Leying Guan
Associate Professor of BiostatisticsDownloadHi-Res Photo
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Associate Professor of Biostatistics
Biography
Leying Guan is an Assistant Professor of Biostatistics at Yale University. She received her Ph.D from the Statistics department at Stanford in 2019. Her research primarily focuses on high dimensional statsitics, robust statistical learning, statistical inference and developing statistical and machine learning methods driven by scientific applications including genetics, immunology, and computational neuroscience.
Last Updated on April 07, 2025.
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Biostatistics
Associate Professor on TermPrimary
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Overview
High-dimensional Statistics; Statistical Inference; Outlier Detection; Machine Learning and Data Science; Statistical Genetics; Computational Neuroscience; Statistical Analysis of Immune Signatures in Human infection.
Medical Research Interests
Computational Biology; Epigenomics; Gene Regulatory Networks; Genetics; Immune System Diseases; Machine Learning; Neurosciences; Statistics
ORCID
0000-0003-0609-1073
Research at a Glance
Yale Co-Authors
Frequent collaborators of Leying Guan's published research.
Publications Timeline
A big-picture view of Leying Guan's research output by year.
Research Interests
Research topics Leying Guan is interested in exploring.
Steven Kleinstein, PhD
David A. Hafler, MD, FANA
Ruth R Montgomery, PhD
Albert Ko, MD
Albert C Shaw, MD, PhD
Charles Dela Cruz, MD, PhD
33Publications
1,039Citations
Computational Biology
Machine Learning
Publications
2025
Baseline predictors for 28-day COVID-19 severity and mortality among hospitalized patients: results from the IMPACC study
Hou J, Haslund-Gourley B, Diray-Arce J, Hoch A, Rouphael N, Becker P, Augustine A, Ozonoff A, Guan L, Kleinstein S, Peters B, Reed E, Altman M, Langelier C, Maecker H, Kim S, Montgomery R, Krammer F, Wilson M, Eckalbar W, Bosinger S, Levy O, Steen H, Rosen L, Baden L, Melamed E, Ehrlich L, McComsey G, Sekaly R, Schaenman J, Shaw A, Hafler D, Corry D, Kheradmand F, Atkinson M, Brakenridge S, Agudelo Higuita N, Metcalf J, Hough C, Messer W, Pulendran B, Nadeau K, Davis M, Fernandez Sesma A, Simon V, Kraft M, Bime C, Calfee C, Erle D, Impacc Network, Robinson L, Cairns C, Haddad E, Comunale M. Baseline predictors for 28-day COVID-19 severity and mortality among hospitalized patients: results from the IMPACC study. Frontiers In Medicine 2025, 12: 1604388. PMID: 40687705, PMCID: PMC12271175, DOI: 10.3389/fmed.2025.1604388.Peer-Reviewed Original ResearchAltmetricConceptsSequential Organ Failure AssessmentPeripheral blood mononuclear cellsLaboratory biomarkersSequential Organ Failure Assessment scoreAntibody titersNasal viral loadOrgan Failure AssessmentBlood mononuclear cellsSARS-CoV-2 antibody titersSARS-CoV-2 infectionCOVID-19 patientsCOVID-19 cohortMortality prediction modelCOVID-19 severityPatient ageViral loadBlood cytometryImmunophenotypic assessmentMononuclear cellsClinical dataBaseline biomarkersFailure AssessmentBiomarkers of COVID-19Hospitalized patientsIL-6Type 2 immune responses are associated with less severe COVID-19 in a hospitalized cohort
Jayavelu N, Qi J, Milliren C, Ozonoff A, Liu S, Levy O, Baden L, Melamed E, McComsey G, Cairns C, Schaenman J, Shaw A, Hafler D, Corry D, Kheradmand F, Atkinson M, Brakenridge S, Higuita N, Metcalf J, Hough C, Messer W, Pulendran B, Nadeau K, Davis M, Geng L, Sesma A, Simon V, Krammer F, Bime C, Calfee C, Bosinger S, Eckalbar W, Steen H, Maecker H, Becker P, Augustine A, Holland S, Rosen L, Lee S, Vaysman T, Ozonoff A, Diray-Arce J, Chen J, Kho A, Milliren C, Hoch A, Chang A, McEnaney K, Barton B, Lentucci C, Murphy M, Saluvan M, Shaheen T, Liu S, Syphurs C, Albert M, Hayati A, Bryant R, Abraham J, Thomas S, Cooney M, Karoly M, Altman M, Jayavelu N, Presnell S, Kohr B, Jancsyk T, Arnett A, Peters B, Overton J, Vita R, Westendorf K, Overton J, Levy O, Steen H, van Zalm P, Fatou B, Smolen K, Viode A, van Haren S, Jha M, Stevenson D, Odumade O, Baden L, Mendez K, Lasky-Su J, Tong A, Rooks R, Desjardins M, Sherman A, Walsh S, Mitre X, Cauley J, Li X, Evans B, Montesano C, Licona J, Krauss J, Issa N, Chang J, Izaguirre N, Hutton S, Michelotti G, Wong K, Tebbutt S, Shannon C, Sekaly R, Fourati S, McComsey G, Harris P, Sieg S, Ribeiro S, Cairns C, Haddad E, Kutzler M, Bernui M, Cusimano G, Connors J, Woloszczuk K, Joyner D, Edwards C, Lee E, Lin E, Melnyk N, Powell D, Kim J, Goonewardene I, Simmons B, Smith C, Martens M, Croen B, Semenza N, Bell M, Furukawa S, McLin R, Tegos G, Rogowski B, Mege N, Ulring K, Schearer P, Sheidy J, Nagle C, Seyfert-Margolis V, Rouphael N, Bosinger S, Boddapati A, Tharp G, Pellegrini K, Johnson B, Panganiban B, Huerta C, Anderson E, Samaha H, Sevransky J, Bristow L, Beagle E, Cowan D, Hamilton S, Hodder T, Bechnak A, Cheng A, Mehta A, Ciric C, Spainhour C, Carter E, Scherer E, Usher J, Hellmeister K, Hussaini L, Hewitt L, Mcnair N, Ribeiro S, Wimalasena S, Fernandez-Sesma A, Simon V, Krammer F, Van Bakel H, Kim-Schulze S, Reiche A, Qi J, Lee B, Carreño J, Singh G, Raskin A, Tcheou J, Khalil Z, van de Guchte A, Farrugia K, Khan Z, Kelly G, Srivastava K, Eaker L, Bermúdez-González M, Mulder L, Beach K, Saksena M, Altman D, Kojic E, Sominsky L, Azad A, Bielak D, Kawabata H, Yellin T, Fried M, Sullivan L, Morris S, Kleiner G, Stadlbauer D, Dutta J, Xie H, Patel M, Nie K, Rahman A, Messer W, Hough C, Siegel S, Sullivan P, Lu Z, Brunton A, Strand M, Lyski Z, Coulter F, Micheleti C, Maecker H, Pulendran B, Nadeau K, Rosenberg-Hasson Y, Leipold M, Sigal N, Rogers A, Fernandes A, Manohar M, Do E, Chang I, Lee A, Blish C, Din H, Roque J, Geng L, Artandi M, Davis M, Ahuja N, Yang S, Chinthrajah S, Hagan T, Reed E, Schaenman J, Salehi-Rad R, Rivera A, Pickering H, Sen S, Elashoff D, Ward D, Brook J, Sanchez E, Llamas M, Perdomo C, Magyar C, Fulcher J, Erle D, Calfee C, Hendrickson C, Kangelaris K, Nguyen V, Lee D, Chak S, Ghale R, Gonzalez A, Jauregui A, Leroux C, Altamirano L, Rashid A, Willmore A, Woodruff P, Krummel M, Carrillo S, Ward A, Langelier C, Patel R, Wilson M, Dandekar R, Alvarenga B, Rajan J, Eckalbar W, Schroeder A, Fragiadakis G, Tsitsiklis A, Mick E, Guerrero Y, Love C, Maliskova L, Adkisson M, Leligdowicz A, Beagle A, Rao A, Sigman A, Samad B, Curiel C, Shaw C, Tietje-Ulrich G, Milush J, Singer J, Vasquez J, Tang K, Betancourt L, Santhosh L, Pierce L, Paz M, Matthay M, Thakur N, Rodriguez N, Sutter N, Jones N, Sinha P, Prasad P, Lota R, Rashid S, Asthana S, Bhide S, Lea T, Abe-Jones Y, Hafler D, Montgomery R, Shaw A, Kleinstein S, Gygi J, Pawar S, Konstorum A, Chen E, Cotsapas C, Wang X, Xu L, Dela Cruz C, Iwasaki A, Mohanty S, Nelson A, Zhao Y, Farhadian S, Asashima H, Chaudhary O, Coppi A, Fournier J, Muenker M, Nelson A, Raddassi K, Rainone M, Ruff W, Salahuddin S, Shulz W, Vijayakumar P, Wang H, Wunder E, Young H, Ko A, Wang X, Duchen D, Esserman D, Guan L, Brito A, Rothman J, Grubaugh N, Corry D, Kheradmand F, Song L, Nelson E, Metcalf J, Higuita N, Sinko L, Booth J, Drevets D, Brown B, Kraft M, Bime C, Mosier J, Erickson H, Schunk R, Kimura H, Conway M, Francisco D, Molzahn A, Wilson C, Schunk R, Hughes T, Sierra B, Atkinson M, Brakenridge S, Ungaro R, Manning B, Moldawer L, Oberhaus J, Guirgis F, Borresen B, Anderson M, Ehrlich L, Melamed E, Maguire C, Wylie D, Rousseau J, Hurley K, Geltman J, Siles N, Rogers J, Augustine A, Diray-Arce J, Haddad E, Sekaly R, Kraft M, Woodruff P, Erle D, Ehrlich L, Montgomery R, Becker P, Altman M, Fourati S. Type 2 immune responses are associated with less severe COVID-19 in a hospitalized cohort. Journal Of Allergy And Clinical Immunology Global 2025, 4: 100515. PMID: 40709330, PMCID: PMC12284355, DOI: 10.1016/j.jacig.2025.100515.Peer-Reviewed Original ResearchCitationsConceptsT2 immune responseClinical outcomesVirus loadImmune responseSARS-CoV-2Primary siteSusceptibility to respiratory viral infectionsType 2 immune responsesAntibody titersCellular markersPrimary site of infectionSeverity of respiratory illnessRespiratory viral infectionsIL-13 levelsDegree of respiratory supportAssociated with less severe COVID-19Site of infectionLow virus loadSevere COVID-19Effects of SARS-CoV-2Severe coronavirus diseaseDiagnosis of asthmaRespiratory supportCoronavirus severe acute respiratory syndrome coronavirus 2Blood cytometryFTO inhibition enhances the therapeutic index of radiation therapy in head and neck cancer
Ji L, Pu L, Wang J, Cao H, Melemenidis S, Sinha S, Guan L, Laseinde E, von Eyben R, Richter S, Nam J, Kong C, Casey K, Graves E, Frock R, Le Q, Rankin E. FTO inhibition enhances the therapeutic index of radiation therapy in head and neck cancer. JCI Insight 2025, 10: e184968. PMID: 40485587, PMCID: PMC12220955, DOI: 10.1172/jci.insight.184968.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsTherapeutic index of radiation therapyHPV- head and neck squamous cell carcinomaRadiation therapyTherapeutic indexRT responseHead and neck squamous cell carcinomaRadiation-induced oral mucositisNeck squamous cell carcinomaPharmacological inhibitionHead and neck cancerDrug-radiotherapy combinationsOverall survival rateEfficacy of RTSquamous cell carcinomaTherapeutic targetObesity-related genesAssociated with increased DNA damageChemoradiation treatmentOral mucositisCell carcinomaHNSCC treatmentHNSCC cellsNeck cancerPotential therapeutic targetCancer therapeutic targetPartially characterized topology guides reliable anchor-free scRNA-integration
He C, Filippidis P, Kleinstein S, Guan L. Partially characterized topology guides reliable anchor-free scRNA-integration. Communications Biology 2025, 8: 561. PMID: 40185996, PMCID: PMC11971424, DOI: 10.1038/s42003-025-07988-y.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsBatch effectsRare cell typesSingle-cell RNA sequencingCell typesDownstream statistical analysisScRNA-seqBiological insightsRNA sequencingBatch correctionCell phenotypeCellular resolutionBiological signalsState-of-the-art methodsAdaptive lossDomain adaptation lossState-of-the-artDiverse setBatch integrationHeterogeneous cell distributionReconstruction lossSequenceTriplet lossPhenotypeSignalCell distributionSalivary gland stem/progenitor cells: advancing from basic science to clinical applications
Langthasa J, Guan L, Jinagal S, Le Q. Salivary gland stem/progenitor cells: advancing from basic science to clinical applications. Cell Regeneration 2025, 14: 4. PMID: 39856475, PMCID: PMC11759724, DOI: 10.1186/s13619-025-00221-5.Peer-Reviewed Original ResearchCitationsAltmetricConceptsSalivary gland stem/progenitor cellsBioengineered organ replacementTissue-based therapiesEffective clinical therapiesRadiation therapySjogren's syndromeStem/progenitor cellsClinical therapyTherapyDifferentiation pathwayClinical applicationRegenerative medicineSyndromeTissue regenerationOrgan replacementCulture techniquesSjogrenTransplantationPatientsEstimation of leading multi-block canonical correlation directions via ℓ1-norm constrained proximal gradient descent
Guan L. Estimation of leading multi-block canonical correlation directions via ℓ1-norm constrained proximal gradient descent. Electronic Journal Of Statistics 2025, 19 DOI: 10.1214/25-ejs2351.Peer-Reviewed Original Research
2024
Gold-siRNA supraclusters enhance the anti-tumor immune response of stereotactic ablative radiotherapy at primary and metastatic tumors
Jiang Y, Cao H, Deng H, Guan L, Langthasa J, Colburg D, Melemenidis S, Cotton R, Aleman J, Wang X, Graves E, Kalbasi A, Pu K, Rao J, Le Q. Gold-siRNA supraclusters enhance the anti-tumor immune response of stereotactic ablative radiotherapy at primary and metastatic tumors. Nature Biotechnology 2024, 43: 1496-1509. PMID: 39448881, PMCID: PMC12018592, DOI: 10.1038/s41587-024-02448-0.Peer-Reviewed Original ResearchCitationsAltmetricConceptsStereotactic ablative radiotherapyAnti-tumor immune responseSmall interfering RNAAblative radiotherapyMetastatic tumorsEffect of stereotactic ablative radiotherapyModel of head and neck cancerHead and neck cancerImmunosuppressive cell populationsPD-1 inhibitorsSmall interfering RNA complexesPD-1Primary tumorImmunotherapeutic effectsNeck cancerGranzyme BGal-1Mouse modelPassive deliveryTumorReduced toxicityCell populationsRadiotherapyRadiosensitivityRenal filtration thresholdA Survival Analysis of Patients with Radiation-Induced Cancers after Prior Radiation for Head and Neck Cancer
Laseinde E, Guan L, Hildebrand R, Meurice N, Gensheimer M, Beadle B, Holsinger F, Sunwoo J, Baik F, Sirjani D, Divi V, Kaplan M, Pinto H, Colevas A, Rahman M, Le Q. A Survival Analysis of Patients with Radiation-Induced Cancers after Prior Radiation for Head and Neck Cancer. International Journal Of Radiation Oncology • Biology • Physics 2024, 120: e764. DOI: 10.1016/j.ijrobp.2024.07.1678.Peer-Reviewed Original ResearchConceptsHead and neck cancerNonsurgical groupNeck cancerRadiation treatmentTreated with non-surgical therapyIRB-approved retrospective reviewSurvival rateKaplan-Meier survival curvesSurvival rate of patientsNon-surgical therapySurvival analysis of patientsLog-rank testAnalysis of patientsNon-surgical groupNon-surgical treatmentRate of patientsRadiation-induced cancerCompare survival ratesPrior RTPostoperative RTMedian followPrior radiationSquamous histologyOverall survivalMedian ageTert-expressing cells contribute to salivary gland homeostasis and tissue regeneration after radiation therapy
Guan L, Viswanathan V, Jiang Y, Vijayakumar S, Cao H, Zhao J, Colburg D, Neuhöfer P, Zhang Y, Wang J, Xu Y, Laseinde E, Hildebrand R, Rahman M, Frock R, Kong C, Beachy P, Artandi S, Le Q. Tert-expressing cells contribute to salivary gland homeostasis and tissue regeneration after radiation therapy. Genes & Development 2024, 38: 569-582. PMID: 38997156, PMCID: PMC11293384, DOI: 10.1101/gad.351577.124.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsSubmandibular glandSalivary gland homeostasisProgenitor cellsGland homeostasisResponse to radiotherapyAdult submandibular glandCell survivalSalivary gland regenerationSelf-renewal capacityEnhanced proliferative activityRadiation therapyDuctal regionsRadiotherapyModulate cell survivalTelomerase-expressingGland regenerationProliferative activityMouse strainsTERT expressionCreERT2 recombinaseSalivary gland biologyRadiation exposureTERT locusIn vitro cultureCell populationsIntegrated longitudinal multiomics study identifies immune programs associated with acute COVID-19 severity and mortality
Gygi J, Maguire C, Patel R, Shinde P, Konstorum A, Shannon C, Xu L, Hoch A, Jayavelu N, Haddad E, Network I, Reed E, Kraft M, McComsey G, Metcalf J, Ozonoff A, Esserman D, Cairns C, Rouphael N, Bosinger S, Kim-Schulze S, Krammer F, Rosen L, van Bakel H, Wilson M, Eckalbar W, Maecker H, Langelier C, Steen H, Altman M, Montgomery R, Levy O, Melamed E, Pulendran B, Diray-Arce J, Smolen K, Fragiadakis G, Becker P, Sekaly R, Ehrlich L, Fourati S, Peters B, Kleinstein S, Guan L. Integrated longitudinal multiomics study identifies immune programs associated with acute COVID-19 severity and mortality. Journal Of Clinical Investigation 2024, 134: e176640. PMID: 38690733, PMCID: PMC11060740, DOI: 10.1172/jci176640.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsClinical outcomesImmune cascadeElevated levels of inflammatory cytokinesDisease severityLevels of inflammatory cytokinesFormation of neutrophil extracellular trapsAcute COVID-19 severityCritically ill patientsNeutrophil extracellular trapsDevelopment of therapiesCOVID-19 cohortCOVID-19 severityViral clearanceImmunosuppressive metabolitesDeep immunophenotypingMultiomic modelIFN-stimulated genesImmunophenotypic assessmentB cellsDisease courseEarly upregulationInflammatory cytokinesDisease progressionIFN inhibitorsExtracellular traps
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