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

TY - JOUR

T1 - A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease

AU - Scott, Robert A

AU - Freitag, Daniel F

AU - Li, Li

AU - Chu, Audrey Y

AU - Surendran, Praveen

AU - Young, Robin

AU - Grarup, Niels

AU - Stancáková, Alena

AU - Chen, Yuning

AU - Varga, Tibor V

AU - Yaghootkar, Hanieh

AU - Luan, Jian'an

AU - Zhao, Jing Hua

AU - Willems, Sara M

AU - Wessel, Jennifer

AU - Wang, Shuai

AU - Maruthur, Nisa

AU - Michailidou, Kyriaki

AU - Pirie, Ailith

AU - van der Lee, Sven J

AU - Gillson, Christopher

AU - Al Olama, Ali Amin

AU - Amouyel, Philippe

AU - Arriola, Larraitz

AU - Arveiler, Dominique

AU - Aviles-Olmos, Iciar

AU - Balkau, Beverley

AU - Barricarte, Aurelio

AU - Barroso, Inês

AU - Garcia, Sara Benlloch

AU - Bis, Joshua C

AU - Blankenberg, Stefan

AU - Boehnke, Michael

AU - Boeing, Heiner

AU - Boerwinkle, Eric

AU - Borecki, Ingrid B

AU - Bork-Jensen, Jette

AU - Bowden, Sarah

AU - Caldas, Carlos

AU - Caslake, Muriel

AU - Cupples, L Adrienne

AU - Cruchaga, Carlos

AU - Czajkowski, Jacek

AU - den Hoed, Marcel

AU - Dunn, Janet A

AU - Earl, Helena M

AU - Ehret, Georg B

AU - Ferrannini, Ele

AU - Ferrieres, Jean

AU - Foltynie, Thomas

AU - Ford, Ian

AU - Forouhi, Nita G

AU - Gianfagna, Francesco

AU - Gonzalez, Carlos

AU - Grioni, Sara

AU - Hiller, Louise

AU - Jansson, Jan-Håkan

AU - Jørgensen, Marit E

AU - Jukema, J Wouter

AU - Kaaks, Rudolf

AU - Kee, Frank

AU - Kerrison, Nicola D

AU - Key, Timothy J

AU - Kontto, Jukka

AU - Kote-Jarai, Zsofia

AU - Kraja, Aldi T

AU - Kuulasmaa, Kari

AU - Kuusisto, Johanna

AU - Linneberg, Allan

AU - Liu, Chunyu

AU - Marenne, Gaëlle

AU - Mohlke, Karen L

AU - Morris, Andrew P

AU - Muir, Kenneth

AU - Müller-Nurasyid, Martina

AU - Munroe, Patricia B

AU - Navarro, Carmen

AU - Nielsen, Sune F

AU - Nilsson, Peter M

AU - Nordestgaard, Børge G

AU - Packard, Chris J

AU - Palli, Domenico

AU - Panico, Salvatore

AU - Peloso, Gina M

AU - Perola, Markus

AU - Peters, Annette

AU - Poole, Christopher J

AU - Quirós, J Ramón

AU - Rolandsson, Olov

AU - Sacerdote, Carlotta

AU - Salomaa, Veikko

AU - Sánchez, María-José

AU - Sattar, Naveed

AU - Sharp, Stephen J

AU - Sims, Rebecca

AU - Slimani, Nadia

AU - Smith, Jennifer A

AU - Thompson, Deborah J

AU - Trompet, Stella

AU - Tumino, Rosario

AU - van der A, Daphne L

AU - van der Schouw, Yvonne T

AU - Virtamo, Jarmo

AU - Walker, Mark

AU - Walter, Klaudia

AU - Abraham, Jean E

AU - Amundadottir, Laufey T

AU - Aponte, Jennifer L

AU - Butterworth, Adam S

AU - Dupuis, Josée

AU - Easton, Douglas F

AU - Eeles, Rosalind A

AU - Erdmann, Jeanette

AU - Franks, Paul W

AU - Frayling, Timothy M

AU - Hansen, Torben

AU - Howson, Joanna M M

AU - Jørgensen, Torben

AU - Kooner, Jaspal

AU - Laakso, Markku

AU - Langenberg, Claudia

AU - McCarthy, Mark I

AU - Pankow, James S

AU - Pedersen, Oluf

AU - Riboli, Elio

AU - Rotter, Jerome I

AU - Saleheen, Danish

AU - Samani, Nilesh J

AU - Schunkert, Heribert

AU - Vollenweider, Peter

AU - O'Rahilly, Stephen

AU - Deloukas, Panos

AU - Danesh, John

AU - Goodarzi, Mark O

AU - Kathiresan, Sekar

AU - Meigs, James B

AU - Ehm, Margaret G

AU - Wareham, Nicholas J

AU - Waterworth, Dawn M

AU - CVD50 consortium

N1 - Copyright © 2016, American Association for the Advancement of Science.

PY - 2016/6/1

Y1 - 2016/6/1

N2 - 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.

AB - 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.

KW - Alleles

KW - Coronary Disease/genetics

KW - Diabetes Mellitus, Type 2/genetics

KW - Dipeptidyl Peptidase 4/genetics

KW - Genotype

KW - Glucagon-Like Peptide-1 Receptor/genetics

KW - Humans

KW - Obesity/genetics

KW - Receptor, Cannabinoid, CB2/genetics

KW - Receptor, Serotonin, 5-HT2C/genetics

KW - Receptors, Somatostatin/genetics

KW - Sodium-Glucose Transporter 1/genetics

U2 - 10.1126/scitranslmed.aad3744

DO - 10.1126/scitranslmed.aad3744

M3 - SCORING: Journal article

C2 - 27252175

VL - 8

SP - 341ra76

JO - SCI TRANSL MED

JF - SCI TRANSL MED

SN - 1946-6234

IS - 341

ER -