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 phenotypePhenotypeEvaluation, validation and refinement of noninvasive diagnostic biomarkers for endometriosis (ENDOmarker): A protocol to phenotype bio-specimens for discovery and validation
Barnhart K, Giudice L, Young S, Thomas T, Diamond MP, Segars J, Youssef WA, Krawetz S, Santoro N, Eisenberg E, Zhang H, Network F. Evaluation, validation and refinement of noninvasive diagnostic biomarkers for endometriosis (ENDOmarker): A protocol to phenotype bio-specimens for discovery and validation. Contemporary Clinical Trials 2018, 68: 1-6. PMID: 29524590, PMCID: PMC5899676, DOI: 10.1016/j.cct.2018.03.002.Peer-Reviewed Original ResearchConceptsReproductive Medicine NetworkDisease-specific questionnaireReproductive-aged womenTime of surgeryEstrogen-dependent conditionStage of endometriosisExtensive clinical evaluationSeverity of diseaseNoninvasive diagnostic biomarkersAcademic medical centerPelvic painEndometrial biopsyNonsurgical diagnosisSerum cytokinesSurgical ablationGynecologic surgeryClinical evaluationClinical reasonsMedical CenterAged womenPharmacological controlEndometriosisGenomic classifierSpecific questionnaireTherapy shiftsWhole 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
2017
Genome‐wide mediation analysis of psychiatric and cognitive traits through imaging phenotypes
Bi X, Yang L, Li T, Wang B, Zhu H, Zhang H. Genome‐wide mediation analysis of psychiatric and cognitive traits through imaging phenotypes. Human Brain Mapping 2017, 38: 4088-4097. PMID: 28544218, PMCID: PMC5568842, DOI: 10.1002/hbm.23650.Peer-Reviewed Original ResearchRacial and ethnic differences in the polycystic ovary syndrome metabolic phenotype
Engmann L, Jin S, Sun F, Legro RS, Polotsky AJ, Hansen KR, Coutifaris C, Diamond MP, Eisenberg E, Zhang H, Santoro N, Network R, Bartlebaugh C, Dodson W, Estes S, Gnatuk C, Ober J, Brzyski R, Easton C, Hernandez A, Leija M, Pierce D, Robinson R, Awonuga A, Cedo L, Cline A, Collins K, Krawetz S, Puscheck E, Singh M, Yoscovits M, Barnhart K, Lecks K, Martino L, Marunich R, Snyder P, Alvero R, Comfort A, Crow M, Schlaff W, Casson P, Hohmann A, Mallette S, Christman G, Ohl D, Ringbloom M, Tang J, Bates G, Mason S, DiMaria N, Usadi R, Lucidi R, Rhea M, Baker V, Turner K, Trussell J, DelBasso D, Huang H, Li Y, Makuch R, Patrizio P, Sakai L, Scahill L, Taylor H, Thomas T, Tsang S, Yan Q, Zhang M, Haisenleder D, Lamar C, DePaolo L, Guzick D, Herring A, Redmond J, Thomas M, Turek P, Wactawski-Wende J, Rebar R, Cato P, Dukic V, Lewis V, Schlegel P, Witter F. Racial and ethnic differences in the polycystic ovary syndrome metabolic phenotype. American Journal Of Obstetrics And Gynecology 2017, 216: 493.e1-493.e13. PMID: 28104402, PMCID: PMC5420474, DOI: 10.1016/j.ajog.2017.01.003.Peer-Reviewed Original ResearchConceptsPolycystic ovarian syndromeNon-Hispanic black womenNon-Hispanic whitesOvarian syndromeMetabolic syndromeNon-Hispanic blacksHispanic womenInsulin resistanceCardiovascular diseaseHigh prevalenceEthnic differencesType 2 diabetes mellitusLower serum triglyceride levelsNon-Hispanic white womenLower sex hormonePrevalence of hypertriglyceridemiaFree androgen indexHomeostasis model assessmentPolycystic ovary syndromeBody mass indexMetabolic phenotypeSerum triglyceride levelsType 2 diabetesBlack womenAndrogen index
2016
A method for integrating neuroimaging into genetic models of learning performance
Mehta CM, Gruen JR, Zhang H. A method for integrating neuroimaging into genetic models of learning performance. Genetic Epidemiology 2016, 41: 4-17. PMID: 27859682, PMCID: PMC5154929, DOI: 10.1002/gepi.22025.Peer-Reviewed Original Research
2015
Association Tests of Multiple Phenotypes: ATeMP
Guo X, Li Y, Ding X, He M, Wang X, Zhang H. Association Tests of Multiple Phenotypes: ATeMP. PLOS ONE 2015, 10: e0140348. PMID: 26479245, PMCID: PMC4610695, DOI: 10.1371/journal.pone.0140348.Peer-Reviewed Original ResearchConceptsExtensive simulation studyStatistical literatureJoint association analysisMultiPhenSimulation studyEquivalence relationshipProportional odds modelReal case studyMeasurement errorMultivariate methodsOdds modelMultiple intermediate phenotypesJoint analysisMultiple phenotypesExplanatory variablesEquivalenceEstimationDistributionPhenotypic distributionATempSolutionErrorCluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms
Esplin MS, Manuck TA, Varner MW, Christensen B, Biggio J, Bukowski R, Parry S, Zhang H, Huang H, Andrews W, Saade G, Sadovsky Y, Reddy UM, Ilekis J. Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms. American Journal Of Obstetrics And Gynecology 2015, 213: 429.e1-429.e9. PMID: 26070700, PMCID: PMC4556543, DOI: 10.1016/j.ajog.2015.06.011.Peer-Reviewed Original ResearchConceptsSpontaneous preterm birthDecidual hemorrhagePlacental dysfunctionProspective case-control multicenter studyCase-control multicenter studyPremature membrane ruptureGroup of womenCommon biologic pathwaysMaternal comorbiditiesPreterm singletonsPreterm birthWeeks' gestationMulticenter studyMaternal stressSecondary analysisBiologic pathwaysFamilial factorsGenetic factorsWomenPhenotypic profileGestationInfectionMembrane ruptureCommon mechanismPhenotypeThe phenotype of spontaneous preterm birth: application of a clinical phenotyping tool
Manuck TA, Esplin MS, Biggio J, Bukowski R, Parry S, Zhang H, Huang H, Varner MW, Andrews W, Saade G, Sadovsky Y, Reddy UM, Ilekis J, Research E. The phenotype of spontaneous preterm birth: application of a clinical phenotyping tool. American Journal Of Obstetrics And Gynecology 2015, 212: 487.e1-487.e11. PMID: 25687564, PMCID: PMC4456184, DOI: 10.1016/j.ajog.2015.02.010.Peer-Reviewed Original ResearchConceptsSpontaneous preterm birthEarly spontaneous preterm birthInfection/inflammationDecidual hemorrhageGestational ageCervical insufficiencyPreterm birthWeeks' gestationPlacental dysfunctionWhite womenMaternal stressSingleton spontaneous preterm birthDelivery gestational ageFinal common pathwayAfrican American womenMaternal comorbiditiesPremature ruptureProspective studyPlanned analysisUterine distentionClinical dataMultiple possible causesGestationHemorrhageComprehensive classification system
2014
Smoking in infertile women with polycystic ovary syndrome: baseline validation of self-report and effects on phenotype
Legro RS, Chen G, Kunselman AR, Schlaff WD, Diamond MP, Coutifaris C, Carson SA, Steinkampf MP, Carr BR, McGovern PG, Cataldo NA, Gosman GG, Nestler JE, Myers ER, Zhang H, Foulds J, Barnhart K, Martino L, Timbers K, Lambe L, DeWire R, Yang H, Bodine C, Mark D, Puscheck E, Ginsburg K, Collins K, Brossoit M, Leach R, Yelian F, Perez M, Buster J, Amato P, Torres M, Dodson W, Gnatuk C, Ober J, Demers L, Heller D, Colon J, Weiss G, Solnica A, Gatlin K, Hahn S, Roark M, Blackwell R, Willis V, Love L, Laychak K, Nazmy M, Stovall D, Evans W, Turner K, Chang J, Malcolm P, Coddington C, Permanente K, Faber K, Hasenleider D, Huang H. Smoking in infertile women with polycystic ovary syndrome: baseline validation of self-report and effects on phenotype. Human Reproduction 2014, 29: 2680-2686. PMID: 25324541, PMCID: PMC4227579, DOI: 10.1093/humrep/deu239.Peer-Reviewed Original ResearchConceptsPolycystic ovary syndromeSerum cotinine levelsCase-control studySmoking statusInfertility treatmentCotinine levelsPast smokersCurrent smokersOvary syndromeInfertile womenInsulin resistanceFirst-line ovulation induction agentsMulti-center clinical trialOvulation induction agentsWorse insulin resistanceTotal testosterone levelsLive birth rateSecond-hand smokePARTICIPANTS/MATERIALSNational InstituteROLE OF CHANCESelf-reported changesHirsutism scoreSmoking groupRecent smokers
2013
Gene–environment interactions in severe intraventricular hemorrhage of preterm neonates
Ment LR, Ådén U, Lin A, Kwon SH, Choi M, Hallman M, Lifton RP, Zhang H, Bauer CR. Gene–environment interactions in severe intraventricular hemorrhage of preterm neonates. Pediatric Research 2013, 75: 241-250. PMID: 24192699, PMCID: PMC3946468, DOI: 10.1038/pr.2013.195.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsApgar ScoreBlood CoagulationCerebral VentriclesCerebrovascular CirculationCollagen Type IVFactor VGene-Environment InteractionGenetic Predisposition to DiseaseGenetic VariationGestational AgeHumansHypoxia, BrainInfantInfant, PrematureInflammation MediatorsIntracranial HemorrhagesMethylenetetrahydrofolate Reductase (NADPH2)PhenotypePremature BirthPrognosisRisk FactorsConceptsIntraventricular hemorrhageCerebral injuryPreterm neonatesFactor V Leiden geneRisk of IVHEnvironmental triggersSevere intraventricular hemorrhageCerebral blood flowMethylenetetrahydrofolate reductase (MTHFR) variantsUnknown environmental triggersPresence of mutationsPeriventricular infarctionApgar scorePerinatal hypoxiaPreclinical dataFetal environmentGerminal matrixCerebral vasculatureBlood flowT polymorphismGene-environment interactionsMTHFR 677CHemorrhageNeonatesVascular pathways
2009
The familial aggregation of cannabis use disorders
Merikangas KR, Li JJ, Stipelman B, Yu K, Fucito L, Swendsen J, Zhang H. The familial aggregation of cannabis use disorders. Addiction 2009, 104: 622-629. PMID: 19335660, PMCID: PMC2794246, DOI: 10.1111/j.1360-0443.2008.02468.x.Peer-Reviewed Original ResearchConceptsSpouses of probandsFirst-degree relativesCannabis use disorderLife-time historyUse disordersAnxiety disordersAlcohol abuse/dependenceFamilial aggregationAbuse/dependenceFirst-degree adult relativesComorbid moodElevated riskFamily-based approachPsychiatric clinicAffective disordersAlcohol dependencePsychiatric conditionsFamily study methodDrug abuseFamilial factorsDisordersAdult relativesCannabisFamilial transmissionGenetic factors
2005
Multivariate linkage analysis using the electrophysiological phenotypes in the COGA alcoholism data
Zhang H, Zhong X, Ye Y. Multivariate linkage analysis using the electrophysiological phenotypes in the COGA alcoholism data. BMC Genomic Data 2005, 6: s118. PMID: 16451575, PMCID: PMC1866820, DOI: 10.1186/1471-2156-6-s1-s118.Peer-Reviewed Original ResearchComparison of single‐nucleotide polymorphisms and microsatellite markers for linkage analysis in the COGA and simulated data sets for Genetic Analysis Workshop 14: Presentation Groups 1, 2, and 3
Wilcox MA, Pugh EW, Zhang H, Zhong X, Levinson DF, Kennedy GC, Wijsman EM. Comparison of single‐nucleotide polymorphisms and microsatellite markers for linkage analysis in the COGA and simulated data sets for Genetic Analysis Workshop 14: Presentation Groups 1, 2, and 3. Genetic Epidemiology 2005, 29: s7-s28. PMID: 16342186, DOI: 10.1002/gepi.20106.Peer-Reviewed Original Research
2004
A High Productivity/Low Maintenance Approach to High-performance Computation for Biomedicine: Four Case Studies
Carriero N, Osier MV, Cheung KH, Miller PL, Gerstein M, Zhao H, Wu B, Rifkin S, Chang J, Zhang H, White K, Williams K, Schultz M. A High Productivity/Low Maintenance Approach to High-performance Computation for Biomedicine: Four Case Studies. Journal Of The American Medical Informatics Association 2004, 12: 90-98. PMID: 15492032, PMCID: PMC543832, DOI: 10.1197/jamia.m1571.Peer-Reviewed Original ResearchConceptsHigh performance computationLow-maintenance approachBioinformatics applicationsRepresentative bioinformatics applicationsIntensive bioinformatics applicationsBioinformatics case studyGenome-wide sequence comparisonHPC expertsHPC platformsComplex genetic analysisBioinformatics researchersSignificant speedupMass spectrometry data setsHigh-throughput biotechnologiesSequence comparisonVast amountProteomic dataOrdinal phenotypesSpectrum of techniquesDNA microarraysGenetic analysisGene expressionCase studyIterative refinementMaintenance approach
2002
Obsessive‐compulsive symptom dimensions in affected sibling pairs diagnosed with Gilles de la Tourette syndrome
Leckman JF, Pauls DL, Zhang H, Rosario‐Campos M, Katsovich L, Kidd KK, Pakstis AJ, Alsobrook JP, Robertson MM, McMahon WM, Walkup JT, van de Wetering BJ, King RA, Cohen DJ. Obsessive‐compulsive symptom dimensions in affected sibling pairs diagnosed with Gilles de la Tourette syndrome. American Journal Of Medical Genetics Part B Neuropsychiatric Genetics 2002, 116B: 60-68. PMID: 12497616, DOI: 10.1002/ajmg.b.10001.Peer-Reviewed Original ResearchGenomewide Scan of Hoarding in Sib Pairs in Which Both Sibs Have Gilles de la Tourette Syndrome
Zhang H, Leckman JF, Pauls DL, Tsai CP, Kidd KK, Campos MR, Genetics T. Genomewide Scan of Hoarding in Sib Pairs in Which Both Sibs Have Gilles de la Tourette Syndrome. American Journal Of Human Genetics 2002, 70: 896-904. PMID: 11840360, PMCID: PMC379118, DOI: 10.1086/339520.Peer-Reviewed Original ResearchAllelesBehavioral SymptomsChromosomes, HumanChromosomes, Human, Pair 17Chromosomes, Human, Pair 4Chromosomes, Human, Pair 5Gene FrequencyGenetic LinkageGenetic MarkersGenome, HumanHumansMatched-Pair AnalysisNuclear FamilyObsessive-Compulsive DisorderPhenotypeQuantitative Trait, HeritableSoftwareStatistics, NonparametricTourette Syndrome
2001
Symptom dimensions in obsessive‐compulsive disorder: Toward quantitative phenotypes
Leckman J, Zhang H, Alsobrook J, Pauls D. Symptom dimensions in obsessive‐compulsive disorder: Toward quantitative phenotypes. American Journal Of Medical Genetics 2001, 105: 28-30. PMID: 11424988, DOI: 10.1002/1096-8628(20010108)105:1<28::aid-ajmg1050>3.0.co;2-8.Peer-Reviewed Original Research
1997
Cost-effective sib-pair designs in the mapping of quantitative-trait loci.
Zhao H, Zhang H, Rotter JI. Cost-effective sib-pair designs in the mapping of quantitative-trait loci. American Journal Of Human Genetics 1997, 60: 1211-21. PMID: 9150169, PMCID: PMC1712450.Peer-Reviewed Original Research
1996
Mapping quantitative-trait loci in humans by use of extreme concordant sib pairs: selected sampling by parental phenotypes.
Zhang H, Risch N. Mapping quantitative-trait loci in humans by use of extreme concordant sib pairs: selected sampling by parental phenotypes. American Journal Of Human Genetics 1996, 59: 951-7. PMID: 8808613, PMCID: PMC1914798.Peer-Reviewed Original Research