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Identification and Experimental Validation of Parkinson’s Disease with Major Depressive Disorder Common Genes

小桶 重性抑郁障碍 基因 计算生物学 候选基因 生物 疾病 遗传学 基因表达 神经科学 医学 转录组 内科学 认知
作者
Huiqing Wang,Shanshan Dou,Chunmei Wang,Wenbin Gao,Baohua Cheng,Fuling Yan
出处
期刊:Molecular Neurobiology [Springer Nature]
卷期号:60 (10): 6092-6108 被引量:2
标识
DOI:10.1007/s12035-023-03451-3
摘要

Parkinson’s disease (PD) is the second most common neurodegenerative disease that affects about 10 million people worldwide. Non-motor and motor symptoms usually accompany PD. Major depressive disorder (MDD) is one of the non-motor manifestations of PD it remains unrecognized and undertreated effectively. MDD in PD has complicated pathophysiologies and remains unclear. The study aimed to explore the candidate genes and molecular mechanisms of PD with MDD. PD (GSE6613) and MDD (GSE98793) gene expression profiles were downloaded from Gene Expression Omnibus (GEO). Above all, the data of the two datasets were standardized separately, and differentially expressed genes (DEGs) were obtained by using the Limma package of R. Take the intersection of the two differential genes and remove the genes with inconsistent expression trends. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were investigated to explore the function of the common DEGs. Additionally, the construction of the protein–protein interaction (PPI) network was to search the hub genes, and then the least absolute shrinkage and selection operator (LASSO) regression was used to further identify the key genes. GSE99039 for PD and GSE201332 for MDD were performed to validate the hub genes by the violin plot and receiver operating characteristic (ROC) curve. Last but not least, immune cell dysregulation in PD was investigated by immune cell infiltration. As a result, a total of 45 common genes with the same trend. Functional analysis revealed that they were enriched in neutrophil degranulation, secretory granule membrane, and leukocyte activation. LASSO was performed on 8 candidate hub genes after CytoHubba filtered 14 node genes. Finally, AQP9, SPI1, and RPH3A were validated by GSE99039 and GSE201332. Additionally, the three genes were also detected by the qPCR in vivo model and all increased compared to the control. The co-occurrence of PD and MDD can be attributed to AQP9, SPI1, and RPH3A genes. Neutrophils and monocyte infiltration play important roles in the development of PD and MDD. Novel insights may be gained from the findings for the study of mechanisms.
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