Incidence of microvascular dysfunction is increased in hyperlipidemic mice, reducing cerebral blood flow and impairing remote memory.
The development of cognitive dysfunction is not necessarily associated with diet-induced obesity. We hypothesized that cognitive dysfunction might require additional vascular damage, for example, in atherosclerotic mice. We induced atherosclerosis in male C57BL/6N mice by injecting AAV-PCSK9DY (2x1011 VG) and feeding them a cholesterol-rich Western diet. After 3 months, mice were examined for cognition using Barnes maze procedure and for cerebral blood flow. Cerebral vascular morphology was examined by immunehistology. In AAV-PCSK9DY-treated mice, plaque burden, plasma cholesterol, and triglycerides are elevated. RNAseq analyses followed by KEGG annotation show increased expression of genes linked to inflammatory processes in the aortas of these mice. In AAV-PCSK9DY-treated mice learning was delayed and long-term memory impaired. Blood flow was reduced in the cingulate cortex (-17%), caudate putamen (-15%), and hippocampus (-10%). Immunohistological studies also show an increased incidence of string vessels and pericytes (CD31/Col IV staining) in the hippocampus accompanied by patchy blood-brain barrier leaks (IgG staining) and increased macrophage infiltrations (CD68 staining). We conclude that the hyperlipidemic PCSK9DY mouse model can serve as an appropriate approach to induce microvascular dysfunction that leads to reduced blood flow in the hippocampus, which could explain the cognitive dysfunction in these mice. Overall design: RNA sequencing (RNAseq) analysis was performed in the descending aorta. Aortic tissue was isolated, trimmed from fat, and snap frozen in liquid nitrogen. Total RNA was isolated with the RNA Mini Kit from Bio& SELL (Nuremberg, Germany) combined with on-column DNase digestion (DNase-Free DNase Set, Qiagen) to avoid genomic DNA contamination. RNA and library preparation integrity were verified with LabChip Gx Touch 24 (Perkin Elmer). As input for VAHTS Stranded mRNA-seq Library preparation, 500 µg of total RNA was used following the manufacturer's protocol (Vazyme). Sequencing was performed on a NextSeq2000 instrument (Illumina) with 1x72-bp single-end setup. The resulting raw reads were assessed for quality, adapter content, and duplication rates with FastQC (RRID:SCR_014583) (Andrews Simon: Andrews Simon: FastQC: a quality control tool for high-throughput sequence data. Available online at http://www.bioinformatics.babraham.ac.uk/projects/fastqc). Trimmomatic version 0.39 was employed to trim reads after a quality drop below a mean of Q15 in a window of 5 nucleotides and keeping only filtered reads longer than 15 nucleotides (20). Reads were aligned versus Ensembl mouse genome version mm10 (Ensembl release 101) with STAR 2.7.10a (21). Aligned reads were filtered to remove duplicates with Picard 2.27.4 (Picard: A set of tools in Java for working with next-generation sequencing data in the BAM format), multi-mapping, ribosomal, or mitochondrial reads. Gene counts were established with featureCounts 2.0.4 by aggregating reads overlapping exons on the correct strand, excluding those overlapping multiple genes (22). The raw count matrix was normalized with DESeq2 version 1.36.0 (23). Contrasts were created with DESeq2 based on the raw count matrix. Genes were classified as significantly differentially expressed at average count > 5, multiple testing adjusted p-value < 0.05, and -0.585 < log2FC > 0.585. The Ensemble annotation was enriched with UniProt data (Activities at the Universal Protein Resource (UniProt))