Use Of Weighted Gene Coexpression Network Analysis To Identify Connectivity Between Gut And Brain Gene Expression

被引:0
|
作者
Khan, Tasnin
Hatami, Asa
Zhu, Chunni
Kawaguchi, Riki
Joshi, Swapna
Chen, Han
Hoffman, Jill
Law, Ivy K. M.
Rankin, Carl R.
John, Varghese
Geschwind, Daniel
机构
[1] Center for Inflammatory Bowel Diseases, Vatche and Tamar Manoukin Division of Digestive Diseases, Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles
[2] The Drug Discovery Lab, Mary S. Easton Center for Alzheimer's Disease Research, Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles
[3] Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles
[4] Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, UCLA, Los Angeles
[5] Center for Systems Biomedicine, Vatche and Tamar Manoukin Division of Digestive Diseases, Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles
[6] Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles
来源
FASEB JOURNAL | 2022年 / 36卷
关键词
D O I
10.1096/fasebj.2022.36.S1.R4859
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
BACKGROUND: Alterations in the gut brain axis are being recognized as a pathogenic factor for an increasing number of diseases, including neurodegenerative diseases such as Parkinson Disease (PD). The extent to which gene expression profiling in the gut and the brain is co-regulated is not well understood. Weighted gene coexpression network analysis (WGCNA) uses unbiased hierarchical clustering to reduce gene expression profiling data to modules of highly correlated genes. HYPOTHESIS: Gut-brain connectivity will be strongest for modules related to physiologic mechanisms with a systemic component, such as immune reactivity. METHODS: WGNCA networks were constructed for distal colon and striatum RNA seq data from mice overexpressing human wild type alpha synuclein (ASO, n=18) and wild type (WT, n=16) mice at 1 and 3 months. Mice with matched colon and striatum data (n=10/6 ASO/WT) were included in this analysis. Linear regression identified associations between colon and striatum modules. For this analysis, we controlled for both age and genotype as genotype- and age-associated modules could be correlated due to these covariates alone. Colon-striatum intermodular connectivity was visualized in Cytoscape. Overrepresented gene ontology (GO) terms in WGCNA modules were determined using the hypergeometric function in the GOstats package in R. Enrichment for gene signatures from single cell sequencing data was determined using the hypergeometric test against cell type signatures from the Panglao and Cellmarker databases. RESULTS: Selected associations are shown in Figure 1. There are strong correlations between colon and striatum modules that are enriched for terms related to the immune response. Modules most clearly related to the immune response are highlighted in yellow, but several other modules are also closely related to the immune response. For example, there is an association between the striatum module enriched for endothelial cells of the blood brain barrier, and the colon module enriched for goblet cells which produce the mucus layer of the epithelium, a key component of the innate immune system. CONCLUSIONS: Through analysis of matched colon and striatum samples, we can see correlations between gene expression in the colon and striatum. Most modules in this gut-brain network have some relevance to the immune system which is not unexpected. These results demonstrate the feasibility of "profiling" the gut-brain axis. A larger sample size would permit evaluation of disease-related changes in this profile. © FASEB.
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