Network propagation of rare variants in Alzheimer's disease reveals tissue-specific hub genes and communities.
State-of-the-art rare variant association testing methods aggregate the contribution of rare variants in biologically relevant genomic regions to boost statistical power. However, testing single genes separately does not consider the complex interaction landscape of genes, nor the downstream effects...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2021-01-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008517&type=printable |
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| author | Marzia Antonella Scelsi Valerio Napolioni Michael D Greicius Andre Altmann Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Alzheimer’s Disease Sequencing Project (ADSP) |
| author_facet | Marzia Antonella Scelsi Valerio Napolioni Michael D Greicius Andre Altmann Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Alzheimer’s Disease Sequencing Project (ADSP) |
| author_sort | Marzia Antonella Scelsi |
| collection | DOAJ |
| description | State-of-the-art rare variant association testing methods aggregate the contribution of rare variants in biologically relevant genomic regions to boost statistical power. However, testing single genes separately does not consider the complex interaction landscape of genes, nor the downstream effects of non-synonymous variants on protein structure and function. Here we present the NETwork Propagation-based Assessment of Genetic Events (NETPAGE), an integrative approach aimed at investigating the biological pathways through which rare variation results in complex disease phenotypes. We applied NETPAGE to sporadic, late-onset Alzheimer's disease (AD), using whole-genome sequencing from the AD Neuroimaging Initiative (ADNI) cohort, as well as whole-exome sequencing from the AD Sequencing Project (ADSP). NETPAGE is based on network propagation, a framework that models information flow on a graph and simulates the percolation of genetic variation through tissue-specific gene interaction networks. The result of network propagation is a set of smoothed gene scores that can be tested for association with disease status through sparse regression. The application of NETPAGE to AD enabled the identification of a set of connected genes whose smoothed variation profile was robustly associated to case-control status, based on gene interactions in the hippocampus. Additionally, smoothed scores significantly correlated with risk of conversion to AD in Mild Cognitive Impairment (MCI) subjects. Lastly, we investigated tissue-specific transcriptional dysregulation of the core genes in two independent RNA-seq datasets, as well as significant enrichments in terms of gene sets with known connections to AD. We present a framework that enables enhanced genetic association testing for a wide range of traits, diseases, and sample sizes. |
| format | Article |
| id | doaj-art-854d9beab71e40a09f04f3efa6b2cb6f |
| institution | Kabale University |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-854d9beab71e40a09f04f3efa6b2cb6f2025-08-20T03:44:40ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-01-01171e100851710.1371/journal.pcbi.1008517Network propagation of rare variants in Alzheimer's disease reveals tissue-specific hub genes and communities.Marzia Antonella ScelsiValerio NapolioniMichael D GreiciusAndre AltmannAlzheimer’s Disease Neuroimaging Initiative (ADNI) and the Alzheimer’s Disease Sequencing Project (ADSP)State-of-the-art rare variant association testing methods aggregate the contribution of rare variants in biologically relevant genomic regions to boost statistical power. However, testing single genes separately does not consider the complex interaction landscape of genes, nor the downstream effects of non-synonymous variants on protein structure and function. Here we present the NETwork Propagation-based Assessment of Genetic Events (NETPAGE), an integrative approach aimed at investigating the biological pathways through which rare variation results in complex disease phenotypes. We applied NETPAGE to sporadic, late-onset Alzheimer's disease (AD), using whole-genome sequencing from the AD Neuroimaging Initiative (ADNI) cohort, as well as whole-exome sequencing from the AD Sequencing Project (ADSP). NETPAGE is based on network propagation, a framework that models information flow on a graph and simulates the percolation of genetic variation through tissue-specific gene interaction networks. The result of network propagation is a set of smoothed gene scores that can be tested for association with disease status through sparse regression. The application of NETPAGE to AD enabled the identification of a set of connected genes whose smoothed variation profile was robustly associated to case-control status, based on gene interactions in the hippocampus. Additionally, smoothed scores significantly correlated with risk of conversion to AD in Mild Cognitive Impairment (MCI) subjects. Lastly, we investigated tissue-specific transcriptional dysregulation of the core genes in two independent RNA-seq datasets, as well as significant enrichments in terms of gene sets with known connections to AD. We present a framework that enables enhanced genetic association testing for a wide range of traits, diseases, and sample sizes.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008517&type=printable |
| spellingShingle | Marzia Antonella Scelsi Valerio Napolioni Michael D Greicius Andre Altmann Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Alzheimer’s Disease Sequencing Project (ADSP) Network propagation of rare variants in Alzheimer's disease reveals tissue-specific hub genes and communities. PLoS Computational Biology |
| title | Network propagation of rare variants in Alzheimer's disease reveals tissue-specific hub genes and communities. |
| title_full | Network propagation of rare variants in Alzheimer's disease reveals tissue-specific hub genes and communities. |
| title_fullStr | Network propagation of rare variants in Alzheimer's disease reveals tissue-specific hub genes and communities. |
| title_full_unstemmed | Network propagation of rare variants in Alzheimer's disease reveals tissue-specific hub genes and communities. |
| title_short | Network propagation of rare variants in Alzheimer's disease reveals tissue-specific hub genes and communities. |
| title_sort | network propagation of rare variants in alzheimer s disease reveals tissue specific hub genes and communities |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008517&type=printable |
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