Analysis of blood-based gene expression in idiopathic Parkinson disease

Shamir, Ron; Klein, Christine; Amar, David; Vollstedt, Eva Juliane; Bonin, Michael; Usenovic, Marija; Wong, Yvette C.; Maver, Aleš; Poths, Sven; Safer, Hershel M.; Corvol, Jean‐Christophe; Lesage, Suzanne; Lavi, Ofer; Deuschl, Günther; Kuhlenbaeumer, Gregor; Pawlack, Heike; Ulitsky, Igor; Kasten, Meike; Rieß, Olaf; Brice, Alexis; Peterlin, Borut; Krainc, Dimitri

doi:10.1212/wnl.0000000000004516

Cited by 112 publications

(88 citation statements)

References 35 publications

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“…Hence, there is a growing interest in detecting blood biomarkers for PD. Importantly, upregulated PTGDS was identified as being a unique blood-based signature capable of differentiating between patients with idiopathic Parkinson disease and controls in previous original studies of the microarrays [8]. A total of 1229 genes (640 up-regulated and 589 down-regulated) across the study were differentially expressed in PD with a P-value < 0.05.…”

Section: Discussionmentioning

confidence: 93%

Identification of potential diagnostic biomarkers for Parkinson's disease

Feng-hua

Sun

et al. 2019

FEBS Open Bio

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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.

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Section: Discussionmentioning

confidence: 93%

Identification of potential diagnostic biomarkers for Parkinson's disease

Feng-hua

Sun

et al. 2019

FEBS Open Bio

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“…We performed a similar analysis of Parkinson disease (IPD) and found no associated genes using any of the considered methods. The dataset (GSE99039 [56]) consisted of whole blood gene expression data for 205 IPD cases and 233 controls.…”

Section: Resultsmentioning

confidence: 99%

Finding associations in a heterogeneous setting: Statistical test for aberration enrichment

Mezlini

Das

Goldenberg

2020

Preprint

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Most two-group statistical tests are implicitly looking for a broad pattern such as an overall shift in mean, median or variance between the two groups. Therefore, they operate best in settings where the effect of interest is uniformly affecting everyone in one group versus the other. In real-world applications, there are many scenarios where the effect of interest is heterogeneous. For example, a drug that works very well on only a proportion of patients and is equivalent to a placebo on the remaining patients, or a disease associated gene expression dysregulation that only occurs in a proportion of cases whereas the remaining cases have expression levels indistinguishable from the controls for the considered gene. In these examples with heterogeneous effect, we believe that using classical two-group statistical tests may not be the most powerful way to detect the signal. In this paper, we developed a statistical test targeting heterogeneous effects and demonstrated its power in a controlled simulation setting compared to existing methods. We focused on the problem of finding meaningful associations in complex genetic diseases using omics data such as gene expression, miRNA expression, and DNA methylation. In simulated and real data, we showed that our test is complementary to the traditionally used statistical tests and is able to detect disease-relevant genes with heterogeneous effects which would not be detectable with previous approaches.

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“…Based on the change in T-cell-related pathways after exercise and its relationship with clinical measures, we hypothesized that T-cell-related functions, especially the T-cell receptor signaling pathway, were dysregulated in PD patients. To test this hypothesis, we reanalyzed publicly available microarray data (GSE99039) (22), which included peripheral blood from 205 PD patients and 233 control subjects. Genes (637 upregulated and 177 downregulated) were identified as DEGs in PD patients.…”

Section: Genes For T-cell Activation and Differentiation Were Upregulmentioning

confidence: 99%

“…In PD patients, blood-brain barrier impairment has been reported (20), and leukocytes have been identified near dopaminergic neurons in postmortem brain tissue from PD cases (21). In addition, many of the pathways implicated in neuronal dysfunction are also perturbed in peripheral blood cells from patients with PD, including altered ubiquitin-proteasome and mitochondrial pathways and the presence of alpha-synuclein peptides (22,23). In addition, evidence has suggested that peripheral inflammation plays a role in the early stages of disease initiation and progression, including the development of preclinical non-motor symptoms (19).…”

Section: Introductionmentioning

confidence: 99%