The Role of Nuclear and Mitochondrial DNA in Myalgic Encephalomyelitis: Molecular Insights into Susceptibility and Dysfunction

Abstract

Myalgic Encephalomyelitis (ME), also known as chronic fatigue syndrome (CFS), is a debilitating and heterogeneous disorder marked by persistent fatigue, post-exertional malaise, cognitive impairment, and multisystem dysfunction. Despite its prevalence and impact, the molecular mechanisms underlying ME remain poorly understood. This review synthesizes current evidence on the role of DNA, both nuclear and mitochondrial, in the susceptibility and pathophysiology of ME. We examined genetic predispositions, including familial clustering and candidate gene associations, and highlighted emerging insights from genome-wide and multi-omics studies. Mitochondrial DNA variants and oxidative stress-related damage are discussed in relation to impaired bioenergetics and symptom severity. Epigenetic modifications, particularly DNA methylation dynamics and transposable element activation, are explored as mediators of gene–environment interactions and immune dysregulation. Finally, we explored the translational potential of DNA-based biomarkers and therapeutic targets, emphasizing the need for integrative molecular approaches to advance diagnosis and treatment. Understanding the DNA-associated mechanisms in ME offers a promising path toward precision medicine in post-viral chronic diseases.

1. Introduction

Myalgic encephalomyelitis (ME) is a chronic, multisystem disorder marked by profound fatigue, cognitive dysfunction, sleep disturbances, autonomic dysregulation, and widespread pain [1,2,3]. The defining clinical feature of ME is post-exertional malaise (PEM), a prolonged exacerbation of symptoms following minimal physical or mental exertion [4,5]. PEM is now recognized as a core diagnostic criterion across contemporary case definitions and clinical guidelines [6].

ME affects an estimated 0.4–2.5% of the global population [7], with a pronounced female predominance (3:1 ratio) [8,9]. Despite its prevalence, up to 91% of cases may remain undiagnosed due to clinical heterogeneity, the absence of validated biomarkers, and historical inconsistencies in diagnostic criteria [10,11,12]. The lack of a definitive diagnostic test continues to hinder early recognition and intervention [13,14,15,16].

The precise etiology of ME remains elusive. It is widely recognized as a multifactorial disorder, often triggered by viral infections [17]. The frequent observation that an acute event precedes chronic illness highlights a critical interplay between environmental factors and host biology [18]. The substantial symptomatic overlap and shared underlying biological disruptions observed between ME and Long COVID further emphasize the urgency and relevance of ME research [19]. Over 95% of symptoms are shared between Long COVID and ME, with a significant proportion of Long COVID patients meeting the diagnostic criteria for ME, with one study reporting that 58% long COVID qualified under the Canadian Consensus Criteria (CCC) [19,20]. This extensive clinical and pathophysiological overlap includes elevated oxidative stress and common epigenetic signatures. Core symptoms shared by both conditions include fatigue, PEM, cognitive impairment, sleep disturbances, and orthostatic intolerance. In contrast, anosmia, dysgeusia, rash, and hair loss are more frequently observed in Long COVID, whereas painful lymph nodes, chemical sensitivities, and tinnitus are more characteristic of ME [19]. Understanding the molecular underpinnings of ME is therefore crucial for developing effective diagnostic tools and therapeutic strategies.

Research into DNA in ME has progressed from candidate gene studies to twin and epigenetic research, and more recently to large-scale multi-omics projects revealing links with Long COVID. This review synthesizes the latest peer-reviewed evidence on the role of DNA in ME susceptibility and dysfunction. We explore how nuclear and mitochondrial DNA influence disease risk, symptom manifestation, and cellular dysregulation, with particular focus on genetic variants, mitochondrial bioenergetics, epigenetic modifications, and transposable element activation. By integrating these findings, we aim to clarify the molecular underpinnings of ME and identify promising avenues for biomarker development and therapeutic intervention.

2. Genetic Predispositions and Susceptibility

2.1. Familial Clustering and Heritability

Evidence supports a genetic component and heritability in ME. Familial clustering, indicating an elevated risk among relatives of affected individuals compared to the general population, has been consistently reported across multiple studies (Table 1) [17,21,22,23]. A population study, for instance, found a notable excess of relatedness among ME cases, observed in both close and more distant family relationships. This research also highlighted a consistently elevated relative risk for ME across first, second, and third-degree relatives [21,23]. To further discern the contributions of genetic versus environmental factors to familial aggregation in ME, investigators have used classic twin methodology. Three independent twin studies provide empirical data in this regard. In one study of 124 twin pairs (79 monozygotic [MZ], 45 dizygotic [DZ]), the cross-twin correlation for prolonged fatigue was substantially higher in MZ twins (r = 0.49) than in DZ twins (r = 0.16), indicating strong genetic influence on familial aggregation of fatigue. Interestingly, while immune activation markers were more strongly shaped by shared environmental factors, fatigue itself showed a major genetic component [24]. A larger study of 1004 adult twin pairs (533 MZ, 471 DZ, all >50 years) similarly found higher concordance for fatigue in MZ twins compared to DZ twins. Multivariate modeling revealed that a common genetic factor contributed to fatigue alongside distress, anxiety, and depression, but also that fatigue was influenced by an additional independent genetic factor, distinct from psychiatric traits. Notably, 44% of the genetic variance for fatigue was unique and not shared with other forms of psychological distress [25]. A third study of 146 female–female twin pairs, in which at least one twin reported ≥6 months of fatigue, found higher concordance rates for fatigue in MZ than in DZ twins across increasingly stringent diagnostic definitions. For idiopathic chronic fatigue (aligned with ME case criteria), concordance was 55% in MZ twins vs. 19% in DZ twins (p = 0.042), with heritability estimated at 51% (95% CI 7–96%) [26]. Together, these studies provide consistent experimental evidence for a heritable contribution to ME susceptibility, particularly when case definitions are more stringent. While shared environmental factors such as infections or stress are also relevant, the magnitude of the twin data indicates that genetic factors play an essential role in disease risk.

Table 1. Summary of Studies on Familial Clustering and Heritability in Myalgic Encephalomyelitis.

Study	Year	Sample Size (Cases, Controls)	Methods Applied	Main Findings	Cohort/Other Relevant Information
Albright et al. [21]	2011	~1.6 million (population registry)	Genealogical database analysis	Significant familial clustering up to 3rd degree relatives	Utah population, large genealogical study
Dibble et al. [22]	2020	Review of multiple studies	Systematic review	Familial clustering reported	Diverse populations, different diagnostic criteria
Crawley et al. [23]	2021	Pediatric patients and relatives	Population epidemiology and registries	High familial risk ratio, strong familial aggregation	Pediatric cohort, national registries
Arron et al. [17]	2024	Meta-analysis & review	Comprehensive review	Confirms genetic effect with heritability estimates	US health insurance claims, UK Biobank data

2.2. Candidate Gene Studies

Initial investigations into the genetic basis of ME focused on candidate gene studies, examining specific gene variants or single-nucleotide polymorphisms (SNPs) that are thought to be involved in relevant biological pathways. Genes implicated in immune function, such as human leukocyte antigen (HLA) genes, have been frequently investigated due to the prominent immune dysregulation observed in ME, including associations with specific HLA class II alleles [26]. Other studies have explored neurological pathways, identifying potential associations with genes like GRIK2 (a glutamate ionotropic receptor kainate type subunit 2, involved in excitatory neurotransmission and potentially contributing to neurological symptoms) and NPAS2 (neuronal PAS domain protein 2, a circadian rhythm gene whose variants might impact sleep disturbances and fatigue) [27]. Metabolic processes have also been a focus, with genes like CYP2D6 (a cytochrome P450 enzyme involved in drug and toxin metabolism, potentially affecting detoxification capacity) [28] and MTHFR (methylenetetrahydrofolate reductase, crucial for folate metabolism and methylation pathways) being examined [29,30]. However, these early studies were often limited by small sample sizes and inconsistent findings, highlighting the need for more robust genomic approaches.

2.3. Genome-Wide Association Studies (GWAS) and Advanced Genomic Approaches

The advent of genome-wide association studies (GWAS) has revolutionized the search for genetic associations by systematically scanning the entire genome for common variants linked to disease [31]. A recent study, the DecodeME project, recruited over 17,000 individuals with ME in its initial launch phase and provided important insights into disease heterogeneity [32]. Analysis of detailed questionnaire data revealed a clear female predominance (83.5% of participants), with females also reporting more comorbidities than males. Greater illness severity was significantly associated with female sex, older age, and illness duration beyond 10 years. Stratification by onset type further highlighted clinical subgroups, including cases following infectious mononucleosis, COVID-19, other infections, non-infectious onset, or onset of unknown infectious status, with the latter notably associated with comorbid fibromyalgia. These findings demonstrate how large-scale, population-based cohorts can identify phenotype–severity relationships that were not previously evident. Complementing this, Das et al. applied GWAS and a combinatorial analytics approach to UK Biobank-derived ME cohorts, identifying 199 SNPs across 14 genes, which stratified into 15 genetic clusters [33]. Many of these genes were linked to mitochondrial dysfunction, immune dysregulation, sleep disturbance, and autoimmunity, with replication across post-viral fatigue and fibromyalgia cohorts. In parallel, novel computational approaches have advanced genomic discovery. Zhang et al. employed whole-genome sequencing combined with the HEAL2 deep learning framework, identifying 115 candidate ME risk genes with intolerance to loss-of-function mutations [34]. Functional analyses implicated central nervous system and immune cell pathways, particularly cytotoxic CD4 T cells, with reduced expression of risk genes in patient-derived multi-omics data. This study supports the notion that both rare variants and gene expression changes contribute to disease risk, complementing common-variant GWAS results. Together, these advances demonstrate that both common and rare variants contribute to ME susceptibility, with converging evidence for roles of immune dysregulation, infection response, mitochondrial function, and neurological pathways.

2.4. Structural Variants and Genotype–Phenotype Correlations

Recent work by Moezzi et al. has highlighted the importance of structural variants in ME genetics, particularly their role in genotype–phenotype correlations underlying symptom heterogeneity [35]. Using high-resolution genomic mapping coupled with detailed clinical phenotyping, the study found that the distribution of haptoglobin (HP) genotypes, most notably Hp2-1, was correlated with more severe PEM and cognitive dysfunction. These findings provide a molecular explanation for some of the clinical variability seen in ME and support genotype-informed stratification as a strategy for biomarker discovery and therapeutic development. Incorporating structural variant analysis represents a pivotal step toward precision phenotyping, complementing SNP-based approaches and offering deeper insight into the genomic architecture driving PEM, cognitive impairment, and other hallmark symptoms.

2.5. Genetic Overlap with Other Conditions

ME and Long COVID exhibit significant overlap not only clinically but also genetically, suggesting shared pathological pathways with important implications for understanding chronic post-viral syndromes and developing therapeutic approaches. Recent genomic investigations have begun to reveal prominent parallels between ME and Long COVID, particularly in individuals with fatigue-dominant phenotypes. A large combinatorial analysis of genetic data from Sano Genetics’ Long COVID GOLD cohort identified 73 genes significantly associated with Long COVID, with notable enrichment in neurological and cardiometabolic pathways. Significantly, 39 SNPs linked to Long COVID were also found in a previous combinatorial genomic analysis of ME patients from the UK Biobank, implicating nine shared genes between the two conditions. Among these, several were involved in circadian rhythm regulation and insulin signaling, pathways long suspected to contribute to ME pathophysiology. Fatigue-dominant Long COVID cases also showed enrichment of metabolic and immune-related pathways, including MAPK/JNK signaling, further aligning with known molecular features of ME [36]. These findings support a shared genetic and mechanistic foundation between the two conditions, consistent with their overlapping symptom profiles and suspected post-viral triggers. Notably, a subset of the identified genes represents tractable drug targets, with compounds such as TLR4 antagonists emerging as potential candidates for therapeutic repurposing in both Long COVID and ME [36]. These insights not only reinforce the biological continuity between these syndromes but also open new avenues for biomarker discovery and targeted treatment strategies.

At the molecular level, gene expression and pathway analyses reveal immune dysregulation as a core feature common to ME and Long COVID. Both conditions show altered expression in genes regulating cytokine signaling, macrophage activation, antigen presentation, and immune exhaustion markers [37]. Furthermore, these shared genetic and immunological signatures underscore the role of impaired viral clearance and an exaggerated inflammatory response as possible mechanisms predisposing individuals to develop chronic illness after viral infections, whether from SARS-CoV-2 in Long COVID or other triggers in ME. This genetic commonality also aligns with clinical overlaps such as PEM, fatigue, cognitive impairments, and autonomic dysfunction, reinforcing that both illnesses belong to a broader family of post-viral chronic syndromes with overlapping etiologies and pathophysiology [38] (Figure 1).

Figure 1. A Timeline of Key Genomic and Epigenetic Research in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. This timeline illustrates the evolving research into the genetic and epigenetic underpinnings of ME. In the early 2000s, studies primarily focused on candidate gene, examining specific gene variants thought to play a role in the disease [26,27,28,29,30]. The 2010s marked a shift toward broader approaches, with twin studies providing strong evidence for heritability [24,25,26] and the start of initial epigenetic research exploring how environmental factors influence gene expression without altering DNA sequence [39]. In the 2020s, the field entered a new phase with the launch of large-scale projects, such as the DecodeME project [31,32], and the rise of multi-omics approaches that analyze multiple biological layers to understand ME complexity [31,40]. This period also saw significant discoveries regarding the genetic overlap with Long COVID, highlighting shared molecular pathways between the two conditions [36,37,38]. Figure created in BioRender Wesam Elremaly. (2025) https://BioRender.com/ (accessed on 7 September 2025). (SG28PQS95K).

3. Mitochondrial DNA (mtDNA) Dysfunction

3.1. Mitochondria as Energy Hubs

Mitochondria are often referred to as the powerhouses of the cell, playing a critical role in cellular energy production through the synthesis of adenosine triphosphate (ATP) via oxidative phosphorylation. This complex process occurs on the inner mitochondrial membrane, converting nutrients into usable cellular energy [41,42]. Given that profound fatigue and PEM are hallmark symptoms of ME, the relevance of mitochondrial dysfunction to the disorder is highly significant [43,44]. Impaired mitochondrial function could directly explain the energy deficit experienced by patients, leading to reduced capacity for physical and cognitive exertion and prolonged recovery times after even minimal activity [45] (Figure 2). Recent studies have emphasized that mitochondrial dysfunction in ME is not limited to energy metabolism but also involves dysregulated redox signaling, calcium homeostasis, and mitochondrial–nuclear communication. These disruptions impair cellular adaptation to stress and contribute to immune dysregulation and neuroinflammation [46,47]. Notably, recent mechanistic hypotheses also implicate dysregulation of mitochondrial dynamics (the balance between fusion and fission), which is essential for quality control. For example, in experimental settings, specific viral proteins such as herpesvirus dUTPases have been shown to induce hyperfusion and clumping of mitochondria [48]. These hyperfused mitochondria resist degradation and recycling via mitophagy, thereby disrupting overall mitochondrial turnover and energy homeostasis, which could directly contribute to the observed structural damage and functional deficits in ME [48]. This process of mitochondrial fusion is crucial as it facilitates the exchange and complementation of mitochondrial contents, including mtDNA and other factors essential for maintaining respiratory function, further emphasizing the link between disrupted dynamics and energy deficits in ME [49].

3.2. Evidence of Mitochondrial Abnormalities in ME

Numerous studies have investigated mitochondrial function in ME patients, reporting various abnormalities across different tissues and cell types [50,51,52,53,54,55,56,57,58]. These investigations have found evidence of reduced ATP synthesis rates, compromised oxidative phosphorylation (OXPHOS) as measured by oxygen consumption rates, and inefficiencies in specific OXPHOS complexes (e.g., Complex I, IV) [43,51,54]. Additionally, electron microscopy studies have revealed altered mitochondrial morphology in ME patients, with swollen or fragmented mitochondria observed in skeletal muscle fibers (subsarcolemmal and intermyofibrillar compartments) [56] and in stimulated peripheral blood mononuclear cells (particularly T cells) [57], suggesting structural damage. Changes in the expression of genes involved in mitochondrial biogenesis have also been reported [58,59,60]. A 2023 study by Wang et al. identified WASF3 as a key regulator of mitochondrial respiration and exercise intolerance in ME, based on analyses of skeletal muscle cells from patient biopsies. Overexpression of WASF3 disrupted respiratory supercomplex formation and reduced complex IV activity, whereas WASF3 knockdown in patient-derived muscle cells restored mitochondrial membrane potential and improved ATP output. These findings were further validated in transgenic mice, linking cytoskeletal signaling to mitochondrial inefficiency and highlighting WASF3 as a potential therapeutic target [59]. Glass et al. used extracellular vesicle proteomics to show post-exercise dysregulation of energy metabolism and ER stress responses in ME males, reinforcing mitochondrial involvement in PEM. Their data revealed persistent upregulation of unfolded protein response markers and mitochondrial chaperones following exertion [60]. Despite methodological variability (e.g., diagnostic criteria, differences in sample collection and processing techniques) and patient heterogeneity, a consensus supports mitochondrial impairment in ME, particularly under exertional stress.

Figure 2. Mitochondrial Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME). This figure illustrates reported key differences in energy metabolism between a healthy mitochondrion and an ME mitochondrion, highlighting the proposed mechanisms contributing to the profound fatigue and post-exertional malaise (PEM) characteristic of the illness. Left Panel: Healthy Mitochondrion. Glucose is metabolized to pyruvate, which is then converted to acetyl-CoA to enter the Tricarboxylic Acid (TCA) cycle. The electron transport chain (Complexes I, II, III, IV, and Cytochrome C) efficiently drives oxidative phosphorylation, leading to robust ATP synthesis [52,61]. The Translocator Protein (TSPO, also known as ADP/ATP translocase or ANT) typically functions to facilitate the import of ADP into the mitochondrial matrix for ATP synthesis and the export of newly synthesized ATP to the cytosol for cellular energy utilization [62]. Right Panel: ME Mitochondrion. In contrast, ME mitochondria exhibit reported dysfunction. Glucose metabolism is often shunted towards anaerobic glycolysis, leading to increased lactate production even with minimal exertion [51,52]. ATP synthesis is markedly reduced, contributing to cellular energy deficits [53,54]. A major factor in this dysfunction is the proposed partial blocking of Translocator Protein (TSPO) sites, which impairs both ADP import and ATP export [62]. Additionally, ME is characterized by elevated oxidative stress, leading to an increased production of Reactive Oxygen Species (ROS), which can damage mitochondrial components and further impair function [45,63]. Deficiencies in essential cofactors like intracellular magnesium [64] and Coenzyme Q10 (CoQ10) [65] are also observed, further compromising ATP production. These combined metabolic impairments contribute to the inability of ME patients’ cells to meet energy demands, particularly under exertional stress, providing a mechanistic explanation for hallmark symptoms such as fatigue and PEM. Figure created in BioRender Wesam Elremaly. (2025) https://BioRender.com/ (accessed on 7 September 2025). (WU28PQTCCB).

3.3. mtDNA Variants and Haplogroups

Mitochondrial DNA (mtDNA) is a small, circular genome (approximately 16.6 kb) inherited maternally and plays a crucial role in mitochondrial protein synthesis, encoding 13 proteins essential for oxidative phosphorylation, 2 ribosomal RNAs, and 22 transfer RNAs [66,67]. Investigations have explored the role of mtDNA SNPs and haplogroups (groups of mtDNA variants that tend to be inherited together, such as J, U, H, K, T, and I) in ME cohorts. While no direct causal mtDNA mutations have been consistently identified as the primary cause of ME across all patients, specific haplogroups or SNPs have been associated with particular symptom constellations or disease severity [68,69]. For instance, certain mtDNA haplogroups have been linked to differences in mitochondrial efficiency or susceptibility to oxidative stress, which could modulate mitochondrial function and disease manifestation in a patient-specific manner [68]. Some studies have suggested that haplogroup J might be associated with increased susceptibility to certain neurological symptoms due to its impact on mitochondrial efficiency [68]. Similarly, haplogroups U and H have been correlated with inflammatory and gastrointestinal symptom clusters, respectively (Table 2), suggesting that mtDNA background may influence symptom expression rather than directly causing disease onset [68].

Table 2. Candidate Genes Investigated in ME.

Gene/Pathway	Proposed Role/Function	Potential Relevance to ME Symptoms
HLA [26]	Immune system regulation, antigen presentation	Immune dysregulation, chronic inflammation
GRIK2 [27]	Glutamate signaling, neuronal excitability	Cognitive dysfunction, neurological symptoms
NPAS2 [27]	Circadian rhythm regulation	Sleep disturbances, fatigue
CYP2D6 [28]	Drug and toxin metabolism	Impaired detoxification, chemical sensitivities
MTHFR [29,30]	Folate metabolism, methylation	Metabolic dysfunction, epigenetic changes

Recent work by Tang-Siegel et al. identified two mtDNA missense mutations (ChrMT:8981A > G and ChrMT:6268C > T) in a patient with EBV-triggered ME, suggesting a role for viral–mitochondrial interactions in disease onset. These mutations affected ND4 and COX1 subunits, impairing electron transport and increasing ROS production [67]. Moreover, analysis of mtDNA heteroplasmy, where multiple mtDNA variants coexist within the same individual, revealed low levels across ME and control groups, indicating that heteroplasmy itself may not be a distinguishing factor in disease status. However, eight specific SNPs were found to be significantly associated with symptom severity, including fatigue, cognitive dysfunction, and PEM [68]. These findings support the hypothesis that mitochondrial dysfunction in ME may arise from subtle, cumulative effects of mildly deleterious mtDNA variants rather than overt pathogenic mutations. Interestingly, population-level studies have shown that ME patients may have a lower prevalence of mildly deleterious mtDNA variants compared to controls, suggesting a complex relationship between mitochondrial genome variation and disease pathophysiology [69]. This paradoxical finding raises the possibility that certain mtDNA backgrounds may confer resilience or vulnerability depending on environmental or nuclear genomic context. Taken together, these insights underscore the importance of considering mitochondrial genomic variation in ME research, not as a singular cause but as a potential modifier of disease trajectory and symptom burden.

While mitochondrial dysfunction is increasingly recognized as a contributor to ME pathophysiology, recent clinical reports underscore the importance of distinguishing primary mitochondrial disorders (MIDs) from ME itself, particularly when mtDNA variants are involved. A case study published by Finsterer et al. described a 52-year-old woman misdiagnosed with ME for over two decades, who was later found to carry a large mtDNA deletion (m.8753_16566) with <10% heteroplasmy in skeletal muscle [70]. This deletion encompassed the entire ATP6 gene and resulted in isolated complex-V dysfunction, an abnormality previously observed in ME lymphocytes [53].

3.4. Oxidative Stress and mtDNA Damage

A consistent finding in ME research is the evidence of increased oxidative stress markers in patients [63,71]. Oxidative stress occurs when there is an imbalance between the production of reactive oxygen species (ROS) and the body’s ability to detoxify them, leading to cellular damage [72]. In ME, elevated levels of malondialdehyde (MDA), protein carbonyls, and reduced glutathione (GSH) have been reported, indicating increased lipid peroxidation and protein oxidation, and diminished antioxidant capacity [63,73,74]. Additional biomarkers confirming this systemic stress include increased levels of plasma peroxides, oxidized LDL, and homocysteine, along with lowered levels of antioxidants like vitamin C, vitamin E, and alpha-tocopherol. The concentration of these damaged molecules often correlates positively with the severity of symptoms experienced by patients [17]. Evidence of direct oxidative damage to DNA is also seen in elevated levels of 8-hydroxy-deoxyguanosine (8-OHdG) in urine. The link between oxidative stress and damage to mtDNA is particularly concerning, as mtDNA is more susceptible to oxidative damage than nuclear DNA due to its proximity to sites of ROS production within the mitochondria, its lack of protective histones, and its less robust repair mechanisms [75].

A 2025 study by Shankar et al. confirmed oxidative stress as a shared molecular hallmark of ME and Long COVID [71]. By directly measuring intracellular redox states and reconstructing metabolic pathways, they showed that both conditions are characterized by elevated oxidative stress in lymphocytes, with downstream effects on mitochondrial function. Similarly, Van Campenhout et al. (2025) linked oxidative stress in ME to immune senescence and mitochondrial exhaustion [76]. Their findings demonstrated that ROS-induced mtDNA damage activates innate immunity, fueling chronic inflammation. This, in turn, impairs mitochondrial respiration, increases ROS generation, and overwhelms antioxidant defenses, creating a self-reinforcing cycle of energy deficit, inflammation, and cellular dysfunction that underpins ME pathology [77].

3.5. Mitochondrial Epigenetics

Recent reviews have highlighted the emerging field of mitoepigenetics—epigenetic regulation within mitochondria via DNA methylation, hydroxymethylation, and non-coding RNAs. These modifications influence mtDNA transcription, replication, and repair, and are responsive to environmental stressors. Cavalcante et al. (2020) and Kumar et al. (2024) describe how mitochondrial epigenetic signatures influence OXPHOS gene expression and interact with nuclear epigenetic landscapes, affecting immune and metabolic regulation in ME [78,79]. Notably, altered methylation of D-loop regions and mitochondrial tRNA genes has been linked to reduced respiratory efficiency and increased oxidative stress [80]. This bidirectional crosstalk between mitochondria and the nucleus, termed “retrograde signaling” may explain how mitochondrial dysfunction drives systemic symptoms in ME, including neurocognitive impairment and immune dysregulation.

4. Epigenetic Modifications

Epigenetics encompasses heritable and reversible changes in gene expression that do not alter the underlying DNA sequence [81] (Table 3). These modifications, primarily DNA methylation, histone alterations, and non-coding RNA regulation, serve as a dynamic interface between genetic predisposition and environmental influences such as infections, toxins, and stress [82,83,84,85,86]. In ME, epigenetic dysregulation is increasingly recognized as a key contributor to immune dysfunction, metabolic imbalance, and symptom variability [87,88,89] (Table 4).

Table 3. Common mtDNA Haplogroups and Potential Associations.

Haplogroup	General Characteristics (Europe)	Potential Relevance to ME (Hypothesized)
H	Most common, generally robust	Potentially protective
J	Associated with higher OXPHOS efficiency, but also increased ROS production	May influence neurological symptoms and oxidative stress susceptibility
U	Diverse, some sub-haplogroups are linked to specific diseases	Varied impact on energy metabolism and disease risk
K	Sub-haplogroup of U, often linked to longevity	Could influence metabolic resilience or vulnerability
T	Relatively common	Less clear direct associations, but part of the overall genetic background

Table 4. Key Epigenetic Mechanisms and Their Relevance to ME.

Epigenetic Mechanism	Description	Potential Impact in ME	Representative Studies
DNA Methylation	Addition of a methyl group to cytosine (CpG sites), often altering transcription factor binding	Altered methylation in immune-related genes (e.g., T-cell activation), metabolic pathways, and neuroendocrine regulation	[39,87,90]
Histone Modification	Acetylation, methylation, and phosphorylation of histone proteins	Regulates chromatin accessibility; changes linked to inflammation and impaired energy metabolism	[84,88]
MicroRNAs (miRNAs)	Small ncRNAs that post-transcriptionally regulate target mRNAs	Circulating miRNAs (e.g., miR-140-5p, and miR-127-3p) associated with PEM, autonomic dysfunction, and immune dysregulation	[89,91,92]
Long Non-coding RNAs (lncRNAs)	Longer ncRNAs modulating chromatin structure and transcription	Suggested roles in chronic inflammation, altered neuronal signaling and oxidative stress	[93,94,95]
Extracellular Vesicle (EV)-mediated Epigenetic Regulation	Transfer of miRNAs and other epigenetic regulators via EVs	EV miRNAs modulate neuroimmune pathways	[96,97,98]

4.1. DNA Methylation in ME

Multiple studies have identified differentially methylated CpG sites in ME patients (Figure 3), particularly in peripheral blood mononuclear cells (PBMCs), which reflect systemic immune and metabolic states [99,100]. These changes affect genes involved in cytokine signaling, T-cell activation, NK cell function, and mitochondrial regulation [87,99]. Both hypo- and hypermethylation patterns are observed. Hypomethylation may lead to overexpression of inflammatory genes, such as those in interferon pathways [84,99], while hypermethylation can silence metabolic enzymes and immune regulators, impairing cellular function [84]. Notably, methylation changes tend to cluster within immune-related gene networks, suggesting coordinated dysregulation [87,90,100](Figure 3).

Recent comparative studies have shown overlapping methylation profiles between ME and Long COVID, reinforcing the hypothesis of shared post-viral epigenetic mechanisms [100]. Moreover, methylation signatures correlate with clinical features like fatigue severity and PEM, highlighting their potential as biomarkers [101,102]. A 2025 study by Peppercorn et al. identified distinct methylation patterns in ME versus Long COVID patients, with ME-specific hypermethylation in mitochondrial biogenesis genes and hypomethylation in interferon-stimulated genes [103]. Preliminary data also suggest that methylation differences may be correlated with clinical features such as fatigue severity, cognitive dysfunction, or PEM, highlighting their potential as biomarkers for disease stratification and prognosis [101]. Longitudinal studies are still needed to clarify whether these methylation changes are causal, compensatory, or secondary to chronic illness.

Figure 3. The Role of DNA Methylation in ME Pathophysiology. This figure illustrates how epigenetic modifications, specifically DNA methylation, can influence gene expression and contribute to the pathophysiology of ME. In a healthy state (top panel), environmental factors such as infections, stress, and toxins can interact with the host genome. The methylation levels on gene promoters are balanced, allowing for normal gene expression [104]. However, in ME (bottom panels), these environmental exposures can trigger aberrant methylation patterns. Hypermethylation (left panel), characterized by an increased density of methyl groups on a gene’s promoter, can suppress gene expression. Conversely, hypomethylation (right panel), a reduction in promoter methylation, can lead to increased gene expression [87]. These dynamic and widespread changes in gene methylation in ME patients are implicated in pathways related to immune dysregulation and metabolomic impairment, directly contributing to the clinical manifestations of the disease. Figure created in BioRender Wesam Elremaly. (2025) https://BioRender.com/ (accessed on 7 September 2025). (OS28PQTKWR).

4.2. Dynamic Epigenetic Changes and Relapses

Emerging research reveals that DNA methylation in ME is dynamic rather than static, fluctuating with symptom severity (e.g., good days vs. bad days). Longitudinal studies using reduced representation bisulfite sequencing (RRBS) have shown that ME patients exhibit 10–20 times greater methylome variability than healthy controls during relapse–recovery cycles [105]. These changes affect regulatory regions linked to immune, metabolic, and neurological pathways. Intra-individual variably methylated fragments (iVMFs) tend to normalize upon recovery, suggesting a reversible epigenetic mechanism tied to symptom dynamics [105,106]. These findings validate the notion that epigenetic flexibility underlies the heterogeneous and fluctuating nature of ME, offering promising biomarkers for predicting relapses and mechanistic targets to stabilize the disease course.

4.3. Transposable Element Activation

A compelling hypothesis linking epigenetic dysregulation to ME pathology involves the transcriptional activation of endogenous dormant transposons, or transposable elements (TEs). These repetitive DNA sequences include long interspersed nuclear elements (LINEs, such as LINE-1), short interspersed nuclear elements (SINEs, such as Alu elements), and endogenous retroviruses (ERVs). Under normal conditions, TEs are tightly silenced by DNA methylation and repressive histone modifications, preserving genomic stability and preventing aberrant gene expression [107,108]. However, when epigenetic silencing is compromised due to factors like chronic viral infections, oxidative stress, or persistent inflammation, TEs can become transcriptionally active. This phenomenon is particularly relevant in ME, where patients commonly exhibit epigenetic instability, latent herpesvirus reactivations (such as Epstein–Barr virus, HHV-6, and cytomegalovirus), and chronic inflammation. Derepressed TEs may produce double-stranded RNA (dsRNA) or viral-like proteins, which are detected by innate immune receptors including RIG-I, MDA5, and TLR3, triggering antiviral immune responses. This “viral mimicry” state, noted also in autoimmune and neurodegenerative diseases, may contribute to chronic immune activation, interferon pathway upregulation, and systemic inflammation in ME. Preliminary transcriptomic analyses have identified upregulation of endogenous retroviral elements, particularly human endogenous retrovirus (HERV) families, in PBMCs of ME patients, coinciding with disrupted DNA methylation at TE regulatory regions [94,109]. Similar patterns of TE activation are reported in related conditions such as Long COVID, where HERV-W env transcripts associate with immune dysregulation and fatigue-like symptoms. Importantly, this activation is also supported at the protein level, as the toxic human endogenous retrovirus W (HERV-W) ENV protein has been found actively expressed (antigenemia) in post-COVID-19 condition patients long after infection and in pre-pandemic cases of ME and Fibromyalgia [110,111]. Therefore, TE activation offers a plausible mechanistic link connecting epigenetic instability, viral reactivation, and persistent immune activation in ME. Validating this mechanism could position TEs as biomarkers for disease activity and targets for therapeutic intervention, including reverse transcriptase inhibitors and epigenetic modulators [94,112].

5. DNA’s Clinical Frontier in ME: Biomarkers, Therapies, and Challenges

5.1. DNA-Focused Integrative Omics Approaches in ME

Understanding the complexity of ME requires a comprehensive, DNA-focused integrative omics approach that combines genomics, epigenomics, transcriptomics, proteomics, and metabolomics. This multi-layered strategy allows researchers to trace the flow of biological information from genetic variants and epigenetic modifications to changes in gene expression, protein function, and metabolic processes. By analyzing these interconnected layers, researchers can uncover molecular pathways and disease drivers that may be missed when studying individual “omics” layers in isolation. For example, SNP may predispose an individual to an epigenetic alteration in a regulatory region, which in turn dysregulates gene expression and disrupts metabolic homeostasis. This integrative perspective is critical for constructing detailed models of ME pathogenesis and identifying targets for diagnosis and therapy [40,113]. Multi-omics approaches have been successfully applied in recent studies to differentiate ME patients from controls with high accuracy by integrating microbiome profiles, plasma metabolomics, immune cell data, and clinical symptoms. These techniques also enable temporal tracking of biomarkers associated with symptom fluctuations, such as PEM, improving disease classification and prognostication [40]. Machine learning further enhances the analysis of complex multi-omics datasets, allowing the discovery of novel biomarker combinations and underlying biological patterns unique to ME subgroups. This precision medicine approach promises more personalized and effective diagnostics and treatments for ME patients [8,40]. This integrative approach represents a paradigm shift toward understanding ME as a multifactorial disease, driven by genome–epigenome interactions and complex cellular dysfunction across multiple biological domains.

5.2. DNA-Based Biomarkers for Diagnosis and Prognosis in ME

Identifying reliable DNA-based biomarkers for diagnosis, prognosis, and treatment monitoring remains a critical priority in ME research. Genetic variants, such as SNPs, contribute to individual susceptibility to ME, while distinct DNA methylation patterns can reflect disease activity and subtypes. For example, specific methylation signatures have shown promise in distinguishing ME from other fatigue-related conditions, providing greater diagnostic precision. Recent large-scale whole-genome sequencing studies using advanced deep learning frameworks have identified dozens of ME risk genes characterized by intolerance to loss-of-function mutations, highlighting their essential biological roles across immune and nervous system tissues [31,32,35]. These genetic risk factors, combined with DNA methylation profiles, enhance the ability to stratify patients into biologically meaningful subgroups, facilitating personalized medicine approaches and improving early and accurate disease detection [34]. Integrating multi-omics data, including genomics, epigenomics, transcriptomics, and proteomics, further refines biomarker discovery, offering comprehensive signatures that correlate with clinical features such as fatigue severity and cognitive dysfunction. AI and machine learning tools have achieved high accuracy in classifying ME patients using blood-based and microbiome biomarkers, underscoring the potential of DNA-based markers in precision diagnostics and prognostics [114,115]. In summary, leveraging genetic variants in conjunction with epigenetic signatures represents a promising strategy for developing objective, clinically relevant DNA-based biomarkers for ME diagnosis and prognosis, ultimately enabling personalized treatment strategies.

5.3. Targeting DNA-Associated Mechanisms for Therapeutic Intervention in ME

Understanding the multifaceted role of DNA in ME opens promising avenues for innovative therapeutic strategies. Recent large-scale genetic studies, such as the DecodeME project, have identified specific genetic loci and risk genes linked to ME, providing concrete molecular targets for intervention. Precision medicine approaches may involve gene editing technologies, such as CRISPR, or small molecules that modulate gene expression or function, aiming to correct underlying genetic dysfunctions that contribute to the disease [17]. Mitochondrial dysfunction is a hallmark of ME, and therapeutic strategies focused on enhancing mitochondrial function hold significant potential. Treatments using nutrients and cofactors such as Coenzyme Q10, L-carnitine, and B vitamins, or drugs that boost ATP production and stimulate mitochondrial biogenesis, may help restore cellular energy balance and alleviate fatigue symptoms [116,117,118].

Epigenetic modulation is another key therapeutic target, as aberrant DNA methylation patterns disrupt normal gene expression in ME. Pharmacologic agents, dietary components, and lifestyle interventions aimed at restoring healthy epigenetic regulation could normalize affected biological pathways and improve symptoms. Reducing oxidative stress and enhancing DNA repair mechanisms are also promising strategies; antioxidants like N-acetylcysteine and resveratrol may neutralize reactive oxygen species, while compounds that promote DNA repair could preserve genomic stability and cellular resilience [46,119] (Figure 4). Emerging biomarkers such as sphingomyelin phosphodiesterase acid-like 3B (SMPDL3B) not only assist in diagnosis but may also represent novel therapeutic targets. Modulating such molecules involved in immune regulation and cellular signaling could help correct disease-specific molecular abnormalities [120]. Together, these DNA-associated therapeutic approaches frame a forward-thinking paradigm for ME treatment, targeting molecular dysfunction at its roots to improve patient outcomes and quality of life.

Figure 4. A Multimodal Therapeutic Approach to ME: Targeting DNA, Mitochondria, and Oxidative Stress. The figure illustrates three key therapeutic strategies for ME based on the molecular mechanisms discussed in the review. The top panel shows that methylation alteration, influenced by environmental factors such as diet and drugs, may be modulated to restore normal gene expression. The bottom-left panel illustrates that mitochondrial dysfunction, a key feature of ME, could be addressed with supplements such as Coenzyme Q10 and L-carnitine to enhance ATP production and mitigate energy deficits. This section also shows that antioxidants such as N-acetylcysteine may reduce cell damage by neutralizing reactive oxygen species (ROS), which contribute to oxidative stress. The bottom-right panel illustrates the potential for gene editing technologies to modulate the gene expression of specific ME targets, providing a precision medicine approach to correct underlying genetic dysfunctions. Figure created in BioRender Wesam Elremaly. (2025) https://BioRender.com/ (accessed on 7 September 2025). (TU28PQT2GO).

5.4. Challenges in Translating DNA Research to Clinical Applications in ME

Translating DNA-focused research into clinical applications for ME faces several significant challenges. One major obstacle is the substantial heterogeneity among ME patients; diverse genetic and epigenetic profiles across patient cohorts complicate the identification of universal diagnostic biomarkers or therapeutic targets. Accurate patient classification requires large, well-phenotyped cohorts integrating genetic, epigenetic, and clinical data to delineate biologically meaningful subgroups.

Another critical challenge is distinguishing causality from consequence. It remains essential to determine whether observed DNA or epigenetic changes drive ME pathogenesis or are secondary effects resulting from chronic illness. This necessitates well-designed longitudinal studies and replication of findings across diverse populations. Genetic and epigenetic variability between ethnic groups further complicates generalizability, emphasizing the need for inclusive, multi-ethnic research efforts.

Addressing these challenges is vital for ensuring the robustness, reproducibility, and clinical relevance of DNA-based discoveries. Ultimately, overcoming these barriers will pave the way for reliable diagnostic tools and targeted interventions in ME grounded in molecular biology.

6. Conclusions

The body of evidence reviewed here underscores the profound and multifaceted role of DNA in the pathology of ME. The illness is not just an isolated event but a complex interplay of genetic predispositions, as shown by familial clustering and identified risk variants in genes related to immunity, neurology, and metabolism. A central finding is the significant contribution of mitochondrial DNA dysfunction to the hallmark symptoms of energy deficit and PEM, a condition worsened by oxidative stress and direct DNA damage. Crucially, epigenetic modifications provide a dynamic link between environmental triggers and a person’s genetic makeup, leading to altered gene expression, immune dysregulation, and metabolic shifts. This includes the activation of transposable elements, which can provoke a state of chronic immune activation. Moving forward, an integrative multi-omics approach that combines genomics, epigenomics, and other molecular data is crucial for unravelling the full complexity of ME. This research is not only critical for discovering much-needed biomarkers for diagnosis and prognosis but also for paving the way for effective, personalized treatments that target the root molecular causes of the disease, ultimately improving the lives of ME patients.