Tag: long Covid

Exploring Cognitive Dysfunction in Long COVID Patients: Eye Movement Abnormalities and Frontal-Subcortical Circuits Implications via Eye-Tracking and Machine Learning

Abstract:

Background: Cognitive dysfunction is regarded as one of the most severe aftereffects following coronavirus disease 2019 (COVID-19). Eye movements, controlled by various brain regions, including the dorsolateral prefrontal cortex and frontal-thalamic circuits, offer a potential metric for evaluating cognitive dysfunction. We aimed to examine the utility of eye movement measurements in identifying cognitive impairments in long COVID patients.

Methods: We recruited 40 long COVID patients experiencing subjective cognitive complaints and 40 healthy controls and used a certified eye-tracking medical device to record saccades and antisaccades. Machine learning was applied to enhance the analysis of eye movement data.

Results: Patients did not differ from the healthy controls regarding age, sex, and years of education. However, the patients’ Montreal Cognitive Assessment total score was significantly lower than healthy controls. Most eye movement parameters were significantly worse in patients: the latencies, gain, and velocity of visually and memory-guided saccades, the number of correct memory saccades, the latencies and duration of reflexive saccades, and the number of errors in the antisaccade test. Machine learning permitted distinguishing between long COVID patients experiencing subjective cognitive complaints and healthy controls.

Conclusion: Our findings suggest impairments in frontal subcortical circuits in long COVID patients experiencing subjective cognitive complaints. Eye-tracking, combined with machine learning, offers a novel, efficient way to assess and monitor long COVID patients’ cognitive dysfunctions, suggesting its utility in clinical settings for early detection and personalized treatment strategies. Further research is needed to determine the long-term implications of these findings and the reversibility of cognitive dysfunctions.

Source: Benito-León J, Lapeña J, García-Vasco L, Cuevas C, Viloria-Porto J, Calvo-Córdoba A, Arrieta-Ortubay E, Ruiz-Ruigómez M, Sánchez-Sánchez C, García-Cena C. Exploring Cognitive Dysfunction in Long COVID Patients: Eye Movement Abnormalities and Frontal-Subcortical Circuits Implications via Eye-Tracking and Machine Learning. Am J Med. 2024 Apr 5:S0002-9343(24)00217-1. doi: 10.1016/j.amjmed.2024.04.004. Epub ahead of print. PMID: 38583751. https://pubmed.ncbi.nlm.nih.gov/38583751/

Long COVID and post-acute sequelae of SARS-CoV-2 pathogenesis and treatment: A Keystone Symposia report

Abstract:

In 2023, the Keystone Symposia held the first international scientific conference convening research leaders investigating the pathology of post-acute sequelae of COVID-19 (PASC) or Long COVID, a growing and urgent public health priority. In this report, we present insights from the talks and workshops presented during this meeting and highlight key themes regarding what researchers have discovered regarding the underlying biology of PASC and directions toward future treatment.

Several themes have emerged in the biology, with inflammation and other immune alterations being the most common focus, potentially related to viral persistence, latent virus reactivation, and/or tissue damage and dysfunction, especially of the endothelium, nervous system, and mitochondria.

In order to develop safe and effective treatments for people with PASC, critical next steps should focus on the replication of major findings regarding potential mechanisms, disentangling pathogenic mechanisms from downstream effects, development of cellular and animal models, mechanism-focused randomized, placebo-controlled trials, and closer collaboration between people with lived experience, scientists, and other stakeholders.

Ultimately, by learning from other post-infectious syndromes, the knowledge gained may help not only those with PASC/Long COVID, but also those with other post-infectious syndromes.

Source: Matthew S. Durstenfeld, Shannon Weiman, Michael Holtzman, Catherine Blish, Resia Pretorius, Steven G. Deeks. Long COVID and post-acute sequelae of SARS-CoV-2 pathogenesis and treatment: A Keystone Symposia report. First published: 09 April 2024 https://doi.org/10.1111/nyas.15132 https://nyaspubs.onlinelibrary.wiley.com/doi/10.1111/nyas.15132 (Full text)

Cluster analysis of long COVID symptoms for deciphering a syndrome and its long-term consequence

Abstract:

The long-term symptoms of COVID-19 are the subject of public and scientific discussions. Understanding how those long COVID symptoms co-occur in clusters of syndromes may indicate the pathogenic mechanisms of long COVID. Our study objective was to cluster the different long COVID symptoms. We included persons who had a COVID-19 and assessed long-term symptoms (at least 4 weeks after first symptoms). Hierarchical clustering was applied to the symptoms as well as to the participants based on the Euclidean distance h of the log-values of the answers on symptom severity. The distribution of clusters within our cohort is shown in a heat map.

From September 2021 to November 2023, 2371 persons with persisting long COVID symptoms participated in the study. Self-assessed long COVID symptoms were assigned to three symptom clusters. Cluster A unites rheumatological and neurological symptoms, cluster B includes neuro-psychological symptoms together with cardiorespiratory symptoms, and a third cluster C shows an association of general infection signs, dermatological and otology symptoms. A high proportion of the participants (n = 1424) showed symptoms of all three clusters.

Clustering of long COVID symptoms reveals similarities to the symptomatology of already described syndromes such as the Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) or rheumatological autoinflammatory diseases. Further research may identify serological parameters or clinical risk factors associated with the shown clusters and might improve our understanding of long COVID as a systemic disease. Furthermore, multimodal treatments can be developed and scaled for symptom clusters and associated impairments.

Source: Niewolik J, Mikuteit M, Klawitter S, Schröder D, Stölting A, Vahldiek K, Heinemann S, Müller F, Behrens G, Klawonn F, Dopfer-Jablonka A, Steffens S. Cluster analysis of long COVID symptoms for deciphering a syndrome and its long-term consequence. Immunol Res. 2024 Apr 16. doi: 10.1007/s12026-024-09465-w. Epub ahead of print. PMID: 38627327. https://link.springer.com/article/10.1007/s12026-024-09465-w (Full text)

Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease

Abstract:

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered.

Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain-gut axis disturbance, was elevated in gastrointestinal symptoms.

Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms.

Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials.

Source: Liew F, Efstathiou C, Fontanella S, Richardson M, Saunders R, Swieboda D, Sidhu JK, Ascough S, Moore SC, Mohamed N, Nunag J, King C, Leavy OC, Elneima O, McAuley HJC, Shikotra A, Singapuri A, Sereno M, Harris VC, Houchen-Wolloff L, Greening NJ, Lone NI, Thorpe M, Thompson AAR, Rowland-Jones SL, Docherty AB, Chalmers JD, Ho LP, Horsley A, Raman B, Poinasamy K, Marks M, Kon OM, Howard LS, Wootton DG, Quint JK, de Silva TI, Ho A, Chiu C, Harrison EM, Greenhalf W, Baillie JK, Semple MG, Turtle L, Evans RA, Wain LV, Brightling C, Thwaites RS, Openshaw PJM; PHOSP-COVID collaborative group; ISARIC investigators. Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease. Nat Immunol. 2024 Apr;25(4):607-621. doi: 10.1038/s41590-024-01778-0. Epub 2024 Apr 8. PMID: 38589621; PMCID: PMC11003868. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11003868/ (Full text)

An Unwanted but Long-Known Company: Post-Viral Symptoms in the Context of Past Pandemics in Switzerland (and Beyond)

Abstract:

Objectives: Some people do not fully recover from an acute viral infection and experience persistent symptoms or incomplete recovery for months or even years. This is not unique to the SARS-CoV-2 virus and history shows that post-viral conditions like post COVID-19 condition, also referred to as Long Covid, are not new. In particular, during and after pandemics caused by respiratory viruses in which large parts of the population were infected or exposed, professional and public attention was increased, not least because of the large number of people affected.

Methods: Given the current relevance of the topic, this article aims to narratively review and summarize the literature on post-viral symptoms during past pandemics and to supplement and illustrate it with Swiss examples from the pandemics of 1890, 1918–1920 and later.

Results: Post-viral diseases were an increasingly emphasised health topic during and after past pandemics triggered by respiratory infections over the last 150 years.

Conclusion: In the next pandemic, it should not be surprising that post-viral conditions will again play a role, and pandemic plans should reflect this.

Source: Staub, Kaspar; Ballouz, Tala; Puhan, Milo (2024). An Unwanted but Long-Known Company: Post-Viral Symptoms in the Context of Past Pandemics in Switzerland (and Beyond). Public Health Reviews, 45:1606966. https://www.ssph-journal.org/articles/10.3389/phrs.2024.1606966/full (Full text)

Reinforcing the Evidence of Mitochondrial Dysfunction in Long COVID Patients Using a Multiplatform Mass Spectrometry-Based Metabolomics Approach

Abstract:

Despite the recent and increasing knowledge surrounding COVID-19 infection, the underlying mechanisms of the persistence of symptoms for a long time after the acute infection are still not completely understood. Here, a multiplatform mass spectrometry-based approach was used for metabolomic and lipidomic profiling of human plasma samples from Long COVID patients (n = 40) to reveal mitochondrial dysfunction when compared with individuals fully recovered from acute mild COVID-19 (n = 40).

Untargeted metabolomic analysis using CE-ESI(+/-)-TOF-MS and GC-Q-MS was performed. Additionally, a lipidomic analysis using LC-ESI(+/-)-QTOF-MS based on an in-house library revealed 447 lipid species identified with a high confidence annotation level. The integration of complementary analytical platforms has allowed a comprehensive metabolic and lipidomic characterization of plasma alterations in Long COVID disease that found 46 relevant metabolites which allowed to discriminate between Long COVID and fully recovered patients.

We report specific metabolites altered in Long COVID, mainly related to a decrease in the amino acid metabolism and ceramide plasma levels and an increase in the tricarboxylic acid (TCA) cycle, reinforcing the evidence of an impaired mitochondrial function. The most relevant alterations shown in this study will help to better understand the insights of Long COVID syndrome by providing a deeper knowledge of the metabolomic basis of the pathology.

Source: Martínez S, Albóniga OE, López-Huertas MR, Gradillas A, Barbas C. Reinforcing the Evidence of Mitochondrial Dysfunction in Long COVID Patients Using a Multiplatform Mass Spectrometry-Based Metabolomics Approach. J Proteome Res. 2024 Apr 2. doi: 10.1021/acs.jproteome.3c00706. Epub ahead of print. PMID: 38566450. https://pubmed.ncbi.nlm.nih.gov/38566450/

Brain and cognitive changes in patients with long COVID compared with infection-recovered control subjects

Abstract:

Between 2.5 and 28% of people infected with SARS-CoV-2 suffer Long COVID or persistence of symptoms for months after acute illness. Many symptoms are neurological, but the brain changes underlying the neuropsychological impairments remain unclear. This study aimed to provide a detailed description of the cognitive profile, the pattern of brain alterations in Long COVID and the potential association between them.

To address these objectives, 83 patients with persistent neurological symptoms after COVID-19 were recruited, and 22 now healthy controls chosen because they had suffered COVID-19 but did not experience persistent neurological symptoms. Patients and controls were matched for age, sex and educational level. All participants were assessed by clinical interview, comprehensive standardized neuropsychological tests and structural MRI. The mean global cognitive function of patients with Long COVID assessed by ACE III screening test (Overall Cognitive level – OCLz= -0.39± 0.12) was significantly below the infection recovered-controls (OCLz= +0.32± 0.16, p< 0.01).

We observed that 48% of patients with Long COVID had episodic memory deficit, with 27% also impaired overall cognitive function, especially attention, working memory, processing speed and verbal fluency. The MRI examination included grey matter morphometry and whole brain structural connectivity analysis. Compared to infection recovered controls, patients had thinner cortex in a specific cluster centred on the left posterior superior temporal gyrus.

In addition, lower fractional anisotropy (FA) and higher radial diffusivity (RD) were observed in widespread areas of the patients’ cerebral white matter relative to these controls. Correlations between cognitive status and brain abnormalities revealed a relationship between altered connectivity of white matter regions and impairments of episodic memory, overall cognitive function, attention and verbal fluency.

This study shows that patients with neurological Long COVID suffer brain changes, especially in several white matter areas, and these are associated with impairments of specific cognitive functions.

Source: Serrano Del Pueblo VM, Serrano-Heras G, Romero Sánchez CM, Piqueras Landete P, Rojas-Bartolome L, Feria I, Morris RGM, Strange B, Mansilla F, Zhang L, Castro-Robles B, Arias-Salazar L, López-López S, Payá M, Segura T, Muñoz-López M. Brain and cognitive changes in patients with long COVID compared with infection-recovered control subjects. Brain. 2024 Apr 2:awae101. doi: 10.1093/brain/awae101. Epub ahead of print. PMID: 38562097. https://pubmed.ncbi.nlm.nih.gov/38562097/

Impaired Hand Grip Strength Correlates with Greater Disability and Symptom Severity in Post-COVID Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Post-COVID syndrome (PCS) encompasses a diverse array of symptoms persisting beyond 3 months after acute SARS-CoV-2 infection, with mental as well as physical fatigue being the most frequent manifestations.
Methods: In 144 female patients with PCS, hand grip strength (HGS) parameters were assessed as an objective measure of muscle fatigue, with 78 meeting the Canadian Consensus Criteria for postinfectious myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The severity of disability and key symptoms was evaluated using self-reported questionnaires.
Results: Patients with ME/CFS exhibited heightened overall symptom severity, including lower physical function (p < 0.001), a greater degree of disability (p < 0.001), more severe fatigue (p < 0.001), postexertional malaise (p < 0.001), and autonomic dysfunction (p = 0.004) compared to other patients with PCS. While HGS was impaired similarly in all patients with PCS and exhibited a significant correlation with physical function across the entire patient group, HGS of patients with ME/CFS uniquely demonstrated associations with key symptoms.
Conclusions: Thus, impaired HGS serves as an objective marker of physical function in patients with PCS. Only in patients meeting ME/CFS criteria is impaired HGS also associated with the severity of hallmark symptoms. This suggests a common mechanism for muscle fatigue and other symptoms in the ME/CFS subtype, distinct from that in other types of PCS.
Source: Paffrath A, Kim L, Kedor C, Stein E, Rust R, Freitag H, Hoppmann U, Hanitsch LG, Bellmann-Strobl J, Wittke K, et al. Impaired Hand Grip Strength Correlates with Greater Disability and Symptom Severity in Post-COVID Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Journal of Clinical Medicine. 2024; 13(7):2153. https://doi.org/10.3390/jcm13072153 https://www.mdpi.com/2077-0383/13/7/2153

Reduced Cortical Thickness Correlates of Cognitive Dysfunction in Post-COVID-19 Condition: Insights from a Long-Term Follow-up

Abstract:

Background and purpose: There is a paucity of data on long-term neuroimaging findings from individuals who have developed the post-coronavirus 2019 (COVID-19) condition. Only 2 studies have investigated the correlations between cognitive assessment results and structural MR imaging in this population. This study aimed to elucidate the long-term cognitive outcomes of participants with the post-COVID-19 condition and to correlate these cognitive findings with structural MR imaging data in the post-COVID-19 condition.

Materials and methods: A cohort of 53 participants with the post-COVID-19 condition underwent 3T brain MR imaging with T1 and FLAIR sequences obtained a median of 1.8 years after Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) infection. A comprehensive neuropsychological battery was used to assess several cognitive domains in the same individuals. Correlations between cognitive domains and whole-brain voxel-based morphometry were performed. Different ROIs from FreeSurfer were used to perform the same correlations with other neuroimaging features.

Results: According to the Frascati criteria, more than one-half of the participants had deficits in the attentional (55%, n = 29) and executive (59%, n = 31) domains, while 40% (n = 21) had impairment in the memory domain. Only 1 participant (1.89%) showed problems in the visuospatial and visuoconstructive domains. We observed that reduced cortical thickness in the left parahippocampal region (t(48) = 2.28, P = .03) and the right caudal-middle-frontal region (t(48) = 2.20, P = .03) was positively correlated with the memory domain.

Conclusions: Our findings suggest that cognitive impairment in individuals with the post-COVID-19 condition is associated with long-term alterations in the structure of the brain. These macrostructural changes may provide insight into the nature of cognitive symptoms.

Source: Dacosta-Aguayo R, Puig J, Lamonja-Vicente N, Carmona-Cervelló M, Biaani León-Gómez B, Monté-Rubio G, López-Linfante VM, Zamora-Putin V, Montero-Alia P, Chacon C, Bielsa J, Moreno-Gabriel E, Garcia-Sierra R, Pachón A, Costa A, Mataró M, Prado JG, Martinez-Cáceres E, Mateu L, Massanella M, Violán C, Torán-Monserrat P; Aliança ProHEpiC-19 Cognitiu (The APC Collaborative Group). Reduced Cortical Thickness Correlates of Cognitive Dysfunction in Post-COVID-19 Condition: Insights from a Long-Term Follow-up. AJNR Am J Neuroradiol. 2024 Apr 4. doi: 10.3174/ajnr.A8167. Epub ahead of print. PMID: 38575319. https://pubmed.ncbi.nlm.nih.gov/38575319/

Machine learning algorithms for detection of visuomotor neural control differences in individuals with PASC and ME

Abstract:

The COVID-19 pandemic has affected millions worldwide, giving rise to long-term symptoms known as post-acute sequelae of SARS-CoV-2 (PASC) infection, colloquially referred to as long COVID. With an increasing number of people experiencing these symptoms, early intervention is crucial. In this study, we introduce a novel method to detect the likelihood of PASC or Myalgic Encephalomyelitis (ME) using a wearable four-channel headband that collects Electroencephalogram (EEG) data. The raw EEG signals are processed using Continuous Wavelet Transform (CWT) to form a spectrogram-like matrix, which serves as input for various machine learning and deep learning models. We employ models such as CONVLSTM (Convolutional Long Short-Term Memory), CNN-LSTM, and Bi-LSTM (Bidirectional Long short-term memory). Additionally, we test the dataset on traditional machine learning models for comparative analysis.

Our results show that the best-performing model, CNN-LSTM, achieved an accuracy of 83%. In addition to the original spectrogram data, we generated synthetic spectrograms using Wasserstein Generative Adversarial Networks (WGANs) to augment our dataset. These synthetic spectrograms contributed to the training phase, addressing challenges such as limited data volume and patient privacy. Impressively, the model trained on synthetic data achieved an average accuracy of 93%, significantly outperforming the original model.

These results demonstrate the feasibility and effectiveness of our proposed method in detecting the effects of PASC and ME, paving the way for early identification and management of the condition. The proposed approach holds significant potential for various practical applications, particularly in the clinical domain. It can be utilized for evaluating the current condition of individuals with PASC or ME, and monitoring the recovery process of those with PASC, or the efficacy of any interventions in the PASC and ME populations. By implementing this technique, healthcare professionals can facilitate more effective management of chronic PASC or ME effects, ensuring timely intervention and improving the quality of life for those experiencing these conditions.

Source: Harit Ahuja, Smriti Badhwar, Heather Edgell, Lauren E. Sergio, Marin Litoiu. Machine learning algorithms for detection of visuomotor neural control differences in individuals with PASC and ME. Front. Hum. Neurosci. Sec. Brain-Computer Interfaces, Volume 18 – 2024 | doi: 10.3389/fnhum.2024.1359162 https://www.frontiersin.org/articles/10.3389/fnhum.2024.1359162/full (Full text)