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Research
Kuan-lin Huang
Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York, NY 10029
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5537-5817
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
Multiple genes with genetic variants or expression changes associated with Alzheimer’s disease (AD) have been identified. Altering their expression and activity levels serve as potential therapeutic strategies, yet the cellular implications of such alterations remain largely unknown.
Methods
Cellular dependencies of 105 AD-associated genes, previously identified by genome-wide association studies (GWAS) and gene expression network studies, were evaluated in over 700 cell lines with CRISPR knockout/RNAi knockdown screen data. Expression-driven dependencies were examined within multiple tissue lineages.
Results
Multiple genes showed widespread cell dependencies across tissue lineages, suggesting their inhibition may yield off-target effects. SPI1, MEF2C, GAB2, and ABCC11 were identified as genes of interest since their genetic knockouts specifically affected high-expressing cells of the hematopoietic and lymphoid lineage related to microglia. Other genes exhibiting expression-driven dependencies include ACTG1 in autonomic ganglia and GLS in central nervous system lineages.
Conclusions
Analyses of genetic screen data identified AD-associated genes whose knockout or knockdown selectively affected cell lines of relevant tissue lineages, prioritizing targets for potential AD treatments.
Keywords
Alzheimer's disease, genetic screens, drug targets
Figure 1
Figure 2
Figure 3
Figure 4
This is a list of supplementary files associated with this preprint. Click to download.
- AdditionalFile1.pdf
Additional File 1 File Format: .pdf Title: Full AD-Associated Gene List Utilized in Study Description: The gene names for the 105 AD-associated genes utilized in the study are provided in alphabetical order.
- AdditionalFile2.pdf
Additional File 2 File Format: .pdf Title: GLS in CNS cell lines against DEMETER2 scores Description: GLS was identified in Figure 2B as a gene showing expression-driven dependency in CNS cell lines from RNAi knockdown screen data. The correlation plots of expression-driven dependency is shown for GLS in CNS cell lines against DEMETER2 scores.
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This is a preprint. It has not completed peer review.
Research
Kuan-lin Huang
Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York, NY 10029
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5537-5817
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 04 Jan, 2021
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cognitive Neuroscience
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
Multiple genes with genetic variants or expression changes associated with Alzheimer’s disease (AD) have been identified. Altering their expression and activity levels serve as potential therapeutic strategies, yet the cellular implications of such alterations remain largely unknown.
Methods
Cellular dependencies of 105 AD-associated genes, previously identified by genome-wide association studies (GWAS) and gene expression network studies, were evaluated in over 700 cell lines with CRISPR knockout/RNAi knockdown screen data. Expression-driven dependencies were examined within multiple tissue lineages.
Results
Multiple genes showed widespread cell dependencies across tissue lineages, suggesting their inhibition may yield off-target effects. SPI1, MEF2C, GAB2, and ABCC11 were identified as genes of interest since their genetic knockouts specifically affected high-expressing cells of the hematopoietic and lymphoid lineage related to microglia. Other genes exhibiting expression-driven dependencies include ACTG1 in autonomic ganglia and GLS in central nervous system lineages.
Conclusions
Analyses of genetic screen data identified AD-associated genes whose knockout or knockdown selectively affected cell lines of relevant tissue lineages, prioritizing targets for potential AD treatments.
Figure 1
Figure 2
Figure 3
Figure 4
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