| Literature DB >> 27252175 |
Robert A Scott1, Daniel F Freitag2, Li Li3, Audrey Y Chu4, Praveen Surendran5, Robin Young5, Niels Grarup6, Alena Stancáková7, Yuning Chen8, Tibor V Varga9, Hanieh Yaghootkar10, Jian'an Luan11, Jing Hua Zhao11, Sara M Willems12, Jennifer Wessel13, Shuai Wang8, Nisa Maruthur14, Kyriaki Michailidou15, Ailith Pirie15, Sven J van der Lee16, Christopher Gillson11, Ali Amin Al Olama15, Philippe Amouyel17, Larraitz Arriola18, Dominique Arveiler19, Iciar Aviles-Olmos20, Beverley Balkau21, Aurelio Barricarte22, Inês Barroso23, Sara Benlloch Garcia15, Joshua C Bis24, Stefan Blankenberg25, Michael Boehnke26, Heiner Boeing27, Eric Boerwinkle28, Ingrid B Borecki29, Jette Bork-Jensen6, Sarah Bowden30, Carlos Caldas31, Muriel Caslake32, L Adrienne Cupples33, Carlos Cruchaga34, Jacek Czajkowski35, Marcel den Hoed36, Janet A Dunn37, Helena M Earl38, Georg B Ehret39, Ele Ferrannini40, Jean Ferrieres41, Thomas Foltynie20, Ian Ford32, Nita G Forouhi11, Francesco Gianfagna42, Carlos Gonzalez43, Sara Grioni44, Louise Hiller37, Jan-Håkan Jansson45, Marit E Jørgensen46, J Wouter Jukema47, Rudolf Kaaks48, Frank Kee49, Nicola D Kerrison11, Timothy J Key50, Jukka Kontto51, Zsofia Kote-Jarai52, Aldi T Kraja35, Kari Kuulasmaa51, Johanna Kuusisto53, Allan Linneberg54, Chunyu Liu55, Gaëlle Marenne56, Karen L Mohlke57, Andrew P Morris58, Kenneth Muir59, Martina Müller-Nurasyid60, Patricia B Munroe61, Carmen Navarro62, Sune F Nielsen63, Peter M Nilsson64, Børge G Nordestgaard63, Chris J Packard32, Domenico Palli65, Salvatore Panico66, Gina M Peloso67, Markus Perola68, Annette Peters69, Christopher J Poole70, J Ramón Quirós71, Olov Rolandsson72, Carlotta Sacerdote73, Veikko Salomaa51, María-José Sánchez74, Naveed Sattar32, Stephen J Sharp11, Rebecca Sims75, Nadia Slimani76, Jennifer A Smith77, Deborah J Thompson15, Stella Trompet47, Rosario Tumino78, Daphne L van der A79, Yvonne T van der Schouw80, Jarmo Virtamo51, Mark Walker81, Klaudia Walter56, Jean E Abraham82, Laufey T Amundadottir83, Jennifer L Aponte84, Adam S Butterworth5, Josée Dupuis8, Douglas F Easton85, Rosalind A Eeles86, Jeanette Erdmann87, Paul W Franks88, Timothy M Frayling10, Torben Hansen6, Joanna M M Howson5, Torben Jørgensen89, Jaspal Kooner90, Markku Laakso91, Claudia Langenberg11, Mark I McCarthy92, James S Pankow93, Oluf Pedersen6, Elio Riboli94, Jerome I Rotter95, Danish Saleheen96, Nilesh J Samani97, Heribert Schunkert98, Peter Vollenweider99, Stephen O'Rahilly100, Panos Deloukas101, John Danesh2, Mark O Goodarzi102, Sekar Kathiresan103, James B Meigs104, Margaret G Ehm84, Nicholas J Wareham1, Dawn M Waterworth105.
Abstract
Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to guide development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in six genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow-up in consortia. We used these data to first compare associations of variants in genes encoding drug targets with the effects of pharmacological manipulation of those targets in clinical trials. We then tested the association of those variants with disease outcomes, including coronary heart disease, to predict cardiovascular safety of these agents. A low-frequency missense variant (Ala316Thr; rs10305492) in the gene encoding glucagon-like peptide-1 receptor (GLP1R), the target of GLP1R agonists, was associated with lower fasting glucose and T2D risk, consistent with GLP1R agonist therapies. The minor allele was also associated with protection against heart disease, thus providing evidence that GLP1R agonists are not likely to be associated with an unacceptable increase in cardiovascular risk. Our results provide an encouraging signal that these agents may be associated with benefit, a question currently being addressed in randomized controlled trials. Genetic variants associated with metabolic traits and multiple disease outcomes can be used to validate therapeutic targets at an early stage in the drug development process.Entities:
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Year: 2016 PMID： 27252175 PMCID： PMC5219001 DOI： 10.1126/scitranslmed.aad3744
Source DB: PubMed Journal: Sci Transl Med ISSN： 1946-6234 Impact factor: 17.956