Lipid changes due to fenofibrate treatment are not associated with changes in DNA methylation patterns in the GOLDN study

A systematic review and metaanalysis of observational studies on the effects of epigenetic factors on serum triglycerides

Epigenetic modifications might be associated with serum triglycerides (TG) levels. This study aims to systematically review the studies on the relationship between the methylation of specific cytosine-phosphate-guanine (CpG) sites and serum TG levels. This systematic review and meta-analysis study was conducted according to the PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. A systematic literature search was conducted in Medline database (PubMed), Scopus, and Cochrane library up to end of 2020. All observational studies (cross-sectional, case-control, and cohort) were included. Studies that assessed the effect of DNA methylation of different CpG sites of ABCG1, CPT1A, and SREBF1 genes on serum TG levels were selected. The National Institutes of Health (NIH) checklist was used to assess the quality of included articles. Among 2790 articles, ten studies were included in the quantitative analysis and fourteen studies were included in the systematic review. DNA methylation of ABCG1 gene had significant positive association with TG levels (β = 0.05, 95% CI = 0.04, 0.05, P heterogeneity < 0.001). There was significant inverse association between DNA methylation of CPT1A gene and serum TG levels (β = -0.03, 95% CI = -0.03, -0.02, P heterogeneity < 0.001). DNA methylation of SREBF1 gene was positively and significantly associated with serum TG levels (β = 0.03; 95% CI = 0.02-0.04, P heterogeneity < 0.001). DNA methylation of ABCG1 and SREBF1 genes has positive association with serum TG level, whereas this association is opposite for CPT1A gene. The role of epigenetic factors should be considered in some populations with high prevalence of hypertriglyceridemia.

Obesity I: Overview and molecular and biochemical mechanisms

Obesity is a chronic, relapsing condition characterized by excess body fat. Its prevalence has increased globally since the 1970s, and the number of obese and overweight people is now greater than those underweight. Obesity is a multifactorial condition, and as such, many components contribute to its development and pathogenesis. This is the first of three companion reviews that consider obesity. This review focuses on the genetics, viruses, insulin resistance, inflammation, gut microbiome, and circadian rhythms that promote obesity, along with hormones, growth factors, and organs and tissues that control its development. It shows that the regulation of energy balance (intake vs. expenditure) relies on the interplay of a variety of hormones from adipose tissue, gastrointestinal tract, pancreas, liver, and brain. It details how integrating central neurotransmitters and peripheral metabolic signals (e.g., leptin, insulin, ghrelin, peptide YY_3-36) is essential for controlling energy homeostasis and feeding behavior. It describes the distinct types of adipocytes and how fat cell development is controlled by hormones and growth factors acting via a variety of receptors, including peroxisome proliferator-activated receptor-gamma, retinoid X, insulin, estrogen, androgen, glucocorticoid, thyroid hormone, liver X, constitutive androstane, pregnane X, farnesoid, and aryl hydrocarbon receptors. Finally, it demonstrates that obesity likely has origins in utero. Understanding these biochemical drivers of adiposity and metabolic dysfunction throughout the life cycle lends plausibility and credence to the "obesogen hypothesis" (i.e., the importance of environmental chemicals that disrupt these receptors to promote adiposity or alter metabolism), elucidated more fully in the two companion reviews.

Fibrate pharmacogenomics: expanding past the genome

Fibrates are a medication class prescribed for decades as 'broad-spectrum' lipid-modifying agents used to lower blood triglyceride levels and raise high-density lipoprotein cholesterol levels. Such lipid changes are associated with a decrease in cardiovascular disease, and fibrates are commonly used to reduce risk of dangerous cardiovascular outcomes. As with most drugs, it is well established that response to fibrate treatment is variable, and this variation is heritable. This has motivated the investigation of pharmacogenomic determinants of response, and multiple studies have discovered a number of genes associated with fibrate response. Similar to other complex traits, the interrogation of single nucleotide polymorphisms using candidate gene or genome-wide approaches has not revealed a substantial portion of response variation. However, recent innovations in technological platforms and advances in statistical methodologies are revolutionizing the use and integration of other 'omes' in pharmacogenomics studies. Here, we detail successes, challenges, and recent advances in fibrate pharmacogenomics.

Endocrine-Mediated Mechanisms of Metabolic Disruption and New Approaches to Examine the Public Health Threat

Obesity and metabolic disorders are of great societal concern and generate substantial human health care costs globally. Interventions have resulted in only minimal impacts on disrupting this worsening health trend, increasing attention on putative environmental contributors. Exposure to numerous environmental contaminants have, over decades, been demonstrated to result in increased metabolic dysfunction and/or weight gain in cell and animal models, and in some cases, even in humans. There are numerous mechanisms through which environmental contaminants may contribute to metabolic dysfunction, though certain mechanisms, such as activation of the peroxisome proliferator activated receptor gamma or the retinoid x receptor, have received considerably more attention than less-studied mechanisms such as antagonism of the thyroid receptor, androgen receptor, or mitochondrial toxicity. As such, research on putative metabolic disruptors is growing rapidly, as is our understanding of molecular mechanisms underlying these effects. Concurrent with these advances, new research has evaluated current models of adipogenesis, and new models have been proposed. Only in the last several years have studies really begun to address complex mixtures of contaminants and how these mixtures may disrupt metabolic health in environmentally relevant exposure scenarios. Several studies have begun to assess environmental mixtures from various environments and study the mechanisms underlying their putative metabolic dysfunction; these studies hold real promise in highlighting crucial mechanisms driving observed organismal effects. In addition, high-throughput toxicity databases (ToxCast, etc.) may provide future benefits in prioritizing chemicals for in vivo testing, particularly once the causative molecular mechanisms promoting dysfunction are better understood and expert critiques are used to hone the databases. In this review, we will review the available literature linking metabolic disruption to endocrine-mediated molecular mechanisms, discuss the novel application of environmental mixtures and implications for in vivo metabolic health, and discuss the putative utility of applying high-throughput toxicity databases to answering complex organismal health outcome questions.

Aberrant DNA methylation of M1-macrophage genes in coronary artery disease

M1 and M2 macrophage balance in atherosclerosis has attracted much interest. Though, it remains unknown how macrophage heterogeneity is regulated. Moreover, the regulation of macrophage polarization and activation also involve DNA methylation. However, it remains ambiguous which genes are under direct regulation by DNA methylation. Our aim was to evaluate the gene-specific promoter DNA methylation status of M1/M2 polarization markers in PBMCs of CAD patients. A case-control study was performed with 25 CAD patients and 25 controls to study the promoter DNA methylation status of STAT1, STAT6, MHC2, IL12b, iNOS, JAK1, JAK2 and SOCS5 using MS-HRM analysis. Our data indicates that there was a clear-cut difference in the pattern of gene-specific promoter DNA methylation of CAD patients in comparison to controls. A significant difference was observed between the percentage methylation of STAT1, IL12b, MHC2, iNOS, JAK1 and JAK2 in CAD patients and control subjects. In conclusion, our data show that MS-HRM assay is a rapid and inexpensive method for qualitatively identifying aberrant gene-specific promoter DNA methylation changes in CAD. Furthermore, we propose that gene-specific promoter DNA methylation based on monocyte/macrophage might aid as diagnostic marker for clinical application or DNA methylation-related drug interventions may offer novel possibilities for atherosclerotic disease management.

Evidence of batch effects masking treatment effect in GAW20 methylation data

Using the real data set from GAW20, we examined changes in the distribution of DNA methylation before and after treatment. Paired analysis of differences in both mean and variance had grossly inflated type 1 error, suggesting either a very large number of changes across the entire epigenome or major non-biological issues, such as batch effects. Separate analysis of Infinium I and II probes indicated differences in the paired t-test statistics between these two types of probes. Examination of combined principal components showed that the first and fourth principal components discriminate between the before and after treatment measurements, further evidencing the presence of batch effects that make any conclusions about treatment effect suspect.

Homozygosity disequilibrium associated with treatment response and its methylation regulation

Homozygosity disequilibrium (HD), indicating a nonrandom pattern of sizable runs of homozygosity that deviates from a random allocation of homozygous and heterozygous genotypes in the genome, is an important phenomenon in population genomics and medical genomics. We performed the first genome-wide study investigating the roles of HD in pharmacogenomics and pharmacoepigenomics by analyzing GAW20 data. We inferred whole-genome profiles of homozygosity intensities and performed genome-wide homozygosity association analyses to identify regions of HD associated with triglyceride (TG) response to fenofibrate by using LOHAS (Loss-of-Heterozygosity Analysis Suite) software. The analysis identified a region of HD contained in MACROD2 at 20p12 to be significantly associated with TG response to fenofibrate. We also examined the common genetic component in TG and methylation responses to fenofibrate. The methylation response to fenofibrate was regarded as a methylation quantitative trait, and our methylation quantitative trait locus analysis identified a cis-acting regulation association with marginal significance between the homozygosity intensity of MACROD2 and the methylation response to fenofibrate. These findings may help delineate the genetic basis of pharmacogenomic and pharmacoepigenomic responses to fenofibrate intervention.

Investigation of parent-of-origin effects induced by fenofibrate treatment on triglycerides levels

Background

Genome-wide association studies performed on triglycerides (TGs) have not accounted for epigenetic mechanisms that may partially explain trait heritability.

Results

Parent-of-origin (POO) effect association analyses using an agnostic approach or a candidate approach were performed for pretreatment TG levels, posttreatment TG levels, and pre- and posttreatment TG-level differences in the real GAW20 family data set. We detected 22 genetic variants with suggestive POO effects with at least 1 phenotype (P ≤ 10^− 5). We evaluated the association of these 22 significant genetic variants showing POO effects with close DNA methylation probes associated with TGs. A total of 18 DNA methylation probes located in the vicinity of the 22 SNPs were associated with at least 1 phenotype and 6 SNP-probe pairs were associated with DNA methylation probes at the nominal level of P < 0.05, among which 1 pair presented evidence of POO effect. Our analyses identified a paternal effect of SNP rs301621 on the difference between pre- and posttreatment TG levels (P = 1.2 × 10^− 5). This same SNP showed evidence for a maternal effect on methylation levels of a nearby probe (cg10206250; P = 0.01). Using a causal inference test we established that the observed POO effect of rs301621 was not mediated by DNA methylation at cg10206250.

Conclusions

We performed POO effect association analyses of SNPs with TGs, as well as association analyses of SNPs with DNA methylation probes. These analyses, which were followed by a causal inference test, established that the paternal effect at the SNP rs301621 is induced by treatment and is not mediated by methylation level at cg10206250.

A Bayesian mixed modeling approach for estimating heritability

BACKGROUND

A Bayesian mixed model approach using integrated nested Laplace approximations (INLA) allows us to construct flexible models that can account for pedigree structure. Using these models, we estimate genome-wide patterns of DNA methylation heritability (h 2 ), which are currently not well understood, as well as h 2 of blood lipid measurements.

METHODS

We included individuals from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study with Infinium 450 K cytosine-phosphate-guanine (CpG) methylation and blood lipid data pre- and posttreatment with fenofibrate in families with up to three-generation pedigrees. For genome-wide patterns, we constructed 1 model per CpG with methylation as the response variable, with a random effect to model kinship, and age and gender as fixed effects.

RESULTS

In total, 425,791 CpG sites pre-, but only 199,027 CpG sites posttreatment were found to have nonzero heritability. Across these CpG sites, the distributions of h 2 estimates are similar in pre- and posttreatment (pre: median = 0.31, interquartile range [IQR] = 0.16; post: median = 0.34, IQR = 0.20). Blood lipid h 2 estimates were similar pre- and posttreatment with overlapping 95% credibility intervals. Heritability was nonzero for treatment effect, that is, the difference between pre- and posttreatment blood lipids. Estimates for triglycerides h 2 are 0.48 (pre), 0.42 (post), and 0.21 (difference); likewise for high-density lipoprotein cholesterol h 2 the estimates are 0.61, 0.68, and 0.10.

CONCLUSIONS

We show that with INLA, a fully Bayesian approach to estimate DNA methylation h 2 is possible on a genome-wide scale. This provides uncertainty assessment of the estimates, and allows us to perform model selection via deviance information criterion (DIC) to identify CpGs with strong evidence for nonzero heritability.

Quality control for Illumina 450K methylation data in the absence of iDat files using correlation structure in pedigrees and repeated measures

BACKGROUND

An important feature in many genomic studies is quality control and normalization. This is particularly important when analyzing epigenetic data, where the process of obtaining measurements can be bias prone. The GAW20 data was from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN), a study with multigeneration families, where DNA cytosine-phosphate-guanine (CpG) methylation was measured pre- and posttreatment with fenofibrate. We performed quality control assessment of the GAW20 DNA methylation data, including normalization, assessment of batch effects and detection of sample swaps.

RESULTS

We show that even after normalization, the GOLDN methylation data has systematic differences pre- and posttreatment. Through investigation of (a) CpGs sites containing a single nucleotide polymorphism, (b) the stability of breeding values for methylation across time points, and (c) autosomal gender-associated CpGs, 13 sample swaps were detected, 11 of which were posttreatment.

CONCLUSIONS

This paper demonstrates several ways to perform quality control of methylation data in the absence of raw data files and highlights the importance of normalization and quality control of the GAW20 methylation data from the GOLDN study.

Longitudinal data methods for evaluating genome-by-epigenome interactions in families

BACKGROUND

Longitudinal measurement is commonly employed in health research and provides numerous benefits for understanding disease and trait progression over time. More broadly, it allows for proper treatment of correlated responses within clusters. We evaluated 3 methods for analyzing genome-by-epigenome interactions with longitudinal outcomes from family data.

RESULTS

Linear mixed-effect models, generalized estimating equations, and quadratic inference functions were used to test a pharmacoepigenetic effect in 200 simulated posttreatment replicates. Adjustment for baseline outcome provided greater power and more accurate control of Type I error rates than computation of a pre-to-post change score.

CONCLUSIONS

Comparison of all modeling approaches indicated a need for bias correction in marginal models and similar power for each method, with quadratic inference functions providing a minor decrement in power compared to generalized estimating equations and linear mixed-effects models.

Integrative methylation score to identify epigenetic modifications associated with lipid changes resulting from fenofibrate treatment in families

Epigenome-wide association studies (EWAS) have traditionally focused on the association test of single epigenetic markers with complex traits. However, it is possible that multiple cytosine-phosphate-guanine (CpG) sites at the same locus could jointly exert their effects on human traits. Therefore, a region-based test that combines multiple markers could be more powerful. We used 2 different region-based tests to investigate the association between changes in DNA methylation and drug response, including the median methylation level test (MMLT) and sequence kernel association test (SKAT). No genes were found to be significantly associated with the drug response (for triglycerides, the false discovery rate ranged from 0.855 to 0.999; for high-density lipoprotein cholesterol, and the false discovery rate ranged from 0.584 to 0.915). Further evidence is needed to explore potential application of gene-level methylation association analysis.

Association between fetal exposure to phthalate endocrine disruptor and genome-wide DNA methylation at birth

BACKGROUND

Phthalic acid esters are ubiquitous and antiandrogenic, and may cause systemic effects in humans, particularly with in utero exposure. Epigenetic modification, such as DNA methylation, has been hypothesized to be an important mechanism that mediates certain biological processes and pathogenic effects of in utero phthalate exposure.

OBJECTIVE

The aim of this study was to examine the association between genome-wide DNA methylation at birth and prenatal exposure to phthalate.

METHODS

We studied 64 infant-mother pairs included in TMICS (Taiwan Maternal and Infant Cohort Study), a long-term follow-up birth cohort from the general population. DNA methylation levels at more than 450,000 CpG sites were measured in cord blood samples using Illumina Infinium HumanMethylation450 BeadChips. The concentrations of three metabolites of di-(2-ethylhexyl) phthalate (DEHP) were measured using liquid chromatography tandem-mass spectrometry (LC-MS/MS) in urine samples collected from the pregnant women during 28-36 weeks gestation.

RESULTS

We identified 25 CpG sites whose methylation levels in cord blood were significantly correlated with prenatal DEHP exposure using a false discovery rate (FDR) of 5% (q-value < 0.05). Via gene-set enrichment analysis (GSEA), we also found that there was significant enrichment of genes involved in the androgen response, estrogen response, and spermatogenesis within those genes showing DNA methylation changes in response to exposure. Specifically, PA2G4, HMGCR, and XRCC6 genes were involved in genes in response to androgen.

CONCLUSIONS

Phthalate exposure in utero may cause significant alterations in the DNA methylation in cord blood. These changes in DNA methylation might serve as biomarkers of maternal exposure to phthalate in infancy and potential candidates for studying mechanisms via which phthalate may impact on health in later life. Future investigations are warranted.

Genomic 5-mC contents in peripheral blood leukocytes were independent protective factors for coronary artery disease with a specific profile in different leukocyte subtypes

Background

Alterations in DNA methylation are demonstrated in atherosclerosis pathogenesis. However, changing rules of global DNA methylation and hydroxymethylation in peripheral blood leukocytes (PBLs) and different blood cell subtypes of coronary artery disease (CAD) patients are still inconclusive, and much less is known about mechanisms underlying.

Results

We recruited 265 CAD patients and 270 healthy controls with genomic DNA from PBLs, of which 50 patients and 50 controls were randomly chosen with DNA from isolated neutrophils, lymphocytes and monocytes, and RNA from PBLs. Genomic 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC) contents were quantified by liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) assay. Genomic 5-mC contents were negatively associated with the serum total cholesterol (TC) level (P = 0.010), age (P = 0.016), and PBL classifications (P = 0.023), explaining 6.8% individual variation in controls. Furthermore, genomic 5-mC contents were inversely associated with an increased risk of CAD (odds ratio (OR) = 0.325, 95% confidence interval (CI) = 0.237~0.445, P = 2.62 × 10^− 12), independent of PBL counts and classifications, age, sex, histories of hyperlipidemia, hypertension, and diabetes. Within-individual analysis showed a general 5-mC decrease in PBL subtypes, but significant difference was found in monocytes only (P = 0.001), accompanied by increased 5-hmC (P = 3.212 × 10^− 4). In addition, coincident to the reduced DNMT1 expression in patients’ PBLs, the expression level of DNMT1 was significantly lower (P = 0.022) in oxidized low-density lipoprotein (ox-LDL) stimulated THP-1-derived foam cells compared to THP-1 monocytes, with decreased genomic 5-mdC content (P = 0.038).

Conclusions

Global hypomethylation of blood cells defined dominantly by the monocyte DNA hypomethylation is independently associated with the risk of CAD in Chinese Han population. The importance of monocytes in atherosclerosis pathophysiology may demonstrate via an epigenetic pathway, but prospective studies are still needed to test the causality.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0443-x) contains supplementary material, which is available to authorized users.

An epigenome-wide association study of inflammatory response to fenofibrate in the Genetics of Lipid Lowering Drugs and Diet Network

AIM

Fenofibrate, a PPAR-α inhibitor used for treating dyslipidemia, has well-documented anti-inflammatory effects that vary between individuals. While DNA sequence variation explains some of the observed variability in response, epigenetic patterns present another promising avenue of inquiry due to the biological links between the PPAR-α pathway, homocysteine and S-adenosylmethionine - a source of methyl groups for the DNA methylation reaction.

HYPOTHESIS

DNA methylation variation at baseline is associated with the inflammatory response to a short-term fenofibrate treatment.

METHODS

We have conducted the first epigenome-wide study of inflammatory response to daily treatment with 160 mg of micronized fenofibrate over a 3-week period in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, n = 750). Epigenome-wide DNA methylation was quantified on CD4⁺ T cells using the Illumina Infinium HumanMethylation450 array.

RESULTS

We identified multiple CpG sites significantly associated with the changes in plasma concentrations of inflammatory cytokines such as high sensitivity CRP (hsCRP, 7 CpG sites), IL-2 soluble receptor (IL-2sR, one CpG site), and IL-6 (4 CpG sites). Top CpG sites mapped to KIAA1324L (p = 2.63E-10), SMPD3 (p = 2.14E-08), SYNPO2 (p = 5.00E-08), ILF3 (p = 1.04E-07), PRR3, GNL1 (p = 6.80E-09), FAM50B (p = 3.19E-08), RPTOR (p = 9.79e-07) and several intergenic regions (p < 1.03E-07). We also derived two inflammatory patterns using principal component analysis and uncovered additional epigenetic hits for each pattern before and after fenofibrate treatment.

CONCLUSION

Our study provides preliminary evidence of a relationship between DNA methylation and inflammatory response to fenofibrate treatment.

DNA methylation as a marker of response in rheumatoid arthritis

Rheumatoid arthritis (RA) is a complex disease affecting approximately 0.5-1% of the population. While there are effective biologic therapies, in up to 40% of patients, disease activity remains inadequately controlled. Therefore, identifying factors that predict, prior to the initiation of therapy, which patients are likely to respond best to which treatment is a research priority and DNA methylation is increasingly being explored as a potential theranostic biomarker. DNA methylation is thought to play a role in RA disease pathogenesis and in mediating the relationship between genetic variants and patient outcomes. The role of DNA methylation has been most extensively explored in cancer medicine, where it has been shown to be predictive of treatment response. Studies in RA, however, are in their infancy and, while showing promise, further investigation in well-powered studies is warranted.

Epigenetics of Lipid Phenotypes

Dyslipidemia is a well-established risk factor for cardiovascular disease, the main cause of death worldwide. Blood lipid profiles are patterned by both genetic and environmental factors. In recent years, epigenetics has emerged as a paradigm that unifies these influences. In this review, we have summarized the latest evidence implicating epigenetic mechanisms-DNA methylation, histone modification, and regulation by RNAs-in lipid homeostasis. Key findings have emerged in a number of novel epigenetic loci located in biologically plausible genes (e.g. CPT1A, ABCG1, SREBF1, and others), as well as microRNA-33a/b. Evidence from animal and cell culture models suggests a complex interplay between different classes of epigenetic processes in the lipid-related genomic regions. While epigenetic findings hold the potential to explain the interindividual variability in lipid profiles as well as the underlying mechanisms, they have yet to be translated into effective therapies for dyslipidemia.

Blood lipids influence DNA methylation in circulating cells

Background

Cells can be primed by external stimuli to obtain a long-term epigenetic memory. We hypothesize that long-term exposure to elevated blood lipids can prime circulating immune cells through changes in DNA methylation, a process that may contribute to the development of atherosclerosis. To interrogate the causal relationship between triglyceride, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol levels and genome-wide DNA methylation while excluding confounding and pleiotropy, we perform a stepwise Mendelian randomization analysis in whole blood of 3296 individuals.

Results

This analysis shows that differential methylation is the consequence of inter-individual variation in blood lipid levels and not vice versa. Specifically, we observe an effect of triglycerides on DNA methylation at three CpGs, of LDL cholesterol at one CpG, and of HDL cholesterol at two CpGs using multivariable Mendelian randomization. Using RNA-seq data available for a large subset of individuals (N = 2044), DNA methylation of these six CpGs is associated with the expression of CPT1A and SREBF1 (for triglycerides), DHCR24 (for LDL cholesterol) and ABCG1 (for HDL cholesterol), which are all key regulators of lipid metabolism.

Conclusions

Our analysis suggests a role for epigenetic priming in end-product feedback control of lipid metabolism and highlights Mendelian randomization as an effective tool to infer causal relationships in integrative genomics data.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-1000-6) contains supplementary material, which is available to authorized users.

The multifaceted interplay between lipids and epigenetics

PURPOSE OF REVIEW

The interplay between lipids and epigenetic mechanisms has recently gained increased interest because of its relevance for common diseases and most notably atherosclerosis. This review discusses recent advances in unravelling this interplay with a particular focus on promising approaches and methods that will be able to establish causal relationships.

RECENT FINDINGS

Complementary approaches uncovered close links between circulating lipids and epigenetic mechanisms at multiple levels. A characterization of lipid-associated genetic variants suggests that these variants exert their influence on lipid levels through epigenetic changes in the liver. Moreover, exposure of monocytes to lipids persistently alters their epigenetic makeup resulting in more proinflammatory cells. Hence, epigenetic changes can both impact on and be induced by lipids.

SUMMARY

It is the combined application of technological advances to probe epigenetic modifications at a genome-wide scale and methodological advances aimed at causal inference (including Mendelian randomization and integrative genomics) that will elucidate the interplay between circulating lipids and epigenetics. Understanding its role in the development of atherosclerosis holds the promise of identifying a new category of therapeutic targets, since epigenetic changes are amenable to reversal.

Fenofibrate inhibited pancreatic cancer cells proliferation via activation of p53 mediated by upregulation of LncRNA MEG3

There is still no suitable drug for pancreatic cancer treatment, which is one of the most aggressive human tumors. Maternally expressed gene 3 (MEG3), a LncRNA, has been suggested as a tumor suppressor in a range of human tumors. Studies found fenofibrate exerted anti-tumor roles in various human cancer cell lines. However, its role in pancreatic cancer remains unknown. The present study aimed to explore the impacts of fenofibrate on pancreatic cancer cell lines, and to investigate MEG3 role in its anti-tumor mechanisms. We used MTT assay to determine cells proliferation, genome-wide LncRNA microarray analysis to identify differently expressed LncRNAs, siRNA or pCDNA-MEG3 transfection to interfere or upregulate MEG3 expression, western blot to detect protein levels, real-time PCR to determine MEG3 level. Fenofibrate significantly inhibited proliferation of pancreatic cancer cells, increased MEG3 expression and p53 levels. Moreover, knockdown of MEG3 attenuated cytotoxicity induced by fenofibrate. Furthermore, overexpression of MEG3 induced cells death and increased p53 expression. Our results indicated fenofibrate inhibited pancreatic cancer cells proliferation via activation of p53 mediated by upregulation of MEG3.