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Pharmacoepigenetics in Type 2 Diabetes Mellitus
C H A P T E R
18 Pharmacoepigenetics in Type 2 Diabetes Mellitus Johanna K. DiStefano*, and Richard M. Watanabe† †
*Diabetes and Fibrotic Disease Unit, Translational Genomics Research Institute, Phoenix, AZ, United States Departments of Preventive Medicine and Physiology & Neuroscience, Keck School of Medicine of USC, Los Angeles, CA, United States
18.1 OVERVIEW OF TYPE 2 DIABETES (T2D): PREVALENCE, DIAGNOSIS, AND CLINICAL MANAGEMENT Diabetes mellitus is a heterogeneous collection of disorders resulting from a state of chronic hyperglycemia. The most prevalent form of diabetes mellitus is type 2 diabetes (T2D), which accounts for approximately 90% of all cases of diabetes1 and develops predominantly in response to multiorgan insulin resistance and inadequate insulin production from pancreatic β-cells.2, 3 The global prevalence of T2D has nearly doubled since 1980: at present more than 420 million individuals are affected by the disease4 and this number is expected to exceed 520 million individuals within 15 years.5 In the United States, diabetes and related neural, retinal, and renal complications, were estimated to cost over $245 billion in direct and indirect costs.6 T2D is a risk factor for other chronic noncommunicable disorders, including cardiovascular disease,7 further underscoring its role as a leading public health concern. Historically, a fasting glycemic threshold (i.e., 126 mg/dL or 7 mM), has been used for diabetes diagnosis, although there is a shift toward implementing hemoglobin A1c (HbA1c) as a diagnostic marker because this measurement represents average glycemia over a 2–3 month period and thus provides information on longer term glycemic control. Regardless of diagnostic concerns, diabetes and its complications are consequences of fasting hyperglycemia to which there are many paths. Moreover, even glycemic levels below the diagnostic threshold have been associated with significantly higher mortality and morbidity from cardiovascular complications,8, 9 resulting in the clinical implementation of aggressive strategies to reduce glycemia in prediabetic individuals. It is of clinical significance to view diabetes on a glycemic continuum, and interpret gradual elevations in glycemia as warning signs requiring immediate intervention to prevent full-blown development of the disease. T2D is characterized by obesity, insulin resistance, and pancreatic β-cell dysfunction.2, 3 Although insulin resistance and pancreatic β-cell dysfunction are both requisite for T2D development, the relative importance of each has been the subject of ongoing debate for decades. However, it is clear that the combination of insulin resistance and pancreatic β-cell dysfunction is required for disease manifestation; insulin resistance alone cannot result in T2D. Further, pancreatic β-cell dysfunction is a strong predictor of diabetes, independent of insulin resistance, suggesting that these cells hold the key to disease pathogenesis. A primary role of pancreatic β-cell dysfunction is also supported by findings from the ADOPT study, which examined the glycemic durability of different pharmacologic therapies that targeted different tissues related to T2D: glyburide (pancreas), metformin (liver), and rosiglitazone (skeletal muscle).10 The study showed that while glyburide, a sulfonylurea antidiabetes drug, was effective in immediately restraining hyperglycemia, the effect was short-lived and efficacy became significantly reduced with continued use. This result suggested that the sulfonylurea class of drugs, which induce insulin secretion (discussed below), might accelerate pancreatic β-cell dysfunction. In contrast, both metformin and rosiglitazone showed more prolonged efficacy over the course of the study, while gradually reducing hyperglycemia. These results provide important clues regarding the treatment of T2D. First, because this
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564 TABLE 18.1
18. PHARMACOEPIGENETICS IN TYPE 2 DIABETES MELLITUS
Major Classes of Noninsulin Antihyperglycemic Drugs
Drug class
Mechanism of action
Generic name (Brand name)
Alpha-glucosidase inhibitors
Delay digestion of carbohydrates in the small intestine
Acarbose (Precose); Miglitol (Glyset)
Biguanides
Decrease hepatic glucose output and increase peripheral insulin sensitivity
Metformin (Glucophage); Metformin-extended release (Glutmetza, Fortamet); Metformin HCl (Riomet)
Bile acid sequestrants
Prevent reabsorption of bile acids from the gut
Colesevelam (Welchol)
Dopamine-2 agonists
Indirectly suppress hepatic glucose production
Bromocriptine (Cycloset)
DPP-4 inhibitors (gliptins)
Prevent breakdown of incretins, resulting in increased insulin production and decreased hepatic glucose output
Alogliptin (Nesina); Linagliptin (Tradjenta); Saxagliptin (Onglyza); Sitagliptin (Januiva)
Incretin mimetics
Promote insulin secretion from pancreas
Albiglutide (Tanzeum); Dulaglutide (Trulicity); Exenatide (Byetta); Exenatide-extended release (Bydureon); Liraglutide (Victoza)
Meglitinides
Promote insulin secretion from pancreas
Nateglinide (Starlix); Repaglinide (Prandin)
Sulfonylureas
Promote insulin secretion from pancreas
Glimepiride (Amaryl); Glipizide (Glucotrol); Glipizide-extended release (Glucotrol XL); Glyburide (Glynase)
Thiazolidinediones
Increase insulin sensitivity and decrease hepatic glucose production
Pioglitazone (Actos); Rosiglitazone (Avandia)
SGLT2-inhibitors
Lower renal glucose threshold, allowing greater urinary glucose excretion
Canagliflozin (Invokana); Dapagliflozin (Farxiga); Empagliflozin (Jardiance)
DPP, Dipeptidyl peptidase; SGLT2, sodium-glucose transporter 2.
form of diabetes involves multiple tissues, for optimal results pharmacologic therapies should target more than one tissue. In accord, this finding, combined with results from other studies,11 has resulted in the development and implementation of combination therapy, which refers to the treatment strategy in which a patient is given two or more drugs for the same disease. Second, although T2D is primarily a disease of the pancreatic β-cell, targeting insulin resistance to reduce demand on the β-cell may be an effective approach to treat or prevent T2D. Buchanan et al.12 first demonstrated this concept by treating individuals at risk for developing T2D with a thiazolidinedione, which significantly reduced the development of disease.12, 13 These findings were subsequently replicated in larger studies.14–16 Lifestyle modification has been the primary intervention to both prevent and treat T2D. However, for a variety of reasons, changing behavior patterns is difficult, which means that pharmacologic or other forms of intervention are necessary. The repertoire of oral and injected antidiabetic agents has expanded greatly during the past decade and encompasses nine major classes of approved oral drugs, two classes of noninsulin-injected medications, and a number of different options for insulin delivery. A list of the major classes of noninsulin antidiabetic agents, including generic and brand names and mechanisms of action, is provided in Table 18.1. Although listed in the table, the thiazolidinedione class of medications has been associated with a number of side effects, resulting in black labeling by the FDA in the United States. Newer forms of therapy for T2D have targeted nontraditional biologic pathways contributing to the pathophysiology of the disease. Recently, drugs targeting the incretin system have gained wide use. Incretin hormones, like glucagon-like peptide 1 (GLP1), act as insulin secretagogues, and drugs affecting this system take two forms: GLP1 memetics or dipeptidyl peptidase 4 (DPP4) inhibitors. DPP4 is the enzyme that degrades GLP1; therefore, inhibiting its action allows GLP1 to remain active. There is controversial evidence that incretin-based therapies may increase risk for pancreatic cancer.17, 18 Also, because these drugs act as insulin secretagogues, there is some concern their long-term effects might be similar to those observed for sulfonylureas in the ADOPT study. Sodium-glucose cotransporter 2 (SGLT2) inhibitors are another new class of medications that inhibit glucose resorption in the proximal convoluted tubule and facilitate excretion of glucose via the urine. Recently, the FDA issued new warnings for SGLT2 inhibitors, including increased risks for urinary tract infections, acute kidney injury, and leg or foot amputations (www.fda.gov/drugs/ drugsafety/ucm446). As noted earlier, combination therapy has become more common as physicians attempt to target more than one tissue or pathway to regulate glucose, and a number of combination products are currently available. Pharmacologic therapies come with side effects that engender alternative medical problems or exacerbate other diabetes comorbidities, as noted by the FDA notices for thiazolidinediones, incretin-based, and SGLT2 inhibitor drugs.
18.3 COMMON EPIGENETIC MODIFICATIONS IN T2D
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FIG. 18.1
Factors affecting interindividual response to pharmacological agents and potential therapeutic outcomes. In some instances external factors directly impact drug response, as represented by the bottom arrow. However, in other cases epigenetic modifications may mitigate the effects of these factors, including genetic variants, on therapeutic outcomes.
Furthermore, reduction in glycemia alone may not affect the risk for diabetes complications or comorbidities. For example, T2D is among the strongest risk factors for death as a result of cardiovascular events. Thus, current clinical strategies recommend the maintenance of glycemia concomitant with control of other cardiovascular risk factors, such as hypertension and hypercholesterolemia. As such, the pharmacologic mix necessary to manage multiple outcomes continues to present challenges for both patient and clinician.
18.2 PHARMACOGENOMICS OF T2D Glycemic response to oral antidiabetic agents is highly variable, and there are a number of factors that contribute to interindividual variations in drug response. As shown in Fig. 18.1, these factors include age, sex, disease, drug and food interactions, and comorbidities.19 Genetic variants also contribute to differential drug response, a phenomenon comprising an entire branch of study known as pharmacogenetics. A number of pharmacogenetics studies have investigated the role of genetic variants in mediating response to such antihyperglycemic drugs as biguanides, sulfonylureas, and thiazolidinediones19; however, genetic factors contribute to only a portion of the variation in response to antidiabetic agents, suggesting that other factors may play a role in variable drug response. Further, while genetic information has had limited success in identifying appropriate drug therapies for rare forms of diabetes, it has not led to significant changes in the clinical management of more common forms of diabetes, such as T2D. This is due, in part, to a paucity of pharmacogenetic studies examining the genetic effects of drug-based adverse events. Sadly, our understanding of T2D pharmacogenomics has not substantially improved over the last decade, and the reader is referred to review articles to learn more about specific variants associated with drug response in diabetes treatment.19–23 Despite the limited success seen with genetic studies, emerging evidence supports the notion that environmental and lifestyle factors influence the development and progression of T2D through epigenetic modulation of genes that play important roles in glucose metabolism, insulin resistance, and β-cell dysfunction.24 Like genetic variants, epigenetic modifications may also contribute to interindividual response to antidiabetic agents24; however, these factors are more likely to interact with other influences, including aging, diet, and other drugs, to uniquely impact drug response.
18.3 COMMON EPIGENETIC MODIFICATIONS IN T2D Epigenetic modifications affect gene expression through the modulation of chromatin structure, accessibility to transcriptional factors, and posttranscriptional regulation without changes in genome sequence.25 Chromatin is a complex comprised of protein, DNA, and RNA, and a primary function of chromatin is regulation of gene expression. An active chromatin sequence allows binding of transcriptional factors leading to gene expression, while condensed chromatin is typically associated with gene inactivation. Chromatin states, and therefore gene transcription, are modulated by DNA methylation and histone modifications.26, 27 DNA methylation is mediated by DNA methyltransferases, which primarily methylate cytosine-5 molecules in cytosine-guanine pairs (CpGs). Regions with a high density of CpG dinucleotides are known as CpG islands, which are typically located near the transcriptional start site in mammalian genes.28 CpG island methylation is a dynamic epigenetic process during mammalian development and is important for the regulation of gene expression and maintaining the stability of the genome. The main protein components are histones, which act to tightly wrap DNA into nucleosomes. Covalent, posttranslational modifications, such as acetylation, phosphorylation, or methylation, to histone proteins can alter chromatin structure and affect
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accessibility for the transcriptional machinery. DNA methylation and histone modifications can be interactive; for example, actively expressed genes are commonly associated with low levels of promoter CpG methylation and high levels of histone acetylation. Noncoding RNAs (ncRNAs) are also considered part of the epigenetic machinery based on their role in the posttranscriptional regulation of gene expression. While there are many classes of ncRNAs,29 the class of microRNAs (miRNAs), which bind to complementary sequences in target genes to exert effects on transcription, is the best studied to date. Changes in DNA methylation, histone modifications, and miRNA expression are dynamic and highly responsive to environmental factors, including aging, dietary components, pharmacological agents, toxins, and physical exercise. Importantly, interactions between genetic susceptibility and environmental exposure leading to differential effects on disease development and progression may be mediated by epigenetic mechanisms.
18.3.1 DNA Methylation and T2D DNA methylation is the most commonly studied epigenetic modification in T2D. In humans, over 30 studies have explored DNA methylation patterns in known candidate genes for T2D susceptibility or glycemic traits.30, 31 Of these, CpG sites in the genes encoding glucagon-like peptide 1 receptor (GLP1R), insulin (INS), peroxisome proliferatoractivated receptor gamma coactivator 1-alpha (PPARGC1A), and potassium voltage-gated channel subfamily Q member 1 (KCNQ1) have shown consistent evidence for differential methylation across multiple studies.30, 31 A number of epigenome-wide studies have also investigated DNA methylation patterns in pancreatic islets, skeletal muscle, adipose tissue, and blood in individuals with T2D or impaired glucose metabolism; major findings from these investigations are summarized in Table 18.2. Despite differences in study design and methodologies, overlap among findings of differentially methylated sites suggests common methylomic mechanisms in T2D, including differential methylation at CpG sites near the ATP-binding cassette subfamily G member 1 (ABCG1), KCNQ1, solute carrier family 30 member 8 (SLCA30A8), and transcription factor 7-like 2 (TCF7L2) genes. DNA methylation patterns are also altered in response to environmental factors relevant to T2D. For example, DNA methylation was higher in human pancreatic islets exposed to palmitate than control islets,38 suggesting that higher circulating free fatty acids, a common feature of T2D, may exert effects through changes in islet methylation. In another study a 6-month exercise intervention in individuals with or without a family history of T2D revealed differential methylation of 134 genes in skeletal muscle, including myocyte enhancer factor 2 (MEF2A), THADA, armadillo repeat containing (THADA), NADH:ubiquinone oxidoreductase subunit C2 (NDUFC2), and interleukin 7 (IL-7), all of which have implications for metabolic function.39 A similar study reported overall decreased global DNA methylation of genes in skeletal muscle following a bout of acute exercise and specific hypomethylation of many candidate genes including PPARGC1A, mitochondrial transcription factor A (TFAM), peroxisome proliferator-activated receptor delta (PPARD), pyruvate dehydrogenase kinase 4 (PDK4), and citrate synthase (CS).40 Studies of DNA methylation in TABLE 18.2
Summary of Genome-Wide DNA Methylation Studies Conducted in T2D Patients
Trait
Source
T2D
Pancreatic islets
Fasting insulin; HOMA-IR
CpG No.
Major findings
References
1649
CDKN1A; EXOC3L2; FTO; IRS1; KCNQ1; PDE7B; PPARG; SEPT9; TCF7L2; THADA
32
CD4(+) T cells
1
ABCG1
33
T2D FBG HOMA-IR
Blood
51 19 24
TXNIP; ABCG1; SAMD12
34
T2D
Skeletal muscle Adipose tissue
789 1458
CDKN2A; DUSP9; HHEX; KCNQ1; PPARGC1A; SLC30A8 ADCY5; CDKN2A; CDKN2B; DUSP9; IDE; IRS1; KCNQ1; MTNR1B; TSPAN8; WFS1
35
T2D
Blood
13
FTO; JAZF1; KCNQ1; SLC30A8; TCF7L2; THADA
36
T2D
Pancreatic islets
276
BCL2; CHAC1; GUCA2B; NIBAN; NR4A1; MKNK2; PER2; SFRS2IP
37
FBG, Fasting blood glucose; HOMA-IR, homeostatic model assessment of insulin resistance
567
18.3 COMMON EPIGENETIC MODIFICATIONS IN T2D
adipose tissue in patients with T2D and following exercise intervention have also been performed, and details from this work have been described elsewhere.31 Together, these findings demonstrate that DNA methylation is a key feature of physiological mechanisms related to β-cell function, insulin resistance, and glucose tolerance and serve to augment our understanding of T2D pathogenesis. Additional studies investigating DNA methylation changes in response to dietary or other lifestyle interventions may help to understand how environmental factors mediate improvements in glycemia in some individuals but not others.
18.3.2 miRNAs and T2D Noncoding RNAs (ncRNAs), particularly miRNAs, have also been implicated in the pathogenesis of T2D. miRNAs have been shown to play critical pathophysiologic roles in insulin-sensitive tissues such as pancreatic β-cells, liver, muscle, and adipose tissue,41 and a number of studies have applied profiling approaches using tissue from diabetic and nondiabetic donors to gain new insight into the molecular mechanisms underlying T2D (Table 18.3). For example, increased levels of miR-21, miR-375, and miR-127-3p have been observed in pancreatic islets of individuals with glucose intolerance compared with normoglycemic controls.42 Levels of miR-375, miR-122, miR-184, and miR-127-3p also correlated positively with insulin gene expression, indicating that these miRNAs may be exerting effects on glucose homeostasis through increased insulin synthesis. In an investigation of 667 miRNAs in islets from 11 T2D donors and 9 controls, only miR-187 and miR-345 showed statistically significant differential expression between the 2 groups.43 Measurement of these two miRNAs in a separate sample failed to validate differential expression of mi-345; however, levels of mi-187 were not only validated, but were also found to be inversely correlated with glucose-stimulated insulin secretion in a sample of 35 normoglycemic donors.43 In earlier studies of the islet miRNome conducted in donors without known T2D,46, 47 miR-187 levels were low or undetectable, suggesting that expression of this miRNA corresponds with the deteriorating condition of β-cells during the progressive development of T2D. In another study sequencing analysis of islet tissue from T2D patients and normoglycemic individuals identified 15 miRNAs showing differential expression between the 2 groups.44 Of the top 10 downregulated miRNAs, seven were derived from the maternally expressed, imprinted DLK1-MEG3 locus on 14q32. Of interest, expression levels of 14q32 miRNAs and the long noncoding MEG3 RNA were 16- to 20-fold higher in β-cells than α-cells.46, 48 Potential targets of 14q32 miRNAs included islet amyloid polypeptide (IAPP) and p53-induced nuclear protein 1 (TP53INP1), both of which increase β-cell apoptosis when overexpressed in islets. A direct targeting relationship was observed between miR-376a and miR-432 and the IAPP 30 UTR. TP53INP1 transcript levels were increased in islets from donors with T2D compared with nondiabetic individuals, and miR-495 was found to downregulate TP53INP1 expression. In an analysis of miRNAs obtained from skeletal muscle, 62 of 171 transcripts were differentially expressed between individuals with T2D compared with normoglycemic controls.45 Interestingly, approximately 10 of these dysregulated miRNAs showed dysregulated expression patterns early in the disease process. Using bioinformatics approaches the authors determined that the potential combinatorial nature of miRNA action in vivo underlies significant changes in target protein levels, which then contributes to the development of insulin resistance and T2D. Despite differences in study design and analysis, as well as limitations associated with small sample sizes, miRNAprofiling studies conducted to date show fairly consistent results. For the most part, however, progress has remained mostly descriptive and little is known of the potential targets of these miRNAs and the mechanisms by which they affect disease development in susceptible individuals. Additional studies aimed at delineating specific miRNA-mRNA networks and consequent effects on β-cell function are expected to further enhance our understanding of the complex pathogenesis of T2D. TABLE 18.3
Major Findings From miRNA-Profiling Studies in Patients With T2D or Glucose Intolerance
Trait
Source
Approach
Major miRNAs identified
References
Glucose intolerant
Islets
Bead-based hybridization
miR-21; miR-127-3p; miR-375
42
T2D
Islets
Microarray
miR-187
43
T2D
Islets
Sequencing
miR-7-1-3p; miR-7-3-5p; miR-23c; miR-30a-5p; miR-187-3p; miR-216a-5p; miR-369-3p; miR-487a-3p; miR-495-3p; miR-539-3p; miR-544a-5p; miR-589-5p; miR-656-3p; miR4716-3p
44
T2D
Muscle
Microarray
miR-15a; miR-15b; miR-98; miR-99a; miR-100a; miR-106b; miR-133a; miR-133b; miR-143; miR-152; miR-185; miR-190
45
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18.3.3 Histone Modifications and T2D Compared with DNA methylation and miRNA studies the investigation of histone modifications in T2D has been limited and uniquely focused on specific loci. For example, Miao et al.49 found higher levels of H2K9me2 around the IL-1A promoter and PTEN-coding regions in diabetic patients than healthy controls. Another study reported higher levels of H3 acetylation in the promoter regions of tumor necrosis factor-alpha (TNFα) and cyclooxygenase-2 (COX2) in peripheral blood mononuclear cells from patients with T2D than control samples,50 while trimethylation at lysine 4 of histone H3 was 40% higher in adipocytes from overweight patients with T2D than normal weight and overweight nondiabetic individuals.51 Today (2018) the study of histone modifications in T2D pathogenesis is in its infancy and additional studies are necessary before the contribution of this epigenetic mechanism to disease development can be fully understood.
18.4 EPIGENETIC MODIFICATIONS AND INTERINDIVIDUAL VARIATION IN RESPONSE TO ANTIDIABETIC DRUGS Epigenetic mechanisms contribute to biological changes that not only underlie disease development, but also modulate how the genome responds to environmental factors, including pharmacological agents. Pharmacoepigenetics encompasses the relationship between pharmaceuticals and epigenetic factors within four broad contexts: interindividual variations in drug response, drug effects on gene expression, adverse drug reactions, and discovery of new drug targets.52, 53 A number of pharmacoepigenetic studies have been conducted, mostly with respect to chemotherapy and drug resistance54; however, studies of epigenetic modulators of the response to antihyperglycemic agents are slowly emerging in the literature. In the following section we review the current state of knowledge of pharmacoepigenetics research in T2D pharmacological treatments. The majority of epigenetics research in antidiabetic agents published to date has focused on metformin, a biguanide. An initial study of the relationship between the DNA methylation status of the insulin promoter and overnutrition reported that metformin significantly increased insulin transcript levels, improved triacylglycerol accumulation, and decreased methylation of the insulin promoter in INS-1 cells, which are β-cell-derived insulin-secreting cells, exposed to high glucose levels.55 These findings suggested that metformin, when directly applied to INS-1 cells, inhibits glucotoxicity-induced insulin mRNA reduction and DNA methylation of the insulin promoter. In the offspring of rats with streptozotocin-induced gestational diabetes, treatment with either metformin or insulin corresponded with increased expression and decreased methylation of PPARGC1A than normal saline administration.56 Metformin has also been reported to contribute to the hypermethylation of tumor-promoting pathway genes through an axis involving miRNA let-7, degradation of H19 long noncoding RNA, and activation of S-adenosylhomocysteine hydrolase.57 Although this work was performed in endometrial cancer cells and tumor samples from endometrial cancer patients, the results suggest that this metformin-mediated mechanism may also operate in normal cells. Garcia-Calzon et al.58 recently reported results from a DNA methylation study of the genes encoding the hepatic metformin transporters SLC22A1, SLC22A3, and SLC47A1 in liver samples from patients with T2D. DNA methylation in all three genes was lower in diabetic subjects receiving metformin than those treated with metformin and insulin together or no treatment at all. The methylation of some individual CpG sites (cg05307864 in SLC22A1; cg02042585, cg06295784, cg17364114 in SLC22A3; and cg12799818 in SLC47A1) were negatively associated with levels of the corresponding transcript, a finding that remained significant following adjustment for age, sex, and presence of nonalcoholic steatohepatitis. The methylation status of transporter CpG sites was likewise correlated with fasting glucose levels and BMI. Higher DNA methylation of genes involved in the hepatic transport of metformin could be a potential mechanism to decrease the expression of transporter genes, which could lead to reduced antidiabetic effects of metformin and result in hyperglycemia.58 SLC22A1/OCT1 serves as a transporter for a number of clinically meaningful drugs in addition to metformin, including the chemotherapeutic agent cisplatin, which is used in the treatment of hepatocellular carcinoma (HCC). SLC22A1 protein expression was significantly decreased in HCC than tumor-free adjacent liver tissue, and the hypermethylation of individual CpG sites within the gene was associated with downregulation of SLC22A1 in HCC.59 The methylation levels of SLC22A1 were highest in HCC, lower in histological tumor-free adjacent liver tissue from HCC patients, and lowest in tumor-free liver tissue from patients without HCC. These results not only provide a potential mechanism by which low response rates and interindividual differences in response to cisplatin-based therapies may be explained,60 but they also provide a basis upon which to speculate that interindividual variation to metformin in T2D patients may follow a similar pattern.
18.5 CONCLUSIONS: IMPLICATIONS FOR TREATMENT STRATEGIES AND PRECISION MEDICINE
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In a model of insulin resistance in which rats were fed a high-fat diet, metformin corresponded with decreased miR21 expression in a dose-dependent manner, which was accompanied by a decrease in homeostasis model assessment of insulin resistance (HOMA-IR).61 Diabetic individuals treated with metformin had higher PBMC levels of the miRNAprocessing protein DICER than sulfonylurea-treated or untreated patients.62 This study also found that metformin altered the subcellular localization of the RNA-binding protein AUF1 in mice, which disrupted its interaction with DICER mRNA, leading to increased DICER levels. Increased DICER levels were associated with increased expression of miRNAs associated with aging, including miR-20a, miR-34a, miR-130a, miR-106b, miR-125, and let-7c.62 In a randomized, placebo-controlled, double-blind study consisting of 18 placebo and 17 metformin-treated T2D patients, plasma concentrations of miR-140-5p, miR-222, miR-142-3p, and miR-192 were significantly different in treated patients than those treated with placebo and paralleled improvements in fasting glucose and HbA1c.63 Systematic profiling of liver histone posttranslational modifications in a prediabetic high-fat-diet-induced obese (DIO) mouse model revealed 170 histone marks, 15 of which varied in abundance compared with liver from chow-fed control animals.64 Treatment of DIO mice with metformin reversed DIO-stimulated histone H3K36me2, suggesting that this mark may not only be associated with the development of T2D, but may also represent a mechanism by which metformin may exert physiological effects. Epigenetic modifications associated with other classes of antidiabetes drugs remain to be characterized. Only recently has the epigenetic regulation of PPARG, the receptor for thiazolidinediones, been studied,65 although such studies have been limited to the study of mechanisms related to cancer. For example, one study reported a dosedependent increase in cell killing in breast cancer cells treated with troglitazone and HDAC inhibitor; this finding was associated with increased H3 lysine 9 (H3K9) and H3K23 acetylation, H2AX and H3S10 phosphorylation, and H3K79 monomethylation and dimethylation.66 In another study miR-130a-3p was found to confer resistance to gemcitabine in patients with cholangiocarcinoma through direct modulation of PPARG expression.67 In addition, a single study provided evidence that DNA methylation regulated expression of the KATP channel subunit, which serves as a receptor for sulfonylureas, in transformed HL-1 cardiomyocytes.68
18.5 CONCLUSIONS: IMPLICATIONS FOR TREATMENT STRATEGIES AND PRECISION MEDICINE Advances in genomic technology and knowledge have led to a “golden age” in common disease genetics. Over 100 loci have shown statistically significant evidence for association with T2D and related traits.69 These discoveries have enormous potential to reveal new targets for drug development and provide a better understanding of the biology underlying existing drug targets to improve T2D pharmacotherapy. However, the majority of these loci are located in intronic or intergenic regions of the genome, suggesting transcriptional or other types of regulation may not only be important contributors to diabetes risk, but may also be important in response to pharmacotherapy or the advent of adverse events. Importantly, as seen in the field of pharmacogenetics, pharmacoepigenetics studies of diabetes and other common diseases face unique challenges. For example, very few drug trials have been designed to address the epigenetic aspects of drug response. Thus relying on archival samples from drug trials may not provide the optimal study design for genetic analysis. Similarly, epidemiologic studies may provide subsamples allowing for assessment of drug response or adverse effects, but many times such studies have not collected adequate information on drug use, dosage, and other critical information necessary to design a substudy. Funding of new drug trials to specifically address pharmacoepigenetics may also be challenging, and replication samples may be hard to identify. Finally, given the differences in methylation patterns, expression of miRNAs, and variability in histone marks among different ethnic groups, the effects discovered in one population may not apply to other populations. Even if new drug trials can be funded and designed, there are issues related to defining “response” to any specific drug. Decreased fasting glucose or HbA1C levels have been traditional metrics used to define drug response. However, glycemia is an output of many upstream events and multiple systems that regulate glycemia. Therefore, whether a specific drug had its intended effect at the target and whether that specific effect was appropriately translated to a change in fasting glycemia or HbA1c is of question. From a clinical perspective a lack of change in either metric could be considered a nonresponse. However, from a mechanistic perspective, if the drug had its intended effect, but as a result of physiologic regulation that effect did not translate into a change in clinical outcome, is that considered a lack of response? Such subtleties can provide important clues regarding diabetes therapies and the effect of epigenetic variation.
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In conclusion, the field of pharmacoepigenetics in T2D represents a novel area of investigation in diabetes research. Efforts to characterize variation in DNA methylation, ncRNA expression and function, as well as differential modifications of histones are critical for understanding the role of epigenetics in mediating interindividual variability in response to diabetes pharmacotherapies.
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A joint editorial statement by the American Diabetes Association; The National Heart, Lung, and Blood Institute; The Juvenile Diabetes Foundation International; The National Institute of Diabetes and Digestive and Kidney Diseases; and The American Heart Association. Circulation. 1999;100(10):1132–1133. 8. Danaei G, Lawes CM, Vander Hoorn S, Murray CJ, Ezzati M. Global and regional mortality from ischaemic heart disease and stroke attributable to higher-than-optimum blood glucose concentration: comparative risk assessment. Lancet. 2006;368(9548):1651–1659. 9. Singh GM, Danaei G, Farzadfar F, et al. The age-specific quantitative effects of metabolic risk factors on cardiovascular diseases and diabetes: a pooled analysis. PLoS One. 2013;8(7)e65174. 10. Kahn SE, Haffner SM, Heise MA, et al. Glycemic durability of rosiglitazone, metformin, or glyburide monotherapy. N Engl J Med. 2006;355 (23):2427–2443. 11. Van Gaal LF, De Leeuw IH. Rationale and options for combination therapy in the treatment of Type 2 diabetes. Diabetologia. 2003;46(suppl 1): M44–M50. 12. Buchanan TA, Xiang AH, Peters RK, et al. Preservation of pancreatic á-cell function and prevention of type 2 diabetes by pharmacological treatment of insulin resistance in high-risk hispanic women. Diabetes. 2002;51:2796–2803. 13. Xiang AH, Peters RK, Kjos SL, et al. Effect of pioglitazone on pancreatic á-cell function and diabetes risk in Hispanic women with prior gestational diabetes. Diabetes. 2006;55:517–522. 14. The DTI. Effect of rosiglitazone on the frequency of diabetes in patients with impaired glucose tolerance or impaired fasting glucose: a randomised controlled trial. Lancet. 2006;368(9541):1096–1105. 15. The Diabetes Prevention Program Research Group. Prevention of type 2 diabetes with troglitazone in the diabetes prevention program. Diabetes. 2005;54:1150–1156. 16. DeFronzo RA, Tripathy D, Schwenke DC, et al. Pioglitazone for diabetes prevention in impaired glucose tolerance. N Engl J Med. 2011;364 (12):1104–1115. 17. Boniol M, Franchi M, Bota M, et al. Incretin-based therapies and the short-term risk of pancreatic cancer: results from two retrospective cohort studies. Diabetes Care. 2018;41(2):286–292. 18. Matveyenko AV, Dry S, Cox HI, et al. Beneficial endocrine but adverse exocrine effects of sitagliptin in the human islet amyloid polypeptide transgenic rat model of type 2 diabetes: interactions with metformin. Diabetes. 2009;58(7):1604–1615. 19. DiStefano JK, Watanabe RM. Pharmacogenetics of anti-diabetes drugs. Pharmaceuticals (Basel). 2010;3(8):2610–2646. 20. Tkac I. Genetics of drug response in type 2 diabetes. Curr Diab Rep. 2015;15(7):43. 21. Dawed AY, Zhou K, Pearson ER. Pharmacogenetics in type 2 diabetes: influence on response to oral hypoglycemic agents. Pharmacogenomics Pers Med. 2016;9:17–29. 22. Florez JC. The pharmacogenetics of metformin. Diabetologia. 2017;60(9):1648–1655. 23. Maruthur NM, Gribble MO, Bennett WL, et al. The pharmacogenetics of type 2 diabetes: a systematic review. Diabetes Care. 2014;37(3):876–886. 24. Raciti GA, Nigro C, Longo M, et al. Personalized medicine and type 2 diabetes: lesson from epigenetics. Epigenomics. 2014;6(2):229–238. 25. Schwenk RW, Vogel H, Schurmann A. Genetic and epigenetic control of metabolic health. Mol Metab. 2013;2(4):337–347. 26. Allis CD, Jenuwein T. The molecular hallmarks of epigenetic control. Nat Rev Genet. 2016;17(8):487–500. 27. Ivanov M, Barragan I, Ingelman-Sundberg M. Epigenetic mechanisms of importance for drug treatment. Trends Pharmacol Sci. 2014;35 (8):384–396. 28. Fatemi M, Pao MM, Jeong S, et al. Footprinting of mammalian promoters: use of a CpG DNA methyltransferase revealing nucleosome positions at a single molecule level. Nucleic Acids Res. 2005;33(20):e176. 29. Hombach S, Kretz M. Non-coding RNAs: classification, biology and functioning. Adv Exp Med Biol. 2016;937:3–17. 30. Muka T, Nano J, Voortman T, et al. The role of global and regional DNA methylation and histone modifications in glycemic traits and type 2 diabetes: a systematic review. Nutr Metab Cardiovasc Dis. 2016;26(7):553–566. 31. Ronn T, Ling C. DNA methylation as a diagnostic and therapeutic target in the battle against Type 2 diabetes. Epigenomics. 2015;7(3):451–460. 32. Dayeh T, Volkov P, Salo S, et al. Genome-wide DNA methylation analysis of human pancreatic islets from type 2 diabetic and non-diabetic donors identifies candidate genes that influence insulin secretion. PLoS Genet. 2014;10(3)e1004160. 33. Hidalgo B, Irvin MR, Sha J, et al. Epigenome-wide association study of fasting measures of glucose, insulin, and HOMA-IR in the genetics of lipid lowering drugs and diet network study. Diabetes. 2014;63(2):801–807. 34. Kulkarni H, Kos MZ, Neary J, et al. Novel epigenetic determinants of type 2 diabetes in Mexican-American families. 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35. Ribel-Madsen R, Fraga MF, Jacobsen S, et al. Genome-wide analysis of DNA methylation differences in muscle and fat from monozygotic twins discordant for type 2 diabetes. PLoS One. 2012;7(12)e51302. 36. Toperoff G, Aran D, Kark JD, et al. Genome-wide survey reveals predisposing diabetes type 2-related DNA methylation variations in human peripheral blood. Hum Mol Genet. 2012;21(2):371–383. 37. Volkmar M, Dedeurwaerder S, Cunha DA, et al. DNA methylation profiling identifies epigenetic dysregulation in pancreatic islets from type 2 diabetic patients. EMBO J. 2012;31(6):1405–1426. 38. Hall E, Volkov P, Dayeh T, et al. Effects of palmitate on genome-wide mRNA expression and DNA methylation patterns in human pancreatic islets. BMC Med. 2014;12:103. 39. Nitert MD, Dayeh T, Volkov P, et al. Impact of an exercise intervention on DNA methylation in skeletal muscle from first-degree relatives of patients with type 2 diabetes. Diabetes. 2012;61(12):3322–3332. 40. Barres R, Yan J, Egan B, et al. Acute exercise remodels promoter methylation in human skeletal muscle. Cell Metab. 2012;15(3):405–411. 41. DiStefano JK. Beyond the protein-coding sequence: noncoding RNAs in the pathogenesis of type 2 diabetes. Rev Diabet Stud. 2015;12(34):260–276. 42. Bolmeson C, Esguerra JL, Salehi A, Speidel D, Eliasson L, Cilio CM. Differences in islet-enriched miRNAs in healthy and glucose intolerant human subjects. Biochem Biophys Res Commun. 2011;404(1):16–22. 43. Locke JM, da Silva Xavier G, Dawe HR, Rutter GA, Harries LW. Increased expression of miR-187 in human islets from individuals with type 2 diabetes is associated with reduced glucose-stimulated insulin secretion. Diabetologia. 2014;57(1):122–128. 44. Kameswaran V, Bramswig NC, McKenna LB, et al. Epigenetic regulation of the DLK1-MEG3 microRNA cluster in human type 2 diabetic islets. Cell Metab. 2014;19(1):135–145. 45. Gallagher IJ, Scheele C, Keller P, et al. Integration of microRNA changes in vivo identifies novel molecular features of muscle insulin resistance in type 2 diabetes. Genome Med. 2010;2(2):9. 46. Klein D, Misawa R, Bravo-Egana V, et al. MicroRNA expression in alpha and beta cells of human pancreatic islets. PLoS One. 2013;8(1)e55064. 47. van de Bunt M, Gaulton KJ, Parts L, et al. The miRNA profile of human pancreatic islets and beta-cells and relationship to type 2 diabetes pathogenesis. PLoS One. 2013;8(1)e55272. 48. Dorrell C, Abraham SL, Lanxon-Cookson KM, Canaday PS, Streeter PR, Grompe M. Isolation of major pancreatic cell types and long-term culture-initiating cells using novel human surface markers. Stem Cell Res. 2008;1(3):183–194. 49. Miao F, Wu X, Zhang L, Yuan YC, Riggs AD, Natarajan R. Genome-wide analysis of histone lysine methylation variations caused by diabetic conditions in human monocytes. J Biol Chem. 2007;282(18):13854–13863. 50. Hou C, Zhao M, Li X, et al. Histone H3 acetylation of tumor necrosis factor-alpha and cyclooxygenase-2 in patients with type 2 diabetes. Zhonghua Yi Xue Za Zhi. 2011;91(26):1805–1808. 51. Jufvas A, Sjodin S, Lundqvist K, Amin R, Vener AV, Stralfors P. Global differences in specific histone H3 methylation are associated with overweight and type 2 diabetes. Clin Epigenetics. 2013;5(1):15. 52. Gomez A, Ingelman-Sundberg M. Pharmacoepigenetics: its role in interindividual differences in drug response. Clin Pharmacol Ther. 2009;85 (4):426–430. 53. Peedicayil J. Pharmacoepigenetics and pharmacoepigenomics. Pharmacogenomics. 2008;9(12):1785–1786. 54. Lauschke VM, Barragan I, Ingelman-Sundberg M. Pharmacoepigenetics and toxicoepigenetics: novel mechanistic insights and therapeutic opportunities. Annu Rev Pharmacol Toxicol. 2018;A58:161–185. 55. Ishikawa K, Tsunekawa S, Ikeniwa M, et al. Long-term pancreatic beta cell exposure to high levels of glucose but not palmitate induces DNA methylation within the insulin gene promoter and represses transcriptional activity. PLoS One. 2015;10(2)e0115350. 56. Song AQ, Sun LR, Zhao YX, Gao YH, Chen L. Effect of insulin and metformin on methylation and glycolipid metabolism of peroxisome proliferator-activated receptor gamma coactivator-1A of rat offspring with gestational diabetes mellitus. Asian Pac J Trop Med. 2016;9(1):91–95. 57. Zhong T, Men Y, Lu L, et al. Metformin alters DNA methylation genome-wide via the H19/SAHH axis. Oncogene. 2017;36(17):2345–2354. 58. Garcia-Calzon S, Perfilyev A, Mannisto V, et al. Diabetes medication associates with DNA methylation of metformin transporter genes in the human liver. Clin Epigenetics. 2017;9:102. 59. Schaeffeler E, Hellerbrand C, Nies AT, et al. DNA methylation is associated with downregulation of the organic cation transporter OCT1 (SLC22A1) in human hepatocellular carcinoma. Genome Med. 2011;3(12):82. 60. Tang J, Xiong Y, Zhou HH, Chen XP. DNA methylation and personalized medicine. J Clin Pharm Ther. 2014;39(6):621–627. 61. Wang J, Gao Y, Duan L, et al. Metformin ameliorates skeletal muscle insulin resistance by inhibiting miR-21 expression in a high-fat dietary rat model. Oncotarget. 2017;8(58):98029–98039. 62. Noren Hooten N, Martin-Montalvo A, Dluzen DF, et al. Metformin-mediated increase in DICER1 regulates microRNA expression and cellular senescence. Aging Cell. 2016;15(3):572–581. 63. Ortega FJ, Mercader JM, Moreno-Navarrete JM, et al. Profiling of circulating microRNAs reveals common microRNAs linked to type 2 diabetes that change with insulin sensitization. Diabetes Care. 2014;37(5):1375–1383. 64. Nie L, Shuai L, Zhu M, et al. The landscape of histone modifications in a high-fat diet-induced obese (DIO) mouse model. Mol Cell Proteomics. 2017;16(7):1324–1334. 65. Sugii S, Evans RM. Epigenetic codes of PPARgamma in metabolic disease. FEBS Lett. 2011;585(13):2121–2128. 66. Davies GF, Ross AR, Arnason TG, Juurlink BH, Harkness TA. Troglitazone inhibits histone deacetylase activity in breast cancer cells. Cancer Lett. 2010;288(2):236–250. 67. Asukai K, Kawamoto K, Eguchi H, et al. Micro-RNA-130a-3p regulates gemcitabine resistance via PPARG in cholangiocarcinoma. Ann Surg Oncol. 2017;24(8):2344–2352. 68. Fatima N, Schooley Jr. JF, Claycomb WC, Flagg TP. Promoter DNA methylation regulates murine SUR1 (Abcc8) and SUR2 (Abcc9) expression in HL-1 cardiomyocytes. PLoS One. 2012;7(7)e41533. 69. Visscher PM, Wray NR, Zhang Q, et al. 10 Years of GWAS discovery: biology, function, and translation. Am J Hum Genet. 2017;101(1):5–22.
18 Pharmacoepigenetics in Type 2 Diabetes Mellitus Johanna K. DiStefano*, and Richard M. Watanabe† †
*Diabetes and Fibrotic Disease Unit, Translational Genomics Research Institute, Phoenix, AZ, United States Departments of Preventive Medicine and Physiology & Neuroscience, Keck School of Medicine of USC, Los Angeles, CA, United States
18.1 OVERVIEW OF TYPE 2 DIABETES (T2D): PREVALENCE, DIAGNOSIS, AND CLINICAL MANAGEMENT Diabetes mellitus is a heterogeneous collection of disorders resulting from a state of chronic hyperglycemia. The most prevalent form of diabetes mellitus is type 2 diabetes (T2D), which accounts for approximately 90% of all cases of diabetes1 and develops predominantly in response to multiorgan insulin resistance and inadequate insulin production from pancreatic β-cells.2, 3 The global prevalence of T2D has nearly doubled since 1980: at present more than 420 million individuals are affected by the disease4 and this number is expected to exceed 520 million individuals within 15 years.5 In the United States, diabetes and related neural, retinal, and renal complications, were estimated to cost over $245 billion in direct and indirect costs.6 T2D is a risk factor for other chronic noncommunicable disorders, including cardiovascular disease,7 further underscoring its role as a leading public health concern. Historically, a fasting glycemic threshold (i.e., 126 mg/dL or 7 mM), has been used for diabetes diagnosis, although there is a shift toward implementing hemoglobin A1c (HbA1c) as a diagnostic marker because this measurement represents average glycemia over a 2–3 month period and thus provides information on longer term glycemic control. Regardless of diagnostic concerns, diabetes and its complications are consequences of fasting hyperglycemia to which there are many paths. Moreover, even glycemic levels below the diagnostic threshold have been associated with significantly higher mortality and morbidity from cardiovascular complications,8, 9 resulting in the clinical implementation of aggressive strategies to reduce glycemia in prediabetic individuals. It is of clinical significance to view diabetes on a glycemic continuum, and interpret gradual elevations in glycemia as warning signs requiring immediate intervention to prevent full-blown development of the disease. T2D is characterized by obesity, insulin resistance, and pancreatic β-cell dysfunction.2, 3 Although insulin resistance and pancreatic β-cell dysfunction are both requisite for T2D development, the relative importance of each has been the subject of ongoing debate for decades. However, it is clear that the combination of insulin resistance and pancreatic β-cell dysfunction is required for disease manifestation; insulin resistance alone cannot result in T2D. Further, pancreatic β-cell dysfunction is a strong predictor of diabetes, independent of insulin resistance, suggesting that these cells hold the key to disease pathogenesis. A primary role of pancreatic β-cell dysfunction is also supported by findings from the ADOPT study, which examined the glycemic durability of different pharmacologic therapies that targeted different tissues related to T2D: glyburide (pancreas), metformin (liver), and rosiglitazone (skeletal muscle).10 The study showed that while glyburide, a sulfonylurea antidiabetes drug, was effective in immediately restraining hyperglycemia, the effect was short-lived and efficacy became significantly reduced with continued use. This result suggested that the sulfonylurea class of drugs, which induce insulin secretion (discussed below), might accelerate pancreatic β-cell dysfunction. In contrast, both metformin and rosiglitazone showed more prolonged efficacy over the course of the study, while gradually reducing hyperglycemia. These results provide important clues regarding the treatment of T2D. First, because this
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564 TABLE 18.1
18. PHARMACOEPIGENETICS IN TYPE 2 DIABETES MELLITUS
Major Classes of Noninsulin Antihyperglycemic Drugs
Drug class
Mechanism of action
Generic name (Brand name)
Alpha-glucosidase inhibitors
Delay digestion of carbohydrates in the small intestine
Acarbose (Precose); Miglitol (Glyset)
Biguanides
Decrease hepatic glucose output and increase peripheral insulin sensitivity
Metformin (Glucophage); Metformin-extended release (Glutmetza, Fortamet); Metformin HCl (Riomet)
Bile acid sequestrants
Prevent reabsorption of bile acids from the gut
Colesevelam (Welchol)
Dopamine-2 agonists
Indirectly suppress hepatic glucose production
Bromocriptine (Cycloset)
DPP-4 inhibitors (gliptins)
Prevent breakdown of incretins, resulting in increased insulin production and decreased hepatic glucose output
Alogliptin (Nesina); Linagliptin (Tradjenta); Saxagliptin (Onglyza); Sitagliptin (Januiva)
Incretin mimetics
Promote insulin secretion from pancreas
Albiglutide (Tanzeum); Dulaglutide (Trulicity); Exenatide (Byetta); Exenatide-extended release (Bydureon); Liraglutide (Victoza)
Meglitinides
Promote insulin secretion from pancreas
Nateglinide (Starlix); Repaglinide (Prandin)
Sulfonylureas
Promote insulin secretion from pancreas
Glimepiride (Amaryl); Glipizide (Glucotrol); Glipizide-extended release (Glucotrol XL); Glyburide (Glynase)
Thiazolidinediones
Increase insulin sensitivity and decrease hepatic glucose production
Pioglitazone (Actos); Rosiglitazone (Avandia)
SGLT2-inhibitors
Lower renal glucose threshold, allowing greater urinary glucose excretion
Canagliflozin (Invokana); Dapagliflozin (Farxiga); Empagliflozin (Jardiance)
DPP, Dipeptidyl peptidase; SGLT2, sodium-glucose transporter 2.
form of diabetes involves multiple tissues, for optimal results pharmacologic therapies should target more than one tissue. In accord, this finding, combined with results from other studies,11 has resulted in the development and implementation of combination therapy, which refers to the treatment strategy in which a patient is given two or more drugs for the same disease. Second, although T2D is primarily a disease of the pancreatic β-cell, targeting insulin resistance to reduce demand on the β-cell may be an effective approach to treat or prevent T2D. Buchanan et al.12 first demonstrated this concept by treating individuals at risk for developing T2D with a thiazolidinedione, which significantly reduced the development of disease.12, 13 These findings were subsequently replicated in larger studies.14–16 Lifestyle modification has been the primary intervention to both prevent and treat T2D. However, for a variety of reasons, changing behavior patterns is difficult, which means that pharmacologic or other forms of intervention are necessary. The repertoire of oral and injected antidiabetic agents has expanded greatly during the past decade and encompasses nine major classes of approved oral drugs, two classes of noninsulin-injected medications, and a number of different options for insulin delivery. A list of the major classes of noninsulin antidiabetic agents, including generic and brand names and mechanisms of action, is provided in Table 18.1. Although listed in the table, the thiazolidinedione class of medications has been associated with a number of side effects, resulting in black labeling by the FDA in the United States. Newer forms of therapy for T2D have targeted nontraditional biologic pathways contributing to the pathophysiology of the disease. Recently, drugs targeting the incretin system have gained wide use. Incretin hormones, like glucagon-like peptide 1 (GLP1), act as insulin secretagogues, and drugs affecting this system take two forms: GLP1 memetics or dipeptidyl peptidase 4 (DPP4) inhibitors. DPP4 is the enzyme that degrades GLP1; therefore, inhibiting its action allows GLP1 to remain active. There is controversial evidence that incretin-based therapies may increase risk for pancreatic cancer.17, 18 Also, because these drugs act as insulin secretagogues, there is some concern their long-term effects might be similar to those observed for sulfonylureas in the ADOPT study. Sodium-glucose cotransporter 2 (SGLT2) inhibitors are another new class of medications that inhibit glucose resorption in the proximal convoluted tubule and facilitate excretion of glucose via the urine. Recently, the FDA issued new warnings for SGLT2 inhibitors, including increased risks for urinary tract infections, acute kidney injury, and leg or foot amputations (www.fda.gov/drugs/ drugsafety/ucm446). As noted earlier, combination therapy has become more common as physicians attempt to target more than one tissue or pathway to regulate glucose, and a number of combination products are currently available. Pharmacologic therapies come with side effects that engender alternative medical problems or exacerbate other diabetes comorbidities, as noted by the FDA notices for thiazolidinediones, incretin-based, and SGLT2 inhibitor drugs.
18.3 COMMON EPIGENETIC MODIFICATIONS IN T2D
565
FIG. 18.1
Factors affecting interindividual response to pharmacological agents and potential therapeutic outcomes. In some instances external factors directly impact drug response, as represented by the bottom arrow. However, in other cases epigenetic modifications may mitigate the effects of these factors, including genetic variants, on therapeutic outcomes.
Furthermore, reduction in glycemia alone may not affect the risk for diabetes complications or comorbidities. For example, T2D is among the strongest risk factors for death as a result of cardiovascular events. Thus, current clinical strategies recommend the maintenance of glycemia concomitant with control of other cardiovascular risk factors, such as hypertension and hypercholesterolemia. As such, the pharmacologic mix necessary to manage multiple outcomes continues to present challenges for both patient and clinician.
18.2 PHARMACOGENOMICS OF T2D Glycemic response to oral antidiabetic agents is highly variable, and there are a number of factors that contribute to interindividual variations in drug response. As shown in Fig. 18.1, these factors include age, sex, disease, drug and food interactions, and comorbidities.19 Genetic variants also contribute to differential drug response, a phenomenon comprising an entire branch of study known as pharmacogenetics. A number of pharmacogenetics studies have investigated the role of genetic variants in mediating response to such antihyperglycemic drugs as biguanides, sulfonylureas, and thiazolidinediones19; however, genetic factors contribute to only a portion of the variation in response to antidiabetic agents, suggesting that other factors may play a role in variable drug response. Further, while genetic information has had limited success in identifying appropriate drug therapies for rare forms of diabetes, it has not led to significant changes in the clinical management of more common forms of diabetes, such as T2D. This is due, in part, to a paucity of pharmacogenetic studies examining the genetic effects of drug-based adverse events. Sadly, our understanding of T2D pharmacogenomics has not substantially improved over the last decade, and the reader is referred to review articles to learn more about specific variants associated with drug response in diabetes treatment.19–23 Despite the limited success seen with genetic studies, emerging evidence supports the notion that environmental and lifestyle factors influence the development and progression of T2D through epigenetic modulation of genes that play important roles in glucose metabolism, insulin resistance, and β-cell dysfunction.24 Like genetic variants, epigenetic modifications may also contribute to interindividual response to antidiabetic agents24; however, these factors are more likely to interact with other influences, including aging, diet, and other drugs, to uniquely impact drug response.
18.3 COMMON EPIGENETIC MODIFICATIONS IN T2D Epigenetic modifications affect gene expression through the modulation of chromatin structure, accessibility to transcriptional factors, and posttranscriptional regulation without changes in genome sequence.25 Chromatin is a complex comprised of protein, DNA, and RNA, and a primary function of chromatin is regulation of gene expression. An active chromatin sequence allows binding of transcriptional factors leading to gene expression, while condensed chromatin is typically associated with gene inactivation. Chromatin states, and therefore gene transcription, are modulated by DNA methylation and histone modifications.26, 27 DNA methylation is mediated by DNA methyltransferases, which primarily methylate cytosine-5 molecules in cytosine-guanine pairs (CpGs). Regions with a high density of CpG dinucleotides are known as CpG islands, which are typically located near the transcriptional start site in mammalian genes.28 CpG island methylation is a dynamic epigenetic process during mammalian development and is important for the regulation of gene expression and maintaining the stability of the genome. The main protein components are histones, which act to tightly wrap DNA into nucleosomes. Covalent, posttranslational modifications, such as acetylation, phosphorylation, or methylation, to histone proteins can alter chromatin structure and affect
566
18. PHARMACOEPIGENETICS IN TYPE 2 DIABETES MELLITUS
accessibility for the transcriptional machinery. DNA methylation and histone modifications can be interactive; for example, actively expressed genes are commonly associated with low levels of promoter CpG methylation and high levels of histone acetylation. Noncoding RNAs (ncRNAs) are also considered part of the epigenetic machinery based on their role in the posttranscriptional regulation of gene expression. While there are many classes of ncRNAs,29 the class of microRNAs (miRNAs), which bind to complementary sequences in target genes to exert effects on transcription, is the best studied to date. Changes in DNA methylation, histone modifications, and miRNA expression are dynamic and highly responsive to environmental factors, including aging, dietary components, pharmacological agents, toxins, and physical exercise. Importantly, interactions between genetic susceptibility and environmental exposure leading to differential effects on disease development and progression may be mediated by epigenetic mechanisms.
18.3.1 DNA Methylation and T2D DNA methylation is the most commonly studied epigenetic modification in T2D. In humans, over 30 studies have explored DNA methylation patterns in known candidate genes for T2D susceptibility or glycemic traits.30, 31 Of these, CpG sites in the genes encoding glucagon-like peptide 1 receptor (GLP1R), insulin (INS), peroxisome proliferatoractivated receptor gamma coactivator 1-alpha (PPARGC1A), and potassium voltage-gated channel subfamily Q member 1 (KCNQ1) have shown consistent evidence for differential methylation across multiple studies.30, 31 A number of epigenome-wide studies have also investigated DNA methylation patterns in pancreatic islets, skeletal muscle, adipose tissue, and blood in individuals with T2D or impaired glucose metabolism; major findings from these investigations are summarized in Table 18.2. Despite differences in study design and methodologies, overlap among findings of differentially methylated sites suggests common methylomic mechanisms in T2D, including differential methylation at CpG sites near the ATP-binding cassette subfamily G member 1 (ABCG1), KCNQ1, solute carrier family 30 member 8 (SLCA30A8), and transcription factor 7-like 2 (TCF7L2) genes. DNA methylation patterns are also altered in response to environmental factors relevant to T2D. For example, DNA methylation was higher in human pancreatic islets exposed to palmitate than control islets,38 suggesting that higher circulating free fatty acids, a common feature of T2D, may exert effects through changes in islet methylation. In another study a 6-month exercise intervention in individuals with or without a family history of T2D revealed differential methylation of 134 genes in skeletal muscle, including myocyte enhancer factor 2 (MEF2A), THADA, armadillo repeat containing (THADA), NADH:ubiquinone oxidoreductase subunit C2 (NDUFC2), and interleukin 7 (IL-7), all of which have implications for metabolic function.39 A similar study reported overall decreased global DNA methylation of genes in skeletal muscle following a bout of acute exercise and specific hypomethylation of many candidate genes including PPARGC1A, mitochondrial transcription factor A (TFAM), peroxisome proliferator-activated receptor delta (PPARD), pyruvate dehydrogenase kinase 4 (PDK4), and citrate synthase (CS).40 Studies of DNA methylation in TABLE 18.2
Summary of Genome-Wide DNA Methylation Studies Conducted in T2D Patients
Trait
Source
T2D
Pancreatic islets
Fasting insulin; HOMA-IR
CpG No.
Major findings
References
1649
CDKN1A; EXOC3L2; FTO; IRS1; KCNQ1; PDE7B; PPARG; SEPT9; TCF7L2; THADA
32
CD4(+) T cells
1
ABCG1
33
T2D FBG HOMA-IR
Blood
51 19 24
TXNIP; ABCG1; SAMD12
34
T2D
Skeletal muscle Adipose tissue
789 1458
CDKN2A; DUSP9; HHEX; KCNQ1; PPARGC1A; SLC30A8 ADCY5; CDKN2A; CDKN2B; DUSP9; IDE; IRS1; KCNQ1; MTNR1B; TSPAN8; WFS1
35
T2D
Blood
13
FTO; JAZF1; KCNQ1; SLC30A8; TCF7L2; THADA
36
T2D
Pancreatic islets
276
BCL2; CHAC1; GUCA2B; NIBAN; NR4A1; MKNK2; PER2; SFRS2IP
37
FBG, Fasting blood glucose; HOMA-IR, homeostatic model assessment of insulin resistance
567
18.3 COMMON EPIGENETIC MODIFICATIONS IN T2D
adipose tissue in patients with T2D and following exercise intervention have also been performed, and details from this work have been described elsewhere.31 Together, these findings demonstrate that DNA methylation is a key feature of physiological mechanisms related to β-cell function, insulin resistance, and glucose tolerance and serve to augment our understanding of T2D pathogenesis. Additional studies investigating DNA methylation changes in response to dietary or other lifestyle interventions may help to understand how environmental factors mediate improvements in glycemia in some individuals but not others.
18.3.2 miRNAs and T2D Noncoding RNAs (ncRNAs), particularly miRNAs, have also been implicated in the pathogenesis of T2D. miRNAs have been shown to play critical pathophysiologic roles in insulin-sensitive tissues such as pancreatic β-cells, liver, muscle, and adipose tissue,41 and a number of studies have applied profiling approaches using tissue from diabetic and nondiabetic donors to gain new insight into the molecular mechanisms underlying T2D (Table 18.3). For example, increased levels of miR-21, miR-375, and miR-127-3p have been observed in pancreatic islets of individuals with glucose intolerance compared with normoglycemic controls.42 Levels of miR-375, miR-122, miR-184, and miR-127-3p also correlated positively with insulin gene expression, indicating that these miRNAs may be exerting effects on glucose homeostasis through increased insulin synthesis. In an investigation of 667 miRNAs in islets from 11 T2D donors and 9 controls, only miR-187 and miR-345 showed statistically significant differential expression between the 2 groups.43 Measurement of these two miRNAs in a separate sample failed to validate differential expression of mi-345; however, levels of mi-187 were not only validated, but were also found to be inversely correlated with glucose-stimulated insulin secretion in a sample of 35 normoglycemic donors.43 In earlier studies of the islet miRNome conducted in donors without known T2D,46, 47 miR-187 levels were low or undetectable, suggesting that expression of this miRNA corresponds with the deteriorating condition of β-cells during the progressive development of T2D. In another study sequencing analysis of islet tissue from T2D patients and normoglycemic individuals identified 15 miRNAs showing differential expression between the 2 groups.44 Of the top 10 downregulated miRNAs, seven were derived from the maternally expressed, imprinted DLK1-MEG3 locus on 14q32. Of interest, expression levels of 14q32 miRNAs and the long noncoding MEG3 RNA were 16- to 20-fold higher in β-cells than α-cells.46, 48 Potential targets of 14q32 miRNAs included islet amyloid polypeptide (IAPP) and p53-induced nuclear protein 1 (TP53INP1), both of which increase β-cell apoptosis when overexpressed in islets. A direct targeting relationship was observed between miR-376a and miR-432 and the IAPP 30 UTR. TP53INP1 transcript levels were increased in islets from donors with T2D compared with nondiabetic individuals, and miR-495 was found to downregulate TP53INP1 expression. In an analysis of miRNAs obtained from skeletal muscle, 62 of 171 transcripts were differentially expressed between individuals with T2D compared with normoglycemic controls.45 Interestingly, approximately 10 of these dysregulated miRNAs showed dysregulated expression patterns early in the disease process. Using bioinformatics approaches the authors determined that the potential combinatorial nature of miRNA action in vivo underlies significant changes in target protein levels, which then contributes to the development of insulin resistance and T2D. Despite differences in study design and analysis, as well as limitations associated with small sample sizes, miRNAprofiling studies conducted to date show fairly consistent results. For the most part, however, progress has remained mostly descriptive and little is known of the potential targets of these miRNAs and the mechanisms by which they affect disease development in susceptible individuals. Additional studies aimed at delineating specific miRNA-mRNA networks and consequent effects on β-cell function are expected to further enhance our understanding of the complex pathogenesis of T2D. TABLE 18.3
Major Findings From miRNA-Profiling Studies in Patients With T2D or Glucose Intolerance
Trait
Source
Approach
Major miRNAs identified
References
Glucose intolerant
Islets
Bead-based hybridization
miR-21; miR-127-3p; miR-375
42
T2D
Islets
Microarray
miR-187
43
T2D
Islets
Sequencing
miR-7-1-3p; miR-7-3-5p; miR-23c; miR-30a-5p; miR-187-3p; miR-216a-5p; miR-369-3p; miR-487a-3p; miR-495-3p; miR-539-3p; miR-544a-5p; miR-589-5p; miR-656-3p; miR4716-3p
44
T2D
Muscle
Microarray
miR-15a; miR-15b; miR-98; miR-99a; miR-100a; miR-106b; miR-133a; miR-133b; miR-143; miR-152; miR-185; miR-190
45
568
18. PHARMACOEPIGENETICS IN TYPE 2 DIABETES MELLITUS
18.3.3 Histone Modifications and T2D Compared with DNA methylation and miRNA studies the investigation of histone modifications in T2D has been limited and uniquely focused on specific loci. For example, Miao et al.49 found higher levels of H2K9me2 around the IL-1A promoter and PTEN-coding regions in diabetic patients than healthy controls. Another study reported higher levels of H3 acetylation in the promoter regions of tumor necrosis factor-alpha (TNFα) and cyclooxygenase-2 (COX2) in peripheral blood mononuclear cells from patients with T2D than control samples,50 while trimethylation at lysine 4 of histone H3 was 40% higher in adipocytes from overweight patients with T2D than normal weight and overweight nondiabetic individuals.51 Today (2018) the study of histone modifications in T2D pathogenesis is in its infancy and additional studies are necessary before the contribution of this epigenetic mechanism to disease development can be fully understood.
18.4 EPIGENETIC MODIFICATIONS AND INTERINDIVIDUAL VARIATION IN RESPONSE TO ANTIDIABETIC DRUGS Epigenetic mechanisms contribute to biological changes that not only underlie disease development, but also modulate how the genome responds to environmental factors, including pharmacological agents. Pharmacoepigenetics encompasses the relationship between pharmaceuticals and epigenetic factors within four broad contexts: interindividual variations in drug response, drug effects on gene expression, adverse drug reactions, and discovery of new drug targets.52, 53 A number of pharmacoepigenetic studies have been conducted, mostly with respect to chemotherapy and drug resistance54; however, studies of epigenetic modulators of the response to antihyperglycemic agents are slowly emerging in the literature. In the following section we review the current state of knowledge of pharmacoepigenetics research in T2D pharmacological treatments. The majority of epigenetics research in antidiabetic agents published to date has focused on metformin, a biguanide. An initial study of the relationship between the DNA methylation status of the insulin promoter and overnutrition reported that metformin significantly increased insulin transcript levels, improved triacylglycerol accumulation, and decreased methylation of the insulin promoter in INS-1 cells, which are β-cell-derived insulin-secreting cells, exposed to high glucose levels.55 These findings suggested that metformin, when directly applied to INS-1 cells, inhibits glucotoxicity-induced insulin mRNA reduction and DNA methylation of the insulin promoter. In the offspring of rats with streptozotocin-induced gestational diabetes, treatment with either metformin or insulin corresponded with increased expression and decreased methylation of PPARGC1A than normal saline administration.56 Metformin has also been reported to contribute to the hypermethylation of tumor-promoting pathway genes through an axis involving miRNA let-7, degradation of H19 long noncoding RNA, and activation of S-adenosylhomocysteine hydrolase.57 Although this work was performed in endometrial cancer cells and tumor samples from endometrial cancer patients, the results suggest that this metformin-mediated mechanism may also operate in normal cells. Garcia-Calzon et al.58 recently reported results from a DNA methylation study of the genes encoding the hepatic metformin transporters SLC22A1, SLC22A3, and SLC47A1 in liver samples from patients with T2D. DNA methylation in all three genes was lower in diabetic subjects receiving metformin than those treated with metformin and insulin together or no treatment at all. The methylation of some individual CpG sites (cg05307864 in SLC22A1; cg02042585, cg06295784, cg17364114 in SLC22A3; and cg12799818 in SLC47A1) were negatively associated with levels of the corresponding transcript, a finding that remained significant following adjustment for age, sex, and presence of nonalcoholic steatohepatitis. The methylation status of transporter CpG sites was likewise correlated with fasting glucose levels and BMI. Higher DNA methylation of genes involved in the hepatic transport of metformin could be a potential mechanism to decrease the expression of transporter genes, which could lead to reduced antidiabetic effects of metformin and result in hyperglycemia.58 SLC22A1/OCT1 serves as a transporter for a number of clinically meaningful drugs in addition to metformin, including the chemotherapeutic agent cisplatin, which is used in the treatment of hepatocellular carcinoma (HCC). SLC22A1 protein expression was significantly decreased in HCC than tumor-free adjacent liver tissue, and the hypermethylation of individual CpG sites within the gene was associated with downregulation of SLC22A1 in HCC.59 The methylation levels of SLC22A1 were highest in HCC, lower in histological tumor-free adjacent liver tissue from HCC patients, and lowest in tumor-free liver tissue from patients without HCC. These results not only provide a potential mechanism by which low response rates and interindividual differences in response to cisplatin-based therapies may be explained,60 but they also provide a basis upon which to speculate that interindividual variation to metformin in T2D patients may follow a similar pattern.
18.5 CONCLUSIONS: IMPLICATIONS FOR TREATMENT STRATEGIES AND PRECISION MEDICINE
569
In a model of insulin resistance in which rats were fed a high-fat diet, metformin corresponded with decreased miR21 expression in a dose-dependent manner, which was accompanied by a decrease in homeostasis model assessment of insulin resistance (HOMA-IR).61 Diabetic individuals treated with metformin had higher PBMC levels of the miRNAprocessing protein DICER than sulfonylurea-treated or untreated patients.62 This study also found that metformin altered the subcellular localization of the RNA-binding protein AUF1 in mice, which disrupted its interaction with DICER mRNA, leading to increased DICER levels. Increased DICER levels were associated with increased expression of miRNAs associated with aging, including miR-20a, miR-34a, miR-130a, miR-106b, miR-125, and let-7c.62 In a randomized, placebo-controlled, double-blind study consisting of 18 placebo and 17 metformin-treated T2D patients, plasma concentrations of miR-140-5p, miR-222, miR-142-3p, and miR-192 were significantly different in treated patients than those treated with placebo and paralleled improvements in fasting glucose and HbA1c.63 Systematic profiling of liver histone posttranslational modifications in a prediabetic high-fat-diet-induced obese (DIO) mouse model revealed 170 histone marks, 15 of which varied in abundance compared with liver from chow-fed control animals.64 Treatment of DIO mice with metformin reversed DIO-stimulated histone H3K36me2, suggesting that this mark may not only be associated with the development of T2D, but may also represent a mechanism by which metformin may exert physiological effects. Epigenetic modifications associated with other classes of antidiabetes drugs remain to be characterized. Only recently has the epigenetic regulation of PPARG, the receptor for thiazolidinediones, been studied,65 although such studies have been limited to the study of mechanisms related to cancer. For example, one study reported a dosedependent increase in cell killing in breast cancer cells treated with troglitazone and HDAC inhibitor; this finding was associated with increased H3 lysine 9 (H3K9) and H3K23 acetylation, H2AX and H3S10 phosphorylation, and H3K79 monomethylation and dimethylation.66 In another study miR-130a-3p was found to confer resistance to gemcitabine in patients with cholangiocarcinoma through direct modulation of PPARG expression.67 In addition, a single study provided evidence that DNA methylation regulated expression of the KATP channel subunit, which serves as a receptor for sulfonylureas, in transformed HL-1 cardiomyocytes.68
18.5 CONCLUSIONS: IMPLICATIONS FOR TREATMENT STRATEGIES AND PRECISION MEDICINE Advances in genomic technology and knowledge have led to a “golden age” in common disease genetics. Over 100 loci have shown statistically significant evidence for association with T2D and related traits.69 These discoveries have enormous potential to reveal new targets for drug development and provide a better understanding of the biology underlying existing drug targets to improve T2D pharmacotherapy. However, the majority of these loci are located in intronic or intergenic regions of the genome, suggesting transcriptional or other types of regulation may not only be important contributors to diabetes risk, but may also be important in response to pharmacotherapy or the advent of adverse events. Importantly, as seen in the field of pharmacogenetics, pharmacoepigenetics studies of diabetes and other common diseases face unique challenges. For example, very few drug trials have been designed to address the epigenetic aspects of drug response. Thus relying on archival samples from drug trials may not provide the optimal study design for genetic analysis. Similarly, epidemiologic studies may provide subsamples allowing for assessment of drug response or adverse effects, but many times such studies have not collected adequate information on drug use, dosage, and other critical information necessary to design a substudy. Funding of new drug trials to specifically address pharmacoepigenetics may also be challenging, and replication samples may be hard to identify. Finally, given the differences in methylation patterns, expression of miRNAs, and variability in histone marks among different ethnic groups, the effects discovered in one population may not apply to other populations. Even if new drug trials can be funded and designed, there are issues related to defining “response” to any specific drug. Decreased fasting glucose or HbA1C levels have been traditional metrics used to define drug response. However, glycemia is an output of many upstream events and multiple systems that regulate glycemia. Therefore, whether a specific drug had its intended effect at the target and whether that specific effect was appropriately translated to a change in fasting glycemia or HbA1c is of question. From a clinical perspective a lack of change in either metric could be considered a nonresponse. However, from a mechanistic perspective, if the drug had its intended effect, but as a result of physiologic regulation that effect did not translate into a change in clinical outcome, is that considered a lack of response? Such subtleties can provide important clues regarding diabetes therapies and the effect of epigenetic variation.
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In conclusion, the field of pharmacoepigenetics in T2D represents a novel area of investigation in diabetes research. Efforts to characterize variation in DNA methylation, ncRNA expression and function, as well as differential modifications of histones are critical for understanding the role of epigenetics in mediating interindividual variability in response to diabetes pharmacotherapies.
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