Mercader, Josep M.

Subjects
TYPE 2 diabetes, RECESSIVE genes, GENOME-wide association studies, ANALYSIS of triglycerides, LDL cholesterol, GENE frequency, TRIGLYCERIDES, RESEARCH, SEQUENCE analysis, GENETIC mutation, METABOLISM, EVALUATION research, SEX distribution, COMPARATIVE studies, DISEASE susceptibility, GENES, GENOTYPES, RESEARCH funding
Abstract

Most genome-wide association studies (GWAS) of complex traits are performed using models with additive allelic effects. Hundreds of loci associated with type 2 diabetes have been identified using this approach. Additive models, however, can miss loci with recessive effects, thereby leaving potentially important genes undiscovered. We conducted the largest GWAS meta-analysis using a recessive model for type 2 diabetes. Our discovery sample included 33,139 case subjects and 279,507 control subjects from 7 European-ancestry cohorts, including the UK Biobank. We identified 51 loci associated with type 2 diabetes, including five variants undetected by prior additive analyses. Two of the five variants had minor allele frequency of <5% and were each associated with more than a doubled risk in homozygous carriers. Using two additional cohorts, FinnGen and a Danish cohort, we replicated three of the variants, including one of the low-frequency variants, rs115018790, which had an odds ratio in homozygous carriers of 2.56 (95% CI 2.05-3.19; P = 1 × 10-16) and a stronger effect in men than in women (for interaction, P = 7 × 10-7). The signal was associated with multiple diabetes-related traits, with homozygous carriers showing a 10% decrease in LDL cholesterol and a 20% increase in triglycerides; colocalization analysis linked this signal to reduced expression of the nearby PELO gene. These results demonstrate that recessive models, when compared with GWAS using the additive approach, can identify novel loci, including large-effect variants with pathophysiological consequences relevant to type 2 diabetes. [ABSTRACT FROM AUTHOR]

Published
2022
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11. 246-OR: A Loss-of-Function Mutation in the Sucrase-Isomaltase Gene Is Linked to a Markedly Healthier Metabolic Profile in Greenlanders

Author

JØRGENSEN, MARIT E., primary, ANDERSEN, METTE K., additional, SKOTTE, LINE, additional, JØRSBOE, EMIL, additional, GRARUP, NIELS, additional, BJERREGAARD, PETER, additional, SOBORG, BOLETTE, additional, PEDERSEN, OLUF, additional, FEENSTRA, BJARKE, additional, FÆRGEMAN, NILS J.K., additional, KOCH, ANDERS, additional, MOLTKE, IDA, additional, HANSEN, TORBEN, additional, and ALBRECHTSEN, ANDERS, additional

Published
2020
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15. G-allele of Intronic rs10830963 in MTNR1B Confers Increased Risk of Impaired Fasting Glycemia and Type 2 Diabetes Through an Impaired Glucose-Stimulated Insulin Release: Studies Involving 19,605 Europeans

Author

Sparsø, Thomas, Bonnefond, Amélie, Andersson, Ehm, Bouatia-Naji, Nabila, Holmkvist, Johan, Wegner, Lise, Grarup, Niels, Gjesing, Anette P., Banasik, Karina, Cavalcanti-Proença, Christine, Marchand, Marion, Vaxillaire, Martine, Charpentier, Guillaume, Jarvelin, Marjo-Riitta, Tichet, Jean, Balkau, Beverley, Marre, Michel, Lévy-Marchal, Claire, Færch, Kristine, Borch-Johnsen, Knut, Jørgensen, Torben, Madsbad, Sten, Poulsen, Pernille, Vaag, Allan, Dina, Christian, Hansen, Torben, Pedersen, Oluf, and Froguel, Philippe

Published
2009

21. ADAMTS9 Regulates Skeletal Muscle Insulin Sensitivity Through Extracellular Matrix Alterations

Author

Graae, Anne-Sofie, primary, Grarup, Niels, additional, Ribel-Madsen, Rasmus, additional, Lystbæk, Sara H., additional, Boesgaard, Trine, additional, Staiger, Harald, additional, Fritsche, Andreas, additional, Wellner, Niels, additional, Sulek, Karolina, additional, Kjolby, Mads, additional, Backe, Marie Balslev, additional, Chubanava, Sabina, additional, Prats, Clara, additional, Serup, Annette K., additional, Birk, Jesper B., additional, Dubail, Johanne, additional, Gillberg, Linn, additional, Vienberg, Sara G., additional, Nykjær, Anders, additional, Kiens, Bente, additional, Wojtaszewski, Jørgen F.P., additional, Larsen, Steen, additional, Apte, Suneel S., additional, Häring, Hans-Ulrich, additional, Vaag, Allan, additional, Zethelius, Björn, additional, Pedersen, Oluf, additional, Treebak, Jonas T., additional, Hansen, Torben, additional, and Holst, Birgitte, additional

Published
2019
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22. Do Greenlandic Carriers of the TBC1D4 p.Arg684Ter Variant Have Increased Risk of Cardiovascular Disease?

Author

JØRGENSEN, MARIT E., primary, TVERMOSEGAARD, MARIA, additional, RØNN, PERNILLE F., additional, BJERREGAARD, PETER, additional, DAHL-PETERSEN, INGER K., additional, LARSEN, CHRISTINA V., additional, PEDERSEN, MICHAEL L., additional, ALBRECHTSEN, ANDERS, additional, MOLTKE, IDA, additional, GRARUP, NIELS, additional, and HANSEN, TORBEN, additional

Published
2018
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23. A Low-Frequency Inactivating Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk.

Author

Manning, Alisa, Highland, Heather M., Gasser, Jessica, Sim, Xueling, Tukiainen, Taru, Fontanillas, Pierre, Grarup, Niels, Rivas, Manuel A., Mahajan, Anubha, Locke, Adam E., Cingolani, Pablo, Pers, Tune H., Viñuela, Ana, Brown, Andrew A., Ying Wu, Flannick, Jason, Fuchsberger, Christian, Gamazon, Eric R., Gaulton, Kyle J., and Hae Kyung Im

Subjects
INSULIN, TYPE 2 diabetes risk factors, DIABETES risk factors, EXOMES, GENOMES, ALLELES, ASIANS, BLACK people, DISEASE susceptibility, FASTING, GENES, HISPANIC Americans, INSULIN resistance, TYPE 2 diabetes, RESEARCH funding, TRANSFERASES, WHITE people, CASE-control method, ODDS ratio, GENOTYPES
Abstract

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2. [ABSTRACT FROM AUTHOR]

Published
2017
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24. A Genome-Wide Association Study of IVGTT-Based Measures of First-Phase Insulin Secretion Refines the Underlying Physiology of Type 2 Diabetes Variants.

Author

Wood AR, Jonsson A, Jackson AU, Wang N, van Leewen N, Palmer ND, Kobes S, Deelen J, Boquete-Vilarino L, Paananen J, Stančáková A, Boomsma DI, de Geus EJC, Eekhoff EMW, Fritsche A, Kramer M, Nijpels G, Simonis-Bik A, van Haeften TW, Mahajan A, Boehnke M, Bergman RN, Tuomilehto J, Collins FS, Mohlke KL, Banasik K, Groves CJ, McCarthy MI, Pearson ER, Natali A, Mari A, Buchanan TA, Taylor KD, Xiang AH, Gjesing AP, Grarup N, Eiberg H, Pedersen O, Chen YD, Laakso M, Norris JM, Smith U, Wagenknecht LE, Baier L, Bowden DW, Hansen T, Walker M, Watanabe RM, 't Hart LM, Hanson RL, and Frayling TM

Subjects
Alleles, C-Peptide genetics, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 physiopathology, Genetic Variation genetics, Genome-Wide Association Study, Genotype, Genotyping Techniques, Glucose Tolerance Test methods, Humans, Insulin metabolism, Insulin Secretion, Insulin-Secreting Cells metabolism, Linear Models, Liver metabolism, Blood Glucose metabolism, Diabetes Mellitus, Type 2 genetics, Genetic Variation physiology, Insulin genetics, Transcription Factor 7-Like 2 Protein physiology
Abstract

Understanding the physiological mechanisms by which common variants predispose to type 2 diabetes requires large studies with detailed measures of insulin secretion and sensitivity. Here we performed the largest genome-wide association study of first-phase insulin secretion, as measured by intravenous glucose tolerance tests, using up to 5,567 individuals without diabetes from 10 studies. We aimed to refine the mechanisms of 178 known associations between common variants and glycemic traits and identify new loci. Thirty type 2 diabetes or fasting glucose-raising alleles were associated with a measure of first-phase insulin secretion at P < 0.05 and provided new evidence, or the strongest evidence yet, that insulin secretion, intrinsic to the islet cells, is a key mechanism underlying the associations at the HNF1A , IGF2BP2 , KCNQ1 , HNF1B , VPS13C/C2CD4A , FAF1 , PTPRD , AP3S2 , KCNK16 , MAEA , LPP, WFS1 , and TMPRSS6 loci. The fasting glucose-raising allele near PDX1 , a known key insulin transcription factor, was strongly associated with lower first-phase insulin secretion but has no evidence for an effect on type 2 diabetes risk. The diabetes risk allele at TCF7L2 was associated with a stronger effect on peak insulin response than on C-peptide-based insulin secretion rate, suggesting a possible additional role in hepatic insulin clearance or insulin processing. In summary, our study provides further insight into the mechanisms by which common genetic variation influences type 2 diabetes risk and glycemic traits., (© 2017 by the American Diabetes Association.)

Published
2017
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