Abstract: An estimated 6.5 million Americans suffer from neurodegenerative diseases such as
Alzheimer’s Disease (AD) and Parkinson’s Disease that result in progressive degeneration and
death of nerve cells (neurons) impairing movement and/or mental functioning. Delayed clearance
of key biomarkers of AD, including amyloid-beta (Aβ) and tau agglomerates, has been suggested
as a possible mechanism for triggering neurodegeneration that could lead to AD. To date,
however, there is little to no quantitative and mechanistic understanding of the transport and
clearance of small molecules, agglomerates, and debris from the brain. Such clearance is thought
to occur through a brain-wide perivascular pathway for cerebrospinal fluid (CSF) and interstitial
fluid (ISF) exchange, known as the glymphatic system. Characterization of glymphatic transport
is currently limited, however, well-validated 3D computational models may enable quantification
of the transport and clearance of key AD biomarkers throughout the brain. The long-term goal of
this proposal is to develop an integrated toolset of image-based computational modeling to
describe subject-specific glymphatic transport that is experimentally parameterized and validated.
We propose a novel approach, using an immersed isogeometric method, where the transport
model is constructed directly from the 3D imaging data, resulting in a flexible, subject-specific
model that accounts for anatomical geometry and heterogeneous material properties. Our
preliminary studies indicate that transport parameters such as CSF flow velocity play a large role
in Aβ deposition. We hypothesize that 1) amyloid-bearing mice exhibit differences in glymphatic
function, including CSF flow velocity, which lead to Aβ deposition and that 2) increased exercise
in a mouse model of amyloid deposition will improve glymphatic function and reduce amyloid
deposition. The main objective therefore is to 1) parameterize subject-specific 3D models of
glymphatic transport and study brain-wide deposition of proteins under pathological conditions in
amyloid bearing mice, and 2) model the effects of exercise on glymphatic transport and
subsequent amyloid deposition. Our advanced image-guided modeling of glymphatic transport
tightly integrated with experiments and adjusted with subject-specific attributes, offers a unique
opportunity to quantitatively assess the effect of glymphatic dysfunction on waste clearance and
study how specific factors such as exercise drive glymphatic function and protein deposition. The
proposed research is significant because it will provide an architecturally and physiologically
faithful platform, grounded in experiments, for informing future preventive and therapeutic
interventions in neurodegenerative disease.