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
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 HRPatientsBiological 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 pandemic
2020
Mouse 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 Research
2018
Is 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
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
2015
Loneliness, eudaimonia, and the human conserved transcriptional response to adversity
Cole SW, Levine ME, Arevalo JM, Ma J, Weir DR, Crimmins EM. Loneliness, eudaimonia, and the human conserved transcriptional response to adversity. Psychoneuroendocrinology 2015, 62: 11-17. PMID: 26246388, PMCID: PMC4637182, DOI: 10.1016/j.psyneuen.2015.07.001.Peer-Reviewed Original ResearchConceptsRisk factorsBehavioral health risk factorsCommunity-dwelling older adultsPeripheral blood samplesPro-inflammatory genesHealth risk factorsSocial isolationMixed effect linear model analysesChronic social adversityCTRA gene expressionStrength of associationGene expressionPsychological resilience factorsResilience factorsAdversity factorsBlood samplesIncreased expressionMeasures of lonelinessOlder adultsSocial adversityAnxiety symptomsUS HealthLinear model analysisRetirement StudyHealth risks