Multiscale modeling in disease

Versypt, Ashlee N. Ford

doi:10.1016/j.coisb.2021.05.001

Cited by 18 publications

(8 citation statements)

References 67 publications

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“…However, modeling signaling networks with many interacting species can become complex and tedious. Ordinary differential equations (ODEs) are often used to model these biochemical networks (26)(27)(28)(29), but these models rely on extensive data, parameter values, and knowledge of reaction kinetics. Alternatively, modelers have used logic-based modeling, fuzzy logic modeling, and extreme pathways analysis to study complex mammalian signaling networks (25,30).…”

Section: Introductionmentioning

confidence: 99%

Logic-Based Modeling of Inflammatory Macrophage Crosstalk with Glomerular Endothelial Cells in Diabetic Kidney Disease

Patidar

Versypt

2023

Preprint

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Diabetic kidney disease is a complication in 1 out of 3 patients with diabetes. Aberrant glucose metabolism in diabetes leads to an immune response causing inflammation, which leads to structural and functional damage in the glomerular cells of the kidney. Complex cellular signaling lies at the core of metabolic and functional derangement. Unfortunately, the mechanism underlying the role of inflammation on glomerular endothelial cell dysfunction in diabetic kidney disease is not fully understood. Computational models in systems biology allow the integration of experimental evidence and cellular signaling networks to understand mechanisms involved in disease progression. To address the knowledge gap, we built a logic-based differential equations model to study macrophage-dependent inflammation in glomerular endothelial cells during diabetic kidney disease progression. We studied the crosstalk between macrophages and glomerular endothelial cells in the kidney using a protein signaling network stimulated with glucose and lipopolysaccharide. The network and model was built using an open-source software package Netflux. This modeling approach overcomes the complexity of studying network model and the need for extensive mechanistic details. The model simulations were trained and validated against available biochemical data from in vitro experiments. We used the model to identify the mechanisms responsible for dysregulated signaling in both macrophages and glomerular endothelial cells during diabetic kidney disease. Our model findings contribute to the understanding of signaling and molecular perturbations on glomerular endothelial cell morphology in early stage of diabetic kidney disease.

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Section: Introductionmentioning

confidence: 99%

Logic-Based Modeling of Inflammatory Macrophage Crosstalk with Glomerular Endothelial Cells in Diabetic Kidney Disease

Patidar

Versypt

2023

Preprint

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“…Multi-scale models of infectious disease dynamics seek to address this challenge by linking mechanistic models representing pathogen-host interactions at cellular to population scales. Developing the mathematical tools for connecting dynamic processes operating at vastly different temporal and spatial scales has been an active focus in infectious disease modeling (Agyingi et al, 2020; Browne and Cheng, 2020; Garabed et al, 2020; Garira, 2020; Jia et al, 2020; Kadelka and M Ciupe, 2019; Rivera et al, 2020; Versypt, 2021; Xue and Xiao, 2020). However, these theoretical innovations have yet to be matched by empirical data generation, providing integrated data sets that consistently document infection processes in the same host-pathogen system across organizational scales.…”

Section: Introductionmentioning

confidence: 99%

Within-host viral growth and immune response rates predict FMDV transmission dynamics for African Buffalo

Macdonald

Gulbudak²,

Beechler

et al. 2022

Preprint

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Infectious disease dynamics operate across biological scales: pathogens replicate within hosts, but transmit among hosts and populations. Functional changes in the pathogen-host interaction thus generate cascading effects from molecular to landscape scales. We investigated within-host dynamics and among-host transmission of three strains of foot-and-mouth disease viruses (FMDVs) in their wildlife host, African buffalo. We combined data on viral dynamics and host immune responses with mathematical models to ask (i) How do viral and immune dynamics vary among FMDV strains? (SAT1, 2, 3); (ii) Which viral and immune parameters determine viral fitness within hosts?; and (iii) How do within-host dynamics relate to virus transmission among hosts? Our data reveal contrasting within-host dynamics among viral strains. However, SAT2 elicited more rapid and effective immune responses than SAT1 and SAT3. Within-host viral fitness was overwhelmingly determined by variation among hosts in immune response activation rates against FMDVs, but not by variation among individual hosts in viral growth rate. By contrast, our analyses investigating across-scale linkages indicate that viral replication rate in the host correlates with transmission rates among buffalo; and that adaptive immune activation rate determines the infectious period. Together, these parameters define the basic reproductive number of the virus, suggesting that viral invasion potential may be predictable from within-host dynamics. Future work should test the generality of these findings by including additional FMDV strains, and create a multi-scale model to link within-host and between-host dynamics explicitly.

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“…As energy-efficiency becomes a bottleneck for large scale computational science, efficient algorithmic development will be necessary for scalable computational medicine. It has been proposed that a modular approach to multi-scale computational medicine, with interoperable and reusable computational tools, mimicking the first principles computational chemistry and physics modeling approaches maybe appropriate as it has been very successful in materials science (Ford Versypt, 2021). Although biological systems differ from physical systems, there is potential in investing in such effort to derive important building blocks that bridge a few spatiotemporal scales.…”

Section: Multiscale Multi-modal Disease Modelingmentioning

confidence: 99%

Computational medicine: Grand challenges and opportunities for revolutionizing personalized healthcare

Tourassi

2023

Front. Med. Eng.

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Multiscale modeling in disease

Cited by 18 publications

References 67 publications

Logic-Based Modeling of Inflammatory Macrophage Crosstalk with Glomerular Endothelial Cells in Diabetic Kidney Disease

Logic-Based Modeling of Inflammatory Macrophage Crosstalk with Glomerular Endothelial Cells in Diabetic Kidney Disease

Within-host viral growth and immune response rates predict FMDV transmission dynamics for African Buffalo

Computational medicine: Grand challenges and opportunities for revolutionizing personalized healthcare

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