Gut Microbiome Wellness Index 2 enhances health status prediction from gut microbiome taxonomic profiles

Abstract:

Recent advancements in translational gut microbiome research have revealed its crucial role in shaping predictive healthcare applications. Herein, we introduce the Gut Microbiome Wellness Index 2 (GMWI2), an enhanced version of our original GMWI prototype, designed as a standardized disease-agnostic health status indicator based on gut microbiome taxonomic profiles.

Our analysis involves pooling existing 8069 stool shotgun metagenomes from 54 published studies across a global demographic landscape (spanning 26 countries and six continents) to identify gut taxonomic signals linked to disease presence or absence. GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence (i.e., outside the “reject option”).

This performance exceeds that of the original GMWI model and traditional species-level α-diversity indices, indicating a more robust gut microbiome signature for differentiating between healthy and non-healthy phenotypes across multiple diseases. When assessed through inter-study validation and external validation cohorts, GMWI2 maintains an average accuracy of nearly 75%.

Furthermore, by reevaluating previously published datasets, GMWI2 offers new insights into the effects of diet, antibiotic exposure, and fecal microbiota transplantation on gut health. Available as an open-source command-line tool, GMWI2 represents a timely, pivotal resource for evaluating health using an individual’s unique gut microbial composition.

Source: Chang, D., Gupta, V.K., Hur, B. et al. Gut Microbiome Wellness Index 2 enhances health status prediction from gut microbiome taxonomic profiles. Nat Commun 15, 7447 (2024). https://doi.org/10.1038/s41467-024-51651-9 https://www.nature.com/articles/s41467-024-51651-9 (Full text)

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Impact on Quality of Life (QoL) of Persons with ME/CFS

Abstract:

Background and Objectives: We previously reported on the impact of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) on the QoL of persons with ME/CFS and their family members. Here, we present the findings of the impact on the QoL of individuals with ME/CFS whose family members did not participate in the survey.

Materials and Methods: A prospective multinational online survey was disseminated via patient charities, support groups and social media. Persons with ME/CFS completed the EuroQoL questionnaire (EQ-5D-3L).

Results: Data were analysed from 876 participants from 26 countries who reported a health care professional diagnosis of ME/CFS. In total, 742 participants identified as female, 124 male and 10 preferred not to say. The mean age of the participants was 47 years (range 18-82), and the mean time to diagnosis was 14 years. The mean overall health status on a visual analogue scale for people with ME/CFS was 36.4 (100 = best health). People with ME/CFS were most often affected by inability to perform usual activities (n = 852, 97%), followed by pain (n = 809, 92%), impaired mobility (n = 724, 83%), difficulty in self-care (n = 561, 64%) and least often affected by anxiety and depression (n = 540, 62%).

Conclusions: The QoL of people with ME/CFS is significantly affected globally. There was no significant difference in quality of life compared with previously published data on those with ME/CFS who did have a family member complete the family member quality of life questionnaire (FROM16). Contrary to popular misconception, anxiety and depression are the least often affected areas in persons with ME/CFS who are most impacted by their inability to perform usual activities.

Source: Muirhead NL, Vyas J, Ephgrave R, Singh R, Finlay AY. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Impact on Quality of Life (QoL) of Persons with ME/CFS. Medicina (Kaunas). 2024 Jul 27;60(8):1215. doi: 10.3390/medicina60081215. PMID: 39202496. https://www.mdpi.com/1648-9144/60/8/1215 (Full text)

Home-based testing protocol to measure physiological responses to everyday activities in ME: a feasibility study

Abstract:

Background and objectives: Individuals with Myalgic Encephalomyelitis (ME) have shown altered physiological responses during maximum cardiopulmonary exercise testing. However, maximal testing is not representative of the everyday activities reported to cause or increase symptoms in ME, and is not accessible for those with severe or very severe illness. The aim of this study was to assess the feasibility and acceptability of a home-based testing protocol to measure physiological responses in ME to everyday activity.

Methods: Researchers attended participants’ homes to collect data and provide equipment for independent testing. Adults with ME who met the International Consensus Criteria wore a portable metabolic assessment system and a physiological stress monitor. Blood pressure, heart rate, oxygen saturation and lactic acid were assessed during a range of everyday positions and activities in their own homes.

Results: Online recruitment yielded 70 volunteers in 24 h. 17 eligible individuals reflecting a range of illness severities were enrolled. All participants found the procedures acceptable with 12 (70%) subjects completing every listed activity. Apparent physiological abnormalities were identified in all participants.

Conclusion: Physiological measurement during everyday activities was feasible for our participants who represented a range of ME severities. Activities must be adapted for different levels of severity to avoid significant symptom exacerbation. Further research is needed to develop home-based assessment protocols to advance the biobehavioral understanding of ME.

Trial registration number: ISRCTN78379409

Source: Nicola Clague-Baker, Sarah Tyson, Karen Leslie, Helen Dawes, Michelle Bull & Natalie Hilliard (2023) Home-based testing protocol to measure physiological responses to everyday activities in ME: a feasibility study, Fatigue: Biomedicine, Health & Behavior, DOI: 10.1080/21641846.2023.2245584 https://www.tandfonline.com/doi/full/10.1080/21641846.2023.2245584 (Full text)

Recommendations for Successful Implementation of the Use of Vocal Biomarkers for Remote Monitoring of COVID-19 and Long COVID in Clinical Practice and Research

Abstract:

The COVID-19 pandemic accelerated the use of remote patient monitoring in clinical practice or research for safety and emergency reasons, justifying the need for innovative digital health solutions to monitor key parameters or symptoms related to COVID-19 or Long COVID. The use of voice-based technologies, and in particular vocal biomarkers, is a promising approach, voice being a rich, easy-to-collect medium with numerous potential applications for health care, from diagnosis to monitoring.

In this viewpoint, we provide an overview of the potential benefits and limitations of using voice to monitor COVID-19, Long COVID, and related symptoms. We then describe an optimal pipeline to bring a vocal biomarker candidate from research to clinical practice and discuss recommendations to achieve such a clinical implementation successfully.

Source: Fischer A, Elbeji A, Aguayo G, Fagherazzi G. Recommendations for Successful Implementation of the Use of Vocal Biomarkers for Remote Monitoring of COVID-19 and Long COVID in Clinical Practice and Research. Interact J Med Res. 2022 Nov 15;11(2):e40655. doi: 10.2196/40655. PMID: 36378504; PMCID: PMC9668331. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9668331/ (Full text)

Myalgic encephalomyelitis/chronic fatigue syndrome and pregnancy: A mixed-methods systematic review

Abstract:

Background Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a fluctuating complex condition. More common in women than men, it tends to develop between mid-20s and mid-40s, including the main childbearing age (15–45 years). There are currently no systematic reviews summarising evidence relating to ME/CFS and pregnancy. The lack of quality assessed, and systematic summary evidence makes it harder for people with ME/CFS to make informed decisions about pregnancy, and harder for health care professionals to offer evidence-based care. This mixed methods systematic review aims to examine and summarise existing evidence relating to ME/CFS and pregnancy, both in relation to pregnancy outcomes and experiences of pregnancy but also the effect of pregnancy on ME/CFS severity and symptoms.

Methods This review followed a convergent segregated design. Seven electronic databases, relevant grey literature, reference lists of relevant reviews, and reference lists and citations of all included studies, were searched. Where necessary, authors were contacted for additional information. Studies of any design published in English, reporting on ME/CFS and pregnancy/postpartum (up to two years), risk of pregnancy outcomes with ME/CFS, or experiences during pregnancy for mother, partner or health and social care professionals following pregnancy with ME/CFS were included. Three researchers performed screening, data extraction and quality assessments independently. Qualitative and quantitative literature was analysed separately using thematic and descriptive syntheses, respectively (meta-analysis was not appropriate). Findings were integrated through configuration.

Results Searches identified n=2,789 studies, n=10 met our inclusion criteria. There were five quantitative studies, two qualitative studies and three pieces of grey literature. Preliminary results suggest that evidence is conflicting. In the qualitative literature, one study suggested one participant thought pregnancy improved ME/CFS symptoms while the other noted a participant commented that ME/CFS may have adversely affected her pregnancy. Of the four quantitative studies that reported on ME severity during pregnancy, two suggested pregnancy negatively impacted on ME/CFS, one study found most women had no change in ME/CFS symptoms during pregnancy, and one found ME/CFS improved during pregnancy. Only one study reported on pregnancy outcomes, finding a higher rate of spontaneous abortions, and increased developmental and learning delays in infants born to mothers with ME/CFS.

Conclusion Current evidence on ME/CFS in pregnancy is limited, and findings are inconsistent. Studies are limited by small sample size and currently, there is no UK evidence. More high-quality research into ME/CFS and pregnancy is urgently needed to support the development of evidence-based guidelines on ME/CFS and pregnancy.

Source: Pearce M, Slack E, Pears K, et alOP72 Myalgic encephalomyelitis/chronic fatigue syndrome and pregnancy: a mixed-methods systematic reviewJ Epidemiol Community Health 2022;76:A35. https://jech.bmj.com/content/76/Suppl_1/A35.1

Predictors of Chronic Fatigue Syndrome and Mood Disturbance After Acute Infection

Abstract:

Prospective cohort studies following individuals from acute infections have documented a prevalent post-infective fatigue state meeting diagnostic criteria for chronic fatigue syndrome (CFS) – that is, a post-infective fatigue syndrome (PIFS). The Dubbo Infection Outcomes Study (DIOS) was a prospective cohort following individuals from acute infection with Epstein-Barr virus (EBV), Ross River virus (RRV), or Q fever through to assessment of caseness for CFS designated by physician and psychiatrist assessments at 6 months. Previous studies in DIOS have revealed that functional genetic polymorphisms in both immunological (pro- and anti-inflammatory cytokines) and neurological (the purinergic receptor, P2X7) genes are associated with both the severity of the acute infection and subsequent prolonged illness.

Principal components analysis was applied to self-report data from DIOS to describe the severity and course of both the overall illness and concurrent mood disturbance. Associations between demographics and acute infection characteristics, with prolonged illness course as well as the PIFS outcome were examined using multivariable statistics. Genetic haplotype-driven functional variations in the neuropeptide Y (NPY) gene previously shown to be associated with brain responses to stress, and to trait anxiety were also examined as predictors.

The sample included 484 subjects (51% female, median age 32, IQR 19-44), of whom 90 (19%) met diagnostic criteria for CFS at 6 months. Participants with greater overall illness severity and concurrent mood disturbance in the acute illness had a more prolonged illness severity (HR = 0.39, 95% CI: 0.34-0.46, p < 0.001) and mood disturbance (HR = 0.36, 95% CI: 0.30-0.42, p < 0.001), respectively. Baseline illness severity and RRV infection were associated with delayed recovery.

Female gender and mood disturbance in the acute illness were associated with prolonged mood disturbance. Logistic regression showed that the odds of an individual being diagnosed with PIFS increased with greater baseline illness severity (OR = 2.24, 95% CI: 1.71-2.94, p < 0.001). There was no association between the NPY haplotypes with overall illness severity or mood disturbance either during the acute illness phase or with prolonged illness (p > 0.05). Severe acute infective illnesses predicted prolonged illness, prolonged mood disturbance and PIFS. These factors may facilitate early intervention to manage both PIFS and mood disturbances.

Source: Sandler CX, Cvejic E, Valencia BM, Li H, Hickie IB, Lloyd AR. Predictors of Chronic Fatigue Syndrome and Mood Disturbance After Acute Infection. Front Neurol. 2022 Jul 25;13:935442. doi: 10.3389/fneur.2022.935442. PMID: 35959390; PMCID: PMC9359311. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9359311/ (Full text)

Chronic fatigue syndrome and occupational status: a retrospective longitudinal study

Dear Sir,

Occupational Medicine recently published a paper from Stevelink et al. [1] called ‘Chronic fatigue syndrome and occupational status: a retrospective longitudinal study’. Unfortunately, the paper features major technical and methodological errors that warrant urgent editorial attention.

To recap: The study started with 508 participants. The primary outcome was occupational status. Many participants had dropped out by follow-up—only 316, or 62%, provided follow-up data. Of those 316, 88% reported no change in employment status. As a group, the participants experienced either no changes or only insignificant ones in a range of secondary outcomes, including fatigue and physical function. The poor follow-up scores on fatigue and physical function alone indicate that the group remained, collectively, severely disabled after treatment.

In several sections of the paper, the authors’ description of their own statistical findings is incorrect. They make a recurring elementary error in their presentation of percentages. The authors repeatedly use the construction ‘X% of patients who did Y at baseline’ when they should have used the construction ‘X% of all 316 patients (i.e. those who provided follow-up data)’. This recurring error involving the core findings undermines the merit and integrity of the entire paper.

For example, in the Abstract, the authors state that ‘53% of patients who were working [at baseline] remained in employment [at follow-up]’. This is not accurate. Their own data (Table 2) show that 185 patients (i.e. 167 + 18) were working at baseline, and that 167 patients were working at both time points. In other words, the proportion working continuously was in fact 90% (i.e. 167 out of 185). The ‘53%’ that the authors refer to is the percentage of the sample who were employed at both time points (i.e. 167 out of 316), which is an entirely different subset. They have either misunderstood the percentage they were writing about, or they have misstated their own finding by linking it to the wrong percentage.

This error is carried over into the section on ‘Key Learning Lessons’, where the authors state that ‘Over half of the patients who were working at baseline were able to remain in work over the follow-up period…’ While 90% is certainly ‘over half’, it seems clear that this phrasing is again incorrectly referring to the 53% subset.

The same error is made with the other key findings. For example, the Abstract states that ‘Of the patients who were not working at baseline, 9% had returned to work at follow-up’. But as above, this is incorrect. A total of 131 patients (i.e. 104 + 27) were recorded as ‘not employed’ at baseline and 27 were recorded as not working at baseline but as working at follow-up. This is 21%, not 9%. Once again, the authors appear to misunderstand their own findings. The ‘9%’ they refer to is a percentage of the sample of 316; it is not, as they have it, a percentage of that subset of the sample who were initially unemployed. This erroneous ‘9%’ conclusion appears as well in the ‘Key Learning Lessons’ and in the Discussion.

And again, the authors state in the Abstract that ‘of those working at baseline, 6% were unable to continue to work at follow-up’, a claim they repeat in the section on ‘Key Learning Lessons’ and in the Discussion. This statement too is wrong. Once more, the authors mistakenly interpret a percentage of the sample of 316 as if it were a percentage of a targeted subset. In this case, they think they are referring to a percentage of patients working at baseline, but they are actually referring to a percentage of the full group that provided follow-up data.

The authors present the raw frequency data in Table 2. Readers can see for themselves how their sample of 316 patients is cross-tabulated into four subsets of interest (i.e. ‘working at baseline and follow-up’; ‘not working at baseline and follow-up’; ‘dropped out of work at follow-up’; ‘returned to work at follow-up’). From Table 2, it is clear that the prose provided in the body of the paper is at odds with the actual data.

It is undeniable that the text of this paper is replete with elementary technical errors, as described. Inevitably, the narrative is distorted by the authors’ failure to understand and correctly explain their own findings. It is unclear to us how these basic and self-evident errors were not picked up during peer review. Although we don’t know the identities of the peer reviewers, we speculate that groupthink and confirmation bias will have played their part. After all, it is generally reasonable for peer reviewers to presume that authors have understood their own computations.

There are several other features of this paper that cause concern. These include the following:

  • The authors state that they evaluated participants using guidance from the UK’s National Institute for Health and Care Excellence (NICE). (Presumably they are referring to the 2007 NICE guidance, not the revision published in October 2021.) But the reference for this statement is a 1991 paper that outlines the so-called ‘Oxford criteria’, a case definition that differs significantly from the 2007 NICE guidance. Moreover, in a paper about the same participant cohort previously published by Occupational Medicine—‘Factors associated with work status in chronic fatigue syndrome’—the authors state explicitly that these patients were diagnosed using the Oxford criteria. This inconsistency is non-trivial, because the differences between these two diagnostic approaches have substantive implications for how the findings should be interpreted. The authors’ confusion over the matter is hard to comprehend and raises fundamental questions about the validity of their research.

  • According to Table 1, there were either no changes or no meaningful changes in average scores for fatigue, physical function and multiple other secondary outcomes between the preliminary sample of 508 and the final follow-up sample of 316. The authors themselves acknowledge that the patients who dropped out before follow-up were likely to have had poorer health than those who remained. Therefore, the fact that Table 1 presents combined averages for the entire preliminary sample—i.e. combined averages for patients who dropped out and those who did not—muddies the waters. Presenting combined baseline scores for all patients will mask any declines that occurred for these variables in the subset who were followed up. It would have been far more appropriate to have isolated and presented the baseline data for the 316 followed up patients alone. Doing so would have reflected the authors’ research question more correctly, as well as enabling readers to make their own like-with-like comparisons.

  • Finally, the authors state that ‘Studies into CFS have placed little emphasis on occupational outcomes, including return to work after illness’. However, they conspicuously fail to mention the PACE trial, a high-profile large-scale British study of interventions for CFS. The PACE trial included employment status as one of four objective outcomes, with the data showing that the interventions used—the same ones as in the Occupational Medicine study—have no effect on occupational outcomes. This previous finding is so salient to the present paper that it is especially curious the authors have chosen to omit it. The omission is all the more disquieting given that the corresponding author of the paper was a lead investigator on the PACE trial itself.

Authors of research papers have an obligation to cite seminal findings from prior studies that have direct implications for the target research question. Not doing so—especially where there is overlapping authorship—falls far short of the common standards expected in scientific reporting.

Even putting these additional matters aside, the technical errors that undermine this paper’s reporting of percentages render its key conclusions meaningless. The sentences used to describe the findings are simply incorrect, and the entire thrust of the paper’s narrative is thereby contaminated. We believe that allowing the authors to publish a correction to these sentences would create only further confusion.

We therefore call on the journal to retract the paper.

Read the rest of this article HERE.

Source: Hughes BM, Tuller D. Chronic fatigue syndrome and occupational status: a retrospective longitudinal study. Occup Med (Lond). 2022 May 23;72(4):e1-e2. doi: 10.1093/occmed/kqac007. PMID: 35604311. https://academic.oup.com/occmed/article/72/4/e1/6590617?login=false (Full article)

Predictors for Developing Severe Myalgic Encephalomyelitis/Chronic Fatigue Syndrome following Infectious Mononucleosis

Background: About 10% of individuals who contract infectious mononucleosis (IM) have symptoms 6 months later that meet criteria for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS).  Our study for the first time examined whether it is possible to predict who will develop ME/CFS following IM.

Methods: We have reported on a prospectively recruited cohort of 4,501 college students, of which 238 (5.3%) developed IM.  Those who developed IM were followed-up at six months to determine whether they recovered or met criteria for ME/CFS. The present study focuses on 48 students who after six months had a diagnosis of ME/CFS, and a matched control group of 58 students who had no further symptoms after their IM. All of these 106 students  had data at baseline (at least 6 weeks prior to the development of IM), when experiencing IM, and 6 months following IM. Of those who did not recover from IM, there were two groups: 30 were classified as ME/CFS and 18 were classified as severe ME/CFS. We measured the results of 7 questionnaires, physical examination findings, the severity of mononucleosis and cytokine analyses at baseline (pre-illness) and at the time of IM.  We examined predictors (e.g., pre-illness variables as well as variables at onset of IM) of  those who developed ME/CFS and severe ME/CFS following IM.

Results: From analyses using receiver operating characteristic statistics, the students who had had severe gastrointestinal symptoms of stomach pain, bloating, and an irritable bowel at baseline  and who also had abnormally low levels of the immune markers IL-13 and/or IL-5 at baseline, as well as severe gastrointestinal symptoms when then contracted IM,  were found to have a nearly 80% chance of having severe ME/CFS persisting six months following IM.

Conclusions: Our findings are consistent with emerging literature that gastrointestinal distress and autonomic symptoms, along with several immune markers, may be implicated in the development of severe ME/CFS.

Source: Jason, Leonard & Cotler, Joseph & Islam, Mohammed & Furst, Jacob & Katz, Ben. (2022). Predictors for Developing Severe Myalgic Encephalomyelitis/Chronic Fatigue Syndrome following Infectious Mononucleosis. Journal of Rehabilitation Therapy. 4. 1-5. 10.29245/2767-5122/2021/1.1129. https://www.rehabiljournal.com/articles/predictors-for-developing-severe-myalgic-encephalomyelitischronic-fatigue-syndrome-following-infectious-mononucleosis.html  (Full text)

Impact of Life Stressors on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Symptoms: An Australian Longitudinal Study

Abstract:

(1) Background: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex, multifaceted illness. The pathomechanism, severity and progression of this illness is still being investigated. Stressors have been implicated in symptom exacerbation for ME/CFS, however, there is limited information for an Australian ME/CFS cohort. The aim of this study was to assess the potential effect of life stressors including changes in work, income, or family scenario on symptom severity in an Australian ME/CFS cohort over five months;

(2) Methods: Australian residents with ME/CFS responded to questions relating to work, income, living arrangement, access to healthcare and support services as well as symptoms experienced;

(3) Results: thirty-six ME/CFS patients (age: 41.25 ± 12.14) completed all questionnaires (response rate 83.7%). Muscle pain and weakness, orthostatic intolerance and intolerance to extreme temperatures were experienced and fluctuated over time. Sleep disturbances were likely to present as severe. Work and household income were associated with worsened cognitive, gastrointestinal, body pain and sleep symptoms. Increased access to healthcare services was associated with improved symptom presentation;

(4) Conclusions: life stressors such as work and financial disruptions may significantly contribute to exacerbation of ME/CFS symptoms. Access to support services correlates with lower symptom scores.

Source: Balinas C, Eaton-Fitch N, Maksoud R, Staines D, Marshall-Gradisnik S. Impact of Life Stressors on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Symptoms: An Australian Longitudinal Study. Int J Environ Res Public Health. 2021 Oct 11;18(20):10614. doi: 10.3390/ijerph182010614. PMID: 34682360; PMCID: PMC8535742.  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8535742/ (Full text)

A Comprehensive Examination of Severely Ill ME/CFS Patients

One in four myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) patients are estimated to be severely affected by the disease, and these house-bound or bedbound patients are currently understudied. Here, we report a comprehensive examination of the symptoms and clinical laboratory tests of a cohort of severely ill patients and healthy controls.
The greatly reduced quality of life of the patients was negatively correlated with clinical depression. The most troublesome symptoms included fatigue (85%), pain (65%), cognitive impairment (50%), orthostatic intolerance (45%), sleep disturbance (35%), post-exertional malaise (30%), and neurosensory disturbance (30%). Sleep profiles and cognitive tests revealed distinctive impairments. Lower morning cortisol level and alterations in its diurnal rhythm were observed in the patients, and antibody and antigen measurements showed no evidence for acute infections by common viral or bacterial pathogens.
These results highlight the urgent need of developing molecular diagnostic tests for ME/CFS. In addition, there was a striking similarity in symptoms between long COVID and ME/CFS, suggesting that studies on the mechanism and treatment of ME/CFS may help prevent and treat long COVID and vice versa.
Source: Chang C-J, Hung L-Y, Kogelnik AM, Kaufman D, Aiyar RS, Chu AM, Wilhelmy J, Li P, Tannenbaum L, Xiao W, Davis RW. A Comprehensive Examination of Severely Ill ME/CFS Patients. Healthcare. 2021; 9(10):1290. https://doi.org/10.3390/healthcare9101290 https://www.mdpi.com/2227-9032/9/10/1290/htm  (Full text)