Integrative enrichment analysis of gene expression based on an artificial neuron

BMC Medical Genomics

卷:14

Research

Xue Jiang¹  Weihao Pan¹  Miao Chen¹  Weidi Wang¹  Weichen Song¹  Guan Ning Lin^1,2 

[1] Shanghai Key Laboratory of Psychotic Disorders, 200030, Shanghai, China

[2] Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China

关键词: Huntington’s disease;    Multi-tissues;    Differentially expressed gene;    Artificial neuron;   

DOI  :  10.1186/s12920-021-00988-x

 received in 2020-11-12, accepted in 2021-05-18,  发布年份 2021

来源: Springer

【 摘 要 】

BackgroundHuntington’s disease is a kind of chronic progressive neurodegenerative disease with complex pathogenic mechanisms. To data, the pathogenesis of Huntington’s disease is still not fully understood, and there has been no effective treatment. The rapid development of high-throughput sequencing technologies makes it possible to explore the molecular mechanisms at the transcriptome level. Our previous studies on Huntington’s disease have shown that it is difficult to distinguish disease-associated genes from non-disease genes. Meanwhile, recent progress in bio-medicine shows that the molecular origin of chronic complex diseases may not exist in the diseased tissue, and differentially expressed genes between different tissues may be helpful to reveal the molecular origin of chronic diseases. Therefore, developing integrative analysis computational methods for the multi-tissues gene expression data, exploring the relationship between differentially expressed genes in different tissues and the disease, can greatly accelerate the molecular discovery process.MethodsFor analysis of the intra- and inter- tissues’ differentially expressed genes, we designed an integrative enrichment analysis method based on an artificial neuron (IEAAN). Firstly, we calculated the differential expression scores of genes which are seen as features of the corresponding gene, using fold-change approach with intra- and inter- tissues’ gene expression data. Then, we weighted sum all the differential expression scores through a sigmoid function to get differential expression enrichment score. Finally, we ranked the genes according to the enrichment score. Top ranking genes are supposed to be the potential disease-associated genes.ResultsIn this study, we conducted large amounts of experiments to analyze the differentially expressed genes of intra- and inter- tissues. Experimental results showed that genes differentially expressed between different tissues are more likely to be Huntington’s disease-associated genes. Five disease-associated genes were selected out in this study, two of which have been reported to be implicated in Huntington’s disease.ConclusionsWe proposed a novel integrative enrichment analysis method based on artificial neuron (IEAAN), which displays better prediction precision of disease-associated genes in comparison with the state-of-the-art statistical-based methods. Our comprehensive evaluation suggests that genes differentially expressed between striatum and liver tissues of health individuals are more likely to be Huntington’s disease-associated genes.

【 授权许可】

CC BY   
© The Author(s) 2021

【 图 表 】

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Figure 2. Flow cytometric analysis of the T-cell activation marker CD69.

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