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Hallmarks of neurodegenerative disease: A systems pharmacology perspective

Review

. 2022 Nov;11(11):1399-1429. doi: 10.1002/psp4.12852. Epub 2022 Aug 17. Hallmarks of neurodegenerative disease: A systems pharmacology perspective Peter Bloomingdale¹, Tatiana Karelina², Vidya Ramakrishnan³, Suruchi Bakshi^{4 5}, Florence Véronneau-Veilleux⁶, Matthew Moye¹, Kazutaka Sekiguchi^{7 8}, Guy Meno-Tetang⁹, Aparna Mohan¹⁰, R Maithreye¹⁰, Veena A Thomas¹¹, Frank Gibbons¹², Antonio Cabal¹³, Jean-Marie Bouteiller^{14 15}, Hugo Geerts⁴

Affiliations

¹ Quantitative Pharmacology and Pharmacometrics, Merck & Co., Inc., Boston, Massachusetts, USA.
² InSysBio, Moscow, Russia.
³ Clinical Pharmacology, Genentech, Inc., South San Francisco, California, USA.
⁴ Certara QSP, Oss, The Netherlands.
⁵ Certara QSP, Princeton, New Jersey, USA.
⁶ Faculté de Pharmacie, University of Montreal, Montreal, Quebec, Canada.
⁷ Shionogi & Co., Ltd., Osaka, Japan.
⁸ SUNY Downstate Medical Center, New York, New York, USA.
⁹ Neuroscience, Biopharmaceuticals R&D, AstraZeneca, Cambridge, UK.
¹⁰ Vantage Research, Chennai, Tamil Nadu, India.
¹¹ Amgen, South San Francisco, California, USA.
¹² Clinical Pharmacology and Pharmacometrics, Biogen, Cambridge, Massachusetts, USA.
¹³ Eisai, Nutley, New Jersey, USA.
¹⁴ Center for Neural Engineering, Department of Biomedical Engineering at the Viterbi School of Engineering, Los Angeles, California, USA.
¹⁵ Institute for Technology and Medical Systems Innovation, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.

PMID: 35894182
PMCID: PMC9662204
DOI: 10.1002/psp4.12852

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Review

Hallmarks of neurodegenerative disease: A systems pharmacology perspective

Peter Bloomingdale et al. CPT Pharmacometrics Syst Pharmacol. 2022 Nov.

. 2022 Nov;11(11):1399-1429. doi: 10.1002/psp4.12852. Epub 2022 Aug 17. Authors Peter Bloomingdale¹, Tatiana Karelina², Vidya Ramakrishnan³, Suruchi Bakshi^{4 5}, Florence Véronneau-Veilleux⁶, Matthew Moye¹, Kazutaka Sekiguchi^{7 8}, Guy Meno-Tetang⁹, Aparna Mohan¹⁰, R Maithreye¹⁰, Veena A Thomas¹¹, Frank Gibbons¹², Antonio Cabal¹³, Jean-Marie Bouteiller^{14 15}, Hugo Geerts⁴ Affiliations

¹ Quantitative Pharmacology and Pharmacometrics, Merck & Co., Inc., Boston, Massachusetts, USA.
² InSysBio, Moscow, Russia.
³ Clinical Pharmacology, Genentech, Inc., South San Francisco, California, USA.
⁴ Certara QSP, Oss, The Netherlands.
⁵ Certara QSP, Princeton, New Jersey, USA.
⁶ Faculté de Pharmacie, University of Montreal, Montreal, Quebec, Canada.
⁷ Shionogi & Co., Ltd., Osaka, Japan.
⁸ SUNY Downstate Medical Center, New York, New York, USA.
⁹ Neuroscience, Biopharmaceuticals R&D, AstraZeneca, Cambridge, UK.
¹⁰ Vantage Research, Chennai, Tamil Nadu, India.
¹¹ Amgen, South San Francisco, California, USA.
¹² Clinical Pharmacology and Pharmacometrics, Biogen, Cambridge, Massachusetts, USA.
¹³ Eisai, Nutley, New Jersey, USA.
¹⁴ Center for Neural Engineering, Department of Biomedical Engineering at the Viterbi School of Engineering, Los Angeles, California, USA.
¹⁵ Institute for Technology and Medical Systems Innovation, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.

PMID: 35894182
PMCID: PMC9662204
DOI: 10.1002/psp4.12852

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Abstract

Age-related central neurodegenerative diseases, such as Alzheimer's and Parkinson's disease, are a rising public health concern and have been plagued by repeated drug development failures. The complex nature and poor mechanistic understanding of the etiology of neurodegenerative diseases has hindered the discovery and development of effective disease-modifying therapeutics. Quantitative systems pharmacology models of neurodegeneration diseases may be useful tools to enhance the understanding of pharmacological intervention strategies and to reduce drug attrition rates. Due to the similarities in pathophysiological mechanisms across neurodegenerative diseases, especially at the cellular and molecular levels, we envision the possibility of structural components that are conserved across models of neurodegenerative diseases. Conserved structural submodels can be viewed as building blocks that are pieced together alongside unique disease components to construct quantitative systems pharmacology (QSP) models of neurodegenerative diseases. Model parameterization would likely be different between the different types of neurodegenerative diseases as well as individual patients. Formulating our mechanistic understanding of neurodegenerative pathophysiology as a mathematical model could aid in the identification and prioritization of drug targets and combinatorial treatment strategies, evaluate the role of patient characteristics on disease progression and therapeutic response, and serve as a central repository of knowledge. Here, we provide a background on neurodegenerative diseases, highlight hallmarks of neurodegeneration, and summarize previous QSP models of neurodegenerative diseases.

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Conflict of interest statement

The authors declared no competing interests for this work.

Figures
FIGURE 1

Hallmarks of neurodegeneration. Neuroimmune alterations,…

FIGURE 1

Hallmarks of neurodegeneration. Neuroimmune alterations, disrupted proteostasis, oxidative and endoplasmic reticulum stress, and…

FIGURE 1

Hallmarks of neurodegeneration. Neuroimmune alterations, disrupted proteostasis, oxidative and endoplasmic reticulum stress, and metabolic dysfunction are key components that could be primary submodels in a platform quantitative systems pharmacology (QSP) model of neurodegenerative diseases.

FIGURE 2

Disrupted proteostasis in neurodegenerative disease.…

FIGURE 2

Disrupted proteostasis in neurodegenerative disease. Cellular and molecular processes involved in disrupted proteostasis…

FIGURE 2

Disrupted proteostasis in neurodegenerative disease. Cellular and molecular processes involved in disrupted proteostasis of pathological proteins in neurodegenerative diseases, focusing on tau protein in this example. Pathological processes cause the aberrant hyperphosphorylation of tau compromising its ability to maintain a healthy normal microtubule function, which results in the disintegration of microtubules and their ability to transport important cargo and organelles. Tau is subsequently released from microtubules, where monomers begin to aggregate into oligomers and form neurofibrillary tangles (NFTs). Intracellular proteins are cleared through autophagy proteasomal degradation. Proteins directly enter lysosomes via microautophagy and chaperone‐mediated autophagy (CMP). Macroautophagy initiates through the formation of a phagophore, which forms vesicle (autophagosome) around tau proteins of all forms to be cleared. Autophagosomes fuse with lysosomes to form autolysosomes, which breaks down proteins through acidification. The ubiquitin‐proteasome system is limited to the clearance monomeric tau and is inhibited by tau oligomers. Tau is ubiquitinated and fed through the proteasome for proteolytic cleavage. Both of these clearance processes experience functional decline with age, which contributes to an increase in pathological protein burden.

FIGURE 3

Oxidative and endoplasmic reticulum (ER)…

FIGURE 3

Oxidative and endoplasmic reticulum (ER) stress pathways in neurodegenerative disease. Oxidative and ER…

FIGURE 3

Oxidative and endoplasmic reticulum (ER) stress pathways in neurodegenerative disease. Oxidative and ER stress leads to neuronal apoptosis through a complex intracellular network. Pathological proteins, such as Aβ, disrupt cellular processes and organelles, such as the plasma membrane, ER, and mitochondria. APP is cleaved to Aβ, which aggregates to form oligomeric Aβ and amyloid plaques. Aβ oligomers activate NMDA receptors, induce the unfolded protein response (UPR), and inhibit components of the mitochondrial electron transport chain, which increases intracellular calcium, decreases ATP production, and increases reactive oxygen species (ROS). The ROS directly induces apoptosis. Mitochondrial dysfunction leads to the mitochondrial permeability transition (MPT) pore opening, releasing cytochrome C (Cyt C), and leading to the intrinsic apoptosis cascade. Misfolded proteins induce the UPR. The UPR has three main signaling pathways, PERK, ATF6, and IRE1, which upregulate genes during stressed conditions. The activation of NRF2 by PERK leads to a decrease in ROS. The upregulation of CHOP by ATF4/ATF6 and JNK by IRE1 leads to apoptosis through shifting the balance between pro‐ and anti‐apoptotic proteins.

FIGURE 4

Transneuronal propagation and gut microbiome…

FIGURE 4

Transneuronal propagation and gut microbiome dysbiosis in neurodegenerative disease. Top: Transneuronal spread of…

FIGURE 4

Transneuronal propagation and gut microbiome dysbiosis in neurodegenerative disease. Top: Transneuronal spread of tau protein occurs via the extracellular space, synaptic vesicles, and transneuronal nanotubes (TNTs). Tau dissociates from microtubules upon post‐translational modifications and aggregates into tau oligomers and neurofibrillary tangles (NFTs). Aβ oligomers can impact synaptic transmission through presynaptic release of glutamate and direct modulation of postsynaptic NMDA receptors, which increases intracellular calcium in postsynaptic neurons and drives excitotoxicity. Bottom: The transition from a healthy gut to dysbiosis has been associated with neurodegenerative diseases. Bacterial components can permeate through the intestinal wall to activate resident intestinal immune cells, which generates chemokines and cytokines that induce inflammation. Based on preclinical evidence, it is hypothesized that the transneuronal migration of pathological proteins, such as alpha‐synuclein, could occur from the gut to the brain via the vagus nerve.

FIGURE 5

Neuroimmune system alterations in neurodegenerative…

FIGURE 5

Neuroimmune system alterations in neurodegenerative disease. Glial cells (microglia, astrocytes, and oligodendrocytes) transition…

FIGURE 5

Neuroimmune system alterations in neurodegenerative disease. Glial cells (microglia, astrocytes, and oligodendrocytes) transition from homeostatic (healthy) toward disease‐associated and senescent states throughout the course of disease progression. Disease induced alterations in the neuroimmune microenvironment modulates cellular signaling pathways, which triggers the transition of glial cells to altered states and results in phenotypic and functional differences. These include changes in phagocytosis, autophagy, chemotaxis, secretion of a variety of biomolecules, generation of oxidative stress, alterations in neuronal synapses and brain barrier function, energy metabolism, and myelination. Although it is represented simplistically, glial cells can assume many different states due to their high plasticity and the categorization of these cells into distinct subtypes is an ongoing area of research. Gene regulatory mechanisms that drive these transition states and the different glial cell subtypes are largely unknown and an active area of research. BBB, blood–brain barrier; ER, endoplasmic reticulum; ROS, reactive oxygen species.

FIGURE 6

Quantitative systems pharmacology (QSP) models…

FIGURE 6

Quantitative systems pharmacology (QSP) models of neurodegenerative diseases. (a) Cumulative number of published…

FIGURE 6

Quantitative systems pharmacology (QSP) models of neurodegenerative diseases. (a) Cumulative number of published models over time, (b) level of biological detail modeled, (c) types of neurodegenerative diseases modeled, and (d) proportion of code in the private versus public domain for published QSP models of neurodegenerative diseases. AD, Alzheimer's disease; ALS, amyotrophic lateral sclerosis; PD, Parkinson's disease.