Conceptual foundations of acetylcarnitine supplementation in neuropsychiatric long COVID syndrome: a narrative review

Abstract:

Post-acute sequelae of COVID-19 can present as multi-organ pathology, with neuropsychiatric symptoms being the most common symptom complex, characterizing long COVID as a syndrome with a significant disease burden for affected individuals. Several typical symptoms of long COVID, such as fatigue, depressive symptoms and cognitive impairment, are also key features of other psychiatric disorders such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and major depressive disorder (MDD). However, clinically successful treatment strategies are still lacking and are often inspired by treatment options for diseases with similar clinical presentations, such as ME/CFS.

Acetylcarnitine, the shortest metabolite of a class of fatty acid metabolites called acylcarnitines and one of the most abundant blood metabolites in humans can be used as a dietary/nutritional supplement with proven clinical efficacy in the treatment of MDD, ME/CFS and other neuropsychiatric disorders. Basic research in recent decades has established acylcarnitines in general, and acetylcarnitine in particular, as important regulators and indicators of mitochondrial function and other physiological processes such as neuroinflammation and energy production pathways.

In this review, we will compare the clinical basis of neuropsychiatric long COVID with other fatigue-associated diseases. We will also review common molecular disease mechanisms associated with altered acetylcarnitine metabolism and the potential of acetylcarnitine to interfere with these as a therapeutic agent. Finally, we will review the current evidence for acetylcarnitine as a supplement in the treatment of fatigue-associated diseases and propose future research strategies to investigate the potential of acetylcarnitine as a treatment option for long COVID.

Source: Helbing DL, Dommaschk EM, Danyeli LV, Liepinsh E, Refisch A, Sen ZD, Zvejniece L, Rocktäschel T, Stabenow LK, Schiöth HB, Walter M, Dambrova M, Besteher B. Conceptual foundations of acetylcarnitine supplementation in neuropsychiatric long COVID syndrome: a narrative review. Eur Arch Psychiatry Clin Neurosci. 2024 Jan 3. doi: 10.1007/s00406-023-01734-3. Epub ahead of print. PMID: 38172332. https://link.springer.com/article/10.1007/s00406-023-01734-3 (Full text)

KombOver: Efficient k-core and K-truss based characterization of perturbations within the human gut microbiome

Abstract:

The microbes present in the human gastrointestinal tract are regularly linked to human health and disease outcomes. Thanks to technological and methodological advances in recent years, metagenomic sequencing data, and computational methods designed to analyze metagenomic data, have contributed to improved understanding of the link between the human gut microbiome and disease. However, while numerous methods have been recently developed to extract quantitative and qualitative results from host-associated microbiome data, improved computational tools are still needed to track microbiome dynamics with short-read sequencing data.

Previously we have proposed KOMB as a de novo tool for identifying copy number variations in metagenomes for characterizing microbial genome dynamics in response to perturbations. In this work, we present KombOver (KO), which includes four key contributions with respect to our previous work: (i) it scales to large microbiome study cohorts, (ii) it includes both k-core and K-truss based analysis, (iii) we provide the foundation of a theoretical understanding of the relation between various graph-based metagenome representations, and (iv) we provide an improved user experience with easier-to-run code and more descriptive outputs/results.

To highlight the aforementioned benefits, we applied KO to nearly 1000 human microbiome samples, requiring less than 10 minutes and 10 GB RAM per sample to process these data. Furthermore, we highlight how graph-based approaches such as k-core and K-truss can be informative for pinpointing microbial community dynamics within a myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) cohort. KO is open source and available for download/use at: https://github.com/treangenlab/komb.

Source: Sapoval N, Tanevski M, Treangen TJ. KombOver: Efficient k-core and K-truss based characterization of perturbations within the human gut microbiome. Pac Symp Biocomput. 2024;29:506-520. PMID: 38160303; PMCID: PMC10764071. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10764071/ (Full text)

Muscle abnormalities worsen after post-exertional malaise in long COVID

Abstract:

A subgroup of patients infected with SARS-CoV-2 remain symptomatic over three months after infection. A distinctive symptom of patients with long COVID is post-exertional malaise, which is associated with a worsening of fatigue- and pain-related symptoms after acute mental or physical exercise, but its underlying pathophysiology is unclear.

With this longitudinal case-control study (NCT05225688), we provide new insights into the pathophysiology of post-exertional malaise in patients with long COVID. We show that skeletal muscle structure is associated with a lower exercise capacity in patients, and local and systemic metabolic disturbances, severe exercise-induced myopathy and tissue infiltration of amyloid-containing deposits in skeletal muscles of patients with long COVID worsen after induction of post-exertional malaise. This study highlights novel pathways that help to understand the pathophysiology of post-exertional malaise in patients suffering from long COVID and other post-infectious diseases.

Source: Appelman, B., Charlton, B.T., Goulding, R.P. et al. Muscle abnormalities worsen after post-exertional malaise in long COVID. Nat Commun 15, 17 (2024). https://doi.org/10.1038/s41467-023-44432-3 https://www.nature.com/articles/s41467-023-44432-3 (Full text)

Heterogenous circulating miRNA changes in ME/CFS converge on a unified cluster of target genes: A computational analysis

Abstract:

Myalgic Encephalomyelitis / Chronic Fatigue Syndrome is a debilitating, multisystem disease of unknown mechanism, with a currently ongoing search for its endocrine mediators. Circulating microRNAs (miRNA) are a promising candidate for such a mediator and have been reported as significantly different in the patient population versus healthy controls by multiple studies. None of these studies, however, agree with each other on which specific miRNA are under- or over-expressed.

This discrepancy is the subject of the computational study presented here, in which a deep dive into the predicted gene targets and their functional interactions is conducted, revealing that the aberrant circulating miRNAs in ME/CFS, although different between patients, seem to mainly target the same specific set of genes (p ≈ 0.0018), which are very functionally related to each other (p ≲ 0.0001).

Further analysis of these functional relations, based on directional pathway information, points to impairments in exercise hyperemia, angiogenic adaptations to hypoxia, antioxidant defenses, and TGF-β signaling, as well as a shift towards mitochondrial fission, corroborating and explaining previous direct observations in ME/CFS. Many transcription factors and epigenetic modulators are implicated as well, with currently uncertain downstream combinatory effects.

As the results show significant similarity to previous research on latent herpesvirus involvement in ME/CFS, the possibility of a herpesvirus origin of these miRNA changes is also explored through further computational analysis and literature review, showing that 8 out of the 10 most central miRNAs analyzed are known to be upregulated by various herpesviruses. In total, the results establish an appreciable and possibly central role for circulating microRNAs in ME/CFS etiology that merits further experimental research.

Source: Kaczmarek MP. Heterogenous circulating miRNA changes in ME/CFS converge on a unified cluster of target genes: A computational analysis. PLoS One. 2023 Dec 29;18(12):e0296060. doi: 10.1371/journal.pone.0296060. PMID: 38157384; PMCID: PMC10756525. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10756525/ (Full text)

Role of pharmacological activity of autoantibodies in ME/CFS

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a condition characterised by extreme fatigue, memory impairment, pain and other symptoms that vary from patient to patient. It affects about 0.9% of the population and is often triggered by an acute viral or bacterial infection, such as Epstein-Barr virus. The underlying physiological and molecular basis of ME/CFS is unknown, and no effective treatments exist.

One proposed mechanism is that the blood flow is altered by autoantibodies against receptors involved in blood flow regulation. Antibodies are generated by the immune system to recognise intruders and under normal conditions, our immune system is trained not to attack our own tissues. However, during a severe infection, the immune system adopts an “all hands on deck” approach, which results in some of the newly-produced antibodies escaping quality control and targeting our own tissues, autoantibodies. Receptors regulation blood flow are located in walls of blood vessels and cause a blood vessel to dilate or contract as the demand for oxygen and nutrients to tissues such as the brain or muscles changes. Research has found increased levels of these autoantibodies in ME/CFS patients and initial trials removing these autoantibodies from the blood using a technique called immunoadsorption have shown improvement in symptoms.

In this project, we will test the hypothesis that autoantibodies can activate or inhibit the receptors responsible for the blood flow regulation, in a similar way medical drugs are used to regulate blood pressure.
We aim to profile serum samples from 325 ME/CFS patients and 130 healthy individuals to determine the presence of autoantibodies against all thirty receptors involved in blood pressure regulation. Importantly, we will study the ability of autoantibodies detected in each sample to activate or inhibit these receptors in order to test the hypothesis that the activity of these autoantibodies is a decisive factor in the disease.
If our hypothesis is correct, we will be able to develop an accurate blood test that may be able to detect ME/CFS earlier or to independently confirm the diagnosis. Ultimately, we hope that these results may also indicate a possible route for therapeutic intervention to counteract the effects of autoantibodies and alleviate the ME/CFS symptoms using a combination of already existing drugs, specific for each individual case.

 

Technical Summary:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a condition of extreme tiredness and brain fog, often triggered by an acute infection. Its prevalence is ca 0.9% and here is no effective treatment. Competing theories for the root cause of ME/CFS include metabolic or redox homeostasis disruption, and presence of autoantibodies (AABs) against G protein coupled receptors (GPCRs) involved in regulation of blood flow.
Triggered by acute infection, autoimmunity is a result of reduced immuno-vigilance during severe infections, when an “all hands on deck” approach confers survival advantage. About 30% of ME/CFS patients show increased titre of autoantibodies against beta2-adrenoceptor and M3/4 muscarinic receptors controlling vasodilation/vasoconstriction, but this could become higher if all 30 receptors controlling blood flow would be taken into account.
In this project, we will test a hypothesis that the pharmacological activity of AABs against GPCRs is the key to their involvement in ME/CFS. Similar to medical drugs, AABs can be stimulatory (agonistic) or inhibitory (antagonistic) and induce a therapeutic or an undesired side effect.
We will profile 325 patient samples and 130 control plasma samples for AABs and their pharmacological activity using a state-of-the art GPCR drug screening pipeline we have established, against all 30 GPCRs involved in blood pressure regulation. We also have machine learning expertise that would allow us to interpret this extensive dataset, extract the most salient features. This will advance the understanding of the molecular basis of ME/CFS and could form the basis of a robust diagnostic blood test for ME/CFS. Ultimately, our findings may point in the direction of developing combination therapy using repurposed drugs to counteract the effects of autoantibodies and mitigate ME/CFS symptoms and stimulate the development of specific B-cell elimination strategy to cure ME/CFS.
Source: Lead Research Organisation: University of Nottingham, Department Name: School of Life Sciences. https://gtr.ukri.org/projects?ref=MR%2FY003667%2F1&pn=0&fetchSize=25&selectedSortableField=date&selectedSortOrder=ASC

Mitochondrial Dysfunction and Coenzyme Q10 Supplementation in Post-Viral Fatigue Syndrome: An Overview

Abstract:

Post-viral fatigue syndrome (PVFS) encompasses a wide range of complex neuroimmune disorders of unknown causes characterised by disabling post-exertional fatigue, myalgia and joint pain, cognitive impairments, unrefreshing sleep, autonomic dysfunction, and neuropsychiatric symptoms. It includes myalgic encephalomyelitis, also known as chronic fatigue syndrome (ME/CFS); fibromyalgia (FM); and more recently post-COVID-19 condition (long COVID). To date, there are no definitive clinical case criteria and no FDA-approved pharmacological therapies for PVFS. Given the current lack of effective treatments, there is a need to develop novel therapeutic strategies for these disorders.
Mitochondria, the cellular organelles responsible for tissue energy production, have recently garnered attention in research into PVFS due to their crucial role in cellular bioenergetic metabolism in these conditions. The accumulating literature has identified a link between mitochondrial dysfunction and low-grade systemic inflammation in ME/CFS, FM, and long COVID. To address this issue, this article aims to critically review the evidence relating to mitochondrial dysfunction in the pathogenesis of these disorders; in particular, it aims to evaluate the effectiveness of coenzyme Q10 supplementation on chronic fatigue and pain symptoms as a novel therapeutic strategy for the treatment of PVFS.
Source: Mantle D, Hargreaves IP, Domingo JC, Castro-Marrero J. Mitochondrial Dysfunction and Coenzyme Q10 Supplementation in Post-Viral Fatigue Syndrome: An Overview. International Journal of Molecular Sciences. 2024; 25(1):574. https://doi.org/10.3390/ijms25010574 https://www.mdpi.com/1422-0067/25/1/574 (Full text)

Why the Psychosomatic View on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Is Inconsistent with Current Evidence and Harmful to Patients

Abstract:

Since 1969, Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) has been classified as a neurological disease in the International Classification of Diseases by the World Health Organization. Although numerous studies over time have uncovered organic abnormalities in patients with ME/CFS, and the majority of researchers to date classify the disease as organic, many physicians still believe that ME/CFS is a psychosomatic illness.
In this article, we show how detrimental this belief is to the care and well-being of affected patients and, as a consequence, how important the education of physicians and the public is to stop misdiagnosis, mistreatment, and stigmatization on the grounds of incorrect psychosomatic attributions about the etiology and clinical course of ME/CFS.
Source: Thoma M, Froehlich L, Hattesohl DBR, Quante S, Jason LA, Scheibenbogen C. Why the Psychosomatic View on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Is Inconsistent with Current Evidence and Harmful to Patients. Medicina. 2024; 60(1):83. https://doi.org/10.3390/medicina60010083 https://www.mdpi.com/1648-9144/60/1/83 (Full text)

A Mechanistic Model for Long COVID Dynamics

Abstract:

Long COVID, a long-lasting disorder following an acute infection of COVID-19, represents a significant public health burden at present. In this paper, we propose a new mechanistic model based on differential equations to investigate the population dynamics of long COVID. By connecting long COVID with acute infection at the population level, our modeling framework emphasizes the interplay between COVID-19 transmission, vaccination, and long COVID dynamics. We conducted a detailed mathematical analysis of the model. We also validated the model using numerical simulation with real data from the US state of Tennessee and the UK.

Source: Derrick J, Patterson B, Bai J, Wang J. A Mechanistic Model for Long COVID Dynamics. Mathematics (Basel). 2023 Nov;11(21):4541. doi: 10.3390/math11214541. Epub 2023 Nov 3. PMID: 38111916; PMCID: PMC10727852. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10727852/ (Full text)

Profound Symptom Alleviation in Long-Covid Patients After PAMP-Immunotherapy: Three Case Reports

Abstract:

Background: Long-Covid patients suffer from a range of symptoms with a largely varying degree of severity, including chronic fatigue syndrome (CFS), myalgic encephalomyelitis (ME), post-exertional malaise (PEM), postural orthostatic tachycardia syndrome (POTS), loss of smell and/or taste, cough, shortness of breath, headache, muscle ache, sleep disturbance, cognitive dysfunction, and depression.

Treatment: PAMP-immunotherapy was developed by one of us (UH), inspired by the old fever therapy a century ago, to treat cancer patients. Unintentionally, in three cases of Long-Covid, quick and profound symptom alleviation could be observed after only a few PAMP treatments.

Conclusion: PAMP-immunotherapy might be a treatment option for Long-Covid patients which is surprisingly brief, cheap, and effective.

Source: Raphaela Gaudek, Holger Porath, Uwe Hobohm. (2023). [Case Report] Profound Symptom Alleviation in Long-Covid Patients After PAMP-Immunotherapy: Three Case Reports. Qeios. doi:10.32388/69I32L. https://www.qeios.com/read/69I32L (Full text)

Data-driven prognosis of long COVID in patients using machine learning

Abstract:

Long-COVID is a health condition in which individuals experience persisting, returning or new symptoms longer than 4 weeks after they have recovered from COVID-19 and this condition can even last for months. It can cause multi-organ failure and in some cases, it can even lead to death. The effects and symptoms of Long COVID can vary from person to person. Even though it’s rising globally, there is a limited understanding about its prediction, risk factors and whether its prognosis can be predicted in the initial first week of acute COVID-19. Artificial Intelligence (AI) and Machine Learning (ML) have aided the medical industry in a variety of ways including the diagnosis, prediction, and prognosis of many diseases.

This paper introduces a novel method to determine Long COVID in the early or first week of acute COVID-19 by considering the basic demographics, and symptoms during COVID-19, along with the clinical lab results of the patients hospitalized. In comparison with different ML models such as Logistic Regression, Support Vector Machine (SVM), XGBoost and Artificial Neural Network (ANN) to predict and classify the patients as Long COVID or Short COVID during the first week of COVID-19, ANN has outperformed the other models with an accuracy of 81% when considering the symptoms of COVID-19 and a 79% for the clinical test data. The predictive factors and the significant clinical tests for the Long COVID are also determined by using different methods like Chi-square Test and Pearson Correlation.

Source: S. S. Parvathy, Nagesh Subbanna, Sethuraman Rao, Rahul Krishnan Pathinarupothi, T. S. Dipu, Merlin Moni, Chithira V. Nair; Data-driven prognosis of long COVID in patients using machine learning. AIP Conf. Proc. 15 December 2023; 2901 (1): 060014. https://doi.org/10.1063/5.0178561 https://pubs.aip.org/aip/acp/article/2901/1/060014/2930006 (Full text available as PDF file)