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 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 studyA mediation analysis framework based on variance component to remove genetic confounding effect
Dong Z, Zhao H, DeWan A. A mediation analysis framework based on variance component to remove genetic confounding effect. Journal Of Human Genetics 2024, 69: 301-309. PMID: 38528049, DOI: 10.1038/s10038-024-01232-x.Peer-Reviewed Original ResearchMediation analysis frameworkSingle nucleotide polymorphismsMediation analysisPleiotropic single nucleotide polymorphismsUK Biobank dataConfounding effectsTrait pairsBiobank dataIndividual-levelEpidemiological studiesCausal effectsGenetic signalsEstimated effectsLinear regressionNucleotide polymorphismsStandard errorData analysisGenetic correlationsPhenotypeIndirect effectsPleiotropyVariance componentsOutcomesRegression
2019
Genome-wide association study of post-traumatic stress disorder reexperiencing symptoms in >165,000 US veterans
Gelernter J, Sun N, Polimanti R, Pietrzak R, Levey DF, Bryois J, Lu Q, Hu Y, Li B, Radhakrishnan K, Aslan M, Cheung KH, Li Y, Rajeevan N, Sayward F, Harrington K, Chen Q, Cho K, Pyarajan S, Sullivan PF, Quaden R, Shi Y, Hunter-Zinck H, Gaziano JM, Concato J, Zhao H, Stein MB. Genome-wide association study of post-traumatic stress disorder reexperiencing symptoms in >165,000 US veterans. Nature Neuroscience 2019, 22: 1394-1401. PMID: 31358989, PMCID: PMC6953633, DOI: 10.1038/s41593-019-0447-7.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesAssociation studiesHigh linkage disequilibrium regionLinkage disequilibrium regionWide association studyDisequilibrium regionBioinformatics analysisTranscriptomic profilesMillion Veteran ProgramChromosome 17Genetic risk factorsNew insightsUK Biobank dataReexperiencing of traumaStriatal medium spiny neuronsVeteran ProgramSignificant regionsCAMKVEuropean AmericansBiobank dataMedium spiny neuronsTCF4BiologyKANSL1African American cohort