title: Epigenetic Age Acceleration Assessed with Human White-Matter Images.
abstract: The accurate estimation of age using methylation data has proved a useful and heritable biomarker, with acceleration in epigenetic age predicting a number of age-related phenotypes. Measures of white matter integrity in the brain are also heritable and highly sensitive to both normal and pathological aging processes across adulthood. We consider the phenotypic and genetic interrelationships between epigenetic age acceleration and white matter integrity in humans. Our goal was to investigate processes that underlie interindividual variability in age-related changes in the brain. Using blood taken from a Mexican-American extended pedigree sample (n= 628; age = 23.28-93.11 years), epigenetic age was estimated using the method developed by Horvath (2013). Forn= 376 individuals, diffusion tensor imaging scans were also available. The interrelationship between epigenetic age acceleration and global white matter integrity was investigated with variance decomposition methods. To test for neuroanatomical specificity, 16 specific tracts were additionally considered. We observed negative phenotypic correlations between epigenetic age acceleration and global white matter tract integrity (ρpheno= -0.119,p= 0.028), with evidence of shared genetic (ρgene= -0.463,p= 0.013) but not environmental influences. Negative phenotypic and genetic correlations with age acceleration were also seen for a number of specific white matter tracts, along with additional negative phenotypic correlations between granulocyte abundance and white matter integrity. These findings (i.e., increased acceleration in epigenetic age in peripheral blood correlates with reduced white matter integrity in the brain and shares common genetic influences) provide a window into the neurobiology of aging processes within the brain and a potential biomarker of normal and pathological brain aging.SIGNIFICANCE STATEMENTEpigenetic measures can be used to predict age with a high degree of accuracy and so capture acceleration in biological age, relative to chronological age. The white matter tracts within the brain are also highly sensitive to aging processes. We show that increased biological aging (measured using epigenetic data from blood samples) is correlated with reduced integrity of white matter tracts within the human brain (measured using diffusion tensor imaging) with data from a large sample of Mexican-American families. Given the family design of the sample, we are also able to demonstrate that epigenetic aging and white matter tract integrity also share common genetic influences. Therefore, epigenetic age may be a potential, and accessible, biomarker of brain aging.
authors.affiliation: Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut 06511, hodgson.karen@gmail.com.
authors.forename: Karen
authors.identifier: 0000-0002-9433-7071
authors.initials: K
authors.lastname: Hodgson
authors.affiliation: Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas 78227.
authors.forename: Melanie A
authors.initials: MA
authors.lastname: Carless
authors.affiliation: South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas 78530.
authors.forename: Hemant
authors.initials: H
authors.lastname: Kulkarni
authors.affiliation: South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas 78530.
authors.forename: Joanne E
authors.initials: JE
authors.lastname: Curran
authors.affiliation: Department of Psychiatry, Icahn Medical Institute, New York, New York 10029.
authors.forename: Emma
authors.initials: E
authors.lastname: Sprooten
authors.affiliation: Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut 06511.
authors.forename: Emma E
authors.initials: EE
authors.lastname: Knowles
authors.affiliation: Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut 06511.
authors.forename: Samuel
authors.identifier: 0000-0002-9332-288X
authors.initials: S
authors.lastname: Mathias
authors.affiliation: South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas 78530.
authors.forename: Harald H H
authors.initials: HHH
authors.lastname: Göring
authors.affiliation: Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut 06511.
authors.forename: Nailin
authors.initials: N
authors.lastname: Yao
authors.affiliation: Department of Psychiatry, University of Texas Health Science Center San Antonio, San Antonio, Texas 78229.
authors.forename: Rene L
authors.identifier: 0000-0003-2112-9463
authors.initials: RL
authors.lastname: Olvera
authors.affiliation: Research Imaging Institute, University of Texas Health Science Center San Antonio, San Antonio, Texas 78229, and.
authors.forename: Peter T
authors.initials: PT
authors.lastname: Fox
authors.affiliation: South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas 78530.
authors.forename: Laura
authors.initials: L
authors.lastname: Almasy
authors.affiliation: South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas 78530.
authors.forename: Ravi
authors.initials: R
authors.lastname: Duggirala
authors.affiliation: South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, Texas 78530.
authors.forename: John
authors.identifier: 0000-0001-6250-5723
authors.initials: J
authors.lastname: Blangero
authors.affiliation: Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut 06511.|Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, Connecticut 06106.
authors.forename: David C
authors.identifier: 0000-0002-4749-6977
authors.initials: DC
authors.lastname: Glahn
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000235:genetics*; D003198:Computer Simulation; D063132:Connectome / Q000379:methods; D056324:Diffusion Tensor Imaging / Q000379:methods*; D044127:Epigenesis, Genetic / Q000235:genetics*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D066127:White Matter / Q000033:anatomy & histology* / Q000502:physiology*; D055815:Young Adult
keywords: aging; epigenetics; genetics; white matter integrity