Pattern analysis of the interaction of regional amyloid load, cortical thickness and APOE genotype in the progression of Alzheimer's disease

Chunfei Li, Chen Fang, Mercedes Cabrerizo, Armando Barreto, Jean Andrian, Ranjan Duara, David Loewenstein, Malek Adjouadi

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

2 Citations (Scopus)

Abstract

Background: Deposition of beta amyloid protein (Aβ) is known to be an early event that is closely associated with the pathogenesis of Alzheimer's disease (AD), along with related downstream events such as neuronal loss, neurofibrillary tangles, cortical thinning and cognitive deficits. APOE e4 allele (E4) is also known to be associated with increased risk for AD. Objectives: The goal of this study is to examine the association of Aβ deposition to cortical thickness (CoTh), in healthy control (CN), early MCI (EMCI), late MCI (LMCI) and AD stages by controlling for E4 load, both in regional and hemispheric levels, and to interpret patterns of different brain regions based on their correlation performance among the four groups. Methods: We analyzed Amyloid PET Scan, Volumetric MRI (CoTh) data from participants in the ADNIGO/ADNI2 cohort whose APOE gene information are available. Statistical analysis includes Pearson partial correlations, Analysis of Covariance (ANCOVA) with post-hoc Tukey HSD. Complete-linkage hierarchical clustering analysis was further performed to group brain regions based on their significant correlation performance. Results: 25 out of 68 regions showed significant correlation of Aβ load and CoTh at least in one diagnostic group. Furthermore, 6 main clusters were recognized based on the performance patterns of those 25 regions across 4 diagnosis groups. Conclusion: Our major finding clustered the cortical regions into 2 general groups, positive correlation in CN or AD, and negative correlation in EMCI and/or LMCI, and 6 more specific groups were then recognized, confirming the interplay between of Aβ and CoTh in the different stages of the disease.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2171-2176
Number of pages6
Volume2017-January
ISBN (Electronic)9781509030491
DOIs
StatePublished - Dec 15 2017
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: Nov 13 2017Nov 16 2017

Other

Other2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
CountryUnited States
CityKansas City
Period11/13/1711/16/17

Fingerprint

Amyloid
Alzheimer Disease
Genotype
Brain
Neurofibrillary Tangles
Amyloid beta-Peptides
Staphylococcal Protein A
Positron-Emission Tomography
Cluster Analysis
Magnetic resonance imaging
Alleles
Statistical methods
Genes

Keywords

  • Alzheimer's disease
  • APOE gene
  • clustering
  • MRI
  • neuroimaging
  • Pearson partial correlation
  • PET

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

Cite this

Li, C., Fang, C., Cabrerizo, M., Barreto, A., Andrian, J., Duara, R., ... Adjouadi, M. (2017). Pattern analysis of the interaction of regional amyloid load, cortical thickness and APOE genotype in the progression of Alzheimer's disease. In Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 (Vol. 2017-January, pp. 2171-2176). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2017.8217994

Pattern analysis of the interaction of regional amyloid load, cortical thickness and APOE genotype in the progression of Alzheimer's disease. / Li, Chunfei; Fang, Chen; Cabrerizo, Mercedes; Barreto, Armando; Andrian, Jean; Duara, Ranjan; Loewenstein, David; Adjouadi, Malek.

Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 2171-2176.

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

Li, C, Fang, C, Cabrerizo, M, Barreto, A, Andrian, J, Duara, R, Loewenstein, D & Adjouadi, M 2017, Pattern analysis of the interaction of regional amyloid load, cortical thickness and APOE genotype in the progression of Alzheimer's disease. in Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 2171-2176, 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, Kansas City, United States, 11/13/17. https://doi.org/10.1109/BIBM.2017.8217994
Li C, Fang C, Cabrerizo M, Barreto A, Andrian J, Duara R et al. Pattern analysis of the interaction of regional amyloid load, cortical thickness and APOE genotype in the progression of Alzheimer's disease. In Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. Vol. 2017-January. Institute of Electrical and Electronics Engineers Inc. 2017. p. 2171-2176 https://doi.org/10.1109/BIBM.2017.8217994
Li, Chunfei ; Fang, Chen ; Cabrerizo, Mercedes ; Barreto, Armando ; Andrian, Jean ; Duara, Ranjan ; Loewenstein, David ; Adjouadi, Malek. / Pattern analysis of the interaction of regional amyloid load, cortical thickness and APOE genotype in the progression of Alzheimer's disease. Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. pp. 2171-2176
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N2 - Background: Deposition of beta amyloid protein (Aβ) is known to be an early event that is closely associated with the pathogenesis of Alzheimer's disease (AD), along with related downstream events such as neuronal loss, neurofibrillary tangles, cortical thinning and cognitive deficits. APOE e4 allele (E4) is also known to be associated with increased risk for AD. Objectives: The goal of this study is to examine the association of Aβ deposition to cortical thickness (CoTh), in healthy control (CN), early MCI (EMCI), late MCI (LMCI) and AD stages by controlling for E4 load, both in regional and hemispheric levels, and to interpret patterns of different brain regions based on their correlation performance among the four groups. Methods: We analyzed Amyloid PET Scan, Volumetric MRI (CoTh) data from participants in the ADNIGO/ADNI2 cohort whose APOE gene information are available. Statistical analysis includes Pearson partial correlations, Analysis of Covariance (ANCOVA) with post-hoc Tukey HSD. Complete-linkage hierarchical clustering analysis was further performed to group brain regions based on their significant correlation performance. Results: 25 out of 68 regions showed significant correlation of Aβ load and CoTh at least in one diagnostic group. Furthermore, 6 main clusters were recognized based on the performance patterns of those 25 regions across 4 diagnosis groups. Conclusion: Our major finding clustered the cortical regions into 2 general groups, positive correlation in CN or AD, and negative correlation in EMCI and/or LMCI, and 6 more specific groups were then recognized, confirming the interplay between of Aβ and CoTh in the different stages of the disease.

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