Cytokine Profile in Different Post-Covid-19 Condition Phenotypes

Background: At least 10% of SARS-CoV-2 infected patients suffer from persistent symptoms for >12 weeks, known as post-COVID-19 condition (PCC) or Long Covid. Reported symptomatology is diverse with >200 physical and neurological debilitating symptoms. Here, we analyzed pro-inflammatory cytokine levels as a potential mechanism underlying persistent symptomatology. Method(s): Clinical data and samples used belong to the KING cohort extension, which includes clinically well characterized PCC (N=358, 59 persistent symptoms evaluated), COVID-19 recovered and uninfected subjects. We used Gower distances to calculate symptom's similarity between PCC and Ward's hierarchical clustering method to identify different symptom patterns among PCC patients. Cytokine levels of randomly selected PCC, recovered and uninfected subjects (N=193) were measured on plasma samples collected >6 months after acute infection using the 30-Plex Panel for Luminex. Mann- Whitney t-test was used to compare PCC vs recovered groups and Kruskal-Wallis t-test for >2 groups comparisons (PCC vs recovered vs Uninfected and within PCC clusters). FDR correction was applied for statistical significance (p-adj). Result(s): Hierarchical clustering identified 5 different PCC clusters according to their symptomatology, where PCC3 and PCC5 clusters showed higher prevalence of women ( >80%) and more persistent symptoms, while acute COVID-19 was mild in >80% of the patients. We selected 91 PCC (belonging to each cluster), 57 recovered and 45 uninfected subjects for cytokine profiling (Table 1). 13 soluble markers were significantly elevated (IL-1beta, Eotaxin, MIP-1beta, MCP-1, IL-15, IL-5, HGF, IFN-alpha, IL-1RA, IL-7, MIG, IL-4 and IL-8) in PCC and recovered groups compared to uninfected subjects (all p-adj< 0.04). In addition, PCC subjects tended towards higher levels of IL-1RA compared to recovered group (padj= 0.071). Within PCC clusters, FGF-basic and RANTES were elevated while IL-2 and MIG were decreased in PCC3 and PCC5 compared to the other PCC clusters (all p-adj< 0.04). TNF-alpha, IP-10, G-CSF and MIP-1alpha were decreased in PCC3 and PCC5 not reaching statistical significance (all p-adj=0.07). Conclusion(s): Some cytokines remained altered in all SARS-CoV-2 infected subjects independently of persistent symptoms after 6 months from acute infection. Differences between PCC and recovered individuals are limited after correction. Importantly, PCC cytokine profiles showed differences between clusters, which suggests different PCC subsyndromes with distinct etiology. Subjects Characteristics (Table Presented).

IDENTIFICATION OF CLINICAL FEATURES ASSOCIATED WITH SARS-CoV-2 REINFECTIONS

Background: Over 600 million of COVID-19 cases have been reported. A remarkable fragment of these cases are reinfections, which are mostly explained by the genomic variability of the SARS-CoV-2 variants. However, little is known about other factors fostering these reinfections. Method(s): We recorded clinical and demographic data from subjects (N=3303, March 2020 - March 2022) with at least 2 PCR+ events separated by >=90 days, analyzed by the Microbiology Department, Northern Metropolitan Clinical Laboratory from Germans Trias i Pujol Hospital (Spain). Data collected included: age, sex, comorbidities, adjusted morbidity group (GMA), hospitalization, symptomatology, NAAT (PCR, TMA) tests, antigen tests, serology, and vaccination. Temporal data was encoded using Python, and demographic characterization was performed under R. Result(s): We identified 2344 cases of confirmed reinfections, where the 2 PCR+ events were separated by >=90 days and a negative test was obtained between episodes. 72.2% of reinfected subjects were females with a median age of 45 IQR [28-63] years. Age density analysis showed three peaks at 24, 45, and 85 years, probably mostly composed of young people, who usually are less cautious, healthcare workers, and people living in nursing homes, respectively, being all of them groups prone to be tested. Regarding health status, 86.2% of participants had at least one chronic condition, with 40.5% of patients having chronic conditions in >=4 systems based on GMA assessment. Interestingly, 75.2% of reinfected subjects < 26 years had at least one chronic condition. 121 (4.2%) participants were hospitalized during a COVID-19 episode, highlighting 8.3% (N=10) of them hospitalized during the reinfection (half of them vaccinated before hospitalization), and 5% (N=6) of them during both infections. The severity of the second infection may be caused by a diminished acquired immunity after the first infection. Time between reinfections density analysis provided three peaks at ~200, ~400, and ~600 days, corresponding with time between waves. A decrease of reinfections was observed between 40 and 100 days after vaccination, which would be the period of highest protection against reinfection. Conclusion(s): SARS-CoV-2 reinfections are more prevalent among women. Importantly, people with an undermined health status, independently of age, are more sensitive to reinfections, but in most of the cases no hospitalization was required. Finally, vaccination seems to have a short protective effect on reinfection.

Severity Clusters and Likelihood of Recovery from Post-Covid-19 Condition

Background: The Post-COVID-19 Condition (PCC) is a novel, long-lasting, poorly understood and highly disabling post-viral syndrome, which poses enormous healthcare, economic and socio-political challenges. Lack of validated biomarkers forces clinical management to be based on clinical definitions, which are imprecise. In the clinic, symptoms tend to present in clusters, which have yet to be properly defined. Also, it is unclear how often PCC resolves, and which factors influence PCC resolution. Method(s): To delineate PCC presentation clusters and explore factors related with PCC resolution, we performed a 2-year prospective cohort study in individuals who recovered from acute COVID-19 regardless of its acute and post-acute severity. All subjects were systematically followed in the outpatient post-COVID-19 clinic of a tertiary care hospital in Spain. PCC was defined as per the WHO 2021 definition. Persistent symptoms were those present >3 months after acute COVID-19, and lasting for >2 consecutive months. PCC recovery was the absence of PCC symptoms during >3 consecutive months. Symptom clusters were identified using Gower's distance matrices, dendograms, PCA and Silhouette techniques. Factors associated with PCC recovery were identified using a directed acyclic graph approach. Result(s): 548 subjects were included;341 (62%) had PCC. The latter were mostly females (69.8%) with mean age of 47.9 (SD 12.2) years. Only 38.1% required hospitalization and 9% required high-flow oxygen during acute COVID-19. Their most frequent comorbidities were allergy (31.4%), obesity (24.8%), dyslipidemia (24.0%) and hypertension (19.6%). At least 3 symptom clusters with additive symptoms were identified: considering only symptoms present in >35% of subjects, Cluster A was enriched in fatigue and dyspnea;Cluster B had Cluster A symptoms plus headache, arthralgia and neurocognitive complains;Cluster C had Cluster B symptoms plus chest pain and tachycardia. PCC recovery was achieved by 26 (7.6%) individuals over 2 years. Male sex (RR 3.01;CI 1.4-6.3), ICU admission (RR 7.85;CI 2.6-23.2), metabolic comorbidity (RR 2.07;CI 1.1-4.1), and mild acute COVID-19 (RR 2.70;CI 1.1-4.6) increased the likelihood of PCC recovery. Conversely, subjects with muscle pain, impaired attention, dyspnea, and tachycardia were less likely to recover from PCC (RR 0.26;CI 0.13-0.52). Conclusion(s): At least 3 severity clusters can be identified in the PCC. Over the first 2 years, only a minority of subjects fully recover from PCC.