Tag: risk factors

Toward a Molecular Reclassification of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Integrating Multi-Omics, Machine Learning, and Precision Medicine

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex, multi-system disease characterized by a multitude of symptoms across various organ systems. Diagnosis has relied heavily on heterogeneous clinical symptom presentation and evolving case definitions, with treatment focused on addressing presenting symptoms due to the paucity of validated biomarkers. Meanwhile, advances have been made in understanding the underlying pathophysiology through strong epidemiologic, clinical, and basic science studies. This narrative review synthesizes recent advances that are likely to drive a shift in understanding from symptom-based classification toward a molecularly defined understanding of the disease.

This shift in understanding will likely provide the foundation for future research efforts focused on targeting diagnosis and treatment more effectively. Specifically, we reference the identification of rare genetic risk variants through the HEAL2 deep learning framework, the large-scale DecodeME genome-wide association study, and dynamic epigenetic markers of disease state.

In addition, the findings revealed the downstream consequences of this genetic and epigenetic priming: chronic innate immune activation, CD8+ T cell exhaustion characterized by upregulation of the exhaustion-driving transcription factors Thymocyte Selection-Associated HMG Box (TOX) and Eomesodermin (EOMES), and a cellular energy crisis centered on mitochondrial dysfunction. Furthermore, results of recent studies have revealed sex-specific transcriptomic and proteomic signatures of maladaptive recovery.

We also highlight the role of machine learning and artificial intelligence integrations in translating high-dimensional multi-omics data into actionable biological insights, including the identification of monocyte subsets via Positive Unlabeled Learning, circulating cell-free RNA diagnostic signatures, and integrated multi-modal disease models such as BioMapAI.

The combination of these findings, which highlight multiple identifiable mechanisms of molecular activity, support the feasibility of molecular subtyping, precision diagnostics, and targeted therapeutic strategies for ME/CFS.

Source: Frank J, Nesterovitch N, Movva C, Klimas NG, Nathanson L. Toward a Molecular Reclassification of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Integrating Multi-Omics, Machine Learning, and Precision Medicine. Int J Mol Sci. 2026 May 15;27(10):4436. doi: 10.3390/ijms27104436. PMID: 42196410; PMCID: PMC13207433. https://pmc.ncbi.nlm.nih.gov/articles/PMC13207433/ (Full text)

Shared genetic risk between functional somatic syndromes, internalizing disorders, and immune-mediated diseases: a twin-sibling study

Abstract:

Functional somatic syndromes frequently co-occur with internalizing disorders such as anxiety disorders and major depressive disorder. Both show familial associations with immune-mediated diseases. Here, we estimate genetic and environmental contributions to functional somatic syndromes and their overlap with immune-mediated diseases, with internalizing disorders included for comparison.

The study sample consisted of 6,097,372 Swedish twins, full siblings, and half-siblings born between 1945 and 2003. From nationwide registers covering inpatient, outpatient and primary care, we extracted ICD diagnoses of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), fibromyalgia (FM), irritable bowel syndrome (IBS), major depression, anxiety disorders, and immune-mediated diseases (consisting of autoimmune and autoinflammatory diseases).

We used bivariate twin-sibling structural equation modeling to estimate genetic and environmental correlations. We found that the heritability of functional somatic syndromes and internalizing disorders ranged from 15 to 44%, with the unique environment explaining 49-84% of the variance. We estimated the heritability of immune-mediated diseases at 37% (95% CI 36-38%), with a unique environmental component of 63% (95% CI 62-63%). Regarding the genetic correlations with immune-mediated diseases, fibromyalgia showed the strongest genetic correlation (rA = 0.52, 95% CI 0.45-0.63), IBS, ME/CFS, and major depression showed more modest genetic correlations (rA range 0.19-0.29), and anxiety disorders showed minimal genetic correlation (rA = 0.04, 95% CI 0.00-0.08).

In summary, fibromyalgia, and to a lesser degree other functional somatic syndromes and major depression, share genetic risk factors with immune-mediated diseases. These findings suggest that immune-related genetic risk factors contribute to the etiology of fibromyalgia and, to a lesser extent, other functional disorders and major depression.

Source: Steen OD, Ohlsson H, van Ockenburg SL, Kendler KS, Rosmalen JGM, Sundquist K, van Loo HM. Shared genetic risk between functional somatic syndromes, internalizing disorders, and immune-mediated diseases: a twin-sibling study. Brain Behav Immun. 2026 May 25:106837. doi: 10.1016/j.bbi.2026.106837. Epub ahead of print. PMID: 42190845. https://www.sciencedirect.com/science/article/pii/S0889159126005854 (Full text)

Incidence age is bimodal for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome, with higher severity burden for early onset disease

Abstract:

Myalgic Encephalomyelitis, or Chronic Fatigue Syndrome (ME/CFS), is a disease of uncertain origin. Studies of Norwegian health records have suggested that ME/CFS incidence across age groups is bimodal–a characteristic that could provide insight into the aetiology of the disease. Here, we analysed survey data from over 9,000 respondents with ME/CFS from 10 European countries, and observe an early onset peak with a mean of 16.0 years old (standard deviation [sd]: 4.3) and a late onset peak at 36.6 years old (sd: 10.5).

Statistical support for multimodal onset age was evident in 7 of the 10 countries examined. Infection as a trigger for ME/CFS is 10 percentage points higher among early compared to late onset disease (P = 2.1 × 10−13). Early onset ME/CFS was associated with greater odds of being severely or very severely affected (OR = 2.15, 95% CI [1.84—2.51], p < 2 × 10−16). Those with first degree relatives with ME/CFS had greater odds of early than late onset ME/CFS (OR = 1.43, 95% CI [1.25—1.63], P = 4.4 × 10−07). We further validated our findings in a UK dataset where we replicated bimodal onset age and observed significantly greater odds of glandular fever/infectious mononucleosis as a trigger in early onset cases (OR = 2.32, 95% CI [1.99—2.71], P = 2.4 × 10−24).

Our findings suggest that incidence of ME/CFS peaks in adolescence and in early middle-age and that early onset ME/CFS is more common in those with affected relatives, more often triggered by infection, and associated with more severe disease.

Source: Simon J Mcgrath, Charles B Hillier, Joshua J Dibble, Trude Schei, Arild Angelsen, Audrey A Ryback, Incidence age is bimodal for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome, with higher severity burden for early onset disease, Oxford Open Immunology, 2026;, iqag007, https://doi.org/10.1093/oxfimm/iqag007 https://academic.oup.com/ooim/advance-article/doi/10.1093/oxfimm/iqag007/8527015

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)