Category: Genetics

Genetic Insights into Circulating Complement Proteins in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Potential Inflammatory Subgroup

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating multi-system illness with heterogeneity that complicates identifying the pathophysiology, biomarkers, and therapeutic targets. Evidence indicates the importance of immune dysregulation, including the complement system, in ME/CFS. This study investigates the contribution of genetic drivers to potential dysregulation of the complement pathway in ME/CFS.

We used protein quantitative trait loci (pQTL) analyses, adjusted for covariates using linear and logistic regression, to identify genetic variants significantly associated with plasma complement protein levels in a study sample identified from the general population (50 ME/CFS and 121 non-fatigued). ME/CFS patients carrying certain pQTLs exhibited dysregulation of the alternative complement pathway, which defined an inflammatory subgroup with a high C3/low Bb profile and established a genetic link to dysregulation of the alternative complement pathway. Six of the significant pQTLs were also associated with fatigue-related phenotypes in the UK Biobank, four of which were complement-associated, providing some validation in an independent population.

Our findings highlight a mechanism by which risk alleles contribute to ME/CFS heterogeneity, providing evidence of a genetic basis for complement dysregulation in a subset of patients. This approach could identify pathway-focused subgroups in ME/CFS and related illnesses to inform personalized approaches to diagnosis and treatment.

Source: Maya J, Unger ER, Lin JS, Rajeevan MS. Genetic Insights into Circulating Complement Proteins in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Potential Inflammatory Subgroup. Int J Mol Sci. 2026 Feb 5;27(3):1574. doi: 10.3390/ijms27031574. PMID: 41683992. https://www.mdpi.com/1422-0067/27/3/1574 (Full text)

Uncovering the genetic architecture of ME/CFS: a precision approach reveals impact of rare monogenic variation

Abstract:

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disabling and heterogeneous disorder lacking validated biomarkers or targeted therapies. Clinical variability and elusive pathophysiology hinder progress toward effective diagnostics and treatment. Core symptoms include persistent fatigue, post-exertional malaise, unrefreshing sleep, cognitive dysfunction, and pain. We tested whether an individualized, “n-of-1” genomic and transcriptomic framework combined with comprehensive, participant-informed phenotyping could reveal molecular signatures unique to each patient.

Methods: Clinical-grade whole-genome sequencing was conducted in 31 affected individuals from 25 families, with RNA-seq performed on a subset (16 affected, 7 unaffected) using blood samples. Machine-learning assisted variant triage, transcript-aware damage prediction, and expert review identified pathogenic or likely pathogenic variants in 8 of 25 probands (32%) and 12 of 31 affected individuals (39%).

Results: Findings revealed marked genetic heterogeneity, including large-effect rare and more common variants. Implicated pathways included ATP generation, oxidative phosphorylation, fatty acid oxidation; regulation of glycolysis, amino acid and lipid turnover; ion and solute homeostasis; synaptic signaling, excitability, oxygen transport, and muscle integrity, resilience, and post-exertional recovery; previously implicated processes. Plausible modifiers influencing disease onset, severity, and relapsing–remitting patterns and possibly explaining intrafamilial variability and inconsistent findings across studies, were also identified. Despite gene-level diversity, downstream effects converged on impaired energy production, reduced stress resilience, and vulnerability to post-exertional metabolic failure; disruptions consistent with core ME/CFS symptoms of exertional intolerance, cognitive fog, and fatigue.

Conclusions: Our findings support the hypothesis that at least a subset of ME/CFS cases represent distinct molecular disorders that converge on shared physiological pathways. Validation in larger, more diverse cohorts will be essential to test this hypothesis and establish generalizability, but increase size alone is unlikely to resolve causation in a disorder defined by rarity, heterogeneity, and molecular complexity. We suggest that progress will require experimental designs that integrate individual-level genomic data with deep, participant-informed deep phenotyping, capturing the combined effects of rare and common variants and environmental modifiers on disease expression and progression. We believe that an individualized precision medicine framework will uncover molecular drivers and modifiers of ME/CFS previously obscured by heterogeneity, enabling biologically informed stratification, improved trial design, biomarker discovery, and targeted interventions in this historically neglected condition.

Source: Birch CL, Wilk BM, Gajapathy M, Hutchins SD, Kaur G, Brown DM, Mamidi TKK, Hodgin KS, Turgut A, Younger JW, Worthey EA. Uncovering the genetic architecture of ME/CFS: a precision approach reveals impact of rare monogenic variation. J Transl Med. 2025 Dec 24. doi: 10.1186/s12967-025-07586-w. Epub ahead of print. PMID: 41444612. https://link.springer.com/article/10.1186/s12967-025-07586-w (Full text available as PDF file)

Identification of Novel Reproducible Combinatorial Genetic Risk Factors for Myalgic Encephalomyelitis in the DecodeME Patient Cohort and Commonalities with Long COVID

Abstract:

Background: Myalgic encephalomyelitis (also known as ME/CFS or simply ME) has severely impacted the lives of tens of millions of people globally, but the disease currently has no accurate diagnostic tools or effective treatments. Identifying the biological causes of ME has proven challenging due to its wide range of symptoms and affected organs, and the lack of reproducible genetic associations across ME populations. This has prolonged misunderstanding, lack of awareness, and denial of the disease, further harming patients.

Methods: We used the PrecisionLife combinatorial analytics platform to identify disease signatures (i.e., combinations of 1-4 SNP-genotypes) that are significantly enriched in two cohorts of ME participants from DecodeME relative to controls from UK Biobank (UKB). We tested whether the number of these signatures possessed by an individual is significantly associated with increased prevalence of ME in a third disjoint cohort of DecodeME participants. We characterized a number of drug repurposing opportunities for a set of candidate core genes whose disease signatures had the strongest association with ME and which were linked to different mechanisms. We then tested gene overlap between the ME signatures identified and previous studies in long COVID, using two independent approaches to explore these shared genetic commonalities.

Results: We identified 22,411 reproducible disease signatures, comprising combinations of 7,555 unique SNPs, that are consistently associated with increased prevalence of ME in three disjoint patient cohorts. The count of reproducible signatures was significantly associated with increased prevalence of ME (p = 4×10-21), and participants with a top 10% signature count had an odds ratio of disease 1.64 times greater than participants with a bottom 10% signature count, confirming that these genetic signatures increase susceptibility for developing ME. These disease signatures map to 2,311 genes. We identified substantial overlap between the genes found by this combinatorial analysis and previous studies. We found that the 259 candidate core genes most strongly associated with ME are enriched in disease mechanisms including neurological dysregulation, inflammation, cellular stress responses and calcium signaling. We demonstrated that 76 out of 180 genes previously linked to long COVID in UKB and the US All of Us cohorts are also significantly associated with ME in the DecodeME cohort. These findings allowed identification of many existing and novel repurposing opportunities, including candidates linked to several genes with shared etiology for long COVID.

Conclusion: These findings provide further evidence that ME is a complex multisystemic condition where the risk of developing the disease has a very clear genetic and biological basis. They give a substantially deeper level of insight into the genetic risk factors and mechanisms involved in ME. The discovery of so many multiply reproducible genetic associations implies that ME is highly polygenic, which has important consequences for its future study and the delivery of clinical care to patients. The striking overlap in genes and mechanisms between long COVID and ME (76 / 180 long COVID genes tested) suggests the potential for development of novel or repurposed drug therapies that could be used to successfully treat either condition. However, although they share significant genetic commonalities, long COVID and ME appear to be best considered as partially overlapping but different diseases.

Source: Lu J, Sun W, Li S, Qu Y, Liu T, Guo S, Feng C, Yang T. Assessment of symptoms in myalgic encephalomyelitis/chronic fatigue syndrome: a comparative study of existing scales. Front Neurol. 2025 Nov 18;16:1618272. doi: 10.3389/fneur.2025.1618272. PMCID: PMC12668935. https://pmc.ncbi.nlm.nih.gov/articles/PMC12668935/ (Full text available as PDF file)

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.
Source: Elremaly W, Elbakry M, Vahdani Y, Franco A, Moreau A. The Role of Nuclear and Mitochondrial DNA in Myalgic Encephalomyelitis: Molecular Insights into Susceptibility and Dysfunction. DNA. 2025; 5(4):53. https://doi.org/10.3390/dna5040053 https://www.mdpi.com/2673-8856/5/4/53 (Full text)

Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome

Abstract:

Myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS) is a common, poorly understood disease that has no effective treatments, and has long been underserved by scientific research and national health systems. It is a sex-biased disease towards females that is often triggered by an infection, and its hallmark symptom is post-exertional malaise. People with ME/CFS often report their symptoms being disbelieved. The biological mechanisms causing ME/CFS remain unclear.
We recruited 21,620 ME/CFS cases and performed genome-wide association studies (GWAS) for up to 15,579 cases and 259,909 population controls with European genetic ancestry. In these GWAS, we discovered eight loci that are significantly associated with ME/CFS, including three near BTN2A2, OLFM4, and RABGAP1L genes that act in the response to viral or bacterial infection. Four of the eight loci (RABGAP1L, FBXL4, OLFM4, CA10) were associated at p < 0.05 with cases ascertained using post-exertional malaise and fatigue in the UK Biobank and the Netherlands biobank Lifelines. We found no evidence of sex-bias among discovered associations, and replicated in males two genetic signals (ARFGEF2, CA10) discovered in females. The ME/CFS association near CA10 colocalises with a known association to multisite chronic pain. We found no evidence that the eight ME/CFS genetic signals share common causal genetic variants with depression or anxiety.
Our findings suggest that both immunological and neurological processes are involved in the genetic risk of ME/CFS.
Source: DecodeME collaboration. Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome. https://www.research.ed.ac.uk/en/publications/initial-findings-from-the-decodeme-genome-wide-association-study- (Full text available as PDF file)

Measurement of Genetic Variations in ME/CFS Patients in the IDO2 Gene Encoding an Enzyme Metabolizing Tryptophan

Abstract:

Genetic variations in the indoleamine 2,3-dioxygenase (IDO2) gene that are commonly found in the general population have been assessed for their frequency in myalgic encephalomyelitis/chronic fatigue (ME/CFS) patients compared with healthy controls. They have potential for being genetic variations that lead to susceptibility to developing ME/CFS following exposure to a triggering stressor like a viral infection or other major stress events.

The IDO2 gene encodes an enzyme that is involved in the tryptophan-kynurenine pathway (TKP), and is activated if there are excessive amounts of tryptophan to prevent excessive serotonin production. The TKP pathway through production of NADH is involved in regulating the immune system and likely plays an important role in ME/CFS.

A simple method was developed to evaluate the 5 commonly occurring mutations in this gene in ME/CFS patients and to determine if one or more were present at higher frequency than in healthy controls. This might indicate a susceptibility factor for developing ME/CFS. In this chapter we describe the techniques used to isolate peripheral blood mononuclear cells (PBMCs), extract the DNA, and then do touchdown PCR and DNA sequencing for the analysis.

Source: Edgar CD, Blair A, Tate WP. Measurement of Genetic Variations in ME/CFS Patients in the IDO2 Gene Encoding an Enzyme Metabolizing Tryptophan. Methods Mol Biol. 2025;2920:247-256. doi: 10.1007/978-1-0716-4498-0_14. PMID: 40372687. https://link.springer.com/protocol/10.1007/978-1-0716-4498-0_14

Dissecting the genetic complexity of myalgic encephalomyelitis/chronic fatigue syndrome via deep learning-powered genome analysis

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, heterogeneous, and systemic disease defined by a suite of symptoms, including unexplained persistent fatigue, post-exertional malaise (PEM), cognitive impairment, myalgia, orthostatic intolerance, and unrefreshing sleep. The disease mechanism of ME/CFS is unknown, with no effective curative treatments.

In this study, we present a multi-site ME/CFS whole-genome analysis, which is powered by a novel deep learning framework, HEAL2. We show that HEAL2 not only has predictive value for ME/CFS based on personal rare variants, but also links genetic risk to various ME/CFS-associated symptoms. Model interpretation of HEAL2 identifies 115 ME/CFS-risk genes that exhibit significant intolerance to loss-of-function (LoF) mutations. Transcriptome and network analyses highlight the functional importance of these genes across a wide range of tissues and cell types, including the central nervous system (CNS) and immune cells.

Patient-derived multi-omics data implicate reduced expression of ME/CFS risk genes within ME/CFS patients, including in the plasma proteome, and the transcriptomes of B and T cells, especially cytotoxic CD4 T cells, supporting their disease relevance. Pan-phenotype analysis of ME/CFS genes further reveals the genetic correlation between ME/CFS and other complex diseases and traits, including depression and long COVID-19.

Overall, HEAL2 provides a candidate genetic-based diagnostic tool for ME/CFS, and our findings contribute to a comprehensive understanding of the genetic, molecular, and cellular basis of ME/CFS, yielding novel insights into therapeutic targets. Our deep learning model also offers a potent, broadly applicable framework for parallel rare variant analysis and genetic prediction for other complex diseases and traits.

Source: Zhang S, Jahanbani F, Chander V, Kjellberg M, Liu M, Glass KA, Iu DS, Ahmed F, Li H, Maynard RD, Chou T, Cooper-Knock J, Zhang MJ, Thota D, Zeineh M, Grenier JK, Grimson A, Hanson MR, Snyder MP. Dissecting the genetic complexity of myalgic encephalomyelitis/chronic fatigue syndrome via deep learning-powered genome analysis. medRxiv [Preprint]. 2025 Apr 16:2025.04.15.25325899. doi: 10.1101/2025.04.15.25325899. PMID: 40321247; PMCID: PMC12047926. https://pmc.ncbi.nlm.nih.gov/articles/PMC12047926/ (Full text available as PDF file)

Actigraphic and Genetic Characterization of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Phenotypes in the UK Biobank (P10-9.007)

Abstract:

Objective: Patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) often experience debilitating fatigue and autonomic dysregulation, yet objective measurements of these symptoms are limited. This study utilized actigraphic data from the United Kingdom Biobank (UKBB) to investigate (1) reduced activity in those with CFS, (2) decreased amplitudes of daily temperature rhythms as a potential indicator of autonomic dysregulation, and (3) the impact of specific single nucleotide polymorphisms (SNPs) associated with CFS on these actigraphic parameters.

Background: ME/CFS is a complex and poorly understood condition characterized by profound fatigue, postural orthostasis, and temperature dysregulation. Objective metrics reflecting these fatigue-related symptoms are scarce. Previous research explored small-scale actigraphic analyses, shedding light on movement and temperature patterns in CFS, but large-scale investigations remain limited. Genetic factors have also emerged as potential contributors to CFS risk, although how they affect phenotypic manifestations remains unclear.

Design/Methods: Actigraphic data from the UKBB were analyzed to compare those with CFS (n = 295) to controls (n = 63,133). Movement parameters, acceleration amplitudes, and temperature amplitudes were assessed. Additionally, the impact of specific SNPs associated with CFS on actigraphic measurements and subjective fatigue experiences was examined.

Results: In addition to profound fatigue, those with CFS exhibited significantly reduced overall movement (Cohen’s d = −0.220, p-value = 2.42 × 10–15), lower acceleration amplitudes (Cohen’s d = −0.377, p-value = 1.74 × 10−6), and decreased temperature amplitudes (Cohen’s d = −0.173, p-value = 0.002) compared to controls. Furthermore, certain SNPs associated with CFS were found to significantly influence both actigraphic measurements and subjective fatigue experiences.

Conclusions: This study provides valuable insights into the objective characterization of CFS using actigraphy, shedding light on the interaction between genetics and symptomatology in CFS. The findings offer avenues for further research into the pathophysiology of CFS and may contribute to a better understanding of fatigue-related conditions in general.

Source: Patrick Liu, David Raizen, Carsten Skarke, Thomas Brooks, and Ron Anafi. Actigraphic and Genetic Characterization of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Phenotypes in the UK Biobank (P10-9.007). Neurology, April 9, 2024 issue
102 (17_supplement_1) https://doi.org/10.1212/WNL.0000000000204829 https://www.neurology.org/doi/abs/10.1212/WNL.0000000000204829

The influence of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) family history on patients with ME/CFS

Abstract:

Aim: It is unclear if individuals with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) with family histories of ME/CFS differ from those with ME/CFS without this family history. To explore this issue, quantitative data from patients with ME/CFS and controls were collected, and we examined those with and without family histories of ME/CFS.

Methods: The samples included 400 patients with ME/CFS, and a non-ME/CFS chronic illness control group of 241 patients with multiple sclerosis (MS) and 173 with post-polio syndrome (PPS).

Results: Confirming findings from prior studies, those with ME/CFS were more likely to have family members with ME/CFS than controls. We found family histories of ME/CFS were significantly higher (18%) among the ME/CFS group than the non-ME/CFS controls (3.9%). In addition, patients with ME/CFS who had family histories of ME/CFS were more likely to have gastrointestinal symptoms than those with ME/CFS without those family histories.

Conclusions: Given the recent reports of gastrointestinal difficulties among those with ME/CFS, our findings might represent one predisposing factor for the emergence of ME/CFS.
Source: Jason LA, Ngonmedje S. The influence of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) family history on patients with ME/CFS. Explor Med. 2024;5:185–92. https://doi.org/10.37349/emed.2024.00215 https://www.explorationpub.com/Journals/em/Article/1001215 (Full text)

Heterogenous circulating miRNA changes in ME/CFS converge on a unified cluster of target genes: A computational analysis

Abstract:

Myalgic Encephalomyelitis / Chronic Fatigue Syndrome is a debilitating, multisystem disease of unknown mechanism, with a currently ongoing search for its endocrine mediators. Circulating microRNAs (miRNA) are a promising candidate for such a mediator and have been reported as significantly different in the patient population versus healthy controls by multiple studies. None of these studies, however, agree with each other on which specific miRNA are under- or over-expressed.

This discrepancy is the subject of the computational study presented here, in which a deep dive into the predicted gene targets and their functional interactions is conducted, revealing that the aberrant circulating miRNAs in ME/CFS, although different between patients, seem to mainly target the same specific set of genes (p ≈ 0.0018), which are very functionally related to each other (p ≲ 0.0001).

Further analysis of these functional relations, based on directional pathway information, points to impairments in exercise hyperemia, angiogenic adaptations to hypoxia, antioxidant defenses, and TGF-β signaling, as well as a shift towards mitochondrial fission, corroborating and explaining previous direct observations in ME/CFS. Many transcription factors and epigenetic modulators are implicated as well, with currently uncertain downstream combinatory effects.

As the results show significant similarity to previous research on latent herpesvirus involvement in ME/CFS, the possibility of a herpesvirus origin of these miRNA changes is also explored through further computational analysis and literature review, showing that 8 out of the 10 most central miRNAs analyzed are known to be upregulated by various herpesviruses. In total, the results establish an appreciable and possibly central role for circulating microRNAs in ME/CFS etiology that merits further experimental research.

Source: Kaczmarek MP. Heterogenous circulating miRNA changes in ME/CFS converge on a unified cluster of target genes: A computational analysis. PLoS One. 2023 Dec 29;18(12):e0296060. doi: 10.1371/journal.pone.0296060. PMID: 38157384; PMCID: PMC10756525. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10756525/ (Full text)