In a recent study published in Cell, researchers examined 152,459 microglial transcriptomes from 443 individuals, identifying 12 transcriptional states and their relationship to Alzheimer's disease (AD).
Background
Microglia play crucial roles in brain cells, changing states to control their activity. Various microglial states have been studied in AD, aging, and mouse models. Neuroinflammation, neurodegeneration, and illness are all affected by changing microglial states. Since single-cell techniques for profiling human microglia from postmortem brains are restricted, the contributions of microglia to AD remain unknown.
About the study
In the present study, researchers identified key regulatory networks poised to govern various microglial states in Alzheimer's disease development by combining gene profiles with single-nucleus ATAC-sequencing (snATAC-seq) data.
The researchers tested the potential of transcription factors (TFs) to control microglial states in AD using microglia-like cells derived from stem cells. The transcriptomes of microglial nuclei obtained from postmortem aged brain samples obtained from 217 AD patients and 226 controls from the Religious Orders Study/Rush Memory and Aging Project (ROS/MAP) were analyzed across six brain regions, including the mid-temporal cortical region, prefrontal cortical region (PFC), hippocampus, angular gyrus, thalamus, and entorhinal cortex.
In total, 174,420 immunological cells were produced utilizing known marker genes from one-nucleus ribonucleic acid sequencing (snRNA-seq) datasets of the brain. The clusters were characterized as separate microglial states based on their molecular fingerprints and activities, and these microglial states were compared to a previously published dataset and mouse microglial transcriptional states.
In the PFC, the statistical significance of cell fractional differences between control, early, and late AD individuals was tested, and a correlation analysis was performed between microglial state proportions and multiple pathological variables in the PFC to investigate the association of those states with specific AD-relevant pathology and confounding factors.
Through immunohistochemistry (IHC) and RNAscope in situ hybridization, the researchers experimentally verified the enrichment of important states of transcription in the AD human brain. They also used enrichment analysis to determine the expression of disease-associated microglia (DAM) genes throughout the dataset. The researchers used single-nucleus ATAC-seq (snATAC-seq) data from human postmortem brain tissues from a few individuals in the same cohort to study the upstream regulators that drive various microglial states.
Gene ontology (GO) analysis, co-expression network analysis, and cell proportional analysis were also done. Microglia-like cells (iMGLs) were produced from induced pluripotent stem cells (iPSCs) for pulse-and-chase investigations. The team identified transcription factors (TFs) using motif enrichment in epigenetically determined state peaks and built TF-target regulatory networks.
To deepen knowledge of the relationship between microglial states and AD genetics, the researchers identified one-cell expression QTLs (eQTLs) in microglial cells and performed a transcriptome-wide association study (TWAS) to investigate the links between genetic expression and Alzheimer's disease. In addition, the researchers examined these states and their possible correlations with genetic variations using genome-wide association study (GWAS) statistics. They also investigated the relative proportions of microglia states in AD, emphasizing the need to ascertain disease progression.
Results
The researchers examined 12 microglia transcription states, including lipid-processing, homeostatic, and inflammatory states associated with Alzheimer's disease., including Alzheimer's disease-related lipid-processing, homeostatic, and inflammatory states. There were 1,542 Alzheimer's disease-differentially expressed genes (DEGs) discovered, including illness-stage-specific and microglia-state-specific changes. The researchers showed that ectopic expression of expected homeostatic-state activators induces homeostatic features in human-induced pluripotent stem cell-derived microglia-like cells, but inhibiting inflammation activators prevents inflammatory development.
The authors proposed that state transitioning might be mediated by the transcriptional activities of master regulator transcription factors and presented a paradigm in which these factors' activity could influence various cellular states. The findings indicated that lipid metabolism and inflammation are inextricably related processes that play a vital role in microglia's contribution to Alzheimer's disease pathogenesis. During illness development, inflammatory processes appeared to precede fat regulation in microglial cells, according to the state- and stage-specific differential analyses.
Activated microglia disrupt blood-brain barrier (BBB) function by generating inflammatory substances that cause BBB hyperpermeability in brain disorders. Distinct microglial states were associated with considerable GWAS signals in lupus, ulcerative colitis, and triglycerides but not in various brain diseases.
The genetic influence of AD on gene expression is time-sensitive, implying the necessity for stage-specific therapies. Only three genes, apolipoprotein (APOE), bridging integrator 1 (BIN1), and phosphatidylinositol-binding clathrin assembly protein (PICALM), were both AD-risk and TWAS genes, demonstrating their importance in the course of AD. Epigenome states did not adequately capture the range of microglial transcriptional states in the human brain, as defined by DAM signatures.
Conclusion
Overall, the study findings demonstrated a link between microglial states and pathological and clinical factors, disease phases, and Alzheimer's disease genetics. They offer unparalleled clarity in characterizing transcriptional alterations related to microglial states, which occur in a disease-stage-specific way. This provides an outline for creating neuroinflammation drugs with illness-stage specificity for disease phases, emphasizing the potential usefulness of stage-specific therapies in Alzheimer's disease.