Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathway.

Interdepartmental Program for Neuroscience, Department of Human Genetics and Biostatistics, University of California, Los Angeles, CA 90095-1769, USA.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 07/2010; 107(28):12698-703. DOI: 10.1073/pnas.0914257107
Source: PubMed


Because mouse models play a crucial role in biomedical research related to the human nervous system, understanding the similarities and differences between mouse and human brain is of fundamental importance. Studies comparing transcription in human and mouse have come to varied conclusions, in part because of their relatively small sample sizes or underpowered methodologies. To better characterize gene expression differences between mouse and human, we took a systems-biology approach by using weighted gene coexpression network analysis on more than 1,000 microarrays from brain. We find that global network properties of the brain transcriptome are highly preserved between species. Furthermore, all modules of highly coexpressed genes identified in mouse were identified in human, with those related to conserved cellular functions showing the strongest between-species preservation. Modules corresponding to glial and neuronal cells were sufficiently preserved between mouse and human to permit identification of cross species cell-class marker genes. We also identify several robust human-specific modules, including one strongly correlated with measures of Alzheimer disease progression across multiple data sets, whose hubs are poorly-characterized genes likely involved in Alzheimer disease. We present multiple lines of evidence suggesting links between neurodegenerative disease and glial cell types in human, including human-specific correlation of presenilin-1 with oligodendrocyte markers, and significant enrichment for known neurodegenerative disease genes in microglial modules. Together, this work identifies convergent and divergent pathways in mouse and human, and provides a systematic framework that will be useful for understanding the applicability of mouse models for human brain disorders.

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Available from: Jeremy A Miller, Jan 08, 2014
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    • "Genes in certain module usually share similar expression pattern and biological functions. Many researchers studied the properties of dynamic modules and their relationships between species (Miller et al. (2010); Langfelder et al. (2011)), tissues (Oldham et al. (2008)) and disease types (Yang et al. (2014)). We find the key challenge of the existing studies is how to accurately match module/graph during the dynamic progresses of the biological systems. "
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    ABSTRACT: The modeling and identification of the spatial-temporal gene networks in transcriptome scale is a challenging problem. To investigate the molecular mechanism of genes in a dynamic and systematic fashion, we develop a novel method for tracking the spatial-temporal modules of gene network reconstructed from the brain development gene expression data. A statistical model based method for module/graph mathch is proposed to track the evolving gene networks. We apply this method to brain spatial-temporal networks and provides new insights into the molecular mechanisms of brain development as well as the functions of the the schizophrenia associated genes.
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    • "A transcriptome analysis across human and mouse brains was developed by analyzing more than 1000 gene microarrays in both species. Among them,thespecies-specificgenemodulesdescribedsome highly conserved transcriptomes with an overlap of genetic networks between the two species [159]. When AD and other neurodegenerative disorders were specifically examined, the transcriptome revealed that the recruitment of microglial cells appeared to play a significant role in the development of AD. "
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    ABSTRACT: Preclinical studies are essential for translation to disease treatments and effective use in clinical practice. An undue emphasis on single approaches to Alzheimer's disease (AD) appears to have retarded the pace of translation in the field, and there is much frustration in the public about the lack of an effective treatment. We critically reviewed past literature (1990-2014), analyzed numerous data, and discussed key issues at a consensus conference on Brain Ageing and Dementia to identify and overcome roadblocks in studies intended for translation. We highlight various factors that influence the translation of preclinical research and highlight specific preclinical strategies that have failed to demonstrate efficacy in clinical trials. The field has been hindered by the domination of the amyloid hypothesis in AD pathogenesis while the causative pathways in disease pathology are widely considered to be multifactorial. Understanding the causative events and mechanisms in the pathogenesis are equally important for translation. Greater efforts are necessary to fill in the gaps and overcome a variety of confounds in the generation, study design, testing, and evaluation of animal models and the application to future novel anti-dementia drug trials. A greater variety of potential disease mechanisms must be entertained to enhance progress.
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    • "However, the functional and phenotypic consequences of these changes largely remain unclear. Changes in gene expression, which has been considered to be the major driving force of phenotypic evolution, have been systematically studied for the evolution of different regions of the brain (Oldham et al., 2008; Johnson et al., 2009; Miller et al., 2010; Kang et al., 2011; Hawrylycz et al., 2012; Konopka et al., 2012). The conclusions of many of these studies, however, are affected by some technological limitations. "
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