title: Next generation transcriptomics and genomics elucidate biological complexity of microglia in health and disease.
abstract: Genome-wide expression profiling technology has resulted in detailed transcriptome data for a wide range of tissues, conditions and diseases. In neuroscience, expression datasets were mostly generated using whole brain tissue samples, resulting in data from a mixture of cell types, including glial cells and neurons. Over the past few years, a rapidly increasing number of expression profiling studies using isolated microglial cell populations have been reported. In these studies, the microglia transcriptome was compared to other cell types, such as other brain cells and peripheral tissue macrophages, and related to aging and neurodegenerative conditions. A commonality found in many of these studies was that microglia possess distinct gene expression signatures. This repertoire of selectively-expressed microglial genes highlight functions beyond immune responses, such as synaptic modulation and neurotrophic support, and open up avenues to explore as-yet-unexpected roles. These data provide improved understanding of disease pathology, and complement not only the aforementioned whole brain tissue transcriptome studies, but also genome- and epigenome-wide association studies. In this review, insights obtained from isolated microglia transcriptome studies are presented, and compared to studies using other genome-wide approaches. The relation of microglia to other tissue macrophages and glial cell populations, as well as the role of microglia in the aging brain and in neurodegenerative conditions, will be discussed. Many more of these types of studies are expected in the near future, hopefully leading to the identification of novel genes and targets for neurodegenerative conditions.
authors.affiliation: Lundbeck Research USA, Paramus, New Jersey.
authors.forename: Paul D
authors.initials: PD
authors.lastname: Wes
authors.affiliation: Department of Neuroscience, Section Medical Physiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
authors.forename: Inge R
authors.initials: IR
authors.lastname: Holtman
authors.affiliation: Department of Neuroscience, Section Medical Physiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
authors.forename: Erik W G M
authors.initials: EW
authors.lastname: Boddeke
authors.affiliation: Lundbeck Research USA, Paramus, New Jersey.
authors.forename: Thomas
authors.initials: T
authors.lastname: Möller
authors.affiliation: Department of Neuroscience, Section Medical Physiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
authors.forename: Bart J L
authors.initials: BJ
authors.lastname: Eggen
mesh_terms: D000818:Animals; D044127:Epigenesis, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D023281:Genomics / Q000379:methods*; D006801:Humans; D008264:Macrophages / Q000378:metabolism; D017628:Microglia / Q000378:metabolism*; D019636:Neurodegenerative Diseases / Q000378:metabolism
keywords: Alzheimer's disease; aging; amyotrophic lateral sclerosisl epigenetics; gene expression