Factors underlying variable DNA methylation in a human community cohort

Epigenome-wide association study of long-term psychosocial stress in older adults

Long-term psychosocial stress is strongly associated with negative physical and mental health outcomes, as well as adverse health behaviours; however, little is known about the role that stress plays on the epigenome. One proposed mechanism by which stress affects DNA methylation is through health behaviours. We conducted an epigenome-wide association study (EWAS) of cumulative psychosocial stress (n = 2,689) from the Health and Retirement Study (mean age = 70.4 years), assessing DNA methylation (Illumina Infinium HumanMethylationEPIC Beadchip) at 789,656 CpG sites. For identified CpG sites, we conducted a formal mediation analysis to examine whether smoking, alcohol use, physical activity, and body mass index (BMI) mediate the relationship between stress and DNA methylation. Nine CpG sites were associated with psychosocial stress (all p < 9E-07; FDR q < 0.10). Additionally, health behaviours and/or BMI mediated 9.4% to 21.8% of the relationship between stress and methylation at eight of the nine CpGs. Several of the identified CpGs were in or near genes associated with cardiometabolic traits, psychosocial disorders, inflammation, and smoking. These findings support our hypothesis that psychosocial stress is associated with DNA methylation across the epigenome. Furthermore, specific health behaviours mediate only a modest percentage of this relationship, providing evidence that other mechanisms may link stress and DNA methylation.

Poverty and neighborhood opportunity effects on neonate DNAm developmental age

BACKGROUND

Children from families with low socioeconomic status (SES), as determined by income, experience several negative outcomes, such as higher rates of newborn mortality and behavioral issues. Moreover, associations between DNA methylation and low income or poverty status are evident beginning at birth, suggesting prenatal influences on offspring development. Recent evidence suggests neighborhood opportunities may protect against some of the health consequences of living in low income households. The goal of this study was to assess whether neighborhood opportunities moderate associations between household income (HI) and neonate developmental maturity as measured with DNA methylation.

METHODS

Umbilical cord blood DNA methylation data was available in 198 mother-neonate pairs from the larger CANDLE cohort. Gestational age acceleration was calculated using an epigenetic clock designed for neonates. Prenatal HI and neighborhood opportunities measured with the Childhood Opportunity Index (COI) were regressed on gestational age acceleration controlling for sex, race, and cellular composition.

RESULTS

Higher HI was associated with higher gestational age acceleration (B = .145, t = 4.969, p = 1.56x10-6, 95% CI [.087, .202]). Contrary to expectation, an interaction emerged showing higher neighborhood educational opportunity was associated with lower gestational age acceleration at birth for neonates with mothers living in moderate to high HI (B = -.048, t = -2.08, p = .03, 95% CI [-.092, -.002]). Female neonates showed higher gestational age acceleration at birth compared to males. However, within males, being born into neighborhoods with higher social and economic opportunity was associated with higher gestational age acceleration.

CONCLUSION

Prenatal HI and neighborhood qualities may affect gestational age acceleration at birth. Therefore, policy makers should consider neighborhood qualities as one opportunity to mitigate prenatal developmental effects of HI.

Hypermethylation of BMPR2 and TGF-β Promoter Regions in Tibetan Patients with High-Altitude Polycythemia at Extreme Altitude

Although the expression of many genes is associated with adaptation to high-altitude hypoxic environments, the role of epigenetics in the response to this harsh environmental stress is currently unclear. We explored whether abnormal DNA promoter methylation levels of six genes, namely, ABCA1, SOD2, AKT1, VEGFR2, TGF-β, and BMPR2, affect the occurrence and development of high-altitude polycythemia (HAPC) in Tibetans. The methylation levels of HAPC and the control group of 130 Tibetans from very high altitudes (> 4500 m) were examined using quantitative methylation-specific real-time PCR (QMSP). Depending on the type of data, the Pearson chi-square test, Wilcoxon rank-sum test, and Fisher exact test were used to assess the differences between the two groups. The correlation between the methylation levels of each gene and the hemoglobin content was explored using a linear mixed model. Our experiment revealed that the methylation levels of the TGF-β and BMPR2 genes differed significantly in the two groups (p < 0.05) and linear mixed model analysis showed that the correlation between the hemoglobin and methylation of ABCA1, TGF-β, and BMPR2 was statistically significant (p < 0.05). Our study suggests that levels of TGF-β and BMPR2 methylation are associated with the occurrence of HAPC in extreme-altitude Tibetan populations among 6 selected genes. Epigenetics may be involved in the pathogenesis of HAPC, and future experiments could combine gene and protein levels to verify the diagnostic value of TGF-β and BMPR2 methylation levels in HAPC.

Cumulative Stress Across the Life Course and Biological Aging in Adulthood

OBJECTIVE

Psychosocial stressors have been linked with accelerated biological aging in adults; however, few studies have examined stressors across the life course in relation to biological aging.

METHODS

In 359 individuals (57% White, 34% Black) from the Child Health and Development Studies Disparities study, economic (income, education, financial strain), social (parent-child relations, caretaker responsibilities) and traumatic (death of a sibling or child, violence exposure) stressors were assessed at multiple time points (birth and ages 9, 15, and 50 years). Experiences of major discrimination were assessed at age 50. Life period stress scores were then assessed as childhood (birth-age 15 years) and adulthood (age 50 years). At age 50 years, participants provided blood samples, and DNA methylation was assessed with the EPIC BeadChip. Epigenetic age was estimated using six epigenetic clocks (Horvath, Hannum, Skin and Blood age, PhenoAge, GrimAge, Dunedin Pace of Aging). Age acceleration was determined using residuals from regressing chronologic age on each of the epigenetic age metrics. Telomere length was assessed using the quantitative polymerase chain reaction-based methods.

RESULTS

In linear regression models adjusted for race and gender, total life stress, and childhood and adult stress independently predicted accelerated aging based on GrimAge and faster pace of aging based on the DunedinPace. Associations were attenuated after adjusting for smoking status. In sex-stratified analyses, greater childhood stress was associated with accelerated epigenetic aging among women but not men. No associations were noted with telomere length.

CONCLUSIONS

We found that cumulative stressors across the life course were associated with accelerated epigenetic age, with differences by sex (e.g., accelerated among women). Further research of this association in large and diverse samples is needed.

Computational deconvolution of DNA methylation data from mixed DNA samples

In this review, we provide a comprehensive overview of the different computational tools that have been published for the deconvolution of bulk DNA methylation (DNAm) data. Here, deconvolution refers to the estimation of cell-type proportions that constitute a mixed sample. The paper reviews and compares 25 deconvolution methods (supervised, unsupervised or hybrid) developed between 2012 and 2023 and compares the strengths and limitations of each approach. Moreover, in this study, we describe the impact of the platform used for the generation of methylation data (including microarrays and sequencing), the applied data pre-processing steps and the used reference dataset on the deconvolution performance. Next to reference-based methods, we also examine methods that require only partial reference datasets or require no reference set at all. In this review, we provide guidelines for the use of specific methods dependent on the DNA methylation data type and data availability.

Reconstructing DNA methylation maps of ancient populations

Studying premortem DNA methylation from ancient DNA (aDNA) provides a proxy for ancient gene activity patterns, and hence valuable information on evolutionary changes in gene regulation. Due to statistical limitations, current methods to reconstruct aDNA methylation maps are constrained to high-coverage shotgun samples, which comprise a small minority of available ancient samples. Most samples are sequenced using in-situ hybridization capture sequencing which targets a predefined set of genomic positions. Here, we develop methods to reconstruct aDNA methylation maps of samples that were not sequenced using high-coverage shotgun sequencing, by way of pooling together individuals to obtain a DNA methylation map that is characteristic of a population. We show that the resulting DNA methylation maps capture meaningful biological information and allow for the detection of differential methylation across populations. We offer guidelines on how to carry out comparative studies involving ancient populations, and how to control the rate of falsely discovered differentially methylated regions. The ability to reconstruct DNA methylation maps of past populations allows for the development of a whole new frontier in paleoepigenetic research, tracing DNA methylation changes throughout human history, using data from thousands of ancient samples.

Living in a low socioeconomic status neighbourhood is associated with lower cumulative ongoing pregnancy rate after IVF treatment

RESEARCH QUESTION

Does an association exist between neighbourhood socioeconomic status (SES) and the cumulative rate of ongoing pregnancies after 2.5 years of IVF treatment?

DESIGN

A retrospective observational study involving 2669 couples who underwent IVF or IVF and intracytoplasmic sperm injection treatment between 2006 and 2020. Neighbourhood SES for each couple was determined based on their residential postal code. Subsequently, SES was categorized into low (p80). Multivariable binary logistic regression analyses were conducted, with the cumulative ongoing pregnancy within 2.5 years as the outcome variable. The SES category (reference category: high), female age (reference category: 32-36 years), body mass index (reference category: 23-25 kg/m2), smoking status (yes/no), number of oocytes after the first ovarian stimulation, embryos usable for transfer or cryopreservation after the first cycle, duration of subfertility before treatment and insemination type were used as covariates.

RESULTS

A variation in ongoing pregnancy rates was observed among SES groups after the first fresh embryo transfer. No difference was found in the median number of IVF treatment cycles carried out. The cumulative ongoing pregnancy rates differed significantly between SES groups (low: 44%; medium: 51%; high: 56%; P < 0.001). Low neighbourhood SES was associated with significantly lower odds for achieving an ongoing pregnancy within 2.5 years (OR 0.66, 95% CI 0.52 to 0.84, P < 0.001).

CONCLUSION

Low neighbourhood SES compared with high neighbourhood SES is associated with reducing odds of achieving an ongoing pregnancy within 2.5 years of IVF treatment.

Epigenetic and inflammatory markers in older adults with cancer: A Young International Society of Geriatric Oncology narrative review

The number of adults aged ≥ 65 years with cancer is rapidly increasing. Older adults with cancer are susceptible to treatment-related acute and chronic adverse events, resulting in loss of independence, reduction in physical function, and decreased quality of life. Nevertheless, evidence-based interventions to prevent or treat acute and chronic adverse events in older adults with cancer are limited. Several promising blood-based biomarkers related to inflammation and epigenetic modifications are available to identify older adults with cancer who are at increased risk of accelerated aging and physical, functional, and cognitive impairments caused by the cancer and its treatment. Inflammatory changes and epigenetic modifications can be reversible and targeted by lifestyle changes and interventions. Here we discuss ways in which changes in inflammatory and epigenetic pathways influence the aging process and how these pathways can be targeted by interventions aimed at reducing inflammation and aging-associated biological markers. As the number of older adults with cancer entering survivorship continues to increase, it is becoming progressively more important to understand ways in which the benefit from treatment can be enhanced while reducing the effects of accelerated aging.

Sex-based differences in placental DNA methylation profiles related to gestational age: an NIH ECHO meta-analysis

The placenta undergoes many changes throughout gestation to support the evolving needs of the foetus. There is also a growing appreciation that male and female foetuses develop differently in utero, with unique epigenetic changes in placental tissue. Here, we report meta-analysed sex-specific associations between gestational age and placental DNA methylation from four cohorts in the National Institutes of Health (NIH) Environmental influences on Child Health Outcomes (ECHO) Programme (355 females/419 males, gestational ages 23-42 weeks). We identified 407 cytosine-guanine dinucleotides (CpGs) in females and 794 in males where placental methylation levels were associated with gestational age. After cell-type adjustment, 55 CpGs in females and 826 in males were significant. These were enriched for biological processes critical to the immune system in females and transmembrane transport in males. Our findings are distinct between the sexes: in females, associations with gestational age are largely explained by differences in placental cellular composition, whereas in males, gestational age is directly associated with numerous alterations in methylation levels.

Age-related promoter-switch regulates Runx1 expression in adult rat hearts

BACKGROUND

Runt-related transcription factor-1 (RUNX1), a key member of the core-binding factor family of transcription factors, has emerged as a novel therapeutic target for cardiovascular disease. There is an urgent need to fully understand the expression pattern of Runx1 in the heart and the mechanisms by which it is controlled under normal conditions and in response to disease. The expression of Runx1 is regulated at the transcriptional level by two promoters designated P1 and P2. Alternative usage of these two promoters creates differential mRNA transcripts diversified in distribution and translational potential. While the significance of P1/P2 promoter-switch in the transcriptional control of Runx1 has been highlighted in the embryogenic process, very little is known about the level of P1- and P2-specific transcripts in adult hearts, and the underlying mechanisms controlling the promoter-switch.

METHODS

To amplify P1/P2 specific sequences in the heart, we used two different sense primers complementary to either P1 or P2 5'-regions to monitor the expression of P1/P2 transcripts. DNA methylation levels were assessed at the Runx1 promoter regions. Rats were grouped by age.

RESULTS

The expression levels of both P1- and P2-derived Runx1 transcripts were decreased in older rats when compared with that in young adults, paralleled with an age-dependent decline in Runx1 protein level. Furthermore, older rats demonstrated a higher degree of DNA methylation at Runx1 promoter regions. Alternative promoter usage was observed in hearts with increased age, as reflected by altered P1:P2 mRNA ratio.

CONCLUSION

Our data demonstrate that the expression of Runx1 in the heart is age-dependent and underscore the importance of gene methylation in the promoter-mediated transcriptional control of Runx1, thereby providing new insights to the role of epigenetic regulation in the heart.

Methods for mediation analysis with high-dimensional DNA methylation data: Possible choices and comparisons

Epigenetic researchers often evaluate DNA methylation as a potential mediator of the effect of social/environmental exposures on a health outcome. Modern statistical methods for jointly evaluating many mediators have not been widely adopted. We compare seven methods for high-dimensional mediation analysis with continuous outcomes through both diverse simulations and analysis of DNAm data from a large multi-ethnic cohort in the United States, while providing an R package for their seamless implementation and adoption. Among the considered choices, the best-performing methods for detecting active mediators in simulations are the Bayesian sparse linear mixed model (BSLMM) and high-dimensional mediation analysis (HDMA); while the preferred methods for estimating the global mediation effect are high-dimensional linear mediation analysis (HILMA) and principal component mediation analysis (PCMA). We provide guidelines for epigenetic researchers on choosing the best method in practice and offer suggestions for future methodological development.

Stress and DNA Methylation of Blood Leukocytes among Pregnant Latina Women

Latinas experience physical and psychological stressors in pregnancy leading to increased morbidity and higher risk for adverse birth outcomes. Epigenetic changes, including DNA methylation (DNAm), have been proposed as markers to create more refined risk stratification, yet few of these studies have examined these changes in Latinas. We conducted a secondary analysis of stored blood leukocytes of Latina women (n = 58) enrolled in a larger National Institutes of Health funded R01 project (2011-2016). We examined DNAm on eight candidate stress genes to compare physically and psychologically stressed participants to healthy (low stress) participants. We found unique CpGs that were differentially methylated in stressed women early- and mid-pregnancy compared to the healthy group, though none remained significant after FDR correction. Both physical and psychological stress were associated with hypomethylation at two consecutive CpG sites on NR3C1 in early pregnancy and one CpG site on NR3C1 in mid-pregnancy before adjustment. Stress was also associated with hypomethylation at two CpG sites on FKBP5 in early and mid-pregnancy but were no longer significant after FDR adjustment. Though we did not find statistically significant differences in DNAm during pregnancy between stressed and healthy women in this sample, signals were consistent with previous findings. Future work in larger samples should further examine the associations between stress and DNAm in pregnancy as this mechanism may explain underlying perinatal health inequities.

A roadmap for social determinants of health and biological nursing research in the National Institute of Nursing Research 2022-2026 Strategic Plan: Optimizing health and advancing health equity using antiracist framing

BACKGROUND

Health equity is essential for improving the well-being of all individuals and groups, and research remains a critical element for understanding barriers to health equity. While considering how to best support research that acknowledges current health challenges, it is crucial to understand the role of social justice frameworks within health equity research and the contributions of minoritized researchers. Additionally, there should be an increased understanding of the influence of social determinants of health on biological mechanisms.

PURPOSE

Biological health equity research seeks to understand and address health disparities among historically excluded populations.

DISCUSSION

While there are examples of studies in this area led by minoritized researchers, some individuals and groups remain understudied due to underfunding. Research within minoritized populations must be prioritized to authentically achieve health equity. Furthermore, there should be increased funding from National Institutes of Health to support minoritized researchers working in this area.

The application of epiphenotyping approaches to DNA methylation array studies of the human placenta

BACKGROUND

Genome-wide DNA methylation (DNAme) profiling of the placenta with Illumina Infinium Methylation bead arrays is often used to explore the connections between in utero exposures, placental pathology, and fetal development. However, many technical and biological factors can lead to signals of DNAme variation between samples and between cohorts, and understanding and accounting for these factors is essential to ensure meaningful and replicable data analysis. Recently, "epiphenotyping" approaches have been developed whereby DNAme data can be used to impute information about phenotypic variables such as gestational age, sex, cell composition, and ancestry. These epiphenotypes offer avenues to compare phenotypic data across cohorts, and to understand how phenotypic variables relate to DNAme variability. However, the relationships between placental epiphenotyping variables and other technical and biological variables, and their application to downstream epigenome analyses, have not been well studied.

RESULTS

Using DNAme data from 204 placentas across three cohorts, we applied the PlaNET R package to estimate epiphenotypes gestational age, ancestry, and cell composition in these samples. PlaNET ancestry estimates were highly correlated with independent polymorphic ancestry-informative markers, and epigenetic gestational age, on average, was estimated within 4 days of reported gestational age, underscoring the accuracy of these tools. Cell composition estimates varied both within and between cohorts, as well as over very long placental processing times. Interestingly, the ratio of cytotrophoblast to syncytiotrophoblast proportion decreased with increasing gestational age, and differed slightly by both maternal ethnicity (lower in white vs. non-white) and genetic ancestry (lower in higher probability European ancestry). The cohort of origin and cytotrophoblast proportion were the largest drivers of DNAme variation in this dataset, based on their associations with the first principal component.

CONCLUSIONS

This work confirms that cohort, array (technical) batch, cell type proportion, self-reported ethnicity, genetic ancestry, and biological sex are important variables to consider in any analyses of Illumina DNAme data. We further demonstrate the specific utility of epiphenotyping tools developed for use with placental DNAme data, and show that these variables (i) provide an independent check of clinically obtained data and (ii) provide a robust approach to compare variables across different datasets. Finally, we present a general framework for the processing and analysis of placental DNAme data, integrating the epiphenotype variables discussed here.

The Epigenetic Legacy of Maternal Protein Restriction: Renal Ptger1 DNA Methylation Changes in Hypertensive Rat Offspring

Nutrient imbalances during gestation are a risk factor for hypertension in offspring. Although the effects of prenatal nutritional deficiency on the development of hypertension and cardiovascular diseases in adulthood have been extensively documented, its underlying mechanisms remain poorly understood. In this study, we aimed to elucidate the precise role and functional significance of epigenetic modifications in the pathogenesis of hypertension. To this end, we integrated methylome and transcriptome data to identify potential salt-sensitive hypertension genes using the kidneys of stroke-prone spontaneously hypertensive rat (SHRSP) pups exposed to a low-protein diet throughout their fetal life. Maternal protein restriction during gestation led to a positive correlation between DNA hypermethylation of the renal prostaglandin E receptor 1 (Ptger1) CpG island and high mRNA expression of Ptger1 in offspring, which is consistently conserved. Furthermore, post-weaning low-protein or high-protein diets modified the Ptger1 DNA hypermethylation caused by fetal malnutrition. Here, we show that this epigenetic variation in Ptger1 is linked to disease susceptibility established during fetal stages and could be reprogrammed by manipulating the postnatal diet. Thus, our findings clarify the developmental origins connecting the maternal nutritional environment and potential epigenetic biomarkers for offspring hypertension. These findings shed light on hypertension prevention and prospective therapeutic strategies.

Translational Epidemiology: Genetic Ancestry in Breast Cancer: What Is the Role of Genetic Ancestry and Socioeconomic Status in Triple-Negative Breast Cancer?

Racial/ethnic and socioeconomic disparities seen in triple-negative breast cancer (TNBC) have prompted questions regarding the role of genetic ancestry in breast cancer (BC) subtype development, tumor biology, and ultimately prognosis. The causes of disparities in TNBC are influenced greatly by both sociopolitical factors and genetic ancestry, and now, the potential genomic underpinnings of social factors. To comprehensively understand disparities in TNBC, it is critical to take a translational epidemiologic approach that takes into account genomic and non-genomic factors. Understanding the interplay between genetic ancestry and social genomics and their proportional influence on outcomes can guide our priorities for screening, diagnosis, and interventions for this aggressive BC subtype.

Parallel shift of DNA methylation and gene expression toward the mean in mouse spleen with aging

Age-associated DNA-methylation drift (AMD) manifests itself in two ways in mammals: global decrease (hypomethylation) and local increase of DNA methylation (hypermethylation). To comprehend the principle behind this bidirectional AMD, we studied methylation states of spatially clustered CpG dinucleotides in mouse splenic DNA using reduced-representation-bisulfite-sequencing (RRBS). The mean methylation levels of whole CpGs declined with age. Promoter-resident CpGs, generally weakly methylated (<5%) in young mice, became hypermethylated in old mice, whereas CpGs in gene-body and intergenic regions, initially moderately (~33%) and extensively (>80%) methylated, respectively, were hypomethylated in the old. Chromosome-wise analysis of methylation revealed that inter-individual heterogeneities increase with age. The density of nearby CpGs was used to classify individual CpGs, which found hypermethylation in CpG-rich regions and hypomethylation in CpG-poor regions. When genomic regions were grouped by methylation level, high-methylation regions tended to become hypomethylated whereas low-methylation regions tended to become hypermethylated, regardless of genomic structure/function. Data analysis revealed that while methylation level and CpG density were interdependent, methylation level was a better predictor of the AMD pattern representing a shift toward the mean. Further analysis of gene-expression data showed a decrease in the expression of highly-expressed genes and an increase in the expression of lowly-expressed genes with age. This shift towards the mean in gene-expression changes was correlated with that of methylation changes, indicating a potential link between the two age-associated changes. Our findings suggest that age-associated hyper- and hypomethylation events are stochastic and attributed to malfunctioning intrinsic mechanisms for methylation maintenance in low- and high-methylation regions, respectively.

DNA Methylation Signatures of Response to Conventional Synthetic and Biologic Disease-Modifying Antirheumatic Drugs (DMARDs) in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a complex condition that displays heterogeneity in disease severity and response to standard treatments between patients. Failure rates for conventional, target synthetic, and biologic disease-modifying rheumatic drugs (DMARDs) are significant. Although there are models for predicting patient response, they have limited accuracy, require replication/validation, or for samples to be obtained through a synovial biopsy. Thus, currently, there are no prediction methods approved for routine clinical use. Previous research has shown that genetics and environmental factors alone cannot explain the differences in response between patients. Recent studies have demonstrated that deoxyribonucleic acid (DNA) methylation plays an important role in the pathogenesis and disease progression of RA. Importantly, specific DNA methylation profiles associated with response to conventional, target synthetic, and biologic DMARDs have been found in the blood of RA patients and could potentially function as predictive biomarkers. This review will summarize and evaluate the evidence for DNA methylation signatures in treatment response mainly in blood but also learn from the progress made in the diseased tissue in cancer in comparison to RA and autoimmune diseases. We will discuss the benefits and challenges of using DNA methylation signatures as predictive markers and the potential for future progress in this area.

Conceptualizing the Mechanisms of Social Determinants of Health: A Heuristic Framework to Inform Future Directions for Mitigation

Policy Points A large body of scientific work examines the mechanisms through which social determinants of health (SDOH) shape health inequities. However, the nuances described in the literature are infrequently reflected in the applied frameworks that inform health policy and programming. We synthesize extant SDOH research into a heuristic framework that provides policymakers, practitioners, and researchers with a customizable template for conceptualizing and operationalizing key mechanisms that represent intervention opportunities for mitigating the impact of harmful SDOH. In light of scarce existing SDOH mitigation strategies, the framework addresses an important research-to-practice translation gap and missed opportunity for advancing health equity.

CONTEXT

The reduction of health inequities is a broad and interdisciplinary endeavor with implications for policy, research, and practice. Health inequities are most often understood as associated with the social determinants of health (SDOH). However, policy and programmatic frameworks for mitigation often rely on broad SDOH domains, without sufficient attention to the operating mechanisms, and effective SDOH mitigation strategies remain scarce. To expand the cadre of effective SDOH mitigation strategies, a practical, heuristic framework for policymakers, practitioners, and researchers is needed that serves as a roadmap for conceptualizing and targeting the key mechanisms of SDOH influence.

METHODS

We conduct a critical review of the extant conceptual and empirical SDOH literature to identify unifying principles of SDOH mechanisms and to synthesize an integrated framework for conceptualizing such mechanisms.

FINDINGS

We highlight eight unifying principles of SDOH mechanisms that emerge from landmark SDOH research. Building on these principles, we introduce and apply a conceptual model that synthesizes key SDOH mechanisms into one organizing, heuristic framework that provides policymakers, practitioners, and researchers with a customizable template for conceptualizing and operationalizing the key SDOH mechanisms that represent intervention opportunities to maximize potential impact for mitigating a given health inequity.

CONCLUSIONS

Our synthesis of the extant SDOH research into a heuristic framework addresses a scarcity of peer-reviewed organizing frameworks of SDOH mechanisms designed to inform practice. The framework represents a practical tool to facilitate the translation of scholarly SDOH work into evidence-based and targeted policy and programming. Such tools designed to close the research-to-practice translation gap for effective SDOH mitigation are sorely needed, given that health inequities in the United States and in many other parts of the world have widened over the past two decades.

Maternal-infant interaction quality is associated with child NR3C1 CpG site methylation at 7 years of age

OBJECTIVE

Infancy is both a critical window for hypothalamic-pituitary-adrenal (HPA) axis development, and a sensitive period for social-emotional influences. We hypothesized that the social-emotional quality of maternal-infant interactions are associated with methylation of HPA-axis gene NR3C1 later in childhood.

METHODS

Using a subsample of 114 mother-infant pairs from the Avon Longitudinal Study of Parents and Children (ALSPAC), linear regression models were created to predict variance in methylation of seven selected CpG sites from NR3C1 in whole blood at age 7 years, including the main predictor variable of the first principal component score of observed maternal-infant interaction quality (derived from the Thorpe Interaction Measure at 12 months of age) and covariates of cell-type proportion, maternal financial difficulties and marital status at 8 months postnatal, child birthweight, and sex.

RESULTS

CpG site cg27122725 methylation was negatively associated with warmer, more positive maternal interaction with her infant (β = 0.19, p = .02, q = 0.13). In sensitivity analyses, the second highest quartile of maternal behavior (neutral, hesitant behavior) was positively associated with cg12466613 methylation. The other five CpG sites were not significantly associated with maternal-infant interaction quality.

CONCLUSIONS

Narrow individual variation of maternal interaction with her infant is associated with childhood methylation of two CpG sites on NR3C1 that may be particularly sensitive to environmental influences. Infancy may be a sensitive period for even small influences from the social-emotional environment on the epigenetic determinants of HPA-axis function.

DNA methylation dynamics during pregnancy

Pregnancy is a state of multiple physiological adaptations. Since methylation of DNA is an epigenetic mechanism that regulates gene expression and contributes to adaptive phenotypic variations, we investigated methylation changes in maternal blood of a longitudinal cohort of pregnant women from the first trimester of gestation to the third. Interestingly, during pregnancy, we found a gain of methylation in genes involved in morphogenesis, such as ezrin, while we identified a loss of methylation in genes promoting maternal-infant bonding (AVP and PPP1R1B). Together, our results provide insights into the biological mechanisms underlying physiological adaptations during pregnancy.

Neighborhood Disadvantage and Breast Cancer-Specific Survival

Importance

Neighborhood-level disadvantage is an important factor in the creation and persistence of underresourced neighborhoods with an undue burden of disparate breast cancer-specific survival outcomes. Although studies have evaluated neighborhood-level disadvantage and breast cancer-specific survival after accounting for individual-level socioeconomic status (SES) in large national cancer databases, these studies are limited by age, socioeconomic, and racial and ethnic diversity.

Objective

To investigate neighborhood SES (using a validated comprehensive composite measure) and breast cancer-specific survival in a majority-minority population.

Design, Setting, and Participants

This retrospective multi-institutional cohort study included patients with stage I to IV breast cancer treated at a National Cancer Institute-designated cancer center and sister safety-net hospital from January 10, 2007, to September 9, 2016. Mean (SD) follow-up time was 60.3 (41.4) months. Data analysis was performed from March 2022 to March 2023.

Exposures

Neighborhood SES was measured using the Area Deprivation Index (tertiles), a validated comprehensive composite measure of neighborhood SES.

Main Outcomes and Measures

The primary outcome was breast cancer-specific survival. Random effects frailty models for breast cancer-specific survival were performed controlling for individual-level sociodemographic, comorbidity, breast cancer risk factor, access to care, tumor, and National Comprehensive Cancer Network guideline-concordant treatment characteristics. The Area Deprivation Index was calculated for each patient at the census block group level and categorized into tertiles (T1-T3).

Results

A total of 5027 women with breast cancer were included: 55.8% were Hispanic, 17.5% were non-Hispanic Black, and 27.0% were non-Hispanic White. Mean (SD) age was 55.5 (11.7) years. Women living in the most disadvantaged neighborhoods (T3) had shorter breast cancer-specific survival compared with those living in the most advantaged neighborhoods (T1) after controlling for individual-level sociodemographic, comorbidity, breast cancer risk factor, access to care, tumor, and National Comprehensive Cancer Network guideline-concordant treatment characteristics (T3 vs T1: hazard ratio, 1.29; 95% CI, 1.01-1.65; P < .04).

Conclusions and Relevance

In this cohort study, a shorter breast cancer-specific survival in women from disadvantaged neighborhoods compared with advantaged neighborhoods was identified, even after controlling for individual-level sociodemographic, comorbidity, breast cancer risk factor, access to care, tumor, and National Comprehensive Cancer Network guideline-concordant treatment characteristics. The findings suggest potential unaccounted mechanisms, including unmeasured social determinants of health and access to care measures. This study also lays the foundation for future research to evaluate whether social adversity from living in a disadvantaged neighborhood is associated with more aggressive tumor biologic factors, and ultimately shorter breast cancer-specific survival, through social genomic and/or epigenomic alterations.

DNA methylation as a potential mediator of the association between indoor air pollution and neurodevelopmental delay in a South African birth cohort

BACKGROUND

Exposure to indoor air pollution during pregnancy has been linked to neurodevelopmental delay in toddlers. Epigenetic modification, particularly DNA methylation (DNAm), may explain this link. In this study, we employed three high-dimensional mediation analysis methods (HIMA, DACT, and gHMA) followed by causal mediation analysis to identify differentially methylated CpG sites and genes that mediate the association between indoor air pollution and neurodevelopmental delay. Analyses were performed using data from 142 mother to child pairs from a South African birth cohort, the Drakenstein Child Health Study. DNAm from cord blood was measured using the Infinium MethylationEPIC and HumanMethylation450 arrays. Neurodevelopment was assessed at age 2 years using the Bayley Scores of Infant and Toddler Development, 3rd edition across four domains (cognitive development, general adaptive behavior, language, and motor function). Particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀) was measured inside participants' homes during the second trimester of pregnancy.

RESULTS

A total of 29 CpG sites and 4 genes (GOPC, RP11-74K11.1, DYRK1A, RNMT) were identified as significant mediators of the association between PM₁₀ and cognitive neurodevelopment. The estimated proportion mediated (95%-confidence interval) ranged from 0.29 [0.01, 0.86] for cg00694520 to 0.54 [0.11, 1.56] for cg05023582.

CONCLUSIONS

Our findings suggest that DNAm may mediate the association between prenatal PM₁₀ exposure and cognitive neurodevelopment. DYRK1A and several genes that our CpG sites mapped to, including CNKSR1, IPO13, IFNGR1, LONP2, and CDH1, are associated with biological pathways implicated in cognitive neurodevelopment and three of our identified CpG sites (cg23560546 [DAPL1], cg22572779 [C6orf218], cg15000966 [NT5C]) have been previously associated with fetal brain development. These findings are novel and add to the limited literature investigating the relationship between indoor air pollution, DNAm, and neurodevelopment, particularly in low- and middle-income country settings and non-white populations.

Methods for Mediation Analysis with High-Dimensional DNA Methylation Data: Possible Choices and Comparison

Epigenetic researchers often evaluate DNA methylation as a mediator between social/environmental exposures and disease, but modern statistical methods for jointly evaluating many mediators have not been widely adopted. We compare seven methods for high-dimensional mediation analysis with continuous outcomes through both diverse simulations and analysis of DNAm data from a large national cohort in the United States, while providing an R package for their implementation. Among the considered choices, the best-performing methods for detecting active mediators in simulations are the Bayesian sparse linear mixed model by Song et al. (2020) and high-dimensional mediation analysis by Gao et al. (2019); while the superior methods for estimating the global mediation effect are high-dimensional linear mediation analysis by Zhou et al. (2021) and principal component mediation analysis by Huang and Pan (2016). We provide guidelines for epigenetic researchers on choosing the best method in practice and offer suggestions for future methodological development.

Effect of MAOA DNA Methylation on Human in Vivo Protein Expression Measured by [11C]harmine Positron Emission Tomography

BACKGROUND

Epigenetic modifications like DNA methylation are understood as an intermediary between environmental factors and neurobiology. Cerebral monoamine oxidase A (MAO-A) levels are altered in depression, as are DNA methylation levels within the MAOA gene, particularly in the promoter/exon I/intron I region. An effect of MAOA methylation on peripheral protein expression was shown, but the extent to which methylation affects brain MAO-A levels is not fully understood.

METHODS

Here, the influence of MAOA promoter/exon I/intron I region DNA methylation on global MAO-A distribution volume (VT), an index of MAO-A density, was assessed via [11C]harmine positron emission tomography in 22 patients (14 females) suffering from seasonal affective disorder and 30 healthy controls (17 females).

RESULTS

No significant influence of MAOA DNA methylation on global MAO-A VT was found, despite correction for health status, sex, season, and MAOA variable number of tandem repeat genotype. However, season affected average methylation in women, with higher levels in spring and summer (Puncorr = .03). We thus did not find evidence for an effect of MAOA DNA methylation on brain MAO-A VT.

CONCLUSIONS

In contrast to a previous study demonstrating an effect of methylation of a MAOA promoter region located further 5' on brain MAO-A, MAOA methylation of the region assessed here appears to affect brain protein levels to a limited extent at most. The observed effect of season on methylation levels is in accordance with extensive evidence for seasonal effects within the serotonergic system.

CLINICALTRIALS.GOV IDENTIFIER

NCT02582398 (https://clinicaltrials.gov/ct2/show/NCT02582398).

Inter-Individual Variation in DNA Methylation Patterns across Two Tissues and Leukocytes in Mature Brahman Cattle

Quantifying the natural inter-individual variation in DNA methylation patterns is important for identifying its contribution to phenotypic variation, but also for understanding how the environment affects variability, and for incorporation into statistical analyses. The inter-individual variation in DNA methylation patterns in female cattle and the effect that a prenatal stressor has on such variability have yet to be quantified. Thus, the objective of this study was to utilize methylation data from mature Brahman females to quantify the inter-individual variation in DNA methylation. Pregnant Brahman cows were transported for 2 h durations at days 60 ± 5; 80 ± 5; 100 ± 5; 120 ± 5; and 140 ± 5 of gestation. A non-transport group was maintained as a control. Leukocytes, amygdala, and anterior pituitary glands were harvested from eight cows born from the non-transport group (Control) and six from the transport group (PNS) at 5 years of age. The DNA harvested from the anterior pituitary contained the greatest variability in DNA methylation of cytosine-phosphate-guanine (mCpG) sites from both the PNS and Control groups, and the amygdala had the least. Numerous variable mCpG sites were associated with retrotransposable elements and highly repetitive regions of the genome. Some of the genomic features that had high variation in DNA methylation are involved in immune responses, signaling, responses to stimuli, and metabolic processes. The small overlap of highly variable CpG sites and features between tissues and leukocytes supports the role of variable DNA methylation in regulating tissue-specific gene expression. Many of the CpG sites that exhibited high variability in DNA methylation were common between the PNS and Control groups within a tissue, but there was little overlap in genomic features with high variability. The interaction between the prenatal environment and the genome could be responsible for the differences in location of the variable DNA methylation.

Associations of peripheral blood DNA methylation and estimated monocyte proportion differences during infancy with toddler attachment style

Attachment is a motivational system promoting felt security to a caregiver resulting in a persistent internal working model of interpersonal behavior. Attachment styles are developed in early social environments and predict future health and development outcomes with potential biological signatures, such as epigenetic modifications like DNA methylation (DNAm). Thus, we hypothesized infant DNAm would associate with toddler attachment styles. An epigenome-wide association study (EWAS) of blood DNAm from 3-month-old infants was regressed onto children's attachment style from the Strange Situation Procedure at 22-months at multiple DNAm Cytosine-phosphate-Guanine (CpG) sites. The 26 identified CpGs associated with proinflammatory immune phenotypes and cognitive development. In post-hoc analyses, only maternal cognitive-growth fostering, encouraging intellectual exploration, contributed. For disorganized children, DNAm-derived cell-type proportions estimated higher monocytes -cells in immune responses hypothesized to increase with early adversity. Collectively, these findings suggested the potential biological embedding of both adverse and advantageous social environments as early as 3-months-old.

Beadchip technology to detect DNA methylation in mouse faithfully recapitulates whole-genome bisulfite sequencing

Aim: To facilitate wide-scale implementation of Illumina Mouse Methylation BeadChip (MMB) technology, array-based measurement of cytosine methylation was compared with the gold-standard assessment of DNA methylation by whole-genome bisulfite sequencing (WGBS). Methods: DNA methylation across two mouse strains (C57B6 and C3H) and both sexes was assessed using the MMB and compared with previously existing deep-coverage WGBS of mice of the same strain and sex. Results & conclusion: The findings demonstrated that 93.3-99.2% of sites had similar measurements of methylation across technologies and that differentially methylated cytosines and regions identified by each technology overlap and enrich for similar biological functions, suggesting that the MMB faithfully recapitulates the findings of WGBS.

Epigenome-Wide Analysis of DNA Methylation and Optimism in Women and Men

OBJECTIVE

Higher optimism is associated with reduced mortality and a lower risk of age-related chronic diseases. DNA methylation (DNAm) may provide insight into mechanisms underlying these relationships. We hypothesized that DNAm would differ among older individuals who are more versus less optimistic.

METHODS

Using cross-sectional data from two population-based cohorts of women with diverse races/ethnicities ( n = 3816) and men (only White, n = 667), we investigated the associations of optimism with epigenome-wide leukocyte DNAm. Random-effects meta-analyses were subsequently used to pool the individual results. Significantly differentially methylated cytosine-phosphate-guanines (CpGs) were identified by the "number of independent degrees of freedom" approach: effective degrees of freedom correction using the number of principal components (PCs), explaining >95% of the variation of the DNAm data (PC-correction). We performed regional analyses using comb-p and pathway analyses using the Ingenuity Pathway Analysis software.

RESULTS

We found that essentially all CpGs (total probe N = 359,862) were homogeneous across sex and race/ethnicity in the DNAm-optimism association. In the single CpG site analyses based on homogeneous CpGs, we identified 13 significantly differentially methylated probes using PC-correction. We found four significantly differentially methylated regions and two significantly differentially methylated pathways. The annotated genes from the single CpG site and regional analyses are involved in psychiatric disorders, cardiovascular disease, cognitive impairment, and cancer. Identified pathways were related to cancer, and neurodevelopmental and neurodegenerative disorders.

CONCLUSION

Our findings provide new insights into possible mechanisms underlying optimism and health.

Selection of Ideal Reference Genes for Gene Expression Analysis in COVID-19 and Mucormycosis

Selection of reference genes during real-time quantitative PCR (qRT-PCR) is critical to determine accurate and reliable mRNA expression. Nonetheless, not a single study has investigated the expression stability of candidate reference genes to determine their suitability as internal controls in SARS-CoV-2 infection or COVID-19-associated mucormycosis (CAM). Using qRT-PCR, we determined expression stability of the nine most commonly used housekeeping genes, namely, TATA-box binding protein (TBP), cyclophilin (CypA), β-2-microglobulin (B2M), 18S rRNA (18S), peroxisome proliferator-activated receptor gamma (PPARG) coactivator 1 alpha (PGC-1α), glucuronidase beta (GUSB), hypoxanthine phosphoribosyltransferase 1 (HPRT-1), β-ACTIN, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in patients with COVID-19 of various severities (asymptomatic, mild, moderate, and severe) and those with CAM. We used statistical algorithms (delta-CT [threshold cycle], NormFinder, BestKeeper, GeNorm, and RefFinder) to select the most appropriate reference gene and observed that clinical severity profoundly influences expression stability of reference genes. CypA demonstrated the most consistent expression irrespective of disease severity and emerged as the most suitable reference gene in COVID-19 and CAM. Incidentally, GAPDH, the most commonly used reference gene, showed the maximum variations in expression and emerged as the least suitable. Next, we determined expression of nuclear factor erythroid 2-related factor 2 (NRF2), interleukin-6 (IL-6), and IL-15 using CypA and GAPDH as internal controls and show that CypA-normalized expression matches well with the RNA sequencing-based expression of these genes. Further, IL-6 expression correlated well with the plasma levels of IL-6 and C-reactive protein, a marker of inflammation. In conclusion, GAPDH emerged as the least suitable and CypA as the most suitable reference gene in COVID-19 and CAM. The results highlight the expression variability of housekeeping genes due to disease severity and provide a strong rationale for identification of appropriate reference genes in other chronic conditions as well. IMPORTANCE Gene expression studies are critical to develop new diagnostics, therapeutics, and prognostic modalities. However, accurate determination of expression requires data normalization with a reference gene, whose expression does not vary across different disease stages. Misidentification of a reference gene can produce inaccurate results. Unfortunately, despite the global impact of COVID-19 and an urgent unmet need for better treatment, not a single study has investigated the expression stability of housekeeping genes across the disease spectrum to determine their suitability as internal controls. Our study identifies CypA and then TBP as the two most suitable reference genes for COVID-19 and CAM. Further, GAPDH, the most commonly used reference gene in COVID-19 studies, turned out to be the least suitable. This work fills an important gap in the field and promises to facilitate determination of an accurate expression of genes to catalyze development of novel molecular diagnostics and therapeutics for improved patient care.

DNA methylation signatures as biomarkers of socioeconomic position

This review article provides a framework for the use of deoxyribonucleic acid (DNA) methylation (DNAm) biomarkers to study the biological embedding of socioeconomic position (SEP) and summarizes the latest developments in the area. It presents the emerging literature showing associations between individual- and neighborhood-level SEP exposures and DNAm across the life course. In contrast to questionnaire-based methods of assessing SEP, we suggest that DNAm biomarkers may offer an accessible metric to study questions about SEP and health outcomes, acting as a personal dosimeter of exposure. However, further work remains in standardizing SEP measures across studies and evaluating consistency across domains, tissue types, and time periods. Meta-analyses of epigenetic associations with SEP are offered as one approach to confirm the replication of DNAm loci across studies. The development of DNAm biomarkers of SEP would provide a method for examining its impact on health outcomes in a more robust way, increasing the rigor of epidemiological studies.

A narrative review of the epigenetics of post-traumatic stress disorder and post-traumatic stress disorder treatment

Epigenetic research in post-traumatic stress disorder (PTSD) is essential, given that environmental stressors and fear play such a crucial role in its development. As such, it may provide a framework for understanding individual differences in the prevalence of the disorder and in treatment response. This paper reviews the epigenetic markers associated with PTSD and its treatment, including candidate genes and epigenome-wide studies. Because the etiopathogenesis of PTSD rests heavily on learning and memory, we also draw upon animal neuroepigenetic research on the acquisition, update and erasure of fear memory, focusing on the mechanisms associated with memory reconsolidation. Reconsolidation blockade (or impairment) treatment in PTSD has been studied in clinical trials and, from a neurological perspective, may hold promise for identifying epigenetic markers of successful therapy. We conclude this paper by discussing several key considerations and challenges in epigenetic research on PTSD in humans.

The immune factors driving DNA methylation variation in human blood

Epigenetic changes are required for normal development, yet the nature and respective contribution of factors that drive epigenetic variation in humans remain to be fully characterized. Here, we assessed how the blood DNA methylome of 884 adults is affected by DNA sequence variation, age, sex and 139 factors relating to life habits and immunity. Furthermore, we investigated whether these effects are mediated or not by changes in cellular composition, measured by deep immunophenotyping. We show that DNA methylation differs substantially between naïve and memory T cells, supporting the need for adjustment on these cell-types. By doing so, we find that latent cytomegalovirus infection drives DNA methylation variation and provide further support that the increased dispersion of DNA methylation with aging is due to epigenetic drift. Finally, our results indicate that cellular composition and DNA sequence variation are the strongest predictors of DNA methylation, highlighting critical factors for medical epigenomics studies.

Targeting DNA methylation can reduce cardiac injury associated with ischemia reperfusion: One step closer to clinical translation with blood-borne assessment

Ischemia reperfusion (I/R) injury is one of the main clinical challenges for cardiac surgeons. No effective strategies or therapy targeting the molecular and cellular mechanisms to reduce I/R exists to date, despite altered gene expression and cellular metabolism/physiology. We aimed to identify whether DNA methylation, an unexplored target, can be a potential site to curb I/R-associated cell death by using the left anterior descending artery occlusion model in male Wistar rats. I/R rat heart exhibited global DNA hypermethylation with a corresponding decline in the mitochondrial genes (PGC-1α, TFAM, POLG, ND1, ND3, ND4, Cyt B, COX1, and COX2), antioxidant genes (SOD2, catalase, and Gpx2) and elevation in apoptotic genes (Casp3, Casp7, and Casp9) expression with corresponding changes in their activity, resulting in injury. Targeting global DNA methylation in I/R hearts by using its inhibitor significantly reduced the I/R-associated infarct size by 45% and improved dysferlin levels via modulating the genes involved in cell death apoptotic pathway (Casp3, Casp7, and PARP), inflammation (IL-1β, TLR4, ICAM1, and MyD88), oxidative stress (SOD1, catalase, Gpx2, and NFkB) and mitochondrial function and its regulation (MT-ND1, ND3, COX1, ATP6, PGC1α, and TFAM) in the cardiac tissue. The corresponding improvement in the genes’ function was reflected in the respective hearts via the reduction in apoptotic TUNEL positive cells and ROS levels, thereby improving myocardial architecture (H&E staining), antioxidant enzymes (SOD, catalase activity) and mitochondrial electron transport chain activities and ATP levels. The analysis of blood from the I/R animals in the presence and absence of methylation inhibition exhibited a similar pattern of changes as that observed in the cardiac tissue with respect to global DNA methylation level and its enzymes (DNMT and TET) gene expression, where the blood cardiac injury markers enzymes like LDH and CK-MB were elevated along with declined tissue levels. Based on these observations, we concluded that targeting DNA methylation to reduce the level of DNA hypermethylation can be a promising approach in ameliorating I/R injury. Additionally, the blood-borne changes reflected I/R-associated myocardial tissue alteration, making it suitable to predict I/R-linked pathology.

Chronic stress-driven glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts

Chronic environmental stress can profoundly impact cell and body function. Although the underlying mechanisms are poorly understood, epigenetics has emerged as a key link between environment and health. The genomic effects of stress are thought to be mediated by the action of glucocorticoid stress hormones, primarily cortisol in humans, which act via the glucocorticoid receptor (GR). To dissect how chronic stress-driven GR activation influences epigenetic and cell states, human fibroblasts underwent prolonged exposure to physiological stress levels of cortisol and/or a selective GR antagonist. Cortisol was found to drive robust changes in cell proliferation, migration, and morphology, which were abrogated by concomitant GR blockade. The GR-driven cell phenotypes were accompanied by widespread, yet genomic context-dependent, changes in DNA methylation and mRNA expression, including gene loci with known roles in cell proliferation and migration. These findings provide insights into how chronic stress-driven functional epigenomic patterns become established to shape key cell phenotypes.

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Physiological stress levels of cortisol drive robust changes in key cell phenotypes

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Stress-driven changes in cell phenotypes are abrogated by concomitant GR blockade

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GR activation induces functional and phenotypically relevant epigenomic changes

Identification of influential probe types in epigenetic predictions of human traits: implications for microarray design

BACKGROUND

CpG methylation levels can help to explain inter-individual differences in phenotypic traits. Few studies have explored whether identifying probe subsets based on their biological and statistical properties can maximise predictions whilst minimising array content. Variance component analyses and penalised regression (epigenetic predictors) were used to test the influence of (i) the number of probes considered, (ii) mean probe variability and (iii) methylation QTL status on the variance captured in eighteen traits by blood DNA methylation. Training and test samples comprised ≤ 4450 and ≤ 2578 unrelated individuals from Generation Scotland, respectively.

RESULTS

As the number of probes under consideration decreased, so too did the estimates from variance components and prediction analyses. Methylation QTL status and mean probe variability did not influence variance components. However, relative effect sizes were 15% larger for epigenetic predictors based on probes with known or reported methylation QTLs compared to probes without reported methylation QTLs. Relative effect sizes were 45% larger for predictors based on probes with mean Beta-values between 10 and 90% compared to those based on hypo- or hypermethylated probes (Beta-value ≤ 10% or ≥ 90%).

CONCLUSIONS

Arrays with fewer probes could reduce costs, leading to increased sample sizes for analyses. Our results show that reducing array content can restrict prediction metrics and careful attention must be given to the biological and distribution properties of CpG probes in array content selection.

Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes

DNA methylation analysis by sequencing is becoming increasingly popular, yielding methylomes at single-base pair and single-molecule resolution. It has tremendous potential for cell-type heterogeneity analysis using intrinsic read-level information. Although diverse deconvolution methods were developed to infer cell-type composition based on bulk sequencing-based methylomes, systematic evaluation has not been performed yet. Here, we thoroughly benchmark six previously published methods: Bayesian epiallele detection, DXM, PRISM, csmFinder+coMethy, ClubCpG and MethylPurify, together with two array-based methods, MeDeCom and Houseman, as a comparison group. Sequencing-based deconvolution methods consist of two main steps, informative region selection and cell-type composition estimation, thus each was individually assessed. With this elaborate evaluation, we aimed to establish which method achieves the highest performance in different scenarios of synthetic bulk samples. We found that cell-type deconvolution performance is influenced by different factors depending on the number of cell types within the mixture. Finally, we propose a best-practice deconvolution strategy for sequencing data and point out limitations that need to be handled. Array-based methods—both reference-based and reference-free—generally outperformed sequencing-based methods, despite the absence of read-level information. This implies that the current sequencing-based methods still struggle with correctly identifying cell-type-specific signals and eliminating confounding methylation patterns, which needs to be handled in future studies.

Social Factors, Epigenomics and Lupus in African American Women (SELA) Study: protocol for an observational mechanistic study examining the interplay of multiple individual and social factors on lupus outcomes in a health disparity population

Introduction

Despite the disproportional impact of SLE on historically marginalised communities, the individual and sociocultural factors underlying these health disparities remain elusive. We report the design and methods for a study aimed at identifying epigenetic biomarkers associated with racism and resiliency that affect gene function and thereby influence SLE in a health disparity population.

Methods and analysis

The Social Factors, Epigenomics and Lupus in African American Women (SELA) Study is a cross-sectional, case–control study. A total of 600 self-reported African American women will be invited to participate. All participants will respond to questionnaires that capture detailed sociodemographic and medical history, validated measures of racial discrimination, social support, as well as disease activity and damage for cases. Participants who wish will receive their genetic ancestry estimates and be involved in research. Blood samples are required to provide peripheral blood mononuclear cell counts, DNA and RNA. The primary goals of SELA are to identify variation in DNA methylation (DNAm) associated with self-reported exposure to racial discrimination and social support, to evaluate whether social DNAm sites affect gene expression, to identify the synergistic effects of social factors on DNAm changes on SLE and to develop a social factors-DNAm predictive model for disease outcomes. This study is conducted in cooperation with the Sea Island Families Project Citizen Advisory Committee.

Discussion and dissemination

SELA will respond to the pressing need to clarify the interplay and regulatory mechanism by which various positive and negative social exposures influence SLE. Results will be published and shared with patients and the community. Knowledge of the biological impact of social exposures on SLE, as informed by the results of this study, can be leveraged by advocacy efforts to develop psychosocial interventions that prevent or mitigate risk exposures, and services or interventions that promote positive exposures. Implementation of such interventions is paramount to the closure of the health disparities gap.

Alpha-synuclein overexpression induces epigenomic dysregulation of glutamate signaling and locomotor pathways

Parkinson’s disease (PD) is a neurological disorder with complex interindividual etiology that is becoming increasingly prevalent worldwide. Elevated alpha-synuclein levels can increase risk of PD and may influence epigenetic regulation of PD pathways. Here, we report genome-wide DNA methylation and hydroxymethylation alterations associated with overexpression of two PD-linked alpha-synuclein variants (wild-type and A30P) in LUHMES cells differentiated to dopaminergic neurons. Alpha-synuclein altered DNA methylation at thousands of CpGs and DNA hydroxymethylation at hundreds of CpGs in both genotypes, primarily in locomotor behavior and glutamate signaling pathway genes. In some cases, epigenetic changes were associated with transcription. SMITE network analysis incorporating H3K4me1 ChIP-seq to score DNA methylation and hydroxymethylation changes across promoters, enhancers, and gene bodies confirmed epigenetic and transcriptional deregulation of glutamate signaling modules in both genotypes. Our results identify distinct and shared impacts of alpha-synuclein variants on the epigenome, and associate alpha-synuclein with the epigenetic etiology of PD.

Epigenetic Determinants of Racial Disparity in Breast Cancer: Looking beyond Genetic Alterations

Simple Summary

A substantial disparity in breast cancer incidence and mortality exists between African American (AA) and European American (EA) women. However, the basis for these disparities is poorly understood. In this article, we describe that gene–environment interactions mediated through epigenetic modifications may play a significant role in racial disparities in BC incidence and outcomes. Our in silico analyses and an in-depth literature survey suggest that there exists a significant difference in epigenetic patterns between AA and EA women with breast cancer. Herein, we describe the environmental factors that contribute to these epigenetic changes, which may underlie the disparate racial burden in patients with breast cancer. We suggest that AA women with higher basal epigenetic changes, may have higher pre-disposition to cancer onset, and an aggressive disease course. Pre-existing racial differences in epigenetic profiles of breast tissues raises the possibility of examining these profiles for early diagnosis.

Abstract

Breast cancer (BC) is the most commonly diagnosed cancer in women. Despite advancements in BC screening, prevention, and treatment, BC incidence and mortality remain high among African American (AA) women. Compared with European American (EA) women, AA women tend to be diagnosed with more advanced and aggressive tumors and exhibit worse survival outcomes. Most studies investigating the determinants of racial disparities in BC have focused on genetic factors associated with African ancestry. However, various environmental and social stressors over an individual’s life course can also shape racial stratification in BC. These social and environmental exposures result in long-term changes in gene expression mediated by epigenetic mechanisms. Epigenetics is often portrayed as an intersection of socially patterned stress and genetic expression. The enduring nature of epigenetic changes makes them suitable for studying the effects of different environmental exposures over an individual’s life course on gene expression. The role of differential social and environmental exposures in racial disparities in BC suggests varied epigenetic profiles or signatures associated with specific BC subtypes in AA and EA women. These epigenetic profiles in EA and AA women could be used as biomarkers for early BC diagnosis and disease prognosis and may prove valuable for the development of targeted therapies for BC. This review article discusses the current state of knowledge regarding epigenetic differences between AA and EA women with BC. We also discuss the role of socio-environmental factors, including psychosocial stress, environmental toxicants, and dietary factors, in delineating the different epigenetic profiles in AA and EA patients with BC.

Evaluating the challenges and reproducibility of studies investigating DNA methylation signatures of psychological stress

Psychological stress can increase the risk of a wide range of negative health outcomes. Studies have been completed to determine if DNA methylation changes occur in the human brain because of stress and are associated with long-term effects and disease, but results have been inconsistent. Human candidate gene studies (150) and epigenome-wide association studies (67) were systematically evaluated to assess how DNA methylation is impacted by stress during the prenatal period, early childhood and adulthood. The association between DNA methylation of NR3C1 exon 1F and child maltreatment and early life adversity was well demonstrated, but other genes did not exhibit a clear association. The reproducibility of individual CpG sites in epigenome-wide association studies was also poor. However, biological pathways, including stress response, brain development and immunity, have been consistently identified across different stressors throughout the life span. Future studies would benefit from the increased sample size, longitudinal design, standardized methodology, optimal quality control, and improved statistical procedures.

Blood DNA methylation signatures are associated with social determinants of health among survivors of childhood cancer

Social epigenomics is an emerging field in which social scientist collaborate with computational biologists, especially epigeneticists, to address the underlying pathway for biological embedding of life experiences. This social epigenomics study included long-term childhood cancer survivors enrolled in the St. Jude Lifetime Cohort. DNA methylation (DNAm) data were generated using the Illumina EPIC BeadChip, and three social determinants of health (SDOH) factors were assessed: self-reported educational attainment, personal income, and an area deprivation index based on census track data. An epigenome-wide association study (EWAS) was performed to evaluate the relation between DNAm at each 5’-cytosine-phosphate-guanine-3’ (CpG) site and each SDOH factor based on multivariable linear regression models stratified by ancestry (European ancestry, n = 1,618; African ancestry, n = 258). EWAS among survivors of European ancestry identified 130 epigenome-wide significant SDOH–CpG associations (P < 9 × 10⁻⁸), 25 of which were validated in survivors of African ancestry (P < 0.05). Thirteen CpGs were associated with all three SDOH factors and resided at pleiotropic loci in cigarette smoking–related genes (e.g., CLDND1 and CPOX). After accounting for smoking and body mass index, these associations remained significant with attenuated effect sizes. Seven of 13 CpGs were associated with gene expression level based on 57 subsamples with blood RNA sequencing data available. In conclusion, DNAm signatures, many resembling the effect of tobacco use, were associated with SDOH factors among survivors of childhood cancer, thereby suggesting that biologically distal SDOH factors influence health behaviours or related factors, the epigenome, and subsequently survivors’ health.

Neighborhood characteristics and breast tumor methylation: using epigenomics to explore cancer outcome disparities

BACKGROUND

Social exposures may drive epigenetic alterations that affect racial disparities in breast cancer outcomes. This study examined the association between neighborhood-level factors and DNA methylation in non-Hispanic Black and White women diagnosed with breast cancer.

METHODS

Genome-wide DNA methylation was measured using the EPIC array in the tumor tissue of 96 women. Linear regression models were used to examine the association between nine neighborhood-level factors and methylation, regressing β values for each cytosine-phosphate guanine dinucleotide (CpG) site on neighborhood-level factors while adjusting for covariates. Neighborhood data were obtained from the Opportunity Atlas. We used a false discovery rate (FDR) threshold < 0.05, and for CpGs below this threshold, we examined interactions with race. We employed multivariable Cox proportional-hazards models to estimate whether aberrant methylation was associated with all-cause mortality.

RESULTS

26 of the CpG sites were associated with job density or college education (FDR < 0.05). Further exploration of these 26 CpG sites revealed no interactions by race, but a single probe in TMEM204 was associated with all-cause mortality.

CONCLUSION

We identified novel associations between neighborhood-level factors and the breast tumor DNA methylome. Our data are the first to show that dysregulation in neighborhood associated CpG sites may be associated with all-cause mortality. Neighborhood-level factors may contribute to differential tumor methylation in genes related to tumor progression and metastasis. This contributes to the increasing body of evidence that area-level factors (such as neighborhood characteristics) may play an important role in cancer disparities through modulation of the breast tumor epigenome.

DNA methylation across the tree of life, from micro to macro-organism

DNA methylation is a process in which methyl (CH3) groups are added to the DNA molecule. The DNA segment does not change in the sequence, but DNA methylation could alter the action of DNA. Different enzymes like DNA methyltransferases (DNMTs) take part in methylation of cytosine/adenine nucleosides in DNA. In prokaryotes, DNA methylation is performed to prevent the attack of phage and also plays a role in the chromosome replication and repair. In fungi, DNA methylation is studied to see the transcriptional changes, as in insects, the DNA methylation is not that well-known, it plays a different role like other organisms. In mammals, the DNA methylation is related to different types of cancers and plays the most important role in the placental development and abnormal DNA methylation connected with diseases like cancer, autoimmune diseases, and rheumatoid arthritis.

The Impact of Exercise on Telomere Length, DNA Methylation and Metabolic Footprints

Aging as a major risk factor influences the probability of developing cancer, cardiovascular disease and diabetes, amongst others. The underlying mechanisms of disease are still not fully understood, but research suggests that delaying the aging process could ameliorate these pathologies. A key biological process in aging is cellular senescence which is associated with several stressors such as telomere shortening or enhanced DNA methylation. Telomere length as well as DNA methylation levels can be used as biological age predictors which are able to detect excessive acceleration or deceleration of aging. Analytical methods examining aging are often not suitable, expensive, time-consuming or require a high level of technical expertise. Therefore, research focusses on combining analytical methods which have the potential to simultaneously analyse epigenetic, genomic as well as metabolic changes.

Holistic Rehabilitation: Biological Embedding of Social Adversity and Its Health Implications

Human health is affected by lived experiences, both past and present. The environments we encounter throughout our lives, therefore, shape how we respond to new challenges, how we maintain a healthy immune system, and even how we respond to treatment and rehabilitation. Early in life and throughout adulthood, social experiences-such as exposure to various forms of adversity-can alter how cells in our body function, with far-reaching consequences for human health, disease, and treatment. This Perspective highlights studies from an ever-growing body of literature on the social determinants of health, with a focus on exposure to social adversities, such as social isolation, discrimination, or low social status, experienced both early in life and adulthood and how they variably impact health. By focusing on recent observational studies in humans and experimental studies on social nonhuman animals, this article details how social adversity can become biologically embedded in our cells at the molecular level. Given that humans are social animals, it is no surprise that social adversity can negatively impact our health, and experimental animal studies have helped us to uncover some of the causal mechanistic pathways underlying the link between social adversity and health outcomes. These molecular consequences can have far-reaching implications and, when combined with our growing knowledge on the social determinants of health, should inform how we approach treatment and rehabilitation.

Infant DNA methylation: an early indicator of intergenerational trauma?

Exposure to adverse childhood experiences (ACEs) increases risk for mental and physical health problems. Intergenerationally, mothers' ACEs predict children's health problems including neurodevelopmental and behavioural problems and poorer physical health. Theories of intergenerational trauma suggest that ACEs experienced in one generation negatively affect the health and well-being of future generations, with DNA methylation (DNAm) being one of several potential biological explanations. To begin exploring this hypothesis, we tested whether infant DNA methylation associated with intergenerational trauma. Secondary analysis employed data from the Alberta Pregnancy Outcomes and Nutrition (APrON) study. Subsample data were collected from mothers during pregnancy and postpartum on measures of distress, stress and ACEs and from infants at 3 months of age on DNAm from blood (n = 92) and buccal epithelial cells (BECs; n = 124; primarily nonoverlapping individuals between tissues). Blood and BECs were examined in separate analyses. Preliminary associations identified in blood and BECs suggest that infant DNAm patterns may relate to maternal ACEs. For the majority of ACE-related DNAm sites, neither maternal perinatal distress, nor maternal cortisol awakening response (CAR; a measure of hypothalamic-pituitary-adrenocortical axis function), substantially reduced associations between maternal ACEs and infant DNAm. However, accounting for maternal perinatal distress and cortisol substantially changed the effect of ACEs in a greater proportion of blood DNAm sites than BEC DNAm sites in the top ACEs-associated correlated methylated regions (CMRs), as well as across all CMRs and all remaining CpGs (that did not fall into CMRs). Possible DNAm patterns in infants, thus, might capture a signature of maternal intergenerational trauma, and this effect appears to be more dependent on maternal perinatal distress and CAR in blood relative to BECs.

Associations between indicators of socioeconomic position and DNA methylation: a scoping review

BACKGROUND

Socioeconomic position (SEP) is a major determinant of health across the life course. Yet, little is known about the biological mechanisms explaining this relationship. One possibility widely pursued in the scientific literature is that SEP becomes biologically embedded through epigenetic processes such as DNA methylation (DNAm), wherein the socioeconomic environment causes no alteration in the DNA sequence but modifies gene activity in ways that shape health.

METHODS

To understand the evidence supporting a potential SEP-DNAm link, we performed a scoping review of published empirical findings on the association between SEP assessed from prenatal development to adulthood and DNAm measured across the life course, with an emphasis on exploring how the developmental timing, duration, and type of SEP exposure influenced DNAm.

RESULTS

Across the 37 identified studies, we found that: (1) SEP-related DNAm signatures varied across the timing, duration, and type of SEP indicator; (2) however, longitudinal studies examining repeated SEP and DNAm measures are generally lacking; and (3) prior studies are conceptually and methodologically diverse, limiting the interpretability of findings across studies with respect to these three SEP features.

CONCLUSIONS

Given the complex relationship between SEP and DNAm across the lifespan, these findings underscore the importance of analyzing SEP features, including timing, duration, and type. To guide future research, we highlight additional research gaps and propose four recommendations to further unravel the relationship between SEP and DNAm.

Risk-focused differences in molecular processes implicated in SARS-CoV-2 infection: corollaries in DNA methylation and gene expression

BACKGROUND

Understanding the molecular basis of susceptibility factors to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global health imperative. It is well-established that males are more likely to acquire SARS-CoV-2 infection and exhibit more severe outcomes. Similarly, exposure to air pollutants and pre-existing respiratory chronic conditions, such as asthma and chronic obstructive respiratory disease (COPD) confer an increased risk to coronavirus disease 2019 (COVID-19).

METHODS

We investigated molecular patterns associated with risk factors in 398 candidate genes relevant to COVID-19 biology. To accomplish this, we downloaded DNA methylation and gene expression data sets from publicly available repositories (GEO and GTEx Portal) and utilized data from an empirical controlled human exposure study conducted by our team.

RESULTS

First, we observed sex-biased DNA methylation patterns in autosomal immune genes, such as NLRP2, TLE1, GPX1, and ARRB2 (FDR < 0.05, magnitude of DNA methylation difference Δβ > 0.05). Second, our analysis on the X-linked genes identified sex associated DNA methylation profiles in genes, such as ACE2, CA5B, and HS6ST2 (FDR < 0.05, Δβ > 0.05). These associations were observed across multiple respiratory tissues (lung, nasal epithelia, airway epithelia, and bronchoalveolar lavage) and in whole blood. Some of these genes, such as NLRP2 and CA5B, also exhibited sex-biased gene expression patterns. In addition, we found differential DNA methylation patterns by COVID-19 status for genes, such as NLRP2 and ACE2 in an exploratory analysis of an empirical data set reporting on human COVID-9 infections. Third, we identified modest DNA methylation changes in CpGs associated with PRIM2 and TATDN1 (FDR < 0.1, Δβ > 0.05) in response to particle-depleted diesel exhaust in bronchoalveolar lavage. Finally, we captured a DNA methylation signature associated with COPD diagnosis in a gene involved in nicotine dependence (COMT) (FDR < 0.1, Δβ > 0.05).

CONCLUSION

Our findings on sex differences might be of clinical relevance given that they revealed molecular associations of sex-biased differences in COVID-19. Specifically, our results hinted at a potentially exaggerated immune response in males linked to autosomal genes, such as NLRP2. In contrast, our findings at X-linked loci such as ACE2 suggested a potentially distinct DNA methylation pattern in females that may interact with its mRNA expression and inactivation status. We also found tissue-specific DNA methylation differences in response to particulate exposure potentially capturing a nitrogen dioxide (NO2) effect-a contributor to COVID-19 susceptibility. While we identified a molecular signature associated with COPD, all COPD-affected individuals were smokers, which may either reflect an association with the disease, smoking, or may highlight a compounded effect of these two risk factors in COVID-19. Overall, our findings point towards a molecular basis of variation in susceptibility factors that may partly explain disparities in the risk for SARS-CoV-2 infection.