Accelerated DNA methylation age and medication use among African Americans

Sexual minority stress and epigenetic aging

Lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ + ) individuals have poorer mental and physical health than heterosexuals, and bisexuals fare worse than individuals who identify as lesbian and gay. However, data on stress biology among sexual minorities are critically insufficient. The current pilot study utilized data from 32 bisexual women - a subset of the National Couples' Health and Time Study - who completed questionnaires and provided blood samples to index biological aging from DNA methylation data (DunedinPACE, GrimAge2). The mean DunedinPACE score was 1.13 (SD = 0.18), which outpaced chronological aging by 13 % (p < 0.001). Likewise, bisexual women in this sample were, on average, 8.67 (SD = 5.96) years older biologically per GrimAge2 as compared to their chronological age. In covariate adjusted models, those reporting greater internalized homonegativity exhibited significantly greater epigenetic age acceleration (GrimAge2: p = 0.01; DunedinPACE: p = 0.041). Those who reported more frequent anti-bisexual experiences also showed accelerated GrimAge2 (p = 0.023). In contrast, those who reported stronger identity centrality (p = 0.017), stronger identity affirmation (p = 0.029), and more friend support (p = 0.018) - a critical type of support for LGBTQ + individuals - had slower GrimAge2. Depressive symptoms, anxiety and loneliness were not associated with GrimAge2 or DunedinPACE. Results suggest that bisexual women are at risk for accelerated aging, and those who have less internal and external affirmation of their sexual identity may be most at risk.

Maximizing insights from longitudinal epigenetic age data: simulations, applications, and practical guidance

BACKGROUND

Epigenetic age (EA) is an age estimate, developed using DNA methylation (DNAm) states of selected CpG sites across the genome. Although EA and chronological age are highly correlated, EA may not increase uniformly with time. Departures, known as epigenetic age acceleration (EAA), are common and have been linked to various traits and future disease risk. Limited by available data, most studies investigating these relationships have been cross-sectional, using a single EA measurement. However, the recent growth in longitudinal DNAm studies has led to analyses of associations with EA over time. These studies differ in (1) their choice of model; (2) the primary outcome (EA vs. EAA); and (3) in their use of chronological age or age-independent time variables to account for the temporal dynamic. We evaluated the robustness of each approach using simulations and tested our results in two real-world examples, using biological sex and birthweight as predictors of longitudinal EA.

RESULTS

Our simulations showed most accurate effect sizes in a linear mixed model or generalized estimating equation, using chronological age as the time variable. The use of EA versus EAA as an outcome did not strongly impact estimates. Applying the optimal model in real-world data uncovered advanced GrimAge in individuals assigned male at birth that decelerates over time.

CONCLUSION

Our results can serve as a guide for forthcoming longitudinal EA studies, aiding in methodological decisions that may determine whether an association is accurately estimated, overestimated, or potentially overlooked.

Diet Quality and Epigenetic Aging in the Women's Health Initiative

BACKGROUND

Higher diet quality scores are associated with a lower risk for many chronic diseases and all-cause mortality; however, it is unclear if diet quality is associated with aging biology.

OBJECTIVE

This study aimed to examine the association between diet quality and a measure of biological aging known as epigenetic aging.

DESIGN

A cross-sectional data analysis was used to examine the association between three diet quality scores based on self-reported food frequency questionnaire data and five measures of epigenetic aging based on DNA methylation (DNAm) data from peripheral blood.

PARTICIPANTS/SETTING

This study included 4,500 postmenopausal women recruited from multiple sites across the United States (1993-98), aged 50 to 79 years, with food frequency questionnaire and DNAm data available from the Women's Health Initiative baseline visit.

MAIN OUTCOME MEASURES

Five established epigenetic aging measures were generated from HumanMethylation450 Beadchip DNAm data, including AgeAccelHannum, AgeAccelHorvath, AgeAccelPheno, AgeAccelGrim, and DunedinPACE.

STATISTICAL ANALYSES PERFORMED

Linear mixed models were used to test for associations between three diet quality scores (Healthy Eating Index, Dietary Approaches to Stop Hypertension, and alternate Mediterranean diet scores) and epigenetic aging measures, adjusted for age, race and ethnicity, education, tobacco smoking, physical activity, Women's Health Initiative substudy from which DNAm data were obtained, and DNAm-based estimates of leukocyte proportions.

RESULTS

Healthy Eating Index, Dietary Approaches to Stop Hypertension, and alternate Mediterranean diet scores were all inversely associated with AgeAccelPheno, AgeAccelGrim, and DunedinPACE (P < 0.05), with the largest effects with DunedinPACE. A one standard deviation increment in diet quality scores was associated with a decrement (β ± SE) in DunedinPACE z score of -0.097 ± 0.014 (P = 9.70 x 10-13) for Healthy Eating Index, -0.107 ± 0.014 (P = 1.53 x 10-14) for Dietary Approaches to Stop Hypertension, and -0.068 ± 0.013 (P = 2.31 x 10-07) for the alternate Mediterranean diet.

CONCLUSIONS

In postmenopausal women, diet quality scores were inversely associated with DNAm-based measures of biological aging, particularly DunedinPACE.

Childhood adversity, accelerated GrimAge, and associated health consequences

Childhood adversity is linked to psychological, behavioral, and physical health problems, including obesity and cardiometabolic disease. Epigenetic alterations are one pathway through which the effects of early life stress and adversity might persist into adulthood. Epigenetic mechanisms have also been proposed to explain why cardiometabolic health can vary greatly between individuals with similar Body Mass Index (BMIs). We evaluated two independent cross-sectional cohorts of adults without known medical illness, one of which explicitly recruited individuals with early life stress (ELS) and control participants (n = 195), and the other a general community sample (n = 477). In these cohorts, we examine associations between childhood adversity, epigenetic aging, and metabolic health. Childhood adversity was associated with increased GrimAge Acceleration (GAA) in both cohorts, both utilizing a dichotomous yes/no classification (both p < 0.01) as well as a continuous measure using the Childhood Trauma Questionnaire (CTQ) (both p < 0.05). Further investigation demonstrated that CTQ subscales for physical and sexual abuse (both p < 0.05) were associated with increased GAA in both cohorts, whereas physical and emotional neglect were not. In both cohorts, higher CTQ was also associated with higher BMI and increased insulin resistance (both p < 0.05). Finally, we demonstrate a moderating effect of BMI on the relationship between GAA and insulin resistance where GAA correlated with insulin resistance specifically at higher BMIs. These results, which were largely replicated between two independent cohorts, suggest that interactions between epigenetics, obesity, and metabolic health may be important mechanisms through which childhood adversity contributes to long-term physical and metabolic health effects.

Epigenetics, Microbiome and Personalized Medicine: Focus on Kidney Disease

Personalized medicine, which involves modifying treatment strategies/drug dosages based on massive laboratory/imaging data, faces large statistical and study design problems. The authors believe that the use of continuous multidimensional data, such as those regarding gut microbiota, or binary multidimensional systems properly transformed into a continuous variable, such as the epigenetic clock, offer an advantageous scenario for the design of trials of personalized medicine. We will discuss examples focusing on kidney diseases, specifically on IgA nephropathy. While gut dysbiosis can provide a treatment strategy to restore the standard gut microbiota using probiotics, transforming epigenetic omics data into epigenetic clocks offers a promising tool for personalized acute and chronic kidney disease care. Epigenetic clocks involve a complex transformation of DNA methylome data into estimated biological age. These clocks can identify people at high risk of developing kidney problems even before symptoms appear. Some of the effects of both the epigenetic clock and microbiota on kidney diseases seem to be mediated by endothelial dysfunction. These "big data" (epigenetic clocks and microbiota) can help tailor treatment plans by pinpointing patients likely to experience rapid declines or those who might not need overly aggressive therapies.

Maximizing Insights from Longitudinal Epigenetic Age Data: Simulations, Applications, and Practical Guidance

Background

Epigenetic Age (EA) is an age estimate, developed using DNA methylation (DNAm) states of selected CpG sites across the genome. Although EA and chronological age are highly correlated, EA may not increase uniformly with time. Departures, known as epigenetic age acceleration (EAA), are common and have been linked to various traits and future disease risk. Limited by available data, most studies investigating these relationships have been cross-sectional - using a single EA measurement. However, the recent growth in longitudinal DNAm studies has led to analyses of associations with EA over time. These studies differ in (i) their choice of model; (ii) the primary outcome (EA vs. EAA); and (iii) in their use of chronological age or age-independent time variables to account for the temporal dynamic. We evaluated the robustness of each approach using simulations and tested our results in two real-world examples, using biological sex and birthweight as predictors of longitudinal EA.

Results

Our simulations showed most accurate effect sizes in a linear mixed model or generalized estimating equation, using chronological age as the time variable. The use of EA versus EAA as an outcome did not strongly impact estimates. Applying the optimal model in real-world data uncovered an accelerated EA rate in males and an advanced EA that decelerates over time in children with higher birthweight.

Conclusion

Our results can serve as a guide for forthcoming longitudinal EA studies, aiding in methodological decisions that may determine whether an association is accurately estimated, overestimated, or potentially overlooked.

Marking Time: Epigenetic Aging May Partially Explain the Arsenic-Cardiovascular Disease Link

New epigenetic clocks point to DNA methylation as a mechanism in the well-known link between arsenic exposure and cardiovascular disease risk. The results validate the use of these clocks in Native American populations.

Traditional Therapeutics and Potential Epidrugs for CVD: Why Not Both?

Cardiovascular disease (CVD) is the leading cause of death worldwide. In addition to the high mortality rate, people suffering from CVD often endure difficulties with physical activities and productivity that significantly affect their quality of life. The high prevalence of debilitating risk factors such as obesity, type 2 diabetes mellitus, smoking, hypertension, and hyperlipidemia only predicts a bleak future. Current traditional CVD interventions offer temporary respite; however, they compound the severe economic strain of health-related expenditures. Furthermore, these therapeutics can be prescribed indefinitely. Recent advances in the field of epigenetics have generated new treatment options by confronting CVD at an epigenetic level. This involves modulating gene expression by altering the organization of our genome rather than altering the DNA sequence itself. Epigenetic changes are heritable, reversible, and influenced by environmental factors such as medications. As CVD is physiologically and pathologically diverse in nature, epigenetic interventions can offer a ray of hope to replace or be combined with traditional therapeutics to provide the prospect of addressing more than just the symptoms of CVD. This review discusses various risk factors contributing to CVD, perspectives of current traditional medications in practice, and a focus on potential epigenetic therapeutics to be used as alternatives.

Differences of RUNX2 gene promoter methylation and transcription level in ankylosing spondylitis

BACKGROUND AND OBJECTIVE

Ankylosing spondylitis is a refractory immune disease that seriously affects the life and work of patients. Epigenetic modifications, especially DNA methylation, have become a research hotspot in complex diseases. We aim to explore the changes in runt-related transcription factor 2 (RUNX2) gene promoter methylation and transcription level in AS.

METHOD

We detected the RUNX2 gene promoter methylation in 83 AS patients and 83 healthy controls (HCs), then inspected the mRNA difference of RUNX2 between 30 AS patients and 30 HCs by the quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR).

RESULTS

The RUNX2 gene promoter was hypomethylated in AS patients compared to HCs (p < .001). The research involved 4 CpG regions and 74 CpG sites of RUNX2, of which CpG-2, CpG-4 regions, and 18 CpG sites have been differentially methylated. The CpG-4 island methylation was negatively correlated with C-reactive protein (p < .05) in AS patients. In the qRT-PCR validation phase, the mRNA level of RUNX2 in AS patients was significantly higher than HCs (p < .05), and in AS patients who were treated with biologics, the methylation level of CpG-2 island showed a negative correlation to mRNA (p < .05). ROC results indicated that RUNX2 methylation and its transcription level have good potential to distinguish AS patients from HCs.

CONCLUSION

The RUNX2 gene promoter was hypomethylated in AS patients. Meanwhile, the qRT-PCR verified the up-regulated expression on the transcription level, suggesting the abnormal methylation of RUNX2 contributes to the pathogenesis of AS.

NSAIDs use history: impact on the genome-wide DNA methylation profile and possible mechanisms of action

BACKGROUND AND OBJECTIVE

NSAIDs inhibit cyclooxygenase, but their role in aging and other diseases is not well understood. Our group previously showed the potential benefit of NSAIDs in decreasing the risk of delirium and mortality. Concurrently, epigenetics signals have also been associated with delirium. Therefore, we sought to find differentially methylated genes and biological pathways related to exposure with NSAIDs by comparing the genome-wide DNA methylation profiles of patients with and without a history of NSAIDs use.

METHODS

Whole blood samples were collected from 171 patients at the University of Iowa Hospital and Clinics from November 2017 to March 2020. History of NSAIDs use was assessed through a word-search function in the subjects' electronic medical records. DNA was extracted from the blood samples, processed with bisulfite conversion, and analyzed using Illumina's EPIC array. The analysis of top differentially methylated CpG sites and subsequent enrichment analysis were conducted using an established pipeline using R statistical software.

RESULTS

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) showed several biological pathways relevant to NSAIDs' function. The identified GO terms included "arachidonic acid metabolic process," while KEGG results included "linoleic acid metabolism," "cellular senescence," and "circadian rhythm." Nonetheless, none of the top GO and KEGG pathways and the top differentially methylated CpG sites reached statistical significance.

CONCLUSION

Our results suggest a potential role of epigenetics in the mechanisms of the action of NSAIDs. However, the results should be viewed with caution as exploratory and hypothesis-generating given the lack of statistically significant findings.

Greater stress and trauma mediate race-related differences in epigenetic age between Black and White young adults in a community sample

Black Americans suffer lower life expectancy and show signs of accelerated aging compared to other Americans. While previous studies observe these differences in children and populations with chronic illness, whether these pathologic processes exist or how these pathologic processes progress has yet to be explored prior to the onset of significant chronic illness, within a young adult population. Therefore, we investigated race-related differences in epigenetic age in a cross-sectional sample of young putatively healthy adults and assessed whether lifetime stress and/or trauma mediate those differences. Biological and psychological data were collected from self-reported healthy adult volunteers within the local New Haven area (399 volunteers, 19.8% Black, mean age: 29.28). Stress and trauma data was collected using the Cumulative Adversity Inventory (CAI) interview, which assessed specific types of stressors, including major life events, traumatic events, work, financial, relationship and chronic stressors cumulatively over time. GrimAge Acceleration (GAA), determined from whole blood collected from participants, measured epigenetic age. In order to understand the impact of stress and trauma on GAA, exploratory mediation analyses were then used. We found cumulative stressors across all types of events (mean difference of 6.9 p = 2.14e-4) and GAA (β = 2.29 years [1.57-3.01, p = 9.70e-10] for race, partial η2 = 0.091, model adjusted R2 = 0.242) were significantly greater in Black compared to White participants. Critically, CAI total score (proportion mediated: 0.185 [0.073-0.34, p = 6e-4]) significantly mediated the relationship between race and GAA. Further analysis attributed this difference to more traumatic events, particularly assaultive traumas and death of loved ones. Our results suggest that, prior to development of significant chronic disease, Black individuals have increased epigenetic age compared to White participants and that increased cumulative stress and traumatic events may contribute significantly to this epigenetic aging difference.

Biomarkers of aging through the life course: A Recent Literature Update

Purpose of review

The development of biomarkers of aging has greatly advanced epidemiological studies of aging processes. However, much debate remains on the timing of aging onset and the causal relevance of these biomarkers. In this review, we discuss the most recent biomarkers of aging that have been applied across the life course.

Recent findings

The most recently developed aging biomarkers that have been applied across the life course can be designated into three categories: epigenetic clocks, epigenetic markers of chronic inflammation, and mitochondrial DNA copy number. While these have been applied at different life stages, the development, validation, and application of these markers has been largely centered on populations of older adults. Few studies have examined trajectories of aging biomarkers across the life course. As the wealth of molecular and biochemical data increases, emerging biomarkers may be able to capture complex and system-specific aging processes. Recently developed biomarkers include novel epigenetic clocks; clocks based on ribosomal DNA, transcriptomic profiles, proteomics, metabolomics, and inflammatory markers; clonal hematopoiesis of indeterminate potential gene mutations; and multi-omics approaches.

Summary

Attention should be placed on aging at early and middle life stages to better understand trajectories of aging biomarkers across the life course. Additionally, novel biomarkers will provide greater insight into aging processes. The specific mechanisms of aging reflected by these biomarkers should be considered when interpreting results.

Longitudinal associations between use of antihypertensive, antidiabetic, and lipid-lowering medications and biological aging

Aging is a major risk factor for many chronic diseases. This study aimed to examine the effects of antihypertensive, lipid-lowering, and antidiabetic drugs on biological aging. We included 672 participants and 2746 repeated measurements from the Swedish Adoption/Twin Study of Aging. Self-reported medicine uses were categorized into antidiabetic, antihypertensive, and lipid-lowering drugs. A total of 12 biomarkers for biological aging (BA biomarkers) were included as outcomes. Conditional generalized estimating equations were applied conditioning on individuals to estimate the drug effect on BA biomarker level within the same person when using or not using the drug. Chronological age, body mass index, smoking status, number of multiple medication uses, blood pressure, blood glucose level, and apoB/apoA ratio were adjusted for as covariates in the model. Overall, using antihypertensive drugs was associated with a decrease in one DNA-methylation age (PCGrimAge: beta = - 0.39, 95%CI = - 0.67 to - 0.12). When looking into drug subcategories, calcium channel blockers (CCBs) were associated with a decrease in several DNA-methylation ages (PCHorvathAge beta = - 1.28, 95%CI = - 2.34 to - 0.21; PCSkin&bloodAge beta = - 1.34, 95%CI = - 2.61 to - 0.07; PCPhenoAge beta = - 1.74, 95%CI = - 2.58 to - 0.89; PCGrimAge beta = - 0.57, 95%CI = - 0.96 to - 0.17) and in functional biological ages (functional age index beta = - 2.18, 95%CI = - 3.65 to - 0.71; frailty index beta = - 1.31, 95%CI = - 2.43 to - 0.18). However, the results within other drug subcategories were inconsistent. Calcium channel blockers may decrease biological aging captured by the BA biomarkers measured at epigenetic and functional level. Future studies are warranted to confirm these effects and understand the underlying biological mechanisms.

Life-course socioeconomic factors are associated with markers of epigenetic aging in a population-based study

Adverse socioeconomic circumstances negatively affect the functioning of biological systems, but the underlying mechanisms remain only partially understood. Here, we explore the associations between life-course socioeconomic factors and four markers of epigenetic aging in a population-based setting. We included 684 participants (52 % women, mean age 52.6 ± 15.5 years) from a population and family-based Swiss study. We used nine life-course socioeconomic indicators as the main exposure variables, and four blood-derived, second generation markers of epigenetic aging as the outcome variables (Levine's DNAmPhenoAge, DunedinPoAm38, GrimAge epigenetic age acceleration (EAA), and the mortality risk score (MS)). First, we investigated the associations between socioeconomic indicators and markers of epigenetic aging via mixed-effect linear regression models, adjusting for age, sex, participant's recruitment center, familial structure (random-effect covariate), seasonality of blood sampling, and technical covariates. Second, we implemented counterfactual mediation analysis to investigate life-course and intermediate mechanisms underlying the socioeconomic gradient in epigenetic aging. Effect-size estimates were assessed using regression coefficients and counterfactual mediation parameters, along with their respective 95 % confidence intervals. Individuals reporting a low father's occupation, adverse financial conditions in childhood, a low income, having financial difficulties, or experiencing unfavorable socioeconomic trajectories were epigenetically older and had a higher mortality risk score than their more advantaged counterparts. Specifically, this corresponded to an average increase of 1.1-1.5 years for Levine's epigenetic age (β and 95 %CI range, β (minimum and maximum): 1.1-1.5 95 %CI[0.0-0.2; 2.3-3.0]), 1.1-1.5 additional years for GrimAge (β: 1.1-1.5 95 %CI[0.2-0.6; 1.9-3.0]), a 1-3 % higher DunedinPoAm38 age acceleration (β: 0.01-0.03 95 %CI[0.00; 0.03-0.04]), and a 10-50 % higher MS score (β: 0.1-0.4 95 %CI[0.0-0.2; 0.3-0.4]) for the aforementioned socioeconomic indicators. By exploring the life-course mechanisms underlying the socioeconomic gradient in epigenetic aging, we found that both childhood and adulthood socioeconomic factors contributed to epigenetic aging, and that detrimental lifestyle factors mediated the relation between socioeconomic circumstances in adulthood and EAA (31-89 % mediated proportion). This study provides emerging evidence for an association between disadvantaged life-course socioeconomic circumstances and detrimental epigenetic aging patterns, supporting the "sensitive-period" life-course model. Counterfactual mediation analyses further indicated that the effect of socioeconomic factors in adulthood operates through detrimental lifestyle factors, whereas associations involving early-life socioeconomic factors were less clear.

Association of Physical Inactivity with MRI Markers of Brain Aging: Assessing Mediation by Cardiometabolic and Epigenetic Factors

INTRODUCTION

Cardiometabolic risk factors and epigenetic patterns, increased in physically inactive individuals, are associated with an accelerated brain aging process.

OBJECTIVE

To determine whether cardiometabolic risk factors and epigenetic patterns mediate the association of physical inactivity with unfavorable brain morphology.

METHODS

We included dementia and stroke free participants from the Framingham Heart Study Third Generation and Offspring cohorts who had accelerometery and brain MRI data (n = 2,507, 53.9% women, mean age 53.9 years). We examined mediation by the 2017-revised Framingham Stroke Risk Profile (FSRP, using weights for age, cardiovascular disease, atrial fibrillation, diabetes and smoking status, antihypertension medications, and systolic blood pressure) and the homeostatic model of insulin resistance (HOMA-IR) in models of the association of physical inactivity with brain aging, adjusting for age, age-squared, sex, accelerometer wear time, cohort, time from exam-to-MRI, and season. We similarly assessed mediation by an epigenetic age-prediction algorithm, GrimAge, in a smaller sample of participants who had DNA methylation data (n = 1,418).

RESULTS

FSRP and HOMA-IR explained 8.3-20.5% of associations of higher moderate-to-vigorous physical activity (MVPA), higher steps, and lower sedentary time with higher brain volume. Additionally, FSRP and GrimAge explained 10.3-22.0% of associations of physical inactivity with lower white matter diffusivity and FSRP explained 19.7% of the association of MVPA with lower free water accumulation.

CONCLUSION

Our results suggest that cardiometabolic risk factors and epigenetic patterns partially mediate the associations of physical inactivity with lower brain volume, higher white matter diffusivity, and aggregation of free water in the extracellular compartments of the brain.

Accelerated epigenetic aging in suicide attempters uninfluenced by high intent-to-die and choice of lethal methods

Suicide attempts (SA) are associated with excess non-suicidal mortality, putatively mediated in part by premature cellular senescence. Epigenetic age (EA) estimators of biological age have been previously demonstrated to strongly predict physiological dysregulation and mortality risk. Herein, we investigate if violent SA with high intent-to-die is predictive of epigenetics-derived estimates of biological aging. The genome-wide methylation pattern was measured using the Illumina Infinium Methylation EPIC BeadChip in whole blood of 88 suicide attempters. Subjects were stratified into two groups based on the putative risk of later committed suicide (low- [n = 58] and high-risk [n = 30]) in dependency of SA method (violent or non-violent) and/or intent-to-die (high/low). Estimators of intrinsic and extrinsic EA acceleration, one marker optimized to predict physiological dysregulation (DNAmPhenoAge/AgeAccelPheno) and one optimized to predict lifespan (DNAmGrimAge/AgeAccelGrim) were investigated for associations to severity of SA, by univariate and multivariate analyses. The study was adequately powered to detect differences of 2.2 years in AgeAccelGrim in relation to SA severity. Baseline DNAmGrimAge exceeded chronological age by 7.3 years on average across all samples, conferring a mean 24.6% increase in relation to actual age. No individual EA acceleration marker was differentiated by suicidal risk group (p > 0.1). Thus, SA per se but not severity of SA is related to EA, implicating that excess non-suicidal mortality in SA is unrelated to risk of committed suicide. Preventative healthcare efforts aimed at curtailing excess mortality after SA may benefit from acting equally powerful to recognize somatic comorbidities irrespective of the severity inherent in the act itself.

Gene expression correlates of advanced epigenetic age and psychopathology in postmortem cortical tissue

Psychiatric stress has been associated with accelerated epigenetic aging (i.e., when estimates of cellular age based on DNA methylation exceed chronological age) in both blood and brain tissue. Little is known about the downstream biological effects of accelerated epigenetic age on gene expression. In this study we examined associations between DNA methylation-derived estimates of cellular age that range from decelerated to accelerated relative to chronological age (“DNAm age residuals”) and transcriptome-wide gene expression. This was examined using tissue from three post-mortem cortical regions (ventromedial and dorsolateral prefrontal cortex and motor cortex, n = 97) from the VA National PTSD Brain Bank. In addition, we examined how posttraumatic stress disorder (PTSD) and alcohol-use disorders (AUD) moderated the association between DNAm age residuals and gene expression. Transcriptome-wide results across brain regions, psychiatric diagnoses, and cohorts (full sample and male and female subsets) revealed experiment-wide differential expression of 11 genes in association with PTSD or AUD in interaction with DNAm age residuals. This included the inflammation-related genes IL1B, RCOR2, and GCNT1. Candidate gene class analyses and gene network enrichment analyses further supported differential expression of inflammation/immune gene networks as well as glucocorticoid, circadian, and oxidative stress-related genes. Gene co-expression network modules suggested enrichment of myelination related processes and oligodendrocyte enrichment in association with DNAm age residuals in the presence of psychopathology. Collectively, results suggest that psychiatric stress accentuates the association between advanced epigenetic age and expression of inflammation genes in the brain. This highlights the role of inflammatory processes in the pathophysiology of accelerated cellular aging and suggests that inflammatory pathways may link accelerated cellular aging to premature disease onset and neurodegeneration, particularly in stressed populations. This suggests that anti-inflammatory interventions may be an important direction to pursue in evaluating ways to prevent or delay cellular aging and increase resilience to diseases of aging.