Mitochondrial DNA Mutations and Epigenetic Regulation in Type 2 Diabetes Mellitus Development

Abstract

The global prevalence of type 2 diabetes mellitus (T2DM) has increased significantly over the past decade and is projected to rise further. While genetic and lifestyle factors are well-established contributors to T2DM pathogenesis, mitochondria have also gained attention as the key players. Many studies suggested that mitochondrial DNA (mtDNA) mutations and epigenetic modifications were implicated in the development and progression of T2DM. This review aimed to provide a comprehensive analysis of mtDNA mutations and epigenetic modifications associated with T2DM. Based on data from 30 published studies, a total of 117 mtDNA mutations were identified to be associated with T2DM, with D-loop region being the mutation hotspot. However, it was reported that the majority of D-loop mutations were also more frequently observed in healthy populations compared to mutations in other mtDNA regions, suggesting their potential non-pathogenic characteristic. Thus, mtDNA mutations found to be associated with T2DM but with lower occurrence in healthy populations may play a more significant role in influencing T2DM susceptibility. Regarding epigenetic modifications, mtDNA methylation was commonly reported in the D-loop and ND6 regions across seven studies. These findings suggested that these regions may play critical roles in the regulation of mitochondrial gene expression under diabetic conditions. Lastly, this review also discussed the technical challenges and limitations of detecting mtDNA mutations and methylation changes. In addition, relevant ethical considerations surrounding mitochondrial genetic research were also addressed. In conclusion, mtDNA mutations and methylation changes could potentially serve as biomarkers for the development and progression of T2DM. These molecular modifications may offer valuable insights for early diagnosis and preventive strategies. However, further research and validation are essential to establish their clinical significance and diagnostic utility.

Introduction

Diabetes mellitus (DM) is recognised as one of the fastest expanding global health crises. In 2024, approximately 589 million adults aged between 20 and 79 were reported to have DM, which is estimated to increase to 853 million adults by 2050 [1]. Notably, around 90% of diabetes cases globally are attributed to type 2 diabetes mellitus (T2DM) [2, 3]. Adding to this concern, T2DM incidence among individuals aged 15 to 39 rose by 56% between 1990 and 2019, further emphasising the urgent need to address this disease [4].

DM is characterised by increased blood glucose levels, often due to impaired insulin secretion from the pancreas, insulin resistance (IR) in peripheral tissues, or both [2]. Insulin is an important hormone secreted by the pancreatic β-cells, which facilitates glucose uptake from bloodstream into cells for energy production or storage [1]. Additionally, it plays a key role in inhibiting hepatic gluconeogenesis [5]. Therefore, reduced insulin production or sensitivity can lead to increased blood glucose levels.

It has been proposed that both genetic and epigenetic factors may influence the development of T2DM [6]. Although genome-wide association studies have identified several common genetic mutations associated with glycaemic traits (e.g., fasting glucose, fasting insulin, insulin secretion and insulin sensitivity), these account for only about 10%–20% of the variance in these traits [7]. This suggests that factors other than nuclear DNA may also play a significant role in T2DM development. In this context, mitochondrial DNA (mtDNA) is thought to affect T2DM progression, in which mutations or epigenetic modifications in mtDNA may disrupt glucose homeostasis. Although studies have been conducted to determine mtDNA mutations related to T2DM, research on mtDNA epigenetic modifications remains limited and less well-documented.

Thus, this review summarises findings from 1994 to 2024 on the link between mtDNA mutations, epigenetic modifications, and T2DM, with most studies published within the past decade. The challenges and limitations to the profiling of mtDNA mutations and methylation have also been addressed. The discovery of mutations or epigenetic variations associated with T2DM susceptibility may enable earlier diagnosis or prevention. Additionally, mtDNA epigenetic profile may serve as a valuable indicator for assessing treatment efficacy or disease progression, contributing to a significant milestone in clinical advancement.

Mitochondrial DNA Mutations in the Development of T2DM

Mitochondria and Mitochondrial DNA

Mitochondria are frequently referred to as the “powerhouse of the cell” due to their essential role in adenosine triphosphate (ATP) synthesis through oxidative phosphorylation. They also play several crucial metabolic roles, such as intracellular calcium homeostasis, reactive oxygen species (ROS) production, synthesis of haem and iron-sulphur clusters [8–10]. Furthermore, they play a central role in regulating programmed cell death by responding to the pro- and anti-apoptotic signals to maintain tissue homeostasis [11].

Mitochondria are distinct from other cytoplasmic organelles as they contain their own DNA, which encodes essential RNAs and proteins [12]. Human mtDNA encodes only 37 genes due to the evolutionary loss or transfer of most mitochondrial genes to nuclear DNA [13]. Among these, 22 genes encode for tRNAs, 2 rRNAs (12S and 16S) and 13 are protein-coding genes (Figure 1) [13]. Unlike traditional Mendelian genetics, mtDNA is inherited maternally as a haploid molecule, allowing mutant mtDNA to accumulate and be passed from mother to offspring [15, 16].

FIGURE 1

Human mtDNA is a circular, polycistronic, double-stranded molecule made up of 16,569 base pairs (bp) and lacks introns (Figure 1) [17]. The nucleotide content of each strand differs, whereby the light strand (L-strand) is rich in cytosine, while the heavy strand (H-strand) is rich in guanine [17]. Next, mtDNA possesses a triple-stranded displacement loop structure known as displacement loop (D-loop), which is a non-coding region that acts as the promoter for both strands [18]. The D-loop regulates mtDNA replication, optimising the mtDNA copy numbers according to the cellular energy demands [19, 20].

Oxidative Stress and Mitochondrial Dysfunction

In mitochondria, ROS (e.g., superoxide radicals, hydrogen peroxide and hydroxyl radicals) are inevitably produced due to the continuous oxidative phosphorylation activity, accounting for approximately 90% of cellular ROS [21, 22]. Under normal circumstances, the cells possess defence mechanisms to counteract ROS generation [23]. For instance, the cells possess antioxidant enzymes that neutralise ROS, including superoxide dismutase, catalase, glutathione reductase, glutathione peroxidase, thioredoxin reductase, thioredoxin and peroxiredoxin [23, 24]. In addition to enzymatic antioxidants, mitochondria contain low molecular weight antioxidants (e.g., coenzyme Q) and repair mechanisms that help mitigate oxidative damage [23]. However, excessive ROS production can still be induced by stress factors, leading to excessive electrons being transferred to oxygen in the electron transport chain without ATP production [25].

Excessive ROS production has been implicated in causing oxidative damage to DNA, contributing to the development of various diseases [26]. It has been strongly associated with mitochondrial dysfunction, resulting in increased mutation rates, reduced mitochondrial biogenesis and accelerated aging [25, 27]. The ROS-induced mitochondrial dysfunction further suppresses ATP production while increasing ROS production, creating the ‘vicious cycle’ that ultimately leads to insulin resistance and onset of DM [25]. Additionally, excessive ROS disrupts the phosphorylation of insulin receptor substrate proteins by serine kinases, which is a critical initial step in the insulin signalling pathway [28].

In turn, insulin resistance or DM can further disrupt the mitochondrial metabolism, causing reduced insulin secretion from pancreatic β-cells, enhanced mitochondrial permeability transition, or increased mitochondrial apoptosis [29, 30]. Studies conducted on the relationship between mitochondrial mutations, mitochondrial dysfunctions and T2DM supported the involvement of mitochondria in T2DM development [31].

Mitochondrial DNA Mutations and T2DM

Mutation is a permanent and heritable alteration in DNA that often leads to changes in protein function [32]. It can also affect the structure and function of non-coding RNAs such as tRNA and rRNA [33]. Mutations may happen spontaneously or be induced by ROS. MtDNA is particularly susceptible to mutation due to its haploid nature and the close proximity to ROS production site, as aforementioned [21, 34]. Additionally, mtDNA lacks protective histones, leaving it more exposed to damage induced by ROS or other mutagens [21]. Moreover, unlike nuclear DNA, mtDNA lacks sufficient repair mechanisms to correct mutation and maintain normal mitochondrial function [35]. This susceptibility of mtDNA to mutation has led to the concept of a ‘vicious cycle’, in which initial ROS-induced mitochondrial dysfunction triggers further ROS production, subsequently exacerbating mitochondrial damage and dysfunction [21].

Recent studies have identified mtDNA mutations as potential contributors to the development of DM. Several mtDNA mutations associated with DM in various populations have been reported (Table 1). Beyond identifying mutations detected in diabetic individuals, it is equally important to determine whether these mutations also occur frequently in healthy individuals. Therefore, gnomAD 3.1 and Helix frequencies were included, which acted as the indicators of whether specific mutations are commonly found in healthy individuals, rather than exclusively in diabetic individuals [37–39]. In most cases, a mutation that appears at high frequency in healthy populations is likely a non-pathogenic polymorphism or mutation hotspot. Thus, the potentially significant mutations were highlighted in bold in Table 1, as they might be the more reliable indicators for different forms of DM.

It was observed that while a majority of the mutations listed were located in the D-loop region, their frequencies in healthy populations based on both databases, were relatively higher compared to mutations in other regions of the mitochondrial genome. This suggests that many of the D-loop mutations linked to T2DM may represent random, non-pathogenic variants, rather than disease-causing mutations. This interpretation is supported by the fact that D-loop, which plays a key role in regulating mtDNA replication and transcription, is the most variable region of the mitochondrial genome in both healthy and diseased individuals [41]. Nevertheless, it is possible that D-loop mutations may still disrupt mtDNA replication, leading to mtDNA depletion and subsequent mitochondrial dysfunction, contributing indirectly to disease pathology [70].

While D-loop mutations are frequently observed in healthy individuals and likely non-pathogenic, certain other mutations may demonstrate a stronger disease association. For instance, one commonly affected site that is rarely found in healthy population is the tRNA^Leu gene, where adenine is substituted with guanine at nucleotide position 3243 (m.A3243G) [71, 72]. This mutation is also referred to as the mitochondrial encephalopathy, lactic acidosis and stroke-like episodes (MELAS) mutation, as it was initially identified in individuals with these clinical manifestations in 1990 [73]. This mutation disrupts the proper folding of tRNA molecule by interfering with key hydrogen bonds between A14 and U8, resulting in increased structural openness, reduced stability and reduced aminoacylation [74, 75]. To compensate, the mutant tRNA may abnormally form dimers with other mutant tRNA molecules, which further reduces the aminoacylation rate [74]. As a result, amino acids may be incorrectly incorporated or entirely omitted during mitochondrial translation, producing defective mitochondrial proteins and ultimately impairing mitochondrial function.

In summary, beyond identifying mutations present in diabetic individuals, it is equally important to assess whether these mutations also occur frequently in healthy populations. This distinction may further refine the understanding of specific genetic factors underlying mitochondrial dysfunction in diabetes, thereby contributing to more efficient risk detection. In this context, oxidative stress represents one of the key factors driving mtDNA mutations due to elevated levels of ROS in mitochondria. Thus, addressing oxidative stress and its effect on mtDNA mutations may offer promising strategies for the prevention or management of mitochondrial dysfunction in T2DM.

Mitoepigenetics in the Development of T2DM

Epigenetics is the study of variations in gene expression that occur without DNA sequence alterations [76]. Key epigenetic mechanisms include DNA methylation, histone modifications and regulation of gene expression by non-coding RNAs (Figure 2) [79]. These mechanisms play important roles in regulating gene expression at the transcriptional, post-transcriptional and translational levels [80]. It is proposed that epigenetics not only occurs in nuclear DNA, but it also affects mtDNA, in which the phenomenon is known as “mitoepigenetics” [81]. The processes underlying mitoepigenetics have not been as thoroughly explored as those governing nuclear DNA, mainly due to the absence of histones in mitochondria [81, 82].

FIGURE 2

While some studies suggest that methylation is a distinct feature of nDNA and absent in mtDNA, others provide evidence supporting its presence in mtDNA [83–86]. Emerging studies have identified N⁶-methyldeoxyadenosine (6mA) as an alternative form of mtDNA methylation, mediated by methyltransferase 4 MTA70 (METTL4), alongside the more commonly studied 5-methylcytosine (5-mC) (Figure 3). Notably, the deletion of METTL4 has been shown to reduce 6mA levels in mtDNA [87]. However, studies have reported conflicting findings regarding the primary methylation sites in mtDNA, with evidence suggesting involvement of both CpG and non-CpG sites [92–95]. While the majority of studies suggest that methylation primarily occurs at CpG sites, Patil et.al. [93] reported that non-CpG sites are the main targets of methylation in mtDNA. Despite these conflicting findings, one consistent observation is that methylation occurs more frequently on the L-strand compared to the H-strand [93–96].

FIGURE 3

Several studies have suggested that mtDNA methylation serves as a protective mechanism against oxidative damage, which could potentially be induced by high blood glucose concentrations in patients with T2DM [97, 98]. The frequency and sites where mtDNA methylation have been detected in the progression of T2DM and related disorders are summarised in Table 2. An in vitro study showed that diabetic condition increased mtDNA methylation by 1.5- to 3-fold at various regions, including the D-loop, Cytb, ND6 and COXII [99]. Similar findings have also been reported by several in vivo studies. For instance, Kowluru (2020) found higher levels of D-loop methylation in the retinal microvasculature of T2DM rats [100]. Meanwhile, another study reported significant methylation at the ND1, ND2, ND6, CYTB and COX1 regions in diabetic mice [95]. The latter study also found significant higher methylation of ND6 in T2DM human subjects compared to healthy controls [95]. Notably, IR subjects displayed significant 4.6-fold increase in DNA methylation compared to insulin-sensitive subjects [103].

Limited clinical research has been conducted to characterise the mtDNA methylation profile in T2DM subjects. However, since T2DM is often associated with obesity or being overweight, studying the methylation profile in such individuals may provide valuable insights. For example, a clinical study reported that increased methylation at specific CpG sites in the D-loop was significantly (p = 0.003) associated with body mass index (BMI) percentiles >85th in female subjects [101]. Similar observations were made in an earlier mixed-gender study, in which a 5.2-fold increase in D-loop methylation was observed in obese subjects compared to lean subjects [103]. This was further supported by a subsequent study that revealed a drastic elevation of methylation levels at ND6 and D-loop regions as BMI increased [102].

Research has also demonstrated the common coexistence of non-alcoholic fatty liver disease (NAFLD) and T2DM. Specifically, NAFLD increases the risk of T2DM by 2- to 5-fold, with about 59.67% of T2DM patients also having NAFLD [104, 105]. This connection suggests that the methylation profile in individuals with NAFLD may be linked to T2DM. For instance, one study reported a significant positive association (p < 0.04) between the methylated-to-unmethylated ratio of mt-ND6 and the severity of NAFL, with methylation levels increasing from 20.6% in simple steatosis to 28.4% in non-alcoholic steatohepatitis [106].

In summary, increased mtDNA methylation is a response to various stress factors in disease states to protect mtDNA from damage and potential mutations. Several findings have indicated that mtDNA methylation profile contains relevant information about body composition and the associated risk of developing diseases such as T2DM. Given its roles in gene expression regulation, the potential of epigenetics in disease development or prevention warrants further research. Consequently, these epigenetic profiles might be a useful indicator for early molecular detection or prevention, as they are often detectable in the early stages of disease progression [107].

Limitations and Challenges in Sequencing Mitochondrial DNA Mutations and Mitochondrial Epigenetic Modifications

While research on mtDNA mutations and epigenetic modifications has advanced the understanding of mitochondrial regulation in T2DM, the accurate detection of these changes remains technically challenging. To date, hundreds of thousands of human mitogenomes have been sequenced using traditional Sanger methods, as well as a range of modern high-throughput sequencing platforms. Meanwhile, studies on the mitoepigenome remain limited but are getting increasing attentions with advancements in sequencing technologies. These sequencing technologies typically involve several steps including DNA isolation, library preparation and sequencing that uses various chemistries, flow-cells and detection systems utilizing base-specific color-coded fluorescence, light emissions, current, or ions changes. This is followed by bioinformatics analysis and each stage of the process presents unique challenges, making mtDNA sequencing particularly challenging.

Mitochondrial DNA Isolation and Purification

The initial step of isolating and enriching pure mtDNA relative to nuclear DNA remains challenging. Contamination with nuclear DNA, including mitochondrial pseudogenes in the lysate, can introduce artifacts during mtDNA analysis, particularly with short-read lengths [108]. Various conventional isolation techniques have been used, such as differential centrifugation, density gradient centrifugation, magnetic bead-based and mitochondrial isolation followed by DNA extraction [109–111]. Several commercial kits for direct mtDNA extraction are widely available. One study has also demonstrated a novel approach for mtDNA isolation and enrichment using a plasmid isolation kit, followed by additional purification with solid-phase reversible immobilisation on paramagnetic beads and limited polymerase chain reaction (PCR) amplification [112]. However, a very high cell number, typically ranging from 5 to 17 million cells is required from cell culture and patient samples to obtain sufficient mtDNA yield for sequencing, regardless of the method used [110, 112]. This requirement may be impractical for certain studies, particularly those involving clinical samples, which are often scarce.

Other options include DNA extraction followed by target enrichment of mtDNA by either long-range PCR amplification or complementary oligonucleotide probe hybridization. Targeted amplification may be suitable for direct sequencing but sequencing artefacts may be introduced during the DNA amplification, which may lead to false positive or negative results [113]. Moreover, mtDNA enrichment via PCR amplification is unsuitable for methylation sequencing, as PCR does not preserve methylation marks (such as 5-mC), compromising accurate quantification of mtDNA methylation [112, 114]. A mtDNA isolation method capable of providing high yield and enrichment with minimal or no amplification is ideal for downstream methylation sequencing and improvements are still needed in DNA extraction methods and protocols for investigation of epigenetic markers in an unbiased manner.

Sequencing Methods

Sequencing technologies are categorised into first-, second- and third-generation methods, with the latter two often referred as next-generation sequencing (NGS) [115]. The selection of an appropriate sequencing technology depends on the specific research question being asked. Different sequencing methods and platforms exhibit varying degrees of error rates, ranging from 0.1% to 5% as compared to the lower error rate of Sanger sequencing (0.001%) [113, 116–122]. Although these error rates might seem to be negligible, their cumulative effect can become significant given the vast size of the human nuclear genome [113].

Sanger sequencing (first-generation) is considered the gold standard due to its high accuracy despite its short-read limitations, but it is expensive compared to the newer technologies that have gained popularity, particularly for human whole genome sequencing [113]. These technologies have been increasingly integrated into clinical diagnostic practices, enabling a holistic analysis of genetic variants in targeted or complete genomes [123].

Besides characterizing genetic variants, it is worthwhile to study epigenetic changes, as epigenetic modifications can be influenced by external factors (e.g., lifestyle factors or intervention). If an individual is diagnosed with a particular genetic variant associated with a specific disease, epigenetic changes may be useful to control or switch off the expression of the specific gene through DNA methylation. By understanding both genetic variants and epigenetic changes in an individual or population, it is possible to offer a more targeted treatment which may potentially reduce the disease occurrence.

Bisulfite conversion with or without PCR amplification is generally used for methylation and mutation sequencing. In methylation sequencing, incomplete conversion of unmethylated cytosine to uracil followed by PCR amplification can lead to overestimation of methylation levels [124]. For mutation sequencing or other applications, biases may arise when short sequences or those with extreme GC content are preferentially or non-preferentially amplified [125]. Although reducing PCR cycles has been proposed as a strategy to minimise bias, research has shown limited improvement with an even lower correlation [125].

While methods such as bisulfite sequencing and methylated DNA immunoprecipitation (MeDIP) are commonly used to study epigenetic modifications, recent advances have enabled PCR-free sequencing approaches that bypass the need for bisulfite conversion. Platforms such as Illumina and Oxford Nanopore have been used for mtDNA sequencing, each offering distinct advantages and limitations (Table 3). Although PacBio technology has the potential to sequence full-length DNA without involving PCR amplification and bisulfite treatment, its application in detecting mtDNA methylation remains limited and underexplored in the current literature.

Data Analysis and Validation

After a successful sequencing run, the large volume of sequencing data requires extensive bioinformatics expertise for analysis to identify significant mutations or epigenetic changes. The computational analysis typically involves three essential steps: (1) Data processing and quality control to ensure accuracy, (2) Data visualisation and statistical analysis to identify patterns and trends, and (3) Validation and interpretation to confirm findings and assess their significance [136]. While minimising error rates remains a key objective for reliable results, ongoing optimisation is still required for different sequencing methods. Despite the availability of various analytical tools, a clear guideline for analysis settings and thresholds has yet to be established [136]. Different studies have adopted different approaches, often employing multiple software tools at different stages [137]. This lack of standardisation poses significant challenges in sequencing analysis. Additionally, comparing results across studies using different analysis methods can further complicate data interpretation.

Ethical Issues

Gene sequencing can reveal extensive genetic information, including adverse functional alleles of protein-coding genes and private individual variations that can be used to identify patients or their close relatives [138]. This raises ethical dilemmas regarding the disclosure of results to the individual or their relatives [139]. While increased awareness of potential hereditary conditions may promote healthier lifestyles, it can also lead to excessive anxiety or detrimental effect on individuals’ perspectives on their health and psychological wellbeing [140, 141].

In cases of maternally inherited mitochondrial diseases, caused by mtDNA mutations, several alternative strategies have been suggested to reduce or prevent the transmission of mtDNA from mother to child. These strategies include egg donation, prenatal testing, preimplantation genetic diagnosis and mitochondrial donation, all raising ethical concerns. Egg donation results in the child being genetically related to only one biological parent without the mitochondrial disease. Prenatal testing and preimplantation genetic diagnosis may risk the pregnancy and bring additional emotional burden on parents in deciding on whether to continue or prematurely terminate the pregnancy, if mitochondrial disease is detected [142]. Mitochondrial donation may be a more permissible approach as only the child’s mtDNA is replaced with mtDNA from a healthy donor while the nuclear DNA remain from both the biological parents [142]. However, concerns remain regarding the technical practicalities of complete faulty mtDNA replacement, as well as potential mismatches between the mtDNA haplotypes of the biological and donor mothers [142].

Conclusions

The increasing prevalence of T2DM in recent decades, along with its future projections and prevalence have raised global concerns. In response, numerous initiatives have been introduced worldwide to promote healthier lifestyles and lower the risk of T2DM. However, while lifestyle factors can have a significant impact on T2DM development, it is also essential to acknowledge the significant influence of inherited genetic factors. Although these genetic predispositions are difficult to alter, epigenetic mechanisms may offer a potential means to regulate harmful gene expression patterns that may contribute to the increased risk of developing T2DM.

This review highlights the emerging roles of mtDNA mutations and epigenetics in the pathogenesis of T2DM. Evidence suggests that alterations in mitochondrial gene expression and function may significantly impair metabolism, leading to T2DM. Given the interplay between inherited genetic predisposition and epigenetic regulation, future research should prioritise large-scale clinical trials to investigate these relationships and susceptibility to T2DM in diverse populations. By integrating genetic background and epigenetic modifications, a more advanced personalised treatment for T2DM could be developed to prevent the development and progression of T2DM.

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