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Epigenetic Aging of Classical Monocytes from Healthy Individuals

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Epigenetic Aging of Classical Monocytes from Healthy Individuals bioRxiv preprint doi: https://doi.org/10.1101/2020.05.10.087023; this version posted May 11, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Epigenetic aging of classical monocytes from healthy individuals Irina Shchukina1,*, Juhi Bagaitkar2,*, Oleg Shpynov1,3,*, Ekaterina Loginicheva1, Sofia Porter1, Denis A. Mogilenko1, Erica Wolin4, Patrick Collins1, German Demidov1,6,7, Mykyta Artomov8,9, Konstantin Zaitsev1, Sviatoslav Sidorov5, Christina Camell5, Monika Bambouskova1, Laura Arthur1, Amanda Swain1, Alexandra Panteleeva1, Aleksei Dievskii3, Evgeny Kurbatsky3, Petr Tsurinov3, Roman Chernyatchik3, Vishwa Deep Dixit5, Marko Jovanovic4, Sheila A. Stewart10, Mark J. Daly8,9,11, Sergey Dmitriev3, Eugene M. Oltz1 and Maxim N. Artyomov1,# AFFILIATIONS 1Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA 2Department of Oral Immunology and Infectious Diseases, University of Louisville, Louisville, KY, USA 3JetBrains Research, St. Petersburg, Russia 4Department of Biological Sciences, Columbia University, New York, NY, USA 5Yale Center for Research on Aging, Yale School of Medicine, New Haven, CT, USA 6Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, 08003, Barcelona, Spain. 7Universitat Pompeu Fabra (UPF), 08003, Barcelona, Spain. 8Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA 9Broad Institute, Cambridge, MA, USA 10Department of Cell Biology and Physiology, Washington University School of Medicine, Saint Louis, MO, USA 11Institute for Molecular Medicine, Helsinki, Finland *These authors contributed equally #Correspondence to [email protected] RUNNING TITLE Epigenetic changes in aging human monocytes KEYWORDS Aging, human monocytes, DNA methylation, transcriptomic, epigenetic, metabolomics, proteomic, plasma 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.05.10.087023; this version posted May 11, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. ABSTRACT The impact of healthy aging on molecular programming of immune cells is poorly understood. Here, we report comprehensive characterization of healthy aging in human classical monocytes, with a focus on epigenomic, transcriptomic, and proteomic alterations, as well as the corresponding proteomic and metabolomic data for plasma, using healthy cohorts of 20 young and 20 older individuals (~27 and ~64 years old on average). For each individual, we performed eRRBS-based DNA methylation profiling, which allowed us to identify a set of age-associated differentially methylated regions (DMRs) – a novel, cell-type specific signature of aging in DNA methylome. Optimized ultra-low-input ChIP-seq (ULI-ChIP-seq) data acquisition and analysis pipelines applied to 5 chromatin marks for each individual revealed lack of large- scale age-associated changes in chromatin modifications and allowed us to link hypo- and hypermethylated DMRs to distinct chromatin modification patterns. Specifically, hypermethylation events were associated with H3K27me3 in the CpG islands near promoters of lowly-expressed genes, while hypomethylated DMRs were enriched in H3K4me1 marked regions and associated with normal pattern of expression. Furthermore, hypo- and hypermethylated DMRs followed distinct functional and genetic association patterns. Hypomethylation events were associated with age-related increase of expression of the corresponding genes, providing a link between DNA methylation and age-associated transcriptional changes in primary human cells. Furthermore, these locations were also enriched in genetic regions associated by GWAS with asthma, total blood protein, hemoglobin levels and MS. On the other side, acceleration of epigenetic age in HIV and asthma stems only from changes in hypermethylated DMRs but not from hypomethylated loci. 2 bioRxiv preprint doi: https://doi.org/10.1101/2020.05.10.087023; this version posted May 11, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. INTRODUCTION Advanced age, even in healthy individuals, is accompanied by progressive decline of cognitive, metabolic and physiological abilities, and can enhance susceptibility to neurodegenerative, cardiovascular, and chronic inflammatory diseases1,2. Operationally, it is often difficult to determine whether age-associated signatures reflect changes of individual cells or changes in cell type abundances, especially when performing whole tissue transcriptional or epigenetic characterization. For example, T cell numbers are reduced in human blood with age3, complicating comparative analyses of whole blood transcriptional or DNA methylation profiles. And even despite a large amount of clinical and epidemiological data4-8, we understand very little about the nature of age-associated changes in specific primary cell populations of healthy individuals, particularly with respect to age-associated alterations of the epigenetic landscape. To address this question directly, we focused on classical CD14+CD16- monocytes, as they are homogeneous, easily accessible, and relatively abundant in blood, which permits multi-omics profiling of these cells obtained from a single blood draw. Also, monocytes have a short differentiation trajectory from bone marrow progenitors, rendering them informative proxies to understand epigenetic changes that occur with age in human hematopoietic stem cells. Epigenetic aging can manifest in two key aspects: via age-associated changes in chromatin modifications and in DNA methylation. Robustness of the connection between aging and DNA methylation has been well acknowledged9-13, yet in spite the large number of studies, cell specific regions of age- associated DNA methylation/demethylation have not been reported to date. Previous studies have been predominantly using DNA methylation arrays which detect changes of a predefined set of distant solitary cytosines across the genome5. This design, however, inherently prevents identification of differentially methylated regions (DMRs), which are expected to be more biologically relevant compared to changes in single isolated CpG sites. Furthermore, while total level of various chromatin modifications has been characterized across age groups and cell populations using CyTOF14, no genomically resolved profiling of major chromatin modifications (e.g. via ChIP-seq) has been reported for primary human cell types and extent of chromatin changes in primary human cells during aging remains unclear. In this study, we used parallel multi-omics approaches to characterize intracellular states and extracellular environments of monocytes along healthy aging. We profiled DNA methylation, five major chromatin modifications, as well as transcriptional and proteomic states of purified CD14+CD16- monocytes from 20 young (24-30 y. o.) and 20 old (57-70 y. o.) donors. To allow identification of continuous DNA regions that change methylation level with age and comprehensive characterization chromatin state, we utilized enhanced Reduced Representation Bisulfite Sequencing (eRRBS) coupled with the Ultra-Low-Input ChIP-Sequencing (ULI-ChIP-seq)15 approach to profile chromatin modifications from limited input material. Our approach led to identification of more than a thousand DMRs, which could not be achieved via 3 bioRxiv preprint doi: https://doi.org/10.1101/2020.05.10.087023; this version posted May 11, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. methylation arrays technology (only ~3% of the DMRs are sufficiently covered in the most commonly used methylation array design). We found no evidence of large-scale remodeling of chromatin modification landscape along the healthy aging yet revealed distinct chromatin features that were characteristic of age- associated DNA hyper- and hypomethylated regions. Integration of the obtained DMR signatures with transcriptional data highlighted connection between age-associated transcriptional alterations and hypomethylated DMRs, while hypermethylated DMRs were not readily associated with transcriptional changes. Together with parallel profiling of plasma proteins and unbiased metabolic profiling from the same individuals, the compendium of data collected in this work comprises a comprehensive aging data resource obtained under stringent inclusion criteria. Easily accessible visualization and exploration of all data from this study, and detailed descriptions of protocols and computational pipelines are available online at http://artyomovlab.wustl.edu/aging/. RESULTS Study design, cohort characteristics, and systemic age-associated changes It has been described that genetic factors, race, sex, body-mass and lifestyles can significantly affect the outcomes of human studies focused on various aspects of aging7,8,10,16,17. Here, we have attempted to assemble a cohort as thoroughly controlled as possible to limit non-age-related contributions in the downstream characterization of monocytes. We used stringent inclusion criteria to eliminate the effect of confounding variables such as inherited genetic traits,
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