The demographic, laboratory and genetic factors associated with long Covid-19 syndrome: a case-control study

HLA-A*03 may confer protection against long COVID through an enhanced immune response

BACKGROUND

The COVID-19 pandemic has led to widespread infection, with a significant subset of patients developing persistent symptoms known as Long COVID. Understanding the genetic factors influencing Long COVID susceptibility and severity is crucial for development of targeted interventions.

OBJECTIVE

This study aimed to evaluate the impact of HLA alleles, KIR receptors, and their interactions on the development of Long COVID in patients from southeastern Spain having contracted COVID-19 during the early 2020 pandemic wave.

METHODS

A cross-sectional prospective study enrolled 153 COVID-19 patients. Three months post-infection, HLA-A, -B, -C, KIR genotyping and immunological variables were analyzed using serum and blood samples. Long COVID was diagnosed three years post- infection based on persistent symptoms.

RESULTS

Among the participants, 71 developed Long COVID. HLA-A*03 was less frequent in Long COVID compared to non-Long COVID patients (10.7 % vs. 30.5 %, p = 0.001). Patients with HLA-A*03 had a higher percentage of CD8+ T cells than patients with other allotypes (33.6 ± 13.4 % vs 28.7 ± 10.8 %, p = 0.033) and showed lower expression of KIR2DL1(1265 ± 547 vs 1465 ± 414 MFI, p = 0.031) and KIR3DL1 (300.6 ± 125.0 vs 398.9 ± 131.0 MFI, p = 0.047). Moreover, NK cells in HLA-A*03 patients showed lower expression of the TIGIT inhibitory receptor (73.7 ± 12.2 % vs 78.2 ± 10.8 %, p = 0.046).

CONCLUSION

HLA-A*03 may play a protective role against Long COVID, potentially through enhanced immune responses involving CD8+ T cells and NK cells. Further research in larger, diverse cohorts is needed to validate these findings and to refine personalized medicine strategies for managing COVID-19 sequelae.

Learning from post-COVID-19 condition for epidemic preparedness: a variable catalogue for future post-acute infection syndromes

SCOPE

The emergence of post-COVID-19 condition (PCC) after SARS-CoV-2 infection underscores the critical need for preparedness in addressing future post-acute infection syndromes (PAIS), particularly those linked to epidemic outbreaks. The lack of standardized clinical and epidemiological data during the COVID-19 pandemic has significantly hindered timely diagnosis and effective treatment of PCC, highlighting the necessity of pre-emptively standardizing data collection in clinical studies to better define and manage future PAIS. In response, the Cohort Coordination Board, a consortium of European-funded COVID-19 research projects, has reviewed data from PCC studies conducted by its members. This paper leverages the Cohort Coordination Board's expertise to propose a standardized catalogue of variables, informed by the lessons learned during the pandemic, intended for immediate use in the design of future observational studies and clinical trials for emerging infections of epidemic potential.

RECOMMENDATIONS

The early implementation of standardized data collection, facilitated by the PAIS data catalogue, is essential for accelerating the identification and management of PAIS in future epidemics. This approach will enable more precise syndrome definitions, expedite diagnostic processes, and optimize treatment strategies, while also supporting long-term follow-up of affected individuals. The availability of harmonized data collection protocols will enhance preparedness across European and international cohort studies, and trials enabling a prompt and coordinated response, as well as more efficient resource allocation, in the event of emerging infections and associated PAIS.

Immune activation and immune-associated neurotoxicity in Long-COVID: A systematic review and meta-analysis of 103 studies comprising 58 cytokines/chemokines/growth factors

BACKGROUND

Multiple studies have shown that Long COVID (LC) disease is associated with heightened immune activation, as evidenced by elevated levels of inflammatory mediators. However, there is no comprehensive meta-analysis focusing on activation of the immune inflammatory response system (IRS) and the compensatory immunoregulatory system (CIRS) along with other immune phenotypes in LC patients.

OBJECTIVES

This meta-analysis is designed to explore the IRS and CIRS profiles in LC patients, the individual cytokines, chemokines, growth factors, along with C-reactive protein (CRP) and immune-associated neurotoxicity.

METHODS

To gather relevant studies for our research, we conducted a thorough search using databases such as PubMed, Google Scholar, and SciFinder, covering all available literature up to July 5th, 2024.

RESULTS

The current meta-analysis encompassed 103 studies that examined multiple immune profiles, C-reactive protein, and 58 cytokines/chemokines/growth factors in 5502 LC patients versus 5962 normal controls (NC). LC patients showed significant increases in IRS/CIRS ratio (standardized mean difference (SMD: 0.156, confidence interval (CI): 0.062;0.250), IRS (SMD: 0.338, CI: 0.236;0.440), M1 macrophage (SMD: 0.371, CI: 0.263;0.480), T helper (Th)1 (SMD: 0.316, CI: 0.185;0.446), Th17 (SMD: 0.439, CI: 0.302;0.577) and immune-associated neurotoxicity (SMD: 0.384, CI: 0.271;0.497). In addition, CRP and 21 different cytokines displayed significantly elevated levels in LC patients compared to NC.

CONCLUSION

LC disease is characterized by IRS activation and increased immune-associated neurotoxicity.

Cluster analysis identifies long COVID subtypes in Belgian patients

Severe acute respiratory syndrome coronavirus infection presents complications known as long COVID, a multisystemic organ disease which allows multidimensional analysis. This study aims to uncover clusters of long COVID cases and establish their correlation with the clinical classification developed at the Clinical Research Unit of Brugmann University Hospital, Brussels. Such an endeavour is instrumental in customizing patient management strategies tailored to the unique needs of each distinct group. A two-stage multidimensional exploratory analysis was performed on a retrospective cohort of 205 long COVID patients, involving a factorial analysis of mixed data, and then hierarchical clustering post component analysis. The study's sample comprised 76% women, with an average age of 44.5 years. Three clinical forms were identified: long, persistent, and post-viral syndrome. Multidimensional analysis using demographic, clinical, and biological variables identified three clusters of patients. Biological data did not provide sufficient differentiation between clusters. This emphasizes the importance of identifying or classifying long COVID patients according to their predominant clinical syndrome. Long COVID phenotypes, as well as clinical forms, appear to be associated with distinct pathophysiological mechanisms or genetic predispositions. This underscores the need for further research.