Qing Lan, MD, PhD
Professor Adjunct of Epidemiology (Environmental Health)DownloadHi-Res Photo
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Professor Adjunct of Epidemiology (Environmental Health)
Professor Adjunct, Environmental Health Sciences
Biography
Dr. Qing Lan a world leader in environmental and occupational exposures, human health studies and gene environment interaction. Her research focuses on molecular epidemiologic studies of populations exposed to several classes of chemical compounds that are known or suspected occupational and environmental carcinogens. She is one of YSPH’s main collaborators at NCI studying environmental exposures, genetic susceptibility for NHL and multiple myeloma, indoor air pollution and gene polymorphisms for lung cancer risk in Xuanwei, China. She has mentored several YSPH PhD candidates.
Dr. Lan received her M.D. at Weifang Medical University and her Ph.D. in molecular epidemiology at the Chinese Academy of Preventive Medicine in Beijing, as part of a joint training program with the United States Environmental Protection Agency and University of North Carolina at Chapel Hill, and received her MPH at Johns Hopkins University.
Last Updated on April 07, 2025.
Appointments
Environmental Health Sciences
Professor AdjunctPrimary
Other Departments & Organizations
Education & Training
- PhD
- Chinese Academy of Preventive Medicine (2001)
- MD
- Weifang Medical College (1985)
Research
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Overview
Public Health Interests
Biomarkers; Environmental Health
ORCID
0000-0002-0888-8839
Research at a Glance
Yale Co-Authors
Frequent collaborators of Qing Lan's published research.
Publications Timeline
A big-picture view of Qing Lan's research output by year.
Melissa Friesen
Robert Homer, MD, PhD
Bonnie E Gould Rothberg, MD, PhD, MPH, MMM, FACP
Huey Cai
Lei Song, MD, PhD
Wei Zheng
68Publications
385Citations
Publications
2026
Systemic Lipid Peroxidation and Colorectal Cancer Risk: A Time‐Varying Relationship
Yang G, Milne G, Nogueira M, Gao Y, Lan Q, Yi H, Shu X, Zheng W, Chen Q. Systemic Lipid Peroxidation and Colorectal Cancer Risk: A Time‐Varying Relationship. International Journal Of Cancer 2026 PMID: 42298759, DOI: 10.1002/ijc.70585.Peer-Reviewed Original ResearchAltmetricConceptsUrinary F2 -isoprostanesColorectal cancer riskColorectal cancerSystemic lipid peroxidationOdds ratioShanghai cohortOxS indicesSystemic OxSChemopreventive benefitsMultivariable-adjusted odds ratioHigh-dose antioxidant supplementationSystemic oxidative stressNo significant associationConditional logistic regressionHigh-risk individualsAntioxidant supplementationRandomized Controlled TrialsTime-dependent associationsCRC riskBenefits of antioxidant supplementationLipid peroxidationUS cohortInverse associationReplication cohortLipid markersReliability of interrater occupation coding and potential impact on occupational exposure assessment
Ge C, Friesen M, Locke S, Rothman N, Lan Q, Vermeulen R. Reliability of interrater occupation coding and potential impact on occupational exposure assessment. Annals Of Work Exposures And Health 2026, 70: wxag013. PMID: 42276589, DOI: 10.1093/annweh/wxag013.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsJob-exposure matrixJob codesInternational Standard ClassificationOccupational codesCoding agreementHospital-based case-control studyJEM estimatesOccupational epidemiological studiesWeighted Cohen's kappaCase-control studyExposure assessmentISCO-88Stratified analysisPercentage agreementExposure assignmentCoder pairsEpidemiological studiesCohen's kappaJob descriptionsOccupational studiesExposure estimatesStudy phaseCenter 1Occupational exposure assessmentMainland ChinaMitochondrial DNA breaks and copy number and the risk of lung cancer in the Shanghai Women’s Health Study
Blechter B, Shu X, Hu W, Francis E, Zheng W, Cai Q, Cai H, Yang G, Hosgood H, Cawthon R, Lan Q. Mitochondrial DNA breaks and copy number and the risk of lung cancer in the Shanghai Women’s Health Study. Cancer Epidemiology Biomarkers & Prevention 2026, 10.1158/1055-9965.epi-26-0047. PMID: 42165669, PMCID: PMC13274563, DOI: 10.1158/1055-9965.epi-26-0047.Peer-Reviewed Original ResearchAltmetricConceptsShanghai Women's Health StudyProspective Shanghai Women's Health StudyWomen's Health StudyLung cancer riskNever-smoking womenHealth StudyCancer riskAssociated with lung cancer riskIncident lung cancer casesOdds ratioRisk of lung cancerConfidence intervalsConditional logistic regressionLung cancer casesBody mass indexCancer mortalityInverse associationCancer casesLow mtDNAcnMass indexLogistic regressionLung cancerMatched ControlsOddsWomenGenetic landscape and functional exploration of kidney cancer predisposition in cross-ancestral populations
Dai H, Chu X, Du H, Yang S, Yao Y, Yu X, Zhao Y, Dong P, Lyu Z, Wang W, Li H, Mi Z, Sheng C, Li X, Zheng H, Song F, Song F, Sun M, Dai J, Lan Q, Rothman N, Hu Z, Wei Q, Ye D, Yao X, Jia W, Chanock S, Shen H, Purdue M, Li M, Chen K. Genetic landscape and functional exploration of kidney cancer predisposition in cross-ancestral populations. Nature Communications 2026, 17: 5382. PMID: 42000752, PMCID: PMC13275800, DOI: 10.1038/s41467-026-71785-2.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsGenome-wide association studiesExpression quantitative trait lociCross-ancestryMulti-ancestry meta-analysisComplex genetic lociCRISPR-based screensQuantitative trait lociFunctional explorationGenetic architectureLatin American ancestryGenetic lociTrait lociAssociation studiesComprehensive genetic investigationGenetic landscapeFunctional screeningAmerican ancestryGenetic underpinningsCancer predispositionLociComplex diseasesGenetic investigationsEast AsiansAfrican AmericansRenal cell carcinomaCirculating levels of insulin‐like growth factor I (IGF‐I) and risk of multiple myeloma: An observational and Mendelian randomisation study
Benavente Y, Hermosa S, Papadimitriou N, Clay‐Gilmour A, Brown E, Hofmann J, Rothman N, Lan Q, Berndt S, Albanes D, Purdue M, Machiela M, Chanock S, Bhatti P, Cozen W, Norman A, Slager S, Cerhan J, Rajkumar V, Kumar S, Vachon C, Novak A, Habermann T, Link B, Salles G, Ghesquieres H, Bracci P, Holly E, Griffin R, Hildebrandt M, Vermeulen R, Kolijn P, Hjalgrim H, Smedby K, Jayasekara H, Cheah S, Monnereau A, Chen Y, Arslan A, Zhang Y, Camp N, Sborov D, Osman A, Ziv E, De Vivo I, Joseph V, Teras L, Patel A, Kane E, Vajdic C, Guilloteau A, Cocco P, Alemany L, Sainz J, McKay J, Birmann B, Casabonne D. Circulating levels of insulin‐like growth factor I (IGF‐I) and risk of multiple myeloma: An observational and Mendelian randomisation study. British Journal Of Haematology 2026, 208: 1942-1953. PMID: 41873017, PMCID: PMC13267475, DOI: 10.1111/bjh.70444.Peer-Reviewed Original ResearchAltmetricConceptsIGF-I levelsInsulin-like growth factorLymphoid neoplasmsIGF-IMultiple myelomaIGFBP-3Circulating LevelsChronic lymphocytic leukaemia/small lymphocytic lymphomaIGF-binding protein-3Circulating levels of insulin-like growth factor-ILevels of insulin-like growth factor-IInsulin-like growth factor-IIGFBP-3 levelsHigher Body Mass IndexRisk of MMBody mass indexGrowth factor-IBaseline serological dataIGF-I concentrationsRisk of multiple myelomaLymphocytic lymphomaIGF-bindingMM riskRandomised studyMass indexVariation on Toxic and Inflammatory Potential of Coal Smoke of Different Sources From a Region With High Lung Cancer Risk
Zhang Y, Hu W, Rothman N, Liu D, Li J, Xu J, Ning B, Vermeulen R, Lan Q, Cassee F, Downward G. Variation on Toxic and Inflammatory Potential of Coal Smoke of Different Sources From a Region With High Lung Cancer Risk. Environmental Toxicology 2026 PMID: 41802872, DOI: 10.1002/tox.70075.Peer-Reviewed Original ResearchConceptsLung cancer riskTransepithelial electrical resistanceCancer riskCo-culture modelInflammatory potentialPolycyclic aromatic hydrocarbonsHigher lung cancer riskEpithelial barrier damageIL-8 releaseLung cancer developmentDose-dependent mannerIL-6 releaseCoal samplesTransient inflammationCalu-3Lung cancerLung EpithelialIL-6Cancer developmentProinflammatory potentialBarrier damageLungTHP-1Carcinogenic mechanismsExcess lung cancer riskGenomic Characterization of Lung Cancer in Never-Smokers Using Deep Learning
Saha M, Tran T, Bhawsar P, Zhang T, Zhao W, Hoang P, Mutreja K, Lawrence S, Rothman N, Lan Q, Homer R, Baine M, Sholl L, Joubert P, Leduc C, Travis W, Chanock S, Shi J, Yang S, Almeida J, Landi M. Genomic Characterization of Lung Cancer in Never-Smokers Using Deep Learning. Modern Pathology 2026, 39: 100973. PMID: 41638573, PMCID: PMC12975288, DOI: 10.1016/j.modpat.2026.100973.Peer-Reviewed Original ResearchConceptsWhole-slide imagesDeep learningCustomized deep convolutional neural networkDeep convolutional neural networkHistological whole-slide imagesConvolutional neural networkHotspot mutationsLung cancerMultilabel classificationBottleneck layerClassification headResidual blockCharacterization of lung cancerKRAS hotspot mutationsResNet50 architectureComputational complexityTumor mutational burdenInception-v3Neural networkReceiver operating characteristic curveHistologically distinctive subsetAPOBEC mutational signaturesOperating characteristics curveALK fusionsCDKN2A deletionAssociations Between Prior Lung Diseases and Risk of Lung Cancer in Populations With No Smoking History A Systematic Review and Meta-Analysis
Swami N, Hong J, Kho S, Kang H, Chun-Chia Lin L, Ni S, Florez N, Lan Q, Rothman N, Dee E, Gomez S, Cheng I. Associations Between Prior Lung Diseases and Risk of Lung Cancer in Populations With No Smoking History A Systematic Review and Meta-Analysis. Chest 2026, 169: 1717-1731. PMID: 41534708, PMCID: PMC13269668, DOI: 10.1016/j.chest.2025.12.034.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsCitationsAltmetricConceptsLung cancer riskCancer riskInternational Prospective RegisterInternational Prospective Register of Systematic ReviewsSystematic reviewRisk of lung cancerProspective Register of Systematic ReviewsProportion of lung cancersInverse variance weightingSmoking historySubgroup meta-analysesNewcastle-Ottawa ScaleAssociation of TBCase-control studyChronic bronchitisRandom-effects modelHistory of TBSocioeconomic statusVariance weightingStudy qualityStudy continentBetween-study varianceCase-controlFunnel plotCohort studyEpigenome-wide association study of household air pollution exposure in an area with high lung cancer incidence
Rahman M, Portengen L, Blechter B, Breeze C, Wong J, Hu W, Downward G, Zhang Y, Cardenas A, Ning B, Li J, Yang K, Hosgood H, Silverman D, Rothman N, Huang Y, Vermeulen R, Lan Q. Epigenome-wide association study of household air pollution exposure in an area with high lung cancer incidence. Environmental Research 2026, 292: 123690. PMID: 41500301, DOI: 10.1016/j.envres.2026.123690.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsPolycyclic aromatic hydrocarbonsHousehold air pollutionHousehold air pollution exposureLung cancer incidenceNever-smoking womenCancer incidenceHAP exposureExposure windowsAir pollution exposureEpigenome-wide association studiesEnvironmental air monitoringPAH exposureAromatic hydrocarbonsGeneralized Estimating EquationsPotential health implicationsPollution exposureCoal combustionEarly-life exposuresAir pollutionStove typeAir monitoringCooking fuel useSmoking markersEpigenome-wide DNA methylationLeukocyte DNA methylation
2025
Microbiome analysis of 940 lung cancers in never-smokers reveals lack of clinically relevant associations
McElderry J, Zhang T, Zhao W, Hoang P, Anyaso-Samuel S, Sang J, Khandekar A, Hartman C, Colón-Matos F, Miraftab M, Saha M, Lee O, Sharma S, Jones K, Zhu B, Díaz-Gay M, Mas L, Arrieta O, Edell E, Santamaría J, Schabath M, Yendamuri S, Manczuk M, Lissowska J, Świątkowska B, Mukeria A, Shangina O, Zaridze D, Holcatova I, Janout V, Mates D, Ognjanovic S, Savic M, Kontic M, Bossé Y, Gould Rothberg B, Christiani D, Gaborieau V, Brennan P, Liu G, Hofman P, Wong M, Leung K, Chen C, Hsiung C, Rothman N, Leduc C, Baine M, Travis W, Sholl L, Joubert P, Homer R, Yang S, Lan Q, Nowak M, Wedge D, Alexandrov L, Chanock S, Vogtmann E, Abnet C, Shi J, Landi M. Microbiome analysis of 940 lung cancers in never-smokers reveals lack of clinically relevant associations. Nature Communications 2025, 17: 192. PMID: 41387456, PMCID: PMC12780107, DOI: 10.1038/s41467-025-66780-y.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsCitationsAltmetricConceptsWhole-genome sequencingRNA-seqMicrobiome associationsRRNA gene sequencesMicrobial readsGene sequencesMicrobiome studiesSpecies levelTissue microbiomeGenetic ancestryMultiple data typesCommensal bacteriaMicrobiome analysisBacterial DNACancer microbiomeMicrobiomeLow biomassGenomic alterationsPaired normal lung tissuesHuman cancersSequenceLung cancerNormal lung tissuesLung tissueGenus
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