Identification and validation of seven new loci showing differential DNA methylation related to serum lipid profile: an epigenome-wide approach. The REGICOR study

Epigenome-wide association study of metabolic syndrome in African-American adults

Background

The high prevalence of obesity among US adults has resulted in significant increases in associated metabolic disorders such as diabetes, dyslipidemia, and high blood pressure. Together, these disorders constitute metabolic syndrome, a clinically defined condition highly prevalent among African-Americans. Identifying epigenetic alterations associated with metabolic syndrome may provide additional information regarding etiology beyond current evidence from genome-wide association studies.

Methods

Data on metabolic syndrome and DNA methylation was assessed on 614 African-Americans from the Hypertension Genetic Epidemiology Network (HyperGEN) study. Metabolic syndrome was defined using the joint harmonized criteria, and DNA methylation was assessed using the Illumina HumanMethylation450K Bead Chip assay on DNA extracted from buffy coat. Linear mixed effects regression models were used to examine the association between CpG methylation at > 450,000 CpG sites and metabolic syndrome adjusted for study covariates. Replication using DNA from a separate sample of 69 African-Americans, as well as meta-analysis combining both cohorts, was conducted.

Results

Two differentially methylated CpG sites in the IGF2BP1 gene on chromosome 17 (cg06638433; p value = 3.10 × 10^− 7) and the ABCG1 gene on chromosome 21 (cg06500161; p value = 2.60 × 10^− 8) were identified. Results for the ABCG1 gene remained statistically significant in the replication dataset and meta-analysis.

Conclusion

Metabolic syndrome was consistently associated with increased methylation in the ABCG1 gene in the discovery and replication datasets, a gene that encodes a protein in the ATP-binding cassette transporter family and is involved in intra- and extra-cellular signaling and lipid transport.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0483-2) contains supplementary material, which is available to authorized users.

DNA methylation in human lipid metabolism and related diseases

PURPOSE OF REVIEW

It is becoming increasingly evident that epigenetic mechanisms, particularly DNA methylation, play a role in the regulation of blood lipid levels and lipid metabolism-linked phenotypes and diseases.

RECENT FINDINGS

Recent genome-wide methylation and candidate gene studies of blood lipids have highlighted several robustly replicated methylation markers across different ethnicities. Furthermore, many of these lipid-related CpG sites associated with blood lipids are also linked to lipid-related phenotypes and diseases. Integrating epigenome-wide association studies (EWAS) data with other layers of molecular data such as genetics or the transcriptome, accompanied by relevant statistical methods (e.g. Mendelian randomization), provides evidence for causal relationships. Recent data suggest that epigenetic changes can be consequences rather than causes of dyslipidemia. There is sparse information on many lipid classes and disorders of lipid metabolism, and also on the interplay of DNA methylation with other epigenetic layers such as histone modifications and regulatory RNAs.

SUMMARY

The current review provides a literature overview of epigenetic modifications in lipid metabolism and other lipid-related phenotypes and diseases focusing on EWAS of DNA methylation from January 2016 to September 2017. Recent studies strongly support the importance of epigenetic modifications, such as DNA methylation, in lipid metabolism and related diseases for relevant biological insights, reliable biomarkers, and even future therapeutics.

Cell-type deconvolution from DNA methylation: a review of recent applications

Recent advances in cell-type deconvolution approaches are adding to our understanding of the biology underlying disease development and progression. DNA methylation (DNAm) can be used as a biomarker of cell types, and through deconvolution approaches, to infer underlying cell type proportions. Cell-type deconvolution algorithms have two main categories: reference-based and reference-free. Reference-based algorithms are supervised methods that determine the underlying composition of cell types within a sample by leveraging differentially methylated regions (DMRs) specific to cell type, identified from DNAm measures of purified cell populations. Reference-free algorithms are unsupervised methods for use when cell-type specific DMRs are not available, allowing scientists to estimate putative cellular proportions or control for potential confounding from cell type. Reference-based deconvolution is typically applied to blood samples and has potentiated our understanding of the relation between immune profiles and disease by allowing estimation of immune cell proportions from archival DNA. Bioinformatic analyses using DNAm to infer immune cell proportions, part of a new field known as Immunomethylomics, provides a new direction for consideration in epigenome wide association studies (EWAS).

Environmental and epigenetic regulation of postprandial lipemia

PURPOSE OF REVIEW

Postprandial lipemia (PPL), the prolonged increase in plasma triglyceride-rich lipoproteins following food consumption, is an independent risk factor for cardiovascular disease. Genetic variation, environment and the interplay between these direct an individual's postprandial lipid response. From such interplay, inducible and reversible epigenetic changes arise. Increasing evidence suggests epigenetic variation contributes to postprandial response in lipids and risk.

RECENT FINDINGS

Diet and exercise are central agents affecting postprandial lipemia - triglyceride, but heterogeneity of the findings warrant more and larger studies. Several epigenetic loci identified from a human intervention study account for a substantial proportion of PPL phenotype variation, but the burden to conduct an intervention study of postprandial responses likely limits translation to personalized nutrition.

SUMMARY

The impact of both DNA methylation patterns and environmental factors such as diet, exercise, sleep and medication on PPL is multifaceted. Discovery of interactions that modify the association between CpG (oligodeoxydinucleotide) methylation and postprandial phenotypes is unfolding.

DNA methylation and obesity traits: An epigenome-wide association study. The REGICOR study

Obesity is associated with increased risk of several diseases and has become epidemic. Obesity is highly heritable but the genetic variants identified by genome-wide association studies explain only limited variability. Epigenetics could contribute to explain the missing variability. The study aim was to discover differential methylation patterns related to obesity. We designed an epigenome-wide association study with a discovery phase in a subsample of 641 REGICOR study participants, validated by analysis of 2,515 participants in the Framingham Offspring Study. Blood DNA methylation was assessed using Illumina HumanMethylation450 BeadChip. Next, we meta-analyzed the data using the fixed effects method and performed a functional and pathway analysis using the Ingenuity Pathway Analysis software. We were able to validate 94 CpGs associated with body mass index (BMI) and 49 CpGs associated with waist circumference, located in 95 loci. In addition, we newly discovered 70 CpGs associated with BMI and 33 CpGs related to waist circumference. These CpGs explained 25.94% and 29.22% of the variability of BMI and waist circumference, respectively, in the REGICOR sample. We also evaluated 65 of the 95 validated loci in the GIANT genome-wide association data; 10 of them had Tag SNPs associated with BMI. The top-ranked diseases and functions identified in the functional and pathway analysis were neurologic, psychological, endocrine, and metabolic.

Epigenome-Wide Association Study Identifies Methylation Sites Associated With Liver Enzymes and Hepatic Steatosis

BACKGROUND & AIMS

Epigenetic mechanisms might be involved in the regulation of liver enzyme level. We aimed to identify CpG sites at which DNA methylation levels are associated with blood levels of liver enzymes and hepatic steatosis.

METHODS

We conducted an epigenome-wide association study in whole blood for liver enzyme levels, including gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT), and aspartate aminotransferase (AST), among a discovery set of 731 participants of the Rotterdam Study and sought replication in a non-overlapping sample of 719 individuals. Significant DNA methylation changes were further analyzed to evaluate their relation with hepatic steatosis. Expression levels of the top identified gene were measured in 9 human liver cell lines and compared with expression profiles of its potential targets associated with lipid traits. The candidate gene was subsequently knocked down in human hepatoma cells using lentiviral vectors expressing small hairpin RNAs.

RESULTS

Eight probes annotated to SLC7A11, SLC1A5, SLC43A1, PHGDH, PSORS1C1, SREBF1, ANKS3 were associated with GGT and 1 probe annotated to SLC7A11 was associated with ALT after Bonferroni correction (1.0 × 10^-7). No probe was identified for AST levels. Four probes for GGT levels including cg06690548 (SLC7A11), cg11376147 (SLC43A1), cg22304262 (SLC1A5), and cg14476101 (PHGDH), and 1 for ALT cg06690548 (SLC7A11) were replicated. DNA methylation at SLC7A11 was associated with reduced risk of hepatic steatosis in participants (odds ratio, 0.69; 95% CI= 0.55-0.93; P value: 2.7 × 10^-3). In functional experiments, SLC7A11 was highly expressed in human liver cells; its expression is positively correlated with expression of a panel of lipid-associated genes, indicating a role of SLC7A11 in lipid metabolism.

CONCLUSIONS

Our results provide new insights into epigenetic mechanisms associated with markers of liver function and hepatic steatosis, laying the groundwork for future diagnostic and therapeutic applications.

Blood triglyceride levels are associated with DNA methylation at the serine metabolism gene PHGDH

Efficient interventions to reduce blood triglycerides are few; newer and more tolerable intervention targets are needed. Understanding the molecular mechanisms underlying blood triglyceride levels variation is key to identifying new therapies. To explore the role of epigenetic mechanisms on triglyceride levels, a blood methylome scan was conducted in 199 individuals from 5 French-Canadian families ascertained on venous thromboembolism, and findings were replicated in 324 French unrelated patients with venous thromboembolism. Genetic context and functional relevance were investigated. Two DNA methylation sites associated with triglyceride levels were identified. The first one, located in the ABCG1 gene, was recently reported, whereas the second one, located in the promoter of the PHGDH gene, is novel. The PHGDH methylation site, cg14476101, was found to be associated with variation in triglyceride levels in a threshold manner: cg14476101 was inversely associated with triglyceride levels only when triglyceride levels were above 1.12 mmol/L (discovery P-value = 8.4 × 10-6; replication P-value = 0.0091). Public databases findings supported a functional role of cg14476101 on PHGDH expression. PHGDH catalyses the first step in the serine biosynthesis pathway. These findings highlight the role of epigenetic regulation of the PHGDH gene in triglyceride metabolism, providing novel insights on putative intervention targets.

Skeletal energy homeostasis: a paradigm of endocrine discovery

Throughout the last decade, significant developments in cellular, molecular and mouse models have revealed major endocrine functions of the skeleton. More recent studies have evolved the interplay between bone-specific hormones, the skeleton, marrow adipose tissue, muscle and the brain. This review focuses on literature from the last decade, addressing the endocrine regulation of global energy metabolism via the skeleton. In addition, we will highlight several recent studies that further our knowledge of new endocrine functions of some organs; explore remaining unanswered questions; and, finally, we will discuss future directions for this more complex era of bone biology research.

Current epigenetic aspects the clinical kidney researcher should embrace

Chronic kidney disease (CKD), affecting 10–12% of the world’s adult population, is associated with a considerably elevated risk of serious comorbidities, in particular, premature vascular disease and death. Although a wide spectrum of causative factors has been identified and/or suggested, there is still a large gap of knowledge regarding the underlying mechanisms and the complexity of the CKD phenotype. Epigenetic factors, which calibrate the genetic code, are emerging as important players in the CKD-associated pathophysiology. In this article, we review some of the current knowledge on epigenetic modifications and aspects on their role in the perturbed uraemic milieu, as well as the prospect of applying epigenotype-based diagnostics and preventive and therapeutic tools of clinical relevance to CKD patients. The practical realization of such a paradigm will require that researchers apply a holistic approach, including the full spectrum of the epigenetic landscape as well as the variability between and within tissues in the uraemic milieu.

Recent Advances in Human Genetics and Epigenetics of Adiposity: Pathway to Precision Medicine?

Obesity is a heritable trait that contributes to substantial global morbidity and mortality. Here, we summarize findings from the past decade of genetic and epigenetic research focused on unravelling the underpinnings of adiposity. More than 140 genetic regions now are known to influence adiposity traits. The genetics of general adiposity, as measured by body mass index, and that of abdominal obesity, as measured by waist-to-hip ratio, have distinct biological backgrounds. Gene expression associated with general adiposity is enriched in the nervous system. In contrast, genes associated with abdominal adiposity function in adipose tissue. Recent population-based epigenetic analyses have highlighted additional distinct loci. We discuss how associated genetic variants can lead to understanding causal mechanisms, and to disentangling reverse causation in epigenetic analyses. Discoveries emerging from population genomics are identifying new disease markers and potential novel drug targets to better define and combat obesity and related diseases.

Association of Body Mass Index with DNA Methylation and Gene Expression in Blood Cells and Relations to Cardiometabolic Disease: A Mendelian Randomization Approach

BACKGROUND

The link between DNA methylation, obesity, and adiposity-related diseases in the general population remains uncertain.

METHODS AND FINDINGS

We conducted an association study of body mass index (BMI) and differential methylation for over 400,000 CpGs assayed by microarray in whole-blood-derived DNA from 3,743 participants in the Framingham Heart Study and the Lothian Birth Cohorts, with independent replication in three external cohorts of 4,055 participants. We examined variations in whole blood gene expression and conducted Mendelian randomization analyses to investigate the functional and clinical relevance of the findings. We identified novel and previously reported BMI-related differential methylation at 83 CpGs that replicated across cohorts; BMI-related differential methylation was associated with concurrent changes in the expression of genes in lipid metabolism pathways. Genetic instrumental variable analysis of alterations in methylation at one of the 83 replicated CpGs, cg11024682 (intronic to sterol regulatory element binding transcription factor 1 [SREBF1]), demonstrated links to BMI, adiposity-related traits, and coronary artery disease. Independent genetic instruments for expression of SREBF1 supported the findings linking methylation to adiposity and cardiometabolic disease. Methylation at a substantial proportion (16 of 83) of the identified loci was found to be secondary to differences in BMI. However, the cross-sectional nature of the data limits definitive causal determination.

CONCLUSIONS

We present robust associations of BMI with differential DNA methylation at numerous loci in blood cells. BMI-related DNA methylation and gene expression provide mechanistic insights into the relationship between DNA methylation, obesity, and adiposity-related diseases.