long covid phenotypes – American ME and CFS Society

Characterizing Long COVID in Children and Adolescents

Key Points:

Question What prolonged symptoms experienced by youth are most associated with SARS-CoV-2 infection?

Findings Among 5367 participants in the RECOVER-Pediatrics cohort study, 14 symptoms in both school-age children (6-11 years) and adolescents (12-17 years) were more common in those with vs without SARS-CoV-2 infection history, with 4 additional symptoms in school-age children only and 3 in adolescents only. Empirically derived indices for PASC research and associated clustering patterns were developed.

Meaning This study developed research indices for characterizing pediatric PASC. Symptom patterns were similar but distinguishable between school-age children and adolescents, highlighting the importance of characterizing PASC separately in different age groups.

Abstract

Importance Most research to understand postacute sequelae of SARS-CoV-2 infection (PASC), or long COVID, has focused on adults, with less known about this complex condition in children. Research is needed to characterize pediatric PASC to enable studies of underlying mechanisms that will guide future treatment.

Objective To identify the most common prolonged symptoms experienced by children (aged 6 to 17 years) after SARS-CoV-2 infection, how these symptoms differ by age (school-age [6-11 years] vs adolescents [12-17 years]), how they cluster into distinct phenotypes, and what symptoms in combination could be used as an empirically derived index to assist researchers to study the likely presence of PASC.

Design, Setting, and Participants Multicenter longitudinal observational cohort study with participants recruited from more than 60 US health care and community settings between March 2022 and December 2023, including school-age children and adolescents with and without SARS-CoV-2 infection history.

Exposure SARS-CoV-2 infection.

Main Outcomes and Measures PASC and 89 prolonged symptoms across 9 symptom domains.

Results A total of 898 school-age children (751 with previous SARS-CoV-2 infection [referred to as infected] and 147 without [referred to as uninfected]; mean age, 8.6 years; 49% female; 11% were Black or African American, 34% were Hispanic, Latino, or Spanish, and 60% were White) and 4469 adolescents (3109 infected and 1360 uninfected; mean age, 14.8 years; 48% female; 13% were Black or African American, 21% were Hispanic, Latino, or Spanish, and 73% were White) were included. Median time between first infection and symptom survey was 506 days for school-age children and 556 days for adolescents. In models adjusted for sex and race and ethnicity, 14 symptoms in both school-age children and adolescents were more common in those with SARS-CoV-2 infection history compared with those without infection history, with 4 additional symptoms in school-age children only and 3 in adolescents only. These symptoms affected almost every organ system. Combinations of symptoms most associated with infection history were identified to form a PASC research index for each age group; these indices correlated with poorer overall health and quality of life. The index emphasizes neurocognitive, pain, and gastrointestinal symptoms in school-age children but change or loss in smell or taste, pain, and fatigue/malaise–related symptoms in adolescents. Clustering analyses identified 4 PASC symptom phenotypes in school-age children and 3 in adolescents.

Conclusions and Relevance This study developed research indices for characterizing PASC in children and adolescents. Symptom patterns were similar but distinguishable between the 2 groups, highlighting the importance of characterizing PASC separately for these age ranges.

Cluster Analysis to Identify Long COVID Phenotypes Using 129Xe Magnetic Resonance Imaging: A Multi-centre Evaluation

Abstract:

Background Long COVID impacts ∼10% of people diagnosed with COVID-19, yet the pathophysiology driving ongoing symptoms is poorly understood. We hypothesised that ¹²⁹Xe magnetic resonance imaging (MRI) could identify unique pulmonary phenotypic subgroups of long COVID, therefore we evaluated ventilation and gas exchange measurements with cluster analysis to generate imaging-based phenotypes.

Methods COVID-negative controls and participants who previously tested positive for COVID-19 underwent ¹²⁹XeMRI ∼14-months post-acute infection across three centres. Long COVID was defined as persistent dyspnea, chest tightness, cough, fatigue, nausea and/or loss of taste/smell at MRI; participants reporting no symptoms were considered fully-recovered. ¹²⁹XeMRI ventilation defect percent (VDP) and membrane (Mem)/Gas, red blood cell (RBC)/Mem and RBC/Gas ratios were used in k-means clustering for long COVID, and measurements were compared using ANOVA with post-hoc Bonferroni correction.

Results We evaluated 135 participants across three centres: 28 COVID-negative (40±16yrs), 34 fully-recovered (42±14yrs) and 73 long COVID (49±13yrs). RBC/Mem (p=0.03) and FEV₁ (p=0.04) were different between long- and COVID-negative; FEV₁ and all other pulmonary function tests (PFTs) were within normal ranges. Four unique long COVID clusters were identified compared with recovered and COVID-negative. Cluster1 was the youngest with normal MRI and mild gas-trapping; Cluster2 was the oldest, characterised by reduced RBC/Mem but normal PFTs; Cluster3 had mildly increased Mem/Gas with normal PFTs; and Cluster4 had markedly increased Mem/Gas with concomitant reduction in RBC/Mem and restrictive PFT pattern.

Conclusion We identified four ¹²⁹XeMRI long COVID phenotypes with distinct characteristics. ¹²⁹XeMRI can dissect pathophysiologic heterogeneity of long COVID to enable personalised patient care.

Source: Rachel L Eddy, David Mummy, Shuo Zhang, Haoran Dai, Aryil Bechtel, Alexandra Schmidt, Bradie Frizzell, Firoozeh V Gerayeli, Jonathon A Leipsic, Janice M Leung, Bastiaan Driehuys, Loretta G Que, Mario Castro, Don D Sin, Peter J Niedbalski. Cluster Analysis to Identify Long COVID Phenotypes Using 129Xe Magnetic Resonance Imaging: A Multi-centre Evaluation. European Respiratory Journal Jan 2024, 2302301; DOI: 10.1183/13993003.02301-2023 https://erj.ersjournals.com/content/early/2024/02/02/13993003.02301-2023 (Full text)

Long COVID is not a uniform syndrome: Evidence from person-level symptom clusters using latent class analysis

Abstract:

Background: The current study aims to enhance insight into the heterogeneity of long COVID by identifying symptom clusters and associated socio-demographic and health determinants.

Methods: A total of 458 participants (M_age 36.0 ± 11.9; 46.5% male) with persistent symptoms after COVID-19 completed an online self-report questionnaire including a 114-item symptom list. First, a k-means clustering analysis was performed to investigate overall clustering patterns and identify symptoms that provided meaningful distinctions between clusters. Next, a step-three latent class analysis (LCA) was performed based on these distinctive symptoms to analyze person-centered clusters. Finally, multinominal logistic models were used to identify determinants associated with the symptom clusters.

Results: From a 5-cluster solution obtained from k-means clustering, 30 distinctive symptoms were selected. Using LCA, six symptom classes were identified: moderate (20.7%) and high (20.7%) inflammatory symptoms, moderate malaise-neurocognitive symptoms (18.3%), high malaise-neurocognitive-psychosocial symptoms (17.0%), low-overall symptoms (13.3%) and high overall symptoms (9.8%). Sex, age, employment, COVID-19 suspicion, COVID-19 severity, number of acute COVID-19 symptoms, long COVID symptom duration, long COVID diagnosis, and impact of long COVID were associated with the different symptom clusters.

Conclusions: The current study’s findings characterize the heterogeneity in long COVID symptoms and underscore the importance of identifying determinants of different symptom clusters.

Source: van den Houdt SCM, Slurink IAL, Mertens G. Long COVID is not a uniform syndrome: Evidence from person-level symptom clusters using latent class analysis. J Infect Public Health. 2023 Dec 29;17(2):321-328. doi: 10.1016/j.jiph.2023.12.019. Epub ahead of print. PMID: 38183882. https://www.sciencedirect.com/science/article/pii/S1876034123004616 (Full text)

Features of acute COVID-19 associated with post-acute sequelae of SARS-CoV-2 phenotypes: results from the IMPACC study

Abstract:

Post-acute sequelae of SARS-CoV-2 (PASC) is a significant public health concern. We describe Patient Reported Outcomes (PROs) on 590 participants prospectively assessed from hospital admission for COVID-19 through one year after discharge. Modeling identified 4 PRO clusters based on reported deficits (minimal, physical, mental/cognitive, and multidomain), supporting heterogenous clinical presentations in PASC, with sub-phenotypes associated with female sex and distinctive comorbidities.

During the acute phase of disease, a higher respiratory SARS-CoV-2 viral burden and lower Receptor Binding Domain and Spike antibody titers were associated with both the physical predominant and the multidomain deficit clusters. A lower frequency of circulating B lymphocytes by mass cytometry (CyTOF) was observed in the multidomain deficit cluster. Circulating fibroblast growth factor 21 (FGF21) was significantly elevated in the mental/cognitive predominant and the multidomain clusters. Future efforts to link PASC to acute anti-viral host responses may help to better target treatment and prevention of PASC.

Source: Ozonoff, A., Jayavelu, N.D., Liu, S. et al. Features of acute COVID-19 associated with post-acute sequelae of SARS-CoV-2 phenotypes: results from the IMPACC study. Nat Commun 15, 216 (2024). https://doi.org/10.1038/s41467-023-44090-5 https://www.nature.com/articles/s41467-023-44090-5 (Full text)

Arterial Stiffness and Oxidized LDL Independently Associated With Post-Acute Sequalae of SARS-CoV-2

Abstract:

Objective: COVID-19 survivors can experience lingering symptoms known as post-acute sequelae of SARS-CoV-2 (PASC) that appear in different phenotypes, and its etiology remains elusive. We assessed the relationship of endothelial dysfunction with having COVID and PASC.

Methods: Data was collected from a prospectively enrolled cohort (n=379) of COVID-negative and COVID-positive participants with and without PASC. Primary outcomes, endothelial function (measured by reactive hyperemic index [RHI]), and arterial elasticity (measured by augmentation index standardized at 75 bpm [AI]), were measured using the FDA approved EndoPAT. Patient characteristics, labs, metabolic measures, markers of inflammation, and oxidized LDL (ox-LDL) were collected at each study visit, and PASC symptoms were categorized into 3 non-exclusive phenotypes: cardiopulmonary, neurocognitive, and general. COVID-negative controls were propensity score matched to COVID-negative-infected cases using the greedy nearest neighbor method.

Results: There were 14.3% of participants who were fully recovered COVID positive and 28.5% who were COVID positive with PASC, averaging 8.64 ± 6.26 total number of symptoms. The mean RHI was similar across the cohort and having COVID or PASC was not associated with endothelial function (P=0.33). Age (P<0.0001), female sex (P<0.0001), and CRP P=0.04) were positively associated with arterial stiffness, and COVID positive PASC positive with neurological and/or cardiopulmonary phenotypes had the worst arterial elasticity (highest AI). Values for AI (P=0.002) and ox-LDL (P<0.0001) were independently and positively associated with an increased likelihood of having PASC.

Conclusion: There is evidence of an independent association between PASC, ox-LDL, and arterial stiffness with neurological and/or cardiopulmonary phenotypes having the worst arterial elasticity. Future studies should continue investigating the role of oxidative stress in the pathophysiology of PASC.

Source: Zisis SN, Durieux JC, Mouchati C, Funderburg N, Ailstock K, Chong M, Labbato D, McComsey GA. Arterial Stiffness and Oxidized LDL Independently Associated With Post-Acute Sequalae of SARS-CoV-2. Pathog Immun. 2023 Dec 20;8(2):1-15. doi: 10.20411/pai.v8i2.634. PMID: 38156116; PMCID: PMC10753933. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10753933/ (Full text)

Large scale phenotyping of long COVID inflammation reveals mechanistic subtypes of disease after COVID-19 hospitalisation

Abstract:

One in ten SARS-CoV-2 infections result in prolonged symptoms termed long COVID, yet disease phenotypes and mechanisms are poorly understood. We studied the blood proteome of 719 previously hospitalised adults with long COVID grouped by symptoms. Elevated markers of myeloid inflammation and complement activation were associated with long COVID; elevated IL1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue, and anxiety/depression, while MATN2 and DPP10 were elevated in gastrointestinal (GI) symptoms, and C1QA in cognitive impairment.

Proteins suggestive of neurodegeneration were elevated in cognitive impairment, whilst SCG3 (indicative of brain-gut axis disturbance) was specific to GI symptoms. Nasal inflammation was apparent after COVID-19 but did not associate with symptoms. Although SARS-CoV-2 specific IgG was elevated with some long COVID symptoms, virus was not detected from sputum. Thus, systemic inflammation is evident in long COVID and could be targeted in therapeutic trials tailored to pathophysiological differences between symptom groups.

Source: Peter Openshaw, Felicity Liew, Claudia Efstathiou et al. Large scale phenotyping of long COVID inflammation reveals mechanistic subtypes of disease after COVID-19 hospitalisation, 04 December 2023, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3427282/v1] https://www.researchsquare.com/article/rs-3427282/v1 (Full text)

Exploring the Influence of VDR Genetic Variants TaqI, ApaI, and FokI on COVID-19 Severity and Long-COVID-19 Symptoms

Abstract:

There is increasing evidence regarding the importance of vitamin D in the prognosis of coronavirus disease 2019 (COVID-19). Genetic variants in the vitamin D receptor (VDR) gene affect the response to vitamin D and have been linked to various diseases. This study investigated the associations of the major VDR genetic variants ApaI, FokI, and TaqI with the severity and long post-infection symptoms of COVID-19. In total, 100 Jordanian patients with confirmed COVID-19 were genotyped for the VDR ApaI, FokI, and TaqI variants using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method.

COVID-19 severity, the most commonly reported long-COVID-19 symptoms that lasted for >4 weeks from the onset of infection, and other variables were analyzed according to VDR genetic variants. In this study, ApaI and FokI polymorphisms showed no significant associations with COVID-19 severity (p > 0.05). However, a significant association was detected between the TaqI polymorphism and the severity of symptoms after infection with the SARS-CoV-2 virus (p = 0.04). The wild-type TaqI genotype was typically present in patients with mild illness, whereas the heterozygous TaqI genotype was present in asymptomatic patients.

With regard to long-COVID-19 symptoms, the VDR heterozygous ApaI and wild-type TaqI genotypes were significantly associated with persistent fatigue and muscle pain after COVID-19 (p ˂ 0.05). Most carriers of the heterozygous ApaI genotype and carriers of the wild-type TaqI genotype reported experiencing fatigue and muscle pain that lasted for more than 1 month after the onset of COVID-19. Furthermore, the TaqI genotype was associated with persistent shortness of breath after COVID-19 (p = 0.003). Shortness of breath was more common among individuals with homozygous TaqI genotype than among individuals with the wild-type or heterozygous TaqI genotype.

VDR TaqI is a possible genetic variant related to both COVID-19 severity and long-COVID-19 symptoms among Jordanian individuals. The associations between VDR TaqI polymorphisms and long-COVID-19 symptoms should be investigated in larger and more diverse ethnic populations.

Source: Alhammadin G, Jarrar Y, Madani A, Lee S-J. Exploring the Influence of VDR Genetic Variants TaqI, ApaI, and FokI on COVID-19 Severity and Long-COVID-19 Symptoms. Journal of Personalized Medicine. 2023; 13(12):1663. https://doi.org/10.3390/jpm13121663 https://www.mdpi.com/2075-4426/13/12/1663 (Full text)

Long Covid Clinical Severity Types Based on Symptoms and Functional Disability: A Longitudinal Evaluation

Abstract:

Background: Long Covid (LC) is a multisystem clinical syndrome with Functional Disability (FD) and compromised Overall Health (OH). There is a lack of distinct clinical symptom clusters (phenotypes) identified in LC so far but there is emerging information on LC clinical severity types. This study explores the consistency of these clinical severity types over time and the relationship between Symptom Severity (SS), FD, and OH in the context of the clinical severity types in a prospective sample.

Methods: A purposive sample of LC patients recruited to the LOng COvid Multidisciplinary consortium Optimising Treatments and servIces acrOss the NHS (LOCOMOTION) study were assessed using the modified COVID-19 Yorkshire Rehabilitation Scale (C19-YRSm) at two assessment time points. A cluster analysis for clinical severity types was undertaken at both time points using k-means partition using two, three, and four initial clusters and different starting values. Cluster analysis was also carried out to assess the presence of symptom phenotypes (symptom clusters).

Findings: Cross-sectional data was available for 759 patients with 356 patients completing C19-YRSm at the two assessment points. Mean age was 46·8 years (SD = 12·7), 69·4% were females, and median duration of LC symptoms at first assessment was 360 days (IQR 217 to 703 days). Cluster analysis revealed three distinct SS and FD clinical severity types – mild (N=96), moderate (N=422), and severe (N=241) – with no distinct symptom phenotypes. The three-level clinical severity pattern remained consistent over time between the two assessments, with 51% of patients switching the clinical severity type between the assessments. The fluctuation was independent of the LC severity and time between the assessments.

Interpretation: This is the first study in the literature to show the consistency of the three clinical severity types over time with patients also switching between severity types indicating the fluctuating nature of LC.

Source: Sivan, Manoj and Smith, Adam B. and Osborne, Thomas and Goodwin, Madeline and Lawrence, Román Rocha and Baley, Sareeta and Williams, Paul and Lee, Cassie and Davies, Helen and Balasundaram, Kumaran and Greenwood, Darren C., Long Covid Clinical Severity Types Based on Symptoms and Functional Disability: A Longitudinal Evaluation. Available at SSRN: https://ssrn.com/abstract=4642650 or http://dx.doi.org/10.2139/ssrn.4642650 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4642650 (Full text available as PDF file)

Dysregulations in hemostasis, metabolism, immune response, and angiogenesis in post-acute COVID-19 syndrome with and without postural orthostatic tachycardia syndrome: a multi-omic profiling study

Abstract:

Post-acute COVID-19 (PACS) are associated with cardiovascular dysfunction, especially postural orthostatic tachycardia syndrome (POTS). Patients with PACS, both in the absence or presence of POTS, exhibit a wide range of persisting symptoms long after the acute infection. Some of these symptoms may stem from alterations in cardiovascular homeostasis, but the exact mechanisms are poorly understood.

The aim of this study was to provide a broad molecular characterization of patients with PACS with (PACS + POTS) and without (PACS-POTS) POTS compared to healthy subjects, including a broad proteomic characterization with a focus on plasma cardiometabolic proteins, quantification of cytokines/chemokines and determination of plasma sphingolipid levels.

Twenty-one healthy subjects without a prior COVID-19 infection (mean age 43 years, 95% females), 20 non-hospitalized patients with PACS + POTS (mean age 39 years, 95% females) and 22 non-hospitalized patients with PACS-POTS (mean age 44 years, 100% females) were studied. PACS patients were non-hospitalized and recruited ≈18 months after the acute infection.

Cardiometabolic proteomic analyses revealed a dysregulation of ≈200 out of 700 analyzed proteins in both PACS groups vs. healthy subjects with the majority (> 90%) being upregulated. There was a large overlap (> 90%) with no major differences between the PACS groups. Gene ontology enrichment analysis revealed alterations in hemostasis/coagulation, metabolism, immune responses, and angiogenesis in PACS vs. healthy controls.

Furthermore, 11 out of 33 cytokines/chemokines were significantly upregulated both in PACS + POTS and PACS-POTS vs. healthy controls and none of the cytokines were downregulated. There were no differences in between the PACS groups in the cytokine levels. Lastly, 16 and 19 out of 88 sphingolipids were significantly dysregulated in PACS + POTS and PACS-POTS, respectively, compared to controls with no differences between the groups.

Collectively, these observations suggest a clear and distinct dysregulation in the proteome, cytokines/chemokines, and sphingolipid levels in PACS patients compared to healthy subjects without any clear signature associated with POTS. This enhances our understanding and might pave the way for future experimental and clinical investigations to elucidate and/or target resolution of inflammation and micro-clots and restore the hemostasis and immunity in PACS.

Source: Mahdi, A., Zhao, A., Fredengren, E. et al. Dysregulations in hemostasis, metabolism, immune response, and angiogenesis in post-acute COVID-19 syndrome with and without postural orthostatic tachycardia syndrome: a multi-omic profiling study. Sci Rep 13, 20230 (2023). https://doi.org/10.1038/s41598-023-47539-1 https://www.nature.com/articles/s41598-023-47539-1 (Full study)

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)