Albert Higgins-Chen, MD/PhD
Assistant Professor of PsychiatryCards
Appointments
Additional Titles
NRTP, Yale Department of Psychiatry
Contact Info
Appointments
Additional Titles
NRTP, Yale Department of Psychiatry
Contact Info
Appointments
Additional Titles
NRTP, Yale Department of Psychiatry
Contact Info
About
Titles
Assistant Professor of Psychiatry
NRTP, Yale Department of PsychiatryBiography
Albert Higgins-Chen is an Assistant Professor in the Department of Psychiatry at Yale University where he is a principal investigator. During his MD/PhD training at the University of Michigan, he worked with C. elegans identifying genes regulating aging and longevity. He is a clinically trained psychiatrist and has applied aging biomarkers to investigate how mental health and treatment affect aging. He now develops new methods for measuring the biological aging process and the effects of aging interventions.
Appointments
Psychiatry
Assistant ProfessorPrimaryPathology
Assistant ProfessorSecondary
Other Departments & Organizations
Education & Training
- MD/PhD
- University of Michigan, Cellular and Molecular Biology (2017)
- AB
- Harvard University, Biochemical Sciences (2009)
Board Certifications
Psychiatry
- Certification Organization
- AB of Psychiatry & Neurology
- Original Certification Date
- 2021
Research
Overview
The Higgins-Chen lab develops and applies novel aging biomarkers to test the modifiability of aging to prevent or delay diseases such as Alzheimer’s, cardiovascular disease, and cancer. The primarily computational lab utilizes machine learning techniques to estimate the biological age of individuals from high-dimensional omics data. These aging biomarkers are then tested in human clinical trials and mouse intervention studies testing geroscience-based treatments to determine if longitudinal changes predict reductions in long-term morbidity and mortality risk. If so, these biomarkers could serve as early indicators for whether an intervention is truly modifying aging for any given individual. We recently reported that epigenetic clocks, commonly used aging biomarkers based on DNA methylation, suffer from technical noise that make their test-retest reliability inadequate for longitudinal and intervention studies, and developed a new machine learning approach to solve this problem (Higgins-Chen 2022, Nature Aging). Using this technique, we are studying the causes, consequences, and molecular mechanisms of longitudinal changes in aging biomarkers, utilizing data from humans, rodents, and in vitro experiments from collaborators. Current projects include studying how aging biomarkers interact with psychiatric disorders, Alzheimer’s, circadian rhythms, and stress. We are utilizing our findings to inform the development of the next generation of machine learning approaches and aging biomarkers.
Given that psychiatric disorders are major risk factors for age-related disease, a central focus of the lab is to study how aging biomarkers are affected by mental health. This includes current collaborations examining how our novel aging biomarkers are affected by schizophrenia, bipolar disorder, depression, Alzheimer’s, PTSD, and stress. We have found that DNA methylation-based aging biomarkers may be reduced by psychiatric medications, which is consistent with reported benefits in ameliorating age-related mortality risk in humans and model organisms. We are developing biomarkers that can specifically monitor morbidity and mortality risk related to mental health and psychiatric treatments, with the aim using these to select personalized geroscience-based treatments that will prevent or delay age-related disease for individuals with psychiatric conditions.
Members of the lab typically develop new machine learning pipelines and aging biomarkers, then apply them to investigate important questions about the aging process. They often lead collaborations with clinicians, experimental biologists, epidemiologists, social scientists, and/or industry. As aging and mental health interact with nearly all other topics in biology, lab members are encouraged to think “outside the box” and feel free to bring any of their interests or passions to the lab.
Research at a Glance
Yale Co-Authors
Publications Timeline
Morgan Levine, PhD
Adam Mecca, MD, PhD
Christopher van Dyck, MD
Yiyun Huang, PhD
Lajos Pusztai, MD, DPhil
Mariya Rozenblit, MD
Publications
2024
Reliable detection of stochastic epigenetic mutations and associations with cardiovascular aging
Markov Y, Levine M, Higgins-Chen A. Reliable detection of stochastic epigenetic mutations and associations with cardiovascular aging. GeroScience 2024, 1-21. PMID: 38736015, DOI: 10.1007/s11357-024-01191-3.Peer-Reviewed Original ResearchCitationsAltmetricConceptsStochastic epigenetic mutationsAge-related DNA methylation changesEpigenetic mutationsBlood cell type compositionDNA methylation changesCell type compositionUnmethylated probesPresence of SNPsGenomic locationsMethylation patternsMethylation changesDinucleotide sitesMethylation probesTechnical noiseBlood cell compositionTechnical replicate dataR packageAging phenotypesFramingham Heart StudyMutationsCell compositionAging biomarkersSNPsType compositionProbeValidation of biomarkers of aging
Moqri M, Herzog C, Poganik J, Ying K, Justice J, Belsky D, Higgins-Chen A, Chen B, Cohen A, Fuellen G, Hägg S, Marioni R, Widschwendter M, Fortney K, Fedichev P, Zhavoronkov A, Barzilai N, Lasky-Su J, Kiel D, Kennedy B, Cummings S, Slagboom P, Verdin E, Maier A, Sebastiano V, Snyder M, Gladyshev V, Horvath S, Ferrucci L. Validation of biomarkers of aging. Nature Medicine 2024, 30: 360-372. PMID: 38355974, PMCID: PMC11090477, DOI: 10.1038/s41591-023-02784-9.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and Concepts
2023
EVALUATING STOCHASTIC EPIGENETIC MUTATIONS: RELIABILITY, SUBTYPES, AND AN ALTERNATIVE DETECTION APPROACH
Markov Y, Higgins-Chen A. EVALUATING STOCHASTIC EPIGENETIC MUTATIONS: RELIABILITY, SUBTYPES, AND AN ALTERNATIVE DETECTION APPROACH. Innovation In Aging 2023, 7: 1029-1030. PMCID: PMC10737955, DOI: 10.1093/geroni/igad104.3309.Peer-Reviewed Original ResearchGeroscience-Centric Perspective for Geriatric Psychiatry: Integrating Aging Biology With Geriatric Mental Health Research
Diniz B, Seitz-Holland J, Sehgal R, Kasamoto J, Higgins-Chen A, Lenze E. Geroscience-Centric Perspective for Geriatric Psychiatry: Integrating Aging Biology With Geriatric Mental Health Research. American Journal Of Geriatric Psychiatry 2023, 32: 1-16. PMID: 37845116, PMCID: PMC10841054, DOI: 10.1016/j.jagp.2023.09.014.Peer-Reviewed Original ResearchCitationsAltmetricBiomarkers of aging for the identification and evaluation of longevity interventions
Moqri, Herzog C, Poganik J, Consortium B, Justice J, Belsky D, Higgins-Chen A, Moskalev A, Fuellen G, Cohen A, Bautmans I, Widschwendter M, Ding J, Fleming A, Mannick J, Han J, Zhavoronkov A, Barzilai N, Kaeberlein M, Cummings S, Kennedy B, Ferrucci L, Horvath S, Verdin E, Maier A, Snyder M, Sebastiano V, Gladyshev V. Biomarkers of aging for the identification and evaluation of longevity interventions. Cell 2023, 186: 3758-3775. PMID: 37657418, PMCID: PMC11088934, DOI: 10.1016/j.cell.2023.08.003.Peer-Reviewed Original ResearchCitationsAltmetricMore than bad luck: Cancer and aging are linked to replication-driven changes to the epigenome
Minteer C, Thrush K, Gonzalez J, Niimi P, Rozenblit M, Rozowsky J, Liu J, Frank M, McCabe T, Sehgal R, Higgins-Chen A, Hofstatter E, Pusztai L, Beckman K, Gerstein M, Levine M. More than bad luck: Cancer and aging are linked to replication-driven changes to the epigenome. Science Advances 2023, 9: eadf4163. PMID: 37467337, PMCID: PMC10355820, DOI: 10.1126/sciadv.adf4163.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsStem cell divisionImmortalized human cellsTissue-specific cancer riskTumorigenic stateCell divisionDNA methylationEpigenetic changesAge-related accumulationHuman cellsMultiple tissuesSomatic mutationsClinical tissuesTissue differencesEpigenomeCellsTissueNormal tissuesMethylationMutationsReplicationNormal breast tissueSignaturesVitroAccumulationDivisionPrincipal component analysis of synaptic density measured with [11C]UCB-J PET in early Alzheimer’s disease
O'Dell R, Higgins-Chen A, Gupta D, Chen M, Naganawa M, Toyonaga T, Lu Y, Ni G, Chupak A, Zhao W, Salardini E, Nabulsi N, Huang Y, Arnsten A, Carson R, van Dyck C, Mecca A. Principal component analysis of synaptic density measured with [11C]UCB-J PET in early Alzheimer’s disease. NeuroImage Clinical 2023, 39: 103457. PMID: 37422964, PMCID: PMC10338149, DOI: 10.1016/j.nicl.2023.103457.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsCognitive domainsCognitive performanceSubjects' scoresCortical regionsNeuropsychological batteryEarly Alzheimer's diseaseAD groupBilateral regionsNormal participantsNegative loadingsCognitive impairmentCN participantsAlzheimer's diseaseParticipantsStructural correlatesStrong contributionParticipant characteristicsScoresPositive loadingsData-driven approachTotal variancePrincipal component analysisSpecific spatial patternsCellular allostatic load is linked to increased energy expenditure and accelerated biological aging
Bobba-Alves N, Sturm G, Lin J, Ware S, Karan K, Monzel A, Bris C, Procaccio V, Lenaers G, Higgins-Chen A, Levine M, Horvath S, Santhanam B, Kaufman B, Hirano M, Epel E, Picard M. Cellular allostatic load is linked to increased energy expenditure and accelerated biological aging. Psychoneuroendocrinology 2023, 155: 106322. PMID: 37423094, PMCID: PMC10528419, DOI: 10.1016/j.psyneuen.2023.106322.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsCellular agingCellular energy expenditureDNA methylation clockMitochondrial oxidative phosphorylationStress adaptationMtDNA instabilityOXPHOS activityMethylation clockOxidative phosphorylationMetabolic shiftEnergetic costHuman fibroblast lineCellular basisPhysiological responsesFibroblast linesStress triggersPotential driversBiological agingEnergy expenditureChronic activationLifespanDamaging effectsPrimary human fibroblast linesCytokine secretionPhosphorylationFrailty Resilience Score: A Novel Measure of Frailty Resilience Associated With Protection From Frailty and Survival
Milman S, Lerman B, Ayers E, Zhang Z, Sathyan S, Levine M, Ye K, Gao T, Higgins-Chen A, Barzilai N, Verghese J. Frailty Resilience Score: A Novel Measure of Frailty Resilience Associated With Protection From Frailty and Survival. The Journals Of Gerontology Series A 2023, 78: 1771-1777. PMID: 37246648, PMCID: PMC10562888, DOI: 10.1093/gerona/glad138.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMultivariable-adjusted analysesHazard of mortalityPhenotypic frailtyBaseline frailtyOverall survivalEffective therapyHigh riskFrailtyResilience AssociatedOlder adultsGenetic riskIdentification of factorsReliable predictorMortalityResilience scoresSurvivalProteomic profilesRiskReliable measureDeviation increaseTherapyCohortThe Cutting Edge of Epigenetic Clocks: In Search of Mechanisms Linking Aging and Mental Health
Harvanek Z, Boks M, Vinkers C, Higgins-Chen A. The Cutting Edge of Epigenetic Clocks: In Search of Mechanisms Linking Aging and Mental Health. Biological Psychiatry 2023, 94: 694-705. PMID: 36764569, PMCID: PMC10409884, DOI: 10.1016/j.biopsych.2023.02.001.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsCitationsAltmetricMeSH Keywords and Concepts
Links & Media
News
- July 18, 2022
A Computational Solution for Bolstering Reliability of Epigenetic Clocks
- June 30, 2021
Residents, Fellows, Faculty Honored at 2021 Commencement Ceremony
- May 19, 2020
2020 Lustman Resident Research Awards announced
- February 10, 2020
Trainee-Led Study Seeks to Better Understand All-Cause Mortality in Schizophrenia Patients