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Lv J, Ma W. Delay induced stability switch in a mathematical model of CD8 T-cell response to SARS-CoV-2 mediated by receptor ACE2. CHAOS (WOODBURY, N.Y.) 2024; 34:043135. [PMID: 38608314 DOI: 10.1063/5.0187872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 03/18/2024] [Indexed: 04/14/2024]
Abstract
The pathogen SARS-CoV-2 binds to the receptor angiotensin-converting enzyme 2 (ACE2) of the target cells and then replicates itself through the host, eventually releasing free virus particles. After infection, the CD8 T-cell response is triggered and appears to play a critical role in the defense against virus infections. Infected cells and their activated CD8 T-cells can cause tissue damage. Here, we established a mathematical model of within-host SARS-CoV-2 infection that incorporates the receptor ACE2, the CD8 T-cell response, and the damaged tissues. According to this model, we can get the basic reproduction number R0 and the immune reproduction number R1. We provide the theoretical proof for the stability of the disease-free equilibrium, immune-inactivated equilibrium, and immune-activated equilibrium. Finally, our numerical simulations show that the time delay in CD8 T-cell production can induce complex dynamics such as stability switching. These results provide insights into the mechanisms of SARS-CoV-2 infection and may help in the development of effective drugs against COVID-19.
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Affiliation(s)
- Jinlong Lv
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, People's Republic of China
| | - Wanbiao Ma
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, People's Republic of China
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2
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Zitzmann C, Ke R, Ribeiro RM, Perelson AS. How robust are estimates of key parameters in standard viral dynamic models? PLoS Comput Biol 2024; 20:e1011437. [PMID: 38626190 PMCID: PMC11051641 DOI: 10.1371/journal.pcbi.1011437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 04/26/2024] [Accepted: 04/01/2024] [Indexed: 04/18/2024] Open
Abstract
Mathematical models of viral infection have been developed, fitted to data, and provide insight into disease pathogenesis for multiple agents that cause chronic infection, including HIV, hepatitis C, and B virus. However, for agents that cause acute infections or during the acute stage of agents that cause chronic infections, viral load data are often collected after symptoms develop, usually around or after the peak viral load. Consequently, we frequently lack data in the initial phase of viral growth, i.e., when pre-symptomatic transmission events occur. Missing data may make estimating the time of infection, the infectious period, and parameters in viral dynamic models, such as the cell infection rate, difficult. However, having extra information, such as the average time to peak viral load, may improve the robustness of the estimation. Here, we evaluated the robustness of estimates of key model parameters when viral load data prior to the viral load peak is missing, when we know the values of some parameters and/or the time from infection to peak viral load. Although estimates of the time of infection are sensitive to the quality and amount of available data, particularly pre-peak, other parameters important in understanding disease pathogenesis, such as the loss rate of infected cells, are less sensitive. Viral infectivity and the viral production rate are key parameters affecting the robustness of data fits. Fixing their values to literature values can help estimate the remaining model parameters when pre-peak data is missing or limited. We find a lack of data in the pre-peak growth phase underestimates the time to peak viral load by several days, leading to a shorter predicted growth phase. On the other hand, knowing the time of infection (e.g., from epidemiological data) and fixing it results in good estimates of dynamical parameters even in the absence of early data. While we provide ways to approximate model parameters in the absence of early viral load data, our results also suggest that these data, when available, are needed to estimate model parameters more precisely.
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Affiliation(s)
- Carolin Zitzmann
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico
| | - Ruian Ke
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico
| | - Ruy M. Ribeiro
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico
| | - Alan S. Perelson
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico
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3
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Padmanabhan P, Dixit NM. Modelling how increased Cathepsin B/L and decreased TMPRSS2 usage for cell entry by the SARS-CoV-2 Omicron variant may affect the efficacy and synergy of TMPRSS2 and Cathepsin B/L inhibitors. J Theor Biol 2023; 572:111568. [PMID: 37393986 DOI: 10.1016/j.jtbi.2023.111568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 06/22/2023] [Accepted: 06/27/2023] [Indexed: 07/04/2023]
Abstract
The SARS-CoV-2 Omicron variant harbours many mutations in its spike protein compared to the original SARS-CoV-2 strain, which may alter its ability to enter cells, cell tropism, and response to interventions blocking virus entry. To elucidate these effects, we developed a mathematical model of SARS-CoV-2 entry into target cells and applied it to analyse recent in vitro data. SARS-CoV-2 can enter cells via two pathways, one using the host proteases Cathepsin B/L and the other using the host protease TMPRSS2. We found enhanced entry efficiency of the Omicron variant in cells where the original strain preferentially used Cathepsin B/L and reduced efficiency where it used TMPRSS2. The Omicron variant thus appears to have evolved to use the Cathepsin B/L pathway better but at the expense of its ability to use the TMPRSS2 pathway compared to the original strain. We estimated >4-fold enhanced efficiency of the Omicron variant in entry via the Cathepsin B/L pathway and >3-fold reduced efficiency via the TMPRSS2 pathway compared to the original or other strains in a cell type-dependent manner. Our model predicted that Cathepsin B/L inhibitors would be more efficacious and TMPRSS2 inhibitors less efficacious in blocking Omicron variant entry into cells than the original strain. Furthermore, model predictions suggested that drugs simultaneously targeting the two pathways would exhibit synergy. The maximum synergy and drug concentrations yielding it would differ for the Omicron variant compared to the original strain. Our findings provide insights into the cell entry mechanisms of the Omicron variant and have implications for intervention targeting these mechanisms.
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Affiliation(s)
- Pranesh Padmanabhan
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane 4072, Australia.
| | - Narendra M Dixit
- Department of Chemical Engineering, Indian Institute of Science, Bangalore 560012, India; Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
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4
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Lv J, Ma W. Global asymptotic stability of a delay differential equation model for SARS-CoV-2 virus infection mediated by ACE2 receptor protein. APPLIED MATHEMATICS LETTERS 2023; 142:108631. [PMID: 36936728 PMCID: PMC10000301 DOI: 10.1016/j.aml.2023.108631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 06/18/2023]
Abstract
The COVID-19 pandemic has brought a serious threat to human life safety worldwide. SARS-CoV-2 virus mainly binds to the target cell surface receptor ACE2 (Angiotensin-converting enzyme 2 ) through the S protein expressed on the surface of the virus, resulting in infection of target cells. During this infection process, the target cell ACE2 receptor plays a very important mediating role. In this paper, a delay differential equation model containing the mediated effect of target cell receptor is established according to the mechanism of SARS-CoV-2 virus invasion of target cells, and the global stability of the infection-free equilibrium and the infected equilibrium of the model is obtained by using the basic reproduction number ℛ 0 and constructing the appropriate Lyapunov functional. The expression of the basic reproduction number ℛ 0 intuitively gives the dependence on the expression ratio of the target cell surface ACE2 receptor, which is helpful for the understanding of the mechanism of SARS-CoV-2 virus infection.
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Affiliation(s)
- Jinlong Lv
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, 100083, PR China
| | - Wanbiao Ma
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, 100083, PR China
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5
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Desikan R, Padmanabhan P, Kierzek AM, van der Graaf PH. Mechanistic Models of COVID-19: Insights into Disease Progression, Vaccines, and Therapeutics. Int J Antimicrob Agents 2022; 60:106606. [PMID: 35588969 PMCID: PMC9110059 DOI: 10.1016/j.ijantimicag.2022.106606] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 04/27/2022] [Accepted: 05/08/2022] [Indexed: 12/02/2022]
Abstract
The COVID-19 pandemic has severely impacted health systems and economies worldwide. Significant global efforts are therefore ongoing to improve vaccine efficacies, optimize vaccine deployment, and develop new antiviral therapies to combat the pandemic. Mechanistic viral dynamics and quantitative systems pharmacology models of SARS-CoV-2 infection, vaccines, immunomodulatory agents, and antiviral therapeutics have played a key role in advancing our understanding of SARS-CoV-2 pathogenesis and transmission, the interplay between innate and adaptive immunity to influence the outcomes of infection, effectiveness of treatments, mechanisms and performance of COVID-19 vaccines, and the impact of emerging SARS-CoV-2 variants. Here, we review some of the critical insights provided by these models and discuss the challenges ahead.
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Affiliation(s)
- Rajat Desikan
- Quantitative Systems Pharmacology (QSP) group, Certara, Sheffield and Canterbury, United Kingdom.
| | - Pranesh Padmanabhan
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Andrzej M Kierzek
- Quantitative Systems Pharmacology (QSP) group, Certara, Sheffield and Canterbury, United Kingdom; School of Biosciences and Medicine, University of Surrey, Guildford, United Kingdom
| | - Piet H van der Graaf
- Quantitative Systems Pharmacology (QSP) group, Certara, Sheffield and Canterbury, United Kingdom; Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
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Padmanabhan P, Desikan R, Dixit NM. Modeling how antibody responses may determine the efficacy of COVID-19 vaccines. NATURE COMPUTATIONAL SCIENCE 2022; 2:123-131. [PMID: 38177523 DOI: 10.1038/s43588-022-00198-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 01/20/2022] [Indexed: 01/06/2024]
Abstract
Predicting the efficacy of COVID-19 vaccines would aid vaccine development and usage strategies, which is of importance given their limited supplies. Here we develop a multiscale mathematical model that proposes mechanistic links between COVID-19 vaccine efficacies and the neutralizing antibody (NAb) responses they elicit. We hypothesized that the collection of all NAbs would constitute a shape space and that responses of individuals are random samples from this space. We constructed the shape space by analyzing reported in vitro dose-response curves of ~80 NAbs. Sampling NAb subsets from the space, we recapitulated the responses of convalescent patients. We assumed that vaccination would elicit similar NAb responses. We developed a model of within-host SARS-CoV-2 dynamics, applied it to virtual patient populations and, invoking the NAb responses above, predicted vaccine efficacies. Our predictions quantitatively captured the efficacies from clinical trials. Our study thus suggests plausible mechanistic underpinnings of COVID-19 vaccines and generates testable hypotheses for establishing them.
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Affiliation(s)
- Pranesh Padmanabhan
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.
| | - Rajat Desikan
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India
- Certara QSP, Certara UK Limited, Sheffield, UK
| | - Narendra M Dixit
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India.
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Chhajer H, Rizvi VA, Roy R. Life cycle process dependencies of positive-sense RNA viruses suggest strategies for inhibiting productive cellular infection. J R Soc Interface 2021; 18:20210401. [PMID: 34753308 PMCID: PMC8580453 DOI: 10.1098/rsif.2021.0401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 10/18/2021] [Indexed: 12/25/2022] Open
Abstract
Life cycle processes of positive-strand (+)RNA viruses are broadly conserved across families, yet they employ different strategies to grow in the cell. Using a generalized dynamical model for intracellular (+)RNA virus growth, we decipher these life cycle determinants and their dependencies for several viruses and parse the effects of viral mutations, drugs and host cell permissivity. We show that poliovirus employs rapid replication and virus assembly, whereas the Japanese encephalitis virus leverages its higher rate of translation and efficient cellular reorganization compared to the hepatitis C virus. Stochastic simulations demonstrate infection extinction if all seeding (inoculating) viral RNA degrade before establishing robust replication critical for infection. The probability of this productive cellular infection, 'cellular infectivity', is affected by virus-host processes and defined by early life cycle events and viral seeding. An increase in cytoplasmic RNA degradation and delay in vesicular compartment formation reduces infectivity, more so when combined. Synergy among these parameters in limiting (+)RNA virus infection as predicted by our model suggests new avenues for inhibiting infections by targeting the early life cycle bottlenecks.
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Affiliation(s)
- Harsh Chhajer
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore 560012, Karnataka, India
| | - Vaseef A. Rizvi
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, Karnataka, India
| | - Rahul Roy
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore 560012, Karnataka, India
- Department of Chemical Engineering, Indian Institute of Science, Bangalore 560012, Karnataka, India
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Zhang H, Zheng X, Li J, Liu Q, Huang XX, Ding H, Suzuki R, Muramatsu M, Song SJ. Flavonoid-triazolyl hybrids as potential anti-hepatitis C virus agents: Synthesis and biological evaluation. Eur J Med Chem 2021; 218:113395. [PMID: 33838584 DOI: 10.1016/j.ejmech.2021.113395] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 02/06/2021] [Accepted: 03/17/2021] [Indexed: 12/15/2022]
Abstract
A series of flavonoid-triazolyl hybrids were synthesized and evaluated as novel inhibitors of hepatitis C virus (HCV). The results of anti-HCV activity assays showed that most of the synthesized derivatives at a concentration of 100 μg/mL inhibited the generation of progeny virus. Among these derivatives, 10m and 10r exhibited the most potent anti-HCV activity and inhibited the production of HCV in a dose-dependent manner. Interestingly, 10m and 10r had no significant inhibitory effect on viral translation or replication. Additional action mechanism studies revealed that the most potent compounds, 10m and 10r, significantly inhibited viral entry to 34.0% and 52.0%, respectively, at 10 μM. These results suggest further effective application of 10m and 10r as potential HCV preventive agents.
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Affiliation(s)
- Han Zhang
- Key Laboratory of Computational Chemistry Based Natural Antitumor Drug Research & Development, Liaoning Province, School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, 110016, People's Republic of China
| | - Xin Zheng
- Department of Cardiology, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China; Department of Virology II, National Institute of Infectious Diseases, 162-8640, Tokyo, Japan
| | - Jichong Li
- Key Laboratory of Computational Chemistry Based Natural Antitumor Drug Research & Development, Liaoning Province, School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, 110016, People's Republic of China
| | - Qingbo Liu
- Key Laboratory of Computational Chemistry Based Natural Antitumor Drug Research & Development, Liaoning Province, School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, 110016, People's Republic of China.
| | - Xiao-Xiao Huang
- Key Laboratory of Computational Chemistry Based Natural Antitumor Drug Research & Development, Liaoning Province, School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, 110016, People's Republic of China
| | - Huaiwei Ding
- Key Laboratory of Structure-Based Drug Design and Discovery, Ministry of Education, Shenyang Pharmaceutical University, Shenyang, 110016, China.
| | - Ryosuke Suzuki
- Department of Virology II, National Institute of Infectious Diseases, 162-8640, Tokyo, Japan
| | - Masamichi Muramatsu
- Department of Virology II, National Institute of Infectious Diseases, 162-8640, Tokyo, Japan.
| | - Shao-Jiang Song
- Key Laboratory of Computational Chemistry Based Natural Antitumor Drug Research & Development, Liaoning Province, School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, 110016, People's Republic of China.
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Padmanabhan P, Desikan R, Dixit NM. Targeting TMPRSS2 and Cathepsin B/L together may be synergistic against SARS-CoV-2 infection. PLoS Comput Biol 2020; 16:e1008461. [PMID: 33290397 PMCID: PMC7748278 DOI: 10.1371/journal.pcbi.1008461] [Citation(s) in RCA: 82] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 12/18/2020] [Accepted: 10/22/2020] [Indexed: 12/15/2022] Open
Abstract
The entry of SARS-CoV-2 into target cells requires the activation of its surface spike protein, S, by host proteases. The host serine protease TMPRSS2 and cysteine proteases Cathepsin B/L can activate S, making two independent entry pathways accessible to SARS-CoV-2. Blocking the proteases prevents SARS-CoV-2 entry in vitro. This blockade may be achieved in vivo through 'repurposing' drugs, a potential treatment option for COVID-19 that is now in clinical trials. Here, we found, surprisingly, that drugs targeting the two pathways, although independent, could display strong synergy in blocking virus entry. We predicted this synergy first using a mathematical model of SARS-CoV-2 entry and dynamics in vitro. The model considered the two pathways explicitly, let the entry efficiency through a pathway depend on the corresponding protease expression level, which varied across cells, and let inhibitors compromise the efficiency in a dose-dependent manner. The synergy predicted was novel and arose from effects of the drugs at both the single cell and the cell population levels. Validating our predictions, available in vitro data on SARS-CoV-2 and SARS-CoV entry displayed this synergy. Further, analysing the data using our model, we estimated the relative usage of the two pathways and found it to vary widely across cell lines, suggesting that targeting both pathways in vivo may be important and synergistic given the broad tissue tropism of SARS-CoV-2. Our findings provide insights into SARS-CoV-2 entry into target cells and may help improve the deployability of drug combinations targeting host proteases required for the entry.
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Affiliation(s)
- Pranesh Padmanabhan
- Clem Jones Centre for Ageing Dementia Research, Queesnsland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Rajat Desikan
- Department of Chemical Engineering, Indian Institute of Science, Bengaluru, India
| | - Narendra M. Dixit
- Department of Chemical Engineering, Indian Institute of Science, Bengaluru, India
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bengaluru, India
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Sen P, Saha A, Dixit NM. You Cannot Have Your Synergy and Efficacy Too. Trends Pharmacol Sci 2019; 40:811-817. [PMID: 31610891 DOI: 10.1016/j.tips.2019.08.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Revised: 08/20/2019] [Accepted: 08/20/2019] [Indexed: 12/28/2022]
Abstract
Synergistic drugs are preferred in combination therapies for many diseases, including viral infections and cancers. Maximizing synergy, however, may come at the cost of efficacy. This synergy-efficacy trade-off appears to be widely prevalent and independent of the specific drug interactions yielding synergy. We present examples of the trade-off in drug combinations used in hepatitis C, HIV, and cancer therapies and believe that screens for optimal drug combinations that presently seek to maximize synergy may be improved by considering the trade-off.
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Affiliation(s)
- Pramita Sen
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India
| | - Ananya Saha
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India
| | - Narendra M Dixit
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India; Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India.
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11
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Raja R, Baral S, Dixit NM. Interferon at the cellular, individual, and population level in hepatitis C virus infection: Its role in the interferon-free treatment era. Immunol Rev 2019; 285:55-71. [PMID: 30129199 DOI: 10.1111/imr.12689] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The advent of powerful direct-acting antiviral agents (DAAs) has revolutionized the treatment of hepatitis C. DAAs cure nearly all patients with short duration, oral treatments. Significant efforts are now underway to optimize DAA-based treatments. We discuss the potential role of interferon in this optimization. Clinical studies present compelling evidence that DAAs perform better in treatment-naive individuals than in individuals who previously failed treatment with interferon, a surprising correlation because interferon and DAAs are thought to act independently. Recent mathematical models explore a mechanistic hypothesis underlying this correlation. The hypothesis invokes the action of interferon at the cellular, individual, and population levels. Strong interferon responses prevent the productive infection of cells, reduce viral replication, and impede the development of resistance to DAAs in infected individuals and improve cure rates elicited by DAAs in treated populations. The models develop descriptions of these processes, integrate them into a comprehensive framework, and capture clinical data quantitatively, providing a successful test of the hypothesis. Individuals with strong endogenous interferon responses thus present a promising subpopulation for reducing DAA treatment durations. This review discusses the conceptual advances made by the models, highlights the new insights they unravel, and examines their applicability to optimize DAA-based treatments.
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Affiliation(s)
- Rubesh Raja
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India
| | - Subhasish Baral
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India
| | - Narendra M Dixit
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.,Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India
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12
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Venugopal V, Padmanabhan P, Raja R, Dixit NM. Modelling how responsiveness to interferon improves interferon-free treatment of hepatitis C virus infection. PLoS Comput Biol 2018; 14:e1006335. [PMID: 30001324 PMCID: PMC6057683 DOI: 10.1371/journal.pcbi.1006335] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2017] [Revised: 07/24/2018] [Accepted: 06/28/2018] [Indexed: 12/14/2022] Open
Abstract
Direct-acting antiviral agents (DAAs) for hepatitis C treatment tend to fare better in individuals who are also likely to respond well to interferon-alpha (IFN), a surprising correlation given that DAAs target specific viral proteins whereas IFN triggers a generic antiviral immune response. Here, we posit a causal relationship between IFN-responsiveness and DAA treatment outcome. IFN-responsiveness restricts viral replication, which would prevent the growth of viral variants resistant to DAAs and improve treatment outcome. To test this hypothesis, we developed a multiscale mathematical model integrating IFN-responsiveness at the cellular level, viral kinetics and evolution leading to drug resistance at the individual level, and treatment outcome at the population level. Model predictions quantitatively captured data from over 50 clinical trials demonstrating poorer response to DAAs in previous non-responders to IFN than treatment-naïve individuals, presenting strong evidence supporting the hypothesis. Model predictions additionally described several unexplained clinical observations, viz., the percentages of infected individuals who 1) spontaneously clear HCV, 2) get chronically infected but respond to IFN-based therapy, and 3) fail IFN-based therapy but respond to DAA-based therapy, resulting in a comprehensive understanding of HCV infection and treatment. An implication of the causal relationship is that failure of DAA-based treatments may be averted by adding IFN, a strategy of potential use in settings with limited access to DAAs. A second, wider implication is that individuals with greater IFN-responsiveness would require shorter DAA-based treatment durations, presenting a basis and a promising population for response-guided therapy.
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Affiliation(s)
- Vishnu Venugopal
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India
| | - Pranesh Padmanabhan
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India
| | - Rubesh Raja
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India
| | - Narendra M. Dixit
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India
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13
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Hepatitis C virus cell entry: a target for novel antiviral strategies to address limitations of direct acting antivirals. Hepatol Int 2016; 10:741-8. [DOI: 10.1007/s12072-016-9724-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 03/16/2016] [Indexed: 12/12/2022]
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