PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease
IntroductionIdentification of Alzheimer's Disease (AD)-related transcriptomic signatures from blood is important for early diagnosis of the disease. Deep learning techniques are potent classifiers for AD diagnosis, but most have been unable to identify biomarkers because of their lack of interp...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-07-01
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| Series: | Frontiers in Aging Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnagi.2023.1126156/full |
| _version_ | 1797780029795467264 |
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| author | Yeojin Kim Hyunju Lee Hyunju Lee |
| author_facet | Yeojin Kim Hyunju Lee Hyunju Lee |
| author_sort | Yeojin Kim |
| collection | DOAJ |
| description | IntroductionIdentification of Alzheimer's Disease (AD)-related transcriptomic signatures from blood is important for early diagnosis of the disease. Deep learning techniques are potent classifiers for AD diagnosis, but most have been unable to identify biomarkers because of their lack of interpretability.MethodsTo address these challenges, we propose a pathway information-based neural network (PINNet) to predict AD patients and analyze blood and brain transcriptomic signatures using an interpretable deep learning model. PINNet is a deep neural network (DNN) model with pathway prior knowledge from either the Gene Ontology or Kyoto Encyclopedia of Genes and Genomes databases. Then, a backpropagation-based model interpretation method was applied to reveal essential pathways and genes for predicting AD.ResultsThe performance of PINNet was compared with a DNN model without a pathway. Performances of PINNet outperformed or were similar to those of DNN without a pathway using blood and brain gene expressions, respectively. Moreover, PINNet considers more AD-related genes as essential features than DNN without a pathway in the learning process. Pathway analysis of protein-protein interaction modules of highly contributed genes showed that AD-related genes in blood were enriched with cell migration, PI3K-Akt, MAPK signaling, and apoptosis in blood. The pathways enriched in the brain module included cell migration, PI3K-Akt, MAPK signaling, apoptosis, protein ubiquitination, and t-cell activation.DiscussionBy integrating prior knowledge about pathways, PINNet can reveal essential pathways related to AD. The source codes are available at https://github.com/DMCB-GIST/PINNet. |
| first_indexed | 2024-03-12T23:38:53Z |
| format | Article |
| id | doaj.art-8e62d17928e14ee1abb0003d8dd8af83 |
| institution | Directory Open Access Journal |
| issn | 1663-4365 |
| language | English |
| last_indexed | 2024-03-12T23:38:53Z |
| publishDate | 2023-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Aging Neuroscience |
| spelling | doaj.art-8e62d17928e14ee1abb0003d8dd8af832023-07-15T03:21:34ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652023-07-011510.3389/fnagi.2023.11261561126156PINNet: a deep neural network with pathway prior knowledge for Alzheimer's diseaseYeojin Kim0Hyunju Lee1Hyunju Lee2Artificial Intelligence Graduate School, Gwangju Institute of Science and Technology, Gwangju, Republic of KoreaArtificial Intelligence Graduate School, Gwangju Institute of Science and Technology, Gwangju, Republic of KoreaSchool of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, Republic of KoreaIntroductionIdentification of Alzheimer's Disease (AD)-related transcriptomic signatures from blood is important for early diagnosis of the disease. Deep learning techniques are potent classifiers for AD diagnosis, but most have been unable to identify biomarkers because of their lack of interpretability.MethodsTo address these challenges, we propose a pathway information-based neural network (PINNet) to predict AD patients and analyze blood and brain transcriptomic signatures using an interpretable deep learning model. PINNet is a deep neural network (DNN) model with pathway prior knowledge from either the Gene Ontology or Kyoto Encyclopedia of Genes and Genomes databases. Then, a backpropagation-based model interpretation method was applied to reveal essential pathways and genes for predicting AD.ResultsThe performance of PINNet was compared with a DNN model without a pathway. Performances of PINNet outperformed or were similar to those of DNN without a pathway using blood and brain gene expressions, respectively. Moreover, PINNet considers more AD-related genes as essential features than DNN without a pathway in the learning process. Pathway analysis of protein-protein interaction modules of highly contributed genes showed that AD-related genes in blood were enriched with cell migration, PI3K-Akt, MAPK signaling, and apoptosis in blood. The pathways enriched in the brain module included cell migration, PI3K-Akt, MAPK signaling, apoptosis, protein ubiquitination, and t-cell activation.DiscussionBy integrating prior knowledge about pathways, PINNet can reveal essential pathways related to AD. The source codes are available at https://github.com/DMCB-GIST/PINNet.https://www.frontiersin.org/articles/10.3389/fnagi.2023.1126156/fullAlzheimer's diseasemachine learningtranscriptomicsbiomarkersbioinformaticsprotein-protein interaction network |
| spellingShingle | Yeojin Kim Hyunju Lee Hyunju Lee PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease Frontiers in Aging Neuroscience Alzheimer's disease machine learning transcriptomics biomarkers bioinformatics protein-protein interaction network |
| title | PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease |
| title_full | PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease |
| title_fullStr | PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease |
| title_full_unstemmed | PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease |
| title_short | PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease |
| title_sort | pinnet a deep neural network with pathway prior knowledge for alzheimer s disease |
| topic | Alzheimer's disease machine learning transcriptomics biomarkers bioinformatics protein-protein interaction network |
| url | https://www.frontiersin.org/articles/10.3389/fnagi.2023.1126156/full |
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