2025
Leveraging local ancestry and cross-ancestry genetic architecture to improve genetic prediction of complex traits in admixed populations
Zhou G, Yolou I, Xie Y, Zhao H. Leveraging local ancestry and cross-ancestry genetic architecture to improve genetic prediction of complex traits in admixed populations. American Journal Of Human Genetics 2025, 112: 1923-1935. PMID: 40633541, PMCID: PMC12252582, DOI: 10.1016/j.ajhg.2025.06.010.Peer-Reviewed Original ResearchMeSH KeywordsBlack PeopleComputer SimulationGenetics, PopulationGenome-Wide Association StudyHumansModels, GeneticMultifactorial InheritancePhenotypePolymorphism, Single NucleotideWhite PeopleConceptsPolygenic risk scoresAdmixed individualsNon-European populationsLocal ancestryTransferability of PRSPerformance of polygenic risk scoresAdmixed populationsCross-ancestryPolygenic risk score calculatorGenetic prediction of complex traitsGenetic predictionEffect sizePrediction of complex traitsPopulation ArchitectureUK BiobankPolygenic predictionAdmixed AmericansAncestry clustersGenetic architectureComplex traitsPRS modelRisk scoreGenetic variantsAncestryIndividualsRobust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk
Hu J, Ye Y, Zhang C, Ruan Y, Natarajan P, Zhao H. Robust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk. PLOS Computational Biology 2025, 21: e1013191. PMID: 40570042, PMCID: PMC12212871, DOI: 10.1371/journal.pcbi.1013191.Peer-Reviewed Original ResearchConceptsPolygenic risk scoresCAD-PRSUK BiobankCoronary artery disease polygenic risk scoreSummary-level dataCAD-related traitsSamples of European ancestryCoronary artery diseaseHigh-risk individualsPotential genetic heterogeneityCurrent smokingPolygenic scoresPolygenic riskTargeted interventionsEuropean ancestryRisk scorePleiotropic regionsRisk predictionGenetic heterogeneityBiological functionsPleiotropySignificant interactionPhenotypic heterogeneityBlood pressureDisease interpretationA Bayesian approach to correcting the attenuation bias of regression using polygenic risk score
Zhou G, Qie X, Zhao H. A Bayesian approach to correcting the attenuation bias of regression using polygenic risk score. Genetics 2025, 229: iyaf018. PMID: 39891671, PMCID: PMC12168083, DOI: 10.1093/genetics/iyaf018.Peer-Reviewed Original ResearchMeSH KeywordsBayes TheoremGenetic Risk ScoreHumansModels, GeneticMultifactorial InheritanceRegression AnalysisConceptsPolygenic risk scoresRisk scoreEstimation of regression coefficientsBayesian approachMeasurement error modelEstimation of coefficientsCoverage probabilityBayesian measurement error modelsAttenuation biasCredible intervalsCoefficient estimatesUK BiobankLogistic regressionMeasurement errorRegression coefficientsRegression modelsComplex traitsRegression analysisScoresEstimationError modelRegressionBiobankErrorCovariatesPolygenic Susceptibility to Diabetes and Poor Glycemic Control in Stroke Survivors
Demarais Z, Conlon C, Rivier C, Clocchiatti-Tuozzo S, Renedo D, Torres-Lopez V, Sheth K, Meeker D, Zhao H, Ohno-Machado L, Acosta J, Huo S, Falcone G. Polygenic Susceptibility to Diabetes and Poor Glycemic Control in Stroke Survivors. Neurology 2025, 104: e210276. PMID: 39889253, DOI: 10.1212/wnl.0000000000210276.Peer-Reviewed Original ResearchConceptsStroke survivorsWorse glycemic controlPoor glycemic controlStroke patientsAssociated with worse glycemic controlGlycemic controlPolygenic risk scoresClinical management of stroke patientsAssociated with poor glycemic controlManagement of stroke patientsCross-sectional designGenetic association studiesUncontrolled diabetesSusceptibility to T2DMUK BiobankType 2 diabetes mellitusAdverse vascular outcomesRisk scoreAssociation studiesHemoglobin A1cSurvivorsVascular outcomesSusceptibility to diabetesStrokeDiabetesThe left amygdala is genetically sexually-dimorphic: multi-omics analysis of structural MRI volumes
Gui Y, Zhou G, Cui S, Li H, Lu H, Zhao H. The left amygdala is genetically sexually-dimorphic: multi-omics analysis of structural MRI volumes. Translational Psychiatry 2025, 15: 17. PMID: 39843917, PMCID: PMC11754786, DOI: 10.1038/s41398-025-03223-8.Peer-Reviewed Original ResearchMeSH KeywordsAdultAmygdalaFemaleHumansMagnetic Resonance ImagingMaleMental DisordersMultifactorial InheritanceMultiomicsOrgan SizeSchizophreniaSex CharacteristicsTranscriptomeConceptsLeft amygdala volumePolygenic risk scoresLeft amygdalaSex differencesBrain volumeMental disordersAmygdala volumeBrain anatomyEffect of polygenic risk scoresStudy of sex differencesExamined sex differencesPsychiatric Genomics ConsortiumMechanisms of sex differencesSex-specific genetic correlationsGenetic correlation analysisAmygdalaStructural MRI volumesSexually-dimorphicGenetic correlationsBrainDisordersRNA-seq dataGenomics ConsortiumCell-type compositionKnowledge of genetic basisPerformance of Polygenic Risk Scores for Primary Open-Angle Glaucoma in Populations of African Descent
Chang-Wolf J, Kinzy T, Driessen S, Cruz L, Iyengar S, Peachey N, Aung T, Khor C, Williams S, Ramsay M, Olawoye O, Ashaye A, Klaver C, Hauser M, Thiadens A, Cooke Bailey J, Bonnemaijer P, Sanywia A, Cook C, Hassan H, Kanyaro N, Ntomoka C, Allingham R, van der Heide C, Taylor K, Rotter J, Wang S, ABDULLAHI S, Abu-Amero K, Anderson M, Akafo S, ALHASSAN M, Asimadu I, Ayyagari R, BAKAYOKO S, BIANGOUP NYAMSI P, Bowden D, Bromley W, Budenz D, Carmichael T, Challa P, Chen Y, Chuka-Okosa C, Costa V, Cruz D, DuBiner H, Ervin J, Feldman R, Flamme-Wiese M, Gaasterland D, Garnai S, Girkin C, GUIROU N, Guo X, Haines J, Hammond C, Herndon L, Hoffmann T, Hulette C, Hydara A, Igo Jr. R, Jorgenson E, KABWE J, KILANGALANGA N, Kizor-Akaraiwe N, Kuchtey R, LAMARI H, Li Z, Liebmann J, Liu Y, Loos R, Melo M, Moroi S, Msosa J, Mullins R, Nadkarni G, NAPO A, Ng M, Nunes H, Obeng-Nyarkoh E, Okeke A, Okeke S, OLANIYI O, Oliveira M, Pasquale L, Perez-Grossmann R, Pericak-Vance M, Qin X, RESNIKOFF S, Richards J, Schimiti R, Sim K, Sponsel W, Svidnicki P, Uche N, van Duijn C, Vasconcellos J, Wiggs J, Zangwill L, Risch N, Milea D, Weinreb R, Ashley-Koch A, Fingert J, Aslan M, Antonelli M, de Asis M, Bauer M, Brophy M, Concato J, Cunningham F, Freedman R, Gaziano M, Gleason T, Harvey P, Huang G, Kelsoe J, Kosten T, Lehner T, Lohr J, Marder S, Miller P, O Leary T, Patterson T, Peduzzi P, Przygodski R, Siever L, Sklar P, Strakowski S, Zhao H, Fanous A, Farwell W, Malhorta A, Mane S, Palacios P, Bigdeli T, Corsey M, Zaluda L, Johnson J, Sueiro M, Cavaliere D, Jeanpaul V, Maffucci A, Mancini L, Deen J, Muldoon G, Whitbourne S, Canive J, Adamson L, Calais L, Fuldauer G, Kushner R, Toney G, Lackey M, Mank A, Mahdavi N, Villarreal G, Muly E, Amin F, Dent M, Wold J, Fischer B, Elliott A, Felix C, Gill G, Parker P, Logan C, McAlpine J, DeLisi L, Reece S, Hammer M, Agbor‐Tabie D, Goodson W, Aslam M, Grainger M, Richtand N, Rybalsky A, Al Jurdi R, Boeckman E, Natividad T, Smith D, Stewart M, Torres S, Zhao Z, Mayeda A, Green A, Hofstetter J, Ngombu S, Scott M, Strasburger A, Sumner J, Paschall G, Mucciarelli J, Owen R, Theus S, Tompkins D, Potkin S, Reist C, Novin M, Khalaghizadeh S, Douyon R, Kumar N, Martinez B, Sponheim S, Bender T, Lucas H, Lyon A, Marggraf M, Sorensen L, Surerus C, Sison C, Amato J, Johnson D, Pagan‐Howard N, Adler L, Alerpin S, Leon T, Mattocks K, Araeva N, Sullivan J, Suppes T, Bratcher K, Drag L, Fischer E, Fujitani L, Gill S, Grimm D, Hoblyn J, Nguyen T, Nikolaev E, Shere L, Relova R, Vicencio A, Yip M, Hurford I, Acheampong S, Carfagno G, Haas G, Appelt C, Brown E, Chakraborty B, Kelly E, Klima G, Steinhauer S, Hurley R, Belle R, Eknoyan D, Johnson K, Lamotte J, Granholm E, Bradshaw K, Holden J, Jones R, Le T, Molina I, Peyton M, Ruiz I, Sally L, Tapp A, Devroy S, Jain V, Kilzieh N, Maus L, Miller K, Pope H, Wood A, Meyer E, Givens P, Hicks P, Justice S, McNair K, Pena J, Tharp D, Davis L, Ban M, Cheatum L, Darr P, Grayson W, Munford J, Whitfield B, Wilson E, Melnikoff S, Schwartz B, Tureson M, D Souza D, Forselius K, Ranganathan M, Rispoli L, Sather M, Colling C, Haakenson C, Kruegar D, Muralidhar S, Ramoni R, Breeling J, Chang K, O Donnell C, Tsao P, Moser J, Brewer J, Warren S, Argyres D, Stevens B, Humphries D, Do N, Shayan S, Nguyen X, Pyarajan S, Cho K, Hauser E, Sun Y, Wilson P, McArdle R, Dellitalia L, Harley J, Whittle J. Performance of Polygenic Risk Scores for Primary Open-Angle Glaucoma in Populations of African Descent. JAMA Ophthalmology 2025, 143: 7-14. PMID: 39541127, PMCID: PMC11565374, DOI: 10.1001/jamaophthalmol.2024.4784.Peer-Reviewed Original ResearchConceptsPrimary open-angle glaucomaEuropean ancestry groupsArea under the receiver operating characteristic curveAfrican descentSouth AfricaOpen-angle glaucomaCross-sectional studyIndividuals of African descentBaseline of ageAfrican ancestryOdds ratioGlaucoma patientsRisk stratificationMillion Veteran ProgramPolygenic risk scoresGenetics of glaucomaRisk scorePatients of African descentEuropean ancestryRisk quintileReceiver operating characteristic curveGhanaiansGhanaPopulations of African descentAmerican individuals
2024
LDER-GE estimates phenotypic variance component of gene–environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information
Dong Z, Jiang W, Li H, DeWan A, Zhao H. LDER-GE estimates phenotypic variance component of gene–environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information. Briefings In Bioinformatics 2024, 25: bbae335. PMID: 38980374, PMCID: PMC11232466, DOI: 10.1093/bib/bbae335.Peer-Reviewed Original ResearchMeSH KeywordsGene-Environment InteractionGenome-Wide Association StudyHumansLinkage DisequilibriumModels, GeneticMultifactorial InheritancePhenotypePolymorphism, Single NucleotideConceptsHuman complex traitsComplex traitsGene-environment interactionsGene-environmentLinkage disequilibriumPhenotypic variance componentsPhenotypic varianceProportion of phenotypic varianceSummary statisticsEuropean ancestry subjectsUK Biobank dataAssociation summary statisticsComplete linkage disequilibriumControlled type I error ratesLD informationLD matrixVariance componentsBiobank dataType I error rateEuropean ancestrySample size increaseGenetic effectsTraitsE-I pairsSimulation studyTuning parameters for polygenic risk score methods using GWAS summary statistics from training data
Jiang W, Chen L, Girgenti M, Zhao H. Tuning parameters for polygenic risk score methods using GWAS summary statistics from training data. Nature Communications 2024, 15: 24. PMID: 38169469, PMCID: PMC10762162, DOI: 10.1038/s41467-023-44009-0.Peer-Reviewed Original Research
2023
OTTERS: a powerful TWAS framework leveraging summary-level reference data
Dai Q, Zhou G, Zhao H, Võsa U, Franke L, Battle A, Teumer A, Lehtimäki T, Raitakari O, Esko T, Epstein M, Yang J. OTTERS: a powerful TWAS framework leveraging summary-level reference data. Nature Communications 2023, 14: 1271. PMID: 36882394, PMCID: PMC9992663, DOI: 10.1038/s41467-023-36862-w.Peer-Reviewed Original Research
2022
SDPRX: A statistical method for cross-population prediction of complex traits
Zhou G, Chen T, Zhao H. SDPRX: A statistical method for cross-population prediction of complex traits. American Journal Of Human Genetics 2022, 110: 13-22. PMID: 36460009, PMCID: PMC9892700, DOI: 10.1016/j.ajhg.2022.11.007.Peer-Reviewed Original ResearchMeSH KeywordsGenetic Predisposition to DiseaseGenome-Wide Association StudyGenotypeHumansMultifactorial InheritanceRisk FactorsConceptsStatistical methodsJoint distributionWide association study (GWAS) summary statisticsNon-European populationsReal traitsSummary statisticsCross-population predictionPrediction accuracyGenome-wide association study summary statisticsLinkage disequilibrium differencesPrediction performancePolygenic risk scoresComplex traitsStatisticsSimulationsApplicationsTraitsSex-specific genetic association between psychiatric disorders and cognition, behavior and brain imaging in children and adults
Gui Y, Zhou X, Wang Z, Zhang Y, Wang Z, Zhou G, Zhao Y, Liu M, Lu H, Zhao H. Sex-specific genetic association between psychiatric disorders and cognition, behavior and brain imaging in children and adults. Translational Psychiatry 2022, 12: 347. PMID: 36028495, PMCID: PMC9418275, DOI: 10.1038/s41398-022-02041-6.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultChildCognitionFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleMental DisordersMultifactorial InheritanceNeuroimagingRisk FactorsConceptsCognitive functionFluid intelligenceCognitive traitsAdolescent Brain Cognitive Development (ABCD) studyPsychiatric disordersCognitive Development StudyMediation effectMost psychiatric disordersPolygenic risk scoresBrain functionBrain structuresBrain imagingEarly etiologySex differencesDevelopment studiesPsychiatric traitsChildrenIntelligenceDisordersSchizophreniaGenetic riskAdultsTraitsCognitionAutismLeveraging LD eigenvalue regression to improve the estimation of SNP heritability and confounding inflation
Song S, Jiang W, Zhang Y, Hou L, Zhao H. Leveraging LD eigenvalue regression to improve the estimation of SNP heritability and confounding inflation. American Journal Of Human Genetics 2022, 109: 802-811. PMID: 35421325, PMCID: PMC9118121, DOI: 10.1016/j.ajhg.2022.03.013.Peer-Reviewed Original ResearchMeSH KeywordsGenome-Wide Association StudyHumansLinkage DisequilibriumModels, GeneticMultifactorial InheritancePhenotypePolymorphism, Single NucleotideConceptsLinkage disequilibrium score regressionComplex traitsSingle nucleotide polymorphismsSNP heritabilityGenome-wide association studiesDisequilibrium score regressionHigh-throughput technologiesHeritable phenotypesAssociation studiesGenetic studiesCryptic relatednessLD informationScore regressionHeritabilityGenetic contributionHeritability estimationPopulation stratificationDisease mechanismsTraitsLD matrixOnly summary statisticsUK BiobankPolygenicitySummary statisticsRelatedness
2021
SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits
Zhang Y, Lu Q, Ye Y, Huang K, Liu W, Wu Y, Zhong X, Li B, Yu Z, Travers BG, Werling DM, Li JJ, Zhao H. SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits. Genome Biology 2021, 22: 262. PMID: 34493297, PMCID: PMC8422619, DOI: 10.1186/s13059-021-02478-w.Peer-Reviewed Original ResearchConceptsLocal genetic correlationsComplex traitsGenetic correlationsGenomic regionsLocal genetic correlation analysisGenome-wide association studiesLocal genomic regionsSpecific genomic regionsGenetic correlation analysisDistinct genetic signaturesGenetic similarityGenetic signaturesAssociation studiesTraitsSample overlapStatistical frameworkSummary statisticsDisequilibriumRegionAccurate estimationSimilarityA fast and robust Bayesian nonparametric method for prediction of complex traits using summary statistics
Zhou G, Zhao H. A fast and robust Bayesian nonparametric method for prediction of complex traits using summary statistics. PLOS Genetics 2021, 17: e1009697. PMID: 34310601, PMCID: PMC8341714, DOI: 10.1371/journal.pgen.1009697.Peer-Reviewed Original ResearchConceptsBayesian nonparametric methodParameter tuningNonparametric methodsExternal reference panelSummary statisticsComputational resourcesParallel algorithmBlock structureExplicit assumptionsExisting methodsStatisticsSeparate validation dataAccurate risk prediction modelsAssumptionPrediction modelPredictionAlgorithm
2020
Leveraging effect size distributions to improve polygenic risk scores derived from summary statistics of genome-wide association studies
Song S, Jiang W, Hou L, Zhao H. Leveraging effect size distributions to improve polygenic risk scores derived from summary statistics of genome-wide association studies. PLOS Computational Biology 2020, 16: e1007565. PMID: 32045423, PMCID: PMC7039528, DOI: 10.1371/journal.pcbi.1007565.Peer-Reviewed Original ResearchMeSH KeywordsComputational BiologyComputer SimulationFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansLinkage DisequilibriumMaleMultifactorial InheritanceSoftwareConceptsEffect size distributionClass of methodsReal data applicationOnly summary statisticsTheoretical resultsSummary statisticsExtensive simulation resultsLD informationSimulation resultsData applicationsFirst methodImportant problemOptimal propertiesGenetic risk predictionAccurate predictionPrediction accuracyStandard PRSStatisticsPrediction method
2019
Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations
Kranzler HR, Zhou H, Kember RL, Vickers Smith R, Justice AC, Damrauer S, Tsao PS, Klarin D, Baras A, Reid J, Overton J, Rader DJ, Cheng Z, Tate JP, Becker WC, Concato J, Xu K, Polimanti R, Zhao H, Gelernter J. Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nature Communications 2019, 10: 1499. PMID: 30940813, PMCID: PMC6445072, DOI: 10.1038/s41467-019-09480-8.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesAssociation studiesMillion Veteran Program sampleGenetic correlationsWide significant lociSignificant genetic correlationsPolygenic risk scoresCell type groupSignificant lociHeritable traitEnrichment analysisTraitsMultiple populationsLociPhenotypeProgram samples
2017
Genetic Risk Variants Associated With Comorbid Alcohol Dependence and Major Depression
Zhou H, Polimanti R, Yang BZ, Wang Q, Han S, Sherva R, Nuñez YZ, Zhao H, Farrer LA, Kranzler HR, Gelernter J. Genetic Risk Variants Associated With Comorbid Alcohol Dependence and Major Depression. JAMA Psychiatry 2017, 74: 1234-1241. PMID: 29071344, PMCID: PMC6331050, DOI: 10.1001/jamapsychiatry.2017.3275.Peer-Reviewed Original ResearchMeSH KeywordsAdultAlcoholismBlack or African AmericanComorbidityDepressive Disorder, MajorDiagnostic and Statistical Manual of Mental DisordersFemaleGenetic Predisposition to DiseaseGenetic VariationHumansMaleMiddle AgedMultifactorial InheritanceOrgan SizePutamenSemaphorin-3AUnited StatesWhite PeopleConceptsGenome-wide association studiesGenetic risk variantsNeuropsychiatric traitsAssociation studiesRisk variantsPolygenic risk allelesPolygenic risk scoresGenetic mechanismsGenetic basisAmerican data setMolecular natureTraitsCriterion countsGenetic causePossible genetic causesMD comorbidityRisk allelesComorbid alcohol dependenceJoint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction
Hu Y, Lu Q, Liu W, Zhang Y, Li M, Zhao H. Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction. PLOS Genetics 2017, 13: e1006836. PMID: 28598966, PMCID: PMC5482506, DOI: 10.1371/journal.pgen.1006836.Peer-Reviewed Original Research
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