Scott, Robert AFreitag, Daniel FLi, LiChu, Audrey YSurendran, PraveenYoung, RobinGrarup, NielsStancáková, AlenaChen, YuningVarga, Tibor VYaghootkar, HaniehLuan, Jian'anZhao, Jing HuaWillems, Sara MWessel, JenniferWang, ShuaiMaruthur, NisaMichailidou, KyriakiPirie, Ailithvan der Lee, Sven JGillson, ChristopherAl Olama, Ali AminAmouyel, PhilippeArriola, LarraitzArveiler, DominiqueAviles-Olmos, IciarBalkau, BeverleyBarricarte, AurelioBarroso, InêsGarcia, Sara BenllochBis, Joshua CBlankenberg, StefanBoehnke, MichaelBoeing, HeinerBoerwinkle, EricBorecki, Ingrid BBork-Jensen, JetteBowden, SarahCaldas, CarlosCaslake, MurielCVD50 consortiumCupples, L AdrienneCruchaga, CarlosCzajkowski, Jacekden Hoed, MarcelDunn, Janet AEarl, Helena MEhret, Georg BFerrannini, EleFerrieres, JeanFoltynie, ThomasFord, IanForouhi, Nita GGianfagna, FrancescoGonzalez, CarlosGrioni, SaraHiller, LouiseJansson, Jan-HåkanJørgensen, Marit EJukema, J WouterKaaks, RudolfKee, FrankKerrison, Nicola DKey, Timothy JKontto, JukkaKote-Jarai, ZsofiaKraja, Aldi TKuulasmaa, KariKuusisto, JohannaLinneberg, AllanLiu, ChunyuMarenne, GaëlleMohlke, Karen LMorris, Andrew PMuir, KennethMüller-Nurasyid, MartinaMunroe, Patricia BNavarro, CarmenNielsen, Sune FNilsson, Peter MNordestgaard, Børge GPackard, Chris JPalli, DomenicoPanico, SalvatorePeloso, Gina MPerola, MarkusPeters, AnnettePoole, Christopher JQuirós, J RamónRolandsson, OlovSacerdote, CarlottaSalomaa, VeikkoSanchez-Perez, Maria-JoseSattar, NaveedSharp, Stephen JSims, RebeccaSlimani, NadiaSmith, Jennifer AThompson, Deborah JTrompet, StellaTumino, Rosariovan der A, Daphne Lvan der Schouw, Yvonne TVirtamo, JarmoWalker, MarkWalter, KlaudiaGERAD_EC ConsortiumNeurology Working Group of the Cohorts for HeartAging Research in Genomic Epidemiology (CHARGE)Alzheimer’s Disease Genetics ConsortiumPancreatic Cancer Cohort ConsortiumEuropean Prospective Investigation into Cancer and Nutrition–Cardiovascular Disease (EPIC-CVD)EPIC-InterActAbraham, Jean EAmundadottir, Laufey TAponte, Jennifer LButterworth, Adam SDupuis, JoséeEaston, Douglas FEeles, Rosalind AErdmann, JeanetteFranks, Paul WFrayling, Timothy MHansen, TorbenHowson, Joanna M MJørgensen, TorbenKooner, JaspalLaakso, MarkkuLangenberg, ClaudiaMcCarthy, Mark IPankow, James SPedersen, OlufRiboli, ElioRotter, Jerome ISaleheen, DanishSamani, Nilesh JSchunkert, HeribertVollenweider, PeterO'Rahilly, StephenCHARGE consortiumCHD Exome+ ConsortiumCARDIOGRAM Exome ConsortiumDeloukas, PanosDanesh, JohnGoodarzi, Mark OKathiresan, SekarMeigs, James BEhm, Margaret GWareham, Nicholas JWaterworth, Dawn M2023-01-252023-01-252016http://hdl.handle.net/10668/10145Regulatory 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.enAllelesCoronary DiseaseDiabetes Mellitus, Type 2Dipeptidyl Peptidase 4GenotypeGlucagon-Like Peptide-1 ReceptorHumansObesityReceptor, Cannabinoid, CB2Receptor, Serotonin, 5-HT2CReceptors, SomatostatinSodium-Glucose Transporter 1research article27252175open access10.1126/scitranslmed.aad37441946-6242PMC5219001https://europepmc.org/articles/pmc5219001?pdf=renderhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5219001/pdf