Proximal and distal effects of genetic susceptibility to multiple sclerosis on the T cell epigenome

Authors

Tina Roostaei, Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center
Hans-Ulrich Klein, Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center
Yiyi Ma, Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center
Daniel Felsky, Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, University of Toronto
Pia Kivisäkk, Alzheimer’s Clinical and Translational Research Unit, Department of Neurology, Massachusetts General Hospital, Boston, MA
Sarah M. Connor, Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center
Alexandra Kroshilina, Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center
Christina Yung, Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center
Belinda J. Kaskow, Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
Xiaorong Shao, Genetic Epidemiology and Genomics Laboratory, University of California, Berkeley, CA
Brooke Rhead, Genetic Epidemiology and Genomics Laboratory, University of California, Berkeley, CA
José M. Ordovás, Genetic Epidemiology and Genomics Laboratory, University of California, Berkeley, CA
Devin M. Absher, HudsonAlpha Institute for Biotechnology, Huntsville, AL
Donna K. Arnett, College of Public Health, University of Kentucky, Lexington, KY
Jia Liu, CUNY Advanced Science Research CenterFollow
Nikolaos Patsopoulos, Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
Lisa F. Barcellos, Genetic Epidemiology and Genomics Laboratory, University of California, Berkeley, CA
Howard L. Weiner, Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
Philip L. De Jager, Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical CenterFollow

Document Type

Article

Publication Date

2021

Abstract

Identifying the effects of genetic variation on the epigenome in disease-relevant cell types can help advance our understanding of the first molecular contributions of genetic susceptibility to disease onset. Here, we establish a genome-wide map of DNA methylation quantitative trait loci in CD4⁺ T-cells isolated from multiple sclerosis patients. Utilizing this map in a colocalization analysis, we identify 19 loci where the same haplotype drives both multiple sclerosis susceptibility and local DNA methylation. We also identify two distant methylation effects of multiple sclerosis susceptibility loci: a chromosome 16 locus affects PRDM8 methylation (a chromosome 4 region not previously associated with multiple sclerosis), and the aggregate effect of multiple sclerosis-associated variants in the major histocompatibility complex influences DNA methylation near PRKCA (chromosome 17). Overall, we present a new resource for a key cell type in inflammatory disease research and uncover new gene targets for the study of predisposition to multiple sclerosis.

Comments

This article was originally published in Nature Communications, available at https://doi.org/10.1038/s41467-021-27427-w

This work is distributed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).