Category: Genetics

Autoimmunity-Related Risk Variants in PTPN22 and CTLA4 Are Associated With ME/CFS With Infectious Onset

Abstract:

Single nucleotide polymorphisms (SNP) in various genes have been described to be associated with susceptibility to autoimmune disease. In this study, myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) patients and controls were genotyped for five immune gene SNPs in tyrosine phosphatase non-receptor type 22 (PTPN22, rs2476601), cytotoxic T-lymphocyte-associated protein 4 (CTLA4, rs3087243), tumor necrosis factor (TNF, rs1800629 and rs1799724), and interferon regulatory factor 5 (IRF5, rs3807306), which are among the most important risk variants for autoimmune diseases.

Analysis of 305 ME/CFS patients and 201 healthy controls showed significant associations of the PTPN22 rs2476601 and CTLA4 rs3087243 autoimmunity-risk alleles with ME/CFS. The associations were only found in ME/CFS patients, who reported an acute onset of disease with an infection (PTPN22 rs2476601: OR 1.63, CI 1.04-2.55, p = 0.016; CTLA4 rs3087243: OR 1.53, CI 1.17-2.03, p = 0.001), but not in ME/CFS patients without infection-triggered onset (PTPN22 rs2476601: OR 1.09, CI 0.56-2.14, p = 0.398; CTLA4 rs3087243: OR 0.89, CI 0.61-1.30, p = 0.268). This finding provides evidence that autoimmunity might play a role in ME/CFS with an infection-triggered onset. Both genes play a key role in regulating B and T cell activation.

Source: Steiner S, Becker SC, Hartwig J, Sotzny F, Lorenz S, Bauer S, Löbel M, Stittrich AB, Grabowski P, Scheibenbogen C. Autoimmunity-Related Risk Variants in PTPN22 and CTLA4 Are Associated With ME/CFS With Infectious Onset. Front Immunol. 2020 Apr 9;11:578. doi: 10.3389/fimmu.2020.00578. eCollection 2020. https://www.ncbi.nlm.nih.gov/pubmed/32328064

Assessing diagnostic value of microRNAs from peripheral blood mononuclear cells and extracellular vesicles in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating multisystemic disease of unknown etiology, affecting thousands of individuals worldwide. Its diagnosis still relies on ruling out medical problems leading to unexplained fatigue due to a complete lack of disease-specific biomarkers. Our group and others have explored the potential value of microRNA profiles (miRNomes) as diagnostic tools for this disease. However, heterogeneity of participants, low numbers, the variety of samples assayed, and other pre-analytical variables, have hampered the identification of disease-associated miRNomes.

In this study, our team has evaluated, for the first time, ME/CFS miRNomes in peripheral blood mononuclear cells (PBMCs) and extracellular vesicles (EVs) from severely ill patients recruited at the monographic UK ME biobank to assess, using standard operating procedures (SOPs), blood fractions with optimal diagnostic power for a rapid translation of a miR-based diagnostic method into the clinic.

Our results show that routine creatine kinase (CK) blood values, plasma EVs physical characteristics (including counts, size and zeta-potential), and a limited number of differentially expressed PBMC and EV miRNAs appear significantly associated with severe ME/CFS (p < 0.05). Gene enrichment analysis points to epigenetic and neuroimmune dysregulated pathways, in agreement with previous reports. Population validation by a cost-effective approach limited to these few potentially discriminating variables is granted.

Source: Almenar-Pérez E, Sarría L, Nathanson L, Oltra E. Assessing diagnostic value of microRNAs from peripheral blood mononuclear cells and extracellular vesicles in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Sci Rep. 2020 Feb 7;10(1):2064. doi: 10.1038/s41598-020-58506-5. https://www.nature.com/articles/s41598-020-58506-5 (Full text)

Epigenetic Components of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Uncover Potential Transposable Element Activation

Abstract:

PURPOSE: Studies to determine epigenetic changes associated with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) remain scarce; however, current evidence clearly shows that methylation patterns of genomic DNA and noncoding RNA profiles of immune cells differ between patients and healthy subjects, suggesting an active role of these epigenetic mechanisms in the disease. The present study compares and contrasts the available ME/CFS epigenetic data in an effort to evidence overlapping pathways capable of explaining at least some of the dysfunctional immune parameters linked to this disease.

METHODS: A systematic search of the literature evaluating the ME/CFS epigenome landscape was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria. Differential DNA methylation and noncoding RNA differential expression patterns associated with ME/CFS were used to screen for the presence of transposable elements using the Dfam browser, a search program nurtured with the Repbase repetitive sequence database and the RepeatMasker annotation tool.

FINDINGS: Unexpectedly, particular associations of transposable elements and ME/CFS epigenetic hallmarks were uncovered. A model for the disease emerged involving transcriptional induction of endogenous dormant transposons and structured cellular RNA interactions, triggering the activation of the innate immune system without a concomitant active infection.

IMPLICATIONS: Repetitive sequence filters (ie, RepeatMasker) should be avoided when analyzing transcriptomic data to assess the potential participation of repetitive sequences (“junk repetitive DNA”), representing >45% of the human genome, in the onset and evolution of ME/CFS. In addition, transposable element screenings aimed at designing cost-effective, focused empirical assays that can confirm or disprove the suspected involvement of transposon transcriptional activation in this disease, following the pilot strategy presented here, will require databases gathering large ME/CFS epigenetic datasets.

Copyright © 2019. Published by Elsevier Inc.

Source: Almenar-Pérez E, Ovejero T, Sánchez-Fito T, Espejo JA, Nathanson L, Oltra E. Epigenetic Components of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Uncover Potential Transposable Element Activation. Clin Ther. 2019 Mar 22. pii: S0149-2918(19)30072-4. doi: 10.1016/j.clinthera.2019.02.012. [Epub ahead of print] https://www.ncbi.nlm.nih.gov/pubmed/30910331

Impact of Polypharmacy on Candidate Biomarker miRNomes for the Diagnosis of Fibromyalgia and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Striking Back on Treatments

Abstract:

Fibromyalgia (FM) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) are diseases of unknown etiology presenting complex and often overlapping symptomatology. Despite promising advances on the study of miRNomes of these diseases, no validated molecular diagnostic biomarker yet exists. Since FM and ME/CFS patient treatments commonly include polypharmacy, it is of concern that biomarker miRNAs are masked by drug interactions.

Aiming at discriminating between drug-effects and true disease-associated differential miRNA expression, we evaluated the potential impact of commonly prescribed drugs on disease miRNomes, as reported by the literature. By using the web search tools SM2miR, Pharmaco-miR, and repoDB, we found a list of commonly prescribed drugs that impact FM and ME/CFS miRNomes and therefore could be interfering in the process of biomarker discovery. On another end, disease-associated miRNomes may incline a patient’s response to treatment and toxicity.

Here, we explored treatments for diseases in general that could be affected by FM and ME/CFS miRNomes, finding a long list of them, including treatments for lymphoma, a type of cancer affecting ME/CFS patients at a higher rate than healthy population. We conclude that FM and ME/CFS miRNomes could help refine pharmacogenomic/pharmacoepigenomic analysis to elevate future personalized medicine and precision medicine programs in the clinic.

Source: Almenar-Pérez E, Sánchez-Fito T, Ovejero T, Nathanson L, Oltra E. Impact of Polypharmacy on Candidate Biomarker miRNomes for the Diagnosis of Fibromyalgia and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Striking Back on Treatments. Pharmaceutics. 2019 Mar 18;11(3). pii: E126. doi: 10.3390/pharmaceutics11030126. https://www.mdpi.com/1999-4923/11/3/126 (Full article)

 

Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome

Abstract:

BACKGROUND: Both of the modern medicine and the traditional Chinese medicine classify depressive disorder (DD) and chronic fatigue syndrome (CFS) to one type of disease. Unveiling the association between depressive and the fatigue diseases provides a great opportunity to bridge the modern medicine with the traditional Chinese medicine.

METHODS: In this work, 295 general participants were recruited to complete Zung Self-Rating Depression Scales and Chalder Fatigue Scales, and meanwhile, to donate plasma and urine samples for 1H NMR-metabolic profiling. Artificial intelligence methods was used to analysis the underlying association between DD and CFS. Principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyze the metabolic profiles with respect to gender and age. Variable importance in projection and t-test were employed in conjunction with the PLS-DA models to identify the metabolite biomarkers. Considering the asymmetry and complexity of the data, convolutional neural networks (CNN) model, an artificial intelligence method, was built to analyze the data characteristics between each groups.

RESULTS: The results showed the gender- and age-related differences for the candidate biomarkers of the DD and the CFS diseases, and indicated the same and different biomarkers of the two diseases. PCA analysis for the data characteristics reflected that DD and CFS was separated completely in plasma metabolite. However, DD and CFS was merged into one group.

LIMITATION: Lack of transcriptomic analysis limits the understanding of the association of the DD and the CFS diseases on gene level.

CONCLUSION: The unmasked candidate biomarkers provide reliable evidence to explore the commonality and differences of the depressive and the fatigue diseases, and thereby, bridge over the traditional Chinese medicine with the modern medicine.

Copyright © 2019 Elsevier B.V. All rights reserved.

Source: Zhang F, Wu C, Jia C, Gao K, Wang J, Zhao H, Wang W, Chen J. Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome. J Affect Disord. 2019 Mar 8;250:380-390. doi: 10.1016/j.jad.2019.03.011. [Epub ahead of print]

Associations between clinical symptoms, plasma norepinephrine and deregulated immune gene networks in subgroups of adolescent with Chronic Fatigue Syndrome

Abstract:

BACKGROUND: Chronic fatigue syndrome (CFS) is one of the most important causes of disability among adolescents while limited knowledge exists on genetic determinants underlying disease pathophysiology.

METHODS: We analyzed deregulated immune-gene modules using Pathifier software on whole blood gene expression data (29 CFS patients, 18 controls). Deconvolution of immune cell subtypes based on gene expression profile was performed using CIBERSORT. Supervised consensus clustering on pathway deregulation score (PDS) was used to define CFS subgroups. Associations between PDS and immune, neuroendocrine/autonomic and clinical markers were examined. The impact of plasma norepinephrine level on clinical markers over time was assessed in a larger cohort (91 patients).

RESULTS: A group of 29 immune-gene sets was shown to differ patients from controls and detect subgroups within CFS. Group 1P (high PDS, low norepinephrine, low naïve CD4+ composition) had strong association with levels of serum C-reactive protein and Transforming Growth Factor-beta. Group 2P (low PDS, high norepinephrine, high naïve CD4+ composition) had strong associations with neuroendocrine/autonomic markers. The corresponding plasma norepinephrine level delineated 91 patients into two subgroups with significant differences in fatigue score.

CONCLUSION: We identified 29 immune-gene sets linked to plasma norepinephrine level that could delineate CFS subgroups. Plasma norepinephrine stratification revealed that lower levels of norepinephrine were associated with higher fatigue. Our data suggests potential involvement of neuro-immune dysregulation and genetic stratification in CFS.

Copyright © 2018. Published by Elsevier Inc.

Source: Nguyen CB, Kumar S, Zucknick M, Kristensen VN, Gjerstad J, Nilsen H, Wyller VB. Associations between clinical symptoms, plasma norepinephrine and deregulated immune gene networks in subgroups of adolescent with Chronic Fatigue Syndrome. Brain Behav Immun. 2018 Nov 9. pii: S0889-1591(18)30796-7. doi: 10.1016/j.bbi.2018.11.008. [Epub ahead of print] https://www.ncbi.nlm.nih.gov/pubmed/30419269

Integration of DNA methylation & health scores identifies subtypes in myalgic encephalomyelitis/chronic fatigue syndrome

Abstract:

AIM: To identify subtypes in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) based on DNA methylation profiles and health scores.

METHODS: DNA methylome profiles in immune cells were integrated with symptomatology from 70 women with ME/CFS using similarity network fusion to identify subtypes.

RESULTS: We discovered four ME/CFS subtypes associated with DNA methylation modifications in 1939 CpG sites, three RAND-36 categories and five DePaul Symptom Questionnaire measures. Methylation patterns of immune response genes and differences in physical functioning and postexertional malaise differentiated the subtypes.

CONCLUSION: ME/CFS subtypes are associated with specific DNA methylation differences and health symptomatology and provide additional evidence of the potential relevance of metabolic and immune differences in ME/CFS with respect to specific symptoms.

Source: de Vega WC, Erdman L, Vernon SD, Goldenberg A, McGowan PO. Integration of DNA methylation & health scores identifies subtypes in myalgic encephalomyelitis/chronic fatigue syndrome. Epigenomics. 2018 Apr 25. doi: 10.2217/epi-2017-0150. [Epub ahead of print] https://www.ncbi.nlm.nih.gov/pubmed/29692205

Glucocorticoid receptor DNA methylation and childhood trauma in chronic fatigue syndrome patient

Abstract:

OBJECTIVE: Although the precise mechanisms are not yet understood, previous studies have suggested that chronic fatigue syndrome(CFS) is associated with hypothalamic-pituitary-adrenal (HPA) axis dysregulation and trauma in early childhood. Consistent with findings suggesting that early life stress-induced DNA methylation changes may underlie dysregulation of the HPA axis, we previously found evidence for the involvement of glucocorticoid receptor (GR) gene (NR3C1) methylation in whole blood of CFS patients.

METHODS: In the current study, we assessed NR3C1-1F region DNA methylation status in peripheral blood from a new and independent sample of 80 female CFS patients and 91 female controls. In CFS patients, history of childhood trauma subtypes was evaluated using the Childhood Trauma Questionnaire short form (CTQ-SF).

RESULTS: Although absolute methylation differences were small, the present study confirms our previous findings of NR3C1-1F DNA hypomethylation at several CpG sites in CFS patients as compared to controls. Following multiple testing correction, only CpG_8 remained significant (DNA methylation difference: 1.3% versus 1.5%, p<0.001). In addition, we found associations between DNA methylation and severity of fatigue as well as with childhood emotional abuse in CFS patients, although these findings were not significant after correction for multiple testing.

CONCLUSIONS: In conclusion, we replicated findings of NR3C1-1F DNA hypomethylation in CFS patients versus controls. Our results support the hypothesis of HPA axis dysregulation and enhanced GR sensitivity in CFS.

Copyright © 2017 Elsevier Inc. All rights reserved.

Source: Vangeel EB, Kempke S, Bakusic J, Godderis L, Luyten P, Van Heddegem L, Compernolle V, Persoons P, Lambrechts D, Izzi B, Freson K, Claes S. Glucocorticoid receptor DNA methylation and childhood trauma in chronic fatigue syndrome patients. J Psychosom Res. 2018 Jan;104:55-60. doi: 10.1016/j.jpsychores.2017.11.011. Epub 2017 Nov 20. https://www.ncbi.nlm.nih.gov/pubmed/29275786

Genome-Epigenome Interactions Associated with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is an example of a complex disease of unknown etiology. Multiple studies point to disruptions in immune functioning in ME/CFS patients as well as with specific genetic polymorphisms and alterations of the DNA methylome in lymphocytes. However, the association between DNA methylation and genetic background in relation to the ME/CFS is currently unknown.

In this study we explored this association by characterizing the genomic (~4.3 million SNPs) and epigenomic (~480 thousand CpG loci) variability between populations of ME/CFS patients and healthy controls. We found significant associations of methylation states in T-lymphocytes at several CpG loci and regions with ME/CFS phenotype. These methylation anomalies are in close proximity to genes involved with immune function and cellular metabolism.

Finally, we found significant correlations of genotypes with methylation phenotypes associated with ME/CFS. The findings from this study highlight the role of epigenetic and genetic interactions in complex diseases, and suggest several genetic and epigenetic elements potentially involved in the mechanisms of disease in ME/CFS.

Source: Santiago Herrera, Wilfred C. de Vega, David Ashbrook, Suzanne D. Vernon, Patrick O. McGowan. Genome-Epigenome Interactions Associated with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. bioRxiv preprint first posted online Dec. 22, 2017; doi: http://dx.doi.org/10.1101/237958. (Full article)

The epigenetic landscape of myalgic encephalomyelitis/chronic fatigue syndrome: deciphering complex phenotypes

By their very nature, complex disease phenotypes are characterized by the dysregulation of multiple physiological systems, polygenic origins and various environmental triggers that result in patient populations with heterogeneous symptom profiles. Less than 10% of the heritability of complex phenotypes and disease traits are due to genetic variation, indicating that other factors play major roles in disease onset and progression [1]. Epigenetic modifications may partly account for this ‘missing heritability’ [2] through mechanisms that regulate transcriptional potential. These mechanisms appear to be, at least to some extent, responsive to environmental exposures or treatments. An improved understanding of the pathophysiology underlying complex phenotypes and new diagnostic tools can help refine and update classification criteria reliant on nonspecific or self-reported symptoms. Consequently, unraveling complex phenotypes depends to a large extent upon an ability to discriminate what are likely many distinct conditions. We and others have argued that epigenetic investigations integrate multiple levels of information (genetic, stochastic and environmental) to enable a better understanding of the dimensions of illness underlying complex phenotypes [2,3]. Here, we turn to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) to illustrate progress and future directions in this regard.

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Source: de Vega WC, McGowan PO. The epigenetic landscape of myalgic encephalomyelitis/chronic fatigue syndrome: deciphering complex phenotypes. Epigenomics. 2017 Nov;9(11):1337-1340. doi: 10.2217/epi-2017-0106. Epub 2017 Oct 18. https://www.futuremedicine.com/doi/full/10.2217/epi-2017-0106 (Full article)