2024
Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program
Verma A, Huffman J, Rodriguez A, Conery M, Liu M, Ho Y, Kim Y, Heise D, Guare L, Panickan V, Garcon H, Linares F, Costa L, Goethert I, Tipton R, Honerlaw J, Davies L, Whitbourne S, Cohen J, Posner D, Sangar R, Murray M, Wang X, Dochtermann D, Devineni P, Shi Y, Nandi T, Assimes T, Brunette C, Carroll R, Clifford R, Duvall S, Gelernter J, Hung A, Iyengar S, Joseph J, Kember R, Kranzler H, Kripke C, Levey D, Luoh S, Merritt V, Overstreet C, Deak J, Grant S, Polimanti R, Roussos P, Shakt G, Sun Y, Tsao N, Venkatesh S, Voloudakis G, Justice A, Begoli E, Ramoni R, Tourassi G, Pyarajan S, Tsao P, O'Donnell C, Muralidhar S, Moser J, Casas J, Bick A, Zhou W, Cai T, Voight B, Cho K, Gaziano J, Madduri R, Damrauer S, Liao K. Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program. Science 2024, 385: eadj1182. PMID: 39024449, DOI: 10.1126/science.adj1182.Peer-Reviewed Original ResearchConceptsMillion Veteran ProgramNon-European populationsVeteran ProgramGenetic architectureAtlas of genetic associationsVeterans Affairs Million Veteran ProgramVA Million Veteran ProgramGenomic risk lociGenome-wide associationHuman genetic studiesHealth disparitiesUnited States veteransCausal variantsRisk lociGenetic insightsGenetic studiesGenetic associationGenetic causeStates veteransDiverse populationsDisease factorsLack of inclusionLongitudinal studyParticipantsTraits
2023
Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program
Cheng Y, Dao C, Zhou H, Li B, Kember R, Toikumo S, Zhao H, Gelernter J, Kranzler H, Justice A, Xu K. Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program. Translational Psychiatry 2023, 13: 148. PMID: 37147289, PMCID: PMC10162964, DOI: 10.1038/s41398-023-02409-2.Peer-Reviewed Original ResearchConceptsSingle-trait genome-wide association studiesGenome-wide association studiesNovel lociPower of GWASJoint genome-wide association studyGenome-wide significant lociMillion Veteran ProgramGenome-wide associationSubstance use traitsGWAS summary statisticsNovel genetic variantsMulti-trait analysisFunctional annotationUse traitsSignificant lociHeritable traitMultiple lociAssociation studiesColocalization analysisLociPleiotropic effectsMTAgVeteran ProgramGenetic variantsTraitsMultivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders
Hatoum A, Colbert S, Johnson E, Huggett S, Deak J, Pathak G, Jennings M, Paul S, Karcher N, Hansen I, Baranger D, Edwards A, Grotzinger A, Tucker-Drob E, Kranzler H, Davis L, Sanchez-Roige S, Polimanti R, Gelernter J, Edenberg H, Bogdan R, Agrawal A. Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders. Nature Mental Health 2023, 1: 210-223. PMID: 37250466, PMCID: PMC10217792, DOI: 10.1038/s44220-023-00034-y.Peer-Reviewed Original ResearchGenome-wide associationGenetic risk lociIndependent single nucleotide polymorphismsProblematic tobacco useSingle nucleotide polymorphismsRisk lociHigh polygenicityLociReceptor geneAddiction risk factorsPolygenic risk scoresEuropean descentPolygenicityGenesSummary statisticsSubstance use disordersSomatic conditionsAncestryRegulationConfersUse disordersPolymorphismGenetic liabilityDopamine regulationPDE4B
2018
Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder
Demontis D, Walters RK, Martin J, Mattheisen M, Als TD, Agerbo E, Baldursson G, Belliveau R, Bybjerg-Grauholm J, Bækvad-Hansen M, Cerrato F, Chambert K, Churchhouse C, Dumont A, Eriksson N, Gandal M, Goldstein JI, Grasby KL, Grove J, Gudmundsson OO, Hansen CS, Hauberg ME, Hollegaard MV, Howrigan DP, Huang H, Maller JB, Martin AR, Martin NG, Moran J, Pallesen J, Palmer DS, Pedersen CB, Pedersen MG, Poterba T, Poulsen JB, Ripke S, Robinson EB, Satterstrom FK, Stefansson H, Stevens C, Turley P, Walters GB, Won H, Wright MJ, Andreassen O, Asherson P, Burton C, Boomsma D, Cormand B, Dalsgaard S, Franke B, Gelernter J, Geschwind D, Hakonarson H, Haavik J, Kranzler H, Kuntsi J, Langley K, Lesch K, Middeldorp C, Reif A, Rohde L, Roussos P, Schachar R, Sklar P, Sonuga-Barke E, Sullivan P, Thapar A, Tung J, Waldman I, Medland S, Stefansson K, Nordentoft M, Hougaard D, Werge T, Mors O, Mortensen P, Daly M, Faraone S, Børglum A, Neale B. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nature Genetics 2018, 51: 63-75. PMID: 30478444, PMCID: PMC6481311, DOI: 10.1038/s41588-018-0269-7.Peer-Reviewed Original ResearchConceptsGenome-wide significant risk lociFunction intolerant genesGenome-wide associationSignificant risk lociGenome-wide significanceAttention-deficit/hyperactivity disorderCommon genetic variantsGenomic regionsIntolerant genesIndependent lociRegulatory marksHeritable traitRisk lociDeficit/hyperactivity disorderGenetic variantsGenetic overlapStudy-specific differencesLociHyperactivity disorderImportant new informationUnderlying biologyChildhood behavioral disordersVariantsStrong concordanceGWASGenome‐wide association meta‐analysis of age at first cannabis use
Minică CC, Verweij KJH, van der Most P, Mbarek H, Bernard M, van Eijk K, Lind PA, Liu MZ, Maciejewski DF, Palviainen T, Sánchez‐Mora C, Sherva R, Taylor M, Walters RK, Abdellaoui A, Bigdeli TB, Branje SJT, Brown SA, Casas M, Corley RP, Davey‐Smith G, Davies GE, Ehli EA, Farrer L, Fedko IO, Garcia‐Martínez I, Gordon SD, Hartman CA, Heath AC, Hickie IB, Hickman M, Hopfer CJ, Hottenga JJ, Kahn RS, Kaprio J, Korhonen T, Kranzler HR, Krauter K, van Lier P, Madden PAF, Medland SE, Neale MC, Meeus WHJ, Montgomery GW, Nolte IM, Oldehinkel AJ, Pausova Z, Ramos‐Quiroga J, Richarte V, Rose RJ, Shin J, Stallings MC, Wall TL, Ware JJ, Wright MJ, Zhao H, Koot HM, Paus T, Hewitt JK, Ribasés M, Loukola A, Boks MP, Snieder H, Munafò MR, Gelernter J, Boomsma DI, Martin NG, Gillespie NA, Vink JM, Derks EM. Genome‐wide association meta‐analysis of age at first cannabis use. Addiction 2018, 113: 2073-2086. PMID: 30003630, PMCID: PMC7087375, DOI: 10.1111/add.14368.Peer-Reviewed Original ResearchConceptsGenome-wide associationSingle nucleotide polymorphismsLinkage disequilibriumTwin-based heritabilityGene-based testsHigh linkage disequilibriumATPase geneWide associationATP2C2 geneChromosome 16Heritability analysisHeritability of ageGenetic variantsNucleotide polymorphismsDiscovery sampleHeritabilityGenesATP2C2Replication sampleEnvironmental factorsRole of calciumIdentified associationsFirst cannabis useFirst cannabisATP2B2