Epigenetic aging is accelerated in alcohol use disorder and regulated by genetic variation in APOL2

Luo, Audrey; Jung, Jeesun; Longley, Martha; Rosoff, Daniel B.; Charlet, Katrin; Muench, Christine; Lee, Sang Hoon; Hodgkinson, Colin A.; Goldman, David; Horvath, Steve; Kaminsky, Zachary; Lohoff, Falk W.

doi:10.1038/s41386-019-0500-y

Cited by 85 publications

(84 citation statements)

References 68 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The role of biological sex in neuropsychiatric conditions is relevant for understanding the trajectory of brain health across the lifespan, as all of the abovementioned conditions have been linked to an "accelerated" profile of aging using neuroimaging [Hajek et al, 2019;Han et al, 2019;Koutsouleris et al, 2014;Van Gestel et al, 2019] and epigenetic indices [Fries et al, 2017;Luo et al, 2020;Wolf et al, 2017]. While these studies use algorithmic tools to determine patterns that appear consistent with "accelerated aging", it is speculative at best to conclude that biological patterns that appear older than expected for a person's chronological age are representative of true biological aging -a phenotypic concept that has no true measurement [Butler et al, 2020;Freund, 2019].…”

Section: Sex Differences In Age-related Neurocognitive Disordersmentioning

confidence: 99%

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

Salminen¹,

Tubi²,

Bright³

et al. 2020

Preprint

View full text Add to dashboard Cite

Sex differences are found in the incidence and expression of psychiatric and neurodegenerative conditions, and many studies suggest these differences are influenced by innate biological differences between males and females and risk factors that interact with these differences. However, few studies have used neuroimaging to examine brain signatures of disease separately by sex, and many studies of sex differences have been based on small samples and their findings have not been replicated in larger cohorts. Large-scale neuroimaging initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analyses (ENIGMA) consortium, the UK Biobank, Human Connectome Project, and others offer an unprecedented source of power to address important questions about the role of sex as a risk or protective factor for suboptimal brain health, as well as sex-specific neuroimaging phenotypes in brain-related illnesses. Here we review the existing neuroimaging literature on sex differences in the human brain in healthy adults and those with the most common and debilitating psychiatric and age-related neurodegenerative conditions. Finally, we discuss key gaps in this literature and opportunities of large-scale collaborative efforts to identify, characterize, and explain how biological sex influences the humanbrain in health and disease.

show abstract

Section: Sex Differences In Age-related Neurocognitive Disordersmentioning

confidence: 99%

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

Salminen¹,

Tubi²,

Bright³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…In forensics, the ability to precisely determine the chronological age of samples from DNA methylation-based age prediction models could greatly help investigators to identify and find unknown individuals 13 . In other bio-medical applications, the estimated age from DNA methylation could give an estimation of the biological age 4 and could also be an indicator of different diseases, risks and health conditions when compared to the chronological age of individuals 14 – 17 .…”

Section: Introductionmentioning

confidence: 99%

“…6 These authors contributed equally: Imene Garali and Mourad Sahbatou. * email: alexandre.how-kit@fjd-ceph.org age from DNA methylation could give an estimation of the biological age 4 and could also be an indicator of different diseases, risks and health conditions when compared to the chronological age of individuals [14][15][16][17] .…”

mentioning

confidence: 99%

Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter

Garali

Sahbatou

Daunay

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Several blood-based age prediction models have been developed using less than a dozen to more than a hundred DNA methylation biomarkers. Only one model (Z-P1) based on pyrosequencing has been developed using DNA methylation of a single locus located in the ELOVL2 promoter, which is considered as one of the best age-prediction biomarker. Although multi-locus models generally present better performances compared to the single-locus model, they require more DNA and present more inter-laboratory variations impacting the predictions. Here we developed 17,018 single-locus age prediction models based on DNA methylation of the ELOVL2 promoter from pooled data of four different studies (training set of 1,028 individuals aged from 0 and 91 years) using six different statistical approaches and testing every combination of the 7 CpGs, aiming to improve the prediction performances and reduce the effects of inter-laboratory variations. Compared to Z-P1 model, three statistical models with the optimal combinations of CpGs presented improved performances (MAD of 4.41–4.77 in the testing set of 385 individuals) and no age-dependent bias. In an independent testing set of 100 individuals (19–65 years), we showed that the prediction accuracy could be further improved by using different CpG combinations and increasing the number of technical replicates (MAD of 4.17).

show abstract

“…Lifetime psychological stress, high body mass index, and alcohol use all accelerate age-related DNA methylation changes that occur in human whole blood or liver. 66 - 69 Epigenetic drift, on the contrary, is superimposed onto the aforementioned age-related epigenetic changes and usually increases the variation in epigenetic marks with age—as demonstrated by comparing twin pairs of different ages. 74 , 75 Thus, in addition to age-related epigenetic changes, environmental chemicals can also deflect (perturb) epigenetic drift.…”

Section: What Do We Know About the Intersection Of Toxicoepigenetics mentioning

confidence: 99%

An Understudied Dimension: Why Age Needs to Be Considered When Studying Epigenetic-Environment Interactions

Barrere‐Cain

Allard

2020

Genet Epigenet

View full text Add to dashboard Cite

We live in a complex chemical environment where there are an estimated 350 000 chemical compounds or mixtures commercially produced. A strong body of literature shows that there are time points during early development when an organism’s epigenome is particularly sensitive to chemicals in its environment. What is less understood is how gene-environment and epigenetic-environment interactions change with age. This question is bidirectional: (1) how do chemicals in the environment affect the aging process and (2) how does aging affect an organism’s response to its chemical environment? The study of gene-environment interactions with age is especially important because, in many parts of the world, older individuals are a large and rapidly growing proportion of the population and because aging is a process universal to most of the animal kingdom. Epigenetics has emerged as a crucial framework for studying aging as epigenetic pathways, often triggered by environmental stimuli, have been shown to be essential regulators of the aging process. In this perspective article, we delineate the connection between aging, epigenetics, and environmental exposures. We discuss why it is essential to consider age when researching how an organism interacts with its environment. We describe recent advances in understanding how the chemical environment affects aging and the gap in research on how age affects an organism’s response to the environment. Finally, we highlight how model organisms and network approaches can help fill this crucial gap. Taken together, systemic changes that occur in the epigenome with age indicate that adult organisms cannot be treated as a homogeneous population and that there are discrete mechanisms modulating the aging epigenome that we do not yet understand.

show abstract

Epigenetic aging is accelerated in alcohol use disorder and regulated by genetic variation in APOL2

Cited by 85 publications

References 68 publications

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter

An Understudied Dimension: Why Age Needs to Be Considered When Studying Epigenetic-Environment Interactions

Contact Info

Product

Resources

About