2024
Charting the metabolic biogeography of the colorectum in cancer: challenging the right sided versus left sided classification
Jain A, Morris M, Berardi D, Arora T, Domingo-Almenara X, Paty P, Rattray N, Kerekes D, Lu L, Khan S, Johnson C. Charting the metabolic biogeography of the colorectum in cancer: challenging the right sided versus left sided classification. Molecular Cancer 2024, 23: 211. PMID: 39342363, PMCID: PMC11438248, DOI: 10.1186/s12943-024-02133-5.Peer-Reviewed Original ResearchMeSH KeywordsAgedBiomarkers, TumorColorectal NeoplasmsFemaleHumansMaleMetabolomeMetabolomicsMiddle AgedRectumConceptsRectal cancerNormal mucosaMetabolite abundancePatient-matched tumorTumor-specific metabolitesMetabolic heterogeneityPatient survivalRectosigmoid colonSigmoid colonAnatomic subsitePatient-matched normal mucosaTransverse colonMetabolomic profilesAscending colonCRC biomarkersMetabolome DatabaseDescending colonMetabolite changesLeft-sidedRight-sidedColorectumRisk factorsMetabolome mapCancerTumor
2023
Urinary Paraben Concentrations and Associations with the Periconceptional Urinary Metabolome: Untargeted and Targeted Metabolomics Analyses of Participants from the Early Pregnancy Study
Vollmar A, Rattray N, Cai Y, Jain A, Yan H, Deziel N, Calafat A, Wilcox A, Jukic A, Johnson C. Urinary Paraben Concentrations and Associations with the Periconceptional Urinary Metabolome: Untargeted and Targeted Metabolomics Analyses of Participants from the Early Pregnancy Study. Environmental Health Perspectives 2023, 131: 097006. PMID: 37702489, PMCID: PMC10498870, DOI: 10.1289/ehp12125.Peer-Reviewed Original ResearchConceptsUrinary paraben concentrationsDiet-related metabolitesEarly Pregnancy StudyUrinary metabolomePregnancy StudyParaben concentrationsReproductive functionMultivariable linear regressionFemale reproductive functionDietary exposure assessmentUltrahigh-performance liquid chromatography-quadrupole timeMetabolomic analysisParaben exposureProspective cohortLiquid chromatography-quadrupole timeOrthogonal partial least squares discriminant analysisPericonceptional periodPotential confoundersUrinary concentrationsMetabolomic markersNutritional epidemiologyUnivariate statistical analysisExposure informationCritical windowUrine samplesDiscovery of decreased ferroptosis in male colorectal cancer patients with KRAS mutations
Yan H, Talty R, Jain A, Cai Y, Zheng J, Shen X, Muca E, Paty P, Bosenberg M, Khan S, Johnson C. Discovery of decreased ferroptosis in male colorectal cancer patients with KRAS mutations. Redox Biology 2023, 62: 102699. PMID: 37086630, PMCID: PMC10172914, DOI: 10.1016/j.redox.2023.102699.Peer-Reviewed Original ResearchConceptsKRAS mutant tumorsMale CRC patientsCRC patientsMale patientsKRAS mutationsMutant tumorsOverall survivalMale colorectal cancer patientsKRAS wild-type tumorsAberrant tumor metabolismColorectal cancer patientsCRC patient cohortsColorectal cancer casesFerroptosis-related genesWild-type tumorsNovel potential avenuesNormal colon tissuesPoor OSKRAS statusAdverse outcomesCRC cellsPatient cohortCancer patientsType tumorsCancer cases
2022
Hemoglobin normalization outperforms other methods for standardizing dried blood spot metabolomics: A comparative study
Jain A, Morris M, Lin EZ, Khan SA, Ma X, Deziel NC, Godri Pollitt KJ, Johnson CH. Hemoglobin normalization outperforms other methods for standardizing dried blood spot metabolomics: A comparative study. The Science Of The Total Environment 2022, 854: 158716. PMID: 36113793, DOI: 10.1016/j.scitotenv.2022.158716.Peer-Reviewed Original ResearchTidyMass an object-oriented reproducible analysis framework for LC–MS data
Shen X, Yan H, Wang C, Gao P, Johnson CH, Snyder MP. TidyMass an object-oriented reproducible analysis framework for LC–MS data. Nature Communications 2022, 13: 4365. PMID: 35902589, PMCID: PMC9334349, DOI: 10.1038/s41467-022-32155-w.Peer-Reviewed Original ResearchMeSH KeywordsChromatography, LiquidEcosystemMetabolomicsReproducibility of ResultsSoftwareTandem Mass SpectrometryWorkflowConceptsObject-oriented computational frameworkComputational frameworkExtensible toolMetabolomics data analysisData structureWorkflow needsModular architectureOwn pipelinesData processingMultiple toolsAnalysis frameworkDesign philosophyR packageFrameworkLC-MS dataData analysisToolUsersArchitectureTraceabilityPipelineProcessingPackageGrammarNon-targeted metabolomics and associations with per- and polyfluoroalkyl substances (PFAS) exposure in humans: A scoping review
Guo P, Furnary T, Vasiliou V, Yan Q, Nyhan K, Jones DP, Johnson CH, Liew Z. Non-targeted metabolomics and associations with per- and polyfluoroalkyl substances (PFAS) exposure in humans: A scoping review. Environment International 2022, 162: 107159. PMID: 35231839, PMCID: PMC8969205, DOI: 10.1016/j.envint.2022.107159.Peer-Reviewed Original ResearchConceptsPolyfluoroalkyl substances (PFAS) exposureSubstance exposurePFAS exposureNon-pregnant adultsNon-targeted metabolomicsLiquid chromatography-mass spectrometryHigh-resolution liquid chromatography-mass spectrometryFatty acid oxidationChromatography-mass spectrometryPregnant womenBiological membrane functionMetabolic pathway alterationsEpidemiological studiesTryptophan metabolismHuman studiesMetabolomic signaturePathway alterationsLipid metabolismLipid metabolitesGlycerophospholipid metabolismProspective designHuman physiological changesMetabolomic profilesAnalytical platformMetabolome changes
2021
Kynurenic acid may underlie sex-specific immune responses to COVID-19
Cai Y, Kim DJ, Takahashi T, Broadhurst DI, Yan H, Ma S, Rattray NJW, Casanovas-Massana A, Israelow B, Klein J, Lucas C, Mao T, Moore AJ, Muenker MC, Oh JE, Silva J, Wong P, team Y, Ko AI, Khan SA, Iwasaki A, Johnson CH. Kynurenic acid may underlie sex-specific immune responses to COVID-19. Science Signaling 2021, 14: eabf8483. PMID: 34230210, PMCID: PMC8432948, DOI: 10.1126/scisignal.abf8483.Peer-Reviewed Original ResearchConceptsKynurenic acidImmune responseClinical outcomesSex-specific immune responsesT cell responsesPoor clinical outcomeCOVID-19 patientsCoronavirus disease 2019COVID-19Sex-related differencesMale patientsCytokine abundanceInflammatory cytokinesKynurenine ratioSerum metabolomeDisease 2019Sex-specific linkKynurenine aminotransferaseCell responsesOld malePatientsMalesOutcomesResponseMetabolitesUse of Untargeted Metabolomics to Explore the Air Pollution-Related Disease Continuum
Jin L, Godri Pollitt KJ, Liew Z, Rosen Vollmar AK, Vasiliou V, Johnson CH, Zhang Y. Use of Untargeted Metabolomics to Explore the Air Pollution-Related Disease Continuum. Current Environmental Health Reports 2021, 8: 7-22. PMID: 33420964, DOI: 10.1007/s40572-020-00298-x.Peer-Reviewed Original ResearchConceptsAir pollutant exposureAdverse health effectsSpecific adverse health effectsOxidative stressHealth effectsPerturbation of metabolitesAir pollution exposureUntargeted metabolomicsPollutant exposureSteroid metabolic pathwaysPregnant womenInflammatory responseDisease continuumReviewThe purposeHealth outcomesLarger sample sizeMetabolic pathwaysDisease statusPollution exposureIdentified metabolitesMetabolic perturbationsMetabolic changesSummaryOur reviewAir pollution componentsMetabolomic analysis
2020
Analyzing Metabolomics Data for Environmental Health and Exposome Research
Cai Y, Rosen Vollmar AK, Johnson CH. Analyzing Metabolomics Data for Environmental Health and Exposome Research. Methods In Molecular Biology 2020, 2104: 447-467. PMID: 31953830, DOI: 10.1007/978-1-0716-0239-3_22.Peer-Reviewed Original ResearchConceptsLiquid chromatography-mass spectrometryChromatography-mass spectrometryBiological samplesExposure chemicalsExternal exposureSimultaneous analysisExposome researchHealth outcomesDisease preventionUnique advantagesBiological responsesUntargeted metabolomicsExposure risk assessmentHost susceptibilityMetabolomics technologyExposomeMetabolomic analysisRecent advancesSpectrometryExposureUntargeted metabolomics dataMetabolomicsHuman healthMetabolomics dataCumulative measure
2018
Beyond genomics: understanding exposotypes through metabolomics
Rattray NJW, Deziel NC, Wallach JD, Khan SA, Vasiliou V, Ioannidis JPA, Johnson CH. Beyond genomics: understanding exposotypes through metabolomics. Human Genomics 2018, 12: 4. PMID: 29373992, PMCID: PMC5787293, DOI: 10.1186/s40246-018-0134-x.Peer-Reviewed Original ResearchConceptsGene-environment interactionsChallenges of metabolomicsIntegration of genomicsHuman genomeMultiple genetic variantsGenetic variationGenomic technologiesAssociation studiesMetabolic traitsMetabolite productionMetabolic processesIndividual phenotypesMetabolome-wide association studyProtein synthesisHuman population levelGenetic variantsBiological impactGenomicsDisease mechanismsMetabolomic informationWealth of informationPopulation levelSmall moleculesMetabolomicsTraitsMetabolomics Reveals that Dietary Xenoestrogens Alter Cellular Metabolism Induced by Palbociclib/Letrozole Combination Cancer Therapy
Warth B, Raffeiner P, Granados A, Huan T, Fang M, Forsberg EM, Benton HP, Goetz L, Johnson CH, Siuzdak G. Metabolomics Reveals that Dietary Xenoestrogens Alter Cellular Metabolism Induced by Palbociclib/Letrozole Combination Cancer Therapy. Cell Chemical Biology 2018, 25: 291-300.e3. PMID: 29337187, PMCID: PMC5856613, DOI: 10.1016/j.chembiol.2017.12.010.Peer-Reviewed Original ResearchConceptsEffects of palbociclibPositive breast cancerUS FDA approvalGlobal metabolomics approachMCF-7 cellsCombination therapyBreast cancerEstrogen receptorMetabolic effectsPhytoestrogen genisteinFDA approvalModel xenoestrogenCellular metabolismCancer therapyFunctional assaysXenoestrogensPathway modificationTherapyMetabolomics approachCombination cancer therapyFatty acidsEstrogenic mycotoxin zearalenoneProliferation experimentsMetabolitesMetabolism
2017
Exposome-Scale Investigations Guided by Global Metabolomics, Pathway Analysis, and Cognitive Computing
Warth B, Spangler S, Fang M, Johnson CH, Forsberg EM, Granados A, Martin RL, Domingo-Almenara X, Huan T, Rinehart D, Montenegro-Burke JR, Hilmers B, Aisporna A, Hoang LT, Uritboonthai W, Benton HP, Richardson SD, Williams AJ, Siuzdak G. Exposome-Scale Investigations Guided by Global Metabolomics, Pathway Analysis, and Cognitive Computing. Analytical Chemistry 2017, 89: 11505-11513. PMID: 28945073, DOI: 10.1021/acs.analchem.7b02759.Peer-Reviewed Original ResearchConceptsUnique small moleculesChemical structureStraightforward elucidationSmall moleculesExposomics researchBiotransformation productsFood contaminantsComprehensive exposure assessmentSpecific biological effectsPotential toxicantsBiological effectsToxic effectsPathway analysisConcurrent exposureHuman healthMoleculesEnvironmental exposuresGlobal metabolomicsEnvironmental toxicantsMetabolomicsContaminantsExposure assessmentWide varietyElucidationToxicantsSystems biology guided by XCMS Online metabolomics
Huan T, Forsberg EM, Rinehart D, Johnson CH, Ivanisevic J, Benton HP, Fang M, Aisporna A, Hilmers B, Poole FL, Thorgersen MP, Adams MWW, Krantz G, Fields MW, Robbins PD, Niedernhofer LJ, Ideker T, Majumder EL, Wall JD, Rattray NJW, Goodacre R, Lairson LL, Siuzdak G. Systems biology guided by XCMS Online metabolomics. Nature Methods 2017, 14: 461-462. PMID: 28448069, PMCID: PMC5933448, DOI: 10.1038/nmeth.4260.Peer-Reviewed Original Research
2016
Metabolomics: beyond biomarkers and towards mechanisms
Johnson CH, Ivanisevic J, Siuzdak G. Metabolomics: beyond biomarkers and towards mechanisms. Nature Reviews Molecular Cell Biology 2016, 17: 451-459. PMID: 26979502, PMCID: PMC5729912, DOI: 10.1038/nrm.2016.25.Peer-Reviewed Original Research
2014
Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling
Benton HP, Ivanisevic J, Mahieu NG, Kurczy ME, Johnson CH, Franco L, Rinehart D, Valentine E, Gowda H, Ubhi BK, Tautenhahn R, Gieschen A, Fields MW, Patti GJ, Siuzdak G. Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling. Analytical Chemistry 2014, 87: 884-891. PMID: 25496351, PMCID: PMC4303330, DOI: 10.1021/ac5025649.Peer-Reviewed Original ResearchConceptsMass spectrometry data acquisitionSystems biology levelMass spectrometry analysisBioinformatics resourcesGlobal profilingTandem mass spectrometry dataProfiling datasetsMass spectrometry databaseMass spectrometry dataSpectrometry analysisProfilingData acquisitionSpectrometry dataRapid metabolite identificationMetabolomic profilingUntargeted metabolomicsBacterial samplesMetabolomicsSimultaneous data processingIdentificationMetabolite identificationMetabolomics workflowsFliesAutomatic searchAutonomous approachBioinformatics: The Next Frontier of Metabolomics
Johnson CH, Ivanisevic J, Benton HP, Siuzdak G. Bioinformatics: The Next Frontier of Metabolomics. Analytical Chemistry 2014, 87: 147-156. PMID: 25389922, PMCID: PMC4287838, DOI: 10.1021/ac5040693.Peer-Reviewed Original Research
2013
Liquid chromatography quadrupole time-of-flight mass spectrometry characterization of metabolites guided by the METLIN database
Zhu ZJ, Schultz AW, Wang J, Johnson CH, Yannone SM, Patti GJ, Siuzdak G. Liquid chromatography quadrupole time-of-flight mass spectrometry characterization of metabolites guided by the METLIN database. Nature Protocols 2013, 8: 451-460. PMID: 23391889, PMCID: PMC3666335, DOI: 10.1038/nprot.2013.004.Peer-Reviewed Original ResearchMeSH KeywordsChromatography, LiquidComputational BiologyDatabases, FactualMass SpectrometryMetabolomicsSoftwareConceptsLiquid chromatography-quadrupole timeProfiling experimentsMETLIN metabolite databaseMore populationsSeven-step protocolFlight mass spectrometry characterizationMost biological samplesFlight mass spectrometryMass spectrometry characterizationTandem MSMetabolomic featuresQuadrupole timeComprehensive platformUntargeted metabolomicsMass spectrometryMS dataMETLIN databaseLC-Q-TOFMetabolitesMetabolite databasesBiological samplesThousands of peaks
2012
Novel metabolites and roles for α-tocopherol in humans and mice discovered by mass spectrometry–based metabolomics
Johnson CH, Slanař O, Krausz KW, Kang DW, Patterson AD, Kim JH, Luecke H, Gonzalez FJ, Idle JR. Novel metabolites and roles for α-tocopherol in humans and mice discovered by mass spectrometry–based metabolomics. American Journal Of Clinical Nutrition 2012, 96: 818-830. PMID: 22952181, PMCID: PMC3441109, DOI: 10.3945/ajcn.112.042929.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAlpha-TocopherolAmino AcidsAnimalsCholesterolChromansChromatography, High Pressure LiquidFemaleGlucuronidesHumansLiverMaleMetabolomicsMiceMice, Inbred C57BLMolecular StructureSpecies SpecificitySpectrometry, Mass, Electrospray IonizationTaurineVitamin E DeficiencyYoung AdultConceptsVitamin EUrinary metabolitesMass spectrometry-based metabolomicsNovel urinary metaboliteLiver fatty acidLiver cholesterolC57BL/6 miceChronic diseasesClinical trialsΑ-tocopherolMouse modelNovel metabolitesVitamin E.Human volunteersDietary supplementsUltraperformance liquid chromatographyMiceSerum samplesInterindividual variationLiver samplesDosingSerumUrineFatty acidsMetabolites
2011
Xenobiotic Metabolomics: Major Impact on the Metabolome
Johnson CH, Patterson AD, Idle JR, Gonzalez FJ. Xenobiotic Metabolomics: Major Impact on the Metabolome. The Annual Review Of Pharmacology And Toxicology 2011, 52: 37-56. PMID: 21819238, PMCID: PMC6300990, DOI: 10.1146/annurev-pharmtox-010611-134748.Peer-Reviewed Original Research