Comparisons of pre- and post-mortem microglial populations

In the study, we propose to directly compare and analyze pre-mortem microglial cells obtained during surgical resection from Young et al [PMID: 34083789] with post-mortem microglia from Lopes et al [PMID: 34992268, Dataset NG00105] to better define the transcriptional landscape of human microglia and the effects of tissue processing. We have previously re-processed and re-analyzed bulk and single cell data from Young et al. to identify expression quantitative trait loci (eQTLs) and develop RNA deconvolution models to partition bulk microglia profiles (like those measured by Dataset NG00105) into cell fractions of 7 important microglial subpopulations/cell states including “homeostatic”, “stress”, and “chemokine/cytokine” using the single cell RNA-seq (scRNA-seq) data from Young et al. We propose to perform this RNA deconvolution in Lopes et al, and test whether any of these cell populations – particularly related to neuroinflammation – are more prevalent in neurodegenerative disorders like Alzheimer’s (AD) or Parkinson’s Diseases (PD). We will also test whether these cell subtype fractions identified in pre-mortem tissue are consistent in postmortem tissue. As validation, we will perform supervised clustering of the NG00108 snRNA-seq data (in mouse) and test whether any AD-associated microglial cell subtypes were enriched in the 5xFAD genotype. Lastly, we propose to combine genotype and RNA data from Lopes et al (NG00105) and Young et al and perform eQTL mega-analysis to double the discovery sample size of microglial eQTLs. We hypothesize that this mega-analysis will produce a much larger number of significant eQTLs, as the GTEx project [PMID: 32913098] found approximately ~3000 eGenes in 100 subject discovery datasets (which was the approximate sample sizes of Young et al and Lopes et al) and ~7000 eGenes in 200 subjects (the combined sample size in this proposal). We will also assess clinical relevance by performing colocalization analysis of this larger eQTL map with genome-wide association studies (GWAS) of neurodegenerative disorders. Overall, this proposal will compare and contrast two recently large-scale genomic efforts profiling human microglia.

Non-technical: This proposal will compare and contrast two recently large-scale genomic efforts profiling human microglia, including from premortem human brain tissue (Young et al, PMID: 34083789) and from postmortem brain tissue (Lopes et al, PMID: 34992268, Dataset: NG00105). We will specifically assess the distribution of various microglial cell states – derived from single cell RNA-seq data – and determine if all of these states are represented in microglia from postmortem tissue. We will perform validation analyses of these cellular states in a mouse model of AD (Dataset: NG00108). Assuming the pre- and post-mortem datasets are comparable, we will combine these datasets and perform joint analysis of genotype and phenotype to better understand variation in microglia gene expression.