Category: Genetics

Clinically proven mtDNA mutations are not common in those with chronic fatigue syndrome

Abstract:

Background: Chronic Fatigue Syndrome (CFS) is a prevalent debilitating condition that affects approximately 250,000 people in the UK. There is growing interest in the role of mitochondrial function and mitochondrial DNA (mtDNA) variation in CFS. It is now known that fatigue is common and often severe in patients with mitochondrial disease irrespective of their age, gender or mtDNA genotype. More recently, it has been suggested that some CFS patients harbour clinically proven mtDNA mutations.

Methods: MtDNA sequencing of 93 CFS patients from the United Kingdom (UK) and South Africa (RSA) was performed using an Ion Torrent Personal Genome Machine. The sequence data was examined for any evidence of clinically proven mutations, currently; more than 200 clinically proven mtDNA mutations point mutations have been identified.

Results: We report the complete mtDNA sequence of 93 CFS patients from the UK and RSA, without finding evidence of clinically proven mtDNA mutations. This finding demonstrates that clinically proven mtDNA mutations are not a common element in the aetiology of disease in CFS patients. That is patients having a clinically proven mtDNA mutation and subsequently being misdiagnosed with CFS are likely to be rare.

Conclusion: The work supports the assertion that CFS should not be considered to fall within the spectrum of mtDNA disease. However, the current study cannot exclude a role for nuclear genes with a mitochondrial function, nor a role of mtDNA population variants in susceptibility to disease. This study highlights the need for more to be done to understand the pathophysiology of CFS.

Source: Schoeman EM, Van Der Westhuizen FH, Erasmus E, van Dyk E, Knowles CV, Al-Ali S, Ng WF, Taylor RW, Newton JL, Elson JL. Clinically proven mtDNA mutations are not common in those with chronic fatigue syndrome. BMC Med Genet. 2017 Mar 16;18(1):29. doi: 10.1186/s12881-017-0387-6. PMID: 28302057; PMCID: PMC5356238. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5356238/ (Full text)

Meet The Scientist: A conversation with Professor Chris Ponting

Professor Chris Ponting is Chair of Medical Bioinformatics at Edinburgh University and a Principal Investigator at the MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine. His research group has made substantial contributions to protein science, evolutionary biology, genetics and genomics. He has served on the editorial boards of numerous medical journals including Genome Research, Genome Biology, Human Molecular Genetics, Annual Review of Genomics and Human Genetics and Trends in Genetics. He is a Fellow of the Academy of Medical Sciences and is Principal Investigator for the Decode ME study over the next 4 years.

Professor Ponting took time out from his busy schedule to talk about the Decode ME study that seeks to understand the causes of ME. In turn, this should help with the discovery of effective treatments for ME which are so desperately needed.

The study will be the largest ever biomedical study of ME as it needs 20,000 participants. If you would like to register an interest in participating in the study then please use the link below.

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Read the rest of this interview HERE. 

Source: ME Association. July 29, 2020

Re-analysis of genetic risks for Chronic Fatigue Syndrome from 23andMe data finds few remain

Abstract:

It is tempting to mine the abundance of DNA data that is now available from direct-to-consumer genetic tests but this approach also has its pitfalls A recent study put forth a list of 50 single nucleotide polymorphisms (SNPs) that predispose to Chronic Fatigue Syndrome (CFS), a potentially major advance in understanding this still mysterious condition. However, only the patient cohort data came from a commercial company (23andMe) while the control was from a genetic database. The extent to which 23andMe data agree with genetic reference databases is unknown.

We reanalyzed the 50 purported CFS SNPs by comparing to control data specifically from 23andMe which are available through public platform OpenSNP. In addition, large high-quality database ALFA was used as an additional control. The analysis lead to dramatic change with the top of the leaderboard for CFS risk reduced and reversed from an astronomical 129,000 times to 0.8. Errors were found both within 23andMe data and the original study-reported Kaviar database control. Only 3 of 50 SNPs survived initial study criterion of at least twice as prevalent in patients, EFCAB4B, involved in calcium ion channel activation, LINC01171, and MORN2 genes.

We conclude that the reported top-50 deleterious polymorphisms for Chronic Fatigue Syndrome were more likely the top-50 errors in the 23andMe and Kaviar databases. In general, however, correlation of 23andMe control with ALFA was a respectable 0.93, suggesting an overall usefulness of 23andMe results for research purposes but only if caution is taken with chips and SNPs.

Source: Felice L. Bedford, Bastian Greshake Tzovaras. Re-analysis of genetic risks for Chronic Fatigue Syndrome from 23andMe data finds few remain. medRxiv 2020.10.27.20220939; doi: https://doi.org/10.1101/2020.10.27.20220939
Now published in Frontiers in Pediatrics doi: 10.3389/fped.2021.590040 https://www.medrxiv.org/content/10.1101/2020.10.27.20220939v2.full-text (Full text)

Recursive ensemble feature selection provides a robust mRNA expression signature for myalgic encephalomyelitis/chronic fatigue syndrome

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic disorder characterized by disabling fatigue. Several studies have sought to identify diagnostic biomarkers, with varying results. Here, we innovate this process by combining both mRNA expression and DNA methylation data. We performed recursive ensemble feature selection (REFS) on publicly available mRNA expression data in peripheral blood mononuclear cells (PBMCs) of 93 ME/CFS patients and 25 healthy controls, and found a signature of 23 genes capable of distinguishing cases and controls.

REFS highly outperformed other methods, with an AUC of 0.92. We validated the results on a different platform (AUC of 0.95) and in DNA methylation data obtained from four public studies on ME/CFS (99 patients and 50 controls), identifying 48 gene-associated CpGs that predicted disease status as well (AUC of 0.97). Finally, ten of the 23 genes could be interpreted in the context of the derailed immune system of ME/CFS.

Source: Metselaar, P.I., Mendoza-Maldonado, L., Li Yim, A.Y.F. et al. Recursive ensemble feature selection provides a robust mRNA expression signature for myalgic encephalomyelitis/chronic fatigue syndrome. Sci Rep 11, 4541 (2021). https://doi.org/10.1038/s41598-021-83660-9 https://www.nature.com/articles/s41598-021-83660-9 (Full text)

Informatics Inference of Exercise-Induced Modulation of Brain Pathways Based on Cerebrospinal Fluid Micro-RNAs in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Introduction: The post-exertional malaise of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) was modeled by comparing micro-RNA (miRNA) in cerebrospinal fluid from subjects who had no exercise versus submaximal exercise.

Materials and Methods: Differentially expressed miRNAs were examined by informatics methods to predict potential targets and regulatory pathways affected by exercise.

Results: miR-608, miR-328, miR-200a-5p, miR-93-3p, and miR-92a-3p had higher levels in subjects who rested overnight (nonexercise n=45) compared to subjects who had exercised before their lumbar punctures (n=15). The combination was examined in DIANA MiRpath v3.0, TarBase, Cytoscape, and Ingenuity software® to select the intersection of target mRNAs. DIANA found 33 targets that may be elevated after exercise, including TGFBR1, IGFR1, and CDC42. Adhesion and adherens junctions were the most frequent pathways. Ingenuity selected seven targets that had complementary mechanistic pathways involving GNAQ, ADCY3, RAP1B, and PIK3R3. Potential target cells expressing high levels of these genes included choroid plexus, neurons, and microglia.

Conclusion: The reduction of this combination of miRNAs in cerebrospinal fluid after exercise suggested upregulation of phosphoinositol signaling pathways and altered adhesion during the post-exertional malaise of ME/CFS.

Clinical Trial Registration Nos.: NCT01291758 and NCT00810225.

Source: Narayan V, Shivapurkar N, Baraniuk JN. Informatics Inference of Exercise-Induced Modulation of Brain Pathways Based on Cerebrospinal Fluid Micro-RNAs in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Netw Syst Med. 2020 Nov 18;3(1):142-158. doi: 10.1089/nsm.2019.0009. PMID: 33274349; PMCID: PMC7703497.  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7703497/ (Full text)

Changes in DNA methylation profiles of myalgic encephalomyelitis/chronic fatigue syndrome patients reflect systemic dysfunctions

Abstract:

Background: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a lifelong debilitating disease with a complex pathology not yet clearly defined. Susceptibility to ME/CFS involves genetic predisposition and exposure to environmental factors, suggesting an epigenetic association. Epigenetic studies with other ME/CFS cohorts have used array-based technology to identify differentially methylated individual sites. Changes in RNA quantities and protein abundance have been documented in our previous investigations with the same ME/CFS cohort used for this study.

Results: DNA from a well-characterised New Zealand cohort of 10 ME/CFS patients and 10 age-/sex-matched healthy controls was isolated from peripheral blood mononuclear (PBMC) cells, and used to generate reduced genome-scale DNA methylation maps using reduced representation bisulphite sequencing (RRBS). The sequencing data were analysed utilising the DMAP analysis pipeline to identify differentially methylated fragments, and the MethylKit pipeline was used to quantify methylation differences at individual CpG sites. DMAP identified 76 differentially methylated fragments and Methylkit identified 394 differentially methylated cytosines that included both hyper- and hypo-methylation. Four clusters were identified where differentially methylated DNA fragments overlapped with or were within close proximity to multiple differentially methylated individual cytosines. These clusters identified regulatory regions for 17 protein encoding genes related to metabolic and immune activity. Analysis of differentially methylated gene bodies (exons/introns) identified 122 unique genes. Comparison with other studies on PBMCs from ME/CFS patients and controls with array technology showed 59% of the genes identified in this study were also found in one or more of these studies. Functional pathway enrichment analysis identified 30 associated pathways. These included immune, metabolic and neurological-related functions differentially regulated in ME/CFS patients compared to the matched healthy controls.

Conclusions: Major differences were identified in the DNA methylation patterns of ME/CFS patients that clearly distinguished them from the healthy controls. Over half found in gene bodies with RRBS in this study had been identified in other ME/CFS studies using the same cells but with array technology. Within the enriched functional immune, metabolic and neurological pathways, a number of enriched neurotransmitter and neuropeptide reactome pathways highlighted a disturbed neurological pathophysiology within the patient group.

Source: Helliwell AM, Sweetman EC, Stockwell PA, Edgar CD, Chatterjee A, Tate WP. Changes in DNA methylation profiles of myalgic encephalomyelitis/chronic fatigue syndrome patients reflect systemic dysfunctions. Clin Epigenetics. 2020 Nov 4;12(1):167. doi: 10.1186/s13148-020-00960-z. PMID: 33148325; PMCID: PMC7641803. https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-020-00960-z  (Full study)

Re-analysis of genetic risks for Chronic Fatigue Syndrome from 23andMe data finds few remain

Abstract:

It is tempting to mine the abundance of DNA data that is now available from direct-to-consumer genetic tests, but this approach has its pitfalls A recent study put forth a list of 50 single nucleotide polymorphisms (SNPs) that predispose to Chronic Fatigue Syndrome (CFS), a potentially major advance in understanding this still mysterious disease. However, only the patient cohort data came from a commercial company (23andMe) while the control was a genetic database. The extent to which 23andMe data agree with genetic reference databases is unknown. We reanalyzed the 50 purported CFS SNPs by comparing to control data from 23andMe which are available through public platform OpenSNP. In addition, large high-quality database ALFA was used as an additional control. The analysis lead to dramatic change with the top of the leaderboard for CFS risk reduced and reversed from an astronomical 129,000 times to 0.8.

Errors were found both within 23andMe data and the original study-reported Kaviar database control. Only 3 of 50 SNPs survived initial study criterion of at least twice as prevalent in patients, EFCAB4B involving calcium ion channel, LINC01171, and MORN2 genes. We conclude the reported top-50 deleterious polymorphisms for Chronic Fatigue Syndrome were more likely the top-50 errors in the 23andMe and Kaviar databases. In general, however, correlation of 23andMe control with ALFA was a respectable 0.93, suggesting an overall usefulness of 23andMe results for research purposes but only if caution is taken with chips and SNPs.

Source: Felice L Bedford, Bastian Greshake Tzovaras. Re-analysis of genetic risks for Chronic Fatigue Syndrome from 23andMe data finds few remain. Frontiers in Pediatrics, October 29. 2020. https://www.medrxiv.org/content/10.1101/2020.10.27.20220939v1.full.pdf+html  (Full study)

Early Growth Response Gene Upregulation in Epstein-Barr Virus (EBV)-Associated Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic multisystem disease exhibiting a variety of symptoms and affecting multiple systems. Psychological stress and virus infection are important. Virus infection may trigger the onset, and psychological stress may reactivate latent viruses, for example, Epstein-Barr virus (EBV). It has recently been reported that EBV induced gene 2 (EBI2) was upregulated in blood in a subset of ME/CFS patients. The purpose of this study was to determine whether the pattern of expression of early growth response (EGR) genes, important in EBV infection and which have also been found to be upregulated in blood of ME/CFS patients, paralleled that of EBI2.

EGR gene upregulation was found to be closely associated with that of EBI2 in ME/CFS, providing further evidence in support of ongoing EBV reactivation in a subset of ME/CFS patients. EGR1, EGR2, and EGR3 are part of the cellular immediate early gene response and are important in EBV transcription, reactivation, and B lymphocyte transformation. EGR1 is a regulator of immune function, and is important in vascular homeostasis, psychological stress, connective tissue disease, mitochondrial function, all of which are relevant to ME/CFS. EGR2 and EGR3 are negative regulators of T lymphocytes and are important in systemic autoimmunity.

Source: Kerr J. Early Growth Response Gene Upregulation in Epstein-Barr Virus (EBV)-Associated Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). Biomolecules. 2020 Oct 26;10(11):E1484. doi: 10.3390/biom10111484. PMID: 33114612. https://www.mdpi.com/2218-273X/10/11/1484  (Full text)

Substrate utilisation of cultured skeletal muscle cells in patients with CFS

Abstract:

Chronic fatigue syndrome (CFS) patients often suffer from severe muscle pain and an inability to exercise due to muscle fatigue. It has previously been shown that CFS skeletal muscle cells have lower levels of ATP and have AMP-activated protein kinase dysfunction. This study outlines experiments looking at the utilisation of different substrates by skeletal muscle cells from CFS patients (n = 9) and healthy controls (n = 11) using extracellular flux analysis.

Results show that CFS skeletal muscle cells are unable to utilise glucose to the same extent as healthy control cells. CFS skeletal muscle cells were shown to oxidise galactose and fatty acids normally, indicating that the bioenergetic dysfunction lies upstream of the TCA cycle. The dysfunction in glucose oxidation is similar to what has previously been shown in blood cells from CFS patients.

The consistency of cellular bioenergetic dysfunction in different cell types supports the hypothesis that CFS is a systemic disease. The retention of bioenergetic defects in cultured cells indicates that there is a genetic or epigenetic component to the disease. This is the first study to use cells derived from skeletal muscle biopsies in CFS patients and healthy controls to look at cellular bioenergetic function in whole cells.

Source: Tomas C, Elson JL, Newton JL, Walker M. Substrate utilisation of cultured skeletal muscle cells in patients with CFS. Sci Rep. 2020 Oct 26;10(1):18232. doi: 10.1038/s41598-020-75406-w. PMID: 33106563.  https://www.nature.com/articles/s41598-020-75406-w (Full text)

Genetic Risk Factors of ME/CFS: A Critical Review

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex multisystem illness that lacks effective therapy and a biomedical understanding of its causes. Despite a prevalence of approximately 0.2-0.4% and its high public health burden, and evidence that it has a heritable component, ME/CFS has not yet benefited from the advances in technology and analytical tools that have improved our understanding of many other complex diseases.

Here we critically review existing evidence that genetic factors alter ME/CFS risk before concluding that most ME/CFS candidate gene associations are not replicated by the larger CFS cohort within UK Biobank. Multiple genome-wide association studies of this cohort also have not yielded consistently significant associations. Ahead of upcoming larger genome-wide association studies we discuss how these could generate new lines of enquiry into the DNA variants, genes and cell-types that are causally involved in ME/CFS disease.

Source: Dibble JJ, McGrath SJ, Ponting CP. Genetic Risk Factors of ME/CFS: A Critical Review [published online ahead of print, 2020 Aug 3]. Hum Mol Genet. 2020;ddaa169. doi:10.1093/hmg/ddaa169 https://pubmed.ncbi.nlm.nih.gov/32744306/