2024
Critical reasoning on the co-expression module QTL in the dorsolateral prefrontal cortex
Cote A, Young H, Huckins L. Critical reasoning on the co-expression module QTL in the dorsolateral prefrontal cortex. Human Genetics And Genomics Advances 2024, 5: 100311. PMID: 38773772, PMCID: PMC11214266, DOI: 10.1016/j.xhgg.2024.100311.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociGene co-expressionCo-expressionExpression quantitative trait locus methodGenetic variantsComplex trait heritabilityMultiple testing burdenGene-based testsQuantitative trait lociTrans-eQTLsCis-eQTLsRegulatory variationSequencing datasetsTrait lociGene regulationTrait heritabilityGene functionGene modulesReal-data applicationModule genesGenesTesting burdenDorsolateral prefrontal cortexVariantsComparison to prior studies
2023
Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals
Zhou H, Kember R, Deak J, Xu H, Toikumo S, Yuan K, Lind P, Farajzadeh L, Wang L, Hatoum A, Johnson J, Lee H, Mallard T, Xu J, Johnston K, Johnson E, Nielsen T, Galimberti M, Dao C, Levey D, Overstreet C, Byrne E, Gillespie N, Gordon S, Hickie I, Whitfield J, Xu K, Zhao H, Huckins L, Davis L, Sanchez-Roige S, Madden P, Heath A, Medland S, Martin N, Ge T, Smoller J, Hougaard D, Børglum A, Demontis D, Krystal J, Gaziano J, Edenberg H, Agrawal A, Justice A, Stein M, Kranzler H, Gelernter J. Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals. Nature Medicine 2023, 29: 3184-3192. PMID: 38062264, PMCID: PMC10719093, DOI: 10.1038/s41591-023-02653-5.Peer-Reviewed Original ResearchAlcoholismGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPhenotypePolymorphism, Single NucleotideRacial GroupsGenetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing
Johnston K, Cote A, Hicks E, Johnson J, Huckins L. Genetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing. Biological Psychiatry 2023, 95: 745-761. PMID: 37678542, PMCID: PMC10924073, DOI: 10.1016/j.biopsych.2023.08.023.Peer-Reviewed Original ResearchMeSH KeywordsArrhythmias, CardiacBrainChronic PainDrug RepositioningGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMetabolic SyndromePhenotypePolymorphism, Single NucleotideTranscriptomeConceptsGenetically regulated gene expressionMultisite chronic painGene-tissue associationsMean pain scoreUnique genesChronic painAssociation studiesS-PrediXcanGene expressionPain scoresTranscriptome-wide association studyPhenome-wide association studyCardiac dysrhythmiasMetabolic syndromeGenome-wide association studiesAssociated with cardiac dysrhythmiasDrug targetsGenotype-phenotype gapChronic pain developmentAssociation study resultsGene expression changesJoint/ligament sprainsDirection of effectTranscriptome imputationPain traitsTranscriptional signatures of heroin intake and relapse throughout the brain reward circuitry in male mice
Browne C, Futamura R, Minier-Toribio A, Hicks E, Ramakrishnan A, Martínez-Rivera F, Estill M, Godino A, Parise E, Torres-Berrío A, Cunningham A, Hamilton P, Walker D, Huckins L, Hurd Y, Shen L, Nestler E. Transcriptional signatures of heroin intake and relapse throughout the brain reward circuitry in male mice. Science Advances 2023, 9: eadg8558. PMID: 37294757, PMCID: PMC10256172, DOI: 10.1126/sciadv.adg8558.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBrainGenome-Wide Association StudyHeroinHumansMaleMiceOpioid-Related DisordersRecurrenceRewardConceptsOpioid use disorderHeroin intakeContext-induced drug-seekingBrain reward circuitryHeroin self-administrationRNA-seqDrug seekingReward circuitryGenome-wide association study dataSelf-administrationHeroin exposureDrug-takingIntegration of RNA-seq dataUse disorderPatterns of transcriptional regulationRNA-seq dataBehavioral outcomesMale miceMolecular changesTranscriptional regulationRegion-specificGene candidatesRNA sequencingHeroinBioinformatics analysisLeveraging base-pair mammalian constraint to understand genetic variation and human disease
Sullivan P, Meadows J, Gazal S, Phan B, Li X, Genereux D, Dong M, Bianchi M, Andrews G, Sakthikumar S, Nordin J, Roy A, Christmas M, Marinescu V, Wang C, Wallerman O, Xue J, Yao S, Sun Q, Szatkiewicz J, Wen J, Huckins L, Lawler A, Keough K, Zheng Z, Zeng J, Wray N, Li Y, Johnson J, Chen J, Paten B, Reilly S, Hughes G, Weng Z, Pollard K, Pfenning A, Forsberg-Nilsson K, Karlsson E, Lindblad-Toh K, Andrews G, Armstrong J, Bianchi M, Birren B, Bredemeyer K, Breit A, Christmas M, Clawson H, Damas J, Di Palma F, Diekhans M, Dong M, Eizirik E, Fan K, Fanter C, Foley N, Forsberg-Nilsson K, Garcia C, Gatesy J, Gazal S, Genereux D, Goodman L, Grimshaw J, Halsey M, Harris A, Hickey G, Hiller M, Hindle A, Hubley R, Hughes G, Johnson J, Juan D, Kaplow I, Karlsson E, Keough K, Kirilenko B, Koepfli K, Korstian J, Kowalczyk A, Kozyrev S, Lawler A, Lawless C, Lehmann T, Levesque D, Lewin H, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu V, Marques-Bonet T, Mason V, Meadows J, Meyer W, Moore J, Moreira L, Moreno-Santillan D, Morrill K, Muntané G, Murphy W, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat N, Pfenning A, Phan B, Pollard K, Pratt H, Ray D, Reilly S, Rosen J, Ruf I, Ryan L, Ryder O, Sabeti P, Schäffer D, Serres A, Shapiro B, Smit A, Springer M, Srinivasan C, Steiner C, Storer J, Sullivan K, Sullivan P, Sundström E, Supple M, Swofford R, Talbot J, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder A, Wirthlin M, Xue J, Zhang X. Leveraging base-pair mammalian constraint to understand genetic variation and human disease. Science 2023, 380: eabn2937. PMID: 37104612, PMCID: PMC10259825, DOI: 10.1126/science.abn2937.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBiological EvolutionDiseaseGenetic VariationGenome-Wide Association StudyGenome, HumanGenomicsHumansMolecular Sequence AnnotationPolymorphism, Single NucleotideConceptsHuman genomeHuman diseasesCopy-number variationsHeritable human diseasesGenome annotationVariant annotationGenomic positionsGenomic regionsDisease heritabilityFunctional annotationEvolutionary constraintsAssociation studiesCopy-numberGenetic variationGenetic findingsGenomeCell typesRegulatory landscapeDisease mechanismsAnnotationBiological mechanismsCancer dataMammalsPredictor of functionHeritabilityIntegrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings
Hicks E, Seah C, Cote A, Marchese S, Brennand K, Nestler E, Girgenti M, Huckins L. Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings. Translational Psychiatry 2023, 13: 129. PMID: 37076454, PMCID: PMC10115809, DOI: 10.1038/s41398-023-02412-7.Peer-Reviewed Original ResearchMeSH KeywordsBrainComputational BiologyDepressive Disorder, MajorGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansTranscriptomeConceptsBioinformatics approachTranscriptomic dataBrain transcriptomeGenome-wide analysisDynamic transcriptional landscapeBrain gene expression dataGene expression dataTranscriptional landscapeTranscriptomic studiesIntegrating GeneticExpression dataPhenotypic signaturesGenomic driversTranscriptomeMajor depressive disorderValuable resourceRecent findingsEnvironmental influencesTranscriptomicsDepressive disorderGeneticsMultiple approachesPathophysiology of depressionSignaturesDysregulationSchizophrenia risk conferred by rare protein-truncating variants is conserved across diverse human populations
Liu D, Meyer D, Fennessy B, Feng C, Cheng E, Johnson J, Park Y, Rieder M, Ascolillo S, de Pins A, Dobbyn A, Lebovitch D, Moya E, Nguyen T, Wilkins L, Hassan A, Burdick K, Buxbaum J, Domenici E, Frangou S, Hartmann A, Laurent-Levinson C, Malhotra D, Pato C, Pato M, Ressler K, Roussos P, Rujescu D, Arango C, Bertolino A, Blasi G, Bocchio-Chiavetto L, Campion D, Carr V, Fullerton J, Gennarelli M, González-Peñas J, Levinson D, Mowry B, Nimgaokar V, Pergola G, Rampino A, Cervilla J, Rivera M, Schwab S, Wildenauer D, Daly M, Neale B, Singh T, O’Donovan M, Owen M, Walters J, Ayub M, Malhotra A, Lencz T, Sullivan P, Sklar P, Stahl E, Huckins L, Charney A. Schizophrenia risk conferred by rare protein-truncating variants is conserved across diverse human populations. Nature Genetics 2023, 55: 369-376. PMID: 36914870, PMCID: PMC10011128, DOI: 10.1038/s41588-023-01305-1.Peer-Reviewed Original ResearchMeSH KeywordsAllelesAutistic DisorderGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansSchizophreniaConceptsProtein-truncating variantsRare protein-truncating variantsControls of diverse ancestryGenetic architecture of schizophreniaRare variant signalsProtein-coding regionsSchizophrenia risk genesCustom sequencing panelAncestral populationsAllelic spectrumGenetic architectureHuman populationDiverse ancestryHuman geneticsRisk genesVariant signalsGenesSequencing panelSchizophrenia casesSchizophrenia riskChronic mental illnessAncestryGeneticsMental illnessVariants
2022
Stem Cell Models for Context-Specific Modeling in Psychiatric Disorders
Seah C, Huckins L, Brennand K. Stem Cell Models for Context-Specific Modeling in Psychiatric Disorders. Biological Psychiatry 2022, 93: 642-650. PMID: 36658083, DOI: 10.1016/j.biopsych.2022.09.033.Peer-Reviewed Original ResearchMeSH KeywordsGene Expression RegulationGenome-Wide Association StudyHumansInduced Pluripotent Stem CellsMental DisordersQuantitative Trait LociConceptsStem cell modelCell typesTarget genesGenome-wide association study (GWAS) lociExpression quantitative trait lociGenome-wide association studiesParallel reporter assaysQuantitative trait lociStem cell-derived cell typesPluripotent stem cell modelsComplex polygenic architectureContext-specific mannerPsychiatric disorder riskTrait lociRegulates transcriptionStudy lociGenetic regulationPolygenic architectureCRISPR screensCell modelCausal variantsRegulated expressionPatient-specific humanReporter assaysAssociation studiesExploring the clinical and genetic associations of adult weight trajectories using electronic health records in a racially diverse biobank: a phenome-wide and polygenic risk study
Xu J, Johnson JS, Signer R, Consortium E, Birgegård A, Jordan J, Kennedy MA, Landén M, Maguire SL, Martin NG, Mortensen PB, Petersen LV, Thornton LM, Bulik CM, Huckins LM. Exploring the clinical and genetic associations of adult weight trajectories using electronic health records in a racially diverse biobank: a phenome-wide and polygenic risk study. The Lancet Digital Health 2022, 4: e604-e614. PMID: 35780037, PMCID: PMC9612590, DOI: 10.1016/s2589-7500(22)00099-1.Peer-Reviewed Original ResearchMeSH KeywordsAdultBiological Specimen BanksBody-Weight TrajectoryElectronic Health RecordsGenome-Wide Association StudyHumansMultifactorial InheritanceConceptsElectronic health recordsPolygenic risk scoresWeight trajectoriesDepression polygenic risk scoresObesity polygenic risk scoresHealth recordsWeight changeUK BiobankIndividual health statusLower disease riskGenetic associationPatient populationUS National InstitutesWeight managementStable weightRisk scoreHealthy populationHealth statusAnorexia nervosaBioMe BiobankDisease riskDisorder diagnosisMental healthWeight lossPhenome-wide association studyMapping anorexia nervosa genes to clinical phenotypes
Johnson J, Cote A, Dobbyn A, Sloofman L, Xu J, Cotter L, Charney A, Consortium E, Birgegård A, Jordan J, Kennedy M, Landén M, Maguire S, Martin N, Mortensen P, Thornton L, Bulik C, Huckins L. Mapping anorexia nervosa genes to clinical phenotypes. Psychological Medicine 2022, 53: 2619-2633. PMID: 35379376, PMCID: PMC10123844, DOI: 10.1017/s0033291721004554.Peer-Reviewed Original ResearchMeSH KeywordsAnorexia NervosaGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPhenotypePolymorphism, Single NucleotideTranscriptomeConceptsBody mass indexGenome-wide association studiesTranscriptome imputationElectronic health record phenotypingAssociation studiesPhenome-wide association studyS-PrediXcan analysisMeasurement of cholesterolTraditional genome-wide association studiesGenes associated with ANAssociation of genetic variantsSubstance useGenetically regulated gene expressionImpact of body mass indexConsequences of aberrant expressionBiobank cohortBiobank populationAssociated with measuresAssociation of ANGWAS findingsSecondary analysisS-PrediXcanDisease riskMass indexSignificant genesPredicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits
Highland H, Wojcik G, Graff M, Nishimura K, Hodonsky C, Baldassari A, Cote A, Cheng I, Gignoux C, Tao R, Li Y, Boerwinkle E, Fornage M, Haessler J, Hindorff L, Hu Y, Justice A, Lin B, Lin D, Stram D, Haiman C, Kooperberg C, Le Marchand L, Matise T, Kenny E, Carlson C, Stahl E, Avery C, North K, Ambite J, Buyske S, Loos R, Peters U, Young K, Bien S, Huckins L. Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits. American Journal Of Human Genetics 2022, 109: 669-679. PMID: 35263625, PMCID: PMC9069067, DOI: 10.1016/j.ajhg.2022.02.013.Peer-Reviewed Original ResearchMeSH KeywordsCardiovascular DiseasesGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansLife StylePolymorphism, Single NucleotideTranscriptomeConceptsAncestrally diverse populationsBody mass indexCardiometabolic traitsEuropean ancestryGene expressionTranscriptomic imputation modelsNon-EA populationsDiverse populationsWhite British participantsReference panelGenetically regulated gene expressionGene-trait associationsTissue-specific gene expressionPopulation ArchitectureUK BiobankMeasurement of gene expressionPredicting gene expressionMulti-omics datasetsRelevant tissuesSusceptibility lociMass indexComplex traitsIdentified genesNovel associationsDiverse sampleUsing phenotype risk scores to enhance gene discovery for generalized anxiety disorder and posttraumatic stress disorder
Wendt FR, Pathak GA, Deak JD, De Angelis F, Koller D, Cabrera-Mendoza B, Lebovitch DS, Levey DF, Stein MB, Kranzler HR, Koenen KC, Gelernter J, Huckins LM, Polimanti R. Using phenotype risk scores to enhance gene discovery for generalized anxiety disorder and posttraumatic stress disorder. Molecular Psychiatry 2022, 27: 2206-2215. PMID: 35181757, PMCID: PMC9133008, DOI: 10.1038/s41380-022-01469-y.Peer-Reviewed Original ResearchMeSH KeywordsAnxiety DisordersDepressive Disorder, MajorFemaleGenome-Wide Association StudyHumansMalePhenotypeRisk FactorsStress Disorders, Post-Traumatic
2021
Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study
Hu Y, Bien S, Nishimura K, Haessler J, Hodonsky C, Baldassari A, Highland H, Wang Z, Preuss M, Sitlani C, Wojcik G, Tao R, Graff M, Huckins L, Sun Q, Chen M, Mousas A, Auer P, Lettre G, Tang W, Qi L, Thyagarajan B, Buyske S, Fornage M, Hindorff L, Li Y, Lin D, Reiner A, North K, Loos R, Raffield L, Peters U, Avery C, Kooperberg C. Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study. BMC Genomics 2021, 22: 432. PMID: 34107879, PMCID: PMC8191001, DOI: 10.1186/s12864-021-07745-5.Peer-Reviewed Original ResearchMeSH KeywordsGenetic Predisposition to DiseaseGenome-Wide Association StudyGenomicsHumansLeukocytesPhenotypePolymorphism, Single NucleotideConceptsGenome-wide association studiesPlatelet traitsAfrican AmericansPopulation ArchitectureAssociation studiesAssociation analysisAncestry-specific genome-wide association studiesEuropean ancestryGenome-wide association analysisAttenuation of effect estimatesGenome-wide significant variantsVariant association analysisGenome-wide significanceRacially/ethnically diverse populationsPopulations of European ancestryGenetic association studiesAncestry-specificComplex traitsSignificant variantsHispanics/LatinosMultiple genesAncestry groupsEffect estimatesEA populationsEA participantsExamining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits
Martin J, Khramtsova E, Goleva S, Blokland G, Traglia M, Walters R, Hübel C, Coleman J, Breen G, Børglum A, Demontis D, Grove J, Werge T, Bralten J, Bulik C, Lee P, Mathews C, Peterson R, Winham S, Wray N, Edenberg H, Guo W, Yao Y, Neale B, Faraone S, Petryshen T, Weiss L, Duncan L, Goldstein J, Smoller J, Stranger B, Davis L, Consortium S, Alda M, Bortolato M, Burton C, Byrne E, Carey C, Erdman L, Huckins L, Mattheisen M, Robinson E, Stahl E. Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits. Biological Psychiatry 2021, 89: 1127-1137. PMID: 33648717, PMCID: PMC8163257, DOI: 10.1016/j.biopsych.2020.12.024.Peer-Reviewed Original ResearchMeSH KeywordsFemaleGenome-Wide Association StudyHumansMaleMultifactorial InheritancePhenotypePolymorphism, Single NucleotideSex CharacteristicsConceptsSex-differential effectsSex differencesGenetic architectureBehavioral traitsSingle nucleotide polymorphism (SNP)-based heritabilityGenetic correlationsGenome-wide association summary statisticsSNP-based heritabilityMultiple gene setsOrigins of sex differencesAssociation summary statisticsIdentified 4 genesGene-based approachRisk-taking behaviorIdentified genesGene setsWell-powered studiesBehavioral phenotypesBiological functionsGenetic contributionBetween-sexGenetic effectsTrait pairsGenetic correlation estimatesNeuron-related
2020
Implicit bias of encoded variables: frameworks for addressing structured bias in EHR–GWAS data
Dueñas H, Seah C, Johnson J, Huckins L. Implicit bias of encoded variables: frameworks for addressing structured bias in EHR–GWAS data. Human Molecular Genetics 2020, 29: r33-r41. PMID: 32879975, PMCID: PMC7530523, DOI: 10.1093/hmg/ddaa192.Peer-Reviewed Original ResearchMeSH KeywordsComputational BiologyDiseaseElectronic Health RecordsGenome-Wide Association StudyHumansPhenotypePolymorphism, Single NucleotidePrejudiceConceptsElectronic health recordsUse of electronic health recordsElectronic health record dataElectronic health record analysisGenome-wide association studiesHealth recordsPhenotype definitionAssociation studiesMedical recordsClinical decisionsPhenotypic characterizationPhenotypic analysisClinically useful insightsPotential biasPresentation of diseaseDegree of biasHomogeneous cohortClinicPhenotypeScalable mannerRecordsCohortBias
2019
Synergistic effects of common schizophrenia risk variants
Schrode N, Ho SM, Yamamuro K, Dobbyn A, Huckins L, Matos MR, Cheng E, Deans PJM, Flaherty E, Barretto N, Topol A, Alganem K, Abadali S, Gregory J, Hoelzli E, Phatnani H, Singh V, Girish D, Aronow B, Mccullumsmith R, Hoffman GE, Stahl EA, Morishita H, Sklar P, Brennand KJ. Synergistic effects of common schizophrenia risk variants. Nature Genetics 2019, 51: 1475-1485. PMID: 31548722, PMCID: PMC6778520, DOI: 10.1038/s41588-019-0497-5.Peer-Reviewed Original ResearchMeSH KeywordsChloride ChannelsCRISPR-Cas SystemsFemaleFurinGene EditingGene Expression RegulationGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansInduced Pluripotent Stem CellsMaleMonomeric Clathrin Assembly ProteinsPolymorphism, Single NucleotideQuantitative Trait LociSchizophreniaSNARE ProteinsConceptsExpression quantitative trait lociComplex genetic disorderEQTL genesCommon variantsQuantitative trait lociRisk variantsGene expression differencesPsychiatric disease riskCommon risk variantsPluripotent stem cellsSchizophrenia risk variantsGenetic disordersTrait lociGene perturbationsGenetic approachesExpression differencesGene editingStem cellsGeneralizable phenomenonSynaptic functionGenesVariantsCRISPRLociSpecific effectsGenome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa
Watson H, Yilmaz Z, Thornton L, Hübel C, Coleman J, Gaspar H, Bryois J, Hinney A, Leppä V, Mattheisen M, Medland S, Ripke S, Yao S, Giusti-Rodríguez P, Hanscombe K, Purves K, Adan R, Alfredsson L, Ando T, Andreassen O, Baker J, Berrettini W, Boehm I, Boni C, Perica V, Buehren K, Burghardt R, Cassina M, Cichon S, Clementi M, Cone R, Courtet P, Crow S, Crowley J, Danner U, Davis O, de Zwaan M, Dedoussis G, Degortes D, DeSocio J, Dick D, Dikeos D, Dina C, Dmitrzak-Weglarz M, Docampo E, Duncan L, Egberts K, Ehrlich S, Escaramís G, Esko T, Estivill X, Farmer A, Favaro A, Fernández-Aranda F, Fichter M, Fischer K, Föcker M, Foretova L, Forstner A, Forzan M, Franklin C, Gallinger S, Giegling I, Giuranna J, Gonidakis F, Gorwood P, Mayora M, Guillaume S, Guo Y, Hakonarson H, Hatzikotoulas K, Hauser J, Hebebrand J, Helder S, Herms S, Herpertz-Dahlmann B, Herzog W, Huckins L, Hudson J, Imgart H, Inoko H, Janout V, Jiménez-Murcia S, Julià A, Kalsi G, Kaminská D, Kaprio J, Karhunen L, Karwautz A, Kas M, Kennedy J, Keski-Rahkonen A, Kiezebrink K, Kim Y, Klareskog L, Klump K, Knudsen G, La Via M, Le Hellard S, Levitan R, Li D, Lilenfeld L, Lin B, Lissowska J, Luykx J, Magistretti P, Maj M, Mannik K, Marsal S, Marshall C, Mattingsdal M, McDevitt S, McGuffin P, Metspalu A, Meulenbelt I, Micali N, Mitchell K, Monteleone A, Monteleone P, Munn-Chernoff M, Nacmias B, Navratilova M, Ntalla I, O’Toole J, Ophoff R, Padyukov L, Palotie A, Pantel J, Papezova H, Pinto D, Rabionet R, Raevuori A, Ramoz N, Reichborn-Kjennerud T, Ricca V, Ripatti S, Ritschel F, Roberts M, Rotondo A, Rujescu D, Rybakowski F, Santonastaso P, Scherag A, Scherer S, Schmidt U, Schork N, Schosser A, Seitz J, Slachtova L, Slagboom P, Slof-Op ‘t Landt M, Slopien A, Sorbi S, Świątkowska B, Szatkiewicz J, Tachmazidou I, Tenconi E, Tortorella A, Tozzi F, Treasure J, Tsitsika A, Tyszkiewicz-Nwafor M, Tziouvas K, van Elburg A, van Furth E, Wagner G, Walton E, Widen E, Zeggini E, Zerwas S, Zipfel S, Bergen A, Boden J, Brandt H, Crawford S, Halmi K, Horwood L, Johnson C, Kaplan A, Kaye W, Mitchell J, Olsen C, Pearson J, Pedersen N, Strober M, Werge T, Whiteman D, Woodside D, Stuber G, Gordon S, Grove J, Henders A, Juréus A, Kirk K, Larsen J, Parker R, Petersen L, Jordan J, Kennedy M, Montgomery G, Wade T, Birgegård A, Lichtenstein P, Norring C, Landén M, Martin N, Mortensen P, Sullivan P, Breen G, Bulik C. Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nature Genetics 2019, 51: 1207-1214. PMID: 31308545, PMCID: PMC6779477, DOI: 10.1038/s41588-019-0439-2.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesAssociation studiesTwin-based heritability estimatesEating Disorders Working GroupPsychiatric Genomics ConsortiumAnorexia nervosaBody-mass indexSignificant lociGenetic architectureRisk lociGenetics InitiativeGenomics ConsortiumLow body-mass indexMetabo-psychiatric disorderGenetic correlationsMetabolic componentsLociCases of anorexia nervosaPhysical activityAnthropometric traitsPsychiatric disordersHeritability estimatesAnorexia Nervosa Genetics InitiativeNervosaImprove outcomesGenetic analyses of diverse populations improves discovery for complex traits
Wojcik G, Graff M, Nishimura K, Tao R, Haessler J, Gignoux C, Highland H, Patel Y, Sorokin E, Avery C, Belbin G, Bien S, Cheng I, Cullina S, Hodonsky C, Hu Y, Huckins L, Jeff J, Justice A, Kocarnik J, Lim U, Lin B, Lu Y, Nelson S, Park S, Poisner H, Preuss M, Richard M, Schurmann C, Setiawan V, Sockell A, Vahi K, Verbanck M, Vishnu A, Walker R, Young K, Zubair N, Acuña-Alonso V, Ambite J, Barnes K, Boerwinkle E, Bottinger E, Bustamante C, Caberto C, Canizales-Quinteros S, Conomos M, Deelman E, Do R, Doheny K, Fernández-Rhodes L, Fornage M, Hailu B, Heiss G, Henn B, Hindorff L, Jackson R, Laurie C, Laurie C, Li Y, Lin D, Moreno-Estrada A, Nadkarni G, Norman P, Pooler L, Reiner A, Romm J, Sabatti C, Sandoval K, Sheng X, Stahl E, Stram D, Thornton T, Wassel C, Wilkens L, Winkler C, Yoneyama S, Buyske S, Haiman C, Kooperberg C, Le Marchand L, Loos R, Matise T, North K, Peters U, Kenny E, Carlson C. Genetic analyses of diverse populations improves discovery for complex traits. Nature 2019, 570: 514-518. PMID: 31217584, PMCID: PMC6785182, DOI: 10.1038/s41586-019-1310-4.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesComplex traitsBiology of complex traitsDiverse populationsEvidence of effect-size heterogeneityGenome-wide effortsLarge-scale genomic studiesReduce health disparitiesNon-European individualsHighest burden of diseaseMulti-ethnic participantsEffect-size heterogeneityBurden of diseaseRepresentation of diverse populationsGWAS associationsNovel lociRisk prediction scoreAdmixed populationsFine-mappingGenetic architectureAssociation studiesGenomic studiesHealth disparitiesHealthcare disparitiesPopulation ArchitectureGene expression imputation across multiple brain regions provides insights into schizophrenia risk
Huckins LM, Dobbyn A, Ruderfer DM, Hoffman G, Wang W, Pardiñas AF, Rajagopal VM, Als TD, T. Nguyen H, Girdhar K, Boocock J, Roussos P, Fromer M, Kramer R, Domenici E, Gamazon ER, Purcell S, Demontis D, Børglum A, Walters J, O’Donovan M, Sullivan P, Owen M, Devlin B, Sieberts S, Cox N, Im H, Sklar P, Stahl E. Gene expression imputation across multiple brain regions provides insights into schizophrenia risk. Nature Genetics 2019, 51: 659-674. PMID: 30911161, PMCID: PMC7034316, DOI: 10.1038/s41588-019-0364-4.Peer-Reviewed Original Research
2018
Analysis of shared heritability in common disorders of the brain
Consortium T, Anttila V, Bulik-Sullivan B, Finucane HK, Walters RK, Bras J, Duncan L, Escott-Price V, Falcone GJ, Gormley P, Malik R, Patsopoulos NA, Ripke S, Wei Z, Yu D, Lee PH, Turley P, Grenier-Boley B, Chouraki V, Kamatani Y, Berr C, Letenneur L, Hannequin D, Amouyel P, Boland A, Deleuze JF, Duron E, Vardarajan BN, Reitz C, Goate AM, Huentelman MJ, Kamboh MI, Larson EB, Rogaeva E, St George-Hyslop P, Hakonarson H, Kukull WA, Farrer LA, Barnes LL, Beach TG, Demirci FY, Head E, Hulette CM, Jicha GA, Kauwe JSK, Kaye JA, Leverenz JB, Levey AI, Lieberman AP, Pankratz VS, Poon WW, Quinn JF, Saykin AJ, Schneider LS, Smith AG, Sonnen JA, Stern RA, Van Deerlin VM, Van Eldik LJ, Harold D, Russo G, Rubinsztein DC, Bayer A, Tsolaki M, Proitsi P, Fox NC, Hampel H, Owen MJ, Mead S, Passmore P, Morgan K, Nöthen MM, Schott J, Rossor M, Lupton M, Hoffmann P, Kornhuber J, Lawlor B, McQuillin A, Al-Chalabi A, Bis J, Ruiz A, Boada M, Seshadri S, Beiser A, Rice K, van der Lee S, De Jager P, Geschwind D, Riemenschneider M, Riedel-Heller S, Rotter J, Ransmayr G, Hyman B, Cruchaga C, Alegret M, Winsvold B, Palta P, Farh K, Cuenca-Leon E, Furlotte N, Kurth T, Ligthart L, Terwindt G, Freilinger T, Ran C, Gordon S, Borck G, Adams H, Lehtimäki T, Wedenoja J, Buring J, Schürks M, Hrafnsdottir M, Hottenga J, Penninx B, Artto V, Kaunisto M, Vepsäläinen S, Martin N, Montgomery G, Kurki M, Hämäläinen E, Huang H, Huang J, Sandor C, Webber C, Muller-Myhsok B, Schreiber S, Salomaa V, Loehrer E, Göbel H, Macaya A, Pozo-Rosich P, Hansen T, Werge T, Kaprio J, Metspalu A, Kubisch C, Ferrari M, Belin A, van den Maagdenberg A, Zwart J, Boomsma D, Eriksson N, Olesen J, Chasman D, Nyholt D, Anney R, Avbersek A, Baum L, Berkovic S, Bradfield J, Buono R, Catarino C, Cossette P, De Jonghe P, Depondt C, Dlugos D, Ferraro T, French J, Hjalgrim H, Jamnadas-Khoda J, Kälviäinen R, Kunz W, Lerche H, Leu C, Lindhout D, Lo W, Lowenstein D, McCormack M, Møller R, Molloy A, Ng P, Oliver K, Privitera M, Radtke R, Ruppert A, Sander T, Schachter S, Schankin C, Scheffer I, Schoch S, Sisodiya S, Smith P, Sperling M, Striano P, Surges R, Thomas G, Visscher F, Whelan C, Zara F, Heinzen E, Marson A, Becker F, Stroink H, Zimprich F, Gasser T, Gibbs R, Heutink P, Martinez M, Morris H, Sharma M, Ryten M, Mok K, Pulit S, Bevan S, Holliday E, Attia J, Battey T, Boncoraglio G, Thijs V, Chen W, Mitchell B, Rothwell P, Sharma P, Sudlow C, Vicente A, Markus H, Kourkoulis C, Pera J, Raffeld M, Silliman S, Perica V, Thornton L, Huckins L, Rayner N, Lewis C, Gratacos M, Rybakowski F, Keski-Rahkonen A, Raevuori A, Hudson J, Reichborn-Kjennerud T, Monteleone P, Karwautz A, Mannik K, Baker J, O’Toole J, Trace S, Davis O, Helder S, Ehrlich S, Herpertz-Dahlmann B, Danner U, van Elburg A, Clementi M, Forzan M, Docampo E, Lissowska J, Hauser J, Tortorella A, Maj M, Gonidakis F, Tziouvas K, Papezova H, Yilmaz Z, Wagner G, Cohen-Woods S, Herms S, Julià A, Rabionet R, Dick D, Ripatti S, Andreassen O, Espeseth T, Lundervold A, Steen V, Pinto D, Scherer S, Aschauer H, Schosser A, Alfredsson L, Padyukov L, Halmi K, Mitchell J, Strober M, Bergen A, Kaye W, Szatkiewicz J, Cormand B, Ramos-Quiroga J, Sánchez-Mora C, Ribasés M, Casas M, Hervas A, Arranz M, Haavik J, Zayats T, Johansson S, Williams N, Elia J, Dempfle A, Rothenberger A, Kuntsi J, Oades R, Banaschewski T, Franke B, Buitelaar J, Vasquez A, Doyle A, Reif A, Lesch K, Freitag C, Rivero O, Palmason H, Romanos M, Langley K, Rietschel M, Witt S, Dalsgaard S, Børglum A, Waldman I, Wilmot B, Molly N, Bau C, Crosbie J, Schachar R, Loo S, McGough J, Grevet E, Medland S, Robinson E, Weiss L, Bacchelli E, Bailey A, Bal V, Battaglia A, Betancur C, Bolton P, Cantor R, Celestino-Soper P, Dawson G, De Rubeis S, Duque F, Green A, Klauck S, Leboyer M, Levitt P, Maestrini E, Mane S, De-Luca D, Parr J, Regan R, Reichenberg A, Sandin S, Vorstman J, Wassink T, Wijsman E, Cook E, Santangelo S, Delorme R, Rogé B, Magalhaes T, Arking D, Schulze T, Thompson R, Strohmaier J, Matthews K, Melle I, Morris D, Blackwood D, McIntosh A, Bergen S, Schalling M, Jamain S, Maaser A, Fischer S, Reinbold C, Fullerton J, Grigoroiu-Serbanescu M, Guzman-Parra J, Mayoral F, Schofield P, Cichon S, Mühleisen T, Degenhardt F, Schumacher J, Bauer M, Mitchell P, Gershon E, Rice J, Potash J, Zandi P, Craddock N, Ferrier I, Alda M, Rouleau G, Turecki G, Ophoff R, Pato C, Anjorin A, Stahl E, Leber M, Czerski P, Edenberg H, Cruceanu C, Jones I, Posthuma D, Andlauer T, Forstner A, Streit F, Baune B, Air T, Sinnamon G, Wray N, MacIntyre D, Porteous D, Homuth G, Rivera M, Grove J, Middeldorp C, Hickie I, Pergadia M, Mehta D, Smit J, Jansen R, de Geus E, Dunn E, Li Q, Nauck M, Schoevers R, Beekman A, Knowles J, Viktorin A, Arnold P, Barr C, Bedoya-Berrio G, Bienvenu O, Brentani H, Burton C, Camarena B, Cappi C, Cath D, Cavallini M, Cusi D, Darrow S, Denys D, Derks E, Dietrich A, Fernandez T, Figee M, Freimer N, Gerber G, Grados M, Greenberg E, Hanna G, Hartmann A, Hirschtritt M, Hoekstra P, Huang A, Huyser C, Illmann C, Jenike M, Kuperman S, Leventhal B, Lochner C, Lyon G, Macciardi F, Madruga-Garrido M, Malaty I, Maras A, McGrath L, Miguel E, Mir P, Nestadt G, Nicolini H, Okun M, Pakstis A, Paschou P, Piacentini J, Pittenger C, Plessen K, Ramensky V, Ramos E, Reus V, Richter M, Riddle M, Robertson M, Roessner V, Rosário M, Samuels J, Sandor P, Stein D, Tsetsos F, Van Nieuwerburgh F, Weatherall S, Wendland J, Wolanczyk T, Worbe Y, Zai G, Goes F, McLaughlin N, Nestadt P, Grabe H, Depienne C, Konkashbaev A, Lanzagorta N, Valencia-Duarte A, Bramon E, Buccola N, Cahn W, Cairns M, Chong S, Cohen D, Crespo-Facorro B, Crowley J, Davidson M, DeLisi L, Dinan T, Donohoe G, Drapeau E, Duan J, Haan L, Hougaard D, Karachanak-Yankova S, Khrunin A, Klovins J, Kučinskas V, Keong J, Limborska S, Loughland C, Lönnqvist J, Maher B, Mattheisen M, McDonald C, Murphy K, Murray R, Nenadic I, van Os J, Pantelis C, Pato M, Petryshen T, Quested D, Roussos P, Sanders A, Schall U, Schwab S, Sim K, So H, Stögmann E, Subramaniam M, Toncheva D, Waddington J, Walters J, Weiser M, Cheng W, Cloninger R, Curtis D, Gejman P, Henskens F, Mattingsdal M, Oh S, Scott R, Webb B, Breen G, Churchhouse C, Bulik C, Daly M, Dichgans M, Faraone S, Guerreiro R, Holmans P, Kendler K, Koeleman B, Mathews C, Price A, Scharf J, Sklar P, Williams J, Wood N, Cotsapas C, Palotie A, Smoller J, Sullivan P, Rosand J, Corvin A, Neale B. Analysis of shared heritability in common disorders of the brain. Science 2018, 360 PMID: 29930110, PMCID: PMC6097237, DOI: 10.1126/science.aap8757.Peer-Reviewed Original ResearchMeSH KeywordsBrain DiseasesGenetic VariationGenome-Wide Association StudyHumansMental DisordersPhenotypeQuantitative Trait, HeritableRisk FactorsConceptsPsychiatric disordersBrain disordersCommon variant riskRisk factorsCommon disorderNeurological disordersDiagnostic misclassificationBrain phenotypesCommon genetic variationControl participantsDisordersVariant riskPhenotypic heterogeneityBrainEtiologic overlapGenetic sharingGenome-wide association studiesCognitive measuresAssociation studiesPhenotype