Malaiya, S.; Serra, R.; Cortes-Gutierrez, M.; Wilhelmy, B. E.; Jusuf, E.; Somalinga, M.; Peprah, D.; Nambiar, H.; Kim, K. T.; Saadon, J. R.; Patel, P. D.; Yarmoska, S. K.; Rakovec, M.; Kim, J.; Lei, C.; Panchagnula, S.; Ambrocio, R. E.; Cherney, M.; Ayithan, N.; Fan, X.; Gerzanich, V.; Simard, J. M.; Badjatia, N.; Schwartzbauer, G.; Parikh, G. Y.; Ament, S. A.; Ciryam, P.

Intraventricular hemorrhage (IVH) is a frequent complication of intracerebral hemorrhage (ICH) and subarachnoid hemorrhage (SAH), and is associated with worse outcomes. Treatment options for IVH are limited in their ability to improve long-term functional status. One promising target for treatment is the profound cellular inflammatory response that occurs after injury, but advances have been limited by our incomplete understanding of this phenomenon. We leveraged Recovery After Cerebral Hemorrhage, a prospective, observational study at the University of Maryland, to address this question. We sought to characterize the immune cell populations in the intraventricular cerebrospinal fluid (CSF) after IVH. To do so, we generated the first reported single-nucleusRNA sequencing (snRNA-seq) data on CSF after acute brain injury. We performed 10x Genomics snRNA-seq of nuclei isolated from the CSF of 7 patients (ICH=6, SAH=1), yielding 11,191 high-quality transcriptomes. We identified four major cell populations, which we annotated as neutrophils (53.8%), monocytes (26.1%), lymphocytes (17.8%), and other cells (2.4%) based on the expression of canonical gene markers. Sub-clustering revealed distinct subtypes of neutrophils, monocytes, and lymphocytes that shared features with populations previously described in the systemic circulation. Neutrophils were categorized into nascent, quiescent, and interferon-activated states. The interferon-activated state has not been observed in the central nervous system previously. Monocytes were predominantly of a classical phenotype. Lymphocytes were predominantly T-cells, with the largest populations being naive and central memory CD4+ T-cells. This snRNA-seq data informed the design of a flow cytometry panel that we used to validate the presence of cell subtypes identified by transcriptomics. This analysis demonstrates the feasibility of snRNA-seq approaches to identify previously unexplored pathways and immune cell types that may be relevant to disease. We anticipate that these tools will enable the discovery of new targets to mitigate inflammation-related secondary damage after IVH.