@article {Hagenauer089391, author = {Megan Hastings Hagenauer and Anton Schulmann and Jun Z. Li and Marquis P. Vawter and David M. Walsh and Robert C. Thompson and Cortney A. Turner and William E. Bunney and Richard M. Myers and Jack D. Barchas and Alan F. Schatzberg and Stanley J. Watson and Huda Akil}, title = {Inference of Cell Type Composition from Human Brain Transcriptomic Datasets Illuminates the Effects of Age, Manner of Death, Dissection, and Psychiatric Diagnosis}, elocation-id = {089391}, year = {2017}, doi = {10.1101/089391}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Psychiatric illness is unlikely to arise from pathology occurring uniformly across all cell types in affected brain regions. Despite this, transcriptomic analyses of the human brain have typically been conducted using macro-dissected tissue due to the difficulty of performing single-cell type analyses with donated post-mortem brains. To address this issue statistically, we compiled a database of several thousand transcripts that were specifically-enriched in one of 10 primary cortical cell types, as identified in previous publications. Using this database, we predicted the relative cell type composition for 833 human cortical samples using microarray or RNA-Seq data from the Pritzker Consortium (GSE92538) or publicly-available databases (GSE53987, GSE21935, GSE21138, CommonMind Consortium). These predictions were generated by averaging normalized expression levels across transcripts specific to each cell type using our R-package BrainlnABlender (validated and publicly-released: https://github.com/hagenaue/BrainInABlender). Using this method, we found that the principal components of variation in the datasets were largely explained by the neuron to glia ratio of the samples. This variability was not simply due to dissection - the relative balance of brain cell types was influenced by a variety of demographic, pre- and post-mortem variables. Prolonged hypoxia around the time of death predicted increased astrocytic and endothelial content in the tissue, illustrating vascular upregulation. Aging was associated with decreased neuronal content. Red blood cell content was reduced in individuals who died following systemic blood loss. Subjects with Major Depressive Disorder had decreased astrocytic content, mirroring previous morphometric observations. Subjects with Schizophrenia had reduced red blood cell content, resembling the hypofrontality detected in fMRI experiments. Finally, in datasets containing samples with especially variable cell content, we found that controlling for predicted sample cell content while evaluating differential expression improved the detection of previously-identified psychiatric effects. We conclude that accounting for cell type can greatly improve the interpretability of microarray data.}, URL = {https://www.biorxiv.org/content/early/2017/12/20/089391}, eprint = {https://www.biorxiv.org/content/early/2017/12/20/089391.full.pdf}, journal = {bioRxiv} }