AUTHOR=Chen Yisheng , Sun Yaying , Luo Zhiwen , Chen Xiangjun , Wang Yi , Qi Beijie , Lin Jinrong , Lin Wei-Wei , Sun Chenyu , Zhou Yifan , Huang Jiebin , Xu Yuzhen , Chen Jiwu , Chen Shiyi 

TITLE=Exercise Modifies the Transcriptional Regulatory Features of Monocytes in Alzheimer’s Patients: A Multi-Omics Integration Analysis Based on Single Cell Technology

JOURNAL=Frontiers in Aging Neuroscience

VOLUME=14

YEAR=2022

URL=https://www.frontiersin.org/journals/aging-neuroscience/articles/10.3389/fnagi.2022.881488

DOI=10.3389/fnagi.2022.881488

ISSN=1663-4365

ABSTRACT=<p>Monocytes have been reported to be important mediators of the protective effect of exercise against the development of Alzheimer’s disease (AD). This study aims explored the mechanism by which monocytes achieve this. Using single cell transcriptome analysis, results showed that CD14 + and CD16 + monocytes interacted with other cells in the circulating blood. <italic>TNF</italic>, <italic>CCR1</italic>, <italic>APP</italic>, and <italic>AREG</italic>, the key ligand-receptor-related genes, were found to be differentially expressed between exercise-treated and AD patients. The SCENIC analysis was performed to identify individual clusters of the key transcription factors (TFs). Nine clusters (M1-M9) were obtained from the co-expression network. Among the identified TFs, <italic>MAFB</italic>, <italic>HES4</italic>, and <italic>FOSL1</italic> were found to be differentially expressed in AD. Moreover, the M4 cluster to which <italic>MAFB</italic>, <italic>HES4</italic>, and <italic>FOSL1</italic> belonged was defined as the signature cluster for AD phenotype. Differential analysis by bulkRNA-seq revealed that the expression of <italic>TNF</italic>, <italic>CCR1</italic>, and <italic>APP</italic> were all upregulated after exercise (<italic>p</italic> &lt; 0.05). And <italic>ATF3</italic>, <italic>MAFB</italic>, <italic>HES4</italic>, and <italic>KLF4</italic> that were identified in M4 clusters may be the TFs that regulate <italic>TNF</italic>, <italic>CCR1</italic>, and <italic>APP</italic> in exercise prescription. After that, <italic>APP</italic>, <italic>CCR1</italic>, <italic>TNF</italic>, <italic>ATF3</italic>, <italic>KLF4</italic>, <italic>HES4</italic>, and <italic>MAFB</italic> formed a regulatory network in the ERADMT gene set, and all of them were mechanistically linked. The ERADMT gene set has been found to be a potential risk marker for the development of AD and can be used as an indicator of compliance to exercise therapy in AD patients. Using single-cell integration analysis, a network of exercise-regulating TFs in monocytes was constructed for AD disease. The constructed network reveals the mechanism by which exercise regulated monocytes to confer therapeutic benefits against AD and its complications. However, this study, as a bioinformatic research, requires further experimental validation.</p>