Category: Overlapping Illnesses

Fatigue in Post-Acute Sequelae of Coronavirus Disease 2019

Abstract:

Fatigue from post-acute sequelae of coronavirus disease 2019 is a complex constellation of symptoms that could be driven by a wide spectrum of underlying etiologies. Despite this, there seems to be hope for treatment plans that focus on addressing possible etiologies and creating a path to improving quality of life and a paced return to activity.

Source: Abbott Z, Summers W, Niehaus W. Fatigue in Post-Acute Sequelae of Coronavirus Disease 2019. Phys Med Rehabil Clin N Am. 2023 Aug;34(3):607-621. doi: 10.1016/j.pmr.2023.04.006. Epub 2023 Apr 24. PMID: 37419535; PMCID: PMC10123359. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123359/ (Full text)

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 Lammi, Tomoko Nakanishi, Samuel E. Jones, Shea J. Andrews, Juha Karjalainen, Beatriz Cortés, Heath E. O’Brien, Brian E. Fulton-Howard, Hele H. Haapaniemi, Axel Schmidt, Ruth E. Mitchell, Abdou Mousas, Massimo Mangino, Alicia Huerta-Chagoya, Nasa Sinnott-Armstrong, Elizabeth T. Cirulli, Marc Vaudel, Alex S.F. Kwong, Amit K. Maiti, Minttu Marttila, Chiara Batini, Francesca Minnai, Anna R. Dearman, C.A. Robert Warmerdam, Celia B. Sequeros, Thomas W. Winkler, Daniel M. Jordan, Lindsay Guare, Ekaterina Vergasova, Eirini Marouli, Pasquale Striano, Ummu Afeera Zainulabid, Ashutosh Kumar, Hajar Fauzan Ahmad, Ryuya Edahiro, Shuhei Azekawa, Long COVID Host Genetics Initiative, FinnGen, DBDS Genomic Consortium, GEN-COVID Multicenter Study, Joseph J. Grzymski, Makoto Ishii, Yukinori Okada, Noam D. Beckmann, Meena Kumari, Ralf Wagner, Iris M. Heid, Catherine John, Patrick J. Short, Per Magnus, Karina Banasik, Frank Geller, Lude H. Franke, Alexander Rakitko, Emma L. Duncan, Alessandra Renieri, Konstantinos K. Tsilidis, Rafael de Cid, Ahmadreza Niavarani, Teresa Tusié-Luna, Shefali S. Verma, George Davey Smith, Nicholas J. Timpson, Mark J. Daly, Andrea Ganna, Eva C. Schulte, J. Brent Richards, Kerstin U. Ludwig, Michael Hultström, Hugo Zeberg, Hanna M. Ollila. Genome-wide Association Study of Long COVID. medRxiv 2023.06.29.23292056; doi: https://doi.org/10.1101/2023.06.29.23292056  https://www.medrxiv.org/content/10.1101/2023.06.29.23292056v1.full-text (Full text)

System and methods to determine ME/CFS & Long Covid disease severity using wearable sensor & survey data

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease with high probability of misdiagnosis and significant unmet medical needs that affects as many as 2.5 million people in the U.S. and causes enormous burden for patients, their caregivers, the healthcare system and society. Between 84 to 91 percent of ME/CFS patients are not yet diagnosed [6, 19], and at least one-quarter of ME/CFS patients are house- or bedbound at some point in their lives [12, 13]. The impact of ME/CFS to the U.S. economy, is about $17 to $24 billion in medical bills and lost income from lost household and labor force productivity per year [7, 13].

Current widely used diagnosis methods of ME/CFS and other diseases with similar clinical symptoms like Long COVID [6, 21] are highly dependent on patients’ self reporting [4, 5] and standardized survey, which are not optimal for medical diagnosis. In a joint study with The Bateman Horne Center (BHC)1, we designed and developed a system prototype that was able to stably collect terabytes of inertial measurement unit (IMU) time-series data, and analyzed multiple candidate parameters derived from them that could be used as reliable biomarkers for ME/CFS and other diseases with similar clinical symptoms.

Utilizing our system prototype, MetaProcessor, we conducted grouped t-tests on data collected from the EndoPAT study group (55 recruited, 51 participated, 30 ME/CFS, 15 Long COVID, 6 healthy control) to evaluate the predictive power of Upright Position Time (UpTime), Hours of Upright Activity (HUA), and Steps/Day. Through statistical analysis, we were able to assert the following for ME/CFS versus healthy control:

1. UpTime yielded a low p-value of 0.00004, indicating a significant difference between the groups and demonstrating its potential as a reliable measure for differentiating ME/CFS from healthy control populations.

2. HUA had a p-value of less than 0.00004, suggesting it could also serve as a useful measure for distinguishing ME/CFS from healthy control groups.

3. Steps/Day, x-axis and y-axis, had p-values of 0.01059 and 0.08665, respectively, indicating that step count may be relevant for differentiating ME/CFS individuals from healthy controls, but step count alone may not be sufficient to reliably distinguish between these groups.

In a linear regression analysis, we found a moderately positive correlation between UpTime and HUA with r 2 = 0.68. Overall, we can confidently conclude that UpTime is a superior overall predictor due to its objective nature and the lowest p-values observed across all groups.

Source: System and methods to determine ME/CFS & Long Covid disease severity using wearable sensor & survey data. Sun, Y. Thesis, Bachelor of Science, The University of Utah. https://ccs.neu.edu/~ysun/publications/system-and-methods-to-determine-mecfs-and-longcovid-disease-severity-using-wearable-sensor-and-survey-data.pdf (Full text)

Association analysis between symptomology and herpesvirus IgG antibody concentrations in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and multiple sclerosis

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and multiple sclerosis (MS) are two complex and multifactorial diseases whose patients experience persistent fatigue, cognitive impairment, among other shared symptoms. The onset of these diseases has also been linked to acute herpesvirus infections or their reactivations.

In this work, we re-analyzed a previously-described dataset related to IgG antibody responses to 6 herpesviruses (CMV – cytomegalovirus; EBV – Epstein-Barr virus; HHV6 – human herpesvirus-6; HSV1 and HSV2 – herpes simplex virus-1 and -2; VZV – varicella-zoster virus) from the United Kingdom ME/CFS biobank. The primary goal was to report the underlying symptomology and its association with herpesvirus IgG antibodies using data from 4 disease-trigger-based subgroups of ME/CFS patients (n = 222) and patients with MS (n = 46). A secondary objective was to assess whether serological data could distinguish ME/CFS and its subgroup from MS using a SuperLearner (SL) algorithm.

There was evidence for a significant negative association between temporary eye insight disturbance and CMV antibody concentrations and for a significant positive association between bladder problems and EBV antibody concentrations in the MS group.

In the ME/CFS or its subgroups, the most significant antibody-symptom association was obtained for increasing HSV1 antibody concentration and brain fog, a finding in line with a negative impact of HSV1 exposure on cognitive outcomes in both healthy and disease conditions. There was also evidence for a higher number of significant antibody-symptom associations in the MS group than in the ME/CFS group.

When we combined all the serological data in an SL algorithm, we could distinguish three ME/CFS subgroups (unknown disease trigger, non-infection trigger, and an infection disease trigger confirmed in the lab at the time of the event) from the MS group. However, we could not find the same for the remaining ME/CFS group (related to an unconfirmed infection disease).

In conclusion, IgG antibody data explains more the symptomology of MS patients than the one of ME/CFS patients. Given the fluctuating nature of symptoms in ME/CFS patients, the clinical implication of these findings remains to be determined with a longitudinal study. This study is likely to ascertain the robustness of the associations during natural disease course.

Source: Tiago Dias Domingues, João Malato, Anna D. Grabowska, Ji-Sook Lee, Jose Ameijeiras-Alonso, Przemyslaw Biecek, Luís Graça, Helena Mouriño, Carmen Scheibenbogen, Francisco Westermeier, Luis Nacul, Jacqueline M. Cliff, Eliana Lacerda, Nuno Sepúlveda,
Association analysis between symptomology and herpesvirus IgG antibody concentrations in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and multiple sclerosis. Heliyon, https://doi.org/10.1016/j.heliyon.2023.e18250 https://www.sciencedirect.com/science/article/pii/S2405844023054580 (Full text)

An understanding of the immune dysfunction in susceptible people who develop the post-viral fatigue syndromes Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Long COVID

Abstract:

Viral infection in most people results in a transient immune/inflammatory response resulting in elimination of the virus and recovery where the immune system returns to that of the pre-infectious state. In susceptible people by contrast there is a transition from an acute immune response to a chronic state that can lead to an ongoing lifelong complex post-viral illness, Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. This susceptibility is proposed to be genetic or be primed by prior health history. Complex abnormalities occur in immune cell functions, immune cell metabolism and energy production, and in cytokine immune modulator regulation. The immune system of the brain/central nervous system becomes activated leading to dysfunction in regulation of body physiology and the onset of many neurological symptoms.

A dysfunctional immune system is core to the development of the post-viral condition as shown with diverse strategies of immune profiling.  Many studies have shown changes in numbers and activity of immune cells of different phenotypes and their metabolism. Immune regulating cytokines show complex altered patterns and vary with the stage of the disease, and there are elements of associated autoimmunity.  These complex changes are accompanied by an altered molecular homeostasis with immune cell transcripts and proteins no longer produced in a tightly regulated manner, reflected in the instability of the epigenetic code that controls gene expression.

Potential key elements of the altered immune function in this disease needing further exploration are changes to the gut-brain-immune axis as a result of changes in the microbiome of the gut, and viral reactivation from latent elements of the triggering virus or from a prior viral infection. Long COVID, an Myalgic Encephalomyelitis/Chronic Fatigue Syndrome-like illness, is the post-viral condition that has arisen in large numbers solely from the pandemic virus Severe Acute Respiratory Syndrome Coronovirus-2.

With over 760 million cases worldwide, an estimated ~100 million cases of Long COVID have occurred within a short period. This now provides an unprecedented opportunity to understand the progression of these post-viral diseases, and to progress from a research phase mainly documenting the immune changes to considering potential immunotherapies that might improve the overall symptom profile of affected patients, and provide them with a better quality of life.

Source: WALKER, Max O.M. et al. An understanding of the immune dysfunction in susceptible people who develop the post-viral fatigue syndromes Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Long COVID. Medical Research Archives, [S.l.], v. 11, n. 7.1, july 2023. ISSN 2375-1924. Available at: <https://esmed.org/MRA/mra/article/view/4083>. Date accessed: 15 july 2023. doi: https://doi.org/10.18103/mra.v11i7.1.4083. https://esmed.org/MRA/mra/article/view/4083/99193547075 (Full text as PDF file)

Mitochondrial impairment but not peripheral inflammation predicts greater Gulf War illness severity

Abstract:

Gulf War illness (GWI) is an important exemplar of environmentally-triggered chronic multisymptom illness, and a potential model for accelerated aging. Inflammation is the main hypothesized mechanism for GWI, with mitochondrial impairment also proposed. No study has directly assessed mitochondrial respiratory chain function (MRCF) on muscle biopsy in veterans with GWI (VGWI).

We recruited 42 participants, half VGWI, with biopsy material successfully secured in 36. Impaired MRCF indexed by complex I and II oxidative phosphorylation with glucose as a fuel source (CI&CIIOXPHOS) related significantly or borderline significantly in the predicted direction to 17 of 20 symptoms in the combined sample. Lower CI&CIIOXPHOS significantly predicted GWI severity in the combined sample and in VGWI separately, with or without adjustment for hsCRP. Higher-hsCRP (peripheral inflammation) related strongly to lower-MRCF (particularly fatty acid oxidation (FAO) indices) in VGWI, but not in controls.

Despite this, whereas greater MRCF-impairment predicted greater GWI symptoms and severity, greater inflammation did not. Surprisingly, adjusted for MRCF, higher hsCRP significantly predicted lesser symptom severity in VGWI selectively. Findings comport with a hypothesis in which the increased inflammation observed in GWI is driven by FAO-defect-induced mitochondrial apoptosis.

In conclusion, impaired mitochondrial function—but not peripheral inflammation—predicts greater GWI symptoms and severity.

Source: Golomb, B.A., Sanchez Baez, R., Schilling, J.M. et al. Mitochondrial impairment but not peripheral inflammation predicts greater Gulf War illness severity. Sci Rep 13, 10739 (2023). https://doi.org/10.1038/s41598-023-35896-w https://www.nature.com/articles/s41598-023-35896-w (Full text)

Determinants of the Onset and Prognosis of the Post-COVID-19 Condition: A 2-Year Prospective Cohort Study

Abstract:

Background: At least 5-10% of subjects surviving COVID-19 develop the post-COVID-19 condition (PCC) or “Long COVID”. The clinical presentation of PCC is heterogeneous, its pathogenesis is being deciphered, and objective, validated biomarkers are lacking. It is unknown if PCC is a single entity or a heterogeneous syndrome with overlapping pathophysiological basis. In a large crossectional evaluation, the RECOVER study in the US identified four clusters of subjects with PCC according to their presenting symptoms. The long-term clinical implications of PCC remain unknown.

Methods: We conducted a 2-year prospective cohort study of subjects surviving COVID-19, including individuals fulfilling the WHO PCC definition and subjects with full clinical recovery. We systematically collected post-COVID-19 symptoms using prespecified questionnaires and performed additional diagnostic imaging tests when needed. Factors associated with PCC were identified and modeled using logistic regression. Unsupervised clustering analysis was used to group subjects with PCC according to their presenting symptoms. Factors associated with PCC recovery were modelled using a direct acyclic graph approach.

Findings: The study included 548 individuals, 341 with PCC, followed for a median of 23 months (IQR 16·5 – 23·5), and 207 subjects fully recovered. In the model with the best fit, subjects who were male and had tertiary studies were less likely to develop PCC, whereas a history of headache, or presence of tachycardia, fatigue, neurocognitive and neurosensitive complaints and dyspnea at COVID-19 diagnosis predicted the development of PCC. The cluster analysis revealed the presence of three symptom clusters with an additive number of symptoms. Only 26 subjects (7·6%) recovered from PCC during follow-up; almost all of them (n=24) belonged to the less symptomatic cluster A, dominated mainly by fatigue. Recovery from PCC was more likely in subjects who were male, required ICU admission, or had cardiovascular comorbidities, hyporexia and/or smell/taste alterations during acute COVID-19. Subjects presenting with muscle pain, impaired attention, dyspnea, or tachycardia, conversely, were less likely to recover from PCC.

Interpretation: Preexisting medical and socioeconomic factors, as well as acute COVID-19 symptoms, predict the development of and recovery from the PCC. Recovery is extremely rare during the first 2 years, posing a major challenge to healthcare systems.

Source: Mateu, Lourdes and Tebe, Cristian and Loste, Cora and Santos, José Ramón and Lladós, Gemma and López, Cristina and España-Cueto, Sergio and Toledo, Ruth and Font, Marta and Chamorro, Anna and Muñoz-López, Francisco and Nevot, Maria and Vallejo, Nuria and Teis, Albert and Puig, Jordi and Fumaz, Carmina Rodríguez and Muñoz-Moreno, José Antonio and Prats, Anna and Estany-Quera, Carla and Coll-Fernández, Roser and Herrero, Cristina and Casares, Patricia and Garcia, Anna and Paredes, Roger and Clotet, Bonaventura and Massanella, Marta, Determinants of the Onset and Prognosis of the Post-COVID-19 Condition: A 2-Year Prospective Cohort Study. Available at SSRN: https://ssrn.com/abstract=4505315 or http://dx.doi.org/10.2139/ssrn.4505315 (Full text available as PDF file)

The immunology of long COVID

Abstract:

Long COVID is the patient-coined term for the disease entity whereby persistent symptoms ensue in a significant proportion of those who have had COVID-19, whether asymptomatic, mild or severe. Estimated numbers vary but the assumption is that, of all those who had COVID-19 globally, at least 10% have long COVID. The disease burden spans from mild symptoms to profound disability, the scale making this a huge, new health-care challenge.

Long COVID will likely be stratified into several more or less discrete entities with potentially distinct pathogenic pathways. The evolving symptom list is extensive, multi-organ, multisystem and relapsing–remitting, including fatigue, breathlessness, neurocognitive effects and dysautonomia. A range of radiological abnormalities in the olfactory bulb, brain, heart, lung and other sites have been observed in individuals with long COVID. Some body sites indicate the presence of microclots; these and other blood markers of hypercoagulation implicate a likely role of endothelial activation and clotting abnormalities.

Diverse auto-antibody (AAB) specificities have been found, as yet without a clear consensus or correlation with symptom clusters. There is support for a role of persistent SARS-CoV-2 reservoirs and/or an effect of Epstein–Barr virus reactivation, and evidence from immune subset changes for broad immune perturbation. Thus, the current picture is one of convergence towards a map of an immunopathogenic aetiology of long COVID, though as yet with insufficient data for a mechanistic synthesis or to fully inform therapeutic pathways.

Source: Altmann, D.M., Whettlock, E.M., Liu, S. et al. The immunology of long COVID. Nat Rev Immunol (2023). https://doi.org/10.1038/s41577-023-00904-7 https://www.nature.com/articles/s41577-023-00904-7 (Full text)

Long COVID prevalence and impact on quality of life 2 years after acute COVID-19

Abstract:

There has been an increasing interest in the long-term impact of long COVID. However, only a few studies have investigated the clinical manifestations of long COVID after 24 months of acute infection. In this study, prospective online surveys were conducted in adults previously diagnosed with coronavirus disease 2019 (COVID-19) in South Korea between February 13 and March 13, 2020, at 6, 12, and 24 months after COVID-19.

We investigated self-reported symptoms and the EuroQol-5-dimension index. Among 900 individuals enrolled initially, 150 completed all 3 surveys. After excluding the cases of COVID-19 reinfection, 132 individuals were included in the final analysis. Among the 132 participants, 94 (71.2%) experienced symptoms of long COVID. The most frequently reported symptoms were fatigue (34.8%), amnesia (30.3%), concentration difficulties (24.2%), insomnia (20.5%), and depression (19.7%). Notably, no significant differences were noted in the incidence of long COVID at 24 months in terms of the number of vaccinations received.

Although the neuropsychiatric quality of life improved over time, it continued to affect 32.7% of participants. Symptoms of long COVID, particularly neuropsychiatric symptoms, tend to persist over time, and COVID-19 vaccination or the number of vaccinations received may not significantly affect the incidence of long COVID.

Source: Kim Y, Bae S, Chang HH, Kim SW. Long COVID prevalence and impact on quality of life 2 years after acute COVID-19. Sci Rep. 2023 Jul 11;13(1):11207. doi: 10.1038/s41598-023-36995-4. PMID: 37433819. https://www.nature.com/articles/s41598-023-36995-4 (Full text)

Altered brain connectivity in Long Covid during cognitive exertion: a pilot study

Abstract:

Introduction: Debilitating Long-Covid symptoms occur frequently after SARS-COVID-19 infection.

Methods: Functional MRI was acquired in 10 Long Covid (LCov) and 13 healthy controls (HC) with a 7 Tesla scanner during a cognitive (Stroop color-word) task. BOLD time series were computed for 7 salience and 4 default-mode network hubs, 2 hippocampus and 7 brainstem regions (ROIs). Connectivity was characterized by the correlation coefficient between each pair of ROI BOLD time series. We tested for HC versus LCov differences in connectivity between each pair of the 20 regions (ROI-to-ROI) and between each ROI and the rest of the brain (ROI-to-voxel). For LCov, we also performed regressions of ROI-to-ROI connectivity with clinical scores.

Results: Two ROI-to-ROI connectivities differed between HC and LCov. Both involved the brainstem rostral medulla, one connection to the midbrain, another to a DM network hub. Both were stronger in LCov than HC. ROI-to-voxel analysis detected multiple other regions where LCov connectivity differed from HC located in all major lobes. Most, but not all connections, were weaker in LCov than HC. LCov, but not HC connectivity, was correlated with clinical scores for disability and autonomic function and involved brainstem ROI.

Discussion: Multiple connectivity differences and clinical correlations involved brainstem ROIs. Stronger connectivity in LCov between the medulla and midbrain may reflect a compensatory response. This brainstem circuit regulates cortical arousal, autonomic function and the sleep-wake cycle. In contrast, this circuit exhibited weaker connectivity in ME/CFS. LCov connectivity regressions with disability and autonomic scores were consistent with altered brainstem connectivity in LCov.

Source: Barnden L, Thapaliya K, Eaton-Fitch N, Barth M, Marshall-Gradisnik S. Altered brain connectivity in Long Covid during cognitive exertion: a pilot study. Front Neurosci. 2023 Jun 22;17:1182607. doi: 10.3389/fnins.2023.1182607. PMID: 37425014; PMCID: PMC10323677. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10323677/ (Full text)