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 ResearchEating disorders: are gut microbiota to blame?
Xu J, Carroll I, Huckins L. Eating disorders: are gut microbiota to blame? Trends In Molecular Medicine 2023, 30: 317-320. PMID: 38040602, PMCID: PMC11009075, DOI: 10.1016/j.molmed.2023.11.007.Peer-Reviewed Original ResearchGenetically 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 ResearchConceptsGenetically 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 ResearchConceptsOpioid 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 ResearchConceptsHuman 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 ResearchConceptsBioinformatics 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 ResearchConceptsProtein-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
Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression
Seah C, Breen M, Rusielewicz T, Bader H, Xu C, Hunter C, McCarthy B, Deans P, Chattopadhyay M, Goldberg J, Desarnaud F, Makotkine I, Flory J, Bierer L, Staniskyte M, Noggle S, Huckins L, Paull D, Brennand K, Yehuda R. Modeling gene × environment interactions in PTSD using human neurons reveals diagnosis-specific glucocorticoid-induced gene expression. Nature Neuroscience 2022, 25: 1434-1445. PMID: 36266471, PMCID: PMC9630117, DOI: 10.1038/s41593-022-01161-y.Peer-Reviewed Original ResearchConceptsPost-traumatic stress disorderPeripheral blood mononuclear cellsGlucocorticoid-induced changesGlucocorticoid-induced gene expressionBlood mononuclear cellsIndividual clinical outcomesEnvironmental risk factorsHuman postmortem brainGlucocorticoid hypersensitivityClinical outcomesGlutamatergic neuronsMononuclear cellsRisk factorsHydrocortisone exposureSevere traumaPostmortem brainsHuman neuronsGlucocorticoid responseInduced neuronsStress disorderNeuronsNew therapeuticsGene expressionGene × environment interactionsCombat veteransStem 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 ResearchConceptsStem 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 studiesConcerns about the use of polygenic embryo screening for psychiatric and cognitive traits
Lencz T, Sabatello M, Docherty A, Peterson R, Soda T, Austin J, Bierut L, Crepaz-Keay D, Curtis D, Degenhardt F, Huckins L, Lazaro-Munoz G, Mattheisen M, Meiser B, Peay H, Rietschel M, Walss-Bass C, Davis L. Concerns about the use of polygenic embryo screening for psychiatric and cognitive traits. The Lancet Psychiatry 2022, 9: 838-844. PMID: 35931093, PMCID: PMC9930635, DOI: 10.1016/s2215-0366(22)00157-2.Peer-Reviewed Original ResearchConceptsRisk of complex diseasesPolygenic risk scoresEthical issuesEthical implicationsPersonal viewEmbryo screeningGenetic riskRisk scorePolygenic embryo screeningPsychiatric geneticsInternational Society of Psychiatric GeneticsComplex diseasesViewsPsychiatric disordersRelevant stakeholdersScreeningIn vitro fertilisationScreen embryosInternational SocietyPersonsPrivate companiesSocietyClinical applicationExploring 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 ResearchConceptsElectronic 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 studyWhat next for eating disorder genetics? Replacing myths with facts to sharpen our understanding
Huckins LM, Signer R, Johnson J, Wu YK, Mitchell KS, Bulik CM. What next for eating disorder genetics? Replacing myths with facts to sharpen our understanding. Molecular Psychiatry 2022, 27: 3929-3938. PMID: 35595976, PMCID: PMC9718676, DOI: 10.1038/s41380-022-01601-y.Peer-Reviewed Original ResearchMapping 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 ResearchConceptsBody 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 ResearchConceptsAncestrally 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 ResearchAltered gene expression and PTSD symptom dimensions in World Trade Center responders
Marchese S, Cancelmo L, Diab O, Cahn L, Aaronson C, Daskalakis NP, Schaffer J, Horn SR, Johnson JS, Schechter C, Desarnaud F, Bierer LM, Makotkine I, Flory JD, Crane M, Moline JM, Udasin IG, Harrison DJ, Roussos P, Charney DS, Koenen KC, Southwick SM, Yehuda R, Pietrzak RH, Huckins LM, Feder A. Altered gene expression and PTSD symptom dimensions in World Trade Center responders. Molecular Psychiatry 2022, 27: 2225-2246. PMID: 35177824, DOI: 10.1038/s41380-022-01457-2.Peer-Reviewed Original ResearchConceptsPTSD symptom dimensionsPosttraumatic stress disorderCAPS scoresAnxious arousal symptomsSymptom dimensionsWorld Trade Center rescueClinician-Administered PTSD Scale scoresBiomarker of PTSDArousal symptomsCD4 T cellsWorld Trade Center respondersDevelopment of PTSDTotal CAPS scoresCase/control statusTherapeutic target developmentIdentification of biomarkersClinical interview dataResponder cohortPTSD symptom severityPotential biological differencesWTC respondersT cellsGene expressionPTSD studiesPsychiatric disorders
2021
Induction of dopaminergic neurons for neuronal subtype-specific modeling of psychiatric disease risk
Powell SK, O’Shea C, Townsley K, Prytkova I, Dobrindt K, Elahi R, Iskhakova M, Lambert T, Valada A, Liao W, Ho SM, Slesinger PA, Huckins LM, Akbarian S, Brennand KJ. Induction of dopaminergic neurons for neuronal subtype-specific modeling of psychiatric disease risk. Molecular Psychiatry 2021, 28: 1970-1982. PMID: 34493831, PMCID: PMC8898985, DOI: 10.1038/s41380-021-01273-0.Peer-Reviewed Original ResearchConceptsInduced dopaminergic neuronsDopaminergic neuronsMidbrain dopaminergic neuron developmentNeuron identityHuman induced pluripotent stem cellsCannabis use disorderDopaminergic neuron developmentAction potential durationGlutamatergic neuronsDopamine synthesisSpontaneous burstsPotential durationUse disordersNeuronal subtypesPsychiatric diseasesBipolar disorderElectrophysiological propertiesDisease riskHyperpolarization potentialPsychiatric disease riskNeuron developmentOscillatory activityNeuronsHeterogenous cell populationsCell populationsMulti-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 ResearchConceptsGenome-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 ResearchConceptsSex-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