A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease

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Robert A. Scott, Daniel F. Freitag, Li Li, Audrey Y. Chu, Praveen Surendran, Robin Young, Niels Grarup, Alena Stancakova, Yuning Chen, Tibor V. Varga, Hanieh Yaghootkar, Jian'an Luan, Jing Hua Zhao, Sara M. Willems, Jennifer Wessel, Shuai Wang, Nisa Maruthur, Kyriaki Michailidou, Ailith Pirie, Sven J. van der Lee & 119 others Christopher Gillson, Ali Amin Al Olama, Philippe Amouyel, Larraitz Arriola, Dominique Arveiler, Iciar Aviles-Olmos, Beverley Balkau, Aurelio Barricarte, Ines Barroso, Sara Benlloch Garcia, Joshua C. Bis, Stefan Blankenberg, Michael Boehnke, Heiner Boeing, Eric Boerwinkle, Ingrid B. Borecki, Jette Bork-Jensen, Sarah Bowden, Carlos Caldas, Muriel Caslake, L. Adrienne Cupples, Carlos Cruchaga, Jacek Czajkowski, Marcel den Hoed, Janet A. Dunn, Helena M. Earl, Georg B. Ehret, Ele Ferrannini, Jean Ferrieres, Thomas Foltynie, Ian Ford, Nita G. Forouhi, Francesco Gianfagna, Carlos Gonzalez, Sara Grioni, Louise Hiller, Jan-Hakan Jansson, Marit E. Jørgensen, J. Wouter Jukema, Rudolf Kaaks, Frank Kee, Nicola D. Kerrison, Timothy J. Key, Jukka Kontto, Zsofia Kote-Jarai, Aldi T. Kraja, Kari Kuulasmaa, Johanna Kuusisto, Allan Linneberg, Chunyu Liu, Galle Marenne, Karen L. Mohlke, Andrew P. Morris, Kenneth Muir, Martina Mueller-Nurasyid, Patricia B. Munroe, Carmen Navarro, Sune F. Nielsen, Peter M. Nilsson, Borge G. Nordestgaard, Chris J. Packard, Domenico Palli, Salvatore Panico, Gina M. Peloso, Markus Perola, Annette Peters, Christopher J. Poole, J. Ramn Quiros, Olov Rolandsson, Carlotta Sacerdote, Veikko Salomaa, Mara-Jose Sanchez, Naveed Sattar, Stephen J. Sharp, Rebecca Sims, Nadia Slimani, Jennifer A. Smith, Deborah J. Thompson, Stella Trompet, Rosario Tumino, Daphne L. van der A, Yvonne T. van der Schouw, Jarmo Virtamo, Mark Walker, Klaudia Walter, Jean E. Abraham, Laufey T. Amundadottir, Jennifer L. Aponte, Adams. Butterworth, Josee Dupuis, Douglas F. Easton, Rosalind A. Eeles, Jeanette Erdmann, Paul W. Franks, Timothy M. Frayling, Torben Hansen, Joanna M. M. Howson, Torben Jørgensen, Jaspal Kooner, Markku Laakso, Claudia Langenberg, Mark I. McCarthy, James S. Pankow, Oluf Pedersen, Elio Riboli, Jerome I. Rotter, Danish Saleheen, Nilesh J. Samani, Heribert Schunkert, Peter Vollenweider, Stephen O'Rahilly, Panos Deloukas, John Danesh, Mark O. Goodarzi, Sekar Kathiresan, James B. Meigs, Margaret G. Ehm, Nicholas J. Wareham, Dawn M. Waterworth

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.
Original languageEnglish
Article number341ra76
JournalScience Translational Medicine
Volume8
Issue number341
Number of pages13
ISSN1946-6234
DOIs
Publication statusPublished - 1 Jun 2016

ID: 163128166