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Melendez J, Sung YJ, Orr M, Yoo A, Schindler S, Cruchaga C, Bateman R. An interpretable machine learning-based cerebrospinal fluid proteomics clock for predicting age reveals novel insights into brain aging. Aging Cell 2024:e14230. [PMID: 38923730 DOI: 10.1111/acel.14230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 05/10/2024] [Accepted: 05/15/2024] [Indexed: 06/28/2024] Open
Abstract
Machine learning can be used to create "biologic clocks" that predict age. However, organs, tissues, and biofluids may age at different rates from the organism as a whole. We sought to understand how cerebrospinal fluid (CSF) changes with age to inform the development of brain aging-related disease mechanisms and identify potential anti-aging therapeutic targets. Several epigenetic clocks exist based on plasma and neuronal tissues; however, plasma may not reflect brain aging specifically and tissue-based clocks require samples that are difficult to obtain from living participants. To address these problems, we developed a machine learning clock that uses CSF proteomics to predict the chronological age of individuals with a 0.79 Pearson correlation and mean estimated error (MAE) of 4.30 years in our validation cohort. Additionally, we analyzed proteins highly weighted by the algorithm to gain insights into changes in CSF and uncover novel insights into brain aging. We also demonstrate a novel method to create a minimal protein clock that uses just 109 protein features from the original clock to achieve a similar accuracy (0.75 correlation, MAE 5.41). Finally, we demonstrate that our clock identifies novel proteins that are highly predictive of age in interactions with other proteins, but do not directly correlate with chronological age themselves. In conclusion, we propose that our CSF protein aging clock can identify novel proteins that influence the rate of aging of the central nervous system (CNS), in a manner that would not be identifiable by examining their individual relationships with age.
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Affiliation(s)
- Justin Melendez
- Tracy Family SILQ Center, Washington University in St. Louis, St. Louis, Missouri, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri, USA
- Department of Biostatistics, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Miranda Orr
- Department of Internal Medicine, Wake Forest School of Medicine Section of Gerontology and Geriatric Medicine Medical Center Boulevard, Winston-Salem, North Carolina, USA
| | - Andrew Yoo
- Department of Developmental Biology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Suzanne Schindler
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Carlos Cruchaga
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
- Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Randall Bateman
- Tracy Family SILQ Center, Washington University in St. Louis, St. Louis, Missouri, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
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2
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Phyo AZZ, Fransquet PD, Wrigglesworth J, Woods RL, Espinoza SE, Ryan J. Sex differences in biological aging and the association with clinical measures in older adults. GeroScience 2024; 46:1775-1788. [PMID: 37747619 PMCID: PMC10828143 DOI: 10.1007/s11357-023-00941-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 09/11/2023] [Indexed: 09/26/2023] Open
Abstract
Females live longer than males, and there are sex disparities in physical health and disease incidence. However, sex differences in biological aging have not been consistently reported and may differ depending on the measure used. This study aimed to determine the correlations between epigenetic age acceleration (AA), and other markers of biological aging, separately in males and females. We additionally explored the extent to which these AA measures differed according to socioeconomic characteristics, clinical markers, and diseases. Epigenetic clocks (HorvathAge, HannumAge, PhenoAge, GrimAge, GrimAge2, and DunedinPACE) were estimated in blood from 560 relatively healthy Australians aged ≥ 70 years (females, 50.7%) enrolled in the ASPREE study. A system-wide deficit accumulation frailty index (FI) composed of 67 health-related measures was generated. Brain age and subsequently brain-predicted age difference (brain-PAD) were estimated from neuroimaging. Females had significantly reduced AA than males, but higher FI, and there was no difference in brain-PAD. FI had the strongest correlation with DunedinPACE (range r: 0.21 to 0.24 in both sexes). Brain-PAD was not correlated with any biological aging measures. Significant correlations between AA and sociodemographic characteristics and health markers were more commonly found in females (e.g., for DunedinPACE and systolic blood pressure r = 0.2, p < 0.001) than in males. GrimAA and Grim2AA were significantly associated with obesity and depression in females, while in males, hypertension, diabetes, and chronic kidney disease were associated with these clocks, as well as DunedinPACE. Our findings highlight the importance of considering sex differences when investigating the link between biological age and clinical measures.
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Affiliation(s)
- Aung Zaw Zaw Phyo
- Biological Neuropsychiatry & Dementia Unit, School of Public Health and Preventive Medicine, Monash University, 553, St. Kilda Road, Melbourne, VIC, 3004, Australia.
| | - Peter D Fransquet
- Biological Neuropsychiatry & Dementia Unit, School of Public Health and Preventive Medicine, Monash University, 553, St. Kilda Road, Melbourne, VIC, 3004, Australia
- School of Psychology, Deakin University, Burwood, Melbourne, VIC, 3125, Australia
| | - Jo Wrigglesworth
- Biological Neuropsychiatry & Dementia Unit, School of Public Health and Preventive Medicine, Monash University, 553, St. Kilda Road, Melbourne, VIC, 3004, Australia
| | - Robyn L Woods
- ASPREE Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Sara E Espinoza
- Center for Translational Geroscience, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Joanne Ryan
- Biological Neuropsychiatry & Dementia Unit, School of Public Health and Preventive Medicine, Monash University, 553, St. Kilda Road, Melbourne, VIC, 3004, Australia
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3
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McMurran CE, Wang Y, Mak JKL, Karlsson IK, Tang B, Ploner A, Pedersen NL, Hägg S. Advanced biological ageing predicts future risk for neurological diagnoses and clinical examination findings. Brain 2023; 146:4891-4902. [PMID: 37490842 PMCID: PMC10690013 DOI: 10.1093/brain/awad252] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 06/15/2023] [Accepted: 07/04/2023] [Indexed: 07/27/2023] Open
Abstract
Age is a dominant risk factor for some of the most common neurological diseases. Biological ageing encompasses interindividual variation in the rate of ageing and can be calculated from clinical biomarkers or DNA methylation data amongst other approaches. Here, we tested the hypothesis that a biological age greater than one's chronological age affects the risk of future neurological diagnosis and the development of abnormal signs on clinical examination. We analysed data from the Swedish Adoption/Twin Study of Aging (SATSA): a cohort with 3175 assessments of 802 individuals followed-up over several decades. Six measures of biological ageing were generated: two physiological ages (created from bedside clinical measurements and standard blood tests) and four blood methylation age measures. Their effects on future stroke, dementia or Parkinson's disease diagnosis, or development of abnormal clinical signs, were determined using survival analysis, with and without stratification by twin pairs. Older physiological ages were associated with ischaemic stroke risk; for example one standard deviation advancement in baseline PhenoAgePhys or KDMAgePhys residual increased future ischaemic stroke risk by 29.2% [hazard ratio (HR): 1.29, 95% confidence interval (CI) 1.06-1.58, P = 0.012] and 42.9% (HR 1.43, CI 1.18-1.73, P = 3.1 × 10-4), respectively. In contrast, older methylation ages were more predictive of future dementia risk, which was increased by 29.7% (HR 1.30, CI 1.07-1.57, P = 0.007) per standard deviation advancement in HorvathAgeMeth. Older physiological ages were also positively associated with future development of abnormal patellar or pupillary reflexes, and the loss of normal gait. Measures of biological ageing can predict clinically relevant pathology of the nervous system independent of chronological age. This may help to explain variability in disease risk between individuals of the same age and strengthens the case for trials of geroprotective interventions for people with neurological disorders.
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Affiliation(s)
- Christopher E McMurran
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm SE 171 77, Sweden
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm SE 171 77, Sweden
| | - Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm SE 171 77, Sweden
| | - Ida K Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm SE 171 77, Sweden
| | - Bowen Tang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm SE 171 77, Sweden
| | - Alexander Ploner
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm SE 171 77, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm SE 171 77, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm SE 171 77, Sweden
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4
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Harvanek ZM, Boks MP, Vinkers CH, Higgins-Chen AT. The Cutting Edge of Epigenetic Clocks: In Search of Mechanisms Linking Aging and Mental Health. Biol Psychiatry 2023; 94:694-705. [PMID: 36764569 PMCID: PMC10409884 DOI: 10.1016/j.biopsych.2023.02.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 01/31/2023] [Accepted: 02/01/2023] [Indexed: 02/11/2023]
Abstract
Individuals with psychiatric disorders are at increased risk of age-related diseases and early mortality. Recent studies demonstrate that this link between mental health and aging is reflected in epigenetic clocks, aging biomarkers based on DNA methylation. The reported relationships between epigenetic clocks and mental health are mostly correlational, and the mechanisms are poorly understood. Here, we review recent progress concerning the molecular and cellular processes underlying epigenetic clocks as well as novel technologies enabling further studies of the causes and consequences of epigenetic aging. We then review the current literature on how epigenetic clocks relate to specific aspects of mental health, such as stress, medications, substance use, health behaviors, and symptom clusters. We propose an integrated framework where mental health and epigenetic aging are each broken down into multiple distinct processes, which are then linked to each other, using stress and schizophrenia as examples. This framework incorporates the heterogeneity and complexity of both mental health conditions and aging, may help reconcile conflicting results, and provides a basis for further hypothesis-driven research in humans and model systems to investigate potentially causal mechanisms linking aging and mental health.
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Affiliation(s)
- Zachary M Harvanek
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Marco P Boks
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University of Utrecht, Utrecht, the Netherlands
| | - Christiaan H Vinkers
- Department of Psychiatry, Amsterdam University Medical Center, location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Mood, Anxiety, Psychosis, Sleep & Stress program, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Albert T Higgins-Chen
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Department of Pathology, Yale University School of Medicine, New Haven, Connecticut.
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5
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Liu L, Qi X, Cheng S, Meng P, Yang X, Pan C, Zhang N, Chen Y, Li C, Zhang H, Zhang Z, Zhang J, Cheng B, Wen Y, Jia Y, Liu H, Zhang F. Epigenetic analysis suggests aberrant cerebellum brain aging in old-aged adults with autism spectrum disorder and schizophrenia. Mol Psychiatry 2023; 28:4867-4876. [PMID: 37612365 DOI: 10.1038/s41380-023-02233-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 08/11/2023] [Accepted: 08/15/2023] [Indexed: 08/25/2023]
Abstract
The aberrant aging hypothesis of schizophrenia (SCZ) and autism spectrum disorder (ASD) has been proposed, and the DNA methylation (DNAm) clock, which is a cumulative evaluation of DNAm levels at age-related CpGs, could serve as a biological aging indicator. This study evaluated epigenetic brain aging of ASD and SCZ using Horvath's epigenetic clock, based on two public genome-wide DNA methylation datasets of post-mortem brain samples (NASD = 222; NSCZ = 142). Total subjects were further divided into subgroups by gender and age. The epigenetic age acceleration (AgeAccel) for each sample was calculated as the residual value resulting from the regression model and compared between groups. Results showed DNAm age has a strong correlation with chronological age in both datasets across multiple brain regions (P < 0.05). When divided into equally sized age groups, the AgeAccel of the cerebellum (CB) region from people over 45 years of age was greater compared to the control sample (AgeAccel of ASD vs control: 5.069 vs -6.249; P < 0.001). And a decelerated epigenetic aging process was observed in the CB region of individuals with SCZ aged 50-70 years (AgeAccel of SCZ vs control: -3.171 vs 2.418; P < 0.05). However, our results showed no significant difference in AgeAccel between ASD and control groups, and between SCZ and control groups in the total and gender-specific groups (P > 0.05). This study's results revealed some evidence for aberrant epigenetic CB brain aging in old-aged patients with ASD and SCZ, indicating a different pattern of CB aging in older adults with these two diseases. However, further studies of larger ASD and SCZ cohorts are necessary to make definitive conclusions on this observation.
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Affiliation(s)
- Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Xin Qi
- Precision Medicine Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P. R. China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Chuyu Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Na Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Yujing Chen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Chune Li
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Huijie Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Zhen Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Jingxi Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Huan Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, P. R. China.
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P. R. China.
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6
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Sathyan S, Ayers E, Adhikari D, Gao T, Milman S, Barzilai N, Verghese J. Biological Age Acceleration and Motoric Cognitive Risk Syndrome. Ann Neurol 2023; 93:1187-1197. [PMID: 36843279 PMCID: PMC10865507 DOI: 10.1002/ana.26624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 01/21/2023] [Accepted: 02/13/2023] [Indexed: 02/28/2023]
Abstract
OBJECTIVE Motoric cognitive risk (MCR) syndrome, a predementia syndrome characterized by slow gait and subjective cognitive concerns, is associated with multiple age-related risk factors. We hypothesized that MCR is associated with biological age acceleration. We examined the associations of biological age acceleration with MCR, and mortality risk in MCR cases. METHODS Biological age was determined using proteomic and epigenetic clocks in participants aged 65 years and older in the LonGenity study (N = 700, females = 57.9%) and Health and Retirement Study (HRS; N = 1,043, females = 57.1%) cohorts. Age acceleration (AgeAccel) was operationally defined as the residual from regressing predicted biological age (from both clocks separately) on chronological age. Association of AgeAccel with incident MCR in the overall sample as well as with mortality risk in MCR cases was examined using Cox models and reported as hazard ratios (HRs). RESULTS AgeAccel scores derived from a proteomic clock were associated with prevalent MCR (odds ratio adjusted for age, gender, education years, and chronic illnesses [aOR] = 1.36, 95% confidence interval [CI] = 1.09-1.71) as well as predicted incident MCR (HR = 1.19, 95% CI = 1.00-1.41) in the LonGenity cohort. In HRS, the association of AgeAccel using an epigenetic clock with prevalent MCR was confirmed (aOR = 1.47, 95% CI = 1.16-1.85). Participants with MCR and accelerated aging (positive AgeAccel score) were at the highest risk for mortality in both LonGenity (HR = 3.38, 95% CI = 2.01-5.69) and HRS (HR = 2.47, 95% CI = 1.20-5.10). INTERPRETATION Accelerated aging predicts risk for MCR, and is associated with higher mortality in MCR patients. ANN NEUROL 2023;93:1187-1197.
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Affiliation(s)
- Sanish Sathyan
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Emmeline Ayers
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Dristi Adhikari
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Tina Gao
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
- Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Sofiya Milman
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
- Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Nir Barzilai
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
- Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Joe Verghese
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
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7
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Schäfer Hackenhaar F, Josefsson M, Nordin Adolfsson A, Landfors M, Kauppi K, Porter T, Milicic L, Laws SM, Hultdin M, Adolfsson R, Degerman S, Pudas S. Sixteen-Year Longitudinal Evaluation of Blood-Based DNA Methylation Biomarkers for Early Prediction of Alzheimer's Disease. J Alzheimers Dis 2023; 94:1443-1464. [PMID: 37393498 PMCID: PMC10473121 DOI: 10.3233/jad-230039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/30/2023] [Indexed: 07/03/2023]
Abstract
BACKGROUND DNA methylation (DNAm), an epigenetic mark reflecting both inherited and environmental influences, has shown promise for Alzheimer's disease (AD) prediction. OBJECTIVE Testing long-term predictive ability (>15 years) of existing DNAm-based epigenetic age acceleration (EAA) measures and identifying novel early blood-based DNAm AD-prediction biomarkers. METHODS EAA measures calculated from Illumina EPIC data from blood were tested with linear mixed-effects models (LMMs) in a longitudinal case-control sample (50 late-onset AD cases; 51 matched controls) with prospective data up to 16 years before clinical onset, and post-onset follow-up. Novel DNAm biomarkers were generated with epigenome-wide LMMs, and Sparse Partial Least Squares Discriminant Analysis applied at pre- (10-16 years), and post-AD-onset time-points. RESULTS EAA did not differentiate cases from controls during the follow-up time (p > 0.05). Three new DNA biomarkers showed in-sample predictive ability on average 8 years pre-onset, after adjustment for age, sex, and white blood cell proportions (p-values: 0.022-<0.00001). Our longitudinally-derived panel replicated nominally (p = 0.012) in an external cohort (n = 146 cases, 324 controls). However, its effect size and discriminatory accuracy were limited compared to APOEɛ4-carriership (OR = 1.38 per 1 SD DNAm score increase versus OR = 13.58 for ɛ4-allele carriage; AUCs = 77.2% versus 87.0%). Literature review showed low overlap (n = 4) across 3275 AD-associated CpGs from 8 published studies, and no overlap with our identified CpGs.
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Affiliation(s)
- Fernanda Schäfer Hackenhaar
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Maria Josefsson
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
- Department of Statistics, USBE, Umeå University, Umeå, Sweden
- Center for Ageing and Demographic Research, Umeå University, Umeå, Sweden
| | | | - Mattias Landfors
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | - Karolina Kauppi
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Tenielle Porter
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Curtin Medical School, Curtin University, Bentley, WA, Australia
| | - Lidija Milicic
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Simon M. Laws
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Curtin Medical School, Curtin University, Bentley, WA, Australia
| | - Magnus Hultdin
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | - Rolf Adolfsson
- Department of Clinical Sciences, Umeå University, Umeå, Sweden
| | - Sofie Degerman
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
- Department of Clinical Microbiology, Umeå University, Umeå, Sweden
| | - Sara Pudas
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
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8
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Vyas CM, Sadreyev RI, Gatchel JR, Kang JH, Reynolds CF, Mischoulon D, Chang G, Hazra A, Manson JE, Blacker D, Vivo ID, Okereke OI. Pilot Study of Second-Generation DNA Methylation Epigenetic Markers in Relation to Cognitive and Neuropsychiatric Symptoms in Older Adults. J Alzheimers Dis 2023; 93:1563-1575. [PMID: 37212116 PMCID: PMC10336852 DOI: 10.3233/jad-230093] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
BACKGROUND Associations between epigenetic aging with cognitive aging and neuropsychiatric measures are not well-understood. OBJECTIVE 1) To assess cross-sectional correlations between second-generation DNA methylation (DNAm)-based clocks of healthspan and lifespan (i.e., GrimAge, PhenoAge, and DNAm-based estimator of telomere length [DNAmTL]) and cognitive and neuropsychiatric measures; 2) To examine longitudinal associations between change in DNAm markers and change in cognition over 2 years. METHODS Participants were members of VITAL-DEP (VITamin D and OmegA-3 TriaL- Depression Endpoint Prevention) study. From previously ascertained cognitive groups (i.e., cognitively normal and mild cognitive impairment), we randomly selected 45 participants, aged≥60 years, who completed in-person neuropsychiatric assessments at baseline and 2 years. The primary outcome was global cognitive score (averaging z-scores of 9 tests). Neuropsychiatric Inventory severity scores were mapped from neuropsychiatric symptoms (NPS) from psychological scales and structured diagnostic interviews. DNAm was assayed using Illumina MethylationEPIC 850K BeadChip at baseline and 2 years. We calculated baseline partial Spearman correlations between DNAm markers and cognitive and NPS measures. We constructed multivariable linear regression models to examine longitudinal relations between DNAm markers and cognition. RESULTS At baseline, we observed a suggestive negative correlation between GrimAge clock markers and global cognition but no signal between DNAm markers and NPS measures. Over 2 years: each 1-year increase in DNAmGrimAge was significantly associated with faster declines in global cognition; each 100-base pair increase in DNAmTL was significantly associated with better global cognition. CONCLUSION We found preliminary evidence of cross-sectional and longitudinal associations between DNAm markers and global cognition.
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Affiliation(s)
- Chirag M. Vyas
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ruslan I. Sadreyev
- Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jennifer R. Gatchel
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Geriatric Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Jae H. Kang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Charles F. Reynolds
- Department of Psychiatry, UPMC and University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - David Mischoulon
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Grace Chang
- Department of Psychiatry, VA Boston Healthcare System and Harvard Medical School, Boston, MA, USA
| | - Aditi Hazra
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - JoAnn E. Manson
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Deborah Blacker
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Immaculata De Vivo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Olivia I. Okereke
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
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O’Shea DM, Galvin JE. Female APOE ɛ4 Carriers with Slow Rates of Biological Aging Have Better Memory Performances Compared to Female ɛ4 Carriers with Accelerated Aging. J Alzheimers Dis 2023; 92:1269-1282. [PMID: 36872781 PMCID: PMC10535361 DOI: 10.3233/jad-221145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
BACKGROUND Evidence suggests that APOE ɛ4 carriers have worse memory performances compared to APOE ɛ4 non-carriers and effects may vary by sex and age. Estimates of biological age, using DNA methylation may enhance understanding of the associations between sex and APOE ɛ4 on cognition. OBJECTIVE To investigate whether associations between APOE ɛ4 status and memory vary according to rates of biological aging, using a DNA methylation age biomarker, in older men and women without dementia. METHODS Data were obtained from 1,771 adults enrolled in the 2016 wave of the Health and Retirement Study. A series of ANCOVAs were used to test the interaction effects of APOE ɛ4 status and aging rates (defined as 1 standard deviation below (i.e., slow rate), or above (i.e., fast rate) their sex-specific mean rate of aging on a composite measure of verbal learning and memory. RESULTS APOE ɛ4 female carriers with slow rates of GrimAge had significantly better memory performances compared to fast and average aging APOE ɛ4 female carriers. There was no effect of aging group rate on memory in the female non-carriers and no significant differences in memory according to age rate in either male APOE ɛ4 carriers or non-carriers. CONCLUSION Slower rates of aging in female APOE ɛ4 carriers may buffer against the negative effects of the ɛ4 allele on memory. However, longitudinal studies with larger sample sizes are needed to evaluate risk of dementia/memory impairment based on rates of aging in female APOE ɛ4 carriers.
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Affiliation(s)
- Deirdre M. O’Shea
- Department of Neurology, Comprehensive Center for Brain Health, University of Miami Miller School of Medicine, Boca Raton, FL, USA
| | - James E. Galvin
- Department of Neurology, Comprehensive Center for Brain Health, University of Miami Miller School of Medicine, Boca Raton, FL, USA
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Coppedè F. DNA methylation as a powerful tool to investigate the biology and pathology of aging. Epigenomics 2022; 14:1541-1544. [PMID: 36803012 DOI: 10.2217/epi-2023-0011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023] Open
Affiliation(s)
- Fabio Coppedè
- Department of Translational Research & of New Surgical & Medical Technologies, Laboratory of Medical Genetics, University of Pisa, Via Roma 55, Pisa, 56126, Italy
- Interdepartmental Research Center of Biology & Pathology of Aging, University of Pisa, Pisa, 56126, Italy
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11
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Liang WS, Goetz LH, Schork NJ. Assessing brain and biological aging trajectories associated with Alzheimer’s disease. Front Neurosci 2022; 16:1036102. [PMID: 36389222 PMCID: PMC9650396 DOI: 10.3389/fnins.2022.1036102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 10/07/2022] [Indexed: 11/24/2022] Open
Abstract
The development of effective treatments to prevent and slow Alzheimer’s disease (AD) pathogenesis is needed in order to tackle the steady increase in the global prevalence of AD. This challenge is complicated by the need to identify key health shifts that precede the onset of AD and cognitive decline as these represent windows of opportunity for intervening and preventing disease. Such shifts may be captured through the measurement of biomarkers that reflect the health of the individual, in particular those that reflect brain age and biological age. Brain age biomarkers provide a composite view of the health of the brain based on neuroanatomical analyses, while biological age biomarkers, which encompass the epigenetic clock, provide a measurement of the overall health state of an individual based on DNA methylation analysis. Acceleration of brain and biological ages is associated with changes in cognitive function, as well as neuropathological markers of AD. In this mini-review, we discuss brain age and biological age research in the context of cognitive decline and AD. While more research is needed, studies show that brain and biological aging trajectories are variable across individuals and that such trajectories are non-linear at older ages. Longitudinal monitoring of these biomarkers may be valuable for enabling earlier identification of divergent pathological trajectories toward AD and providing insight into points for intervention.
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Affiliation(s)
- Winnie S. Liang
- NetBio, Inc., Los Angeles, CA, United States
- Translational Genomics Research Institute, Phoenix, AZ, United States
- *Correspondence: Winnie S. Liang,
| | - Laura H. Goetz
- NetBio, Inc., Los Angeles, CA, United States
- Translational Genomics Research Institute, Phoenix, AZ, United States
| | - Nicholas J. Schork
- NetBio, Inc., Los Angeles, CA, United States
- Translational Genomics Research Institute, Phoenix, AZ, United States
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12
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Zhou A, Wu Z, Zaw Phyo AZ, Torres D, Vishwanath S, Ryan J. Epigenetic aging as a biomarker of dementia and related outcomes: a systematic review. Epigenomics 2022; 14:1125-1138. [PMID: 36154448 DOI: 10.2217/epi-2022-0209] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Background: Biological aging may be a robust biomarker of dementia or cognitive performance. This systematic review synthesized the evidence for an association between epigenetic aging and dementia, mild cognitive impairment and cognitive function. Methods: A systematic search was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results: 30 eligible articles were included. There was no strong evidence that accelerated epigenetic aging was associated with dementia/mild cognitive impairment (n = 7). There was some evidence of an association with poorer cognition (n = 20), particularly with GrimAge acceleration, but this was inconsistent and varied across cognitive domains. A meta-analysis was not performed due to high study heterogeneity. Conclusion: There is insufficient evidence to indicate that current epigenetic aging clocks can be clinically useful biomarkers of dementia or cognitive aging.
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Affiliation(s)
- Aoshuang Zhou
- Division of Epidemiology, Jockey Club School of Public Health & Primary Care, Chinese University of Hong Kong, Hong Kong, China
| | - Zimu Wu
- Biological Neuropsychiatry & Dementia Unit, School of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Aung Zaw Zaw Phyo
- Biological Neuropsychiatry & Dementia Unit, School of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Daniel Torres
- Biological Neuropsychiatry & Dementia Unit, School of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Swarna Vishwanath
- Biological Neuropsychiatry & Dementia Unit, School of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
| | - Joanne Ryan
- Biological Neuropsychiatry & Dementia Unit, School of Public Health & Preventive Medicine, Monash University, Melbourne, Victoria, 3004, Australia
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