Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study

Abstract:

Objectives: We sought to 1) identify long COVID phenotypes based on patient reported outcome measures (PROMs) and 2) determine whether the phenotypes were associated with quality of life (QoL) and/or lung function.

Methods: This was a longitudinal cohort study of hospitalized and non-hospitalized patients from March 2020 to January 2022 that was conducted across 4 Post-COVID Recovery Clinics in British Columbia, Canada. Latent class analysis was used to identify long COVID phenotypes using baseline PROMs (fatigue, dyspnea, cough, anxiety, depression, and post-traumatic stress disorder). We then explored the association between the phenotypes and QoL (using the EuroQoL 5 dimensions visual analogue scale [EQ5D VAS]) and lung function (using the diffusing capacity of the lung for carbon monoxide [DLCO]).

Results: There were 1,344 patients enrolled in the study (mean age 51 ±15 years; 780 [58%] were females; 769 (57%) were of a non-White race). Three distinct long COVID phenotypes were identified: Class 1) fatigue and dyspnea, Class 2) anxiety and depression, and Class 3) fatigue, dyspnea, anxiety, and depression. Class 3 had a significantly lower EQ5D VAS at 3 (50±19) and 6 months (54 ± 22) compared to Classes 1 and 2 (p<0.001). The EQ5D VAS significantly improved between 3 and 6 months for Class 1 (median difference of 6.0 [95% CI, 4.0 to 8.0]) and Class 3 (median difference of 5.0 [95% CI, 0 to 8.5]). There were no differences in DLCO between the classes.

Conclusions: There were 3 distinct long COVID phenotypes with different outcomes in QoL between 3 and 6 months after symptom onset. These phenotypes suggest that long COVID is a heterogeneous condition with distinct subpopulations who may have different outcomes and warrant tailored therapeutic approaches.

Source: Wong AW, Tran KC, Binka M, Janjua NZ, Sbihi H, Russell JA, Carlsten C, Levin A, Ryerson CJ. Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study. PLoS One. 2023 Jun 2;18(6):e0286588. doi: 10.1371/journal.pone.0286588. PMID: 37267379; PMCID: PMC10237387. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10237387/ (Full text)

Persistent serum protein signatures define an inflammatory subcategory of long COVID

Abstract:

Long COVID or post-acute sequelae of SARS-CoV-2 (PASC) is a clinical syndrome featuring diverse symptoms that can persist for months following acute SARS-CoV-2 infection. The aetiologies may include persistent inflammation, unresolved tissue damage or delayed clearance of viral protein or RNA, but the biological differences they represent are not fully understood. Here we evaluate the serum proteome in samples, longitudinally collected from 55 PASC individuals with symptoms lasting ≥60 days after onset of acute infection, in comparison to samples from symptomatically recovered SARS-CoV-2 infected and uninfected individuals.

Our analysis indicates heterogeneity in PASC and identified subsets with distinct signatures of persistent inflammation. Type II interferon signaling and canonical NF-κB signaling (particularly associated with TNF), appear to be the most differentially enriched signaling pathways, distinguishing a group of patients characterized also by a persistent neutrophil activation signature.

These findings help to clarify biological diversity within PASC, identify participants with molecular evidence of persistent inflammation, and highlight dominant pathways that may have diagnostic or therapeutic relevance, including a protein panel that we propose as having diagnostic utility for differentiating inflammatory and non-inflammatory PASC.

Source: Talla, A., Vasaikar, S.V., Szeto, G.L. et al. Persistent serum protein signatures define an inflammatory subcategory of long COVID. Nat Commun 14, 3417 (2023). https://doi.org/10.1038/s41467-023-38682-4 https://www.nature.com/articles/s41467-023-38682-4 (Full text)

New-onset type 1 diabetes in children and adolescents as postacute sequelae of SARS-CoV-2 infection: A systematic review and meta-analysis of cohort studies

Abstract:

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in children and adolescents may increase risk for a variety of post-acute sequelae including new-onset type 1 diabetes mellitus (T1DM). Therefore, this meta-analysis aims to estimate the risk of developing new-onset type 1 diabetes in children and adolescents as post-acute sequelae of SARS-CoV-2 infection.

PubMed/MEDLINE, CENTRAL, and EMBASE were systematically searched up to March 20, 2023. A systematic review and subsequent meta-analyses were performed to calculate the pooled effect size, expressed as risk ratio (RR) with corresponding 95% confidence interval (CI) of each outcome based on a one-stage approach and the random-effects estimate of the pooled effect sizes of each outcome were generated with the use of the DerSimonian-Laird method. Eight reports from seven studies involving 11 220 530 participants (2 140 897 patients with a history of diagnosed SARS-CoV-2 infection and 9 079 633 participants in the respective control groups) were included. The included studies reported data from four U.S. medical claims databases covering more than 503 million patients (IQVIA, HealthVerity, TriNetX, and Cerner Real-World Data), and three national health registries for all children and adolescents in Norway, Scotland, and Denmark.

It was shown that the risk of new-onset T1DM following SARS-CoV-2 infection in children and adolescents was 42% (95% CI 13%-77%, p = 0.002) higher compared with non-COVID-19 control groups. The risk of developing new-onset T1DM following SARS-CoV-2 infection was significantly higher (67%, 95% CI 32 %-112%, p = 0.0001) in children and adolescents between 0 and 11 years, but not in those between 12 and 17 years (RR = 1.10, 95% CI 0.54-2.23, p = 0.79). We also found that the higher risk for developing new-onset T1DM following SARS-CoV-2 infection only exists in studies from the United States (RR = 1.70, 95% CI 1.37-2.11, p = 0.00001) but not Europe (RR = 1.02, 95% CI 0.67-1.55, p = 0.93). Furthermore, we found that SARS-CoV-2 infection was associated with an elevation in the risk of diabetic ketoacidosis (DKA) in children and adolescents compared with non-COVID-19 control groups (RR = 2.56, 95% CI 1.07-6.11, p = 0.03).

Our findings mainly obtained from US medical claims databases, suggest that SARS-CoV-2 infection is associated with higher risk of developing new-onset T1DM and diabetic ketoacidosis in children and adolescents. These findings highlight the need for targeted measures to raise public health practitioners and physician awareness to provide intervention strategies to reduce the risk of developing T1DM in children and adolescents who have had COVID-19.

Source: Rahmati M, Yon DK, Lee SW, Udeh R, McEVoy M, Kim MS, Gyasi RM, Oh H, López Sánchez GF, Jacob L, Li Y, Koyanagi A, Shin JI, Smith L. New-onset type 1 diabetes in children and adolescents as postacute sequelae of SARS-CoV-2 infection: A systematic review and meta-analysis of cohort studies. J Med Virol. 2023 Jun;95(6):e28833. doi: 10.1002/jmv.28833. PMID: 37264687. https://onlinelibrary.wiley.com/doi/10.1002/jmv.28833

Long COVID Clinical Phenotypes Up to Six Months After Infection Identified by Latent Class Analysis of Self-Reported Symptoms

Abstract:

Background: The prevalence, incidence, and interrelationships of persistent symptoms after SARS-CoV-2 infection (Long COVID) vary. There are limited data on specific phenotypes of persistent symptoms. Using latent class analysis (LCA) modeling, we sought to identify whether specific phenotypes of COVID-19 were present three months and six months after acute infection.

Methods: This was a multicenter, prospective study of symptomatic adults tested for SARS-CoV-2 with prospectively collected data on general symptoms and fatigue-related symptoms up to six-months post-diagnosis. Using LCA, we identified symptomatically homogenous groups among participants with COVID-19 (COVID-positive) and among others without COVID-19 (COVID-negative) at each time period for both general and fatigue-related symptoms.

Results: Among 5,963 baseline participants (4,504 COVID-positive and 1,459 COVID-negative), 4,056 had three-month and 2,856 had six-month data at the time of analysis. We identified four distinct phenotypes of post-COVID conditions at three- and six-months for both general and fatigue-related symptoms; minimal symptom groups represented 70% of participants at three and six months. When compared with the COVID-negative cohort, COVID-positive participants had higher occurrence of loss of taste and smell, as well cognition problems. There was substantial class-switching over time; those in one symptom class at three months were equally likely to remain or enter a new phenotype at six months.

Conclusions: We identified distinct classes of post-COVID phenotypes for general and fatigue-related symptoms. Most participants had minimal or no symptoms at three and six months follow-up. Significant proportions of participants changed symptom groups over time, suggesting that symptoms present during the acute illness may differ from prolonged symptoms and that post-COVID conditions may have a more dynamic nature than previously recognized.

Source: Michael Gottlieb, MD and others, Long COVID Clinical Phenotypes Up to Six Months After Infection Identified by Latent Class Analysis of Self-Reported Symptoms, Open Forum Infectious Diseases, 2023;, ofad277, https://doi.org/10.1093/ofid/ofad277 (Full text available as PDF file)

Major Depressive Disorder and Chronic Fatigue Syndrome Show Characteristic Heart Rate Variability Profiles Reflecting Autonomic Dysregulations: Differentiation by Linear Discriminant Analysis

Abstract:

Major depressive disorder (MDD) and chronic fatigue syndrome (CFS) have overlapping symptoms, and differentiation is important to administer the proper treatment.

The present study aimed to assess the usefulness of heart rate variability (HRV) indices.

Frequency-domain HRV indices, including high-frequency (HF) and low-frequency (LF) components, their sum (LF+HF), and their ratio (LF/HF), were measured in a three-behavioral-state paradigm composed of initial rest (Rest), task load (Task), and post-task rest (After) periods to examine autonomic regulation.

It was found that HF was low at Rest in both disorders, but was lower in MDD than in CFS. LF and LF+HF at Rest were low only in MDD. Attenuated responses of LF, HF, LF+HF, and LF/HF to task load and an excessive increase in HF at After were found in both disorders.

The results indicate that an overall HRV reduction at Rest may support a diagnosis of MDD. HF reduction was found in CFS, but with a lesser severity.

Response disturbances of HRV to Task were observed in both disorders, and would suggest the presence of CFS when the baseline HRV has not been reduced.

Linear discriminant analysis using HRV indices was able to differentiate MDD from CFS, with a sensitivity and specificity of 91.8% and 100%, respectively. HRV indices in MDD and CFS show both common and different profiles, and can be useful for the differential diagnosis.

Source: Shinba T, Kuratsune D, Shinba S, Shinba Y, Sun G, Matsui T, Kuratsune H. Major Depressive Disorder and Chronic Fatigue Syndrome Show Characteristic Heart Rate Variability Profiles Reflecting Autonomic Dysregulations: Differentiation by Linear Discriminant Analysis. Sensors. 2023; 23(11):5330. https://doi.org/10.3390/s23115330 https://www.mdpi.com/1424-8220/23/11/5330 (Full text)

Increasing serum soluble CD40 ligand (sCD40L) may be a biomarker of ME/CFS and chronic Long COVID progression

Abstract:

To date, no single blood lab test exists to diagnose or track ME/CFS or chronic Long COVID. Based on existing literature, this article brings together evidence that a molecule secreted by the immune system called sCD40L tends to become increasingly elevated in ME/CFS, Long COVID, and Multiple Sclerosis.

These studies, along with what’s known about the role of sCD40L in health and other diseases, suggest sCD40L may be useful to track over time in ME/CFS and Long COVID patients.

Source: Vijay Iyer. Increasing serum soluble CD40 ligand (sCD40L) may be a biomarker of ME/CFS and chronic Long COVID progression. Patient-Generated Hypotheses Journal | Issue 1, May 2023. https://patientresearchcovid19.com/storage/2023/05/Patient-Generated-Hypotheses-Issue-1-May-2023.pdf#page=42 (Full text)

Inflammation-induced pain and fatigue in fibromyalgia and ME/CFS and role of variant connective tissue

Abstract:

Background: Fibromyalgia and ME/CFS are multifaceted conditions with overlapping symptoms(1); the pathophysiological mechanisms are under debate. It remains unclear whether dysregulated inflammation, induced either by an exogenous stimulus (eg a virus or other stressor), or autoimmunity, is of prime importance [2].

Objectives: 1. To determine in a novel human model the effects of an in vivo inflammatory challenge in the induction of pain and fatigue in fibromyalgia and ME/CFS compared to controls. 2. Explore potential mediators and moderators involved.

Methods: Data were available for 48 patients with confirmed diagnoses of Fibromyalgia and/ or ME/CFS and 22 matched controls, who had undergone a placebo controlled inflammatory challenge (typhoid vaccination) as part of ISRCTN78820481. Participants underwent full research diagnostic evaluation including a hypermobility assessment. Subjective pain and fatigue were assessed after saline injection and typhoid vaccination (VAS). Linear regression models were used to explore predictors, with adjustment for potential confounders (age/gender) and baseline levels as appropriate.

Mediation analyses (looking for mechanistic effects) were conducted according to the method of Hayes (3) and mediation considered significant if bootstrapped confidence intervals of the estimated indirect effect did not cross zero. In these mediation analyses predictor variable was group membership (patient or control), outcome variable was change in 1) pain and 2) fatigue induced by challenge and mediators/moderators included change in IL-6 induced by inflammatory challenge and hypermobility features.

Results: Being a patient rather than control significantly predicted inflammation-induced fatigue (B=14.89 (95%CI 3.29-26.50), t=2.56, p=0.013) and pain (B=12.88 (95%CI 0.65-25.10), t=2.11, p=0.039) after adjusting for levels induced by placebo.

Induced pain was independently predicted by level of IL-6 induced by inflammatory challenge (B=23.44 (95%CI 5.15-41.72),t=2.57, p=0.013) as was induced fatigue (B=10.63 (95%CI 2.84-18.41), t=2.73, p=0.008) Mediated moderation analyses suggested the link to induced pain and fatigue through induced inflammation was associated with hypermobility features (Index of mediated moderation 11.02 (95%CI 1.45-22.73) and 6.20 (95%CI 0.07-13.64) respectively))

Conclusion: To our knowledge this is the first human study to evaluate directly the effect of an exogenous inflammatory challenge (typhoid vaccination) in a combined group of Fibromyalgia and ME/CFS patients. Il-6 was shown to be a critical mediator. This work strongly supports the hypothesis that inflammation is key to the pathophysiology of ME/CFS. We are evaluating associated CNS inflammation in the model, as well as other associations, such as autonomic dysfunction and hypermobility. Further understanding the mediators involved in the condition should in future open the way to testing targeted anti-inflammatory therapy.

Source: Eccles J, Amato M, Themelis K, et alOP0194 INFLAMMATION-INDUCED PAIN AND FATIGUE IN FIBROMYALGIA AND ME/CFS AND ROLE OF VARIANT CONNECTIVE TISSUEAnnals of the Rheumatic Diseases 2023;82:129. https://ard.bmj.com/content/82/Suppl_1/129.2 (Full text)

The relevance of pacing strategies in managing symptoms of post-COVID-19 syndrome

Abstract:

Background: Post-COVID-19 syndrome (PCS) shares many features with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). PCS represents a major health issue worldwide because it severely impacts patients’ work activities and their quality of life. In the absence of treatment for both conditions and given the beneficial effect of pacing strategies in ME/CFS, we conducted this study to assess the effectiveness of pacing in PCS patients.

Methods: We retrospectively included patients meeting the World Health Organization definition of PCS who attended the Internal Medicine Department of Angers University Hospital, France between June 2020 and June 2022, and were followed up until December 2022. Pacing strategies were systematically proposed for all patients. Their medical records were reviewed and data related to baseline and follow-up assessments were collected. This included epidemiological characteristics, COVID-19 symptoms and associated conditions, fatigue features, perceived health status, employment activity, and the degree of pacing adherence assessed by the engagement in pacing subscale (EPS). Recovery was defined as the ability to return to work, and improvement was regarded as the reduction of the number and severity of symptoms.

Results: A total of 86 patients were included and followed-up for a median time of 10 [6-13] months. Recovery and improvement rates were 33.7% and 23.3%, respectively. The EPS score was the only variable significantly associated with recovery on multivariate analysis (OR 40.43 [95% CI 6.22-262.6], p < 0.001). Patients who better adhered to pacing (high EPS scores) experienced significantly higher recovery and improvement rates (60-33.3% respectively) than those with low (5.5-5.5% respectively), or moderate (4.3-17.4% respectively) scores.

Conclusion: Our findings demonstrated that pacing is effective in the management of patients with PCS, and that high levels of adherence to pacing are associated with better outcomes.

Source: Ghali A, Lacombe V, Ravaiau C, Delattre E, Ghali M, Urbanski G, Lavigne C. The relevance of pacing strategies in managing symptoms of post-COVID-19 syndrome. J Transl Med. 2023 Jun 8;21(1):375. doi: 10.1186/s12967-023-04229-w. PMID: 37291581; PMCID: PMC10248991. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248991/ (Full text)

Analysis of tumor progression among patients with glioma after COVID-19 infection

Background: As of January 2023, there have been 6.7 million worldwide deaths attributed to SARS-CoV-2 COVID-19, which has impacted outcomes and medical care for all patients. Relatively little is known about the direct effects mediated by the virus on CNS tumor biology, despite the fact that viral neurotropism is well described, various coronavirus receptors have been observed in glioblastoma (GBM) tissues, and differential monocytic infiltration has been proposed to dysregulate the immune microenvironment. We detected a trend of rapid progression following COVID-19 infection among several patients with primary brain tumor patients and sought to systematically evaluate the pace of progression among infected patients in our institution.

Methods: A single-institutional database of COVID-19 patients and an electronic medical record (EMR) search tool were used to identify a total cohort of 67 patients with glioma for retrospective analysis. This included 38 GBMs, 18 IDH-mutant gliomas, 5 ependymomas, 2 pilocytic astrocytomas, 1 diffuse midline glioma, 1 diffuse hemispheric glioma, and 1 ganglioglioma patients, each of whom had a documented COVID-19 infection between June 2020-December 2022. Hyperprogression was defined as tumor increase ≥40% compared to previous scan using RECIST size criteria.

Results: Thirty-nine (58%) patients experienced tumor progression following COVID-19 infection at a median of 34 days (range=1-734 days) after testing positive for COVID-19. Twenty-two (56%) had received COVID-19 vaccine before their infection and 5 (13%) had asymptomatic infections. Twenty-two patients had measurably increased tumor area by a median of 63% (range=10-2,900%), 18 of which constituted hyperprogression;16 patients developed multifocal disease, 8 developed new nodular enhancement, 3 developed leptomeningeal disease (LMD), and 2 experienced increased infiltrative disease alone. Ten patients’ presentation with new glioma was preceded by COVID-19 infection by a median of 31 days. GBM patients represented the majority of progression events, among whom 59% progressed within 60 days of documented infection (median 25 days). This subgroup of GBM with rapid progression within 60 days had a mOS from infection of 5.2 months; 89% had TERT promotor mutations and 42% had MGMT promoter methylation.

Conclusions: Glioma patients appear to have disease progression at an accelerated pace in the first two months after COVID-19 infection. This suggests that glioma patients should continue observing strict precautions to prevent infection and should be clinically monitored vigilantly after infection, with consideration for short interval imaging during treatment. These preliminary data warrant further investigation exploring changes of immune cell infiltration in the tumor microenvironment and the possible correlation between tumor progression and COVID-19.

Source: Tim Gregory, Stephanie Knight, Ashley Aaroe, Barbara Jane O’Brien, Chirag B Patel, Shiao-Pei S. Weathers, Nazanin Majd, Vinay K. Puduvalli, and Carlos Kamiya-Matsuoka. Analysis of tumor progression among patients with glioma after COVID-19 infection.
Journal of Clinical Oncology 2023 41:16_suppl, 2041-2041 https://ascopubs.org/action/showCitFormats?doi=10.1200/JCO.2023.41.16_suppl.2041