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Identification of potential diagnostic biomarkers for Parkinson's disease.

ABSTRACT: The identification of biomarkers for early diagnosis of Parkinson's disease (PD) prior to the onset of symptoms may improve the effectiveness of therapy. To identify potential biomarkers, we downloaded microarray datasets of PD from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between PD and normal control (NC) groups were obtained, and the feature selection procedure and classification model were used to identify optimal diagnostic gene biomarkers for PD. A total of 1229 genes (640 up-regulated and 589 down-regulated) were obtained for PD, and nine DEGs (PTGDS, GPX3, SLC25A20, CACNA1D, LRRN3, POLR1D, ARHGAP26, TNFSF14 and VPS11) were selected as optimal PD biomarkers with great diagnostic value. These nine DEGs were significantly enriched in regulation of circadian sleep/wake cycle, sleep and gonadotropin-releasing hormone signaling pathway. Finally, we examined the expression of GPX3, SLC25A20, LRRN3 and POLR1D in blood samples of patients with PD by qRT-PCR. GPX3, LRRN3 and POLR1D exhibited the same expression pattern as in our analysis. In conclusion, this study identified nine DEGs that may serve as potential biomarkers of PD.

SUBMITTER: Jiang F

PROVIDER: S-EPMC6668373 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Identification of potential diagnostic biomarkers for Parkinson's disease.

Jiang Fenghua F Wu Qianqian Q Sun Shuqian S Bi Guanghui G Guo Ling L

FEBS open bio 20190703 8

The identification of biomarkers for early diagnosis of Parkinson's disease (PD) prior to the onset of symptoms may improve the effectiveness of therapy. To identify potential biomarkers, we downloaded microarray datasets of PD from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between PD and normal control (NC) groups were obtained, and the feature selection procedure and classification model were used to identify optimal diagnostic gene biomarkers for PD. A total ...[more]

PMID: 31199560

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Project description:The definition of biomarkers correlating with disease progression could have impact on the rational design of novel diagnostic approaches for bovine tuberculosis in cattle. We have used the advantages of the murine model to identify promising candidates in the host transcriptome post-infection. RNA from BALB/c splenocytes and lung cells after aerogenic Mycobacterium bovis infection were with high-density microarrays to defining biomarkers of disease progression. In antigen-stimulated splenocytes we found statically significant modulation of 1109 genes early after infection and 1134 at later time-point post-infection. 618 of these genes were modulated at both time points. In the lung 282 genes were significantly modulated post-infection. Amongst the most strongly up-regulated genes were granzyme A in spleen, and cxcl9, granzyme B, interleukin-22, interluekin-17A receptor, and ccr6 in lungs. The expression of 20 of the most up-regulated genes identified in the murine studies were evaluated using PBMC from uninfected and naturally infected cattle. We could show that the expression of cxcl9, granzyme A and interleukin-22 following in vitro stimulation with PPD was significantly increased in infected cows compared to naïve animals. Thus, we have demonstrated that murine transcriptome analysis can be used to predict responses in cattle. In addition, we have prioritised CXCL9, GnzA and IL-22 as potential additional readout systems for the ante-mortem diagnosis of bovine tuberculosis. Two groups of 5 BALB/c mice each were infecetd with approx 600 CFU M. bovis via the intranasal route. At days 3 and 14 post challenge five mice per group were euthanized and spleens and lungs harvested. One group of 5 mice were used as a control. Their splenocytes and lung cells were stimulated in vitro for 3 days with M7 protein pool. Antigen cell culture stimulations in mice were performed using an equal pool of seven secreted, immunogenic recombinant mycobacterial proteins (Rv1886c, Rv3019c, Rv3763, Rv3804c, Rv0251, Rv0287 and Rv0288) common to M. bovis and BCG, referred here as M7 protein cocktail. Each protein was used at final concentration of 2μg/ml in 3-day culture.

Project description:The aim of this study is to investigate mRNA expression profiling by RNA sequencing (RNA-seq) in patients with coronary artery disease (CAD) and validate differentially expressed genes (DEGs) as novel biomarkers for CAD. Transcriptome-wide mRNA expression analysis of peripheral blood mononuclear cells was performed in five CAD patients and five controls. Functional enrichment analyses, protein-protein interaction network construction, and hub gene selection were further conducted. Relative expression levels of hub genes were validated by quantitative reverse transcription PCR in larger cohorts. Spearman correlation test and multiple linear regression analysis were applied to examine the relationship between confounding factors with severity of coronary artery atherosclerosis. Receiver operating characteristic (ROC) curve analysis was adopted to identify potentially diagnostic biomarkers for CAD. A total of 527 upregulated and 653 downregulated mRNAs were identified as DEGs in CAD patients. The relative expression levels of beta-transducin repeat containing E3 ubiquitin protein ligase (BTRC), F-box and leucine-rich repeat protein 4 (FBXL4), ubiquitin conjugating enzyme E2 D2 (UBE2D2), and ankyrin repeat and SOCS box containing 1 (ASB1) were significantly different between two groups (all p ≤ 0.05). The severity of coronary artery atherosclerosis was negatively associated with the BTRC gene relative expression level (r = -0.323, p < 0.001) and positively with UBE2D2 (r = 0.285, p < 0.001). ROC analysis of BTRC and UBE2D2 genes showed that the areas under the curve were 0.782 (95% CI: 0.720-0.845, p < 0.001) and 0.753 (95% CI: 0.681-0.824, p < 0.001), respectively. We described the characteristics of mRNA expression in the peripheral blood of CAD patients and controls by RNA-seq. Combined with Spearman correlation analysis and ROC analyses, BTRC and UBE2D2 genes had significantly diagnostic values, which may have potential to act as novel diagnostic biomarkers and therapeutic targets for CAD.

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Identification of potential diagnostic biomarkers for Parkinson's disease.

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Identification of potential diagnostic biomarkers for Parkinson's disease.

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