Toward Personalized Network Biomarkers in Alzheimer's Disease: Computing Individualized Genomic and Protein Crosstalk Maps
Abstract
We call for the AD field to move beyond discrete biomarkers and utilize the full power of informatics and big data approaches to build and test personalized markers at a pathway and network level. While we have chosen AD as an example, the issues we propose are also highly relevant to other neurodegenerative disorders, such as vascular dementia or dementia with Lewy bodies, where even less is known about how various biomarkers interact. Indeed, the availability of rich biomarker data across a range of neurodegenerative disorders would enable more accurate pathology-based classification of such conditions (as opposed to the current predominantly clinical classifications). We further hypothesize that building dynamic network biomarkers and pathway crosstalk reference maps using the combined power of several protein/gene-level knowledge priors could accelerate discovery of disease-specific mechanisms and novel drug targets by enrichment with patient specific genetic information. Application of this methodology to large public AD datasets is needed to test our hypotheses and refine the methods. Subsequent replication in independent datasets and population studies as well as functional validation of mechanisms in laboratory models will be the next steps. Ultimately, it is our hope that such novel methods may yield further insights into both diseasemore »
- Authors:
-
- North Carolina State Univ., Raleigh, NC (United States). Dept. of Computer Science; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division
- Stanford Univ., CA (United States). School of Medicine
- North Carolina State Univ., Raleigh, NC (United States). Dept. of Computer Science
- Duke Univ., Durham, NC (United States). Dept. of Psychiatry; Duke Univ., Durham, NC (United States). Duke Inst. for Brain Sciences
- North Carolina State Univ., Raleigh, NC (United States). Dept. of Computer Science; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
- OSTI Identifier:
- 1629468
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Frontiers in aging neuroscience
- Additional Journal Information:
- Journal Volume: 9; Journal ID: ISSN 1663-4365
- Publisher:
- Frontiers
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 60 APPLIED LIFE SCIENCES; Alzheimer’s disease; pathways; crosstalk; SNP data; bioinformatics; biomarker
Citation Formats
Padmanabhan, Kanchana, Shpanskaya, Katie, Bello, Gonzalo, Doraiswamy, P. Murali, and Samatova, Nagiza F. Toward Personalized Network Biomarkers in Alzheimer's Disease: Computing Individualized Genomic and Protein Crosstalk Maps. United States: N. p., 2017.
Web. doi:10.3389/fnagi.2017.00315.
Padmanabhan, Kanchana, Shpanskaya, Katie, Bello, Gonzalo, Doraiswamy, P. Murali, & Samatova, Nagiza F. Toward Personalized Network Biomarkers in Alzheimer's Disease: Computing Individualized Genomic and Protein Crosstalk Maps. United States. https://doi.org/10.3389/fnagi.2017.00315
Padmanabhan, Kanchana, Shpanskaya, Katie, Bello, Gonzalo, Doraiswamy, P. Murali, and Samatova, Nagiza F. Tue .
"Toward Personalized Network Biomarkers in Alzheimer's Disease: Computing Individualized Genomic and Protein Crosstalk Maps". United States. https://doi.org/10.3389/fnagi.2017.00315. https://www.osti.gov/servlets/purl/1629468.
@article{osti_1629468,
title = {Toward Personalized Network Biomarkers in Alzheimer's Disease: Computing Individualized Genomic and Protein Crosstalk Maps},
author = {Padmanabhan, Kanchana and Shpanskaya, Katie and Bello, Gonzalo and Doraiswamy, P. Murali and Samatova, Nagiza F.},
abstractNote = {We call for the AD field to move beyond discrete biomarkers and utilize the full power of informatics and big data approaches to build and test personalized markers at a pathway and network level. While we have chosen AD as an example, the issues we propose are also highly relevant to other neurodegenerative disorders, such as vascular dementia or dementia with Lewy bodies, where even less is known about how various biomarkers interact. Indeed, the availability of rich biomarker data across a range of neurodegenerative disorders would enable more accurate pathology-based classification of such conditions (as opposed to the current predominantly clinical classifications). We further hypothesize that building dynamic network biomarkers and pathway crosstalk reference maps using the combined power of several protein/gene-level knowledge priors could accelerate discovery of disease-specific mechanisms and novel drug targets by enrichment with patient specific genetic information. Application of this methodology to large public AD datasets is needed to test our hypotheses and refine the methods. Subsequent replication in independent datasets and population studies as well as functional validation of mechanisms in laboratory models will be the next steps. Ultimately, it is our hope that such novel methods may yield further insights into both disease mechanisms as well as novel targets for biomarker development and drug discovery.},
doi = {10.3389/fnagi.2017.00315},
journal = {Frontiers in aging neuroscience},
number = ,
volume = 9,
place = {United States},
year = {Tue Sep 26 00:00:00 EDT 2017},
month = {Tue Sep 26 00:00:00 EDT 2017}
}
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Works referencing / citing this record:
Uncovering Biologically Coherent Peripheral Signatures of Health and Risk for Alzheimer’s Disease in the Aging Brain
journal, November 2018
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