Tag: 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)

Exploring a genetic basis for the metabolic perturbations in ME/CFS using UK Biobank

Highlights:

  • ME/CFS shows distinct genetic influences on metabolic regulation.
  • Lipid and hormone-related pathways emerge as key areas of interest.
  • Many small genetic effects may collectively disrupt metabolic resilience in ME/CFS.

Summary:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a clinically heterogeneous disease lacking approved therapies. To assess genetic susceptibility towards a specific metabolic phenotype, we performed a genome-wide association study on plasma biomarker levels (mGWAS) in ME/CFS patients (n=875) and healthy controls (HCs) (n=36,033).
We identified 112 significant SNP–biomarker associations in ME/CFS, compared with 4,114 in HCs. Two SNPs specific to ME/CFS, mapping to HSD11B1 and SCGN, were associated to phospholipids in extra-large very low-density lipoproteins (VLDL) and total fatty acids respectively. Genetic effects of VLDL associations were among the least correlated between ME/CFS and HCs. Heterogeneity tests found differential effects for several lipid traits at ADAP1, NR1H3 and CD40, which are involved in immune regulation.
ME/CFS mGWAS summary statistics were decomposed to uncover shared genetic-metabolic patterns, where enrichment analysis highlighted pathways in lipid metabolism, neurotransmitter transport, and inflammation. These findings provide a genetic and molecular rationale for patient heterogeneity and suggest a polygenic predisposition in which many small-effect variants may jointly perturb metabolic mechanisms.
Source: Katherine Huang, Muhammad Muneeb, Natalie Thomas, Elena K. Schneider-Futschik, Paul R. Gooley, David B. Ascher, Christopher W. Armstrong. Exploring a genetic basis for the metabolic perturbations in ME/CFS using UK Biobank. iScience, 2025, 114316 ISSN 2589-0042, https://doi.org/10.1016/j.isci.2025.114316. https://www.sciencedirect.com/science/article/pii/S2589004225025775 (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)

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)

Neurodevelopment Genes Encoding Olduvai Domains Link Myalgic Encephalomyelitis to Neuropsychiatric Disorders

Abstract:

Background/Objectives: The aetiology of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), a chronic and severe debilitating disease with a complex phenotype, remains elusive. Associations with infectious diseases and autoimmune and neuropsychiatric disorders have been observed, without the identification of mechanisms. Previous studies suggest that genetic predisposition plays a role, but results are difficult to replicate, with Genome-Wide Association Studies of ME/CFS being challenging due to the relative rareness and heterogeneity of the disorder.
Methods: We studied a well-defined Australian patient cohort diagnosed via the International Consensus Criteria, recruited by a specialist ME/CFS clinic. The whole-exome sequences of 77 patients were contrasted against genome variation in the 1000 Genome Project’s genome-matched population.
Results: Significant associations with ME/CFS were harboured in genes that belong to the Neuroblastoma Breakpoint Family encoding Olduvai (DUF1220) domains, namely NBPF1 (rs3897177, p-value = 3.15 × 10−8), NBPF10 (rs1553120233, p-value = 9.262 × 10−13), and NBPF16 (rs200632836, p-value = 1.04 × 10−6). Other significantly associated variants were detected in the ATR, RSPH10B, ADGRE5-CD97, and NTRK2 genes, among others. Replication of these results was attempted via a GWAS on raw data from a US cohort, which confirmed shared significant associations with variation identified in the PTPRD, CSMD3, RAPGEF5, DCC, ALDH18A1, GALNT16, UNC79, and NCOA3 genes.
Conclusions: These genes are involved in cortical neurogenesis, brain evolution, and neuroblastoma, and have been implicated by several studies in schizophrenia and autism. The sharing of these associations by the two cohorts supports their validity and grants the necessity of future studies to evaluate the implications for ME/CFS aetiology.
Source: Arcos-Burgos, M., Arcos-Holzinger, M., Mastronardi, C., Isaza-Ruget, M. A., Vélez, J. I., Lewis, D. P., Patel, H., & Lidbury, B. A. (2025). Neurodevelopment Genes Encoding Olduvai Domains Link Myalgic Encephalomyelitis to Neuropsychiatric Disorders. Diagnostics, 15(12), 1542. https://doi.org/10.3390/diagnostics15121542 https://www.mdpi.com/2075-4418/15/12/1542 (Full text)

Causal relationship between immune cells and post-viral fatigue syndrome: a Mendelian randomization study

Abstract:

Background: Accumulating evidence has hinted at a correlation between immune cells and post-viral fatigue syndrome (PVFS). However, it is still ambiguous whether these associations indicate a causal connection.

Objective: To elucidate the potential causal link between immune cells and PVFS, we performed a two-sample Mendelian randomization (MR) study.

Methods: We obtained summary data on PVFS cases (Ncase = 195) and controls (Ncontrol = 382,198) from the FinnGen consortium. Additionally, we retrieved comprehensive statistical information on 731 immune cell features. Our analysis encompassed both forward and reverse MR approaches. To ensure the reliability and validity of our findings, we conducted rigorous sensitivity analyses, addressing issues of robustness and heterogeneity.

Result: Our study presents compelling evidence of a probable causal link between immune cells and PVFS. Notably, we have pinpointed 28 distinct types of immune cell traits that potentially exhibit a causal association with PVFS. Among a pool of 7 31 immune cell traits, we identified 28 immune cell types that exhibited a potential causal association with PVFS. These included 9 B cells, 1 conventional dendritic cell (cDC), 1 maturation stage of T cell, 3 myeloid cells, 9 T, B, NK, and monocyte cells (TBNK), and 5 regulatory T cells (Treg).

Conclusion: Through genetic analyses, our study has unveiled profound causal connections between specific types of immune cells and PVFS, offering valuable guidance for forthcoming clinical investigations.

Source: Wang Z, Bai Z, Sun Y. Causal relationship between immune cells and post-viral fatigue syndrome: a Mendelian randomization study. Virol J. 2025 May 30;22(1):171. doi: 10.1186/s12985-025-02809-4. PMID: 40448142; PMCID: PMC12124062. https://pmc.ncbi.nlm.nih.gov/articles/PMC12124062/ (Full text)

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

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: the biology of a neglected disease

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic, debilitating disease characterised by a wide range of symptoms that severely impact all aspects of life. Despite its significant prevalence, ME/CFS remains one of the most understudied and misunderstood conditions in modern medicine. ME/CFS lacks standardised diagnostic criteria owing to variations in both inclusion and exclusion criteria across different diagnostic guidelines, and furthermore, there are currently no effective treatments available.

Moving beyond the traditional fragmented perspectives that have limited our understanding and management of the disease, our analysis of current information on ME/CFS represents a significant paradigm shift by synthesising the disease’s multifactorial origins into a cohesive model. We discuss how ME/CFS emerges from an intricate web of genetic vulnerabilities and environmental triggers, notably viral infections, leading to a complex series of pathological responses including immune dysregulation, chronic inflammation, gut dysbiosis, and metabolic disturbances.

This comprehensive model not only advances our understanding of ME/CFS’s pathophysiology but also opens new avenues for research and potential therapeutic strategies. By integrating these disparate elements, our work emphasises the necessity of a holistic approach to diagnosing, researching, and treating ME/CFS, urging the scientific community to reconsider the disease’s complexity and the multifaceted approach required for its study and management.

Source: Arron HE, Marsh BD, Kell DB, Khan MA, Jaeger BR, Pretorius E. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: the biology of a neglected disease. Front Immunol. 2024 Jun 3;15:1386607. doi: 10.3389/fimmu.2024.1386607. PMID: 38887284; PMCID: PMC11180809. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11180809/ (Full text)

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