Systems modeling of white matter microstructural abnormalities in Alzheimer's disease

Introduction: Microstructural abnormalities in white matter (WM) are often reported in Alzheimer's disease (AD). However, it is unclear which brain regions have the strongest WM changes in presymptomatic AD and what biological processes underlie WM abnormality during disease progression. Method...

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Main Authors: Emrin Horgusluoglu-Moloch, Gaoyu Xiao, Minghui Wang, Qian Wang, Xianxiao Zhou, Kwangsik Nho, Andrew J. Saykin, Eric Schadt, Bin Zhang
Format: Article
Language:English
Published: Elsevier 2020-01-01
Series:NeuroImage: Clinical
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2213158220300401
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spelling doaj-19614da17c594868af86df231837ea8a2020-11-25T02:09:52ZengElsevierNeuroImage: Clinical2213-15822020-01-0126Systems modeling of white matter microstructural abnormalities in Alzheimer's diseaseEmrin Horgusluoglu-Moloch0Gaoyu Xiao1Minghui Wang2Qian Wang3Xianxiao Zhou4Kwangsik Nho5Andrew J. Saykin6Eric Schadt7Bin Zhang8Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USADepartment of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USADepartment of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USADepartment of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USADepartment of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USACenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USACenter for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USADepartment of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USADepartment of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USA; Corresponding author at: Department of Genetics & Genomic Sciences, Director, Mount Sinai Center for Transformative Disease Modeling, Member, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029Introduction: Microstructural abnormalities in white matter (WM) are often reported in Alzheimer's disease (AD). However, it is unclear which brain regions have the strongest WM changes in presymptomatic AD and what biological processes underlie WM abnormality during disease progression. Methods: We developed a systems biology framework to integrate matched diffusion tensor imaging (DTI), genetic and transcriptomic data to investigate regional vulnerability to AD and identify genetic risk factors and gene subnetworks underlying WM abnormality in AD. Results: We quantified regional WM abnormality and identified most vulnerable brain regions. A SNP rs2203712 in CELF1 was most significantly associated with several DTI-derived features in the hippocampus, the top ranked brain region. An immune response gene subnetwork in the blood was most correlated with DTI features across all the brain regions. Discussion: Incorporation of image analysis with gene network analysis enhances our understanding of disease progression and facilitates identification of novel therapeutic strategies for AD.http://www.sciencedirect.com/science/article/pii/S2213158220300401Alzheimer's diseaseDiffusion tensor imagingWhite matterBrain regionsCELF1Immune response
collection DOAJ
language English
format Article
sources DOAJ
author Emrin Horgusluoglu-Moloch
Gaoyu Xiao
Minghui Wang
Qian Wang
Xianxiao Zhou
Kwangsik Nho
Andrew J. Saykin
Eric Schadt
Bin Zhang
spellingShingle Emrin Horgusluoglu-Moloch
Gaoyu Xiao
Minghui Wang
Qian Wang
Xianxiao Zhou
Kwangsik Nho
Andrew J. Saykin
Eric Schadt
Bin Zhang
Systems modeling of white matter microstructural abnormalities in Alzheimer's disease
NeuroImage: Clinical
Alzheimer's disease
Diffusion tensor imaging
White matter
Brain regions
CELF1
Immune response
author_facet Emrin Horgusluoglu-Moloch
Gaoyu Xiao
Minghui Wang
Qian Wang
Xianxiao Zhou
Kwangsik Nho
Andrew J. Saykin
Eric Schadt
Bin Zhang
author_sort Emrin Horgusluoglu-Moloch
title Systems modeling of white matter microstructural abnormalities in Alzheimer's disease
title_short Systems modeling of white matter microstructural abnormalities in Alzheimer's disease
title_full Systems modeling of white matter microstructural abnormalities in Alzheimer's disease
title_fullStr Systems modeling of white matter microstructural abnormalities in Alzheimer's disease
title_full_unstemmed Systems modeling of white matter microstructural abnormalities in Alzheimer's disease
title_sort systems modeling of white matter microstructural abnormalities in alzheimer's disease
publisher Elsevier
series NeuroImage: Clinical
issn 2213-1582
publishDate 2020-01-01
description Introduction: Microstructural abnormalities in white matter (WM) are often reported in Alzheimer's disease (AD). However, it is unclear which brain regions have the strongest WM changes in presymptomatic AD and what biological processes underlie WM abnormality during disease progression. Methods: We developed a systems biology framework to integrate matched diffusion tensor imaging (DTI), genetic and transcriptomic data to investigate regional vulnerability to AD and identify genetic risk factors and gene subnetworks underlying WM abnormality in AD. Results: We quantified regional WM abnormality and identified most vulnerable brain regions. A SNP rs2203712 in CELF1 was most significantly associated with several DTI-derived features in the hippocampus, the top ranked brain region. An immune response gene subnetwork in the blood was most correlated with DTI features across all the brain regions. Discussion: Incorporation of image analysis with gene network analysis enhances our understanding of disease progression and facilitates identification of novel therapeutic strategies for AD.
topic Alzheimer's disease
Diffusion tensor imaging
White matter
Brain regions
CELF1
Immune response
url http://www.sciencedirect.com/science/article/pii/S2213158220300401
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