Tag: risk factors

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)

A Case of Psoriasis Concurrently Complicated by Sacroiliitis and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a systemic chronic disorder characterized by persistent and unexplained severe fatigue. Recent population-based studies have revealed that patients with chronic inflammatory skin dermatoses, including psoriasis, are more likely to develop ME/CFS.

Here, we report a case of psoriasis, whose exacerbation occurred concurrently with the development of sacroiliitis and the onset of ME/CFS. The pathogenesis of ME/CFS has not yet been fully elucidated, while inflammatory cytokines are involved in dysregulated interactions among the nervous, immune, and endocrine systems in the disease.

We discussed the shared immunological abnormalities of psoriasis and ME/CFS based on previous literature. Our case contributes to the understanding of the association between psoriasis and ME/CFS.

Source: Iijima M, Miyagaki T, Nakajima K, Kadono T, Watabe H. A Case of Psoriasis Concurrently Complicated by Sacroiliitis and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Cureus. 2025 Sep 16;17(9):e92435. doi: 10.7759/cureus.92435. PMID: 41111852; PMCID: PMC12529862. https://pmc.ncbi.nlm.nih.gov/articles/PMC12529862/ (Full text)

Functional and internalizing disorders co-aggregate with cardiometabolic and immune-related diseases within families: a population-based cohort study

Abstract:

Background: Functional disorders share familial risk with internalizing disorders such as generalized anxiety disorder and depression, and are comorbid with cardiometabolic and immune-related diseases. We investigated whether functional and internalizing disorders co-aggregate with these diseases in families to gain insight into the aetiology of functional and internalizing disorders.

Methods: We included 166,774 subjects (aged 3-94), from the population-based Lifelines Cohort Study, a Dutch general population cohort. We defined cases for three functional disorders (myalgic encephalomyelitis/chronic fatigue syndrome; ME/CFS, fibromyalgia, and irritable bowel syndrome; IBS), two internalizing disorders (major depressive disorder; MDD and generalized anxiety disorder; GAD), cardiometabolic diseases (obesity, metabolic associated steatotic liver disease, type 2 diabetes, hypertension and cardiovascular disease) and immune-related diseases (composite measures of auto-immune disease and atopy). We used logistic regression to model the prevalence of these disorders in the general population and in participants with affected relatives. Using these prevalence estimates, we assessed familial co-aggregation with (1) recurrence risk ratios (λR), and (2) familial correlations (rf).

Results: All functional and internalizing disorders co-aggregated with immune-related diseases (λR range 1.06-1.24). ME/CFS, FM, and MDD co-aggregated with most cardiometabolic diseases (λR range 1.00-1.23). MDD, fibromyalgia, and ME/CFS showed similar familial correlation patterns with both disease groups (rf range 0.12-0.44), while patterns of IBS and GAD were more variable.

Conclusions: Internalizing and functional disorders share familial risk with immune-related and cardiometabolic diseases. This suggests that risk factors relevant to immune-related and cardiometabolic diseases may also be relevant for FDs. Future studies should investigate such risk factors to identify novel treatment targets.

Source: Steen OD, Bos M, van Ockenburg SL, Zhou Y, Nolte IM, Snieder H, Kendler K, Rosmalen JGM, van Loo HM. Functional and internalizing disorders co-aggregate with cardiometabolic and immune-related diseases within families: a population-based cohort study. BMC Med. 2025 Aug 11;23(1):469. doi: 10.1186/s12916-025-04293-7. PMID: 40784894. https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-025-04293-7 (Full text)

Immune Signatures in Post-Acute Sequelae of COVID-19 (PASC) and Myalgia/Chronic Fatigue Syndrome (ME/CFS): Insights from the Fecal Microbiome and Serum Cytokine Profiles

Abstract:

While there are many postulates for the etiology of post-viral chronic fatigue and other symptomatology, little is known. We draw on our past experience of these syndromes to devise means which can expose the primary players of this malady in terms of a panoply participating biomolecules and the state of the stool microbiome.
Using databases established from a large dataset of patients at risk of colorectal cancer who were followed longitudinally over 3 decades, and a smaller database dedicated to building a Long PASC cohort (Post-Acute Sequelae of COVID-19), we were able to ascertain factors that predisposed patients to (and resulted in) significant changes in various biomarkers, i.e., the stool microbiome and serum cytokine levels, which we verified by collecting stool and serum samples.
There were significant changes in the stool microbiome with an inversion from the usual Bacillota and Bacteroidota species. Serum cytokines showed significant differences in MIP-1β versus TARC (CC chemokine ligand 17) in patients with either PASC or COVID-19 (p < 0.02); IL10 versus IL-12p70a (p < 0.02); IL-1b versus IL-6 (p < 0.01); MCP1 versus TARC (p < 0.03); IL-8 versus TARC (p < 0.002); and Eotaxin3 versus TARC (p < 0.004) in PASC. Some changes were seen solely in COVID-19, including MDC versus MIP-1α (p < 0.01); TNF-α versus IL-1-β (p < 0.06); MCP4 versus TARC (p < 0.0001). We also show correlates with chronic fatigue where an etiology was not identified.
These findings in patients with positive criteria for PASC show profound changes in the microbiome and serum cytokine expression. Patients with chronic fatigue without clear viral etiologies also have common associations, including a history of tonsillectomy, which evokes a likely immune etiology.
Source: Tobi, M., Chaudhari, D., Ryan, E. P., Rossi, N. F., Koka, O., Baxter, B., Tipton, M., Dutt, T. S., Tobi, Y., McVicker, B., & Angoa-Perez, M. (2025). Immune Signatures in Post-Acute Sequelae of COVID-19 (PASC) and Myalgia/Chronic Fatigue Syndrome (ME/CFS): Insights from the Fecal Microbiome and Serum Cytokine Profiles. Biomolecules, 15(7), 928. https://doi.org/10.3390/biom15070928 https://www.mdpi.com/2218-273X/15/7/928 (Full text)

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)

The Implications and Predictability of Sleep Reversal for People with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Machine Learning Approach

Abstract:

Background/objectives: Impaired sleep is one of the core symptoms of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), yet the mechanisms and impact of sleep-related issues are poorly understood. Sleep dysfunctions for patients with ME/CFS include frequent napping, difficulties falling asleep, waking up early, and sleep reversal patterns (e.g., sleeping throughout the day and staying awake throughout the night). The current study focuses on sleep reversal for patients with ME/CFS.

Methods: We explored the symptoms and functional impairment of those with and without sleep reversal by analyzing the responses of a large international sample (N = 2313) using the DePaul Symptom Questionnaire (DSQ) and Medical Outcomes Study 36-item Short-Form Health Survey (SF-36).

Results: We found that those in our Sleep Reversal group (N = 327) compared to those without sleep reversal (N = 1986) reported higher symptom burden for 53 out of 54 DSQ symptoms and greater impairments for all six SF-36 subscales. The most accurate predictors of sleep reversal included age (p < 0.05), body mass index (p < 0.05), eleven DSQ symptoms (p < 0.01), and two SF-36 subscales (p < 0.01).

Conclusions: These features provide clues regarding some of the possible pathophysiological underpinnings of sleep reversal among those with ME/CFS.

Source: Dietrich MP, Pravin R, Furst J, Jason LA. The Implications and Predictability of Sleep Reversal for People with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Machine Learning Approach. Healthcare (Basel). 2025 May 26;13(11):1255. doi: 10.3390/healthcare13111255. PMID: 40508869. https://www.mdpi.com/2227-9032/13/11/1255 (Full text)

Evaluating the Causal Role of Genetically Inferred Immune Cells and Inflammatory Cytokines on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Background/Objectives: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a multifaceted and diverse disorder with an ambiguous etiology. Recent evidence indicates that immune system impairment and inflammatory mechanisms are pivotal to the initiation and advancement of ME/CFS. Nonetheless, the causal relationships among these factors remain inadequately comprehended.

Methods: This study investigated the causative contributions of immunological dysfunction and inflammatory variables in ME/CFS utilizing genome-wide association study (GWAS) data. We employed Mendelian randomization (MR) to investigate associations between 91 inflammatory cytokines, 731 immune cell characteristics, and the risk of ME/CFS. Summary statistics for immune cell traits and inflammatory cytokines were sourced from European GWAS cohorts (n = 3757 and n = 14,824, respectively), while ME/CFS data were obtained from the UK Biobank (n = 462,933, including 2076 cases). We predominantly employed the inverse variance weighted (IVW) approach, complemented by MR-Egger, weighted median, BWMR, and MR-RAPS tests to guarantee robust and precise outcomes.

Results: The study revealed significant causal links between various inflammatory factors, immune cell characteristics, and the risk of ME/CFS. Increased CXCL5 and CCL20 levels were significantly linked to a higher risk of ME/CFS, while elevated TNF levels were inversely related to ME/CFS risk. Furthermore, 13 immune cell characteristics were identified as having substantial causal associations with the likelihood of ME/CFS. These data are supportive of the causality that immune system dysfunction and inflammatory variables play a pivotal role in the development of ME/CFS.

Conclusions: This study provides new insights into the causal role of immune system dysfunction in the development of ME/CFS, contributing to a deeper understanding of its underlying mechanisms. These results offer a foundation for identifying diagnostic biomarkers and developing targeted therapeutic strategies. Future research should validate these findings using multi-center cohort studies and further investigate the mechanisms behind key factors to enable the development of personalized treatment approaches.

Source: Duan L, Yang J, Zhao J, Chen Z, Yang H, Cai D. Evaluating the Causal Role of Genetically Inferred Immune Cells and Inflammatory Cytokines on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Biomedicines. 2025 May 15;13(5):1200. doi: 10.3390/biomedicines13051200. PMID: 40427027; PMCID: PMC12109099. https://pmc.ncbi.nlm.nih.gov/articles/PMC12109099/ (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

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)