2021
Biological Aging Predicts Vulnerability to COVID-19 Severity in UK Biobank Participants
Kuo CL, Pilling LC, Atkins JL, Masoli JAH, Delgado J, Tignanelli C, Kuchel GA, Melzer D, Beckman KB, Levine ME. Biological Aging Predicts Vulnerability to COVID-19 Severity in UK Biobank Participants. The Journals Of Gerontology Series A 2021, 76: e133-e141. PMID: 33684206, PMCID: PMC7989601, DOI: 10.1093/gerona/glab060.Peer-Reviewed Original ResearchConceptsCOVID-19 severity outcomeCOVID-19 severityDiseases/conditionsAge-related comorbid conditionsCOVID-19-related mortalityPrevalent chronic diseasesCOVID-19 infectionBiggest risk factorCOVID-19Severity outcomesUK Biobank participantsLogistic regression modelsComorbid conditionsTest positivityRisk factorsChronic diseasesInpatient settingFurther adjustmentSymptom severityEarly pandemicBiobank participantsDisease prevalenceAgeSeverityCOVID-19 pandemicAging biomarkers and the brain
Higgins-Chen AT, Thrush KL, Levine ME. Aging biomarkers and the brain. Seminars In Cell And Developmental Biology 2021, 116: 180-193. PMID: 33509689, PMCID: PMC8292153, DOI: 10.1016/j.semcdb.2021.01.003.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements
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 overlapMethylationPhenotypicCpGDNAmAgeBindingMiceClockSchizophrenia 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 ResearchMeSH KeywordsAgingBiomarkersClozapineDNA MethylationEpigenesis, GeneticHumansMaleNeoplasmsSchizophreniaConceptsAge-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
2018
An epigenetic biomarker of aging for lifespan and healthspan
Levine ME, Lu AT, Quach A, Chen BH, Assimes TL, Bandinelli S, Hou L, Baccarelli AA, Stewart JD, Li Y, Whitsel EA, Wilson JG, Reiner AP, Aviv A, Lohman K, Liu Y, Ferrucci L, Horvath S. An epigenetic biomarker of aging for lifespan and healthspan. Aging 2018, 10: 573-591. PMID: 29676998, PMCID: PMC5940111, DOI: 10.18632/aging.101414.Peer-Reviewed Original ResearchConceptsEpigenetic biomarkersDNA damage responseTranslational machineryMitochondrial signatureTranscriptional analysisDamage responseNew epigenetic biomarkersMultiple tissuesNovel CpGsInterferon pathwayHealthspanSorted cellsImportant pathwayPathwayCellsLifespanActivationBiological ageDiverse outcomesDNAm PhenoAgeMachineryMajor goalTissueCpGGeroscience
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 ResearchMeSH KeywordsAgingBiological ClocksBiomarkersCohort StudiesFemaleHumansMaleMiddle AgedTelomere HomeostasisBiological 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 models
2015
Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer’s disease related cognitive functioning
Levine ME, Lu AT, Bennett DA, Horvath S. Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer’s disease related cognitive functioning. Aging 2015, 7: 1198-1211. PMID: 26684672, PMCID: PMC4712342, DOI: 10.18632/aging.100864.Peer-Reviewed Original ResearchConceptsCognitive functioningBrain ageCognitive declineGlobal cognitive functioningAccurate epigenetic biomarkerPre-frontal cortexEpisodic memoryAge related neurodegenerationReligious Orders StudyRush MemoryMemoryAging ProjectAlzheimer's diseaseNeuropathological measurementsNeuropathological markersFunctioningRelated neurodegenerationDorsolateral prefrontal cortex samplesOrders StudyEpigenetic age accelerationComplex trait analysisDLPFCSignificant genetic correlationsAge accelerationAmyloid loadQuantification of biological aging in young adults
Belsky DW, Caspi A, Houts R, Cohen HJ, Corcoran DL, Danese A, Harrington H, Israel S, Levine ME, Schaefer JD, Sugden K, Williams B, Yashin AI, Poulton R, Moffitt TE. Quantification of biological aging in young adults. Proceedings Of The National Academy Of Sciences Of The United States Of America 2015, 112: e4104-e4110. PMID: 26150497, PMCID: PMC4522793, DOI: 10.1073/pnas.1506264112.Peer-Reviewed Original ResearchConceptsYoung adultsYoung humansSame chronological ageSelf-reported bad healthCognitive declineOlder adultsBiological agingYoung individualsChronological ageMultiple organ systemsBrain agingLongitudinal measuresAge-related diseasesChronic diseasesAdultsFourth decadeBirth cohortOrgan systemsWorse healthIndividualsRejuvenation therapyTime pointsHuman agingMultiple biomarkersTherapyEarly-Life Intelligence Predicts Midlife Biological Age
Schaefer JD, Caspi A, Belsky DW, Harrington H, Houts R, Israel S, Levine ME, Sugden K, Williams B, Poulton R, Moffitt TE. Early-Life Intelligence Predicts Midlife Biological Age. The Journals Of Gerontology Series B 2015, 71: 968-977. PMID: 26014827, PMCID: PMC5067943, DOI: 10.1093/geronb/gbv035.Peer-Reviewed Original ResearchConceptsBiological ageEarly-life intelligencePopulation-representative birth cohortNutrition Examination SurveyRates of morbidityMost age-related diseasesAdvanced biological ageHeart ageExamination SurveyAge-related diseasesNational HealthChildhood healthBirth cohortParental socioeconomic statusStudy membersDunedin StudySocioeconomic statusMultiple causesTelomere lengthSignificant predictorsAgeEarly childhoodMortalityMidlifeChildhood
2014
Evidence of accelerated aging among African Americans and its implications for mortality
Levine ME, Crimmins EM. Evidence of accelerated aging among African Americans and its implications for mortality. Social Science & Medicine 2014, 118: 27-32. PMID: 25086423, PMCID: PMC4197001, DOI: 10.1016/j.socscimed.2014.07.022.Peer-Reviewed Original ResearchConceptsBiological ageNutrition Examination SurveyThird National HealthHigher biological ageMajor age-related diseasesChronological ageCancer mortalityExamination SurveyAge-related diseasesNational HealthEarly deathAge 60Age 30MortalityAge accountRacial disparitiesAgePremature declineWhite participantsAfrican AmericansCurrent studyMortality selectionHealthWhitesAging processNot All Smokers Die Young: A Model for Hidden Heterogeneity within the Human Population
Levine M, Crimmins E. Not All Smokers Die Young: A Model for Hidden Heterogeneity within the Human Population. PLOS ONE 2014, 9: e87403. PMID: 24520332, PMCID: PMC3919713, DOI: 10.1371/journal.pone.0087403.Peer-Reviewed Original ResearchConceptsLung function levelsProportional hazards modelMost age groupsCurrent smokersSimilar inflammationNHANES IIIMortality riskSmokersAge 50Age 80Hazards modelExtreme old ageAge groupsMeans of biomarkersOlder ageResilient phenotypeHigh exposureFunction levelUnderstanding of heterogeneityDamaging factorsLongevity extensionAging processBiological advantagesSmokingInflammation
2013
Response to Dr. Mitnitski’s and Dr. Rockwood’s Letter to the Editor: Biological Age Revisited
Levine ME. Response to Dr. Mitnitski’s and Dr. Rockwood’s Letter to the Editor: Biological Age Revisited. The Journals Of Gerontology Series A 2013, 69A: 297-298. PMID: 24115775, PMCID: PMC3976142, DOI: 10.1093/gerona/glt138.Peer-Reviewed Original Research
2012
Modeling the Rate of Senescence: Can Estimated Biological Age Predict Mortality More Accurately Than Chronological Age?
Levine ME. Modeling the Rate of Senescence: Can Estimated Biological Age Predict Mortality More Accurately Than Chronological Age? The Journals Of Gerontology Series A 2012, 68: 667-674. PMID: 23213031, PMCID: PMC3660119, DOI: 10.1093/gerona/gls233.Peer-Reviewed Original Research