Tag: Ponting

Replicated blood-based biomarkers for Myalgic Encephalomyelitis not explicable by inactivity

Abstract:

Myalgic Encephalomyelitis (ME; sometimes referred to as chronic fatigue syndrome) is a relatively common and female-biased disease of unknown pathogenesis that profoundly decreases patients’ health-related quality-of-life. ME diagnosis is hindered by the absence of robustly-defined and specific biomarkers that are easily measured from available sources such as blood, and unaffected by ME patients’ low level of physical activity.

Previous studies of blood biomarkers have not yielded replicated results, perhaps due to low study sample sizes (n<100). Here, we use UK Biobank (UKB) data for up to 1,455 ME cases and 131,303 population controls to discover hundreds of molecular and cellular blood traits that differ significantly between cases and controls. Importantly, 116 of these traits are replicated, as they are significant for both female and male cohorts.

Our analysis used semi-parametric efficient estimators, an initial Super Learner fit followed by a one-step correction, three types of mediators, and natural direct and indirect estimands, to decompose the average effect of ME status on molecular and cellular traits. Strikingly, these trait differences cannot be explained by ME cases’ restricted activity.

Of 3,237 traits considered, ME status had a significant effect on only one, via the “Duration of walk” (UKB field 874) mediator. By contrast, ME status had a significant direct effect on 290 traits (9%). As expected, these effects became more significant with increased stringency of case and control definition.

Significant female and male traits were indicative of chronic inflammation, insulin resistance and liver disease. Individually, significant effects on blood traits, however, were not sufficient to cleanly distinguish cases from controls. Nevertheless, their large number, lack of sex-bias, and strong significance, despite the ‘healthy volunteer’ selection bias of UKB participants, keep alive the future ambition of a blood-based biomarker panel for accurate ME diagnosis.

Source: Sjoerd V Beentjes, Julia Kaczmarczyk, Amanda Cassar, Gemma Louise Samms, Nima S Hejazi, Ava Khamseh, Chris P Ponting. Replicated blood-based biomarkers for Myalgic Encephalomyelitis not explicable by inactivity. medRxiv 2024.08.26.24312606; doi: https://doi.org/10.1101/2024.08.26.24312606 https://www.medrxiv.org/content/10.1101/2024.08.26.24312606v1 (Full text available as PDF file)

Unequal access to diagnosis of myalgic encephalomyelitis in England

Abstract:

Background People with Myalgic Encephalomyelitis (ME/CFS; sometimes referred to as chronic fatigue syndrome) experience very poor health-related quality of life and only rarely recover. ME/CFS has no curative treatment and no single diagnostic test. Public health and policy decisions relevant to ME/CFS require knowledge of its prevalence and barriers to diagnosis. However, people with ME/CFS report lengthy diagnostic delays and widespread misunderstanding of their symptoms. Published prevalence estimates vary greatly by country, gender, age and ethnicity.

Methods Hospital Episode Statistics data is routinely collected by the NHS in England together with patient age, gender and ethnicity. This data, downloaded from the Feasibility Self-Service of NHS DigiTrials, was used to stratify individuals with the ICD-10 code that best reflects ME/CFS symptoms (G93.3; “Postviral fatigue syndrome”) according to their age, self-reported gender and ethnicity, General Practice and NHS England Integrated Care Board (ICB).

Results In all, 100,055 people in England had been diagnosed with ME/CFS (ICD-10:G93.3) between April 1 1989 and October 7 2023, 0.16% of all registered patients. Of these, 79,445 were females and 20,590 males, a female-to-male ratio of 3.88:1. Female relative to male prevalence peaked at about 6-to-1 in individuals’ fourth and fifth decades of life. Prevalence varied widely across the 42 ICBs: 0.086%-0.82% for females and 0.024%-0.21% for males. White individuals were approximately 5-fold more likely to be diagnosed with ME/CFS than others; black, Asian or Chinese ethnicities are associated with particularly low rates of ME/CFS diagnoses. This ethnicity bias is stronger than for other common diseases. Among active English GP practices, 176 (3%) had no registered ME/CFS patients. Eight ICBs (19%) each contained fewer than 8 other-than-white individuals with a G93.3 code despite their registers containing a total of 293,770 other-than-white patients.

Conclusion Those who are disproportionately undiagnosed with ME/CFS are other-than-white ethnic groups, older females (>60y), older males (>80y), and people living in areas of multiple deprivation. The lifetime prevalence of ME/CFS for English females and males may be as high as 0.92% and 0.25%, respectively, or approximately 390,000 UK individuals overall. This improved estimate of ME/CFS prevalence allows more accurate assessment of the socioeconomic and disease burden imposed by ME/CFS.

Source: Gemma L. Samms, Chris P. Ponting. Unequal access to diagnosis of myalgic encephalomyelitis in England. medRxiv 2024.01.31.24302070; doi: https://doi.org/10.1101/2024.01.31.24302070 https://www.medrxiv.org/content/10.1101/2024.01.31.24302070v1.full-text (Full text)

Comparison of T-cell Receptor Diversity of people with Myalgic Encephalomyelitis versus controls

Abstract:

Objective: Myalgic Encephalomyelitis (ME; sometimes referred to as Chronic Fatigue Syndrome or CFS) is a chronic disease without laboratory test, detailed aetiological understanding or effective therapy. Its symptoms are diverse, but it is distinguished from other fatiguing illnesses by the experience of post-exertional malaise, the worsening of symptoms even after minor physical or mental exertion. Its frequent onset after infection might indicate that it is an autoimmune disease or that it arises from abnormal T-cell activation.

Results: To test this hypothesis, we sequenced the genomic loci of a/d, b and g T-cell receptors (TCR) from 40 human blood samples from each of four groups: severely affected people with ME/CFS; mildly or moderately affected people with ME/CFS; people diagnosed with Multiple Sclerosis, as disease controls; and, healthy controls. Seeking to automatically classify these individuals’ samples by their TCR repertoires, we applied P-SVM, a machine learning method. However, despite working well on a simulated data set, this approach did not partition samples into the four subgroups, beyond what was expected by chance alone.  Our findings do not support the hypothesis that blood samples from people with ME/CFS frequently contain altered T-cell receptor diversity.

Source: Joshua J Dibble, Ben Ferneyhough, Matthew Roddis et al. Comparison of T-cell Receptor Diversity of people with Myalgic Encephalomyelitis versus controls, 19 July 2023, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3164397/v1]  https://www.researchsquare.com/article/rs-3164397/v1 (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)