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 studyStatistical methods for assessing the effects of de novo variants on birth defects
Xie Y, Wu R, Li H, Dong W, Zhou G, Zhao H. Statistical methods for assessing the effects of de novo variants on birth defects. Human Genomics 2024, 18: 25. PMID: 38486307, PMCID: PMC10938830, DOI: 10.1186/s40246-024-00590-z.Peer-Reviewed Original ResearchConceptsDe novo variantsAnalyzed de novo variantsDevelopment of next-generation sequencing technologiesNext-generation sequencing technologiesSequencing technologiesImprove statistical powerGenetic heterogeneitySequenced samplesStatistical powerBirth defectsDiseased individualsLow occurrenceCongenital heart diseaseVariantsGenesDeleterious effectsSequenceGeneral workflowStatistical methodsPhenome- and genome-wide analyses of retinal optical coherence tomography images identify links between ocular and systemic health
Zekavat S, Jorshery S, Rauscher F, Horn K, Sekimitsu S, Koyama S, Nguyen T, Costanzo M, Jang D, Burtt N, Kühnapfel A, Shweikh Y, Ye Y, Raghu V, Zhao H, Ghassemi M, Elze T, Segrè A, Wiggs J, Del Priore L, Scholz M, Wang J, Natarajan P, Zebardast N. Phenome- and genome-wide analyses of retinal optical coherence tomography images identify links between ocular and systemic health. Science Translational Medicine 2024, 16: eadg4517. PMID: 38266105, DOI: 10.1126/scitranslmed.adg4517.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesRetinal layer thicknessPhotoreceptor segmentsOptical coherence tomographyRetinal layersUK Biobank participantsLIFE-Adult-StudyInherited genetic lociGenome-wide associationGanglion cell complex layerRetinal optical coherence tomography imagesRetinal nerve fiber layerAge-related macular degenerationBiobank participantsEye careNerve fiber layerOptical coherence tomography imagesIncident mortalityMacular OCT imagesLIFE-AdultIndependent associationsAssociation studiesSystemic healthGenetic associationGenome-wide analysisTuning parameters for polygenic risk score methods using GWAS summary statistics from training data
Jiang W, Chen L, Girgenti M, Zhao H. Tuning parameters for polygenic risk score methods using GWAS summary statistics from training data. Nature Communications 2024, 15: 24. PMID: 38169469, PMCID: PMC10762162, DOI: 10.1038/s41467-023-44009-0.Peer-Reviewed Original Research
2023
scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles
Zhu B, Wang Y, Ku L, van Dijk D, Zhang L, Hafler D, Zhao H. scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles. Genome Biology 2023, 24: 292. PMID: 38111007, PMCID: PMC10726524, DOI: 10.1186/s13059-023-03129-y.Peer-Reviewed Original ResearchProfilin1 is required to prevent mitotic catastrophe in murine and human glomerular diseases
Tian X, Pedigo C, Li K, Ma X, Bunda P, Pell J, Lek A, Gu J, Zhang Y, Rangel P, Li W, Schwartze E, Nagata S, Lerner G, Perincheri S, Priyadarshini A, Zhao H, Lek M, Menon M, Fu R, Ishibe S. Profilin1 is required to prevent mitotic catastrophe in murine and human glomerular diseases. Journal Of Clinical Investigation 2023, 133: e171237. PMID: 37847555, PMCID: PMC10721156, DOI: 10.1172/jci171237.Peer-Reviewed Original ResearchConceptsProteinuric kidney diseaseKidney diseasePodocyte lossHuman glomerular diseasesMitotic catastrophePodocyte cell cycleSevere proteinuriaCell cycle reentryKidney failureGlomerular diseaseCell cycleKidney tissueG1/S checkpointUnsuccessful repairCyclin D1Glomerular integrityIrregular nucleiTissue-specific lossMouse podocytesPodocytesAltered expressionDiseaseCyclin B1Ribosome affinity purificationMultinucleated cellsCell-type-specific co-expression inference from single cell RNA-sequencing data
Su C, Xu Z, Shan X, Cai B, Zhao H, Zhang J. Cell-type-specific co-expression inference from single cell RNA-sequencing data. Nature Communications 2023, 14: 4846. PMID: 37563115, PMCID: PMC10415381, DOI: 10.1038/s41467-023-40503-7.Peer-Reviewed Original ResearchA statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases
Liu W, Deng W, Chen M, Dong Z, Zhu B, Yu Z, Tang D, Sauler M, Lin C, Wain L, Cho M, Kaminski N, Zhao H. A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases. PLOS Genetics 2023, 19: e1010825. PMID: 37523391, PMCID: PMC10414598, DOI: 10.1371/journal.pgen.1010825.Peer-Reviewed Original ResearchConceptsCell typesDisease-associated tissuesWide association studyComplex diseasesCell type proportionsDisease-relevant tissuesReal GWAS dataFunctional genesTranscriptomic dataGWAS dataGenetic dataAssociation studiesNovel statistical frameworkChronic obstructive pulmonary diseaseStatistical frameworkObstructive pulmonary diseaseIdiopathic pulmonary fibrosisBreast cancer riskType proportionsBlood CD8Pulmonary diseasePulmonary fibrosisPredictive biomarkersLung tissueBreast cancerMulti-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program
Cheng Y, Dao C, Zhou H, Li B, Kember R, Toikumo S, Zhao H, Gelernter J, Kranzler H, Justice A, Xu K. Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program. Translational Psychiatry 2023, 13: 148. PMID: 37147289, PMCID: PMC10162964, DOI: 10.1038/s41398-023-02409-2.Peer-Reviewed Original ResearchConceptsSingle-trait genome-wide association studiesGenome-wide association studiesNovel lociPower of GWASJoint genome-wide association studyGenome-wide significant lociMillion Veteran ProgramGenome-wide associationSubstance use traitsGWAS summary statisticsNovel genetic variantsMulti-trait analysisFunctional annotationUse traitsSignificant lociHeritable traitMultiple lociAssociation studiesColocalization analysisLociPleiotropic effectsMTAgVeteran ProgramGenetic variantsTraitsEarly breast cancer risk detection: a novel framework leveraging polygenic risk scores and machine learning
Tao L, Ye Y, Zhao H. Early breast cancer risk detection: a novel framework leveraging polygenic risk scores and machine learning. Journal Of Medical Genetics 2023, 60: 960-964. PMID: 37055164, DOI: 10.1136/jmg-2022-108582.Peer-Reviewed Original ResearchConceptsBreast cancerPolygenic risk scoresRisk scoreBC risk assessmentClinical breast examNon-genetic risk factorsHigh-risk individualsFemale participantsBreast examCancer deathCommon cancerBC screeningRisk factorsBC diagnosisDisease risk predictionDiagnostic stepsPopulation screeningGenetic riskRisk predictionUK BiobankCancerDiagnosisDiagnostic pipelineWomenDetection testEstimation on risk of spontaneous abortions by genomic disorders from a meta‐analysis of microarray results on large case series of pregnancy losses
Peng G, Zhou Q, Chai H, Wen J, Zhao H, Taylor H, Jiang Y, Li P. Estimation on risk of spontaneous abortions by genomic disorders from a meta‐analysis of microarray results on large case series of pregnancy losses. Molecular Genetics & Genomic Medicine 2023, 11: e2181. PMID: 37013615, PMCID: PMC10422064, DOI: 10.1002/mgg3.2181.Peer-Reviewed Original ResearchConceptsGenomic disordersChromosome microarray analysisWilliams-Beuren syndromePathogenic copy number variantsPopulation genetic studiesWolf-Hirschhorn syndromeCopy number variantsDiGeorge syndromeMicroarray analysisMicroarray resultsChromosomal abnormalitiesGenetic studiesNumber variantsGenetic counselingA genome-wide association study of frailty identifies significant genetic correlation with neuropsychiatric, cardiovascular, and inflammation pathways
Ye Y, Noche R, Szejko N, Both C, Acosta J, Leasure A, Brown S, Sheth K, Gill T, Zhao H, Falcone G. A genome-wide association study of frailty identifies significant genetic correlation with neuropsychiatric, cardiovascular, and inflammation pathways. GeroScience 2023, 45: 2511-2523. PMID: 36928559, PMCID: PMC10651618, DOI: 10.1007/s11357-023-00771-z.Peer-Reviewed Original ResearchConceptsFried frailty scoreBiology of frailtyEuropean descent participantsOccurrence of frailtyGenome-wide association studiesMendelian randomization analysisFrailty scoreChronic painJoint disordersPolygenic risk scoresRespiratory diseaseInflammation pathwaysRisk scoreClinical phenotypeBrain tissueCausal associationFrailtyAge-related pathwaysRandomization analysisGenetic factorsAssociation studiesUK BiobankRetirement StudyPerson's vulnerabilitySignificant genetic correlationsWhole-Exome Sequencing Analyses Support a Role of Vitamin D Metabolism in Ischemic Stroke
Xie Y, Acosta J, Ye Y, Demarais Z, Conlon C, Chen M, Zhao H, Falcone G. Whole-Exome Sequencing Analyses Support a Role of Vitamin D Metabolism in Ischemic Stroke. Stroke 2023, 54: 800-809. PMID: 36762557, PMCID: PMC10467223, DOI: 10.1161/strokeaha.122.040883.Peer-Reviewed Original ResearchConceptsGene-based testingRare genetic variationGene-based analysisGenetic variationAssociation studiesGenome-wide association studiesSingle-variant association analysisWide significance levelSusceptibility risk lociWide association studyDeleterious missense variantsMissense rare variantsBonferroni-corrected thresholdWhole-exome sequencing dataRare variantsSingle variant analysisHeritable traitRisk lociExome-wide studySequencing dataExome sequencing analysisAssociation analysisSequencing analysisMissense variantsTraitsHBV-infected hepatocellular carcinoma can be robustly classified into three clinically relevant subgroups by a novel analytical protocol
Cheng Z, Li L, Zhang Y, Ren Y, Gu J, Wang X, Zhao H, Lu H. HBV-infected hepatocellular carcinoma can be robustly classified into three clinically relevant subgroups by a novel analytical protocol. Briefings In Bioinformatics 2023, 24: bbac601. PMID: 36736372, DOI: 10.1093/bib/bbac601.Peer-Reviewed Original ResearchConceptsHepatocellular carcinomaClinical stageImmune microenvironmentTumor sizeHepatitis B virus infectionLow alpha-fetoprotein levelsMetabolism-related proteinsRelevant subgroupsB virus infectionSevere liver dysfunctionGood liver functionHigh AFP levelsAlpha-fetoprotein levelsPrimary liver malignancySmaller tumor sizeLarger tumor sizeLower clinical stageHigher clinical stageCancer-related deathProliferation activityPrevention of HBVNear-normal levelsLow proliferation activityLiver dysfunctionHigh proliferation activityIdentification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans
Kimbrel N, Ashley-Koch A, Qin X, Lindquist J, Garrett M, Dennis M, Hair L, Huffman J, Jacobson D, Madduri R, Trafton J, Coon H, Docherty A, Mullins N, Ruderfer D, Harvey P, McMahon B, Oslin D, Beckham J, Hauser E, Hauser M, Agarwal K, Ashley-Koch A, Aslan M, Beckham J, Begoli E, Bhattacharya T, Brown B, Calhoun P, Cheung K, Choudhury S, Cliff A, Cohn J, Crivelli S, Cuellar-Hengartner L, Deangelis H, Dennis M, Dhaubhadel S, Finley P, Ganguly K, Garvin M, Gelernter J, Hair L, Harvey P, Hauser E, Hauser M, Hengartner N, Jacobson D, Jones P, Kainer D, Kaplan A, Katz I, Kember R, Kimbrel N, Kirby A, Ko J, Kolade B, Lagergren J, Lane M, Levey D, Levin D, Lindquist J, Liu X, Madduri R, Manore C, Martins S, McCarthy J, McDevitt-Cashman M, McMahon B, Miller I, Morrow D, Oslin D, Pavicic-Venegas M, Pestian J, Pyarajan S, Qin X, Rajeevan N, Ramsey C, Ribeiro R, Rodriguez A, Romero J, Santel D, Schaefferkoetter N, Shi Y, Stein M, Sullivan K, Sun N, Tamang S, Townsend A, Trafton J, Walker A, Wang X, Wangia-Anderson V, Yang R, Yoon H, Yoo S, Zamora-Resendiz R, Zhao H, Docherty A, Mullins N, Coleman J, Shabalin A, Kang J, Murnyak B, Wendt F, Adams M, Campos A, DiBlasi E, Fullerton J, Kranzler H, Bakian A, Monson E, Rentería M, Andreassen O, Bulik C, Edenberg H, Kessler R, Mann J, Nurnberger J, Pistis G, Streit F, Ursano R, Awasthi S, Bergen A, Berrettini W, Bohus M, Brandt H, Chang X, Chen H, Chen W, Christensen E, Crawford S, Crow S, Duriez P, Edwards A, Fernández-Aranda F, Fichter M, Galfalvy H, Gallinger S, Gandal M, Gorwood P, Guo Y, Hafferty J, Hakonarson H, Halmi K, Hishimoto A, Jain S, Jamain S, Jiménez-Murcia S, Johnson C, Kaplan A, Kaye W, Keel P, Kennedy J, Kim M, Klump K, Levey D, Li D, Liao S, Lieb K, Lilenfeld L, Lori A, Magistretti P, Marshall C, Mitchell J, Myers R, Okazaki S, Otsuka I, Pinto D, Powers A, Ramoz N, Ripke S, Roepke S, Rozanov V, Scherer S, Schmahl C, Sokolowski M, Starnawska A, Strober M, Su M, Thornton L, Treasure J, Ware E, Watson H, Witt S, Woodside D, Yilmaz Z, Zillich L, Agerbo E, Børglum A, Breen G, Demontis D, Erlangsen A, Esko T, Gelernter J, Glatt S, Hougaard D, Hwu H, Kuo P, Lewis C, Li Q, Liu C, Martin N, McIntosh A, Medland S, Mors O, Nordentoft M, Nurnberger J, Olsen C, Porteous D, Smith D, Stahl E, Stein M, Wasserman D, Werge T, Whiteman D, Willour V, Coon H, Ruderfer D, Dedert E, Elbogen E, Fairbank J, Hurley R, Kilts J, Martindale S, Marx C, McDonald S, Moore S, Morey R, Naylor J, Rowland J, Shura R, Swinkels C, Tupler L, Van Voorhees E, Yoash-Gantz R, Gaziano J, Muralidhar S, Ramoni R, Chang K, O’Donnell C, Tsao P, Breeling J, Hauser E, Sun Y, Huang G, Casas J, Moser J, Whitbourne S, Brewer J, Conner T, Argyres D, Stephens B, Brophy M, Humphries D, Selva L, Do N, Shayan S, Cho K, Churby L, Wilson P, McArdle R, Dellitalia L, Mattocks K, Harley J, Whittle J, Jacono F, Wells J, Gutierrez S, Gibson G, Hammer K, Kaminsky L, Villareal G, Kinlay S, Xu J, Hamner M, Mathew R, Bhushan S, Iruvanti P, Godschalk M, Ballas Z, Ivins D, Mastorides S, Moorman J, Gappy S, Klein J, Ratcliffe N, Florez H, Okusaga O, Murdoch M, Sriram P, Yeh S, Tandon N, Jhala D, Liangpunsakul S, Oursler K, Whooley M, Ahuja S, Constans J, Meyer P, Greco J, Rauchman M, Servatius R, Gaddy M, Wallbom A, Morgan T, Stapley T, Sherman S, Ross G, Strollo P, Boyko E, Meyer L, Gupta S, Huq M, Fayad J, Hung A, Lichy J, Hurley R, Robey B, Striker R. Identification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans. JAMA Psychiatry 2023, 80: 135-145. PMID: 36515925, PMCID: PMC9857322, DOI: 10.1001/jamapsychiatry.2022.3896.Peer-Reviewed Original ResearchConceptsMolecular genetic basisRisk lociSingle nucleotide variantsGWS lociGenetic basisGenomic risk lociRisk genesGenome-wide association studiesSignificant enrichmentGene-based analysisGenetic risk lociCandidate risk genesCyclic adenosine monophosphate (cAMP) signalingIdentification of novelPolygenic risk score analysisGene clusterFocal adhesionsGenetic substructureUbiquitination processChromosome 2Enrichment analysisAssociation studiesAxon guidanceAfrican ancestryNCAM1-TTC12Massively parallel knock-in engineering of human T cells
Dai X, Park J, Du Y, Na Z, Lam S, Chow R, Renauer P, Gu J, Xin S, Chu Z, Liao C, Clark P, Zhao H, Slavoff S, Chen S. Massively parallel knock-in engineering of human T cells. Nature Biotechnology 2023, 41: 1239-1255. PMID: 36702900, DOI: 10.1038/s41587-022-01639-x.Peer-Reviewed Original ResearchTargeting ATAD3A-PINK1-mitophagy axis overcomes chemoimmunotherapy resistance by redirecting PD-L1 to mitochondria
Xie X, Yang Y, Wang Q, Liu H, Fang X, Li C, Jiang Y, Wang S, Zhao H, Miao J, Ding S, Liu X, Yao X, Yang W, Jiang J, Shao Z, Jin G, Bian X. Targeting ATAD3A-PINK1-mitophagy axis overcomes chemoimmunotherapy resistance by redirecting PD-L1 to mitochondria. Cell Research 2023, 33: 215-228. PMID: 36627348, PMCID: PMC9977947, DOI: 10.1038/s41422-022-00766-z.Peer-Reviewed Original ResearchConceptsImmune checkpoint inhibitorsPD-L1Combination therapyTherapeutic responsePD-1/PD-L1 signalingShorter progression-free survivalBreast cancer benefitProgression-free survivalPD-L1 signalingCheckpoint inhibitorsNab-paclitaxelCancer benefitImmunotherapy cohortImmune microenvironmentPreclinical resultsTumor cell membranesTumor samplesPaclitaxelHigh expressionPromising targetPatientsTherapyTumorsResistant factorATAD3A expression
2022
Association of Gulf War Illness with Characteristics in Deployed vs. Non-Deployed Gulf War Era Veterans in the Cooperative Studies Program 2006/Million Veteran Program 029 Cohort: A Cross-Sectional Analysis
Duong L, Djotsa A, Vahey J, Steele L, Quaden R, Harrington K, Ahmed S, Polimanti R, Streja E, Gaziano J, Concato J, Zhao H, Radhakrishnan K, Hauser E, Helmer D, Aslan M, Gifford E. Association of Gulf War Illness with Characteristics in Deployed vs. Non-Deployed Gulf War Era Veterans in the Cooperative Studies Program 2006/Million Veteran Program 029 Cohort: A Cross-Sectional Analysis. International Journal Of Environmental Research And Public Health 2022, 20: 258. PMID: 36612580, PMCID: PMC9819371, DOI: 10.3390/ijerph20010258.Peer-Reviewed Original ResearchConceptsGulf War IllnessGulf War Era VeteransChronic multisymptom illnessStudy inclusion criteriaCross-sectional analysisGW theaterGW veteransMultisymptom illnessEligible participantsUncertain etiologyInclusion criteriaKS symptomsDisease controlIllnessEra veteransMilitary characteristicsVeteransCohortPersistent presencePhenotypeFurther explorationPathophysiologyEtiologySymptomsPrevalenceAn unbiased kinship estimation method for genetic data analysis
Jiang W, Zhang X, Li S, Song S, Zhao H. An unbiased kinship estimation method for genetic data analysis. BMC Bioinformatics 2022, 23: 525. PMID: 36474154, PMCID: PMC9727941, DOI: 10.1186/s12859-022-05082-2.Peer-Reviewed Original ResearchConceptsRigorous mathematical proofGenetic data analysisReal data analysisUnbiased estimation methodEstimation methodIndividual-level genotype dataSample correlation coefficientMathematical proofMathematical derivationMean square errorCoefficient estimationMatrix methodEstimation accuracyEstimation biasHeritability estimationRoot mean square errorData analysisSquare errorAccurate estimatesEstimationUKINVariances of genotypesSpurious associationsKinship coefficientsEstimatesSDPRX: 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 traitsStatisticsSimulationsApplicationsTraits