The microglial transcriptome of age-associated deep subcortical white matter lesions suggests a neuroprotective response to blood-brain barrier dysfunction
Age-associated deep-subcortical white matter lesions (DSCL) are an independent risk factor for dementia, displaying high levels of CD68+ microglia. This study aimed to characterise the transcriptomic profile of microglia in DSCL and surrounding radiologically normal-appearing white matter (NAWM) compared to non-lesional control white matter.  CD68+ microglia were isolated from white matter groups (n=4 cases per group) from the Cognitive Function and Ageing Study neuropathology cohort by immuno-laser capture microdissection.  Microarray gene expression profiling, but not RNA-sequencing, was found to be compatible with immuno-LCM-ed post-mortem material and identified significantly differentially expressed genes (DEG).  Functional grouping and pathway analysis was assessed using DAVID, and immunohistochemistry was performed to validate gene expression changes at the protein level.  Transcriptomic profiling of microglia in DSCL compared to non-lesional control white matter identified 181 significant DEG (93 upregulated and 88 downregulated).  Functional clustering analysis revealed dysregulation of haptoglobin-hemoglobin binding (Enrichment score 2.15, p=0.017), confirmed by CD163 immunostaining, suggesting a neuroprotective microglial response to blood-brain barrier dysfunction in DSCL.  In NAWM versus control white matter, microglia exhibited 347 DEGs (209 upregulated, 138 downregulated), with significant dysregulation of protein de-ubiquitination (Enrichment score 5.14, p<0.0001), implying an inability to maintain protein homeostasis in NAWM that may contribute to lesion spread. These findings enhance understanding of microglial transcriptomic changes in aging white matter pathology, highlighting a neuroprotective adaptation in DSCL microglia and a potentially lesion-promoting phenotype in NAWM microglia. Overall design: 1- Isolate microglia from frozen post-mortem cases using immuno-LCM, and Perform transcriptomic profiling of microglia in control, NAWM and DSCL samples using RNA-seq. 2- Perform bioinformatics analysis of the datasets generated by RNA-seq to identify significantly differentially expressed genes and dysregulated pathways, and functional groups.