A Network Medicine Approach to Investigating ME/CFS Pathogenesis in Severely Ill Patients: A Pilot Study

Abstract:

This pilot study harnessed the power of network medicine to unravel the complex pathogenesis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). By utilizing a network analysis on whole genome sequencing (WGS) data from the Severely Ill Patient Study (SIPS), we identified ME/CFS-associated proteins and delineated the corresponding network-level module, termed the SIPS disease module, together with its relevant pathways. This module demonstrated significant overlap with genes implicated in fatigue, cognitive disorders, and neurodegenerative diseases.

Our pathway analysis revealed potential associations between ME/CFS and conditions such as COVID-19, Epstein-Barr virus (EBV) infection, neurodegenerative diseases, and pathways involved in cortisol synthesis and secretion, supporting the hypothesis that ME/CFS is a neuroimmune disorder. Additionally, our findings underscore a potential link between ME/CFS and estrogen signaling pathways, which may elucidate the higher prevalence of ME/CFS in females.

These findings provide insights into the pathogenesis of ME/CFS from a network medicine perspective and highlight potential therapeutic targets. Further research is needed to validate these findings and explore their implications for improving diagnosis and treatment.

Source: Li-Yuan Hung, Chan-Shuo Wu, Chia-Jung Chang, Peng Li, Kimberly Hicks, Becky Taurog, Joshua J Dibble, Braxton Morrison, Chimere L Smith, Ronald W Davis, Wenzhong Xiao. A Network Medicine Approach to Investigating ME/CFS Pathogenesis in Severely Ill Patients: A Pilot Study.
medRxiv 2024.09.26.24314417; doi: https://doi.org/10.1101/2024.09.26.24314417 https://www.medrxiv.org/content/10.1101/2024.09.26.24314417v1 (Full text available as PDF file)

Genome-wide Association Study of Long COVID

Abstract:

Infections can lead to persistent or long-term symptoms and diseases such as shingles after varicella zoster, cancers after human papillomavirus, or rheumatic fever after streptococcal infections(1,2). Similarly, infection by SARS-CoV-2 can result in Long COVID, a condition characterized by symptoms of fatigue and pulmonary and cognitive dysfunction(3-5). The biological mechanisms that contribute to the development of Long COVID remain to be clarified.

We leveraged the COVID-19 Host Genetics Initiative(6,7) to perform a genome-wide association study for Long COVID including up to 6,450 Long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We identified the first genome-wide significant association for Long COVID at the FOXP4 locus. FOXP4 has been previously associated with COVID-19 severity(6), lung function(8), and cancers(9), suggesting a broader role for lung function in the pathophysiology of Long COVID.

While we identify COVID-19 severity as a causal risk factor for Long COVID, the impact of the genetic risk factor located in the FOXP4 locus could not be solely explained by its association to severe COVID-19. Our findings further support the role of pulmonary dysfunction and COVID-19 severity in the development of Long COVID.

Source: Vilma LammiTomoko NakanishiSamuel E. JonesShea J. AndrewsJuha KarjalainenBeatriz CortésHeath E. O’BrienBrian E. Fulton-HowardHele H. HaapaniemiAxel SchmidtRuth E. MitchellAbdou MousasMassimo ManginoAlicia Huerta-ChagoyaNasa Sinnott-ArmstrongElizabeth T. CirulliMarc VaudelAlex S.F. KwongAmit K. MaitiMinttu MarttilaChiara BatiniFrancesca MinnaiAnna R. DearmanC.A. Robert WarmerdamCelia B. SequerosThomas W. WinklerDaniel M. JordanLindsay GuareEkaterina VergasovaEirini MarouliPasquale StrianoUmmu Afeera ZainulabidAshutosh KumarHajar Fauzan AhmadRyuya EdahiroShuhei AzekawaLong COVID Host Genetics InitiativeFinnGenDBDS Genomic ConsortiumGEN-COVID Multicenter StudyJoseph J. GrzymskiMakoto IshiiYukinori OkadaNoam D. BeckmannMeena KumariRalf WagnerIris M. HeidCatherine JohnPatrick J. ShortPer MagnusKarina BanasikFrank GellerLude H. FrankeAlexander RakitkoEmma L. DuncanAlessandra RenieriKonstantinos K. TsilidisRafael de CidAhmadreza NiavaraniTeresa Tusié-LunaShefali S. VermaGeorge Davey SmithNicholas J. TimpsonMark J. DalyAndrea GannaEva C. SchulteJ. Brent RichardsKerstin U. LudwigMichael HultströmHugo ZebergHanna M. Ollila. Genome-wide Association Study of Long COVID. https://www.medrxiv.org/content/10.1101/2023.06.29.23292056v1.full-text (Full text)

SARS-CoV-2 infection induces DNA damage, through CHK1 degradation and impaired 53BP1 recruitment, and cellular senescence

Abstract:

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Although SARS-CoV-2 was reported to alter several cellular pathways, its impact on DNA integrity and the mechanisms involved remain unknown. Here we show that SARS-CoV-2 causes DNA damage and elicits an altered DNA damage response.

Mechanistically, SARS-CoV-2 proteins ORF6 and NSP13 cause degradation of the DNA damage response kinase CHK1 through proteasome and autophagy, respectively. CHK1 loss leads to deoxynucleoside triphosphate (dNTP) shortage, causing impaired S-phase progression, DNA damage, pro-inflammatory pathways activation and cellular senescence. Supplementation of deoxynucleosides reduces that. Furthermore, SARS-CoV-2 N-protein impairs 53BP1 focal recruitment by interfering with damage-induced long non-coding RNAs, thus reducing DNA repair.

Key observations are recapitulated in SARS-CoV-2-infected mice and patients with COVID-19. We propose that SARS-CoV-2, by boosting ribonucleoside triphosphate levels to promote its replication at the expense of dNTPs and by hijacking damage-induced long non-coding RNAs’ biology, threatens genome integrity and causes altered DNA damage response activation, induction of inflammation and cellular senescence.

Source: Gioia U, Tavella S, Martínez-Orellana P, Cicio G, Colliva A, Ceccon M, Cabrini M, Henriques AC, Fumagalli V, Paldino A, Presot E, Rajasekharan S, Iacomino N, Pisati F, Matti V, Sepe S, Conte MI, Barozzi S, Lavagnino Z, Carletti T, Volpe MC, Cavalcante P, Iannacone M, Rampazzo C, Bussani R, Tripodo C, Zacchigna S, Marcello A, d’Adda di Fagagna F. SARS-CoV-2 infection induces DNA damage, through CHK1 degradation and impaired 53BP1 recruitment, and cellular senescence. Nat Cell Biol. 2023 Mar 9. doi: 10.1038/s41556-023-01096-x. Epub ahead of print. PMID: 36894671. https://www.nature.com/articles/s41556-023-01096-x (Full text)

DecodeME: community recruitment for a large genetics study of myalgic encephalomyelitis / chronic fatigue syndrome

Abstract:

Background: Myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS) is a common, long-term condition characterised by post-exertional malaise, often with fatigue that is not significantly relieved by rest. ME/CFS has no confirmed diagnostic test or effective treatment and we lack knowledge of its causes. Identification of genes and cellular processes whose disruption adds to ME/CFS risk is a necessary first step towards development of effective therapy.

Methods: Here we describe DecodeME, an ongoing study co-produced by people with lived experience of ME/CFS and scientists. Together we designed the study and obtained funding and are now recruiting up to 25,000 people in the UK with a clinical diagnosis of ME/CFS. Those eligible for the study are at least 16 years old, pass international study criteria, and lack any alternative diagnoses that can result in chronic fatigue. These will include 5,000 people whose ME/CFS diagnosis was a consequence of SARS-CoV-2 infection. Questionnaires are completed online or on paper. Participants’ saliva DNA samples are acquired by post, which improves participation by more severely-affected individuals. Digital marketing and social media approaches resulted in 29,000 people with ME/CFS in the UK pre-registering their interest in participating. We will perform a genome-wide association study, comparing participants’ genotypes with those from UK Biobank as controls. This should generate hypotheses regarding the genes, mechanisms and cell types contributing to ME/CFS disease aetiology.

Discussion: The DecodeME study has been reviewed and given a favourable opinion by the North West – Liverpool Central Research Ethics Committee (21/NW/0169). Relevant documents will be available online ( www.decodeme.org.uk ). Genetic data will be disseminated as associated variants and genomic intervals, and as summary statistics. Results will be reported on the DecodeME website and via open access publications.

Source: Devereux-Cooke A, Leary S, McGrath SJ, Northwood E, Redshaw A, Shepherd C, Stacey P, Tripp C, Wilson J, Mar M, Boobyer D, Bromiley S, Chowdhury S, Dransfield C, Almas M, Almelid Ø, Buchanan D, Garcia D, Ireland J, Kerr SM, Lewis I, McDowall E, Migdal M, Murray P, Perry D, Ponting CP, Vitart V, Wolfe JC. DecodeME: community recruitment for a large genetics study of myalgic encephalomyelitis / chronic fatigue syndrome. BMC Neurol. 2022 Jul 19;22(1):269. doi: 10.1186/s12883-022-02763-6. PMID: 35854226. https://bmcneurol.biomedcentral.com/articles/10.1186/s12883-022-02763-6 (Full text)

 

Genetic association study in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) identifies several potential risk loci

Highlights:

• Largest ME/CFS genetic study to date.

• Three different cohorts totaling >2500 patients.

• First Immunochip study in ME/CFS.

• Possible implication of TPPP genetic region.

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disease of unknown etiology and pathogenesis, which manifests in a variety of symptoms like post-exertional malaise, brain fog, fatigue and pain. Hereditability is suggested by an increased disease risk in relatives, however, genome-wide association studies in ME/CFS have been limited by small sample sizes and broad diagnostic criteria, therefore no established risk loci exist to date.

In this study, we have analyzed three ME/CFS cohorts: a Norwegian discovery cohort (N = 427), a Danish replication cohort (N = 460) and a replication dataset from the UK biobank (N = 2105). To the best of our knowledge, this is the first ME/CFS genome-wide association study of this magnitude incorporating 2532 patients for the genome-wide analyses and 460 patients for a targeted analysis. Even so, we did not find any ME/CFS risk loci displaying genome-wide significance.

In the Norwegian discovery cohort, the TPPP gene region showed the most significant association (rs115523291, P = 8.5 × 10−7), but we could not replicate the top SNP. However, several other SNPs in the TPPP gene identified in the Norwegian discovery cohort showed modest association signals in the self-reported UK biobank CFS cohort, which was also present in the combined analysis of the Norwegian and UK biobank cohorts, TPPP (rs139264145; P = 0.00004). Interestingly, TPPP is expressed in brain tissues, hence it will be interesting to see whether this association, with time, will be verified in even larger cohorts. Taken together our study, despite being the largest to date, could not establish any ME/CFS risk loci, but comprises data for future studies to accumulate the power needed to reach genome-wide significance.

Source: Hajdarevic R, Lande A, Mehlsen J, Rydland A, Sosa DD, Strand EB, Mella O, Pociot F, Fluge Ø, Lie BA, Viken MK. Genetic association study in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) identifies several potential risk loci. Brain Behav Immun. 2022 Mar 19:S0889-1591(22)00078-2. doi: 10.1016/j.bbi.2022.03.010. Epub ahead of print. PMID: 35318112. https://www.sciencedirect.com/science/article/pii/S0889159122000782 (Full study)

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/

Review of the Quality Control Checks Performed by Current Genome-Wide and Targeted-Genome Association Studies on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Introduction:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating disease characterized by persistent fatigue and post-exertion malaise, accompanied by other symptoms (1, 2). The direct cause of the disease remains elusive, but it may include genetic factors alongside environmental triggers, such as strong microbial infections and other stressors (3, 4).

With the aim to identify putative genetic factors that could explain the pathophysiological mechanisms of ME/CFS, four genome-wide association studies (GWAS) and two targeted-genome association studies (TGAS) were conducted in the past decade (5–10). In the four GWAS, thousands of genetic markers located across the whole genome were evaluated for their statistical association with ME/CFS (5–8). The two TGAS had the same statistical objective of the four GWAS, but alternatively investigated the association of the disease with numerous genetic markers located in candidate genes related to inflammation and immunity (9) and in genes encoding diverse adrenergic receptors (10).

The findings from all these different studies suggested conflicting evidence of genetic association with ME/CFS: from absence of association (7), through mild association (10) up to moderate associations of a relatively small number of genetic markers (5, 6, 9). The most optimistic GWAS suggested more than 5,500 candidate gene-disease associations (8). This inconsistency in the reported findings prompted us to review the respective data. With this purpose, the present opinion paper first revisits the recommended quality control (QC) checks for GWAS and TGAS, and then summarizes which ones were performed by those studies on ME/CFS.

Source: Grabowska AD, Lacerda EM, Nacul L, Sepúlveda N. Review of the Quality Control Checks Performed by Current Genome-Wide and Targeted-Genome Association Studies on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Front Pediatr. 2020;8:293. Published 2020 Jun 12. doi:10.3389/fped.2020.00293 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304330/ (Full text)

Genetic Predisposition for Immune System, Hormone, and Metabolic Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Pilot Study

Abstract:

Introduction: Myalgic Encephalomyelitis/ Chronic Fatigue Syndrome (ME/CFS) is a multifactorial illness of unknown etiology with considerable social and economic impact. To investigate a putative genetic predisposition to ME/CFS we conducted genome-wide single-nucleotide polymorphism (SNP) analysis to identify possible variants.

Methods: 383 ME/CFS participants underwent DNA testing using the commercial company 23andMe. The deidentified genetic data was then filtered to include only non-synonymous and nonsense SNPs from exons and microRNAs, and SNPs close to splice sites. The frequencies of each SNP were calculated within our cohort and compared to frequencies from the Kaviar reference database. Functional annotation of pathway sets containing SNP genes with high frequency in ME/CFS was performed using over-representation analysis via ConsensusPathDB. Furthermore, these SNPs were also scored using the Combined Annotation Dependent Depletion (CADD) algorithm to gauge their deleteriousness.

Results: 5693 SNPs were found to have at least 10% frequency in at least one cohort (ME/CFS or reference) and at least two-fold absolute difference for ME/CFS. Functional analysis identified the majority of SNPs as related to immune system, hormone, metabolic, and extracellular matrix organization. CADD scoring identified 517 SNPs in these pathways that are among the 10% most deleteriousness substitutions to the human genome.

Source: Perez M, Jaundoo R, Hilton K, Del Alamo A, Gemayel K, Klimas NG, Craddock TJA, Nathanson L. Genetic Predisposition for Immune System, Hormone, and Metabolic Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Pilot Study. Front Pediatr. 2019 May 24;7:206. doi: 10.3389/fped.2019.00206. eCollection 2019. https://www.ncbi.nlm.nih.gov/pubmed/31179255

Genetic Predisposition for Immune System, Hormone, and Metabolic Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Pilot Study

Abstract:

Introduction: Myalgic Encephalomyelitis/ Chronic Fatigue Syndrome (ME/CFS) is a multifactorial illness of unknown etiology with considerable social and economic impact. To investigate a putative genetic predisposition to ME/CFS we conducted genome-wide single-nucleotide polymorphism (SNP) analysis to identify possible variants.

Methods: 383 ME/CFS participants underwent DNA testing using the commercial company 23andMe. The deidentified genetic data was then filtered to include only non-synonymous and nonsense SNPs from exons and microRNAs, and SNPs close to splice sites. The frequencies of each SNP were calculated within our cohort and compared to frequencies from the Kaviar reference database. Functional annotation of pathway sets containing SNP genes with high frequency in ME/CFS was performed using over-representation analysis via ConsensusPathDB. Furthermore, these SNPs were also scored using the Combined Annotation Dependent Depletion (CADD) algorithm to gauge their deleteriousness.

Results: 5693 SNPs were found to have at least 10% frequency in at least one cohort (ME/CFS or reference) and at least two-fold absolute difference for ME/CFS. Functional analysis identified the majority of SNPs as related to immune system, hormone, metabolic, and extracellular matrix organization. CADD scoring identified 517 SNPs in these pathways that are among the 10% most deleteriousness substitutions to the human genome.

Source: Melanie Perez, Rajeev Jaundoo, Kelly Hilton, Ana Del Alamo, Kristina Gemayel, Nancy G. Klimas, Travis J. A. Craddock and Lubov Nathanson. Genetic Predisposition for Immune System, Hormone, and Metabolic Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Pilot Study. Front. Pediatr., 24 May 2019 | https://doi.org/10.3389/fped.2019.00206 (Full article)

Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome

Abstract:

Myalgic encephalomyelitis, also known as chronic fatigue syndrome or ME/CFS, is a multifactorial and debilitating disease that has an impact on over 4 million people in the United States alone. The pathogenesis of ME/CFS remains largely unknown; however, a genetic predisposition has been suggested.

In the present study, we used a DNA single-nucleotide polymorphism (SNP) chip representing over 906,600 known SNPs to analyze DNA from ME/CFS subjects and healthy controls. To the best of our knowledge, this study represents the most comprehensive genome-wide association study (GWAS) of an ME/CFS cohort conducted to date.

Here 442 SNPs were identified as candidates for association with ME/CFS (adjusted P-value<0.05). Whereas the majority of these SNPs are represented in non-coding regions of the genome, 12 SNPs were identified in the coding region of their respective gene. Among these, two candidate SNPs resulted in missense substitutions, one in a pattern recognition receptor and the other in an uncharacterized coiled-coil domain-containing protein. We also identified five SNPs that cluster in the non-coding regions of T-cell receptor loci.

Further examination of these polymorphisms may help identify contributing factors to the pathophysiology of ME/CFS, as well as categorize potential targets for medical intervention strategies.

 

Source: Schlauch KA, Khaiboullina SF, De Meirleir KL, Rawat S, Petereit J, Rizvanov AA, Blatt N, Mijatovic T, Kulick D, Palotás A, Lombardi VC. Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome. Transl Psychiatry. 2016 Feb 9;6:e730. doi: 10.1038/tp.2015.208. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4872418/ (Full article)