A composite multivariate polygenic and neuroimaging score for prediction of conversion to Alzheimer's disease

Roman Filipovych, Bilwaj Gaonkar, Christos Davatzikos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012
Pages105-108
Number of pages4
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012 - London, United Kingdom
Duration: Jul 2 2012Jul 4 2012

Other

Other2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012
CountryUnited Kingdom
CityLondon
Period7/2/127/4/12

Fingerprint

Neuroimaging
Composite materials
Brain
Imaging techniques
Discriminators
Pattern recognition

Keywords

  • Alzheimer's disease
  • imaging genetics
  • mild cognitive impairment
  • multivariate analysis
  • pattern classification

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

Cite this

Filipovych, R., Gaonkar, B., & Davatzikos, C. (2012). A composite multivariate polygenic and neuroimaging score for prediction of conversion to Alzheimer's disease. In Proceedings - 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012 (pp. 105-108). [6295901] https://doi.org/10.1109/PRNI.2012.9

A composite multivariate polygenic and neuroimaging score for prediction of conversion to Alzheimer's disease. / Filipovych, Roman; Gaonkar, Bilwaj; Davatzikos, Christos.

Proceedings - 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012. 2012. p. 105-108 6295901.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Filipovych, R, Gaonkar, B & Davatzikos, C 2012, A composite multivariate polygenic and neuroimaging score for prediction of conversion to Alzheimer's disease. in Proceedings - 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012., 6295901, pp. 105-108, 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012, London, United Kingdom, 7/2/12. https://doi.org/10.1109/PRNI.2012.9
Filipovych R, Gaonkar B, Davatzikos C. A composite multivariate polygenic and neuroimaging score for prediction of conversion to Alzheimer's disease. In Proceedings - 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012. 2012. p. 105-108. 6295901 https://doi.org/10.1109/PRNI.2012.9
Filipovych, Roman ; Gaonkar, Bilwaj ; Davatzikos, Christos. / A composite multivariate polygenic and neuroimaging score for prediction of conversion to Alzheimer's disease. Proceedings - 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012. 2012. pp. 105-108
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