Bibliographic Details
| Title: |
Brain high-throughput multi-omics data reveal molecular heterogeneity in Alzheimer's disease. |
| Authors: |
Eteleeb, Abdallah M.1,2 (AUTHOR), Novotny, Brenna C.1 (AUTHOR), Tarraga, Carolina Soriano1 (AUTHOR), Sohn, Christopher1 (AUTHOR), Dhungel, Eliza3 (AUTHOR), Brase, Logan1 (AUTHOR), Nallapu, Aasritha1 (AUTHOR), Buss, Jared1 (AUTHOR), Farias, Fabiana1,4 (AUTHOR), Bergmann, Kristy1,4 (AUTHOR), Bradley, Joseph1,4 (AUTHOR), Norton, Joanne1,4 (AUTHOR), Gentsch, Jen1,4 (AUTHOR), Wang, Fengxian1,4 (AUTHOR), Davis, Albert A.5,6 (AUTHOR), Morris, John C.2,5,6 (AUTHOR), Karch, Celeste M.1,2,4,6 (AUTHOR), Perrin, Richard J.2,5,6,7 (AUTHOR), Benitez, Bruno A.8 (AUTHOR), Harari, Oscar1,2,6 (AUTHOR) oscar.harari@usumc.edu |
| Source: |
PLoS Biology. 4/30/2024, Vol. 22 Issue 4, p1-45. 45p. |
| Subject Terms: |
*ALZHEIMER'S disease, *ENDOCYTOSIS, *MULTIOMICS, *ALZHEIMER'S patients, *DATA integration, *HETEROGENEITY |
| Abstract: |
Unbiased data-driven omic approaches are revealing the molecular heterogeneity of Alzheimer disease. Here, we used machine learning approaches to integrate high-throughput transcriptomic, proteomic, metabolomic, and lipidomic profiles with clinical and neuropathological data from multiple human AD cohorts. We discovered 4 unique multimodal molecular profiles, one of them showing signs of poor cognitive function, a faster pace of disease progression, shorter survival with the disease, severe neurodegeneration and astrogliosis, and reduced levels of metabolomic profiles. We found this molecular profile to be present in multiple affected cortical regions associated with higher Braak tau scores and significant dysregulation of synapse-related genes, endocytosis, phagosome, and mTOR signaling pathways altered in AD early and late stages. AD cross-omics data integration with transcriptomic data from an SNCA mouse model revealed an overlapping signature. Furthermore, we leveraged single-nuclei RNA-seq data to identify distinct cell-types that most likely mediate molecular profiles. Lastly, we identified that the multimodal clusters uncovered cerebrospinal fluid biomarkers poised to monitor AD progression and possibly cognition. Our cross-omics analyses provide novel critical molecular insights into AD. Omics studies have found molecular features associated with different clinical and pathological profiles in patients with Alzheimer's disease. This study combines multiple high-throughput omics datasets and machine learning to identify four distinct molecular profiles of Alzheimer's disease, one of which was associated with worse cognitive function and neuropathological features. [ABSTRACT FROM AUTHOR] |
|
Copyright of PLoS Biology is the property of Public Library of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Academic Search Complete |
|
Full text is not displayed to guests. |
Login for full access.
|
