A cell epigenotype specific model for the correction of brain cellular heterogeneity bias and its application to age, brain region and major depression

• Published in: Epigenetics Vol. 8; no. 3; pp. 290 - 302
• Main Authors: Guintivano, Jerry, Aryee, Martin J., Kaminsky, Zachary A.
• Format: Journal Article
• Language: English
• Published: United States Taylor & Francis 01.03.2013; Landes Bioscience
• Subjects: Adolescent; Adult; age; Age Factors; Brain - metabolism; Brain - pathology; brain region; Case-Control Studies; cellular heterogeneity; Depressive Disorder, Major - genetics; Depressive Disorder, Major - metabolism; DNA Methylation; Epigenesis, Genetic; epigenetics; Female; Flow Cytometry; fluorescence activated cell sorting; Genetic Markers; glia; Humans; Male; microarray; Middle Aged; Models, Genetic; neurons; Neurons - classification; Neurons - metabolism; Neurons - pathology; Research Paper; Sex Factors; brain region; microarray; DNA methylation; cellular heterogeneity; glia; neurons; age; epigenetics; fluorescence activated cell sorting
• ISSN: 1559-2294; 1559-2308; 1559-2308
• DOI: 10.4161/epi.23924

Brain cellular heterogeneity may bias cell type specific DNA methylation patterns, influencing findings in psychiatric epigenetic studies. We performed fluorescence activated cell sorting (FACS) of neuronal nuclei and Illumina HM450 DNA methylation profiling in post mortem frontal cortex of 29 major depression and 29 matched controls. We identify genomic features and ontologies enriched for cell type specific epigenetic variation. Using the top cell epigenotype specific (CETS) marks, we generated a publically available R package, "CETS," capable of quantifying neuronal proportions and generating in silico neuronal profiles from DNA methylation data. We demonstrate a significant overlap in major depression DNA methylation associations between FACS separated and CETS model generated neuronal profiles relative to bulk profiles. CETS derived neuronal proportions correlated significantly with age in the frontal cortex and cerebellum and accounted for epigenetic variation between brain regions. CETS based control of cellular heterogeneity will enable more robust hypothesis testing in the brain.