2020
Super‐variants identification for brain connectivity
Li T, Hu J, Wang S, Zhang H. Super‐variants identification for brain connectivity. Human Brain Mapping 2020, 42: 1304-1312. PMID: 33236465, PMCID: PMC7927294, DOI: 10.1002/hbm.25294.Peer-Reviewed Original ResearchConceptsCombination of allelesSingle nucleotide polymorphismsNovel lociBrain connectivityUK Biobank databaseChromosome 1Multiple lociGenetic effectsGenetic variantsNucleotide polymorphismsAssociation detectionLociGenetic associationGenesNeurodegenerative disordersBiobank databaseBrain issuesGenetic biomarkersBrain functionBrain structuresGenomeRSPO2Discovery phaseAssociationTMEM74
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
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
NCK2 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 analysisGeneticsVariants
2011
Propensity score‐based nonparametric test revealing genetic variants underlying bipolar disorder
Jiang Y, Zhang H. Propensity score‐based nonparametric test revealing genetic variants underlying bipolar disorder. Genetic Epidemiology 2011, 35: 125-132. PMID: 21254220, PMCID: PMC3077545, DOI: 10.1002/gepi.20558.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsGenetic variantsWellcome Trust Case Control ConsortiumRPGRIP1L geneGenetic studiesAssociation analysisHaplotype blocksChromosome 16Nucleotide polymorphismsComplex diseasesGenesComplex disorderStrong signalUnreported regionsVariantsImportant roleStrong evidencePolymorphismBipolar disorderRegion
2009
Detecting Genes and Gene–Gene Interactions for Age-Related Macular Degeneration with a Forest-based Approach
Wang M, Zhang M, Chen X, Zhang H. Detecting Genes and Gene–Gene Interactions for Age-Related Macular Degeneration with a Forest-based Approach. Statistics In Biopharmaceutical Research 2009, 1: 424-430. PMID: 20161521, PMCID: PMC2799940, DOI: 10.1198/sbr.2009.0046.Peer-Reviewed Original ResearchMachine 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