Accounting for Life-Course Exposures in Epigenetic Biomarker Association Studies: Early Life Socioeconomic Position, Candidate Gene DNA Methylation, and Adult Cardiometabolic Risk

Emerging Theories of Allostatic-Interoceptive Overload in Neurodegeneration

Recent integrative multilevel models offer novel insights into the etiology and course of neurodegenerative conditions. The predictive coding of allostatic-interoception theory posits that the brain adapts to environmental demands by modulating internal bodily signals through the allostatic-interoceptive system. Specifically, a domain-general allostatic-interoceptive network exerts adaptive physiological control by fine-tuning initial top-down predictions and bottom-up peripheral signaling. In this context, adequate adaptation implies the minimization of prediction errors thereby optimizing energy expenditure. Abnormalities in top-down interoceptive predictions or peripheral signaling can trigger allostatic overload states, ultimately leading to dysregulated interoceptive and bodily systems (endocrine, immunological, circulatory, etc.). In this context, environmental stress, social determinants of health, and harmful exposomes (i.e., the cumulative life-course exposition to different environmental stressors) may interact with physiological and genetic factors, dysregulating allostatic interoception and precipitating neurodegenerative processes. We review the allostatic-interoceptive overload framework across different neurodegenerative diseases, particularly in the behavioral variant frontotemporal dementia (bvFTD). We describe how concepts of allostasis and interoception could be integrated with principles of predictive coding to explain how the brain optimizes adaptive responses, while maintaining physiological stability through feedback loops with multiple organismic systems. Then, we introduce the model of allostatic-interoceptive overload of bvFTD and discuss its implications for the understanding of pathophysiological and neurocognitive abnormalities in multiple neurodegenerative conditions.

Epigenome-wide association study of incident type 2 diabetes in Black and White participants from the Atherosclerosis Risk in Communities Study

DNA methylation studies of incident type 2 diabetes in US populations are limited, and to our knowledge none included individuals of African descent living in the US. We performed an epigenome-wide association analysis of blood-based methylation levels at CpG sites with incident type 2 diabetes using Cox regression in 2,091 Black and 1,029 White individuals from the Atherosclerosis Risk in Communities study. At an epigenome-wide significance threshold of 10-7, we detected 7 novel diabetes-associated CpG sites in C1orf151 (cg05380846: HR= 0.89, p = 8.4 × 10-12), ZNF2 (cg01585592: HR= 0.88, p = 1.6 × 10-9), JPH3 (cg16696007: HR= 0.87, p = 7.8 × 10-9), GPX6 (cg02793507: HR= 0.85, p = 2.7 × 10-8 and cg00647063: HR= 1.20, p = 2.5 × 10-8), chr17q25 (cg16865890: HR= 0.8, p = 6.9 × 10-8), and chr11p15 (cg13738793: HR= 1.11, p = 7.7 × 10-8). The CpG sites at C1orf151, ZNF2, JPH3 and GPX6, were identified in Black adults, chr17q25 was identified in White adults, and chr11p15 was identified upon meta-analyzing the two groups. The CpG sites at JPH3 and GPX6 were likely associated with incident type 2 diabetes independent of BMI. All the CpG sites, except at JPH3, were likely consequences of elevated glucose at baseline. We additionally replicated known type 2 diabetes-associated CpG sites including cg19693031 at TXNIP, cg00574958 at CPT1A, cg16567056 at PLBC2, cg11024682 at SREBF1, cg08857797 at VPS25, and cg06500161 at ABCG1, 3 of which were replicated in Black adults at the epigenome-wide threshold. We observed modest increase in type 2 diabetes variance explained upon addition of the significantly associated CpG sites to a Cox model that included traditional type 2 diabetes risk factors and fasting glucose (increase from 26.2% to 30.5% in Black adults; increase from 36.9% to 39.4% in White adults). We examined if groups of proximal CpG sites were associated with incident type 2 diabetes using a gene-region specific and a gene-region agnostic differentially methylated region (DMR) analysis. Our DMR analyses revealed several clusters of significant CpG sites, including a DMR consisting of a previously discovered CpG site at ADCY7 and promoter regions of TP63 which were differentially methylated across all race groups. This study illustrates improved discovery of CpG sites/regions by leveraging both individual CpG site and DMR analyses in an unexplored population. Our findings include genes linked to diabetes in experimental studies (e.g., GPX6, JPH3, and TP63), and future gene-specific methylation studies could elucidate the link between genes, environment, and methylation in the pathogenesis of type 2 diabetes.

Epigenetics of Early Cardiometabolic Disease: Mechanisms and Precision Medicine

Epigenetics has transformed our understanding of the molecular basis of complex diseases, including cardiovascular and metabolic disorders. This review offers a comprehensive overview of the current state of knowledge on epigenetic processes implicated in cardiovascular and metabolic diseases, highlighting the potential of DNA methylation as a precision medicine biomarker and examining the impact of social determinants of health, gut bacterial epigenomics, noncoding RNA, and epitranscriptomics on disease development and progression. We discuss challenges and barriers to advancing cardiometabolic epigenetics research, along with the opportunities for novel preventive strategies, targeted therapies, and personalized medicine approaches that may arise from a better understanding of epigenetic processes. Emerging technologies, such as single-cell sequencing and epigenetic editing, hold the potential to further enhance our ability to dissect the complex interplay between genetic, environmental, and lifestyle factors. To translate research findings into clinical practice, interdisciplinary collaborations, technical and ethical considerations, and accessibility of resources and knowledge are crucial. Ultimately, the field of epigenetics has the potential to revolutionize the way we approach cardiovascular and metabolic diseases, paving the way for precision medicine and personalized health care, and improving the lives of millions of individuals worldwide affected by these conditions.

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.

Genetically predicted higher educational attainment decreases the risk of stroke: a multivariable Mendelian randomization study

Background

The causal association between educational attainment (EA) and stroke remains unclear. Hence, a novel multivariable Mendelian randomization (MVMR) approach was applied to solve this issue.

Methods

The single nucleotide polymorphisms (SNPs) from a recent genome-wide association study (GWAS) on years of schooling served as instruments. Univariable mendelian randomization (MR) and MVMR analyses were performed to detect the relationship between genetically predicted EA and the stroke risk. In the MVMR, cigarette consumption, alcohol consumption, body mass index (BMI), intelligence, and hypertension were adjusted. The summary statistics for stroke from the MEGASTROKE consortium included 446,696 participants (40,585 cases of stroke and 34,217 cases of ischemic stroke), most of whom were of European descent.

Results

In the univariable MR, genetically predicated EA could decrease the risks of total stroke (OR = 0.66, 95% CI 0.61–0.72, P = 2.70 × 10^–23), ischemic stroke (OR = 0.67, 95% CI 0.61–0.73, P = 2.58 × 10^–18), large artery atherosclerosis (OR = 0.51, 95% CI 0.40–0.64, P = 1.80 × 10^–8), small vessel stroke (OR = 0.60, 95% CI 0.49–0.73, P = 5.59 × 10^–7), and cardioembolic stroke (OR = 0.81, 95% CI 0.68–0.96, P = 1.46 × 10^–2) using the inverse-variance weighted (IVW) estimator. Higher EA might be negatively correlated with the odds of total stroke (OR = 0.62, 95% CI 0.50–0.77, P = 1.44 × 10^–5), ischemic stroke (OR = 0.63, 95% CI 0.50–0.80, P = 1.41 × 10^–4), and cardioembolic stroke (OR = 0.59, 95% CI 0.39–0.90, P = 0.01), but was not significant in large artery atherosclerosis (OR = 0.65, 95% CI 0.37–1.15, P = 0.14) and small vessel stroke (OR = 0.68, 95% CI 0.41–1.13, P = 0.14) after controlling other exposures.

Conclusions

We found that genetically predicated higher EA decreased the risks of total stroke, ischemic stroke, and cardioembolic stroke, independent of smoking, alcohol consumption, BMI, intelligence, and hypertension.

Understanding Health Inequalities Through the Lens of Social Epigenetics

Longstanding racial/ethnic inequalities in morbidity and mortality persist in the United States. Although the determinants of health inequalities are complex, social and structural factors produced by inequitable and racialized systems are recognized as contributing sources. Social epigenetics is an emerging area of research that aims to uncover biological pathways through which social experiences affect health outcomes. A growing body of literature links adverse social exposures to epigenetic mechanisms, namely DNA methylation, offering a plausible pathway through which health inequalities may arise. This review provides an overview of social epigenetics and highlights existing literature linking social exposures—i.e., psychosocial stressors, racism, discrimination, socioeconomic position, and neighborhood social environment—to DNA methylation in humans.We conclude with a discussion of social epigenetics as a mechanistic link to health inequalities and provide suggestions for future social epigenetics research on health inequalities.

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.

Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach

Assisted reproductive technologies (ART) are increasingly used, however little is known about the long-term health of ART-conceived offspring. Weak selection of comparison groups and poorly characterized mechanisms impede current understanding. In a prospective cohort (Growing Up in Singapore Towards healthy Outcomes; GUSTO; Clinical Trials ID: NCT01174875) including 83 ART-conceived and 1095 spontaneously-conceived singletons, we estimate effects of ART on anthropometry, blood pressure, serum metabolic biomarkers, and cord tissue DNA methylation by emulating a pragmatic trial supported by machine learning-based estimators. We find ART-conceived children to be shorter (-0.5 SD [95% CI: -0.7, -0.2]), lighter (-0.6 SD [-0.9, -0.3]) and have lower skinfold thicknesses (e.g. -14% [-24%, -3%] suprailiac), and blood pressure (-3 mmHg [-6, -0.5] systolic) at 6-6.5 years, with no strong differences in metabolic biomarkers. Differences are not explained by parental anthropometry or comorbidities, polygenic risk score, breastfeeding, or illnesses. Our simulations demonstrate ART is strongly associated with lower NECAB3 DNA methylation, with negative control analyses suggesting these estimates are unbiased. However, methylation changes do not appear to mediate observed differences in child phenotype.

The Early Life Course of Body Weight and Gene Expression Signatures for Disease

We examined the way body-weight patterns through the first 4 decades of life relate to gene expression signatures of common forms of morbidity, including cardiovascular disease (CVD), type 2 diabetes (T2D), and inflammation. As part of wave V of the nationally representative National Longitudinal Study of Adolescent to Adult Health (1997–2018) in the United States, mRNA abundance data were collected from peripheral blood (n = 1,132). We used a Bayesian modeling strategy to examine the relative associations between body size at 5 life stages—birth, adolescence, early adulthood, young adulthood, and adulthood—and gene expression–based disease signatures. We compared life-course models that consider critical or sensitive periods, as well as accumulation over the entire period. Our results are consistent with a sensitive-period model when examining CVD and T2D gene expression signatures: Birth weight has a prominent role for the CVD and T2D signatures (explaining 33.1% and 22.1%, respectively, of the total association accounted for by body size), while the most recent adult obesity status (ages 33–39) is important for both of these gene expression signatures (24.3% and 35.1%, respectively). Body size in all life stages was associated with inflammation, consistent with the accumulation model.

A Structured Approach to Evaluating Life-Course Hypotheses: Moving Beyond Analyses of Exposed Versus Unexposed in the -Omics Context

The structured life-course modeling approach (SLCMA) is a theory-driven analytical method that empirically compares multiple prespecified life-course hypotheses characterizing time-dependent exposure-outcome relationships to determine which theory best fits the observed data. In this study, we performed simulations and empirical analyses to evaluate the performance of the SLCMA when applied to genomewide DNA methylation (DNAm). Using simulations (n = 700), we compared 5 statistical inference tests used with SLCMA, assessing the familywise error rate, statistical power, and confidence interval coverage to determine whether inference based on these tests was valid in the presence of substantial multiple testing and small effects-2 hallmark challenges of inference from -omics data. In the empirical analyses (n = 703), we evaluated the time-dependent relationship between childhood abuse and genomewide DNAm. In simulations, selective inference and the max-|t|-test performed best: Both controlled the familywise error rate and yielded moderate statistical power. Empirical analyses using SLCMA revealed time-dependent effects of childhood abuse on DNAm. Our findings show that SLCMA, applied and interpreted appropriately, can be used in high-throughput settings to examine time-dependent effects underlying exposure-outcome relationships over the life course. We provide recommendations for applying the SLCMA in -omics settings and encourage researchers to move beyond analyses of exposed versus unexposed individuals.

Statistical methods for mediation analysis in the era of high-throughput genomics: Current successes and future challenges

Mediation analysis investigates the intermediate mechanism through which an exposure exerts its influence on the outcome of interest. Mediation analysis is becoming increasingly popular in high-throughput genomics studies where a common goal is to identify molecular-level traits, such as gene expression or methylation, which actively mediate the genetic or environmental effects on the outcome. Mediation analysis in genomics studies is particularly challenging, however, thanks to the large number of potential mediators measured in these studies as well as the composite null nature of the mediation effect hypothesis. Indeed, while the standard univariate and multivariate mediation methods have been well-established for analyzing one or multiple mediators, they are not well-suited for genomics studies with a large number of mediators and often yield conservative p-values and limited power. Consequently, over the past few years many new high-dimensional mediation methods have been developed for analyzing the large number of potential mediators collected in high-throughput genomics studies. In this work, we present a thorough review of these important recent methodological advances in high-dimensional mediation analysis. Specifically, we describe in detail more than ten high-dimensional mediation methods, focusing on their motivations, basic modeling ideas, specific modeling assumptions, practical successes, methodological limitations, as well as future directions. We hope our review will serve as a useful guidance for statisticians and computational biologists who develop methods of high-dimensional mediation analysis as well as for analysts who apply mediation methods to high-throughput genomics studies.

How are social determinants of health integrated into epigenetic research? A systematic review

OBJECTIVE

We systematically review the literature on social epigenetics, examining how empirical research to date has conceptualized and operationalized social determinants of health (SDOH).

METHODS

Using comprehensive search procedures, we identified studies that consider the impact of SDOH on DNA methylation (DNAm), the most common measure of epigenetic change in research on human adult populations. We analyzed the studies to determine: 1) which populations and environments have been investigated in the literature; 2) how SDOH are defined and operationalized; 3) which SDOH have been linked to DNAm; and 4) what lessons from the SDOH literature can be better integrated into future studies exploring the social determinants of health and epigenetic outcomes.

RESULTS

We identified 67 studies, with 39 to 8397 participants. The SDOH most commonly considered were early life socioeconomic exposures and early life trauma or mental health. Our review highlights four broad challenges: a) high dependence on convenience sampling, b) limited racial/ethnic, and geographic diversity in sampling frames, c) overreliance on individual sociodemographic characteristics as proxies for broader stratification processes, and d) a focus on downstream social determinants of health and individualized experiences with social stressors.

CONCLUSIONS

Future social epigenetics research should prioritize larger, more diverse and representative population-based samples and employ the SDOH framework to better inform the conceptualization of research questions and interpretation of findings. In particular, the simplified depiction of race/ethnicity, gender, and socioeconomic status as individual-level characteristics should be updated with an explicit acknowledgement that these characteristics are more accurately interpreted as cues used by society to differentiate subpopulations. Social epigenetics research can then more clearly elucidate the biological consequences of these social exposures for patterns of gene expression, subsequent disease etiology, and health inequities.

Genetically predicted education attainment in relation to somatic and mental health

A deeper understanding of the causal links from education level to health outcomes may shed a light for disease prevention. In the present Mendelian randomization study, we found that genetically higher education level was associated with lower risk of major mental disorders and most somatic diseases, independent of intelligence. Higher education level adjusted for intelligence was associated with lower risk of suicide attempts, insomnia, major depressive disorder, heart failure, stroke, coronary artery disease, lung cancer, breast cancer, type 2 diabetes and rheumatoid arthritis but with higher risk of obsessive-compulsive disorder, anorexia nervosa, anxiety, bipolar disorder and prostate cancer. Higher education level was associated with reduced obesity and smoking, which mediated quite an extent of the associations between education level and health outcomes. These findings emphasize the importance of education to reduce the burden of common diseases.

Scars of childhood socioeconomic stress: A systematic review

Childhood socioeconomic position (SEP) is associated with the development of adult psychological outcomes, with DNA methylation (DNAm) as a mechanism to potentially explain these changes. We present the first systematic review synthesising the literature investigating childhood SEP and DNAm. Thirty-two publications were included. Seventeen studies focused on candidate genes, typically focusing on genes implicated with the stress response and/or development of psychiatric conditions. These studies typically investigated different regions of the genes, which revealed inconsistent results. Six studies calculated epigenetic age, with a small number revealing an elevated significant association with childhood SEP. Epigenome-wide studies revealed altered patterns of DNAm which varied between the nine studies. This research area is emerging and demonstrated great variance in findings with no clear patterns identified across studies. Multiple methodological shortcomings are identified, including at the phenotypic level where construct validity of childhood SEP is highly inconsistent, with studies using a wide range of measures. Larger cohorts will be required with international collaborations to strengthen this research area.

Socioeconomic Position and DNA Methylation Age Acceleration Across the Life Course

Accelerated DNA methylation age is linked to all-cause mortality and environmental factors, but studies of associations with socioeconomic position are limited. Researchers generally use small selected samples, and it is unclear how findings obtained with 2 commonly used methods for calculating methylation age (the Horvath method and the Hannum method) translate to general population samples including younger and older adults. Among 1,099 United Kingdom adults aged 28-98 years in 2011-2012, we assessed the relationship of Horvath and Hannum DNA methylation age acceleration with a range of social position measures: current income and employment, education, income and unemployment across a 12-year period, and childhood social class. Accounting for confounders, participants who had been less advantaged in childhood were epigenetically "older" as adults: In comparison with participants who had professional/managerial parents, Hannum age was 1.07 years higher (95% confidence interval: 0.20, 1.94) for participants with parents in semiskilled/unskilled occupations and 1.85 years higher (95% confidence interval: 0.67, 3.02) for those without a working parent at age 14 years. No other robust associations were seen. Results accord with research implicating early life circumstances as critical for DNA methylation age in adulthood. Since methylation age acceleration as measured by the Horvath and Hannum estimators appears strongly linked to chronological age, researchers examining associations with the social environment must take steps to avoid age-related confounding.

FADS1-FADS2 genetic polymorphisms are associated with fatty acid metabolism through changes in DNA methylation and gene expression

Background

Genome-wide association studies (GWASs) have shown that genetic variants are important determinants of free fatty acid levels. The mechanisms underlying the associations between genetic variants and free fatty acid levels are incompletely understood. Here, we aimed to identify genetic markers that could influence diverse fatty acid levels in a Chinese population and uncover the molecular mechanisms in terms of DNA methylation and gene expression.

Results

We identified strong associations between single-nucleotide polymorphisms (SNPs) in the fatty acid desaturase (FADS) region and multiple polyunsaturated fatty acids. Expression quantitative trait locus (eQTL) analysis of rs174570 on FADS1 and FADS2 mRNA levels proved that minor allele of rs174570 was associated with decreased FADS1 and FADS2 expression levels (P < 0.05). Methylation quantitative trait locus (mQTL) analysis of rs174570 on DNA methylation levels in three selected regions of FADS region showed that the methylation levels at four CpG sites in FADS1, one CpG site in intragenic region, and three CpG sites in FADS2 were strongly associated with rs174570 (P < 0.05). Then, we demonstrated that methylation levels at three CpG sites in FADS1 were negatively associated with FADS1 and FADS2 expression, while two CpG sites in FADS2 were positively associated with FADS1 and FADS2 expression. Using mediation analysis, we further show that the observed effect of rs174570 on gene expression was tightly correlated with the effect predicted through association with methylation.

Conclusions

Our findings suggest that genetic variants in the FADS region are major genetic modifiers that can regulate fatty acid metabolism through epigenetic gene regulation.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0545-5) contains supplementary material, which is available to authorized users.

DNA methylation signatures of educational attainment

Educational attainment is a key behavioural measure in studies of cognitive and physical health, and socioeconomic status. We measured DNA methylation at 410,746 CpGs (N = 4152) and identified 58 CpGs associated with educational attainment at loci characterized by pleiotropic functions shared with neuronal, immune and developmental processes. Associations overlapped with those for smoking behaviour, but remained after accounting for smoking at many CpGs: Effect sizes were on average 28% smaller and genome-wide significant at 11 CpGs after adjusting for smoking and were 62% smaller in never smokers. We examined sources and biological implications of education-related methylation differences, demonstrating correlations with maternal prenatal folate, smoking and air pollution signatures, and associations with gene expression in cis, dynamic methylation in foetal brain, and correlations between blood and brain. Our findings show that the methylome of lower-educated people resembles that of smokers beyond effects of their own smoking behaviour and shows traces of various other exposures.

Associations of social environment, socioeconomic position and social mobility with immune response in young adults: the Jerusalem Perinatal Family Follow-Up Study

OBJECTIVES

Immune response to cytomegalovirus (CMV) impacts adult chronic disease. This study investigates associations of childhood and adulthood social environment, socioeconomic position (SEP) and social mobility with CMV response in young adults.

DESIGN

Historical prospective study design.

SETTING

Subcohort of all 17 003 births to residents of Jerusalem between 1974 and 1976.

PARTICIPANTS

Participants included 1319 young adults born in Jerusalem with extensive archival and follow-up data, including childhood and adulthood SEP-related factors and anti-CMV IgG titre levels and seroprevalence measured at age 32.

MAIN EXPOSURE AND OUTCOME MEASURES

Principal component analysis was used to transform correlated social environment and SEP-related variables at two time points (childhood and adulthood) into two major scores reflecting household (eg, number of siblings/children, religiosity) and socioeconomic (eg, occupation, education) components. Based on these components, social mobility variables were created. Linear and Poisson regression models were used to investigate associations of components and mobility with anti-CMV IgG titre level and seroprevalence, adjusted for confounders.

RESULTS

Lower levels of household and socioeconomic components in either childhood or adulthood were associated with higher anti-CMV IgG titre level and seropositivity at age 32. Compared with individuals with stable favourable components, anti-CMV IgG titre level and risk for seropositivity were higher in stable unfavourable household and socioeconomic components (household: β=3.23, P<0.001; relative risk (RR)=1.21, P<0.001; socioeconomic: β=2.20, P=0.001; RR=1.14, P=0.01), downward household mobility (β=4.32, P<0.001; RR=1.26, P<0.001) and upward socioeconomic mobility (β=1.37, P=0.04; RR=1.19, P<0.001). Among seropositive individuals, associations between household components and mobility with anti-CMV IgG titre level were maintained and associations between socioeconomic components and mobility with anti-CMV IgG titre level were attenuated.

CONCLUSIONS

Our study provides evidence that accumulating low SEP from childhood through adulthood and social mobility may compromise immune response in young adulthood.

From forensic epigenetics to forensic epigenomics: broadening DNA investigative intelligence

Human genetic variation is a major resource in forensics, but does not allow all forensically relevant questions to be answered. Some questions may instead be addressable via epigenomics, as the epigenome acts as an interphase between the fixed genome and the dynamic environment. We envision future forensic applications of DNA methylation analysis that will broaden DNA-based forensic intelligence. Together with genetic prediction of appearance and biogeographic ancestry, epigenomic lifestyle prediction is expected to increase the ability of police to find unknown perpetrators of crime who are not identifiable using current forensic DNA profiling.

Maternal gestational weight gain and DNA methylation in young women: application of life course mediation methods

AIM

To investigate the role of maternal gestational weight gain (GWG) and prepregnancy BMI on programming offspring DNA methylation.

METHODS

Among 589 adult (age = 32) women participants of the Jerusalem Perinatal Study, we quantified DNA methylation in five candidate genes. We used inverse probability-weighting and parametric g-formula to estimate direct effects of maternal prepregnancy BMI and GWG on methylation.

RESULTS

Higher maternal GWG, but not prepregnancy BMI, was inversely related to offspring ABCA1 methylation (β = -1.1% per quartile; 95% CI: -2.0, -0.3) after accounting for ancestry, parental and offspring exposures. Total and controlled direct effects were nearly identical suggesting included offspring exposures did not mediate this relationship. Results were robust to sensitivity analyses for missing data and model specification.

CONCLUSION

We find some support for epigenetic programming and highlight strengths and limitations of these methods relative to other prevailing approaches.