Tag: long covid predictors

Headache or Disturbed Smell and Taste During Acute COVID-19 as Predictors of Long COVID at One Year

Abstract:

Purpose: Long coronavirus disease (COVID) poses a significant health concern for a substantial proportion of COVID-19 patients. Viral pathogenesis studies suggest the potential of central nervous system (CNS) affection in the acute phase of COVID-19 predicting long COVID.

This study investigates whether acute COVID-19 symptoms, particularly headache and disturbed smell and taste, predict manifestations of long COVID.

Methods: This prospective cohort study included COVID-19 patients hospitalized between March 2020, and May 2021. One year after discharge, patients responded to a symptom questionnaire. Logistic regression analysis was used to determine the odds ratio (OR) for these outcomes.

Results: Of 288 eligible patients, 111 responded to the follow-up questionnaire. At 1 year follow-up, disturbed smell and taste during acute COVID-19 did not elevate the risk of long COVID. However, patients with acute headache demonstrated a tendency towards an elevated risk of CNS-related long COVID. Notably, this risk significantly increased in patients reporting dizziness (adjusted OR=4.20; 95% confidence interval (CI) 1.19 – 14.85). Neither disturbed smell and taste nor headache during acute COVID-19 indicated a statistically significant risk of worsening in fatigue, health, or total symptom score at 1-year follow-up.

Conclusion: Headache, and not disturbed smell and taste, predicted CNS-related long COVID. Further research is warranted to clarify pathways connecting CNS-related symptoms during acute COVID-19 with long COVID, aiding the efforts of addressing the range of symptoms observed among long COVID patients and developing effective interventions.

Source: Jane Agergaard. Headache or Disturbed Smell and Taste During Acute COVID-19 as Predictors of Long COVID at One Year, 07 February 2024, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3930891/v1] https://www.researchsquare.com/article/rs-3930891/v1 (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)

Neuroinflammatory imaging markers in white matter: insights into the cerebral consequences of post-acute sequelae of COVID-19 (PASC)

Abstract:

Symptoms of coronavirus disease 2019 (COVID-19) can persist for months or years after infection, a condition called Post-Acute Sequelae of COVID-19 (PASC). Whole-brain white matter and cortical gray matter health were assessed using multi-shell diffusion tensor imaging. Correlational tractography was utilized to dissect the nature and extent of white matter changes.

In this study of 42 male essential workers, the most common symptoms of Neurological PASC (n = 24) included fatigue (n = 19) and headache (n = 17). Participants with neurological PASC demonstrated alterations to whole-brain white matter health when compared to controls made up of uninfected, asymptomatic, or mildly infected controls (n = 18). Large differences were evident between PASC and controls in measures of fractional anisotropy (Cohen’s D=-0.54, P = 0.001) and cortical isotropic diffusion (Cohen’s D = 0.50, P = 0.002).

Symptoms were associated with white matter fractional anisotropy (fatigue: rho = -0.62, P < 0.001; headache: rho = -0.66, P < 0.001), as well as nine other measures of white and gray matter health. Brain fog was associated with improved cerebral functioning including improved white matter isotropic diffusion and quantitative anisotropy.

This study identified changes across measures of white and gray matter connectivity, neuroinflammation, and cerebral atrophy that were interrelated and associated with differences in symptoms of PASC. These results provide insights into the long-term cerebral implications of COVID-19.

Source: Sean Clouston, Chuan Huang, Jia Ying et al. Neuroinflammatory imaging markers in white matter: insights into the cerebral consequences of post-acute sequelae of COVID-19 (PASC), 19 January 2024, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3760289/v1] https://www.researchsquare.com/article/rs-3760289/v1 (Full text)

T4 apoptosis in the acute phase of SARS-CoV-2 infection predicts long COVID

Abstract:

Background: As about 10% of patients with COVID-19 present sequelae, it is important to better understand the physiopathology of so-called long COVID.

Method: To this aim, we recruited 29 patients hospitalized for SARS-CoV-2 infection and, by Luminex®, quantified 19 soluble factors in their plasma and in the supernatant of their peripheral blood mononuclear cells, including inflammatory and anti-inflammatory cytokines and chemokines, Th1/Th2/Th17 cytokines, and endothelium activation markers. We also measured their T4, T8 and NK differentiation, activation, exhaustion and senescence, T cell apoptosis, and monocyte subpopulations by flow cytometry. We compared these markers between participants who developed long COVID or not one year later.

Results: None of these markers was predictive for sequelae, except programmed T4 cell death. T4 lymphocytes from participants who later presented long COVID were more apoptotic in culture than those of sequelae-free participants at Month 12 (36.9 ± 14.7 vs. 24.2 ± 9.0%, p = 0.016).

Conclusions: Our observation raises the hypothesis that T4 cell death during the acute phase of SARS-CoV-2 infection might pave the way for long COVID. Mechanistically, T4 lymphopenia might favor phenomena that could cause sequelae, including SARS-CoV-2 persistence, reactivation of other viruses, autoimmunity and immune dysregulation. In this scenario, inhibiting T cell apoptosis, for instance, by caspase inhibitors, could prevent long COVID.

Source: Cezar R, Kundura L, André S, Lozano C, Vincent T, Muller L, Lefrant JY, Roger C, Claret PG, Duvnjak S, Loubet P, Sotto A, Tran TA, Estaquier J, Corbeau P. T4 apoptosis in the acute phase of SARS-CoV-2 infection predicts long COVID. Front Immunol. 2024 Jan 3;14:1335352. doi: 10.3389/fimmu.2023.1335352. PMID: 38235145; PMCID: PMC10791767. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10791767/ (Full text)

Nirmatrelvir/ritonavir and risk of long COVID symptoms: a retrospective cohort study

Abstract:

We conducted a retrospective cohort study to assess whether treatment with nirmatrelvir/ritonavir was associated with a reduced risk of long COVID. We enrolled 500 adults with confirmed SARS-CoV-2 who were eligible for nirmatrelvir/ritonavir; 250 who took nirmatrelvir/ritonavir and 250 who did not. The primary outcome was the development of one or more of eleven prespecified long COVID symptoms, assessed through a structured telephone interview four months after the positive SARS-CoV-2 test. Multivariable logistic regression models controlled for age, sex, race/ethnicity, chronic conditions, and COVID-19 vaccination status.

We found that participants who took nirmatrelvir/ritonavir were no less likely to develop long COVID symptoms, compared to those who did not take the medication (44% vs. 49.6%, p = 0.21). Taking nirmatrelvir/ritonavir was associated with a lower odds of two of the eleven long COVID symptoms, brain fog (OR 0.58, 95% CI 0.38-0.88) and chest pain/tightness (OR 0.51, 95% CI 0.28-0.91). Our finding that treatment with nirmatrelvir/ritonavir was not associated with a lower risk of developing long COVID is different from prior studies that obtained data only from electronic medical records.

Source: Congdon S, Narrowe Z, Yone N, Gunn J, Deng Y, Nori P, Cowman K, Islam M, Rikin S, Starrels J. Nirmatrelvir/ritonavir and risk of long COVID symptoms: a retrospective cohort study. Sci Rep. 2023 Nov 11;13(1):19688. doi: 10.1038/s41598-023-46912-4. PMID: 37951998; PMCID: PMC10640584. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10640584/ (Full text)

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)

Characterization of neurocognitive deficits in patients with post-COVID-19 syndrome: persistence, patients’ complaints, and clinical predictors.

Abstract:

Introduction: Cognitive symptoms persisting beyond 3 months following COVID-19 present a considerable disease burden. We aimed to establish a domain-specific cognitive profile of post-COVID-19 syndrome (PCS). We examined the deficits’ persistence, relationships with subjective cognitive complaints, and clinical variables, to identify the most relevant cognitive deficits and their predictors.

Methods: This cross-sectional study examined cognitive performance and patient-reported and clinical predictors of cognitive deficits in PCS patients (n = 282) and socio-demographically comparable healthy controls (n = 52).

Results: On the Oxford Cognitive Screen-Plus, the patient group scored significantly lower in delayed verbal memory, attention, and executive functioning than the healthy group. In each affected domain, 10 to 20% of patients performed more than 1.5 SD below the control mean. Delayed memory was particularly affected, with a small effect of hospitalization and age. Attention scores were predicted by hospitalization and fatigue.

Discussion: Thus, PCS is associated with long-term cognitive dysfunction, particularly in delayed memory, attention, and executive functioning. Memory deficits seem to be of particular relevance to patients’ experience of subjective impairment. Hospitalization, fatigue, and age seem to predict cognitive deficits, while time since infection, depression, and pre-existing conditions do not.

Source: Kozik V, Reuken P, Utech I, Gramlich J, Stallmach Z, Demeyere N, Rakers F, Schwab M, Stallmach A, Finke K. Characterization of neurocognitive deficits in patients with post-COVID-19 syndrome: persistence, patients’ complaints, and clinical predictors. Front Psychol. 2023 Oct 17;14:1233144. doi: 10.3389/fpsyg.2023.1233144. PMID: 37915528; PMCID: PMC10616256. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616256/ (Full text)

Brain-targeted autoimmunity is strongly associated with Long COVID and its chronic fatigue syndrome as well as its affective symptoms

Abstract:

Background Autoimmune responses contribute to the pathophysiology of Long COVID, affective symptoms and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS).

Objectives To examine whether Long COVID, and its accompanying affective symptoms and CFS are associated with immunoglobulin (Ig)A/IgM/IgG directed at neuronal proteins including myelin basic protein (MBP), myelin oligodendrocyte glycoprotein (MOG), synapsin, α+β-tubulin, neurofilament protein (NFP), cerebellar protein-2 (CP2), and the blood-brain-barrier-brain-damage (BBD) proteins claudin-5 and S100B.

Methods IgA/IgM/IgG to the above neuronal proteins, human herpes virus-6 (HHV-6) and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) were measured in 90 Long COVID patients and 90 healthy controls, while C-reactive protein (CRP), and advanced oxidation protein products (AOPP) in association with affective and CFS ratings were additionally assessed in a subgroup thereof.

Results Long COVID is associated with significant increases in IgG directed at tubulin (IgG-tubulin), MBP, MOG and synapsin; IgM-MBP, MOG, CP2, synapsin and BBD; and IgA-CP2 and synapsin. IgM-SARS-CoV-2 and IgM-HHV-6 antibody titers were significantly correlated with IgA/IgG/IgM-tubulin and -CP2, IgG/IgM-BBD, IgM-MOG, IgA/IgM-NFP, and IgG/IgM-synapsin. Binary logistic regression analysis shows that IgM-MBP and IgG-MBP are the best predictors of Long COVID. Multiple regression analysis shows that IgG-MOG, CRP and AOPP explain together 41.7% of the variance in the severity of CFS. Neural network analysis shows that IgM-synapsin, IgA-MBP, IgG-MOG, IgA-synapsin, IgA-CP2, IgG-MBP and CRP are the most important predictors of affective symptoms due to Long COVID with a predictive accuracy of r=0.801.

Conclusion Brain-targeted autoimmunity contributes significantly to the pathogenesis of Long COVID and the severity of its physio-affective phenome.

Source: Abbas F. Almulla, Michael Maes, Bo Zhou, Hussein K. Al-Hakeim, Aristo Vojdani. Brain-targeted autoimmunity is strongly associated with Long COVID and its chronic fatigue syndrome as well as its affective symptoms. medRxiv [Preprint] https://www.medrxiv.org/content/10.1101/2023.10.04.23296554v1 (Full text available as PDF file)

Neurologic sequelae of COVID-19 are determined by immunologic imprinting from previous coronaviruses

Abstract:

Coronavirus disease 2019 (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains a global public health emergency. Although SARS-CoV-2 is primarily a respiratory pathogen, extra-respiratory organs, including the CNS, can also be affected. Neurologic symptoms have been observed not only during acute SARS-CoV-2 infection, but also at distance from respiratory disease, also known as long-COVID or neurological post-acute sequelae of COVID-19 (neuroPASC). The pathogenesis of neuroPASC is not well understood, but hypotheses include SARS-CoV-2-induced immune dysfunctions, hormonal dysregulations and persistence of SARS-CoV-2 reservoirs.

In this prospective cohort study, we used a high throughput systems serology approach to dissect the humoral response to SARS-CoV-2 (and other common coronaviruses: 229E, HKU1, NL63 and OC43) in the serum and CSF from 112 infected individuals who developed (n = 18) or did not develop (n = 94) neuroPASC. Unique SARS-CoV-2 humoral profiles were observed in the CSF of neuroPASC compared with serum responses. All antibody isotypes (IgG, IgM, IgA) and subclasses (IgA1-2, IgG1-4) were detected in serum, whereas CSF was characterized by focused IgG1 (and absence of IgM).

These data argue in favour of compartmentalized brain-specific responses against SARS-CoV-2 through selective transfer of antibodies from the serum to the CSF across the blood-brain barrier, rather than intrathecal synthesis, where more diversity in antibody classes/subclasses would be expected.

Compared to individuals who did not develop post-acute complications following infection, individuals with neuroPASC had similar demographic features (median age 65 versus 66.5 years, respectively, P = 0.55; females 33% versus 44%, P = 0.52) but exhibited attenuated systemic antibody responses against SARS-CoV-2, characterized by decreased capacity to activate antibody-dependent complement deposition (ADCD), NK cell activation (ADNKA) and to bind Fcγ receptors. However, surprisingly, neuroPASC individuals showed significantly expanded antibody responses to other common coronaviruses, including 229E, HKU1, NL63 and OC43.

This biased humoral activation across coronaviruses was particularly enriched in neuroPASC individuals with poor outcome, suggesting an ‘original antigenic sin’ (or immunologic imprinting), where pre-existing immune responses against related viruses shape the response to the current infection, as a key prognostic marker of neuroPASC disease.

Overall, these findings point to a pathogenic role for compromised anti-SARS-CoV-2 responses in the CSF, likely resulting in incomplete virus clearance from the brain and persistent neuroinflammation, in the development of post-acute neurologic complications of SARS-CoV-2 infection.

Source: Spatola M, Nziza N, Jung W, Deng Y, Yuan D, Dinoto A, Bozzetti S, Chiodega V, Ferrari S, Lauffenburger DA, Mariotto S, Alter G. Neurologic sequelae of COVID-19 are determined by immunologic imprinting from previous coronaviruses. Brain. 2023 Oct 3;146(10):4292-4305. doi: 10.1093/brain/awad155. PMID: 37161609. https://academic.oup.com/brain/article/146/10/4292/7158783 (Full text)

Sequential multi-omics analysis identifies clinical phenotypes and predictive biomarkers for long COVID

Abstract:

The post-acute sequelae of COVID-19 (PASC), also known as long COVID, is often associated with debilitating symptoms and adverse multisystem consequences. We obtain plasma samples from 117 individuals during and 6 months following their acute phase of infection to comprehensively profile and assess changes in cytokines, proteome, and metabolome.

Network analysis reveals sustained inflammatory response, platelet degranulation, and cellular activation during convalescence accompanied by dysregulation in arginine biosynthesis, methionine metabolism, taurine metabolism, and tricarboxylic acid (TCA) cycle processes.

Furthermore, we develop a prognostic model composed of 20 molecules involved in regulating T cell exhaustion and energy metabolism that can reliably predict adverse clinical outcomes following discharge from acute infection with 83% accuracy and an area under the curve (AUC) of 0.96.

Our study reveals pertinent biological processes during convalescence that differ from acute infection, and it supports the development of specific therapies and biomarkers for patients suffering from long COVID.

Source: Wang K, Khoramjoo M, Srinivasan K, Gordon PMK, Mandal R, Jackson D, Sligl W, Grant MB, Penninger JM, Borchers CH, Wishart DS, Prasad V, Oudit GY. Sequential multi-omics analysis identifies clinical phenotypes and predictive biomarkers for long COVID. Cell Rep Med. 2023 Oct 18:101254. doi: 10.1016/j.xcrm.2023.101254. Epub ahead of print. PMID: 37890487. https://www.cell.com/cell-reports-medicine/fulltext/S2666-3791(23)00431-7 (Full text)