AUTHOR=Li Ting , Qu Jingru , Xu Chaofei , Fang Ting , Sun Bei , Chen Liming 

TITLE=Exploring the common gene signatures and pathogeneses of obesity with Alzheimer’s disease via transcriptome data

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2022.1072955

DOI=10.3389/fendo.2022.1072955

ISSN=1664-2392

ABSTRACT=Background: Obesity is a complex condition that influences several organ systems and physiologic systems. Obesity (OB) is closely linked to Alzheimer’s disease (AD). However, the interrelationship between them remains unclear. The purpose of this study is to explore the key genes and potential molecular mechanisms in obesity and AD.
Methods: The microarray data of OB and AD were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene correlation network analysis (WGCNA) was used to delineate the co-expression modules related to OB and AD. The shared genes existing in the obesity and AD were performed with biological processes analyses using the DAVID website, then constructed Protein-Protein Interaction (PPI) Network and selected the hub genes by cytoscape. The results were validated in other microarray data by differential gene analysis. Moreover, the hub genes expressions were further determined in mice by qPCR. 
Results: WGCNA identifies five modules and four modules as the significant modules with OB and AD, respectively. Functional analysis of shared genes emphasized inflammation response and mitochondrial functionality were a common feature in the pathophysiology of OB and AD. The results of differential gene analysis in other microarray data were extremely similar to them. Then six important hub genes were selected and identified using cytoHubba, including MMP9, PECAM1, C3AR1, IL1R1, PPARGC1α and COQ3. Finally, we validated the hub genes expressions via qPCR.
Conclusions: Our work revealed the high inflammation/immune response and mitochondrial impairment in OB patients might be a crucial susceptible factor for AD. Meanwhile, we identified novel gene candidates such as MMP9, PECAM1, C3AR1, IL1R1, PPARGC1α and COQ3 that could be used as biomarkers or potential therapeutic targets for OB with AD.