Tag: acute covid

SARS-CoV2 evokes structural brain changes resulting in declined executive function

Abstract:

Background: Several research has underlined the multi-system character of COVID-19. Though effects on the Central Nervous System are mainly discussed as disease-specific affections due to the virus’ neurotropism, no comprehensive disease model of COVID-19 exists on a neurofunctional base by now. We aimed to investigate neuroplastic grey- and white matter changes related to COVID-19 and to link these changes to neurocognitive testings leading towards a multi-dimensional disease model.

Methods: Groups of acutely ill COVID-19 patients (n = 16), recovered COVID-19 patients (n = 21) and healthy controls (n = 13) were prospectively included into this study. MR-imaging included T1-weighted sequences for analysis of grey matter using voxel-based morphometry and diffusion-weighted sequences to investigate white matter tracts using probabilistic tractography. Comprehensive neurocognitive testing for verbal and non-verbal domains was performed.

Results: Alterations strongly focused on grey matter of the frontal-basal ganglia-thalamus network and temporal areas, as well as fiber tracts connecting these areas. In acute COVID-19 patients, a decline of grey matter volume was found with an accompanying diminution of white matter tracts. A decline in executive function and especially verbal fluency was found in acute patients, partially persisting in recovered.

Conclusion: Changes in gray matter volume and white matter tracts included mainly areas involved in networks of executive control and language. Deeper understanding of these alterations is necessary especially with respect to long-term impairments, often referred to as ‘Post-COVID’.

Source: Deuter D, Hense K, Kunkel K, Vollmayr J, Schachinger S, Wendl C, Schicho A, Fellner C, Salzberger B, Hitzenbichler F, Zeller J, Vielsmeier V, Dodoo-Schittko F, Schmidt NO, Rosengarth K. SARS-CoV2 evokes structural brain changes resulting in declined executive function. PLoS One. 2024 Mar 12;19(3):e0298837. doi: 10.1371/journal.pone.0298837. PMID: 38470899; PMCID: PMC10931481. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10931481/ (Full text)

Blood–brain barrier disruption and sustained systemic inflammation in individuals with long COVID-associated cognitive impairment

Abstract:

Vascular disruption has been implicated in coronavirus disease 2019 (COVID-19) pathogenesis and may predispose to the neurological sequelae associated with long COVID, yet it is unclear how blood–brain barrier (BBB) function is affected in these conditions. Here we show that BBB disruption is evident during acute infection and in patients with long COVID with cognitive impairment, commonly referred to as brain fog.

Using dynamic contrast-enhanced magnetic resonance imaging, we show BBB disruption in patients with long COVID-associated brain fog. Transcriptomic analysis of peripheral blood mononuclear cells revealed dysregulation of the coagulation system and a dampened adaptive immune response in individuals with brain fog.

Accordingly, peripheral blood mononuclear cells showed increased adhesion to human brain endothelial cells in vitro, while exposure of brain endothelial cells to serum from patients with long COVID induced expression of inflammatory markers.

Together, our data suggest that sustained systemic inflammation and persistent localized BBB dysfunction is a key feature of long COVID-associated brain fog.

Source: Greene C, Connolly R, Brennan D, Laffan A, O’Keeffe E, Zaporojan L, O’Callaghan J, Thomson B, Connolly E, Argue R, Martin-Loeches I, Long A, Cheallaigh CN, Conlon N, Doherty CP, Campbell M. Blood-brain barrier disruption and sustained systemic inflammation in individuals with long COVID-associated cognitive impairment. Nat Neurosci. 2024 Mar;27(3):421-432. doi: 10.1038/s41593-024-01576-9. Epub 2024 Feb 22. PMID: 38388736; PMCID: PMC10917679. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10917679/ (Full text)

SSRI Use During Acute COVID-19 Infection Associated with Lower Risk of Long COVID Among Patients with Depression

Abstract:

Background Long COVID, also known as post-acute sequelae of COVID-19 (PASC), is a poorly understood condition with symptoms across a range of biological domains that often have debilitating consequences. Some have recently suggested that lingering SARS-CoV-2 virus in the gut may impede serotonin production and that low serotonin may drive many Long COVID symptoms across a range of biological systems. Therefore, selective serotonin reuptake inhibitors (SSRIs), which increase synaptic serotonin availability, may prevent or treat Long COVID. SSRIs are commonly prescribed for depression, therefore restricting a study sample to only include patients with depression can reduce the concern of confounding by indication.

Methods In an observational sample of electronic health records from patients in the National COVID Cohort Collaborative (N3C) with a COVID-19 diagnosis between September 1, 2021, and December 1, 2022, and pre-existing major depressive disorder, the leading indication for SSRI use, we evaluated the relationship between SSRI use at the time of COVID-19 infection and subsequent 12-month risk of Long COVID (defined by ICD-10 code U09.9). We defined SSRI use as a prescription for SSRI medication beginning at least 30 days before COVID-19 infection and not ending before COVID-19 infection. To minimize bias, we estimated the causal associations of interest using a nonparametric approach, targeted maximum likelihood estimation, to aggressively adjust for high-dimensional covariates.

Results We analyzed a sample (n = 506,903) of patients with a diagnosis of major depressive disorder before COVID-19 diagnosis, where 124,928 (25%) were using an SSRI. We found that SSRI users had a significantly lower risk of Long COVID compared to nonusers (adjusted causal relative risk 0.90, 95% CI (0.86, 0.94)).

Conclusion These findings suggest that SSRI use during COVID-19 infection may be protective against Long COVID, supporting the hypothesis that serotonin may be a key mechanistic biomarker of Long COVID.

Source: Zachary Butzin-Dozier, Yunwen Ji, Sarang Deshpande, Eric Hurwitz, Jeremy Coyle, Junming (Seraphina) Shi, Andrew Mertens, Mark J. van der Laan, John M. Colford Jr., Rena C. Patel, Alan E. Hubbard, the National COVID Cohort Collaborative (N3C) Consortium. SSRI Use During Acute COVID-19 Infection Associated with Lower Risk of Long COVID Among Patients with Depression. medRxiv 2024.02.05.24302352; doi: https://doi.org/10.1101/2024.02.05.24302352 https://www.medrxiv.org/content/10.1101/2024.02.05.24302352v1.full-text (Full text) 

Analysis and clinical determinants of post-COVID-19 syndrome in the Lombardy region: evidence from a longitudinal cohort study

Abstract:

Objective: To define macro symptoms of long COVID and to identify predictive factors, with the aim of preventing the development of the long COVID syndrome.

Design: A single-centre longitudinal prospective cohort study conducted from May 2020 to October 2022.

Setting: The study was conducted at Luigi Sacco University Hospital in Milan (Italy). In May 2020, we activated the ARCOVID (Ambulatorio Rivalutazione COVID) outpatient service for the follow-up of long COVID.

Participants: Hospitalised and non-hospitalised patients previously affected by COVID-19 were either referred by specialists or general practitioners or self-referred.

Intervention: During the first visit, a set of questions investigated the presence and the duration of 11 symptoms (palpitations, amnesia, headache, anxiety/panic, insomnia, loss of smell, loss of taste, dyspnoea, asthenia, myalgia and telogen effluvium). The follow-up has continued until the present time, by sending email questionnaires every 3 months to monitor symptoms and health-related quality of life.

Primary and secondary outcome measures: Measurement of synthetic scores (aggregation of symptoms based on occurrence and duration) that may reveal the presence of long COVID in different clinical macro symptoms. To this end, a mixed supervised and empirical strategy was adopted. Moreover, we aimed to identify predictive factors for post-COVID-19 macro symptoms.

Results: In the first and second waves of COVID-19, 575 and 793 patients (respectively) were enrolled. Three different post-COVID-19 macro symptoms (neurological, sensorial and physical) were identified. We found significant associations between post-COVID-19 symptoms and (1) the patients’ comorbidities, and (2) the medications used during the COVID-19 acute phase. ACE inhibitors (OR=2.039, 95% CI: 1.095 to 3.892), inhaled steroids (OR=4.08, 95% CI: 1.17 to 19.19) and COVID therapies were associated with increased incidence of the neurological macro symptoms. Age (OR=1.02, 95% CI: 1.01 to 1.04), COVID-19 severity (OR=0.42, 95% CI: 0.21 to 0.82), number of comorbidities (OR=1.22, 95% CI: 1.01 to 1.5), metabolic (OR=2.52, 95% CI: 1.25 to 5.27), pulmonary (OR=1.87, 95% CI: 1.10 to 3.32) and autoimmune diseases (OR=4.57, 95% CI: 1.57 to 19.41) increased the risk of the physical macro symptoms.

Conclusions: Being male was the unique protective factor in both waves. Other factors reflected different medical behaviours and the impact of comorbidities. Evidence of the effect of therapies adds valuable information that may drive future medical choices.

Source: Borgonovo F, Lovaglio PG, Mariani C, Berta P, Cossu MV, Rizzardini G, Vittadini G, Capetti AF. Analysis and clinical determinants of post-COVID-19 syndrome in the Lombardy region: evidence from a longitudinal cohort study. BMJ Open. 2024 Feb 6;14(2):e075185. doi: 10.1136/bmjopen-2023-075185. PMID: 38320835; PMCID: PMC10860093. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10860093/ (Full text)

Early immune factors associated with the development of post-acute sequelae of SARS-CoV-2 infection in hospitalized and non-hospitalized individuals

Abstract:

Background: Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can lead to post-acute sequelae of SARS-CoV-2 (PASC) that can persist for weeks to years following initial viral infection. Clinical manifestations of PASC are heterogeneous and often involve multiple organs. While many hypotheses have been made on the mechanisms of PASC and its associated symptoms, the acute biological drivers of PASC are still unknown.

Methods: We enrolled 494 patients with COVID-19 at their initial presentation to a hospital or clinic and followed them longitudinally to determine their development of PASC. From 341 patients, we conducted multi-omic profiling on peripheral blood samples collected shortly after study enrollment to investigate early immune signatures associated with the development of PASC.

Results: During the first week of COVID-19, we observed a large number of differences in the immune profile of individuals who were hospitalized for COVID-19 compared to those individuals with COVID-19 who were not hospitalized. Differences between individuals who did or did not later develop PASC were, in comparison, more limited, but included significant differences in autoantibodies and in epigenetic and transcriptional signatures in double-negative 1 B cells, in particular.

Conclusions: We found that early immune indicators of incident PASC were nuanced, with significant molecular signals manifesting predominantly in double-negative B cells, compared with the robust differences associated with hospitalization during acute COVID-19. The emerging acute differences in B cell phenotypes, especially in double-negative 1 B cells, in PASC patients highlight a potentially important role of these cells in the development of PASC.

Source: Leung JM, Wu MJ, Kheradpour P, Chen C, Drake KA, Tong G, Ridaura VK, Zisser HC, Conrad WA, Hudson N, Allen J, Welberry C, Parsy-Kowalska C, Macdonald I, Tapson VF, Moy JN, deFilippi CR, Rosas IO, Basit M, Krishnan JA, Parthasarathy S, Prabhakar BS, Salvatore M, Kim CC. Early immune factors associated with the development of post-acute sequelae of SARS-CoV-2 infection in hospitalized and non-hospitalized individuals. Front Immunol. 2024 Jan 22;15:1348041. doi: 10.3389/fimmu.2024.1348041. PMID: 38318183; PMCID: PMC10838987. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10838987/ (Full text)

Analysis of post-COVID symptoms and predisposing factors for chronic post-COVID syndrome

Abstract:

Introduction: While there is sufficient information about acute COVID-19, which can cause a multisystemic and fatal disease, post-COVID syndrome and risk factors for this condition remain poorly known. We aimed to identify postCOVID symptoms and risk factors for chronic post-COVID syndrome through this study.

Materials and methods: This prospective cross-sectional study was conducted on 254 out of 384 COVID-19 patients admitted to our COVID-19 polyclinic between February and April 2021. The patients were questioned with a list of 37 symptoms at the fifth and twelfth weeks after disease onset via phone review, and their acute post-COVID (APC) and chronic post-COVID (CPC) symptoms were recorded. Data on risk factors were collected from the hospital’s medical records system. Associations between symptom count in the CPC phase and age, sex, hospitalization, RT-PCR result, specific radiological findings, comorbidities, and long-term medications were evaluated.

Result: Two hundred twenty-one patients had APC symptoms, and 138 patients had CPC symptoms. While the most common symptom was fatigue at week five, it was hair loss at week 12. Symptoms were observed significantly less in the CPC phase than in the APC phase (Z= -12.301, p= 0.00). Female sex and the presence of specific radiological findings were significantly associated with the occurrence of CPC symptoms (p= 0.03, p= 0.00, respectively). Long-term use of angiotensin-2 receptor blockers (ARBs) was correlated with a low symptom count in the CPC phase (p= 0.00).

Conclusions: Female sex and the presence of specific radiological findings were risk factors for developing CPC. Long-term use of ARBs was associated with a low chronic post-COVID symptom burden. A substantial cluster of multisystemic symptoms was observed in both phases, and this condition highlights the requirement for customized outpatient management that includes long-term follow-up and treatment of COVID-19 patients. Identifying the high-risk patients that will develop persistent symptoms can guide this management.

Source: Abalı H, Demir D, Gül Ş, Şimşek Veske N, Tural Onur S. Analysis of post-COVID symptoms and predisposing factors for chronic post-COVID syndrome. Tuberk Toraks. 2023 Dec;71(4):378-389. English. doi: 10.5578/tt.20239606. PMID: 38152008. https://pubmed.ncbi.nlm.nih.gov/38152008/ (Full text available as PDF file)

Predictive models of long COVID

Abstract:

Background: The cause and symptoms of long COVID are poorly understood. It is challenging to predict whether a given COVID-19 patient will develop long COVID in the future.

Methods: We used electronic health record (EHR) data from the National COVID Cohort Collaborative to predict the incidence of long COVID. We trained two machine learning (ML) models – logistic regression (LR) and random forest (RF). Features used to train predictors included symptoms and drugs ordered during acute infection, measures of COVID-19 treatment, pre-COVID comorbidities, and demographic information. We assigned the ‘long COVID’ label to patients diagnosed with the U09.9 ICD10-CM code. The cohorts included patients with (a) EHRs reported from data partners using U09.9 ICD10-CM code and (b) at least one EHR in each feature category. We analysed three cohorts: all patients (n = 2,190,579; diagnosed with long COVID = 17,036), inpatients (149,319; 3,295), and outpatients (2,041,260; 13,741).

Findings: LR and RF models yielded median AUROC of 0.76 and 0.75, respectively. Ablation study revealed that drugs had the highest influence on the prediction task. The SHAP method identified age, gender, cough, fatigue, albuterol, obesity, diabetes, and chronic lung disease as explanatory features. Models trained on data from one N3C partner and tested on data from the other partners had average AUROC of 0.75.

Interpretation: ML-based classification using EHR information from the acute infection period is effective in predicting long COVID. SHAP methods identified important features for prediction. Cross-site analysis demonstrated the generalizability of the proposed methodology.

Source: Antony B, Blau H, Casiraghi E, Loomba JJ, Callahan TJ, Laraway BJ, Wilkins KJ, Antonescu CC, Valentini G, Williams AE, Robinson PN, Reese JT, Murali TM; N3C consortium. Predictive models of long COVID. EBioMedicine. 2023 Oct;96:104777. doi: 10.1016/j.ebiom.2023.104777. Epub 2023 Sep 4. PMID: 37672869; PMCID: PMC10494314. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494314/ (Full text)

Pulmonary embolism in patients in acute COVID-19, long-COVID and post-COVID syndrome

Abstract:

COVID-19 is a disease caused by the SARS-CoV-2 virus, which, after entering a living organism, uses the ACE-2 protein as a receptor and several other proteins as cofactors of infection. Disease symptomatology is extensive, involving mostly predominant respiratory symptoms, as well as those of the nervous, gastrointestinal, circulatory and other systems. Incidence of COVID-19 also results in markedly different laboratory findings on the hemostatic system with the predominant feature of increased D-dimer levels.

In the pathogenesis of thromboembolic complications in COVID-19, all elements of Virchow’s triad are involved: endothelial damage, coagulation disorders and blood flow disorders. Coagulopathy increases with the severity of the clinical course of COVID-19.

One of the causes of mortality associated with COVID-19 is pulmonary embolism. SARS-CoV-2 infection increases the risk of thromboembolic complications not only in the acute period of the disease. Also in the period of about a month after recovery, there is an increased risk of venous thrombosis and consequently, life-threatening pulmonary embolism.

The classic biomarker of pulmonary embolism in the general population is D-dimers. Among imaging studies, the gold standard for diagnosing this disease is computed tomography of the pulmonary arteries (CTPA). Other useful diagnostic tests are ventilation-perfusion lung scintigraphy (VQ Scans) or echocardiography. Currently reviewed guidelines and recommendations recommend extensive thromboprophylaxis in COVID-19 patients in both acute and chronic phases of the disease.

Source: Tomczyk P, Tomczyk D. Pulmonary embolism in patients in acute COVID-19, long-COVID and post-COVID syndrome. Przegl Epidemiol. 2023;77(2):172-184. doi: 10.32394/pe.77.17. PMID: 37846660. https://pubmed.ncbi.nlm.nih.gov/37846660/

Monocytes subpopulations pattern in the acute respiratory syndrome coronavirus 2 virus infection and after long COVID-19

Abstract:

Introduction and objective: The present study sought to characterize the pattern of monocyte subpopulations in patients during the course of the infections caused by SARS-CoV-2 virus or who presented long COVID-19 syndrome compared to monocytes from patients with zika virus (Zika) or chikungunya virus (CHIKV).

Casuistry: Study with 89 peripheral blood samples from patients, who underwent hemogram and serology (IgG and IgM) for detection of Zika (Control Group 1, n = 18) or CHIKV (Control Group 2, n = 9), and from patients who underwent hemogram and reverse transcription polymerase chain reaction for detection of SARS-CoV-2 at the acute phase of the disease (Group 3, n = 19); and of patients who presented long COVID-19 syndrome (Group 4, n = 43). The monocyte and subpopulations counts were performed by flow cytometry.

Results: No significant difference was observed in the total number of monocytes between the groups. The classical (CD14++CD16–) and intermediate (CD14+CD16+) monocytes counts were increased in patients with acute infection or with long COVID-19 syndrome. The monocytes subpopulations counts were lower in patients with infection Zika or CHIKV.

Conclusion: Increase in the monocyte subpopulations in patients with acute infection or with long COVID-19 syndrome may be an important finding of differentiated from the infection Zika or CHIKV.

Source: Pereira VIC, de Brito Junior LC, Falcão LFM, da Costa Vasconcelos PF, Quaresma JAS, Berg AVVD, Paixão APS, Ferreira RIS, Diks IBC. Monocytes subpopulations pattern in the acute respiratory syndrome coronavirus 2 virus infection and after long COVID-19. Int Immunopharmacol. 2023 Oct 5;124(Pt B):110994. doi: 10.1016/j.intimp.2023.110994. Epub ahead of print. PMID: 37804653. https://www.sciencedirect.com/science/article/abs/pii/S156757692301319X

Predicting Myalgic Encephalomyelitis/Chronic Fatigue Syndrome from Early Symptoms of COVID-19 Infection

Abstract:

It is still unclear why certain individuals after viral infections continue to have severe symptoms. We investigated if predicting myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) development after contracting COVID-19 is possible by analyzing symptoms from the first two weeks of COVID-19 infection.
Using participant responses to the 54-item DePaul Symptom Questionnaire, we built predictive models based on a random forest algorithm using the participants’ symptoms from the initial weeks of COVID-19 infection to predict if the participants would go on to meet the criteria for ME/CFS approximately 6 months later.
Early symptoms, particularly those assessing post-exertional malaise, did predict the development of ME/CFS, reaching an accuracy of 94.6%. We then investigated a minimal set of eight symptom features that could accurately predict ME/CFS. The feature reduced models reached an accuracy of 93.5%. Our findings indicated that several IOM diagnostic criteria for ME/CFS occurring during the initial weeks after COVID-19 infection predicted Long COVID and the diagnosis of ME/CFS after 6 months.
Source: Hua C, Schwabe J, Jason LA, Furst J, Raicu D. Predicting Myalgic Encephalomyelitis/Chronic Fatigue Syndrome from Early Symptoms of COVID-19 Infection. Psych. 2023; 5(4):1101-1108. https://doi.org/10.3390/psych5040073 https://www.mdpi.com/2624-8611/5/4/73