scholarly journals Brain age acceleration as biomarker of Alzheimer’s disease progression: Functional network connectivity analysis

2021 ◽  
Vol 17 (S1) ◽  
Author(s):  
Mohammad S.E. Sendi ◽  
David H Salat ◽  
Vince D Calhoun
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Progression ◽  
Network Connectivity ◽  
Functional Network ◽  
Connectivity Analysis ◽  
Functional Network Connectivity ◽  
Brain Age

scholarly journals The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer’s disease

2021 ◽  
Author(s):  
Mohammad S. E. Sendi ◽  
Elaheh Zendehrouh ◽  
Charles A. Ellis ◽  
Jiayu Chen ◽  
Robyn L. Miller ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Risk ◽  
Pearson Correlation ◽  
Network Connectivity ◽  
Risk Groups ◽  
Functional Network ◽  
Functional Network Connectivity ◽  
Normal Individuals ◽  
Data Driven Approach

AbstractApolipoprotein E (APOE) polymorphic alleles are genetic factors associated with Alzheimer’s disease (AD) risk. Although previous studies have explored the link between AD genetic risk and static functional network connectivity (sFNC), to the best of our knowledge, no previous studies have evaluated the association between dynamic FNC (dFNC) and AD genetic risk. Here, we examined the link between sFNC, dFNC, and AD genetic risk with a reproducible, data-driven approach. We used rs-fMRI, demographic, and APOE data from cognitively normal individuals (N=894) between 42 to 95 years of age (mean = 70 years). We divided individuals into low, moderate, and high-risk groups. Using Pearson correlation, we calculated sFNC across seven brain networks. We also calculated dFNC with a sliding window and Pearson correlation. The dFNC windows were partitioned into three distinct states with k-means clustering. Next, we calculated the amount of time each subject spent in each state, called occupancy rate or OCR. We compared both sFNC and OCR, estimated from dFNC, across individuals with different genetic risk and found that both sFNC and dFNC are related to AD genetic risk. We found that higher AD risk reduces within-visual sensory network (VSN) sFNC and that individuals with higher AD risk spend more time in a state with lower within-VSN dFNC. Additionally, we found that AD genetic risk affects whole-brain sFNC and dFNC in women but not in men. In conclusion, we presented novel insights into the links between sFNC, dFNC, and AD genetic risk.

P1-395: FUNCTIONAL NETWORK CONNECTIVITY CHANGES IN EARLY AND LATE ONSET ALZHEIMER'S DISEASE

2006 ◽  
Vol 14 (7S_Part_8) ◽  
pp. P453-P454
Author(s):  
Lorenzo Pini ◽  
Cristina Geroldi ◽  
Roberta Baruzzi ◽  
Samantha Galluzzi ◽  
Monica Bertocchi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Late Onset ◽  
Network Connectivity ◽  
Functional Network ◽  
Functional Network Connectivity

IC-P-040: FUNCTIONAL NETWORK CONNECTIVITY CHANGES IN EARLY AND LATE ONSET ALZHEIMER'S DISEASE

2006 ◽  
Vol 14 (7S_Part_1) ◽  
pp. P41-P41
Author(s):  
Lorenzo Pini ◽  
Cristina Geroldi ◽  
Roberta Baruzzi ◽  
Samantha Galluzzi ◽  
Monica Bertocchi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Late Onset ◽  
Network Connectivity ◽  
Functional Network ◽  
Functional Network Connectivity
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