Racial discrimination during middle age predicts higher serum phosphorylated tau and neurofilament light chain levels a decade later: A study of aging black Americans.

INTRODUCTION: Recent evidence suggests that exposure to the stress of racism may increase the risk of dementia for Black Americans. METHODS: The present study used 17 years of data from a sample of 255 Black Americans to investigate the extent to which exposure to racial discrimination predicts subsequent changes in serum Alzheimer's Disease Research Center (ADRC) biomarkers: serum phosphorylated tau181(p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). We hypothesized that racial discrimination assessed during middle age would predict increases in these serum biomarkers as the participants aged into their 60s. RESULTS: Our findings indicate that exposure to various forms of racial discrimination during a person's 40s and early 50s predicts an 11-year increase in both serum p-tau181 and NfL. Racial discrimination was not associated with subsequent levels of GFAP. DISCUSSION: These findings suggest that racial discrimination in midlife may contribute to increased AD pathology and neurodegeneration later in life. HIGHLIGHTS: A 17-year longitudinal study of Black Americans. Assessments of change in serum p-tau181, neurofilament light, and glial fibrillary acidic protein. Exposure to racial discrimination during middle age predicted increases in p-tau181 and neurofilament light. Education was positively related to both p-tau181 and exposure to racial discrimination.

The Use of Precision Epigenetic Methods for the Diagnosis and Care of Stable Coronary Heart Disease Reduces Healthcare Costs.

INTRODUCTION: The cost of secondary prevention of coronary heart disease (CHD) is continuing to increase, with a substantial portion of this acceleration being driven by the expense of confirmatory diagnostic testing. Conceivably, newly developed precision epigenetic technologies could drive down these costs. However, at the current time, their impact on overall expense for CHD care is poorly understood. We hypothesized that the use of a newly developed, highly sensitive, and specific epigenetic test, PrecisionCHD, could decrease the costs of secondary prevention. METHODS: To test this hypothesis, we constructed a budget impact analysis using a cost calculation model that examined the effects of substituting PrecisionCHD for conventional CHD diagnostic tests on the expenses of the initial evaluation and first year of care of stable CHD using a 1-year time horizon with no discounting. RESULTS: The model projected that for a commercial insurer with one million members, full adoption of PrecisionCHD as the primary method of initial CHD assessment would save approximately $113.6 million dollars in the initial year. CONCLUSION: These analyses support the use of precision epigenetic methods as part of the initial diagnosis and care of stable CHD and can meaningfully reduce cost. Real-world pilots to test the reliability of these analyses are indicated.

ZSCAN25 methylation predicts seizures and severe alcohol withdrawal syndrome.

Currently, clinicians use their judgement and indices such as the Prediction of Alcohol Withdrawal Syndrome Scale (PAWSS) to determine whether patients are admitted to hospitals for consideration of withdrawal syndrome (AWS). However, only a fraction of those admitted will experience severe AWS. Previously, we and others have shown that epigenetic indices, such as the Alcohol T-Score (ATS), can quantify recent alcohol consumption. However, whether these or other alcohol biomarkers, such as carbohydrate deficient transferrin (CDT), could identify those at risk for severe AWS is unknown. To determine this, we first conducted genome-wide DNA methylation analyses of subjects entering and exiting alcohol treatment to identify loci whose methylation quickly reverted as a function of abstinence. We then tested whether methylation at a rapidly reverting locus, cg07375256, or other existing metrics including PAWSS scores, CDT levels, or ATS, could predict outcome in 125 subjects admitted for consideration of AWS. We found that PAWSS did not significantly predict severe AWS nor seizures. However, methylation at cg07375256 (ZSCAN25) and CDT strongly predicted severe AWS with ATS (p < 0.007) and cg07375256 (p < 6 × 10-5) methylation also predicting AWS associated seizures. We conclude that epigenetic methods can predict those likely to experience severe AWS and that the use of these or similar Precision Epigenetic approaches could better guide AWS management.

Validation of an Integrated Genetic-Epigenetic Test for the Assessment of Coronary Heart Disease.

BACKGROUND: Coronary heart disease (CHD) is the leading cause of death in the world. Unfortunately, many of the key diagnostic tools for CHD are insensitive, invasive, and costly; require significant specialized infrastructure investments; and do not provide information to guide postdiagnosis therapy. In prior work using data from the Framingham Heart Study, we provided in silico evidence that integrated genetic-epigenetic tools may provide a new avenue for assessing CHD. METHODS AND RESULTS: In this communication, we use an improved machine learning approach and data from 2 additional cohorts, totaling 449 cases and 2067 controls, to develop a better model for ascertaining symptomatic CHD. Using the DNA from the 2 new cohorts, we translate and validate the in silico findings into an artificial intelligence-guided, clinically implementable method that uses input from 6 methylation-sensitive digital polymerase chain reaction and 10 genotyping assays. Using this method, the overall average area under the curve, sensitivity, and specificity in the 3 test cohorts is 82%, 79%, and 76%, respectively. Analysis of targeted cytosine-phospho-guanine loci shows that they map to key risk pathways involved in atherosclerosis that suggest specific therapeutic approaches. CONCLUSIONS: We conclude that this scalable integrated genetic-epigenetic approach is useful for the diagnosis of symptomatic CHD, performs favorably as compared with many existing methods, and may provide personalized insight to CHD therapy. Furthermore, given the dynamic nature of DNA methylation and the ease of methylation-sensitive digital polymerase chain reaction methodologies, these findings may pave a pathway for precision epigenetic approaches for monitoring CHD treatment response.

Precision epigenetics provides a scalable pathway for improving coronary heart disease care globally.

Coronary heart disease (CHD) is the world's leading cause of death. Up to 90% of all CHD deaths are preventable, but effective prevention of this mortality requires more scalable, precise methods for assessing CHD status and monitoring treatment response. Unfortunately, current diagnostic methods have barriers to implementation, particularly in rural areas and lower-income countries. This gap may be bridged by highly scalable advances in DNA methylation testing methods and artificial intelligence. Herein, we review prior studies of CHD related to methylation alone and in combination with other biovariables. We compare these new methods with established methods for diagnosing CHD. Finally, we outline pathways through which methylation-based testing methods may allow the democratization of improved methods for assessing CHD globally.

Diagnosing coronary heart disease is both costly and difficult at the present time. As a result, many patients in both mature and developing economies die prematurely. New developments in artificial intelligence, epigenetics and laboratory tools may lead to better methods for diagnosing and monitoring heart disease. In this article, we review how advancements in these three areas converge to create methods that are more sensitive for detecting heart disease. They are also more affordable. As a result, it is likely that the new computer-guided laboratory tools will become more common in clinical settings throughout the world.

The Reversion of the Epigenetic Signature of Coronary Heart Disease in Response to Smoking Cessation.

Coronary heart disease (CHD) is the leading cause of death worldwide. However, current diagnostic tools for CHD, such as coronary computed tomography angiography (CCTA), are poorly suited for monitoring treatment response. Recently, we have introduced an artificial-intelligence-guided integrated genetic-epigenetic test for CHD whose core consists of six assays that determine methylation in pathways known to moderate the pathogenesis of CHD. However, whether methylation at these six loci is sufficiently dynamic to guide CHD treatment response is unknown. To test that hypothesis, we examined the relationship of changes in these six loci to changes in cg05575921, a generally accepted marker of smoking intensity, using DNA from a cohort of 39 subjects undergoing a 90-day smoking cessation intervention and methylation-sensitive digital PCR (MSdPCR). We found that changes in epigenetic smoking intensity were significantly associated with reversion of the CHD-associated methylation signature at five of the six MSdPCR predictor sites: cg03725309, cg12586707, cg04988978, cg17901584, and cg21161138. We conclude that methylation-based approaches could be a scalable method for assessing the clinical effectiveness of CHD interventions, and that further studies to understand the responsiveness of these epigenetic measures to other forms of CHD treatment are in order.

Epigenetic biomarkers for smoking cessation.

Cigarette smoking has been associated with epigenetic alterations that may be reversible upon cessation. As the most-studied epigenetic modification, DNA methylation is strongly associated with smoking exposure, providing a potential mechanism that links smoking to adverse health outcomes. Here, we reviewed the reversibility of DNA methylation in accessible peripheral tissues, mainly blood, in relation to cigarette smoking cessation and the utility of DNA methylation as a biomarker signature to differentiate current, former, and never smokers and to quantify time since cessation. We summarized thousands of differentially methylated Cytosine-Guanine (CpG) dinucleotides and regions associated with smoking cessation from candidate gene and epigenome-wide association studies, as well as the prediction accuracy of the multi-CpG predictors for smoking status. Overall, there is robust evidence for DNA methylation signature of cigarette smoking cessation. However, there are still gaps to fill, including (1) cell-type heterogeneity in measuring blood DNA methylation; (2) underrepresentation of non-European ancestry populations; (3) limited longitudinal data to quantitatively measure DNA methylation after smoking cessation over time; and (4) limited data to study the impact of smoking cessation on other epigenetic features, noncoding RNAs, and histone modifications. Epigenetic machinery provides promising biomarkers that can improve success in smoking cessation in the clinical setting. To achieve this goal, larger and more-diverse samples with longitudinal measures of a broader spectrum of epigenetic marks will be essential to developing a robust DNA methylation biomarker assay, followed by meeting validation requirements for the assay before being implemented as a clinically useful tool.

Changes in Loneliness, BDNF, and Biological Aging Predict Trajectories in a Blood-Based Epigenetic Measure of Cortical Aging: A Study of Older Black Americans.

A recent epigenetic measure of aging has developed based on human cortex tissue. This cortical clock (CC) dramatically outperformed extant blood-based epigenetic clocks in predicting brain age and neurological degeneration. Unfortunately, measures that require brain tissue are of limited utility to investigators striving to identify everyday risk factors for dementia. The present study investigated the utility of using the CpG sites included in the CC to formulate a peripheral blood-based cortical measure of brain age (CC-Bd). To establish the utility of CC-Bd, we used growth curves with individually varying time points and longitudinal data from a sample of 694 aging African Americans. We examined whether three risk factors that have been linked to cognitive decline-loneliness, depression, and BDNFm-predicted CC-Bd after controlling for several factors, including three new-generation epigenetic clocks. Our findings showed that two clocks-DunedinPACE and PoAm-predicted CC-BD, but that increases in loneliness and BDNFm continued to be robust predictors of accelerated CC-Bd even after taking these effects into account. This suggests that CC-Bd is assessing something more than the pan-tissue epigenetic clocks but that, at least in part, brain health is also associated with the general aging of the organism.

Direct and Indirect Effects of Socioeconomic Status and Discrimination on Subjective Cognitive Decline: A Longitudinal Study of African American Women.

OBJECTIVES: The present study builds on recent findings suggesting that the stress of institutional and interpersonal racism may contribute to African Americans' elevated risk for dementia. We investigated the extent to which 2 consequences of racism-low socioeconomic status (SES) and discrimination-predict self-reported cognitive decline (SCD) 19 years later. Further, we examined potential mediating pathways that might link SES and discrimination to cognitive decline. Potential mediators included depression, accelerated biological aging, and onset of chronic illnesses. METHODS: Hypotheses were tested using a sample of 293 African American women. SCD was assessed using the Everyday Cognition Scale. Structural equation modeling was used to assess the effects of SES and racial discrimination, both measured in 2002, on SCD reported in 2021. Turning to the mediators, midlife depression was assessed in 2002, accelerated aging in 2019, and chronic illness in 2019. Age and prodrome depression were included as covariates. RESULTS: There were direct effects of SES and discrimination on SCD. In addition, these 2 stressors showed a significant indirect effect on SCD through depression. Finally, there was evidence for a more complex pathway where SES and discrimination accelerate biological aging, with accelerated aging, in turn leading to chronic illness, which then predicted SCD. DISCUSSION: Results of the present study add to a growing literature indicating that living in a racialized society is a central factor in explaining the high risk for dementia among Black Americans. Future research should continue to emphasize the various ways that exposure to racism over the life course effects cognition.

Epigenetic and Proteomic Biomarkers of Elevated Alcohol Use Predict Epigenetic Aging and Cell-Type variation Better Than Self-Report.

Excessive alcohol consumption (EAC) has a generally accepted effect on morbidity and mortality, outcomes thought to be reflected in measures of epigenetic aging (EA). As the association of self-reported EAC with EA has not been consistent with these expectations, underscoring the need for readily employable non-self-report tools for accurately assessing and monitoring the contribution of EAC to accelerated EA, newly developed alcohol consumption DNA methylation indices, such as the Alcohol T Score (ATS) and Methyl DetectR (MDR), may be helpful. To test that hypothesis, we used these new indices along with the carbohydrate deficient transferrin (CDT), concurrent as well as past self-reports of EAC, and well-established measures of cigarette smoking to examine the relationship of EAC to both accelerated EA and immune cell counts in a cohort of 437 young Black American adults. We found that MDR, CDT, and ATS were intercorrelated, even after controlling for gender and cotinine effects. Correlations between EA and self-reported EAC were low or non-significant, replicating prior research, whereas correlations with non-self-report indices were significant and more substantial. Comparing non-self-report indices showed that the ATS predicted more than four times as much variance in EA, CDT4 cells and B-cells as for both the MDR and CDT, and better predicted indices of accelerated EA. We conclude that each of the non-self-report indices have differing predictive capacities with respect to key alcohol-related health outcomes, and that the ATS may be particularly useful for clinicians seeking to understand and prevent accelerated EA. The results also underscore the likelihood of substantial underestimates of problematic use when self-report is used and a reduction in correlations with EA and variance in cell-types.

Do Loneliness and Per Capita Income Combine to Increase the Pace of Biological Aging for Black Adults across Late Middle Age?

In a sample of 685 late middle-aged Black adults (M age at 2019 = 57.17 years), we examined the effects of loneliness and per capita income on accelerated aging using a newly developed DNA-methylation based index: the DunedinPACE. First, using linear, mixed effects regression in a growth curve framework, we found that change in DunedinPACE was dependent on age, with a linear model best fitting the data (b = 0.004, p < 0.001), indicating that average pace of change increased among older participants. A quadratic effect was also tested, but was non-significant. Beyond the effect of age, both change in loneliness (b = 0.009, p < 0.05) and change in per capita income (b = -0.016, p < 0.001) were significantly associated with change in DunedinPACE across an 11-year period, accounting for significant between person variability observed in the unconditional model. Including non-self-report indices of smoking and alcohol use did not reduce the association of loneliness or per capita income with DunedinPACE. However, change in smoking was strongly associated with change in DunedinPACE such that those reducing their smoking aged less rapidly than those continuing to smoke. In addition, both loneliness and per capita income were associated with DunedinPACE after controlling for variation in cell-types.

Digital methylation assessments of alcohol and cigarette consumption account for common variance in accelerated epigenetic ageing.

Smoking and Heavy Alcohol Consumption (HAC) are established risk factors for myriad complex disorders of ageing. Yet many prior studies of Epigenetic Ageing (EA) have shown only modest effects of smoking and drinking on accelerated ageing. One potential reason for this conundrum might be the reliance of some prior EA studies on self-reported substance use, which may be unreliable in many samples. To test whether novel, non-self-reported indices would show a stronger association of smoking and HAC to EA, we used methylation sensitive digital PCR (MSdPCR) and data from 437 African American subjects from Wave 7 of the Family and Community Health Study Offspring Cohort to examine the effects of subjective and objective measures of smoking and HAC on 7 indices of EA. Because of limited overall correlations between the various EA indices, we examined patterns of association separately for each index. Consistent with expectations, MSdPCR assessments of smoking and HAC, but not self-reported alcohol consumption, were strongly correlated with accelerated EA. MSdPCR assessments of smoking and HAC accounted for 57% of GrimAge acceleration and the shared variance in GrimAge and DunedinPOAM accelerated EA. We conclude that MSdPCR assessments of smoking and HAC are valuable tools for understanding EA, represent directly targetable conditions for the prevention of premature ageing, and substantially improve upon self-reported assessment of smoking and HAC.

Shifts in lifestyle and socioeconomic circumstances predict change-for better or worse-in speed of epigenetic aging: A study of middle-aged black women.

BACKGROUND: While numerous studies have documented the power of new generation epigenetic clocks to predict morbidity and mortality, research regarding the causes of variation in speed of epigenetic aging is in the early stages. To the extent that these epigenetic clocks are robust measures of biological aging, they should be sensitive to various nutritional, behavioral, ecological, and social factors that have been shown to affect health. OBJECTIVE: Investigate over an 11-year period the extent to which changes in socioeconomic stress and lifestyle predict changes in speed of epigenetic aging among a sample of middle-aged African American women. METHODS: Using data from the Family and Community Health Study, we investigated whether changes in socioeconomic stress, diet, smoking, exercise, alcohol consumption, and relationship status predict changes in speed of biological aging assessed with 3 s-generation epigenetic clocks: AccelGrimAge, DunedinPoAm, and AccelPhenoAge. The study was able to avoid the challenges associated with self-reports of diet and smoking by employing recently developed epigenetic measures. RESULTS: Changes in socioeconomic stress and diet were associated with changes in speed of biological aging as assessed by all three epigenetic clocks, and changes in smoking was related to changes in AccelGrimAge and DunedinPoAm. Analyses controlling for cell-type indicated that in large measure diet exerts its effect on aging through its impact on the immune system. CONCLUSIONS: These findings suggest that adoption of a healthy diet and reduction in the use of tobacco are related to a decrease in epigenetic aging, whereas increased pressure relating to income, housing and economic independence are associated with an increase in the speed of aging. These effects were especially strong for the two epigenetic clocks AccelGrimAge and DunedinPoAm. Overall, the results indicate that stress and lifestyle changes may, for better or worse, influence the "biological weathering" often experienced by middle-aged African American women.

Additive and Interactive Genetically Contextual Effects of HbA1c on cg19693031 Methylation in Type 2 Diabetes.

Type 2 diabetes mellitus (T2D) has a complex genetic and environmental architecture that underlies its development and clinical presentation. Despite the identification of well over a hundred genetic variants and CpG sites that associate with T2D, a robust biosignature that could be used to prevent or forestall clinical disease has not been developed. Based on the premise that underlying genetic variation influences DNA methylation (DNAm) independently of or in combination with environmental exposures, we assessed the ability of local and distal gene x methylation (GxMeth) interactive effects to improve cg19693031 models for predicting T2D status in an African American cohort. Using genome-wide genetic data from 506 subjects, we identified a total of 1476 GxMeth terms associated with HbA1c values. The GxMeth SNPs map to biological pathways associated with the development and complications of T2D, with genetically contextual differences in methylation observed only in diabetic subjects for two GxMeth SNPs (rs2390998 AG vs. GG, p = 4.63 × 10-11, Δß = 13%, effect size = 0.16 [95% CI = 0.05, 0.32]; rs1074390 AA vs. GG, p = 3.93 × 10-4, Δß = 9%, effect size = 0.38 [95% CI = 0.12, 0.56]. Using a repeated stratified k-fold cross-validation approach, a series of balanced random forest classifiers with random under-sampling were built to evaluate the addition of GxMeth terms to cg19693031 models to discriminate between normoglycemic controls versus T2D subjects. The results were compared to those obtained from models incorporating only the covariates (age, sex and BMI) and the addition of cg19693031. We found a post-pruned classifier incorporating 10 GxMeth SNPs and cg19693031 adjusted for covariates predicted the T2D status, with the AUC, sensitivity, specificity and precision of the positive target class being 0.76, 0.81, 0.70 and 0.63, respectively. Comparatively, the AUC, sensitivity, specificity and precision using the covariates and cg19693031 were only 0.71, 0.74, 0.67 and 0.59, respectively. Collectively, we demonstrate correcting for genetic confounding of cg19693031 improves its ability to detect type 2 diabetes. We conclude that an integrated genetic-epigenetic approach could inform personalized medicine programming for more effective prevention and treatment of T2D.

Unstable Childhood, Adult Adversity, and Smoking Accelerate Biological Aging Among Middle-Age African Americans: Similar Findings for GrimAge and PoAm.

Objectives: The recent biological clocks GrimAge and PoAm are robust predictors of morbidity and mortality. Little research, however, has investigated the factors that influence their ticking speed. No study has used multivariate analyses to examine whether childhood adversity, adult hardship, lifestyle practices, or some combination of these factors best explains acceleration of these indices. Methods: Using a sample of 506 middle-age African Americans, the present study investigated the extent to which childhood instability, adult adversity, and lifestyle predict accelerated GrimAge and PoAm. Results: The two clocks were highly correlated and the pattern of findings was very similar for the two measures. Childhood instability, adult financial hardship, and smoking were significant predictors of both clocks. Discussion: The findings support a life course perspective where both the long arm of childhood as well as later life conditions influence speed of aging. Similar results across the two clocks enhance confidence in the findings.

DNA methylation differentiates smoking from vaping and non-combustible tobacco use.

Increasing use of non-combusted forms of nicotine such as e-cigarettes poses important public health questions regarding their specific risks relative to combusted tobacco products such as cigarettes. To fully delineate these risks, improved biomarkers that can distinguish between these forms of nicotine use are needed. Prior work has suggested that methylation status at cg05575921 may serve as a specific biomarker of combusted tobacco smoke exposure. We hypothesized combining this epigenetic biomarker with conventional metabolite assays could classify the type of nicotine product consumption. Therefore, we determined DNA methylation and serum cotinine values in samples from 112 smokers, 35 e-cigarette users, 19 smokeless tobacco users, and 269 controls, and performed mass spectroscopy analyses of urine samples from all nicotine users and 22 verified controls to determine urinary levels of putatively nicotine product-specific substances; propylene glycol, 2-cyanoethylmercapturic acid (CEMA), and anabasine. 1) Cigarette smoking was associated with a dose dependent demethylation of cg05575921 and increased urinary CEMA and anabasine levels, 2) e-cigarette use did not demethylate cg05575921, 3) smokeless tobacco use also did not demethylate cg05575921 but was positively associated with anabasine levels 4) CEMA and cg05575921 levels were highly correlated and 5) propylene glycol levels did not reliably distinguish use groups. Cg05575921 assessments distinguish exposure to tobacco smoke from smokeless sources of nicotine including e-cigarettes and smokeless tobacco, neither of which are associated with cg05575921 demethylation. A combination of methylomic and metabolite profiling may allow for accurate classification use status of a variety of nicotine containing products.

Methylation of FKBP5 is associated with accelerated DNA methylation ageing and cardiometabolic risk: replication in young-adult and middle-aged Black Americans.

Methylation of FKBP5 is involved in the regulation of the stress response and is influenced by early stress exposure. Two CpG sites, cg20813374 and cg00130530, have been identified as potential reporters of early stress. We examined whether FKBP5 methylation was associated with accelerated DNA methylation ageing and indirectly predicted poorer cardiovascular health among both young adult and middle-aged Black Americans. Four hundred and forty-nine young adults, with a mean age of 28.67 and N = 469 middle-age parents and their current partners with a mean age of 57.21, provided self-reports, biometric assessments, and blood draws. Methylation values were obtained using the Illumina Epic Array. Cardiometabolic risk was calculated by summing the standardized log-transformed scores for the body mass index, mean arterial blood pressure, and HbA1c. We also used a more standard index of risk, the Framingham 10-year cardiometabolic risk index, as an alternative measure of cardiometabolic risk. To measure accelerated ageing, four widely used indices of accelerated, DNA methylation-based ageing were used controlling sex, age, other variation in FKBP5, and cell-type. Exposure to community danger was associated with demethylation of FKBP5. FKBP5 methylation was significantly associated with accelerated ageing for both young-adult and middle-aged samples, with significant indirect effects from FKBP5 methylation to cardiometabolic risk through accelerated ageing for both. Early exposure to danger may influence FKBP5 methylation. In turn, FKBP5 methylation may help explain intrinsic accelerated ageing and elevated cardiometabolic risk in adulthood for Black Americans.

Childhood adversity predicts black young adults' DNA methylation-based accelerated aging: A dual pathway model.

We expand upon prior work (Gibbons et al., ) relating childhood stressor effects, particularly harsh childhood environments, to risky behavior and ultimately physical health by adding longer-term outcomes - deoxyribonucleic acid (DNA) methylation-based measures of accelerated aging (DNAm-aging). Further, following work on the effects of early exposure to danger (McLaughlin et al., ), we also identify an additional pathway from harsh childhood environments to DNAm-aging that we label the danger/FKBP5 pathway, which includes early exposure to dangerous community conditions that are thought to impact glucocorticoid regulation and pro-inflammatory mechanisms. Because different DNAm-aging indices provide different windows on accelerated aging, we contrast effects on early indices of DNAm-aging based on chronological age with later indices that focused on predicting biological outcomes. We utilize data from Family and Community Health Study participants (N = 449) from age 10 to 29. We find that harshness influences parenting, which, in turn, influences accelerated DNAm-aging through the risky cognitions and substance use (i.e., behavioral) pathway outlined by Gibbons et al. (). Harshness is also associated with increased exposure to threat/danger, which, in turn, leads to accelerated DNAm-aging through effects on FKBP5 activity and enhanced pro-inflammatory tendencies (i.e., the danger/FKBP5 pathway).

Predictors of Smoking in Older Adults and an Epigenetic Validation of Self-Report.

There are several established predictors of smoking, but it is unknown if these predictors operate similarly for young and old smokers. We examined clinical data from the National Lung Screening Trial (NLST) to determine the predictive ability of gender, body mass index (BMI), marital status, and race on smoking behavior, with emphasis on gender interactions. In addition, we validated the self-report of smoking behaviors for a subgroup that had available epigenetic data in the form of cg05575921 methylation. Participants were N=9572 current or former smokers from the NLST biofluids database, age 55-74, minimum of 30 pack years, and mostly White. A subgroup of N=3084 who had DNA were used for the self-report validation analysis. The predictor analysis was based on the larger group and used penalized logistic regression to predict the self-report of being a former or current smoker at baseline. Cg05575921 methylation showed a moderate ability to discriminate among former and current smokers, AUC = 0.85 (95% confidence interval = [0.83, 0.86]). The final selected variables for the prediction model were BMI, gender, BMI by gender, age, divorced (vs. married), education, and race. The gender by BMI interaction was such that males had a higher probability of current smoking for lower BMI, but this switched to females having higher current smoking for overweight to obese. There is evidence that the self-reported smoking behavior in NLST is moderately accurate. The results of the primary analysis are consistent with the general smoking literature, and our results provide additional specificity regarding the gender by BMI interaction. Body weight issues might play a role in smoking cessation for older established smokers in a similar manner as younger smokers. It could be that women have less success with cessation when their BMI increases.