2024
Variant Selection and Aggregation of Genetic Association Studies in Precision Medicine
Hu J, Wang S, Zhang H. Variant Selection and Aggregation of Genetic Association Studies in Precision Medicine. ICSA Book Series In Statistics 2024, 423-451. DOI: 10.1007/978-3-031-50690-1_17.Peer-Reviewed Original ResearchAssociation studiesGenetic association studiesPrecision medicineTests of associationHeterogeneous drug responsesDisease risk predictionVariant identificationSignal variantsControl of type I errorDisease riskDrug responseGenomic profilingType I errorRisk predictionGenetic biomarkersVariantsPharmaceutical interventionsMarginal testsAssociation methodAssociationMedicineInterventionIdentificationReplicationDisease
2020
Supervariants identification for breast cancer
Hu J, Li T, Wang S, Zhang H. Supervariants identification for breast cancer. Genetic Epidemiology 2020, 44: 934-947. PMID: 32808324, PMCID: PMC7924970, DOI: 10.1002/gepi.22350.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesCombination of allelesRare variantsNovel lociChromosome 2UK Biobank databaseChromosome 1Multiple lociAssociation studiesLociComplex diseasesGenesBiobank databaseAssociation methodGenomeVariantsTens of thousandsAllelesPolymorphismNovel resultsSignalsClassic conceptIdentification
2019
Common genetic variants have associations with human cortical brain regions and risk of schizophrenia
Bi X, Feng L, Wang S, Lin Z, Li T, Zhao B, Zhu H, Zhang H. Common genetic variants have associations with human cortical brain regions and risk of schizophrenia. Genetic Epidemiology 2019, 43: 548-558. PMID: 30941828, PMCID: PMC6559856, DOI: 10.1002/gepi.22203.Peer-Reviewed Original ResearchConceptsCortical regionsCortical brain regionsRisk of schizophreniaPrefrontal cortical regionsSymptom durationProdromal symptomsMental disordersSignificant associationBrain regionsCommon genetic variantsPhiladelphia Neurodevelopmental CohortPediatric imagingSchizophreniaNeurodevelopmental CohortCommon variantsHuman brainGenetic variantsHeritable mental disorderMagnetic resonanceAssociationWide association studyAssociation studiesGenetic effectsCohortSymptoms
2018
A univariate perspective of multivariate genome‐wide association analysis
Guo X, Zhu J, Fan Q, He M, Wang X, Zhang H. A univariate perspective of multivariate genome‐wide association analysis. Genetic Epidemiology 2018, 42: 470-479. PMID: 29781551, DOI: 10.1002/gepi.22128.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesMultivariate genome-wide association studyMultivariate genome-wide association analysisGenome-wide association analysisMultiple correlated phenotypesGenetic signalsAssociation studiesCorrelated phenotypesAssociation analysisMultiple phenotypesSingle phenotypePhenotypeWhole genome association study of brain‐wide imaging phenotypes: A study of the ping cohort
Wen C, Mehta CM, Tan H, Zhang H. Whole genome association study of brain‐wide imaging phenotypes: A study of the ping cohort. Genetic Epidemiology 2018, 42: 265-275. PMID: 29411414, PMCID: PMC5851842, DOI: 10.1002/gepi.22111.Peer-Reviewed Original ResearchConceptsGenetic markersGenome-wide association study datasetWhole-genome association studiesComplex genetic basisGenome association studiesBrain-wide imaging phenotypesMultivariate phenotypesGenetic basisAssociation studiesGenetic studiesNeuropsychological disordersClinical diagnostic criteriaCovariance testBiological basisPhenotypeDiagnostic criteriaNeuroimaging biomarkersBrain functionBrain structuresPediatric imagingGWASImaging phenotypesDiffusion tensor
2014
TARV: Tree‐based Analysis of Rare Variants Identifying Risk Modifying Variants in CTNNA2 and CNTNAP2 for Alcohol Addiction
Song C, Zhang H. TARV: Tree‐based Analysis of Rare Variants Identifying Risk Modifying Variants in CTNNA2 and CNTNAP2 for Alcohol Addiction. Genetic Epidemiology 2014, 38: 552-559. PMID: 25041903, PMCID: PMC4154634, DOI: 10.1002/gepi.21843.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesSequence kernel association testRare variant dataTree-based analysisRare variantsNext-generation sequencing technologiesVariant dataGeneration sequencing technologyKernel association testGene-gene interactionsSequencing technologiesMultiple genesAssociation studiesDisease modelsRisk genesCTNNA2Genetic variantsSAGE dataComplex disease modelsGenesStudy of AddictionComplex diseasesCommon variantsSpecific variantsRisk of alcoholismIdentifying Genetic Variants for Addiction via Propensity Score Adjusted Generalized Kendall’s Tau
Jiang Y, Li N, Zhang H. Identifying Genetic Variants for Addiction via Propensity Score Adjusted Generalized Kendall’s Tau. Journal Of The American Statistical Association 2014, 109: 905-930. PMID: 25382885, PMCID: PMC4219655, DOI: 10.1080/01621459.2014.901223.Peer-Reviewed Original ResearchGenome-wide association studiesGenetic variantsU-statisticsU-statistic methodNovel genetic variantsGWAS analysisPhenotype-genotype associationsEnvironmental factorsReplicable genetic variantsAssociation studiesSemiparametric methodAssociation analysisStatistical methodsStudy of AddictionParametric methodsGene-environment interactionsParametric estimatesInverse probability weightingSimulation resultsProbability weightingNull hypothesisVariantsKendall's tauGeneticsTraits
2013
NKAIN1–SERINC2 is a functional, replicable and genome-wide significant risk gene region specific for alcohol dependence in subjects of European descent
Zuo L, Wang K, Zhang XY, Krystal JH, Li CS, Zhang F, Zhang H, Luo X. NKAIN1–SERINC2 is a functional, replicable and genome-wide significant risk gene region specific for alcohol dependence in subjects of European descent. Drug And Alcohol Dependence 2013, 129: 254-264. PMID: 23455491, PMCID: PMC3628730, DOI: 10.1016/j.drugalcdep.2013.02.006.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesExpression quantitative loci (eQTL) analysisGene regionMetabolic pathwaysQuantitative loci analysisSNP-expression associationsCis-acting regulatory effectsDiscovery sampleSNP-disease associationsNumerous genesReplication sampleLocus analysisAssociation studiesAssociation analysisRisk SNPsTranscript expressionSNPsRegulatory effectsGenesPathwayEuropean descentExpressionNCK2 Is Significantly Associated with Opiates Addiction in African‐Origin Men
Liu Z, Guo X, Jiang Y, Zhang H. NCK2 Is Significantly Associated with Opiates Addiction in African‐Origin Men. The Scientific World JOURNAL 2013, 2013: 748979. PMID: 23533358, PMCID: PMC3603435, DOI: 10.1155/2013/748979.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsNCK2 geneGenome-wide significant associationGenome-wide significant levelWide association studyGene-based methodsNumerous genetic variantsGWAS discoveryChromosome 2Association studiesNck2Genetic variantsGenesNucleotide polymorphismsComplex diseasesFirst evidenceGenetic disordersDiscoverySignificant levelsPolymorphismVariantsSubstantial effort
2012
Large Scale Association Analysis for Drug Addiction: Results from SNP to Gene
Guo X, Liu Z, Wang X, Zhang H. Large Scale Association Analysis for Drug Addiction: Results from SNP to Gene. The Scientific World JOURNAL 2012, 2012: 939584. PMID: 23365539, PMCID: PMC3543790, DOI: 10.1100/2012/939584.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesAssociation studiesAssociation analysisGene-based association analysisLarge-scale association analysisSingle nucleotide polymorphism dataWide association studyComplex diseasesGene-based analysisGene-based methodsNucleotide polymorphism dataGenetic association studiesPolymorphism dataGene findingGenetic variantsIndividual SNPsStudy of AddictionSNPsGenetic etiologyGenesComprehensive analysisGeneticsVariantsGenetic Association Test for Multiple Traits at Gene Level
Guo X, Liu Z, Wang X, Zhang H. Genetic Association Test for Multiple Traits at Gene Level. Genetic Epidemiology 2012, 37: 122-129. PMID: 23032486, PMCID: PMC3524409, DOI: 10.1002/gepi.21688.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesMultiple traitsGene levelSingle nucleotide polymorphismsGenetic association testsCommon genesAssociation studiesAssociation TestNucleotide polymorphismsTraitsStudy of AddictionComplex diseasesBiological mechanismsDisease of interestAssociation informationGenesGeneticsSuch studiesStrong evidencePolymorphismPrevious findingsLevels
2011
A LASSO-based approach to analyzing rare variants in genetic association studies
Brennan JS, He Y, Calixte R, Nyirabahizi E, Jiang Y, Zhang H. A LASSO-based approach to analyzing rare variants in genetic association studies. BMC Proceedings 2011, 5: s100. PMID: 22373373, PMCID: PMC3287823, DOI: 10.1186/1753-6561-5-s9-s100.Peer-Reviewed Original Research
2009
Memory management in genome-wide association studies
Chen X, Zhang M, Wang M, Zhu W, Cho K, Zhang H. Memory management in genome-wide association studies. BMC Proceedings 2009, 3: s54. PMID: 20018047, PMCID: PMC2795954, DOI: 10.1186/1753-6561-3-s7-s54.Peer-Reviewed Original ResearchGenome-wide association studiesAssociation studiesIdentification of genesNorth American Rheumatoid Arthritis Consortium studyGenome-wide associationMemory management toolsMemory management approachCentral processing unitLimited computer memorySignificant computational challengesMemory managementMemory usageProcessing unitMost usersComputational challengesPowerful toolComputer memoryGenesCommon diseaseManagement toolGenotypesDetecting significant single-nucleotide polymorphisms in a rheumatoid arthritis study using random forests
Wang M, Chen X, Zhang M, Zhu W, Cho K, Zhang H. Detecting significant single-nucleotide polymorphisms in a rheumatoid arthritis study using random forests. BMC Proceedings 2009, 3: s69. PMID: 20018063, PMCID: PMC2795970, DOI: 10.1186/1753-6561-3-s7-s69.Peer-Reviewed Original ResearchSignificant single nucleotide polymorphismsGenome-wide dataGenetic Analysis Workshop 16 Problem 1 dataGenes/SNPsSNP markersSignificant SNPsSingle nucleotide polymorphismsGenetic association studiesWhole genomeChromosome 6Association studiesRheumatoid arthritis statusAntigen geneTraitsSNPsForestHLA-DRAArray experimentsGenomeMarkersHuman leukocyte antigen (HLA) genesGenesFurther analysisIndividual markersHigh levelsA genome-wide association analysis of Framingham Heart Study longitudinal data using multivariate adaptive splines
Zhu W, Cho K, Chen X, Zhang M, Wang M, Zhang H. A genome-wide association analysis of Framingham Heart Study longitudinal data using multivariate adaptive splines. BMC Proceedings 2009, 3: s119. PMID: 20017984, PMCID: PMC2795891, DOI: 10.1186/1753-6561-3-s7-s119.Peer-Reviewed Original ResearchTraits of interestGenome-wide analysisGenome-wide association studiesWide association analysisGenome-wide dataMultivariate adaptive splinesAssociation studiesAssociation analysisGene-environment interactionsTraitsLongitudinal phenotypesGene-environment interaction effectsMasalFramingham Heart StudyPermutation testGenesPhenotypeMachine learning in genome‐wide association studies
Szymczak S, Biernacka JM, Cordell HJ, González‐Recio O, König IR, Zhang H, Sun YV. Machine learning in genome‐wide association studies. Genetic Epidemiology 2009, 33: s51-s57. PMID: 19924717, DOI: 10.1002/gepi.20473.Peer-Reviewed Original ResearchConceptsGenome-wide SNP dataSingle nucleotide polymorphismsSNP dataAssociation studiesGenome-wide association studiesOverall genetic architectureMachine learning approachesGenetic Analysis Workshop 16Wide association studyComplex human diseasesMain genetic effectsGenetic architectureLearning approachGenetic risk variantsEnsemble methodHuman diseasesGenetic effectsRisk variantsGenetic variantsComplex diseasesMachineNew variable selection procedureNetwork analysisVariable selection procedureDifferent approaches
2006
Detection of Genes for Ordinal Traits in Nuclear Families and a Unified Approach for Association Studies
Zhang H, Wang X, Ye Y. Detection of Genes for Ordinal Traits in Nuclear Families and a Unified Approach for Association Studies. Genetics 2006, 172: 693-699. PMID: 16219774, PMCID: PMC1456175, DOI: 10.1534/genetics.105.049122.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsQuantitative traitsOrdinal traitsTraditional linkage studiesGenomewide association analysisAssociation of genesDetection of genesGametic disequilibriumLoci existAssociation studiesAssociation analysisGenesLinkage disequilibriumTraitsComplex diseasesLinkage studiesGrowth-associated protein 43Protein 43DisequilibriumPolymorphismFamilyMarkersNuclear families
2005
A genome-wide tree- and forest-based association analysis of comorbidity of alcoholism and smoking
Ye Y, Zhong X, Zhang H. A genome-wide tree- and forest-based association analysis of comorbidity of alcoholism and smoking. BMC Genomic Data 2005, 6: s135. PMID: 16451594, PMCID: PMC1866801, DOI: 10.1186/1471-2156-6-s1-s135.Peer-Reviewed Original ResearchConceptsAssociation analysisGenetic Analysis Workshop 14Single nucleotide polymorphism dataJoint association analysisNew genesSingle nucleotide polymorphismsGenetic mechanismsPolymorphism dataAssociation studiesDeterministic forestsGenetics of AlcoholismGenesTreesUseful candidateGeneticsForestPolymorphismFuture studiesStudy of alcoholism
2001
Tree‐Based Linkage and Association Analyses of Asthma
Zhang H, Tsai C, Yu C, Bonney G. Tree‐Based Linkage and Association Analyses of Asthma. Genetic Epidemiology 2001, 21: s317-s322. PMID: 11793691, DOI: 10.1002/gepi.2001.21.s1.s317.Peer-Reviewed Original ResearchConceptsGenetic Analysis Workshop 12Chromosome 1Association studiesLinkage analysisAssociation analysisStrong evidenceLinkageData sets
2000
Use of classification trees for association studies
Zhang H, Bonney G. Use of classification trees for association studies. Genetic Epidemiology 2000, 19: 323-332. PMID: 11108642, DOI: 10.1002/1098-2272(200012)19:4<323::aid-gepi4>3.0.co;2-5.Peer-Reviewed Original ResearchConceptsGenetic Analysis Workshop 9Association studiesTree-based analysisGenetic studiesDisease allelesTreesAlleles