Replicating associations between DNA methylation and body mass index in a longitudinal sample of older twins

Protein epigenetic scores and overall mortality in the longitudinal Swedish Adoption/Twin Study of Aging (SATSA)

INTRODUCTION

DNA methylation (DNAm) has a functional role in gene regulation, and it has been used to estimate various human characteristics. Variation in DNAm is associated with aging and variability of the proteome. Therefore, understanding the relationship between blood circulating proteins, aging, and mortality is critical to identify disease-causing pathways. We aimed to estimate the association between protein epigenetic scores (EpiScores) and overall mortality in the Swedish Adoption/Twin Study of Aging (SATSA).

METHODS

We included information from 374 individuals collected between 1992 and 2014. Our exposures were 109 protein EpiScores generated using DNAm data and prediction models by the MethylDetectR shiny app. All-cause mortality was the outcome of interest. To estimate the protein EpiScores associations with all-cause mortality, we fitted Cox proportional hazard models adjusted for age, sex, education, smoking status, body mass index, and occupation. We also conducted co-twin control analyses to control for shared familial factors.

RESULTS

The mean age of participants at the first assessment was 68.6 years. In total, nine protein EpiScores (e.g., Stanniocalcin 1) were associated with a higher risk for all-cause mortality. In contrast, five protein EpiScores (e.g., Prolyl endopeptidase) were associated with a lower risk for all-cause mortality.

CONCLUSION

The protein EpiScores associated with an increased mortality risk represent proteins involved in metabolic functions, immune response, and inflammation. Conversely, those associated with a lower risk represent proteins involved in neurogenesis and cellular functions. Overall, it is possible to predict protein levels from DNAm data that could have clinical relevance.

Trends of genetic contributions on epigenetic clocks and related methylation sites with aging: A population-based adult twin study

Several crucial acceleration periods exist during aging process. Epigenetic clocks, serving as indicators of aging, are influenced by genetic factors. Investigating how the genetic contributions on these clocks change with age may provide novel insights into the aging process. In this study, based on 1084 adult twins from the Chinese National Twin Registry (CNTR), we established structural equation models (SEMs) to evaluate the trends in genetic influence with aging for epigenetic clocks, which include PC-Horvath, PC-Hannum, PC-PhenoAge, PC-GrimAge, and DunedinPACE. A decline in overall heritability was observed for all five clocks from ages 31 to 70, with a relatively stable trend at first. Subsequently, apart from PC-GrimAge, the other four clocks displayed a more evident drop in heritability: DunedinPACE and PC-PhenoAge experienced a clear decline between 55 and 65 years, while PC-Horvath and PC-Hannum showed a similar decrease between 60 and 70 years. In contrast, the heritability of PC-GrimAge remained stable throughout. An analysis of methylation sites (CpGs) from these clocks identified 41, 26, 4, and 36 CpG sites potentially underlying heritability changes in DunedinPACE, PC-Horvath, PC-Hannum, and PC-PhenoAge, respectively. Data from the CNTR were collected through two surveys in 2013 and 2018. Based on 308 twins with longitudinal data, declines in genetic components were observed at follow-up compared to baseline, with significant decreases in the four PC-clocks. DunedinPACE peaked in 5-year longitudinal genetic contribution changes at age 55-60, while PC-clocks consistently peaked at age 50-55. These findings may offer novel insights into the role of genetic variations in aging.

Dual Regulation Mechanism of Obesity: DNA Methylation and Intestinal Flora

Obesity is a multifactorial chronic inflammatory metabolic disorder, with pathogenesis influenced by genetic and non-genetic factors such as environment and diet. Intestinal microbes and their metabolites play significant roles in the occurrence and development of obesity by regulating energy metabolism, inducing chronic inflammation, and impacting intestinal hormone secretion. Epigenetics, which involves the regulation of host gene expression without changing the nucleotide sequence, provides an exact direction for us to understand how the environment, lifestyle factors, and other risk factors contribute to obesity. DNA methylation, as the most common epigenetic modification, is involved in the pathogenesis of various metabolic diseases. The epigenetic modification of the host is induced or regulated by the intestinal microbiota and their metabolites, linking the dynamic interaction between the microbiota and the host genome. In this review, we examined recent advancements in research, focusing on the involvement of intestinal microbiota and DNA methylation in the etiology and progression of obesity, as well as potential interactions between the two factors, providing novel perspectives and avenues for further elucidating the pathogenesis, prevention, and treatment of obesity.

Genetic and environmental factors driving congenital solitary functioning kidney

BACKGROUND

Congenital solitary functioning kidney (CSFK) is an anomaly predisposing to hypertension, albuminuria and chronic kidney disease. Its aetiology is complex and includes genetic and environmental factors. The role of gene-environment interactions (G×E), although relevant for other congenital anomalies, has not yet been investigated. Therefore, we performed a genome-wide G×E analysis with six preselected environmental factors to explore the role of these interactions in the aetiology of CSFK.

METHODS

In the AGORA (Aetiologic research into Genetic and Occupational/environmental Risk factors for Anomalies in children) data- and biobank, genome-wide single-nucleotide variant (SNV) data and questionnaire data on prenatal exposure to environmental risk factors were available for 381 CSFK patients and 598 healthy controls. Using a two-step strategy, we first selected independent significant SNVs associated with one of the six environmental risk factors. These SNVs were subsequently tested in G×E analyses using logistic regression models, with Bonferroni-corrected P-value thresholds based on the number of SNVs selected in step one.

RESULTS

In step one, 7-40 SNVs were selected per environmental factor, of which only rs3098698 reached statistical significance (P = .0016, Bonferroni-corrected threshold 0.0045) for interaction in step two. The interaction between maternal overweight and this SNV, which results in lower expression of the Arylsulfatase B (ARSB) gene, could be explained by lower insulin receptor activity in children heterozygous for rs3098698. Eight other G×E interactions had a P-value <.05, of which two were biologically plausible and warrant further study.

CONCLUSIONS

Interactions between genetic and environmental factors may contribute to the aetiology of CSFK. To better determine their role, large studies combining data on genetic and environmental risk factors are warranted.

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.

Lipid Phenotypes and DNA Methylation: a Review of the Literature

PURPOSE OF REVIEW

Epigenetic modifications via DNA methylation have previously been linked to blood lipid levels, dyslipidemias, and atherosclerosis. The purpose of this review is to discuss current literature on the role of DNA methylation on lipid traits and their associated pathologies.

RECENT FINDINGS

Candidate gene and epigenome-wide approaches have identified differential methylation of genes associated with lipid traits (particularly CPT1A, ABCG1, SREBF1), and novel approaches are being implemented to further characterize these relationships. Moreover, studies on environmental factors have shown that methylation variations at lipid-related genes are associated with diet and pollution exposure. Further investigation is needed to elucidate the directionality of the associations between the environment, lipid traits, and epigenome. Future studies should also seek to increase the diversity of cohorts, as European and Asian ancestry populations are the predominant study populations in the current literature.

The epigenetic etiology of cardiovascular disease in a longitudinal Swedish twin study

BACKGROUND

Studies on DNA methylation have the potential to discover mechanisms of cardiovascular disease (CVD) risk. However, the role of DNA methylation in CVD etiology remains unclear.

RESULTS

We performed an epigenome-wide association study (EWAS) on CVD in a longitudinal sample of Swedish twins (535 individuals). We selected CpGs reaching the Bonferroni-corrected significance level (2 [Formula: see text] 10-7) or the top-ranked 20 CpGs with the lowest P values if they did not reach this significance level in EWAS analysis associated with non-stroke CVD, overall stroke, and ischemic stroke, respectively. We further applied a bivariate autoregressive latent trajectory model with structured residuals (ALT-SR) to evaluate the cross-lagged effect between DNA methylation of these CpGs and cardiometabolic traits (blood lipids, blood pressure, and body mass index). Furthermore, mediation analysis was performed to evaluate whether the cross-lagged effects had causal impacts on CVD. In the EWAS models, none of the CpGs we selected reached the Bonferroni-corrected significance level. The ALT-SR model showed that DNA methylation levels were more likely to predict the subsequent level of cardiometabolic traits rather than the other way around (numbers of significant cross-lagged paths of methylation → trait/trait → methylation were 84/4, 45/6, 66/1 for the identified three CpG sets, respectively). Finally, we demonstrated significant indirect effects from DNA methylation on CVD mediated by cardiometabolic traits.

CONCLUSIONS

We present evidence for a directional association from DNA methylation on cardiometabolic traits and CVD, rather than the opposite, highlighting the role of epigenetics in CVD development.

DNA methylome analysis identifies BMI-related epigenetic changes associated with non-small cell lung cancer susceptibility

Background

Body mass index (BMI) has been reported to be inversely associated with incident risk of non‐small cell lung cancer (NSCLC). However, the underlying mechanism is still unclear. This study aimed to investigate the role of DNA methylation in the relationship between BMI and NSCLC.

Methods

We carried out a genome‐wide DNA methylation study of BMI in peripheral blood among 2266 Chinese participants by using Illumina Methylation arrays. For the BMI‐related DNA methylation changes, their associations with NSCLC risk were further analyzed and their mediation effects on BMI‐NSCLC association were also evaluated.

Results

The methylation levels of four CpGs (cg12593793, cg17061862, cg11024682, and cg06500161, annotated to LMNA, ZNF143, SREBF1, and ABCG1, respectively) were found to be significantly associated with BMI. Methylation levels of cg12593793, cg11024682, and cg06500161 were observed to be inversely associated with NSCLC risk [OR (95%CI) =0.22 (0.16, 0.31), 0.39 (0.30, 0.50), and 0.66 (0.53, 0.82), respectively]. Additionally, cg11024682 in SREBF1 and cg06500161 in ABCG1 mediated 45.3% and 19.5% of the association between BMI and decreased NSCLC risk, respectively.

Conclusions

In this study, we identified four DNA methylation sites associated with BMI in the Chinese populations at the genome‐wide significant level. We also found that the BMI‐related methylations of SREBF1 and ABCG1 could mediate about a quintile‐to‐half of the effect of BMI on reduced NSCLC risk, which adds a potential mechanism underlying this association.

DNA methylation and lipid metabolism: an EWAS of 226 metabolic measures

BACKGROUND

The discovery of robust and trans-ethnically replicated DNA methylation markers of metabolic phenotypes, has hinted at a potential role of epigenetic mechanisms in lipid metabolism. However, DNA methylation and the lipid compositions and lipid concentrations of lipoprotein sizes have been scarcely studied. Here, we present an epigenome-wide association study (EWAS) (N = 5414 total) of mostly lipid-related metabolic measures, including a fine profiling of lipoproteins. As lipoproteins are the main players in the different stages of lipid metabolism, examination of epigenetic markers of detailed lipoprotein features might improve the diagnosis, prognosis, and treatment of metabolic disturbances.

RESULTS

We conducted an EWAS of leukocyte DNA methylation and 226 metabolic measurements determined by nuclear magnetic resonance spectroscopy in the population-based KORA F4 study (N = 1662) and replicated the results in the LOLIPOP, NFBC1966, and YFS cohorts (N = 3752). Follow-up analyses in the discovery cohort included investigations into gene transcripts, metabolic-measure ratios for pathway analysis, and disease endpoints. We identified 161 associations (p value < 4.7 × 10-10), covering 16 CpG sites at 11 loci and 57 metabolic measures. Identified metabolic measures were primarily medium and small lipoproteins, and fatty acids. For apolipoprotein B-containing lipoproteins, the associations mainly involved triglyceride composition and concentrations of cholesterol esters, triglycerides, free cholesterol, and phospholipids. All associations for HDL lipoproteins involved triglyceride measures only. Associated metabolic measure ratios, proxies of enzymatic activity, highlight amino acid, glucose, and lipid pathways as being potentially epigenetically implicated. Five CpG sites in four genes were associated with differential expression of transcripts in blood or adipose tissue. CpG sites in ABCG1 and PHGDH showed associations with metabolic measures, gene transcription, and metabolic measure ratios and were additionally linked to obesity or previous myocardial infarction, extending previously reported observations.

CONCLUSION

Our study provides evidence of a link between DNA methylation and the lipid compositions and lipid concentrations of different lipoprotein size subclasses, thus offering in-depth insights into well-known associations of DNA methylation with total serum lipids. The results support detailed profiling of lipid metabolism to improve the molecular understanding of dyslipidemia and related disease mechanisms.