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12 results on '"Banasik, Karina"'

1. The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions

Author

Rahmioglu, Nilufer, Mortlock, Sally, Ghiasi, Marzieh, Møller, Peter L, Stefansdottir, Lilja, Galarneau, Geneviève, Turman, Constance, Danning, Rebecca, Law, Matthew H, Sapkota, Yadav, Christofidou, Paraskevi, Skarp, Sini, Giri, Ayush, Banasik, Karina, Krassowski, Michal, Lepamets, Maarja, Marciniak, Błażej, Nõukas, Margit, Perro, Danielle, Sliz, Eeva, Sobalska-Kwapis, Marta, Thorleifsson, Gudmar, Topbas-Selcuki, Nura F, Vitonis, Allison, Westergaard, David, Arnadottir, Ragnheidur, Burgdorf, Kristoffer S, Campbell, Archie, Cheuk, Cecilia SK, Clementi, Caterina, Cook, James, De Vivo, Immaculata, DiVasta, Amy, Dorien, O, Donoghue, Jacqueline F, Edwards, Todd, Fontanillas, Pierre, Fung, Jenny N, Geirsson, Reynir T, Girling, Jane E, Harkki, Paivi, Harris, Holly R, Healey, Martin, Heikinheimo, Oskari, Holdsworth-Carson, Sarah, Hostettler, Isabel C, Houlden, Henry, Houshdaran, Sahar, Irwin, Juan C, Jarvelin, Marjo-Riitta, Kamatani, Yoichiro, Kennedy, Stephen H, Kepka, Ewa, Kettunen, Johannes, Kubo, Michiaki, Kulig, Bartosz, Kurra, Venla, Laivuori, Hannele, Laufer, Marc R, Lindgren, Cecilia M, MacGregor, Stuart, Mangino, Massimo, Martin, Nicholas G, Matalliotaki, Charoula, Matalliotakis, Michail, Murray, Alison D, Ndungu, Anne, Nezhat, Camran, Olsen, Catherine M, Opoku-Anane, Jessica, Padmanabhan, Sandosh, Paranjpe, Manish, Peters, Maire, Polak, Grzegorz, Porteous, David J, Rabban, Joseph, Rexrode, Kathyrn M, Romanowicz, Hanna, Saare, Merli, Saavalainen, Liisu, Schork, Andrew J, Sen, Sushmita, Shafrir, Amy L, Siewierska-Górska, Anna, Słomka, Marcin, Smith, Blair H, Smolarz, Beata, Szaflik, Tomasz, Szyłło, Krzysztof, Takahashi, Atsushi, Terry, Kathryn L, Tomassetti, Carla, Treloar, Susan A, Vanhie, Arne, Vincent, Katy, Vo, Kim C, Werring, David J, Zeggini, Eleftheria, Zervou, Maria I, and Adachi, Sosuke

Subjects
Biological Sciences, Genetics, Contraception/Reproduction, Clinical Research, Endometriosis, Prevention, Pain Research, Chronic Pain, Infertility, 2.1 Biological and endogenous factors, Aetiology, Female, Humans, Genetic Predisposition to Disease, Genome-Wide Association Study, Pain, Comorbidity, DBDS Genomic Consortium, FinnGen Study, FinnGen Endometriosis Taskforce, Celmatix Research Team, 23andMe Research Team, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention.

Published
2023

2. Whole-Exome Sequencing of 2,000 Danish Individuals and the Role of Rare Coding Variants in Type 2 Diabetes

Author

Lohmueller, Kirk E, Sparsø, Thomas, Li, Qibin, Andersson, Ehm, Korneliussen, Thorfinn, Albrechtsen, Anders, Banasik, Karina, Grarup, Niels, Hallgrimsdottir, Ingileif, Kiil, Kristoffer, Kilpeläinen, Tuomas O, Krarup, Nikolaj T, Pers, Tune H, Sanchez, Gaston, Hu, Youna, DeGiorgio, Michael, Jørgensen, Torben, Sandbæk, Annelli, Lauritzen, Torsten, Brunak, Søren, Kristiansen, Karsten, Li, Yingrui, Hansen, Torben, Wang, Jun, Nielsen, Rasmus, and Pedersen, Oluf

Subjects
Biological Sciences, Genetics, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Published
2014

3. Whole-Exome Sequencing of 2,000 Danish Individuals and the Role of Rare Coding Variants in Type 2 Diabetes

Author

Lohmueller, Kirk E, Sparsø, Thomas, Li, Qibin, Andersson, Ehm, Korneliussen, Thorfinn, Albrechtsen, Anders, Banasik, Karina, Grarup, Niels, Hallgrimsdottir, Ingileif, Kiil, Kristoffer, Kilpeläinen, Tuomas O, Krarup, Nikolaj T, Pers, Tune H, Sanchez, Gaston, Hu, Youna, DeGiorgio, Michael, Jørgensen, Torben, Sandbæk, Annelli, Lauritzen, Torsten, Brunak, Søren, Kristiansen, Karsten, Li, Yingrui, Hansen, Torben, Wang, Jun, Nielsen, Rasmus, and Pedersen, Oluf

Subjects
Human Genome, Genetic Testing, Diabetes, Biotechnology, Cardiovascular, Genetics, Autoimmune Disease, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Computational Biology, Denmark, Diabetes Mellitus, Type 2, Exome, Genetic Association Studies, Genetic Variation, Genotype, High-Throughput Nucleotide Sequencing, Humans, Models, Statistical, Open Reading Frames, Polymorphism, Single Nucleotide, White People, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

It has been hypothesized that, in aggregate, rare variants in coding regions of genes explain a substantial fraction of the heritability of common diseases. We sequenced the exomes of 1,000 Danish cases with common forms of type 2 diabetes (including body mass index > 27.5 kg/m(2) and hypertension) and 1,000 healthy controls to an average depth of 56×. Our simulations suggest that our study had the statistical power to detect at least one causal gene (a gene containing causal mutations) if the heritability of these common diseases was explained by rare variants in the coding regions of a limited number of genes. We applied a series of gene-based tests to detect such susceptibility genes. However, no gene showed a significant association with disease risk after we corrected for the number of genes analyzed. Thus, we could reject a model for the genetic architecture of type 2 diabetes where rare nonsynonymous variants clustered in a modest number of genes (fewer than 20) are responsible for the majority of disease risk.

Published
2013

4. Genetic Variants Close to TTN , NKX2-5 , and MYH6 Associate With AVNRT

Author

Andreasen, Laura, Ahlberg, Gustav, Ægisdóttir, Hildur M., Sveinbjörnsson, Gardar, Lundegaard, Pia R., Hartmann, Jacob P., Paludan-Müller, Christian, Hadji-Turdeghal, Katra, Ghouse, Jonas, Pehrson, Steen, Jensen, Henrik K., Riahi, Sam, Hansen, Jim, Sandgaard, Niels, Sørensen, Erik, Banasik, Karina, Sækmose, Susanne G., Bruun, Mie T., Hjalgrim, Henrik, Erikstrup, Christian, Pedersen, Ole B., Wittig, Michael, Haunsø, Stig, Ostrowski, Sisse R., Genomic Consortium, Dbds, Franke, Andre, Brunak, Søren, Kanters, Jørgen K., Ellervik, Christina, Bundgaard, Henning, Ullum, Henrik, Gudbjartsson, Daniel F., Thorsteinsdottir, Unnur, Holm, Hilma, Arnar, David O., Stefansson, Kari, Svendsen, Jesper H., and Olesen, Morten S.

Subjects
Electrocardiography, supraventricular tachycardia, Heart Conduction System, Physiology, atrioventricular nodal reentry tachycardia, atrioventricular node, genetics, Cardiology and Cardiovascular Medicine
Published
2022
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5. Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration

Author

Wilman, Henry R., Parisinos, Constantinos A., Atabaki-Pasdar, Naeimeh, Kelly, Matt, Thomas, E. Louise, Neubauer, Stefan, Jennison, Christopher, Ehrhardt, Beate, Baum, Patrick, Schoelsch, Corinna, Freijer, Jan, Grempler, Rolf, Graefe-Mody, Ulrike, Hennige, Anita, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinecich, Iryna, Pattou, Francois, Raverdi, Violeta, Caiazzo, Robert, Torres, Fanelly, Verkindt, Helene, Mari, Andrea, Tura, Andrea, Giorgino, Toni, Bizzotto, Roberto, Froguel, Philippe, Bonneford, Amelie, Canouil, Mickael, Dhennin, Veronique, Brorsson, Caroline, Brunak, Soren, De Masi, Federico, Gudmundsdóttir, Valborg, Pedersen, Helle, Banasik, Karina, Thomas, Cecilia, Sackett, Peter, Staerfeldt, Hans Henrik, Lundgaard, Agnete, Nilsson, Birgitte, Nielsen, Agnes, Mazzoni, Gianluca, Karaderi, Tugce, Rasmussen, Simon, Johansen, Joachim, Allesøe, Rosa, Fritsche, Andreas, Thorand, Barbara, Adamski, Jurek, Grallert, Harald, Haid, Mark, Sharma, Sapna, Troll, Martina, Adam, Jonathan, Ferrer, Jorge, Eriksen, Heather, Frost, Gary, Haussler, Ragna, Hong, Mun gwan, Schwenk, Jochen, Uhlen, Mathias, Nicolay, Claudia, Pavo, Imre, Steckel-Hamann, Birgit, Thomas, Melissa, Adragni, Kofi, Wu, Han, Hart, Leen't, Roderick, Slieker, van Leeuwen, Nienke, Dekkers, Koen, Frau, Francesca, Gassenhuber, Johann, Jablonka, Bernd, Musholt, Petra, Ruetten, Hartmut, Tillner, Joachim, Baltauss, Tania, Bernard Poenaru, Oana, de Preville, Nathalie, Rodriquez, Marianne, Arumugam, Manimozhiyan, Allin, Kristine, Engelbrechtsen, Line, Hansen, Torben, Hansen, Tue, Forman, Annemette, Jonsson, Anna, Pedersen, Oluf, Dutta, Avirup, Vogt, Josef, Vestergaard, Henrik, Laakso, Markku, Kokkola, Tarja, Kuulasmaa, Teemu, Franks, Paul, Giordano, Nick, and Pomares-Millan, Hugo

Subjects
Genome-wide association study, Magnetic resonance imaging, Metabolism, Iron, Genetics, Metabolic syndrome
Abstract

Background & Aims: Excess liver iron content is common and is linked to the risk of hepatic and extrahepatic diseases. We aimed to identify genetic variants influencing liver iron content and use genetics to understand its link to other traits and diseases. Methods: First, we performed a genome-wide association study (GWAS) in 8,289 individuals from UK Biobank, whose liver iron level had been quantified by magnetic resonance imaging, before validating our findings in an independent cohort (n = 1,513 from IMI DIRECT). Second, we used Mendelian randomisation to test the causal effects of 25 predominantly metabolic traits on liver iron content. Third, we tested phenome-wide associations between liver iron variants and 770 traits and disease outcomes. Results: We identified 3 independent genetic variants (rs1800562 [C282Y] and rs1799945 [H63D] in HFE and rs855791 [V736A] in TMPRSS6) associated with liver iron content that reached the GWAS significance threshold (p

Published
2019
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6. The effect of FOXA2 rs1209523 on glucose-related phenotypes and risk of type 2 diabetes in Danish individuals

Author

Banasik Karina, Hollensted Mette, Andersson Ehm, Sparsø Thomas, Sandbæk Annelli, Lauritzen Torsten, Jørgensen Torben, Witte Daniel R, Pedersen Oluf, and Hansen Torben

Subjects
Internal medicine, RC31-1245, Genetics, QH426-470
Abstract

Abstract Background Variations within the FOXA family have been studied for a putative contribution to the risk of type 2 diabetes (T2D), and recently the minor T-allele of FOXA2 rs1209523 was reported to associate with decreased fasting plasma glucose levels in a study using a weighted false discovery rate control procedure to enhance the statistical power of genome wide association studies in detecting associations between low-frequency variants and a given trait. Thus, the primary aim of this study was to investigate whether the minor T-allele of rs1205923 in FOXA2 associated with 1) decreased fasting plasma glucose and 2) a lower risk of developing T2D. Secondly, we investigated whether rs1205923 in FOXA2 associated with other glucose-related phenotypes. Methods The variant was genotyped in Danish individuals from four different study populations using KASPar® PCR SNP genotyping system. We examined for associations of the FOXA2 genotype with fasting plasma glucose and estimates of insulin release and insulin sensitivity following an oral glucose tolerance test in 6,162 Danish individuals from the population-based Inter99 study while association with T2D risk was assessed in 10,196 Danish individuals including four different study populations. Results The FOXA2 rs1209523 was not associated with fasting plasma glucose (effect size (β) = -0.03 mmol/l (95%CI: -0.07; 0.01), p = 0.2) in glucose-tolerant individuals from the general Danish population. Furthermore, when employing a case-control setting the variant showed no association with T2D (odds ratio (OR) = 0.82 (95%CI: 0.62-1.07), p = 0.1) among Danish individuals. However, when we performed the analysis in a subset of 6,022 non-obese individuals (BMI < 30 kg/m2) an association with T2D was observed (OR = 0.68 (95%CI: 0.49-0.94), p = 0.02). Also, several indices of insulin release and β-cell function were associated with the minor T-allele of FOXA2 rs1209523 in non-obese individuals. Conclusions We failed to replicate association of the minor T-allele of FOXA2 rs1209523 with fasting plasma glucose in a population based sample of glucose tolerant individuals. More extensive studies are needed in order to fully elucidate the potential role of FOXA2 in glucose homeostasis.

Published
2012
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7. The minor C-allele of rs2014355 in ACADS is associated with reduced insulin release following an oral glucose load

Author

Pisinger Charlotta, Lauritzen Torsten, Sandbæk Annelli, Andersson Åsa, Sandholt Camilla H, Krarup Nikolaj T, Justesen Johanne M, Banasik Karina, Hornbak Malene, Witte Daniel R, Sørensen Thorkild IA, Pedersen Oluf, and Hansen Torben

Subjects
Internal medicine, RC31-1245, Genetics, QH426-470
Abstract

Abstract Background A genome-wide association study (GWAS) using metabolite concentrations as proxies for enzymatic activity, suggested that two variants: rs2014355 in the gene encoding short-chain acyl-coenzyme A dehydrogenase (ACADS) and rs11161510 in the gene encoding medium-chain acyl-coenzyme A dehydrogenase (ACADM) impair fatty acid β-oxidation. Chronic exposure to fatty acids due to an impaired β-oxidation may down-regulate the glucose-stimulated insulin release and result in an increased risk of type 2 diabetes (T2D). We aimed to investigate whether the two variants associate with altered insulin release following an oral glucose load or with T2D. Methods The variants were genotyped using KASPar® PCR SNP genotyping system and investigated for associations with estimates of insulin release and insulin sensitivity following an oral glucose tolerance test (OGTT) in a random sample of middle-aged Danish individuals (nACADS = 4,324; nACADM = 4,337). The T2D-case-control study involved a total of ~8,300 Danish individuals (nACADS = 8,313; nACADM = 8,344). Results In glucose-tolerant individuals the minor C-allele of rs2014355 of ACADS associated with reduced measures of serum insulin at 30 min following an oral glucose load (per allele effect (β) = -3.8% (-6.3%;-1.3%), P = 0.003), reduced incremental area under the insulin curve (β = -3.6% (-6.3%;-0.9%), P = 0.009), reduced acute insulin response (β = -2.2% (-4.2%;0.2%), P = 0.03), and with increased insulin sensitivity ISIMatsuda (β = 2.9% (0.5%;5.2%), P = 0.02). The C-allele did not associate with two other measures of insulin sensitivity or with a derived disposition index. The C-allele was not associated with T2D in the case-control analysis (OR 1.07, 95% CI 0.96-1.18, P = 0.21). rs11161510 of ACADM did not associate with any indices of glucose-stimulated insulin release or with T2D. Conclusions In glucose-tolerant individuals the minor C-allele of rs2014355 of ACADS was associated with reduced measures of glucose-stimulated insulin release during an OGTT, a finding which in part may be mediated through an impaired β-oxidation of fatty acids.

Published
2011
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8. The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study

Author

Winkler, Thomas W, Justice, Anne E, Graff, Mariaelisa, Barata, Llilda, Feitosa, Mary F, Chu, Su, Czajkowski, Jacek, Esko, Tõnu, Fall, Tove, Kilpeläinen, Tuomas O, Lu, Yingchang, Mägi, Reedik, Mihailov, Evelin, Pers, Tune H, Rüeger, Sina, Teumer, Alexander, Ehret, Georg B, Ferreira, Teresa, Heard-Costa, Nancy L, Karjalainen, Juha, Lagou, Vasiliki, Mahajan, Anubha, Neinast, Michael D, Prokopenko, Inga, Simino, Jeannette, Teslovich, Tanya M, Jansen, Rick, Westra, Harm-Jan, White, Charles C, Absher, Devin, Ahluwalia, Tarunveer S, Ahmad, Shafqat, Albrecht, Eva, Alves, Alexessander Couto, Bragg-Gresham, Jennifer L, de Craen, Anton JM, Bis, Joshua C, Bonnefond, Amélie, Boucher, Gabrielle, Cadby, Gemma, Cheng, Yu-Ching, Chiang, Charleston WK, Delgado, Graciela, Demirkan, Ayse, Dueker, Nicole, Eklund, Niina, Eiriksdottir, Gudny, Eriksson, Joel, Feenstra, Bjarke, Fischer, Krista, Frau, Francesca, Galesloot, Tessel E, Geller, Frank, Goel, Anuj, Gorski, Mathias, Grammer, Tanja B, Gustafsson, Stefan, Haitjema, Saskia, Hottenga, Jouke-Jan, Huffman, Jennifer E, Jackson, Anne U, Jacobs, Kevin B, Johansson, Åsa, Kaakinen, Marika, Kleber, Marcus E, Lahti, Jari, Mateo Leach, Irene, Lehne, Benjamin, Liu, Youfang, Lo, Ken Sin, Lorentzon, Mattias, Luan, Jian'an, Madden, Pamela AF, Mangino, Massimo, McKnight, Barbara, Medina-Gomez, Carolina, Monda, Keri L, Montasser, May E, Müller, Gabriele, Müller-Nurasyid, Martina, Nolte, Ilja M, Panoutsopoulou, Kalliope, Pascoe, Laura, Paternoster, Lavinia, Rayner, Nigel W, Renström, Frida, Rizzi, Federica, Rose, Lynda M, Ryan, Kathy A, Salo, Perttu, Sanna, Serena, Scharnagl, Hubert, Shi, Jianxin, Smith, Albert Vernon, Southam, Lorraine, Stančáková, Alena, Steinthorsdottir, Valgerdur, Strawbridge, Rona J, Sung, Yun Ju, Tachmazidou, Ioanna, Tanaka, Toshiko, Thorleifsson, Gudmar, Trompet, Stella, Pervjakova, Natalia, Tyrer, Jonathan P, Vandenput, Liesbeth, van der Laan, Sander W, van der Velde, Nathalie, van Setten, Jessica, van Vliet-Ostaptchouk, Jana V, Verweij, Niek, Vlachopoulou, Efthymia, Waite, Lindsay L, Wang, Sophie R, Wang, Zhaoming, Wild, Sarah H, Willenborg, Christina, Wilson, James F, Wong, Andrew, Yang, Jian, Yengo, Loïc, Yerges-Armstrong, Laura M, Yu, Lei, Zhang, Weihua, Zhao, Jing Hua, Andersson, Ehm A, Bakker, Stephan JL, Baldassarre, Damiano, Banasik, Karina, Barcella, Matteo, Barlassina, Cristina, Bellis, Claire, Benaglio, Paola, Blangero, John, Blüher, Matthias, Bonnet, Fabrice, Bonnycastle, Lori L, Boyd, Heather A, Bruinenberg, Marcel, Buchman, Aron S, Campbell, Harry, Chen, Yii-Der Ida, Chines, Peter S, Claudi-Boehm, Simone, Cole, John, Collins, Francis S, de Geus, Eco JC, de Groot, Lisette CPGM, Dimitriou, Maria, Duan, Jubao, Enroth, Stefan, Eury, Elodie, Farmaki, Aliki-Eleni, Forouhi, Nita G, Friedrich, Nele, Gejman, Pablo V, Gigante, Bruna, Glorioso, Nicola, Go, Alan S, Gottesman, Omri, Gräßler, Jürgen, Grallert, Harald, Grarup, Niels, Gu, Yu-Mei, Broer, Linda, Ham, Annelies C, Hansen, Torben, Harris, Tamara B, Hartman, Catharina A, Hassinen, Maija, Hastie, Nicholas, Hattersley, Andrew T, Heath, Andrew C, Henders, Anjali K, Hernandez, Dena, Hillege, Hans, Holmen, Oddgeir, Hovingh, Kees G, Hui, Jennie, Husemoen, Lise L, Hutri-Kähönen, Nina, Hysi, Pirro G, Illig, Thomas, De Jager, Philip L, Jalilzadeh, Shapour, Jørgensen, Torben, Jukema, J Wouter, Juonala, Markus, Kanoni, Stavroula, Karaleftheri, Maria, Khaw, Kay Tee, Kinnunen, Leena, Kittner, Steven J, Koenig, Wolfgang, Kolcic, Ivana, Kovacs, Peter, Krarup, Nikolaj T, Kratzer, Wolfgang, Krüger, Janine, Kuh, Diana, Kumari, Meena, Kyriakou, Theodosios, Langenberg, Claudia, Lannfelt, Lars, Lanzani, Chiara, Lotay, Vaneet, Launer, Lenore J, Leander, Karin, Lindström, Jaana, Linneberg, Allan, Liu, Yan-Ping, Lobbens, Stéphane, Luben, Robert, Lyssenko, Valeriya, Männistö, Satu, Magnusson, Patrik K, McArdle, Wendy L, Menni, Cristina, Merger, Sigrun, Milani, Lili, Montgomery, Grant W, Morris, Andrew P, Narisu, Narisu, Nelis, Mari, Ong, Ken K, Palotie, Aarno, Pérusse, Louis, Pichler, Irene, Pilia, Maria G, Pouta, Anneli, Rheinberger, Myriam, Ribel-Madsen, Rasmus, Richards, Marcus, Rice, Kenneth M, Rice, Treva K, Rivolta, Carlo, Salomaa, Veikko, Sanders, Alan R, Sarzynski, Mark A, Scholtens, Salome, Scott, Robert A, Scott, William R, Sebert, Sylvain, Sengupta, Sebanti, Sennblad, Bengt, Seufferlein, Thomas, Silveira, Angela, Slagboom, P Eline, Smit, Jan H, Sparsø, Thomas H, Stirrups, Kathleen, Stolk, Ronald P, Stringham, Heather M, Swertz, Morris A, Swift, Amy J, Syvänen, Ann-Christine, Tan, Sian-Tsung, Thorand, Barbara, Tönjes, Anke, Tremblay, Angelo, Tsafantakis, Emmanouil, van der Most, Peter J, Völker, Uwe, Vohl, Marie-Claude, Vonk, Judith M, Waldenberger, Melanie, Walker, Ryan W, Wennauer, Roman, Widén, Elisabeth, Willemsen, Gonneke, Wilsgaard, Tom, Wright, Alan F, Zillikens, M Carola, van Dijk, Suzanne C, van Schoor, Natasja M, Asselbergs, Folkert W, de Bakker, Paul IW, Beckmann, Jacques S, Beilby, John, Bennett, David A, Bergman, Richard N, Bergmann, Sven, Böger, Carsten A, Boehm, Bernhard O, Boerwinkle, Eric, Boomsma, Dorret I, Bornstein, Stefan R, Bottinger, Erwin P, Bouchard, Claude, Chambers, John C, Chanock, Stephen J, Chasman, Daniel I, Cucca, Francesco, Cusi, Daniele, Dedoussis, George, Erdmann, Jeanette, Eriksson, Johan G, Evans, Denis A, de Faire, Ulf, Farrall, Martin, Ferrucci, Luigi, Ford, Ian, Franke, Lude, Franks, Paul W, Froguel, Philippe, Gansevoort, Ron T, Gieger, Christian, Grönberg, Henrik, Gudnason, Vilmundur, Gyllensten, Ulf, Hall, Per, Hamsten, Anders, van der Harst, Pim, Hayward, Caroline, Heliövaara, Markku, Hengstenberg, Christian, Hicks, Andrew A, Hingorani, Aroon, Hofman, Albert, Hu, Frank, Huikuri, Heikki V, Hveem, Kristian, James, Alan L, Jordan, Joanne M, Jula, Antti, Kähönen, Mika, Kajantie, Eero, Kathiresan, Sekar, Kiemeney, Lambertus ALM, Kivimaki, Mika, Knekt, Paul B, Koistinen, Heikki A, Kooner, Jaspal S, Koskinen, Seppo, Kuusisto, Johanna, Maerz, Winfried, Martin, Nicholas G, Laakso, Markku, Lakka, Timo A, Lehtimäki, Terho, Lettre, Guillaume, Levinson, Douglas F, Lind, Lars, Lokki, Marja-Liisa, Mäntyselkä, Pekka, Melbye, Mads, Metspalu, Andres, Mitchell, Braxton D, Moll, Frans L, Murray, Jeffrey C, Musk, Arthur W, Nieminen, Markku S, Njølstad, Inger, Ohlsson, Claes, Oldehinkel, Albertine J, Oostra, Ben A, Palmer, Lyle J, Pankow, James S, Pasterkamp, Gerard, Pedersen, Nancy L, Pedersen, Oluf, Penninx, Brenda W, Perola, Markus, Peters, Annette, Polašek, Ozren, Pramstaller, Peter P, Psaty, Bruce M, Qi, Lu, Quertermous, Thomas, Raitakari, Olli T, Rankinen, Tuomo, Rauramaa, Rainer, Ridker, Paul M, Rioux, John D, Rivadeneira, Fernando, Rotter, Jerome I, Rudan, Igor, den Ruijter, Hester M, Saltevo, Juha, Sattar, Naveed, Schunkert, Heribert, Schwarz, Peter EH, Shuldiner, Alan R, Sinisalo, Juha, Snieder, Harold, Sørensen, Thorkild IA, Spector, Tim D, Staessen, Jan A, Stefania, Bandinelli, Thorsteinsdottir, Unnur, Stumvoll, Michael, Tardif, Jean-Claude, Tremoli, Elena, Tuomilehto, Jaakko, Uitterlinden, André G, Uusitupa, Matti, Verbeek, André LM, Vermeulen, Sita H, Viikari, Jorma S, Vitart, Veronique, Völzke, Henry, Vollenweider, Peter, Waeber, Gérard, Walker, Mark, Wallaschofski, Henri, Wareham, Nicholas J, Watkins, Hugh, Zeggini, Eleftheria, arcOGEN Consortium, CHARGE Consortium, DIAGRAM Consortium, GLGC Consortium, Global-BPGen Consortium, ICBP Consortium, MAGIC Consortium, Chakravarti, Aravinda, Clegg, Deborah J, Cupples, L Adrienne, Gordon-Larsen, Penny, Jaquish, Cashell E, Rao, DC, Abecasis, Goncalo R, Assimes, Themistocles L, Barroso, Inês, Berndt, Sonja I, Boehnke, Michael, Deloukas, Panos, Fox, Caroline S, Groop, Leif C, Hunter, David J, Ingelsson, Erik, Kaplan, Robert C, McCarthy, Mark I, Mohlke, Karen L, O'Connell, Jeffrey R, Schlessinger, David, Strachan, David P, Stefansson, Kari, van Duijn, Cornelia M, Hirschhorn, Joel N, Lindgren, Cecilia M, Heid, Iris M, North, Kari E, Borecki, Ingrid B, Kutalik, Zoltán, Loos, Ruth JF, Division of Statistical Genomics, Washington University School of Medicine, Institut Pasteur du Cambodge, Réseau International des Instituts Pasteur (RIIP), Estonian Genome and Medicine, University of Tartu, Institute of Molecular and Cell Biology, Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet [Stockholm], Institute of Metabolic Science, MRC, Brown University, Center for Biological Sequence Analysis [Lyngby], Technical University of Denmark [Lyngby] (DTU), King‘s College London, Groningen Bioinformatics Centre, GBB, University of Groningen [Groningen], University of Queensland [Brisbane], National Institut of Food Science and Technology, University of Agriculture, Department of Biostatistics and Center for Statistical Genetics, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Department of neurology, Leiden University Medical Center (LUMC), University of Washington [Seattle], Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (GI3M), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Genetic Epidemiology Unit, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Deptartment of Medical Biochemistry and Microbiology, Uppsala University, Infectious diseases division, Department of internal medicine, Washington University in Saint Louis (WUSTL), Limnology, Ecology, Department of Ecology and Evolutionary Biology, University of California, Core Genotyping Facility, National Cancer Institute [Bethesda] (NCI-NIH), National Institutes of Health [Bethesda] (NIH)-National Institutes of Health [Bethesda] (NIH), Division of Cancer Epidemiology and Genetics, Institute of Health Sciences and Biocenter Oulu, University of Oulu, Department of Chemical Engineering Taiwan (DCET - NTHU), National Tsing Hua University [Hsinchu] (NTHU), University of Oxford [Oxford], Department of Epidemiology, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), Human Genetics, The Wellcome Trust Sanger Institute [Cambridge], Departments of Epidemiology and Nutrition, Harvard School of Public Health, Department of Clinical Sciences, Lund University [Lund]-Lund University Diabetes Centre, Genetic Epidemiology and Clinical Research Group, Umea University Hospital, Department of Medicine, University of Eastern Finland-Kuopio University Hospital, Department of Medical Sciences, Department of Educational Psychology and Counseling, National Taiwan Normal University (NTNU), Laboratory for Cardiovascular Genomics and Informatics [Yokohama] (RIKEN IMS), RIKEN Center for Integrative Medical Sciences [Yokohama] (RIKEN IMS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN)-RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), deCODE Genetics, deCODE genetics [Reykjavik], Interuniversity Cardiology Institute Netherlands, Molecular Genetics Section, University of Groningen [Groningen]-University Medical Centre Groningen, Kidney Center, University Medical Center Groningen [Groningen] (UMCG), The University of Texas Health Science Center at Houston (UTHealth), Texas Biomedical Research Institute [San Antonio, TX], Medical Department III, Universität Leipzig [Leipzig], Foie, métabolismes et cancer, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Dept. of Epidemiology Research, Statens Serum Institut [Copenhagen], GNS Science, Blackett Laboratory, Imperial College London, Medstar Research Institute, University of Rochester [USA], MRC Epidemiology Unit, University of Cambridge [UK] (CAM)-Institute of Metabolic Science, Institute of Epidemiology [Neuherberg] (EPI), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR), Faculty of Health and Medical Sciences, University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU), Dept Biochem & Mol Biol, Pennsylvania State University (Penn State), Penn State System-Penn State System, Genomic Research Laboratory, Service of Infectious Disease, Hôpitaux Universitaires de Genève (HUG), Epidemiology, University Medical Centre Groningen, Unit for Molecular Epidemiology, German Research Center for Environmental Health-Helmholtz-Zentrum München (HZM), Program in Translational NeuroPsychiatric Genomics, Brigham and Women's Hospital [Boston], Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA, Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Harvard Medical School [Boston] (HMS), Research Centre for Prevention and Health (RCPH), Department of Public Health [Copenhagen], University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU)-Faculty of Health and Medical Sciences, University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU)-Capital Region of Denmark, University of Copenhagen = Københavns Universitet (KU), Faculty of Medicine, Institute of Public Health, Aalborg University [Denmark] (AAU), Department of Nutrition-Dietetics, Harokopio University of Athens, Department of Medical Statistics, Epidemiology and Medical Informatics, University of Zagreb, MRC National Survey of Health and Development, MRC Unit for Lifelong Health and Ageing, Department of Epidemiology and Public Health, University College of London [London] (UCL), Department of Public health and Caring Sciences, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden, Research Center for Prevention and Health, Glostrup Hospital, Génétique des maladies multifactorielles (GMM), Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), Cambridge Institute of Public Health, University of Cambridge [UK] (CAM), Chronic Disease Epidemiology and Prevention Unit, National Institute for Health and Welfare [Helsinki], Queensland Institute of Medical Research, Medical Research Council Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Head of Medical Sequencing, Department of Biostatistics, University of Washington, Department of Chronic Disease Prevention, Molecular Epidemiology, Department of Genetics, Université Laval [Québec] (ULaval), Interfaculty Institute for Genetics and Functional Genomics, Universität Greifswald - University of Greifswald, Netherlands Genomics Initiative, Netherlands Consortium for Healthy Aging [Leiden, Netherlands] (NCHA), Department of Internal Medicine, Université de Lausanne (UNIL), Carl Gustav Carus University Hospital, Loughborough University, Genomics and Bioinformatics Platform, Fondazione Filarete, Department of Medicine, Surgery, and Dentistry, University of Milano, Medizinische Klinik II, Universität zu Lübeck [Lübeck], Department of Genomic Medicine, University of Manchester [Manchester], The Wellcome Trust Centre for Human Genetics [Oxford], National Institutes of Health [Bethesda] (NIH), Department of Nephrology, University Medical Center, University of Groningen, Helmholtz-Zentrum München (HZM), Icelandic Heart Association, Kopavogur, Iceland., Faculty of Medicine, University of Iceland [Reykjavik], Genetics and Pathology, Department of child and adolescent psychiatry, Universität Duisburg-Essen [Essen], Department of Internal Medicine II, Division of Respirology, University of Regensburg, Regensburg, Germany, Universität Regensburg (UR), Franz-Volhard-Centrum für Klinische Forschung, ECRC, Department of Clinical Physiology, University of Tampere [Finland]-Tampere University Hospital, Finnish Institute of Occupational Health of Helsinki, Department of Clinical Chemistry, Faculty of Medecine [Helsinki], University of Helsinki-University of Helsinki, Department of Oncology, University of Tampere Medical School, University of Tampere, Department of Physiology, University of Eastern Finland-Institute of Biomedicine, Department of Medicine, Montreal, Developmental Brain and Behaviour Unit, University of Southampton, Division of Gastroenterology and Hepatology, Department of Immunology, Mayo Clinic, Centre for Bone and Arthritis Research, Institute of Medicine-University of Gothenburg (GU), Interdisciplinary Center for Psychiatric Epidemiology, Experimental Cardiology Laboratory, University Medical Center [Utrecht], Peter MacCallum Cancer Center, Faculty of Health Sciences, Aarhus University [Aarhus], Institute for Molecular Medicine Finland [Helsinki] (FIMM), Helsinki Institute of Life Science (HiLIFE), Department of Health Services, University of Washington, Group Health Research Institute, Group Health Cooperative, Department of Epidemiology, University of Washington, Department of Medicine, University of Washington, Cardiovascular Health Research Unit, University of Washington, The Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku University Hospital (TYKS), Erasmus Medical Centre, Cedars-Sinai Medical Center, Department of Pathological Biochemistry, Royal Infirmary, Unit of Genetic Epidemiology and Bioinformatics, Department of Epidemiology, University Medical Center Groningen, Department of Pediatrics, Augusta University - Medical College of Georgia, University System of Georgia (USG)-University System of Georgia (USG), Institute of Preventive Medicine, Copenhagen University Hospital-Bispebjerg and Frederiksberg Hospitals, Maastricht University [Maastricht], Department of Public Health, South Ostrobothnia Central Hospital, Department of Clinical and Preventive Medicine, Danube-University Krems, Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Department of Epidemiology & Biostatistics, Radboud University Medical Center [Nijmegen], Institute for Community Medicine, Centre Hospitalier Universitaire Vaudois [Lausanne] (CHUV), MRC epidemiology Unit, Framingham Heart Study, National Heart, Lung, and Blood Institute [Bethesda] (NHLBI)-Boston University [Boston] (BU), Metabolic Disease Group, University of Cambridge Metabolic Research Laboratories, Department of Genetics and Biotechnology, Wellcome Trust, Divisions of Genetics and Endocrinology and Program in Genomics, Boston Children's Hospital, Metabolism Initiative and Program in Medical and Population Genetics, Endocrinology and Metabolism, The Churchill Hospital-Oxford Centre for Diabetes, Department of Epidemiology and Preventive Medicine, Regensburg University Medical Center, University of North Carolina System (UNC)-University of North Carolina System (UNC)-UNC Gillings School of Global Public Health-Carolina Center for Genome Sciences, Department of Medical Genetics, Epidemiology Unit, Addenbrooke's Hospital-Medical Research Council (MRC), P30 AG010161/AG/NIA NIH HHS/United States, Psychiatry, Epidemiology and Data Science, NCA - Neurobiology of mental health, EMGO - Lifestyle, overweight and diabetes, APH - Amsterdam Public Health, AMS - Amsterdam Movement Sciences, Geriatrics, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, Other departments, Biological Psychology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, EMGO+ - Lifestyle, Overweight and Diabetes, RS: CARIM - R3 - Vascular biology, MUMC+: DA BV AIOS Radiologie (9), Epidemiologie, Orthopedie, Institute for Molecular Medicine Finland, Helsinki Collegium for Advanced Studies, Behavioural Sciences, University of Helsinki, Transplantation Laboratory, Medicum, Research Programs Unit, Research Programme of Molecular Medicine, Aarno Palotie / Principal Investigator, Elisabeth Ingrid Maria Widen / Principal Investigator, Clinicum, Johan Eriksson / Principal Investigator, Department of General Practice and Primary Health Care, Children's Hospital, Lastentautien yksikkö, Marja-Liisa Lokki / Principal Investigator, Kardiologian yksikkö, Leif Groop Research Group, Quantitative Genetics, Developmental Psychology Research Group, Genomics of Neurological and Neuropsychiatric Disorders, Genomic Discoveries and Clinical Translation, Ehret, Georg Benedikt, Danmarks Tekniske Universitet = Technical University of Denmark (DTU), Universiteit Leiden-Universiteit Leiden, Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (EGENODIA (GI3M)), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), University of California (UC), University of Oxford, Lund University [Lund], Universität Leipzig, Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH), Helmholtz Zentrum München = German Research Center for Environmental Health, University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH)-Faculty of Health and Medical Sciences, University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH)-Capital Region of Denmark, University of Copenhagen = Københavns Universitet (UCPH), Université de Lausanne = University of Lausanne (UNIL), Universität zu Lübeck = University of Lübeck [Lübeck], Universität Duisburg-Essen = University of Duisburg-Essen [Essen], Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, University of Gothenburg (GU)-Institute of Medicine, Boston University [Boston] (BU)-National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), Luan, Jian'an [0000-0003-3137-6337], Tyrer, Jonathan [0000-0003-3724-4757], Forouhi, Nita [0000-0002-5041-248X], Khaw, Kay-Tee [0000-0002-8802-2903], Langenberg, Claudia [0000-0002-5017-7344], Luben, Robert [0000-0002-5088-6343], Ong, Kenneth [0000-0003-4689-7530], Johnson, Kathleen [0000-0002-6823-3252], Wareham, Nicholas [0000-0003-1422-2993], Barroso, Ines [0000-0001-5800-4520], Apollo - University of Cambridge Repository, CHARGE Consortium, DIAGRAM Consortium, GLGC Consortium, Global-BPGen Consortium, ICBP Consortium, MAGIC Consortium, Biochemistry, Surgery, Internal Medicine, Public Health, Medical Oncology, Pathology, Erasmus MC other, Child and Adolescent Psychiatry / Psychology, and Clinical Genetics

Subjects
0301 basic medicine, Netherlands Twin Register (NTR), Male, Cancer Research, endocrine system diseases, Biological pathways, QH426-470, Genome, Body Mass Index, Body Size, Genetics (clinical), ddc:616, Genetics & Heredity, Sex Characteristics, Loci, MAGIC Consortium, Mass index, Age Factors, Chromosome Mapping, Middle Aged, Genealogy, Self-reported height, Peripheral-blood, Scale (social sciences), ICBP Consortium, Female, Life Sciences & Biomedicine, Medical Genetics, Research Article, arcOGEN Consortium, musculoskeletal diseases, Adult, European Continental Ancestry Group, Natural menopause, Aged, Body Size/genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Waist-Hip Ratio, Biology, Body size, DIAGRAM Consortium, Age and sex, White People, Fat distribution, GLGC Consortium, 03 medical and health sciences, Life-course, Genetics, Weight-gain, Molecular Biology, Ecology, Evolution, Behavior and Systematics, Medicinsk genetik, [SDV.GEN]Life Sciences [q-bio]/Genetics, 0604 Genetics, Science & Technology, nutritional and metabolic diseases, Correction, 030104 developmental biology, GWAS meta-analysis, Global-BPGen Consortium, Common SNPS, CHARGE Consortium, 3111 Biomedicine, Developmental Biology
Abstract

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR, Author Summary Adult body size and body shape differ substantially between men and women and change over time. More than 100 genetic variants that influence body mass index (measure of body size) or waist-to-hip ratio (measure of body shape) have been identified. While there is evidence that some genetic loci affect body shape differently in men than in women, little is known about whether genetic effects differ in older compared to younger adults, and whether such changes differ between men and women. Therefore, we conducted a systematic genome-wide search, including 114 studies (>320,000 individuals), to specifically identify genetic loci with age- and or sex-dependent effects on body size and shape. We identified 15 loci of which the effect on BMI was different in older compared to younger adults, whereas we found no evidence for loci with different effects in men compared to women. The opposite was seen for body shape as we identified 44 loci of which the effect on waist-to-hip ratio differed between men and women, but no difference between younger and older adults were observed. Our observations may provide new insights into the biology that underlies weight change with age or the sexual dimorphism of body shape.

Published
2014
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9. Integrative network analysis highlights biological processes underlying GLP-1 stimulated insulin secretion: A DIRECT study.

Author

Gudmundsdottir, Valborg, Pedersen, Helle Krogh, Allebrandt, Karla Viviani, Brorsson, Caroline, van Leeuwen, Nienke, Banasik, Karina, Mahajan, Anubha, Groves, Christopher J., van de Bunt, Martijn, Dawed, Adem Y., Fritsche, Andreas, Staiger, Harald, Simonis-Bik, Annemarie M. C., Deelen, Joris, Kramer, Mark H. H., Dietrich, Axel, Hübschle, Thomas, Willemsen, Gonneke, Häring, Hans-Ulrich, and de Geus, Eco J. C.

Subjects
GLUCAGON-like peptide 1, PHENOTYPES, INSULIN, PROTEIN-protein interactions, FOCAL adhesions, GENE expression
Abstract

Glucagon-like peptide 1 (GLP-1) stimulated insulin secretion has a considerable heritable component as estimated from twin studies, yet few genetic variants influencing this phenotype have been identified. We performed the first genome-wide association study (GWAS) of GLP-1 stimulated insulin secretion in non-diabetic individuals from the Netherlands Twin register (n = 126). This GWAS was enhanced using a tissue-specific protein-protein interaction network approach. We identified a beta-cell protein-protein interaction module that was significantly enriched for low gene scores based on the GWAS P-values and found support at the network level in an independent cohort from Tübingen, Germany (n = 100). Additionally, a polygenic risk score based on SNPs prioritized from the network was associated (P < 0.05) with glucose-stimulated insulin secretion phenotypes in up to 5,318 individuals in MAGIC cohorts. The network contains both known and novel genes in the context of insulin secretion and is enriched for members of the focal adhesion, extracellular-matrix receptor interaction, actin cytoskeleton regulation, Rap1 and PI3K-Akt signaling pathways. Adipose tissue is, like the beta-cell, one of the target tissues of GLP-1 and we thus hypothesized that similar networks might be functional in both tissues. In order to verify peripheral effects of GLP-1 stimulation, we compared the transcriptome profiling of ob/ob mice treated with liraglutide, a clinically used GLP-1 receptor agonist, versus baseline controls. Some of the upstream regulators of differentially expressed genes in the white adipose tissue of ob/ob mice were also detected in the human beta-cell network of genes associated with GLP-1 stimulated insulin secretion. The findings provide biological insight into the mechanisms through which the effects of GLP-1 may be modulated and highlight a potential role of the beta-cell expressed genes RYR2, GDI2, KIAA0232, COL4A1 and COL4A2 in GLP-1 stimulated insulin secretion. [ABSTRACT FROM AUTHOR]

Published
2018
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10. Studies of association of AGPAT6 variants with type 2 diabetes and related metabolic phenotypes in 12,068 Danes.

Author

Sønder Snogdal, Lena, Grarup, Niels, Banasik, Karina, Wod, Mette, Jørgensen, Torben, Witte, Daniel R., Lauritzen, Torsten, Nielsen, Aneta A., Brandslund, Ivan, Christensen, Cramer, Pedersen, Oluf, Yderstræde, Knud, Beck-Nielsen, Henning, Henriksen, Jan Erik, Hansen, Torben, and Højlund, Kurt

Subjects
TYPE 2 diabetes, OBESITY, PHENOTYPES, INSULIN resistance, MEDICAL genetics
Abstract

Background Type 2 diabetes, obesity and insulin resistance are characterized by hypertriglyceridemia and ectopic accumulation of lipids in liver and skeletal muscle. AGPAT6 encodes a novel glycerol-3 phosphate acyltransferase, GPAT4, which catalyzes the first step in the de novo triglyceride synthesis. AGPAT6-deficient mice show lower weight and resistance to diet- and genetically induced obesity. Here, we examined whether common or low-frequency variants in AGPAT6 associate with type 2 diabetes or related metabolic traits in a Danish population. Methods Eleven variants selected by a candidate gene approach capturing the common and low-frequency variation of AGPAT6 were genotyped in 12,068 Danes from four study populations of middle-aged individuals. The case-control study involved 4,638 type 2 diabetic and 5,934 glucose-tolerant individuals, while studies of quantitative metabolic traits were performed in 5,645 non-diabetic participants of the Inter99 Study. Results None of the eleven AGPAT6 variants were robustly associated with type 2 diabetes in the Danish case-control study. Moreover, none of the AGPAT6 variants showed association with measures of obesity (waist circumference and BMI), serum lipid concentrations, fasting or 2- h post-glucose load levels of plasma glucose and serum insulin, or estimated indices of insulin secretion or insulin sensitivity. Conclusions Common and low-frequency variants in AGPAT6 do not significantly associate with type 2 diabetes susceptibility, or influence related phenotypic traits such as obesity, dyslipidemia or indices of insulin sensitivity or insulin secretion in the population studied. [ABSTRACT FROM AUTHOR]

Published
2013
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11. Bioinformatics-Driven Identification and Examination of Candidate Genes for Non-Alcoholic Fatty Liver Disease.

Author

Banasik, Karina, Justesen, Johanne M., Hornbak, Malene, Krarup, Nikolaj T., Gjesing, Anette P., Sandholt, Camilla H., Jensen, Thomas S., Grarup, Niels, Andersson, Åsa, Jørgensen, Torben, Witte, Daniel R., Sandbæk, Annelli, Lauritzen, Torsten, Thorens, Bernard, Brunak, Søren, Sørensen, Thorkild I. A., Pedersen, Oluf, and Hansen, Torben

Subjects
*BIOINFORMATICS, *GENES, *LIVER diseases, *FATTY liver, *FATTY degeneration, *PHENOTYPES, *GENETICS, *OBESITY, *METABOLIC disorders
Abstract

Objective: Candidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes. Research Design and Methods: By integrating public database text mining, trans-organism protein-protein interaction transferal, and information on liver protein expression a protein-protein interaction network was constructed and from this a smaller isolated interactome was identified. Five genes from this interactome were selected for genetic analysis. Twentyone tag single-nucleotide polymorphisms (SNPs) which captured all common variation in these genes were genotyped in 10,196 Danes, and analyzed for association with NAFLD-related quantitative traits, type 2 diabetes (T2D), central obesity, and WHO-defined metabolic syndrome (MetS). Results: 273 genes were included in the protein-protein interaction analysis and EHHADH, ECHS1, HADHA, HADHB, and ACADL were selected for further examination. A total of 10 nominal statistical significant associations (P<0.05) to quantitative metabolic traits were identified. Also, the case-control study showed associations between variation in the five genes and T2D, central obesity, and MetS, respectively. Bonferroni adjustments for multiple testing negated all associations. Conclusions: Using a bioinformatics approach we identified five candidate genes for NAFLD. However, we failed to provide evidence of associations with major effects between SNPs in these five genes and NAFLD-related quantitative traits, T2D, central obesity, and MetS. [ABSTRACT FROM AUTHOR]

Published
2011
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12. Systems genetics analysis identifies calcium-signaling defects as novel cause of congenital heart disease.

Author

Izarzugaza, Jose M. G., Ellesøe, Sabrina G., Doganli, Canan, Ehlers, Natasja Spring, Dalgaard, Marlene D., Audain, Enrique, Dombrowsky, Gregor, Banasik, Karina, Sifrim, Alejandro, Wilsdon, Anna, Thienpont, Bernard, Breckpot, Jeroen, Gewillig, Marc, Competence Network for Congenital Heart Defects, Germany, Abdul-Khaliq, Hashim, Kramer, Hans-Heiner, Berger, Felix, Stiller, Brigitte, Bauer, Ulrike, and Pickardt, Thomas

Subjects
CONGENITAL heart disease, SYSTEM analysis, SYSTEMS biology, ETIOLOGY of diseases, HEART disease related mortality, GENE silencing, EXOMES
Abstract

Background: Congenital heart disease (CHD) occurs in almost 1% of newborn children and is considered a multifactorial disorder. CHD may segregate in families due to significant contribution of genetic factors in the disease etiology. The aim of the study was to identify pathophysiological mechanisms in families segregating CHD. Methods: We used whole exome sequencing to identify rare genetic variants in ninety consenting participants from 32 Danish families with recurrent CHD. We applied a systems biology approach to identify developmental mechanisms influenced by accumulation of rare variants. We used an independent cohort of 714 CHD cases and 4922 controls for replication and performed functional investigations using zebrafish as in vivo model. Results: We identified 1785 genes, in which rare alleles were shared between affected individuals within a family. These genes were enriched for known cardiac developmental genes, and 218 of these genes were mutated in more than one family. Our analysis revealed a functional cluster, enriched for proteins with a known participation in calcium signaling. Replication in an independent cohort confirmed increased mutation burden of calcium-signaling genes in CHD patients. Functional investigation of zebrafish orthologues of ITPR1, PLCB2, and ADCY2 verified a role in cardiac development and suggests a combinatorial effect of inactivation of these genes. Conclusions: The study identifies abnormal calcium signaling as a novel pathophysiological mechanism in human CHD and confirms the complex genetic architecture underlying CHD. [ABSTRACT FROM AUTHOR]

Published
2020
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