iSTAGING (Imaging-based coordinate SysTem for AGing and NeurodeGenerative diseases)
Approved Research ID: 35148
Approval date: September 10th 2018
Alzheimers Disease (AD) presently affects over 5 million individuals in USA alone, posing a significant burden to patients, families, and the society. It is clear that treatments would require early detection of AD at stages even decades before onset. Modern advanced neuroimaging methods offer the opportunity to study diverse brain changes present in aging and prodromal AD in ways that were previously impossible. We aim to harmonize large data sets and capture the heterogeneity of brain aging and prodromal AD patterns. We will establish normative aging curves for various neuroimaging measures. Our lab is an international leader in development of neuroimaging tools for disease prediction and monitoring. Sensitive tools for pathological aging or early AD prediction will help in the development of individualized medicine. This proposed research will allow the neuroimaging community to place each scan into a manageable coordinate system, and relate his/her imaging pattern coordinates to cognition, clinical progression, risk factors, and ultimately response to treatments for Alzheimers Disease. Within one year of receipt of UK Biobank data, region of interest (ROI) segmentations, brain ageing prediction measures (SPARE-BA), Alzherimers disease measure (SPARE-AD) and functional networks will be calculated. The following year we will investigate the associations with cognition and other life style risk factors.
Our goal is to leverage current machine learning methods to measure patterns of brain atrophy, small vessel disease and functional connectivity; to distill imaging data down to a few dozen informative dimensions, which we will use as indices to quantify and distinguish normative, resilient, and advanced (pathological) brain aging; and to capture anatomical and functional brain changes due to pathology.
Our aim is to develop an Imaging-based coordinate SysTem for AGing and NeurodeGenerative diseases (iSTAGING); each dimension will reflect a different aspect of brain change, and quantify underlying neuroanatomical, neurofunctional and neuropathological heterogeneities.
Furthermore, we aim to correlate these neuroimaging phenotypes with cognitive phenotypes and clinical progression of dementia. This will allow us to place each individual into a dimensional brain coordinate system of aging; to map his/her trajectory; and to determine predictive indices emanating from multi-parametric imaging data.
The result of this project will be a major resource for researchers and clinicians: to compare imaging measures against normative brain aging curves; to quantify how much and in which ways a unique individual falls off the curve, or is ahead of the curve; and to relate the deviation from resilient and normal brain aging to the cognitive function.
Human aging is complex and heterogeneous that involve interactions of multidimensional biological systems in cognitive, mental and physical functions. Our goal is to correlate the physical activity assessments with brain aging and better explain the heterogeneity of the various aging phenotypes and changes in cognition. We aim to estimate a physical aging index that complements brain aging and jointly identify subclusters of subjects with distinct aging trajectories.
We will extend the analyses described above to investigate associations between imaging phenotypes derived using machine learning and other advanced analytics methods, genetic risk factors and polygenic risk scores, and clinical measures. We will also investigate the synergistic value of combining imaging, genetic and clinical variables to render personalized prognosis of cognitive decline and clinical progression. Finally, we will investigate such phenotypes beyond aging, neurodegenerative, and neuropsychiatric diseases, in order to determine the interplay between other disease-related phenotypes, genotypes, and accelerated brain aging.