Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease.
Title | Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease. |
Publication Type | Journal Article |
Year of Publication | 2013 |
Authors | Zhang, B, Gaiteri, C, Bodea, L-G, Wang, Z, McElwee, J, Podtelezhnikov, AA, Zhang, C, Xie, T, Tran, L, Dobrin, R, Fluder, E, Clurman, B, Melquist, S, Narayanan, M, Suver, C, Shah, H, Mahajan, M, Gillis, T, Mysore, J, MacDonald, ME, Lamb, JR, Bennett, DA, Molony, C, Stone, DJ, Gudnason, V, Myers, AJ, Schadt, EE, Neumann, H, Zhu, J, Emilsson, V |
Journal | Cell |
Volume | 153 |
Issue | 3 |
Pagination | 707-20 |
Date Published | 2013 Apr 25 |
ISSN | 1097-4172 |
Keywords | Adaptor Proteins, Signal Transducing, Alzheimer Disease, Animals, Bayes Theorem, Brain, Gene Regulatory Networks, Humans, Membrane Proteins, Mice, Microglia |
Abstract | The genetics of complex disease produce alterations in the molecular interactions of cellular pathways whose collective effect may become clear through the organized structure of molecular networks. To characterize molecular systems associated with late-onset Alzheimer's disease (LOAD), we constructed gene-regulatory networks in 1,647 postmortem brain tissues from LOAD patients and nondemented subjects, and we demonstrate that LOAD reconfigures specific portions of the molecular interaction structure. Through an integrative network-based approach, we rank-ordered these network structures for relevance to LOAD pathology, highlighting an immune- and microglia-specific module that is dominated by genes involved in pathogen phagocytosis, contains TYROBP as a key regulator, and is upregulated in LOAD. Mouse microglia cells overexpressing intact or truncated TYROBP revealed expression changes that significantly overlapped the human brain TYROBP network. Thus the causal network structure is a useful predictor of response to gene perturbations and presents a framework to test models of disease mechanisms underlying LOAD. |
DOI | 10.1016/j.cell.2013.03.030 |
Alternate Journal | Cell |
PubMed ID | 23622250 |
PubMed Central ID | PMC3677161 |
Grant List | R01 AG17917 / AG / NIA NIH HHS / United States K08 AG034290 / AG / NIA NIH HHS / United States NS032765 / NS / NINDS NIH HHS / United States R01 AG030146 / AG / NIA NIH HHS / United States R01 AG017917 / AG / NIA NIH HHS / United States P30 AG10161 / AG / NIA NIH HHS / United States R01 AG11101 / AG / NIA NIH HHS / United States P30 AG010161 / AG / NIA NIH HHS / United States R01 AG15819 / AG / NIA NIH HHS / United States R01 MH097276 / MH / NIMH NIH HHS / United States R01 AG034504 / AG / NIA NIH HHS / United States R01 NS032765 / NS / NINDS NIH HHS / United States R01 AG011101 / AG / NIA NIH HHS / United States R01 AG015819 / AG / NIA NIH HHS / United States |