TY - GEN
T1 - A composite multivariate polygenic and neuroimaging score for prediction of conversion to Alzheimer's disease
AU - Filipovych, Roman
AU - Gaonkar, Bilwaj
AU - Davatzikos, Christos
PY - 2012
Y1 - 2012
N2 - Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) are characterized by widespread pathological changes in the brain. At the same time, Alzheimer's disease is heritable with complex genetic underpinnings that may influence the timing of the related pathological changes in the brain and can affect the progression from MCI to AD. In this paper, we present a multivariate imaging genetics approach for prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment. We employ multivariate pattern recognition approaches to obtain neuroimaging and polygenic discriminators between the healthy individuals and AD patients. We then design, in a linear manner, a composite imaging-genetic score for prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment. We apply our approach within the Alzheimer's Disease Neuroimaging Initiative and show that the integration of polygenic and neuroimaging information improves prediction of conversion to AD.
AB - Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) are characterized by widespread pathological changes in the brain. At the same time, Alzheimer's disease is heritable with complex genetic underpinnings that may influence the timing of the related pathological changes in the brain and can affect the progression from MCI to AD. In this paper, we present a multivariate imaging genetics approach for prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment. We employ multivariate pattern recognition approaches to obtain neuroimaging and polygenic discriminators between the healthy individuals and AD patients. We then design, in a linear manner, a composite imaging-genetic score for prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment. We apply our approach within the Alzheimer's Disease Neuroimaging Initiative and show that the integration of polygenic and neuroimaging information improves prediction of conversion to AD.
KW - Alzheimer's disease
KW - imaging genetics
KW - mild cognitive impairment
KW - multivariate analysis
KW - pattern classification
UR - http://www.scopus.com/inward/record.url?scp=84867802618&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867802618&partnerID=8YFLogxK
U2 - 10.1109/PRNI.2012.9
DO - 10.1109/PRNI.2012.9
M3 - Conference contribution
AN - SCOPUS:84867802618
SN - 9780769547657
T3 - Proceedings - 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012
SP - 105
EP - 108
BT - Proceedings - 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012
T2 - 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012
Y2 - 2 July 2012 through 4 July 2012
ER -