bioRxivNeurosciencePreprint
Brain shuttle target expression levels vary by individual, not by brain region, disease, age, or sex
Ana Raquel Santa-MariaiD, Sanjid ShahriariD, Vasanth Chandrasekhar, Emma Luteijn, Robin Horber, Samuel Hornstein, Sasha L. TkacheviD, Tyler M. LevyiD, Ivan V. GregorettiiD, Claire M. Simpson, Majd ArissiD, Vilas MenoniD, Donald E. IngberiD, James R. GormaniD
Abstract
Therapeutics fused to brain shuttles that exploit endogenous receptor-mediated transport at the blood-brain barrier (BBB) offer a promising strategy to deliver large molecule drugs and biologics to the CNS. A fundamental but untested assumption underlying their clinical development is that their endothelial receptor targets are consistently expressed between individuals and between patient populations. Here, we analyzed gene and protein expression of eleven canonical brain shuttle targets in isolated human brain microvascular endothelial cells and brain microvessels from 11 large cohorts, using single-cell and single-nucleus transcriptomics and quantitative proteomics. Expression was remarkably stable between brain regions, sexes, ages, and normal health versus four major neurodegenerative conditions, Alzheimers disease, Parkinsons disease, Huntingtons disease, and amyotrophic lateral sclerosis, with 612 of 631 comparisons (97%) showing no significant difference. Regional heterogeneity of brain shuttle targets previously reported in rodent models was not observed in human tissue, and disease states had minimal impact in all diseases examined. In striking contrast, target abundance differed consistently among individuals in every demographic and clinical group, for all eleven targets and all data modalities. These findings establish individual receptor abundance as a critical and previously uncharacterized variable for brain shuttle translational research, including clinical trial design and patient stratification.
- organism: human
- assay: scRNA-seq
- assay: proteomics
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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