Dissociation of Structural and Functional Changes in Alzheimer's Disease

Poster No:

311 

Submission Type:

Abstract Submission 

Authors:

Annie Dang1, Di Wang1, Mohamad Habes2, Peter Fox3

Institutions:

1UT Health San Antonio, San Antonio, TX, 2University of Texas Health San Antonio, San Antonio, TX, 3The University of Texas Health Science Center at San Antonio, San Antonio, TX

First Author:

Annie Dang  
UT Health San Antonio
San Antonio, TX

Co-Author(s):

Di Wang  
UT Health San Antonio
San Antonio, TX
Mohamad Habes  
University of Texas Health San Antonio
San Antonio, TX
Peter Fox, MD  
The University of Texas Health Science Center at San Antonio
San Antonio, TX

Introduction:

The Amyloid-Tau-Neurodegeneration (ATN) biomarker framework for Alzheimer's disease (AD) indicates binary (positive/negative) designations for each type of pathology, without regard for anatomical distribution. Neurodegeneration is designated as positive if atrophy or hypometabolism is found on imaging [1]. However, Clifford Jack et al., 2016 noted that atrophy and hypometabolism were differently distributed and referenced each to different co-localized pathologies [2]. Thus, there exists a need to further characterize atrophy and hypometabolic changes in AD, with the goal of advancing the application of anatomically-based biomarkers in the ATN framework.

Methods:

Query of the BrainMap databases of published, group-wise neuroimaging, case-control contrasts was used to identify AD and mild cognitive impairment (MCI) studies for meta-analysis. The voxel-based morphometry (VBM) and voxel-based physiology (VBP) databases were used to identify studies involving atrophy and hypometabolism respectively. 157 VBM contrasts (110 AD, 47 MCI) and 146 VBP contrasts (88 AD, 58 MCI) were identified. Activation likelihood estimation coordinate-based meta-analysis was performed separately for VBM and VBP, to identify cross-study convergence of brain alteration patterns. Mango was then used to visualize results and quantify spatial overlap between VBM and VBP.

Results:

Structural (atrophy) and functional (hypophysiology) neurodegenerations in AD/MCI exhibit markedly different neuroanatomical distributions (Figure 1). Structural abnormalities chiefly involve the bilateral hippocampus and bilateral temporal lobes; functional abnormalities chiefly involve the bilateral parietal lobes and posterior cingulate. There is a small overlap (2184 mm3) between VBM and VBP, accounting for 10.1% of VBM and 7.1% of VBP.
Supporting Image: Dang_Figure1.png
 

Conclusions:

VBM and VBP patterns of alteration appear distinct, aligning with the anterior and posterior default mode network respectively. This dissociation may reflect distinct underlying neuropathologies. We suggest that this knowledge can be used to advance the application of anatomically-based biomarkers in the ATN framework. Network modeling of VBM and VBP data is currently ongoing.

Disorders of the Nervous System:

Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1

Modeling and Analysis Methods:

Activation (eg. BOLD task-fMRI) 2

Keywords:

Aging
Computational Neuroscience
Data analysis
Degenerative Disease
fMRI CONTRAST MECHANISMS
FUNCTIONAL MRI
Meta- Analysis
Positron Emission Tomography (PET)
STRUCTURAL MRI

1|2Indicates the priority used for review

Provide references using author date format

[1] Jack, C.R. (2018), ‘NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease’, Alzheimer’s & Dementia, vol. 14, pp. 535 - 62

[2] Jack, C.R. (2016), ‘A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers’, Neurology, vol 87, pp. 539-547