2021
Epigenetic age acceleration, fatigue, and inflammation in patients undergoing radiation therapy for head and neck cancer: A longitudinal study
Xiao C, Beitler JJ, Peng G, Levine ME, Conneely KN, Zhao H, Felger JC, Wommack EC, Chico CE, Jeon S, Higgins KA, Shin DM, Saba NF, Burtness BA, Bruner DW, Miller AH. Epigenetic age acceleration, fatigue, and inflammation in patients undergoing radiation therapy for head and neck cancer: A longitudinal study. Cancer 2021, 127: 3361-3371. PMID: 34027995, DOI: 10.1002/cncr.33641.Peer-Reviewed Original ResearchConceptsC-reactive proteinIL-6 levelsEpigenetic age accelerationNeck cancerInterleukin-6Inflammatory markersHigher epigenetic age accelerationLower C-reactive proteinAge accelerationHigher C-reactive proteinMultidimensional Fatigue Inventory-20Poor functional outcomeBlood DNA methylationMonths postradiotherapyAdvanced diseaseConcurrent chemoradiationMost patientsDistant metastasisFunctional outcomeSevere fatigueTreatment completionRadiation therapyPatientsGreater fatigueInflammationA systematic review of biological, social and environmental factors associated with epigenetic clock acceleration
Oblak L, van der Zaag J, Higgins-Chen AT, Levine ME, Boks MP. A systematic review of biological, social and environmental factors associated with epigenetic clock acceleration. Ageing Research Reviews 2021, 69: 101348. PMID: 33930583, DOI: 10.1016/j.arr.2021.101348.Peer-Reviewed Original ResearchAssociation 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
A rat epigenetic clock recapitulates phenotypic aging and co-localizes with heterochromatin
Levine M, McDevitt RA, Meer M, Perdue K, Di Francesco A, Meade T, Farrell C, Thrush K, Wang M, Dunn C, Pellegrini M, de Cabo R, Ferrucci L. A rat epigenetic clock recapitulates phenotypic aging and co-localizes with heterochromatin. ELife 2020, 9: e59201. PMID: 33179594, PMCID: PMC7661040, DOI: 10.7554/elife.59201.Peer-Reviewed Original ResearchConceptsTranscriptional factor bindingNovel epigenetic clockEpigenetic signalsIntergenic regionEpigenetic age measuresDNA methylationFactor bindingSequencing dataEpigenetic clocksBiochemical advantagesNetwork analysisH3K9me3H3K27me3HeterochromatinCaloric restrictionRobust biomarkersSubstantial overlapMethylationPhenotypicCpGDNAmAgeBindingMiceClockUnderlying 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 ResearchSchizophrenia and Epigenetic Aging Biomarkers: Increased Mortality, Reduced Cancer Risk, and Unique Clozapine Effects
Higgins-Chen AT, Boks MP, Vinkers CH, Kahn RS, Levine ME. Schizophrenia and Epigenetic Aging Biomarkers: Increased Mortality, Reduced Cancer Risk, and Unique Clozapine Effects. Biological Psychiatry 2020, 88: 224-235. PMID: 32199607, PMCID: PMC7368835, DOI: 10.1016/j.biopsych.2020.01.025.Peer-Reviewed Original ResearchConceptsAge-associated proteinsEpigenetic clocksDNA methylation data setsMethylation data setsEpigenetic ageing biomarkersReduced cancer riskCD8 T cellsBody mass indexLong-term outcomesHorvath's epigenetic clockLower cancer ratesDNA methylationDNA methylation predictorsBiological age differencesMitotic clockMitotic divisionAge clocksCause mortalityNatural killerMass indexEarly mortalityMedication dataSZ casesClozapine's effectIncreased Mortality
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 Health
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 samples
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 cohortsAn epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease
Horvath S, Gurven M, Levine ME, Trumble BC, Kaplan H, Allayee H, Ritz BR, Chen B, Lu AT, Rickabaugh TM, Jamieson BD, Sun D, Li S, Chen W, Quintana-Murci L, Fagny M, Kobor MS, Tsao PS, Reiner AP, Edlefsen KL, Absher D, Assimes TL. An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome Biology 2016, 17: 171. PMID: 27511193, PMCID: PMC4980791, DOI: 10.1186/s13059-016-1030-0.Peer-Reviewed Original ResearchConceptsMortality rateRace/ethnicityRisk factorsTraditional cardio-metabolic risk factorsCardio-metabolic risk factorsCHD risk factorsCoronary heart diseaseCardio-metabolic diseasesEpigenetic clock analysisIntrinsic epigenetic age accelerationAfrican AmericansEpigenetic aging ratesLonger life expectancyCHD outcomesOlder African AmericansHeart diseaseHigh burdenEpigenetic age accelerationLower mortalityDifferent mortality ratesBrain samplesEthnic groupsBrain tissueBloodSocioeconomic differences