Modelling neurodevelopment, neurodegeneration, and amyloid beta aggregation in the context of Alzheimer's using COBWEB

Melisa Gumus, Alessandro Leonardo Ricci


Alzheimer’s disease (AD) is a neurodegenerative disease. It is a growing concern, demanding the attention of families, scientists, and pharmaceutical companies due to its devastating impacts on patients. The disease is believed to be triggered by pathogenic amyloid beta protein (Aβ) formations in the brain. In order to understand the protein production and the plaque formation in the AD brain, we specifically focused on the ‘Amyloid Cascade Hypothesis,’ which explains the biological pathways and the players in the disease. Focusing on the macro-side, we modelled the progression of AD from neurodevelopment (healthy brain) to neurodegeneration (the disease state) by using the agent based computer simulation program called COBWEB. Our model begins with healthy, developing neurons thriving in the hippocampus and cerebrospinal fluid (CSF) working efficiently. The brain ages throughout the adulthood phase. The onset of the disease and its progression is modelled with plaque formation, a decline in neuron counts, and an inefficient cleaning mechanism close to the end of the experiment. We conclude that our model fulfills its purpose: to provide a visual contrast between health and disease through the slow progression of AD in real time, increasing one’s understanding of this illness. Its accuracy is attributed to Aβ plaque formation, neuronal death, and CSF deterioration. Future projects include testing, designing, and refining new treatments using this model, diminishing the barrier to entry for new ideas, and providing a new tool for teaching AD.

La maladie d’Alzheimer (MA) est une maladie neurodégénérative. Elle est un souci croissant, exigeant l’attention des familles, des scientifiques et des sociétés pharmaceutiques en raison de ses effets dévastateurs sur les patients. Nous pensons que la maladie est provoquée par la formation pathogénique de la protéine bêta amyloïde (Aß) dans le cerveau. Afin de comprendre la production de la protéine et la formation de plaques dans le cerveau
d’un patient atteint de MA, nous avons mis l’accent spécifiquement sur l’hypothèse de la cascade amyloïde, ce qui explique les voies biologiques et les acteurs impliqués dans la maladie. En nous concentrant sur la macroscopie, nous avons modélisé la progression de la MA du début du neurodéveloppement (le cerveau en bonne santé) à la neurodégénérescence (l’état de la maladie) en utilisant le programme de simulation numérique basé sur un agent appelé COBWEB. Notre modèle commence avec des neurones qui se développent normalement, grandissant dans l’hippocampe et le liquide céphalo-rachidien (LCR) et travaillant efficacement. Le cerveau vieillit tout au long de la phase adulte. L’apparition de la maladie et de sa progression est modélisée avec la formation des plaques, une diminution du nombre neurones, et un mécanisme de nettoyage inefficace près de la fin. Nous concluons que notre modèle répond à son but de fournir un contraste visuel entre la santé et la maladie à travers la lente progression de la MA en temps réel, ce qui augmente notre compréhension de la MA. Sa précision est attribuée à la formation de plaques Aß, la mort neuronale et la détérioration du LCR. Les projets futurs incluent des tests, la conception et le raffinage de nouveaux traitements en utilisant ce modèle, ce qui diminue la barrière à l’entrée pour de nouvelles idées, et de fournir un nouvel outil pour enseigner la MA.


neuroscience; computational biology; neurodegenerative diseases; Alzheimer’s disease; COBWEB

Full Text:



Bateman, R. J.; Munsell, L.Y.; Morris, J.C.; Swarm,

R.; Yarasheski, K.E.; Holtzman, D. M. Human

amyloid-beta synthesis and clearance rates as

measured in cerebrospinal fluid in vivo. Nat Med.

, 12(7):856–61.10.1038/nm1438

Ewers, M.; Sperling, R. A.; Klunk, W. E.; Weiner,

M. W.; Hampel, H. Neuroimaging markers for

the prediction and early diagnosis of Alzheimer’s

disease dementia. Trends in Neurosciences,

, 34(8), 430–442. 10.1016/j.tins.2011.05.005

Iliff, J.J.; Wang, M.; Liao, Y.; Plogg, B.A.; Peng,

W.; Gundersen, G.A. et al. A paravascular

pathway facilitates CSF flow through the brain

parenchyma and the clearance of interstitial

solutes, including amyloid β. Sci Transl

Med. 2012, 15;4(147):147ra111. 10.1126/


Iliff, J.J.; Lee, H.; Yu, M.;Feng, T.; Logan, J.;

Nedergaard, M. et al. Brain-wide pathway for

waste clearance captured by contrast-enhanced

MRI. Journal of Clinical Investigation. 2013,


Jin, K.; Peel, A.L.; Mao, X.O.; Xie, L.; Cottrell,

B.A.; Henshall, D.C.; Greenberg, D.A. Increased

hippocampal neurogenesis in Alzheimer’s

Disease. PINAS. 2003, 101: 343-347. 10.1073/


Jetha, M. K.; Segalowitz, S. J. Chapter 1 -

Structural brain development in late childhood,

adolescence, and early adulthood. In Adolescent

Brain Development; Jetha, M. K., Segalowitz, S.

J.; Academic Press: San Diego, 2012; p 1.

Kang, J-E.; Lim, M. M.; Bateman, R. J.; Lee, J.

J.; Smyth, L.P.; Cirrito, J. R. et al. Amyloid-beta

dynamics are regulated by orexin and the sleepwake

cycle. Science. 2009, 13;326(5955):1005–


Kovacech, B.; Skrabana, R.; and Novak, M.

Transition of Tau Protein from Disordered

to Misordered in Alzheimer’s Disease.

Neurodegenerative Diseases. 2010, 7: 24–


Krogsrud, S. K.; Tamnes, C. K.; Fjell, A. M.;

Amlien, I.; Grydeland, H.; Sulutvedt, U.; et al.

Development of hippocampal subfield volumes

from 4 to 22 years. Hum Brain Mapp. 2014,


Mayeux, R. Early Alzheimer’s Disease. The New

England Journal of Medicine. 2010, 362: 2194–


Prokop, S.; Miller, K.; Heppner, F. Microglia actions

in Alzheimer’s disease. Acta Neuropathologica.

, 126(4), 461–477. 10.1007/s00401-013-


Querfurth, H. W.; LaFerla, F. M. Alzheimer’s

Disease Mechanisms of Disease. The

New England Journal of Medicine. 2010,

;362(4):329–44. 10.1056/NEJMra0909142

Sanai, N.; Nguyen, T.; Ihrie, R.A.; Mirzadeh, Z.;

Tsai, H.H.; Wong, M.; Gupta, N.; Berger, M.S.;

Huang, E.; Garcia-Verdugo, J. M. Corridors of

migrating neurons in the human brain and their

decline during infancy. Nature. 2011, 478:382–

, 10.1038/nature10487

Serrano-Pozo, A.; Mielke, M. L.; Muzitansky,

A.; Gómez-Isla, T.; Growdon, J. H.; Bacskai, B.

J.; Betensky, R. A.; Frosch, M.P.; Hyman, B.T. Stable Size Distribution of Amyloid Plaques

Over the Course of Alzheimer Disease.

Journal of Neuropathology and Experimental

Neurology. 2012, 71, 694–701.10.1097/


Sherrington, R. et al. Cloning of a gene bearing

missense mutations in early-onset familial

Alzheimer’s disease. Nature. 1995, 375, 754–


Sperling, R.A.; Aisen, P.S.; Beckett, L.A.; Bennett,

D.A.; Craft, S.; Fagan, A. M.; et al. Toward defining

the preclinical stages of Alzheimer’s disease:

Recommendations from the National Institute

on Aging-Alzheimer’s Association workgroups

on diagnostic guidelines for Alzheimer’s

disease. Alzheimer’s & Dementia: The Journal

of the Alzheimer’s Association. 2011, 7(3):280–


Spiros, A.; Geerts, H. New Insight Into Human

Brain Amyloid Kinetics From a Humanized

Computer Modelling Study. Alzheimer’s &

Dementia: The Journal of the Alzheimer’s

Association. 2014, 1;10(4):P314. http://dx.doi.


Tam, W.Y.; Ma, C.H.E. Bipolar/rod-shaped

microglia are proliferating microglia with

distinct M1/M2 phenotypes. Sci Rep. 2014, 4,


Tanzi, R.E.; Bertram, L.; Twenty Years of the

Alzheimer’s Disease Amyloid Hypothesis: A

Genetic Perspective. Cell. 2005, 120: 545–555.


Teare, M.D.; Barrett, J.H.; Genetic Linkage Studies.

The Lancet. 2005, 366(9490): 1036-1044. http://

Tran, A. Simulating Land Use: An Exploration of

the Stability of a Two Zone City. The Journal of

Student Science and Technology. 2015, 8(2): 21-

10.13034 / JSST-2015-016

Wood, A.J.; Cummings, J.L. Alzheimer’s Disease.

The New England Journal of Medicine. 2014, 351:

-67. 10.1056/NEJMra040223

Xie, L.; Kang, H.; Xu, Q.; Chen, M.J.; Liao, Y.;

Thiyagarajan, M.; O’Donnell, J.; Christensen,

D.J.; Nicholson, C.; Iliff, J.J., et al. Sleep

Drives Metabolite Clearance from the Adult

Brain. Science. 2013, 342, 373–377. 10.1126/


Zeng, H.; Wu, X.; Alzheimer’s disease drug

development based on Computer-Aided Drug

Design. Eur J Med Chem. 2015, S0223-

(15)30223-310. 1016/j.ejmech.2015.08.039.



  • There are currently no refbacks.

Copyright (c) 2017 Journal of Student Science and Technology