Austin Endocrinol Diabetes Case Rep. 2016; 1(1): 1004.
Samer El-Kaissi*, Christine Hughes and Hussein Saadi
Cellular and Molecular Endocrine Research Center, Shahid Beheshti University of Medical Sciences, Iran
*Corresponding author: Mehdi Hedayati, Cellular and Molecular Endocrine Research Center (CMERC), Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Received: November 16, 2016; Accepted: December 08, 2016; Published: December 09, 2016
Diabetes mellitus has become one of the most common chronic diseases across the globe, especially in developing countries. Type 2 Diabetes Mellitus (T2DM) depends on multiple genetic loci as well as environmental factors; it is known as a complex polygenic disorder. Patterns of inheritance suggest that T2DM is both polygenic and heterogeneous; multiple genes are involved and different combinations of genes play a role in different subsets of individuals. Overall, estimates have shown that 30-70% of T2DM risk can be ascribed to genetic factors. With the genetic variations, the environmental changes can lead to a disease phenotype by affecting the gene expression through epigenetic modifications. These changes associated with T2DM are therefore still poorly understood. Further insight into these associations will improve the variety and quality of existing predictive T2DM biomarkers, thereby increasing the possibilities to postpone or prevent T2DM in the individuals at high risk for the disease. Nevertheless, epigenetics may play an important role in the growing incidence of T2DM, and over the next few years, it will be a great challenge to dissect the role of DNA methylation, histone modifications, and non-coding RNAs in the pathogenesis of the disease and its complications.
Keywords: Genetics; Epigenetics; Type 2 diabetes mellitus
Diabetes mellitus has become one of the most common chronic diseases in human populations across the globe, especially in the modern societies, with a prevalence of 6.5%, representing 285 million adults in 2010 . In 2015, according to International Diabetes Federation (IDF) Atlas, about 415 million adults worldwide had diabetes. It is estimated that by 2030, the number will be rising to 366 million and shows that diabetes mellitus will become an epidemic, reaching a prevalence of 7.7% .
Diabetes mellitus is a syndrome of disordered metabolism with abnormally high blood glucose levels (hyperglycemia) . Two most common forms of diabetes are Type 1 Diabetes (T1D) (absent production of insulin) and Type 2 Diabetes Mellitus (T2DM) (diminished insulin secretion and followed by decline of the beta cell mass). However, other rare forms of diabetes are inherited directly that includes Maturity Onset Diabetes in the Young (MODY) and diabetes due to mutations in mitochondrial DNA. Most diabetes (~90%) is T2DM caused by a combination of impaired insulin secretion from pancreatic β-cells and insulin resistance of the peripheral target tissues, especially muscle and liver. This form of diabetes is most often associated with age, obesity (i.e. increased abdominal fat), family history of diabetes, hypertension, history of gestational diabetes, lack of physical activity, and ethnic background .
Type 2 diabetes mellitus depends on multiple genetic loci as well as environmental factors and is known as a complex polygenic disorder (Figure 1). The environmental disorders can lead to a disease phenotype by affecting gene expression through epigenetic modifications . Epigenetic modifications of the genome provide a mechanism that allows the stable proliferation of gene expression from one generation of cells to the next . From the genetic point of view, the genetic risk influenced by the conjoint effects of variation at an undetermined number of genomic sites, some with an affecting and some with a protective effect. Genome-wide studies identified many genetic loci associated with T2DM . However, it is not clear how many genes are involved or how much control each gene exerts over the development of the disease, but several researchers have identified several promising candidates [3,7-14]. In this review, we first consider the evidence in favor of a genetic basis for T2DM, focusing specifically on the specific DNA sequence variants that have been implicated in risk predisposition. Second, we critically review the evidence supporting a role for T2DM epigenetic mechanisms.
Figure 1: Model proposing a role for epigenetic mechanisms in the pathogenesis of T2DM.
A review of the literature was conducted to identify all English language studies published between 2000-2015 on genetics and epigenetics in T2DM in the databases Medline, Embase, and PubMed. We considered all types of original published studies, reviews, and meta-analysis studies and excluding case reports, clinical trials, and conference abstracts. Duplicate publications were eliminated and eligible records were screened independently, first by title and abstract followed by full text. Overall, 1075 articles were found that 87 eligible articles were selected. Search terms included (diabetes mellitus, type 2 OR diabet*) AND genetics AND/OR epigenetics (DNA methylation, histone modification, microRNA).
With progression in genotyping, sequencing techniques, and in the statistical handling of data, different approaches have been used to recognize the genetic influences in T2DM. Current methods classify these influences into two main categories include 1) analysis of genomic regions shared by relatives more often than expected (so called linkage analysis using polymorphic markers such as microsatellites or tandem repeats) and 2) candidate gene studies, particularly by attempts to correlate biological variation (phenotype) with variation in DNA sequences (genotype) as a Single Nucleotide Polymorphism (SNP). The first approach (genome-wide studies) includes both Genome-Wide Linkage Studies (GWLS) and Genome- Wide Association Studies (GWAS) . With these methods, 20 common genetic variants have been recognized in association with T2DM in 2009 .
Genome linkage analysis is a genetic method that tests the cosegregation of a chromosomal region by genotyping several hundred microsatellite markers with a disease locus expanded all over the genome on families with two or more affected siblings. Moreover, this method was used to identify genes associated with disorders, and has been very successful for mapping genes with strong penetrance and a known inheritance mode that underlie monogenic ‘Mendelian’ diseases , but it has been less useful for identifying genes that cause complex diseases such as T2DM . Although great efforts have been put into linkage studies of T2DM, only 2 genes have been reported by linkage: Transcription Factor 7-Like 2 (TCF7L2) and Calpain 10 (CAPN10). The association between T2DM and a number of TCF7L2 SNPs has been confirmed in numerous studies in different ethnic groups [19,20]. In 2006, deCODE genetics identified common variation in the TCF7L2 gene to have a substantial effect on T2DM susceptibility. People who carry one copy of a variant TCF7L2 have an approximately 1.5 times increased risk of T2DM, while subjects who carry two copies of a variant have an about 2.4 times increased risk .
In 2000, the results of a genome-wide screen for T2DM genes showed that a gene located in the NIDDM1 region had association with the disease which encodes a ubiquitously expressed member of the calpain-like cysteine protease family, CAPN10, with largely unknown functions in glucose metabolism . Despite several negative replication studies, several meta-analyses have shown a consistent association of CAPN10 with T2DM. Nevertheless, CAPN10 has not been confirmed as a candidate gene for T2DM by the large GWAS [19,23].
Genome-wide association is a special type of association study that searches the whole genome (or at least most of it) for causal genetic variants and it can be attempted even without persuading evidence regarding the function or location of the candidate causal genes . This approach became possible as a result of the completion of the human genome sequence in 2001 [25,26], the creation of SNP Linkage Disequilibrium (LD) maps by the International HapMap Project , and great advancements in microarray-based genotyping technology and statistical tools due to the vast amount of genetic variants . The Diabetes Genetics Replication and Meta-Analysis (DIAGRAM) consortium combined the data from the three GWAS. Through meta-analysis followed by large-scale replication, six additional T2DM susceptibility genes were detected . The results of the first GWAS on T2DM were published in 2007 by Sladek et al . This GWAS was conducted in 661 cases and 614 controls from France and led to identification of two new diabetes loci: 1) Hematopoietically Expressed Homeobox (HHEX) and 2) solute carrier family 30 (zinc transporter that makes zinc available for co-crystallization with and subsequent secretion of insulin) member 8 (SLC30A8). Another gene was Peroxisome Proliferator-Activated Receptor Gamma (PPARγ) which is the first gene reproducibly associated with T2DM . To date, more than 70 susceptibility loci have been detected by GWAS via establishing large research consortia using intermediary diabetes phenotypes (e.g. fasting glucose) and applying study samples of different ethnicities and delivered a whole set of new susceptibility loci for T2DM over the last five years [32-34].
The trans-ethnic meta-analysis comprised from different ethnicity (European, East Asian, South Asian, Mexican, and Mexican- American ancestry) showed excess in the directional consistency of T2DM risk alleles across ancestry groups. Seven new T2DM susceptibility loci were identified by following up the strongest signals of association from the trans-ethnic meta-analysis of European ancestry (rs6813195, rs17106184, rs3132524, rs9502570, rs1727313, rs6808574, and rs702634) . Some validated T2DM susceptibility loci are summarized along with their discovery method, cellular function and putative intermediary mechanism in diabetes (Table 1).
Cellular function and putative intermediary mechanism in diabetes
Encodes the prospero-related homeobox 1. Implicated in cell proliferation and development. Associated with elevated FG.
Transmembrane receptor implicated in pancreatic organogenesis; regulates cell differentiation.
The function of this family of transmembrane proteins has not, as yet, been determined. However, it is thought to decrease Beta Cell Function. Diabetogenic impact of the C-allele of TMEM154-rs6813195 is mediated through reduced beta cell function.
Interaction of TNFSF6 with the FAS antigen (TNFRSF6) mediates programmed cell death.
Adaptor protein binding to insulin receptor and insulin-like growth factor receptors to inhibit kinase signaling. Associated with reduced insulin sensitivity.
Involved in both B- and T-lymphocyte development and β-cell function. Affects insulin response to glucose.
Encodes RNA-binding motif, single-stranded interacting protein 1. Implicated in DNA replication, gene transcription, cell cycle progression and apoptosis. Unknown diabetogenic mechanism.
Glucokinase regulatory protein. Involved in signal transduction, glucose transport and sensing. Associated with FG, fasting insulin and HOMA-IR.
Encodes insulin receptor substrate-1. Associates with reduced adiposity and impaired metabolic profile (e.g. visceral to subcutaneous fat ratio, IR, dyslipidemia, CVD, adiponectin levels).
Thyroid adenoma-associated gene. Associates with PPAR; Involved in apoptosis. Associated with β-cell dysfunction, lower β-cell response to GLP-1 and reduced β-cell mass.
Enzyme located in Golgi apparatus, involved in post-translational modification of cell-surface components by glycosylation.
Encodes adenylate cyclase 5. Involved in signal transduction. Associated with elevated FG.
Proteolytic enzyme. Affects insulin response to glucose. Primary effect on insulin action not driven by obesity.
Growth factor (IGF2-mRNA) binding protein. Involved inpancreatic development and stimulation of insulin action.
TRF involved in adipocyte development. TRF receptor for TZDs and prostaglandins. Effect on IR.
This protein also shuttles through the nucleus and may function as a transcriptional co-activator.
Endoplasmic reticulum transmembrane protein involved in stress and β-cell apoptosis. Insulin response.
Encodes an axin-interacting protein activating wnt/beta-catenin signaling. Unknown diabetogenic mechanism.
The function of ARL15 is not known yet.
Cyklin kinase (CDK5) inhibitor. Involved in cell cycle regulation in the β-cell. Insulin response.
The encoded protein is thought to function during the G1/S transition in the cell cycle. Alternate splicing results in multiple transcript variants.
Relevant to nephropathy susceptibility, RREB1 polymorphisms reportedly interact with APOL1 and associate with kidney function. Implicated with fat distribution and fasting glucose, effects potentially related to the observed T2DM associations.
Basic transcription element-binding protein. "Master switch" controlling other genes associated with BMI, insulin, glucose and cholesterol.
Encodes diacylglycerol kinase beta. Implicated in signal transduction. Associated with elevated FG.
Encodes the enzyme glucokinase. Involved in signal transduction, glucose transport and sensing. Associated with elevated FG and HbA1c.
Zinc-finger protein. Function as a transcriptional repressor. Associated with prostate cancer. Insulin response.
Encodes the p53-dependent damage-inducible nuclear protein. May regulate p53-dependent apoptosis. Unknown diabetogenic mechanism.
β-cell zinc transporter ZnT8. Involved in insulin storage and secretion. Associated with fasting proinsulin levels.
Encodes the transducin-like enhancer of split 4. Unknown diabetogenic mechanism.
Encodes the tyrosine phosphatase receptor type D protein. Associated with increased HOMA-IR and may affect insulin signaling on its target cells.
Cyclin-dependent kinase inhibitor and p15/16 tumor suppressor. Involved in islet development. Also associated with CVD and several cancers. Insulin response.
Multimeric protein involved in transport of proteins from endosomes to the trans-Golgi network. Expressed in pancreatic and adipose tissues.
Cell cycle kinase, required for S-phase entry. Affects different aspects of insulin response to glucose.
TRF involved i pancreatic development. Might influence both insulin release and insulin sensitivity.
TRF involved in wnt-signaling. Influencing insulin and glucagon secretion. Most important polygene identified for T2DM.
Associated with lower proinsulin levels, as well as lower β-cell function (HOMA-B and insulinogenic index).
Oncogene implicated in body size (height). Primary effect on insulin action not driven by obesity.
Receptor for melatonin. Involved in glucose homeostasis. Associated with increased FG and reduced β-cell function.
Encodes the pore-forming alfa subunit of IKaK+ channel. Insulin response.
Inwardly rectifying potassium channel. Risk allele impairs insulin secretion.
TRF essential for pancreatic β-cell development and function.
Cell surface glycoprotein implicated in GI cancers. Insulin response.
Inhibitor of tyrosine kinase signaling. Associated with body fat percentage. Homologs inhibit insulin receptor-transduced MAPK signaling. Regulates development of pancreas.
Clathrin-associated adaptor complex expressed in adipocytes and pancreatic islets. Involved in vesicle transport and sorting. Unknown diabetogenic mechanism
High mobility group non-histone chromosomal protein influencing histone methylation. Involved in neuronal development. Unknown diabetogenic mechanism.
Nuclear calcium-dependent domain-containing protein. Impairs glucose-stimulated insulin response. Associated with levels of fasting glucose and proinsulin.
Encodes a zinc finger AN1 Domain-containing protein. Unknown diabetogenic mechanism.
Protein regulating cytokinesis. Unknown diabetogenic mechanism.
2-oxoglutarate-dependent demethylase. Alters BMI i general population.
Encodes a serine racemase protein. May play a role in regulation of insulin and glucagon secretion.
TRF involved in development of the kidney, pancreas, liver, and Mullerian duct. Implicated in MODY and renal cyst. Associated with prostate cancer.
Nuclear TRF expressed in liver. Regulates transcription of several genes, e.g. HNF1A. Elevated hepatic glucose production. Defective pancreatic β-cell function and impaired insulin secretion.
MAP kinase phosphatase. Decreased insulin release for male risk allele carriers. Up-regulated during adipocyte differentiation. Involved in insulin signaling and stress induced IR.
Table 1: Laboratory values at hospital admission.
The candidate gene approach to conducting genetic association studies focuses on the known function of the genes. Several candidate genes identified in monogenic forms of diabetes proved to be also involved in the genetics of common forms of T2DM. The rare forms of diabetes include pregnancy, certain medications, or diseases such as MODY characterized by monogenic, autosomal dominant transmission and early age of onset. Although several studies have reported an association between functional and/or positional candidates, only some of them have been consistently associated with T2DM. The most robust candidate variants reported were the E23K variant in the KCNJ11 gene [36,37], the P12A variant in the PPARγ gene , and common variants in the HNF1B and the Wolfram Syndrome 1 (WFS1) genes [39,40]. Notably, rare mutations in all four genes cause monogenic forms of diabetes [41,42] and KCNJ11 and PPARγ are targets of anti-diabetic therapies. KCNJ11 encodes a component of the β-cell potassium channel that is a target for the sulphonylurea class of drugs and PPARγ encodes a transcription factor involved in adipocyte differentiation that is a target for the thiazolidinedione class of drugs [3,43].
Some different studies were considered as known risk factors for T2DM with different combinations. For instance, a correlation has been observed between Catechol-O-Methyl Transferase (COMT) polymorphism (900 I/D C) and the family history of T2DM in Pakistani Punjabi population . Zhang Y.H. et al showed a significant correlation between polymorphism of platelet alloantigen genes HPA-1, -2, -3, and -5 and T2DM complication of carotid atherosclerosis in 99 T2DM patients of Chinese population . A meta-analysis suggested that D allele of G1057D polymorphism in Insulin Receptor Substrate (IRS)-2 gene had a significant effect on reducing risk of T2DM . Moreover, Ninomiya H. et indicated an association between Monocyte Chemoattractant Protein-1 (MCP-1) A-2518G polymorphism and new onset of diabetic retinopathy in 758 T2DM patients in which the new onset of retinopathy increased with the increase of the number of G alleles . Furthermore, in another study, Amle D. et al observed that 18bp insertion/ deletion (I/D) polymorphism, at -2549 position of VEGF gene was associated with increased susceptibility to diabetic nephropathy in 40 T2DM patients . Besides, a study by Zhong X. et al showed a significant association between VDR rs2228570 polymorphism with the development of retinopathy in 204 Han Chinese population with T2DM . In another study, Fathi M. et al investigated the combination between Angiotensin Converting Enzyme (ACE) I/D (rs4646994) and Vascular Endothelial Growth Factor (VEGF) polymorphism (+405G/C; rs2010963) with the development of albuminuria in 490 Iranian patients with T2DM . They indicated that ACE-D and VEGF-G alleles could be an independent risk factor for microalbominuria in T2DM.
According to our knowledge, more than 40 genes were recognized increasing susceptibility to diabetes. Except a few functional candidate genes, most of the newly described genes were not suspected to be associated with diabetes. Most identified loci by GWAS appear to affect insulin secretion, but the accurate molecular mechanisms are still incompletely established. The number of loci involved in the development of T2DM has risen from just three in 2006 to almost 20 today. Across all the GWAS completed, TCF7L2 clearly shows the largest effect size with an odd ratio (OR) of 1.37. Up to now, all other confirmed loci display more modest effect sizes (OR 1.1-1.20) . KCNQ1 has been shown to have second largest effect size (OR 1.29) next to TCF7L2 [52,53]. Genetic risk loci identified by standard genetic and genome-wide association approaches account for less than 10% of the observed heritability. These results have led to speculation that epigenetic effects may also play a remarkable role in the development of T2DM .
Epigenetics are described as heritable changes in the gene expression and function that occurs without a change in the nucleotide sequence. Epigenetic modifications can be passed from one cell generation to the next (mitotic inheritance) or among generations of individuals (meiotic inheritance) . Although data analysis has suggested that the epigenetic variations play a vital role in the initiation and progression of T2DM, there are only a limited number of studies that have examined epigenetic changes in target tissues from patients with T2DM [56,57]. Epigenetic impacts may also affected by the environmental changes making them potentially important pathogenic mechanisms in the complex multifactorial diseases. There are at least three distinct mechanisms through which epigenetic information can be inherited: 1) chromosomal DNA methylations, 2) histone modifications (acetylation, methylation, phosphorylation, ubiquitination, SUMOylation, and ADP ribosylation), and 3) noncoding RNAs (e.g. microRNAs) regulation. They can help to explain how cells with identical DNA can differentiate into different cell types with different phenotypes.
Patterns of DNA methylation (DNA Methyltransferases (DNMT) catalyzed addition of methyl group to cytosine ring) are often linked to decrease gene expression and in an extreme form of that suppresses it completely. Methylation in a gene promotes region generally correlates with gene silencing [58,59]. DNA methylation is limited to cytosine that follows a guanosine in the DNA sequence (the CpG dinucleotide distributed in the genome asymmetric) in humans and other mammals occurring in small clusters called “CpG islands”. The CpG islands are often in promoter regions of genes and are usually un-methylated regardless of the transcriptional state . Zou L. et al indicated that the PRKCZ gene promoter was hyper-methylated and serum level of PRKCZ protein expression was decreased in 152 T2DM subjects. PRKCZ is an important regulatory molecule that affects the signaling pathway of insulin through epigenetic changes. They suggested that the hypermethylation of PRKCZ gene may be involved in the pathogenesis of T2DM . Another study suggested that hypermethylation of the Glucose Transporter Protein 2 (GLUT2) promoter suppresses its gene expression and thus leads to the reduced consumption of glucose . Kuroda A. et al indicated that the expression of the insulin gene is closely related to the level of methylation at its promoter .
PPARγC1A encodes PGC1α, which is a transcriptional coactivator that regulates expression of numerous genes with a key role in mitochondrial function. A series of research have revealed that hypermethylation of PPARγ and methylation of PPARγC1A promoter resulting in decreased gene expression in human pancreatic islets whereas DNA methylation of the PPARγ promoter is elevated in patients with T2DM and glucose stimulated insulin secretion [64,65]. Park J.H. et al reported that intrauterine growth retardation has also been associated with increased DNA methylation of the Pancreatic and Duodenal Homeobox 1 (Pdx1) promoter in islets from experimental animals . In a study by Toperoff G. et al, DNA methylation of a regulatory site, located in a region within an intron of the FTO gene, in Peripheral Blood Leukocytes (PBLs) is associated with impaired glucose metabolism and T2DM independent of sex, and BMI . Also, Seman N.A. et al showed that increased DNA methylation of the SLC30A8 gene promoter is associated with T2DM . Besides, Jun Z. et al indicated that increased adiponectin promoter methylation results in decreased mRNA expression, which induces glucose and lipid metabolic disorder . In addition, they found a negative correlation in DNA promoter methylation and mRNA expression of adiponectin gene. The above-mentioned studies demonstrate how epigenetic mechanisms especially DNA methylation might regulate gene expression, such as insulin secretion in human beings.
Posttranslational variations on the N-terminal histone tails in the chromatin play an essential role in the regulation of gene expression and function. These modifications could affect chromatin structure came from solving the high-resolution X-ray structure of the nucleosome . The most common of these changes include acetylation and methylation of lysine residues in the amino termini of H3 and H4. Increased acetylation induces transcription activation, whereas decreased acetylation usually induces transcription repression. Methylation of histones, by contrast, is associated with both transcription repression and activation . Some studies have been prepared to explore the relationship between chromatin modifications and gene expression. They showed that modification of the chromatin structure could allow or prevent access of proteins to binding with a transcription factor, which has been shown for TCF7L2 intronic variant which is located in islet-selective open chromatin . A genome-wide map of histone modifications has been reported for the human pancreatic islet in which three of them associated with gene activation (H3K4me1, near the start site and the enhancer of the PDX1 gene, H3K4me2, and H3K4me3, at the promoter of GAPDH (a housekeeping gene) and one associated with gene repression (H3K27me3) . The methylation patterns at the highly active promoters of these major islet hormones suggest that epigenetic regulation of these genes in human islets is different from the regulation in mouse pancreatic islets and cell lines, which is dependent on hyper-methylation of histone H3 at the insulin promoter . A study by Vecellio M. et al have been shown that acetylation of histone H3 Lysine 9 and Lysine 14 (H3K9Ac; H3K14Ac) was decreased in histone code profiling of Cardiac Mesenchymal Cells (CMSC) obtained from normoglycaemic (ND-CMSC) while the tri-methylation of histone H3 Lysine 9 and Lysine 27 (H3K9Me3; H3K27Me3) significantly increased . Analyzing the data of methylation at lysine 4 and lysine 9 of histone H3 in primary human adipocytes showed that the level of lysine 9 di-methylation was stable, while adipocytes from T2DM and non-diabetic overweight subjects exhibited about 40% lower levels of lysine 4 di-methylation compared with cells from normal-weight subjects. In contrast, tri-methylation at lysine 4 was 40% higher in adipocytes from overweight diabetic subjects compared with normal-weight and overweight non-diabetic subjects .
Both DNA methylation and histone modification are involved in establishing patterns of gene repression during development. Certain forms of histone methylation cause local formation of heterochromatin, which is readily reversible, whereas DNA methylation leads to stable long-term repression. Recent evidence indicates that this two-sided relationship between histone and DNA methylation might be accomplished by direct interactions between histone and DNA methyltransferases . Thus, chromatin modifications induced by adverse stimuli are self-reinforcing and can propagate.
Beside biochemical modifications of DNA and histone molecules, gene expression may also be regulated by non-coding RNAs or MicroRNAs (miRNAs), which are 20–30 nucleotides with imperfect sequence complementary to the 3’ untranslated region of the target mRNA leading to either posttranscriptional silencing and translational repression or RNA degradation . MiRNAs provide a rapid but reversible means of gene regulation, which also allows the cell/tissue/organism to respond to environmental stimuli without changing the DNA sequence itself. MiRNAs have been identified as negative regulators in various pathways targeting signaling molecules, transcription factors, and numerous other enzymes and proteins. There is also the potential role for miRNAs to target chromatinmodifying enzymes, resulting in epigenetic modifications affecting gene expression .
It is estimated that up to 60% of human genes are subject to regulation by miRNAs and that miRNAs are involved in cell proliferation, differentiation, and apoptosis. Recent studies have shown that miRNAs have a vital role in many different gene regulatory pathways. A subset of miRNAs has been shown to be involved in the metabolic regulation of glucose homeostasis and in the epigenetics of T2DM. They are important in X-chromosome inactivation and genomic imprinting . Kameswarn V. et al revealed that a cluster of microRNAs in an imprinted locus on human chromosome 14q32 of β cells expressed specifically and down-regulated dramatically in islets from T2DM organ donors. The down-regulation of this locus strongly correlates with hypermethylation of its promoter. Therefore, disease-relevant targets of the chromosome 14q32 microRNAs, such as Islet Amyloid Polypeptide (IAPP) and Tumor Protein P53- Inducible Nuclear Protein 1 (TP53INP1) that cause increased β cell apoptosis upon overexpression in human islets . Sun K. et al demonstrated that the miR-375 was overexpressed in plasma in patients with T2DM, and this may be used as a novel biomarker to distinguish between patients with T2DM and healthy individuals. Furthermore, hypomethylation of miR-375 promoter was found in patients with T2DM, which may regulate the expression of miR-375 and contribute to the pathogenesis of T2DM . In addition, Rong Y. et al found that circulating miRNA-146a levels were significantly elevated in T2DM patients compared with healthy subjects . Another study by Zhu Y. et al presented a novel network between nutrient overload and genetic diabetes via miR-24 in which a link was observed between this microRNA and MODY gene regulatory pathway to the onset of T2DM. Silencing of two MODY genes (Hnf1a and Neurod1) as direct targets of miR-24 imitated the cellular phenotype caused by miR-24 overexpression, whereas restoring their expression rescued β-cell function . MiR-103 plays a critical role in regulating glucose homeostasis in T2DM. Luo M. et al suggested that platelet-derived miR-103b could negatively regulate the expression of SFRP4 mRNA/protein in pre- T2DM, indicating that miR-103b could be a biomarker for the early diagnosis of T2DM . Higuchi C. et al demonstrated that the circulating miR-101, miR- 375 and miR-802 levels are significantly increased in T2DM patients . Decreased GLUT4 expression and impaired GLUT4 cell membrane translocation are involved in T2DM pathogenesis. Yan ST. et al revealed that a high level of miR-199a that reduce GLUT4 expression contributed to the insulin resistance in T2DM patients . They suggested that miR-199a might be a novel biomarker for risk estimation and classification in T2DM patients.
Study of epigenome patterns using numerous advanced technologies such as massively parallel sequencing in combination with bisulfite conversion and RNA or miRNA profiling by microarrays will greatly facilitate a comprehensive understanding of the roles of epigenetic modifications in normal physiology and disease processes. In addition, the advances in comprehension of epigenetic mechanisms implicated in modulating chromatin conformation, gene transcription and diverse cellular signaling pathways have provided the essential basis for the current development of epigeneticsbased biomarkers and drugs for the diagnosis and treatment of T2DM. Without detailed characterization of physiological as well as pathological patterns of epigenetic modifications in specific tissues, it would be impossible to identify epigenetic alterations that are causative and specific to disease process, which is essential for developing innovative epigenetics based therapies for diabetes.
Despite of a large volume of published work on the T2DM, no gene(s) has been directly implicated; however, the role of all the variants in increasing susceptibility will be known only by gaining further knowledge of the underlying biology. However, genetic background (personal or family history) of T2DM contributes in estimating the risk of developing of the disease in high-risk subjects. Despite of genetic studies, novel research in the field of epigenetics presents new opportunities for identifying distinguish biomarkers for risk and progression of complex metabolic diseases such as T2DM. Through Epigenome-Wide Association Studies (EWAS) as well as DNA methylation, histone modifications and non-coding RNAs, the most studied in the context of individual gene regulation, may provide important insight into disease pathogenesis which cannot be explained by genetic changes. The flexibility of epigenetic regulation and influencing by nutritional status and environmental changes point to the importance of understanding the effects of lifestyle factors on the molecular changes affect health. Further insight into these associations will improve the variety and quality of existing predictive T2DM biomarkers, thereby increasing the possibilities to postpone or prevent T2DM in the individuals at high risk for the disease.
- Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract. 2010; 87: 4-14.
- Davidson MB. Diabetes mellitus: Diagnosis and treatment. Wiley. 1986.
- Doria A, Patti ME, Kahn CR. The emerging genetic architecture of type 2 diabetes. Cell Metab. 2008; 8: 186-200.
- Jin W, Patti ME. Genetic determinants and molecular pathways in the pathogenesis of Type 2 diabetes. Clin Sci (Lond). 2009; 116: 99-111.
- Putiri EL, Robertson KD. Epigenetic mechanisms and genome stability. Clinical epigenetics. 2010; 2: 299.
- Florez JC. Clinical review: the genetics of type 2 diabetes: a realistic appraisal in 2008. J Clin Endocrinol Metab. 2008; 93: 4633-4642.
- Billings LK, Florez JC. The genetics of type 2 diabetes: what have we learned from GWAS? Ann N Y Acad Sci. 2010; 1212: 59-77.
- Imamura M, Maeda S. Genetics of type 2 diabetes: the GWAS era and future perspectives [Review]. Endocr J. 2011; 58: 723-739.
- Cariaso MLG. SNPedia: a wiki supporting personal genome annotation, interpretation and analysis. Nucleic Acids Res. 2012; 40: 1308-1312.
- Fallah S, Jafarzadeh M, Hedayati M. No association of the SUMO4 polymorphism M55V variant in type 2 diabetes in Iranian subjects. Diabetes Res Clin Pract. 2010; 90: 191-195.
- Fallah S, Ja'farzadeh M, Hedayati M, R Haji Hosseini. Association of M55V Polymorphism of Sumo4 with Type 2 Diabetes. Razi Journal of Medical Sciences. 2010; 17: 42-48.
- Shahsavar F, Jafarzadeh M, Azargoon A, Mehdi Hedayati, Behnam Asadifar. Small ubiquitin-like modifier 4 M55V polymorphism is not associated with diabetic nephropathy in Iranian type 2 diabetes patients. Indian J Hum Genet. 2013; 19: 179.
- Shahsavar F, Kheirollahi A, Jafarzadeh M. SUMO4 M55V Polymorphism is associated with diabetic nephropathy in Iranian type 2 diabetes patients. Life Science Journal. 2013; 10.
- Shojaei S, Daneshpour M, Halalkhor S, et al. Genetic Association Between Metabolic Syndrome and Apolipoproteins. Iranian Journal of Endocrinology & Metabolism. 2011; 13.
- McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JP. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat Rev Genet. 2008; 9: 356-369.
- Ridderstrale M, Groop L. Genetic dissection of type 2 diabetes. Mol Cell Endocrinol. 2009; 297: 10-17.
- Jimenez-Sanchez G, Childs B, Valle D. Human disease genes. Nature. 2001; 409: 853-855.
- Altmuller J, Palmer LJ, Fischer G, Scherb H, Wjst M. Genomewide scans of complex human diseases: true linkage is hard to find. Am J Hum Genet. 2001; 69: 936-950.
- Weedon MN, Schwarz PE, Horikawa Y, et al. Meta-analysis and a large association study confirm a role for calpain-10 variation in type 2 diabetes susceptibility. Am J Hum Genet. 2003; 73: 1208-1212.
- Gloyn AL, Braun M, Rorsman P. Type 2 diabetes susceptibility gene TCF7L2 and its role in beta-cell function. Diabetes. 2009; 58: 800-802.
- Grant SF, Thorleifsson G, Reynisdottir I, Benediktsson R, Manolescu A, Sainz J, et al. Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nat Genet. 2006; 38: 320-323.
- Horikawa Y, Oda N, Cox NJ, Li X, Orho-Melander M, Hara M, et al. Genetic variation in the gene encoding calpain-10 is associated with type 2 diabetes mellitus. 2000; 26: 163-175.
- Song Y, Niu T, Manson JE. Are variants in the CAPN10 gene related to risk of type 2 diabetes? A quantitative assessment of population and family-based association studies. Am J Hum Genet. 2004; 74: 208-222.
- Grarup N, Sparso T, Hansen T. Physiologic characterization of type 2 diabetes-related loci. 2010; 10: 485-497.
- Lander ES, Linton LM, Birren B, et al. Initial sequencing and analysis of the human genome. Nature. 2001; 409: 860-921.
- Venter J C, Adams MD, Myers EW, et al. The sequence of the human genome. Science. 2001; 291: 1304-1351.
- Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, Gibbs RA, et al. A second generation human haplotype map of over 3.1 million SNPs. Nature. 2007; 449: 851-861.
- Altshuler D, Daly MJ, Lander ES. Genetic mapping in human disease. Science. 2008; 322: 881-888.
- Zeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T, et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nature genetics. 2008; 40: 638-645.
- Sladek R, Rocheleau G, Rung J, Dina C, Shen L, Serre D, et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature. 2007; 445: 881-885.
- Deeb SS, Fajas L, Nemoto M, Pihlajamäki J, Mykkänen L, Kuusisto J, et al. A Pro12Ala substitution in PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity. Nat Genet. 1998; 20: 284-287.
- Kooner JS, Saleheen D, Sim X, Sehmi J, Zhang W, Frossard P, et al. Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci. Nat Genet. 2011; 43: 984-989.
- McCarthy MI. Genomics, type 2 diabetes, and obesity. N Engl J Med. 2010; 363: 2339-2350.
- Sun X, Yu W, Hu C. Genetics of Type 2 Diabetes: Insights into the Pathogenesis and Its Clinical Application. BioMed Research International. 2014; 2014: 15.
- Replication DIG, Meta-analysis C, Asian Genetic Epidemiology Network Type 2 Diabetes C, et al. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat Genet. 2014; 46: 234-244.
- Florez JC, Burtt N, de Bakker PI, Almgren P, Tuomi T, Holmkvist J, et al. Haplotype structure and genotype-phenotype correlations of the sulfonylurea receptor and the islet ATP-sensitive potassium channel gene region. Diabetes. 2004; 53: 1360-1368.
- Nielsen EM, Hansen L, Carstensen B, Echwald SM, Drivsholm T, Glumer C, et al. The E23K variant of Kir6.2 associates with impaired post-OGTT serum insulin response and increased risk of type 2 diabetes. Diabetes. 2003; 52: 573-537.
- Altshuler D, Hirschhorn JN, Klannemark M, Lindgren CM, Vohl MC, Nemesh J, et al. The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet. 2000; 26: 76-80.
- Sandhu MS, Weedon MN, Fawcett KA, Wasson J, Debenham SL, Daly A, et al. Common variants in WFS1 confer risk of type 2 diabetes. Nat Genet. 2007; 39: 951-953.
- Winckler W, Weedon MN, Graham RR, McCarroll SA, Purcell S, Almgren P, et al. Evaluation of common variants in the six known Maturity-Onset Diabetes of the Young (MODY) genes for association with type 2 diabetes. Diabetes. 2007; 56: 685-693.
- Barroso I, Gurnell M, Crowley VE, Agostini M, Schwabe JW, Soos MA, et al. Dominant negative mutations in human PPARgamma associated with severe insulin resistance, diabetes mellitus and hypertension. Nature. 1999; 402: 880-883.
- Nishigori H, Yamada S, Kohama T, Tomura H, Sho K, Horikawa Y, et al. Frameshift mutation, A263fsinsGG, in the hepatocyte nuclear factor-1beta gene associated with diabetes and renal dysfunction. Diabetes. 1998; 47: 1354-1355.
- Frayling TM. Genome-wide association studies provide new insights into type 2 diabetes aetiology. Nat Rev Genet. 2007; 8: 657-662.
- Zain M, Awan FR, Amir S, et al. A case control association study of COMT gene polymorphism (I/D) with type 2 diabetes and its related factors in Pakistani Punjabi population. J Diabetes Metab Disord. 2015; 14: 40.
- Zhang YH, Xu SF, Zheng J, Hong HS, Fan LM, et al. Correlation between polymorphism of platelet alloantigen genes HPA-1-5 and type 2 diabetes complication by carotid atherosclerosis in a Chinese population. Genet Mol Res. 2015; 14: 4607-4615.
- Jiang F, Li S, Pan L, Jia C. Association of the G1057D polymorphism in insulin receptor substrate 2 gene with type 2 diabetes mellitus: a meta-analysis. J Diabetes Complications. 2015.
- Ninomiya H, Katakami N, Osonoi T, Saitou M3, Yamamoto Y, Takahara M, et al. Association between new onset diabetic retinopathy and Monocyte Chemoattractant Protein-1 (MCP-1) polymorphism in Japanese type 2 diabetes. Diabetes Res Clin Pract. 2015.
- Amle D, Mir R, Khaneja A, et al. Association of 18bp insertion/deletion polymorphism, at -2549 position of VEGF gene, with diabetic nephropathy in type 2 diabetes mellitus patients of North Indian population. J Diabetes Metab Disord. 2015; 14: 19.
- Zhong X, Du Y, Lei Y, Liu N, Guo Y, Pan T. Effects of vitamin D receptor gene polymorphism and clinical characteristics on risk of diabetic retinopathy in Han Chinese type 2 diabetes patients. Gene. 2015; 566: 212-216.
- Fathi M, Nikzamir A.R, Esteghamati A, Nakhjavani M, Yekaninejad MS. Combination of Angiotensin Converting Enzyme Insertion/Deletion (I/D) (rs4646994) and VEGF Polymorphism (+405G/C; rs2010963) Synergistically Associated With the Development, of Albuminuria in Iranian Patients With Type 2 Diabetes. Iran Red Crescent Med J. 2015; 17: 19469.
- Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM, et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science. 2007; 316: 889-894.
- Yasuda K, Miyake K, Horikawa Y, Hara K, Osawa H, Furuta H, et al. Variants in KCNQ1 are associated with susceptibility to type 2 diabetes mellitus. Nat Genet. 2008; 40: 1092-1097.
- Unoki H, Takahashi A, Kawaguchi T, Kazuo Hara, Momoko Horikoshi, Gitte Andersen, et al. SNPs in KCNQ1 are associated with susceptibility to type 2 diabetes in East Asian and European populations. Nat Genet. 2008; 40: 1098-1102.
- Drong AW, Lindgren CM, McCarthy MI. The genetic and epigenetic basis of type 2 diabetes and obesity. Clin Pharmacol Ther. 2012; 92: 707-715.
- Cubas P, Vincent C, Coen E. An epigenetic mutation responsible for natural variation in floral symmetry. Nature. 1999; 401: 157-161.
- Gardner RJ, Mackay DJ, Mungall AJ, Polychronakos C, Siebert R, Shield JP, et al. An imprinted locus associated with transient neonatal diabetes mellitus. Hum Mol Genet. 2000; 9: 589-596.
- Longnecker D.S. Abnormal methyl metabolism in pancreatic toxicity and diabetes. J Nutr. 2002; 132: 2373-2376.
- Barres R, Zierath JR. DNA methylation in metabolic disorders. The American journal of clinical nutrition. 2011; 93: 897-900.
- Jin B, Li Y, Robertson KD. DNA Methylation Superior or Subordinate in the Epigenetic Hierarchy? Genes & cancer. 2011; 2: 607-617.
- Ban N, Yamada Y, Someya Y, et al. Hepatocyte nuclear factor-1alpha recruits the transcriptional co-activator p300 on the GLUT2 gene promoter. Diabetes. 2002; 51: 1409-1418.
- Zou L, Yan S, Guan X, et al. Hypermethylation of the PRKCZ Gene in Type 2 Diabetes Mellitus. J Diabetes Res. 2013; 2013: 721493.
- Ban N, Yamada Y, Someya Y, Miyawaki K, Ihara Y, Hosokawa M, et al. Hepatocyte nuclear factor-1α recruits the transcriptional co-activator p300 on the GLUT2 gene promoter. Diabetes. 2002; 51: 1409-1418.
- Kuroda A, Rauch TA, Todorov I, Teresa HK, Al-Abdullah, Kandeel F, et al. Insulin gene expression is regulated by DNA methylation. PLoS One. 2009; 4: 6953.
- Ling C, Del Guerra S, Lupi R, Ronn T, Granhall C, Luthman H, et al. Epigenetic regulation of PPARGC1A in human type 2 diabetic islets and effect on insulin secretion. Diabetologia. 2008; 51: 615-622.
- Fujiki K, Kano F, Shiota K, Murata M. Expression of the peroxisome proliferator activated receptor gamma gene is repressed by DNA methylation in visceral adipose tissue of mouse models of diabetes. BMC Biol. 2009; 7: 38.
- Park JH, Stoffers DA, Nicholls RD, Simmons RA. Development of type 2 diabetes following intrauterine growth retardation in rats is associated with progressive epigenetic silencing of Pdx1. J Clin Invest. 2008; 118: 2316-2324.
- Toperoff G, Kark JD, Aran D, Nassar, Ahmad HA, Sinnreichet R, et al. Premature aging of leukocyte DNA methylation is associated with type 2 diabetes prevalence. Clin Epigenetics. 2015; 7: 35.
- Seman N.A, Mohamud W.N, Ostenson C.G, et al. Increased DNA methylation of the SLC30A8 gene promoter is associated with type 2 diabetes in a Malay population. Clin Epigenetics. 2015; 7: 30.
- Jun Z, Wangqiang Z, Yulei D, et al. Correlation between type 2 diabetes and DNA methylation and mRNA expression of APN in abdominal adipose tissues in Xinjiang Uygur population. Yi Chuan. 2015; 37: 269-275.
- Luger K, Mader AW, Richmond RK, Sargent DF, Richmond TJ. Crystal structure of the nucleosome core particle at 2.8 A resolution. Nature. 1997; 389: 251-260.
- McCarthy M.I. Progress in defining the molecular basis of type 2 diabetes mellitus through susceptibility-gene identification. Hum Mol Genet. 2004; 13: 33-41.
- Gaulton K.J, Nammo T, Pasquali L, Simon JM, Giresi PG, Fogarty MP, et al. A map of open chromatin in human pancreatic islets. Nat Genet. 2010; 42: 255-259.
- Bhandare R, Schug J, Le Lay J, Fox A, Smirnova O, Liu C, et al. Genome-wide analysis of histone modifications in human pancreatic islets. Genome Res. 2010; 20: 428-433.
- Deering TG, Ogihara T, Trace AP, Maier B, Mirmira RG. Methyltransferase Set7/9 maintains transcription and euchromatin structure at islet-enriched genes. Diabetes. 2009; 58: 185-193.
- Vecellio M, Spallotta F, Nanni S, Claudia Colussi, Chiara Cencioni, Anja Derlet, et al. The Histone Acetylase Activator Pentadecylidenemalonate 1b Rescues Proliferation and Differentiation in Human Cardiac Mesenchymal Cells of Type 2 Diabetic Patients. Diabetes. 2014.
- Jufvas A, Sjodin S, Lundqvist K, Amin R, Vener AV, Strålfors P. Global differences in specific histone H3 methylation are associated with overweight and type 2 diabetes. Clin Epigenetics. 2013; 5: 15.
- Cedar H. and Bergman Y. Linking DNA methylation and histone modification: patterns and paradigms. Nat Rev Genet. 2009; 10: 295-304.
- Bartel D.P. MicroRNAs: target recognition and regulatory functions. Cell. 2009; 136: 215-233.
- Barski A, Jothi R, Cuddapah S, Cui K, Roh TY, Schones DE, et al. Chromatin poises miRNA- and protein-coding genes for expression. Genome Res. 2009; 19: 1742-1751.
- Reik W, Walter J. Genomic imprinting: parental influence on the genome. Nat Rev Genet. 2001; 21-32.
- Kameswaran V, Bramswig NC, McKenna LB, Penn M, Schug J, Hand NJ, et al. Epigenetic Regulation of the DLK1-MEG3 MicroRNA Cluster in Human Type 2 Diabetic Islets. Cell Metab. 2014; 19: 135-145.
- Sun K, Chang X, Yin L, Li J, Zhou T, Zhang C, et al. Expression and DNA methylation status of microRNA-375 in patients with type 2 diabetes mellitus. Mol Med Rep. 2013.
- Rong Y, Bao W, Shan Z, Liu J, Yu X, Xia S, et al. Increased microRNA-146a levels in plasma of patients with newly diagnosed type 2 diabetes mellitus. PLoS One. 2013; 8: 73272.
- Zhu Y, You W, Wang H, Yating Li, Nan Qiao, Yuguang Shi, et al. MicroRNA-24/MODY gene regulatory pathway mediates pancreatic beta-cell dysfunction. Diabetes. 2013; 62: 3194-3206.
- Luo M, Li R, Deng X, Ren M, Chen N, Zeng M, et al. Platelet-derived miR-103b as a novel biomarker for the early diagnosis of type 2 diabetes. Acta Diabetol. 2015.
- Higuchi C, Nakatsuka A, Eguchi J, Teshigawara S, Kanzaki M, Katayama A, et al. Identification of circulating miR-101, miR-375 and miR-802 as biomarkers for type 2 diabetes. Metabolism. 2015; 64: 489-497.
- Yan ST, Li CL, Tian H, Li J, Pei Y, Liu Y, et al. MiR-199a is overexpressed in plasma of type 2 diabetes patients which contributes to type 2 diabetes by targeting GLUT4. Mol Cell Biochem. 2014; 397: 45-51.
Citation: Zarkesh M, Ehsandar S and Hedayati M. Genetic and Epigenetic Aspects of Type 2 Diabetes Mellitus: A Review. Austin Endocrinol Diabetes Case Rep. 2016; 1(1): 1004.