2025
Knockoff procedure improves susceptibility gene identifications in conditional transcriptome-wide association studies
Zhang X, Wang L, Zhao J, Zhao H. Knockoff procedure improves susceptibility gene identifications in conditional transcriptome-wide association studies. American Journal Of Human Genetics 2025 PMID: 40902598, PMCID: PMC12412983, DOI: 10.1016/j.ajhg.2025.08.007.Peer-Reviewed Original ResearchTranscriptome-wide association studyExpression quantitative trait lociGenome-wide association studiesGene-trait pairsFalse discovery rateAssociation studiesTranscriptome-wide association study approachTranscriptome-wide association study methodExpression quantitative trait loci dataGenes associated with complex traitsGenetic variantsGenome-wide association study summary statisticsSusceptibility genesGene-trait associationsSusceptibility gene identificationQuantitative trait lociParametric bootstrap samplingGene expression levelsGenomic regionsGenetic elementsComplex traitsGene identificationTrait lociFalse discovery rate levelKnockoff procedureLeveraging 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 ResearchConceptsPolygenic 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 variantsAncestryIndividualsIncorporating local ancestry information to predict genetically associated DNA methylation in admixed populations
Cheng Y, Zhou G, Li H, Zhang X, Justice A, Martinez C, Aouizerat B, Xu K, Zhao H. Incorporating local ancestry information to predict genetically associated DNA methylation in admixed populations. Briefings In Bioinformatics 2025, 26: bbaf325. PMID: 40622482, PMCID: PMC12232425, DOI: 10.1093/bib/bbaf325.Peer-Reviewed Original ResearchConceptsMethylome-wide association studiesAdmixed populationsComplex traitsLocal ancestryAssociation studiesDNA methylationAssociated with complex traitsLocal ancestry informationPopulations of European ancestryCpG methylation levelsNon-European populationsMeasurement of methylationAncestry informationCpG sitesMethylation levelsEuropean ancestryEpigenetic underpinningsCpGAncestryTraitsMethylationAmerican populationAfrican American populationDNAPopulationA 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 ResearchConceptsPolygenic 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 modelRegressionBiobankErrorCovariates
2024
HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data
Cheng Y, Cai B, Li H, Zhang X, D’Souza G, Shrestha S, Edmonds A, Meyers J, Fischl M, Kassaye S, Anastos K, Cohen M, Aouizerat B, Xu K, Zhao H. HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data. Genome Biology 2024, 25: 273. PMID: 39407252, PMCID: PMC11476968, DOI: 10.1186/s13059-024-03411-7.Peer-Reviewed Original ResearchConceptsMethylation quantitative trait lociQuantitative trait lociTrait lociMethylation dataFunctional annotation of genetic variantsAnnotation of genetic variantsGenetic variantsBisulfite sequencing dataEffects of genetic variantsBiologically relevant cell typesDNA methylation levelsCell typesFunctional annotationSequence dataComplex traitsMethylation datasetsRelevant cell typesMeQTLsMethylation levelsMethylation regulatorsReal data analysesLociVariantsMethylationDNAJoint modeling of human cortical structure: Genetic correlation network and composite-trait genetic correlation
Shen J, Zhang Y, Zhu Z, Cheng Y, Cai B, Zhao Y, Zhao H. Joint modeling of human cortical structure: Genetic correlation network and composite-trait genetic correlation. NeuroImage 2024, 297: 120739. PMID: 39009250, PMCID: PMC11367654, DOI: 10.1016/j.neuroimage.2024.120739.Peer-Reviewed Original ResearchGenetic networksComplex traitsGenetic architecture of complex traitsArchitecture of complex traitsGenome-wide association analysisGenetic correlationsGenetic architectureGenetic variationAssociation analysisGenetic basisPhenotypic similarityGenetic effectsFunctional variationRight hemisphereBrain regionsUK BiobankCortical thicknessTraitsCortical measuresCorrelation networkSignificant pairsHeritabilitySimilarity matrixBrainBrain lobesLDER-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 ResearchConceptsHuman 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 studyIntegration of expression QTLs with fine mapping via SuSiE.
Zhang X, Jiang W, Zhao H. Integration of expression QTLs with fine mapping via SuSiE. PLOS Genetics 2024, 20: e1010929. PMID: 38271473, PMCID: PMC10846745, DOI: 10.1371/journal.pgen.1010929.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociGenome-wide association studiesFine-mapping methodsLinkage disequilibriumBody mass indexFine-mappingExpression quantitative trait loci informationGenome-wide association study resultsExpression quantitative trait loci analysisPresence of linkage disequilibriumExternal reference panelGenetic fine-mappingQuantitative trait lociPosterior inclusion probabilitiesInclusion probabilitiesAlzheimer's diseaseExpression QTLsLD patternsComplex traitsCandidate variantsAssociation studiesTrait lociAssociation to causationReference panelFunctional variants
2023
eQTL studies: from bulk tissues to single cells
Zhang J, Zhao H. eQTL studies: from bulk tissues to single cells. Journal Of Genetics And Genomics 2023, 50: 925-933. PMID: 37207929, PMCID: PMC10656365, DOI: 10.1016/j.jgg.2023.05.003.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociBulk tissueIdentification of eQTLContext-dependent gene regulationCell typesQuantitative trait lociMost eQTL studiesSingle cellsComplex traitsGene regulationEQTL studiesFunctional genesTrait lociSpecific genesChromosomal regionsDynamic regulationGene expressionBiological processesDifferent tissuesGenetic variantsExpression levelsDisease mechanismsGenesRegulationRecent studiesRobustness of quantifying mediating effects of genetically regulated expression on complex traits with mediated expression score regression
Lin C, Liu W, Jiang W, Zhao H. Robustness of quantifying mediating effects of genetically regulated expression on complex traits with mediated expression score regression. Biology Methods And Protocols 2023, 8: bpad024. PMID: 37901453, PMCID: PMC10599978, DOI: 10.1093/biomethods/bpad024.Peer-Reviewed Original ResearchExpression quantitative trait lociGenome-wide association studiesComplex traitsGene expression regulationGenetic association signalsQuantitative trait lociScore regressionDisease-Associated VariantsSNP annotationGene annotationExpression regulationGWAS resultsTrait lociTrait heritabilityEQTL effectsAssociation signalsGene expressionAssociation studiesGene effectsSNP effectsHuman diseasesHeritabilityTraitsBiological realityAnnotation
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 ResearchConceptsStatistical methodsJoint distributionWide association study (GWAS) summary statisticsNon-European populationsReal traitsSummary statisticsCross-population predictionPrediction accuracyGenome-wide association study summary statisticsLinkage disequilibrium differencesPrediction performancePolygenic risk scoresComplex traitsStatisticsSimulationsApplicationsTraitsLeveraging 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 ResearchConceptsLinkage 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 estimationSimilarity
2020
Leveraging functional annotation to identify genes associated with complex diseases
Liu W, Li M, Zhang W, Zhou G, Wu X, Wang J, Lu Q, Zhao H. Leveraging functional annotation to identify genes associated with complex diseases. PLOS Computational Biology 2020, 16: e1008315. PMID: 33137096, PMCID: PMC7660930, DOI: 10.1371/journal.pcbi.1008315.Peer-Reviewed Original ResearchConceptsExpression quantitative trait lociComplex traitsNovel lociIdentification of eQTLGene expressionTranscriptome-wide association study methodLinkage disequilibriumQuantitative trait lociAssociation study methodsCombined Annotation Dependent Depletion (CADD) scoresAnnotation-dependent depletion scoreExpression levelsDisease-associated genesEpigenetic annotationsEpigenetic informationFunctional annotationTrait lociGenetic variationGenesPrevious GWASLociGenetic effectsTraitsComplex diseasesGWASGenome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals
Xu K, Li B, McGinnis KA, Vickers-Smith R, Dao C, Sun N, Kember RL, Zhou H, Becker WC, Gelernter J, Kranzler HR, Zhao H, Justice AC. Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals. Nature Communications 2020, 11: 5302. PMID: 33082346, PMCID: PMC7598939, DOI: 10.1038/s41467-020-18489-3.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesLarge genome-wide association studiesMillion Veteran ProgramAssociation studiesExpression quantitative trait lociQuantitative trait lociChromatin interactionsComplex traitsFunctional annotationTrait lociSequencing ConsortiumDozen genesSignificant lociSmoking phenotypesLociMultiple populationsNew insightsPhenotypeVeteran ProgramGenetic vulnerabilityGenesTraitsAnnotationEuropean AmericansConsortium
2019
Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies
Fang H, Hui Q, Lynch J, Honerlaw J, Assimes T, Huang J, Vujkovic M, Damrauer S, Pyarajan S, Gaziano J, DuVall S, O’Donnell C, Cho K, Chang K, Wilson P, Tsao P, Sun Y, Tang H, Gaziano J, Ramoni R, Breeling J, Chang K, Huang G, Muralidhar S, O’Donnell C, Tsao P, Muralidhar S, Moser J, Whitbourne S, Brewer J, Concato J, Warren S, Argyres D, Stephens B, Brophy M, Humphries D, Do N, Shayan S, Nguyen X, Pyarajan S, Cho K, Hauser E, Sun Y, Zhao H, Wilson P, McArdle R, Dellitalia L, Harley J, Whittle J, Beckham J, Wells J, Gutierrez S, Gibson G, Kaminsky L, Villareal G, Kinlay S, Xu J, Hamner M, Haddock K, Bhushan S, Iruvanti P, Godschalk M, Ballas Z, Buford M, Mastorides S, Klein J, Ratcliffe N, Florez H, Swann A, Murdoch M, Sriram P, Yeh S, Washburn R, Jhala D, Aguayo S, Cohen D, Sharma S, Callaghan J, Oursler K, Whooley M, Ahuja S, Gutierrez A, Schifman R, Greco J, Rauchman M, Servatius R, Oehlert M, Wallbom A, Fernando R, Morgan T, Stapley T, Sherman S, Anderson G, Sonel E, Boyko E, Meyer L, Gupta S, Fayad J, Hung A, Lichy J, Hurley R, Robey B, Striker R. Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies. American Journal Of Human Genetics 2019, 105: 763-772. PMID: 31564439, PMCID: PMC6817526, DOI: 10.1016/j.ajhg.2019.08.012.Peer-Reviewed Original ResearchA statistical framework for cross-tissue transcriptome-wide association analysis
Hu Y, Li M, Lu Q, Weng H, Wang J, Zekavat SM, Yu Z, Li B, Gu J, Muchnik S, Shi Y, Kunkle BW, Mukherjee S, Natarajan P, Naj A, Kuzma A, Zhao Y, Crane PK, Lu H, Zhao H. A statistical framework for cross-tissue transcriptome-wide association analysis. Nature Genetics 2019, 51: 568-576. PMID: 30804563, PMCID: PMC6788740, DOI: 10.1038/s41588-019-0345-7.Peer-Reviewed Original ResearchConceptsTranscriptome-wide association analysisAssociation analysisGene-trait associationsGene expression dataGene expression levelsGenetic architectureComplex traitsMore genesGene expressionSingle tissueExpression dataAssociation resultsExpression levelsPowerful approachImputation modelHuman tissuesImputation accuracyGenotypesStatistical frameworkTissueGenesKey componentTraitsPowerful metricExpression
2017
A Powerful Approach to Estimating Annotation-Stratified Genetic Covariance via GWAS Summary Statistics
Lu Q, Li B, Ou D, Erlendsdottir M, Powles RL, Jiang T, Hu Y, Chang D, Jin C, Dai W, He Q, Liu Z, Mukherjee S, Crane PK, Zhao H. A Powerful Approach to Estimating Annotation-Stratified Genetic Covariance via GWAS Summary Statistics. American Journal Of Human Genetics 2017, 101: 939-964. PMID: 29220677, PMCID: PMC5812911, DOI: 10.1016/j.ajhg.2017.11.001.Peer-Reviewed Original ResearchConceptsGWAS summary statisticsGenome-wide association studiesComplex traitsSingle nucleotide polymorphismsGenetic covarianceGenetic architectureLarge-scale genome-wide association studiesStrong genetic covarianceDistinct genetic architecturesSignificant genetic covarianceLate-onset Alzheimer's diseaseHigh minor allele frequencyGenetic profileFunctional genomeAmyotrophic lateral sclerosisMajor neurodegenerative diseasesMinor allele frequencyGenetic basisAssociation studiesTraitsLarge-scale inferenceSummary statisticsBiological interpretabilityAllele frequenciesNeurodegenerative diseases
2016
Integrative Tissue-Specific Functional Annotations in the Human Genome Provide Novel Insights on Many Complex Traits and Improve Signal Prioritization in Genome Wide Association Studies
Lu Q, Powles RL, Wang Q, He BJ, Zhao H. Integrative Tissue-Specific Functional Annotations in the Human Genome Provide Novel Insights on Many Complex Traits and Improve Signal Prioritization in Genome Wide Association Studies. PLOS Genetics 2016, 12: e1005947. PMID: 27058395, PMCID: PMC4825932, DOI: 10.1371/journal.pgen.1005947.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGWAS signalsComplex traitsFunctional annotationAssociation studiesHuman complex traitsFunctional regionsNon-coding regionsGWAS p-valuesWide association studyNovel biological insightsRelevant tissue typesEpigenetic annotationsGenomic functionsRegulatory machineryTransposable elementsHuman genomeGenoSkylineRisk lociBiological insightsIntegrative analysisGenetic studiesRegulatory miRNAPrioritization performanceSpecific annotations
2000
Transmission/Disequilibrium Tests Using Multiple Tightly Linked Markers
Zhao H, Zhang S, Merikangas K, Trixler M, Wildenauer D, Sun F, Kidd K. Transmission/Disequilibrium Tests Using Multiple Tightly Linked Markers. American Journal Of Human Genetics 2000, 67: 936-946. PMID: 10968775, PMCID: PMC1287895, DOI: 10.1086/303073.Peer-Reviewed Original Research
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