| Literature DB >> 31391546 |
Jay Penney1, William T Ralvenius1, Li-Huei Tsai2.
Abstract
Alzheimer's disease is a devastating neurodegenerative disorder with no cure. Countless promising therapeutics have shown efficacy in rodent Alzheimer's disease models yet failed to benefit human patients. While hope remains that earlier intervention with existing therapeutics will improve outcomes, it is becoming increasingly clear that new approaches to understand and combat the pathophysiology of Alzheimer's disease are needed. Human induced pluripotent stem cell (iPSC) technologies have changed the face of preclinical research and iPSC-derived cell types are being utilized to study an array of human conditions, including neurodegenerative disease. All major brain cell types can now be differentiated from iPSCs, while increasingly complex co-culture systems are being developed to facilitate neuroscience research. Many cellular functions perturbed in Alzheimer's disease can be recapitulated using iPSC-derived cells in vitro, and co-culture platforms are beginning to yield insights into the complex interactions that occur between brain cell types during neurodegeneration. Further, iPSC-based systems and genome editing tools will be critical in understanding the roles of the numerous new genes and mutations found to modify Alzheimer's disease risk in the past decade. While still in their relative infancy, these developing iPSC-based technologies hold considerable promise to push forward efforts to combat Alzheimer's disease and other neurodegenerative disorders.Entities:
Mesh:
Year: 2019 PMID: 31391546 PMCID: PMC6906186 DOI: 10.1038/s41380-019-0468-3
Source DB: PubMed Journal: Mol Psychiatry ISSN: 1359-4184 Impact factor: 15.992
Fig. 1Brain cell types in Alzheimer’s disease. A summary of the major human brain cell types and the alterations they exhibit in AD
Alzheimer’s disease risk genes
| Human Brain FPKM | ||||||||
|---|---|---|---|---|---|---|---|---|
| Gene | Mutation type | Molecular function | % identity | Neurons | Astrocytes | Microglia | Oligodendrocytes | Endothelial |
| ABCA7 | Both | ATP-binding cassette transporter | 76.4 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 |
| ACE | Non-coding | Metalloprotease | 82.8 | 0.1 | 0.1 | 0.1 | 0.1 | 0.4 |
| ADAM10 | Non-coding | Metalloprotease | 95.9 | 9.1 | 7.4 | 22.6 | 15.6 | 6.3 |
| ADAMTS1 | Non-coding | Metalloprotease | 80.8 | 3.5 | 0.9 | 0.1 | 9.7 | 3.1 |
| APOE | Coding | Lipoprotein | 71.7 | 0.5 | 3.3 | 0.5 | 0.2 | 0.1 |
| BIN1 | Non-coding | Endocytic adaptor | 95.6 | 1.2 | 0.9 | 6.9 | 6.7 | 1.7 |
| CASS4 | Non-coding | Tyrosine kinase docking | 63.1 | 0.3 | 0.2 | 8.5 | 0.3 | 1.5 |
| CD2AP | Non-coding | Scaffolding, actin cytoskeleton | 86.5 | 1.4 | 1.7 | 7.9 | 1.4 | 4 |
| CD33 | Non-coding | Surface receptor | 39.0a | 0.1 | 0.2 | 9.5 | 1 | 0.1 |
| CELF1 | Non-coding | RNA-binding protein | 99.6 | 7.9 | 6.3 | 9.5 | 4.9 | 3.1 |
| CLU | Non-coding | Extracellular chaperone | 76.6 | 19.3 | 384.2 | 0.5 | 9.6 | 15.6 |
| CR1 | Non-coding | Surface receptor | 48.9 | 0.1 | 0.1 | 0.2 | 0.1 | 0.1 |
| EPHA1 | Non-coding | Receptor tyrosine kinase | 87.2 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 |
| FERMT2 | Non-coding | Extracellular matrix scaffolding | 98.2 | 3.3 | 43.2 | 2.9 | 6.9 | 6.8 |
| HLA-DRB1 | Non-coding | Antigen presentation | 58.9a | 0.6 | 1.1 | 27.1 | 3 | 0.7 |
| INPP5D | Non-coding | Phosphatidylinositol phosphatase | 87.5 | 0.1 | 0.5 | 18.9 | 1.4 | 2.3 |
| IQCK | Non-coding | Calmodulin-binding domain | 71.8 | 4.7 | 20.8 | 0.2 | 6.4 | 0.6 |
| MEF2C | Non-coding | Transcription factor | 93.5 | 51.9 | 3.8 | 44 | 3.9 | 4.1 |
| MS4A6A | Non-coding | Transmembrane protein | 53.7a | 0.1 | 0.7 | 24 | 5.2 | 0.1 |
| PICALM | Non-coding | Endocytosis, clathrin assembly | 96.5 | 12.3 | 14.6 | 65.6 | 37.3 | 20.5 |
| PTK2B | Non-coding | Tyrosine kinase | 95.3 | 2 | 0.9 | 1.3 | 0.4 | 0.8 |
| SLC24A4 | Non-coding | Na+/K+/Ca2+ exchanger | 94.4 | 1.9 | 0.2 | 0.5 | 0.2 | 0.1 |
| SORL1 | Non-coding | Endocytic receptor/sorting | 93.2 | 9.9 | 17.9 | 78.9 | 6.7 | 0.8 |
| SPI1 | Non-coding | Transcription factor | 87.9 | 0.1 | 0.1 | 0.3 | 0.1 | 0.1 |
| TREM2 | Coding | Surface receptor | 50.6 | 0.1 | 0.4 | 27.1 | 1.4 | 0.4 |
| TXNDC3 | Non-coding | Thioredoxin domain | 63.5 | 0.1 | 0.1 | 0.2 | 0.2 | 0.1 |
| WWOX | Non-coding | Oxidoreductase | 93.7 | 4.6 | 5.1 | 1.1 | 1.8 | 0.8 |
| ZCWPW1 | Non-coding | Zinc finger domain | 60 | 0.2 | 0.5 | 0.5 | 0.7 | 0.1 |
FAD causative genes are shown in bold, SAD risk genes in normal font [20–22, 29–32, 34, 35]. Percent amino acid identity of mouse to human orthologue is indicated (ensembl.org [46])
aIndicates multiple orthologues. Fragments Per Kilobase of transcript per Million mapped reads (FPKM) of AD-linked genes from purified human brain cell types are also indicated (brainrnaseq.org [226])
Fig. 2Human iPSC differentiation to brain cell types. Somatic cells from patients or healthy individuals can be reprogrammed to iPSCs and subsequently differentiated into all major brain cell types for in vitro studies. Such studies can examine cellular functions as well as how they are impacted by AD hallmark pathologies or AD-linked mutations. Genome editing techniques can be used to introduce or correct AD-linked mutations to examine phenotypes in isogenic backgrounds. 3D and co-culture models allow for examination of interactions occurring between cell types and sub-types to better model processes occurring in vivo. These and developing techniques hold promise for better understanding the relevant pathomechanisms underlying AD, and will hopefully facilitate development of effective therapeutics to combat dementia
Select important AD studies utilizing iPSC-derived brain cells
| Model | Reference | Mutation(s) | Significance |
|---|---|---|---|
| Neurons | Israel et al. [ | sAD, APPDp | Early study of iPSC modeling; elevated Aβ, p-tau, endosome accumulation in AD neurons |
| Shi et al. [ | Down syndrome | Elevated Aβ secretion, Aβ aggregation, tau phosphorylation in DS neurons | |
| Wang et al. [ | Isogenic APOE3, APOE4 and APOE null | Elevated Aβ and p-tau levels, GABAergic neuron degeneration in APOE4 neurons; identification of small molecule APOE4 structure corrector | |
| Astrocytes | Oksanen et al. [ | Isogenic PSEN1ΔE9 | Increased Aβ production and oxidative stress, altered cytokine release and Ca2+ homeostasis, reduced neuronal support function in PSEN1 astrocytes |
| Lin et al. [ | Isogenic APOE3 and APOE4 | Impaired Aβ clearance and increased cholesterol content of APOE4 astrocytes | |
| Microglia | Lin et al. [ | Isogenic APOE3 and APOE4 | Reduced Aβ uptake from media and fAD organoids, reduced morphological complexity of APOE4 microglia |
| 3D cultures | Choi et al. [ | Overexpression of APPK670N/M671L, APPV717I, PSEN1ΔE9 | Robust deposition of Aβ and filamentous tau in vitro; demonstrates that Aβ can cause tau deposition |
| Park et al. [ | Overexpression of APPK670N/M671L, APPV717I, PSEN1ΔE9 | Triculture model system incorporating iPSC-derived neurons, astrocytes, and immortalized human microglia; recapitulates AD phenotypes, microglial recruitment, and neuroinflammation |