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 traitsIntegrating 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
Mapping 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 sample
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 participants
2020
Analysis of Genetically Regulated Gene Expression Identifies a Prefrontal PTSD Gene, SNRNP35, Specific to Military Cohorts
Huckins L, Chatzinakos C, Breen M, Hartmann J, Klengel T, da Silva Almeida A, Dobbyn A, Girdhar K, Hoffman G, Klengel C, Logue M, Lori A, Maihofer A, Morrison F, Nguyen H, Park Y, Ruderfer D, Sloofman L, van Rooij S, Consortium P, Baker D, Chen C, Cox N, Duncan L, Geyer M, Glatt S, Im H, Risbrough V, Smoller J, Stein D, Yehuda R, Liberzon I, Koenen K, Jovanovic T, Kellis M, Miller M, Bacanu S, Nievergelt C, Buxbaum J, Sklar P, Ressler K, Stahl E, Daskalakis N. Analysis of Genetically Regulated Gene Expression Identifies a Prefrontal PTSD Gene, SNRNP35, Specific to Military Cohorts. Cell Reports 2020, 31: 107716. PMID: 32492425, PMCID: PMC7359754, DOI: 10.1016/j.celrep.2020.107716.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsCase-Control StudiesCohort StudiesDexamethasoneDown-RegulationGene Expression RegulationGene Regulatory NetworksGenetic Predisposition to DiseaseHumansLeukocytesMaleMiceMice, Inbred C57BLMilitary PersonnelPrefrontal CortexRepressor ProteinsRibonucleoproteins, Small NuclearRNA InterferenceRNA, Small InterferingStress Disorders, Post-TraumaticConceptsPost-traumatic stress disorderGenetically regulated gene expressionPost-traumatic stress disorder casesDorsolateral prefrontal cortexGene expressionU12 intron splicingPrefrontal cortexStress disorderDeployment stressTranscriptome imputationTissue-specific gene expressionDifferential gene expressionMilitary cohortZNF140U12 intronsGenetic heterogeneityExpression changesFunctional roleExogenous glucocorticoidsPeripheral leukocytesEuropean cohortCortexCohortDisordersExpression
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 effectsPenetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients Across Four Health Care Systems
Zheutlin A, Dennis J, Karlsson Linnér R, Moscati A, Restrepo N, Straub P, Ruderfer D, Castro V, Chen C, Ge T, Huckins L, Charney A, Kirchner H, Stahl E, Chabris C, Davis L, Smoller J. Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients Across Four Health Care Systems. American Journal Of Psychiatry 2019, 176: 846-855. PMID: 31416338, PMCID: PMC6961974, DOI: 10.1176/appi.ajp.2019.18091085.Peer-Reviewed Original ResearchMeSH KeywordsDelivery of Health CareFemaleGenetic PleiotropyGenetic Predisposition to DiseaseHumansMaleMiddle AgedMultifactorial InheritancePenetranceRisk FactorsSchizophreniaConceptsPolygenic risk scoresHealth care systemCare systemGenetic riskAssociated with schizophreniaPolygenic risk score distributionPhenome-wide association studyMeasures of genetic riskRisk scoreHighest risk decileHealth care settingsElectronic health recordsOdds of schizophreniaAssociated with other phenotypesCare settingsRisk decileHealth recordsHigher oddsHealth consequencesResearch cohortAssociation studiesHealthEarly interventionMeta-analysisPersonality disorderGenome-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 ResearchMeSH KeywordsAdultAnorexia NervosaBody Mass IndexCase-Control StudiesFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyGenomicsHumansMaleMental DisordersMetabolic DiseasesPhenotypePrognosisQuantitative Trait LociConceptsGenome-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 outcomesGene 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
Recent Genetics and Epigenetics Approaches to PTSD
Daskalakis N, Rijal C, King C, Huckins L, Ressler K. Recent Genetics and Epigenetics Approaches to PTSD. Current Psychiatry Reports 2018, 20: 30. PMID: 29623448, PMCID: PMC6486832, DOI: 10.1007/s11920-018-0898-7.Peer-Reviewed Original ResearchMeSH KeywordsEpigenesis, GeneticEpigenomicsGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansStress Disorders, Post-TraumaticConceptsPosttraumatic stress disorderTrauma exposureGenome-wide association studiesEpigenetic approachesTargeted genetic studiesEpigenome-wide studiesInduce epigenetic changesResponse to trauma exposureAssociation studiesAdult trauma exposureGenetic studiesNegative emotional symptomsEpigenetic alterationsEpigenetic changesFunctional regulationEpigenetic riskIntrusive memoriesStress disorderTraumatic exposureImpaired cognitionEmotional symptomsAvoidance behaviorDisability syndromeBiological riskElectronic medical recordsCommon schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection
Pardiñas A, Holmans P, Pocklington A, Escott-Price V, Ripke S, Carrera N, Legge S, Bishop S, Cameron D, Hamshere M, Han J, Hubbard L, Lynham A, Mantripragada K, Rees E, MacCabe J, McCarroll S, Baune B, Breen G, Byrne E, Dannlowski U, Eley T, Hayward C, Martin N, McIntosh A, Plomin R, Porteous D, Wray N, Caballero A, Geschwind D, Huckins L, Ruderfer D, Santiago E, Sklar P, Stahl E, Won H, Agerbo E, Als T, Andreassen O, Bækvad-Hansen M, Mortensen P, Pedersen C, Børglum A, Bybjerg-Grauholm J, Djurovic S, Durmishi N, Pedersen M, Golimbet V, Grove J, Hougaard D, Mattheisen M, Molden E, Mors O, Nordentoft M, Pejovic-Milovancevic M, Sigurdsson E, Silagadze T, Hansen C, Stefansson K, Stefansson H, Steinberg S, Tosato S, Werge T, GERAD1 Consortium, CRESTAR Consortium, Collier D, Rujescu D, Kirov G, Owen M, O’Donovan M, Walters J. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nature Genetics 2018, 50: 381-389. PMID: 29483656, PMCID: PMC5918692, DOI: 10.1038/s41588-018-0059-2.Peer-Reviewed Original ResearchMeSH KeywordsAllelesCase-Control StudiesGene FrequencyGenes, LethalGenetic LociGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansInheritance PatternsPolymorphism, Single NucleotideSchizophreniaSelection, GeneticConceptsMutation-intolerant genesGenetic architecture of schizophreniaGenome-wide association studiesChromosome conformation dataGenome fine mappingVariant association signalsAssociation signalsFine-mappingGenetic architectureCausal genesGenomic studiesAssociation studiesRisk variantsSelection pressureGenesLociBrain expressionAssociated with poor qualityBiologyConformational dataDecreased life expectancyChromosomeDebilitating psychiatric conditionAllelesLife expectancy
2017
Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa
Huckins L, Hatzikotoulas K, Southam L, Thornton L, Steinberg J, Aguilera-McKay F, Treasure J, Schmidt U, Gunasinghe C, Romero A, Curtis C, Rhodes D, Moens J, Kalsi G, Dempster D, Leung R, Keohane A, Burghardt R, Ehrlich S, Hebebrand J, Hinney A, Ludolph A, Walton E, Deloukas P, Hofman A, Palotie A, Palta P, van Rooij F, Stirrups K, Adan R, Boni C, Cone R, Dedoussis G, van Furth E, Gonidakis F, Gorwood P, Hudson J, Kaprio J, Kas M, Keski-Rahonen A, Kiezebrink K, Knudsen G, Slof-Op 't Landt M, Maj M, Monteleone A, Monteleone P, Raevuori A, Reichborn-Kjennerud T, Tozzi F, Tsitsika A, van Elburg A, Collier D, Sullivan P, Breen G, Bulik C, Zeggini E. Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa. Molecular Psychiatry 2017, 23: 1169-1180. PMID: 29155802, PMCID: PMC5828108, DOI: 10.1038/mp.2017.88.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide significanceGenomic search spaceGenome-wide variationLow-frequency variantsDetect low-frequency variantsPopulations of European originDe novo replicationIntergenic variantVariant associationsExome-chipAssociation studiesIntronic variantsRare variantsIn silicoEuropean originVariantsEffect sizeLociOPCMLWell-poweredSilicoReplicationNeuropsychiatric disorders