Anat Cell Biol.  2019 Dec;52(4):469-477. 10.5115/acb.19.048.

Big data differential analysis of microglial cell responses in neurodegenerative diseases

• Tabassum R
• Jeong NY
• Chung HJ

• KMID: 2466701
• DOI: http://doi.org/10.5115/acb.19.048

Abstract

Microarray technology has become an indispensable tool for monitoring the levels of gene expression in a given organism through organization, analysis, interpretation, and utilization of biological sequences. Importantly, preliminary microarray gene expression differs from experimentally validated gene expression. Generally, microarray analysis of gene expression in microglial cells is used to identify genes in the brain and spinal cord that are responsible for the onset of neurodegenerative diseases; these genes are either upregulated or downregulated. In the present study, 770 genes identified in prior publications, including experimental studies, were analyzed to determine whether these genes encode novel disease genes. Among the genes published, 340 genes were matched among multiple publications, whereas 430 genes were mismatched; the matched genes were presumed to have the greatest likelihood of contributing to neurodegenerative diseases and thus to be potentially useful target genes for treatment of neurodegenerative diseases. In protein and mRNA expression studies, matched and mismatched genes showed 99% and 97% potentiality, respectively. In addition, some genes identified in microarray analyses were significantly different from those in experimentally validated expression patterns. This study identified novel genes in microglial cells through comparative analysis of published microarray and experimental data on neurodegenerative diseases.

Keyword

Microarray analysis; Microglia; Neurodegenerative diseases; Big data; Genes

MeSH Terms

Brain
Gene Expression
Microarray Analysis
Microglia
Neurodegenerative Diseases*
RNA, Messenger
Spinal Cord
RNA, Messenger

Figure

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  Fig. 1 Microarray study of microglial cell in neurodegenerative disease. This figure describes the activation of microglia is a hallmark of brain pathology. Under neurodegenerative disease condition, the inflammatory response is mediated by the activated microglia. This figure illustrates the gene expression pattern by microarray study in microglial cell under neurodegenerative diseases.

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  Fig. 2 Working procedure of finding various types of promising gene from microarray study. The procedure of searching genes of microglial cell study in the published research article regarding the DNA microarray to collect the data according to upregulated genes, downregulated genes as well as the unchanged genes. The novel genes are identified by microarray study. This illustration describes how each gene is searched in NCBI for collecting experimental data such as the polymerase chain reaction (PCR), real-time PCR, western blotting, or immunohistochemistry data. In this process, some target molecules are found from the microarray study.

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  Fig. 3 Mechanism of microglial cell under neurodegenerative disease state. Neuronal cell death occurs under neurodegenerative disease state including motor and peripheral neuron. Microglial cell is activated when neuronal disease occurs. Microglia releases interferon (IF), interleukin (IL), brainderived neurotrophic factors (BDNF), purinoreceptor (P2RX4), chemokine receptor 1 (CX3CR1), DAP12, and IRF when neuropathic pain as well as neurodegenerative disease occur. This diagram depicts how microglial cell becomes active under neurodegenerative diseases. DRG, dorsal root ganglia; CSF, cerebrospinal fluid.

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  Fig. 4 Linear graph of upregulated and downregulated genes. (A) According to DNA microarray data, the overall numbers of total upregulated and downregulated genes found in the study which are studies related to microglial cell. Analyzing the total genes of upregulated and downregulated and the genes are searched for the experimental data such as polymerase chain reaction (PCR), real-time PCR, and quantitative PCR, etc. which indicates to find out possibility of some genes. (B) Illustration of the total amount of upregulated as well as downregulated gene. The upregulated genes are categorized when the fold-change value is >1 and the downregulated genes are categorized when the fold-change value is <1. The unchanged gene is marked when the fold-change value is 1. The total number of upregulated genes is 456 and the number of downregulated genes is 314 among the total 770 genes.

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  Fig. 5 Potentiality of gene compare to the experimental value. (A) According to the number of fold change, the upregulated and downregulated total genes are arranged in a unified way and according to the data, the genes are classified into most potential, potential, and moderately potential genes for identification. (B) Total amount of experimented genes compare to the published genes.The number of published genes is 770. Among them, 120 genes are most potential, 61 genes are potential, and 20 genes are moderately potential which are named as type 1, type 2, and type 3, respectively.

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  Fig. 6 Comparison between microarray gene expression and the real experimental value. (A) Total promising gene confirmation from the total published genes. As the left side of this graph shows these genes are highly upregulated and the right side of this graph shows highly downregulated, the blue marked area (both left and right) of both sides have good match and these are significant genes in this study. X-axis shows the total number of gene, n=770 and Y-axis shows the fold-change value. IHC, immunohistochemistry; ISH, in situ hybridization. (B) Differential range between the matched and mismatched gene. These figures show microarray data versus real experimental data such as western blotting (WB) and polymerase chain reaction (PCR)/quantitative PCR data. This figure shows the difference between experimental and microarray data. This graph also denotes the identification of find out highly promising gene in this study. (C) Differential range between the published, matched and promised gene. In the pie chart, the green color indicates published genes that occupied large space. Then the blue color indicates matched genes. The least number of promising genes are represented by the yellow color.

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