[O2–13–04]: CELL‐TYPE PROFILING TO IDENTIFY THE TRANSCRIPTOMIC DOWNSTREAM EVENTS TRIGGERED BY EARLY‐ONSET AUTOSOMAL DOMINANT AD MUTATIONS

Background:Genes that are expressed in a cell-specific fashion in the human brain were identified from transcriptome-wide (RNAseq) expression measures of purified cell populations (Zhang Y. et al, Neuron, 2016). Leveraging these findings, we estimated the relative proportions of cell-types in a temporal cortex (TCX), tissue-based, transcriptome dataset (RNAseq: Allen M. et al, Sci Data, 2016) of 268 subjects with a pathological diagnosis of Alzheimer’s disease (AD; N1⁄480), progressive supranuclear palsy (PSP; N1⁄482), pathologic aging (PA; N1⁄430) or normal controls (CON; N1⁄476), to identify disease relevant changes and cell-specific vulnerabilities. Methods:We generated expression residuals, adjusting for appropriate covariates, for cell–specific genes (Zhang. Y et al, Neuron 2016) expressed in our dataset (neurons1⁄4415; astrocytes1⁄4234; oligodendroglia1⁄4117; microglia1⁄4352, endothelia1⁄498 genes). We used principal components analysis to generate a surrogate variable (signed eigenvector 1: EV1) representing cell-specific transcripts for each cell type. Each cell-specific EV1 was used as a quantitative variable to test for association with diagnosis, age, sex or APOEε4 genotype (linear regression, R software). Pairwise correlations were tested between all cell-specific EV1 levels (Pearson correlation, R). Analyses were done on the complete cohort, adjusting for diagnosis, and for each individual diagnostic group. We also performed a genome-wide association study (GWAS; linear regression, PLINK) for each cellspecific EV1 on the complete cohort. Results: Significant positive correlations (r2>0.5; p<2.2E-16) were identified between endothelial EV1 and astrocyte or microglia EV1 levels. Neuronal EV1 was negatively correlated with EV1 levels for all other cell types. These correlations were similar across the diagnostic groups. EV1 for astrocytes, microglia, and endothelia were higher, and for neurons lower, in AD subjects compared to other groups, with similar trends observed also for female sex and APOEε4. GWAS did not identify genome-wide significant variants (p<1E08), although suggestive associations include variants at the TMEM106B locus with astrocytes (p1⁄49.0E-07), and an intergenic locus (Chr2) flanked by NXPH2 and LRP1B(p1⁄42.1E-08) with microglia. Conclusions:We have identified brain cell type variability across different diagnosis groups and genetic associations that may influence these. These findings imply specific vulnerabilities for different cell types. We are performing similar analyses in cerebellum, and additional human and mouse brain transcriptome datasets.