For whom the bell tolls: psychopathological and neurobiological correlates of a DNA methylation index of time-to-death

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Psychopathology is a risk factor for accelerated biological aging and early mortality. We examined associations between broad underlying dimensions of psychopathology (reflecting internalizing and externalizing psychiatric symptoms), PTSD, and age-adjusted GrimAge (“GrimAge residuals”), a DNA methylation biomarker of mortality risk relative to age. We also examined neurobiological correlates of GrimAge residuals, including neurocognitive functioning, blood-based biomarkers (of inflammation, neuropathology, metabolic disease), and cortical thickness. Data from two independent trauma-exposed military cohorts ( n = 647 [62.9% male, M _age = 52], n = 434 [90% male, M _age = 32]) were evaluated using linear regression models to test associations between GrimAge residuals, psychopathology, and health correlates. Externalizing psychopathology significantly predicted GrimAge residuals in both cohorts ( ps < 0.028). PTSD predicted GrimAge residuals in the younger ( p = 0.001) but not the older cohort. GrimAge residuals were associated with several neurobiological variables available in the younger cohort, including cognitive disinhibition ( p _adj = 0.021), poorer memory recall ( p _adj = 0.023), cardiometabolic pathology ( p _adj < 0.001), oxidative stress ( p _adj = 0.003), astrocyte damage ( p _adj = 0.021), inflammation (C-reactive protein: p _adj < 0.001; IL-6: p _adj < 0.001), and immune functioning ( p _adj < 0.001). A subset of inflammatory and neuropathology analytes were available in the older cohort and showed associations with GrimAge residuals (IL-6: p _adj < 0.001; TNF-α: p _adj < 0.001). GrimAge residuals were also associated with reduced cortical thickness in right lateral orbitofrontal cortex ( p _adj = 0.018) and left fusiform gyrus ( p _adj = 0.030), which are related to emotion regulation and facial recognition, respectively. Psychopathology may be a common risk factor for elevated mortality risk. GrimAge could help identify those at risk for adverse health outcomes and allow for early disease identification and treatment.

Related collections

Most cited references 58

Record: found
Abstract: found
Article: not found

DNA methylation age of human tissues and cell types

Steve Horvath, Ilias Lagkouvardos (2014)

Background It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure. Results I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance. Conclusions I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.

0 comments Cited 1658 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.

Martin Aryee, Andrew E Jaffe, Héctor Corrada Bravo … (2014)

The recently released Infinium HumanMethylation450 array (the '450k' array) provides a high-throughput assay to quantify DNA methylation (DNAm) at ∼450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years. Here we describe a suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. The software is structured to easily adapt to future versions of the technology. We include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. We show how our software provides a powerful and flexible development platform for future methods. We also illustrate how our methods empower the technology to make discoveries previously thought to be possible only with sequencing-based methods. http://bioconductor.org/packages/release/bioc/html/minfi.html. khansen@jhsph.edu; rafa@jimmy.harvard.edu Supplementary data are available at Bioinformatics online.

0 comments Cited 1237 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

An epigenetic biomarker of aging for lifespan and healthspan

Morgan E Levine, Ake T. Lu, Austin Quach … (2018)

Identifying reliable biomarkers of aging is a major goal in geroscience. While the first generation of epigenetic biomarkers of aging were developed using chronological age as a surrogate for biological age, we hypothesized that incorporation of composite clinical measures of phenotypic age that capture differences in lifespan and healthspan may identify novel CpGs and facilitate the development of a more powerful epigenetic biomarker of aging. Using an innovative two-step process, we develop a new epigenetic biomarker of aging, DNAm PhenoAge, that strongly outperforms previous measures in regards to predictions for a variety of aging outcomes, including all-cause mortality, cancers, healthspan, physical functioning, and Alzheimer's disease. While this biomarker was developed using data from whole blood, it correlates strongly with age in every tissue and cell tested. Based on an in-depth transcriptional analysis in sorted cells, we find that increased epigenetic, relative to chronological age, is associated with increased activation of pro-inflammatory and interferon pathways, and decreased activation of transcriptional/translational machinery, DNA damage response, and mitochondrial signatures. Overall, this single epigenetic biomarker of aging is able to capture risks for an array of diverse outcomes across multiple tissues and cells, and provide insight into important pathways in aging.

0 comments Cited 1035 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Erika J. Wolf:

ORCID: http://orcid.org/0000-0003-2666-2435

Erika.Wolf@va.gov

Journal

Journal ID (nlm-ta): Transl Psychiatry

Journal ID (iso-abbrev): Transl Psychiatry

Title: Translational Psychiatry

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2158-3188

Publication date (Electronic): 24 September 2022

Publication date PMC-release: 24 September 2022

Publication date Collection: 2022

Volume: 12

Electronic Location Identifier: 406

Affiliations

[1 ]GRID grid.410370.1, ISNI 0000 0004 4657 1992, National Center for PTSD at VA Boston Healthcare System, ; Boston, MA USA

[2 ]GRID grid.189504.1, ISNI 0000 0004 1936 7558, Boston University School of Medicine, Department of Psychiatry, ; Boston, MA USA

[3 ]GRID grid.189504.1, ISNI 0000 0004 1936 7558, Boston University School of Medicine, Department of Medicine, Biomedical Genetics, ; Boston, MA USA

[4 ]GRID grid.189504.1, ISNI 0000 0004 1936 7558, Boston University School of Public Health, Department of Biostatistics, ; Boston, MA USA

[5 ]GRID grid.410370.1, ISNI 0000 0004 4657 1992, Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Educational and Clinical Center (GRECC), , VA Boston Healthcare System, ; Boston, MA USA

[6 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Psychiatry, , Harvard Medical School, ; Boston, MA USA

[7 ]GRID grid.261368.8, ISNI 0000 0001 2164 3177, Present Address: Department of Psychology, , Old Dominion University, ; Mills Godwin Bldg (134A), Norfolk, VA USA

Author information

Sage E. Hawn http://orcid.org/0000-0001-8501-4169

Danielle R. Sullivan http://orcid.org/0000-0002-0141-5887

Mark W. Miller http://orcid.org/0000-0001-6393-8563

Erika J. Wolf http://orcid.org/0000-0003-2666-2435

Article

Publisher ID: 2164

DOI: 10.1038/s41398-022-02164-w

PMC ID: 9509393

SO-VID: f1381918-1939-4940-bfdc-99474d948218

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 29 March 2022

Date revision received : 6 September 2022

Date accepted : 8 September 2022

Funding

Funded by: FundRef https://doi.org/10.13039/100000738, U.S. Department of Veterans Affairs (Department of Veterans Affairs);

Award ID: I01 CX-001276-01

Award ID: 1 IK2 CX001772-01

Award ID: B9254-C

Award Recipient : Danielle R. Sullivan William Milberg Erika J. Wolf

Funded by: FundRef https://doi.org/10.13039/100000049, U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging);

Award ID: RF1AG068121

Award Recipient : Erika J. Wolf

Funded by: FundRef https://doi.org/10.13039/100000025, U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH);

Award ID: R21MH102834

Award ID: 5T32MH019836

Award Recipient : Sage E. Hawn Erika J. Wolf

Funded by: U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)