↓ Skip to main content

Blood transcriptomics of drug-naïve sporadic Parkinson’s disease patients

Overview of attention for article published in BMC Genomics, October 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
1 news outlet
twitter
9 X users

Citations

dimensions_citation
65 Dimensions

Readers on

mendeley
107 Mendeley
citeulike
2 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Blood transcriptomics of drug-naïve sporadic Parkinson’s disease patients
Published in
BMC Genomics, October 2015
DOI 10.1186/s12864-015-2058-3
Pubmed ID
Authors

Raffaella Calligaris, Mihaela Banica, Paola Roncaglia, Elisa Robotti, Sara Finaurini, Christina Vlachouli, Lucia Antonutti, Francesco Iorio, Annamaria Carissimo, Tatiana Cattaruzza, Andrea Ceiner, Dejan Lazarevic, Alberto Cucca, Nicola Pangher, Emilio Marengo, Diego di Bernardo, Gilberto Pizzolato, Stefano Gustincich

Abstract

Parkinson's disease (PD) is a chronic progressive neurodegenerative disorder that is clinically defined in terms of motor symptoms. These are preceded by prodromal non-motor manifestations that prove the systemic nature of the disease. Identifying genes and pathways altered in living patients provide new information on the diagnosis and pathogenesis of sporadic PD. Changes in gene expression in the blood of 40 sporadic PD patients and 20 healthy controls ("Discovery set") were analyzed by taking advantage of the Affymetrix platform. Patients were at the onset of motor symptoms and before initiating any pharmacological treatment. Data analysis was performed by applying Ranking-Principal Component Analysis, PUMA and Significance Analysis of Microarrays. Functional annotations were assigned using GO, DAVID, GSEA to unveil significant enriched biological processes in the differentially expressed genes. The expressions of selected genes were validated using RT-qPCR and samples from an independent cohort of 12 patients and controls ("Validation set"). Gene expression profiling of blood samples discriminates PD patients from healthy controls and identifies differentially expressed genes in blood. The majority of these are also present in dopaminergic neurons of the Substantia Nigra, the key site of neurodegeneration. Together with neuronal apoptosis, lymphocyte activation and mitochondrial dysfunction, already found in previous analysis of PD blood and post-mortem brains, we unveiled transcriptome changes enriched in biological terms related to epigenetic modifications including chromatin remodeling and methylation. Candidate transcripts as CBX5, TCF3, MAN1C1 and DOCK10 were validated by RT-qPCR. Our data support the use of blood transcriptomics to study neurodegenerative diseases. It identifies changes in crucial components of chromatin remodeling and methylation machineries as early events in sporadic PD suggesting epigenetics as target for therapeutic intervention.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 106 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 16%
Researcher 17 16%
Student > Master 13 12%
Student > Bachelor 7 7%
Student > Doctoral Student 6 6%
Other 18 17%
Unknown 29 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 15%
Agricultural and Biological Sciences 12 11%
Neuroscience 11 10%
Medicine and Dentistry 9 8%
Computer Science 7 7%
Other 15 14%
Unknown 37 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 November 2015.
All research outputs
#2,237,754
of 23,881,329 outputs
Outputs from BMC Genomics
#624
of 10,793 outputs
Outputs of similar age
#32,913
of 287,384 outputs
Outputs of similar age from BMC Genomics
#21
of 385 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,793 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 287,384 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 385 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.