DNA methylation, CpG dinucleotides, CpG islands

In mammalian cells, most DNA methylation occurs on CpG dinucleotides⁽ Reference Lister, Pelizzola and Dowen ^{63 )}. Regions enriched in CpG dinucleotides are known as CpG islands. However, the definitions of CpG islands have been evolving. In 1987, Gardiner-Garden and Frommer⁽ Reference Gardiner-Garden and Frommer ^{64 )} defined CpG island as ‘a stretch of DNA sequence where moving average of % G + C was >50, and the moving average of ratio of the observed to expected CpG was greater than 0·6.’ These calculations are based on a 100 bp window and sliding across the sequence at 1 bp intervals. However, in regions rich in repetitive elements, this definition results in an overestimation of its presence. Therefore, Takai and Jones set up more stringent criteria for CpG islands, including % G + C>55, ratio of observed to expected CpG greater than 0·65 and sequence length being ≥500 bp. With Takai and Jones’ criteria, a web page service algorithm CpGIS was developed⁽ Reference Takai and Jones ^{65 )}. Furthermore, Ponger and Mouchiroud⁽ Reference Ponger and Mouchiroud ^{66 )} extended their criteria to estimate the transcription start sites associated CpG islands with the algorithm CpGProD. However, both criteria are subjective and computationally inefficient for the analysis of the genome-wide DNA sequences, so a new definition, named CpGcluster⁽ Reference Hackenberg, Previti and Luque-Escamilla ^{67 )}, was proposed. This algorithm is based on the distance between two consecutive CpG and uses an integer arithmetic algorithm, which makes it fast and computationally efficient compared to previous methods. However, it has low sensitivity. Recently, a new algorithm CpG_MI⁽ Reference Su, Zhang and Lv ^{68 )} was developed to take into account more variability of the test such as different locations of CpG dinucleotide among different CpG islands. With the growing availability of the experimental results of DNA methylation, the prediction of DNA methylation based on machine learning approach is possible. More specifically speaking, EpiGRAPH⁽ Reference Bock, Halachev and Buch ^{69 )} algorithm for prediction of DNA methylation was trained by the wet-lab experiments data, and then this algorithm could be used to predict the methylation probability of another stretch of DNA sequence.

DNA methylation and genetic variants

It has been shown that proximal sequence elements are both necessary and sufficient for regulating DNA methylation⁽ Reference Lienert, Wirbelauer and Som ^{70 )}. Moreover, SNP can regulate DNA methylation⁽ Reference Wang, Ogawa and Wood ^{71 –} Reference Kerkel, Spadola and Yuan ^{77 )}. For example, the C allele of a SNP located within the promoter region of matrix metalloproteinase 1 was shown to have significantly higher DNA methylation status than the corresponding T allele⁽ Reference Wang, Ogawa and Wood ^{71 )}. Also, the G allele of one SNP located within the potassium-chloride co-transporter 3 (KCC3, SLC12A6) was found to be methylated at the adjacent C nucleotide⁽ Reference Moser, Ekawardhani and Kumsta ^{72 )}.

Systematic analyses of the whole human genome have identified an array of such genetic variants having regulatory effects on DNA methylation patterns, indicating that genetic regulation on DNA methylation is prevalent across the whole genome. For instance, a genomic survey using methylation-sensitive SNP analysis based on a 50 and 250 K SNP genotyping platform showed that sixteen SNP-tagged loci were confirmed to have allele-specific DNA methylation events⁽ Reference Kerkel, Spadola and Yuan ^{77 )}. Also, in brain samples, approximately 10 % of the CpG sites included in the analysis were found to be affected by the genotypes of the SNP in cis-position, while 0·1 % of the analysed CpG sites were regulated by the genotypes of the SNP in the trans-position⁽ Reference Zhang, Cheng and Badner ^{74 )}. Furthermore, it was suggested by studies with sixteen human pluripotent and adult cell lines that approximately one-third (23–37 %) heterozygous SNP in the human genome may regulate DNA methylation patterns⁽ Reference Shoemaker, Deng and Wang ^{73 )}, and a big proportion of the observed loci with allele-specific DNA methylation events (38–88 %) is dependent on the allele status of CpG-related SNP, a type of SNP with one allele to disrupt and the other allele to create CpG dinucleotides⁽ Reference Shoemaker, Deng and Wang ^{73 )}. Finally, the effect of genetic variants outweighed the influence of imprinting on DNA methylation, because it was shown that the number of methylation loci affected by genetic variants were way more than those loci influenced by the sex of parent of origin⁽ Reference Gertz, Varley and Reddy ^{75 )} and there is convincing evidence of the interesting interdependence between genetics and epigenetics underlying diversity in the human genome.⁽ Reference Hellman and Chess ^{78 )}

DNA methylation within promoter regions and gene transcription

The negative correlation between DNA methylation and gene transcription is common to most genetic regions across the whole genome with rare exceptions⁽ Reference Eden and Cedar ^{79 ,} Reference Razin and Cedar ^{85 )}. The first experiment indicating the transcription-regulatory effects of DNA methylation was conducted by McGhee and Ginder⁽ Reference McGhee and Ginder ^{86 )}. Since then, a large body of evidence has accumulated supporting an inverse correlation between DNA methylation and gene transcription for most genes, including but not limited to house-keeping genes⁽ Reference Stein, Sciaky-Gallili and Razin ^{87 )}, genes located on the inactive X chromosome⁽ Reference Toniolo, D'Urso and Martini ^{88 –} Reference Wolf, Dintzis and Toniolo ^{90 )}, imprinted genes⁽ Reference Kerkel, Spadola and Yuan ^{77 ,} Reference Orozco, Rubbi and Martin ^{91 )}, tumour suppressor genes or oncogenes⁽ Reference Yamada, Nishida and Tsutsumida ^{92 –} Reference Harada, Toyooka and Maitra ^{94 )}, cellular differentiation and development-related genes⁽ Reference Lu, Wang and Chen ^{95 –} Reference Nishino, Hattori and Tanaka ^{98 )}, metabolic genes⁽ Reference Devlin, Singh and Wade ^{35 ,} Reference Brons, Jacobsen and Nilsson ^{53 ,} Reference Laker, Lillard and Okutsu ^{99 –} Reference Ling, Del Guerra and Lupi ^{101 )} and inflammation-related genes⁽ Reference Nile, Read and Akil ^{59 ,} Reference Tekpli, Landvik and Anmarkud ^{102 –} Reference El Gazzar, Yoza and Hu ^{105 )}. However, in some instances, DNA methylation has been positively correlated with gene expression⁽ Reference Bell and Felsenfeld ^{106 –} Reference Bahar Halpern, Vana and Walker ^{110 )}. Most of such transcriptional regulation effects were related to DNA methylation within promoter regions⁽ Reference Portela and Esteller ^{30 )} by direct blocking the binding of transcriptional activators or indirect recruitment of methyl-binding proteins and co-repressor complexes to facilitate the formation of heterochromatin in a cooperative way⁽ Reference Klose and Bird ^{111 )}.

DNA methylation within gene bodies and alternative promoter and splicing events

DNA methylation is also found on CpG sites located within gene bodies⁽ Reference Maunakea, Nagarajan and Bilenky ^{82 ,} Reference Deaton, Webb and Kerr ^{112 –} Reference Liang, Song and Ghosh ^{114 )}, suggesting a potential genetic function besides gene transcription. By comparing differential DNA methylation patterns on a genome-wide scale across different tissues (brain, heart, liver and testis) and different developmental stages of mice, approximately 16 % of the identified tissue differential methylation regions or developmental stage differential methylation regions were located within intragenic regions⁽ Reference Liang, Song and Ghosh ^{114 )}. Also, it was found that the majority of methylated CpG sites were located within gene bodies⁽ Reference Maunakea, Nagarajan and Bilenky ^{82 ,} Reference Deaton, Webb and Kerr ^{112 ,} Reference Illingworth, Kerr and Desousa ^{113 ,} Reference Rauch, Wu and Zhong ^{115 )}. According to analysis with human normal tissues (whole blood, monocyte, granulocyte, skeletal muscle, spleen and brain), 15·4 % of CpG islands located within the gene bodies were found to be methylated, which is higher than the proportion of methylated CpG islands within 5′ promoter region (7·8 %) and the whole gene region (10·6 %)⁽ Reference Illingworth, Kerr and Desousa ^{113 )}. Using human brain tissue, Maunakea et al. ⁽ Reference Maunakea, Nagarajan and Bilenky ^{82 )} generated high-resolution methylome maps with dense coverage of 24·7 million of the 28 million CpG sites across the whole genome. They found that 34 % of all intragenic CpG islands were methylated, whereas only 2 % of the CpG islands located within the 5′ promoter regions were methylated, so they concluded that ‘DNA methylation may serve a broader role in intragenic compared with 5′ promoter CpG islands in the human brain’. Again, the altered DNA methylation in the immune system was shown to occur predominantly at CpG islands within gene bodies based on the analysis with both mouse cells within haematopoietic lineage⁽ Reference Deaton, Webb and Kerr ^{112 )} and human B cells⁽ Reference Rauch, Wu and Zhong ^{115 )}.

The methylation within gene bodies may be related to alternative promoters⁽ Reference Maunakea, Nagarajan and Bilenky ^{82 )} and alternative splicing events⁽ Reference Maunakea, Chepelev and Cui ^{80 ,} Reference Gelfman and Ast ^{81 ,} Reference Shukla, Kavak and Gregory ^{83 ,} Reference Anastasiadou, Malousi and Maglaveras ^{84 )}. Based on methylome maps of human brain tissues, differentially methylated intragenic CpG islands may act as promoters, and novel transcripts have been found to be initiated from these intragenic promoters, indicating that intragenic methylation functions to regulate cell context-specific alternative promoters in gene bodies⁽ Reference Maunakea, Nagarajan and Bilenky ^{82 )}. With a computational analysis of human chromosome 6, 20 and 22 based on datasets from the Human Epigenome Project and the Human Genome Project, hypermethylated CpG sites were found to be prevalent in alternatively spliced sites, and the frequency of methylation increases in loci harbouring multiple putative exonic splicing enhancers⁽ Reference Anastasiadou, Malousi and Maglaveras ^{84 )}. According to the analysis of data from RNA-seq experiments and methylome data with single nucleotide resolution of human cell lines, DNA methylation was found to be enriched in included alternatively spliced exons, and inhibition of DNA methylation lead to aberrant splicing of alternatively spliced exons. Further, they found that the alternative splicing may be because of the alternative definitions of exons via recruitment of methylated CpG site-binding protein 2 to the methylated CpG sites⁽ Reference Maunakea, Chepelev and Cui ^{80 )}. Another potential mechanism for the regulation of DNA methylation on alternative splicing events may be the fact that DNA methylation patterns affect chromatin structure⁽ Reference Gelfman and Ast ^{81 )}. Finally, a DNA methylation related protein, CCCTC-binding factor, was shown to promote alternative splicing events on a genome-wide scale, providing potential links between DNA methylation and alternative splicing events⁽ Reference Shukla, Kavak and Gregory ^{83 )}.

DNA methylation and ageing

DNA methylation is affected by ageing partially because of its intimate relationship with development. DNA methylation patterns change during each stage of development⁽ Reference Cedar and Bergman ^{116 )}. Before implantation, almost all DNA methylation becomes erased except for those imprinting regions. During implantation, the entire genome gets methylated except for the CpG islands. After implantation, pluripotency genes are de novo methylated and tissue-specific genes are demethylated in the cell types for their expression.

The correlations between ageing and DNA methylation were also suggested by in vitro studies. For example, compared to immortal cell lines, normal diploid fibroblasts were found to have a dramatic decrease in their 5-methylcytosine contents during their growth in culture⁽ Reference Wilson and Jones ^{117 )}. Furthermore, the observation that the decrease rate in mouse primary diploid fibroblasts was faster than in hamsters and human subjects and the fact that mouse has the shortest lifespan suggested that the rate of loss of 5-methylcytosine is positively correlated with growth potential. Also, the treatment of human diploid fibroblasts with DNA methylation inhibitors, azacytidine and azadeoxycytidine, were shown to inhibit the initial cellular growth⁽ Reference Holliday ^{118 )}.

Recently, epidemiological analyses have indicated the potential relationships between ageing and DNA methylation patterns. A cross-sectional study with monozygotic twins⁽ Reference Fraga, Ballestar and Paz ^{33 )} found that younger twins have significantly lower levels of 5-methylated cytosines than older twins, and that the variance of DNA methylation of the older twins was significantly greater than that of the younger twins. The observed differences in DNA methylation were consistent with the findings with gene expression by showing that the 50-year-old twins had dramatically different expression profiles while the 3-year-old twins had almost identical ones. The observed discordance of DNA methylation with age was consistent across different tissues within the analysis, including lymphocytes, epithelial mouth cells, intra-abdominal fat and skeletal muscle biopsies. Later, another study with thirty-four male monozygotic twins with age ranging from 21 to 55 years identified eighty-eight sites located within or near eighty genes of which DNA methylation patterns were significantly correlated with age⁽ Reference Bocklandt, Lin and Sehl ^{119 )}. Three genes from that list of eighty genes were further validated and replicated with the analysis of their correlations with age in a population-based sample of thirty-one males and twenty-nine females with age ranging from 18 to 70 years, which are Edar-associated death domain, target of myb1 (chicken)-like 1 and neuronal pentraxin II. Interestingly, all of these three genes have been reported to be associated with a wide array of age-related phenotypes, such as wound healing⁽ Reference Langton, Herrick and Headon ^{120 )}, Parkinson disease⁽ Reference Moran, Hickey and Michael ^{121 )}, cancer⁽ Reference Park, Ryu and Lee ^{122 ,} Reference Qi, Li and Zhao ^{123 )}, and loss of teeth, hair and sweat glands⁽ Reference Yan, Zhang and Brady ^{124 )}. Also, a longitudinal study found that DNA methylation differs by age because methylation patterns of candidate genetic loci, such as the dopamine receptor 4 gene, the serotonin transporter gene, and the X-linked monoamine oxidase A gene, were shown to change during the period when these children grew from age 5 to 10 years⁽ Reference Wong, Caspi and Williams ^{34 )}.

Finally, changes in DNA methylation patterns have been reported to be associated with a series of age-related diseases. The evidence suggests that global hypomethylation and gene-specific promoter hypermethylation were associated with different types of cancer. It was found that the number of a subpopulation of cells in human colonic mucosa increase with age, and the promoter of oestrogen receptor gene in this subpopulation of cells becomes hypermethylated. This age-related hypermethylation of oestrogen receptor was found in all cells in colorectal tumours examined⁽ Reference Issa, Ottaviano and Celano ^{125 )}. Also, age-dependent methylation of oestrogen receptor alpha was associated with prostate cancer⁽ Reference Li, Shiina and Deguchi ^{126 )}. The hypermethylation of several tumour suppressor genes have been suggested as biomarkers of lung cancer⁽ Reference Belinsky ^{127 )}. Alzheimer's disease was correlated with DNA methylation of CpG sites located near or within the genetic loci reported to harbour genetic susceptible risk variants for Alzheimer's disease⁽ Reference De Jager, Srivastava and Lunnon ^{128 )}. Compared with the normal retinas, those of patients with age-related macular degeneration were found to have hypermethylation and gene repression of glutathione S-transferase isoform mu1 and glutathione S-transferase isoform mu5⁽ Reference Hunter, Spechler and Cwanger ^{129 )}.

DNA methylation and fatty acids

FA affect expressions of a wide array of genes by acting as ligands for transcription factors, such as PPAR, the liver X receptors (LXR), retinoid X receptor, hepatocyte NF 4, sterol regulatory element-binding proteins (SREBP), NF-κ-light-chain enhancer of activated B cells, cyclooxygenase and lipoxygenase⁽ Reference Calder ^{130 )}. PPAR and LXR are members of the nuclear hormone receptor superfamily of transcription factors, which bind to specific motifs within the promoters of genes as heterodimers with the retinoid X receptor⁽ Reference Kidani and Bensinger ^{131 )}. There are three isoforms of PPAR, including PPARα, PPARβ and PPARγ. In general, PPAR bind with both saturated and unsaturated FA with a relatively more potent binding with n-6 and n-3 PUFA and their derivatives to regulate expressions of genes that control lipid and glucose homeostasis and inflammation. Regarding LXR, there are two family members, LXRα and LXRβ. As a sensor of cholesterol in the nucleus, LXR can be activated by increased intracellular cholesterol concentrations. Also, the binding of long-chain FA to LXR⁽ Reference Janowski, Grogan and Jones ^{132 )} was shown to regulate expression of genes involved in sterol and FA metabolism⁽ Reference Geyeregger, Zeyda and Stulnig ^{133 )}, lipogenesis⁽ Reference Peet, Turley and Ma ^{134 –} Reference Yoshikawa, Shimano and Yahagi ^{137 )}, carbohydrate metabolism⁽ Reference Laffitte, Chao and Li ^{138 ,} Reference Cao, Liang and Broderick ^{139 )}. Hepatocyte NF 4α is an orphan member of the steroid hormone receptor superfamily and functions by binding with the activated (CoA) form of FA to regulate expression of genes participating in the lipid, lipoprotein⁽ Reference Naiki, Nagaki and Shidoji ^{140 ,} Reference Krapivner, Iglesias and Silveira ^{141 )} and glucose metabolism⁽ Reference Boj, Parrizas and Maestro ^{142 ,} Reference Odom, Zizlsperger and Gordon ^{143 )}. SREBP have three isoforms, which are SREBP-1a, SREBP-1c and SREBP-2, and all of them are transcription factors playing a critical role in controlling synthesis of FA, TAG and cholesterol⁽ Reference Goldstein, DeBose-Boyd and Brown ^{144 )}. PUFA were found to lower the mature form of the protein levels of SREBP by raising cellular cholesterol levels or by reducing SREBP mRNA stability and SREBP transcription or by promoting degradation of SREBP protein⁽ Reference Thewke, Panini and Sinensky ^{145 –} Reference Yahagi, Shimano and Hasty ^{148 )}. Cyclooxygenase and lipoxygenase function to convert n-6 and n-3 PUFA into pro- and anti-inflammatory signalling molecules to regulate activity of transcription factors of inflammation such as NF-κ-light-chain enhancer of activated B cells⁽ Reference Patterson and Georgel ^{149 )}.

The effect of FA on DNA methylation was also suggested by a study with mice heterozygous for disruption of cystathionine beta-synthase (Cbs ^+/−)⁽ Reference Devlin, Singh and Wade ^{35 )}, which could be induced to have hyperhomocysteinaemia (HHcy), providing an indirect evidence because of the potential modifications on DNA methylation by homocysteine through its participation in the C₁ metabolism. In that study, a dosage of HHcy (normal, mild and moderate) was developed by treating the mice (Cbs ^+/+) with control diet (normal), the mice (Cbs ^+/+) with diet to induce HHcy (mild) and the mice (Cbs ^+/−) with diet to induce HHcy (moderate). The potential relationship between homocysteine and DNA methylation was supported by the significantly inverse correlation between total homocysteine levels and liver methylation capacity, measured by the ratio of S-adenosylmethionine to S-adenosylhomocysteine. Correspondingly, mice with moderate HHcy had higher methylation of candidate CpG sites within the promoter region of FA desaturase 2 in liver, leading to lower gene expression of  FA desaturase 2 and lower protein activity of δ(6)-desaturase (encoded by FA desaturase 2) in liver, compared with mice with mild and normal HHcy. Also, mice with moderate HHcy have lowest level of arachidonic acid and DHA in total liver than those mice with mild and normal HHcy.

Direct evidence for the link between FA and DNA methylation were conducted with in vitro and in vivo studies. Incubation of human skeletal muscle cells with 48 h treatment with free FA, such as palmitate and oleate, can increase DNA methylation levels of the promoter region of PPARγ coactivator-1α in primary human skeletal cells, leading to suppression of its gene expression⁽ Reference Barres, Osler and Yan ^{36 )}. Also, in vitro treatment of U937 leukemia cells with EPA was found to decrease methylation of the promoter regions of a myeloid lineage-specific transcription factor CCAAT/enhancer-binding protein, a tumour suppressor gene, resulting in an increased gene expression⁽ Reference Ceccarelli, Racanicchi and Martelli ^{37 )}. One in vivo study with rats found that feeding a diet high in n-3 PUFA, mainly with EPA and DHA could significantly decrease global DNA methylation levels⁽ Reference Kulkarni, Dangat and Kale ^{150 )}.

A randomised control trial with high-fat overfeeding in young adults with low or normal birth-weight supported a relationship between FA and DNA methylation. Having high-fat overfeeding (+50 % energy) for 5 d increased DNA methylation in the promoter region of PPARGC1A, measured in the skeletal muscle cells extracted from healthy young men with low birth-weight⁽ Reference Brons, Jacobsen and Nilsson ^{53 )}. The observed induction of DNA methylation in PPARGC1A was found to be reversible because DNA methylation returned to its baseline level after the high-fat diets were withdrawn. Although DNA methylation of PPARGC1A was not found to have significant correlation with its gene expression, high-fat challenge in the subjects with low birth-weight were shown to induce peripheral insulin resistance and decrease gene expression of PPARGC1A.

DNA methylation and other environmental factors

Besides ageing and dietary FA, DNA methylation patterns are modifiable by several other environmental factors, including global nutrition status, air pollution, weather and smoking. In mice, supplementation of methyl donors during gestation was shown to have a dose–response relationship with the methylation of viable yellow agouti (A^vy ) locus and browness of coat colour in the offspring⁽ Reference Waterland and Jirtle ^{45 )}. Energy restriction in utero decreased the overall methylation and changes in the methylation patterns of imprinted loci in mice⁽ Reference Chen, Ganguly and Rubbi ^{151 )}. Similarly in human subjects, those subjects having experienced famine prenatally because of their in utero exposure to the Dutch Hunger Winter were shown to have less DNA methylation of the imprinted gene, insulin-like growth factor 2⁽ Reference Heijmans, Tobi and Stein ^{39 ,} Reference Tobi, Lumey and Talens ^{40 )}. Moreover, increased concentrations of ozone and components of fine particle mass were associated with hypomethylation of tissue factor (F3), intercellular adhesion molecule 1 and toll-like receptor 2 and hypermethylation of interferon-γ and IL6 ⁽ Reference Bind, Lepeule and Zanobetti ^{152 )} and with decreases in global DNA methylation in whole blood⁽ Reference De Prins, Koppen and Jacobs ^{153 )}. A genome-wide analysis followed by an independent replication study showed that smokers have decreased level of DNA methylation of a single CpG site located within the coagulation factor II (thrombin) receptor-like 3 (F2RL3)⁽ Reference Breitling, Yang and Korn ^{50 )}. Also, methylation of tumour suppressor genes, cyclin-dependent kinase inhibitor 2A (p16) and death-associated protein kinase might lead to lung cancer⁽ Reference Belinsky, Palmisano and Gilliland ^{51 )}. Sun exposure was associated with the phenotypic changes related with skin ageing by their modifications of DNA methylation across the genome⁽ Reference Gronniger, Weber and Heil ^{49 )}. Finally, individuals with in utero exposure to rainy season in rural Gambia were shown to increase methylation of genetic regions contributing to the dramatic and systemic inter-individual variations in epigenetic regulation⁽ Reference Waterland, Kellermayer and Laritsky ^{38 )}.

DNA methylation and inflammation

Accumulating evidence supports that DNA methylation patterns are associated with inflammatory markers, such as IL6 ⁽ Reference Nile, Read and Akil ^{59 ,} Reference Tekpli, Landvik and Anmarkud ^{102 ,} Reference Peluso, Bollati and Munnia ^{154 –} Reference Stefani, Viana and Dupim ^{156 )}, IL1β ⁽ Reference Tekpli, Landvik and Anmarkud ^{102 )}, and IL8 ⁽ Reference Tekpli, Landvik and Anmarkud ^{102 )} and high-sensitivity C-reactive protein⁽ Reference Kim, Bhattacharjee and Khalyfa ^{157 )}, vascular cell adhesion molecule-1⁽ Reference Baccarelli, Tarantini and Wright ^{158 )}. A case–control study found that patients with rheumatoid arthritis have lower DNA methylation levels of a CpG site, which was located at −1099 bp to the transcription start site of IL6, measured in peripheral blood mononuclear cells. In the macrophages from healthy control subjects, lower methylation of the previously identified CpG site was in line with the higher IL6 expression stimulated by lipopolysaccharide. Experiments with electrophoretic mobility shift assay provided potential mechanistic explanation for these associations by identifying the methylation-dependent affinity of protein–DNA interactions⁽ Reference Nile, Read and Akil ^{59 )}. In vitro treatment of 5-aza-2′-deoxycytidine activated IL6 expression in human pancreatic adenocarcinoma cell lines, indicating an important role of DNA methylation at the IL6 genetic locus⁽ Reference Dandrea, Donadelli and Costanzo ^{60 )}. Also, chromatin immune-precipitation assays with the same cell lines identified a potential response element to the binding of methyl-CpG-binding protein 2, located from −666 to −426 bp to the transcription start sites, providing potentially a mechanistic explanation for the DNA methylation of IL6 ⁽ Reference Dandrea, Donadelli and Costanzo ^{60 )}. A cross-sectional study with blood leucocyte found that workers living in an industrial area had the lowest, whereas rural and urban residents had the highest and intermediate methylation levels of the second intron of IL6 ⁽ Reference Peluso, Bollati and Munnia ^{154 )}. Another cross-sectional study with leucocytes found that a prudent diet, characterised by a high intake of vegetables and fruit, was associated with DNA methylation levels of the promoter region of IL6 ⁽ Reference Zhang, Santella and Wolff ^{155 )}. According to the analysis of DNA methylation patterns of IL6 in periodontal tissues, patients with periodontitis were found to have lower methylation and higher gene expression⁽ Reference Stefani, Viana and Dupim ^{156 )}. An in vitro study with cultured human lung cells showed that the DNA methylation levels of promoter regions of a panel of inflammation related genes (IL6, IL1β and IL8) were higher in cancer cells than normal ones, and the higher methylations went along with the lower gene expressions⁽ Reference Tekpli, Landvik and Anmarkud ^{102 )}. A study with patients with paediatric obstructive sleep apnoea found that DNA methylation of forkhead box P3 had a significantly positive correlation with serum levels of high-sensitivity C-reactive protein⁽ Reference Kim, Bhattacharjee and Khalyfa ^{157 )}. A cross-sectional study with blood samples from 742 community-dwelling elderly individuals found that hypomethylation of repetitive element LINE-1 was associated with increased levels of serum vascular cell adhesion molecule-11⁽ Reference Baccarelli, Tarantini and Wright ^{158 )}. Finally, a study with samples of leucocytes from 966 African American identified that DNA methylations of 257 CpG sites within 240 genes contribute to serum levels of C-reactive protein ⁽ Reference Sun, Lazarus and Smith ^{159 )}.

DNA methylation and dyslipidaemia

DNA methylation patterns have been related to dyslipidaemia⁽ Reference Lund, Andersson and Lauria ^{55 ,} Reference Panin, Tuzikov and Gimautdinova ^{56 ,} Reference Irvin, Zhi and Joehanes ^{160 ,} Reference Guay, Brisson and Munger ^{161 )}. After stimulation with lipoproteins, the global levels of 5-methylated cytosines within the differentiated human monocyte-macrophage cell line THP-1 were significantly increased⁽ Reference Lund, Andersson and Lauria ^{55 )}. According to a genome-wide DNA methylation analysis with samples of CD4⁺ cells from 991 individuals of the Genetics of Lipid-lowering Drugs and Diet Network (GOLDN) study, four CpG sites located within the intron 1 of carnitine palmitoyltransferase 1A were found to be associated with fasting levels of VLDL-cholesterol and TAG. DNA methylation of the CpG site with top findings was further found to be associated with carnitine palmitoyltransferase 1A expression. The observed association between DNA methylation, gene expression and fasting TAG was replicated in the Framingham Heart Study⁽ Reference Irvin, Zhi and Joehanes ^{160 )}. Also, a higher methylation pattern of the promoter region of ATP-binding cassette A1 (ABCA1) in samples of whole blood was found to be associated with a lower circulating HDL-cholesterol and HDL2-phospholipid levels in ninety-seven patients with familial hypercholesterolaemia⁽ Reference Guay, Brisson and Munger ^{161 )}. Similarly in patients with familial hypercholesterolaemia, leucocyte DNA methylations of lipoprotein lipase had positive correlations with HDL-cholesterol and HDL particle size, whereas DNA methylation of cholesteryl ester transfer protein had a negative association with LDL-cholesterol in all the participants and negative associations with HDL-cholesterol, HDL-TAG levels, and HDL particle size⁽ Reference Guay, Brisson and Lamarche ^{162 )}. Further, the methylations of lipoprotein lipase in visceral adipose tissue extracted from thirty men with severe obesity were found to have negative correlations with HDL-cholesterol and gene expression of lipoprotein lipase⁽ Reference Guay, Brisson and Lamarche ^{162 )}. The potential mechanism for the effects of lipoproteins on DNA methylation is unknown. The modifications of chromatin structure may account as one potential mechanism, because it was found that ApoA1 can physically bind to a CG-rich oligonucleotide in vitro, leading to the remodelling of chromatin structure⁽ Reference Panin, Tuzikov and Gimautdinova ^{56 )}.