Tag: long covid predictors

Immunoglobulin signature predicts risk of post-acute COVID-19 syndrome

Abstract:

Following acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) a significant proportion of individuals develop prolonged symptoms, a serious condition termed post-acute coronavirus disease 2019 (COVID-19) syndrome (PACS) or long COVID. Predictors of PACS are needed. In a prospective multicentric cohort study of 215 individuals, we study COVID-19 patients during primary infection and up to one year later, compared to healthy subjects. We discover an immunoglobulin (Ig) signature, based on total IgM and IgG3 levels, which – combined with age, history of asthma bronchiale, and five symptoms during primary infection – is able to predict the risk of PACS independently of timepoint of blood sampling. We validate the score in an independent cohort of 395 individuals with COVID-19. Our results highlight the benefit of measuring Igs for the early identification of patients at high risk for PACS, which facilitates the study of targeted treatment and pathomechanisms of PACS.

Source: Cervia C, Zurbuchen Y, Taeschler P, Ballouz T, Menges D, Hasler S, Adamo S, Raeber ME, Bächli E, Rudiger A, Stüssi-Helbling M, Huber LC, Nilsson J, Held U, Puhan MA, Boyman O. Immunoglobulin signature predicts risk of post-acute COVID-19 syndrome. Nat Commun. 2022 Jan 25;13(1):446. doi: 10.1038/s41467-021-27797-1. PMID: 35078982. https://www.nature.com/articles/s41467-021-27797-1 (Full text)

Multiple Early Factors Anticipate Post-Acute COVID-19 Sequelae

Summary:

Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms.
We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.

Source: : Su, Y., Yuan, D., Chen, D.G., Ng, R.H., Wang, K., Choi, J., Li, S., Hong, S., Zhang, R., Xie, J., Kornilov, S.A., Scherler, K., Pavlovitch-Bedzyk, A.J., Dong, S., Lausted, C., Lee, I., Fallen, S., Dai, C.L., Baloni, P., Smith, B., Duvvuri, V.R., Anderson, K.G., Li, J., Yang, F., Duncombe, C.J., McCulloch, D.J., Rostomily, C., Troisch, P., Zhou, J., Mackay, S., DeGottardi, Q., May, D.H, Taniguchi, R., Gittelman, R.M, Klinger, M., Snyder, T.M, Roper, R., Wojciechowska, G., Murray, K., Edmark, R., Evans, S., Jones, L., Zhou, Y., Rowen, L., Liu, R., Chour, W., Algren, H.A, Berrington, W.R., Wallick, J.A., Cochran, R.A., Micikas, M.E., the ISB-Swedish COVID19 Biobanking Unit, Terri Wrin, Petropoulos, C.J., Cole, H.R., Fischer, T.D., Wei, W., Hoon, D.S.B., Price, N.D., Subramanian, N., Hill, J.A, Hadlock, J., Magis, A.T., Ribas, A., Lanier, L.L., Boyd, S.D., Bluestone, J.A., Chu, H., Hood, L., Gottardo, R., Greenberg, P.D., Davis, M.M., Goldman, J.D., Heath, J.R., Multiple Early Factors Anticipate Post-Acute COVID-19 Sequelae, Cell (2022), doi: https://doi.org/10.1016/j.cell.2022.01.014. (Full text)

Prevalence, characteristics, and predictors of Long COVID among diagnosed cases of COVID-19

Abstract:

Background: Long COVID or long-term complication after COVID-19 has the ability to affect health and quality of life. Knowledge about the burden and predictors could aid in their prevention and management. Most of the studies are from high-income countries and focus on severe cases. We did this study to estimate the prevalence and identify the characteristics and predictors of Long COVID among our patients.

Methodology: We recruited adult (≥18 years) patients who were diagnosed as Reverse Transcription Polymerase Chain Reaction (RTPCR) confirmed SARS-COV-2 infection and were either hospitalized or tested on outpatient basis. Eligible participants were followed up telephonically after four weeks of diagnosis of SARS-COV-2 infection to collect data on sociodemographic, clinical history, vaccination history, Cycle threshold (Ct) values during diagnosis and other variables. Characteristics of Long COVID were elicited, and multivariable logistic regression was done to find the predictors of Long COVID.

Results: We have analyzed 487 individual data with a median follow-up of 44 days (Inter quartile range (IQR): 39,47). Overall, Long COVID was reported by 29.2% (95% Confidence interval (CI): 25.3%,33.4%) participants. Prevalence of Long COVID among patients with mild/moderate disease (n = 415) was 23.4% (95% CI: 19.5%,27.7%) as compared to 62.5% (95% CI: 50.7%,73%) in severe/critical cases(n=72). The most common Long COVID symptom was fatigue (64.8%) followed by cough (32.4%). Statistically significant predictors of Long COVID were – Pre-existing medical conditions (Adjusted Odds ratio (aOR)=2.00, 95% CI: 1.16,3.44), having a more significant number of symptoms during acute phase of COVID-19 disease (aOR=11.24, 95% CI: 4.00,31.51), two doses of COVID-19 vaccination (aOR=2.32, 95% CI: 1.17,4.58), the severity of illness (aOR=5.71, 95% CI: 3.00,10.89) and being admitted to hospital (Odds ratio (OR)=3.89, 95% CI: 2.49,6.08).

Conclusion: A considerable proportion of COVID-19 cases reported Long COVID symptoms. More research is needed in Long COVID to objectively assess the symptoms and find the biological and radiological markers.

Source: M. C. Arjun, Arvind Kumar Singh, Debkumar Pal, Kajal Das, Alekhya Gajjala, Mahalingam Venkateshan, Baijayantimala Mishra, Binod Kumar Patro, Prasanta Raghab Mohapatra, Sonu Hangma Subba. Prevalence, characteristics, and predictors of Long COVID among diagnosed cases of COVID-19. medRxiv 2022.01.04.21268536; doi: https://doi.org/10.1101/2022.01.04.21268536 https://www.medrxiv.org/content/10.1101/2022.01.04.21268536v1.full-text (Full text)