bioRxivImmunologyPreprint
Somatic mutations reveal the ontogeny of human microglia
Julia A. BelkiD, Yaowen ZhangiD, Quanming ShiiD, Lisa Ma, Raja Sab Kalluru, Alejandro Medina EncisoiD, Emily E. ReillyiD, Jacob WeissiD, Rui LiiD, Anna E. EastmaniD, Nicole L. Womack-Gambrel, Debasmita PauliD, Arnav ChakravarthyiD, Syed Abbas BukhariiD, Dipabarna BhattacharyaiD, Suyash Raj, Daniel J. RichardiD, Simone BrioschiiD, Matthew R. ChrostekiD, Daniel C. NachuniD, Christopher Maximilian ArendsiD, Jayakrishnan GopakumariD, Isak W. TengesdaliD, Ademar Bynum, Shaneice Renee MitchelliD, , Siddhartha JaiswaliD
Abstract
Microglia are the resident hematopoietic cells of the central nervous system1. In mice, microglia seed the brain during embryogenesis and can be maintained throughout life with minimal input from adult hematopoiesis2-4. The origins of human microglia are less clear, but recent evidence suggests that marrow-derived cells may be able to supplement the human microglial pool in certain individuals5,6. Here, to investigate the ontogeny of human microglia, we develop a method that uses the collection of accumulated somatic mutations which uniquely labels each clone of cells to track the infiltration of marrow-derived cells into the human brain. Applying this method to 20 aged individuals, we find evidence of an influx of marrow-derived cells into the brain in all examined individuals. Single cell analysis, including single cell lineage tracing using mitochondrial DNA variants, demonstrates that these infiltrating cells are nearly identical to microglia and can comprise a large fraction of the microglial pool. Analysis of large-scale sequencing cohorts demonstrates a protective association between most types of clonal hematopoiesis and Alzheimers disease. In sum, this work uncovers a widespread influx of myeloid cells into the healthy human brain which serves to reinforce the pool of human microglia and becomes common with aging.
- organism: human
- assay: whole-genome sequencing
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 3
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