Tag: long covid biomarker

Examining the relationship between inflammatory biomarkers during COVID-19 hospitalization and subsequent long-COVID symptoms: A longitudinal and retrospective study

Abstract:

Introduction: Long-COVID is a heterogeneous condition with a litany of physical and neuropsychiatric presentations and its pathophysiology remains unclear. Little is known about the association between inflammatory biomarkers, such as interleukin-6 (IL-6) and C-reactive protein (CRP) in the acute phase, and persistent symptoms after hospitalization in COVID-19 patients.

Methods: IL-6, CRP, troponin-T, and ferritin were analyzed at admission for all patients with COVID-19 between September 1, 2020 to January 10, 2021. Survivors were followed up 3-months following hospital discharge and were asked to report persistent symptoms they experienced. Admission data were retrospectively collected. Independent t-tests and Mann-Whitney U tests were performed.

Results: In a sample of 144 patients (62.5% male, mean Age 62 years [SD = 13.6]) followed up 3 months after hospital discharge, the commonest symptoms reported were fatigue (54.2%), breathlessness (52.8%), and sleep disturbance (37.5%). In this sample, admission levels of IL-6, CRP and ferritin were elevated. However, those reporting myalgia, low mood, and anxiety at follow-up had lower admission levels of IL-6 (34.9 vs. 52.0 pg/mL, p = .043), CRP (83 vs. 105 mg/L, p = .048), and ferritin (357 vs. 568 ug/L, p = .01) respectively, compared with those who did not report these symptoms. Multivariate regression analysis showed that these associations were confounded by gender, as female patients had significantly lower levels of IL-6 and ferritin on admission (29.5 vs. 56.1, p = .03 and 421.5 vs. 589, p = .001, respectively) and were more likely to report myalgia, low mood and anxiety, when compared to males.

Conclusions: Our data demonstrate that female patients present more often with lower levels of inflammatory biomarkers on admission which are subsequently associated with long-term post-COVID symptoms, such as myalgia and anxiety, in those discharged from hospital with severe COVID-19. Further research is needed into the role of serum biomarkers in post-COVID prognostication.

Source: Sykes DL, Van der Feltz-Cornelis CM, Holdsworth L, Hart SP, O’Halloran J, Holding S, Crooks MG. Examining the relationship between inflammatory biomarkers during COVID-19 hospitalization and subsequent long-COVID symptoms: A longitudinal and retrospective study. Immun Inflamm Dis. 2023 Oct;11(10):e1052. doi: 10.1002/iid3.1052. PMID: 37904690; PMCID: PMC10614127. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614127/ (Full text)

Blood T cell phenotypes correlate with fatigue severity in post-acute sequelae of COVID-19

Abstract:

Purpose: Post-acute sequelae of COVID-19 (PASC) affect approximately 10% of convalescent patients. The spectrum of symptoms is broad and heterogeneous with fatigue being the most often reported sequela. Easily accessible blood biomarkers to determine PASC severity are lacking. Thus, our study aimed to correlate immune phenotypes with PASC across the severity spectrum of COVID-19.

Methods: A total of 176 originally immunonaïve, convalescent COVID-19 patients from a prospective cohort during the first pandemic phase were stratified by initial disease severity and underwent clinical, psychosocial, and immune phenotyping around 10 weeks after first COVID-19 symptoms. COVID-19-associated fatigue dynamics were assessed and related to clinical and immune phenotypes.

Results: Fatigue and severe fatigue were commonly reported irrespective of initial COVID-19 severity or organ-specific PASC. A clinically relevant increase in fatigue severity after COVID-19 was detected in all groups. Neutralizing antibody titers were higher in patients with severe acute disease, but no association was found between antibody titers and PASC. While absolute peripheral blood immune cell counts in originally immunonaïve PASC patients did not differ from unexposed controls, peripheral CD3+CD4+ T cell counts were independently correlated with fatigue severity across all strata in multivariable analysis.

Conclusions: Patients were at similar risk of self-reported PASC irrespective of initial disease severity. The independent correlation between fatigue severity and blood T cell phenotypes indicates a possible role of CD4+ T cells in the pathogenesis of post-COVID-19 fatigue, which might serve as a blood biomarker.

Source: Pink, I., Hennigs, J.K., Ruhl, L. et al. Blood T cell phenotypes correlate with fatigue severity in post-acute sequelae of COVID-19. Infection (2023). https://doi.org/10.1007/s15010-023-02114-8 https://link.springer.com/article/10.1007/s15010-023-02114-8 (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)

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

THU581 Possible Markers For Myalgic Encephalomyelitis / Chronic Fatigue Syndrome Developed In Long Covid: Utility Of Serum Ferritin And Insulin-like Growth Factor-I

Abstract:

Almost three years have passed since coronavirus disease 2019 (COVID-19) pandemic broke out, and along with the number of acute COVID-19 patients, the number of patients suffering from chronic prolonged symptoms after COVID-19, long COVID, or post COVID-19 condition, has also increased.

We established an outpatient clinic specialized for COVID-19 after care (CAC) in Okayama University Hospital in Japan in February 2021. Our recent study has revealed that the most common symptom is “fatigue”, a part of which potentially may develop into myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). However, the pathogenesis and specific prognosticator have yet to be elucidated. The aim of this study was to elucidate the clinical characteristics of patients who developed ME/CFS after COVID-19.

This retrospective observational study investigated the patients who visited our CAC outpatient clinic between February 2021 and March 2022. Of the 234 patients, 139 (59.4%) had fatigue symptoms, of whom 50 (21.4%) met the criteria for ME/CFS (ME/CFS group), while other 89 did not (non-ME/CFS group); 95 patients had no fatigue complaints (no-fatigue group). Although the patients’ backgrounds were not significantly different among the three groups, the ME/CFS group presented the highest scores on the self-rating symptom scales, including the Fatigue Assessment Scale (FAS), EuroQol, and Self-Rating Depression Scale (SDS).

Of note, serum ferritin levels, which were correlated to FAS and SDS scores, were significantly higher in the ME/CFS group (193.0 μg/mL; interquartile range (IQR), 58.8-353.8) than those of non-ME/CFS (98.2 μg/mL; 40.4-251.5) and no-fatigue (86.7 μg/mL; 37.5-209.0) groups, and this trend was prominent in the female patients. Endocrine workup further showed that the ME/CFS group had higher thyrotropin levels but lower growth hormone levels in the serum, and that insulin-like growth factor (IGF)-I levels were inversely correlated with ferritin levels (R = -0.328, p < 0.05).

Collectively, we revealed that serum ferritin levels could be a possible predictor for developing ME/CFS related to long COVID, especially in female patients. Earlier studies have suggested that hyperferritinemia is a clinical feature in the patients of long COVID, in which hepcidin-like effects could also be involved. Our present study also uncovered a relationship between hyperferrinemia and endocrine disorders among patients developing ME/CFS after COVID-19, although further investigations are necessary to understand the characteristics of ferritin metabolism.

Presentation: Thursday, June 15, 2023

Source: Yukichika Yamamoto, Yuki Otsuka, Kazuki Tokumasu, Naruhiko Sunada, Yasuhiro Nakano, Hiroyuki Honda, Yasue Sakurada, Toru Hasegawa, Hideharu Hagiya, Fumio Otsuka, THU581 Possible Markers For Myalgic Encephalomyelitis / Chronic Fatigue Syndrome Developed In Long Covid: Utility Of Serum Ferritin And Insulin-like Growth Factor-I, Journal of the Endocrine Society, Volume 7, Issue Supplement_1, October-November 2023, bvad114.1370, https://doi.org/10.1210/jendso/bvad114.1370 (Full text available as PDF file)

Autonomic dysregulation in long-term patients suffering from Post-COVID-19 Syndrome assessed by heart rate variability

Abstract:

Post-COVID-19 Syndrome (PCS) is a condition with multiple symptoms partly related to dysregulation of the autonomic nerve system. Assessment of heart rate variability (HRV) using 24 h Holter-ECG may serve as a surrogate to characterize cardiac autonomic activity. A prospective study including 103 PCS patients (time after infection = 252 days, age = 49.0 ± 11.3 years, 45.7% women) was performed and patients underwent detailed clinical screening, cardiopulmonary exercise testing, and 24 h Holter monitoring.

Data of PCS patients was compared to 103 CAD patients and a healthy control group (n = 90). After correction for age and sex, frequency-related variables differed in PCS patients compared to controls including LF/HFpower, LF/HFnu, and LF/HF ratio (24 h; p ≤ 0.001). By contrast, these variables were largely comparable between PCS and CAD patients, while sympathetic activation was highest in PCS patients during the 24 h period.

Overall, PCS patients showed disturbed diurnal adjustment of HRV, with impaired parasympathetic activity at night. Patients hospitalized during acute infection showed an even more pronounced overactivation of sympathetic activity compared to patients who underwent ambulant care.

Our data demonstrate persistent HRV alterations in PCS patients with long-term symptom duration, suggesting a sustained impairment of sympathovagal balance. Moreover, sympathetic overstimulation and diminished parasympathetic response in long-term PCS patients are comparable to findings in CAD patients. Whether HRV variables have a prognostic value in PCS and/or might serve as biomarkers indicating a successful interventional approach warrants further longitudinal studies.

Source: Mooren FC, Böckelmann I, Waranski M, Kotewitsch M, Teschler M, Schäfer H, Schmitz B. Autonomic dysregulation in long-term patients suffering from Post-COVID-19 Syndrome assessed by heart rate variability. Sci Rep. 2023 Sep 22;13(1):15814. doi: 10.1038/s41598-023-42615-y. PMID: 37739977; PMCID: PMC10516975. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516975/ (Full text)

Exploring the mechanisms of long COVID: Insights from computational analysis of SARS-CoV-2 gene expression and symptom associations

Abstract:

Long coronavirus disease (COVID) has emerged as a global health issue, affecting a substantial number of people worldwide. However, the underlying mechanisms that contribute to the persistence of symptoms in long COVID remain obscure, impeding the development of effective diagnostic and therapeutic interventions.

In this study, we utilized computational methods to examine the gene expression profiles of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and their associations with the wide range of symptoms observed in long COVID patients. Using a comprehensive data set comprising over 255 symptoms affecting multiple organ systems, we identified differentially expressed genes and investigated their functional similarity, leading to the identification of key genes with the potential to serve as biomarkers for long COVID.

We identified the participation of hub genes associated with G-protein-coupled receptors (GPCRs), which are essential regulators of T-cell immunity and viral infection responses. Among the identified common genes were CTLA4, PTPN22, KIT, KRAS, NF1, RET, and CTNNB1, which play a crucial role in modulating T-cell immunity via GPCR and contribute to a variety of symptoms, including autoimmunity, cardiovascular disorders, dermatological manifestations, gastrointestinal complications, pulmonary impairments, reproductive and genitourinary dysfunctions, and endocrine abnormalities. GPCRs and associated genes are pivotal in immune regulation and cellular functions, and their dysregulation may contribute to the persistent immune responses, chronic inflammation, and tissue abnormalities observed in long COVID.

Targeting GPCRs and their associated pathways could offer promising therapeutic strategies to manage symptoms and improve outcomes for those experiencing long COVID. However, the complex mechanisms underlying the condition require continued study to develop effective treatments. Our study has significant implications for understanding the molecular mechanisms underlying long COVID and for identifying potential therapeutic targets. In addition, we have developed a comprehensive website (https://longcovid.omicstutorials.com/) that provides a curated list of biomarker-identified genes and treatment recommendations for each specific disease, thereby facilitating informed clinical decision-making and improved patient management. Our study contributes to the understanding of this debilitating disease, paving the way for improved diagnostic precision, and individualized therapeutic interventions.

Source: Das S, Kumar S. Exploring the mechanisms of long COVID: Insights from computational analysis of SARS-CoV-2 gene expression and symptom associations. J Med Virol. 2023 Sep;95(9):e29077. doi: 10.1002/jmv.29077. PMID: 37675861. https://pubmed.ncbi.nlm.nih.gov/37675861/

Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation

Abstract:

Introduction: Persistent symptoms after COVID-19 infection (“long COVID”) negatively affects almost half of COVID-19 survivors. Despite its prevalence, its pathophysiology is poorly understood, with multiple host systems likely affected. Here, we followed patients from hospital to discharge and used a systems-biology approach to identify mechanisms of long COVID.

Methods: RNA-seq was performed on whole blood collected early in hospital and 4-12 weeks after discharge from 24 adult COVID-19 patients (10 reported post-COVID symptoms after discharge). Differential gene expression analysis, pathway enrichment, and machine learning methods were used to identify underlying mechanisms for post-COVID symptom development.

Results: Compared to patients with post-COVID symptoms, patients without post-COVID symptoms had larger temporal gene expression changes associated with downregulation of inflammatory and coagulation genes over time. Patients could also be separated into three patient endotypes with differing mechanistic trajectories, which was validated in another published patient cohort. The “Resolved” endotype (lowest rate of post-COVID symptoms) had robust inflammatory and hemostatic responses in hospital that resolved after discharge. Conversely, the inflammatory/hemostatic responses of “Suppressive” and “Unresolved” endotypes (higher rates of patients with post-COVID symptoms) were persistently dampened and activated, respectively. These endotypes were accurately defined by specific blood gene expression signatures (6-7 genes) for potential clinical stratification.

Discussion: This study allowed analysis of long COVID whole blood transcriptomics trajectories while accounting for the issue of patient heterogeneity. Two of the three identified and externally validated endotypes (“Unresolved” and “Suppressive”) were associated with higher rates of post-COVID symptoms and either persistently activated or suppressed inflammation and coagulation processes. Gene biomarkers in blood could potentially be used clinically to stratify patients into different endotypes, paving the way for personalized long COVID treatment.

Source: An AY, Baghela A, Zhang PGY, Blimkie TM, Gauthier J, Kaufmann DE, Acton E, Lee AHY, Levesque RC, Hancock REW. Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation. Front Immunol. 2023 Aug 23;14:1243689. doi: 10.3389/fimmu.2023.1243689. PMID: 37680625; PMCID: PMC10482103. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10482103/ (Full text)

Acute blood biomarker profiles predict cognitive deficits 6 and 12 months after COVID-19 hospitalization

Abstract:

Post-COVID cognitive deficits, including ‘brain fog’, are clinically complex, with both objective and subjective components. They are common and debilitating, and can affect the ability to work, yet their biological underpinnings remain unknown.

In this prospective cohort study of 1,837 adults hospitalized with COVID-19, we identified two distinct biomarker profiles measured during the acute admission, which predict cognitive outcomes 6 and 12 months after COVID-19.

A first profile links elevated fibrinogen relative to C-reactive protein with both objective and subjective cognitive deficits. A second profile links elevated D-dimer relative to C-reactive protein with subjective cognitive deficits and occupational impact. This second profile was mediated by fatigue and shortness of breath. Neither profile was significantly mediated by depression or anxiety.

Results were robust across secondary analyses. They were replicated, and their specificity to COVID-19 tested, in a large-scale electronic health records dataset. These findings provide insights into the heterogeneous biology of post-COVID cognitive deficits.

Source: Taquet, M., Skorniewska, Z., Hampshire, A. et al. Acute blood biomarker profiles predict cognitive deficits 6 and 12 months after COVID-19 hospitalization. Nat Med (2023). https://doi.org/10.1038/s41591-023-02525-y https://www.nature.com/articles/s41591-023-02525-y (Full text)

Chronic inflammation, neutrophil activity, and autoreactivity splits long COVID

Abstract:

While immunologic correlates of COVID-19 have been widely reported, their associations with post-acute sequelae of COVID-19 (PASC) remain less clear. Due to the wide array of PASC presentations, understanding if specific disease features associate with discrete immune processes and therapeutic opportunities is important.

Here we profile patients in the recovery phase of COVID-19 via proteomics screening and machine learning to find signatures of ongoing antiviral B cell development, immune-mediated fibrosis, and markers of cell death in PASC patients but not in controls with uncomplicated recovery. Plasma and immune cell profiling further allow the stratification of PASC into inflammatory and non-inflammatory types.

Inflammatory PASC, identifiable through a refined set of 12 blood markers, displays evidence of ongoing neutrophil activity, B cell memory alterations, and building autoreactivity more than a year post COVID-19. Our work thus helps refine PASC categorization to aid in both therapeutic targeting and epidemiological investigation of PASC.

Source: Woodruff MC, Bonham KS, Anam FA, Walker TA, Faliti CE, Ishii Y, Kaminski CY, Ruunstrom MC, Cooper KR, Truong AD, Dixit AN, Han JE, Ramonell RP, Haddad NS, Rudolph ME, Yalavarthi S, Betin V, Natoli T, Navaz S, Jenks SA, Zuo Y, Knight JS, Khosroshahi A, Lee FE, Sanz I. Chronic inflammation, neutrophil activity, and autoreactivity splits long COVID. Nat Commun. 2023 Jul 14;14(1):4201. doi: 10.1038/s41467-023-40012-7. PMID: 37452024; PMCID: PMC10349085. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10349085/ (Full text)