Inference of cell type content from human brain transcriptomic datasets illuminates the effects of age, manner of death, dissection, and psychiatric diagnosis

• Published in: PloS one Vol. 13; no. 7; p. e0200003
• Main Authors: Hagenauer, Megan Hastings, Schulmann, Anton, Li, Jun Z., Vawter, Marquis P., Walsh, David M., Thompson, Robert C., Turner, Cortney A., Bunney, William E., Myers, Richard M., Barchas, Jack D., Schatzberg, Alan F., Watson, Stanley J., Akil, Huda
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 17.07.2018; Public Library of Science (PLoS)
• Subjects: Age factors; Aging; Autopsy; Biology and Life Sciences; Blood; Brain; Brain mapping; Brain research; Cells (Biology); Consortia; Cortex; Datasets; Demographic variables; Demographics; Diagnosis; Dissection; DNA microarrays; Erythrocytes; Functional magnetic resonance imaging; Gene expression; Genetic aspects; Genomes; Health aspects; Hypoxia; Medical diagnosis; Medicine and Health Sciences; Mental depression; Mental disorders; Meta-analysis; Metabolism; Neuronal-glial interactions; Neurons; Neurosciences; Physical Sciences; Predictive control; Psychiatry; Research and Analysis Methods; Researchers; Ribonucleic acid; RNA; Schizophrenia; Statistical analysis; Statistical methods; Transcription (Genetics); Ann Arbor Michigan; United States > US; California
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0200003

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 analys...