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A systematic review and integrative approach to decode the common molecular link between levodopa response and Parkinson’s disease

Overview of attention for article published in BMC Medical Genomics, September 2017
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Title
A systematic review and integrative approach to decode the common molecular link between levodopa response and Parkinson’s disease
Published in
BMC Medical Genomics, September 2017
DOI 10.1186/s12920-017-0291-0
Pubmed ID
Authors

Debleena Guin, Manish Kumar Mishra, Puneet Talwar, Chitra Rawat, Suman S. Kushwaha, Shrikant Kukreti, Ritushree Kukreti

Abstract

PD is a progressive neurodegenerative disorder commonly treated by levodopa. The findings from genetic studies on adverse effects (ADRs) and levodopa efficacy are mostly inconclusive. Here, we aim to identify predictive genetic biomarkers for levodopa response (LR) and determine common molecular link with disease susceptibility. A systematic review for LR was conducted for ADR, and drug efficacy, independently. All included articles were assessed for methodological quality on 14 parameters. GWAS of PD were also reviewed. Protein-protein interaction (PPI) analysis using STRING and functional enrichment using WebGestalt was performed to explore the common link between LR and PD. From 37 candidate studies on levodopa toxicity, 18 genes were found associated, of which, CAn STR 13, 14 (DRD2) was most significantly associated with dyskinesia, followed by rs1801133 (MTHFR) with hyper-homocysteinemia, and rs474559 (HOMER1) with hallucination. Similarly, 8 studies on efficacy resulted in 4 genes in which rs28363170, rs3836790 (SLC6A3) and rs4680 (COMT), were significant. To establish the molecular connection between LR with PD, we identified 35 genes significantly associated with PD. With 19 proteins associated with LR and 35 with PD, two independent PPI networks were constructed. Among the 67 nodes (263 edges) in LR, and 62 nodes (190 edges) in PD pathophysiology, UBC, SNCA, FYN, SRC, CAMK2A, and SLC6A3 were identified as common potential candidates. Our study revealed the genetically significant polymorphism concerning the ADRs and levodopa efficacy. The six common genes may be used as predictive markers for therapy optimization and as putative drug target candidates.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 15%
Student > Bachelor 8 15%
Student > Master 8 15%
Researcher 7 13%
Student > Postgraduate 5 10%
Other 9 17%
Unknown 7 13%
Readers by discipline Count As %
Medicine and Dentistry 9 17%
Agricultural and Biological Sciences 8 15%
Neuroscience 8 15%
Biochemistry, Genetics and Molecular Biology 7 13%
Engineering 2 4%
Other 4 8%
Unknown 14 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 21 September 2017.
All research outputs
#9,063,389
of 11,805,455 outputs
Outputs from BMC Medical Genomics
#409
of 543 outputs
Outputs of similar age
#179,394
of 267,737 outputs
Outputs of similar age from BMC Medical Genomics
#5
of 7 outputs
Altmetric has tracked 11,805,455 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 543 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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