<table class="infobox infobox-cell">
<tr>
<th class="infobox-header" colspan="2">iPSC-Derived Microglia</th>
</tr>
<tr>
<td class="label">Taxonomy</td>
<td>ID</td>
</tr>
<tr>
<td class="label">Cell Ontology (CL)</td>
<td>[CL:0000129](https://www.ebi.ac.uk/ols4/ontologies/cl/classes/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FCL_0000129)</td>
</tr>
<tr>
<td class="label">Database</td>
<td>ID</td>
</tr>
<tr>
<td class="label">Cell Ontology</td>
<td>[CL:0000129](https://www.ebi.ac.uk/ols4/ontologies/cl/classes/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FCL_0000129)</td>
</tr>
<tr>
<td class="label">Marker</td>
<td>Expression</td>
</tr>
<tr>
<td class="label">TMEM119</td>
<td>High</td>
</tr>
<tr>
<td class="label">P2RY12</td>
<td>High</td>
</tr>
<tr>
<td class="label">CX3CR1</td>
<td>High</td>
</tr>
<tr>
<td class="label">CD11b (ITGAM)</td>
<td>High</td>
</tr>
<tr>
<td class="label">CD45 (PTPRC)</td>
<td>Variable</td>
</tr>
<tr>
<td class="label">CD68</td>
<td>Inducible</td>
</tr>
<tr>
<td class="label">Iba1 (AIF1)</td>
<td>High</td>
</tr>
<tr>
<td class="label">TREM2</td>
<td>Variable</td>
</tr>
<tr>
<td class="label">Cluster</td>
<td>Marker Genes</td>
</tr>
<tr>
<td class="label">Homeostatic</td>
<td>CX3CR1, P2RY12, TMEM119</td>
</tr>
<tr>
<td class="label">Inflammatory</td>
<td>IL1B, CCL2, TNF<
<table class="infobox infobox-cell">
<tr>
<th class="infobox-header" colspan="2">iPSC-Derived Microglia</th>
</tr>
<tr>
<td class="label">Taxonomy</td>
<td>ID</td>
</tr>
<tr>
<td class="label">Cell Ontology (CL)</td>
<td>[CL:0000129](https://www.ebi.ac.uk/ols4/ontologies/cl/classes/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FCL_0000129)</td>
</tr>
<tr>
<td class="label">Database</td>
<td>ID</td>
</tr>
<tr>
<td class="label">Cell Ontology</td>
<td>[CL:0000129](https://www.ebi.ac.uk/ols4/ontologies/cl/classes/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FCL_0000129)</td>
</tr>
<tr>
<td class="label">Marker</td>
<td>Expression</td>
</tr>
<tr>
<td class="label">TMEM119</td>
<td>High</td>
</tr>
<tr>
<td class="label">P2RY12</td>
<td>High</td>
</tr>
<tr>
<td class="label">CX3CR1</td>
<td>High</td>
</tr>
<tr>
<td class="label">CD11b (ITGAM)</td>
<td>High</td>
</tr>
<tr>
<td class="label">CD45 (PTPRC)</td>
<td>Variable</td>
</tr>
<tr>
<td class="label">CD68</td>
<td>Inducible</td>
</tr>
<tr>
<td class="label">Iba1 (AIF1)</td>
<td>High</td>
</tr>
<tr>
<td class="label">TREM2</td>
<td>Variable</td>
</tr>
<tr>
<td class="label">Cluster</td>
<td>Marker Genes</td>
</tr>
<tr>
<td class="label">Homeostatic</td>
<td>CX3CR1, P2RY12, TMEM119</td>
</tr>
<tr>
<td class="label">Inflammatory</td>
<td>IL1B, CCL2, TNF</td>
</tr>
<tr>
<td class="label">Disease-Associated</td>
<td>APOE, TREM2, CLEC7A</td>
</tr>
<tr>
<td class="label">Phagocytic</td>
<td>CD68, LPL, CST3</td>
</tr>
<tr>
<td class="label">Target</td>
<td>Compound Class</td>
</tr>
<tr>
<td class="label">Inflammation</td>
<td>NSAIDs, kinase inhibitors</td>
</tr>
<tr>
<td class="label">Phagocytosis</td>
<td>Complement modulators</td>
</tr>
<tr>
<td class="label">Metabolism</td>
<td>Lipid regulators</td>
</tr>
<tr>
<td class="label">Mitochondrial</td>
<td>Antioxidants, mitophagy inducers</td>
</tr>
<tr>
<td class="label">Parameter</td>
<td>Target Range</td>
</tr>
<tr>
<td class="label">Viability</td>
<td>>90%</td>
</tr>
<tr>
<td class="label">Purity</td>
<td>>95% CD11b+</td>
</tr>
<tr>
<td class="label">Maturation</td>
<td>TMEM119+, P2RY12+</td>
</tr>
<tr>
<td class="label">Function</td>
<td>Phagocytosis positive</td>
</tr>
<tr>
<td class="label">Sterility</td>
<td>No contamination</td>
</tr>
<tr>
<td class="label">System</td>
<td>Applications</td>
</tr>
<tr>
<td class="label">Brain organoids</td>
<td>Development, disease modeling</td>
</tr>
<tr>
<td class="label">Assembloids</td>
<td>Circuit formation, connectivity</td>
</tr>
<tr>
<td class="label">Microfluidic chips</td>
<td>BBB modeling, drug transport</td>
</tr>
<tr>
<td class="label">3D scaffolds</td>
<td>Tissue engineering</td>
</tr>
</table>
Induced pluripotent stem cell (iPSC)-derived microglia represent a revolutionary breakthrough in neurodegenerative disease research, providing human cellular models that faithfully recapitulate microglial biology in health and disease. These cells are generated through directed differentiation of patient-derived or gene-edited iPSCs into microglia-like cells, offering unprecedented opportunities to study microglial pathophysiology, perform drug screening, and develop personalized therapeutic approaches. The ability to derive microglia from individuals with specific genetic backgrounds—including Alzheimer's disease (AD) patients carrying APOE4 alleles or Parkinson's disease (PD) patients with LRRK2 mutations—has transformed our understanding of how genetic risk factors influence microglial function and contribute to neurodegeneration. [@douvaras2017]
iPSC-derived microglia have emerged as essential tools for addressing fundamental questions about neuroinflammation that cannot be answered using rodent models alone. Human microglia exhibit distinct transcriptional signatures and disease-specific phenotypes that differ substantially from their murine counterparts. By generating microglia from patients with neurodegenerative diseases, researchers can now investigate disease mechanisms in a human genetic context, identify novel therapeutic targets, and screen potential drugs for efficacy in patient-specific cellular models. This approach represents a paradigm shift from traditional drug discovery methods toward precision medicine strategies that account for individual genetic variation. [@haenseler2017]
The development of robust differentiation protocols has enabled the scalable production of microglia-like cells from multiple iPSC lines, making it feasible to conduct comprehensive studies comparing microglia from different disease states and genetic backgrounds. These advances have particular relevance for understanding the role of microglia in Alzheimer's disease, where the APOE4 allele represents the strongest genetic risk factor for late-onset disease, and in Parkinson's disease, where microglial activation contributes to disease progression. The integration of iPSC-derived microglia with brain organoids and other advanced culture systems has further enhanced their utility for modeling complex neuroimmune interactions that underlie neurodegenerative disease pathogenesis. [@mcquade2020]
iPSC-derived microglia are microglia generated from induced pluripotent stem cells (iPSCs), providing a human cellular model for studying microglial biology, neuroimmune interactions, and therapeutic drug screening. These cells offer significant advantages over immortalized cell lines and rodent primary microglia, enabling research into disease-specific microglial phenotypes and personalized medicine approaches. The ability to derive microglia from patients with specific genetic backgrounds—including APOE4 allele carriers for Alzheimer's disease or LRRK2 mutation carriers for Parkinson's disease—has transformed our understanding of how genetic risk factors influence microglial function. [@douvaras2017]
iPSC-derived microglia recapitulate many key features of primary human microglia, including: [@haenseler2017]
<!-- multi-taxonomy-enrichment -->
The most common approach involves:
An alternative approach uses transcription factor-mediated conversion:
Modern Good Manufacturing Practice (GMP)-compatible methods:
RNA-seq analyses show iPSC-microglia cluster with primary human microglia:
iPSC-microglia from AD patients reveal:
PD iPSC-microglia demonstrate:
ALS patient-derived microglia:
The APOE4 allele represents the strongest genetic risk factor for late-onset Alzheimer's disease. iPSC-derived microglia from APOE4 carriers demonstrate profound molecular and cellular alterations that recapitulate disease phenotypes. [@lin2018]
Lipid Metabolism Impairment: APOE4 microglia exhibit defective cholesterol efflux and lipid droplet accumulation. The APOE4 protein adopts a domain interaction phenotype that reduces its lipid-binding capacity, leading to intracellular lipid accumulation and foam cell formation. [@zhang2022]
Inflammatory Response Amplification: APOE4 microglia show elevated baseline inflammation with increased expression of pro-inflammatory cytokines including IL-1β, IL-6, and TNF-α. This hyper-inflammatory state contributes to chronic neuroinflammation and neuronal dysfunction. [@brown2021]
Synaptic Pruning Dysregulation: APOE4 microglia demonstrate enhanced synaptic elimination through complement-mediated mechanisms. Increased C1q and C3 expression leads to excessive tagging of synapses for phagocytosis, contributing to synaptic loss in AD. [@hasselmann2021]
iPSC-derived microglia facilitate the spread of tau pathology through several mechanisms: [@taylor2021]
iPSC-microglia from Parkinson's disease patients show impaired handling of α-synuclein: [@schildt2022]
AD patient-derived iPSC-microglia exhibit mitochondrial defects: [@gomez2020]
Single-cell RNA sequencing has revealed substantial heterogeneity in iPSC-derived microglia: [@van2020]
iPSC-microglia integration into brain organoids provides sophisticated disease modeling: [@mcquade2020]
Microfluidic chips enable precise control of microenvironment:
Recent CRISPR screens have identified novel microglial therapeutic targets: [@liu2023]
iPSC-microglia enable phenotypic drug screening:
iPSC-derived microglia recapitulate developmental functions: [@martinez2022]
iPSC-microglia enable human-specific studies:
Patient-specific iPSC-microglia offer therapeutic potential:
HLA-typed iPSC lines enable "off-the-shelf" therapies:
iPSC-microglia enable high-throughput screening:
Autologous iPSC-derived microglia transplantation:
iPSC-microglia in advanced culture models:
The combination of iPSC technology with CRISPR-Cas9 gene editing has opened new avenues for mechanistic studies:
Emerging bioprinting technologies enable precise spatial patterning of microglia within brain-like structures:
iPSC-derived microglia hold promise for clinical applications:
The following diagram shows the key molecular relationships involving iPSC-Derived Microglia discovered through SciDEX knowledge graph analysis: