Systems neuroimmunology: a review of multiomics methodologies to characterize neuroimmunological interactions in spinal and cranial diseases

Neuroimmunology plays a critical role in our understanding of the pathophysiological processes that underlie a variety of diseases treated by neurosurgeons, including degenerative disc disease (DDD), glioblastoma (GBM), aneurysmal subarachnoid hemorrhage (aSAH), and others. Compared with traditional methods in neuroimmunology, which study one pathway or gene at a time, emerging multiomics methodologies allow for holistic interrogation of multiple immune signaling pathways to test hypotheses and the effects of therapeutics at a systems level. In this review, the authors summarize key concepts for gathering and analyzing multiomics data so that neurosurgeons can contribute to the emerging field of systems neuroimmunology. Additionally, they describe 3 use cases, based on original research published by their group and others, that utilize transcriptomic, metabolomic, and proteomic analyses to study immune-signaling pathways in DDD, aSAH, and GBM. Through these use cases, techniques for performing machine learning and network-based analyses to generate new clinical insights from multiomics data are shared. The authors hope that neurosurgeons might use this review as a summary of common tools and principles in systems immunology to better engage in creating the immunotherapies of tomorrow.

Automated summary

Neuroimmunology plays a critical role in neurosurgical diseases, and emerging multiomics methods provide new ways to study immune signaling pathways. This review summarizes methods for gathering and analyzing multiomics data and shares use cases that utilize machine learning and network analysis in clinical research.