2024
Fasting-mimicking diet causes hepatic and blood markers changes indicating reduced biological age and disease risk
Brandhorst S, Levine M, Wei M, Shelehchi M, Morgan T, Nayak K, Dorff T, Hong K, Crimmins E, Cohen P, Longo V. Fasting-mimicking diet causes hepatic and blood markers changes indicating reduced biological age and disease risk. Nature Communications 2024, 15: 1309. PMID: 38378685, PMCID: PMC10879164, DOI: 10.1038/s41467-024-45260-9.Peer-Reviewed Original ResearchConceptsMultiple cardiometabolic risk factorsAssociated with reduced insulin resistanceCardiometabolic risk factorsFasting-mimicking dietImmune system agingRandomized clinical trialsAnalysis of blood samplesAutoimmune cellsBiological ageClinical trialsReduce inflammationMarker changesRisk factorsHepatic fatInsulin resistanceAdult study participantsBlood samplesNormal cellsWeight lossReducing biological ageBiomarker of biological agingDamaged cellsStudy participantsDisease riskAge
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 goalTissueCpGGeroscienceIs 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
Biological 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
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
2015
Early-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
A comparison of methods for assessing mortality risk
Levine ME, Crimmins EM. A comparison of methods for assessing mortality risk. American Journal Of Human Biology 2014, 26: 768-776. PMID: 25088793, PMCID: PMC4286244, DOI: 10.1002/ajhb.22595.Peer-Reviewed Original ResearchConceptsFramingham risk scoreDisease-specific mortalityRisk scoreAllostatic loadBiological ageNutrition Examination Survey IIICox proportional hazards modelStratified age groupsStrong associationExamination Survey IIIProportional hazards modelParticipants ages 50CVD mortalityPerson yearsCancer mortalityNational HealthStudy populationMortality riskAge 50Hazards modelAge 30Age groupsMortalityAge rangeSurvey IIIEvidence 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 process
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