Fig. 1

Study design development of the brain cell-type transcriptomic reference panel (left column): the expression signatures of key cell types of the brain were curated by compiling publicly available RNA-seq data from neurons, astrocytes, oligodendrocytes, and microglia. The panel was curated iteratively to retain only those samples that showed the most faithful expression signature, while evaluating alternative digital deconvolution methods. The accuracy of digital deconvolution to estimate brain cellular proportion was validated using additional cell-type-specific samples and also by generating chimeric libraries. To study cellular population structure in AD (right column), we accessed publicly available data from the AMP-AD, including Mayo Clinic and MSBB datasets. In addition, we generated RNA-seq from participants of the Knight-ADRC and DIAN studies. These three studies generated RNA-seq data from PA brains, AD cases, and neuropath-free controls in a total of six cerebral cortex regions and cerebellum. We quantified the gene expression for all of the samples included in these studies using the same RNA-seq processing pipeline. Using digital deconvolution methods, we estimated the brain cellular proportions of the samples and compared the proportion between AD cases and controls. We studied the cell structure of brain carriers of Mendelian pathological mutations and variants that confer high-risk to AD. APC anterior prefrontal cortex, STG superior temporal gyrus, PHG parahippocampal gyrus, IFG inferior frontal gyrus, MSBB Mount Sinai Brain Bank, AD Alzheimer’s disease, PA pathological aging