Tag: phenotypes

Defining a High-Quality Myalgic Encephalomyelitis/Chronic Fatigue Syndrome cohort in UK Biobank

Abstract:

Background: Progress in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) research is being slowed by the relatively small-scale studies being performed whose results are often not replicated. Progress could be accelerated by analyses of large population-scale projects, such as UK Biobank (UKB), which provide extensive phenotype and genotype data linked to both ME/CFS cases and controls.

Methods: Here, we analysed the overlap and discordance among four UKB-defined ME/CFS cohorts, and additional questionnaire data when available.

Results: A total of 5,354 UKB individuals were linked to at least one piece of evidence of MECFS, a higher proportion (1.1%) than most prevalence estimates. Only a third (36%; n=1,922) had 2 or more pieces of evidence for MECFS, in part due to data missingness. For the same UKB participant, ME/CFS status defined by ICD-10 (International Classification of Diseases, Tenth Revision) code G93.3 (Post-viral fatigue syndrome) was most likely to be supported by another data type (72%); ME/CFS status defined by Pain Questionnaire responses is least likely to be supported (43%), in part due to data missingness.

Conclusions: We conclude that ME/CFS status in UKB, and potentially other biobanks, is best supported by multiple, and not single, lines of evidence. Finally, we raise the estimated ME/CFS prevalence in the UK to 410,000 using the most consistent evidence for ME/CFS status, and accounting for those who had no opportunity to participate in UKB due to being bed- or house-bound.

Source: Samms GL, Ponting CP. Defining a High-Quality Myalgic Encephalomyelitis/Chronic Fatigue Syndrome cohort in UK Biobank. NIHR Open Res. 2025 Apr 28;5:39. doi: 10.3310/nihropenres.13956.1. PMID: 40443420; PMCID: PMC12120426. https://pmc.ncbi.nlm.nih.gov/articles/PMC12120426/ (Full text)

Cerebrospinal fluid immune phenotyping reveals distinct immunotypes of myalgic encephalomyelitis/chronic fatigue syndrome

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex heterogeneous multiorgan disease that can have severe impact on individuals’ quality of life. Diagnosis of ME/CFS is based on symptom presentation, and a significant goal for the field is to establish meaningful subtypes. The heterogeneity in the literature suggests that individuals living with ME/CFS may suffer from overlapping but different underlying pathophysiological mechanisms.

We enrolled 40 participants with ME/CFS and 41 matched healthy control subjects at the Bragée Clinic in Sweden. We assessed plasma samples from both ME/CFS cases and control groups and cerebrospinal fluid (CSF) samples from individuals with ME/CFS.

We investigated dysregulated pathways and disease profiles through clinical questionnaires; multiplex analyses of cytokines, hormones, and matrix metalloproteinases; pathogen seroreactivity through peptide display bacteria libraries; and high-throughput microarray for autoantibodies. All samples used were from humans.

We show altered interaction patterns between circulating biological factors in plasma of ME/CFS participants. Our analysis of CSF from individuals with ME/CFS revealed different immunotypes of disease. We found 2 patient clusters based on matrix metalloproteinases profiles. The subgroups had similar clinical presentation but distinct pathogen exposure and CSF inflammatory profiles.

Our findings shed light on ME/CFS immune phenotypes and generate hypotheses for future research in disease pathogenesis and treatment development by exploring disease subgroups.

Source: Bastos VC, Greene KA, Tabachnikova A, Bhattacharjee B, Sjögren P, Bertilson B, Reifert J, Zhang M, Kamath K, Shon J, Gehlhausen JR, Guan L, VanElzakker M, Proal A, Bragée B, Iwasaki A. Cerebrospinal fluid immune phenotyping reveals distinct immunotypes of myalgic encephalomyelitis/chronic fatigue syndrome. J Immunol. 2025 May 15:vkaf087. doi: 10.1093/jimmun/vkaf087. Epub ahead of print. PMID: 40373264. https://academic.oup.com/jimmunol/advance-article/doi/10.1093/jimmun/vkaf087/8133211 (Full text)

Fatigue and symptom-based clusters in post COVID-19 patients: a multicentre, prospective, observational cohort study

Abstract:

Background: In the Netherlands, the prevalence of post COVID-19 condition is estimated at 12.7% at 90-150 days after SARS-CoV-2 infection. This study aimed to determine the occurrence of fatigue and other symptoms, to assess how many patients meet the Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) criteria, to identify symptom-based clusters within the P4O2 COVID-19 cohort and to compare these clusters with clusters in a ME/CFS cohort.

Methods: In this multicentre, prospective, observational cohort in the Netherlands, 95 post COVID-19 patients aged 40-65 years were included. Data collection at 3-6 months after infection included demographics, medical history, questionnaires, and a medical examination. Follow-up assessments occurred 9-12 months later, where the same data were collected. Fatigue was determined with the Fatigue Severity Scale (FSS), a score of ≥ 4 means moderate to high fatigue. The frequency and severity of other symptoms and the percentage of patients that meet the ME/CFS criteria were assessed using the DePaul Symptom Questionnaire-2 (DSQ-2). A self-organizing map was used to visualize the clustering of patients based on severity and frequency of 79 symptoms. In a previous study, 337 Dutch ME/CFS patients were clustered based on their symptom scores. The symptom scores of post COVID-19 patients were applied to these clusters to examine whether the same or different clusters were found.

Results: According to the FSS, fatigue was reported by 75.9% of the patients at 3-6 months after infection and by 57.1% of the patients 9-12 months later. Post-exertional malaise, sleep disturbances, pain, and neurocognitive symptoms were also frequently reported, according to the DSQ-2. Over half of the patients (52.7%) met the Fukuda criteria for ME/CFS, while fewer patients met other ME/CFS definitions. Clustering revealed specific symptom patterns and showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort, where 2 clusters had > 10 patients.

Conclusions: This study shows persistent fatigue and diverse symptomatology in post COVID-19 patients, up to 12-18 months after SARS-CoV-2 infection. Clustering showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort.

Source: Cornelissen MEB, Bloemsma LD, Vaes AW, Baalbaki N, Deng Q, Beijers RJHCG, Noij LCE, Houweling L, Bazdar S, Spruit MA, Maitland-van der Zee AH; on behalf of the P4O2 Consortium. Fatigue and symptom-based clusters in post COVID-19 patients: a multicentre, prospective, observational cohort study. J Transl Med. 2024 Feb 21;22(1):191. doi: 10.1186/s12967-024-04979-1. PMID: 38383493. https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-024-04979-1 (Full text)

Evolving phenotypes of non-hospitalized patients that indicate long COVID

Abstract:

Background: For some SARS-CoV-2 survivors, recovery from the acute phase of the infection has been grueling with lingering effects. Many of the symptoms characterized as the post-acute sequelae of COVID-19 (PASC) could have multiple causes or are similarly seen in non-COVID patients. Accurate identification of PASC phenotypes will be important to guide future research and help the healthcare system focus its efforts and resources on adequately controlled age- and gender-specific sequelae of a COVID-19 infection.

Methods: In this retrospective electronic health record (EHR) cohort study, we applied a computational framework for knowledge discovery from clinical data, MLHO, to identify phenotypes that positively associate with a past positive reverse transcription-polymerase chain reaction (RT-PCR) test for COVID-19. We evaluated the post-test phenotypes in two temporal windows at 3-6 and 6-9 months after the test and by age and gender. Data from longitudinal diagnosis records stored in EHRs from Mass General Brigham in the Boston Metropolitan Area was used for the analyses. Statistical analyses were performed on data from March 2020 to June 2021. Study participants included over 96 thousand patients who had tested positive or negative for COVID-19 and were not hospitalized.

Results: We identified 33 phenotypes among different age/gender cohorts or time windows that were positively associated with past SARS-CoV-2 infection. All identified phenotypes were newly recorded in patients’ medical records 2 months or longer after a COVID-19 RT-PCR test in non-hospitalized patients regardless of the test result. Among these phenotypes, a new diagnosis record for anosmia and dysgeusia (OR 2.60, 95% CI [1.94-3.46]), alopecia (OR 3.09, 95% CI [2.53-3.76]), chest pain (OR 1.27, 95% CI [1.09-1.48]), chronic fatigue syndrome (OR 2.60, 95% CI [1.22-2.10]), shortness of breath (OR 1.41, 95% CI [1.22-1.64]), pneumonia (OR 1.66, 95% CI [1.28-2.16]), and type 2 diabetes mellitus (OR 1.41, 95% CI [1.22-1.64]) is one of the most significant indicators of a past COVID-19 infection. Additionally, more new phenotypes were found with increased confidence among the cohorts who were younger than 65.

Conclusions: The findings of this study confirm many of the post-COVID-19 symptoms and suggest that a variety of new diagnoses, including new diabetes mellitus and neurological disorder diagnoses, are more common among those with a history of COVID-19 than those without the infection. Additionally, more than 63% of PASC phenotypes were observed in patients under 65 years of age, pointing out the importance of vaccination to minimize the risk of debilitating post-acute sequelae of COVID-19 among younger adults.

Source: Estiri H, Strasser ZH, Brat GA, Semenov YR; Consortium for Characterization of COVID-19 by EHR (4CE), Patel CJ, Murphy SN. Evolving phenotypes of non-hospitalized patients that indicate long COVID. BMC Med. 2021 Sep 27;19(1):249. doi: 10.1186/s12916-021-02115-0. PMID: 34565368. https://pubmed.ncbi.nlm.nih.gov/34565368/

A map of metabolic phenotypes in patients with myalgic encephalomyelitis/chronic fatigue syndrome

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease usually presenting after infection. Emerging evidence supports that energy metabolism is affected in ME/CFS, but a unifying metabolic phenotype has not been firmly established. We performed global metabolomics, lipidomics, and hormone measurements, and we used exploratory data analyses to compare serum from 83 patients with ME/CFS and 35 healthy controls.

Some changes were common in the patient group, and these were compatible with effects of elevated energy strain and altered utilization of fatty acids and amino acids as catabolic fuels. In addition, a set of heterogeneous effects reflected specific changes in 3 subsets of patients, and 2 of these expressed characteristic contexts of deregulated energy metabolism. The biological relevance of these metabolic phenotypes (metabotypes) was supported by clinical data and independent blood analyses.

In summary, we report a map of common and context-dependent metabolic changes in ME/CFS, and some of them presented possible associations with clinical patient profiles. We suggest that elevated energy strain may result from exertion-triggered tissue hypoxia and lead to systemic metabolic adaptation and compensation. Through various mechanisms, such metabolic dysfunction represents a likely mediator of key symptoms in ME/CFS and possibly a target for supportive intervention.

Source: Hoel F, Hoel A, Pettersen IK, Rekeland IG, Risa K, Alme K, Sørland K, Fosså A, Lien K, Herder I, Thürmer HL, Gotaas ME, Schäfer C, Berge RK, Sommerfelt K, Marti HP, Dahl O, Mella O, Fluge Ø, Tronstad KJ. A map of metabolic phenotypes in patients with myalgic encephalomyelitis/chronic fatigue syndrome. JCI Insight. 2021 Aug 23;6(16):149217. doi: 10.1172/jci.insight.149217. PMID: 34423789. https://pubmed.ncbi.nlm.nih.gov/34423789/

Salivary DNA Loads for Human Herpesviruses 6 and 7 Are Correlated With Disease Phenotype in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex chronic condition affecting multiple body systems, with unknown cause, unclear pathogenesis mechanisms, and fluctuating symptoms which may lead to severe debilitation. It is frequently reported to have been triggered by an infection, but there are no clear differences in exposure to, or seroprevalence of, any particular viruses between people with ME/CFS and healthy individuals. However, herpes viruses have been repeatedly hypothesized to underlie the chronic relapsing/remitting form of MS/CFS due to their persistence in a latent form with periodic reactivation. It is possible that ME/CFS is associated with herpes virus reactivation, which has not been detectable previously due to insufficiently sensitive testing methods.

Saliva samples were collected from 30 people living with ME/CFS at monthly intervals for 6 months and at times when they experienced symptom exacerbation, as well as from 14 healthy control individuals. The viral DNA load of the nine humanherpes viruses was determined by digital droplet PCR. Symptoms were assessed by questionnaire at each time point. Human herpesvirus (HHV) 6B, HHV-7, herpes simplex virus 1 and Epstein-Barr virus were detectable within the saliva samples, with higher HHV-6B and HHV-7 viral loads detected in people with ME/CFS than in healthy controls.

Participants with ME/CFS could be broadly separated into two groups: one group displayed fluctuating patterns of herpesviruses detectable across the 6 months while the second group displayed more stable viral presentation. In the first group, there was positive correlation between HHV-6B and HHV-7 viral load and severity of symptom scores, including pain, neurocognition, and autonomic dysfunction.

The results indicate that fluctuating viral DNA load correlates with ME/CFS symptoms: this is in accordance with the hypothesis that pathogenesis is related to herpesvirus reactivation state, and this should be formally tested. Herpesvirus reactivation might be a cause or consequence of dysregulated immune function seen in ME/CFS. The sampling strategy and molecular tools developed here permit such large-scale epidemiological investigations.

Source: Lee JS, Lacerda EM, Nacul L, Kingdon CC, Norris J, O’Boyle S, Roberts CH, Palla L, Riley EM, Cliff JM. Salivary DNA Loads for Human Herpesviruses 6 and 7 Are Correlated With Disease Phenotype in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Front Med (Lausanne). 2021 Aug 6;8:656692. doi: 10.3389/fmed.2021.656692. PMID: 34422848; PMCID: PMC8378328. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378328/  (Full text)

Autonomic Phenotypes in Chronic Fatigue Syndrome (CFS) Are Associated with Illness Severity: A Cluster Analysis

Abstract:

In this study we set out to define the characteristics of autonomic subgroups of patients with Chronic Fatigue Syndrome (CFS). The study included 131 patients with CFS (Fukuda criteria). Participants completed the following screening symptom assessment tools: Chalder Fatigue Scale, Fatigue Impact Scale, Fatigue Severity Scale, Epworth Sleepiness Scales, the self-reported Composite Autonomic Symptom Scale. Autonomic parameters were measured at rest with a Task Force Monitor (CNS Systems) and arterial stiffness using an Arteriograph (TensioMed Kft.).

Principal axis factor analysis yielded four factors: fatigue, subjective and objective autonomic dysfunction and arterial stiffness. Using cluster analyses, these factors were grouped in four autonomic profiles: 34% of patients had sympathetic symptoms with dysautonomia, 5% sympathetic alone, 21% parasympathetic and 40% had issues with sympathovagal balance.

Those with a sympathetic-dysautonomia phenotype were associated with more severe disease, reported greater subjective autonomic symptoms with sympathetic over-modulation and had the lowest quality of life. The highest quality of life was observed in the balance subtype where subjects were the youngest, had lower levels of fatigue and the lowest values for arterial stiffness. Future studies will aim to design autonomic profile-specific treatment interventions to determine links between autonomic phenotypes CFS and a specific treatment.

Source: Słomko J, Estévez-López F, Kujawski S, et al. Autonomic Phenotypes in Chronic Fatigue Syndrome (CFS) Are Associated with Illness Severity: A Cluster Analysis. J Clin Med. 2020;9(8):E2531. Published 2020 Aug 5. doi:10.3390/jcm9082531  https://www.mdpi.com/2077-0383/9/8/2531  (Full text)

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)

Are current chronic fatigue syndrome criteria diagnosing different disease phenotypes?

Abstract:

Importance: Chronic fatigue syndrome (CFS) is characterised by a constellation of symptoms diagnosed with a number of different polythetic criteria. Heterogeneity across these diagnostic criteria is likely to be confounding research into the as-yet-unknown pathophysiology underlying this stigmatised and debilitating condition and may diagnose a disease spectrum with significant implications for clinical management. No studies to date have objectively investigated this possibility using a validated measure of CFS symptoms–the DePaul Symptom Questionnaire (DSQ).

Objective: To examine whether current CFS diagnostic criteria are identifying different disease phenotypes using the DSQ.

Design: Case control study.

Setting: Clinical Research Facility of the Royal Victoria Infirmary, Newcastle upon Tyne, UK.

Participants: 49 CFS subjects and ten matched, sedentary community controls, excluded for co-morbid depression.

Main outcomes and measures: Self-reported autonomic and cognitive features were assessed with the Composite Autonomic Symptom Score (COMPASS) and Cognitive Failures Questionnaire (COGFAIL) respectively. Objective autonomic cardiovascular parameters were examined using the Task Force® Monitor and a battery of neuropsychological tests administered for objective cognitive assessment.

Results: Self-reported autonomic and cognitive symptoms were significantly greater in CFS subjects compared to controls. There were no statistically significant differences in objective autonomic measures between CFS and controls. There were clinically significant differences between DSQ subgroups on objective autonomic testing. Visuospatial memory, verbal memory and psychomotor speed were significantly different between DSQ subgroups.

Conclusions and relevance: The finding of no significant differences in objective autonomic testing between CFS and control subjects may reflect the inclusion of sedentary controls or exclusion for co-morbid depression. Consistent exclusion criteria would enable better delineation of these two conditions and their presenting symptoms. Findings across CFS subgroups suggest subjects have a different disease burden on subjective and objective measures of function, autonomic parameters and cognitive impairment when categorised using the DSQ. Different CFS criteria may at best be diagnosing a spectrum of disease severities and at worst different CFS phenotypes or even different diseases. This complicates research and disease management and may contribute to the significant stigma associated with the condition.

Source: Laura Maclachlan, Stuart Watson, Peter Gallagher, Andreas Finkelmeyer, Leonard A. Jason, Madison Sunnquist, Julia L. Newton. Are current chronic fatigue syndrome criteria diagnosing different disease phenotypes? PLoS ONE. Published: October 20, 2017https://doi.org/10.1371/journal.pone.0186885   http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0186885 (Full article)

Predictive immunophenotypes: disease-related profile in chronic fatigue syndrome

Abstract:

BACKGROUND: There is a growing body of evidence supporting the theory that problems with immune function play an important role in chronic fatigue syndrome (CFS).

METHODS: We studied 90 CFS cases and 50 healthy controls from two different areas of upstate New York to determine whether there were differences in the absolute number and pattern of natural killer (NK) and cytotoxic T-cell phenotypes between CFS cases and healthy controls in the two regions. One group was from a small town where a cluster of cases existed; the other was from a large metropolitan area where there was not a known cluster.

RESULTS: The number of CD56+CD3+CD8+ and CD56+CD3+CD8- cells in cases from the two areas were both significantly elevated over that of controls from the metropolitan area (P < 0.03). The number of CD56+CD3-CD8+ and CD56+CD3-CD8- cells was significantly reduced in the two case groups compared to that of controls from the metropolitan area (P = 0.04). However, controls who were from the same town as the cluster cases had numbers of CD56+CD3+CD8+, CD56+CD3+CD8-, and CD56+CD3-CD8- cells that were more like that of cases than controls. Only the number of CD56+CD3-CD8+ cells (an NK cell subset) was significantly different in cases versus controls from the cluster area (P = 0.022).

CONCLUSIONS: These data suggest that differences in controls from cluster and noncluster areas may be responsible for some of the inconsistencies in results from other studies. Furthermore, they suggest the possibility that NK cell function may play an important role in preventing the development of CFS in individuals who live in a community where a cluster of cases have been identified.

Copyright 2003 Wiley-Liss, Inc.

 

Source: Stewart CC, Cookfair DL, Hovey KM, Wende KE, Bell DS, Warner CL. Predictive immunophenotypes: disease-related profile in chronic fatigue syndrome. Cytometry B Clin Cytom. 2003 May;53(1):26-33. http://onlinelibrary.wiley.com/doi/10.1002/cyto.b.10034/full  (Full article)