Effect of APOE ε4 on multimodal brain connectomic traits: a persistent homology study
Abstract Background Although genetic risk factors and network-level neuroimaging abnormalities have shown effects on cognitive performance and brain atrophy in Alzheimer’s disease (AD), little is understood about how apolipoprotein E (APOE) ε4 allele, the best-known genetic risk for AD, affect brain...
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| Format: | Article |
| Language: | English |
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BMC
2020-12-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-020-03877-9 |
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| author | Jin Li Chenyuan Bian Dandan Chen Xianglian Meng Haoran Luo Hong Liang Li Shen for the Alzheimer’s Disease Neuroimaging Initiative |
| author_facet | Jin Li Chenyuan Bian Dandan Chen Xianglian Meng Haoran Luo Hong Liang Li Shen for the Alzheimer’s Disease Neuroimaging Initiative |
| author_sort | Jin Li |
| collection | DOAJ |
| description | Abstract Background Although genetic risk factors and network-level neuroimaging abnormalities have shown effects on cognitive performance and brain atrophy in Alzheimer’s disease (AD), little is understood about how apolipoprotein E (APOE) ε4 allele, the best-known genetic risk for AD, affect brain connectivity before the onset of symptomatic AD. This study aims to investigate APOE ε4 effects on brain connectivity from the perspective of multimodal connectome. Results Here, we propose a novel multimodal brain network modeling framework and a network quantification method based on persistent homology for identifying APOE ε4-related network differences. Specifically, we employ sparse representation to integrate multimodal brain network information derived from both the resting state functional magnetic resonance imaging (rs-fMRI) data and the diffusion-weighted magnetic resonance imaging (dw-MRI) data. Moreover, persistent homology is proposed to avoid the ad hoc selection of a specific regularization parameter and to capture valuable brain connectivity patterns from the topological perspective. The experimental results demonstrate that our method outperforms the competing methods, and reasonably yields connectomic patterns specific to APOE ε4 carriers and non-carriers. Conclusions We have proposed a multimodal framework that integrates structural and functional connectivity information for constructing a fused brain network with greater discriminative power. Using persistent homology to extract topological features from the fused brain network, our method can effectively identify APOE ε4-related brain connectomic biomarkers. |
| first_indexed | 2024-12-24T05:33:14Z |
| format | Article |
| id | doaj.art-6d9779e5f20843d5a5831c9e3bc7fbad |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-24T05:33:14Z |
| publishDate | 2020-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-6d9779e5f20843d5a5831c9e3bc7fbad2022-12-21T17:13:05ZengBMCBMC Bioinformatics1471-21052020-12-0121S2111810.1186/s12859-020-03877-9Effect of APOE ε4 on multimodal brain connectomic traits: a persistent homology studyJin Li0Chenyuan Bian1Dandan Chen2Xianglian Meng3Haoran Luo4Hong Liang5Li Shen6for the Alzheimer’s Disease Neuroimaging InitiativeCollege of Automation, Harbin Engineering UniversityCollege of Automation, Harbin Engineering UniversityCollege of Automation, Harbin Engineering UniversitySchool of Computer Information and Engineering, Changzhou Institute of TechnologyCollege of Automation, Harbin Engineering UniversityCollege of Automation, Harbin Engineering UniversityDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of PennsylvaniaAbstract Background Although genetic risk factors and network-level neuroimaging abnormalities have shown effects on cognitive performance and brain atrophy in Alzheimer’s disease (AD), little is understood about how apolipoprotein E (APOE) ε4 allele, the best-known genetic risk for AD, affect brain connectivity before the onset of symptomatic AD. This study aims to investigate APOE ε4 effects on brain connectivity from the perspective of multimodal connectome. Results Here, we propose a novel multimodal brain network modeling framework and a network quantification method based on persistent homology for identifying APOE ε4-related network differences. Specifically, we employ sparse representation to integrate multimodal brain network information derived from both the resting state functional magnetic resonance imaging (rs-fMRI) data and the diffusion-weighted magnetic resonance imaging (dw-MRI) data. Moreover, persistent homology is proposed to avoid the ad hoc selection of a specific regularization parameter and to capture valuable brain connectivity patterns from the topological perspective. The experimental results demonstrate that our method outperforms the competing methods, and reasonably yields connectomic patterns specific to APOE ε4 carriers and non-carriers. Conclusions We have proposed a multimodal framework that integrates structural and functional connectivity information for constructing a fused brain network with greater discriminative power. Using persistent homology to extract topological features from the fused brain network, our method can effectively identify APOE ε4-related brain connectomic biomarkers.https://doi.org/10.1186/s12859-020-03877-9APOE ε4Brain networkPersistent homologyAlzheimer’s disease |
| spellingShingle | Jin Li Chenyuan Bian Dandan Chen Xianglian Meng Haoran Luo Hong Liang Li Shen for the Alzheimer’s Disease Neuroimaging Initiative Effect of APOE ε4 on multimodal brain connectomic traits: a persistent homology study BMC Bioinformatics APOE ε4 Brain network Persistent homology Alzheimer’s disease |
| title | Effect of APOE ε4 on multimodal brain connectomic traits: a persistent homology study |
| title_full | Effect of APOE ε4 on multimodal brain connectomic traits: a persistent homology study |
| title_fullStr | Effect of APOE ε4 on multimodal brain connectomic traits: a persistent homology study |
| title_full_unstemmed | Effect of APOE ε4 on multimodal brain connectomic traits: a persistent homology study |
| title_short | Effect of APOE ε4 on multimodal brain connectomic traits: a persistent homology study |
| title_sort | effect of apoe ε4 on multimodal brain connectomic traits a persistent homology study |
| topic | APOE ε4 Brain network Persistent homology Alzheimer’s disease |
| url | https://doi.org/10.1186/s12859-020-03877-9 |
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