2022
Evidence of accelerated epigenetic aging of breast tissues in patients with breast cancer is driven by CpGs associated with polycomb-related genes
Rozenblit M, Hofstatter E, Liu Z, O’Meara T, Storniolo AM, Dalela D, Singh V, Pusztai L, Levine M. Evidence of accelerated epigenetic aging of breast tissues in patients with breast cancer is driven by CpGs associated with polycomb-related genes. Clinical Epigenetics 2022, 14: 30. PMID: 35209953, PMCID: PMC8876160, DOI: 10.1186/s13148-022-01249-z.Peer-Reviewed Original ResearchConceptsNormal breast tissueBreast cancerEpigenetic age accelerationBreast tissuePeripheral bloodAge accelerationStrong risk factorBreast cancer riskTissue/blood samplesGood surrogate markerBreast cancer diagnosisHealthy controlsRisk factorsSurrogate markerCancer riskBlood samplesTumor tissueCancerCancer diagnosisNew scoreTissueUnaffected individualsBloodEpigenetic aging signaturesEpigenetic aging
2021
Association of Epigenetic Age Acceleration With Risk Factors, Survival, and Quality of Life in Patients With Head and Neck Cancer
Xiao C, Miller AH, Peng G, Levine ME, Conneely KN, Zhao H, Eldridge RC, Wommack EC, Jeon S, Higgins KA, Shin DM, Saba NF, Smith AK, Burtness B, Park HS, Irwin ML, Ferrucci LM, Ulrich B, Qian DC, Beitler JJ, Bruner DW. Association of Epigenetic Age Acceleration With Risk Factors, Survival, and Quality of Life in Patients With Head and Neck Cancer. International Journal Of Radiation Oncology • Biology • Physics 2021, 111: 157-167. PMID: 33882281, PMCID: PMC8802868, DOI: 10.1016/j.ijrobp.2021.04.002.Peer-Reviewed Original ResearchConceptsProgression-free survivalBody mass indexQuality of lifeHigher epigenetic age accelerationTreatment-related symptomsOverall survivalEpigenetic age accelerationRadiation therapyRisk factorsClinical characteristicsNeck cancerAge accelerationWorse overall survivalHuman papilloma virusFaster biological agingAdverse eventsDistant metastasisLifestyle factorsMass indexCancer outcomesBlood biomarkersPapilloma virusFunctional assessmentHigher HRPatientsAssociations of Age, Sex, Race/Ethnicity, and Education With 13 Epigenetic Clocks in a Nationally Representative U.S. Sample: The Health and Retirement Study
Crimmins EM, Thyagarajan B, Levine ME, Weir DR, Faul J. Associations of Age, Sex, Race/Ethnicity, and Education With 13 Epigenetic Clocks in a Nationally Representative U.S. Sample: The Health and Retirement Study. The Journals Of Gerontology Series A 2021, 76: 1117-1123. PMID: 33453106, PMCID: PMC8140049, DOI: 10.1093/gerona/glab016.Peer-Reviewed Original Research
2020
Reprogramming to recover youthful epigenetic information and restore vision
Lu Y, Brommer B, Tian X, Krishnan A, Meer M, Wang C, Vera DL, Zeng Q, Yu D, Bonkowski MS, Yang JH, Zhou S, Hoffmann EM, Karg MM, Schultz MB, Kane AE, Davidsohn N, Korobkina E, Chwalek K, Rajman LA, Church GM, Hochedlinger K, Gladyshev VN, Horvath S, Levine ME, Gregory-Ksander MS, Ksander BR, He Z, Sinclair DA. Reprogramming to recover youthful epigenetic information and restore vision. Nature 2020, 588: 124-129. PMID: 33268865, PMCID: PMC7752134, DOI: 10.1038/s41586-020-2975-4.Peer-Reviewed Original ResearchMeSH KeywordsAgingAnimalsAxonsCell Line, TumorCell SurvivalCellular ReprogrammingDependovirusDioxygenasesDisease Models, AnimalDNA MethylationDNA-Binding ProteinsEpigenesis, GeneticEyeFemaleGenetic VectorsGlaucomaHumansKruppel-Like Factor 4Kruppel-Like Transcription FactorsMiceMice, Inbred C57BLNerve RegenerationOctamer Transcription Factor-3Optic Nerve InjuriesProto-Oncogene ProteinsRetinal Ganglion CellsSOXB1 Transcription FactorsTranscriptomeVision, OcularConceptsDNA methylation patternsMethylation patternsTissue functionCentral nervous systemGene expression patternsCause of agingEpigenetic noiseEpigenetic informationDNA methylationEctopic expressionExpression patternsKLF4 geneMouse retinal ganglion cellsMammalian tissuesRetinal ganglion cellsAged miceGanglion cellsVision lossTissue dysfunctionMouse modelCNS tissueAxon regenerationNervous systemDegenerative processOlder individualsUnderlying features of epigenetic aging clocks in vivo and in vitro
Liu Z, Leung D, Thrush K, Zhao W, Ratliff S, Tanaka T, Schmitz LL, Smith JA, Ferrucci L, Levine ME. Underlying features of epigenetic aging clocks in vivo and in vitro. Aging Cell 2020, 19: e13229. PMID: 32930491, PMCID: PMC7576259, DOI: 10.1111/acel.13229.Peer-Reviewed Original ResearchConceptsEpigenetic clocksTranscriptional associationsTissues/cellsHuman tissues/cellsEpigenetic aging clockMultiple tissues/cellsDifferent biological processesMulti-omics analysisDNA methylation dataMulti-omics dataBiological processesMethylation dataAging clockMitochondrial dysfunctionEpigenetic agingBiological agingClockHallmarkCellsSenescenceAutophagyStriking lackPathwayCpGMetabolismMouse brain transcriptome responses to inhaled nanoparticulate matter differed by sex and APOE in Nrf2-Nfkb interactions
Haghani A, Cacciottolo M, Doty KR, D'Agostino C, Thorwald M, Safi N, Levine ME, Sioutas C, Town TC, Forman HJ, Zhang H, Morgan TE, Finch CE. Mouse brain transcriptome responses to inhaled nanoparticulate matter differed by sex and APOE in Nrf2-Nfkb interactions. ELife 2020, 9: e54822. PMID: 32579111, PMCID: PMC7314548, DOI: 10.7554/elife.54822.Peer-Reviewed Original ResearchVasomotor Symptoms and Accelerated Epigenetic Aging in the Women’s Health Initiative (WHI)
Thurston RC, Carroll JE, Levine M, Chang Y, Crandall C, Manson JE, Pal L, Hou L, Shadyab AH, Horvath S. Vasomotor Symptoms and Accelerated Epigenetic Aging in the Women’s Health Initiative (WHI). The Journal Of Clinical Endocrinology & Metabolism 2020, 105: dgaa081. PMID: 32080740, PMCID: PMC7069347, DOI: 10.1210/clinem/dgaa081.Peer-Reviewed Original ResearchConceptsVasomotor symptomsWomen's Health InitiativePostmenopausal womenHealth initiativesMenopausal vasomotor symptomsSevere hot flashesBody mass indexAdverse health indicatorsPoor health outcomesYears of ageBiological agingRace/ethnicityAccelerated Epigenetic AgingHormone therapyHot flashesMass indexMenopausal symptomsSleep disturbancesEpigenetic agingEarly deathDNAm PhenoAgeHealth outcomesTiming groupsDNAm GrimAgeSymptoms
2019
Midlife Study of the Louisville Twins: Connecting Cognitive Development to Biological and Cognitive Aging
Beam CR, Turkheimer E, Finkel D, Levine ME, Zandi E, Guterbock TM, Giangrande EJ, Ryan L, Pasquenza N, Davis DW. Midlife Study of the Louisville Twins: Connecting Cognitive Development to Biological and Cognitive Aging. Behavior Genetics 2019, 50: 73-83. PMID: 31820295, PMCID: PMC7033012, DOI: 10.1007/s10519-019-09983-6.Peer-Reviewed Original ResearchConceptsLouisville Twin StudyCognitive developmentCognitive agingCognitive functioningCognitive developmental trajectoriesLongitudinal Twin StudyTwin studiesPhysical health factorsEpisodic memoryLower biological ageFunctional ability measuresIQ measuresAbility measuresDevelopmental trajectoriesFSIQ scoresMidlife phaseMidlife studyPhysical functioningFunctional abilityChronological ageFunctioningPsychiatric outcomesSecond pilot studySecond studyIQAssociations of genetics, behaviors, and life course circumstances with a novel aging and healthspan measure: Evidence from the Health and Retirement Study
Liu Z, Chen X, Gill TM, Ma C, Crimmins EM, Levine ME. Associations of genetics, behaviors, and life course circumstances with a novel aging and healthspan measure: Evidence from the Health and Retirement Study. PLOS Medicine 2019, 16: e1002827. PMID: 31211779, PMCID: PMC6581243, DOI: 10.1371/journal.pmed.1002827.Peer-Reviewed Original ResearchConceptsCoronary artery diseaseArtery diseasePhenotypic agingUS older adultsSelf-reported circumstancesRetirement StudyLife course circumstancesAssociation of geneticMorbidity riskMultivariable associationsPotential policy targetsRetrospective natureAdulthood circumstancesPhenotypic AgeAdulthood adversityGenetic predispositionHealth behaviorsSocioenvironmental circumstancesUS populationOlder adultsPotential interventionsDisadvantaged subpopulationsGenetic riskGenetic scoreUS HealthThe role of epigenetic aging in education and racial/ethnic mortality disparities among older U.S. Women
Liu Z, Chen BH, Assimes TL, Ferrucci L, Horvath S, Levine ME. The role of epigenetic aging in education and racial/ethnic mortality disparities among older U.S. Women. Psychoneuroendocrinology 2019, 104: 18-24. PMID: 30784901, PMCID: PMC6555423, DOI: 10.1016/j.psyneuen.2019.01.028.Peer-Reviewed Original Research
2018
A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: A cohort study
Liu Z, Kuo PL, Horvath S, Crimmins E, Ferrucci L, Levine M. A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: A cohort study. PLOS Medicine 2018, 15: e1002718. PMID: 30596641, PMCID: PMC6312200, DOI: 10.1371/journal.pmed.1002718.Peer-Reviewed Original ResearchConceptsPhenotypic AgeNHANES IVCause mortalityMortality riskHealth behaviorsRepresentative US adult populationDisease-free personsOld-old adultsChronological ageRisk of deathAge 85 yearsCause-specific mortalityCause of deathProportional hazards modelUS adult populationHealth behavior characteristicsDisease countsPotential biological mechanismsEfficacy of interventionsRace/ethnicityNormal BMICohort studyDiverse subpopulationsHazards modelRisk individualsHumanin Prevents Age-Related Cognitive Decline in Mice and is Associated with Improved Cognitive Age in Humans
Yen K, Wan J, Mehta HH, Miller B, Christensen A, Levine ME, Salomon MP, Brandhorst S, Xiao J, Kim SJ, Navarrete G, Campo D, Harry GJ, Longo V, Pike CJ, Mack WJ, Hodis HN, Crimmins EM, Cohen P. Humanin Prevents Age-Related Cognitive Decline in Mice and is Associated with Improved Cognitive Age in Humans. Scientific Reports 2018, 8: 14212. PMID: 30242290, PMCID: PMC6154958, DOI: 10.1038/s41598-018-32616-7.Peer-Reviewed Original ResearchPredictors and implications of accelerated cognitive aging
Levine ME, Harrati A, Crimmins EM. Predictors and implications of accelerated cognitive aging. Biodemography And Social Biology 2018, 64: 83-101. PMID: 31007841, PMCID: PMC6469682, DOI: 10.1080/19485565.2018.1552513.Peer-Reviewed Original ResearchConceptsCognitive ageCognitive agingCognitive declineNon-demented older adultsPathological cognitive declineAge-related declineIndividual differencesCognitive slopesOlder adultsLongitudinal studyComposite measureRetirement StudyAPOE ε4Performance testsDementia transitionSubsequent dementiaDementiaMeasuresRate of declineParticipantsAgingDeclineDifferent conclusionsRace/ethnicityAbsolute levelsIs 60 the New 50? Examining Changes in Biological Age Over the Past Two Decades
Levine ME, Crimmins EM. Is 60 the New 50? Examining Changes in Biological Age Over the Past Two Decades. Demography 2018, 55: 387-402. PMID: 29511995, PMCID: PMC5897168, DOI: 10.1007/s13524-017-0644-5.Peer-Reviewed Original ResearchConceptsBiological ageModifiable health behaviorsModifiable risk factorsLife expectancySex-specific changesNHANES IVMedication useNHANES IIIRisk factorsDegree of improvementHealth behaviorsOlder groupOlder adultsPace of agingAgeSex groupsGreater declineGreater improvementChronological ageContribution of changesHealthExpectancy
2017
Eleven Telomere, Epigenetic Clock, and Biomarker-Composite Quantifications of Biological Aging: Do They Measure the Same Thing?
Belsky DW, Moffitt TE, Cohen AA, Corcoran DL, Levine ME, Prinz JA, Schaefer J, Sugden K, Williams B, Poulton R, Caspi A. Eleven Telomere, Epigenetic Clock, and Biomarker-Composite Quantifications of Biological Aging: Do They Measure the Same Thing? American Journal Of Epidemiology 2017, 187: 1220-1230. PMID: 29149257, PMCID: PMC6248475, DOI: 10.1093/aje/kwx346.Peer-Reviewed Original ResearchBiological Age, Not Chronological Age, Is Associated with Late-Life Depression
Brown PJ, Wall MM, Chen C, Levine ME, Yaffe K, Roose SP, Rutherford BR. Biological Age, Not Chronological Age, Is Associated with Late-Life Depression. The Journals Of Gerontology Series A 2017, 73: 1370-1376. PMID: 28958059, PMCID: PMC6132120, DOI: 10.1093/gerona/glx162.Peer-Reviewed Original ResearchConceptsLate-life depressionCES-D scoresDepressive symptomsBaseline CES-D scoreBiological ageChronological ageCovariate-adjusted regression modelsOlder biological ageEpidemiologic Studies Depression ScaleSignificant depressive symptomsBody Composition StudyMean chronological ageAge-associated changesNumerous physiological systemsAge-related processesKidney functioningLife depressionDepression ScaleDepression groupBrain disordersHealth AgingLongitudinal associationsSymptomsAgeRegression modelsContemporaneous Social Environment and the Architecture of Late-Life Gene Expression Profiles
Levine ME, Crimmins EM, Weir DR, Cole SW. Contemporaneous Social Environment and the Architecture of Late-Life Gene Expression Profiles. American Journal Of Epidemiology 2017, 186: 503-509. PMID: 28911009, PMCID: PMC5860329, DOI: 10.1093/aje/kwx147.Peer-Reviewed Original ResearchConceptsTranscriptional responseGene expression programsGene regulation pathwaysBioinformatics-based approachGene expression profilesTranscription factor activationGene expression levelsExpression programsLow socioeconomic statusRegulation pathwaysExpression profilesStress response systemNeuroendocrine signalingFactor activationAntiviral responseExpression levelsSocioeconomic statusPhysiological changesDistinct patternsChronic activationLong-term healthActivationGenesSignalingBiologyGenetic architecture of epigenetic and neuronal ageing rates in human brain regions
Lu AT, Hannon E, Levine ME, Crimmins EM, Lunnon K, Mill J, Geschwind DH, Horvath S. Genetic architecture of epigenetic and neuronal ageing rates in human brain regions. Nature Communications 2017, 8: 15353. PMID: 28516910, PMCID: PMC5454371, DOI: 10.1038/ncomms15353.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overAgingBrainBrain MappingCalcium-Binding ProteinsChildChild, PreschoolCognitive DysfunctionDNA MethylationEpigenesis, GeneticFemaleGenome, HumanGenome-Wide Association StudyHumansInfantMaleMiddle AgedNerve Tissue ProteinsNeurodegenerative DiseasesNeuronsQuantitative Trait LociConceptsGenome-wide association studiesCis-expression quantitative trait lociGenome-wide significant lociProportion of neuronsQuantitative trait lociEpigenetic aging ratesDNA methylation-based biomarkersEpigenetic agingMethylation-based biomarkersGenetic architectureTrait lociSignificant lociAssociation studiesBrain regionsAge-related macular degenerationType 2 diabetesAging rateGenesLociHuman brain regionsUlcerative colitisWaist circumferenceMacular degenerationParkinson's diseaseBrain samplesEpigenetic clock analysis of diet, exercise, education, and lifestyle factors
Quach A, Levine ME, Tanaka T, Lu AT, Chen BH, Ferrucci L, Ritz B, Bandinelli S, Neuhouser ML, Beasley JM, Snetselaar L, Wallace RB, Tsao PS, Absher D, Assimes TL, Stewart JD, Li Y, Hou L, Baccarelli AA, Whitsel EA, Horvath S. Epigenetic clock analysis of diet, exercise, education, and lifestyle factors. Aging 2017, 9: 419-437. PMID: 28198702, PMCID: PMC5361673, DOI: 10.18632/aging.101168.Peer-Reviewed Original ResearchConceptsIntrinsic epigenetic age accelerationExtrinsic epigenetic age accelerationModerate alcohol consumptionMetabolic syndromeLifestyle factorsAlcohol consumptionEpigenetic age accelerationHealth initiativesItalian cohort studyPostmenopausal female participantsFirst-line medicationWomen's Health InitiativeBlood carotenoid levelsType 2 diabetesAge accelerationAge-related functional declineHealth-related outcomesEpigenetic clock analysisFemale participantsIndicator of fruitCause mortalityCohort studyPoultry intakeChronic conditionsFish intake
2016
DNA methylation-based measures of biological age: meta-analysis predicting time to death
Chen BH, Marioni RE, Colicino E, Peters MJ, Ward-Caviness CK, Tsai PC, Roetker NS, Just AC, Demerath EW, Guan W, Bressler J, Fornage M, Studenski S, Vandiver AR, Moore AZ, Tanaka T, Kiel DP, Liang L, Vokonas P, Schwartz J, Lunetta KL, Murabito JM, Bandinelli S, Hernandez DG, Melzer D, Nalls M, Pilling LC, Price TR, Singleton AB, Gieger C, Holle R, Kretschmer A, Kronenberg F, Kunze S, Linseisen J, Meisinger C, Rathmann W, Waldenberger M, Visscher PM, Shah S, Wray NR, McRae AF, Franco OH, Hofman A, Uitterlinden AG, Absher D, Assimes T, Levine ME, Lu AT, Tsao PS, Hou L, Manson JE, Carty CL, LaCroix AZ, Reiner AP, Spector TD, Feinberg AP, Levy D, Baccarelli A, van Meurs J, Bell JT, Peters A, Deary IJ, Pankow JS, Ferrucci L, Horvath S. DNA methylation-based measures of biological age: meta-analysis predicting time to death. Aging 2016, 8: 1844-1859. PMID: 27690265, PMCID: PMC5076441, DOI: 10.18632/aging.101020.Peer-Reviewed Original ResearchConceptsCause mortalityBlood cell compositionRisk factorsTraditional risk factorsBlood cell countAdditional risk factorsChronological ageEpigenetic ageCell compositionBiological ageEpigenetic age accelerationStudy ACell countEthnic groupsSignificant associationHuman cohortsRobust biomarkersMortalityTotal sample sizeMethylation-based measuresDNA methylation-based measuresEpigenetic age estimatesAgeAge accelerationDifferent cohorts