DNA methylation and adiposity phenotypes: an epigenome-wide association study among adults in the Strong Heart Study

Neonatal adiposity is associated with microRNAs in adipocyte-derived extracellular vesicles in maternal and cord blood, a discovery analysis

BACKGROUND

Maternal body size, nutrition, and hyperglycemia contribute to neonatal body size and composition. There is little information on maternal-fetal transmission of messages which influence fetal growth. We analyzed adipocyte-derived small extracellular vesicular (ADsEV) microRNAs in maternal and cord blood to explore their adipogenic potential.

METHODS

There were 279 mother-neonate pairs with all phenotypic data (normal glucose tolerant NGT = 148, gestational diabetes mellitus GDM = 131). Neonates with adiposity were those in the highest tertile (T3) of sex-specific sum of skinfolds and those without adiposity (lean) in the lowest tertile T1 of NGT pregnancies. We studied ADsEV miRNAs in 76 and 51 neonates with and without adiposity respectively and their mothers based on power calculations (68 NGT and 59 GDM pregnancies). ADsEV miRNAs from maternal and cord blood plasma samples were profiled on Agilent 8*60 K microarray. Differential expression (DE) of ADsEV miRNAs in adipose vs. lean groups was studied before and after adjustment for maternal GDM, adiposity, and vitamin B12-folate status.

RESULTS

Multiple miRNAs were common in maternal and cord blood and positively correlated. We identified 24 maternal and 5 cord blood miRNAs differentially expressed (discovery p ≤ 0.1) in the adipose group in unadjusted, and 19 and 26, respectively, in the adjusted analyses. Even though DE miRNAs were different in maternal and cord blood, they targeted similar adipogenic pathways (e.g., the forkhead box O (FOXO) family of transcription factors, mitogen‑activated protein kinase (MAPK) pathway, transforming growth factor beta (TGF-β) pathway). Maternal GDM and adiposity were associated with many DE ADsEV miRNAs.

CONCLUSION

Our results suggest that the ADsEV miRNAs in mothers are potential regulators of fetal adiposity. The expression and functionality of miRNAs appear to be influenced by maternal adiposity, hyperglycemia, and micronutrient status during pregnancy.

Blood-based genome-wide DNA methylation correlations across body-fat- and adiposity-related biochemical traits

The recent increase in obesity levels across many countries is likely to be driven by nongenetic factors. The epigenetic modification DNA methylation (DNAm) may help to explore this, as it is sensitive to both genetic and environmental exposures. While the relationship between DNAm and body-fat traits has been extensively studied, there is limited literature on the shared associations of DNAm variation across such traits. Akin to genetic correlation estimates, here, we introduce an approach to evaluate the similarities in DNAm associations between traits: DNAm correlations. As DNAm can be both a cause and consequence of complex traits, DNAm correlations have the potential to provide insights into trait relationships above that currently obtained from genetic and phenotypic correlations. Utilizing 7,519 unrelated individuals from Generation Scotland with DNAm from the EPIC array, we calculated DNAm correlations between body-fat- and adiposity-related traits by using the bivariate OREML framework in the OSCA software. For each trait, we also estimated the shared contribution of DNAm between sexes. We identified strong, positive DNAm correlations between each of the body-fat traits (BMI, body-fat percentage, and waist-to-hip ratio, ranging from 0.96 to 1.00), finding larger associations than those identified by genetic and phenotypic correlations. We identified a significant deviation from 1 in the DNAm correlations for BMI between males and females, with sex-specific DNAm changes associated with BMI identified at eight DNAm probes. Employing genome-wide DNAm correlations to evaluate the similarities in the associations of DNAm with complex traits has provided insight into obesity-related traits beyond that provided by genetic correlations.

Exploring Single-Cell Exposomics by Mass Spectrometry

Single-cell exposomics, a revolutionary approach that investigates cell-environment interactions at cellular and subcellular levels, stands distinct from conventional bulk exposomics. Leveraging advancements in mass spectrometry, it provides a detailed perspective on cellular dynamics, interactions, and responses to environmental stimuli and their impacts on human health. This work delves into this innovative realm, highlighting the nuanced interplay between environmental stressors and biological responses at cellular and subcellular levels. The application of spatial mass spectrometry in single-cell exposomics is discussed, revealing the intricate spatial organization and molecular composition within individual cells. Cell-type-specific exposomics, shedding light on distinct susceptibilities and adaptive strategies of various cell types to environmental exposures, is also examined. The Perspective further emphasizes the integration with molecular and cellular biology approaches to validate hypotheses derived from single-cell exposomics in a comprehensive biological context. Looking toward the future, we anticipate continued technological advancements and convergence with other -omics approaches and discuss implications for environmental health research, disease progression studies, and precision medicine. The final emphasis is on the need for robust computational tools and interdisciplinary collaboration to fully leverage the potential of single-cell exposomics, acknowledging the complexities inherent to this paradigm.

DNA methylation-based biomarkers for cardiometabolic-related traits and their importance for risk stratification

Recent findings

The prevalence of cardiometabolic syndrome in adults is increasing worldwide, highlighting the importance of biomarkers for individuals' classification based on their health status. Although cardiometabolic risk scores and diagnostic criteria have been developed aggregating adverse health effects of individual conditions on the overall syndrome, none of them has gained unanimous acceptance. Therefore, novel molecular biomarkers have been developed to better understand the risk, onset and progression of both individual conditions and the overall cardiometabolic syndrome.

Summary

Consistent associations between whole blood DNA methylation (DNAm) levels at several single genomic (i.e. CpG) sites and both individual and aggregated cardiometabolic conditions supported the creation of second-generation DNAm-based cardiometabolic-related biomarkers. These biomarkers linearly combine individual DNAm levels from key CpG sites, selected by a two-step machine learning procedures. They can be used, even retrospectively, in populations with extant whole blood DNAm levels and without observed cardiometabolic phenotypes.

Purpose of review

Here we offer an overview of the second-generation DNAm-based cardiometabolic biomarkers, discussing methodological advancements and implications on the interpretation and generalizability of the findings. We finally emphasize the contribution of DNAm-based biomarkers for risk stratification beyond traditional factors and discuss limitations and future directions of the field.

DNA methylation patterns at birth predict health outcomes in young adults born very low birthweight

Background

Individuals born very low birthweight (VLBW) are at increased risk of impaired cardiovascular and respiratory function in adulthood. To identify markers to predict future risk for VLBW individuals, we analyzed DNA methylation at birth and at 28 years in the New Zealand (NZ) VLBW cohort (all infants born < 1500 g in NZ in 1986) compared with age-matched, normal birthweight controls. Associations between neonatal methylation and cardiac structure and function (echocardiography), vascular function and respiratory outcomes at age 28 years were documented.

Results

Genomic DNA from archived newborn heel-prick blood (n = 109 VLBW, 51 controls) and from peripheral blood at ~ 28 years (n = 215 VLBW, 96 controls) was analyzed on Illumina Infinium MethylationEPIC 850 K arrays. Following quality assurance and normalization, methylation levels were compared between VLBW cases and controls at both ages by linear regression, with genome-wide significance set to p < 0.05 adjusted for false discovery rate (FDR, Benjamini-Hochberg). In neonates, methylation at over 16,400 CpG methylation sites differed between VLBW cases and controls and the canonical pathway most enriched for these CpGs was Cardiac Hypertrophy Signaling (p = 3.44E⁻¹¹). The top 20 CpGs that differed most between VLBW cases and controls featured clusters in ARID3A, SPATA33, and PLCH1 and these 3 genes, along with MCF2L, TRBJ2-1 and SRC, led the list of 15,000 differentially methylated regions (DMRs) reaching FDR-adj significance. Fifteen of the 20 top CpGs in the neonate EWAS showed associations between methylation at birth and adult cardiovascular traits (particularly LnRHI). In 28-year-old adults, twelve CpGs differed between VLBW cases and controls at FDR-adjusted significance, including hypermethylation in EBF4 (four CpGs), CFI and UNC119B and hypomethylation at three CpGs in HIF3A and one in KCNQ1. DNA methylation GrimAge scores at 28 years were significantly greater in VLBW cases versus controls and weakly associated with cardiovascular traits. Four CpGs were identified where methylation differed between VLBW cases and controls in both neonates and adults, three reversing directions with age (two CpGs in EBF4, one in SNAI1 were hypomethylated in neonates, hypermethylated in adults). Of these, cg16426670 in EBF4 at birth showed associations with several cardiovascular traits in adults.

Conclusions

These findings suggest that methylation patterns in VLBW neonates may be informative about future adult cardiovascular and respiratory outcomes and have value in guiding early preventative care to improve adult health.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-023-01463-3.

Neonatal adiposity is associated with microRNAs in adipocyte-derived extracellular vesicles in maternal and cord blood

Background

Maternal body size, nutrition, and hyperglycemia contribute to neonatal body size and composition. There is little information on maternal-fetal transmission of messages which influence fetal growth. We analyzed adipocyte-derived small extracellular vesicular (ADsEV) microRNAs in maternal and cord blood to explore their adipogenic potential.

Methods

We studied 127 mother-neonate pairs (51 lean and 76 adipose neonates, in 68 NGT and 59 GDM pregnancies). Adiposity refers to the highest tertile (T3) of sum of skinfolds in neonates of normal glucose tolerant (NGT) mothers, lean to the to lowest tertile (T1). ADsEV miRNAs from maternal and cord blood samples were profiled on Agilent 8*60K microarray. Differential expression (DE) of ADsEV miRNAs in adipose vs. lean neonates was studied before and after adjustment for maternal gestational diabetes mellitus (GDM), adiposity, and vitamin B12-folate status.

Results

Multiple miRNAs were common in maternal and cord blood and positively correlated. We identified 24 maternal and 5 cord blood miRNAs differentially expressed (p ≤ 0.1) in the adipose neonate group, and 19 and 26 respectively, in the adjusted analyses. Even though DE miRNAs were different in maternal and cord blood, they targeted similar adipogenic pathways (e.g., the forkhead box O (FOXO) family of transcription factors, mitogen-activated protein kinase (MAPK) pathway, transforming growth factor beta (TGF-β) pathway). Maternal GDM and adiposity were associated with many DE ADsEV miRNAs.

Conclusion

Our results suggest that the ADsEV miRNAs in mothers are potential regulators of fetal adiposity. The expression and functionality of miRNAs appears to be influenced by maternal adiposity, hyperglycemia, and micronutrient status during pregnancy.

Epigenome-wide association study of BMI in Black populations from InterGEN and GENOA

OBJECTIVE

Obesity is a significant public health concern across the globe. Research investigating epigenetic mechanisms related to obesity and obesity-associated conditions has identified differences that may contribute to cellular dysregulation that accelerates the development of disease. However, few studies include Black women, who experience the highest incidence of obesity and early onset of cardiometabolic disorders.

METHODS

The association of BMI with epigenome-wide DNA methylation (DNAm) was examined using the 850K Illumina EPIC BeadChip in two Black populations (Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure [InterGEN], n = 239; and The Genetic Epidemiology Network of Arteriopathy [GENOA] study, n = 961) using linear mixed-effects regression models adjusted for batch effects, cell type heterogeneity, population stratification, and confounding factors.

RESULTS

Cross-sectional analysis of the InterGEN discovery cohort identified 28 DNAm sites significantly associated with BMI, 24 of which had not been previously reported. Of these, 17 were replicated using the GENOA study. In addition, a meta-analysis, including both the InterGEN and GENOA cohorts, identified 658 DNAm sites associated with BMI with false discovery rate < 0.05. In a meta-analysis of Black women, we identified 628 DNAm sites significantly associated with BMI. Using a more stringent significance threshold of Bonferroni-corrected p value 0.05, 65 and 61 DNAm sites associated with BMI were identified from the combined sex and female-only meta-analyses, respectively.

CONCLUSIONS

This study suggests that BMI is associated with differences in DNAm among women that can be identified with DNA extracted from salivary (discovery) and peripheral blood (replication) samples among Black populations across two cohorts.

DNA methylation-based predictors of health: applications and statistical considerations

DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.

Blood DNA Methylation and Incident Coronary Heart Disease: Evidence From the Strong Heart Study

Importance

American Indian communities experience a high burden of coronary heart disease (CHD). Strategies are needed to identify individuals at risk and implement preventive interventions.

Objective

To investigate the association of blood DNA methylation (DNAm) with incident CHD using a large number of methylation sites (cytosine-phosphate-guanine [CpG]) in a single model.

Design, Setting, and Participants

This prospective study, including a discovery cohort (the Strong Heart Study [SHS]) and 4 additional cohorts (the Women's Health Initiative [WHI], the Framingham Heart Study [FHS], the Atherosclerosis Risk in Communities Study ([ARIC]-Black, and ARIC-White), evaluated 12 American Indian communities in 4 US states; African American women, Hispanic women, and White women throughout the US; White men and White women from Massachusetts; and Black men and women and White men and women from 4 US communities. A total of 2321 men and women (mean [SD] follow-up, 19.1 [9.2] years) were included in the SHS, 1874 women (mean [SD] follow-up, 15.8 [5.9] years) in the WHI, 2128 men and women (mean [SD] follow-up, 7.7 [1.8] years) in the FHS, 2114 men and women (mean [SD] follow-up, 20.9 [7.2] years) in the ARIC-Black, and 931 men and women (mean [SD] follow-up, 20.9 [7.2] years) in the ARIC-White. Data were collected from May 1989 to December 2018 and analyzed from February 2019 to May 2021.

Exposure

Blood DNA methylation.

Main Outcome and Measure

Using a high-dimensional time-to-event elastic-net model for the association of 407 224 CpG sites with incident CHD in the SHS (749 events), this study selected the differentially methylated CpG positions (DMPs) selected in the SHS and evaluated them in the WHI (531 events), FHS (143 events), ARIC-Black (350 events), and ARIC-White (121 events) cohorts.

Results

The median (IQR) age of participants in SHS was 55 (49-62) years, and 1359 participants (58.6%) were women. Elastic-net models selected 505 DMPs associated with incident CHD in the SHS beyond established risk factors, center, blood cell counts, and genetic principal components. Among those DMPs, 33 were commonly selected in 3 or 4 of the other cohorts and the pooled hazard ratios from the standard Cox models were significant at P < .05 for 10 of the DMPs. For example, the hazard ratio (95% CI) for CHD comparing the 90th and 10th percentiles of differentially methylated CpGs was 0.86 (0.78-0.95) for cg16604233 (tagged to COL11A2) and 1.23 (1.08-1.39) for cg09926486 (tagged to FRMD5). Some of the DMPs were consistent in the direction of the association; others showed associations in opposite directions across cohorts. Untargeted independent elastic-net models of CHD showed distinct DMPs, genes, and network of genes in the 5 cohorts.

Conclusions and Relevance

In this multi-cohort study, blood-based DNAm findings supported an association between a complex blood epigenomic signature and CHD that was largely different across populations.

Distinct Associations of BMI and Fatty Acids With DNA Methylation in Fasting and Postprandial States in Men

We have previously shown that blood global DNA methylation (DNAm) differs between postprandial state (PS) and fasting state (FS) and is associated with BMI and polyunsaturated fatty acid (PUFA) (negatively and positively, respectively) in 12 metabolically healthy adult Mexican men (AMM cohort) equally distributed among conventional BMI classes. Here, we detailed those associations at CpG dinucleotide level by exploiting the Infinium methylation EPIC array (Illumina). We sought differentially methylated CpG (dmCpG) that were (1) associated with BMI (BMI-dmCpG) and/or fatty acids (FA) (FA-dmCpG) in FS or PS and (2) different across FS and PS within a BMI class. BMI-dmCpG and FA-dmCpG were more numerous in FS compared to PS and largely prandial state-specific. For saturated and monounsaturated FA, dmCpG overlap was higher across than within the respective saturation group. Several BMI- and FA-dmCpG mapped to genes involved in metabolic disease and in some cases matched published experimental data sets. Notably, SETDB1 and MTHFS promoter dmCpG could explain the previously observed associations between global DNAm, PUFA content, and BMI in FS. Surprisingly, overlap between BMI-dmCpG and FA-dmCpG was limited and the respective dmCpG were differentially distributed across functional genomic elements. BMI-dmCpG showed the highest overlap with dmCpG of the saturated FA palmitate, monounsaturated C20:1 and PUFA C20:2. Of these, selected promoter BMI-dmCpG showed opposite associations with palmitate compared to C20:1 and C20:2. As for the comparison between FS and PS within BMI classes, dmCpG were strikingly more abundant and variably methylated in overweight relative to normoweight or obese subjects (∼70–139-fold, respectively). Overweight-associated dmCpG-hosting genes were significantly enriched in targets for E47, SREBP1, and RREB1 transcription factors, which are known players in obesity and lipid homeostasis, but none overlapped with BMI-dmCpG. We show for the first time that the association of BMI and FA with methylation of disease-related genes is distinct in FS and PS and that limited overlap exists between BMI- and FA-dmCpG within and across prandial states. Our study also identifies a transcriptional regulation circuitry in overweight that might contribute to adaptation to that condition or to transition to obesity. Further work is necessary to define the pathophysiological implications of these findings.

Emergent expansion of clinical epigenetics in patients with cardiovascular diseases

PURPOSE OF REVIEW

Cardiovascular diseases (CVDs) are typically caused by multifactorial events including mutations in a large number of genes. Epigenetic-derived modifications in the cells are normal but can be amended by aging, lifestyle, and exposure to toxic substances. Major epigenetic modifications are DNA methylation, histone modification, chromatin remodeling as well as the noncoding RNAs. These pivotal players are involved in the epigenetic-induced modifications observed during CVDs. Nevertheless, despite impressive efforts capitalized in epigenetic research in the last 50 years, clinical applications are still not satisfactory.

RECENT FINDINGS

Briefly, we present some of the recent steps forward in the epigenetic studies of CVDs. There is an increased appreciation for the contribution of epigenetic alterations in the development of CVDs. Now, we have novel epigenetic biomarkers and therapeutic trials with the use of statins, metformin, and some compounds affecting epigenetic pathways including a BET inhibitor apabetalone. The new knowledge of epigenetic regulation is also discussed in the light of precision medicine of CVDs.

SUMMARY

Epigenetic studies of CVDs have the promise to yield both mechanistic insights as well as adjunct treatments (repurposed drugs and apabetalone). The overall concept of precision medicine is not widely recognized in routine medical practice and the so-called reductionist approach remains the most used way to treat CVD patients.