Transcriptomic Analysis of Postmortem Human Brains during Neurodegeneration at Single-Cell Resolution

Identification: Tsai, Li-Huei


Description

Transcriptomic Analysis of Postmortem Human Brains during Neurodegeneration at Single-Cell Resolution
 
Hansruedi Mathys1,2, Shahin Mohammadi3,4, Jose Davila Velderrain3,4, Fan Gao1,2, Zhuyu Peng1,2, Thorvald Andreassen5, David A. Bennett6, Manolis Kellis3,4, and Li-Huei Tsai1,2,3
1Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; 2Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; 3Broad Institute of MIT and Harvard, Cambridge, MA, USA; 4MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA; 5McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; 6Rush Alzheimer Disease Center, Rush University Medical Center, Chicago, IL, USA
 
Transcriptomic analyses of human postmortem Alzheimer's disease (AD) brains have revealed global changes in gene expression patterns that are characterized by the downregulation of genes associated with synaptic function, learning and memory, and the upregulation of adaptive as well as innate immune response genes. However, since the brain is a complex system built from many different functionally specialized cell types, ensemble-based approaches measuring gene expression from bulk populations of cells can only report population averages that may not reflect the responses of individual cells. Moreover, during neurodegeneration, cell type composition changes over time which further confounds the analysis and interpretation of transcriptional changes of various cell types.  Recent advances in high-throughput single-cell RNA sequencing technology allow us to determine how the different cell types and their subclasses in the brain are affected by AD. We previously conducted single-cell RNA-sequencing to determine the phenotypic heterogeneity of microglia during the progression of neurodegeneration in a mouse model. In this model we identified multiple disease stage-specific microglia cell states that are not present in the healthy brain. Specifically, we identified two molecularly distinct reactive microglia phenotypes that are typified by modules of co- regulated type I and type II interferon response genes, respectively.  Currently, we are conducting massive single nucleus profiling of postmortem human prefrontal cortex samples with low vs high amyloid pathology from the ROS-MAP cohort.  We have identified human brain cell types that exhibit pathology-, cognitive function- and gender-specific transcriptomic signatures.  These data provide unprecedented insight into cellular networks most vulnerable to the presence of AD pathology.

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