Pharmacologically reversible zonation-dependent endothelial cell transcriptomic changes with neurodegenerative disease associations in the aged brain

The molecular signatures of cells in the brain have been revealed in unprecedented detail, yet the ageing-associated genome-wide expression changes that may contribute to neurovascular dysfunction in neurodegenerative diseases remain elusive. Here, we report zonation-dependent transcriptomic changes in aged mouse brain endothelial cells (ECs), which prominently implicate altered immune/cytokine signaling in ECs of all vascular segments, and functional changes impacting the blood–brain barrier (BBB) and glucose/energy metabolism especially in capillary ECs (capECs). An overrepresentation of Alzheimer disease (AD) GWAS genes is evident among the human orthologs of the differentially expressed genes of aged capECs, while comparative analysis revealed a subset of concordantly downregulated, functionally important genes in human AD brains. Treatment with exenatide, a glucagon-like peptide-1 receptor agonist, strongly reverses aged mouse brain EC transcriptomic changes and BBB leakage, with associated attenuation of microglial priming. We thus revealed transcriptomic alterations underlying brain EC ageing that are complex yet pharmacologically reversible.


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Ho Ko
Aug 5, 2020 For mouse brain cell RNA sequencing, the raw fastq files were aligned by Cell Ranger (v3.0.0, 10X Genomics, US) and converted to count matrix for further processing.
The sequencing data processing were performed with the Seurat (v3.0.1) package and custom scripts in R (v3.5.1). For differential expression analysis, the MAST (v1.8.2) package was used (which was already incorporated in the Seurat package). Figures were generated by the Seurat package, the ggplot2 (3.1.1) package, and custom scripts in R (v3.5.1). For two-photon imaging data processing, the Imaris software (v6.4, Bitplane, Belfast, UK) was used. Immunohistochemistry data was analyzed using the Fiji (ImageJ) software with cell counter plugin (64-bit version based on ImageJ 1.52p).
The raw and processed RNA sequencing data from this study have been deposited in the UCSC Cell Browser ("Aging Brain

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For the Allen Brain Aging, Dementia and TBI dataset, the normalized FPKM data matrix was downloaded from [https://aging.brain-map.org/download/index] alongside subject information.
For the Mayo Clinic AD brain RNA-seq dataset and DEGs, data was downloaded from [http://dx.doi.org/10.7303/syn3163039] alongside subject information. Source data and Supplementary Figs 7b,9b) are provided with this paper.
We used 5 mice per group (young adult, aged and exenatide-treated aged groups) for the the scRNA-seq experiments and 3 mice per group for the imaging experiments (young adult, aged, vehicle-treated and exenatide-treated aged groups, with two batches of experiments done).
For the qPCR and WB experiments, 3 mice for each group (young adult and aged groups) were used for each experiment. For the IHC experiments, 4, 3 and 3 animals for the young adult, aged, and exenatide-treated aged groups were used respectively. No prior sample size calculation was performed. Selection of sample sizes was based on past research experience judging potential biological effects relative to expected variability, typically requiring 3-5 animals per group for the types of experiments carried out.
For sequencing data quality control, genes expressed by fewer than 3 cells were excluded; low quality cells were excluded by the following criteria: 1. lower than 5% or higher than 95% UMI count or gene count, or 2. proportion of mitochondrial genes > 20%. This was a preestablished criteria.
For differential expression analysis, endothelial cells with unstable subtype classification on three independent repeated runs of CellAssign were excluded (1074 out of 12357, 8.7%). This was a pre-established criteria. For WB, we assayed the expression changes of LEF1, SMAD7, MFSD2A and SLC2A1 across age. The antibodies we used worked for LEF1, SMAD7 and MFSD2A, but very broad and possibly non-specific binding bands were noted for the anti-SLC2A1 in our experiment (see Source Data file for uncropped WB images for Fig. 2e, rightmost image), hence only the results of LEF1, SMAD7 and MFSD2A were included in the main figure.
Repeating independent batches of experiments was the major means to ensure reproducibility (i.e. instead of relying on data from one single experiment). The sequencing data presented came from three independent batches of experiments with a total of 5 animal subjects used for each group. The in vivo imaging experiments were carried out in two independent batches. The first batch (with 3 animals per group) was performed to test the therapeutic efficacy of exenatide treatment. During each imaging session, 3 image stacks were taken from each animal within the specified time window (i.e. 15-35 mins post-IV dextran dye injection), thereby serving as replicates of sampling for each animal. In the second batch, additional experiments (also with 3 animals per group) were carried out with identical protocol to verify the therapeutic efficacy of exenatide over saline vehicle. Analysis of data from the different batches of experiments arrived at the same conclusion on the therapeutic efficacy of exenatide treatment.
The consistency of findings hence support the reproducibility of the findings. We confirm all attempts at replication were successful for all the experiments.