There is a critical need to define the state and predict the behavior of human brain cells in health and disease. The number of different cell types in the CNS remains undefined, and despite a demographically ordained wave of neurodegenerative diseases, not a single disease-modifying therapy exists. Our knowledge of the CNS and the foundation for intervening rationally in disease would be dramatically advanced by generating quantitative molecular phenotypes essentially cell signatures of human neurons, astrocytes and oligodendrocytes from healthy people and from patients with motor neuron disease, Huntington's disease, and Parkinson's disease. The CNS is so unique that studying non-neuronal cells does not provide much assistance. Despite this desperate need, the inaccessibility of human brain cells meant studying them would have been impossible until the recent discovery of cellular reprogramming and induced pluripotent stem cell technology. Here we propose to form the NeuroLINCS consortium to accomplish these goals. We have handpicked the team to bring in critical expertise in iPSC technology, disease modeling, transcriptomics, epigenomics, metabolomics, whole genome sequencing, proteomics, high content, high throughput longitudinal single cell analysis, other cell-based assays, bioinformatics, statistics and computational biology. In addition, we are collaborating with Google to bring in special expertise in machine learning and the integration of signatures across platforms into highly predictive models of responses to perturbagens. Together, we expect to develop cell signatures of an array of human brain cell types under different conditions that should be broadly applicable to the LINCs community. We also anticipate generating innovative software tools and approaches that will make the signature generating process cheaper, faster, and more reliable. Besides the unique combination of expertise represented within NeuroLINCS, another distinguishing feature is the long track record that its members have of collaborating with each other. That collaborative spirit will be expressed in NeuroLINCS through its significant and multifaceted community outreach programs. These will involve specific and detailed plans to make the data and tools that NeuroLINCS generates available to the community, to interact with other LINCS sites, and to prepare for DCIC and the prospect of disseminating knowledge and resources at scale.

Public Health Relevance

The cellular signatures of human neurons we identify can be used to provide insights into the molecular factors that distinguish central neurons from healthy people from those of patients with neurodegenerative diseases such as ALS, SMA, PD and HD. These insights will provide molecular targets that can be used to develop new drugs to block the progression of these diseases which are presently untreatable.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
3U54NS091046-06S1
Application #
10095893
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Swanson-Fischer, Christine R
Project Start
2014-09-30
Project End
2020-06-30
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
6
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California Irvine
Department
Psychiatry
Type
Schools of Medicine
DUNS #
046705849
City
Irvine
State
CA
Country
United States
Zip Code
92617
Nicolas, Aude (see original citation for additional authors) (2018) Genome-wide Analyses Identify KIF5A as a Novel ALS Gene. Neuron 97:1268-1283.e6
Christiansen, Eric M; Yang, Samuel J; Ando, D Michael et al. (2018) In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images. Cell 173:792-803.e19
Keenan, Alexandra B; Jenkins, Sherry L; Jagodnik, Kathleen M et al. (2018) The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations. Cell Syst 6:13-24
Köksal, Ali Sinan; Beck, Kirsten; Cronin, Dylan R et al. (2018) Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data. Cell Rep 24:3607-3618
Pereira, Gavin C; Sanchez, Laura; Schaughency, Paul M et al. (2018) Properties of LINE-1 proteins and repeat element expression in the context of amyotrophic lateral sclerosis. Mob DNA 9:35
Gendron, Tania F; Chew, Jeannie; Stankowski, Jeannette N et al. (2017) Poly(GP) proteins are a useful pharmacodynamic marker for C9ORF72-associated amyotrophic lateral sclerosis. Sci Transl Med 9:
Gendron, Tania F; C9ORF72 Neurofilament Study Group; Daughrity, Lillian M et al. (2017) Phosphorylated neurofilament heavy chain: A biomarker of survival for C9ORF72-associated amyotrophic lateral sclerosis. Ann Neurol 82:139-146
Qu, Ying; Han, Bingchen; Gao, Bowen et al. (2017) Differentiation of Human Induced Pluripotent Stem Cells to Mammary-like Organoids. Stem Cell Reports 8:205-215
Lim, Ryan G; Quan, Chris; Reyes-Ortiz, Andrea M et al. (2017) Huntington's Disease iPSC-Derived Brain Microvascular Endothelial Cells Reveal WNT-Mediated Angiogenic and Blood-Brain Barrier Deficits. Cell Rep 19:1365-1377
Woo, Caroline J; Maier, Verena K; Davey, Roshni et al. (2017) Gene activation of SMN by selective disruption of lncRNA-mediated recruitment of PRC2 for the treatment of spinal muscular atrophy. Proc Natl Acad Sci U S A 114:E1509-E1518

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