Epigenetic Age is Minimally Correlated with Leukocyte Telomere Length in Pediatric Onset Multiple Sclerosis
Jennifer Yang1, Jonathan Race3, Paige Sumowski2, Kayla Jacques4, Soha Fardad2, Ashley Fair5, Allison Schuette3, Jue Lin6, Defne Yilmaz7, Gregory Aaen8, Aaron Abrams9, Leslie Benson10, Charlie Casper3, Tanuja Chitnis11, Mark Gorman10, Timothy Lotze12, lauren krupp13, Soe Mar14, Jayne Ness15, Mary Rensel16, John Rose17, Teri Schreiner18, Jan-Mendelt Tillema19, Amy Waldman20, Yolanda Wheeler21, Lisa Barcellos22, Emmanuelle Waubant23, Jennifer Graves24
1Neurosciences, UC San Diego, 2UC San Diego, 3University of Utah, 4University of California San Diego, 5Boston University, 6UC San Francisco, 7UC Berkeley, 8Loma Linda University School of Medicine, 9Cleveland Clinic Foundation, 10Children's Hospital Boston, 11Brigham and Women's Hospital, 12Texas Children's Hospital, 13NYU Langone Medical Center, 14Washington University School of Medicine, 15UAB Dept of Pediatrics, Div Pediatric Neurology, 16Cleveland Clinic, 17Imaging and Neurosciences Center, 18University of Colorado/ Children's Hospital of Colorado, 19Mayo Clinic, 20Children's Hospital of Philadelphia, 21University of Alabama Birmingham, 22University of California, Berkeley, 23USCF MS Center, 24UCSD
Objective:
To determine the correlation between epigenetic clocks and telomere length in pediatric-onset MS (POMS) participants and age-similar pediatric controls.
Background:
Age is the strongest factor determining disease expression in multiple sclerosis (MS). Biological aging markers may capture these effects better than birthdate age. We previously demonstrated biological age acceleration in POMS compared to controls with both epigenetic clocks and telomere length. It is unknown whether these biomarkers are reporting overlapping or distinct aging-related processes.
Design/Methods:
We conducted a cross-sectional case control study leveraging DNA samples and clinical data from the US Network of Pediatric MS Centers. Methylation scores were processed using Illumina’s Infinium Methylation EPIC BeadChip. Age acceleration residuals were calculated based on published lifespan and healthspan epigenetic clocks (Horvath, Hannum, PhenoAge, GrimAge). Leukocyte telomere length (LTL), measured by real time qPCR, was expressed as a telomere to single copy gene ratio (T/S). We employed multivariable analysis of covariance to assess correlation between epigenetic clocks and LTL adjusting for chronological age, sex, race, ethnicity, tobacco exposure, socioeconomic status, and BMI. We used multiple imputation to account for missingness.
Results:
We analyzed 300 POMS cases (mean age 15.7 years, SD 2.6) and 200 age-matched pediatric controls (mean age 15.2 years, SD 3.3). There was moderate to strong correlation among the epigenetic clocks and minimal correlation between these clocks and LTL for the entire cohort (POMS and controls) – Horvath (rho=0.083), Hannum (rho=0.014), PhenoAge (rho=0.055), and GrimAge (rho=0.075). When analyzed separately, the POMS and control participants demonstrated similar minimal correlations between epigenetic clocks and LTL.
Conclusions:
Epigenetic age and leukocyte telomere length were minimally correlated in this sample, suggesting the measures capture different processes and should not be used in place of each other. Our results support the use of multiple biomarkers to capture the complexities of aging in MS.
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