scholarly journals A Multicompartment Mathematical Model Based on Host Immunity for Dissecting COVID-19 Heterogeneity

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3132-3132
Author(s):  
Jianghua Wu ◽  
Heng Mei ◽  
Jianwei Li ◽  
Jingpeng Zhang ◽  
Lu Tang ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Innate Immunity ◽  
Viral Load ◽  
Bacterial Infection ◽  
B Cell ◽  
Immune Cells ◽  
Scientific Community ◽  
Host Immunity ◽  
Viral Shedding ◽  
Cell Pool

Abstract Background: As of early August 2021, more than 190 million people have developed coronavirus disease (COVID-19), a pandemic that has killed approximately 4 million people. Caused by acute respiratory syndrome coronavirus 2 (SARS-CoV-2), COVID-19 exhibited a highly variable clinical course, ranging from a high proportion of asymptomatic and mild infections to severe and fatal disease. However, the immunological determinants underlying the heterogeneity of COVID-19 remain to be fully elucidated. Methods: To systemically analyze the immunopathogenesis of COVID-19, a multicompartment mathematical model based on both immunological principles and COVID-19-related work performed by the scientific community was built to illustrate the dynamics of host immunity after SARS-CoV-2 infection. We used ordinary differential equations (ODEs) to simulate the time-dependent functions of immunologic variations in the four compartments, which were draining lymph nodes, peripheral blood, lung and distant lymph nodes and spleen. Our model consisted of equations for 109 immunologic variations, which contained 223 parameters. K was used to characterize the adequacy of the SARS-CoV-2-specific naïve T/B cell pool; K I represented the hill coefficient of antigen-presenting cell (APC) differentiation. Further, we used method of pseudo landscape to visualize the effect of APC capacity and the SARS-CoV-2-specific naïve T/B cell pool on clinical outcomes. Results: Based on both immunologic knowledge and extensive COVID-19-related work performed by the scientific community, we constructed a knowledge-driven mathematical model that incorporated SARS-CoV-2 infection, bacterial infection, leukocyte chemotaxis, innate immunity and adaptive immunity. The model simulated and predicted the different trajectories of the viral load, bacterial load, immune cells, cytokines and infected epithelial cells in patients with different severities. A higher viral load and longer virus-shedding period were observed in patients with higher severity, along with an increase in SARS-CoV-2-infected lung epithelial cells. The trajectories of both peripheral blood IL-6 and lymphocytes predicted COVID-19 outcomes. Based on the distribution, trafficking and differentiation of immune cells after SARS-CoV-2 infection, we proposed that early-stage lymphopenia is related to lymphocyte chemotaxis. The delayed initiation of both innate and adaptive immunity resulted in elevated SARS-CoV-2 shedding and was a pivotal cause of COVID-19 severity. Spatiotemporally, viral shedding and postviral bacterial infection evoked stronger innate immunity. Viral shedding could be restrained by the rapid initiation of APC, antibody-secreting cell (ASC) and cytotoxic T cell (CTL). Moreover, our model predicted that the insufficient SARS-CoV-2-specific naïve T/B cell pools and inactive APC caused a series of chain reactions, including viral shedding, bacterial infection, sepsis and cytokine storms. Finally, pseudopotential analysis revealed that a high state characterized by severe bacterial infections and cytokine storms was a stable attractor for patients with insufficient SARS-CoV-2-specific naïve T/B cells and inactive APC (Figure 1). Conclusion: Overall, our analysis provided a comprehensive view of the dynamics of host immunity after SARS-CoV-2 infection and highlighted that the antigen-specific naïve T/B cell pool and APC ability may essentially determine COVID-19 heterogeneity from an immunological standpoint. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

scholarly journals Relative COVID-19 viral persistence and antibody kinetics

2020 ◽  
Author(s):  
Chung-Guei Huang ◽  
Ching-Tai Huang ◽  
Avijit Dutta ◽  
Pi-Yueh Chang ◽  
Mei-Jen Hsiao ◽  
...  
Keyword(s):  
Viral Load ◽  
Antibody Response ◽  
B Cell ◽  
Vaccine Development ◽  
Cell Pool ◽  
Strong Antibody Response ◽  
Key Factor ◽  
The Absolute ◽  
Antibody Levels ◽  
Relative Persistence

AbstractImportanceThe COVID-19 antibody response is a critical indicator for evaluating immunity and also serves as the knowledge base for vaccine development. The picture is still not clear because of many limitations including testing tools, time of sampling, and the unclear impact of varying clinical status. In addition to these problems, antibody levels may not be equivalent to protective capacity.ObjectiveTo define the key factor for the different patterns of COVID-19 antibody response.DesignWe elucidated the antibody response with time-series throat and serum samples for viral loads and antibody levels, then used a neutralization test to evaluate protectiveness.SettingA medical center that typically cares for patients with moderate to severe diseases. Because of the low prevalence of COVID-19 in Taiwan and local government policy, however, we also admit COVID-19 patients with mild disease or even those without symptoms for inpatient care.ParticipantsRT-PCR-confirmed COVID-19 patients.ResultsWe found that only patients with relative persistence of virus at pharynx displayed strong antibody responses that were proportional to the pharyngeal viral load. They also had proportional neutralization titers per unit of serum. Although antibody levels decreased around 2 weeks after symptom onset, the neutralization efficacy per unit antibody remained steady and even continued to increase over time. The antibody response in patients with rapid virus clearance was weak, but the neutralization efficacy per unit antibody in these patients was comparable to those with persistent presence of virus. The deceased were with higher viral load, higher level of antibody, and higher neutralization titers in the serum, but the neutralization capacity per unit antibody is relatively low.Conclusions and RelevanceStrong antibody response depends on the relative persistence of the virus, instead of the absolute virus amount. The antibody response is still weak if large amount of virus is cleared quickly. The neutralization efficacy per unit antibody is comparable between high and low antibody patterns. Strong antibody response contains more inefficient and maybe even harmful antibodies. Low antibody response is also equipped with a capable B cell pool of efficient antibodies, which may expand with next virus encounter and confer protection.Key pointsQuestionThe key factor for the different “patterns” of COVID-19 antibody response.FindingsStrong antibody response depends on the relative persistence of the virus, instead of the absolute virus amount. The antibody response is still weak if large amount of virus is cleared quickly. The neutralization efficacy per unit antibody is comparable between high and low antibody patterns. High antibody level contains more inefficient antibodies.MeaningStrong response contains inefficient and maybe harmful antibodies. Low antibody response is also equipped with a capable B cell pool of efficient antibodies, which may expand with next virus encounter and confer protection.

scholarly journals Correlation of Pandemic (H1N1) 2009 Viral Load with Disease Severity and Prolonged Viral Shedding in Children

2010 ◽  
Vol 16 (8) ◽  
pp. 1265-1272 ◽  
Author(s):  
Chung-Chen Li ◽  
Lin Wang ◽  
Hock-Liew Eng ◽  
Huey-Ling You ◽  
Ling-Sai Chang ◽  
...  
Keyword(s):  
Viral Load ◽  
Disease Severity ◽  
Pandemic H1n1 ◽  
Viral Shedding ◽  
Pandemic H1n1 2009

scholarly journals Risk Factors for Kaposi’s Sarcoma–Associated Herpesvirus DNA in Blood and in Saliva in Rural Uganda

2019 ◽  
Vol 71 (4) ◽  
pp. 1055-1062 ◽  
Author(s):  
Angela Nalwoga ◽  
Marjorie Nakibuule ◽  
Vickie Marshall ◽  
Wendell Miley ◽  
Nazzarena Labo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Viral Load ◽  
Kaposi's Sarcoma ◽  
Kaposi’S Sarcoma ◽  
Young Males ◽  
Viral Shedding ◽  
Antibody Titres ◽  
Kaposi's Sarcoma Associated Herpesvirus ◽  
Kaposi’S Sarcoma Associated Herpesvirus ◽  
Ugandan Population

Abstract Background Detectable Kaposi’s sarcoma–associated herpesvirus (KSHV) DNA in blood and increased antibody titres may indicate KSHV reactivation, while the transmission of KSHV occurs via viral shedding in saliva. Methods We investigated the risk factors for KSHV DNA detection by real-time polymerase chain reaction in blood and by viral shedding in saliva, in 878 people aged 3 to 89 years of both sexes in a rural Ugandan population cohort. Helminths were detected using microscopy and the presence of malaria parasitaemia was identified using rapid diagnostic tests. Regression modelling was used for a statistical analysis. Results The KSHV viral load in blood did not correlate with the viral load in saliva, suggesting separate immunological controls within each compartment. The proportions of individuals with a detectable virus in blood were 23% among children aged 3–5 years and 22% among those 6–12 years, thereafter reducing with increasing age. The proportions of individuals with a detectable virus in saliva increased from 30% in children aged 3–5 years to 45% in those aged 6–12 years, and decreased subsequently with increasing age. Overall, 29% of males shed in saliva, compared to 19% of females (P = .008). Conclusions Together, these data suggest that young males may be responsible for much of the onward transmission of KSHV. Individuals with a current malaria infection had higher levels of viral DNA in their blood (P = .031), compared to uninfected individuals. This suggests that malaria may lead to KSHV reactivation, thereby increasing the transmission and pathogenicity of the virus.

scholarly journals Higher Viral Load and Prolonged Viral Shedding Period is Associated with Impaired Th17 Cell Response in Patients with H1N1 Influenza A

2012 ◽  
Vol 1 (3) ◽  
pp. 137-145
Author(s):  
Gui-lin Yang ◽  
Ying-xia Liu ◽  
Mu-tong Fang ◽  
Wei-long Liu ◽  
Xin-chun Chen ◽  
...  
Keyword(s):  
T Cells ◽  
Viral Load ◽  
Cell Response ◽  
Th17 Cell ◽  
Influenza A ◽  
H1n1 Influenza ◽  
Cell Frequency ◽  
Viral Loads ◽  
Viral Shedding ◽  
Ifn Γ

Abstract Objective To explore whether age, disease severity, cytokines and lymphocytes in H1N1 influenza A patients correlate with viral load and clearance. Methods Total of 70 mild and 16 severe patients infected with H1N1 influenza A virus were enrolled in this study. Results It was found that the patients under 14 years old and severe patients displayed significantly higher viral loads and prolonged viral shedding periods compared with the patients over 14 years old and mild patients, respectively (P < 0.05). Moreover, the patients under 14 years old and severe patients displayed significantly lower Th17 cell frequency than the patients over 14 years old and mild patients (P < 0.01). The viral shedding period inversely correlated with the frequency of IL-17+IFN-γ-CD4+ T cells. Additionally, the decreased concentration of serum TGF-β correlated with the decreased frequency of IL-17+IFN-γ-CD4+ T cells. Conclusions Both younger and severe patients are associated with higher viral loads and longer viral shedding periods, which may partially be attributed to the impaired Th17 cell response.

scholarly journals Tuning cancer fate: the unremitting role of host immunity

Open Biology ◽  
2017 ◽  
Vol 7 (4) ◽  
pp. 170006 ◽  
Author(s):  
B. Calì ◽  
B. Molon ◽  
A. Viola
Keyword(s):  
Immune Cells ◽  
Immune Cell ◽  
Tumour Progression ◽  
Host Immunity ◽  
Adaptive Immune ◽  
Adaptive Immune Cells ◽  
Immune Mediated ◽  
Immune Cell Subsets ◽  
Therapeutic Protocols

Host immunity plays a central and complex role in dictating tumour progression. Solid tumours are commonly infiltrated by a large number of immune cells that dynamically interact with the surrounding microenvironment. At first, innate and adaptive immune cells successfully cooperate to eradicate microcolonies of transformed cells. Concomitantly, surviving tumour clones start to proliferate and harness immune responses by specifically hijacking anti-tumour effector mechanisms and fostering the accumulation of immunosuppressive immune cell subsets at the tumour site. This pliable interplay between immune and malignant cells is a relentless process that has been concisely organized in three different phases: elimination, equilibrium and escape. In this review, we aim to depict the distinct immune cell subsets and immune-mediated responses characterizing the tumour landscape throughout the three interconnected phases. Importantly, the identification of key immune players and molecules involved in the dynamic crosstalk between tumour and immune system has been crucial for the introduction of reliable prognostic factors and effective therapeutic protocols against cancers.

Regulation of the Size of the Recirculating B Cell Pool of Adult Rats

1958 ◽  
pp. 593-601
Author(s):  
J. Lortan ◽  
D. Gray ◽  
D. S. Kumararatne ◽  
B. Platteau ◽  
H. Bazin ◽  
...  
Keyword(s):  
B Cell ◽  
Adult Rats ◽  
Cell Pool

scholarly journals Early Reconstitution of Antibody Secreting Cells after Allogeneic Stem Cell Transplantation

2022 ◽  
Vol 11 (1) ◽  
pp. 270
Author(s):  
Martina Hinterleitner ◽  
Clemens Hinterleitner ◽  
Elke Malenke ◽  
Birgit Federmann ◽  
Ursula Holzer ◽  
...  
Keyword(s):  
Innate Immunity ◽  
T Cells ◽  
Stem Cell ◽  
T Cell ◽  
B Cells ◽  
Stem Cell Transplantation ◽  
B Cell ◽  
Cell Transplantation ◽  
Antibody Secreting Cells

Immune cell reconstitution after stem cell transplantation is allocated over several stages. Whereas cells mediating innate immunity recover rapidly, adaptive immune cells, including T and B cells, recover slowly over several months. In this study we investigated kinetics and reconstitution of de novo B cell formation in patients receiving CD3 and CD19 depleted haploidentical stem cell transplantation with additional in vivo T cell depletion with monoclonal anti-CD3 antibody. This model enables a detailed in vivo evaluation of hierarchy and attribution of defined lymphocyte populations without skewing by mTOR- or NFAT-inhibitors. As expected CD3+ T cells and their subsets had delayed reconstitution (<100 cells/μL at day +90). Well defined CD19+ B lymphocytes of naïve and memory phenotype were detected at day +60. Remarkably, we observed a very early reconstitution of antibody-secreting cells (ASC) at day +14. These ASC carried the HLA-haplotype of the donor and secreted the isotypes IgM and IgA more prevalent than IgG. They correlated with a population of CD19− CD27− CD38low/+ CD138− cells. Of note, reconstitution of this ASC occurred without detectable circulating T cells and before increase of BAFF or other B cell stimulating factors. In summary, we describe a rapid reconstitution of peripheral blood ASC after CD3 and CD19 depleted haploidentical stem cell transplantation, far preceding detection of naïve and memory type B cells. Incidence before T cell reconstitution and spontaneous secretion of immunoglobulins allocate these early ASC to innate immunity, eventually maintaining natural antibody levels.

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